Zobrazeno 1 - 10
of 420
pro vyhledávání: '"Somayajulu, P."'
With increasing computational demand, Neural-Network (NN) based models are being developed as pre-trained surrogates for different thermohydraulics phenomena. An area where this approach has shown promise is in developing higher-fidelity turbulence c
Externí odkaz:
http://arxiv.org/abs/2412.08818
Covariance-free Bi-fidelity Control Variates Importance Sampling for Rare Event Reliability Analysis
Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities a significant computational challenge for complex real-world problems,
Externí odkaz:
http://arxiv.org/abs/2405.03834
Neural Table-to-Text models tend to hallucinate, producing texts that contain factual errors. We investigate whether such errors in the output can be traced back to problems with the input. We manually annotated 1,837 texts generated by multiple mode
Externí odkaz:
http://arxiv.org/abs/2404.04103
Autor:
Thaler, Denny, Dhulipala, Somayajulu L. N., Bamer, Franz, Markert, Bernd, Shields, Michael D.
We present a new Subset Simulation approach using Hamiltonian neural network-based Monte Carlo sampling for reliability analysis. The proposed strategy combines the superior sampling of the Hamiltonian Monte Carlo method with computationally efficien
Externí odkaz:
http://arxiv.org/abs/2401.05244
Autor:
Thakolkaran, Prakash, Espinal, Michael A., Dhulipala, Somayajulu, Kumar, Siddhant, Portela, Carlos M.
Spinodal metamaterials, with architectures inspired by natural phase-separation processes, have presented a significant alternative to periodic and symmetric morphologies when designing mechanical metamaterials with extreme performance. While their e
Externí odkaz:
http://arxiv.org/abs/2312.11648
Autor:
Dhulipala, Somayajulu L. N.
Due to the paucity of strong recorded accelerograms, earthquake engineering analysis relies on accelerogram amplitude scaling for structural damage/collapse assessment and target spectrum matching. This paper investigates seismological characteristic
Externí odkaz:
http://arxiv.org/abs/2305.05631
Autor:
Chakroborty, Promit, Dhulipala, Somayajulu L. N., Che, Yifeng, Jiang, Wen, Spencer, Benjamin W., Hales, Jason D., Shields, Michael D.
Estimating the probability of failure for complex real-world systems using high-fidelity computational models is often prohibitively expensive, especially when the probability is small. Exploiting low-fidelity models can make this process more feasib
Externí odkaz:
http://arxiv.org/abs/2212.03375
Autor:
Dhulipala, Somayajulu L. N., Chakroborty, Promit, Shields, Michael D., Jiang, Wen, Spencer, Benjamin W., Hales, Jason D.
The Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel proposed to be used for multiple modern nuclear technologies. Therefore, characterizing its safety is vital for the reliable operation of nuclear technologies. However,
Externí odkaz:
http://arxiv.org/abs/2211.11115
Although the no-u-turn sampler (NUTS) is a widely adopted method for performing Bayesian inference, it requires numerous posterior gradients which can be expensive to compute in practice. Recently, there has been a significant interest in physics-bas
Externí odkaz:
http://arxiv.org/abs/2209.09349
When sampling for Bayesian inference, one popular approach is to use Hamiltonian Monte Carlo (HMC) and specifically the No-U-Turn Sampler (NUTS) which automatically decides the end time of the Hamiltonian trajectory. However, HMC and NUTS can require
Externí odkaz:
http://arxiv.org/abs/2208.06120