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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 127 records · Page 7

A new method of measuring radio source parameters of a partially polarized distributed source from spacecraft observations

An experimental system is analyzed which is designed to determine the angular and polarization properties of low frequency radio sources from measurements made on a spinning spacecraft. The system has been optimized to provide high accuracies for sources at high as well as low elevation angles. Theoretical expressions are derived for the response of this system to a partially polarized point source. Integrations are then carried out to get the system response to a uniform circular distributed source. Data processing techniques are derived so that computer simulations can be carried out to investigate the accuracy of this technique. It is shown that using 24 measurements of a partially polarized source (with Q = U = V = 0.5), taken in one spacecraft rotation, the resulting rms errors in angular position are less than one degree and the errors in determining the Stokes parameters are generally 1-10% for a wide range of source elevations.

Manning, R.↗

Moment preserving constrained resampling with applications to particle-in-cell methods

The Moment Preserving Constrained Resampling (MPCR) algorithm for particle resampling is introduced and applied to particle-in-cell (PIC) methods to increase simulation accuracy, reduce compute cost, and/or avoid numerical instabilities. The general algorithm partitions the system space into smaller subsets and resamples the distribution within each subset. Further, the algorithm is designed to conserve any number of particle and grid moments with a high degree of accuracy (i.e. machine accuracy). The effectiveness of MPCR is demonstrated with several numerical tests, including a use-case study in gyrokinetic fusion plasma simulations. Finally, the computational cost of MPCR is negligible compared to the cost of particle evolution in PIC methods, and the tests demonstrate that periodic particle resampling yields a significant improvement in the accuracy and stability of the results.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Situational Awareness of Grid Anomalies (SAGA)

The modern power industry becomes more vulnerable to cyber events due to the growing interconnectivity, interdependence, and complexity of the electric power grid. High-fidelity modeling and simulation tools that support the preventative risk analysis on potential cyber-relevant events is essential for ensuring the situational awareness of the system operator as it provides an inexpensive and risk-free environment to test the system responses under various cyber-relevant events and hereby can support research on cyber anomaly detection, optimal protective resource allocation, and mitigation measures. In this webinar, we will share NREL's cybersecurity research capabilities by highlighting the development of a scalable cyber-physical event test bed and demonstration with real hardware in the loop. The developed cyber-physical event test bed is backboned by an integrated transmission, distribution, and communication dynamic co-simulation framework and a plug-and-play cyber event generation module. It is designed to be modular and compatible with parallel computing, and thereby supports large-scale system simulations at an affordable computation cost. The test bed can capture millisecond-to-minutes dynamic frequency and voltage responses under cyber events from the bulk transmission system to the active distribution systems and distributed energy resources at the grid edge.

co-simulation↗

An Object Oriented Extensible Architecture for Affordable Aerospace Propulsion Systems

Driven by a need to explore and develop propulsion systems that exceeded current computing capabilities, NASA Glenn embarked on a novel strategy leading to the development of an architecture that enables propulsion simulations never thought possible before. Full engine 3 Dimensional Computational Fluid Dynamic propulsion system simulations were deemed impossible due to the impracticality of the hardware and software computing systems required. However, with a software paradigm shift and an embracing of parallel and distributed processing, an architecture was designed to meet the needs of future propulsion system modeling. The author suggests that the architecture designed at the NASA Glenn Research Center for propulsion system modeling has potential for impacting the direction of development of affordable weapons systems currently under consideration by the Applied Vehicle Technology Panel (AVT). This paper discusses the salient features of the NPSS Architecture including its interface layer, object layer, implementation for accessing legacy codes, numerical zooming infrastructure and its computing layer. The computing layer focuses on the use and deployment of these propulsion simulations on parallel and distributed computing platforms which has been the focus of NASA Ames. Additional features of the object oriented architecture that support MultiDisciplinary (MD) Coupling, computer aided design (CAD) access and MD coupling objects will be discussed. Included will be a discussion of the successes, challenges and benefits of implementing this architecture.

Follen, Gregory J.↗

A Comparison of Filter-based Approaches for Model-based Prognostics

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

prognostics↗

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗

Seamless integration of commercial Clouds with ATLAS Distributed Computing

The CERN ATLAS Experiment successfully uses a worldwide dis-tributed computing Grid infrastructure to support its physics programme at the Large Hadron Collider (LHC). The Grid workflow system PanDA routinely manages up to 700,000 concurrently running production and analysis jobs to process simulation and detector data. In total more than 500 PB of data are distributed over more than 150 sites in the WLCG and handled by the ATLAS data management system Rucio. To prepare for the ever growing data rate in future LHC runs new developments are underway to embrace industry accepted protocols and technologies, and utilize opportunistic resources in a standard way. This paper reviews how the Google and Amazon Cloud computing ser-vices have been seamlessly integrated as a Grid site within PanDA and Rucio. Performance and brief cost evaluations will be discussed. Such setups could offer advanced Cloud tool-sets and provide added value for analysis facilities that are under discussions for LHC Run-4.

97 MATHEMATICS AND COMPUTING↗

Programming approaches for scalability, performance, and portability of combustion physics codes

Here, this paper presents the process, strategy, and results associated with porting a typical combustion physics flow solver to current state-of-the-art and future massively-parallel computer architectures. Major focus is placed on the distinct algorithmic structure of these types of codes and how it can be integrated with modern programming paradigms for heterogeneous platforms (i.e., distributed many-core systems with accelerators). An end-to-end case study is presented that exemplifies the process in a generic manner, which then serves as a clear guide with respect to the strategy and best practices leading to a robust and adaptable framework that performs well, is durable over time, is portable, and requires minimal human-effort. This end is accomplished beginning with the use of a mature, validated, structured, multiblock code framework optimized for application of both Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). This code has been ported to a variety of platforms over the past decade, including most recently the Oak Ridge Leadership Computing Facility’s “Summit” Platform. The experience gained on these multiple platforms provides general insights and thus the results presented are not specific to any one code or platform other than the overarching trend toward distributed many-core systems with accelerators in order to move toward exascale performance. The resultant performance and scalability of the ported code is demonstrated on a real-world application; a state-of-the-art rotating detonation rocket engine simulation that matches the complex geometry and boundary conditions imposed as part of a companion experimental campaign.

97 MATHEMATICS AND COMPUTING↗

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Effect of melt-solid interface shape on lateral compositional distribution of unidirectionally solidified 2-6 semiconducting alloys

A computer code developed previously has been used to simulate lateral compositional distributions for several 2-6 semiconducting systems. The code is based on analytical results obtained previously. The system under study is an azimuthal symmetric cylindrical system with a curved melt-solid interface shape during an unidirectional solidification process. It is assumed that the system is under a steady state diffusion limited growth condition.

Wang, Jai-Ching↗

NASA Virtual Glovebox: An Immersive Virtual Desktop Environment for Training Astronauts in Life Science Experiments

The International Space Station will soon provide an unparalleled research facility for studying the near- and longer-term effects of microgravity on living systems. Using the Space Station Glovebox Facility - a compact, fully contained reach-in environment - astronauts will conduct technically challenging life sciences experiments. Virtual environment technologies are being developed at NASA Ames Research Center to help realize the scientific potential of this unique resource by facilitating the experimental hardware and protocol designs and by assisting the astronauts in training. The Virtual GloveboX (VGX) integrates high-fidelity graphics, force-feedback devices and real- time computer simulation engines to achieve an immersive training environment. Here, we describe the prototype VGX system, the distributed processing architecture used in the simulation environment, and modifications to the visualization pipeline required to accommodate the display configuration.

Twombly, I. Alexander↗

Design outline for a new multiman ATC simulation facility at NASA-Ames Research Center

A new and unique facility for studying human factors aspects in aeronautics is being planned for use in the Man-Vehicle Systems Research Division at the NASA-Ames Research Center. This facility will replace the existing three cockpit-single ground controller station and be expandable to include approximately seven cockpits and two ground controller stations. Unlike the previous system, each cockpit will be mini-computer centered and linked to a main CPU to effect a distributed computation facility. Each simulator will compute its own flight dynamic and flight path predictor. Mechanical flight instruments in each cockpit will be locally supported and CRT cockpit displays of (e.g.) traffic and or RNAV information will be centrally computed and distributed as a means of extending the existing computational and graphical resources. An outline of the total design is presented which addresses the technical design options and research possibilities of this unique man-machine facility and which may also serve as a model for other real time distributed simulation facilities.

Kreifeldt, J. G.↗

fp-tools

The output of a molecular dynamics simulation is a data file containing properties of the motion of the simulated particles as a function of time (e.g., positions, velocities). From this output, scientists can extract various properties which give insight into the physics of the system; for example, the radial distribution function can be computed from the particle positions, which gives insight into how close the system is to melting or freezing. Many publicly available codes to perform molecular dynamics simulations exist and have been well adopted by the scientific community (e.g., LAMMPS, VASP). However, it remains standard practice for scientists to write their own post-processing scripts to extract various properties of interest from the molecular dynamics simulation data. Since in many cases scientists are interested in the same set of “textbook” properties, there is a large duplication of effort in writing these post-processing scripts. Our proposed code, FP-Tools, is a C++ toolkit designed to help scientists extract and analyze quantities of interest from the output of a molecular dynamics simulation, eliminating the need for them to write these codes themselves and thus reducing this duplication of effort. The quantities which are computed by our code are well documented in the literature (either in publications or textbooks), and the algorithms we implement to compute these properties are also well known in the field. We are not introducing new science or methods here; rather, our primary goal is to provide a useful tool to the community in the form of a well-documented, easy to use package.

Hartman, Leah↗

Dataflow computing approach in high-speed digital simulation

New computational tools and methodologies for the digital simulation of continuous systems were explored. Programmability, and cost effective performance in multiprocessor organizations for real time simulation was investigated. Approach is based on functional style languages and data flow computing principles, which allow for the natural representation of parallelism in algorithms and provides a suitable basis for the design of cost effective high performance distributed systems. The objectives of this research are to: (1) perform comparative evaluation of several existing data flow languages and develop an experimental data flow language suitable for real time simulation using multiprocessor systems; (2) investigate the main issues that arise in the architecture and organization of data flow multiprocessors for real time simulation; and (3) develop and apply performance evaluation models in typical applications.

Ercegovac, M. D.↗

Investigating the influence of particle distribution on force and torque statistics using hierarchical machine learning

An accurate representation of hydrodynamic force and torque experienced by every particle in a distribution can be obtained from particle resolved (PR) simulations. These unique quantities are influenced by the deterministic position of surrounding particles. However, systems simulated with this methodology are typically limited to particles due to the involved computational cost. This resource requirement is a major bottleneck in analyzing the effect of variations in particle distribution. Here, this article attempts to address this bottleneck by availing relatively inexpensive deep learning models. The surrogate models that we employ in this article use a physics‐based hierarchical framework and symmetry‐preserving neural networks to achieve robustness with limited training data. This article first performs additional generalizability tests on PR data of distinct distributions that are not involved in the training process. The models are then deployed on several different particle distributions. Impact of clustering and structure on the observed statistics are investigated.

42 ENGINEERING↗

Computational Methods for HSCT-Inlet Controls/CFD Interdisciplinary Research

A program aimed at facilitating the use of computational fluid dynamics (CFD) simulations by the controls discipline is presented. The objective is to reduce the development time and cost for propulsion system controls by using CFD simulations to obtain high-fidelity system models for control design and as numerical test beds for control system testing and validation. An interdisciplinary team has been formed to develop analytical and computational tools in three discipline areas: controls, CFD, and computational technology. The controls effort has focused on specifying requirements for an interface between the controls specialist and CFD simulations and a new method for extracting linear, reduced-order control models from CFD simulations. Existing CFD codes are being modified to permit time accurate execution and provide realistic boundary conditions for controls studies. Parallel processing and distributed computing techniques, along with existing system integration software, are being used to reduce CFD execution times and to support the development of an integrated analysis/design system. This paper describes: the initial application for the technology being developed, the high speed civil transport (HSCT) inlet control problem; activities being pursued in each discipline area; and a prototype analysis/design system in place for interactive operation and visualization of a time-accurate HSCT-inlet simulation.

Cole, Gary L.↗

Multiscale Experiments and Multiphysics Simulation of Multiphase Flow for Transportable Small Modular Reactors

A new type of safe, small, transportable nuclear reactor would address the intense and ever-growing global demand for energy produced via a resilient, carbon-free energy source. In this regard, transportable small modular reactors (SMRs) are being designed and developed for electricity generation within small/micro-grid/off-grid isolated systems, as well as for heat generation in industrial/residential applications. These reactors feature the capability to be fully factory fabricated and then directly transported to utilities’ sites as “plug-and-play” systems. Research and development (R&D) programs are underway at Idaho National Laboratory (INL) to successfully design, develop, and demonstrate such safe-by-design mobile reactor technologies, in collaboration with partner organizations. Multiscale experimental facilities and multiphysics simulation tools are required for reactor design verification and validation (V&V), and licensing. These advanced reactors are intended to feature passive safety systems such as passive containment cooling systems (PCCS), which consist of multiphase flows and multispecies distributions. This seminar talk will focus on designing and analyzing transportable SMR PCCS by using multiscale experiments and multiphysics computational fluid dynamics (CFD) simulations to support reactor licensing and safety. The corresponding research challenges are addressed via supportive verification and validation results generated by the models and simulation tools in combination with selective parametric and uncertainty analysis. This solution approach could blaze the trail for commercial adoption of such technologies. The facilities, simulation capabilities, and research opportunities available at INL in regard to such reactors and the integrated energy systems with which they go hand in hand are also discussed briefly, and may spark interest in deeper research as well as new collaborative projects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗