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1,718 results on '"Chen, Jingyu"'

1. A Thermomechanical Hybrid Incompressible Material Point Method

Author

Kala, Victoria, Chen, Jingyu, Hyde, David, Stomakhin, Alexey, and Teran, Joseph

Subjects
Computer Science - Graphics, Physics - Fluid Dynamics
Abstract

We present a novel hybrid incompressible flow/material point method solver for simulating the combustion of flammable solids. Our approach utilizes a sparse grid representation of solid materials in the material point method portion of the solver and a hybrid Eulerian/FLIP solver for the incompressible portion. We utilize these components to simulate the motion of heated air and particulate matter as they interact with flammable solids, causing combustion-related damage. We include a novel particle sampling strategy to increase Eulerian flow accuracy near regions of high temperature. We also support control of the flame front propagation speed and the rate of solid combustion in an artistically directable manner. Solid combustion is modeled with temperature-dependent elastoplastic constitutive modeling. We demonstrate the efficacy of our method on various real-world three-dimensional problems, including a burning match, incense sticks, and a wood log in a fireplace.

Published
2024

4. Position-Based Nonlinear Gauss-Seidel for Quasistatic Hyperelasticity

Author

Chen, Yizhou, Han, Yushan, Chen, Jingyu, and Teran, Joseph

Subjects
Computer Science - Graphics
Abstract

Position based dynamics is a powerful technique for simulating a variety of materials. Its primary strength is its robustness when run with limited computational budget. We develop a novel approach to address problems with PBD for quasistatic hyperelastic materials. Even though PBD is based on the projection of static constraints, PBD is best suited for dynamic simulations. This is particularly relevant since the efficient creation of large data sets of plausible, but not necessarily accurate elastic equilibria is of increasing importance with the emergence of quasistatic neural networks. Furthermore, PBD projects one constraint at a time. We show that ignoring the effects of neighboring constraints limits its convergence and stability properties. Recent works have shown that PBD can be related to the Gauss-Seidel approximation of a Lagrange multiplier formulation of backward Euler time stepping, where each constraint is solved/projected independently of the others in an iterative fashion. We show that a position-based, rather than constraint-based nonlinear Gauss-Seidel approach solves these problems. Our approach retains the essential PBD feature of stable behavior with constrained computational budgets, but also allows for convergent behavior with expanded budgets. We demonstrate the efficacy of our method on a variety of representative hyperelastic problems and show that both successive over relaxation (SOR) and Chebyshev acceleration can be easily applied.

Published
2023

6. ZLN005 improves the protective effect of mitochondrial function on alveolar epithelial cell aging by upregulating PGC-1α.

Author

Kishaba, Tomoo, Tanino, Yoshinori, Sakairi, Yuichi, Chen, Jingyu, Dai, Jinghong, Cai, Hourong, Ma, Miao, Gao, Yujuan, Qiu, Xiaohua, Gui, Xianhua, Tian, Yaqiong, Tian, Mi, and Albertson, Timothy

Subjects
Idiopathic pulmonary fibrosis (IPF), alveolar epithelial cells (AECs), cellular senescence, mitochondrial function, peroxisome proliferator-activated receptor-γ coactivator-1 alpha (PGC-1α)
Abstract

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal pulmonary interstitial disease that usually occurs in the elderly. The senescence of alveolar epithelial cells (AECs) is an important mechanism of IPF. The AECs of patients with IPF have lower expression of peroxisome proliferator-activated receptor-γ coactivator-1 alpha (PGC-1α), which has been shown to play an important role in maintaining mitochondrial morphology and energy metabolism. This study sought to explore the mechanism by which ZLN005 improves mitochondrial function by upregulating PGC-1α to protect AECs from aging. METHODS: Western blot was used to detect the expression of PGC-1α, mitochondrial synthesis protein nuclear respiratory factor-1 (NRF-1), and p21WAF1 in the lung tissue of the IPF patients and the mice with bleomycin (BLM)-induced pulmonary fibrosis. A549 cells and mice AEC2 cells were treated with hydrogen peroxide (H2O2) to construct cell senescence models. Cell senescence was detected by senescence-associated beta-galactosidase staining. The mitochondrial respiratory function was measured, including the adenosine triphosphate (ATP) generation, reactive oxygen species (ROS) level, changes in cell membrane potential, and energy metabolism. Using lentivirus as a vector and using gene editing technology to over express (upPGC-1α) and knockdown PGC-1α (shPGC-1α) in the A549 cells. The PGC-1α agonist ZLN005 was used to pretreat the A549 and shPGC-1α A549 cells, and cell aging and mitochondrial respiratory function were observed. RESULTS: The Western blot and immunofluorescence assays showed that the expression of PGC-1α and NRF-1 was decreased in the lung tissues of the IPF patients and BLM-induced mice pulmonary fibrosis model, while the expression of p21WAF1 was increased. The results of the immunofluorescence and mitochondrial function experiments also indicated that the expression of PGC-1α and mitochondrial synthesis protein NRF-1 were decreased in the senescent cells. Further, the mitochondrial morphology was abnormal and the mitochondrial function was impaired. PGC-1α was involved in the AEC senescence by regulating mitochondrial morphology and function. Treatment with the agonist of PGC-1α (i.e., ZLN005) blocked the H2O2-induced cell senescence by enhancing the expression of PGC-1α. CONCLUSIONS: These results provide preliminary insights into the potential clinical application of ZLN005 as a novel therapeutic agent for the treatment of IPF.

Published
2023

9. Research on the Exchange of Chinese and Foreign Dances during the Republic of China

Author

Chen, Jingyu, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Rad, Dana, editor, Chew, Fong Peng, editor, Hutagalung, Fonny Dameaty, editor, and Birkök, Cüneyt, editor

Published
2024
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10. Learning Temporal Graph Representation via Memory-Aware Autoencoder

Author

Chen, Jingyu, He, Chengxin, Qu, Yuening, Yu, Zhenyang, Zhang, Yuanhao, Duan, Lei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Song, Xiangyu, editor, Feng, Ruyi, editor, Chen, Yunliang, editor, Li, Jianxin, editor, and Min, Geyong, editor

Published
2024
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13. PieTrack: An MOT solution based on synthetic data training and self-supervised domain adaptation

Author

Wang, Yirui, He, Shenghua, Tang, Youbao, Chen, Jingyu, Zhou, Honghao, Hong, Sanliang, Liang, Junjie, Huang, Yanxin, Zhang, Ning, Lin, Ruei-Sung, and Han, Mei

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In order to cope with the increasing demand for labeling data and privacy issues with human detection, synthetic data has been used as a substitute and showing promising results in human detection and tracking tasks. We participate in the 7th Workshop on Benchmarking Multi-Target Tracking (BMTT), themed on "How Far Can Synthetic Data Take us"? Our solution, PieTrack, is developed based on synthetic data without using any pre-trained weights. We propose a self-supervised domain adaptation method that enables mitigating the domain shift issue between the synthetic (e.g., MOTSynth) and real data (e.g., MOT17) without involving extra human labels. By leveraging the proposed multi-scale ensemble inference, we achieved a final HOTA score of 58.7 on the MOT17 testing set, ranked third place in the challenge., Comment: Third place solution for the MOTSynth-MOT-CVPR22 Challenge

Published
2022

14. UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View

Author

Qin, Zequn, Chen, Jingyu, Chen, Chao, Chen, Xiaozhi, and Li, Xi

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Bird's eye view (BEV) representation is a new perception formulation for autonomous driving, which is based on spatial fusion. Further, temporal fusion is also introduced in BEV representation and gains great success. In this work, we propose a new method that unifies both spatial and temporal fusion and merges them into a unified mathematical formulation. The unified fusion could not only provide a new perspective on BEV fusion but also brings new capabilities. With the proposed unified spatial-temporal fusion, our method could support long-range fusion, which is hard to achieve in conventional BEV methods. Moreover, the BEV fusion in our work is temporal-adaptive and the weights of temporal fusion are learnable. In contrast, conventional methods mainly use fixed and equal weights for temporal fusion. Besides, the proposed unified fusion could avoid information lost in conventional BEV fusion methods and make full use of features. Extensive experiments and ablation studies on the NuScenes dataset show the effectiveness of the proposed method and our method gains the state-of-the-art performance in the map segmentation task.

Published
2022

16. Yersinia enterocolitica

Author

Rakin, Alexander, primary, Garzetti, Debora, additional, Bouabe, Hicham, additional, Sprague, Lisa D., additional, and Chen, Jingyu, additional

Published
2024
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17. List of contributors

Author

Aizawa, Shin-Ichi, primary, Alberdi, Pilar, additional, Alexander, David C., additional, Alía, Alberto, additional, Allison, D.G., additional, Amyes, Sebastian G.B., additional, An, Haoran, additional, Andrade, María J., additional, Antelmann, Haike, additional, Arias, Cesar A., additional, Asensio, Miguel A., additional, Axell-House, Dierdre B., additional, Bae, Hee-Won, additional, Baena, Laura Muñoz, additional, Baig, Abdul Mannan, additional, Bailey, Spenser O., additional, Baize, Sylvain, additional, Baldi, Pablo C., additional, Barbosa, Angela Silva, additional, Barbuddhe, Sukhadeo B., additional, Bard, Emilie, additional, Barry, Eileen M., additional, Basarab, Gregory S., additional, Beloborodova, N.V, additional, Bermúdez, Elena, additional, Bidmos, Fadil A., additional, Bisgaard, Magne, additional, Blakely, Garry W., additional, Bloch, Evan, additional, Boesen, Thias Oberg, additional, Bose, Dipayan, additional, Botero, Javier Enrique, additional, Bouabe, Hicham, additional, Bouchard, Michael J., additional, Bozue, Joel A., additional, Bradbury, Richard S., additional, Brett Moreau, G., additional, Cabezas-Cruz, Alejandro, additional, Cai, Rong-Jun, additional, Calderón, Enrique J., additional, Cao, Boyang, additional, Carmena, David, additional, Carvalho, Eneas, additional, Caulfield, Amanda D., additional, Cen, Shan, additional, Chai, Jong-Yil, additional, Chamberland, Robin R., additional, Champredon, David, additional, Chan, Edward D., additional, Charbon, Godefroid, additional, Chato, Connor, additional, Chelomina, G.N., additional, Chen, Jingyu, additional, Chen, Min, additional, Chen, Shuyu, additional, Chen, Suilin, additional, Chen, Yanfei, additional, Chen, Zhaoyuan, additional, Cheng, Aimin, additional, Cheng, Keding, additional, Chiu, Charles Y., additional, Cho, You-Hee, additional, Christensen, Henrik, additional, Chrtdernevskaya, E.A., additional, Contreras, Adolfo, additional, Contreras, Marinela, additional, Córdoba, Juan J., additional, Córdoba, María G., additional, Costa, Rita, additional, Cote, Christopher K., additional, Cui, Xiangling, additional, Cui, Yujun, additional, Dacal, Elena, additional, Dammann, Allison N., additional, Das, Shubhagata, additional, Dashti, Alejandro, additional, de la Fuente, José, additional, de la Garza, Mireya, additional, Delgado, Josué, additional, Delgado-Cuesta, Juan, additional, Deng, Haiteng, additional, Deng, Li, additional, Dey, Debajit, additional, Dhama, Kuldeep, additional, Diego, Juan García-Bernalt, additional, Ding, Hao, additional, Doern, Christopher D., additional, Dorman, Charles J., additional, Du, Zongmin, additional, Dunbar, Sherry A., additional, Duthie, Malcolm, additional, Dybvig, Kevin F., additional, Eakin, Ann E., additional, Eallonardo, Samuel J., additional, Eberly, Allison R., additional, Echeverry, Adriana Jaramillo, additional, Egland, Paul G., additional, El Zowalaty, Mohamed E., additional, Endsley, Janice Jones, additional, Eom, Keeseon S., additional, Evans, Benjamin A., additional, Falkinham, Joseph O., additional, Feng, Siwei, additional, Feng, Yaoyu, additional, Feng, Zongdi, additional, Fernández-Soto, Pedro, additional, Ferreira, Roux-Cil, additional, Flores-Huerta, Nadia, additional, Foster, Timothy J., additional, Fox-Moon, Sandra M., additional, Fraga, Tatiana Rodrigues, additional, Fredricks, David N., additional, Freitag, Nancy E., additional, Frimodt-Møller, Jakob, additional, Fuller, Risa, additional, Ganesh, Balasubramanian, additional, Gao, Ning, additional, García-Carnero, Laura C., additional, Garzetti, Debora, additional, Geoghegan, Joan A., additional, Ghenim, Raed, additional, Giambartolomei, Guillermo H., additional, Gilbert, Nicole M., additional, Gillis, Thomas Phillip, additional, Gladstone, Camilla A., additional, Gómez-Gaviria, Manuela, additional, Gómez-Marín, Jorge E., additional, Gong, Tengfang, additional, González, Ramón A., additional, Gray-Owen, Scott D., additional, Gu, Bing, additional, Guzmán-Téllez, Paula, additional, Hajal, Caroline, additional, Han, Yanping, additional, Hao, Yi, additional, Harrington, Amanda T., additional, Harris, Jason B., additional, Harvill, Eric T., additional, Hasan, S. Saif, additional, He, Guang-Jun, additional, He, Yongqun, additional, Heffron, Jared D., additional, Hidalgo, Paloma, additional, Hindiyeh, Musa Y., additional, Hreha, Teri N., additional, Hu, Xiaoyu, additional, Huang, Guanghua, additional, Huang, Jiangqing, additional, Huang, Liang, additional, Huang, Shifeng, additional, Huang, Xingxu, additional, Huang, Xueting, additional, Huang, Yilun, additional, Huffman, Anthony, additional, Humphreys, Tricia L., additional, Hunstad, David A., additional, Inglis, Timothy J.J., additional, Isaac, Lourdes, additional, Jacobs, Samantha E., additional, Janowicz, Diane M., additional, Jeon, Hyeong-Kyu, additional, Ji, Quanjiang, additional, Jia, Qi, additional, Jia, Wei, additional, Jin, Shouguang, additional, Jneidi, Lama, additional, Jose, Shinsmon, additional, Jung, Bong-Kwang, additional, Kattan, Randa, additional, Kaushik, Rahul, additional, Khare, Reeti, additional, Kim, Eun Sook, additional, Kirn, Thomas J., additional, Koo, Hyun, additional, Köster, Pamela C., additional, Krause, Peter J., additional, Kumar, Sanjai, additional, Kupz, Andreas, additional, Lambert, P.A., additional, Lamont, Richard J., additional, Langford, Paul R., additional, Lebeaux, David, additional, Legname, Giuseppe, additional, Li, Bin, additional, Li, Chunhao, additional, Li, Fen, additional, Li, Jun, additional, Li, Lanjuan, additional, Li, Ruofan, additional, Li, Ruoyu, additional, Li, Ting, additional, Li, Yang-Yang, additional, Li, Yanhua, additional, Li, Zhuorong, additional, Liang, Xiaomeng, additional, Liao, Guojian, additional, Lin, Ping, additional, Ling, Yun, additional, Liu, Bo, additional, Liu, Dongyou, additional, Liu, Guohua, additional, Liu, Huidi, additional, Liu, Jiafeng, additional, Liu, Jintao, additional, Liu, Qi, additional, Liu, Shu-Lin, additional, Liu, Taiping, additional, Liu, Tongbao, additional, Liu, Wei, additional, Liu, Yan, additional, Liu, Yanni, additional, Liu, Yisong, additional, Liu, Yuan, additional, Løbner-Olesen, Anders, additional, Loeffelholz, Michael, additional, Lu, Hongzhou, additional, Luna, Brian, additional, Ma, Bingting, additional, Ma, Chengying, additional, Ma, Shuang, additional, Ma, TianLi, additional, Madan, Rajat, additional, Mahle, Rachael E., additional, Mahlen, Steven D., additional, Malik, Satya Veer Singh, additional, Malik, Yashpal Singh, additional, Malvy, Denis, additional, Mann, Barbara J., additional, Marasini, Daya, additional, Maris, Alexander S., additional, Marjomäki, Varpu, additional, Marjuki, Henju, additional, Martín, Alberto, additional, Martín, Irene, additional, Martínez-Castillo, Moisés, additional, Martínez-Pabón, María Cecilia, additional, Mathison, Blaine A., additional, Ma’ayeh, Showgy, additional, McDowell, Andrew, additional, McLaughlin, Stephanie E., additional, McSheffrey, Gordon G., additional, Medrano, Francisco J., additional, Meehan, Conor J., additional, Mehta, Dhwani, additional, Mejía-Oquendo, Manuela, additional, Melo-Cristino, José, additional, Mendoza-Barberá, Elena, additional, Meng, Xinan, additional, Merino, Susana, additional, Merritt, Adam J., additional, Miller, Steve, additional, Miller, William R., additional, Minamino, Tohru, additional, Mirzaei, Mohammadali Khan, additional, Mora-Montes, Héctor M., additional, Mortensen, Joel, additional, Mostafa, Heba H., additional, Muhsen, Khitam, additional, Mujahed, Ahlam, additional, Muro, Antonio, additional, Murphy, Olwen C., additional, Newton, Hayley J., additional, Nguyen, April H., additional, Nichols, Wright W., additional, Niu, Siqiang, additional, Núñez, Félix, additional, Obregon, Dasiel, additional, Okamoto, Akira, additional, Okutani, Akiko, additional, Olabode, Abayomi, additional, Omar, Muna, additional, Ong, Edison, additional, Ouyang, Zhiming, additional, Pacak, Christina A., additional, Pacheco-Yépez, Judith, additional, Palmer, John, additional, Pang, Xiaoli, additional, Paredes-Sabja, Daniel, additional, Peng, Zhong, additional, Peng, Zonggen, additional, Pérez-Nevado, Francisco, additional, Poon, Art, additional, Pospíšilová, Petra, additional, Potts, Caelin C., additional, Pu, Qinqin, additional, Pujic, Petar, additional, Qi, Rui, additional, Qian, Chenyun, additional, Qian, Liu, additional, Qin, Aiping, additional, Qu, Fen, additional, Rakin, Alexander, additional, Ramesh, Ashwin, additional, Ramirez, Mario, additional, Rao, Yu, additional, Ratner, Adam J., additional, Rawool, Deepak B., additional, Rehman, Asma, additional, Ren, Jie, additional, Ren, Ping, additional, Retchless, Adam C., additional, Robertson, Erle S., additional, Rodríguez, Alicia, additional, Rodriguez, Azucena, additional, Rodríguez-Medina, Carolina, additional, Rodriguez-Nava, Veronica, additional, Rohde, Manfred, additional, Romero-Rodríguez, Alba, additional, Rosales-Morgan, Gabriela, additional, Rosenkranz, Andrea L., additional, Ruiz-Moyano, Santiago, additional, Ruokolainen, Visa, additional, Sabateen, Ali, additional, Sahu, Radhakrishna, additional, Sails, Andrew, additional, Sang, Yu, additional, Santana, Clarissa H., additional, Santos, Jesus A., additional, Santos, Renato L., additional, Schmitz, Jonathan E., additional, Serrano-Luna, Jesús, additional, Shen, Jianzhong, additional, Shen, Zhangqi, additional, Shibayama, Mineko, additional, Shirtliff, Mark E., additional, Silva-Costa, Catarina, additional, Silva-Olivares, Angélica, additional, Singh, Niraj Kumar, additional, Šmajs, David, additional, Smith, Robert P., additional, Smith, Sophie, additional, Snyder, Lori A.S., additional, Song, Yinggai, additional, Soro, Aurea Simon, additional, Spearman, Paul, additional, Spellberg, Brad, additional, Sprague, Lisa D., additional, Stratton, Charles W., additional, Strenk, Susan M., additional, Strugnell, Richard A., additional, Sun, Keer, additional, Suo, Xun, additional, Suzuki-Hatano, Silveli, additional, Svärd, Staffan, additional, Talbot, Elizabeth A., additional, Tamez-Castrellón, Alma K., additional, Tan, Nie, additional, Tang, Cynthia Y., additional, Tang, Yi-Wei, additional, Tao, Jia, additional, Tao, Lili, additional, Terrero-Salcedo, David, additional, Tharmalingam, Jayaraman, additional, Thwe, Phyu M., additional, Tiamani, Kawtar, additional, Tomás, Juan M., additional, Topaz, Nadav, additional, Tsai, Ang-Chen, additional, Tsalik, Ephraim L., additional, Tuomanen, Elaine I., additional, Turenne, Christine Y., additional, Tyagi, Anuj, additional, Uprety, Priyanka, additional, Valour, Florent, additional, van Hensbergen, Vincent P., additional, Venkatesan, Arun, additional, Vergis, Jess, additional, Villar, Margarita, additional, Vollmer, Waldemar, additional, Waites, Ken B., additional, Wan, Xiu-Feng, additional, Wang, Guiqing, additional, Wang, Lijun, additional, Wang, Lin, additional, Wang, Linqi, additional, Wang, Xiangru, additional, Wang, Xin, additional, Wang, Xinjie, additional, Wang, Ya-Ting, additional, Wang, Yang, additional, Wang, Yating, additional, Weil, Ana A., additional, Welkos, Susan L., additional, Wengenack, Nancy L., additional, Westblade, Lars F., additional, Whitfield, Chris, additional, Wu, Hui, additional, Wu, Lijuan, additional, Wu, Min, additional, Wu, Yarong, additional, Wu, Zhaowei, additional, Xiang, Ye, additional, Xiao, Di, additional, Xiao, Li, additional, Xiao, Lihua, additional, Xu, Tao, additional, Xu, Wenyue, additional, Xu, Xinping, additional, Xue, Jinling, additional, Yadav, Jay Prakash, additional, Yan, Junxiang, additional, Yan, Yixin, additional, Yang, Changmei, additional, Yang, Ruifu, additional, Yang, Ying, additional, Yao, Kaihu, additional, Yao, Yu-Feng, additional, Yeakle, Kyle C., additional, Yu, Demin, additional, Yu, Hao, additional, Yu, Xue-Jie, additional, Yuan, Zhenghong, additional, Zai, Wenjing, additional, Zhang, Jianzhong, additional, Zhang, Jing-Ren, additional, Zhang, Lanyue, additional, Zhang, Lijie, additional, Zhang, Qiwei, additional, Zhang, Wenbao, additional, Zhang, Wenhong, additional, Zhang, Xinxin, additional, Zhao, Youbao, additional, Zhou, Chuanmin, additional, Zhu, Feng, additional, Zhu, Jingting, additional, and Zhu, Yongqun, additional

Published
2024
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18. A Deep Conjugate Direction Method for Iteratively Solving Linear Systems

Author

Kaneda, Ayano, Akar, Osman, Chen, Jingyu, Kala, Victoria, Hyde, David, and Teran, Joseph

Subjects
Computer Science - Machine Learning, Mathematics - Numerical Analysis, 65F10 (Primary) 68T07, 65N22 (Secondary), G.1.3, I.2.6, I.3.0
Abstract

We present a novel deep learning approach to approximate the solution of large, sparse, symmetric, positive-definite linear systems of equations. These systems arise from many problems in applied science, e.g., in numerical methods for partial differential equations. Algorithms for approximating the solution to these systems are often the bottleneck in problems that require their solution, particularly for modern applications that require many millions of unknowns. Indeed, numerical linear algebra techniques have been investigated for many decades to alleviate this computational burden. Recently, data-driven techniques have also shown promise for these problems. Motivated by the conjugate gradients algorithm that iteratively selects search directions for minimizing the matrix norm of the approximation error, we design an approach that utilizes a deep neural network to accelerate convergence via data-driven improvement of the search directions. Our method leverages a carefully chosen convolutional network to approximate the action of the inverse of the linear operator up to an arbitrary constant. We train the network using unsupervised learning with a loss function equal to the $L^2$ difference between an input and the system matrix times the network evaluation, where the unspecified constant in the approximate inverse is accounted for. We demonstrate the efficacy of our approach on spatially discretized Poisson equations with millions of degrees of freedom arising in computational fluid dynamics applications. Unlike state-of-the-art learning approaches, our algorithm is capable of reducing the linear system residual to a given tolerance in a small number of iterations, independent of the problem size. Moreover, our method generalizes effectively to various systems beyond those encountered during training., Comment: 12 pages, 4 figures

Published
2022

47. A Momentum-Conserving Implicit Material Point Method for Surface Energies with Spatial Gradients

Author

Chen, Jingyu, Kala, Victoria, Marquez-Razon, Alan, Gueidon, Elias, Hyde, David A. B., and Teran, Joseph

Subjects
Computer Science - Graphics, Computer Science - Computational Engineering, Finance, and Science, I.3.0, I.6.0
Abstract

We present a novel Material Point Method (MPM) discretization of surface tension forces that arise from spatially varying surface energies. These variations typically arise from surface energy dependence on temperature and/or concentration. Furthermore, since the surface energy is an interfacial property depending on the types of materials on either side of an interface, spatial variation is required for modeling the contact angle at the triple junction between a liquid, solid and surrounding air. Our discretization is based on the surface energy itself, rather than on the associated traction condition most commonly used for discretization with particle methods. Our energy based approach automatically captures surface gradients without the explicit need to resolve them as in traction condition based approaches. We include an implicit discretization of thermomechanical material coupling with a novel particle-based enforcement of Robin boundary conditions associated with convective heating. Lastly, we design a particle resampling approach needed to achieve perfect conservation of linear and angular momentum with AffineParticle-In-Cell (APIC) [Jiang et al. 2015]. We show that our approach enables implicit time stepping for complex behaviors like the Marangoni effect and hydrophobicity/hydrophilicity. We demonstrate the robustness and utility of our method by simulating materials that exhibit highly diverse degrees of surface tension and thermomechanical effects, such as water, wine and wax.

Published
2021
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