A5013533662- Theoretical and Computational Physics
- Gas Dynamics and Kinetic Theory
- Advanced Thermodynamics and Statistical Mechanics
- Fluid Dynamics and Turbulent Flows
- Lattice Boltzmann Simulation Studies
- Gene Regulatory Network Analysis
- Machine Learning in Materials Science
- Probabilistic and Robust Engineering Design
- Stochastic processes and statistical mechanics
- Markov Chains and Monte Carlo Methods
- Material Dynamics and Properties
- Scientific Computing and Data Management
- Bioinformatics and Genomic Networks
- Microbial Metabolic Engineering and Bioproduction
- Gaussian Processes and Bayesian Inference
- Big Data and Business Intelligence
- Machine Learning and Algorithms
- Nonlinear Dynamics and Pattern Formation
- Advanced Multi-Objective Optimization Algorithms
- Phase Equilibria and Thermodynamics
- Manufacturing Process and Optimization
- Meteorological Phenomena and Simulations
- Fault Detection and Control Systems
- Statistical Mechanics and Entropy
- Computational Drug Discovery Methods
National Taiwan University of Science and Technology
2024
Argonne National Laboratory
2022-2024
Brookhaven National Laboratory
2019-2023
Park University
2022
Binus University
2022
Lawrence Berkeley National Laboratory
2022
University of Washington
2022
Los Alamos National Laboratory
2005-2021
Rutgers Sexual and Reproductive Health and Rights
2011
Lawrence Livermore National Laboratory
1994-2008
We introduce a lattice Boltzmann computational scheme capable of modeling thermohydrodynamic flows monatomic gases. The parallel nature this approach provides numerically efficient alternative to traditional methods fluid dynamics. uses small number discrete velocity states and linear, single-time relaxation collision operator. Numerical simulations in two dimensions agree well with exact solutions for adiabatic sound propagation Couette flow heat transfer.
Numerical simulation of the hydrodynamics gas flow and fluid is described using Direct Simulation Monte Carlo method. (AIP) © 1997 American Institute Physics.
Using the Green–Kubo theory, dependence of viscosity and thermal conductivity on cell size is obtained explicitly for stochastic particle methods such as direct simulation Monte Carlo (DSMC) its generalization, consistent Boltzmann algorithm (CBA). These analytical results confirm empirical observations that significant errors occur when dimensions are larger than a mean free path.
As noted in Wikipedia, skin the game refers to having ‘incurred risk by being involved achieving a goal’, where ‘ is synecdoche for person involved, and metaphor actions on field of play under discussion’. For exascale applications development US Department Energy Exascale Computing Project, nothing could be more apt, with delivering comprehensive science-based computational that effectively exploit high-performance computing technologies provide breakthrough modelling simulation data...
The direct simulation Monte Carlo (DSMC) scheme is used to study the gas flow under a read/write head positioned nanometers above moving disk drive platter (the slider bearing problem). In most cases, impressive agreement found between particle-based and numerical solutions of continuum hydrodynamic Reynolds equation which has been corrected for slip. However, at very high speeds far from equilibrium, load capacity cannot be accurately computed pressure.
We formulate a lattice Boltzmann model which simulates compressible fluids. By choosing the parameters of equilibrium distribution appropriately, we are able to select sound speed (which may be set arbitrarily low), bulk viscosity, and kinematic viscosity. This flows can include shocks. With proper rescaling zero-sound speed, this Burgers's equation. The viscosity determined by Chapman-Enskog expansion compares well with that measured from simulations. also compare exact solutions equation...
We examine the effects of hydrodynamics on late-stage kinetics in spinodal decomposition. From computer simulations a lattice Boltzmann scheme we observe, for critical quenches, that single-phase domains grow asymptotically like ${\mathit{t}}^{\mathrm{\ensuremath{\alpha}}}$, with \ensuremath{\alpha}\ensuremath{\approxeq}0.66 two dimensions and \ensuremath{\alpha}\ensuremath{\approxeq}1.0 three dimensions, both excellent agreement theoretical predictions.
The direct simulation Monte Carlo method for the Boltzmann equation is modified by an additional displacement in advection process and enhanced collision rate order to obtain exact hard sphere of state at all densities. This leads consistent thermodynamic transport properties low density (Boltzmann) regime. At higher densities are comparable predictions Enskog model. algorithm faster than molecular dynamics moderate readily run on a parallel architecture.
Molecular design based on generative models, such as variational autoencoders (VAEs), has become increasingly popular in recent years due to its efficiency for exploring high-dimensional molecular space identify molecules with desired properties. While the efficacy of initial model strongly depends training data, sampling suggesting novel enhanced properties can be further via latent optimization (LSO). In this paper, we propose a multi-objective LSO method that significantly enhance...
Using a Langevin description of spinodal decomposition in fluids, we examine domain growth the diffusive, viscous, and inertial regimes. In framework this model, numerical results corroborate earlier theoretical predictions based on scaling arguments dimensional analysis. \textcopyright{} 1996 The American Physical Society.
The effects of hydrodynamics on domain growth and scaling in a two-dimensional binary fluid are studied. Using Langevin model for the fluid, we find narrow range value fluid--order-parameter coupling below which domains grow asymptotically as ${t}^{1/3}$ (Lifshitz-Slyozov) above they ${t}^{0.46\ifmmode\pm\else\textpm\fi{}.02}$ ${t}^{0.72\ifmmode\pm\else\textpm\fi{}.02}$ off-critical critical quenches, respectively. small $x$ behavior scaled structure function varies this coupling.
A method for data assimilation currently being developed is the ensemble Kalman filter. This evolves statistics of system by computing an empirical sample realizations and incorporates measurements a linear interpolation between observations predictions. However, such only justified dynamics Gaussian statistics, it known to produce erroneous results nonlinear with far-from-Gaussian statistics. For example, filter method, when used in models multimodal fails track state transitions correctly....
This introduction to the special issue on big data discusses significant scientific opportunities offered by massive amounts of data, along with some directions for future research.
A key element of materials discovery and design is to learn from available data prior knowledge guide the next experiments or calculations in order focus on with targeted properties. We suggest that tight coupling feedback between experiments, theory informatics demands a codesign approach, very reminiscent computational involving software hardware computer science. This requires dealing constrained optimization problem which uncertainties are used adaptively explore exploit predictions...
We derive robust linear filtering and experimental design for systems governed by stochastic differential equations (SDEs) under model uncertainty. Given a of signal observation processes, an optimal filter is found solving the Wiener-Hopf equation; with uncertainty, it desirable to corresponding filter. This article assumes that physical process modeled via SDE system unknown parameters; signals are degraded blurring additive noise. Due time-dependent stochasticity in systems,...
We investigate the thermal equilibrium properties of kinks in a classical ${\mathrm{\ensuremath{\Phi}}}^{4}$ field theory 1+1 dimensions. From large-scale Langevin simulations we identify temperature below which dilute-gas description is valid. The standard or WKB shown to be remarkably accurate this temperature. At higher ``intermediate'' temperatures, where still exist, breaks down. By introducing double-Gaussian variational ansatz for eigenfunctions statistical transfer operator system,...
We demonstrate the utility of a Rayleigh-Ritz scheme recently proposed to compute nonequilibrium effective potential nonperturbatively in strong noise regime far from equilibrium. A simple Kramers model an ionic conductor is used illustrate efficiency method.
Radiation exposure poses a significant threat to human health. Emerging research indicates that even low-dose radiation once believed be safe, may have harmful effects. This perception has spurred growing interest in investigating the potential risks associated with across various scenarios. To comprehensively explore health consequences of radiation, our study employs robust statistical framework examines whether specific groups genes, belonging known pathways, exhibit coordinated...