Input: Therefore, a measurement of the flow pattern is of great importance for improving the printing quality of the inkjet printing process.

measurement

flow pattern

quality

inkjet printing process


Input: Most of the current works use static images for the study of the drop evolution process.

images

evolution


Input: The problem of the static images is that the images can not recognize the motion information (i.e., temporal transformation) of the droplet.

images

images

droplet


Input: Thus the information of the jetting process in the temporal domain will be lost.

jetting

domain

be


Input: Instead of using the images, this paper takes the video data as the study subject to investigate the droplet evolution behavior in the inkjet printing process.

images

data

droplet

as

inkjet printing process


Input: Compared to most of the current learning approaches conducted in a supervised/semi-supervised manner for manufacturing process data, we propose an unsupervised learning method for studying the flow pattern of the droplet, which does not require well-defined ground-truth labels.

manufacturing process

data

flow pattern

droplet


Input: Regarding the spatial and temporal transformation of the droplet in video data, we apply a deep recurrent neural network (DRNN) to implement the proposed unsupervised learning.

droplet

data

neural network


Input: Experimental results demonstrate that the proposed method can learn latent representations of the droplet jetting process video data, which is very useful for the prediction of the droplet behavior.

Experimental

droplet

process

data

prediction

droplet


Input: Furthermore, through latent space decoding, the learned representations can infer the droplet forming stimulus parameters such as material properties, which would be very helpful for further understanding of the process dynamics and achieving real-time in-situ droplet deposition quality monitoring and control.

droplet

parameters

properties

process

in-situ

droplet

as

be

deposition quality


Input: The surface of SLMed composite shows low roughness and high homogeneity.

surface

SLMed

composite

roughness


Input: A phase transition from bcc martensite to fcc austensite appears with the addition of WC.

phase

bcc

fcc

WC


Input: Metallurgical bonding between reinforcement and matrix is realized.

Metallurgical bonding

reinforcement


Input: Tensile behavior of SLMed composite is different from that of SLMed maraging steel.

Tensile

SLMed

SLMed

composite

maraging steel


Input: In this work, tungsten carbide (WC) reinforced maraging steel matrix composites were in-situ manufactured by selective laser melting (SLM) from powder mixture.

tungsten carbide

WC

maraging steel

composites

powder

reinforced

in-situ

selective laser melting

SLM


Input: The SLM processed samples presented high relative density (over 99%) with a homogenous distribution of WC.

SLM

processed

distribution

relative density

WC


Input: The as-fabricated surface quality of SLM processed samples was improved significantly by the addition of WC.

surface quality

SLM

processed

WC


Input: Focused ion beam and transmission electron microscopy were employed to characterize the interfacial properties between tungsten carbide and steel matrix.

ion

properties

beam

transmission electron microscopy

tungsten carbide

steel


Input: The elemental analysis indicates that metallurgical bonding appears at interfacial region due to the diffusion.

elemental analysis

metallurgical bonding

diffusion


Input: Tensile behavior of SLM processed maraging steel was different from their composite with several WC contents.

Tensile

SLM

processed

maraging steel

composite

WC


Input: To understand the fundamentals of microstructure formation in an electron beam melting (EBM) additive-manufacturing process, which is classified as a type of electron beam powder bed fusion (EB-PBF) in ISO562910/ASTM-F42, single bead experiments were conducted by using an electron beam to scan an IN718 plate, using various combinations of power and scan speed, focusing on the relationship between (i) the beam irradiation level, (ii) the melt pool geometry, and (iii) the solidification microstructure.

microstructure

process

electron beam

electron beam

geometry

solidification microstructure

electron beam melting

EBM

bed fusion

as

melt pool

bead

power

scan speed

beam


Input: The width and depth of the melt pool increases almost linearly with the line energy.

melt pool


Input: Elongated grains, which are generally called “columnar grains” were observed in almost the entire cross-section of the beads regardless of the process parameters.

grains

process parameters

columnar grains

beads


Input: Temporal evolution of the temperature distribution for the single bead experiments was simulated by finite element analysis (FEA) with thermal conduction and recoalescence taken into account.

evolution

distribution

finite element analysis

temperature

bead


Input: The surface heat source model used in the simulation was modified to cause the geometry of the simulated melt pool to align with that which was observed experimentally.

surface

heat source

geometry

simulation

melt pool


Input: The distributions of the temperature gradient (G) and solidification rate (R) on the solidification interface were evaluated from the simulation results.

distributions

solidification interface

temperature gradient

solidification rate

simulation


Input: The distributions of the microstructures were constructed from the distributions of G and R, as obtained from a solidification map in the literature.

distributions

distributions

solidification

microstructures

as


Input: Contrary to the experimental observations, the constructed microstructure consisted mostly of equiaxed and mixed grains.

experimental

microstructure

grains


Input: While the volumetric energy density is commonly used to qualify a process parameter set, and to quantify its influence on the microstructure and performance of additively manufactured (AM) materials and components, it has been already shown that this description is by no means exhaustive.

energy density

process parameter

microstructure

performance

materials

additively manufactured

AM

components


Input: In this work, new aspects of the optimization of the selective laser melting process are investigated for AM Ti-6Al-4V.

optimization

selective laser melting process

AM


Input: We focus on the amount of near-surface residual stress (RS), often blamed for the failure of components, and on the porosity characteristics (amount and spatial distribution).

residual stress

porosity

failure

components

spatial distribution


Input: First, using synchrotron x-ray diffraction we show that higher RS in the subsurface region is generated if a lower energy density is used.

synchrotron

diffraction

energy density


Input: Second, we show that laser de-focusing and sample positioning inside the build chamber also play an eminent role, and we quantify this influence.

laser

sample

build chamber


Input: In parallel, using X-ray Computed Tomography, we observe that porosity is mainly concentrated in the contour region, except in the case where the laser speed is small.

X-ray Computed Tomography

porosity

contour

laser


Input: 3D-printed Ti-6Al-4V components have great potential in the aerospace and biomedical industries.

components

aerospace

biomedical industries


Input: However, their wide application is limited by some inherent disadvantages, such as poor surface finish and high porosity.

as

surface finish

porosity


Input: In this study, an innovative method, electrically-assisted ultrasonic nanocrystal surface modification (EA-UNSM) was introduced to process 3D-printed Ti-6Al-4V samples.

surface modification

process

samples


Input: The effect of EA-UNSM on surface finish, microstructure, porosity and in-depth hardness was investigated.

surface finish

microstructure

porosity

hardness


Input: Compared with the conventional UNSM process, smoother surfaces and lower subsurface porosities were obtained after EA-UNSM.

process

surfaces

porosities


Input: Numerical modelling showed that localized heating occurs near the pores in 3D-printed Ti-6Al-4V subjected to electric current.

modelling

heating

pores


Input: This localized heating could potentially facilitate pore closure under ultrasonic striking.

heating

pore


Input: Selective laser melting (SLM) technology is a layer-wise powder-based additive manufacturing method capable of building 3D components from their CAD models.

Selective laser melting

SLM

powder-based additive manufacturing

technology

CAD models


Input: This approach offers enormous benefits for generating objects with geometrical complexity.

geometrical complexity


Input: However, due to the layer-wise nature of the process, surface roughness is formed between layers, thus influenced by layer thickness and other processing parameters.

process

parameters

surface roughness

layer thickness


Input: In this study, systematic research has been carried out to study the influence of processing parameters on surface roughness in Hastelloy X alloy.

research

parameters

surface roughness

Hastelloy

alloy


Input: All samples were manufactured using an EOSINT M 280 machine.

samples

manufactured

machine


Input: Laser power, scan speed, layer thickness and sloping angle of a surface were systematically varied to understand their effects on surface roughness.

Laser power

scan speed

layer thickness

surface

surface roughness


Input: The arithmetic average roughness, Ra, was measured using a surface roughness tester, and optimum conditions for achieving the lowest roughness for both up-skin surfaces and down-skin surfaces have been obtained.

average

surfaces

surfaces

surface roughness

roughness


Input: The formation mechanism for the roughness on these two types of surfaces has been studied.

mechanism

surfaces

roughness


Input: Computer simulation was also used to understand thermal profiles at those two surfaces and their resultant influence on surface roughness.

Computer simulation

thermal profiles

surfaces

surface roughness


Input: Contour scan and skywriting scan strategies were found to be helpful for reducing the surface roughness.

Contour

be

surface roughness


Input: Selective laser sintering (SLS) is a promising additive manufacturing technique, where powder particles are fused together under the influence of a laser beam.

Selective laser sintering

SLS

additive manufacturing

powder particles

fused

laser beam


Input: To obtain good material properties in the final product, the powder particles need to form a homogeneous melt during the fabrication process.

material properties

homogeneous

powder particles

fabrication


Input: On the other hand, you want the process to be as fast as possible.

process

be

as

as


Input: We developed a computational model based on the finite element method to study the material and process parameters concerning the melt flow of the powder particles.

computational model

finite element method

process parameters

melt flow

material

powder particles


Input: In this work, we restrict ourselves to varying the temperature-dependent viscosity, the process parameters, and the convective heat transfer coefficient of the sintering of two polymer (polyamide 12) particles.

viscosity

process parameters

heat transfer

particles

sintering

polymer

polyamide 12


Input: The simulations allow for a quantitative analysis of the influence of the different material and processing parameters.

simulations

quantitative

parameters

material


Input: From the simulations follows that an optimal sintering process has a low ambient temperature, a narrow beam width with enough power to heat the particles only a few degrees above the melting temperature, and a polymer of which the viscosity decreases significantly within these few degrees.

simulations

sintering

process

heat

particles

temperature

power

melting temperature

beam

polymer

viscosity


Input: Laser Engineered Net Shaping (LENS™) was utilized to create novel silica (SiO2) coatings onto commercially-pure titanium (Cp-Ti).

Laser Engineered Net Shaping

silica

titanium

coatings


Input: It was hypothesized that if silica could be deposited as a coating via laser surface engineering, high hardness and wear resistance could be added to existing Cp-Ti material.

silica

be

as

be

material

coating

engineering

laser

hardness

wear resistance


Input: Post-deposition heat-treatments in the form of laser passes (LP) and a furnace residual-stress relief were completed on the coatings and mechanical/material properties were subsequently evaluated.

laser

furnace

coatings

properties


Input: Titanium silicide (Ti5Si3) formation and related dendritic microstructures were identified throughout the coating by X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), scanning electron microscopic (SEM) analysis, and appeared more ordered after stress-relief heat treatment.

Titanium silicide

microstructures

coating

X-ray diffraction

XRD

energy dispersive spectroscopy

EDS

SEM

scanning

heat treatment


Input: High hardness values of approximately 1500 HV were measured at the coating’ s topmost surface while specific wear rates showed a maximum 98% reduction from 346.2 × 10−6 mm3/N-m in the Cp-Ti substrate to 7.1 × 10−6 mm3/N-m in the heat treated 1 LP coating.

hardness

coating

coating

s

substrate

surface

wear

reduction

heat


Input: In situ tribofilm formation was observed during wear, which indicated self-healing properties from the material and likely aided further in wear reduction.

In situ

wear

properties

wear reduction

material


Input: Our results show that silica coating on titanium via laser surface engineering could be used as a suitable manufacturing practice to create hard, Ti5Si3-reinforced ceramic coatings with high wear resistance and self-healing properties for applications ranging from biomedical to aerospace.

silica coating

titanium

be

as

ceramic coatings

laser

engineering

biomedical

aerospace

manufacturing

wear resistance

properties


Input: To increase the mechanical strength of Zircaloy-4 cladding at high temperatures, partial oxide dispersion-strengthened (ODS) treatment of the cladding tube surface was achieved by using laser processing technology.

mechanical strength

oxide

cladding

cladding

temperatures

surface

laser processing


Input: The microstructural characteristics and stability of the ODS layer formed on the Zircaloy-4 cladding surface were analyzed at temperatures up to 1000 °C.

microstructural

stability

layer

temperatures

cladding


Input: Ring tensile and loss-of-coolant accident (LOCA) simulation tests were performed to evaluate the mechanical properties of the surface ODS treated Zircaloy-4 cladding tube.

tensile

simulation

mechanical properties

surface

cladding


Input: The formation and uniform distribution of Y2O3 particles formed in the Zr matrix were identified, and the stability of the particles was confirmed up to 1000 °C.

distribution

particles

particles

Zr

stability


Input: When compared to the reference Zircaloy-4 cladding tube, the surface ODS treated Zircaloy-4 cladding tube showed improved mechanical properties at both room temperature and 500 °C, as well as under LOCA simulation conditions.

as

as

cladding

cladding

surface

mechanical properties

temperature

simulation


Input: Material extrusion is an Additive Manufacturing process able to fabricate a physical object directly from a virtual model using layer by layer deposition of a thermoplastic filament extruded by a nozzle.

Material extrusion

Additive Manufacturing process

fabricate

extruded

virtual model

layer by layer

deposition

thermoplastic filament

nozzle


Input: The fabrication of functional components implies the need for the assembly with other parts with different properties in terms of material and surface quality.

fabrication

assembly

functional components

properties

material

surface quality


Input: One of the most used assembly method involving plastic materials is the interference fit.

assembly

plastic

materials

interference fit


Input: It consists of fastening elements in which the two parts are pushed together, by means of a fit force, and no other fastener is necessary.

elements

fit

fastener


Input: It requires the accurate design of the interference, typically carried out by the designers through diagrams and theoretical formulations supplied by the material manufacturers.

accurate

theoretical

material


Input: At present no theory has been provided for material extrusion parts due to the anisotropic behavior: the mesostructure, the surface roughness and the dimensional deviations mainly depend upon the build orientation.In this work the effects of the surface morphology and the interference grade on the assembly and disassembly forces in an interference fit joint are investigated.

material extrusion

assembly

anisotropic

surface roughness

build

surface morphology

disassembly

interference fit


Input: For the purpose, a design of experiment with a factorial plan has been carried out.

design of experiment


Input: Through this model it is possible to know in advance the force necessary to assemble a material extrusion part with an assigned interference grade.

model

force

material extrusion


Input: Fused filament fabrication (FFF) enables production of 3D objects over a range of material compositions at low-cost relative to traditional manufacturing approaches.

Fused filament fabrication

FFF

production

traditional manufacturing

3D objects

range

material


Input: To date, a limited but growing number of materials are able to be used with FFF, however many applications exist where specific mechanical, thermal, or chemical properties are needed that can not currently be met with the available feedstock selection.

materials

properties

be

be

feedstock

FFF

mechanical


Input: Therefore, a need exists to tune these materials for specific chemical or mechanical properties.

materials

mechanical properties


Input: One common formulation strategy to address these demanding design parameters is to develop composites or polymer blend filaments.

design

composites

polymer blend

filaments


Input: This mixing occurs via software-controlled rotating hardware in the chamber of an extruder’ s hot-end.

mixing

extruder

s


Input: The efficiency of mixing within the printed layers has been characterized in detail as a function of the rotational speed and geometry of the blending hardware.

mixing

geometry

as

blending


Input: These parameters were exploited to program the ratio and distribution of thermoplastic-based filaments blended within printed extrudate.

parameters

distribution

filaments

extrudate


Input: Example printed specimens were produced with thermoplastic polyurethane (TPU) elastomer blended with rigid polylactic acid (PLA) and Nylon blended with PLA.

thermoplastic polyurethane

elastomer

polylactic acid

PLA

Nylon

PLA


Input: In addition, a conductive carbon nanotube (CNT) -PLA composite was blended as a function of mixer geometry and input feed ratios with non-conductive PLA and resistance values were measured across the resulting printed specimens.

carbon nanotube

CNT

composite

as

PLA

geometry

feed

resistance


Input: SLM fabricated Al-Mg-Sc-Zr alloy showed a heterogeneous grain structure.

SLM

fabricated

heterogeneous grain structure

alloy


Input: A good strength-ductility synergy was achieved in SLMed Al-Mg-Sc-Zr alloy.

SLMed

alloy


Input: Strain partitioning among heterogeneous grain structure provided additional back stress hardening.

Strain

stress

heterogeneous grain structure

hardening


Input: In this work, a Sc/Zr modified Al-Mg alloy was processed by both selective laser melting (SLM) and directed energy deposition (DED).

Al-Mg alloy

processed

selective laser melting

SLM

directed energy deposition

DED


Input: Due to different precipitation behavior of primary Al3 (Sc, Zr) -L12 nucleation sites, a heterogeneous grain structure was formed in SLMed sample, which consisted of ultrafine equiaxed grains bands and columnar grains domains, while a fully equiaxed grain structure was obtained in DEDed sample.

precipitation

nucleation

heterogeneous grain structure

sample

equiaxed grains

equiaxed grain

sample

Zr

SLMed

columnar grains


Input: Tensile results showed that the as built SLMed sample had a good combination of strength and ductility.

Tensile

strength

ductility

as

SLMed

sample


Input: The yield strength of SLMed sample (335 ± 4 MPa) was about 2.8 times that of DEDed sample (118 ± 3 MPa), however, the ductility in uniform elongation (23.6 ± 1.9%) was still comparable to that of DEDed sample (23.8 ± 2.6%).

yield strength

ductility

SLMed

sample

MPa

sample

MPa

sample

uniform elongation


Input: Based on the relationship between the heterogeneous grain structure and strain hardening behavior, the strength-ductility synergy mechanism of the SLMed Al-Mg-Sc-Zr alloy was discussed.

heterogeneous grain structure

mechanism

strain hardening

SLMed

alloy


Input: Stress partitioning tests showed that the contribution of back stress hardening to flow stress was higher in SLMed sample than DEDed sample, while effective stress hardening showed an opposite trend.

Stress

stress

flow stress

stress

hardening

SLMed

hardening

sample

sample

trend


Input: Despite the overall strain hardening ability of SLMed sample was limited by the high dynamic recovery rate of ultrafine equiaxed grains, additional back stress hardening, which was caused by strain partitioning between equiaxed grains bands and columnar grains domains, improved its strain hardening ability and resulted in the good combination of strength and ductility.

strain hardening

SLMed

hardening

strain hardening

sample

dynamic

equiaxed grains

equiaxed grains

stress

strain

columnar grains

strength

ductility


Input: Silicone elastomers are of commercial interest in a number of areas because of their distinctive properties.

Silicone elastomers

areas

properties


Input: Current 3D-printing (additive manufacturing) technologies for silicones mainly rely on the extrusion of high-viscosity pre-elastomer inks of one or two parts.

additive manufacturing

extrusion

technologies

silicones


Input: Some of the challenges presented by high viscosity materials, for instance, difficulties in mixing and changing inks to create devices from more than one type of silicone, could be overcome by use of lower viscosity inks.

viscosity

viscosity

materials

mixing

silicone

be


Input: Here we describe a family of rapidly curing (shape holding within < 2 s, full cure in < 20 s), readily mixed, low-viscosity silicone inks using a combination of chain-extender, cross-linker, base polymer and photoinduced thiol-ene click chemistry.

curing

s

s

silicone inks

polymer

cure

chemistry


Input: A key advantage of low viscosity is the facility to mix or change ink constituents, which facilitates changing inks, and the properties of the resulting cured materials.

viscosity

ink

properties

cured


Input: Microfluidic printheads and pneumatic control systems that switch rapidly between multiple inks, and then cure them using a UV exposure system, are also described.

control systems

cure

UV exposure


Input: The combination of fast curing inks, and the printhead that extrudes and then cures them, allows 3D extrusion printing of low-viscosity silicone materials without the use of supporting material.

curing

silicone materials

material


Input: The ability to print overhanging structures, discrete and continuous structures, as well as multimaterial structures using a single nozzle is demonstrated.

print

overhanging structures

as

as

nozzle


Input: The technology described here is scalable to produce higher resolution, multimaterial silicone structures that should find application in rapid prototyping and mold making.

technology

higher resolution

silicone

rapid prototyping

mold


Input: Continuous direct metal deposition in Z direction is carried out successfully.

direct metal deposition


Input: Superior austenite/ferrite dual phase microstructure is formed.

phase microstructure


Input: Thin 316L stainless steel rods were fabricated by continuous directed energy deposition in Z direction.

316L stainless steel

fabricated

directed energy deposition


Input: The process parameters (laser power, scan velocity, and powder feeding rate) were carefully selected to obtain a stable deposition process and the effects of powder feeding rate and scan velocity were studied.

process parameters

laser power

powder feeding

powder feeding

deposition process


Input: A preliminary study on microstructure and tensile properties of the specimens was carried out.

microstructure

tensile properties


Input: Results indicated that the specimen showed superior austenite/ferrite (γ/δ) dual phase microstructure, high strength (608.24 MPa), and good plastic deformation capacity (65.08% shrinkage rate) when setting the laser power at 45.2 W, powder feeding rate at 2.81 g/min, and scan velocity at 0.5 mm/s.

phase microstructure

MPa

capacity

shrinkage

strength

plastic deformation

laser power

powder feeding


Input: The technique reported in this paper is expected to lay the foundation for the deposition of wire or frame structures more efficiently than traditional layer-by-layer directed energy deposition.

lay

deposition

layer-by-layer

directed energy deposition


Input: Thermal modeling of additive manufacturing processes such as laser powder bed fusion is able to calculate a thermal history of a build.

Thermal modeling

additive manufacturing processes

powder bed fusion

as

build


Input: This simulated thermal history can in turn be used as an input to further simulate temperature related characteristics such as residual stress, distortion, microstructure, lack of fusion porosity, and hot spots.

be

as

as

temperature

stress

distortion

microstructure

fusion


Input: In order to estimate the heat loss to the powder bed during the process, convective heat transfer is widely used as thermal boundary condition in finite element modeling of laser powder fusion processes.

heat

process

heat transfer

boundary condition

finite element

fusion

powder bed

as

laser


Input: However, this convection coefficient is usually selected based on empirical estimation or model tuning.

empirical

model


Input: In this work, FEA models of the part and surrounding powder are used as a reference to determine the surface convection BC's for modeling the part only.

powder

as

surface

modeling


Input: Seven types of commonly used AM materials with a wide range of thermal conductivities were studied for better testing of the conductivity dependency of the convection coefficient.

AM materials

range

thermal conductivities

conductivity

testing


Input: The convection coefficient values, which predict similar thermal history as the powder model, are found to be a function of thermal conductivity of the deposited material and the cross-sectional thickness of the part feature.

as

powder

be

material

model

thermal conductivity

feature


Input: A new thickness dependent convection boundary condition is proposed and found to be capable of predicting much closer thermal history to the powder model.

boundary condition

model

be

powder


Input: These newly developed boundary conditions improve the peak temperature prediction accuracy by 36% while running in 1/4th of the time as the powder model.

boundary conditions

prediction

model

temperature

accuracy

as

powder


Input: The computed tomography (CT) evaluation of the material extrusion (MEX) of a short carbon fiber (SCF) Nylon-12 filament and part is presented.

computed tomography

CT

material extrusion

short carbon fiber

filament


Input: CT, a non-destructive testing method, was used to quantify the internal structure of specimens into three phases: pore, Nylon, and SCF.

CT

non-destructive testing

internal structure

pore

Nylon


Input: The intensity histograms from the CT data were fit using a mixed skew-Gaussian distribution (MSGD) algorithm to segment the CT image into phases.

CT

CT

fit

distribution

algorithm


Input: Thresholded images were used to isolate pores in the CT image to determine pore volume and distribution within both the MEX SCF filament and part.

images

distribution

pores

pore

CT

filament


Input: The phase volume percentages of the MEX SCF filament were found to be 1.6% pore, 62.2% Nylon, and 36.2% SCF.

phase

filament

be

Nylon

pore


Input: The volume of most pores within the filament were found to be under 100 μm3.

volume

pores

filament

be


Input: The highest frequency of pores was located near the outside of the filament, but the large pores were located near the center of the filament.

pores

pores

filament

filament


Input: This result indicates that the thermoplastic filament extrusion process likely entraps large bubbles in the center of filament or causes large thermal gradients and residual stresses that induce voids during post-extrusion cooling.

thermoplastic filament extrusion process

cooling

filament

thermal gradients

residual stresses

voids


Input: MSGD analysis of sections of the MEX SCF part estimated phase volume percentages to be 9.8% pore, 59.6% Nylon, and 30.9% SCF.

phase

be

Nylon

pore


Input: For the MEX SCF part, the average pore area was found to be highest (> 250 μm2) at the bottom of the layer and smallest (< 100 μm2) at the top of the layer, which could be explained by a large temperature gradient between and contractile thermal stresses inside the layer that cause the thermoplastic to shrink into a smaller volume allowing the voids to grow during deposition.

average

volume

voids

deposition

area

layer

layer

temperature gradient

layer

be

be

thermoplastic

thermal stresses

shrink


Input: A qualitative analysis of fiber orientation conducted on the SCF filament indicated that the SCFs maintain their orientation from filament to part except in the intersection zone of rasters.

qualitative

orientation

fiber orientation

filament

filament


Input: In the quest to achieve functional 3D printed parts with open source machines and tools it is required to study all the error sources.

3D printed parts

source

machines

tools

error


Input: Flow control is a major contributor to accuracy of parts manufactured additively with material extrusion and a precise filament feed rate is therefore essential.

accuracy

manufactured

material extrusion

filament

feed


Input: Filament slippage is measured in this work.

Filament


Input: The speed difference between filament feed gear speed and filament speed is measured with a cost effective, automated setup, using a low cost USB microscope video camera and image processing.

filament

filament

feed

microscope

camera

image


Input: The filament width is also measured simultaneously, allowing for real time volumetric flow rate estimation.

filament

flow rate


Input: Extrusion temperature and feed rate are found to influence the amount of slippage.

Extrusion

feed


Input: Proof of concept closed loop control of the extruder is also implemented and reduces the amount of slippage considerably.

closed loop control

extruder


Input: In this paper we present the results of a study on the impact of a thin reflective film between the substrate and photoresin on the two-photon polymerization procedure.

impact

substrate

polymerization


Input: We have proposed a model for the elementary polymerization volume (voxel) formation for the introduced case and carried out simulations to examine the influence of the refractive indexes relation, layer thickness, roughness, and polymerization depth on the polymerization performance.

model

voxel

performance

polymerization

polymerization

polymerization

simulations

layer thickness

roughness


Input: The experiments on fabrication of 2D and 2.5D structures have shown the benefit of the proposed configuration for the substrate/photoresin interface localization as well as for the distortion-free fabrication.

fabrication

fabrication

configuration

interface

as

as


Input: Directed energy deposition (DED) is a promising technique for cladding and repair due to its ability to deposit molten metal onto existing surfaces.

Directed energy deposition

DED

cladding

molten metal

surfaces


Input: To date, much still needs to be understood regarding the microstructure evolution during DED.

be

microstructure evolution

DED


Input: The work herein seeks to reveal the effect of build height on mechanical properties and corrosion for austenitic stainless steel 316L.

build height

mechanical properties

corrosion

austenitic stainless steel


Input: A large 316L block was fabricated via DED and horizontal tensile specimens were taken from every 3 mm along the build height in order to assess the effect of build height on the mechanical response.

fabricated

mechanical response

DED

mm

tensile specimens

build height

build height


Input: Electron backscatter diffraction mapping was also conducted on sections taken from the bottom, middle and top heights of the build, to assess the microstructural evolution.

Electron backscatter diffraction

build

microstructural evolution


Input: Cyclic polarisation testing was performed on sections from the build to assess the pitting potential and re-passivation as a function of build height.

testing

build

build height

pitting

as


Input: Parameters for selective laser melting of Zr59.3Cu28.8Al10.4Nb1.5 (trade name AMZ4), allowing crack-free bulk metallic glass with low porosity, have been developed.

Parameters

selective laser melting

metallic glass

porosity


Input: The phase formation was found to be strongly influenced by the heating power of the laser.

phase

be

heating

laser


Input: X-ray amorphous samples were obtained with laser power at and below 75 W. The as-processed bulk metallic glass was found to devitrify by a two-stage crystallization process within which the presence of oxygen was concluded to play an essential role.

X-ray

samples

crystallization

laser power

metallic glass

oxygen


Input: At laser powers above 75 W, the observed crystallites were found to be a cubic phase (Cu2Zr4O).

laser powers

crystallites

be

phase


Input: The hardness and Young’ s modulus in the as-processed samples was found to increase marginally with increased fraction of the crystalline phase.

hardness

s

samples

fraction

phase


Input: Large-scale printing technology is proposed for non-metallic lightning protection.

printing technology


Input: The printing process integrates continuous carbon fiber and E-Beam irradiation curing.

printing process

irradiation

curing

continuous carbon fiber


Input: Low-energy E-Beam is applied for fast and low-temperature curing adequacy of print.

curing

print


Input: Regarding impregnation of epoxy, the fiber content of this printing reached 58 wt%.

impregnation

epoxy

fiber


Input: Continuous fiber mesh provides comparative protection as commercial copper mesh.

Continuous fiber

as

copper


Input: Wind-turbine blades are more vulnerable to lightning strikes as they lack a protection system for large-scale glass fiber reinforced polymer (GFRP) composite structures.

as

glass fiber

polymer

composite structures


Input: A low-energy electron beam (EB) cured printing process for fabricating a continuous carbon fiber-reinforced thermoset resin as a non-metallic lightning protection mesh on a GFRP composite surface was carried out in this study.

electron beam

process

cured

fabricating

carbon

resin

as

composite


Input: During the proposed process, a continuous carbon fiber mesh was printed through a Fused Filament Fabrication that integrates the rapid curing of an epoxy resin with low-energy EB irradiation.

process

continuous carbon fiber

epoxy

Fused Filament Fabrication

curing

irradiation


Input: The printing process was analyzed and optimized by examining the correlation between the EB exposure dose and the printing height.

printing process

exposure


Input: Results from artificial lightning strikes showed that the printed carbon fiber mesh prevented damage, and the structure remained relatively intact with residual strength reaching 90.1% at 100 kA maximum peak current.

carbon fiber

damage

structure

residual


Input: The protection mechanism was investigated using a high-speed camera, which revealed that the carbon fiber mesh spreads the striking current outside the laminate instead of penetrating inside.

mechanism

laminate

camera

carbon fiber


Input: In selective laser melting (SLM) products are built by melting layers of metal powder successively.

selective laser melting

SLM

melting

metal powder


Input: Optimal process parameters are usually obtained by scanning single vectors and subsequently determining which settings lead to a good compromise between product density and build speed.

Optimal process

build speed

scanning

lead

density


Input: This paper proposes a model that describes the effects occurring when scanning single vectors.

model

scanning


Input: Energy absorption and heat conduction are modeled to determine the temperature distribution and melt pool characteristics for different laser powers, scan speeds and layer thicknesses.

Energy absorption

heat conduction

distribution

temperature

laser powers

scan speeds

layer thicknesses

melt pool


Input: The model shows good agreement with experimentally obtained scan vectors and can therefore be used to predict SLM process parameters.

model

process parameters

be

SLM


Input: This research investigates the microstructure, mechanical, residual stress and tribological properties of as-printed Inconel 718 by laser powder bed fusion.

research investigates

microstructure

tribological properties

mechanical

residual stress

Inconel 718

laser powder bed fusion


Input: The microstructure exhibits a hierarchical structure composed of melt pool boundaries and directionally solidified columnar thin dendrites.

microstructure

melt pool boundaries

hierarchical structure

directionally solidified

dendrites


Input: No significant size of defects or undesirable phases such as Laves phases or macrosegregation was found in the microstructure.

defects

macrosegregation

microstructure

as


Input: The Vickers microhardness results did not show any significant differences in hardness value across the tracks and layers of melt pool boundaries.

microhardness

melt pool boundaries

hardness


Input: The hot tribological behaviour of the alloy was investigated for the range of temperatures (28 °C, 400 °C, 500 °C and 600 °C) in a high temperature pin (Inconel 718) on disc (EN31 steel) set up.

tribological

alloy

Inconel 718

steel

range

temperatures

temperature

set


Input: The worn surface and loose wear debris were analysed with the aid of SEM/EDS and XRD analysis.

surface

wear

XRD


Input: The wear loss and friction coefficient increase with the test temperature.

wear

friction

temperature


Input: The friction results show the running-in-period and steady-state-period for the high temperature cases.

friction

temperature


Input: The abrasion wear is predominant at 28 °C.

wear


Input: In contrast, delamination wear and oxidation wear are dominant for high temperature cases.

delamination

oxidation

temperature


Input: The observation of high friction and wear loss with the test temperature is attributed to the increased intensity of delamination wear and oxidation rate of non-lubricative NiO.

friction

wear

delamination

temperature

oxidation

NiO


Input: The wear debris size increases with the test temperature and the shape has undergone changes from short angular to long angular sheets.

wear

temperature

sheets


Input: Single-pass depositions of columnar René 142 on investment cast single-crystal (SX) René N5 substrates having [100] and [001] primary dendrite growth directions were obtained through scanning laser epitaxy (SLE), a laser powder bed fusion (LPBF) -based additive manufacturing (AM) process.

cast

laser powder bed fusion

LPBF

additive manufacturing

AM

dendrite

scanning

epitaxy

process

laser


Input: The microstructure and the microhardness properties of the René 142 deposits were investigated through high-resolution optical microscopy (HR-OM), scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDS), x-ray diffraction (XRD), electron backscatter diffraction (EBSD), and micro-hardness measurements.

microstructure

microhardness

high-resolution

microscopy

scanning electron microscopy

SEM

energy dispersive x-ray spectroscopy

EDS

x-ray diffraction

XRD

electron backscatter diffraction

EBSD


Input: SEM investigations demonstrated that the primary γ/γ′ precipitates in the deposit region were 90% finer in size compared to the substrate.

SEM

precipitates

substrate


Input: Microhardness measurements showed an increase in the hardness values by ∼10% in the deposit region compared to the cast substrate.

Microhardness

hardness

cast


Input: The results showed that the SLE process has tremendous potential in producing epitaxial deposits of nickel-based superalloys and, therefore, the findings reported in this work can pave ways to fabricate components with dissimilar-chemistry high-γ′ nickel-based superalloys using an LPBF-based AM process.

process

epitaxial

nickel-based superalloys

nickel-based superalloys

fabricate

AM process

components


Input: Neutron diffraction study of poly-crystalline bulk samples of Ti-6Al-4V, prepared using selective laser melting (SLM) and electron beam melting (EBM), and of their ingredient powders, is reported.

Neutron diffraction

samples

powders

selective laser melting

SLM

electron beam melting

EBM


Input: Both the SLM and EBM samples do not contain the macro- and micro-strain, found in the ingredient powder particles.

SLM

EBM

powder particles


Input: In addition, the micro-structure of the EBM sample is found free of preferential orientation, whereas in the SLM sample significant preference towards the hexagonal basal plane is found.

EBM

SLM

orientation

sample

basal plane

hexagonal


Input: Hot-rolled Inconel 718 showed superior creep performance to LPBF Inconel 718.

Inconel 718

Inconel 718

creep

LPBF


Input: HIPing worsened creep life and HT improved creep life of LPBF Inconel 718.

creep

creep

LPBF

Inconel 718


Input: Intergranular precipitation in the HIP’ d samples explained worse creep performance.

precipitation

samples

HIP

creep


Input: Hot-rolled samples avoided intergranular fracture.

samples

fracture


Input: In this study, the creep performance of laser powder bed fusion manufactured Inconel 718 specimens is studied in detail and compared with conventional hot-rolled specimens alongside as-built then heat-treated and as-built then hot-isostatic pressed specimens.

creep

laser powder bed fusion

heat-treated

pressed

Inconel 718


Input: Hot-rolled specimens showed the best creep resistance, while the hot-isostatic pressed specimens yielded the worst performance, inferior to the as-built condition.

creep

pressed

performance


Input: Creep testing of all samples showed increased secondary creep rate was consistently correlated with a reduced life.

Creep

creep

samples

correlated


Input: Fractography revealed intergranular fracture was the primary failure mode for all as-built samples.

Fractography

fracture

samples

failure mode


Input: Preferential intergranular precipitation in the case of the hot-isostatic pressed specimens during hot-isostatic pressing extensive intergranular cracking as the primary failure mechanism.

precipitation

cracking

pressed

pressing

as

failure mechanism


Input: Heat-treated specimens possessed only sparse intergranular precipitates, thereby explaining an improved creep lifetime.

Heat-treated

precipitates

creep


Input: The hot-rolled specimens, having smallest grain size, showed the least extensive cracking, particularly in locations of finest grains, explaining avoidance of intergranular fracture as a key creep mechanism, thereby explaining the ductile creep fracture surfaces in the case of the hot-rolled samples.

grain size

creep

ductile creep

cracking

grains

fracture

surfaces

samples

as


Input: The build-up of residual stresses in a part during laser powder bed fusion provides a significant limitation to the adoption of this process.

residual stresses

laser powder bed fusion

process


Input: These residuals stresses may cause a part to fail during a build or fall outside the specified tolerances after fabrication.

residuals

build

tolerances

fabrication


Input: In the present work a thermomechanical model is used to simulate the build process and calculate the residual stress state for Ti–6Al–4V specimens built with continuous and island scan strategies.

thermomechanical model

build

residual stress


Input: A material model is developed to naturally capture the strain-rate dependence and annealing behavior of Ti–6Al–4V at elevated temperatures.

material

annealing

temperatures


Input: Results from the thermomechanical simulations showed good agreement with synchrotron X-ray diffraction measurements used to determine the residual elastic strains in these parts.

thermomechanical

residual

simulations

synchrotron

diffraction

elastic


Input: However, the experimental measurements showed higher residual strains for the specimen built with an island scan strategy; a trend not fully captured by the simulations.

experimental

residual

trend

simulations


Input: Parameter studies were performed to fully understand the advantages and limitations of the current simulation methodology.

Parameter

methodology

simulation


Input: Using defocus can lead to a stable SLM process with high build rates.

lead

SLM

process

build rates


Input: Melt pool morphology can be predicted by normalized enthalpy and Rosenthal equation Melt pool depth is more influenced by defocusing than its width.

Melt pool

be

Rosenthal equation

Melt pool depth


Input: Despite its many benefits, Selective Laser Melting's (SLM) relatively low productivity compared to deposition-based additive manufacturing techniques is a major drawback.

Selective Laser Melting

SLM

additive manufacturing

productivity


Input: Increasing the laser beam diameter improves SLM's build rate, but causes loss of precision.

laser beam diameter

SLM

build rate

precision


Input: The aim of this study is to investigate laser beam focus shift, or “defocus”, using a dynamic focusing unit, in order to increase the laser spot size.

laser beam

dynamic

laser spot size


Input: When applied to the SLM process, focus shift can be integrated into a “hull-core” strategy.

SLM

process

be


Input: This involves scanning the core with a high productivity parameter set using defocus while enabling return to the focused smaller spot size position for hull scanning.

scanning

productivity

parameter

scanning

core

spot size


Input: To assess the process stability, single line scans were made from 316L stainless steel powder.

process

316L stainless steel powder


Input: The consolidated melt pool morphology was analyzed and correlated with the process parameters comprising laser power, scanning speed and defocus distance.

melt pool

correlated

process parameters

laser power

scanning speed


Input: In order to link the melt pool morphology with the heat input, Volumetric Energy Density, Normalized Enthalpy and Rosenthal equation were considered.

melt pool

heat

Rosenthal equation

Energy Density


Input: The suitability of using the Normalized Enthalpy as a design parameter to predict the melt pool depth and Rosenthal equation to predict its width was highlighted.

as

design

melt pool depth

Rosenthal equation


Input: This study shows that within a single laser setup, implementing defocus can lead to a potential productivity increase by 840%, i.e.

laser

lead

productivity


Input: New generation of selective Laser Melting (SLM) machines are evolving towards higher power lasers as well as multi laser systems in order to increase the productivity.

selective Laser Melting

SLM

machines

power

as

as

laser

productivity


Input: The increase in laser power and the modification of the laser power distribution leads to microstructural and mechanical property variations that are still not well understood.This work aims at better understanding the interaction of a 1 kW top-hat power distribution laser on a well know material, 316 L stainless steel.

laser power

laser power

power

distribution

microstructural

mechanical property

distribution

material

stainless steel


Input: The influence of texture and microstructure on relative density and crack density, when varying scan rotation, was evaluated.

texture

microstructure

relative density

density


Input: The high power (HP) laser and low power (LP) laser were compared with respect to microstructure and mechanical properties.

power

power

laser

laser

microstructure

mechanical properties


Input: HP leads to an increase in morphological and crystallographic texture together with a coarsening of the cell structure in contrast to the more random and finer cells found in LP processed material.

texture

cell

cells

processed material


Input: Hot isostatic pressing was applied as a post-process treatment in order to close remaining pores and cracks.

Hot isostatic pressing

as

post-process

pores


Input: This helped in achieving higher elongations for LP and HP processed materials, while competitive mechanical properties to the 316 L material specifications were obtained in both cases.

processed materials

mechanical properties

material


Input: Laser sintering (LS) of polymer materials is a process that has been developed over the last two decades and has been applied in industries ranging from aerospace to sporting goods.

Laser sintering

polymer materials

process

industries

aerospace


Input: However, one of the current major limitations of the process is the restricted range of usable materials.

process

materials

range


Input: Various material characteristics have been proposed as being important to optimise the laser sintering process, key aspects of which have been combined in this work to develop an understanding of the most crucial requirements for LS process design and materials selection.

Various material

as

laser sintering

process

materials

design


Input: Using the favourable characteristics of polyamide-12 (the most often used material for laser sintering) as a benchmark, a previously un-sintered thermoplastic elastomer material was identified as being suitable for the LS process, through a combination of information from Differential Scanning Calorimetry (DSC), hot stage microscopy (HSM) and knowledge of viscosity data.

material

as

thermoplastic elastomer

material

as

laser sintering

benchmark

process

Scanning

data

DSC

microscopy

viscosity


Input: Subsequent laser sintering builds confirmed the viability of this new material, and tensile test results were favourable when compared with materials that are currently commercially available, thereby demonstrating the efficacy of the chosen selection process.

laser sintering

builds

tensile test

material

materials

process


Input: Selective laser melting is already established as a commercial production technique.

Selective laser melting

production

as


Input: In-situ process monitoring is a promising means to accommodate this issue, but quantitative correlations between monitoring signals and actual part defects have been lacking.

In-situ

quantitative

defects


Input: In this paper, results are presented that have been obtained with an off-axis melt pool monitoring system on a 3D Systems ProX DMP 320 using Ti-6Al-4 V ELI.

melt pool

Ti-6Al-4 V

3D Systems


Input: The focus is on the development of a method for predicting the presence and location of lack of fusion porosities as they can have a large impact on part quality and are not always easily detected post-build.

fusion

impact

quality

as


Input: The processed signals from the monitoring system are shown to have a high degree of correlation with the presence of lack of fusion porosities as measured by CT scans.

processed

fusion

as

CT


Input: A prediction sensitivity of 90% for lack of fusion events in the range of pores having a volume greater than 0.001 mm3, roughly equivalent to 160 μm in diameter, was obtained.

prediction

fusion

volume

diameter

range

pores


Input: Relationships between prior beta grain size in solidified Ti-6Al-4V and melting process parameters in the Electron Beam Melting (EBM) process are investigated.

grain size

melting

Electron Beam Melting

EBM

parameters

process


Input: Samples are built by varying a machine-dependent proprietary speed function to cover the process space.

Samples

process


Input: Optical microscopy is used to measure prior beta grain widths and assess the number of prior beta grains present in a melt pool in the raster region of the build.

Optical microscopy

grain

grains

melt pool

build


Input: Despite the complicated evolution of beta grain sizes, the beta grain width scales with melt pool width.

evolution

grain

grain sizes

melt pool


Input: The resulting understanding of the relationship between primary machine variables and prior beta grain widths is a key step toward enabling the location specific control of as-built microstructure in the EBM process.

machine

grain

step

microstructure

EBM


Input: The selective laser melting (SLM) process is used throughout the world.

selective laser melting

SLM

process


Input: This process is based on the continuous (layer by layer) surfacing of metallic powder which is fused by laser or high-power electron beam.

process

layer by layer

fused

electron beam

metallic powder

laser


Input: In this paper is presented studies of the structure of a nickel alloy (EP718) component formed using the SLM process, and the effects of heat treatment and hot isostatic pressing (HIP) on the mechanical properties of samples manufactured by SLM technology.

structure

process

mechanical properties

samples manufactured

nickel alloy

component

SLM

heat treatment

hot isostatic pressing

HIP

SLM


Input: Mechanical tests have shown that components formed using SLM exhibit a low level of strength but with a high degree of plasticity.

Mechanical tests

components

SLM

strength

plasticity


Input: Subsequent heat treatment led to an increase in strength and a corresponding reduction in plasticity owing to the formation of reinforcing particles of molybdenum silicides and an incomplete relaxation, with low grain growth.

heat treatment

strength

plasticity

reduction

particles

grain growth

molybdenum


Input: However, a combination of SLM + HIP + heat treatment resulted in optimum levels of strength and plasticity in comparison with other samples.

SLM

HIP

heat treatment

strength

plasticity

samples


Input: In this work, 3D cubic test specimens were manufactured by Selective Laser Melting (SLM) from commercially available Ni/Fe-based superalloy powder, and were further subjected to heat treatment.

manufactured

Selective Laser Melting

SLM

heat treatment

powder


Input: The evolution of their microstructure, phase composition and microhardness were analysed in relation to the applied heat-treatment procedure.Parametric study of the SLM process allows determination of a suitable parametric set for obtaining of 3D objects from the Ni/Fe-based single-crystal superalloy Thymonel-2, with the resulting porosity of 0.35% .The manufactured 3D specimens were subjected to three different heat-treatment procedures.

evolution

microstructure

phase composition

microhardness

process

manufactured 3D

SLM

set

3D objects

porosity


Input: The microstructure and the phase composition of the as-manufactured and the heat-treated samples were analysed in order to study the microstructure-microhardness correlation of Thymonel-2.XRD analysis of the as-manufactured samples reveals the presence of the fcc γ- (Fe, Ni) phase only.

microstructure

phase composition

samples

fcc

phase

heat-treated

Fe

Ni


Input: The literature reports a considerable amount of γ′ phase in Ni/Fe-based superalloys processed by conventional metallurgy.

phase

processed

metallurgy

superalloys


Input: The absence of the γ′ can be explained by extremely high cooling rates during SLM which prevents precipitation.

be

cooling rates

SLM

precipitation


Input: Post heat-treatment of the specimens leads to significant changes in microstructure and the resulting 30–90% increase in microhardness.Recommendations on SLM strategy and post heat-treatment of Thymonel-2 are provided.

Post heat-treatment

SLM

post heat-treatment

microstructure


Input: This work presents a novel modeling framework combining computational fluid dynamics (CFD) and cellular automata (CA), to predict the solidification microstructure evolution of laser powder bed fusion (PBF) fabricated 316 L stainless steel.

modeling

framework

solidification microstructure

evolution

fabricated

computational fluid dynamics

CFD

CA

stainless steel

laser powder bed fusion

PBF


Input: A CA model is developed which is based on the modified decentered square method to improve computational efficiency.

CA

computational efficiency


Input: Using this framework, the fluid dynamics of the melt pool flow in the laser melting process is found to be mainly driven by the competing Marangoni force and the recoil pressure on the liquid metal surface.

framework

process

force

pressure

fluid

melt pool

be

liquid metal

laser


Input: Evaporation occurs at the front end of the laser spot.

Evaporation

laser


Input: The initial high temperature occurs in the center of the laser spot.

temperature

laser


Input: However, due to Marangoni force, which drives high-temperature liquid flowing to low-temperature region, the highest temperature region shifts to the front side of the laser spot where evaporation occurs.

force

evaporation

temperature

laser


Input: Additionally, the recoil pressure pushes the liquid metal downward to form a depression zone.

pressure

liquid metal


Input: The simulated melt pool depths are compared well with the experimental data.

melt pool depths

experimental data


Input: Additionally, the simulated solidification microstructure using the CA model is in a good agreement with the experimental observation.

solidification microstructure

experimental

CA


Input: The simulations show that higher scan speeds result in smaller melt pool depth, and lack-of-fusion pores can be formed.

simulations

scan speeds

melt pool depth

pores

be


Input: Higher laser scan speed also leads to finer grain size, larger laser-grain angle, and higher columnar grain contents, which are consistent with experimental observations.

laser scan

grain size

columnar grain

experimental


Input: This model can be potentially used as a tool to optimize the metal powder bed fusion process, through generating desired microstructure and resultant material properties.

model

microstructure

material properties

be

as

tool

metal powder bed fusion


Input: We report our efforts toward 3D printing of polyether ether ketone (PEEK) at room temperature by direct-ink write technology.

3D printing

PEEK

temperature

technology


Input: The room-temperature extrusion printing method was enabled by a unique formulation comprised of commercial PEEK powder, soluble epoxy-functionalized PEEK (ePEEK), and fenchone.

extrusion

PEEK

PEEK

soluble


Input: This combination formed a Bingham plastic that could be extruded using a readily available direct-ink write printer.

plastic

be

printer


Input: The initial green body specimens were strong enough to be manipulated manually after drying.

green body

be

drying


Input: After printing, thermal processing at 230 °C resulted in crosslinking of the ePEEK components to form a stabilizing network throughout the specimen, which helped to preclude distortion and cracking upon sintering.

components

distortion

cracking

sintering


Input: The final parts were found to have excellent thermal stability and solvent resistance.

thermal stability

resistance


Input: The Tg of the product specimens was found to be 158 °C, which is 13 °C higher than commercial PEEK as measured by DSC.

Tg

DSC

be

PEEK

as


Input: Moreover, the thermal decomposition temperature was found to be 528 °C, which compares well against commercial molded PEEK samples.

thermal decomposition

temperature

be

PEEK


Input: Chemical resistance in trifluoroacetic acid and 8 common organic solvents, including CH2Cl2 and toluene, were also investigated and no signs of degradation or weight changes were observed from parts submerged for 1 week in each solvent.

Chemical resistance

degradation

weight


Input: Test specimens also displayed desirable mechanical properties, such as a Young’ s modulus of 2.5 GPa, which corresponds to 63% of that of commercial PEEK (reported to be 4.0 GPa).

mechanical properties

as

s

PEEK

be

GPa

GPa


Input: Due to the relative youth of metallic powder bed additive manufacturing technologies and difficulties with monitoring the process in situ, there is little consensus in the user community on how to optimize user variable parameters to ensure the highest quality and most cost effective build.

metallic powder

bed

additive manufacturing

process

in situ

parameters

quality

build


Input: Temperature distribution is the critical factor that dictates melting, microstructure and eventually the final part quality.

Temperature

distribution

microstructure

quality

critical factor

melting


Input: Monitoring or measuring the temperature during the process is extremely difficult due to the ultra-high speeds and microscale size of the laser or electron beam.

temperature

process

microscale

electron beam

laser


Input: Therefore, other tools such as finite element modeling can be utilized to optimize these processes and predict the behavior of the system for different materials.

tools

as

element

be

processes

materials


Input: This research presents transient, dynamic finite element model of the build process for both laser and electron beam melting techniques.

research

transient

dynamic

element

build

laser

electron beam melting


Input: The model includes melting and solidification of the powder as well as different thermal aspects such as conduction and radiation.

model

solidification

melting

radiation

powder

as

as

as


Input: Diffusivity of the powder is modeled and phase change is modeled such that latent heat of fusion is considered.

Diffusivity

powder

phase

latent heat of fusion


Input: Melt pool geometry and temperature distribution was obtained for different heat sources and different materials such as Ti6Al4V, Stainless Steel 316, and 7075 Aluminum powders.

Melt pool

as

Stainless Steel

Aluminum

geometry

distribution

heat sources

materials

temperature


Input: It was determined that heat accumulation is most consolidated within titanium powder beds, with steel being the second most consolidated, and aluminum powder beds having the most heat dissipation.

heat accumulation

titanium powder

steel

aluminum

heat dissipation


Input: As a result, titanium was seen to exhibit the highest local temperatures and largest melt pools, followed by steel and aluminum in decreasing order.

As

titanium

melt pools

steel

aluminum

temperatures


Input: Naturally, laser models showed smaller melt pool sizes and depths due to lower power.

laser

melt pool

power


Input: The beam speed and power used for Ti were found inadequate for creating a sustained and continuous melting of Al and Steel.

beam

power

Ti

Al

Steel

melting


Input: Therefore, adjustments were made to these parameters and presented in this research.

parameters

research


Input: An effective liquid conductivity approach has been developed to describe the convective transport modes existing within the melt pool in powder bed additive manufacturing processes.

conductivity

transport

melt pool

powder bed additive manufacturing


Input: A first principles approach is introduced to derive an effective conductive transport mode that encompasses conduction and advection within the melt pool.

first principles

transport

melt pool


Input: A modified Bond number was calculated by comparing surface tension forces with viscous forces within the melt pool region.

surface tension

forces

viscous forces

melt pool


Input: It was determined, due to the small size scale of melt pools in powder bed processes, that the surface tension gradient driven flow, or the Marangoni effect, is the dominant mass transport phenomenon within the melt pool.

melt pools

melt pool

powder bed

surface tension

transport


Input: Validation was conducted by comparing simulation melt pool widths and depths against experimental measurements for Inconel 718 built at beam powers of 150 W, 200 W and 300 W and a scan speed of 200 mm/s.

Validation

experimental

simulation

melt pool

Inconel 718

beam

scan speed


Input: By introducing the effective liquid conductivity, simulated melt pool widths were up to 50% closer to experimental widths and simulated melt pool depths were up to 80% closer to experimental measurements.

conductivity

melt pool

experimental

experimental

melt pool depths


Input: Analytic temperature profiles and melt pool dimensions are compared between Ti6Al4V, Stainless Steel 316L, Aluminum 7075 and Inconel 718 built with similar process parameters, while including effective liquid conductivity.

temperature

melt pool dimensions

profiles

Stainless Steel

Aluminum 7075

Inconel 718

process parameters

conductivity


Input: The reasons for differences in temperature and melt pool geometry are discussed.

temperature

melt pool

geometry


Input: Experimental measurements are a critical component of model development, as they are needed to validate the accuracy of the model predictions.

Experimental

model

model

component

as

accuracy


Input: Currently, there is a deficiency in the availability of experimental data for laser powder bed fusion made parts.

experimental data

laser powder bed fusion


Input: Here, two experimental builds of cylindrical geometry, one using a rotating scan pattern and the other using a constant scan pattern, are designed to provide post-build distortion measurements.

experimental

cylindrical

distortion

builds

scan pattern

scan pattern

designed


Input: Measurements show that for these cylindrical thin wall builds, there is no discernable effect on distortion from using the rotating versus constant scan patterns.

cylindrical

discernable

distortion

builds

scan patterns


Input: Project Pan finite element modeling software is used to model each of the experimental builds.

finite element

software

model

experimental

builds


Input: The simulation results show good agreement with experimental measurements of post-build deformation, within a 12% percent error as compared to experimental measurements.

simulation

experimental

deformation

error

experimental

as


Input: Using the FE model, the effect of a flexible versus a rigid substrate on distortion profile is examined.

FE

substrate

distortion


Input: The FE model is validated against in situ experimental measurements of substrate distortion.

FE

substrate

in situ

experimental

distortion


Input: The simulated results are used to study stress and distortion evolution during the build process.

stress

distortion

build


Input: Internal stresses calculated by the model throughout the part are used in explaining the final part distortion.

Internal stresses

model

distortion


Input: The combination of experimental and simulation results from this study show that the distortion of the top layer is relatively small (less than 30%) throughout the duration of the build process compared to the peak distortion, which occurs several layers below the most recently deposited layer.

experimental

distortion

distortion

simulation

layer

build

deposited layer


Input: Designing metallic cellular structures with triply periodic minimal surface (TPMS) sheet cores is a novel approach for lightweight and multi-functional structural applications.

metallic

sheet

cellular structures

triply periodic minimal surface

lightweight

cores


Input: Different from current honeycombs and lattices, TPMS sheet structures are composed of continuous and smooth shells, allowing for large surface areas and continuous internal channels.

lattices

sheet

surface areas


Input: In this paper, we investigate the mechanical properties and energy absorption abilities of three types of TPMS sheet structures (Primitive, Diamond, and Gyroid) fabricated by selective laser melting (SLM) with 316 L stainless steel under compression loading and classify their failure mechanisms and printing accuracy with the help of numerical analysis.

mechanical properties

fabricated

energy absorption

accuracy

sheet

Diamond

stainless steel

selective laser melting

SLM

compression

failure mechanisms


Input: Experimental results reveal the superior stiffness, plateau stress and energy absorption ability of TPMS sheet structures compared to body-centred cubic lattices, with Diamond-type sheet structures performing best.

Experimental

lattices

stiffness

stress

energy absorption

sheet

sheet


Input: Nonlinear finite element simulation results also show that Diamond and Gyroid sheet structures display relatively uniform stress distributions across all lattice cells under compression, leading to stable collapse mechanisms and desired energy absorption performance.

finite element

lattice

Diamond

sheet

stress distributions

compression

cells

energy absorption


Input: Parts manufactured by laser powder bed fusion contain significant residual stress.

manufactured

laser powder bed fusion

residual stress


Input: This stress causes failures during the build process, distorts parts and limits in-service performance.

stress

build

limits

performance


Input: A pragmatic finite element model of the build process is introduced here to predict residual stress in a computationally efficient manner.

finite element model

build

residual stress


Input: The part is divided into coarse sections which activate at the melting temperature in an order that imitates the build process.

melting temperature

build


Input: Temperature and stress in the part are calculated using a sequentially coupled thermomechanical analysis with temperature dependent material properties.

Temperature

temperature

stress

thermomechanical

material properties


Input: The model is validated against two sets of experimental measurements: the first from a bridge component made from 316L stainless steel and the second from a cuboidal component made from Inconel 718.

model

experimental

bridge

316L stainless steel

Inconel 718

component


Input: For the bridge component the simulated distortion is within 5% of the experimental measurement when modelled with a section height of 0.8 mm.

bridge

distortion

experimental

mm


Input: This is 16 times larger than the 50 μm layer height in the experimental part.

layer height

experimental


Input: For the cuboid component the simulated distortion is within 10% of experimental measurement with a section height 10 times larger than the experiment layer height.

component

distortion

experimental

experiment


Input: These results show that simulation of every layer in the build process is not required to obtain accurate results, reducing computational effort and enabling the prediction of residual stress in larger components.

simulation

layer

build

accurate

prediction

residual stress

components


Input: A mesoscale multi-physics model is developed to simulate rapid solidification.

mesoscale

model

rapid solidification


Input: Solute transport, phase transition, heat transfer, latent heat, and melt flow are modeled.

transport

phase

heat transfer

heat

melt flow


Input: Powder bed fusion is a recently developed additive manufacturing (AM) technique for alloys, which builds parts by selectively melting metallic powders with a high-energy laser or electron beam.

Powder bed fusion

additive manufacturing

AM

melting

alloys

powders

builds

laser

electron beam


Input: Nevertheless, there is still a lack of fundamental understanding of the rapid solidification process for better quality control.

rapid solidification process

quality control


Input: To simulate the microstructure evolution of alloys during the rapid solidification, in this research, a mesoscale multi-physics model is developed to simultaneously consider solute transport, phase transition, heat transfer, latent heat, and melt flow.

microstructure evolution

research

mesoscale

model

phase

heat transfer

heat

melt flow

alloys

rapid solidification

transport


Input: In this model, the phase-field method simulates the dendrite growth of alloys, whereas the thermal lattice Boltzmann method models heat transfer and fluid flow.

model

lattice

heat transfer

dendrite

alloys

fluid flow


Input: The simulation results of Ti-6Al-4V show that the consideration of latent heat is necessary because it reveals the details of the formation of secondary arms and provides more realistic kinetics of dendrite growth.

simulation

heat

dendrite


Input: The proposed multi-physics simulation model provides new insights into the complex solidification process in AM.

simulation

model

solidification process

AM


Input: Relationship between laser energy density and thermal expansion was explained.

laser energy density

thermal expansion


Input: Critical laser energy density exists for each material.

laser energy density

material


Input: Void formation and alloying element vaporization occurred during selective laser melting of Ni- and Fe-based alloys.

Void

alloying element

alloys

selective laser melting


Input: Magnetic properties and thermal expansion coefficients of parts produced were quantified.

properties

thermal expansion coefficients


Input: Process window was determined for Invar 36 and stainless steel 316 L based on stable melting.

Process

Invar

stainless steel

melting


Input: This paper presents an experimental study on the metallurgical issues associated with selective laser melting of Invar 36 and stainless steel 316 L and the resulting coefficient of thermal expansion.

experimental

metallurgical

selective laser melting

Invar

stainless steel

coefficient of thermal expansion


Input: Invar 36 has been used in aircraft control systems, electronic devices, optical instruments, and medical instruments that are exposed to significant temperature changes.

Invar

control systems

optical

medical

temperature


Input: Stainless steel 316 L is commonly used for applications that require high corrosion resistance in the aerospace, medical, and nuclear industries.

Stainless steel

corrosion resistance

aerospace

medical

industries


Input: Both Invar 36 and stainless steel 316 L are weldable austenitic face-centered cubic crystal structures, but stainless steel 316 L may experience chromium evaporation and Invar 36 may experience weld cracking during the welding process.

Invar

stainless steel

austenitic

stainless steel

chromium

Invar

crystal structures

weld

cracking

process

welding


Input: Various laser process parameters were tested based on a full factorial design of experiments.

laser

parameters

factorial design


Input: The microstructure, material composition, coefficient of thermal expansion, and magnetic dipole moment were measured for both materials.

microstructure

composition

materials

material

coefficient of thermal expansion


Input: It was found that there exists a critical laser energy density for each material, EC, for which selective laser melting process is optimal for material properties.

laser energy density

material

selective laser melting process

material properties


Input: The critical laser energy density provides enough energy to induce stable melting, homogeneous microstructure and chemical composition, resulting in thermal expansion and magnetic properties in line with that expected for the wrought material.

laser energy density

melting

homogeneous

chemical composition

thermal expansion

properties

wrought material


Input: Below the critical energy, a lack of fusion due to insufficient melt tracks and discontinuous beads was observed.

fusion

melt

beads


Input: The melt track was also unstable above the critical energy due to vaporization and microsegregation of alloying elements.

melt

microsegregation

alloying elements


Input: Both cases can generate stress risers and part flaws during manufacturing.

stress

risers

flaws

manufacturing


Input: These flaws could be avoided by finding the critical laser energy needed for each material.

flaws

laser energy

be

material


Input: The critical laser energy density was determined to be 86.8 J/mm3 for Invar 36 and 104.2 J/mm3 for stainless steel 316 L. The present study investigated the effects of set radius of curvature and fiber bundle size on the precision of the radius of curvature during continuous carbon fiber three-dimensional (3D) printing.

laser energy density

be

Invar

stainless steel

fiber bundle

continuous carbon fiber

set

precision


Input: First, individual circles with various radii using various sizes of fiber bundles were printed with a 3D printer.

fiber bundles

3D printer


Input: It was demonstrated that with a larger fiber bundle size or a smaller set radius, the printed radius would be lower than the set value.

fiber bundle

be

set

set


Input: Equiatomic CoCrFeMnNi HEA was successfully fabricated by SLM.

fabricated

SLM


Input: The XRD profiles of the SLM-CoCrFeMnNi HEA were refined by the Rietveld program.

XRD

profiles


Input: The effect of the peak load on the creep deformation was investigated by nanoindentation with a Berkovich indenter.

creep

nanoindentation

Berkovich indenter


Input: The creep was mainly dominated by deformation controlled by dislocation motion.

creep

deformation

dislocation motion


Input: Selective laser melting (SLM) was used to fabricate an equiatomic CoCrFeMnNi high-entropy alloy (HEA).

Selective laser melting

SLM

fabricate

alloy


Input: The SLM-fabricated CoCrFeMnNi HEA samples were studied with X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), electron backscatter diffraction (EBSD) and nanoindentation techniques to characterize the microstructure and creep behavior.

samples

microstructure

X-ray diffraction

XRD

scanning electron microscopy

FESEM

electron backscatter diffraction

EBSD

nanoindentation

creep behavior


Input: It was found that the HEA comprised a single face-centered cubic (fcc) structure.

fcc

structure


Input: Due to the fast solidification and high temperature gradients of the molten pool during the SLM process, the microstructure comprised cellular subgrains with grain boundary angles lower than 5°.

solidification

molten pool

process

microstructure

subgrains

grain boundary

temperature gradients

SLM


Input: Moreover, the effect of the peak holding load on the nanoindentation creep deformation of the SLM-fabricated HEA was investigated using a Berkovich indenter.

nanoindentation

Berkovich indenter

creep


Input: The results of this study indicated that the creep was mainly dominated by deformation controlled by dislocation motion.

creep

deformation

dislocation motion


Input: Spatter distribution on AlSi10Mg powder bed was quantified in terms of mass, size and processed images.

Spatter

distribution

processed images

bed


Input: Established vision methodology showed moderate positive relationship with quantified mass of spatter.

methodology

spatter


Input: Spatter mass and size distributions could serve as ground truth validation data for future simulation studies.

Spatter

distributions

validation data

as

simulation


Input: Exponential decay in the Stk number with respect to the distance travelled by the spatter particles.

spatter

particles


Input: In Selective Laser Melting (SLM), inert gas is pumped into the chamber to eliminate the deleterious by-products, which includes spatter.

Selective Laser Melting

SLM

inert gas

spatter


Input: Despite this, traces of spatter on the powder bed have always been observed.

spatter

powder bed


Input: Earlier research mainly focussed on the formation and characterization of spatter particles that were freshly ejected from the melt pool.

research

particles

spatter

melt pool


Input: However, in this study, the quantification of the spatter distribution on the powder bed was performed, following their transport by the inert gas flow which was varied at two gas pump settings (60 and 67%).

spatter

transport

distribution

inert gas

gas

powder bed


Input: Image processing for spatter detection based on contrast was first conducted.

Image

spatter


Input: The sieved out spatter particles were quantified by precision weighing of mass.

spatter

precision

particles


Input: Optical microscopy was then utilised for size determination.

Optical microscopy


Input: The majority of spatter particles were originally distributed along the −x direction, as observed from the top down images taken.

spatter

particles

images

as


Input: However, increasing the gas flow velocity did not correspond to a lesser mass distribution.

gas

distribution


Input: Computations on the Stk number revealed that at the gas pump setting of 67%, spatter particles of greater size were deposited earlier on the powder bed, suggesting that increasing the gas flow velocity to a large extent would increase the likelihood of powder bed contamination.

gas

particles

gas

spatter

powder bed

powder bed


Input: The forward extrapolation of the exponential Stk number trendlines also elucidated the reason for the limitations on the width of the powder bed in machines designed by SLM Solutions.

powder bed

machines

designed

SLM


Input: Bulk high strength and thermally stable Al85Nd8Ni5Co2 samples have been prepared by selective laser melting (SLM).

strength

samples

selective laser melting

SLM


Input: The alloy shows a composite-like microstructure consisting of submicron-sized stable intermetallic phases dispersed in an Al matrix, which leads to high compressive strength (1–0.5 GPa) at elevated temperatures (303–573 K).

alloy

intermetallic

Al

K

microstructure

compressive strength

GPa

temperatures


Input: These results indicate that SLM is an effective alternative to conventional routes for producing dense, thermally stable and near net shaped components from high strength Al-based alloys.

SLM

components

strength

alloys


Input: In this study, novel biomedical Co29Cr9W3Cu samples were fabricated using selective laser melting (SLM) technology.

biomedical

samples

fabricated

technology

selective laser melting

SLM


Input: In order to better understand the formation of the lattice defects during the melting process, and the tensile deformation mechanism of the SLM-produced Co29Cr9W3Cu samples, the microstructures of the samples before and after tensile deformation were observed using a scanning electron microscope (SEM), a transmission electron microscope (TEM), and an electron back-scattered diffraction (EBSD), respectively.

lattice defects

deformation

samples

samples

deformation

melting

tensile

tensile

microstructures

scanning electron microscope

SEM

transmission electron microscope

TEM

diffraction

EBSD


Input: The SEM morphology indicated that the non-equilibrium structure of the SLM-produced Co29Cr9W3Cu samples contained cellular and columnar subgrains.

SEM

morphology

structure

samples

subgrains


Input: The TEM observation and EBSD analysis showed that the accumulated residual stress during the SLM process predominated in the overlapping regions between the adjacent scanning tracks, which consequently induced a larger number of the lattice defects, such as dislocations and overlapping stacking faults.

TEM

EBSD

residual stress

SLM

process

scanning

lattice defects

as


Input: The analysis of the tensile deformation revealed that the main plastic deformation was caused by the strain-induced martensitic transformation effect in the SLM-produced Co29Cr9W3Cu samples.

tensile

plastic deformation

deformation

samples


Input: Alumina/aluminum titanate composites were prepared using directed laser deposition.

composites

laser

deposition


Input: Scanning speed has a significant effect on the microstructure and macro features.

Scanning speed

microstructure

macro


Input: Microstructure and macro defects are responsible for the trend of properties.

Microstructure

defects

trend

properties

macro


Input: Optimal forming quality was achieved at the medium-speed scanning process window.

forming

scanning process


Input: Directed energy deposition (DED) has developed rapidly in recent years as a new material-structure integration manufacturing technology for preparing melt-growth ceramics.

Directed energy deposition

DED

manufacturing technology

as

ceramics


Input: However, the influence of process conditions on the forming quality has not been systematically studied.

process

forming


Input: Alumina/aluminum titanate composite ceramics were directly prepared using DED technology with an extensive process window.

composite ceramics

DED

process


Input: The effects of the scanning speed on the typical defects, microstructure, and mechanical properties of prepared samples were systematically investigated, and the optimized process parameters were determined.

scanning speed

defects

microstructure

mechanical properties

samples

process parameters


Input: Results show that the scanning speed has a significant effect on the macroscopic defects, such as cracks and pores, microstructure characteristics, such as grain morphology and size, and mechanical properties, such as flexural strength.

scanning speed

macroscopic defects

microstructure

morphology

mechanical properties

as

as

as

pores

strength


Input: Slow-speed scanning achieved a longer retention time of the liquid molten pool, which was beneficial to pore suppression.

scanning

molten pool

pore


Input: Rapid scanning reduced the temperature gradient at the bottom of the molten pool to obtain crack-free samples.

scanning

molten pool

samples

temperature gradient


Input: The directional growth tendency of α-Al2O3 cellular dendrites that were discretely distributed in the Al6Ti2O13 matrix phase weakened, and the secondary dendrites gradually developed by increasing the scanning speed.

dendrites

phase

secondary dendrites

scanning speed


Input: This phenomenon was attributed to the change of the heat-dissipation direction and the solidification rate of solid/liquid interface caused by the scanning speed.

solidification rate

scanning speed

interface


Input: Moreover, the fracture toughness of the prepared samples gradually increased as the scanning speed increased, while the flexural strength showed a parabolic law behavior.

fracture

samples

as

scanning speed

flexural strength


Input: The trend of the properties was due to microstructure refinement and macroscopic defects.

trend

properties

microstructure

macroscopic defects


Input: Generally, the optimal forming quality was achieved at a scanning speed of 300-500 mm/min.

forming

scanning speed


Input: Within this process window, the sample had up to 98% densification, 1640 Hv hardness, 3.75 MPa m1/2 fracture toughness, and 212 MPa flexural strength.

process

sample

MPa

fracture

MPa

densification

hardness

flexural strength


Input: In-situ uniaxial tensile tests coupled with X-ray computed tomography (XCT) were carried out on a Cu-4.3Sn alloy fabricated by selective laser melting.

In-situ

tensile tests

X-ray computed tomography

alloy

selective laser melting


Input: XCT models were constructed to enable step-by-step visualization of pore growth during deformation.

pore

deformation


Input: Evolution of pores (mean diameter, density, volume fraction and sphericity) was quantified as a function of plastic strain.

Evolution

diameter

pores

density

volume fraction

as

plastic


Input: Results show that macroscopic instability begins once the largest internal pores reach the surface.

macroscopic

surface

pores


Input: Also, accelerated growth and coalescence of the largest 50 pores leads to rapid localization of strain followed by fracture.

pores

strain

fracture


Input: Pore growth was modeled using the Rice-Tracey (RT) and Huang models for different populations of pores and the parameters were optimized.

Pore

pores

RT

parameters


Input: The RT and Huang constants were found to depend on the initial mean pore diameter.

RT

pore

diameter


Input: With increasing industrial interest and significance of the selective laser melting the importance for profound process knowledge increases so that new materials can be qualified faster.

industrial

selective laser melting

process

materials

be


Input: Therefore a 3D numerical model for the selective laser melting process is presented that allows a detailed look into the process dynamics at comparably low calculation effort.

model

process

selective laser melting process


Input: It combines a finite difference method with a combined level set volume of fluid method for the simulation of the process and starts with a homogenized powder bed in its initial configuration.

set

fluid

simulation

process

configuration

homogenized

bed


Input: The model uses a comprehensive representation of various physical effects like dynamic laser power absorption, buoyancy effect, Marangoni effect, capillary effect, evaporation, recoil pressure and temperature dependent material properties.

model

dynamic

absorption

capillary effect

evaporation

pressure

material properties

power

temperature


Input: It is validated for different process parameters using cubic samples of stainless steel 316L and nickel-based superalloy IN738LC.

process parameters

samples

stainless steel


Input: The results show the significance of evaporation and its related recoil pressure for a feasible prediction of the melt pool dynamics.

evaporation

pressure

prediction

melt pool


Input: Furthermore a possible way to reduce the times and costs for material qualification by using the simulation model to predict possible process parameters and therefore to reduce the necessary experimental effort for material qualification to a minimum is shown.

material

material

simulation

model

process parameters

experimental


Input: Selective laser melting is an increasingly attractive technology for the manufacture of complex and low volume/high value metal parts.

Selective laser melting

technology

manufacture

metal


Input: However, the inevitable residual stresses that are generated can lead to defects or build failure.

residual stresses

lead

defects

build failure


Input: Due to the complexity of this process, efficient and accurate prediction of residual stress in large components remains challenging.

complexity

process

accurate

residual stress

components


Input: For the development of predictive models of residual stress, knowledge on their generation is needed.

predictive models

residual stress


Input: This study investigates the geometrical effect of scan strategy on residual stress development.

investigates

residual stress


Input: It was shown that the laser scan strategy becomes less important for scan vector length beyond 3 mm.

laser scan

mm


Input: Together, these findings, provide a route towards optimising scan strategies at the meso-scale, and additionally, developing a model abstraction for predicting residual stress based on scan vectors alone.

model abstraction

residual stress


Input: Fused filament fabrication (FFF), sometimes called material extrusion (ME) offers an alternative option to traditional polymer manufacturing techniques to allow the fabrication of objects without the need of a mold or template.

Fused filament fabrication

FFF

material extrusion

manufacturing

fabrication

polymer

mold

template


Input: However, these parts are limited in the degree to which the welding interface is eliminated post deposition, resulting in a decrease in the interlaminar fracture toughness relative to the bulk material.

welding interface

deposition

fracture

material


Input: Here reptation theory under nonisothermal conditions is utilized to predict the development of healing over time, from the rheological and thermal properties of Acrylonitrile-Butadiene-Styrene (ABS).

rheological

thermal properties

ABS


Input: ABS is rheologically complex and acts as a gel and as such considerations had to be made for the relaxation time of the matrix which is important in predicting the degree of interfacial healing.

ABS

as

gel

as

be


Input: The nonsiothermal healing model developed is then successfully compared to experimental interlaminar fracture experiments at variable printing temperatures, allowing future optimization of the process to make stronger parts.

model

experimental

fracture

optimization

process

temperatures


Input: Modeling of mechanical behavior for the material-jet printed polymers including composites.

Modeling

mechanical

polymers

composites


Input: Validation of the material models was conducted.

Validation

material


Input: A desired strain field can be created by locally tuning the printed material distribution.

strain

be

material

distribution


Input: The goal of this work is to validate the material models for parts created with a Material Jetting 3-dimensional printer through the comparison of Finite Element Analysis (FEA) simulations and physical tests.

material

Material Jetting

printer

Finite Element Analysis

simulations


Input: The strain maps generated by a video extensometer for multi-material samples are compared to the FEA results based on our material models.

strain

multi-material

material


Input: Two base materials (ABS-like and rubber-like) and their composites are co-printed in the graded tensile test samples.

materials

samples

composites

tensile test


Input: The simulations were conducted utilizing previously fitted material models, a two-parameter Mooney-Rivlin model for the elastic materials (Tango Black+, DM95, and DM60) and a bilinear model for the rigid material (Vero White+).

simulations

material

material

model

model

elastic


Input: The results show that the simulation results based on our material models can predict the deformation behaviors of the multi-material samples during a uniaxial tensile test.

simulation

material

deformation

multi-material

tensile test


Input: Our simulation results are able to predict the maximum strain in the matrix material (TB+) within 5% error.

simulation

strain

material

error


Input: Both global deformation pattern and local strain level confirm the validity of the simulated material models.

deformation

strain

material


Input: Selective Laser Melting (SLM) of a high strength low alloy steel HY100 is considered in the present investigation.

Selective Laser Melting

SLM

high strength low alloy steel


Input: The current work describes (i) optimization of SLM process parameters for producing fully dense parts in HY100 steel and (ii) the effects of post-processing heat treatment on the microstructure and mechanical properties.

optimization

process parameters

post-processing heat

microstructure

mechanical properties

SLM

fully dense

steel


Input: Samples have been fabricated by SLM using different combinations of laser power, laser scan speed, and hatch spacing.

Samples

fabricated

SLM

laser power

hatch spacing

laser scan


Input: Fully dense samples were achieved at an energy density of 65 J/mm3.

Fully dense

energy density


Input: Microstructures of the as-built and heat treated samples were investigated using optical and scanning electron microscopes, X-ray diffraction, and electron backscattered diffraction techniques.

Microstructures

heat

samples

optical

X-ray diffraction

diffraction

scanning electron microscopes


Input: The as-built parts are unsuitable for direct application due to untempered, hard and brittle martensite microstructure.

brittle

microstructure


Input: The as-built parts were subjected to post-processing heat treatments (“direct temper” and “quench and temper”).

post-processing heat

temper

temper


Input: The direct tempered samples exhibited higher yield strength and ultimate strength than the quench and temper ones.

tempered

temper

samples

yield strength

ultimate strength


Input: Noticeable amounts of anisotropy with respect to the build orientation, especially in tensile elongation, were observed in the direct tempered samples due to in-homogenous microstructure.

anisotropy

tensile elongation

build orientation

tempered

samples

microstructure


Input: Quench and temper treatment of the parts resulted in recrystallized grains with uniform microstructure.

temper

recrystallized

grains

microstructure


Input: The current investigation shows that quench and temper at 650 °C is an optimum post processing treatment for HY100 SLM parts as it manifests desired strength with good tensile elongation.

temper

SLM

post processing

as

strength

tensile elongation


Input: Surface pore defects are always formed during directed energy deposition processes, which may stem from entrapped gas bubbles.

Surface

defects

gas

pore

directed energy deposition processes


Input: Such defects have detrimental effects on the build quality and performance of safety-critical metal parts.

defects

performance

build

metal


Input: Despite previous experimental and theoretical studies devoted to this subject, direct observations of the dynamic behavior of gas bubbles and elucidation of how they form surface pore defects have not yet been achieved.

experimental

theoretical

dynamic

gas

surface

defects

pore


Input: In this work, the relationships between surface pore defects and the bubbles originating on the melt pool surface were carefully studied using high-speed photography at up to 20,000 frames per second.

surface

defects

pore

melt pool


Input: The appearance of surface pores was a result of dynamic competition between bubble explosion and solidification of the surrounding melt, where the final location of the surface pores is determined by the melt convection and the boundary motion of the melt pool.

surface

dynamic

solidification

melt

surface

melt

pores

pores

boundary

melt pool