Input: To build a statistical foundation upon which design guidelines can be compiled, multiple copies of the test part are fabricated within existing commercial builds in a factorial study with materials, build orientations, and locations within the build chamber as control factors.

build

build orientations

build chamber

design

be

as

fabricated

materials

builds


Input: Enhancing the corrosion resistance and improving the biological response to 316 L stainless steel is a long-standing and active area of biomedical research.

corrosion resistance

stainless steel

area

biomedical


Input: Here, we analyzed the structure and corrosion tendency of selective laser melted-additively manufactured (AM) 316 L stainless steel (AM 316L SS) and its wrought counterpart.

structure

corrosion

manufactured

wrought

selective laser

AM

AM

stainless steel

SS


Input: SEM analysis showed a fine (500–800 nm) interconnected sub-granular structure for the AM 316L SS, but a polygonal coarse-grained structure for the wrought sample.

SEM

structure

structure

wrought sample

AM

SS


Input: Relative to the wrought sample, the AM 316L SS also exhibited a higher charge transfer resistance and higher breakdown potential (˜1000 mV vs. SCE) when tested in biological electrolytes, which included human serum, PBS, and 0.9 M NaCl.

wrought sample

AM

SS

PBS

NaCl

resistance

electrolytes


Input: A higher pitting resistance (extended passive region) and improved stability of the AM 316L SS was attributed to its dense structure of oxide film and refined microstructure.

pitting

structure

microstructure

stability

AM

SS

oxide


Input: Finally, material compatibility with pre-osteoblasts was analyzed.

material


Input: Large cytoplasmic extension of osteoblast cells and retention of stiller morphology was observed when cells were cultured on the AM 316L SS as compared to its wrought counterpart, suggesting that the AM 316L SS was a better substrate for cell spreading and differentiation.

osteoblast cells

morphology

wrought

cells

cell

AM

AM

SS

as

SS

substrate


Input: Runx2, an anti–proliferative marker indicative of differentiation, was equivalent in cells cultured on either samples, but overall more cells were present on the AM 316L SS.

cells

cells

samples

AM

SS


Input: Given its higher corrosion resistance and ability to support osteoblast adherence, spreading and differentiation, the AM 316L SS has potential for use in the biomedical industry.

corrosion resistance

support

biomedical industry

osteoblast

AM

SS


Input: Simulations of the material deposition in extrusion-based additive manufacturing.

Simulations

material

deposition

additive manufacturing


Input: Prediction of the strand cross-section as function of the processing parameters.

Prediction

parameters

as


Input: Negative linear relationship between the printing force and the printing speed.

force

printing speed


Input: We propose a numerical model to simulate the extrusion of a strand of semi-molten material on a moving substrate, within the computation fluid dynamics paradigm.

model

computation

extrusion

semi-molten

material

substrate


Input: According to the literature, the deposition flow of the strands has an impact on the inter-layer bond formation in extrusion-based additive manufacturing, as well as the surface roughness of the fabricated part.

deposition

impact

fabricated

additive manufacturing

as

as

surface roughness


Input: Under the assumptions of an isothermal Newtonian fluid and a creeping laminar flow, the deposition flow is controlled by two parameters: the gap distance between the extrusion nozzle and the substrate, and the velocity ratio of the substrate to the average velocity of the flow inside the nozzle.

isothermal

deposition

parameters

average

fluid

substrate

substrate

extrusion

nozzle


Input: The numerical simulation fully resolves the deposition flow and provides the cross-section of the printed strand.

numerical simulation

deposition


Input: The adoption of additive manufacturing (AM) for fabricating biomedical implants at hospitals provides many potential benefits.

additive manufacturing

AM

fabricating

biomedical


Input: Relative to biomedical implants fabricated via traditional manufacturing (TM), typically available by suppliers out of the immediate region, biomedical implants fabricated through AM provides an opportunity to receive more patient-specific, customized parts with faster response, a lower inventory level, and reduced delivery costs.

biomedical

biomedical

fabricated

fabricated

traditional manufacturing

AM


Input: Despite the promising features of AM technologies, the make-or-buy decisions are not straightforward and require careful investigation due to the relatively high AM machine and production costs.

AM technologies

AM machine

production costs


Input: No research efforts, to the best of our knowledge, have been dedicated to the quantitative analysis of the costs of supply chains integrated with AM facilities, e.g., inventory cost, transportation cost, product lead time, etc.

research

quantitative

supply chains

AM

lead time


Input: In this study, we propose a stochastic cost model to quantify the supply-chain level costs associated with the production of biomedical implants using AM techniques, and investigate the economic feasibility of using such technologies to fabricate biomedical implants at the sites of hospitals.

stochastic

cost model

feasibility

technologies

production

AM techniques

fabricate

biomedical

biomedical


Input: The problem is formulated in the form of a stochastic programming model, which determines the number of AM facilities to be established and volume of product flow between manufacturing facilities and hospitals.

stochastic

model

volume

AM

manufacturing

be


Input: A customized Sample Average Algorithm (SAA) is developed to obtain the solutions.

Sample

Average Algorithm


Input: We apply the cost model to a real-world case study that focuses on the use of biomedical implants for hospitals in the state of Mississippi (MS), and identify the conditions and cost parameters that have significant impact on the economic feasibility of AM.

cost model

case study

parameters

impact

feasibility

biomedical

AM


Input: We find that the ratio between the unit production costs of AM and TM (ATR), as well as product lead time and demands, are key cost parameters that determine the economic feasibility of AM.

production costs

parameters

feasibility

AM

AM

as

as

lead time


Input: Popular dialogue around additive manufacturing (AM) often assumes that AM will cause a move from centralized to distributed manufacturing.

additive manufacturing

AM

AM

manufacturing


Input: We combine a Process-Based Cost Model and an optimization model to analyze the optimal location and number of manufacturing sites, and the tradeoffs between production, transportation and inventory costs.

Cost Model

optimization model

manufacturing

production


Input: We use as a case study the commercial aviation maintenance market and a titanium jet engine bracket as an exemplar of a class of parts that are not flight-critical.

as

titanium

as

case study

bracket


Input: We run our analysis for three different scenarios, one corresponding to the current state of the technology, and two which represent potential improvements in AM technology.

technology

AM technology


Input: Our results suggest that the cost-minimizing number of manufacturing locations does not vary significantly when taking into account a range of plausible improvements in the technology.

manufacturing

range

technology


Input: In this case, distributed manufacturing is only favorable for a set of non-critical components that can be produced on the same equipment with minimal certification requirements and whose annual demand is in the tens of thousands.

manufacturing

set

components

equipment

be


Input: Distributed manufacturing is attractive at lower volumes for components that require no hot isostatic pressing.

manufacturing

hot isostatic pressing

components


Input: Through the combination of in-situ alloying and additive manufacturing with gas tungsten arc welding, a new approach to fabricating titanium aluminide alloys is proposed.

in-situ

alloying

additive manufacturing

gas tungsten arc welding

fabricating

alloys


Input: This innovative and low cost process has many similarities to multipass welding.

process

welding


Input: It has been a generally accepted practice to maintain a specified interpass temperature when multipass welding many different alloys to prevent defects such as cracks.

interpass temperature

welding

alloys

as

defects


Input: Increasing the interpass temperature can facilitate phase transformation by extending the high temperature period and produce the desired weld microstructure.This study examines the influence of different interpass temperatures on in-situ alloyed and additively manufactured γ-TiAl alloy.

interpass temperature

temperature

interpass temperatures

phase

in-situ

weld

additively manufactured

alloy


Input: The microstructure, chemical composition, phase constitution and microhardness of all the test components were respectively examined by using light microscopy, SEM-EDS, X-ray diffraction and a Duromain 70 Hardness Tester.

microstructure

chemical composition

phase

microhardness

components

microscopy

X-ray diffraction

Hardness


Input: No appreciable changes in microstructure and composition were found as interpass temperature was changed.

microstructure

composition

as

temperature


Input: However, as the interpass temperature was increased from 100 °C to 400 °C, a decrease of α2 phase fraction was observed due to the lower cooling rate.

as

interpass temperature

cooling rate

phase fraction


Input: Consequently, the microhardness value also decreased.

microhardness


Input: A further increase of interpass temperature to 500 °C produced only minor reductions in the brittle α2 phase fraction and the microhardness value.

interpass temperature

brittle

phase fraction

microhardness


Input: In view of these results, a suitable interpass temperature was found for producing crack-free components.

interpass temperature

components


Input: Increasingly, metal parts made by additive manufacturing are produced using powder bed fusion (PBF).

metal

additive manufacturing

powder bed fusion

PBF


Input: In this paper we report upon the combined effects of PBF parameters, including power and scan speed, in layer-by-layer manufacturing of gas atomized non-modulated (NM) Ni-Mn-Ga alloy.

PBF

gas atomized

parameters

layer-by-layer

power

scan speed

alloy


Input: The effects of process parameters upon PBF is studied by applying nine different parameter sets in the as-printed state and after homogenization and ordering.

process parameters

parameter

PBF

homogenization


Input: The chemical composition of the samples is analyzed using EDX attached to an SEM, and the crystal structures are determined by X-ray diffraction.

chemical composition

samples

EDX

SEM

X-ray diffraction

crystal structures


Input: The phase transformation temperatures are measured using a low-field ac susceptibility measurement system and the magnetic properties are measured with a vibrating sample magnetometer (VSM).

phase

properties

sample

temperatures

susceptibility

measurement

VSM


Input: Before the heat-treatment, all as-printed samples showed paramagnetic behavior with low magnetization and no phase transformations could be observed in the susceptibility measurements.

samples

phase

be

susceptibility


Input: After annealing, the samples recovered the ferromagnetic behavior with comparable magnetization to annealed gas atomized powder.

annealing

gas atomized

samples


Input: The as-printed samples were composed of a mixture of different crystal structures.

samples

crystal structures


Input: However, after annealing the original NM structure with a = b = 5.47 Å and c = 6.66 Å with a c/a -ratio of 1.22 was recovered and crystallographic twins could be observed in an SEM.

annealing

structure

b

c

be

SEM


Input: Expanding on prior process mapping work by the authors, multiple melt pool cross-sections are measured at multiple process parameter combinations for the Inconel 718 alloy in a Laser Powder Bed Fusion (L-PBF) process.

process

cross-sections

process parameter

process

melt pool

Inconel 718 alloy

Laser Powder Bed Fusion

L-PBF


Input: Collection of such data enables the study of the variability of melt pool geometry (e.g.

data

variability

geometry

melt pool


Input: width, depth, and cross-sectional area) across process space.

area

process


Input: Furthermore, the statistical distribution of the measured melt pool geometries is compared to that of an equivalent normal distribution and intriguing outliers are observed.

distribution

geometries

distribution

melt pool


Input: The cross-sectional morphology of the melt pools are associated with defects such as keyholing porosity and balling and the variability of the defects is quantified.

morphology

defects

variability

defects

melt pools

as

porosity


Input: The final product of this work is a robust description of L-PBF In718 melt pool behavior, based on ex-situ observations, which can be linked to in-situ observations of melt pool morphology in future work.

L-PBF

be

melt pool

in-situ


Input: This study evaluates the performance of continuous carbon, Kevlar and glass fibre reinforced composites manufactured using the fused deposition modelling (FDM) additive manufacturing technique.

performance

fused deposition

carbon

Kevlar

glass fibre

composites

FDM

additive manufacturing


Input: The fibre reinforced nylon composites were fabricated using a Markforged Mark One 3D printing system.

fibre

nylon composites

fabricated

3D printing


Input: The mechanical performance of the composites was evaluated both in tension and flexure.

mechanical

composites

flexure


Input: The influence of fibre orientation, fibre type and volume fraction on mechanical properties were also investigated.

fibre

fibre

volume fraction

mechanical properties


Input: The results were compared with that of both non-reinforced nylon control specimens, and known material property values from literature.

nylon

material property


Input: It was demonstrated that of the fibres investigated, those fabricated using carbon fibre yielded the largest increase in mechanical strength per fibre volume.

fibres

carbon fibre

fibre

fabricated

mechanical strength


Input: Its tensile strength values were up to 6.3 times higher than those obtained with the non-reinforced nylon polymer.

tensile strength

nylon


Input: As the carbon and glass fibre volume fraction increased so too did the level of air inclusion in the composite matrix, which impacted on mechanical performance.

As

carbon

glass fibre

inclusion

composite

fraction

mechanical


Input: As a result, a maximum efficiency in tensile strength was observed in glass specimen as fibre content approached 22.5%, with higher fibre contents (up to 33%), yielding only minor increases in strength.

As

glass

as

fibre

tensile strength

strength


Input: Approaches used in Computational Welding Mechanics are applicable for additive Manufacturing.

Welding

additive Manufacturing


Input: The model sizes pose additional challenges in case of simulating AM.

model

AM


Input: Models must couple microstructural and material behavior.

microstructural

material


Input: The paper describes the application of modeling approaches used in Computational Welding Mechanics (CWM) applicable for simulating Additive Manufacturing (AM).

modeling

Welding

Additive Manufacturing

AM


Input: It focuses on the approximation of the behavior in the process zone and the behavior of the solid material, particularly in the context of changing microstructure.

process

microstructure

material


Input: Two examples are shown, one for the precipitation hardening Alloy 718 and one for Ti-6Al-4V.

precipitation hardening

Alloy


Input: The latter alloy is subject to phase changes due to the thermal cycling.

alloy

phase

thermal cycling


Input: A model for additive manufacturing by selective laser melting of a powder bed with application to alumina ceramic is presented.

model

additive manufacturing

selective laser melting

powder bed

alumina


Input: Based on Beer–Lambert law, a volume heat source model taking into account the material absorption is derived.

volume

heat source

absorption

material


Input: The level set method is used to track the shape of deposed bead.

set

bead


Input: Shrinkage during consolidation from powder to liquid and compact medium is modeled by a compressible Newtonian constitutive law.

Shrinkage

consolidation

powder

compact


Input: A semi-implicit formulation of surface tension is used, which permits a stable resolution to capture the liquid/gas interface.

surface tension

resolution

interface


Input: The influence of different process parameters on temperature distribution, melt pool profiles and bead shapes is discussed.

process parameters

distribution

temperature

melt pool

bead


Input: The effects of liquid viscosity and surface tension on melt pool dynamics are investigated.

viscosity

surface tension

melt pool


Input: Three dimensional simulations of several passes are also presented to study the influence of the scanning strategy.

simulations

scanning strategy


Input: A wire-arc additive manufacturing (WAAM) system is used to fabricate iron rich Fe–Al intermetallics with 25 at% aluminum content.

wire-arc additive manufacturing

WAAM

fabricate

intermetallics

aluminum


Input: The alloy is produced in situ through controlled addition of the elemental iron and aluminum components into the welding process.

alloy

iron

aluminum

in situ

process

welding


Input: The properties of the fabricated material are assessed using optical microstructure analysis, hardness testing, tensile testing, X-ray diffraction phase characterization and electron dispersive spectrometry.

properties

fabricated

microstructure

phase

optical

tensile testing

X-ray diffraction

hardness


Input: It is shown that the WAAM system is capable of producing iron rich Fe–Al intermetallics with higher yield strength and similar room temperature ductility when compared to equivalent materials produced using powder metallurgy.

WAAM system

iron

intermetallics

yield strength

ductility

temperature

materials

powder metallurgy


Input: Support structures are required in powder bed fusion (PBF) additive manufacturing of metallic components with overhanging structures in order to reinforce and anchor the part, preventing warping during fabrication.

Support structures

powder bed fusion

PBF

additive manufacturing

fabrication

metallic

components

overhanging structures

warping


Input: In this study, we tested the tensile structural strength of support structures with four different 2-dimensional lattice geometries by fabricating samples composed of solid material on the bottom, followed by support material in the middle, followed by solid material on the top.

tensile

strength

support structures

lattice geometries

fabricating

material

support material

material


Input: The support structure regions were fabricated with a lower linear heat input than the solid material, providing deliberate geometrical stress concentrations to enable the removal of support material after processing.

support structure

fabricated

heat

material

material

stress concentrations

removal of support


Input: These samples were subjected to tension in the vertical direction to measure the strengths of the support structure-solid material interfaces.

samples

vertical

strengths

support

material


Input: Two strengths were computed: an effective structural strength defined as the total force that the structure withstood normalized by the full cross-sectional area, and a ligament structural strength, defined as the effective structural strength normalized by the density of the solid material, thereby ignoring the volume of the surrounding powder and voids that do not contribute to the strength of the lattice.

strengths

strength

strength

strength

density

strength

as

as

material

powder

force

structure

volume

voids

lattice

area


Input: The effective structural strength was 14–32% of the strength of fully dense Ti-6Al-4V made by PBF and the ligament structural strength was 34–49% of the strength of fully dense material.

strength

strength

strength

strength

fully dense

fully dense

PBF


Input: These interface strengths are lower than that of fully-dense material due to the stress concentrations at the support structure-solid material interfaces, not any intrinsic difference in the intrinsic strength of support structure versus solid material.

interface

material

material

material

stress concentrations

support

strength

support structure


Input: These results can be used to tailor the support structure geometry to balance sufficient anchoring strength during fabrication and ease of part removal and subsequent machining during post-processing.

be

support structure

geometry

post-processing

strength

fabrication

machining


Input: In-situ detection of processing defects is a critical challenge for Laser Powder Bed Fusion Additive Manufacturing.

In-situ

defects

Laser Powder Bed Fusion Additive Manufacturing


Input: Many of these defects are related to interactions between the recoater blade, which spreads the powder, and the powder bed.

defects

recoater blade

powder bed

powder


Input: This work leverages Deep Learning, specifically a Convolutional Neural Network (CNN), for autonomous detection and classification of many of these spreading anomalies.

Neural Network

classification

anomalies


Input: Importantly, the input layer of the CNN is modified to enable the algorithm to learn both the appearance of the powder bed anomalies as well as key contextual information at multiple size scales.

layer

algorithm

anomalies

powder bed

as


Input: These modifications to the CNN architecture are shown to improve the flexibility and overall classification accuracy of the algorithm while mitigating many human biases.

architecture

flexibility

classification

algorithm

accuracy


Input: A case study is used to demonstrate the utility of the presented methodology and the overall performance is shown to be superior to that of methodologies previously reported by the authors.

case study

methodology

performance

be


Input: The observation of sub-grained cellular features in additively manufactured (AM) /selectively laser melted (SLM) 316L stainless steel components has remained an interesting, though incompletely understood phenomenon.

additively manufactured

AM

SLM

laser

316L stainless steel


Input: However, the recently observed correlation linking the presence of these features with significantly enhanced mechanical strength in SLM 316L materials has driven a renewed interest and effort toward elucidating the mechanism (s) by which they are formed.

mechanical strength

SLM

materials

mechanism

s


Input: These phenomena include SLM-induced intrinsic strain-aging, Cottrell atmosphere formation, and twin-boundary enhanced mass diffusion to structural defects.

mass diffusion

structural defects


Input: Furthermore, evidence is provided to support the proposed theory that the observed chemical heterogeneity coincident with dislocation cell structures is actually the result of local, strain energy density induced solid state diffusion.

support

cell

chemical heterogeneity

dislocation

solid state diffusion

strain

energy density


Input: Numerical simulation of residual deformation in metallic components with dense lattice support structures by the laser powder bed fusion (L-PBF) additive manufacturing process has been a significant challenge due to the very high computational expense in performing both finite element meshing and analysis.

Numerical simulation

residual deformation

lattice

finite element

metallic

components

laser powder bed fusion

L-PBF

additive manufacturing process


Input: In this work, the modified inherent strain method is extended to enable efficient residual deformation simulation of l-PBF components with lattice support structures.

modified inherent strain method

residual deformation

lattice

l-PBF

components


Input: The asymptotic homogenization method is employed to obtain the equivalent mechanical properties including the anisotropic elastic modulus and inherent strains given the topological configuration and laser scanning strategy of the thin-walled lattice support structures.

homogenization method

mechanical properties

configuration

lattice

anisotropic

laser


Input: A key finding is that the in-plane homogenized inherent strain values decrease with increasing volume density, which can be attributed to the directional dependence of inherent strains for the AM-processed material.

homogenized

strain

density

volume

be

material


Input: Based on the homogenized mechanical properties and inherent strains, the thin-walled lattice support structures can be considered to be an effective solid continuum so that the simulation can be accelerated significantly to obtain residual deformation.

homogenized

properties

lattice

continuum

residual deformation

be

be

be

simulation


Input: Good accuracy of the homogenized mechanical property and inherent strains is validated by comparing the simulated residual deformation with experimental deformation measurement of several lattice structured beams of different volume densities.

accuracy

homogenized

property

residual deformation

experimental deformation

lattice

volume


Input: In addition, the scalability of the proposed method is also verified through application to a complex L-PBF component fabricated with thin-walled support structures.

L-PBF

component

support structures


Input: Additive manufacturing (AM) promises great potential benefits for industrial manufacturers who require low volume and functional, highly complex, end-use products.

Additive manufacturing

AM

industrial

volume


Input: Commercial adoption of AM has been slow due to factors such as quality control, production rates, and repeatability.

AM

production

as

repeatability


Input: However, given AM's potential, numerous research efforts are underway to improve the quality of the product realization process.

AM

research

quality

process


Input: A major area of opportunity is to complement existing efforts with advancements in end-to-end digital implementations of AM processes.

area

AM processes


Input: Systematically configured digital implementations would facilitate informational transformations through standard interfaces, streamlining the AM digital spectrum.

standard

AM


Input: Here, we propose the development of a federated, information systems architecture for additive manufacturing.

architecture

additive manufacturing


Input: We establish an information requirements workflow for streamlining information throughput during product realization.

workflow

throughput


Input: The architecture is delivered through the development of a solution stack, including the identification of areas where advancements in information representations will have the highest impact.

architecture

solution

impact

areas


Input: Common data structures and interfaces will allow developers and end users of additive manufacturing technologies to simplify, coordinate, validate, and verify end-to-end digital implementations.

data

additive manufacturing

coordinate


Input: This paper investigates the development of a novel high temperature polymer composite material by modifying polyetherimide (PEI) ULTEM™ 1010 with the addition of functional additives and processing it into filaments for Fused Filament Fabrication (FFF).

investigates

temperature

polymer composite

material

additives

filaments

Fused Filament Fabrication

FFF


Input: Through twin-screw extrusion, four different formulations were obtained using combinations of hollow glass microspheres, nanoclay, and non-halogenated flame-retardant additives.

extrusion

glass

additives


Input: These additives were designed to create a material that exhibits low density, high char yield, and low flammability.

additives

material

designed

density


Input: Filament quality was characterized and reported.

Filament


Input: SiC particles were added in-situ during WAAM of an high strength low alloy steel.

SiC

high strength low alloy steel

particles

in-situ

WAAM


Input: Cementite formed in the SiC-containing parts due to SiC dissociation in the melt pool.

Cementite

SiC

melt pool


Input: Non-melted SiC particles acted as nucleating agents promoting grain refinement.

SiC

as

particles

grain refinement


Input: Improved mechanical properties were obtained upon the use of SiC.

mechanical properties

SiC


Input: In this work, SiC particles were added to the molten pool during WAAM of a high strength low alloy steel.

SiC

high strength low alloy steel

particles

molten pool

WAAM


Input: The introduction of these high melting point particles promoted grain refinement, and the precipitation of Fe3C due to SiC dissociation.

melting point

grain refinement

precipitation

SiC


Input: The microstructural evolution was studied by optical and electron microscopy techniques and high energy synchrotron X-ray diffraction.

microstructural evolution

optical

electron microscopy

diffraction

synchrotron


Input: Additionally, mechanical testing and hardness profiles were obtained for the SiC-containing and SiC-free parts.

mechanical testing

hardness


Input: An improvement in the mechanical strength of the SiC-added WAAM parts was observed, which was attributed to the refined grain structure and finely dispersed Fe3C.

mechanical strength

WAAM

grain structure


Input: The present study systematically investigated the mechanical properties of wire-based (wire and arc additive manufacturing, known as WAAM) deposition of steel metals, both stainless steel 304 and mild steel ER70S.

mechanical properties

deposition

wire and arc additive manufacturing

as

steel metals

stainless steel

mild steel


Input: Graded material properties of stainless steel 304 were observed for wear and hardness in the direction of deposition and in Z height, due to variations in local thermal histories of the metal.

material properties

wear

deposition

variations

stainless steel

metal

hardness


Input: The yield and ultimate strength, however, were not found to be statistically significantly different (p = 0.55) along the direction of deposition for SS304.

ultimate strength

be

p

deposition


Input: During wear testing, a grain refinement was observed directly beneath the wear scar in these materials in a focused ion beam channel observed under scanning electron microscopy.

wear

wear

materials

ion

testing

grain refinement

scanning electron microscopy

beam


Input: Additionally, no significant difference in yield strength was observed in printed mild steel (ER70S) between vertical and horizontal specimens.

yield strength

mild steel

vertical

horizontal specimens


Input: The observed graded mechanical properties in stainless steel 304 allow the opportunity for varying the processing conditions to design parts with locally optimized or functionally graded mechanical properties.

mechanical properties

functionally graded

properties

stainless steel

design


Input: Lattice structures are frequently found in nature and engineering due to their myriad attractive properties, with applications ranging from molecular to architectural scales.

Lattice structures

engineering

properties


Input: Lattices have also become a key concept in additive manufacturing, which enables precise fabrication of complex lattices that would not be possible otherwise.

Lattices

lattices

additive manufacturing

precise fabrication

be


Input: While design and simulation tools for stiff lattices are common, here we present a digital design and nonlinear simulation approach for additive manufacturing of soft lattices structures subject to large deformations and instabilities, for which applications in soft robotics, healthcare, personal protection, energy absorption, fashion and design are rapidly emerging.

design

design

design

simulation

simulation

lattices

lattices

deformations

fashion

additive manufacturing

soft robotics

energy absorption


Input: Our framework enables design of soft lattices with curved members conforming to freeform geometries, and with variable, gradually changing member thickness and material, allowing the local control of stiffness.

framework

lattices

freeform geometries

design

material

stiffness


Input: We model the lattice members as 3D curved rods and using a spline-based isogeometric method that allows the efficient simulation of nonlinear, large deformation behavior of these structures directly from the CAD geometries.

model

lattice

deformation

as

simulation

CAD


Input: Furthermore, we enhance the formulation with a new joint stiffening approach, which is based on parameters derived from the actual node geometries.

joint

parameters

geometries


Input: Simulation results are verified against experiments with soft lattices realized by PolyJet multi-material polymer 3D printing, highlighting the potential for simulation-driven, digital design and application of non-uniform and curved soft lattice structures.

Simulation

simulation-driven

lattices

PolyJet multi-material

3D printing

design

lattice structures


Input: Premelting electron beam-assisted freeform fabrication (PEBF3) method is proposed for the first time.

freeform fabrication


Input: Al and Ti are joined by PEBF3 with no defects.

Al

Ti

defects


Input: Meanwhile, TiAl3 reinforced aluminum matrix composites are obtained.

reinforced

aluminum

composites


Input: TiAl3 reinforced aluminum matrix composites have better wear resistance than aluminum alloy with no TiAl3.

reinforced

aluminum

composites

aluminum alloy

wear resistance


Input: The reasons for the friction coefficient of the deposition with TiAl3 changes periodically are explained and verified.

friction

deposition


Input: Premelting electron beam-assisted freeform fabrication, as a new method to avoid the direct coupling of wire-beam-molten pool during electron beam freeform fabrication, is proposed for the first time.

freeform fabrication

electron beam freeform fabrication

as


Input: The three factors referring to wire, beam and molten pool, are decomposed into two factors as wire and beam.

beam

beam

molten pool

as


Input: The liquid metal is formed in the diversion nozzle, as the wire is heated and melted inside it by an electron beam, and, subsequently, is transferred to the substrate with solidification process.

liquid metal

as

substrate

nozzle

melted

electron beam

solidification process


Input: Finally, a continuous and stable process of premelting electron beam-assisted freeform fabrication is achieved.

process

freeform fabrication


Input: When an aluminum alloy was deposited on a TC4 substrate by premelting electron beam-assisted freeform fabrication, the TC4 base metal did not melt because the electron beam did not directly act on the TC4 substrate.

aluminum alloy

substrate

base metal

substrate

freeform fabrication

melt

electron beam


Input: There is no stirring of the electron beam inside the liquid deposition body, and the dissolution and diffusion of elemental Ti exists, which ensures the effective connection between the deposition and the TC4 substrate.

electron beam

deposition

diffusion

deposition

Ti

substrate


Input: Although TiAl3 intermetallic compounds were generated in the deposition, the interface between TiAl3 and the Al matrix was coherent, as (101) TiAl3// (020) Al was clearly detected in the center of the deposition.

intermetallic compounds

Al

as

Al

deposition

interface

deposition


Input: There are no cracks or other defects in the deposition.

defects

deposition


Input: The acicular TiAl3 intermetallic compounds are dispersed in the deposition, which improves the wear resistance of the deposition.

intermetallic compounds

deposition

deposition

wear resistance


Input: Additive manufacturing (AM) enables production of geometrically-complex elastomeric structures.

Additive manufacturing

AM

production

geometrically-complex


Input: The elastic recovery and strain-rate dependence of these materials means they are ideal for use in dynamic, repetitive mechanical loading.

elastic recovery

materials

dynamic

mechanical loading


Input: Their process-dependence, and the frequent emergence of new AM elastomers, commonly necessitates full material characterisation; however, accessing specialised equipment means this is often a time-consuming and expensive process.

AM

material

equipment

process


Input: This work presents an innovative equi-biaxial rig that enables full characterisation via a conventional material testing machine (supplementing uni-axial tension and planar tension tests).

material

machine

tension tests


Input: Combined with stress relaxation data, this provides a novel route for hyperelastic material modelling with viscoelastic components.

stress relaxation

data

material

viscoelastic

components


Input: This approach was validated by recording the force-displacement and deformation histories from finite element modelling a honeycomb structure.

deformation

finite element modelling

honeycomb structure


Input: These data compared favourably to experimental quasistatic and dynamic compression testing, validating this novel and convenient route for characterising complex elastomeric materials.

data

experimental

dynamic

materials

compression


Input: Supported by data describing the potential for high build-quality production using an AM process with low barriers to entry, this study should serve to encourage greater exploitation of this emerging manufacturing process for fabricating elastomeric structures within industrial communities.

data

production

AM process

manufacturing process

fabricating

industrial


Input: Additive manufacturing (AM) allows for layer-by-layer fabrication of complex metallic parts with features typically unobtainable via conventional manufacturing.

Additive manufacturing

AM

fabrication

conventional manufacturing

layer-by-layer

metallic parts


Input: For heat exchangers, such complex features are desirable for enhancing their heat transfer capability and conformability to specific applications.

heat exchangers

heat transfer


Input: In this case study, Selective Laser Melting (SLM), a laser-based additive manufacturing process, was utilized to fabricate a compact (5.08 cm × 3.81 cm × 1.58 cm) flat-plate oscillating heat pipe (FP-OHP) with innovative design features, including a Ti–6Al–4V casing and a closed-loop, circular mini-channel (1.53 mm in diameter) consisting of four interconnected layers.

case study

heat

diameter

Selective Laser Melting

SLM

laser-based additive manufacturing

fabricate

compact

mm

design


Input: Venting holes were integrated to intersect each layer to allow for a unique layer-by-layer, plug-and-pressurize de-powdering procedure.

layer

layer-by-layer

de-powdering


Input: The device channel surface was inspected via Scanning Electron Microscopy (SEM)–and it was found that the channel wall consisted of partially un-melted particles, as well as amorphous melt regions; surface characteristics influential on surface/fluid capillarity and heat transfer.

channel

channel

Scanning Electron Microscopy

SEM

particles

melt

surface

heat transfer

as

as


Input: This study also highlights important design and manufacturing concerns encountered during SLM of channel-embedded parts, such as channel surface quality and de-powdering.

design

manufacturing

SLM

as

surface quality

de-powdering


Input: The Ti–6Al–4V FP-OHP was found to operate successfully with an effective thermal conductivity of approximately 110 W/m K at a power input of 50 W; demonstrating a 400–500% increase relative to solid Ti–6Al–4V.

effective thermal conductivity

power

K


Input: This paper addresses a comprehensive analytical model for the laser powder-fed additive manufacturing (LPF-AM) process, also known as directed energy deposition AM.

model

process

deposition

laser

additive manufacturing

AM

as


Input: The model analytically couples the moving laser beam with Gaussian energy distribution, the powder stream and the semi-infinite substrate together, while considering the attenuated laser power intensity distribution, the heated powder spatial distribution and the melt pool 3D shape with its boundary variation.

model

laser beam

Gaussian

distribution

distribution

distribution

powder

substrate

powder

melt pool

laser power

boundary


Input: The particles concentration on transverse plane is modeled with Gaussian distribution based on optical measurement.

particles

Gaussian

distribution

optical measurement


Input: The model can effectively be used for process development/optimization and controller design, while predicting adequate clad geometry as well as the catchment efficiency rapidly.

model

process

geometry

be

as

as

controller


Input: Experimental validation through the deposition of Inconel 625 proves the model can accurately predict the clad geometry and catchment efficiency in the range of specific energy that is corresponding to high clad quality (maximum percentage difference is 6.2% for clad width, 7.8% for clad height and 6.8% for catchment efficiency).

Experimental

deposition

model

geometry

quality

Inconel 625

accurately

range

specific energy


Input: To produce complex functional devices while eliminating the need for assembly calls for a multi-material additive manufacturing technology.

assembly

multi-material additive manufacturing


Input: This paper presented a 3D-printing system that integrated fused filament fabrication (FFF) and laser-based powder bed fusion (PBF) to produce hybrid metal and polymer components.

fused filament fabrication

FFF

powder bed fusion

PBF

metal

polymer

components


Input: PBF-printed metal and FFF-printed polymer, both of which differ in material properties, were joined through PBF-printed interlocking structures, with their joining strength enhanced by laser heating.

metal

polymer

material properties

joining

heating

laser


Input: Tensile and shear tests confirmed good joint strength of the printed metal/polymer components, which were created without adhesives.

Tensile

shear tests

joint

components

adhesives


Input: In addition, metal powder deposition onto the top of polymer substrates through laser melting was demonstrated.

metal powder

polymer

deposition

laser


Input: Finally, several 3D components consisting of hybrid stainless steel (SS 316L), copper (Cu10Sn) and polymer (PLA, PET) were successfully printed and their potential applications were discussed.

stainless steel

SS

copper

polymer

PLA


Input: Depending on the available laser powder bed fusion (LPBF) system, and the intended application, the use of highly-optimized LPBF parameters to fabricate near-perfect density alloys may not be feasible, economical or required.

laser powder bed fusion

LPBF

LPBF

fabricate

density

alloys

be


Input: Thus, it is important to understand how sub-optimal density and microstructure can simultaneously affect the mechanical properties of alloys.

density

microstructure

mechanical properties

alloys


Input: Here we study the microstructure and properties of an AlSi10Mg alloy fabricated with sub-optimal parameters and investigate the effectiveness of post-processing by hot isostatic pressing (HIP) and T6 heat treatment.

microstructure

properties

parameters

effectiveness

post-processing

AlSi10Mg alloy

hot isostatic pressing

HIP

heat treatment


Input: Defects were characterized using micro-computed tomography while the microstructure was analysed using transmission and scanning electron microscopy.

Defects

microstructure

micro-computed tomography

transmission

scanning electron microscopy


Input: The as-built microstructure features dendritically-arranged nano-crystalline Si particles that are favourable for high hardness, strength and impact toughness while T6 generally caused these properties to degrade.

microstructure

particles

impact

properties

Si

hardness

strength


Input: HIP was unable to close large defects due to trapped gases, which limited fatigue life improvements.

HIP

defects

fatigue life


Input: Defects oriented normal to the loading axis (or parallel to the fracture plane) are very detrimental, but when oriented favourably, the alloy was still able to achieve comparable strength and ductility to results reported in literature for LPBF-fabricated AlSi10Mg alloys.

Defects

fracture

alloy

AlSi10Mg alloys

strength

ductility


Input: Interestingly, the anisotropic nano-crystalline Si structures of the as-built alloy resulted in substantially improved toughness even when defects were oriented unfavourably.

anisotropic

toughness

Si

alloy

defects


Input: Additive manufacturing (AM) processes are being frequently used in industry as they allow the manufacture of complex parts with reduced lead times.

Additive manufacturing

AM

processes

manufacture

industry

as

lead times


Input: Electron beam-powder bed fusion (EB-PBF) as an AM technology is known for its near-net-shape production capacity with low residual stress.

bed fusion

AM technology

near-net-shape

as

capacity

residual stress


Input: However, the surface quality and geometrical accuracy of the manufactured parts are major obstacles for the wider industrial adoption of this technology, especially when enhanced mechanical performance is taken into consideration.

surface quality

accuracy

manufactured

technology

industrial

mechanical


Input: Identifying the origins of surface features such as satellite particles and sharp valleys on the parts manufactured by EB-PBF is important for a better understanding of the process and its capability.

surface

particles

manufactured

process

as


Input: Moreover, understanding the influence of the contour melting strategy, by altering process parameters, on the surface roughness of the parts and the number of near-surface defects is highly critical.

contour

process parameters

defects

surface roughness


Input: In this study, processing parameters of the EB-PBF technique such as scanning speed, beam current, focus offset, and number of contours (one or two) with the linear melting strategy were investigated.

parameters

offset

as

beam

contours

melting


Input: A sample manufactured using Arcam-recommended process parameters (three contours with the spot melting strategy) was used as a reference.

sample

manufactured

process parameters

contours

melting

as


Input: For the samples with one contour, the scanning speed had the greatest effect on the arithmetical mean height (Sa), and for the samples with two contours, the beam current and focus offset had the greatest effect.

samples

samples

offset

contour

contours

scanning speed

beam


Input: For the samples with two contours, a lower focus offset and lower scan speed (at a higher beam current) resulted in a lower Sa; however, increasing the scan speed for the samples with one contour decreased Sa.

samples

offset

samples

contours

contour

scan speed

scan speed

beam


Input: In general, the samples with two contours provided a lower Sa (∼22%) but with slightly higher porosity (∼8%) compared to the samples with one contour.

samples

samples

contours

contour

porosity


Input: Fewer defects were detected with a lower scanning speed and higher beam current.

defects

scanning speed

beam


Input: The number of defects and the Sa value for the samples with two contours manufactured using the linear melting strategy were ∼85% and 16%, respectively, lower than those of the reference samples manufactured using the spot melting strategy.

defects

samples

samples manufactured

contours

melting

melting


Input: Given the attention around additive manufacturing (AM), organizations want to know if their products should be fabricated using AM.

additive manufacturing

AM

AM

be


Input: To facilitate product development decisions, a reference system is shown describing the key attributes of a product from a manufacturability stand-point: complexity, customization, and production volume.

product development

manufacturability

complexity

production


Input: A geometric complexity factor developed for cast parts is modified for a more general application.

complexity

cast


Input: Parts with varying geometric complexity are then analyzed and mapped into regions of the complexity, customization, and production volume model.

complexity

complexity

model

production


Input: Implications for product development and manufacturing business approaches are discussed.

product development

manufacturing


Input: Rod shaped samples of AlSi10Mg additively manufactured using recycled powder through direct metal laser sintering (DMLS) process showed higher quasi-static uniaxial tensile strength in both horizontal and vertical build directions than those of cast counterpart alloy.

Rod

samples

recycled

process

quasi-static

vertical

powder

alloy

additively manufactured

direct metal laser sintering

DMLS

cast

tensile strength

build directions


Input: In addition, they offered mechanical properties within the range of other additively manufactured counterparts.

mechanical properties

range

additively manufactured


Input: TEM showed that the microstructure of the as-built samples comprised of cell-like structures featured by dislocation networks and Si precipitates.

TEM

microstructure

samples

dislocation

Si

precipitates


Input: HRTEM studies revealed the semi-coherency characteristics of the Si precipitates.

HRTEM

Si

precipitates


Input: After deformation, the dislocation density increased as a result of generation of new dislocations due to dislocation motion.

deformation

dislocations

dislocation motion

dislocation density

as


Input: The dislocations bypassed the precipitates by bowing around them and penetrating the semi-coherent precipitates.

dislocations

precipitates

precipitates


Input: Strengthening of recycled DMLS-AlSi10Mg alloys manufactured in both directions was attributed to Orowan mechanism (due to existence of Si precipitates), Hall-Petch effect (due to eutectic cell walls), and dislocation hardening (due to pre-existing dislocation networks).

Strengthening

recycled

mechanism

eutectic

dislocation

dislocation

alloys

Si

precipitates

cell


Input: Due to the slightly different microstructure, the contribution of each strengthening mechanism was slightly different in identical samples made with virgin powder.

microstructure

strengthening mechanism

samples

virgin powder


Input: Three different AlSi10Mg_200C samples with near optimum process parameters were built.

samples

process parameters


Input: AlSi10Mg_200C samples with very low surface roughness were produced.

samples

surface roughness


Input: AlSi10Mg_200C samples also possessed very low porosity levels.

samples

porosity


Input: OM and SEM Microscopy analyses were performed to investigate causality.

OM

SEM

Microscopy


Input: Laser sintered aluminum alloys produced by metal 3D printers can replace cast aluminum alloys in aerospace, defense, and marine industries by offering better mechanical properties, less porosity, and competitive fatigue characteristics.

Laser

aluminum alloys

metal

cast aluminum alloys

3D printers

aerospace

marine industries

mechanical properties

porosity

fatigue


Input: One of the major issues currently is the considerable surface roughness of additively manufactured aluminum alloys demanding post-processing procedures such as bead blasting or machining.

surface roughness

additively manufactured

machining

alloys

as

post-processing


Input: In the current study, the process parameters such as laser power, scan speed, and hatch spacing were altered such that better surface roughness could be achieved for AlSi10Mg_200C using a Direct Metal Laser Sintering (DMLS) system.

process parameters

as

be

power

scan speed

hatch spacing

surface roughness

Direct Metal Laser Sintering

DMLS


Input: The process parameters were chosen such that three samples with the same core properties but different upskin characteristics were produced.

process parameters

samples

core


Input: The achieved surface roughness of the additively manufactured aluminum samples were almost as low as one fifth of the regular samples manufactured using standard process parameters.

surface roughness

additively manufactured

samples

samples manufactured

standard

process parameters

as

as


Input: The microstructure and the porosity level of the samples printed by different process parameters were studied to reveal the causality of the low surface roughness for the proposed process.

microstructure

samples

process parameters

process

porosity

surface roughness


Input: Large-scale polymer AM is very susceptible to part failure due to thermal warping.

polymer

AM

failure

warping


Input: A 1D heat transfer model can predict the temperature evolution of thin walls.

heat transfer

evolution

temperature


Input: Parameter studies provide guidance for minimizing the likelihood of build failure.

Parameter

build failure


Input: Higher thermal conductivity is shown to be detrimental to the success of the build.

thermal conductivity

be

build


Input: The incremental deposition process utilized by most additive manufacturing (AM) technologies presents significant challenges related to residual stresses and warping which arise from repeated deposition of hot material onto cooler material.

deposition process

additive manufacturing

AM

technologies

warping

deposition

residual stresses

material

material


Input: In this work we investigate the thermal evolution in thin walls of carbon fiber/acrylonitrile butadiene styrene (CF/ABS) composite materials fabricated via Big Area Additive Manufacturing (BAAM).

evolution

carbon

composite materials

Area

Additive Manufacturing


Input: We measure the thermal evolution of composite parts during the build process using infrared imaging, and develop a simple 1D transient thermal model to describe the build process.

evolution

infrared

transient

model

composite

build

build

imaging

simple


Input: The model predictions are in excellent agreement with the observed temperature profiles and from the results we develop criteria to guide deposition parameter selection to minimize the likelihood of cracking during printing.

model

deposition

cracking

temperature

profiles


Input: Selective Laser Melting (SLM) was used to produce 3D-printed net shape NdFeB (Neodymium Iron Boron) permanent magnets that exhibit relatively large internal permanent magnetization structures, without exposure to any external magnetizing field.

Selective Laser Melting

SLM

Neodymium

Iron Boron

permanent magnets

exposure


Input: The permanent magnetization can be detected via the stray field that appears after cutting the sample into pieces.

be

cutting

sample


Input: Maximum magnetic flux densities of almost 80 mT are recorded 1 mm above the cut surfaces in the air.

flux

mm

surfaces


Input: Dependencies of the effect on SLM process parameters, as well as on the sample size and shape are discussed.

SLM

process parameters

sample size

as

as


Input: The discovered effect may offer new routes for producing magnetized rare earth-transition metal (RE-TM) permanent magnets without using a magnetizer, and it shows that the SLM 3D-printing process can lead to new material behavior.

metal

permanent magnets

lead

material

SLM 3D-printing

process


Input: Thermally induced residual stresses and residual distortions in the additive manufactured (AM) parts are two of the major obstacles that are preventing AM technology from gaining wide adoption.

residual stresses

residual distortions

additive manufactured

AM

AM technology


Input: In this work, a three-dimensional thermo-elastic-plastic model is proposed to predict the thermomechanical behavior in the laser engineered net shaping (LENS) process of Ti-6Al-4V using Finite Element Method (FEM).

three-dimensional

model

thermomechanical

process

Finite Element Method

FEM

laser engineered net shaping

LENS


Input: It is shown that the computed thermal history and mechanical deformations are in good agreement with the experimental measurements.

mechanical

deformations

experimental


Input: The main contributions of this study are: (I) in the past, a point-wise comparison between simulation results and experimental measurements is more favored to validate the employed model, where the general picture is lost; rather, to validate the proposed model, the simulated distortion of the bottom surface of a thin substrate is compared with experimental measurements using a 3D laser scanner, in terms of both magnitude and distribution map.

simulation

experimental

model

model

distortion

surface

experimental

distribution

substrate

magnitude


Input: (II) Rather few works have been done to show the effectiveness of widely employed quasi-static mechanical analysis in the transient LENS process; as such, both quasi-static and dynamic simulations are performed and compared mechanically to demonstrate the validity of using quasi-static modeling to save computational cost.

effectiveness

quasi-static mechanical analysis

transient

quasi-static

dynamic

quasi-static

LENS

as

modeling


Input: Additively manufactured (AM) conformal cooling channels are currently the state of the art for high performing tooling with reduced cycle times.

Additively manufactured

AM

conformal cooling channels

art

tooling


Input: This paper introduces the concept of conformal cooling layers which challenges the status quo in providing higher heat transfer rates that also provide less variation in tooling temperatures.The cooling layers are filled with self-supporting repeatable unit cells that form a lattice throughout the cooling layers.

conformal cooling

heat transfer

variation

tooling

unit cells

lattice

cooling

cooling

self-supporting


Input: The lattices increase fluid vorticity which improves convective heat transfer.

lattices

heat transfer

fluid


Input: Mechanical testing of the lattices shows that the design of the unit cell significantly varies the compression characteristics.A virtual case study of the injection moulding of a plastic enclosure is used to compare the performance of conformal cooling layers with that of conventional (drilled) cooling channels and conformal (AM) cooling channels.

Mechanical testing

lattices

unit cell

case study

performance

conformal cooling

design

compression

injection moulding

AM

plastic

cooling channels

cooling channels


Input: The results show the conformal layers reduce cooling time by 26.34% over conventional cooling channels.

cooling

conventional cooling channels


Input: A wide range of materials is suitable for processing by powder bed fusion (PBF) techniques.

range

materials

powder bed fusion

PBF


Input: Among the latest formulations, maraging steel 18Ni-300, which is a martensite-hardenable alloy, is often used when both high fracture toughness and high strength are required, or if dimensional changes need to be minimised.

maraging steel

alloy

be

fracture

strength


Input: In direct tooling, 18Ni-300 can be successfully employed in numerous applications, for example in the production of dies for injection moulding and for casting of aluminium alloys; moreover, it is particularly valuable for high-performance engineering parts.Even though bibliographic data are available on the effects that parameters, employed in PBF processes, have on the obtained density, roughness, hardness and microstructure of 18Ni-300, there is still a lack of knowledge on the fatigue life of PBF manufactured parts.

tooling

data

parameters

microstructure

manufactured

be

aluminium alloys

production

injection moulding

casting

PBF

PBF

dies

engineering

density

roughness

hardness

fatigue life


Input: This paper describes the fatigue behaviour of 18Ni-300 steel manufactured by PBF, as compared by forging.

fatigue

steel

as

manufactured

PBF

forging


Input: Relevant negative effects of the cross-contamination of the raw material are originally identified in this paper, which emphasizes the inadequacy of current acceptability protocols for PBF powders.

cross-contamination

protocols

raw material

PBF


Input: In the absence of contamination, endurance achieved by PBF is found equal to that by forging and consistent with tooling requirements as set out by industrial partners, based on injection moulding process modelling.

PBF

forging

injection moulding

tooling

as

industrial

modelling


Input: Metal powder bed additive manufacturing technologies, such as the Electron Beam Melting process, facilitate a high degree of geometric flexibility and have been demonstrated as useful production techniques for metallic parts.However, the EBM process is typically associated with lower resolutions and higher surface roughness compared to similar laser-based powder bed metal processes.

Metal powder

as

as

metallic

metal

bed

powder bed

additive manufacturing

Electron Beam Melting

production

EBM

flexibility

surface roughness


Input: In part, this difference is related to the larger powder size distribution and thicker layers normally used.

powder

distribution


Input: As part of an effort to improve the resolution and surface roughness of EBM fabricated components, this study investigates the feasibility of fabricating components with a smaller powder size fraction and layer thickness (similar to laser based processes).

As

powder

resolution

layer thickness

surface roughness

EBM

fabricating

components

components

investigates

feasibility

fraction

processes

laser


Input: The surface morphology, microstructure and tensile properties of the produced samples were evaluated.

surface morphology

microstructure

samples

tensile properties


Input: The findings indicate that microstructure is dependent on wall-thickness and that, for thin walled structures, tensile properties can become dominated by variations in surface roughness.

microstructure

thin walled structures

variations

tensile properties

surface roughness


Input: Additive manufacturing provides new chances in the manufacturing of highly complex, mass-customized structures with negligible wastes.

Additive manufacturing

manufacturing


Input: Binder jetting holds distinctive promise among additive manufacturing technologies due to its fast, low-cost manufacturing; stress-free structures with complex internal and external geometries; and the isotropic properties of the final printed parts.

Binder jetting

additive manufacturing

manufacturing

geometries

isotropic


Input: An ExOne binder jet 3D printer is used to produce frameworks for removable partial dentures from metallic powder.

binder

metallic powder

3D printer

dentures


Input: Initially, an existing framework is scanned using micro-computed tomography and then the obtained model is printed.

framework

model

micro-computed tomography


Input: Consolidation of the printed parts is achieved with the relative density higher than 99% density with controlled shrinkage.

Consolidation

shrinkage

relative density

density


Input: Presented results demonstrate that binder jetting may be used to produce mechanically sound complex-shaped structures as shown here on a denture metal framework model.

binder jetting

be

as

complex-shaped

framework

denture


Input: Numerical simulation is used to understand the melting and pressurization mechanism in fused filament fabrication (FFF).

Numerical simulation

melting

fused filament fabrication

FFF

mechanism


Input: The results show the incoming fiber melts axisymmetrically, forming a cone of unmelted material in the center surrounded by melted polymer.

fiber

material

forming

melted


Input: Details of the simulation reveal that a recirculating vortex of melted polymer is formed at the fiber entrance to the hot end.

simulation

melted

fiber

hot end


Input: The Generalized Newtonian Fluid (GNF) model was appropriate for simulation within the region that melts the fiber, however, a viscoelastic model, the Phan-Thien-Tanner (PTT) model, was required to capture flow within the nozzle.

Newtonian Fluid

model

model

model

simulation

fiber

viscoelastic

nozzle


Input: This is due to the presence of an elongational flow as molten material transitions from the melting region (diameter of 3 mm) to the nozzle at the exit (diameter of 0.5 mm).

as

material

melting

mm

mm

diameter

diameter

nozzle


Input: Increased manufacturing rates are limited by high pressures, necessitating more consideration in the nozzle design of future FFF printers.

manufacturing

FFF

pressures

nozzle

design


Input: A unique and efficient semi-analytic method is presented for quickly predicting the three-dimensional thermal field produced by conduction from a heat source moving along an arbitrary path.

three-dimensional

heat source


Input: A Green's function approach is used to decouple the solution at each time step into the analytical source contribution and a conduction contribution.

solution

step

source


Input: The latter is solved numerically using efficient Gaussian convolution algorithms.

Gaussian

algorithms


Input: This decoupling allows for boundary conditions on side boundaries to be satisfied numerically and lowers computational expenses by allowing calculations to be localized around the heat source.

boundary conditions

heat source

boundaries

be

be


Input: The thermal field resulting from arbitrary scan paths is constructed using analytical solutions for elementary linear segments.

analytical solutions


Input: The results of various scan patterns are presented and successfully verified against finite element simulations.

scan patterns

finite element


Input: The computational times of predictions are shown to be faster than the corresponding finite element simulation by an order of magnitude with less than 1% average error.

predictions

finite element

average

be

magnitude


Input: Given its ability to quickly predict the thermal history and changes in melt pool geometry due to arbitrary scan paths, this method provides a potentially powerful tool for exploration and optimization of laser powder bed fusion processes.

melt pool

geometry

optimization

tool

laser powder bed fusion


Input: The origins of nano-scale oxide inclusions in 316 L austenitic stainless steel (SS) manufactured by laser powder bed fusion (L-PBF) was investigated by quantifying the possible intrusion pathways of oxygen contained in the precursor powder, extraneous oxygen from the process environment during laser processing, and moisture contamination during powder handling and storage.

nano-scale

manufactured

process

laser processing

inclusions

austenitic stainless steel

SS

oxygen

precursor powder

oxygen

powder

laser powder bed fusion

L-PBF


Input: When processing the fresh, as-received powder in a well-controlled environment, the oxide inclusions contained in the precursor powder were the primary contributors to the formation of nano-scale oxides in the final additive manufactured (AM) product.

powder

oxide inclusions

precursor powder

nano-scale

additive manufactured

AM


Input: These oxide inclusions were found to be enriched with oxygen getter elements like Si and Mn.

oxide inclusions

be

oxygen

elements

Si

Mn


Input: By controlling the extraneous oxygen level in the process environment, the oxygen level in AM produced parts was found to increase with the extraneous oxygen level.

oxygen

oxygen

oxygen

process

AM


Input: The intrusion pathway of this extra oxygen was found to be dominated by the incorporation of spatter particles into the build during processing.

oxygen

be

spatter

particles

build


Input: Moisture induced oxidation during powder storage was also found to result in a higher oxide density in the AM produced parts.

oxidation

AM

powder

oxide

density


Input: SS 316 L powder free of Si and Mn oxygen getters was processed in a well-controlled environment and resulted in a similar level of oxygen intrusion.

SS

powder

Si

Mn

oxygen

processed


Input: Microhardness testing indicated that the oxide volume fraction increase from extraneous oxygen did not influence hardness values.

Microhardness

fraction

oxide

oxygen

hardness


Input: However, a marked decrease in hardness was found for the humidified and Si-Mn free AM processed parts.

hardness

AM


Input: Laser Engineered Net Shaping (LENS®) is a metal Additive Manufacturing (AM) technique that carries great potential for the fabrication and repair of high-integrity structural and engine components.

Laser Engineered Net Shaping

metal Additive Manufacturing

AM

fabrication

components


Input: Confident application of the LENS technique requires a fundamental understanding of the microstructure and properties of the fabricated materials, as well as their correlations to processing conditions.

LENS

microstructure

properties

fabricated

as

as


Input: In this study, two alloys fabricated by LENS, Ti-6Al-4V and Inconel 718, were examined and compared to their wrought counterparts.

alloys

Inconel 718

LENS

wrought


Input: The differences between low and high laser power fabrications, as well as the effects of various post-LENS heat treatments were systematically investigated and discussed.

laser power

as

as

heat treatments


Input: The interfacial bond strength between LENS depositions and substrates were also evaluated for repair purposes.

interfacial bond

LENS


Input: The residual porosity and surface roughness of metal materials generated via additive manufacturing are generally regarded as the major influence factors on the fatigue strength.

residual

porosity

surface roughness

fatigue strength

metal materials

as

additive manufacturing


Input: The mechanical properties of specimens out of tool steel 1.2344 were investigated.

mechanical properties

tool

steel


Input: Tensile strength and hardness achieved results in the range of conventionally fabricated parts, whereas a significantly lower fatigue strength was observed.

Tensile strength

hardness

fatigue strength

range

fabricated


Input: Cracks were induced by the present cavities as well as in the steel matrix.

as

as

steel


Input: Further investigations of the oxygen content showed a high oxygen content of 570 ppm homogeneously distributed inside the specimens potentially limiting the strength of the matrix itself.

oxygen

oxygen

strength


Input: Process monitoring in additive manufacturing (AM) is a crucial component in the mission of broadening AM industrialization.

Process monitoring

additive manufacturing

AM

AM

component


Input: However, conventional part evaluation and qualification techniques, such as computed tomography (CT), can only be utilized after the build is complete, and thus eliminate any potential to correct defects during the build process.

as

be

CT

build

build

defects


Input: In contrast to post-build CT, in situ defect detection based on in situ sensing, such as layerwise visual inspection, enables the potential for in-process re-melting and correction of detected defects and thus facilitates in-process part qualification.

CT

in situ

defect

in situ

defects

as

inspection


Input: This paper describes the development and implementation of such an in situ defect detection strategy for powder bed fusion (PBF) AM using supervised machine learning.During the build process, multiple images were collected at each build layer using a high resolution digital single-lens reflex (DSLR) camera.

in situ

defect

images

powder bed fusion

PBF

AM

machine

camera

build

build layer

high resolution


Input: For each neighborhood in the resulting layerwise image stack, multi-dimensional visual features were extracted and evaluated using binary classification techniques, i.e.

image

extracted

binary


Input: a linear support vector machine (SVM).

support

machine


Input: Through binary classification, neighborhoods are then categorized as either a flaw, i.e.

binary

flaw

as


Input: an undesirable interruption in the typical structure of the material, or a nominal build condition.

structure

material

build


Input: the true location of flaws and nominal build areas, which are needed to train the binary classifiers, were obtained from post-build high-resolution 3D CT scan data.

flaws

binary

data

build areas

high-resolution


Input: In CT scans, discontinuities, e.g.

CT


Input: incomplete fusion, porosity, cracks, or inclusions, were identified using automated analysis tools or manual inspection.

fusion

porosity

inclusions

tools

inspection


Input: After the classifier had been properly trained, in situ defect detection accuracies greater than 80% were demonstrated during cross-validation experiments.

in situ

defect


Input: In this paper the heat transfer and residual stress evolution in the direct metal laser sintering process of the additive manufacturing of titanium alloy products are studied.

heat transfer

evolution

residual stress

direct metal laser sintering

additive manufacturing

titanium alloy


Input: A numerical model is developed in a COMSOL multiphysics environment considering the temperature-dependent material properties of TiAl6V4.

model

material properties


Input: The thermo-mechanical coupled simulation is performed.

thermo-mechanical

simulation


Input: 3-D simulation is used to study single-layer laser sintering.

laser sintering


Input: A 2-D model is used to study the multi-layer effects of additive manufacturing.

model

additive manufacturing


Input: The results reveal the behavior of the melt pool size, temperature history, and change of the residual stresses of a single layer and among the multiple layers of the effects of the change of the local base temperature and laser power etc.

melt pool

temperature

layer

temperature

laser power

residual stresses


Input: The result of the simulation provides a better understanding of the complex thermo-mechanical mechanisms of laser sintering additive manufacturing processes.

simulation

thermo-mechanical

laser sintering additive manufacturing processes


Input: Laser-matter interactions in laser additive manufacturing (LAM) occur on short time scales (10−6–10−3 s) and have traditionally proven difficult to characterise.

laser additive manufacturing

LAM

time scales

s


Input: We investigate these interactions during LAM of stainless steel SS316L and 13-93 bioactive glass powders using a custom built LAM process replicator (LAMPR) with in situ and operando synchrotron X-ray real-time radiography.

LAM

LAM

stainless steel

bioactive glass

in situ

synchrotron

radiography


Input: This reveals a wide range of melt track solidification phenomena as well as spatter and porosity formation.

range

melt

solidification

as

as

porosity


Input: We hypothesise that the SS316L powder absorbs the laser energy at its surface while the trace elements in the 13-93 bioactive glass powder absorb and remit the infra-red radiation.

powder

trace elements

bioactive glass

laser energy

surface

radiation


Input: Our results show that a low viscosity melt, e.g.

viscosity

melt


Input: 8 mPa s for SS316L, tends to generate spatter (diameter up to 250 μm and an average spatter velocity of 0.26 m s−1) and form a melt track by molten pool wetting.

mPa

diameter

average

melt

molten pool

spatter


Input: In contrast, a high viscosity melt, e.g.

viscosity

melt


Input: 2 Pa s for 13-93 bioactive glass, inhibits spatter formation by damping the Marangoni convection, forming a melt track via viscous flow.

Pa

spatter

bioactive glass

forming

melt


Input: The viscous flow in 13-93 bioactive glass resists pore transport; combined with the reboil effect, this promotes pore growth during LAM, resulting in a pore size up to 600 times larger than that exhibited in the SS316L sample.

bioactive glass

pore

pore

LAM

pore size

sample


Input: An evaluation of low-cost, high-oxygen content Zr-Cu-Al-Nb bulk metallic glasses (BMGs) produced through laser powder bed fusion (PBF) was performed.

metallic glasses

laser powder bed fusion

PBF


Input: Four-point bending and wear resistance tests were used to compare the mechanical properties of the printed alloy with laboratory grade cast parts.

bending

cast

wear resistance

mechanical properties

laboratory

alloy


Input: It is shown that the laser PBF parts, while not being able to be cast as a bulk glass, can be printed amorphous up to at least several millimeters thick and yet still have reasonable mechanical properties.

laser

be

as

glass

be

mechanical properties


Input: Additive manufacturing (AM) of highly viscous materials, e.g., polysiloxane (silicone) has gained attention in academia and different industries, specifically the medical and healthcare sectors.

Additive manufacturing

AM

materials

silicone

industries

medical


Input: Different AM processes including micro-syringe nozzle dispensing systems have demonstrated promising results in the deposition of highly viscous materials.

AM processes

nozzle

deposition

materials


Input: This contact-based 3D printing system has drawbacks such as overfilling of material at locations where there is a change in the direction of the trajectory, thereby reducing the printing quality.

3D printing

as

material

quality


Input: Modeling the continuous flow of a highly viscous polysiloxane in the nozzle dispensing AM system using finite element analysis will be the first step to solve this overfilling phenomenon.

Modeling

nozzle

AM

finite element analysis

step

be


Input: The results of simulation can be used to predict the required variation in the value of pressure before the nozzle reaches a corner.

simulation

be

variation

pressure

nozzle


Input: The level-set method is employed for this simulation, and the results are validated by comparing the flow profile and geometrical parameters of the model with those of the experimental trials of the dispensing of polysiloxane.

simulation

profile

parameters

model

experimental


Input: Comparisons show that the model is able to predict the location of the droplet before it reaches the substrate, as well as the height of the droplet generated on the substrate accurately.

model

droplet

droplet

substrate

as

as

substrate

accurately


Input: To predict the width of the droplet, adjustment factors need to be considered in calculations based on the value of the pressure.

droplet

pressure

be


Input: A significant microstructural inhomogeneity in EBM fabricated Co-Cr-Mo alloy along building direction.

microstructural

EBM

alloy

building direction


Input: Post-production heat treatment regime homogenized microstructures and enhanced mechanical properties.

heat treatment

homogenized

mechanical properties


Input: The phase constituents significantly affected the mechanical behaviors of Co-Cr-Mo alloy.

phase

mechanical

alloy


Input: The electron beam melting (EBM), a layer-by-layer additive manufacturing (AM) technique, has been recently utilized for fabricating metallic components with complex shape and geometry.

electron beam melting

EBM

additive manufacturing

AM

fabricating

layer-by-layer

geometry

components

complex shape


Input: However, the inhomogeneity in microstructures and mechanical properties are the main drawbacks constraining the serviceability of the EBM-built parts.

microstructures

mechanical properties


Input: In the present study, we found remarkable microstructural inhomogeneity along build direction in the EBM-built Co-based alloy, owing to the competitive grain growth and subsequent isothermal γ-fcc → ε-hcp phase transformation, which affects the corresponding tensile properties significantly.

microstructural

grain growth

isothermal

phase

build direction

alloy

tensile properties


Input: Then, we succeeded in eliminating the inhomogeneities, modifying the phase structures and refining grain sizes via comprehensive post-production heat treatment regimes, which provides a valuable implication for improving the reliabilities of AM-built metals and alloys.

phase

grain sizes

heat treatment

metals

alloys


Input: The Co-based alloy can be selectively transformed into predominant ε or predominant γ phase by the regime, and the grains were refined to 1/10 of the initial sizes by repeated heat treatment.

alloy

be

phase

grains

heat treatment


Input: Finally, we investigated the tensile properties and fracture behaviors of the alloy before and after each heat treatment.

tensile properties

fracture

alloy

heat treatment


Input: The γ → ε strain-induced martensitic transformation is the major deformation mode of the γ phase, meanwhile the formation of stripped ε phase at {111} γ habit planes contributed to a good combination of strength and ductility.

deformation

phase

phase

strength

ductility


Input: Nevertheless, the ε phase was deformed mainly by (0001) ε < 11 2¯0 > ε basal and {1 1¯00} ε < 11 2¯0 > ε prismatic slip systems, exhibiting very limited ductility and strength.

phase

prismatic

deformed

ductility

strength


Input: In addition, the ε grains act as secondary hardening factor in the samples consisting of dual γ/ε phase, leading to a non-uniform deformation behavior.

grains

samples

phase

deformation

as

hardening


Input: Two new high-carbon high speed steel alloys; Febal-C-Cr-Mo-V and Febal−x-C-Cr-Mo-V-Wx were additively manufactured by directed energy deposition (DED) process.

high speed steel alloys

Febal-C-Cr-Mo-V

additively manufactured

directed energy deposition

DED

process


Input: Micro-hardness (0.5 HV) measurement of multilayer additively manufactured samples showed no softening of martensite matrix under complex thermal cycling.

measurement

additively manufactured

martensite

thermal cycling


Input: Due to larger phase fraction of metal carbides and formation of a relatively stable oxide layer, Febal−x-C-Cr-Mo-V-Wx showed better high temperature (500 °C) wear resistance than Febal-C-Cr-Mo-V. Neutron diffraction of powders and additively manufactured samples of Febal-C-Cr-Mo-V and Febal−x-C-Cr-Mo-V-Wx alloys showed weak scattering properties.

phase fraction

properties

metal carbides

oxide

powders

Febal-C-Cr-Mo-V

alloys

layer

temperature

wear resistance

Neutron diffraction

additively manufactured


Input: The inconclusive strain scanning was either result of a strong crystallographic texture in the bulk or due to existence of nano- or semi-crystalline phases.

strain

scanning

texture


Input: Directed energy deposition (DED) of two high-carbon high speed steel alloys Febal-C-Cr-Mo-V and Febal−x-C-Cr-Mo-V-Wx was performed by using a 4 kW Nd: YAG laser source.

Directed energy deposition

DED

high speed steel alloys

Febal-C-Cr-Mo-V

Nd: YAG

laser source


Input: The purpose of additive manufacturing was design and evaluation of thermally stable–high temperature wear resistant alloys.

additive manufacturing

design

temperature

alloys


Input: High temperature (500 °C) pin-on-disc tests were conducted to investigate the effect of carbides phase fraction on friction and wear.

temperature

carbides

fraction

friction

wear


Input: Strain scanning of the powder and additively manufactured materials was carried out by Neutron diffraction.Microstructures of both alloys consisted of a martensitic matrix with networks of primary and eutectic carbides.

Strain

scanning

Neutron

eutectic

powder

alloys

carbides

additively manufactured


Input: Febal−x-C-Cr-Mo-V-Wx showed a better high temperature wear resistance due to greater phase fraction of VC and Mo2C carbides.

temperature

resistance

phase fraction

VC

carbides


Input: Fracture surfaces of post-heat treated tensile samples of Febal-C-Cr-Mo-V and Febal−x-C-Cr-Mo-V-Wx revealed brittle failures with minimal plasticity.

Fracture

samples

brittle failures

tensile

plasticity

Febal-C-Cr-Mo-V


Input: Neutron strain mapping of the metal powders and the additively manufactured materials resulted in a weak diffraction signal and peak widening effect.

Neutron

metal powders

additively manufactured

diffraction


Input: Ti–6Al–4V parts made using additive manufacturing processes such as selective laser melting (SLM) and electron beam melting (EBM) are subject to the inclusion of defects.

additive manufacturing processes

SLM

electron beam melting

EBM

as

inclusion

laser

defects


Input: This study purposely fabricated Ti–6Al–4V samples with defects by varying process parameters from the factory default settings in both SLM and EBM systems.

fabricated

samples

defects

process parameters

SLM

EBM


Input: Process parameters are classified according to their tendency to create certain types of porosity.

Process parameters

porosity


Input: Finally, defect characteristics are discussed with respect to defect generation mechanisms; and effective process windows for SLM and EBM system are discussed.

defect

defect

process

SLM

EBM


Input: Developed intra-layer, closed-loop control of additive manufacturing build plan.

closed-loop control

additive manufacturing


Input: Control affected macrostructure, microstructure, and mechanical properties.

microstructure

mechanical properties


Input: Demonstrated reduced variability in microstructure and hardness with control.

variability

microstructure

hardness


Input: The location, timing, and arrangement of depositions paths used to build an additively manufactured component–collectively called the build plan–are known to impact local thermal history, microstructure, thermal distortion, and mechanical properties.

build

build

additively manufactured

impact

microstructure

thermal distortion

mechanical properties


Input: In this work, a novel system architecture for intra-layer, closed-loop control of the build plan is introduced and demonstrated for directed-energy deposition of Ti–6Al–4V.

architecture

closed-loop control

build

deposition


Input: The control strategy altered the build plan in real time to ensure that the temperature around the start point of each hatch, prior to deposition, was below a threshold temperature of 415 °C.

build

temperature

temperature

deposition


Input: Compared with open-loop processing, closed-loop control resulted in vertical alignment of columnar prior-β grains, more uniform α-lath widths, and more-uniform microhardness values within the deposited component.

closed-loop control

component

vertical

grains

microhardness


Input: Recently, laser-powder bed fusion (L-PBF) has been utilized to produce a NiTi shape memory alloy actuator with embedded channels for liquid metal forced fluid convection to increase actuator heat transfer rates.

bed fusion

L-PBF

NiTi

alloy

liquid metal

fluid

actuator

actuator


Input: To enable further increases in performance, it is critical to characterize and control the surface quality of fully interior channels which have higher surface roughness compared to exterior top surfaces.

performance

surfaces

surface quality

surface roughness


Input: This work utilizes a design of experiments methodology by varying laser power, scan speed, hatch space, scan pattern, channel orientation, and channel diameter on the as-fabricated surface roughness of the overhangs and walls of interior channels in NiTi.

design of experiments

laser power

scan speed

scan pattern

overhangs

channel

channel diameter

surface roughness

NiTi


Input: To enable post-process increases in surface quality, the channels are subjected to an electropolishing treatment and further characterized.

post-process

surface quality

electropolishing


Input: Internal channel surfaces are characterized using optical profilometry and SEM imaging.

channel

imaging

optical

SEM


Input: It is concluded that channel orientation plays a prominent role in determining the surface roughness of as-fabricated interior channels, and a lower laser energy density results in the highest reduction in surface roughness after an electropolishing treatment.

channel

surface roughness

surface roughness

laser energy density

reduction

electropolishing


Input: Laser powder bed fusion (LPBF) additive manufacturing and laser welding are powerful metal processing techniques with broad applications in advanced sectors such as the biomedical and aerospace industries.

Laser powder bed fusion

LPBF

additive manufacturing

laser welding

metal

as

biomedical

aerospace industries


Input: One common process variable that can tune laser-material interaction dynamics in these two techniques is adjustment of the composition and pressure of the atmosphere in which the process is conducted.

process

composition

pressure

process


Input: While some of the physical mechanisms that are governed by the ambient pressure are well known from the welding literature, it remains unclear how these mechanisms extend to the distinct process conditions of LPBF.

pressure

process

welding

LPBF


Input: In situ studies of the differences in subsurface structure and behavior are essential for understanding the effects of gas pressure and composition on the LPBF processes.

In situ

structure

gas

composition

LPBF


Input: This article reports the use of in situ X-ray imaging to directly probe the morphological evolution of the liquid-vapor interface during laser melting as a function of ambient pressure and oxygen partial pressure under LPBF conditions in 316 L steel, Ti-64, aluminum 6061, and Nickel 400.

in situ

evolution

interface

pressure

pressure

imaging

probe

laser

as

oxygen

steel

aluminum

Nickel

LPBF


Input: We observe significant changes in melt pool morphology as a function of pressure.

melt pool

as

pressure


Input: Furthermore, similar changes in morphology occur due to an increase in oxygen partial pressure in the process atmosphere.

morphology

pressure

process

oxygen


Input: Temperature- and composition-dependent changes in surface tension of the liquid metal drive this change in behavior, which has the potential to influence defect creation and final morphology in LPBF parts.

surface tension

liquid metal

defect

morphology

LPBF


Input: Electron beam additive manufacturing (EBAM) is a relatively new technology to produce metallic parts in a layer by layer fashion by melting and fusing the metallic powders.

Electron beam additive manufacturing

EBAM

melting

technology

layer by layer

fashion

fusing

metallic parts

metallic powders


Input: Ti–6Al–4V is one of the most used industrial alloys used for aerospace and biomedical application.

industrial

aerospace

biomedical application

alloys


Input: EBAM is a rapid solidification process and the properties of the build material depend on the solidification behavior as well as the microstructure of the build material.

EBAM

rapid solidification process

properties

solidification

microstructure

build material

as

as

build material


Input: Thus, the prediction of part microstructures during the process may be an important factor for process optimization.

prediction

process

process optimization

microstructures

be


Input: In this study, a phase field model is developed for microstructure evolution of Ti–6Al–4V powder in EBAM process.

phase

model

microstructure evolution

powder

EBAM


Input: FORTRAN code is used to solve the phase field equations, which incorporates the temperature gradient and solidification velocity as the simulation parameters.

phase

parameters

temperature gradient

solidification velocity

as

simulation


Input: The effect of temperature gradient and the beam scan speed on microstructure is investigated through simulation.

temperature gradient

beam

microstructure

simulation


Input: The simulation results are compared with the analytical model and experimental findings by measuring the spacing evolution under the solidification condition Exciting progress in additive manufacturing (AM) technology, which enables fabrication of cellular structures with highly complex lattices and pores, has stimulated the development of lightweight structural products with improved performance and increased functionality.

simulation

model

experimental

evolution

solidification

technology

lattices

lightweight

performance

additive manufacturing

AM

fabrication

cellular structures

pores


Input: However, conventional design and analysis tools lack the ability to optimize complex geometries efficiently and robustly.

design

tools

complex geometries


Input: With this motivation, in this study, homogenized material models of open-cell polymeric foams with spherical cell architectures that are manufactured by using an AM technology are formulated through both experimental and numerical investigations, which in turn can be employed in a novel micromechanics based topology optimization algorithm developed for the optimization of cellular structures.

homogenized

AM technology

spherical

manufactured

experimental

algorithm

optimization

cell

be

topology optimization

cellular structures


Input: In this regard, generating computer aided drawing (CAD) data, which is mandatory for AM, randomly intersected spherical ensemble method is employed.

computer

CAD

drawing

AM

data

spherical


Input: Several foam models with different porosities are generated, and utilized in nonlinear finite element analyses (FEAs) to determine constitutive elastic constants.

foam

porosities

finite element analyses

elastic constants


Input: Plastic stress-strain data for the bulk AM material are obtained through static tensile tests in a variety of different loading directions and these results used in FEA as true stress-strain data.

Plastic

AM material

as

data

data

tensile tests


Input: Homogenization is performed based on a quadratic form of the widely used Gibson and Ashby foam model, which describes the Young’ s modulus E∗ and yield strength σpl∗ of cellular structures in terms of relative density.

Homogenization

foam

s

yield strength

relative density

cellular structures


Input: Predicting residual distortion in metal additive manufacturing (AM) is important to ensure quality of the fabricated component.

residual distortion

quality

fabricated

metal additive manufacturing

AM

component


Input: The inherent strain method is ideal for this purpose, but has not been well developed for AM parts yet.

strain

AM parts


Input: In this paper, a modified inherent strain model is proposed to estimate the inherent strains from detailed AM process simulation of single line depositions on top of each other.

strain

model

AM process


Input: The obtained inherent strains are employed in a layer-by-layer static equilibrium analysis to simulate residual distortion of the AM part efficiently.

layer-by-layer

equilibrium

residual distortion

AM part


Input: To validate the model, depositions of a single wall and a rectangular contour wall models with different number of layers deposited by a representative directed energy deposition (DED) process are studied.

model

process

contour

number of layers

directed energy deposition

DED


Input: The proposed model is demonstrated to be accurate by comparing with full-scale detailed process simulation and experimental results.

model

experimental

be

accurate

process simulation


Input: Based on this approach, simulation results applied to the rectangular contour wall structures of different heights show that the modified inherent strain method is quite efficient, while the residual distortion of AM parts can be accurately computed within a short time.

simulation

contour

modified inherent strain method

residual distortion

AM parts

be

accurately


Input: The improvement of the computational efficiency can be up to 80 times in some specific cases.

computational efficiency

be


Input: Stainless steel 316L dogbones produced using two production methods were studied.

Stainless steel

production


Input: General corrosion was not considered to be a major form of corrosion after 2184 h. Mechanical properties for the traditionally manufactured samples did not change.

corrosion

corrosion

Mechanical properties

manufactured

be


Input: Mechanical properties for the AM samples decreased during the exposure time.

Mechanical properties

exposure

AM


Input: Hydrogen embrittlement in the AM samples caused the mechanical properties decrease.

Hydrogen embrittlement

mechanical properties

AM


Input: The effects on the surface and mechanical properties of stainless steel AISI316L dogbones created using either traditional manufacturing (TM) or laser powder bed fusion (LPBF) exposed to 0.75 M sulfuric acid solution over 2184 h were studied.

surface

mechanical properties

solution

stainless steel

traditional manufacturing

laser powder bed fusion

LPBF


Input: General corrosion was not a major form of corrosion, based on surface feature changes, surface roughness, and mass loss for either method.

corrosion

corrosion

surface

feature

surface roughness


Input: No change to the mechanical properties occurred for the TM samples.

mechanical properties

samples


Input: Both tensile stress and strain decreased for the LPBF samples.

tensile stress

strain

LPBF


Input: The decrease was caused by hydrogen embrittlement, due to the formation of large brittle particles, as demonstrated by scanning electron microscopy.

hydrogen embrittlement

brittle

as

scanning electron microscopy


Input: Additive manufacturing (AM) of complex tungsten carbide-cobalt (WC-Co) parts was achieved using binder jet additive manufacturing (BJAM) of WC powders followed by Co infiltration.

Additive manufacturing

AM

additive manufacturing

tungsten

binder

WC

powders

Co


Input: Using BJAM with infiltration of the metal phase can limit shrinkage and grain growth in ceramic-metal (cermet) composites compared to other additive manufacturing (AM) methods.

infiltration

limit

grain growth

metal

ceramic-metal

cermet

composites

additive manufacturing

AM


Input: Knowledge of previous infiltration studies was used to help process parts to imitate production of parts.

infiltration

process

production


Input: The properties such as density, microstructure, grain size, and hardness of the parts are characterized along the infiltration height.

properties

microstructure

infiltration

as

grain size

hardness


Input: Fracture toughness is measured where applicable.

Fracture