Search

Your search keyword '"Jha A. K."' showing total 5,711 results
Start Over Author "Jha A. K." Search Limiters Peer Reviewed
5,711 results on '"Jha A. K."'

11. Nodal finite element approximation of peridynamics

Author

Jha, Prashant K., Diehl, Patrick, and Lipton, Robert

Subjects
Mathematics - Numerical Analysis, 65M12, 65M60, 65M15, 74A70
Abstract

This work considers the nodal finite element approximation of peridynamics, in which the nodal displacements satisfy the peridynamics equation at each mesh node. For the nonlinear bond-based peridynamics model, it is shown that, under the suitable assumptions on an exact solution, the discretized solution associated with the central-in-time and nodal finite element discretization converges to the exact solution in $L^2$ norm at the rate $C_1 \Delta t + C_2 h^2/\epsilon^2$. Here, $\Delta t$, $h$, and $\epsilon$ are time step size, mesh size, and the size of the horizon or nonlocal length scale, respectively. Constants $C_1$ and $C_2$ are independent of $h$ and $\Delta t$ and depend on norms of the solution and nonlocal length scale. Several numerical examples involving pre-crack, void, and notch are considered, and the efficacy of the proposed nodal finite element discretization is analyzed., Comment: 35 pages, 22 figures

Published
2024
Full Text
View/download PDF

17. Comparative effectiveness research trial for antidepressant incomplete and non-responders with treatment resistant depression (ASCERTAIN-TRD) a randomized clinical trial

Author

Papakostas, George I., Trivedi, Madhukar H., Shelton, Richard C., Iosifescu, Dan V., Thase, Michael E., Jha, Manish K., Mathew, Sanjay J., DeBattista, Charles, Dokucu, Mehmet E., Brawman-Mintzer, Olga, Currier, Glenn W., McCall, William Vaughn, Modirrousta, Mandana, Macaluso, Matthew, Bystritsky, Alexander, Rodriguez, Fidel Vila, Nelson, Erik B., Yeung, Albert S., Feeney, Anna, MacGregor, Leslie C., Carmody, Thomas, and Fava, Maurizio

Published
2024
Full Text
View/download PDF

24. Molecular and clinical analyses of PHF6 mutant myeloid neoplasia provide their pathogenesis and therapeutic targeting

Author

Kubota, Yasuo, Gu, Xiaorong, Terkawi, Laila, Bodo, Juraj, Przychodzen, Bartlomiej P., Awada, Hussein, Williams, Nakisha, Gurnari, Carmelo, Kawashima, Naomi, Aly, Mai, Durmaz, Arda, Mori, Minako, Ponvilawan, Ben, Kewan, Tariq, Bahaj, Waled, Meggendorfer, Manja, Jha, Babal K., Visconte, Valeria, Rogers, Heesun J., Haferlach, Torsten, and Maciejewski, Jaroslaw P.

Published
2024
Full Text
View/download PDF

34. Residual-Based Error Corrector Operator to Enhance Accuracy and Reliability of Neural Operator Surrogates of Nonlinear Variational Boundary-Value Problems

Author

Jha, Prashant K.

Subjects
Mathematics - Numerical Analysis, Computer Science - Machine Learning, 65N22, 65N30, 62M45
Abstract

This work focuses on developing methods for approximating the solution operators of a class of parametric partial differential equations via neural operators. Neural operators have several challenges, including the issue of generating appropriate training data, cost-accuracy trade-offs, and nontrivial hyperparameter tuning. The unpredictability of the accuracy of neural operators impacts their applications in downstream problems of inference, optimization, and control. A framework based on the linear variational problem that gives the correction to the prediction furnished by neural operators is considered based on earlier work in JCP 486 (2023) 112104. The operator, called Residual-based Error Corrector Operator or simply Corrector Operator, associated with the corrector problem is analyzed further. Numerical results involving a nonlinear reaction-diffusion model in two dimensions with PCANet-type neural operators show almost two orders of increase in the accuracy of approximations when neural operators are corrected using the correction scheme. Further, topology optimization involving a nonlinear reaction-diffusion model is considered to highlight the limitations of neural operators and the efficacy of the correction scheme. Optimizers with neural operator surrogates are seen to make significant errors (as high as 80 percent). However, the errors are much lower (below 7 percent) when neural operators are corrected., Comment: 36 pages, 14 figures, 3 tables

Published
2023
Full Text
View/download PDF

38. Tunable bistability, optomechanical and magnomechanically induced transparency in opto-magnomechanical system.

Author

Kumar Singh, Madhav, Mahajan, Sonam, Bhatt, Vijay, Yadav, Surabhi, Jha, Pradip K, and Bhattacherjee, Aranya B

Subjects
YTTRIUM iron garnet, OPTICAL devices, OPTICAL switching, MAGNETIC dipoles, OPTICAL properties
Abstract

We investigate theoretically the optical properties of a hybrid optomechanical system embedded with a yttrium iron garnet (YIG) sphere. It is considered that YIG interacts with a single mode of the microcavity through magnetic dipole coupling. To enhance the magnomechanical coupling, the magnon mode is directly driven by a microwave field. The microcavity is driven by the control and probe field. The study of steady-state dynamics of the system shows bistable behavior. Furthermore, optomechanically induced transparency under the influence of a strong control field in the system is explored. In addition, magnomechanically induced transparency (MMIT) due to the presence of nonlinear magnon–phonon interaction is studied. Fano like shape is observed in MMIT. The impact of different system parameters is studied. Our results will provide a theoretical approach to understand opto-magnomechanical systems. These results may be useful in all optical switching devices and optical transistors. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results