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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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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Rapid Load Transition for Integrated Solid Oxide Fuel Cell - Gas Turbine (SOFC-GT) Energy Systems: A Demonstration of the Potential for Grid Response

Rapid load transition is an essential requirement for integrated energy systems to maintain grid resilience as more renewable resources are added to the grid. Integrated solid oxide fuel cell - gas turbine (SOFC-GT) systems can provide high efficiency and low carbon emissions over a broad range of turndown. These hybrids also have the potential to enable rapid grid response. The challenge has been to demonstrate effective control strategies to manage load transitions. In the present study, a load transition of ~50% was achieved in 10 s using a novel but simple strategy. Power demand on the SOFC and the GT were ramped down concurrently. During this transition, the SOFC anode fuel was manipulated to maintain SOFC fuel utilization while the cathode inlet air flow and temperature were also manipulated to thermally protect the SOFC. This study was conducted using the Hybrid Performance (Hyper) facility at the National Energy Technology Laboratory (NETL) in a co-simulation environment with the Idaho National Laboratory (INL)'s grid-simulation. The load ramping strategy was tested using a hardware-based cyber-physical simulation methodology. The results demonstrate a high-fidelity representation of SOFC-GT hybrid dynamics and validation of the control strategy. Thermal and electrochemical transients indicated that the SOFC was well protected during rapid load turndown without violating operability constraints. This demonstration revealed the non-linear nature of tightly coupled SOFC-GT system components, especially the non-linear response of SOFC cathode air flow and inlet temperature controls. These results highlight the needs and challenges in developing adaptive automatic controls for autonomous rapid load transitions. This work demonstrates that SOFC-GT hybrids are a viable option to provide the fast-ramping characteristics essential to accommodate high levels of variable renewable power while maintaining grid resilience, reliability, and environmental performance. The results also demonstrate the utility of co-simulation in advancing the tightly-coupled integrated energy systems needed to meet goals for zero-carbon power generation.

DIRECT ENERGY CONVERSION,POWER TRANSMISSION AND DI↗
DOE OSTI2017

Subtle Effects of Aliphatic Alcohol Structure on Water Extraction and Solute Aggregation in Biphasic Water/ n -Dodecane

Organic phase aggregation behavior of 1-octanol and its structural isomer, 2-ethylhexanol, in a biphasic n-dodecane water system is studied with a combination of physical measurement, small-angle X-ray scattering (SAXS), and atomistic molecular dynamic simulations. Physical properties of the organic phases are probed following their mixing and equilibration with immiscible water phases. Studies reveal that the interfacial tension decreases as a function of increasing alcohol concentration over the solubility range of the alcohol with no evidence for a critical aggregate concentration (cac). An uptake of water into the organic phases is quantified, as a function of alcohol content, by Karl Fischer titrations. The extraction of water into dodecane was further assessed as a function of alcohol concentration via the slope-analysis method sometimes employed in chemical separations. This provides a qualitative understanding of solute (water/alcohol) aggregation in the organic phase. The physical results are supported by analyses of SAXS data that reveals an emergence of aggregates in n-dodecane at elevated alcohol concentrations. The observed aggregate structure is dependent on the alcohol tail group geometry, consistent with surfactant packing parameter. The formation of these aggregates is discussed at a molecular level, where alcohol-alcohol and alcohol-water H-bonding interactions likely dominate the occurrence and morphology of the aggregates.

Knight, Andrew W.↗
DOE OSTI2014

TU-C-17A-08: Improving IMRT Planning and Reducing Inter-Planner Variability Using the Stochastic Frontier Method: Validation Based On Clinical and Simulated Data

Purpose: Intensity modulated radiation therapy always requires compromises between PTV coverage and organs at risk (OAR) sparing. We previously developed metrics that correlate doses to OAR to specific patients’ morphology using stochastic frontier analysis (SFA). Here, we aim to examine the validity of this approach using a large set of realistically simulated dosimetric and geometric data. Methods: SFA describes a set of treatment plans as an asymmetric distribution with respect to a frontier defining optimal plans. Eighty head and neck IMRT plans were used to establish a metric predicting the mean dose to parotids as a function of simple geometric parameters. A database of 140 parotids was used as a basis distribution to simulate physically plausible data of geometry and dose. Distributions comprising between 20 and 5000 were simulated and the SFA was applied to obtain new frontiers, which were compared to the original frontier. Results: It was possible to simulate distributions consistent with the original dataset. Below 160 organs, the SFA could not always describe distributions as asymmetric: a few cases showed a Gaussian or half-Gaussian distribution. In order to converge to a stable solution, the number of organs in a distribution must ideally be above 100, but in many cases stable parameters could be achieved with as low as 60 samples of organ data. Mean RMS value of the error of new frontiers was significantly reduced when additional organs are used. Conclusion: The number of organs in a distribution showed to have an impact on the effectiveness of the model. It is always possible to obtain a frontier, but if the number of organs in the distribution is small (< 160), it may not represent de lowest dose achievable. These results will be used to determine number of cases necessary to adapt the model to other organs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SHARP Multiphysics Tutorials

SHARP, developed under the NEAMS Reactor Product Line, is an advanced modeling and simulation toolkit for the analysis of advanced nuclear reactors. SHARP is comprised of three physics modules currently including neutronics, thermal hydraulics, and structural mechanics. SHARP empowers designers to produce accurate results for modeling physical phenomena that have been identified as important for nuclear reactor analysis. SHARP can use existing physics codes and take advantage of existing infrastructure capabilities in the MOAB framework and the coupling driver/solver library, the Coupled Physics Environment (CouPE), which utilizes the widely used, scalable PETSc library. This report aims at identifying the coupled-physics simulation capability of SHARP by introducing the demonstration example called sahex in advance of the SHARP release expected by Mar 2016. sahex consists of 6 fuel pins with cladding, 1 control rod, sodium coolant and an outer duct wall that encloses all the other components. This example is carefully chosen to demonstrate the proof of concept for solving more complex demonstration examples such as EBR II assembly and ABTR full core. The workflow of preparing the input files, running the case and analyzing the results is demonstrated in this report. Moreover, an extension of the sahex model called sahex_core, which adds six homogenized neighboring assemblies to the full heterogeneous sahex model, is presented to test homogenization capabilities in both Nek5000 and PROTEUS. Some primary information on the configuration and build aspects for the SHARP toolkit, which includes capability to auto-download dependencies and configure/install with optimal flags in an architecture-aware fashion, is also covered by this report. A step-by-step instruction is provided to help users to create their cases. Details on these processes will be provided in the SHARP user manual that will accompany the first release.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2007

Generative Representations for Automated Design of Robots

A method of automated design of complex, modular robots involves an evolutionary process in which generative representations of designs are used. The term generative representations as used here signifies, loosely, representations that consist of or include algorithms, computer programs, and the like, wherein encoded designs can reuse elements of their encoding and thereby evolve toward greater complexity. Automated design of robots through synthetic evolutionary processes has already been demonstrated, but it is not clear whether genetically inspired search algorithms can yield designs that are sufficiently complex for practical engineering. The ultimate success of such algorithms as tools for automation of design depends on the scaling properties of representations of designs. A nongenerative representation (one in which each element of the encoded design is used at most once in translating to the design) scales linearly with the number of elements. Search algorithms that use nongenerative representations quickly become intractable (search times vary approximately exponentially with numbers of design elements), and thus are not amenable to scaling to complex designs. Generative representations are compact representations and were devised as means to circumvent the above-mentioned fundamental restriction on scalability. In the present method, a robot is defined by a compact programmatic form (its generative representation) and the evolutionary variation takes place on this form. The evolutionary process is an iterative one, wherein each cycle consists of the following steps: 1. Generative representations are generated in an evolutionary subprocess. 2. Each generative representation is a program that, when compiled, produces an assembly procedure. 3. In a computational simulation, a constructor executes an assembly procedure to generate a robot. 4. A physical-simulation program tests the performance of a simulated constructed robot, evaluating the performance according to a fitness criterion to yield a figure of merit that is fed back into the evolutionary subprocess of the next iteration. In comparison with prior approaches to automated evolutionary design of robots, the use of generative representations offers two advantages: First, a generative representation enables the reuse of components in regular and hierarchical ways and thereby serves a systematic means of creating more complex modules out of simpler ones. Second, the evolved generative representation may capture intrinsic properties of the design problem, so that variations in the representations move through the design space more effectively than do equivalent variations in a nongenerative representation. This method has been demonstrated by using it to design some robots that move, variously, by walking, rolling, or sliding. Some of the robots were built (see figure). Although these robots are very simple, in comparison with robots designed by humans, their structures are more regular, modular, hierarchical, and complex than are those of evolved designs of comparable functionality synthesized by use of nongenerative representations.

Homby, Gregory S.↗
DOE OSTI2014

An asymptotic preserving automatic domain decomposition method for the Vlasov–Poisson–BGK system with applications to plasmas

In this work we present an efficient strategy to deal with plasma physics simulations in which localized departures from thermodynamical equilibrium are present. The method is based on the introduction of intermediate regions which allows smooth transitions between kinetic and fluid zones. In this paper we extend Domain Decomposition techniques, obtained through dynamic coupling and buffer zones, to the study of plasmas and, moreover, we combine them with Asymptotic Preserving and Asymptotically Accurate strategies for the time integration. We use a hybrid scheme in which both kinetic and fluid descriptions are considered and coupled together while the kinetic model is solved by asymptotic preserving and accurate methods, in order to guarantee high efficiency and accuracy in all regimes. The numerical scheme is validated and its performances are analyzed by numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Simulating plasma production from hypervelocity impacts

Hypervelocity particles, such as meteoroids and space debris, routinely impact spacecraft and are energetic enough to vaporize and ionize themselves and as well as a portion of the target material. The resulting plasma rapidly expands into the surrounding vacuum. While plasma measurements from hypervelocity impacts have been made using ground-based technologies such as light gas guns and Van de Graaff dust accelerators, some of the basic plasma properties vary significantly between experiments. There have been both ground-based and in-situ measurements of radio frequency (RF) emission from hypervelocity impacts, but the physical mechanism responsible and the possible connection to the impact-produced plasma are not well understood. Under certain conditions, the impact-produced plasma can have deleterious effects on spacecraft electronics by providing a new current path, triggering an electrostatic discharge, causing electromagnetic interference, or generating an electromagnetic pulse. Multi-physics simulations of plasma production from hypervelocity impacts are presented. These simulations incorporate elasticity and plasticity of the solid target, phase change and plasma formation, and non-ideal plasma physics due to the high density and low temperature of the plasma. A smoothed particle hydrodynamics method is used to perform a continuum dynamics simulation with these additional physics. By examining a series of hypervelocity impacts, basic properties of the impact produced plasma plume (density, temperature, expansion speed, charge state) are determined for impactor speeds between 10 and 72 km/s. For a large range of higher impact speeds (30–72 km/s), we find the temperature is unvarying at 2.5 eV. We also find that the plasma plume is weakly ionized for impact speeds less than 14 km/s and fully ionized for impact speeds greater than 20 km/s, independent of impactor mass. This is the same velocity threshold for the detection of RF emission in recent Van de Graaff experiments, suggesting that the RF is correlated to the formation of fully ionized plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Performance tuning of CEED software and first wave apps

The goal of this milestone was the performance tuning of the CEED software and first wave apps. In this milestone, the CEED team developed optimization techniques and tuned for performance the CEED software. Specifically, the focus was on the following: (1) Fast finite element operator storage and evaluation using partial assembly/matrix-free algorithms that take advantage of tensor-product element structure; (2) Architecture optimizations, including the development of performant discretization libraries targeting heterogeneous systems with multi-core CPUs, GPUs, and/or many-core CPUs in single node, cluster, or large-scale ECP supercomputer configurations; and (3) Global kernels for finite element operators, including the development of algorithms and libraries for fast gather-scatter exchanges for action assembly on unstructured graphs and for components needed for global linear solvers. A main part of this milestone was the performance tuning of the CEED first-wave ECP applications. This included the ExaSMR application – Coupled Monte Carlo Neutronics and Fluid Flow Simulation of Small Modular Reactors (ORNL), and the MARBL application – Next-Gen Multi-physics Simulation Code (LLNL). The artifacts delivered include performance improvements in CEED’s 1st wave of applications, and tuned CEED software for various architectures through a number of backends, freely available in the CEED’s repository on GitHub. See the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed for more details. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q4 of FY18 including: CEED’s second annual meeting, a successful minisymposium at the premier international conference on high-order methods (ICOSAHOM), making the CEED milestone reports publicly available, new Laghos release, and other outreach efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

ExactPack: A python library of exact analytic solutions

Verification of multi-physics simulation software against problems with known analytic or semi-analytic solutions is an important aspect of research into a wide variety of fields involving the motion of fluids, shock physics and other dynamic material properties. Previous work comparing simulation results against analytic solutions has been ad-hoc, with developers frequently writing their own analytic solvers. This has resulted in a large amount of duplicated effort. The python library ExactPack has been developed as a collection of analytic and semi-analytic solvers to a variety of multi-physics problems, providing a consistent API to a set of well-tested solver implementations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Simulation of open quantum systems via low-depth convex unitary evolutions

Simulating physical systems on quantum devices is one of the most promising applications of quantum technology. Current quantum approaches to simulating open quantum systems are still practically challenging on NISQ-era devices, because they typically require ancilla qubits and extensive controlled sequences. In this work, we propose a hybrid quantum-classical approach for simulating a class of open system dynamics called random-unitary channels. These channels naturally decompose into a series of convex unitary evolutions, which can then be efficiently sampled and run as independent circuits. The method does not require deep ancilla frameworks and thus can be implemented with lower noise costs. We implement simulations of open quantum systems up to dozens of qubits and with large channel ranks. Published by the American Physical Society 2024

Peetz, Joseph (ORCID:0000000274458028)↗
NASA NTRS1987

Advances in magnetospheric physics by numerical simulations - A critical analysis by an outsider

This is a selective, somewhat editorialized assessment, based on a literature survey, of computer simulation as it exists today in magnetospheric physics. Both large (MHD) and small scale dynamical simulations are described and considered from the perspective of what they are trying to do and with what success. Several specific problem areas where simulations are being carried out are called for commentary: global magnetospheric structure, magnetotail and magnetopause reconnection, Kelvin-Helmholtz instability, hydrodynamic expansion of ionospheric ions, electric double layers, heavy ion heating, and auroral kilometric radiation. It is concluded that simulation is a necessary tool for understanding magnetospheric physics and that significant progress has been made in simulation development. However, results should be evaluated knowing that many factors, some real and physical, others structural, may contribute to such output. A plea is made for greater intercalibration among different simulators working in parallel areas, so that facts can be distinguished from artifacts.

Birmingham, Thomas J.↗
DOE OSTI2018

Control rod treatment for FEM based radiation transport methods

This paper presents a novel control rod treatment for finite element method (FEM) based reactor physics simulations. The new method falls into the class of homogenization methods which treat material interfaces within mesh elements by defining a representative, homogenized nuclear cross section set. In contrast to existing homogenization based cusping treatments that attempt to approximate flux-volume weighting of the cross sections, we propose to exactly integrate terms appearing in the variational form of the transport or diffusion equation over mixed material elements. This goal is achieved by defining smoothly varying cross sections in elements that straddle material boundaries. It is shown that the smoothly varying cross sections can be obtained by projecting the piecewise set of cross sections onto the set of Legendre polynomials up to a finite order. Implementation of smoothly varying cross sections is supported within the Rattlesnake radiation multiphysics code that is currently under development at the Idaho National Laboratory. Homogenization methods traditionally suffer from cusping effects that originate from overestimation of absorption cross sections in strongly neutron-absorbing materials as found in control rods. We demonstrate that the presented method is (1) highly effective in removing cusping effects and (2) provides accurate results based on the C5G7-TD benchmark, a time-dependent version of the C5G7 benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

High-precision Galaxy Clustering Predictions from Small-volume Hydrodynamical Simulations via Control Variates

Abstract Cosmological simulations of galaxy formation are an invaluable tool for understanding galaxy formation and its impact on cosmological parameter inference from large-scale structures. However, their high computational cost is a significant obstacle for running simulations that probe cosmological volumes comparable to those analyzed by contemporary large-scale structure experiments. In this work, we explore the possibility of obtaining high-precision galaxy clustering predictions from small-volume hydrodynamical simulations such as MillenniumTNG and FLAMINGO via control variates. In this approach, the hydrodynamical full-physics simulation is paired with a matched low-resolution gravity-only simulation. By learning the galaxy–halo connection from the hydrodynamical simulation and applying it to the gravity-only counterpart, one obtains a galaxy population that closely mimics the one in the more expensive simulation. One can then construct an estimator of galaxy clustering that combines the clustering amplitudes in the small-volume hydrodynamical and gravity-only simulations with clustering amplitudes in a large-volume gravity-only simulation. Depending on the galaxy sample, clustering statistic, and scale, this galaxy clustering estimator can have an effective volume of up to around 100 times the volume of the original hydrodynamical simulation in the nonlinear regime. With this approach, we can construct galaxy clustering predictions from existing simulations that are precise enough for mock analyses of next-generation large-scale structure surveys such as the Dark Energy Spectroscopic Instrument and the Legacy Survey of Space and Time.

Doytcheva, Alexandra (ORCID:0009000111254888)↗
DOE OSTI2015

CAEBAT OAS/VIBE Production Release v1.1

The objective of the project is to develop a mathematical and computational infrastructure, and modeling framework that will enable seamless multi-scale and multi-physics simulations of battery performance and safety. The modeling framework will transfer the information between models in a physically consistent and mathematically rigorous fashion for both spatial and temporal variations. The end result will be a verified, computationally scalable, portable, and flexible (extensible and easily-modified) framework that can integrate models from the other CAEBAT tasks and industrial partners. The framework will be used to validate models and modeling approaches against experiments and to support rapid prototyping of advanced battery concepts. Fig. 2 shows different parts of CAEBAT VIBE simulation environment that work together to provide user with flexibility in the problem setup, solution formulation and simulation launch. Each of the parts is discussed in subsequent sections with corresponding examples.

25 ENERGY STORAGE↗
DOE OSTI2017

An Isomorphism between Lyapunov Exponents and Shannon's Channel Capacity

We demonstrate that discrete Lyapunov exponents are isomorphic to numeric overflows of the capacity of an arbitrary noiseless and memoryless channel in a Shannon communication model with feedback. The isomorphism allows the understanding of Lyapunov exponents in terms of Information Theory, rather than the traditional definitions in chaos theory. The result also implies alternative approaches to the calculation of related quantities, such as the Kolmogorov Sinai entropy which has been linked to thermodynamic entropy. This work provides a bridge between fundamental physics and information theory. It suggests, among other things, that machine learning and other information theory methods can be employed at the core of physics simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Data-Efficient Generation of Protein Conformational Ensembles with Backbone-to-Side-Chain Transformers

Excitement at the prospect of using data-driven generative models to sample configurational ensembles of biomolecular systems stems from the extraordinary success of these models on a diverse set of high-dimensional sampling tasks. Unlike image generation or even the closely related problem of protein structure prediction, there are currently no data sources with sufficient breadth to parametrize generative models for conformational ensembles. To enable discovery, a fundamentally different approach to building generative models is required: models should be able to propose rare, albeit physical, conformations that may not arise in even the largest data sets. Here, in this work, we introduce a modular strategy to generate conformations based on “backmapping” from a fixed protein backbone that (1) maintains conformational diversity of the side chains and (2) couples the side-chain fluctuations using global information about the protein conformation. Our model combines simple statistical models of side-chain conformations based on rotamer libraries with the now ubiquitous transformer architecture to sample with atomistic accuracy. Together, these ingredients provide a strategy for rapid data acquisition and hence a crucial ingredient for scalable physical simulation with generative neural networks.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Nek5000 Simulations on Turbulent Coolant Flow in a Fuel Assembly Experiment - AREVA/ANL collaboration for advancing CFD tools

The NEAMS program aims to develop an integrated multi physics simulation capability “pellet to plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite’s multi resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Numerical Simulations of a Jet–Cloud Collision and Starburst: Application to Minkowski’s Object

In this work, we present results of three-dimensional, multi-physics simulations of an AGN jet colliding with an intergalactic cloud. The purpose of these simulations is to assess the degree of "positive feedback," i.e., jet-induced star formation, that results. We have specifically tailored our simulation parameters to facilitate a comparison with recent observations of Minkowski's Object (MO), a stellar nursery located at the termination point of a radio jet coming from galaxy NGC 541. As shown in our simulations, such a collision triggers shocks, which propagate around and through the cloud. These shocks condense the gas and under the right circumstances may trigger cooling instabilities, creating runaway increases in density, to the point that individual clumps can become Jeans unstable. Our simulations provide information about the expected star formation rate, total mass converted to H I, H 2 , and stars, and the relative velocity of the stars and gas. Finally, our results confirm the possibility of jet-induced star formation, and agree well with the observations of MO.

79 ASTRONOMY AND ASTROPHYSICS↗