scholarly journals Calibration Technique of Thermal Analysis Model for Metal Additive Manufacturing Process Simulation by Nonlinear Regression and Optimization

2021 ◽  
Vol 11 (24) ◽  
pp. 11647
Author(s):  
Eun Gyo Park ◽  
Jae Won Kang ◽  
Jin Yeon Cho ◽  
Jeong Ho Kim
Keyword(s):  
Thermal Analysis ◽  
Process Simulation ◽  
Reference Data ◽  
Analysis Model ◽  
Melt Pool ◽  
Manufactured Products ◽  
Optimal Values ◽  
Melt Pool Size ◽  
The Given ◽  
Metal Additive

A numerical analysis model that can accurately predict the physical characteristics of the actually additive manufactured products can significantly reduce time and costs for experimental builds and tests. Thermal analysis for the metal AM process simulation requires a lot of analysis parameters and conditions. However, their accuracy and reliability are not clear, and the current understanding of their influence on the analysis results is very insufficient. Therefore, in this study, the influence of uncertain analysis parameters on the thermal analysis results is estimated, and a procedure to calibrate these analysis parameters is proposed. By using the thermal analysis results for parameter cases determined by a design of experiments, a regression analysis model is constructed to estimate the sensitivity of the analysis parameters to the thermal analysis results. Additionally, it is used to determine the optimal values of analysis parameters that can produce the thermal analysis results closest to the given reference data from actual builds. By using the melt pool size computed from a numerical model as reference data, the proposed procedure is validated. From this result, it is confirmed that a high-fidelity thermal analysis model that can predict the characteristics of actual builds from minimal experimental builds can be constructed efficiently.

Effect of Time Spacing and Hatch Spacing on Thermal Material Properties and Melt Pool Geometry in Additive Manufacturing of S316L

2019 ◽  
Author(s):  
Elham Mirkoohi ◽  
Daniel E. Sievers ◽  
Steven Y. Liang
Keyword(s):  
Heat Transfer ◽  
Additive Manufacturing ◽  
Material Properties ◽  
Metal Additive Manufacturing ◽  
Melt Pool ◽  
Experimental Values ◽  
Melt Pool Size ◽  
Transfer Mechanisms ◽  
Hatch Spacing ◽  
Metal Additive

Abstract A physics-based analytical solution is proposed in order to investigate the effect of hatch spacing and time spacing (which is the time delay between two consecutive irradiations) on thermal material properties and melt pool geometry in metal additive manufacturing processes. A three-dimensional moving point heat source approach is used in order to predict the thermal behavior of the material in additive manufacturing process. The thermal material properties are considered to be temperature dependent since the existence of the steep temperature gradient has a substantial influence on the magnitude of the thermal conductivity and specific heat, and as a result, it has an influence on the heat transfer mechanisms. Moreover, the melting/solidification phase change is considered using the modified heat capacity since it has an influence on melt pool geometry. The proposed analytical model also considers the multi-layer aspect of metal additive manufacturing since the thermal interaction of the successive layers has an influence on heat transfer mechanisms. Temperature modeling in metal additive manufacturing is one of the most important predictions since the presence of the temperature gradient inside the build part affect the melt pool size and geometry, thermal stress, residual stress, and part distortion. In this paper, the effect of time spacing and hatch spacing on thermal material properties and melt pool geometry is investigated. Both factors are found statistically significant with regard to their influence on thermal material properties and melt pool geometry. The predicted melt pool size is compared to experimental values from independent reports. Good agreement is achieved between the proposed physics-based analytical model and experimental values.

Development of a Thermal Analysis Model for a Nuclear Spent Fuel Storage Cask and Experimental Verification With Prototype Testing

1989 ◽  
Vol 111 (4) ◽  
pp. 647-651 ◽  
Author(s):  
J. Y. Hwang ◽  
L. E. Efferding
Keyword(s):  
Thermal Analysis ◽  
Storage Period ◽  
Department Of Energy ◽  
Pressurized Water Reactor ◽  
Spent Fuel ◽  
Analysis Model ◽  
Pressurized Water ◽  
Fuel Assemblies ◽  
Spent Fuel Storage ◽  
Fuel Storage

A thermal analysis evaluation is presented of a nuclear spent fuel dry storage cask designed by the Westinghouse Nuclear Components Division. The cask is designed to provide passive cooling of 24 Pressurized Water Reactor (PWR) spent fuel assemblies for a storage period of at least 20 years at a nuclear utility site (Independent Spent Fuel Storage Installation). A comparison is presented between analytical predictions and experimental results for a demonstration cask built by Westinghouse and tested under a joint program with the Department of Energy and Virginia Power Company. Demonstration testing with nuclear spent fuel assemblies was performed on a cask configuration designed to store 24 intact spent fuel assemblies or canisters containing fuel consolidated from 48 assemblies.

A Physics-Informed Two-Level Machine Learning Model for Predicting Melt-Pool Size in Laser Powder Bed Fusion

2021 ◽  
Author(s):  
Yong Ren ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris
Keyword(s):  
Machine Learning ◽  
Initial Temperature ◽  
Pool Size ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Input Feature ◽  
Melt Pool Size ◽  
Melt Pool Characteristics

Abstract Laser powder bed fusion (L-PBF) additive manufacturing (AM) is one type of metal-based AM process that is capable of producing high-value complex components with a fine geometric resolution. As melt-pool characteristics such as melt-pool size and dimensions are highly correlated with porosity and defects in the fabricated parts, it is crucial to predict how process parameters would affect the melt-pool size and dimensions during the build process to ensure the build quality. This paper presents a two-level machine learning (ML) model to predict the melt-pool size during the scanning of a multi-track build. To account for the effect of thermal history on melt-pool size, a so-called (pre-scan) initial temperature is predicted at the lower-level of the modeling architecture, and then used as a physics-informed input feature at the upper-level for the prediction of melt-pool size. Simulated data sets generated from the Autodesk's Netfabb Simulation are used for model training and validation. Through numerical simulations, the proposed two-level ML model has demonstrated a high prediction performance and its prediction accuracy improves significantly compared to a naive one-level ML without using the initial temperature as an input feature.

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D Is Driving Speed, Scale, and Efficiency

2020 ◽  
Author(s):  
Brian T. Gibson ◽  
Paritosh Mhatre ◽  
Michael C. Borish ◽  
Justin L. West ◽  
Emma D. Betters ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Large Scale ◽  
Closed Loop ◽  
Size Control ◽  
Pool Size ◽  
Large Format ◽  
Layer Height ◽  
Melt Pool ◽  
The Impact ◽  
Melt Pool Size

Abstract This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

A deep neural network for classification of melt-pool images in metal additive manufacturing

2018 ◽  
Vol 31 (2) ◽  
pp. 375-386 ◽  
Author(s):  
Ohyung Kwon ◽  
Hyung Giun Kim ◽  
Min Ji Ham ◽  
Wonrae Kim ◽  
Gun-Hee Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Additive Manufacturing ◽  
Deep Neural Network ◽  
Metal Additive Manufacturing ◽  
Melt Pool ◽  
Metal Additive

scholarly journals THE STATIC OPTIMIZATION TASK OF OPTIMAL DESIGN OF NONLINEAR ELECTRONIC SCHEME

2019 ◽  
pp. 109-115
Author(s):  
Didmanidze Ibraim ◽  
Donadze Mikheil
Keyword(s):  
Optimal Design ◽  
Optimality Criteria ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Design Task ◽  
Optimization Task ◽  
Minimum Capacity ◽  
Optimal Values ◽  
The Given ◽  
Selection Of

The article deals with such an important selection of the elements of electronic scheme of the given configuration, when the certain requirements of technical task are satisfied and at the same time the selected optimality criteria reach the extreme value. The gives task has been solved by the method of one-criterion optimization, in particular, the method of center gravity. To formalize the given scheme we have compiled a mathematical model of optimization, which considers the requirements of technical task. The optimal design task of the presented electronic scheme was brought to the task of multi criteria optimization. The computational experiments have been resulted in the Pareto-optimal solutions, from which there was selected a compromise on that corresponds to the minimum capacity, required by the scheme. According to the optimal values of resistors, we have conducted a computerized analysis of the transient process of the given electronic scheme with the help of a computer program Electronics Workbench.

Behavior of thermal properties of AgCu1−xFexS compounds under non-isothermal conditions

2019 ◽  
Vol 33 (28) ◽  
pp. 1950339 ◽  
Author(s):  
Y. I. Aliyev ◽  
P. R. Khalilzade ◽  
Y. G. Asadov ◽  
T. M. Ilyasli ◽  
F. M. Mammadov ◽  
...  
Keyword(s):  
Phase Transition ◽  
Thermal Analysis ◽  
Differential Thermal Analysis ◽  
Thermal Properties ◽  
Phase Transitions ◽  
Structural Phase Transition ◽  
Structural Phase ◽  
Partial Replacement ◽  
Isothermal Conditions ◽  
The Given

AgCu[Formula: see text]Fe[Formula: see text]S compounds were synthesized by partial Cu[Formula: see text][Formula: see text][Formula: see text]Fe replacement in the AgCuS crystal at a concentration range of 0[Formula: see text][Formula: see text][Formula: see text]x[Formula: see text][Formula: see text][Formula: see text]0.03. In the differential thermal analysis spectrum obtained at a temperature range of 300 K[Formula: see text][Formula: see text][Formula: see text]T[Formula: see text][Formula: see text][Formula: see text]1300 K, endoeffect corresponding to the structural phase transition in the AgCuS compound was observed at the temperature T[Formula: see text]=[Formula: see text]938 K. It has been determined that this result is also observed in the AgCu[Formula: see text]Fe[Formula: see text]S compound obtained by partial replacement of Cu atoms by Fe atoms. However, in the compound of AgCu[Formula: see text]Fe[Formula: see text]S this effect was observed at higher temperatures. The thermal capacities and enthalpies of phase transitions were calculated for the given compounds.

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