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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 37 records · Page 2

DeepSurveySim: Simulation Software and Benchmark Challenges for Astronomical Observation Scheduling

Modern astronomical surveys have multiple competing scientific goals. Optimizing the observation schedule for these goals presents significant computational and theoretical challenges, and state-of-the-art methods rely on expensive human inspection of simulated telescope schedules. Automated methods, such as Reinforcement Learning (RL), have recently been explored to accelerate scheduling. DeepSurveySim provides methods for tracking and approximating sky conditions for a set of observations from a user-supplied telescope configuration.

79 ASTRONOMY AND ASTROPHYSICS↗

An Efficient Implementation of Multiscale Simulation Software PNP-cDFT

An efficient implementation of PNP-cDFT, a multiscale method for computing the chemical potentials of charged species is designed and evaluated. Spatial decomposition of the multi particle system is employed in the parallelization of classical density functional theory (cDFT) algorithm. Furthermore, a truncated strategy is used to reduce the computational complexity of cDFT algorithm. The simulation results show that the parallel implementation has close to linear scalability in parallel computing environments for both 1D and 3D systems. It also shows that the truncated versions of cDFT improve the efficiency of the methods substantially.

99 GENERAL AND MISCELLANEOUS↗

Final Report on DOE SciDAC project on Next Generation of Multi-Scale Quantum Simulation Software for Strongly Correlated Materials

This report summarizes the accomplishments of the University of California Davis team which is part of a larger SciDAC collaboration including Mark Jarrell of Louisiana State University, Karen Tomko of the Ohio Supercomputer Center, and Eduardo F. D'Azevedo and Thomas A. Maier of Oak Ridge National Laboratory. In this report, we focus on the major UCD accomplishments. As the paper authorship list emphasizes, much of our work is the result of a tightly integrated effort; hence this compendium of UCD efforts of necessity contains some overlap with the work at our partner institutions.

Bai, Zhaojun↗

Final report for next generation multi-scale quantum simulation software for strongly correlated materials

The goal of this project was to develop a new formalism for the correlated electron problem, which we call, the Multi Scale Many Body formalism. This report will focus on the work done at the Louisiana State University (LSU) since the mid term report. The LSU group moved from the University of Cincinnati (UC) to LSU in the summer of 2008. In the last full year at UC, only half of the funds were received and it took nearly two years for the funds to be transferred from UC to LSU . This effectively shut down the research at LSU until the transfer was completed in 2011, there were also two no-cost extensions of the grant until August of this year. The grant ended for the other SciDAC partners at Davis and ORNL in 2011. Since the mid term report, the LSU group has published 19 papers [P1-P19] acknowledging this SciDAC, which are listed below. In addition, numerous invited talked acknowledged the SciDAC. Below, we will summarize the work at LSU since the mid-term report and mainly since funding resumed. The projects include the further development of multi-scale methods for correlated systems (1), the study of quantum criticality at finite doping in the Hubbard model (2), the description of a promising new method to study Anderson localization with a million-fold reduction of computational complexity!, the description of other projects (4), and (5) a workshop to close out the project that brought together exascale program developers (Stellar, MPI, OpenMP,...) with applications developers.

97 MATHEMATICS AND COMPUTING↗

Qualification of Simulation Software for Safety Assessment of Sodium Cooled Fast Reactors. Requirements and Recommendations

The goal of this review is to enable application of codes or software packages for safety assessment of advanced sodium-cooled fast reactor (SFR) designs. To address near-term programmatic needs, the authors have focused on two objectives. First, the authors have focused on identification of requirements for software QA that must be satisfied to enable the application of software to future safety analyses. Second, the authors have collected best practices applied by other code development teams to minimize cost and time of initial code qualification activities and to recommend a path to the stated goal.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Benchmarking the Performance of Neuromorphic and Spiking Neural Network Simulators

Software simulators play a critical role in the development of new algorithms and system architectures in any field of engineering. Neuromorphic computing, which has shown potential in building brain-inspired energy-efficient hardware, suffers a slow-down in the development cycle due to a lack of flexible and easy-to-use simulators of either neuromorphic hardware itself or of spiking neural networks (SNNs), the type of neural network computation executed on most neuromorphic systems. While there are several openly available neuromorphic or SNN simulation packages developed by a variety of research groups, they have mostly targeted computational neuroscience simulations, and only a few have targeted small-scale machine learning tasks with SNNs. Evaluations or comparisons of these simulators have often targeted computational neuroscience-style workloads. In this work, we seek to evaluate the performance of several publicly available SNN simulators with respect to non-computational neuroscience workloads, in terms of speed, flexibility, and scalability. We evaluate the performance of the NEST, Brian2, Brian2GeNN, BindsNET and Nengo packages under a common front-end neuromorphic framework. Our evaluation tasks include a variety of different network architectures and workload types to mimic the computation common in different algorithms, including feed-forward network inference, genetic algorithms, and reservoir computing. We also study the scalability of each of these simulators when running on different computing hardware, from single core CPU workstations to multi-node supercomputers. Our results show that the BindsNET simulator has the best speed and scalability for most of the SNN workloads (sparse, dense, and layered SNN architectures) on a single core CPU. However, when comparing the simulators leveraging the GPU capabilities, Brian2GeNN outperforms the others for these workloads in terms of scalability. NEST performs the best for small sparse networks and is also the most flexible simulator in terms of reconfiguration capability NEST shows a speedup of at least 2x compared to the other packages when running evolutionary algorithms for SNNs. The multi-node and multi-thread capabilities of NEST show at least 2x speedup compared to the rest of the simulators (single core CPU or GPU based simulators) for large and sparse networks. We conclude our work by providing a set of recommendations on the suitability of employing these simulators for different tasks and scales of operations. We also present the characteristics for a future generic ideal SNN simulator for different neuromorphic computing workloads.

97 MATHEMATICS AND COMPUTING↗

Impact of K-factor on Short Circuit Program Convergence for Inverter-Based Resources during Faults

Classical short-circuit programs that linearize the power network are no longer applicable for inverter based resources (IBRs), necessitating an iterative approach. Phasor domain programs can model the IBRs using an iterative approach considering nonlinear fault responses. In phasor domain models, the IBR can be modeled as a voltage controlled current source (VCCS) in tabular form with positive, negative, and zero sequence information for balanced and unbalance short-circuit faults. In the VCCS modeling of the IBR, positive and negative incremental reactive current, also known as the k-factor, plays an important role in short circuit program convergence. In this work, a few approaches: conventional VCCS modeling with a k-factor of 2, conventional VCCS modeling with a k-factor of 2 with modified pre-fault voltages, VCCS characteristics based on the power flow solution with a k-factor of 2, and VCCS characteristics based on the power flow solution with a k-factor of 1 are investigated for short circuit program convergence under higher IBR penetration. The IEEE 39 bus New England Test System is taken as the test system, and simulations are carried out in PSS®CAPE 15.0.26 simulation software. Simulation results demonstrate that IBR penetration is higher for the VCCS model, which corresponds to the power flow solution with k-factor 1, compared to other approaches.

42 ENGINEERING↗

Idea Paper: The Lifecycle of Software for Scientific Simulations

The software lifecycle is a well researched topic that has produced many models to meet the needs of different types of software projects. However, one class of projects, software development for scientific computing, has received relatively little attention from lifecycle researchers. In particular, software for end-to-end computations for obtaining scientific results has received few lifecycle proposals and no formalization of a development model. An examination of development approaches employed by the teams implementing large multicomponent codes reveals a great deal of similarity in their strategies. This idea paper formalizes these related approaches into a lifecycle model for end-to-end scientific application software, featuring loose coupling between submodels for development of infrastructure and scientific capability. We also invite input from stakeholders to converge on a model that captures the complexity of this development processes and provides needed lifecycle guidance to the scientific software community.

Dubey, Anshu↗

Locust: C++ software for simulation of RF detection

The Locust simulation package is the new C++ software tool developed to simulate the measurement of time-varying electromagnetic fields using RF detection techniques. Modularity and flexibility allow for arbitrary input signals, while concurrently supporting tight integration with physics-based simulations as input. External signals driven by the Kassiopeia particle tracking package are discussed, demonstrating conditional feedback between Locust and Kassiopeia during software execution. An application of the simulation to the Project 8 experiment is described. Locust is publicly available at https://github.com/project8/locust_mc

97 MATHEMATICS AND COMPUTING↗

Study of the characteristics of reconfigurable plasma antenna array

This paper presents a design and simulation of a reconfigurable array of plasma antenna. The plasma column is used as radiating elements instead of metal to create an antenna. The advantages of the plasma antenna over the conventional antenna are its possible to change the operating parameters, such as the working pressure, input power, radius of the discharge tube, resonant frequency, and length of the plasma column. In addition, plasma antenna can be reconfigurable with respect to shape, frequency and radiation parameters in a very short time. The plasma discharge tube was designed with a length of 200 mm, the radius of the plasma column was 2.5 mm and the coupling sleeve was connected to the SMA as the ground. This simulation was performed by using the simulation software Computer Simulation Technology (CST). The frequency is set in the range of 1 GHz to 10 GHz. The performance of the designed antenna was analyzed in term of return loss, gain and radiation pattern. For reconfigurable plasma antenna array, it shows that the gain is increase when the number of antenna element is increase. The combination of the discharge tube and metal rod as an antenna array has been done, and the result shows that an array with the plasma element can achieve higher gain.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Incorporating Wind Energy in Power System Restoration Planning

Wind energy is rapidly growing. While wind brings us clean and inexpensive energy, its inherent variability and uncertainty present challenges for the power grid. In particular, employing wind energy for power system restoration is very challenging. A fast and reliable restoration plays a vital role to achieve the self-healing power grid. This paper develops a novel offline restoration planning tool for harnessing wind energy to enhance grid resilience. The Wind-for-Restoration problem is formulated as a stochastic mixed-integer linear programming problem with generated wind energy scenarios. The problem is then decomposed into two stages and solved with the integer Lshaped algorithm. Numerical experiments have been conducted through different case studies using the modified IEEE 57-bus system. The developed tool can provide the scheduled wind power at each restoration time. The impact of wind energy is investigated from the aspects of location and inertia capability, as well as wind penetration, fluctuation, and uncertainty. Moreover, a dynamic response validation tool is developed to validate the results of optimization problem in a dynamic simulation software. Finally, simulation results demonstrate that the optimal wind harnessing strategy can help improve system restoration process and enhance system resilience.

17 WIND ENERGY↗