关注
Joseph P. Molnar
Joseph P. Molnar
PhD Student, Penn State
在 psu.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
Estimating density, velocity, and pressure fields in supersonic flows using physics-informed BOS
JP Molnar, L Venkatakrishnan, BE Schmidt, TA Sipkens, SJ Grauer
Experiments in Fluids 64 (1), 14, 2023
352023
Flow field tomography with uncertainty quantification using a Bayesian physics-informed neural network
JP Molnar, SJ Grauer
Measurement Science and Technology 33 (6), 065305, 2022
332022
Age of information for queues in tandem
C Kam, JP Molnar, S Kompella
MILCOM 2018-2018 IEEE Military Communications Conference (MILCOM), 1-6, 2018
282018
Physics-Informed Background-Oriented Schlieren of Turbulent Underexpanded Jets
JP Molnar, SJ Grauer, O Léon, D Donjat, F Nicolas
AIAA SCITECH 2023 Forum, 2441, 2023
82023
Reconstructing Hypersonic Flow Over a Bluff Body from Experimental Background-Oriented Schlieren Data
JP Molnar, EJ LaLonde, CS Combs, SJ Grauer
AIAA SCITECH 2024 Forum, 2493, 2024
22024
Forward and inverse modeling of depth-of-field effects in background-oriented schlieren
JP Molnar, EJ LaLonde, CS Combs, O Léon, D Donjat, SJ Grauer
arXiv preprint arXiv:2402.15954, 2024
2024
Time-resolved WMS tomography with velocimetry for high-enthalpy flows
JP Molnar, S Grauer, J France, B Ochs, J Donbar
Bulletin of the American Physical Society, 2023
2023
Aggregate Loss Data Assimilation (ALDA) for Supersonic BOS
A Singh, JP Molnar, S Grauer, GS Sidharth
Bulletin of the American Physical Society 67, 2022
2022
Reconstructing Experimental Measurements of Supersonic Flow via Physics-Informed BOS
JP Molnar, S Grauer
Bulletin of the American Physical Society 67, 2022
2022
Physics-Informed Flow Field Tomography with UQ using a B-PINN
JP Molnar, S Grauer
APS Division of Fluid Dynamics Meeting Abstracts, P20. 007, 2021
2021
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