Somayajulu L. N. Dhulipala

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Benjamin SpencerIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Michael D. ShieldsJohns Hopkins UniversityGeverifieerd e-mailadres voor jhu.edu
Chandrakanth BolisettiIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Wen JiangIdaho National LabGeverifieerd e-mailadres voor inl.gov
Jason HalesIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Promit ChakrobortyPh.D. Student, Dept of Civil and Systems Engg., Johns Hopkins UniversityGeverifieerd e-mailadres voor jhu.edu
Yifeng CheIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Adrian Rodriguez-MarekProfessor, Civil and Environmental engineering department, Virginia techGeverifieerd e-mailadres voor vt.edu
Lynn MundayIdaho National LabGeverifieerd e-mailadres voor inl.gov
Stephen NovasconeComputational Scientist, Idaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Vincent LaboureIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Aysenur ToptanWestinghouse Electric Company (United States)Geverifieerd e-mailadres voor westinghouse.com
Péter GermanIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Gyanender P. SinghIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Derek GastonIdaho National LaboratoryGeverifieerd e-mailadres voor inl.gov
Daniel SchwenIdaho National LaboratoryGeverifieerd e-mailadres voor schwen.de
Kyungtae KimCalifornia Department of TransportationGeverifieerd e-mailadres voor dot.ca.gov
Denny ThalerRWTH Aachen UniversityGeverifieerd e-mailadres voor iam.rwth-aachen.de
Franz BamerPostDoc, RWTH Aachen UniversityGeverifieerd e-mailadres voor iam.rwth-aachen.de
Bernd MarkertUniversity Professor, Director at Institute of General Mechanics, RWTH Aachen UniversityGeverifieerd e-mailadres voor iam.rwth-aachen.de

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Somayajulu L. N. Dhulipala

Andere namenSLN Dhulipala, Som Dhulipala, Somayajulu Dhulipala

Computational Scientist, Idaho National Lab

Geverifieerd e-mailadres voor inl.gov

Physics-based machine learning Predictive modeling HPC Uncertainty quantification


Titel Sorteren op citaties Sorteren op jaar Sorteren op titel	Geciteerd door Geciteerd door	Jaar
Series of Semi-Markov Processes to Model Infrastructure Resilience under Multihazards SLN Dhulipala, MM Flint Reliability Engineering and System Safety 193, 106659, 2020	46	2020
Active learning with multifidelity modeling for efficient rare event simulation SLN Dhulipala, MD Shields, BW Spencer, C Bolisetti, AE Slaughter, ... Journal of Computational Physics, 2022	31	2022
A Markov Framework for Generalized Post-Event Infrastructure Recovery Modeling: From Single to Multihazards SLN Dhulipala, HV Burton, H Baroud Structural Safety, 2021	27	2021
Reliability Estimation of an Advanced Nuclear Fuel using Coupled Active Learning, Multifidelity Modeling, and Subset Simulation SLN Dhulipala, MD Shields, P Chakroborty, W Jiang, BW Spencer, ... Reliability Engineering and System Safety 226, 108693, 2022	22	2022
Efficient high-fidelity TRISO statistical failure analysis using Bison: Applications to AGR-2 irradiation testing W Jiang, G Singh, JD Hales, A Toptan, BW Spencer, SR Novascone, ... Journal of Nuclear Materials 562, 153585, 2022	22	2022
MOOSE Stochastic Tools: A module for performing parallel, memory-efficient in situ stochastic simulations AE Slaughter, ZM Prince, P German, I Halvic, W Jiang, BW Spencer, ... SoftwareX 22, 101345, 2023	21	2023
MASTODON: an open-source software for seismic analysis and risk assessment of critical infrastructure S Veeraraghavan, C Bolisetti, A Slaughter, J Coleman, S Dhulipala, ... Nuclear Technology 207 (7), 1073-1095, 2021	19	2021
Developing a Decision Framework for Multi-Hazard Design of Resilient, Sustainable Buildings M Flint, SLN Dhulipala, Y Shahtaheri, H Tahir, T Ladipo, MR Eatherton, ... 1st International conference on natural hazards and Infrastructure (ICHONIC2016), 2016	19	2016
Accelerated statistical failure analysis of multifidelity TRISO fuel models SLN Dhulipala, W Jiang, BW Spencer, JD Hales, MD Shields, ... Journal of Nuclear Materials 563, 153604, 2022	18	2022
A site-consistent method to quantify sufficiency of alternative IMs in relation to PSDA SLN Dhulipala, A Rodriguez-Marek, R Shyam, MM Flint Earthquake Engineering and Structural Dynamics 47 (2), 377-396, 2018	18	2018
Computation of vector hazard using salient features of seismic hazard deaggregation SLN Dhulipala, A Rodriguez-Marek, MM Flint Earthquake Spectra 34 (4), 1893-1912, 2018	16	2018
Development, verification, and validation of comprehensive acoustic fluid‐structure interaction capabilities in an open‐source computational platform SLN Dhulipala, C Bolisetti, LB Munday, WM Hoffman, CC Yu, FUH Mir, ... Earthquake Engineering & Structural Dynamics 51 (10), 2188-2219, 2022	10	2022
Dysfunctionality Hazard Curve: A Risk-Based Tool to Support the Resilient Design of Systems Subjected to Multihazards SLN Dhulipala ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part-A …, 2020	10	2020
Multiscale-informed modeling of high temperature component response with uncertainty quantification LB Munday, SLN Dhulipala, SA Pitts, A Casagranda, BW Spencer, ... Idaho National Lab.(INL), Idaho Falls, ID (United States); Los Alamos …, 2020	8	2020
General Multifidelity Surrogate Models: Framework and Active-Learning Strategies for Efficient Rare Event Simulation P Chakroborty, SLN Dhulipala, Y Che, W Jiang, BW Spencer, JD Hales, ... Journal of Engineering Mechanics 149 (12), 04023096, 2023	7	2023
Intensity Measure Adequacy Assessment for Nonlinear Site Response usingInformation Theory SLN Dhulipala, A Rodriguez-Marek, M Bahrampouri Soil Dynamics and Earthquake Engineering 134, 106144, 2020	7	2020
Efficient Bayesian Inference with Latent Hamiltonian Neural Networks in No-U-Turn Sampling S Dhulipala, Y Che, M Shields Journal of Computational Physics, 2023	6	2023
Seismic Risk Assessment of Safety-Critical Nuclear Facilities for the Purpose of Risk-Informed Periodic Re-evaluation SLN Dhulipala, C Bolisetti, R Yorg, P Hashimoto, J Coleman, M Cox Nuclear Technology, 2020	6	2020
Bayesian Methods for Intensity Measure and Ground Motion Selection in Performance-Based Earthquake Engineering SLN Dhulipala Virginia Tech, 2019	6	2019
Importance of Intensity Measure sufficiency for structural seismic demand hazard analysis SLN Dhulipala, A Rodriguez-Marek, MM Flint National Conference on Earthquake Engineering 2018, 2018	6	2018

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