Seid Koric

According to our database, Seid Koric authored at least 31 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Deep learning operator network for plastic deformation with variable loads and material properties.

Seid Koric, Asha Viswantah, Diab W. Abueidda, Nahil A. Sobh, Kamran A Khan

Eng. Comput., April, 2024

Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads.

Junyan He, Shashank Kushwaha, Jaewan Park, Seid Koric, Diab W. Abueidda, Iwona Jasiuk

Eng. Appl. Artif. Intell., January, 2024

Nonlinear Inverse Design of Mechanical Multi-Material Metamaterials Enabled by Video Denoising Diffusion and Structure Identifier.

Jaewan Park, Shashank Kushwaha, Junyan He, Seid Koric, Qibang Liu, Iwona Jasiuk, Diab W. Abueidda

CoRR, 2024

Advanced Deep Operator Networks to Predict Multiphysics Solution Fields in Materials Processing and Additive Manufacturing.

Shashank Kushwaha, Jaewan Park, Seid Koric, Junyan He, Iwona Jasiuk, Diab W. Abueidda

CoRR, 2024

Geom-DeepONet: A Point-cloud-based Deep Operator Network for Field Predictions on 3D Parameterized Geometries.

Junyan He, Seid Koric, Diab W. Abueidda, Ali Najafi, Iwona Jasiuk

CoRR, 2024

Material-Response-Informed DeepONet and its Application to Polycrystal Stress-strain Prediction in Crystal Plasticity.

Junyan He, Deepankar Pal, Ali Najafi, Diab W. Abueidda, Seid Koric, Iwona Jasiuk

CoRR, 2024

2023

Multi-component Predictions of Transient Solution Fields with Sequential Deep Operator Network.

Junyan He, Shashank Kushwaha, Jaewan Park, Seid Koric, Diab W. Abueidda, Iwona Jasiuk

CoRR, 2023

Towards Exascale Computation for Turbomachinery Flows.

Yuhang Fu, Weiqi Shen, Jiahuan Cui, Yao Zheng, Guangwen Yang, Zhao Liu, Jifa Zhang, Tingwei Ji, Fangfang Xie, Xiaojing Lv, Hanyue Liu, Xu Liu, Xiyang Liu, Xiaoyu Song, Guocheng Tao, Yan Yan, Paul Tucker, Steven A. E. Miller, Shirui Luo, Seid Koric, Weimin Zheng

CoRR, 2023

Sequential Deep Learning Operator Network (S-DeepONet) for Time-Dependent Loads.

Jaewan Park, Shashank Kushwaha, Junyan He, Seid Koric, Diab W. Abueidda, Iwona Jasiuk

CoRR, 2023

Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads.

Junyan He, Seid Koric, Shashank Kushwaha, Jaewan Park, Diab W. Abueidda, Iwona Jasiuk

CoRR, 2023

Gyroid-like metamaterials: Topology optimization and Deep Learning.

Asha Viswanath, Diab W. Abueidda, Mohamad Modrek, Kamran A Khan, Seid Koric, Rashid K. Abu Al-Rub

CoRR, 2023

Cybershuttle: An End-to-End Cyberinfrastructure Continuum to Accelerate Discovery in Science and Engineering.

Suresh Marru, Marlon E. Pierce, Beth Plale, Sudhakar Pamidighantam, Dimuthu Wannipurage, Marcus Christie, Isuru Ranawaka, Eroma Abeysinghe, Rob Quick, Emad Tajkhorshid, Seid Koric, Jim Basney, Mariano Spivak, Barry Isralewitz, Rafael C. Bernardi, Diego Gomes, Giri P. Krishnan, Maxim Bazhenov, Shava Smallen, Amit Majumdar, Anton Arkhipov, Kael Dai, Xiao-Ping Liu, Kenneth Yoshimoto

Proceedings of the Practice and Experience in Advanced Research Computing, 2023

Toward Exascale Computation for Turbomachinery Flows.

Yuhang Fu, Weiqi Shen, Jiahuan Cui, Yao Zheng, Guangwen Yang, Zhao Liu, Jifa Zhang, Tingwei Ji, Fangfang Xie, Xiaojing Lv, Hanyue Liu, Xu Liu, Xiyang Liu, Xiaoyu Song, Guocheng Tao, Yan Yan, Paul Tucker, Steven A. E. Miller, Shirui Luo, Seid Koric, Weimin Zheng

Proceedings of the International Conference for High Performance Computing, 2023

2022

A deep learning energy-based method for classical elastoplasticity.

Junyan He, Diab W. Abueidda, Rashid K. Abu Al-Rub, Seid Koric, Iwona Jasiuk

CoRR, 2022

On the use of graph neural networks and shape-function-based gradient computation in the deep energy method.

Junyan He, Diab W. Abueidda, Seid Koric, Iwona Jasiuk

CoRR, 2022

Deep energy method in topology optimization applications.

Junyan He, Shashank Kushwaha, Charul Chadha, Seid Koric, Diab W. Abueidda, Iwona Jasiuk

CoRR, 2022

Enhanced physics-informed neural networks for hyperelasticity.

Diab W. Abueidda, Seid Koric, Erman Guleryuz, Nahil A. Sobh

CoRR, 2022

Surrogate Neural Network Model for Sensitivity Analysis and Uncertainty Quantification of the Mechanical Behavior in the Optical Lens-Barrel Assembly.

Shantanu Shahane, Erman Guleryuz, Diab W. Abueidda, Allen Lee, Joe Liu, Xin Yu, Raymond Chiu, Seid Koric, Narayana R. Aluru, Placid M. Ferreira

CoRR, 2022

A deep learning energy method for hyperelasticity and viscoelasticity.

Diab W. Abueidda, Seid Koric, Rashid K. Abu Al-Rub, Corey M. Parrott, Kai A. James, Nahil A. Sobh

CoRR, 2022

2021

High-Performance Computing Comparison of Implicit and Explicit Nonlinear Finite Element Simulations of Trabecular Bone.

Fereshteh A. Sabet, Seid Koric, Ashraf Idkaidek, Iwona Jasiuk

Comput. Methods Programs Biomed., 2021

Turbomachinery Blade Surrogate Modeling Using Deep Learning.

Shirui Luo, Jiahuan Cui, Vignesh Sella, Jian Liu, Seid Koric, Volodymyr V. Kindratenko

Proceedings of the High Performance Computing - ISC High Performance Digital 2021 International Workshops, Frankfurt am Main, Germany, June 24, 2021

2020

Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure.

Eliu A. Huerta, Asad Khan, Edward Davis, Colleen Bushell, William D. Gropp, Daniel S. Katz, Volodymyr V. Kindratenko, Seid Koric, William T. C. Kramer, Brendan McGinty, Kenton McHenry, Aaron Saxton

J. Big Data, 2020

Deep learning collocation method for solid mechanics: Linear elasticity, hyperelasticity, and plasticity as examples.

Diab W. Abueidda, Qiyue Lu, Seid Koric

CoRR, 2020

Machine learning accelerated topology optimization of nonlinear structures.

Diab W. Abueidda, Seid Koric, Nahil A. Sobh

CoRR, 2020

Parameter Identification of RANS Turbulence Model Using Physics-Embedded Neural Network.

Shirui Luo, Madhu Vellakal, Seid Koric, Volodymyr V. Kindratenko, Jiahuan Cui

Proceedings of the High Performance Computing, 2020

Scalability Challenges of an Industrial Implicit Finite Element Code.

François-Henry Rouet, Cleve Ashcraft, Jef Dawson, Roger Grimes, Erman Guleryuz, Seid Koric, Robert F. Lucas, James S. Ong, Todd A. Simons, Ting-Ting Zhu

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

2016

Alya: Multiphysics engineering simulation toward exascale.

Mariano Vázquez, Guillaume Houzeaux, Seid Koric, Antoni Artigues, Jazmin Aguado-Sierra, Ruth Aris, Daniel Mira, Hadrien Calmet, Fernando M. Cucchietti, Herbert Coppola-Owen, Ahmed Taha, Evan Dering Burness, José María Cela, Mateo Valero

J. Comput. Sci., 2016

Evaluation of parallel direct sparse linear solvers in electromagnetic geophysical problems.

Vladimir Puzyrev, Seid Koric, Scott Wilkin

Comput. Geosci., 2016

Effective Minimally-Invasive GPU Acceleration of Distributed Sparse Matrix Factorization.

Anshul Gupta, Natalia Gimelshein, Seid Koric, Steven C. Rennich

Proceedings of the Euro-Par 2016: Parallel Processing, 2016

2014

XSEDE OpenACC workshop enables Blue Waters Researchers to Accelerate Key Algorithms.

Galen Wesley Arnold, Manisha Gajbe, Seid Koric, John Urbanic

Proceedings of the Annual Conference of the Extreme Science and Engineering Discovery Environment, 2014

2009

Sparse matrix factorization on massively parallel computers.

Anshul Gupta, Seid Koric, Thomas George

Proceedings of the ACM/IEEE Conference on High Performance Computing, 2009