Article
Mathematics, Applied
C. Luthi, M. Afrasiabi, M. Bambach
Summary: This work presents a spatially fully-adaptive smoothed particle hydrodynamics (SPH) scheme and applies it for simulating melt pool behavior in laser powder bed fusion (LPBF) additive manufacturing. By utilizing particle splitting and merging along with a novel sorting algorithm, the code achieves a 5x speed improvement in powder-based AM applications, enabling the simulation of multi-track LPBF processes within reasonable times without parallel computing.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2023)
Article
Materials Science, Coatings & Films
Hamed Jamshidi Aval
Summary: This article investigates the application of the SPH model to AA6061 aluminum coating by friction surfacing, showing that the SPH model accurately simulates the coating profile compared to the ALE model.
SURFACE & COATINGS TECHNOLOGY
(2021)
Article
Automation & Control Systems
My Ha Dao, Jing Lou
Summary: This paper presents a novel application of a three-dimensional smoothed particle hydrodynamics model to simulate directed energy deposition (DED) additive manufacturing processes. The simulation results are in good agreement with experimental data and reveal the internal characteristics of the melt-pool.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Manufacturing
Parand Akbari, Francis Ogoke, Ning-Yu Kao, Kazem Meidani, Chun-Yu Yeh, William Lee, Amir Barati Farimani
Summary: Characterizing melt pool shape and geometry is crucial in Metal Additive Manufacturing to control the printing process and prevent defects. Machine learning techniques can be applied to predict melt pool flaws based on process parameters. This study introduces a comprehensive framework for benchmarking machine learning for melt pool characterization. By collecting experimental data and developing models, melt pool control and process optimization can be improved.
ADDITIVE MANUFACTURING
(2022)
Article
Chemistry, Physical
N. Jeyaprakash, M. Saravana Kumar, Che-Hua Yang, Yanhai Cheng, N. Radhika, S. Sivasankaran
Summary: Laser Powder Bed Fusion (LPBF) based SS316L parts have a wide range of industrial applications due to their high strength and good structural integrity. Various analysis methods were used to study grain orientation and phase transformation, as well as to predict material properties through nano-mechanical and wear analysis.
JOURNAL OF ALLOYS AND COMPOUNDS
(2024)
Article
Thermodynamics
Mohamad Bayat, Venkata K. Nadimpalli, David B. Pedersen, Jesper H. Hattel
Summary: This study utilizes a multi-physics numerical model to investigate the effects of thermo-capillarity on the melt pool morphology and thermal fluid conditions during the Laser Powder Bed Fusion process. The results demonstrate that higher Marangoni numbers lead to decreased temperature gradients and more uniform temperature fields in the melt pool. Additionally, a novel methodology is introduced for calculating the melt pool's average Nusselt number, which can be used to simplify heat conduction simulations with effective liquid conductivity.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2021)
Article
Engineering, Manufacturing
Zhilang Zhang, Chang Shu, Muhammad Saif Ullah Khalid, Yangyang Liu, Zhenyu Yuan, Qinghua Jiang, Wei Liu
Summary: In this study, an improved SPH method was proposed, which successfully implemented three-dimensional particle modeling and study of the multi-layer multi-track cold spray problem. The simulation results closely matched the experimental results, and comprehensive analyses were conducted on the bonding behavior of different materials and the coating behavior of different layers and tracks.
JOURNAL OF MANUFACTURING PROCESSES
(2022)
Article
Nanoscience & Nanotechnology
Heng Lu, Yi He, Zhe Zhao, Chen Zhang, Yaowu Hu
Summary: A novel synchronous laser shock modulation of melt pool method was proposed to address the columnar crystal growth issue in additive manufacturing high entropy alloys. Experimental and numerical simulations were conducted to validate the effectiveness of this method.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2022)
Review
Engineering, Manufacturing
Chaolin Tan, Runsheng Li, Jinlong Su, Dafan Du, Yang Du, Bonnie Attard, Youxiang Chew, Haiou Zhang, Enrique J. Lavernia, Yves Fautrelle, Jie Teng, Anping Dong
Summary: This work provides an updated review of field-assisted additive manufacturing (FAAM) in metallic materials, including mainstream auxiliary magnetic, acoustic, mechanical, and thermal fields. The interaction mechanism between the fields and deposited metallic materials is elucidated, and the effects of these fields on various aspects of the manufacturing process are discussed in detail.
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
(2023)
Article
Optics
Robert Sampson, Robert Lancaster, Mark Sutcliffe, David Carswell, Carl Hauser, Josh Barras
Summary: Measuring melt pool width is critical in additive manufacturing for developing advanced control systems and defect detection algorithms. Parametric studies are crucial in identifying optimal settings, requiring in-depth process/material knowledge. Understanding parametric interaction and melt pool mechanics is essential for developing state of the art additive manufacturing components.
OPTICS AND LASER TECHNOLOGY
(2021)
Article
Materials Science, Multidisciplinary
Antonio Magana, Jonathan Yoshioka, Mohsen Eshraghi, Pareekshith Allu
Summary: In this study, a three-dimensional multiphysics computational fluid dynamics model was used to simulate the melt pool on a bare Inconel 625 substrate, accurately predicting its geometry, thermal behavior, and surface topology. The simulation results were in good agreement with experimental results and can be used to predict microstructure and material properties.
MATERIALS & DESIGN
(2022)
Article
Materials Science, Ceramics
Zhenhong Zhou, Shichun Li, Xiangdong Gao
Summary: This paper studies the heat absorption, transfer, and solidification of the melt pool in the laser additive manufacturing of Ni-Cr metal bonded diamond tools. The influence of diamond and Ni-Cr alloy powder parameters on laser energy absorptivity is analyzed and a temperature model of the powder bed is constructed. The impact of diamond arrangement and position on the temperature distribution and shape of the melt pool is explored. The study reveals the influence of diamond on the solidification and microstructure of the melt pool.
CERAMICS INTERNATIONAL
(2022)
Article
Computer Science, Interdisciplinary Applications
J. Michel, A. Vergnaud, G. Oger, C. Hermange, D. Le Touze
Summary: This paper examines the Particle Shifting Technique (PST) in SPH schemes, discussing its principles, conditions, and the shortcomings of existing PSTs. A new PST is proposed to address these limitations, and its effectiveness is validated in various SPH schemes and test cases.
JOURNAL OF COMPUTATIONAL PHYSICS
(2022)
Article
Thermodynamics
Y. Lin, C. Luthi, M. Afrasiabi, M. Bambach
Summary: Particle-based spatial discretization methods, such as smoothed particle hydrodynamics (SPH), are suitable for high-fidelity laser manufacturing simulations. Ray tracing (RT) is a realistic and accurate approach for heat source modeling in these simulations. However, implementing RT heat source modeling in particle-based numerical methods is challenging due to the lack of explicit surface representation and computational complexities. This work proposes an enhanced and efficient RT heat source model that overcomes these challenges and achieves negligible computational overhead and no need for surface mesh reconstruction. The computational performance of the RT model is demonstrated through validation against analytical and experimental results, showing a computing workload between 0.1% and 25% of the total runtime in different SPH-based laser manufacturing simulations. With its efficiency and robustness, the RT model enables precise simulations of processes like laser drilling and laser powder bed fusion beyond conventional volumetric heat sources.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2023)
Article
Engineering, Manufacturing
Wei Feng, Zhuangzhuang Mao, Yang Yang, Heng Ma, Kai Zhao, Chaoqi Qi, Ce Hao, Zhanwei Liu, Huimin Xie, Sheng Liu
Summary: This study proposed an online melt pool defect detection method and system for the laser engineered net shaping (LENS) printing process, based on temperature distribution similarity detection (TDSD), which enables synchronous monitoring and efficient defect identification during the printing process.
ADDITIVE MANUFACTURING
(2022)
Article
Chemistry, Physical
Nicholas T. Dee, Martin Schneider, Dmitri N. Zakharov, Piran R. Kidambi, A. John Hart
Summary: This study utilizes high-resolution, high-rate video capture of ETEM experimentation and automated image processing to quantitatively analyze particle formation and nucleation efficiency in CNT synthesis. The results show that pretreating the catalyst with carbon in a hydrogen atmosphere significantly improves particle density, CNT nucleation efficiency, and CNT density. Adding carbon during exposure to hydrogen is more effective than NH3 in increasing CNT nucleation efficiency, despite NH3 being a stronger reducing agent for iron. The insights from this study are important for improving CNT yield and productivity.
Article
Materials Science, Paper & Wood
Abhinav Rao, Thibaut Divoux, Crystal E. Owens, A. John Hart
Summary: This study presents the formulation and processing of crosslinked cellulose nanocrystal (CNC)-epoxy composites with a CNC fraction exceeding 50 wt%. The microstructure of the composites resembles the lamellar structure of nacre, combining bulk ductility with the brittle behavior of the aggregates at the nanoscale. The resulting composites exhibit high hardness and fracture toughness, making them suitable for various applications in the field of nanocomposites.
Article
Chemistry, Multidisciplinary
Cecile A. C. Chazot, Behzad Damirchi, Byeongdu Lee, Adri C. T. van Duin, A. John Hart
Summary: Molecularly organized nanocomposites of polymers and carbon nanotubes show great promise as high-performance materials. However, achieving controllable interaction between the polymer and carbon nanotubes remains a challenge. In this study, the researchers successfully coated carbon nanotubes with a conformal coating of meta-aramid, providing insights for future investigation of the mechanical properties of these composites and the application of in situ polymerization to other substrates.
Article
Statistics & Probability
Christoph Striegel, Jonas Biehler, Wolfgang A. Wall, Goeran Kauermann
Summary: This paper predicts the outcomes of high fidelity multivariate computer simulations using function-to-function regression with low fidelity counterparts. The compression of data and the use of a Gaussian Markov random field for model fitting are employed to handle the high dimensional but low sample size data. The proposed model enables real multivariate predictions on the complete grid.
Article
Computer Science, Interdisciplinary Applications
Rui Fang, Christoph P. Schmidt, Wolfgang A. Wall
Summary: In this article, a coupled finite element approach is presented for studying lithium plating and stripping in lithium-ion cells. The approach considers variables such as local film thickness and solves the resulting nonlinear equations using the Newton-Raphson method. A novel regularization technique is introduced to ensure stability and fast convergence. Numerical examples demonstrate the applicability and accuracy of the approach.
JOURNAL OF COMPUTATIONAL PHYSICS
(2022)
Article
Engineering, Multidisciplinary
Volker Gravemeier, Sevket Mert Civaner, Wolfgang A. Wall
Summary: A computational method for the coupled four-field problem of TFSI using finite elements is proposed in this study. The method utilizes residual-based variational multiscale formulations to ensure stable and accurate solutions. It is applied to various examples and proves to be robust and capable of simulating complex technical devices.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Jonas Nitzler, Jonas Biehler, Niklas Fehn, Phaedon-Stelios Koutsourelakis, Wolfgang A. Wall
Summary: This article presents a generalized formulation of a Bayesian multi-fidelity Monte-Carlo framework that addresses the challenges of high computational cost and high dimensionality in uncertainty quantification. By exploiting lower-fidelity model versions and learning the relationship between high-fidelity models and lower-fidelity models, the curse of dimensionality is circumvented. Despite the limitations of small data and inaccurate information from low-fidelity models, accurate and certifiable estimates for uncertainty quantification can be obtained with significantly fewer high-fidelity model runs.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Mechanical
Kaitlyn Gee, Suh In Kim, Haden Quinlan, A. John Hart
Summary: This study presents a framework to estimate the throughput and cost of additive manufacturing (AM). The framework takes into account process parameters, material thermodynamic properties, and machine specifications. The study also analyzes the tradeoff between production cost and machine capability, providing insights beyond the limits of current commercially available equipment.
RAPID PROTOTYPING JOURNAL
(2023)
Article
Engineering, Chemical
Mostafa Faraji, Alexander Seitz, Christoph Meier, Wolfgang A. Wall
Summary: This work presents a new model and numerical formulation for lubricated contact problems involving deformable 3D solid bodies and a fluid film. The model considers frictional contact tractions and hydrodynamic fluid tractions at each local point on the contact surface, and covers the entire range of lubrication. The finite element method is used for spatial discretization and several benchmark tests demonstrate the accuracy of the model.
Article
Biology
Silvia Hervas-Raluy, Barbara Wirthl, Pedro E. Guerrero, Gil Robalo Rei, Jonas Nitzler, Esther Coronado, Jaime Font de Mora Sainz, Bernhard A. Schrefler, Maria Jose Gomez-Benito, Jose Manuel Garcia-Aznar, Wolfgang A. Wall
Summary: In order to understand the growth of solid tumors, it is crucial to link knowledge of cancer biology with the physical properties of the tumor and its interaction with the surrounding microenvironment. Computational physics-based models were developed to incorporate these interactions using porous media theory. However, experimental validation of these models is challenging for clinical use. This study combines a physics-based model with in vitro experiments using microfluidic devices to mimic a three-dimensional tumor microenvironment, validating the proposed workflow.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Mechanics
Maximilian J. Grill, Wolfgang A. Wall, Christoph Meier
Summary: The study focuses on accurate analytical descriptions of adhesive and repulsive forces in complex fibrous systems. The research presents three different analytical solutions for disk-cylinder interaction potential laws, considering arbitrary mutual orientations and small surface separations. The derived potential laws show correct asymptotic scaling behavior and provide a theoretical prediction for the angle dependence.
INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES
(2023)
Article
Electrochemistry
Stephan Sinzig, Thomas Hollweck, Christoph P. Schmidt, Wolfgang A. Wall
Summary: All-solid-state batteries are promising candidates to replace conventional batteries with liquid electrolytes in many applications, but their feasibility is limited for certain applications. This study focuses on identifying physical effects inside all-solid-state batteries and their quantitative influence on battery performance. Simulation models are used to systematically study the effects and the influence of space-charge layers (SCLs) is heavily discussed. A new model is proposed to predict the spatial development of SCLs within realistic microstructures, enabling the quantification of the geometric influence on SCL formation. The SCLs in realistic microstructures differ significantly from those computed with simplified one-dimensional models.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2023)
Article
Chemistry, Physical
Christian Schneider, Christoph P. Schmidt, Anton Neumann, Moritz Clausnitzer, Marcel Sadowski, Sascha Harm, Christoph Meier, Timo Danner, Karsten Albe, Arnulf Latz, Wolfgang A. Wall, Bettina V. Lotsch
Summary: This study investigates the particle size dependent compression mechanics and ionic conductivity of thiophosphate solid electrolyte t-LiSiPS under pressure. It is found that stack and pelletizing pressure can effectively influence the microstructure and ionic conductivity of t-LiSiPS. The study emphasizes the importance of microstructure, particle size distribution, and pressure control in solid electrolytes.
ADVANCED ENERGY MATERIALS
(2023)
Article
Mechanics
Christoph Meier, Maximilian J. Grill, Wolfgang A. Wall
Summary: This paper proposes a universal framework for formulating generalized section-section interaction potentials (SSIP) in geometrically exact beam theory. By assuming undeformable cross-sections, an objective description of SSIPs is proposed using a minimal set of six relative coordinates. Work-pairing and a variational principle are used to identify work-conjugated interaction forces and moments. The proposed formulation allows for the modeling of interactions and constraints in fiber-based structures and materials.
INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES
(2023)
Meeting Abstract
Ophthalmology
Simon Salzmann, Christian Burri, Sami Al-Nawaiseh, Philip Wakili, Christoph Meier
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE
(2022)
Article
Engineering, Multidisciplinary
Akshay J. Thomas, Mateusz Jaszczuk, Eduardo Barocio, Gourab Ghosh, Ilias Bilionis, R. Byron Pipes
Summary: We propose a physics-guided transfer learning approach to predict the thermal conductivity of additively manufactured short-fiber reinforced polymers using micro-structural characteristics obtained from tensile tests. A Bayesian framework is developed to transfer the thermal conductivity properties across different extrusion deposition additive manufacturing systems. The experimental results demonstrate the effectiveness and reliability of our method in accounting for epistemic and aleatory uncertainties.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Zhen Zhang, Zongren Zou, Ellen Kuhl, George Em Karniadakis
Summary: In this study, deep learning and artificial intelligence were used to discover a mathematical model for the progression of Alzheimer's disease. By analyzing longitudinal tau positron emission tomography data, a reaction-diffusion type partial differential equation for tau protein misfolding and spreading was discovered. The results showed different misfolding models for Alzheimer's and healthy control groups, indicating faster misfolding in Alzheimer's group. The study provides a foundation for early diagnosis and treatment of Alzheimer's disease and other misfolding-protein based neurodegenerative disorders using image-based technologies.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jonghyuk Baek, Jiun-Shyan Chen
Summary: This paper introduces an improved neural network-enhanced reproducing kernel particle method for modeling the localization of brittle fractures. By adding a neural network approximation to the background reproducing kernel approximation, the method allows for the automatic location and insertion of discontinuities in the function space, enhancing the modeling effectiveness. The proposed method uses an energy-based loss function for optimization and regularizes the approximation results through constraints on the spatial gradient of the parametric coordinates, ensuring convergence.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Bodhinanda Chandra, Ryota Hashimoto, Shinnosuke Matsumi, Ken Kamrin, Kenichi Soga
Summary: This paper proposes new and robust stabilization strategies for accurately modeling incompressible fluid flow problems in the material point method (MPM). The proposed approach adopts a monolithic displacement-pressure formulation and integrates two stabilization strategies to ensure stability. The effectiveness of the proposed method is validated through benchmark cases and real-world scenarios involving violent free-surface fluid motion.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Chao Peng, Alessandro Tasora, Dario Fusai, Dario Mangoni
Summary: This article discusses the importance of the tangent stiffness matrix of constraints in multibody systems and provides a general formulation based on quaternion parametrization. The article also presents the analytical expression of the tangent stiffness matrix derived through linearization. Examples demonstrate the positive effect of this additional stiffness term on static and eigenvalue analyses.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Thibaut Vadcard, Fabrice Thouverez, Alain Batailly
Summary: This contribution presents a methodology for detecting isolated branches of periodic solutions to nonlinear mechanical equations. The method combines harmonic balance method-based solving procedure with the Melnikov energy principle. It is able to predict the location of isolated branches of solutions near families of autonomous periodic solutions. The relevance and accuracy of this methodology are demonstrated through academic and industrial applications.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Weisheng Zhang, Yue Wang, Sung-Kie Youn, Xu Guo
Summary: This study proposes a sketch-guided topology optimization approach based on machine learning, which incorporates computer sketches as constraint functions to improve the efficiency of computer-aided structural design models and meet the design intention and requirements of designers.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Leilei Chen, Zhongwang Wang, Haojie Lian, Yujing Ma, Zhuxuan Meng, Pei Li, Chensen Ding, Stephane P. A. Bordas
Summary: This paper presents a model order reduction method for electromagnetic boundary element analysis and extends it to computer-aided design integrated shape optimization of multi-frequency electromagnetic scattering problems. The proposed method utilizes a series expansion technique and the second-order Arnoldi procedure to reduce the order of original systems. It also employs the isogeometric boundary element method to ensure geometric exactness and avoid re-meshing during shape optimization. The Grey Wolf Optimization-Artificial Neural Network is used as a surrogate model for shape optimization, with radar cross section as the objective function.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
C. Pilloton, P. N. Sun, X. Zhang, A. Colagrossi
Summary: This paper investigates the smoothed particle hydrodynamics (SPH) simulations of violent sloshing flows and discusses the impact of volume conservation errors on the simulation results. Different techniques are used to directly measure the particles' volumes and stabilization terms are introduced to control the errors. Experimental comparisons demonstrate the effectiveness of the numerical techniques.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Ye Lu, Weidong Zhu
Summary: This work presents a novel global digital image correlation (DIC) method based on a convolution finite element (C-FE) approximation. The C-FE based DIC provides highly smooth and accurate displacement and strain results with the same element size as the usual finite element (FE) based DIC. The proposed method's formulation and implementation, as well as the controlling parameters, have been discussed in detail. The C-FE method outperformed the FE method in all tested examples, demonstrating its potential for highly smooth, accurate, and robust DIC analysis.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Mojtaba Ghasemi, Mohsen Zare, Amir Zahedi, Pavel Trojovsky, Laith Abualigah, Eva Trojovska
Summary: This paper introduces Lung performance-based optimization (LPO), a novel algorithm that draws inspiration from the efficient oxygen exchange in the lungs. Through experiments and comparisons with contemporary algorithms, LPO demonstrates its effectiveness in solving complex optimization problems and shows potential for a wide range of applications.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jingyu Hu, Yang Liu, Huixin Huang, Shutian Liu
Summary: In this study, a new topology optimization method is proposed for structures with embedded components, considering the tension/compression asymmetric interface stress constraint. The method optimizes the topology of the host structure and the layout of embedded components simultaneously, and a new interpolation model is developed to determine interface layers between the host structure and embedded components.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Qiang Liu, Wei Zhu, Xiyu Jia, Feng Ma, Jun Wen, Yixiong Wu, Kuangqi Chen, Zhenhai Zhang, Shuang Wang
Summary: In this study, a multiscale and nonlinear turbulence characteristic extraction model using a graph neural network was designed. This model can directly compute turbulence data without resorting to simplified formulas. Experimental results demonstrate that the model has high computational performance in turbulence calculation.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jacinto Ulloa, Geert Degrande, Jose E. Andrade, Stijn Francois
Summary: This paper presents a multi-temporal formulation for simulating elastoplastic solids under cyclic loading. The proper generalized decomposition (PGD) is leveraged to decompose the displacements into multiple time scales, separating the spatial and intra-cyclic dependence from the inter-cyclic variation, thereby reducing computational burden.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Utkarsh Utkarsh, Valentin Churavy, Yingbo Ma, Tim Besard, Prakitr Srisuma, Tim Gymnich, Adam R. Gerlach, Alan Edelman, George Barbastathis, Richard D. Braatz, Christopher Rackauckas
Summary: This article presents a high-performance vendor-agnostic method for massively parallel solving of ordinary and stochastic differential equations on GPUs. The method integrates with a popular differential equation solver library and achieves state-of-the-art performance compared to hand-optimized kernels.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)