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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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DIANA, a digital-analog simulation program for IBM 1620 2 computer, simulates physical systems by solving the simultaneous differential equations describing the systems. It expands and optimizes the input-output capabilities, permits additional flexibility in midstream program alternation, and minimizes the computational time.
In this study, we demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.
This presentation provides an overview of the work and accomplishments in cyber-physical simulation of solid oxide cell hybrid systems, which is funded by the SOFC FWP Task 5 (FWP-1022411).
The ExaStar project aims to deliver an efficient, versatile, and portable software ecosystem for multi-physics astrophysics simulations run on exascale machines. The code suite is a component-based multi-physics toolkit, built on the capabilities of current simulation codes (in particular Flash-X and Castro), and based on the massively parallel adaptive mesh refinement framework AMReX. It includes modules for hydrodynamics, advanced radiation transport, thermonuclear kinetics, and nuclear microphysics. The code will reach exascale efficiency by building upon current multi- and many-core packages integrated into an orchestration system that uses a combination of configuration tools, code translators, and a domain-specific asynchronous runtime to manage performance across a range of platform architectures. The target science includes multi-physics simulations of astrophysical explosions (such as supernovae and neutron star mergers) to understand the cosmic origin of the elements and the fundamental physics of matter and neutrinos under extreme conditions.
Ocean physics (currents, mixing, air-sea transfer of heat and gases) and biogeochemistry (carbon and oxygen cycles, ecosystem dynamics, nutrient distributions) are tightly coupled. We used the DOE-developed Energy Exascale Earth System Model (E3SM) to simulate physical and biogeochemical dynamics of the global ocean, with an emphasis on the western North Pacific. In particular, we used the grid refinement capability of E3SM’s ocean component (LANL-developed MPASOcean) to quantify the effect of model resolution on the carbon and oxygen cycles using a pair of century-long simulations that differ only in the western North Pacific grid. Regional grid refinement has a noticeable impact on biogeochemistry. Distribution of important nutrients (such as nitrate) changes the amount of photosynthesis by phytoplankton, which in turn affects air-sea transfer of CO2 and the local carbon cycle.
1. Kennedy Space Center (KSC) is developing a mobile launching system with autonomous propellant loading capabilities for liquid-fueled rockets. An autonomous system will be responsible for monitoring and controlling the storage, loading and transferring of cryogenic propellants. The Physics Simulation Software will reproduce the sensor data seen during the delivery of cryogenic fluids including valve positions, pressures, temperatures and flow rates. The simulator will provide insight into the functionality of the propellant systems and demonstrate the effects of potential faults. This will provide verification of the communications protocols and the autonomous system control. 2. The High Pressure Gas Facility (HPGF) stores and distributes hydrogen, nitrogen, helium and high pressure air. The hydrogen and nitrogen are stored in cryogenic liquid state. The cryogenic fluids pose several hazards to operators and the storage and transfer equipment. Constant monitoring of pressures, temperatures and flow rates are required in order to maintain the safety of personnel and equipment during the handling and storage of these commodities. The Gas House Autonomous System Monitoring software will be responsible for constantly observing and recording sensor data, identifying and predicting faults and relaying hazard and operational information to the operators.
To produce green hydrogen at scale and at low cost, the solid oxide electrolysis cell (SOEC) systems would be tied to renewable power sources (mainly solar and wind), leveraging zero-carbon electricity at low prices and even nearly free during overgeneration scenarios. However, due to the intermittency of renewable power generation, the SOEC system is subjected to rapid load transitions that occur not only in diurnal cycles but also in short timeframes (e.g., sub-minute). This can result in fast degradation and thus greatly reduce the SOEC’s lifetime. Our team at the National Energy Technology Laboratory has demonstrated that the anode air flow can have a crucial role in SOEC thermal management. Typically, a higher air flow rate can help to mitigate the local temperature gradient distortion during rapid load transitions. To move a large amount of air, the gas turbine (GT; i.e., compressor-turbine-generator set) has been regarded as the most mature and efficient technology. In this presentation, we show the configuration and preliminary results of an innovative SOEC-GT hybrid energy system in a cyber-physical simulation (CPS) approach.
The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended durations or under accident condition. As one of the most significant components of a Reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Ageing degradation mechanisms (e.g. thermo-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary.
With existing programming tools, writing high-performance simulation code is labor intensive and requires sacrificing readability and portability. Here, the alternative is to prototype simulations in a high-level language like Matlab, thereby sacrificing performance. The Matlab programming model naturally describes the behavior of an entire physical system using the language of linear algebra. However, simulations also manipulate individual geometric elements, which are best represented using linked data structures like meshes. Translating between the linked data structures and linear algebra comes at significant cost, both to the programmer and to the machine. High-performance implementations avoid the cost by rephrasing the computation in terms of linked or index data structures, leaving the code complicated and monolithic, often increasing its size by an order of magnitude. In this article, we present Simit, a new language for physical simulations that lets the programmer view the system both as a linked data structure in the form of a hypergraph and as a set of global vectors, matrices, and tensors depending on what is convenient at any given time. Simit provides a novel assembly construct that makes it conceptually easy and computationally efficient to move between the two abstractions. Using the information provided by the assembly construct, the compiler generates efficient in-place computation on the graph. We demonstrate that Simit is easy to use: a Simit program is typically shorter than a Matlab program; that it is high performance: a Simit program running sequentially on a CPU performs comparably to hand-optimized simulations; and that it is portable: Simit programs can be compiled for GPUs with no change to the program, delivering 4 to 20× speedups over our optimized CPU code.
Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pilot projects at intermediate scales are costly and time-consuming. An alternative, the pilot-scale model, relies on high-fidelity numerical simulations, but even these simulations can be computationally prohibitive at larger scales. To overcome these limitations, we propose a scalable, physics-constrained reduced order model (ROM) method. The ROM identifies critical physics modes from small-scale unit components, projecting governing equations onto these modes to create a reduced model that retains essential physics details. We also employ Discontinuous Galerkin Domain Decomposition (DG-DD) to apply ROM to unit components and interfaces, enabling the construction of large-scale global systems without data at such large scales. Here this method is demonstrated on the Poisson and Stokes flow equations, showing that it can solve equations about 15–40 times faster with only ~1% relative error. Furthermore, ROM takes one order of magnitude less memory than the full order model, enabling larger scale predictions at a given memory limitation.
Fluid flow inside a beam blank mold fed through a three-port SEN (two lateral ports and one bottom port), positioned at the center of the mold, has been investigated. Literature survey shows that this kind of configuration is not frequently used. It had been shown that it is possible to get a symmetrical flow with this configuration. The downward inclination of the ports should influence the transient fluid flow. The greater the downward inclination, the greater is the instability of the jet and of the interface between the immiscible fluids that simulate the slag/metal behavior. The flow characterization was made by dye dispersion, PIV technique, measurement of the meniscus oscillation using ultrasonic sensors, and CFD simulations. The slag/metal behavior was simulated using water and oils with different physical properties. The results from PIV as well as from observations of the water–oil interface have been used to validate the CFD simulations. Oils with density close to water resulted in more instability at the interface with entrainment starting from fluid flow rate of 125 L/min (equivalent to casting speed of 1 m/min). Decreasing the viscosity of slag (oils) and increasing the casting velocity (water flow rate) result in reduction of the interfacial stability.
To aid in design and licensing of molten salt reactors, a framework integrating the complex interaction of reactor neutronics, thermal hydraulics, and chemistry is being developed within the Department of Energy Advanced Reactor Technology Program’s Molten Salt Reactor (MSR) campaign. The challenges of integrating thermochemical and thermophysical behavior into a multi-physics reactor simulations include the following: (1) population of data needed for refinement of current models and development of nonexistent models through experimental measurements, first principles calculations, and development of a machine learning approach (2) thermochemical and thermophysical model development, (3) further development of Thermochimica, an open-source efficient equilibrium solver used to link thermochemical models to the multi-physics code, (4) a framework for integrating kinetic phenomena: nucleation, precipitation, mass/heat transport, and corrosion models, and (5) a computational environment to efficiently utilize the data and models within a multi-physics modeling tool. These challenges are being addressed through a collaboration among Oak Ridge National Laboratory, Argonne National Laboratory, the University of South Carolina, and the University of Ontario Institute of Technology.
GEOS is a simulation framework focused on solving tightly coupled multi-physics problems with an initial emphasis on subsurface reservoir applications. Currently, GEOS supports capabilities for studying carbon sequestration, geothermal energy, hydrogen storage, and related subsurface applications. The unique aspect of GEOS that differentiates it from existing reservoir simulators is the ability to simulate tightly coupled compositional flow, poromechanics, fault slip, fracture propagation, and thermal effects, etc. Extensive documentation is available on the GEOS documentation pages (GEOS Documentation, 2024). Note that GEOS, as presented here, is a complete rewrite of the previous incarnation of the GEOS referred to in (Settgast et al., 2017).
We present our SciDAC FASTMath-HEP partnership results for tuning generative adversarial models (GANs) for high energy physics applications. The GANs are used in hybrid simulations to accelerate otherwise time-consuming computations. We optimize for both, prediction accuracy and variability with the goal to find GAN architectures that are reliable and robust.
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The Grizzly code is being developed under the US Department of Energy’s Light Water Sustainability program as a tool to model aging mechanisms and their effects on the integrity of critical nuclear power plant components. An important application for Grizzly is the modeling of aging in concrete structures, which can be due to a number of mechanisms. Initial focus in this area has been on modeling expansive reactions due to alkali-silica reactions or radiation-induced volumetric expansion. Grizzly is an inherently multiphysics modeling platform that naturally permits including the effects of multiple coupled physics in a simulation. Models have been developed for transport of heat and moisture in concrete, and these have been coupled and used as inputs to models for expansive reactions. This paper summarizes this capability as well as work currently underway to couple it with mechanical deformation models that account for nonlinear constitutive behavior.
Modeling nonlinear effects of laser plasma instabilities (LPI) is critically important for ICF/HED experiments. Our project has the following goals: • Develop physics-based nonlinear LPI models using PIC simulations • Couple the nonlinear LPI effects to macroscopic modeling of ICF/HED exp. through laser ray-tracing (LRT).
This study evaluates reactor physics aspects of the proposed High Flux Isotope Reactor (HFIR) permanent beryllium reflector number 5 design. HFIR is a pressurized, light water–cooled, and beryllium reflected research reactor that operates at 85 MW for cycle lengths of approximately 24 to 26 days. A new permanent reflector design is highly desirable for increased versatility in irradiation experiments, to arrange the vertical experiment facilities (VXFs) to minimize their impact on neutron scattering if loaded with neutronabsorbing experiments, to enhance reflector thermal-structural-hydraulic performance, and to simplify the complex fabrication process. The current number 4 and concept number 5 reflectors have 22 and 28 VXFs, respectively, and are modeled and analyzed in this study with the MCNP5 and SCALE 6.1.3 nuclear simulation codes.