Related papers: Physics-informed Data-driven Cavitation Model for …
NICER has enabled mass-radius inferences for pulsars using pulse profile modeling (PPM), providing constraints on the equation of state (EOS) of cold, dense matter. To date, PPM and EOS inference have been carried out as two separate steps,…
An alternative to the well-known complete form of the Mie-Gr\"uneisen equation of state (EOS) for water is suggested. A closed analytical description of the self-consistent EOS for an arbitrary medium based only on the first law of…
We investigate the role of hybrid and nucleonic equations of state (EOSs) within neutron star (NS) interiors using Bayesian inference to evaluate their alignment with recent observational data from NICER and LIGO-Virgo (LV) collaborations.…
We establish a high-resolution, high-performance, and high-confidence compressible multiphysics system in a Cartesian grid with irregular boundary topologies to simulate intensive blast waves propagating in large-scale and extremely complex…
The well-known Carnahan-Starling (CS) equation of state (EoS) [1] for the hard sphere (HS) fluid was derived from a quadratic relation between the integer portions of the virial coefficients, Bn, and their orders, n. Here we extend the…
Equation of state (EOS) describes the thermodynamic properties of substances. It has important applications in many fields such as power mechanics, geophysics, astrophysics, and detonation physics. Currently, most EOSs have been constructed…
We demonstrate that embedding physics-driven constraints into machine learning process can dramatically improve accuracy and generalizability of the resulting model. Physics-informed learning is illustrated on the example of analysis of…
Physics Informed Neural Networks offer a mesh free framework for solving PDEs but are highly sensitive to loss weight selection. We propose two dimensional analysis based weighting schemes, one based on quantifiable terms, and another also…
The equation of state (EOS) embodies thermodynamic properties of compressible fluid materials and usually has very complicated forms in real engineering applications, subject to the physical requirements of thermodynamics. The complexity of…
With ongoing advancements in nuclear theory and experimentation, together with a growing body of neutron star (NS) observations, a wealth of information on the equation of state (EOS) for matter at extreme densities has become accessible.…
Accurate characterization of subsurface heterogeneity is challenging but essential for applications such as reservoir pressure management, geothermal energy extraction and CO$_2$, H$_2$, and wastewater injection operations. This challenge…
A continuum description is essential for understanding a variety of collective phenomena in active matter. However, building quantitative continuum models of active matter from first principles can be extremely challenging due to both the…
Equations of state (EOS) calculated from a computationally efficient atom-in-jellium treatment of the electronic structure have recently been shown to be consistent with more rigorous path integral Monte Carlo (PIMC) and quantum molecular…
We utilize the now substantial amount of astrophysical observations of neutron stars (NSs), along with perturbative quantum chromodynamics (pQCD) calculations at high density, to directly constrain the NS equation of state (EOS). To this…
Different equations of state (EOS) have been used to study pressure as a function of volume compressions at a given temperature. The critical test of EOS' for solids under low compressions (<10GPa) by evaluating the pressure-volume…
In this work, an innovative data-driven moving horizon state estimation is proposed for model dynamic-unknown systems based on Bayesian optimization. As long as the measurement data is received, a locally linear dynamics model can be…
Based on the survey of the literatures on the new improvements on the equation of state (EOS) for the hard sphere fluids, we here compare lots of different EOSs and present a very accurate equation of state for this kind of fluids. The new…
A novel data-driven constitutive modeling approach is proposed, which combines the physics-informed nature of modeling based on continuum thermodynamics with the benefits of machine learning. This approach is demonstrated on…
This paper deals with the analytic derivation of a complete equation of state (EOS) for solids from shock-wave data in the range of pressures and temperatures, attained by detonation of chemical explosives. The caloric, the thermal and the…
Optimal experimental design (OED) is a framework that leverages a mathematical model of the experiment to identify optimal conditions for conducting the experiment. Under a Bayesian approach, the design objective function is typically…