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rag
information-retrieval
evaluation-benchmark
glass-manufacturing
furnace
scientific-literature
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", with volumes ranging from 0.1 to 30.1 mm3. The wall cell y + on the plate is between 5 and 41, which is partly too low for the high Reynolds number turbulence model used. This is unavoidable because of the strong flow field variations due to the impinging jets, but poses no major difficulty since the CFD solver ... | true | openai_compatible | [
"10.1016/j.applthermaleng.2007.12.014#chunk-0012"
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"10.1016/j.applthermaleng.2007.12.014"
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"10.1016/j.applthermaleng.2007.12.014"
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[
"Numerical model and flow field analysis",
"Cooling flow field in the tempering zone"
]
] | In the simulation of impinging jet cooling in a glass tempering unit, why does a typical fountain flow pattern appear near the plate surface? What are its main flow characteristics, what is the range of jet impinging angles, and what are the key boundary conditions set in the calculation? | glass-eval-v0.1-q001 | concept_mechanism | 在玻璃钢化风栅的冲击射流冷却模拟中，板面附近为何会出现典型的“喷泉流”模式？该流动有哪些主要特征，射流冲击角的变化范围是多少，计算中设定的关键边界条件又是什么？ | 模拟中，喷嘴排底部的孔构成流动入口，钢化区的所有表面被视为对称面或具有指定压力条件的出口；来自喷嘴的空气射流被假设为均匀，平均法向入口速度为100 m/s，温度T_a=298 K，玻璃表面温度设为T_0=923 K。流场显示，在z=0 mm中心平面及靠近板端的平面中，局部投影速度矢量均表现出典型的喷泉流（fountain flow）模式，其特征是射流冲击后的相互干涉（post-impingement interference）。在中心平面，这一现象延伸到射流之间的大部分空间，可见侧向堆积并产生显著的向左横流。流动主要朝侧面方向，但平均运动略朝外喷嘴端；该纵向分量造成沿x方向的额外堆积，从而使壁面区域增厚并将喷泉流向上推回。此外，由于... | human_verified | 0.1.0 | dev | [
"annealing_tempering",
"heat_transfer_cfd",
"quality_defects"
] |
true | [
"Radical process transition (RT) accrues fuel savings worth nearly two-thirds (63%) of total fuel savings from its roadmap [16,19]. In contrast, deploying CCS technology involves an energy penalty and reduces consequential savings [5]. Coal use retains a significant share under the RA-CCS scenario (Fig. 7), togethe... | true | openai_compatible | [
"10.1016/j.adapen.2021.100037#chunk-0033"
] | [
"10.1016/j.adapen.2021.100037"
] | [
"10.1016/j.adapen.2021.100037"
] | [
[
"UK technology roadmaps for the glass and comparator sectors out to 2050",
"UK technology roadmap projections2"
]
] | In the breakthrough roadmap scenarios, why does radical process transition (RT) achieve a greater cumulative GHG emission reduction by 2050 compared with CCS, and what is the underlying mechanism? | glass-eval-v0.1-q002 | concept_mechanism | 在突破性路线图情景中，激进工艺转型（RT）相比CCS为何能在2050年实现更大的累计温室气体减排？其作用机理是什么？ | 在突破性路线图（RA-CCS、RA-CCS [bio]和RT）中，RT情景的燃料节约约占其路线图总燃料节约的近三分之二（63%）；相反，部署CCS技术会带来能源惩罚，从而减少相应的节约。到2050年（与1990年水平相比），Scope 1-2/3温室气体减排在RA-CCS下为78%，在RA-CCS [bio]下为88%，在RT下为79%，因此所有突破性路线图都实现了英国初始碳计划为工业设定的70%目标。虽然RT和RA-CCS到2050年的脱碳量相近，但RT在累计温室气体减排上更大，原因在于RT在短中期主要通过更快地摆脱能源密集型（EI）工艺和技术实现更深的减排。 | human_verified | 0.1.0 | dev | [
"combustion_fuels",
"emissions_decarbonization",
"energy_waste_heat",
"technoeconomic_lca"
] |
true | [
". (1)–(18) included in the constraint set refer equation (19). For example, it would take time to transfer heat generated by fuel combustion to the bottom of the glass melt. Similarly, transferring heat from the bottom electrodes to the top layer of the glass can be expected to be slow. In this case, to change the... | true | openai_compatible | [
"10.1016/j.apenergy.2020.115077#chunk-0024"
] | [
"10.1016/j.apenergy.2020.115077"
] | [
"10.1016/j.apenergy.2020.115077"
] | [
[
"Optimization problem",
"Optimization problem"
]
] | In a glass melting furnace, what are the heat transfer lag characteristics of fuel combustion and electric boosting? How do these lags affect the adjustment of the electricity-to-gas firing ratio, and why is temperature distribution considered a key measurable indicator of melting quality? | glass-eval-v0.1-q003 | concept_mechanism | 玻璃熔窑中，燃料燃烧和电助熔的热量传递存在哪些滞后特点？这些滞后如何影响电、气配比调整，且为何温度分布是熔制质量的关键可测指标？ | 燃料燃烧产生的热量传递到玻璃液底部需要时间，底部电极产生的热量向上层玻璃液传递也同样缓慢，因此玻璃熔窑的热响应存在明显滞后。在需要改变电力与燃气燃烧之间的配比时，不能等待滞后效应显现，而应主动提前调整燃料能量供给，以使温度达到期望目标。原料熔化、气泡去除（澄清）和均化是熔制性能的重要指标，这些过程取决于玻璃液温度、玻璃液流速、停留时间和浓度；其中许多因素无法在线测量，所以可测的玻璃液温度分布成为判断熔制性能的关键指标，并可作为最终产品的质量指数。为保证运行约束和玻璃质量，玻璃熔制温度需被控制在期望目标温度附近的允许偏差范围内，且燃烧器与电极对的功率分别受到其最大容量限制；期望目标温度本身采用启发式给定值。电价与天然气价格分别取自对应... | human_verified | 0.1.0 | dev | [
"combustion_fuels",
"electric_melting",
"emissions_decarbonization",
"energy_waste_heat",
"manufacturing_planning",
"melting_furnace",
"optimization_scheduling"
] |
true | [
"spectrum range were calculated and an average of all evaluations was taken as the actual temperature result. Fig. 3 shows an example for a measured spectrum and the calculated Planck functions for five different temperatures. The measured spectrum used for the temperature calculations was acquired by the ruled gra... | true | openai_compatible | [
"10.1016/j.applthermaleng.2004.07.020#chunk-0017"
] | [
"10.1016/j.applthermaleng.2004.07.020"
] | [
"10.1016/j.applthermaleng.2004.07.020"
] | [
[
"Temperature and spectral peak calculations"
]
] | In glass furnace flame diagnostics, how can emission spectroscopy be used to determine flame temperature and monitor combustion stoichiometry via the OH radical emission band near 310 nm, and what factors influence the measured OH emission intensity? | glass-eval-v0.1-q004 | concept_mechanism | 在玻璃熔窑火焰诊断中，如何利用发射光谱确定火焰温度，并通过OH自由基在310 nm附近的发射带监测燃烧化学计量？OH发射强度会受到哪些因素影响？ | 通过测量火焰发射光谱，并用不同温度的普朗克函数对测量光谱进行拟合，取所有评价值的平均值作为实际温度结果；例如在200–850 nm波段用刻划光栅获取光谱，最佳拟合函数对应的温度可为2157 K。发射光谱的UV区可作为火焰化学计量的指示：不同波长范围的发射线对应OH、C2、CH、CN、HCN等自由基的电子-振动光谱活动，Li、Na、K、Mg、Ca等碱金属和碱土金属的微量化合物也可能产生较强峰，它们可能来自玻璃液和耐火材料。实验证实，OH谱带在310 nm发射线附近的变化对燃烧进程具有很好的响应和敏感性，可作为燃烧进程指示器。OH自由基光谱强度随燃烧器空气或氧气/燃料比变化；同时OH发射强度还取决于探头的观测位置和透镜聚焦位置，因此实际... | human_verified | 0.1.0 | dev | [
"combustion_fuels",
"emissions_decarbonization",
"energy_waste_heat",
"melting_furnace",
"process_control",
"sensing_monitoring"
] |
true | [
"Among the heat consumed by heating equipments, such as glass kiln stove, there are about 40% released by flue gas emission. The recovered flue gas heat from glass kiln of float line one is insufficient for generating 15 tons low-pressure saturated steam. Therefore, it is suggested that the recovered flue gas heat ... | true | openai_compatible | [
"10.1016/j.apenergy.2010.02.029#chunk-0014"
] | [
"10.1016/j.apenergy.2010.02.029"
] | [
"10.1016/j.apenergy.2010.02.029"
] | [
[
"Potential analysis and suggestions on energy conservation"
]
] | Why should the flue gas waste heat from a glass melting furnace be preferentially used for power generation rather than directly producing low-pressure saturated steam? | glass-eval-v0.1-q005 | concept_mechanism | 为什么玻璃熔窑的烟气余热应优先用于发电而非直接产生低压饱和蒸汽？ | 在加热设备（如玻璃窑炉）消耗的热量中，约有40%通过烟气排放。浮法一线玻璃窑回收的烟气热量不足以产生15吨低压饱和蒸汽，因此建议将回收的烟气余热首先用于发电，再将产生的电能转化为热能供应，这样可以提高余热的利用效率。也就是说，由于余热量有限，直接产汽不能满足要求，先发电再供热的方式更能有效利用这部分余热。 | human_verified | 0.1.0 | dev | [
"combustion_fuels",
"energy_waste_heat",
"sensing_monitoring"
] |
true | [
"number of bins or stock sheets required, there is an increasing trend of considering leftovers as reusable and therefore not counting them as waste. In particular, the idea of considering just the unused part of the last bin as reusable has appeared in recent bin packing studies (Bennell, Cabo, & Martinez-Sykora, ... | true | openai_compatible | [
"10.1016/j.ejor.2020.05.016#chunk-0020"
] | [
"10.1016/j.ejor.2020.05.016"
] | [
"10.1016/j.ejor.2020.05.016"
] | [
[
"Related work"
]
] | In optimization research for cutting and further processing, what are the trends in handling leftovers and the application scope of beam search? | glass-eval-v0.1-q006 | concept_mechanism | 在切割与深加工的优化研究中，关于余料的处理趋势以及束搜索算法的应用范围分别是什么？ | 在切割与装箱优化中，关于所需料箱或板材数量，越来越倾向于将余料视为可重复使用，因此不计入废料；特别是只将最后一个料箱的未使用部分视为可重复使用的想法已出现在近期的装箱研究中。此外，束搜索算法已应用于许多组合优化问题，尤其是当解可定义为元素序列或移动序列时；在切割与装箱领域，束搜索已被应用于不规则件切割、集装箱装载和装箱问题。 | human_verified | 0.1.0 | dev | [
"finishing_cutting",
"manufacturing_planning",
"optimization_scheduling"
] |
true | [
"Ferric iron is the main oxidizer in the float glass which is reduced by the stannous tin diffusing into the glass. Sulfur is also a polyvalent species and it is added to the glass as sulfate to act as a reefing agent. Depending on the redox state of the float glass, the sulfur exists in the 6+, 4+ and 2+ states. T... | true | openai_compatible | [
"10.1016/j.applthermaleng.2010.12.030#chunk-0014"
] | [
"10.1016/j.applthermaleng.2010.12.030"
] | [
"10.1016/j.applthermaleng.2010.12.030"
] | [
[
"Tin penetration mechanisms",
"Kinetic modeling"
]
] | In float glass manufacturing, what substance mainly controls the oxidation of Sn2+? Why does sulfur contribute less to oxidation even though it is present? | glass-eval-v0.1-q007 | concept_mechanism | 在浮法玻璃生产过程中，锡离子（Sn2+）的氧化主要受哪种物质控制？为什么硫虽然存在，但其氧化贡献较小？ | 在浮法玻璃中，三价铁（ferric iron）是主要的氧化剂，Sn2+的氧化主要归因于扩散进入玻璃的亚锡离子被三价铁还原。硫虽然以硫酸盐形式加入玻璃中作为澄清剂，且以6+、4+和2+等多价态存在，但有效硫扩散系数比有效铁扩散系数低两个数量级；在高铁玻璃中，硫酸盐可提供的氧浓度比铁低一个数量级。同时，只有低铁高硫玻璃才会显著改变锡的渗透剖面。因此，Sn2+氧化的主要原因可归因于三价铁，这意味着锡氧化还原反应的氧活度可由三价铁浓度确定，并可据此评估锡离子的氧化还原反应速度。 | human_verified | 0.1.0 | dev | [
"float_tin_bath",
"heat_transfer_cfd",
"quality_defects"
] |
true | [
"when the glass reaches the mold wall a local rapid cooling occurs, resulting in a strong increment of viscosity, thus altering the shape evolution: zones with the higher temperature will undergo stronger stretching and thinning [25]. Thus, inclusion of the heat equation is mandatory and purely mechanical models ig... | true | openai_compatible | [
"10.1016/j.compstruc.2016.09.007#chunk-0021"
] | [
"10.1016/j.compstruc.2016.09.007"
] | [
"10.1016/j.compstruc.2016.09.007"
] | [
[
"Numerical model"
]
] | Why must the heat equation be included in glass bottle forming simulations instead of relying on purely mechanical models? | glass-eval-v0.1-q008 | concept_mechanism | 在玻璃瓶成形过程中，为什么必须把热方程纳入模型，而不能只用纯力学模型来模拟？ | 当玻璃到达模具壁时会发生局部快速冷却，导致黏度显著增大，从而改变形状演化；温度较高的区域会经历更强的拉伸和减薄。因此，包含热方程是强制性的，忽略传热的纯力学模型不适用于该问题的建模。热传导假设服从傅里叶定律，它把热流与温度和导热系数联系起来。在拉格朗日参考系中，热传递方程写为：ρ c DT/Dt = k ∇²T + q，其中c是比热，T是温度，k是导热系数，q是内部生成的热流。该拉格朗日框架中不存在对流项，因为热对流由随材料运动的拉格朗日网格自动实现。 | human_verified | 0.1.0 | dev | [
"forming_feeder",
"heat_transfer_cfd",
"quality_defects"
] |
true | [
"Difference in oxygen concentration between the inlet and outlet of the regenerator indicates the presence of air leakage into the regenerator. If there is no air leakage into the regenerator, low flue gas temperature indicates efficient performance of regenerator. During normal operation of a furnace, oxygen is se... | true | openai_compatible | [
"10.1016/j.apenergy.2011.05.028#chunk-0011"
] | [
"10.1016/j.apenergy.2011.05.028"
] | [
"10.1016/j.apenergy.2011.05.028"
] | [
[
"Results and discussion"
]
] | In glass furnace regenerator operation, why can low flue gas temperature alone not be taken as efficient operation, and what quantifiable effects does regenerator blockage have on performance? | glass-eval-v0.1-q009 | concept_mechanism | 在玻璃熔窑蓄热室运行中，为什么仅凭烟气温度低不能判定其运行高效？蓄热室堵塞会对性能产生哪些可量化的影响？ | 蓄热室进出口之间的氧气浓度差表明有空气漏入蓄热室。如果蓄热室没有空气泄漏，低烟气温度才表示蓄热室高效运行。在熔窑正常操作中，蓄热室出口处很少测量氧气，因此由空气泄漏造成的低烟气温度常被误判为高效运行；通过测量蓄热室进出口的氧气和温度，可以获得真实的蓄热室性能。模型的基本输出显示，空气预热中回收的热量约为蓄热室总供热的48%，而空气预热热回收的目标性能约为54%。模型预测的蓄热室堵塞为：doghouse侧被堵塞的开口数为76 ± 12个，非doghouse侧为34 ± 12个；每侧设计有152个开口；doghouse侧与非doghouse侧的堵塞预测不确定度分别为15%和30%，源于测量误差。蓄热室通道中形成的堵塞会减少参与蓄热的表面... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"+ 1 + p i, π i, k, l, ∀ i ∈ m, ⋯, 1, k ∈ m i, ⋯, 1, j ∈ n ik, ⋯, 1 with C ̄ m + 1, π m + 1, i, k, j = C ̄ i, π i, k, n ik + 1 = 0\n\nSuppose that operation O i σ of a solution Π ik (belonging to job σ ) is removed from stage i and then inserted at a different location within the same stage. At this time, the calcu... | true | openai_compatible | [
"10.1016/j.cie.2023.109325#chunk-0018"
] | [
"10.1016/j.cie.2023.109325"
] | [
"10.1016/j.cie.2023.109325"
] | [
[
"Problem-specific heuristic"
]
] | In the distributed hybrid flow shop scheduling problem, when an operation is moved to a different position within the same stage, how are forward and backward calculations used to update completion times and determine the new makespan? | glass-eval-v0.1-q010 | concept_mechanism | 在分布式混合流水车间调度问题中，当某一阶段内移动一个操作到同一阶段的其他位置时，如何通过前向与后向计算来更新完工时间并确定新的最大完工时间？ | 对于分布式混合流水车间调度问题，当将一个属于某工件的操作从所在阶段移除并插入到该阶段内的另一个位置时，需要重新计算调度方案的完工时间。首先进行前向计算，利用递推公式得到移除操作后各工序的完成时间；随后进行后向计算，得到对应的后向完成时间。在此基础上，针对每个机器上的每个可插入位置，根据定理给出的计算公式评估插入该操作后的新最大完工时间。该公式取原最大完工时间与插入操作带来的局部最大完成时间中的较大值，其中局部最大完成时间包含该操作所在前一阶段对应工序的完成时间、该操作自身的加工时间，以及该操作所在阶段当前位置后续工序的后向完成时间与下一阶段对应工序后向完成时间中的较大值。最终，在全部候选位置中选择使新最大完工时间最小的位置进行插入，... | human_verified | 0.1.0 | test | [
"energy_waste_heat",
"manufacturing_planning",
"optimization_scheduling"
] |
true | [
"the Richardson number.\n\nThe Peclet number and the Reynolds number are still two similitude criteria and are respected in the same way as in the cold period. But, the dimensionless energy equation give rise to a new similitude criterion defined as (the refraction index is equal to unity, n = 1) (13) • The Planck ... | true | openai_compatible | [
"10.1016/j.applthermaleng.2004.12.012#chunk-0017"
] | [
"10.1016/j.applthermaleng.2004.12.012"
] | [
"10.1016/j.applthermaleng.2004.12.012"
] | [
[
"Theory"
]
] | In the dimensionless energy equation for heat-transfer simulations of a glass furnace regenerator, how is the Planck number defined, and how does the weighted-sum-of-grey-gases model calculate the total emissivity of the gas mixture? | glass-eval-v0.1-q011 | concept_mechanism | 在玻璃窑蓄热室传热模拟的无量纲能量方程中，普朗克数是如何定义的？加权和灰气体模型（WSGGM）又是如何计算混合气体的总发射率？ | 在玻璃窑炉蓄热室模拟中，无量纲能量方程引入了一个新的相似准则——普朗克数；当折射率取为1（n=1）时，它可写成 κλ/(n²σT³)，其中σ是Stefan-Boltzmann常数。由于模型中考虑了热导率随温度的变化，只有当吸收系数κ被正确计入时，该相似准则才能得到满足。对于气体辐射，模型采用加权和灰气体模型（WSGGM），该模型最早由Hottel和Sarofim提出，将全局发射率写成 ε = Σ_i a_i (1 - e^{-κ_i L})，其中 a_i 和 κ_i 分别指灰气体 i 的权重项和吸收率；权重项依赖于温度和吸收率，并且是温度和特征长度的函数。当存在H2O和CO2混合气体时，权重项满足 Σ_i a_i = 1。这些 a_... | human_verified | 0.1.0 | test | [
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"two-way interference effect D × H, D × S and S × V have a moderate significance while the interference effect of D × V is strong compared to experimental error. Considering now the uniformity parameter (U), the interference effect between D and H (D × H) is clearly significant while S × V has a moderate effect com... | true | openai_compatible | [
"10.1016/j.applthermaleng.2008.06.005#chunk-0010"
] | [
"10.1016/j.applthermaleng.2008.06.005"
] | [
"10.1016/j.applthermaleng.2008.06.005"
] | [
[
"Results"
]
] | In the numerical heat transfer simulation of annealing and tempering processes, how do interactions between control parameters affect the target functions? What is the mechanistic difference between synergistic and antisynergistic interactions, and how is the predictive model constructed and validated? | glass-eval-v0.1-q012 | concept_mechanism | 在退火与钢化过程的传热数值模拟中，控制参数之间的交互作用如何影响目标函数？协同与反协同交互在机理上有何区别，预测模型又是如何构建和验证的？ | 在退火与钢化过程的传热数值模拟中，控制参数之间的双向交互作用对目标函数（传热系数和均匀性参数）产生不同强度的影响。其中，距离与速度的交互对传热系数的影响较强，而距离与喷口间距、喷口间距与速度的交互影响为中等；对均匀性参数而言，距离与高度的交互作用显著，喷口间距与速度的交互影响为中等，其余交互作用则相对可忽略。从作用机理上看，交互作用可分为协同与反协同两种类型：距离与喷口间距、距离与速度对传热系数的影响均为单调协同，即一个参数效应的斜率不随另一参数水平的变化而改变方向；而距离与高度对均匀性参数的影响是反协同的，具体表现为参数效应曲线的斜率会随另一参数水平的变化而改变符号。为了建立参数预测模型，研究者定量评估了控制因子效应与第二个控制参... | human_repaired | 0.1.0 | test | [
"annealing_tempering",
"heat_transfer_cfd",
"optimization_scheduling"
] |
true | [
"= b ( T ) for the steady state and C ( T n + 1 ) T n + 1 = A ( T n ) T n + b ( ( T n + 1, T n ) for the transient behaviour where T is the vector of the mean temperatures in the cells, n is the index of the time step, b is the effect of the sources, it depends on the temperatures of boundaries: the walls and the b... | true | openai_compatible | [
"10.1016/j.conengprac.2008.04.005#chunk-0018"
] | [
"10.1016/j.conengprac.2008.04.005"
] | [
"10.1016/j.conengprac.2008.04.005"
] | [
[
"Simplified first-principles model of the combustion chamber",
"Coupling strategy, performances and validation of the model"
]
] | Why can the combustion chamber be assumed quasi-steady in transient simulations of a glass melting furnace? How are the steady-state and transient behaviors handled, and what are the solution method and computational performance? | glass-eval-v0.1-q013 | concept_mechanism | 在玻璃熔窑数值模拟中，燃烧室为何能采用准稳态假设？该模型如何处理稳态与瞬态行为，其求解方法和计算性能如何？ | 该模型以单元平均温度T为未知量，n为时间步索引；稳态方程写作 = b ( T )，瞬态方程写作 C ( T n + 1 ) T n + 1 = A ( T n ) T n + b ( ( T n + 1, T n )，其中b为源项效应，取决于炉壁和玻璃液等边界温度。这些隐式方程采用不动点法（fixed-point method）求解。由于燃烧特征时间比其他现象快得多，在瞬态模拟中燃烧室可假设为准稳态。模型的耦合算法计算速度很快：稳态时每个空间分解分区计算时间为一秒，几分钟即可得到网格几百个点的温度场预测，其空间分辨率比传感器更细；瞬态时模型要求每分区每秒10–5 s，达到数百倍实时速度。该模型已用TNO RCM模型以及Ford浮法窑... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"heat_transfer_cfd",
"melting_furnace",
"optimization_scheduling",
"process_control"
] |
true | [
"can form bubbles of a variety of sizes. Assume that the fraction of gas trapped in the liquid is α and the mass fraction of the gas in each size group is the same. Thus, the mass generation by the melting for each size group is αR m,CO2 /N where N is the total size group. The first source term of Eq. (10) becomes ... | true | openai_compatible | [
"10.1016/j.applthermaleng.2005.03.014#chunk-0019"
] | [
"10.1016/j.applthermaleng.2005.03.014"
] | [
"10.1016/j.applthermaleng.2005.03.014"
] | [
[
"Technical approach",
"Glass melt flow",
"Phenomenological models"
]
] | In a bubble-size-group model of a glass melter, how do batch melting, fining-agent gas generation, and gas dissolution act as sources or sinks of bubbles? What are the corresponding source-term expressions? | glass-eval-v0.1-q014 | concept_mechanism | 在玻璃熔窑气泡尺寸分组模型中，配合料熔化、澄清剂反应产气和气体溶解分别如何影响气泡的生成与消耗？这些过程的源项表达式是什么？ | 在气泡尺寸分组模型中，三项源项分别对应熔化产气、澄清剂产气和气泡气体溶解。
配合料熔化时，液相中截留气体的比例为α，假设各尺寸组内气体质量分数相同，则每个尺寸组因熔化产生的CO2质量源项为 S_batch = α R_m,CO2 / N，其中N为总尺寸组数，R_m,CO2为熔化产生的CO2质量速率。
澄清剂与玻璃组分反应生成气体，简化反应为 a1 glass1 + a2 fining → a3 glass2 + a4 gas；其反应速率和产气速率由经验速率式确定，分别为R_f和R_f,g。澄清气通过气泡表面积进入气泡，因此第k组获得澄清气的份额为 α_k = 4π r_k^2 n_k / Σ_{i=1}^N 4π r_i^2 n... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"heat_transfer_cfd",
"melting_furnace",
"quality_defects"
] |
true | [
"In spite of their difference in composition and preparation conditions, no spalling is observed in all AZ samples after 30 cycles of heating at 1100 °C and cooling to ambient temperature. Zircon (4.5×10−6) and zirconia (10.3×10−6) have low thermal expansion coefficients. This provides AZ samples with high resistiv... | true | openai_compatible | [
"10.1016/j.ceramint.2014.09.100#chunk-0008",
"10.1016/j.ceramint.2014.09.100#chunk-0006"
] | [
"10.1016/j.ceramint.2014.09.100",
"10.1016/j.ceramint.2014.09.100"
] | [
"10.1016/j.ceramint.2014.09.100",
"10.1016/j.ceramint.2014.09.100"
] | [
[
"Results and discussion"
],
[
"Results and discussion"
]
] | In AZ refractories, what are the key mechanisms governing sintering densification, thermal shock resistance, and resistance to molten soda glass attack? Please explain the mechanisms considering the roles of gelcasting, zircon content, and TiO2 addition. | glass-eval-v0.1-q015 | concept_mechanism | 在AZ耐火材料中，影响其烧结致密化、抗热震性和抗熔融钠玻璃侵蚀性的关键机理是什么？请结合凝胶浇注成型、锆英石含量以及TiO2添加剂的作用进行解释。 | AZ样品在1100°C加热至环境温度冷却的30次循环后均未发生剥落，原因是锆英石（4.5×10−6）和氧化锆（10.3×10−6）具有低热膨胀系数，这使AZ样品对伴随加热冷却的热应力和应变具有高抵抗力；莫来石（8.2×10−6）的形成及其含量增加也进一步增强了抗热震性。对于熔融钠玻璃的侵蚀，凝胶浇注样品表现出最高的抗蚀性，熔融玻璃对其结构的穿透程度最小，这归因于其结构的高度均匀性和致密性。相比之下，压制成型和熔铸（fuse-casted）样品的侵蚀程度明显更高，表现为样品表面形成空洞以及熔融玻璃更高程度的穿透，其较差的抗蚀性可能与烧成过程中形成的组织结构有关。在烧结致密化方面，凝胶浇注AZ样品的体积密度和抗压强度高于半干压样品，原因... | human_repaired | 0.1.0 | test | [
"electric_melting",
"melting_furnace",
"refractory_corrosion"
] |
true | [
"environmental impact and flat glass the highest. In the EU, the median values for coloured container, colourless container, flat and glass fibre are 360 kgCO2/t, 480 kgCO2/t, 500 kgCO2/t, and 440 kgCO2/t, respectively [42]. In the US, specific CO2 emissions are slightly higher, with values of 400 kgCO2/t for conta... | true | openai_compatible | [
"10.1016/j.ecmx.2024.100720#chunk-0020"
] | [
"10.1016/j.ecmx.2024.100720"
] | [
"10.1016/j.ecmx.2024.100720"
] | [
[
"Overview of glass manufacturing",
"Energy and carbon profile"
]
] | In glass manufacturing, what are the main emission sources by mechanism, what factors influence their relative importance, and how do using cullet and site location affect them? | glass-eval-v0.1-q016 | concept_mechanism | 在玻璃生产中，主要排放来源按机理可分为哪几类？它们的重要性受何种因素影响，采用碎玻璃和厂址选择又分别如何起作用？ | 玻璃制造中的排放按来源机理主要分为三类：原料中碳的氧化所产生的工艺排放、燃料燃烧产生的排放，以及电力使用带来的间接排放。这三类排放的相对重要性因产品而异，并与热能和电能的比能耗密切相关。总体而言，能源相关排放即燃料燃烧与间接电力排放，在所有玻璃类型中至少占四分之三，特种玻璃中几乎达到百分之九十五。使用碎玻璃替代原始原料可减少配合料中的碳酸盐数量，从而降低工艺排放。而间接能源排放的重要性则强烈依赖工厂所在位置。 | human_verified | 0.1.0 | test | [
"emissions_decarbonization",
"energy_waste_heat",
"sensing_monitoring"
] |
true | [
"uncertainty in the economic performance of the configurations, a TAC threshold of 300 €/tglass is selected from the CDFs for 2030, 2040 and 2050. Since the 2025 TAC for the base case (NGfur) was 237 €/tglass (cf. Section 3.2.3), a moderate increase over time makes 300 €/tglass a suitable benchmark for evaluating c... | true | openai_compatible | [
"10.1016/j.compchemeng.2025.109329#chunk-0035"
] | [
"10.1016/j.compchemeng.2025.109329"
] | [
"10.1016/j.compchemeng.2025.109329"
] | [
[
"Results and discussion",
"Uncertainty analysis",
"Probability of achieving a competitive TAC"
]
] | In the techno-economic comparison of glass furnace decarbonization pathways, why do natural gas-based furnace configurations have a high probability of keeping TAC below 300 €/tglass in 2030 but face significantly increased risks by 2040 and 2050, while electrified and carbon capture configurations change in competitiv... | glass-eval-v0.1-q017 | concept_mechanism | 在玻璃熔窑脱碳路径的技术经济比较中，为什么天然气基熔窑配置在2030年维持TAC低于300 €/tglass的概率较高，但到2040和2050年风险显著上升，而电气化与碳捕集配置的竞争力会随之变化？其中体现的成本风险机理是什么？ | 基于2030、2040和2050年TAC累积分布函数（CDFs），选取300 €/tglass作为TAC阈值；2025年基准NGfur的TAC为237 €/tglass。2030年，NGfur、NGOxyfur和Hybfur配置保持TAC低于300 €/tglass的概率很高（>90 %），表明天然气基方案在近期具有成本效益；而ELfur和H2fur配置的概率显著较低，反映其在中等碳价和能源价格下的经济劣势。到2040和2050年，随着碳价上升和能源市场不确定性增加，天然气基配置的概率急剧下降，风险变大；ELfur和H2fur则获得竞争力，在2050年达到更高概率。Hybfur虽然概率下降，但仍是稳定性最好的非CC选项，其下降幅度远... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"electric_melting",
"emissions_decarbonization",
"energy_waste_heat",
"melting_furnace",
"technoeconomic_lca"
] |
true | [
"the melt free surface and the streamlines of the glass melt that are calculated in each case guide the designer to select an optimum combination of above values.\n\nFor an existing furnace, on the other hand, the simulation can be used to modify its operating conditions in response to different situations. For exa... | true | openai_compatible | [
"10.1016/j.applthermaleng.2007.05.011#chunk-0017"
] | [
"10.1016/j.applthermaleng.2007.05.011"
] | [
"10.1016/j.applthermaleng.2007.05.011"
] | [
[
"Results and discussion",
"Optimization of glass furnace"
]
] | How does numerical simulation of a glass melting furnace support design through the computed melt free surface and streamlines, and how can it help operators respond when one burner port is plugged? How does the simulation also analyze heat consumption and lead to energy-saving improvements? | glass-eval-v0.1-q018 | concept_mechanism | 玻璃熔窑数值模拟如何通过计算熔体自由表面与流线来辅助设计，并在实际运行中帮助应对某个烧嘴堵塞的情况？它又是怎样剖析窑内热量消耗并据此提出节能改进措施的？ | 数值模拟中算出的熔体自由表面和玻璃液流线，可用于指导设计者从不同方案中选取最优的参数组合。对于已在运行的熔窑，模拟也能用于调整操作条件，例如当某个烧嘴堵塞时，操作人员可以据此改变其他烧嘴的流量或过量空气来适应新工况。此外，模拟还可以用来区分熔窑内不同热量消耗的比例：计算得到燃烧烟气、燃烧空间耐火材料和玻璃池窑耐火材料的平均温度后，将这些温度代入能量平衡方程，结果表明一部分总能量用于玻璃熔化，另一部分在蓄热室中被回收，其余能量则分别通过燃烧空间耐火材料、玻璃池窑耐火材料以及烟囱烟气散失。这些分析促使工厂管理层考虑提高热效率，提出的改进方向包括进一步预热助燃空气和原料、改善燃烧空间耐火材料的保温，以及采用多孔燃烧器。 | human_verified | 0.1.0 | test | [
"combustion_fuels",
"heat_transfer_cfd",
"melting_furnace",
"quality_defects"
] |
true | [
"Based on the steady-state condition, the thermal losses in different components were calculated and the results are shown in Table 4 . Out of a total thermal loss of 81.44 kW in the ESCCIM, heat lost in the crucible wall was 75.75 kW (93.01%) which was comprised of an I 2 R loss of 17.94 kW due to induction heatin... | true | openai_compatible | [
"10.1016/j.applthermaleng.2007.12.011#chunk-0010"
] | [
"10.1016/j.applthermaleng.2007.12.011"
] | [
"10.1016/j.applthermaleng.2007.12.011"
] | [
[
"Results and discussion",
"Thermal characteristics"
]
] | In the cold crucible induction glass melting system, what are the thermal loss distributions, melter efficiency, and overall efficiency under steady-state conditions, and why is the heat loss from the melter base very low? | glass-eval-v0.1-q019 | concept_mechanism | 在冷坩埚感应玻璃熔融系统中，稳态时的热损失分布、熔制效率和整体效率分别是多少？为什么熔制器底部的热损失很低？ | 在冷坩埚感应玻璃熔融系统（ESCCIM）中，基于稳态条件的热平衡计算显示，系统总热损失为81.44 kW，其中坩埚壁热损失为75.75 kW，占93.01%。该坩埚壁热损失由三部分组成：感应加热引起的I²R损失17.94 kW，玻璃表面辐射损失13.74 kW，以及通过玻璃熔体物理接触传热损失的剩余部分44.07 kW。当感应器输出功率为85.51 kW时，熔制器因金属坩埚的I²R损失和玻璃池热传导共损失67.7 kW，因此熔化效率为20.83%，其余输入功率可有效用于批料熔化。熔制器底部的热损失小于1%，原因是存在65 mm厚的固体玻璃，这提供了很高的热阻，从而在采用突出的水冷机械塞组件进行产品玻璃取出时提高了熔制器的热效率。基于... | human_verified | 0.1.0 | test | [
"electric_melting",
"energy_waste_heat",
"melting_furnace"
] |
true | [
"Q ˙ bg convective heat flow between batch and molten glass (kW) Q ˙ hlc heat loss through the combustion chamber walls (kW) Q ˙ hw heat loss through the tank walls (kW) Q ˙ gr radiation heat flow on the batch surface (kW) Q ˙ br radiation heat flow on the glass surface (kW)"
] | true | openai_compatible | [
"10.1016/j.applthermaleng.2012.11.018#chunk-0019"
] | [
"10.1016/j.applthermaleng.2012.11.018"
] | [
"10.1016/j.applthermaleng.2012.11.018"
] | [
[
"Untitled section 13",
"Nomenclature"
]
] | In the thermal model of a glass melting furnace, what heat flow rates are represented by the symbols Q̇bg, Q̇gr, and Q̇br respectively, and what is their unit? | glass-eval-v0.1-q020 | concept_mechanism | 在玻璃熔窑热模型中，符号 Q̇bg、Q̇gr 和 Q̇br 分别表示哪些热流量？它们的单位是什么？ | 在玻璃熔窑热模型中，Q̇bg 表示批料与熔融玻璃之间的对流热流（convective heat flow between batch and molten glass），单位是 kW。Q̇gr 表示批料表面的辐射热流（radiation heat flow on the batch surface），单位是 kW。Q̇br 表示玻璃表面的辐射热流（radiation heat flow on the glass surface），单位是 kW。 | human_verified | 0.1.0 | test | [
"combustion_fuels",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"period for the petroleum coke case is longer than that for the natural gas case at any certain pinch point.\n\nTo compare the two cases under the same pinch point, the pinch point of 20 °C will be used in the following discussion.\n\nIn the thermal analysis of the waste heat boiler, the surface radiation heat loss... | true | openai_compatible | [
"10.1016/j.applthermaleng.2013.10.038#chunk-0012"
] | [
"10.1016/j.applthermaleng.2013.10.038"
] | [
"10.1016/j.applthermaleng.2013.10.038"
] | [
[
"Waste heat power generation of a 1200 t/d flat glass furnace"
]
] | In the waste heat boiler for flat glass furnaces, what heat exchange equipment do the flue gas and the feed water/steam pass through respectively? In the natural gas case and the petroleum coke case, where do the main differences of the waste heat boiler lie? | glass-eval-v0.1-q021 | concept_mechanism | 在平板玻璃熔窑的余热锅炉中，烟气与给水/蒸汽各自经过哪些换热设备？天然气工况与石油焦工况下，余热锅炉的主要差异体现在哪里？ | 在平板玻璃熔窑的余热锅炉中，烟气首先进入过热器，将热量传递给蒸汽，随后依次通过蒸发器和省煤器，最后经过除氧器后离开锅炉。水侧流程为：冷水先进入除氧器被加热至饱和温度，再进入省煤器进一步升温，然后进入锅筒变成饱和水；部分饱和水经蒸发器吸热后形成汽水混合物并返回锅筒，从锅筒分离出的饱和蒸汽则进入过热器升温。天然气工况与石油焦工况的主要差异体现在省煤器和除氧器上，这两种工况下这两台换热设备的参数有所不同。 | human_verified | 0.1.0 | test | [
"combustion_fuels",
"emissions_decarbonization",
"energy_waste_heat",
"melting_furnace"
] |
true | [
"of these factors on TA are shown in Fig. 6. Due to the stronger magnetic flux density exists near the middle of coils along axial and crucible wall along radial respectively [18], stronger electromagnetic coupling would obtained when the starting material is placed at the middle of coils with larger diameter [24],... | true | openai_compatible | [
"10.1016/j.applthermaleng.2017.04.050#chunk-0009"
] | [
"10.1016/j.applthermaleng.2017.04.050"
] | [
"10.1016/j.applthermaleng.2017.04.050"
] | [
[
"Results and discussion",
"Glass melting by ISM under different start-up conditions"
]
] | In cold crucible induction melting of glass, how do the diameter and material of the starting material affect the establishment of the glass melt pool and its steady-state temperature through electromagnetic coupling? Please describe the mechanism. | glass-eval-v0.1-q022 | concept_mechanism | 在冷坩埚感应熔化玻璃过程中，起始材料的直径与材质如何通过电磁耦合影响玻璃熔池的建立和稳态温度？请阐述其机理。 | 在冷坩埚感应熔化玻璃时，起始材料的尺寸与材质通过电磁耦合影响熔池形成和稳态温度。由于磁通密度在轴向线圈中部和径向坩埚壁附近更强，将起始材料放置于线圈中部并采用较大直径，可使电磁耦合更强；但较大直径同时会因冷壁强烈冷却而使升温速率下降。熔化初期，直径较小且靠近坩埚中心的起始材料会让更多感应热先流向中心某点，使该点玻璃更早被加热；而较大直径的起始材料被放置在线圈中部附近，使相应区域在稳态时获得更高的玻璃温度。材质方面，石墨的电阻率高于TC4，因此由石墨传给玻璃的感应热通量更多，石墨起始材料能在同一时刻使玻璃达到更高温度并更早进入稳态，从而熔化出更高温度的玻璃。此外，起始材料直径相对较大时，达到稳态所需时间更短、稳态玻璃温度更高，因此采用... | human_verified | 0.1.0 | test | [
"electric_melting",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"bustion Q ̇ sh, CH 4 or 44.2 % of the power input P in. With 99.0 %, the majority of the melting heat is transferred through radiation while 1.0 % is transferred through convection. Nonetheless, the convection part must not be neglected, which has been the case in most of the other studies, as it introduces an unn... | true | openai_compatible | [
"10.1016/j.applthermaleng.2021.117166#chunk-0032"
] | [
"10.1016/j.applthermaleng.2021.117166"
] | [
"10.1016/j.applthermaleng.2021.117166"
] | [
[
"Results and discussion",
"Evaluating the Simulated Heat Transfer Rates"
]
] | In a glass melting furnace using oxy-fuel combustion with an actual cullet content of 77 %, through which modes is the melting heat mainly transferred and what are their respective proportions? Why is the energy utilization efficiency of this furnace relatively high (η ex = 40.5 %)? What is the quantitative effect of c... | glass-eval-v0.1-q023 | concept_mechanism | 在采用氧燃料燃烧、实际碎玻璃含量为77 %的玻璃熔窑中，熔化热主要通过哪些方式传递，各自所占比例是多少？该熔窑能量利用效率较高（η ex = 40.5 %）的原因是什么？碎玻璃含量对能量需求有何定量影响？ | 在采用氧燃料燃烧的玻璃熔窑中，燃烧热（CH4）占输入功率P in的44.2 %。熔化热中99.0 %通过辐射传递，1.0 %通过对流传递；对流部分虽然占比很小，但不可忽略，因为大多数其他研究中忽略对流会在数值过程中引入不必要且可避免的误差。该熔窑在实际碎玻璃含量为77 %时的能量利用效率η ex为40.5 %，相对较高，可归因于实际运行条件下的高碎玻璃含量和氧燃料燃烧的利用。每增加10 %的碎玻璃含量，能量需求下降2.5 % - 3 %。此外，在烟气损失方面，氧气燃烧室优于空气燃烧室。该熔窑在以标准化碎玻璃含量50 %进行比较时，表现低于Beerkens和van Limpt调查中的最节能容器玻璃端烧炉（带热回收），原因包括：耐火材料... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"electric_melting",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"Notice, however, that the RC-SLW method, as with all other full spectrum models [7,8], is mostly restricted to gray boundaries, even if some recent works have attempted to extend them to non-gray boundary conditions [9]. The assumption of gray walls will be made here. Gray wall emissivities used in the calculation... | true | openai_compatible | [
"10.1016/j.applthermaleng.2022.119020#chunk-0016"
] | [
"10.1016/j.applthermaleng.2022.119020"
] | [
"10.1016/j.applthermaleng.2022.119020"
] | [
[
"Introduction"
]
] | In three-dimensional flame radiation simulations of glass furnaces, what limitations do full-spectrum models such as RC-SLW have regarding boundary condition treatment, and how is the wall emissivity determined in the calculations? | glass-eval-v0.1-q024 | concept_mechanism | 在玻璃熔窑的三维火焰辐射模拟中，RC-SLW等全谱模型在边界条件处理上有什么限制？计算中壁面发射率是如何确定的？ | 该研究指出，RC-SLW方法与所有其他全谱模型一样，主要局限于灰边界（gray boundaries）条件，尽管近期有工作尝试将其扩展到非灰边界条件。因此，本文在此采用灰墙（gray walls）假设，计算中使用的灰墙发射率基于实验数据。本研究的主要创新在于超越通常用于比较气体辐射模型的一维和三维轴对称情形，在圣戈班（Saint-Gobain）实际工业炉构型中对火焰辐射方法进行公平比较；其参考解为LBL高分辨率计算，且三维构型是强非对称的端部入口玻璃熔窑几何。用于比较的输入热物理场（温度和气体组分浓度）来自Ansys Fluent模拟结果，这些模拟采用了近似气体辐射模型，并且不考虑烟灰（soot）。 | human_verified | 0.1.0 | test | [
"combustion_fuels",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"Unlike the melting factor, the melting index M I (-) represents a more meaningful quantity due to its dimensionless nature. Derived from the Sherwood number S h = f ( d p 2 / 3 , D − 1 / 3 , ( ∇ v ) 1 / 3 ) , this index describes the mass transfer from a SiO2-grain to the melt which is induced by convective transp... | true | openai_compatible | [
"10.1016/j.applthermaleng.2023.121022#chunk-0031"
] | [
"10.1016/j.applthermaleng.2023.121022"
] | [
"10.1016/j.applthermaleng.2023.121022"
] | [
[
"Theoretical basis",
"Glass quality",
"Melting and mixing behavior"
]
] | In numerical simulation of glass melting, what is the melting index? How is it calculated, and why is it also called the mixing index? | glass-eval-v0.1-q025 | concept_mechanism | 在玻璃熔窑熔化过程的数值模拟中，熔化指数（Melting Index）是什么？它如何计算？为什么该指数又被称为混合指数？ | 熔化指数（M I）是一个无量纲量，由舍伍德数推导而来，用于描述SiO2颗粒向熔体的质量传递，该传递由对流输运引起。该指数最终由速度梯度张量|∇v|、砂粒代表性直径d p以及扩散系数D SiO2计算，其中扩散系数取值为1 . 5 ⋅ 1 0 − 12 m 2 / s。熔化指数的定义式为M I = ∫ 0 t e n d 4 ⋅ | ∇ v | 2 / 3 ⋅ D SiO2 1 / 3 3 ⋅ d p 2 / 3 d τ。由于它强烈依赖速度梯度，因而在一定程度上表征对流混合，可作为玻璃均匀性的可比度量，因此又被称为混合指数。较高的M I表示由批料向熔体的相转变增强以及均匀性改善；若所有可能轨迹的M I ≫ 1，则表明所有砂粒大概率会在熔... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"electric_melting",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace",
"quality_defects"
] |
true | [
"fact that the coupled thermal-structural calculation did not consider the flow pattern of the air jet impact. In addition, the temperature of the air near the glass wall changes with time during the actual tempering process, which causes the thermophysical properties of the air to change as well. The above factors... | true | openai_compatible | [
"10.1016/j.applthermaleng.2023.122260#chunk-0026"
] | [
"10.1016/j.applthermaleng.2023.122260"
] | [
"10.1016/j.applthermaleng.2023.122260"
] | [
[
"Results and discussions",
"Stress analysis",
"Compared with the stress under uniform heat transfer coefficient boundary conditions"
]
] | Why do fluid-thermal-structural coupling and thermal-structural coupling differ in glass tempering simulations? What are the specific differences in heat transfer coefficient, temperature difference between glass interior and exterior, and residual stress? | glass-eval-v0.1-q026 | concept_mechanism | 在玻璃钢化模拟中，为什么流体-热-结构耦合与热-结构耦合会存在差异？这种差异在换热系数、玻璃内外温差和残余应力上有哪些具体表现？ | 热-结构耦合与流体-热-结构耦合产生偏差的原因主要有：耦合的热-结构计算没有考虑空气射流冲击的流动模式；实际钢化过程中玻璃壁附近的空气温度随时间变化，导致空气的热物理性质也随时间改变。这些因素使热-结构耦合计算得到的玻璃温度分布和应力分布与实际情况出现较大偏差。为量化两种方法的差异，研究者分析了玻璃表面驻点 O 及其内部对应点 O1 的温度和应力历史。结果显示，在两种模拟中，点 O 的换热系数 h 的最大偏差为 21.3 %。由于玻璃导热系数相对较低，表面换热系数 h 较高时，玻璃内外温差 ΔT 会更大。热-结构耦合模拟中，O 与 O1 之间的最大温差 ΔT 出现在 t = 8.7 s，达到 71.18 K；流体-热-结构耦合模拟中... | human_verified | 0.1.0 | test | [
"annealing_tempering",
"heat_transfer_cfd",
"quality_defects"
] |
true | [
"The results show that by expanding the oxyfuel combustion burner, the flame can reach 2–3 times the existing length, which facilitates the better melting of glass liquid and its batch materials for production needs. In addition, preheating the fuel gas with mixed flue gas can increase the overall flame combustion ... | true | openai_compatible | [
"10.1016/j.applthermaleng.2024.122384#chunk-0012"
] | [
"10.1016/j.applthermaleng.2024.122384"
] | [
"10.1016/j.applthermaleng.2024.122384"
] | [
[
"Summarize"
]
] | In an oxyfuel combustion glass melting furnace, how do expanding the burner, preheating the fuel gas with mixed flue gas, and expanding the exhaust gas outlets affect flame length, combustion temperature, and in-furnace flue gas recirculation, respectively? How do these changes improve the furnace thermal efficiency? | glass-eval-v0.1-q027 | concept_mechanism | 在全氧燃烧玻璃熔窑中，扩大燃烧器、用混合烟气预热燃气以及扩大排烟口分别会如何影响火焰长度、燃烧温度和炉内烟气循环？这些变化如何提升熔窑热效率？ | 数值模拟结果显示：通过扩大全氧燃烧烧嘴（oxyfuel combustion burner），火焰长度可达到现有长度的2–3倍，有利于玻璃液及其配合料的熔化。用混合烟气预热燃料气体，可使整体火焰燃烧温度和烟气温度在空间上提高约150 K。扩大两端排气口可有效改善纵向和横向再循环，有助于烟气充满炉膛、延长烟气在炉内停留时间、增强烟气对下方液面的传热速率，并降低出口烟气温度，从而大幅提高烟气余热利用，最终提升熔窑热效率。此外，全氧燃烧热系统的独特结构设计有助于利用烟气余热，用烟气预热燃料提高燃烧火焰温度，更适合满足玻璃熔化系统需求，并改善玻璃液的流动效果；采用图像模拟更直观地展示数值计算结果，对全氧燃烧在玻璃熔窑中的应用研究以及现有窑炉... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"Obtained result indicates that the deviation of the arc voltage for the hybrid plasma was larger than that for the multi-phase AC arc. This is derived from the following factors, which should have strong effect on the arc instability, (i) the additional gas flow from upper side of the arc increase in length of the... | true | openai_compatible | [
"10.1016/j.cap.2011.05.037#chunk-0008"
] | [
"10.1016/j.cap.2011.05.037"
] | [
"10.1016/j.cap.2011.05.037"
] | [
[
"Results and discussion",
"Stability analysis of multi-phase AC arc"
]
] | Why is the arc voltage deviation larger for the hybrid plasma compared with the multi-phase AC arc? How does shortening the upper electrode distance affect arc stability, and what is the role of electrode distance in processing capacity and stability? | glass-eval-v0.1-q028 | concept_mechanism | 混合等离子体（hybrid plasma）与普通多相交流电弧相比，电弧电压偏差为什么会更大？缩短上部电极间距如何影响电弧稳定性？电极距离对处理能力和稳定性又有什么作用？ | 混合等离子体的电弧电压偏差（deviation of the arc voltage）大于普通多相交流电弧，原因主要有两个：一是来自电弧上方的附加气体流增加了电弧长度，电弧电压和波动变大，导致电弧不稳定；二是火焰气体中的分子难以电离，也导致了电弧不稳定。为减小上方火焰气体流的影响，上部六个电极之间的距离（du）从100 mm缩短到80 mm，结果显示较短的du使电弧电压偏差降低，说明通过调整电极位置可以获得更均匀的电弧。电极距离对处理能力也很重要，因为它直接与等离子体的高温体积相关：电极距离越宽，高温体积越大，处理能力越大；但电极距离过长又会导致混合等离子体不稳定，因此需要在处理能力和高温源稳定性之间进行优化。 | human_verified | 0.1.0 | test | [
"electric_melting",
"melting_furnace"
] |
true | [
"-rate stream (direct way for structures 2 and 3 and in reverse way for structures 1 and 4). This stream passes through various CSTRs that fill a global volume of between 76 and 79 m3. Once more, this observation indicates that a ‘useless’ volume can be considered, with a very important relative size towards the gl... | true | openai_compatible | [
"10.1016/j.cep.2009.06.001#chunk-0023"
] | [
"10.1016/j.cep.2009.06.001"
] | [
"10.1016/j.cep.2009.06.001"
] | [
[
"Systemic approach implementation",
"Combustion chamber"
]
] | Why does a significant 'useless' volume appear in reactor network modeling of the flame space in a glass melting furnace? What treatments are used to confirm its existence and simplify the network, and how do the simplified response characteristics behave? | glass-eval-v0.1-q029 | concept_mechanism | 在玻璃熔窑火焰空间的反应器网络建模中，为什么会出现显著的“无用体积”？为了确认其存在并简化网络，通常采用哪些处理方式，简化后的响应特性如何？ | 在火焰发展流动的反应器网络模型中，存在一个相对总体积而言很大的无用体积。这一现象可从火焰流动的物理特性得到解释：火焰发展流动的主要能量传递方式为辐射，因此流动并不必然充满一个很大的空间体积，这使得无用体积的存在并不令人意外。为了确认该无用体积并简化网络，可以去除弱流率流股及其关联的混合反应器，并将该弱流率并入循环流股。尽管模拟的精度有所下降，但输出响应曲线仍能保持实验信号的主要特征，例如最小停留时间和斜率变化，从而验证了无用体积的真实存在。进一步地，还可以将体积相对很小的平推流反应器也去除，将其体积并入无用体积，并将相应流股的流量计入循环流股，所得响应曲线与先前几乎相同，说明该进一步简化是可行的。最后，以简化后的网络作为初始超级结构... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"heat_transfer_cfd",
"melting_furnace",
"optimization_scheduling"
] |
true | [
"the second-order upwind scheme to elevate accuracy. Gravity effects were accounted for, with gravitational acceleration set to 9.81 m/s2. The standard k-ε model was chosen for turbulence modeling. To ensure computational accuracy, the convergence residual criterion for the SO2 species transport equation was strict... | true | openai_compatible | [
"10.1016/j.cep.2025.110541#chunk-0016"
] | [
"10.1016/j.cep.2025.110541"
] | [
"10.1016/j.cep.2025.110541"
] | [
[
"Simulation and experimental methods"
]
] | In the float glass production line, what numerical schemes, physical models, and convergence control measures are adopted in the CFD simulation of SO2 species transport? Meanwhile, how are experimental samples collected to study the chemical structure of the dealkalized glass surface, and which surface analysis techniq... | glass-eval-v0.1-q030 | concept_mechanism | 在浮法玻璃生产线的锡槽环境中，对SO2组分输运进行数值模拟时，采用了哪些数值格式、物理模型和收敛控制措施？同时，为研究玻璃表面脱碱硫膜的化学结构，实验样品是如何采集的，并综合运用了哪些表面分析技术？ | 在对浮法玻璃生产线锡槽内SO2组分输运进行CFD模拟时，为提高计算精度采用了二阶迎风离散格式，并计及重力效应；湍流模拟选用标准k-ε模型，同时针对SO2组分输运方程设置了严格的收敛残差判据以确保计算准确。实验方面，样品取自浮法玻璃生产线上新鲜且未清洗的原始玻璃板，以保留玻璃表面的硫酸盐薄膜成分。表面化学结构信息通过ATR-FTIR光谱获取，采用硒化锌晶体作为内反射元件，并以相对于法线的一定入射角进行测量。采集得到的高分辨率光谱数据通过Python程序对特征吸收峰进行定量积分分析。进一步地，利用平行光照明勾画出脱碱玻璃表面的硫膜区域，并使用扫描电子显微镜和能量色散X射线光谱获取表面形貌及X射线谱，最终以平均元素含量作为表征结果。 | human_verified | 0.1.0 | test | [
"float_tin_bath",
"heat_transfer_cfd",
"optimization_scheduling",
"quality_defects"
] |
true | [
"Table 1: Batch raw-materials combination (in g) to yield 100 g glass each for the formulated glass compositions selected in the present study.\n| Raw Materials | SLBS-0 | SLBS-A1 | SLBS-A2 | SLBS-A3 | SLBS-B1 | SLBS-B2 | SLBS-B3 | SLBS-B4 | SLBS-B5 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n... | true | openai_compatible | [
"10.1016/j.ceramint.2021.09.203#chunk-0028"
] | [
"10.1016/j.ceramint.2021.09.203"
] | [
"10.1016/j.ceramint.2021.09.203"
] | [
[
"Materials and experimental procedures",
"Glass synthesis"
]
] | In the SLBS glass series formulations, from SLBS-0 to SLBS-B5, what are the added amounts (in g) of each raw material (Quartz, Soda ash, Feldspar, Limestone, Al2O3, MgO, Colemanite, BPH, TiO2) respectively? | glass-eval-v0.1-q031 | numeric_table | 在SLBS玻璃系列配方中，从SLBS-0到SLBS-B5，各原料（Quartz、Soda ash、Feldspar、Limestone、Al2O3、MgO、Colemanite、BPH、TiO2）的加入量分别是多少（单位g）？ | 由给出的玻璃配方组合数据可知，每个配方均以100 g玻璃为基准，各原料加入量单位均为g。Quartz从SLBS-0到SLBS-B5依次为71.36、65.57、59.78、56.07、51.61、47.15、42.69、38.23、33.77；Soda ash依次为22.95、22.91、22.87、22.85、19.28、15.72、12.16、8.59、5.03；Feldspar在所有配方中均为4.12；Limestone依次为18.88、12.22、4.79、0.03、0.02、0.02、0.01、0.01、0；Al2O3依次为0.77、0.75、0.74、0.73、0.73、0.72、0.72、0.72、0.72；MgO仅在... | human_verified | 0.1.0 | dev | [
"emissions_decarbonization",
"energy_waste_heat",
"melting_furnace",
"quality_defects"
] |
true | [
"Table 1: Physical and thermal properties of thermal insulators [30,31].\n| | Temperature [°C] | Insulator A | Insulator B |\n| --- | --- | --- | --- |\n| Specific mass (ρ) [kg m −3 ] | | 1300 | 2150 |\n| Specific Heat (C p ) [kJ kg −1 K −1 ] | | 680 | 800 |\n| Thermal conductivity (k) [W m −1 K −1 ] | 200 | | ... | true | openai_compatible | [
"10.1016/j.ceramint.2022.04.018#chunk-0016"
] | [
"10.1016/j.ceramint.2022.04.018"
] | [
"10.1016/j.ceramint.2022.04.018"
] | [
[
"Materials and methods",
"Materials and properties"
]
] | For the two thermal insulators, what are the density and specific heat of each, and what are the thermal conductivities of Insulator A at 500, 800, 1100 and 1400 °C and of Insulator B at 200 and 1000 °C? | glass-eval-v0.1-q032 | numeric_table | 对于所述两种隔热材料，它们的密度和比热容各是多少？隔热材料A在500°C、800°C、1100°C、1400°C下的导热系数分别是多少？隔热材料B在200°C和1000°C下的导热系数又是多少？ | 隔热材料A的密度为1300 kg m −3，比热容为680 kJ kg −1 K −1；隔热材料B的密度为2150 kg m −3，比热容为800 kJ kg −1 K −1。在200°C时，隔热材料B的导热系数为1 W m −1 K −1；在1000°C时，隔热材料B的导热系数为2 W m −1 K −1。隔热材料A在500°C和800°C时导热系数均为0.94 W m −1 K −1，在1100°C时为1.02 W m −1 K −1，在1400°C时为1.19 W m −1 K −1。 | human_verified | 0.1.0 | dev | [
"heat_transfer_cfd",
"melting_furnace",
"refractory_corrosion"
] |
true | [
"Table 3: XRF results of the glass sample composition converted to oxide values.\n| Composition | Electric | City gas | | | | Ammonia | | | | Composition | Electric | City gas | | | | Ammonia | | | |\n| | Cullet | Cullet | | | | Cullet | | | | | Batches | Batches | | | | Batches | | | |\n|... | true | openai_compatible | [
"10.1016/j.ceramint.2024.01.236#chunk-0024"
] | [
"10.1016/j.ceramint.2024.01.236"
] | [
"10.1016/j.ceramint.2024.01.236"
] | [
[
"Results and discussion",
"Glass composition and physical properties"
]
] | In the XRF oxide results, what are the values of Cr2O3, CuO, NiO, P2O5, Cl, and ZnO under the Electric Reference condition for the Cullet group, and what are the corresponding values under the Electric Reference condition for the Batches group? | glass-eval-v0.1-q033 | numeric_table | 在XRF氧化物结果中，Cullet组的Electric Reference条件下Cr2O3、CuO、NiO、P2O5、Cl、ZnO的数值各是多少？Batches组的Electric Reference条件下这些氧化物的数值又各是多少？ | Cullet组的Electric Reference条件下，Cr2O3为0.005，CuO为0.001，NiO为0.002，P2O5为0.009，Cl为0.000，ZnO为0.002。Batches组的Electric Reference条件下，Cr2O3为0.003，CuO为0.000，NiO为0.003，P2O5为0.011，Cl为0.022，ZnO为0.000。上述数值取自玻璃样品XRF结果换算为氧化物值的表格，其中Cullet组对应第一组Reference列，Batches组对应第二组Reference列。 | human_verified | 0.1.0 | dev | [
"combustion_fuels",
"emissions_decarbonization",
"melting_furnace",
"quality_defects"
] |
true | [
"Table 3: Validation of MPM. Unsteady simulation of single bubble rise and its terminal velocity for 7 different sets of parameters. Eo—Eotwos and Mo—Morton numbers are basic characteristics of the bubbles and allow for quick finding their location in the canonical bubble shape diagram, spanned over the co-ordinate... | true | openai_compatible | [
"10.1016/j.ces.2015.01.052#chunk-0036"
] | [
"10.1016/j.ces.2015.01.052"
] | [
"10.1016/j.ces.2015.01.052"
] | [
[
"Results and discussion",
"Results of MPM (multi-phase-model, complete solution)",
"Validation"
]
] | What are the Eo numbers, Mo numbers, bubble diameters, liquid viscosities, densities, surface tensions, and terminal velocities from experiments, Clift correlation, and MPM simulations for the seven sets of single bubble rise validation cases? Please list all values and units. | glass-eval-v0.1-q034 | numeric_table | 在MPM模型对单气泡上升的验证中，七组模拟条件各自对应的Eo数、Mo数、气泡直径、液体粘度、密度、表面张力，以及实验、Clift关联式和MPM模拟的终速度数值和单位是什么？请全部列出。 | 该验证数据包含7组不同Eo数和Mo数下的单气泡上升模拟结果。其中，第1至第6组的密度ρ均为1390 kg/m3，表面张力σ均为0.08 N/m；第7组的ρ=2288.4 kg/m3，σ=0.33 N/m。具体数值如下：第1组Eo=17.7，Mo=711，气泡直径d=0.0102 m，液体粘度μ=2.68 Pas，Re exp=0.232，实验终速度w0,exp=0.044 m/s，Clift关联式计算值w0,Clift=0.043 m/s，MPM模拟值w0,MPM=0.039 m/s。第2组Eo=243，Mo=266，d=0.0378 m，μ=2.1 Pas，Re exp=7.77，w0,exp=0.310 m/s，w0,Clift... | human_verified | 0.1.0 | dev | [
"heat_transfer_cfd",
"melting_furnace",
"quality_defects"
] |
true | [
"Table 2: Bubble chain data & calculated buoyancy forces f b,z for method 1) constant and 2) variable with an underlying gas input of V ˙ g , s t p = 100 Nl∕h.\n| | z ˜ [m] | d B [mm] | w B [m∕s] | D[mm] | f b,z [N∕m 3] | |\n| --- | --- | --- | --- | --- | --- | --- |\n| Method 1) | 0.6 | 39.8 | 0.517 | 40 | 4847... | true | openai_compatible | [
"10.1016/j.cherd.2022.07.044#chunk-0029"
] | [
"10.1016/j.cherd.2022.07.044"
] | [
"10.1016/j.cherd.2022.07.044"
] | [
[
"Results and discussion",
"Validation and calibration",
"Vertically variable source term"
]
] | At a gas input of 100 Nl∕h, for the constant buoyancy force method and the variable buoyancy force method, what are the bubble diameter d_B, rising velocity w_B, diameter D, and buoyancy force f_b,z at each height interval? | glass-eval-v0.1-q035 | numeric_table | 在气体输入量为 100 Nl∕h 时，采用恒定浮力法与变化浮力法计算气泡链参数，各高度区间的气泡直径 d_B、上升速度 w_B、直径 D 和浮力 f_b,z 分别是多少？ | 在气体输入量为 V ˙ g , s t p = 100 Nl∕h 的条件下，表格给出两种方法的气泡链计算数据。方法1（method 1) constant）在 z ˜ = 0.6 m 处：气泡直径 d_B = 39.8 mm，上升速度 w_B = 0.517 m∕s，直径 D = 40 mm，浮力 f_b,z = 4847.3 N∕m 3。方法2（method 2) variable）按高度区间给出：0 − 0.3 m 区间 d_B = 38.1 mm，w_B = 0.426 m∕s，D = 38 mm，f_b,z = 5753.0 N∕m 3；0.3 − 0.6 m 区间 d_B = 38.7 mm，w_B = 0.477 m∕s... | human_verified | 0.1.0 | dev | [
"heat_transfer_cfd",
"melting_furnace",
"quality_defects"
] |
true | [
"incorporates the spatial dependence of the heat input and geometric factors. In this way both gas burners and electrodes can be modeled as heat input. In this contribution only the first case is considered. For this case, the control input is related to the flow rate of the gas and thus to the valve opening. The s... | true | openai_compatible | [
"10.1016/j.conengprac.2011.09.004#chunk-0014"
] | [
"10.1016/j.conengprac.2011.09.004"
] | [
"10.1016/j.conengprac.2011.09.004"
] | [
[
"Modeling and identification"
]
] | In the identification of the glass feeder model, what is the assumed range for the average glass flow velocity, and what are the identified heat loss coefficient and the coefficients of the spatial characteristic polynomial for the third zone, including their units? | glass-eval-v0.1-q036 | numeric_table | 在玻璃供料道的模型辨识中，假设玻璃平均流速处于什么范围？第三区识别得到的热损失系数和空间特性多项式各项系数分别是多少，单位是什么？ | 在玻璃供料道的模型辨识中，假设玻璃的平均流速约为二至八毫米每秒，并据此假定为层流流动，同时认为玻璃在一个分区内的密度和黏度保持恒定。对第三区进行辨识时，采用二阶多项式表示空间特性，即空间特性等于常数项、一次项与二次项之和。辨识得到的热损失系数为八点七六乘以十的负四次方每秒；空间特性的常数项为三点一五乘以十的负四次方每秒，一次项系数为八点二三乘以十的负四次方米每秒，二次项系数为五点零零乘以十的负四次方平方米每秒。辨识模型与测量数据拟合良好，但验证中仍存在明显偏差，这些偏差可能来自燃气热值变化、环境温度影响等未建模扰动，也可能与被忽略的非线性和更强的激励有关。 | human_verified | 0.1.0 | test | [
"forming_feeder",
"process_control"
] |
true | [
"Table 1: Multiplicative factors of the parametric study.\n| Case | x fuel | x glass | notation |\n| --- | --- | --- | --- |\n| Case 1 (IC) | 1.0 | 1.0 | 1.0 ∣ 1.0 |\n| Case 2 | 0.9 | 1.0 | 0.9 ∣ 1.0 |\n| Case 3 | 1.1 | 1.0 | 1.1 ∣ 1.0 |\n| Case 4 | 1.0 | 0.9 | 1.0 ∣ 0.9 |\n| Case 5 | 1.0 | 1.1 | 1.0 ∣ 1.1 |"
] | true | openai_compatible | [
"10.1016/j.ecmx.2022.100252#chunk-0025"
] | [
"10.1016/j.ecmx.2022.100252"
] | [
"10.1016/j.ecmx.2022.100252"
] | [
[
"Numerical setup",
"Boundary conditions and parametric variation of fuel and batch mass flows"
]
] | In the parametric study, what are the fuel multiplication factor and glass multiplication factor for each of the five cases? | glass-eval-v0.1-q037 | numeric_table | 在玻璃熔窑参数研究中，五个案例的燃料乘法因子和玻璃乘法因子分别是什么？ | 该参数研究给出了五个案例的乘法因子：Case 1 (IC) 的燃料因子为1.0，玻璃因子为1.0，记作1.0∣1.0；Case 2 的燃料因子为0.9，玻璃因子为1.0，记作0.9∣1.0；Case 3 的燃料因子为1.1，玻璃因子为1.0，记作1.1∣1.0；Case 4 的燃料因子为1.0，玻璃因子为0.9，记作1.0∣0.9；Case 5 的燃料因子为1.0，玻璃因子为1.1，记作1.0∣1.1。其中x fuel代表燃料乘法因子，x glass代表玻璃乘法因子。 | human_verified | 0.1.0 | test | [
"combustion_fuels",
"electric_melting",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace",
"quality_defects"
] |
true | [
"Table 1: Raw data.\n| Set number | Comprehensive electricity consumption of unit flat glass output (MWh/thousand cases) | Comprehensive carbon emissions of unit flat glass production (kg/thousand cases) |\n| --- | --- | --- |\n| 1 | 3.875753038 | 1.583256293 |\n| 2 | 5.287862319 | 1.469746614 |\n| 3 | 6.157965661 ... | true | openai_compatible | [
"10.1016/j.egyr.2022.08.143#chunk-0013"
] | [
"10.1016/j.egyr.2022.08.143"
] | [
"10.1016/j.egyr.2022.08.143"
] | [
[
"Results and discussion"
]
] | In the given data, the comprehensive electricity consumption per unit flat glass output for set numbers 7, 10, and 133 are 0.5291733406, 2.940186076, and 3.8227242 MWh/thousand cases, respectively. What are the corresponding comprehensive carbon emissions per unit flat glass production for these sets? | glass-eval-v0.1-q038 | numeric_table | 在给出的平板玻璃生产数据中，第7组、第10组和第133组的单位平板玻璃产量综合电耗分别为0.5291733406、2.940186076和3.8227242 MWh/千箱，那么这三组对应的单位平板玻璃生产综合碳排放各为多少？ | 第7组的单位平板玻璃生产综合碳排放为1.397508072 kg/千箱，第10组的单位平板玻璃生产综合碳排放为2.184099077 kg/千箱，第133组的单位平板玻璃生产综合碳排放为1.732602918 kg/千箱。 | human_verified | 0.1.0 | test | [
"emissions_decarbonization",
"energy_waste_heat"
] |
true | [
"As the furnace is a multi-task machine, if it has 100 minutes to process an operation which only takes 10, it uses just 10% of its capacity, and the remaining 90% is available to operations of other jobs requiring this furnace. The pair of operations constitutes a block and the block is considered as a single item... | true | openai_compatible | [
"10.1016/j.ejor.2004.04.020#chunk-0013"
] | [
"10.1016/j.ejor.2004.04.020"
] | [
"10.1016/j.ejor.2004.04.020"
] | [
[
"The scheduling problem"
]
] | In the synchronization block of multi-task furnace scheduling, if an operation itself only needs 10 minutes but the furnace is allocated 100min of processing time, what is the furnace capacity utilization and how much capacity remains available for other jobs? Also, in the scheduling objective, how does the piecewise c... | glass-eval-v0.1-q039 | numeric_table | 在炉窑多任务调度的同步块中，如果一个操作本身只需要10分钟，但炉窑被分配了100min处理时间，那么该炉窑的容量利用率是多少？剩余多少容量可供其他作业使用？同时，调度目标中的分段成本函数c(f_i)如何根据完工时间f_i与交货期d_i、最早时间e_i、最晚时间l_i的位置关系取值？其中k1、k2、k3分别起到什么作用？ | 炉窑作为多任务机器，若一个操作只需10分钟却被分配100min处理时间，则其容量利用率仅为10%，其余90%容量仍可供给需要该炉窑的其他作业。在同步块中，一对操作构成一个块并作为单个排程项；有时同步会涉及2个以上操作，并包含装包前的固定等待时间，该等待时间即工件由传送带运输所需时间。同步还必须考虑各机器可能的不同班次；若某机器在给定时刻停止某操作，其他操作也须在相应时刻停止，例如吹瓶机的非工作时段（阴影区）会传递给块内其他机器，同时考虑块最后操作的等待时间。调度目标为最小化成品完工时间相关总成本，即MinΣ_i u_i c(f_i)。分段成本函数为：当f_i等于d_i时c(f_i)=0；当e_i≤f_i≤d_i时c(f_i)=k1(... | human_verified | 0.1.0 | test | [
"manufacturing_planning",
"optimization_scheduling"
] |
true | [
"| C(i) | Coating type of product i (1 if coated, 0 otherwise) |"
] | true | openai_compatible | [
"10.1016/j.ejor.2008.11.024#chunk-0023"
] | [
"10.1016/j.ejor.2008.11.024"
] | [
"10.1016/j.ejor.2008.11.024"
] | [
[
"Mathematical model"
]
] | In the symbol table of the float glass production scheduling optimization model, how is the parameter C(i), which represents the coating type of a product, defined and valued? Please provide its complete definition. | glass-eval-v0.1-q040 | numeric_table | 在浮法玻璃生产调度优化模型的符号表中，表示产品镀膜类型的参数C(i)是如何定义取值的？请给出其完整定义。 | 参数C(i)表示产品i的镀膜类型（coating type）。其定义中明确说明：如果产品为镀膜产品（coated），则取值为1；否则（otherwise）取值为0。因此C(i)是一个二元指示参数，取值为1或0。 | human_verified | 0.1.0 | test | [
"float_tin_bath",
"manufacturing_planning",
"optimization_scheduling"
] |
true | [
"Table 14: Detailed energy loss estimation for different streams\n| col1 | col2 | col3 | col4 |\n| --- | --- | --- | --- |\n| Furnace details | | | |\n| Furnace capacity | ton/day | 100 | |\n| Furnace draw | ton/day | 90 | |\n| Fuel used | | Natural gas | |\n| Type of glass | | Container glass | |\n| Type ... | true | openai_compatible | [
"10.1016/j.enconman.2007.04.013#chunk-0034"
] | [
"10.1016/j.enconman.2007.04.013"
] | [
"10.1016/j.enconman.2007.04.013"
] | [
[
"Furnace case study",
"Results",
"Achievable minimum energy consumption"
]
] | In an end-fired natural gas container glass furnace with a furnace capacity of 100 ton/day, a furnace draw of 90 ton/day, and a cullet percentage of 40% by weight in the batch, what are the fuel energy input, the energy from secondary preheated air, and the values (kJ/kg) and percentages of the various heat losses, inc... | glass-eval-v0.1-q041 | numeric_table | 一座使用天然气生产彩色容器玻璃的端烧式熔窑，熔窑能力为100 ton/day，实际出料量为90 ton/day，配合料中碎玻璃质量分数为40%。请给出该熔窑的燃料能量输入、二次预热空气能量，以及各主要热损失（包括熔化池侧墙、端墙、炉底、流液洞冷却、大碹、蓄热室、排烟等）的数值（kJ/kg）和百分比。 | 该端烧式天然气彩色容器玻璃熔窑的产能为100 ton/day，实际出料量为90 ton/day，碎玻璃质量占配合料的40%。燃料燃烧输入能量为3833 kJ/kg，对应百分比为100.0%；二次预热空气带入能量为1481 kJ/kg，对应百分比为38.6%。在热输出侧：熔化池侧墙热损失为87 kJ/kg，百分比为2.3%；熔化池端墙热损失为68 kJ/kg，百分比为1.8%；熔化池炉底热损失为36 kJ/kg，百分比为0.9%；流液洞冷却热损失为5 kJ/kg，百分比为0.1%；大碹热损失为74 kJ/kg，百分比为1.9%；侧墙上部结构热损失为25 kJ/kg，百分比为0.7%；端墙上部结构热损失为22 kJ/kg，百分比为0.6... | human_verified | 0.1.0 | test | [
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"Table 3: Natural gas composition.\n| Component name | Formula | % by volume |\n| --- | --- | --- |\n| Carbon dioxide | CO2 | 0.12 |\n| Nitrogen | N2 | 0.05 |\n| Methane | CH4 | 97.14 |\n| Ethane | C2H6 | 1.88 |\n| Propane | C3H8 | 0.52 |\n| Isobutene | C4H10 | 0.12 |\n| Butane | C4H10 | 0.06 |\n| Pentane | C5H12 |... | true | openai_compatible | [
"10.1016/j.energy.2016.11.077#chunk-0019"
] | [
"10.1016/j.energy.2016.11.077"
] | [
"10.1016/j.energy.2016.11.077"
] | [
[
"Experimental measurements"
]
] | In the natural gas composition table, what are the volume percentages of each component, especially methane and ethane? | glass-eval-v0.1-q042 | numeric_table | 天然气组成表中各组分的体积分数分别是多少？其中甲烷和乙烷各占多少？ | 天然气组成表中，各组分按体积分数计为：二氧化碳0.12%，氮气0.05%，甲烷97.14%，乙烷1.88%，丙烷0.52%，异丁烯（C4H10）0.12%，丁烷（C4H10）0.06%，戊烷（C5H12）0.06%，异戊烷（C5H12）0.01%，总计100.00%。其中甲烷占比最高，达到97.14%，乙烷为1.88%。 | human_verified | 0.1.0 | test | [
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"Table 4: Comparison of systems performance for the medium-size furnace.\n| | Symbol | Unit | Air Brayton-Joule cycle | Standard sCO2 cycle | sCO2+air PH cycle | ORC |\n| --- | --- | --- | --- | --- | --- | --- |\n| Net power output [kW] | P n e t | [kW] | 700 | 848.8 | 1184 | 832 |\n| Working fluid mass flow rate... | true | openai_compatible | [
"10.1016/j.energy.2018.11.089#chunk-0036"
] | [
"10.1016/j.energy.2018.11.089"
] | [
"10.1016/j.energy.2018.11.089"
] | [
[
"Results",
"Design optimization",
"Heat recovery systems for the medium-size furnace"
]
] | For the medium-size furnace system performance comparison, what are the net power output, working fluid mass flow rate, heat source temperature, thermal efficiency, heat recovery coefficient, heat recovery efficiency, and furnace plus HRS thermal efficiency for the Air Brayton-Joule cycle, the standard sCO2 cycle, the ... | glass-eval-v0.1-q043 | numeric_table | 在给出的中型熔炉系统性能对比中，空气布雷顿-焦耳循环、标准超临界二氧化碳循环、超临界二氧化碳加空气预热循环以及有机朗肯循环这四种方案，其净功率输出、工质质量流量、热源温度、热效率、余热回收系数、余热回收效率以及炉子加HRS热效率分别对应多少数值？ | 在介质尺寸熔炉的系统性能对比中，空气布雷顿-焦耳循环的净功率输出为700 kW，工质质量流量为13.461 kg/s，热源温度为641 °C，热效率为0.140，余热回收系数为0.768，余热回收效率为0.108，炉子加HRS热效率为0.377；标准超临界二氧化碳循环的净功率输出为848.8 kW，工质质量流量为15.473 kg/s，热源温度为470 °C，热效率为0.224，余热回收系数为0.926，余热回收效率为0.207，炉子加HRS热效率为0.381；超临界二氧化碳加空气预热循环的净功率输出为1184 kW，工质质量流量为12.978 kg/s，热源温度为648 °C，热效率为0.336，余热回收系数为0.522，余热回收... | human_verified | 0.1.0 | test | [
"energy_waste_heat",
"melting_furnace",
"technoeconomic_lca"
] |
true | [
"Table 5: Results of the algorithm runs\n| Experiment | Results | | | | | |\n| | f 1 | f 2 | f 3 | f 4 | f 5 | f 6 |\n| | (D B) | (D S) | (D C) | ( q ̇ G ) | (T 1) | (T 2) |\n| --- | --- | --- | --- | --- | --- | --- |\n| 1 | 2.9 | 22.4 | 24.3 | 97.7 | 1470 | 1465 |\n| 2 | 3.4 | 9.6 | 17.9 | 107.1 | 1470 | 1... | true | openai_compatible | [
"10.1016/j.engappai.2003.10.002#chunk-0020"
] | [
"10.1016/j.engappai.2003.10.002"
] | [
"10.1016/j.engappai.2003.10.002"
] | [
[
"Experimental results",
"Furnace performance optimisation",
"PMOS parameters"
]
] | In the glass melting furnace optimization and scheduling, how many experiments are included in the algorithm run results? What are the values of the six indicators (DB, DS, DC, heat release rate, T1, T2) for each experiment? Are there any experiments with identical results? | glass-eval-v0.1-q044 | numeric_table | 在玻璃熔窑熔化过程的优化与调度中，算法运行结果表格共包含多少个实验？每个实验的六个指标（DB、DS、DC、热释放率、T1、T2）的数值分别是多少？其中是否存在结果完全相同的实验？ | 该算法运行结果表格共列出了8个实验（编号1至8）。每个实验的六个指标值依次为：实验1：DB=2.9，DS=22.4，DC=24.3，q̇_G=97.7，T1=1470，T2=1465；实验2：DB=3.4，DS=9.6，DC=17.9，q̇_G=107.1，T1=1470，T2=1500；实验3：DB=4.0，DS=24.0，DC=11.9，q̇_G=114.1，T1=1420，T2=1500；实验4：DB=7.3，DS=17.1，DC=14.7，q̇_G=113.1，T1=1443，T2=1494；实验5：DB=9.2，DS=10.9，DC=17.5，q̇_G=108.0，T1=1458，T2=1494；实验6：DB=2.9，DS... | human_verified | 0.1.0 | test | [
"melting_furnace",
"optimization_scheduling",
"process_control"
] |
true | [
"Table 14: Detailed information of the case.\n| Φj | Kj | DDj | Φj | Kj | DDj | Φj | Kj | DDj | Φj | Kj | DDj |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| 300 | 1 | 86400 | 375 | 5 | 259200 | 450 | 3 | 432000 | 850 | 12 | 518400 |\n| 300 | 2 | 86400 | 500 | 18 | 259200 | 450 | 4 |... | true | openai_compatible | [
"10.1016/j.engappai.2024.108299#chunk-0064"
] | [
"10.1016/j.engappai.2024.108299"
] | [
"10.1016/j.engappai.2024.108299"
] | [
[
"Numerical experiments",
"A case study of real-world application"
]
] | In the detailed job parameter information for this case, for all records with job number Kj equal to 18, what are the corresponding Φj and DDj values? Please list them all. | glass-eval-v0.1-q045 | numeric_table | 在案例的作业参数明细中，作业编号Kj为18的所有记录分别对应什么Φj值和DDj值？请完整列出。 | 根据给出的表格数据，Kj为18的记录共有2条：第1条中Φj=500、DDj=259200；第2条中Φj=1100、DDj=518400。注意表格原文只给出DDj数值，未给出单位。 | human_verified | 0.1.0 | test | [
"manufacturing_planning",
"optimization_scheduling"
] |
true | [
"Table 1: Chemical composition.\n| Oxide | % Weight |\n| --- | --- |\n| Al2O3 | 43 |\n| SiO2 | 20 |\n| ZrO2 | 37 |"
] | true | openai_compatible | [
"10.1016/j.engfailanal.2014.09.003#chunk-0008"
] | [
"10.1016/j.engfailanal.2014.09.003"
] | [
"10.1016/j.engfailanal.2014.09.003"
] | [
[
"Results and discussion",
"New refractory"
]
] | What are the weight percentages of Al2O3, SiO2, and ZrO2 in the chemical composition of this refractory material? | glass-eval-v0.1-q046 | numeric_table | 该耐火材料的化学组成中，Al2O3、SiO2和ZrO2的重量百分比分别是多少？ | 该耐火材料的化学组成以重量百分比计，Al2O3为43%，SiO2为20%，ZrO2为37%。 | human_verified | 0.1.0 | test | [
"melting_furnace",
"refractory_corrosion"
] |
true | [
"Table 3: Elemental analysis of section in the centre of large fragment of the molybdenum insert on the side with refractory coating shown in Fig. 12c. All elements included (normalized).\n| Spectrum | Content of elements, weight % | | | | | | | | | | | |\n| | O | Na | Mg | Al | Si | K | Ca | Fe | Ni | ... | true | openai_compatible | [
"10.1016/j.engfailanal.2018.08.012#chunk-0017"
] | [
"10.1016/j.engfailanal.2018.08.012"
] | [
"10.1016/j.engfailanal.2018.08.012"
] | [
[
"Results and discussion",
"SEM characterization of structure and chemical compound of the molybdenum insert"
]
] | In the elemental analysis of the section in the centre of the large fragment of the molybdenum insert on the side with refractory coating, what elements are present at the four spectrum measurement points and what are their weight percentages? What is the trend in molybdenum and oxygen contents? | glass-eval-v0.1-q047 | numeric_table | 在带有耐火涂层一侧的钼插入件大碎片中心截面的元素分析中，四个能谱测量点各自包含哪些元素，各元素的重量百分比（weight %）是多少？其中钼和氧的含量变化有何规律？ | 该截面元素分析采用归一化处理，结果以重量百分比（weight %）表示。四个光谱点的具体数据如下：光谱点1：O 46.66、Na 10.25、Mg 0.49、Al 7.14、Si 26.16、K 0.76、Ca 2.95、Fe 0.22、Ni（空白）、Zr 4.44、Mo 0.92，总和100.00；光谱点2：O 20.21、Na 1.82、Mg（空白）、Al 0.06、Si 0.25、K 0.15、Ca 0.16、Fe 4.77、Ni 2.41、Zr（空白）、Mo 70.16，总和100.00；光谱点3：O 13.19、Na 2.57、Mg（空白）、Al（空白）、Si 0.14、K（空白）、Ca 0.13、Fe 0.66、Ni 0... | human_verified | 0.1.0 | test | [
"melting_furnace",
"refractory_corrosion"
] |
true | [
"Table 3: Overall final energy consumption of the European glass industry (2007).\n| | Total a | CG | FG | DG | SG | FF | GW | FS |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| EU25 | | | | | | | | |\n| Fuel consumption (PJ) | 284.4 | 133.8 | 84.1 | 23.2 | 11.8 | 11.0 | 9.5 | 9.5 |\n| Data c... | true | openai_compatible | [
"10.1016/j.enpol.2010.09.022#chunk-0031"
] | [
"10.1016/j.enpol.2010.09.022"
] | [
"10.1016/j.enpol.2010.09.022"
] | [
[
"Overall CO2 emissions and energy consumption of the European glass industry",
"Direct CO2 emissions and fuel consumption"
]
] | In the 2007 overall final energy consumption statistics for the European glass industry, what are the total fuel consumption and total final energy consumption for EU27? Among the EU27 glass types, which one has the highest fuel consumption, and what is its value and unit? | glass-eval-v0.1-q048 | numeric_table | 在2007年欧洲玻璃行业整体最终能源消耗统计中，欧盟27国（EU27）的燃料消耗总量和最终能源消耗总量分别是多少？EU27各玻璃类型中燃料消耗最高的是哪一种，其具体数值和单位是什么？ | 在2007年欧洲玻璃行业整体最终能源消耗统计中，EU27的燃料消耗总量为291.6 PJ，总最终能源消耗为352.0 PJ。分类型来看，EU27中燃料消耗最高的玻璃类型为CG，其燃料消耗为136.0 PJ。 | human_verified | 0.1.0 | test | [
"combustion_fuels",
"emissions_decarbonization",
"energy_waste_heat"
] |
true | [
"Table E: Energy balance of the oxygen-assisted fiberglass furnace.\n| Material input | | | | | Material output | | | | |\n| Number | Symbol | Item | Amount (kJ/kg) | Percentage (%) | Number | Symbol | Item | Amount (kJ/kg) | Percentage (%) |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n|... | true | openai_compatible | [
"10.1016/j.fuel.2023.128484#chunk-0032"
] | [
"10.1016/j.fuel.2023.128484"
] | [
"10.1016/j.fuel.2023.128484"
] | [
[
"Appendix"
]
] | In the energy balance of the oxygen-assisted fiberglass furnace, the combustion heat of the fuel is 4549.28 kJ/kg; what are the values and percentages of the input and output heat items? | glass-eval-v0.1-q049 | numeric_table | 在氧助燃玻纤熔窑的能量平衡中，燃料燃烧热为4549.28 kJ/kg，那么输入侧和输出侧各项热量的数值与占比分别是多少？ | 输入侧：燃料燃烧热为4549.28 kJ/kg，占比98.17%；燃料显热为4.06 kJ/kg，占比0.09%；助燃气体显热为7.61 kJ/kg，占比0.16%；配合料显热为22.59 kJ/kg，占比0.49%；玻璃原料显热为20.94 kJ/kg，占比0.45%；化工原料显热为1.65 kJ/kg，占比0.04%；进入空气预热器的空气显热为50.30 kJ/kg，占比1.09%。输出侧：玻璃液显热为1577.61 kJ/kg，占比34.05%；玻璃液潜热为1488.53 kJ/kg，占比32.12%；硅酸盐形成反应热为758.66 kJ/kg，占比16.37%；玻璃形成耗热为341.47 kJ/kg，占比7.37%；配合料水... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"emissions_decarbonization",
"energy_waste_heat",
"melting_furnace"
] |
true | [
"Table 1: Burner power in ( kW ) as well as fuel and oxidizer flow rates in ( N m 3 / h ) and mean inlet velocities in ( m/s ) for burners B1–B6 in NG and H2 oxy-fuel operation.\n| | Position | Burner | NG oxy-fuel | | | | H2 oxy-fuel | | | |\n| | x / L | Power | V ̇ f u e l | V ̇ O2 | v f u e l | v O2 | V ... | true | openai_compatible | [
"10.1016/j.fuel.2024.133576#chunk-0031"
] | [
"10.1016/j.fuel.2024.133576"
] | [
"10.1016/j.fuel.2024.133576"
] | [
[
"Results and discussion",
"Local effects on flame characteristics",
"Burner operation parameters"
]
] | In natural gas and hydrogen oxy-fuel operation, what are the respective burner powers, fuel flow rates, oxidizer flow rates, and mean inlet velocities for the six burners? | glass-eval-v0.1-q050 | numeric_table | 在天然气和氢气纯氧燃烧工况下，六个燃烧器的各自功率、燃料流量、氧化剂流量以及燃料和氧化剂的平均入口速度分别是多少？ | 在天然气与氢气纯氧燃烧工况中，位于x/L为0.28、0.47、0.55、0.66、0.78和0.88的六个燃烧器的功率依次为568 kW、634 kW、735 kW、601 kW、396 kW和396 kW。天然气纯氧燃烧时，上述燃烧器的燃料流量依次为57.1 N m3/h、63.8 N m3/h、73.9 N m3/h、60.5 N m3/h、40.3 N m3/h和40.3 N m3/h，氧气流量依次为115.4 N m3/h、129.0 N m3/h、149.3 N m3/h、122.2 N m3/h、81.5 N m3/h和81.5 N m3/h，燃料平均入口速度依次为7.25 m/s、8.10 m/s、9.38 m/s、7... | human_verified | 0.1.0 | test | [
"combustion_fuels",
"emissions_decarbonization",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace"
] |
true | [
"Investigations of the influence of hydrogen on the flame characteristics of large-scale oxyfuel burners have not been extensively investigated in the literature. In this study, for the first time, it was possible to stabilize a natural gas oxyfuel flame with hydrogen admixture up to 100 vol% in a multi-module comb... | true | openai_compatible | [
"10.1016/j.fuel.2025.134397#chunk-0008"
] | [
"10.1016/j.fuel.2025.134397"
] | [
"10.1016/j.fuel.2025.134397"
] | [
[
"Introduction"
]
] | In a multi-module combustion chamber, what monitoring methods were used to study natural gas oxyfuel flames with hydrogen admixture up to 100 vol%, and what were the findings regarding the relationship between oxidizer quality and NOx emissions? | glass-eval-v0.1-q051 | method_control | 在大型多模块燃烧室中研究天然气富氧火焰掺混氢气至100 vol%时，采用了哪些监测手段？关于氧化剂质量与NOx排放的关系有哪些发现？ | 该研究首次在多模块燃烧室中将天然气富氧火焰与氢气掺混至最高100 vol%并实现稳定燃烧。研究采用的关键监测手段是测量干废气中的NOx含量，并考察引入假空气（false air）对NOx值升高的影响。结果表明，氧化剂的质量显著影响NOx含量：即使氧化剂中仅含少量N2，也可使NOx含量加倍；该机制在氢气火焰中更为明显，因为氢气火焰可测得更高的火焰温度。 | human_verified | 0.1.0 | dev | [
"combustion_fuels",
"emissions_decarbonization",
"melting_furnace",
"sensing_monitoring"
] |
true | [
"(37) r = G x y − b = G x ( x + ε ) − b where r is the residual, a n d G x is the incidence matrix of measured variables. Using these residual values r and covariance matrix of measurement, the reliability of the dataset and the model is tested. The covariance matrix of residues Φ can be easily found by Eq. (38). (... | true | openai_compatible | [
"10.1016/j.heliyon.2025.e42624#chunk-0021",
"10.1016/j.heliyon.2025.e42624#chunk-0038"
] | [
"10.1016/j.heliyon.2025.e42624",
"10.1016/j.heliyon.2025.e42624"
] | [
"10.1016/j.heliyon.2025.e42624",
"10.1016/j.heliyon.2025.e42624"
] | [
[
"Material and methods"
],
[
"Tables"
]
] | In glass furnace combustion and melting process monitoring, how are the variable relationships in energy balance equations, redundancy checks, and statistical tests used to achieve data reconciliation and observability analysis? | glass-eval-v0.1-q052 | method_control | 在玻璃熔窑燃烧与熔化过程监测中，如何利用能量平衡方程中的变量关系、冗余校验与统计检验来实现数据协调和可观测性分析？ | 该研究在玻璃熔窑能量平衡建模与数据协调中，采用包含质量流量、比焓、标准生成焓、热、功、能量等物理量的模型函数，并以关联矩阵描述各流股与设备之间的拓扑连接。系统同时考虑测量变量、未测量变量以及经协调后的变量，借助残差、随机误差及其协方差矩阵进行冗余校验与可观测性分析，以判断哪些未测量变量可以被可靠估计。统计检验方面，运用标准正态检验准则、全局检验统计量、卡方值与置信区间来验证模型与测量的一致性；平方和误差则作为数据协调效果的量度。针对熔窑的燃烧与熔化过程，比能耗、能量效率以及由斯蒂芬-玻尔兹曼系数描述的辐射热传等指标，被用于分析燃烧空间、蓄热室空间和玻璃液池中的热量传递、热损失与余热回收。符号体系中对环境、烟气、冷热助燃空气、冷热烟气... | human_repaired | 0.1.0 | dev | [
"combustion_fuels",
"electric_melting",
"energy_waste_heat",
"melting_furnace",
"sensing_monitoring"
] |
true | [
"assigned to HSS machines.\n\nNext, we create a priority list for each construction algorithm. For WTT, the list is (4, 2, 3, 1, 6, 5, 7, 8, 9), and for WTS the list is (3, 4, 1, 2, 6, 5, 9, 8, 7). We then apply the construction algorithms to each list of orders. Fig. 14 illustrates the schedules after applying the... | true | openai_compatible | [
"10.1016/j.ijpe.2013.04.024#chunk-0019"
] | [
"10.1016/j.ijpe.2013.04.024"
] | [
"10.1016/j.ijpe.2013.04.024"
] | [
[
"Solution approach",
"An illustrative example"
]
] | In the scheduling optimization for glass manufacturing and furnace technology, what priority lists are used by the WTT and WTS construction algorithms respectively? What end effects do the schedules they generate produce? How are these effects eliminated through push-back, relocation, and order exchange during the loca... | glass-eval-v0.1-q053 | method_control | 在玻璃制造与炉窑技术的调度优化中，WTT和WTS构造算法分别使用怎样的优先级列表？它们生成的调度会产生什么末端效应？在局部改进阶段如何通过push-back、relocation和订单交换来消除这些效应？ | 对于WTT构造算法，优先级列表为(4, 2, 3, 1, 6, 5, 7, 8, 9)；对于WTS构造算法，优先级列表为(3, 4, 1, 2, 6, 5, 9, 8, 7)。将构造算法应用于每个订单列表后，生成的调度存在末端效应，导致显著的周期时间废料（cycle time scrap）。在局部改进的重定位阶段，对于WTS生成的调度，订单8因空余空间不足无法直接向后推，但被重新定位到第三台HSS机器上，然后与订单9一起被向后推。对于WTT生成的调度，订单8因空间不足（δ 2 > δ 3）无法向后推，但当订单8与订单7交换后，迭代push-back可以成功应用以消除末端效应。 | human_verified | 0.1.0 | dev | [
"finishing_cutting",
"float_tin_bath",
"manufacturing_planning",
"optimization_scheduling"
] |
true | [
"different mass flows the output temperature is not always the same. This is due to the range of acceptable temperatures mentioned in Section 3.2 which can result in different solutions for the same mass flow. As a consequence it is possible for a higher mass flow to have a lower input power. Nevertheless, by evalu... | true | openai_compatible | [
"10.1016/j.ijthermalsci.2016.08.015#chunk-0018"
] | [
"10.1016/j.ijthermalsci.2016.08.015"
] | [
"10.1016/j.ijthermalsci.2016.08.015"
] | [
[
"Results",
"Sensitivity studies",
"Mass flow"
]
] | In the study of a microwave heating system, how are numerical simulation and field distribution analysis used to examine the influence of mass flow rate on heating process quality and global efficiency, and what role do the temperature constraints in the control algorithm play? | glass-eval-v0.1-q054 | method_control | 在微波加热系统的研究中，怎样利用数值模拟和场分布分析来考察质量流量对加热过程质量及全局效率的影响，并说明控制算法中的温度约束所起的作用？ | 该研究通过对比用于加热和熔化材料的功率与输入功率的比值来评估加热过程质量，这一做法能够反映质量流量对加热效果的影响。研究发现，全局效率随质量流量增加而上升直至某个程度，其初始提升主要归因于停留时间缩短，使材料来不及向管壁和腔体传导过多热量，从而降低了自然对流和热辐射损失的比例。然而，微波效率本身随质量流量变化并无明显规律，因为微波效率取决于温度场，而温度场受材料速度、连续柱塞调整形成的电场分布以及由控制算法中温度约束所限定的波导功率共同作用。因此，在不借助数值模拟的情况下无法预测全局效率的趋势。通过分析不同流量下的温度分布、耗散场和电场分布，可以揭示各区域的高温区范围与损耗因子之间的关系。例如，最低流量时高温区几乎覆盖整个管子，耗散... | human_verified | 0.1.0 | dev | [
"electric_melting",
"energy_waste_heat",
"heat_transfer_cfd",
"melting_furnace",
"optimization_scheduling",
"process_control"
] |
true | [
"crack pattern, the 3 and 4 mm thick glass was semi-tempered. Generally speaking, the 3 mm thick glass was not easy to temper by air-cooled tempering method. Pure air-cooling gave only 9 fracturing counts [13]. However, the mist-cooled tempering method significantly increased the number of fragments to 27. It can b... | true | openai_compatible | [
"10.1016/j.ijthermalsci.2022.107475#chunk-0019"
] | [
"10.1016/j.ijthermalsci.2022.107475"
] | [
"10.1016/j.ijthermalsci.2022.107475"
] | [
[
"Results and discussion",
"Influence factors during the spray cooling of glass tempering",
"Effect of glass thickness"
]
] | For thin glass where air-cooled tempering struggles to produce enough fragments, what are the process-control characteristics of mist-cooled tempering, and why is it considered to improve thin-glass temperability and cooling efficiency? | glass-eval-v0.1-q055 | method_control | 针对厚度较薄的玻璃，风冷钢化难以获得足够碎片数，雾冷钢化方法在工艺控制上有哪些特点，为什么说它能提高薄玻璃钢化能力并提升冷却效率？ | 对于薄玻璃，单纯风冷钢化获得的碎片数量较低，而雾冷钢化显著增加了碎片数量，因此可以推测，只要找到合适的喷射条件，薄玻璃也能实现钢化。淬火时间被定义为玻璃从初始温度降至规定温度所需的时间。在给定喷射参数下，玻璃越厚，其内部所含能量越高，最大温差和淬火时间也越大，因而厚玻璃更容易建立温度梯度。相比之下，雾冷钢化在实际使用中达到相同淬火阶段的耗时明显短于风冷钢化生产中的耗时，说明雾冷钢化方法比风冷钢化方法具有更高的冷却效率。 | human_verified | 0.1.0 | test | [
"annealing_tempering",
"heat_transfer_cfd",
"quality_defects"
] |
true | [
"is shown in Fig. 14 (solid line). The response of T p ( t ) when the furnace system is controlled using the SDC-based SMC is shown in Fig. 15 (solid line). In both figures, the response of the controlled furnace system with the nominal values of α and β is plotted using the dotted lines. It can be seen from these ... | true | openai_compatible | [
"10.1016/j.isatra.2015.11.005#chunk-0023"
] | [
"10.1016/j.isatra.2015.11.005"
] | [
"10.1016/j.isatra.2015.11.005"
] | [
[
"Simulation results"
]
] | In the control of a tempered glass furnace's absolute temperatures, how do the two proposed sliding mode control schemes cope with uncertainties in warming rates and load step disturbances? Describe the control strategies and the simulation verification results. | glass-eval-v0.1-q056 | method_control | 在钢化玻璃炉的绝对温度控制中，所提出的两种滑模控制方案是如何应对升温速率不确定性和负载阶跃扰动的？请描述其控制策略与仿真验证结论。 | 针对钢化玻璃炉的温度控制，提出了两种滑模控制方案，其中一种为基于SDC的滑模控制。这两种方案均对炉壁和玻璃板升温速率的变化具有鲁棒性。为检验控制效果，在系统达到平衡后施加负载阶跃扰动，同时保留升温速率的不确定性。仿真结果表明，两种滑模控制方案都能迫使所有绝对温度收敛到共同的期望值，并且控制信号即输入电功率会自动调整其数值以补偿阶跃负载扰动。因此，两种控制方案对负载阶跃扰动以及升温速率不确定性均表现出鲁棒性。 | human_verified | 0.1.0 | test | [
"annealing_tempering",
"process_control"
] |
End of preview. Expand in Data Studio
Glass Manufacturing & Furnace Technology RAG Eval v0.1
玻璃制造与炉窑技术领域的中文检索与有据问答评测基准。语料为 111 篇玻璃制造、熔窑、浮法、钢化、能源、排放与过程控制方向的英文科研论文（结构化解析产物）；评测集为 100 道中文题（80 道可回答 + 20 道语料范围外），每题附英文 gold 证据块、gold 文档/章节标注与中文参考答案。
评测集构成
- 总量：100 题（开发集 25 / 测试集 75）
- 可回答题 80 道：概念/机理 30、数字/表格 20、方法与控制 15、技术比较 10、多文献综合 5
- 范围外题 20 道：用于检验检索拒答与幻觉抑制
- 证据：gold 证据块 ID 对齐到切块索引；gold 文档以规范化小写 DOI 标识
金标准质量（双人盲审，2026-08-20）
评测集经两名未参与构建的评审人双人独立盲审（随机乱序、隐藏生成来源）：
| 维度 | 一致率 | Cohen's Kappa |
|---|---|---|
| 题目质量 | 98.0% | —（多数类占 99%，Kappa 失真） |
| 证据充分性/范围外确认 | 97.0% | 0.830 |
| 参考答案正确性 | 95.0% | 0.908 |
- 20 道范围外题经双人确认 100% 确实超出语料；
- 人工判断与机器标签宽松一致率 96%~97%；
- 评审发现的 7 处实质问题全部按原文修复，完整过程见随附质检报告（
docs/质检报告_20260820.md）。
独立 LLM 裁判（Cursor Grok 4.6 / xAI，非 DeepSeek）
与人工同款 rubric（D1 题目质量 / D2 证据充分性或范围外确认 / D3 答案忠实度；详见 docs/data_card.md）：
| 维度 | 是 | 部分 | 否 | 无法判断 |
|---|---|---|---|---|
| D1（100） | 100 | 0 | 0 | 0 |
| D2（100） | 86 | 14 | 0 | 0 |
| D3（100） | 61 | 18 | 1 | 20 |
同版本对照（未整改 94 题）：D2 Kappa 0.501–0.544，D3 Kappa 0.778–0.796。范围外 20 题全部确认超语料。D3「否」仅 q068。
交叉检索器（切块与题目不变）
跨家族应把 E5/GTE 与无重排的 BGE 比，不要只和带 rerank 的 baseline 比。
| 系统 | Recall@5 | Recall@10 | MRR@10 | nDCG@10 | 表格题 Recall@10 |
|---|---|---|---|---|---|
| baseline（bge-m3 + BM25 + rerank） | 0.7812 | 0.8125 | 0.7431 | 0.7451 | 0.8000 |
| bge_norerank | 0.7125 | 0.7750 | 0.6061 | 0.6354 | 0.9000 |
| bm25 | 0.1625 | 0.1875 | 0.1353 | 0.1478 | 0.4000 |
| e5（multilingual-e5-large） | 0.6312 | 0.7250 | 0.4805 | 0.5354 | 0.9000 |
| gte（gte-multilingual-base） | 0.7063 | 0.7188 | 0.5404 | 0.5838 | 0.8500 |
金标没有只被 BGE-M3 找到。纯 BM25 Recall@10 = 0.1875，符合中文问、英文块。
题目–块泄漏（2026-08-21）
正式检索用中文题。英文题面相对 gold 的连续词重叠：可答题中位数 3.0 词；62/80 最长连续 ≤4 词；整题是 chunk 子串 0 道；中文汉字落入英文 gold 0。
| 集合 | rewrite | heavy（5–7 词术语串） | copy（≥8 连续词） |
|---|---|---|---|
| 全量 100 | 83 | 13 | 4 |
| 可回答 80 | 63 | 13 | 4 |
| 范围外 20 | 20 | 0 | 0 |
4 道英文对照题嵌了长条件从句或名词短语：q075 / q047 / q076 / q027。这不等于中文检索泄漏。
数据文件
| 文件 | 内容 |
|---|---|
eval/questions.jsonl |
100 道评测题（题目、gold 证据、参考答案、复核状态） |
docs/data_card.md |
数据说明（来源、处理、边界、Kappa、交叉检索、裁判 rubric、泄漏审计） |
docs/judge_rubric.md |
独立 LLM 裁判口径（与人工盲审同款 D1/D2/D3） |
docs/质检报告_20260820.md |
人工复核质检报告（Markdown） |
docs/质检报告_20260820.pdf |
人工复核质检报告（PDF） |
croissant.json |
Croissant 元数据 |
使用边界
- 适用于 RAG 检索/问答原型评测、证据定位与研究综述辅助；
- 不适用于工程设计审查、操作规程、标准合规判断或产线安全决策；
- 原始英文正文版权归原出版方所有，本发布不包含论文全文；正文重建需自行获取语料后使用构建器复现；
- 6 道
human_repaired题为评审后按原文修复，修复本身未经第二轮双人复验（详见质检报告第 3 节）； - 英文对照题 4 道含 ≥8 连续词（
q075/q047/q076/q027）；正式检索用中文题，汉字落入英文 gold 为 0。
引用
@dataset{glass_rag_eval_v01_2026,
title = {Glass Manufacturing \& Furnace Technology RAG Eval v0.1},
author = {SZHZX},
year = {2026},
note = {100-question Chinese retrieval and grounded-QA benchmark over 111 English scientific papers on glass manufacturing; gold standard verified by double-blind human review. License: CTIEC-BL-1.0}
}
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