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At least 1,693 records · Page 94

Accelerating Multiphase Simulations With Denoising Diffusion Model Driven Initializations

This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics‐based simulations, aiming at reducing the computational costs of flow simulations while still honoring all the physical properties of interest. Pore‐scale simulations enhance our understanding of applications such as assessing hydrogen and storage efficiency in underground reservoirs. Nevertheless, they are computationally expensive and the presence of non‐unique solutions can require multiple simulations within a single geometry. To overcome the computational cost hurdle, we propose a method that couples generative diffusion models and physics‐based simulations. While training the data‐driven model, we simultaneously generate initial conditions and perform physics‐based simulations using these. This integrated approach enables us to receive real‐time feedback on a single compute node equipped with both CPUs and GPUs. By efficiently managing these processes within a single compute node, we can continuously monitor performance and halt training once the model meets the specified criteria. To test our model, we generate realizations in a real Berea sandstone fracture which shows that our technique is up to 4.4 times faster than commonly used flow simulation initializations.

36 MATERIALS SCIENCE↗

Numerical study of fluid motion in bioreactor with two mixers

Numerical study of hydrodynamic laminar behavior of a viscous fluid in bioreactor with multiple mixers is provided in the present paper. The reactor is equipped with two disk impellers. The fluid motion is studied in stream function-vorticity formulation. The calculations are made by a computer program, written in MATLAB. The fluid structure is described and numerical results are graphically presented and commented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Time evolution of ML-MCTDH wavefunctions. II. Application of the projector splitting integrator

The multi-layer multi-configuration time-dependent Hartree (ML-MCTDH) approach can suffer from numerical instabilities whenever the wavefunction is weakly entangled. These instabilities arise from singularities in the equations of motion (EOMs) and necessitate the use of regularization of the EOMs. The Projector Splitting Integrator (PSI) has previously been presented as an approach for evolving ML-MCTDH wavefunctions that is free of singularities. Here, we will discuss the implementation of the multi-layer PSI with a particular focus on how the steps required relate to those required to implement standard ML-MCTDH. We demonstrate the efficiency and stability of the PSI for large ML-MCTDH wavefunctions containing up to hundreds of thousands of nodes by considering a series of spin-boson models with up to 106 bath modes and find that for these problems, the PSI requires roughly 3–4 orders of magnitude fewer Hamiltonian evaluations and 2–3 orders of magnitude fewer Hamiltonian applications than standard ML-MCTDH and 2–3/1–2 orders of magnitude fewer evaluations/applications than approaches that use improved regularization schemes. Finally, we consider a series of significantly more challenging multi-spin-boson models that require much larger numbers of single-particle functions with wavefunctions containing up to ~1.3×10 9 parameters to obtain accurate dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven Quasi-static Surrogate Model for Nuclear-powered Integrated Energy Systems

The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), energy manifold (EM), balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational overhead and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The findings shed light on the accuracy and applicability of the surrogate models in practical scenarios, demonstrating their potential to expedite the analysis of nuclear-powered IES and inform future research and development efforts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Simulation of Motion of H{sub 2} and D{sub 2} Molecules in Sextupole Magnets

We simulate the motion of hydrogen and deuterium molecules in the magnetic system of a setup intended for obtaining nuclear-spin-polarized molecules. Spatial separation of molecules with different magnetic moment projections by the spin filtration method in a nonuniform magnetic field is performed using superconducting sextupole magnets. Calculations are carried out for a magnetic field induction of 3.7 T at the poles and a nozzle temperature of 7 K. Simulation show that the ratio of polarized flux of hydrogen molecules to the detector to the total flux from the source nozzle is 2.3 × 10{sup –6}, nuclear polarization being close to 100%. Calculations performed for deuterium reveal that this ratio is 7 times smaller due to the smallness of the magnetic moment relative to hydrogen molecules. Trajectories of molecules in the magnetic system and their spatial distribution are represented graphically. Mathematical aspects of the algorithm of the computer program developed for this purpose are considered.

74 ATOMIC AND MOLECULAR PHYSICS↗

Cyber–Physical System Security of Distribution Systems

The Information and Communications Technology (ICT) for control and monitoring of power systems is a layer on top of the physical power system infrastructure. The cyber system and physical power system components form a tightly coupled Cyber–Physical System (CPS). Sources of vulnerabilities arise from the computing and communication systems of the cyber–power grid. Cyber intrusions targeting the power grid are serious threats to the reliability of electricity supply that is critical to society and the economy. In a typical Information Technology environment, numerous attack scenarios have shown how unauthorized users can access and manipulate protected information from a network domain. The need for cyber security has led to industry standards that power grids must meet to ensure that the monitoring, operation, and control functions are not disrupted by cyber intrusions. Cyber security technologies such as encryption and authentication have been deployed on the CPS. Intrusion or anomaly detection and mitigation tools developed for power grids are emerging. Furthermore, this survey paper provides the basic concepts of cyber vulnerabilities of distribution systems and CPS security. The important ICT subjects for distribution systems covered in this paper include Supervisory Control And Data Acquisition, Distributed Energy Resources, including renewable energy and smart meters.

97 MATHEMATICS AND COMPUTING↗

Dynamics of Nuclear Regions of Galaxies

Current research carried out with the help of the ASEE-NASA Summer Faculty Program, at NASA-Ames, is concentrated on the dynamics of nuclear regions of galaxies. From a dynamical point of view a galaxy is a collection of around 10(sup 11) stars like our Sun, each of which moves in the summed gravitational field of all the remaining stars. Thus galaxy dynamics becomes a self-consistent n-body problem with forces given by Newtonian gravitation. Strong nonlinearity in the gravitational force and the inherent nonlinearity of self-consistent problems both argue for a numerical approach. The technique of numerical experiments consis of constructing an environment in the computer that is as close as possible to the physical conditions in a real galaxy and then carrying out experiments much like laboratory experiments in physics or engineering, in this environment. Computationally, an experiment is an initial value problem, and a good deal of thought and effort goes into the design of the starting conditions that serve as initial values. Experiments are run at Ames because all the 'equipment' is in place-the programs, the necessary computational power, and good facilities for post-run analysis. Our goal for this research program is to study the nuclear regions in detail and this means replacing most of the galaxy by a suitable boundary condition to allow the full capability of numerical experiments to be brought to bear on a small region perhaps 1/1000 of the linear dimensions of an entire galaxy. This is an extremely delicate numerical problem, one in which some small feature overlook, can easily lead to a collapse or blow-up of the entire system. All particles attract each other in gravitational problems, and the 1/r(sup 2) force is: (1) nonlinear; (2) strong at short range; (3) long-range, and (4) unscreened at any distance.

Miller, Richard H.↗

Data-driven Quasi-static Surrogate Models for Nuclear-powered Integrated Energy Systems

The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), steam manifold, balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational resource and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The exceptional performance, with low root-mean-squared errors and R-squared scores of at least 99.8% across all individual surrogate models, underscores their accuracy and practical applicability. These results demonstrate the potential of these models to expedite the analysis of nuclear-powered IES, offering insights that can shape future research and development efforts.

08 HYDROGEN↗

Computing properties of hadrons, nuclei and nuclear matter from quantum chromodynamics

The goal of the research of the William and Mary group (PI from Computer Science and Co-PI from Physics) is to develop algorithms that address the limitations in computational scalability of current methods in lattice QCD. Of particular interest is the problem of computing traces of certain functions of a matrix, which arises in nuclear physics calculations of disconnected diagrams and requires the solution of a large number of linear systems of equations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Accurate real space iterative reconstruction (RESIRE) algorithm for tomography

Tomography has made a revolutionary impact on the physical, biological and medical sciences. The mathematical foundation of tomography is to reconstruct a three-dimensional (3D) object from a set of two-dimensional (2D) projections. As the number of projections that can be measured from a sample is usually limited by the tolerable radiation dose and/or the geometric constraint on the tilt range, a main challenge in tomography is to achieve the best possible 3D reconstruction from a limited number of projections with noise. Over the years, a number of tomographic reconstruction methods have been developed including direct inversion, real-space, and Fourier-based iterative algorithms. Here, we report the development of a real-space iterative reconstruction (RESIRE) algorithm for accurate tomographic reconstruction. RESIRE iterates between the update of a reconstructed 3D object and the measured projections using a forward and back projection step. The forward projection step is implemented by the Fourier slice theorem or the Radon transform, and the back projection step by a linear transformation. Our numerical and experimental results demonstrate that RESIRE performs more accurate 3D reconstructions than other existing tomographic algorithms, when there are a limited number of projections with noise. Furthermore, RESIRE can be used to reconstruct the 3D structure of extended objects as demonstrated by the determination of the 3D atomic structure of an amorphous Ta thin film. We expect that RESIRE can be widely employed in the tomography applications in different fields. Finally, to make the method accessible to the general user community, the MATLAB source code of RESIRE and all the simulated and experimental data are available at https://zenodo.org/record/7273314.

97 MATHEMATICS AND COMPUTING↗

SDA: a symbolic differential algebra package in C++

Truncated Power Series Algebra (TPSA), or Differential Algebra (DA), is a well-established tool in accelerator physics, commonly used for generating high-order maps of dynamic systems, as well as in symplectic tracking, normal form analysis, verified integration, optimization, and fast multipole methods. This package is the first to perform symbolic DA computations, enabling traceability of initial condition contributions and runtime reduction for repeated DA calculations, potentially expanding DA’s applications.

97 MATHEMATICS AND COMPUTING↗

Center for Momentum Transport and Flow Organization (CMTFO) (Final Technical Report)

The Center for Momentum Transport and Flow Organization (CMTFO) is a DOE Plasma Science Center formed in late 2009 to focus on the general principles underlying momentum transport in magnetic fusion and astrophysical systems. It is composed of funded researchers from UCSD, UW Madison, U. Colorado, PPPL. As of 2011, UCSD supported postdocs are collaborating at MIT/Columbia and UC Santa Cruz and beginning in 2012, will also be based at PPPL. In the initial startup period, the Center supported the construction of two basic experiments at PPPL and UW Madison to focus on accretion disk hydrodynamic instabilities and solar physics issues. We now have computational efforts underway focused on understanding recent experimental tests of dynamos, solar tachocline physics, intrinsic rotation in tokamak plasmas and L-H transition physics in tokamak devices. In addition, we have the basic experiments discussed above complemented by work on a basic linear plasma device at UCSD and a collaboration at the LAPD located at UCLA. We are also performing experiments on intrinsic rotation and L-H transition physics in the DIII-D, NSTX, C-Mod, HBT EP, HL-2A, and EAST tokamaks in the US and China, and expect to begin collaborations on K-STAR in the coming year. Center funds provide support to over 10 postdocs and graduate students each year, who work with 8 senior faculty and researchers at their respective institutions. The Center has sponsored a mini-conference at the APS DPP 2010 meeting, and co-sponsored the recent Festival de Theorie (2011) with the CEA in Cadarache, and will co-sponsor a Winter School in January 2012 in collaboration with the CMSO-UW Madison. Center researchers have published over 50 papers in the peer reviewed literature, and given over 10 talks at major international meetings. In addition, the Center co-PI, Professor Patrick Diamond, shared the 2011 Alfven Prize at the EPS meeting. Key scientific results from this startup period include initial simulations of the effects of boundary conditions on turbulent dynamo experiments; simulations of intrinsic rotation showing the strong link between toroidal rotation and temperature gradients and elucidation of the turbulence symmetry breaking mechanisms that lead to this macroscopic behavior; first experiments in a large tokamak testing the roll of turbulent momentum transport in driving intrinsic rotation; experiments in tokamaks showing strong evidence that zonal flows, together with the more widely recognized mean sheared ExB flow, act to trigger the L-H transition in tokamak devices and the first experimental measurement of collisional viscosity in an unmagnetized plasma. In the coming three year period, we will continue these efforts by a combination of basic hydrodynamic, liquid metal and plasma experiments combined with experiments on numerous tokamak devices around the world. In addition, we will use MHD, gyrofluid and gyrokinetic codes combined with theory to address the problems of interest to the Center.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Center for Momentum Transport and Flow Organization (CMTFO) (Final Technical Report)

The Center for Momentum Transport and Flow Organization (CMTFO) is a DOE Plasma Science Center formed in late 2009 to focus on the general principles underlying momentum transport in magnetic fusion and astrophysical systems. It is composed of funded researchers from UCSD, UW Madison, U. Colorado, PPPL. As of 2011, UCSD supported postdocs are collaborating at MIT/Columbia and UC Santa Cruz and beginning in 2012, will also be based at PPPL. In the initial startup period, the Center supported the construction of two basic experiments at PPPL and UW Madison to focus on accretion disk hydrodynamic instabilities and solar physics issues. We now have computational efforts underway focused on understanding recent experimental tests of dynamos, solar tacholine physics, intrinsic rotation in tokamak plasmas and L-H transition physics in tokamak devices. In addition, we have the basic experiments discussed above complemented by work on a basic linear plasma device at UCSD and a collaboration at the LAPD located at UCLA. We are also performing experiments on intrinsic rotation and L-H transition physics in the DIII-D, NSTX, C-Mod, HBT EP, HL-2A, and EAST tokamaks in the US and China, and expect to begin collaborations on K-STAR in the coming year. Center funds provide support to over 10 postdocs and graduate students each year, who work with 8 senior faculty and researchers at their respective institutions. The Center has sponsored a mini-conference at the APS DPP 2010 meeting, and co-sponsored the recent Festival de Theorie (2011) with the CEA in Cadarache, and will co-sponsor a Winter School in January 2012 in collaboration with the CMSO-UW Madison. Center researchers have published over 50 papers in the peer reviewed literature, and given over 10 talks at major international meetings. In addition, the Center co-PI, Professor Patrick Diamond, shared the 2011 Alfven Prize at the EPS meeting. Key scientific results from this startup period include initial simulations of the effects of boundary conditions on turbulent dynamo experiments; simulations of intrinsic rotation showing the strong link between toroidal rotation and temperature gradients and elucidation of the turbulence symmetry breaking mechanisms that lead to this macroscopic behavior; first experiments in a large tokamak testing the roll of turbulent momentum transport in driving intrinsic rotation; experiments in tokamaks showing strong evidence that zonal flows, together with the more widely recognized mean sheared ExB flow, act to trigger the L-H transition in tokamak devices and the first experimental measurement of collisional viscosity in an unmagnetized plasma. In the coming three year period, we will continue these efforts by a combination of basic hydrodynamic, liquid metal and plasma experiments combined with experiments on numerous tokamak devices around the world. In addition, we will use MHD, gyrofluid and gyrokinetic codes combined with theory to address the problems of interest to the Center.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Unsteady airloads due to separated flow on airfoils and wings

Experimental and computational studies of airloads due to separated flows over airfoils and wings conducted at the NASA Langley Research Center are surveyed. Results are presented for cases involving local flow separation such as shock-induced separation, for the initiation of leading-edge vortex flows, and for cases involving unsteady airloads due to flows separating over remote aircraft components. Good correlation is obtained between experiment and computation for cases of locally separating flow and steady computations of vortex flow over delta wings and complex forebody geometries are shown. Physical flow modeling issues and computational requirements for the case of vertical tail buffeting are developed.

Edwards, John W.↗

Unsteady airloads due to separated flow on airfoils and wings

Experimental and computational studies of airloads due to separated flows over airfoils and wings conducted at the NASA Langley Research Center are surveyed. Results are presented for cases involving local flow separation such as shock-induced separation, for the initiation of leading-edge vortex flows, and for cases involving unsteady airloads due to flows separating over remote aircraft components. Good correlation is obtained between experiment and computation for cases of locally separating flow and steady computations of vortex flow over delta wings and complex forebody geometries are shown. Physical flow modeling issues and computational requirements for the case of vertical tail buffeting are developed.

Edwards, John W.↗

An Integrated Approach to Scaling Task-Based Runtime Systems for Next Generation Engineering problems

The need to scale next-generation industrial engineering problems to the largest computational platforms presents unique challenges. Such problems may have complex coupled multi-physics models, as well as computationally and communication intensive algorithms not often seen in standard academic problems, while also needing high-demand I/O for analysis purposes. In such cases even codes with good existing scaling properties may need significant changes, addressed in a cross-cutting way to solve such problems at extreme scales. These challenges relate to system components that were not previously problematic on less complex problems and/or at smaller computational scales. This paper illustrates these challenges for Uintah, a highly scalable asynchronous many-task runtime system being applied to the modeling of a 1000 MWe ultra-supercritical coal boiler. In order to model this formidable, production engineering problem, not only was an integrated approach needed that built upon existing scalable components in areas such as complex stencil calculations and linear algebra, but the significant challenges of high demand I/O, complex task graphs, and infrastructure inefficiencies also had to be addressed. This integrated approach allowed this problem to run on 256K CPU cores on Mira, with good weak scaling to 512K CPU cores and similar strong scaling, except for radiation. The need for strong scaling of a new ray tracing-based radiation model required substantial Uintah infrastructure improvements before 119K CPU cores and 7.5K GPUs on Titan could be used, with scaling out to 256K CPU cores and 16K GPUs. The resulting code demonstrates not only excellent overall scalability but a significant improvement in overall performance for the full-scale, production boiler problem.

97 MATHEMATICS AND COMPUTING↗