A5056104910- Cavitation Phenomena in Pumps
- Computational Fluid Dynamics and Aerodynamics
- Blood properties and coagulation
- Ultrasound and Cavitation Phenomena
- Rheology and Fluid Dynamics Studies
- Fluid Dynamics and Mixing
- Gas Dynamics and Kinetic Theory
- Model Reduction and Neural Networks
- Parallel Computing and Optimization Techniques
- Lattice Boltzmann Simulation Studies
- Fluid Dynamics Simulations and Interactions
- Advanced Data Storage Technologies
- Platelet Disorders and Treatments
- Fluid Dynamics and Heat Transfer
- Quantum Computing Algorithms and Architecture
- Underwater Acoustics Research
- Fluid Dynamics and Turbulent Flows
- Advanced Numerical Methods in Computational Mathematics
- Spectroscopy and Quantum Chemical Studies
- Coagulation and Flocculation Studies
- Electrostatics and Colloid Interactions
- Distributed and Parallel Computing Systems
- Innovative Microfluidic and Catalytic Techniques Innovation
- Combustion and Detonation Processes
- Underwater Vehicles and Communication Systems
Georgia Institute of Technology
2022-2025
University of Illinois Urbana-Champaign
2015-2022
Nvidia (United States)
2022
Institute of Technology of Cambodia
2022
University of Basel
2022
Swisscom (Switzerland)
2022
CSCS - Swiss National Supercomputing Centre
2022
Sandia National Laboratories
2022
Helmholtz-Zentrum Dresden-Rossendorf
2022
University of Delaware
2022
A weakly conducting liquid droplet immersed in another leaky dielectric can exhibit rich dynamical behaviors under the effect of an applied electric field. Depending on material properties and field strength, nonlinear coupling interfacial charge transport fluid flow trigger electrohydrodynamic instabilities that lead to shape deformations complex dynamics. We present a spectral boundary integral method simulate electrohydrodynamics uniform All physical variables, such as drop density, are...
Partial differential equation solvers are required to solve the Navier-Stokes equations for fluid flow. Recently, algorithms have been proposed simulate dynamics on quantum computers. Fault-tolerant devices might enable exponential speedups over classical However, current and upcoming hardware presents noise in computations, requiring that make modest use of resources: shallower circuit depths fewer qubits. Variational more appropriate robust under resource restrictions. This work a hybrid...
Fluid flow simulations marshal our most powerful computational resources. In many cases, even this is not enough. Quantum computers provide an opportunity to speed up traditional algorithms for simulations. We show that lattice-based mesoscale numerical methods can be executed as efficient quantum due their statistical features. This approach revises a algorithm lattice gas automata reduce classical computations and state preparation at every time step. For this, the approximates qubit...
Abstract
Computational fluid dynamics (CFD) simulations often entail a large computational burden on classical computers. At present, these can require up to trillions of grid points and millions time steps. To reduce costs, novel architectures like quantum computers may be intrinsically more efficient at the appropriate computation. Current algorithms for solving CFD problems use single circuit and, in some cases, lattice-based methods. We introduce multiple circuits algorithm that makes lattice...
Highly confined capsules---most notably red blood cells---are observed to flow in a seemingly stable train. However, with less confinement this striking order is disrupted, and the train breaks apart into an apparently chaotic flow. Non-modal stability analysis of model capsule illuminates mechanisms break-up.
Neural networks can be trained to solve partial differential equations (PDEs) by using the PDE residual as loss function. This strategy is called "physics-informed neural networks" (PINNs), but it currently cannot produce high-accuracy solutions, typically attaining about $0.1\%$ relative error. We present an adversarial approach that overcomes this limitation, which we call competitive PINNs (CPINNs). CPINNs train a discriminator rewarded for predicting mistakes PINN makes. The and...
Solving the population balance equation (PBE) for dynamics of a dispersed phase coupled to continuous fluid is expensive. Still, one can reduce cost by representing evolving particle density function in terms its moments. In particular, quadrature-based moment methods (QBMMs) invert these moments with quadrature rule, approximating required statistics. QBMMs have been shown accurately model sprays and soot relatively compact set However, significantly non-Gaussian processes such as bubble...
Flowing trains of red blood cells are stable when tightly confined but can otherwise break down into an irregular flow. A linear stability formulation is developed to analyze this biological phenomena, advancing understanding its origin and guiding the design devices that process cells.
This paper assesses and reports the experience of ten teams working to port, validate, benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The consists eight NVIDIA HPC Developer Kit systems, each one equipped with server-class CPU from Ampere two data center GPUs Corp. systems are connected together using InfiniBand interconnect. selected mini-apps written programming languages use multiple accelerator-based models for such as CUDA,...
QBMMlib is an open source Mathematica package of quadrature-based moment methods and their algorithms. Such are commonly used to solve fully-coupled disperse flow combustion problems, though formulating closing the corresponding governing equations can be complex. aims make analyzing these techniques simple more accessible. Its routines use symbolic manipulation formulate transport for a population balance equation prescribed dynamical system. However, resulting unclosed. trades moments set...
Humpback whales can generate intricate bubbly regions, called bubble nets, via blowholes. appear to exploit these nets for feeding loud vocalizations. A fully-coupled phase-averaging approach is used model the flow, dynamics, and corresponding acoustics. previously hypothesized waveguiding mechanism assessed varying acoustic frequencies net void fractions. Reflections within region result in observable only a small range of flow parameters. configuration multiple surrounding vocalizing...
Fluid flow simulations marshal our most powerful computational resources. In many cases, even this is not enough. Quantum computers provide an opportunity to speedup traditional algorithms for simulations. We show that lattice-based mesoscale numerical methods can be executed as efficient quantum due their statistical features. This approach revises a algorithm lattice gas automata eliminate classical computations and measurements at every time step. For this, the approximates qubit relative...