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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

CRF Network Simulations for the South

In order to monitor and improve the CRF in both the Southern Hemisphere and along the ecliptic, we perform various simulations using station networks based mostly on the Australian AuScope network, New Zealand s Warkworth antenna, and several Chinese antennas. The effect of other stations such as HartRAO and Kokee Park to enhance the East-West baseline coverage is also considered. It is anticipated that the simulation results will help IVS to decide on the composition of the CRF sessions of the IVS to be run from 2011 onward.

Titov, Oleg↗
DOE OSTI2018

Validating quantum-classical programming models with tensor network simulations

The exploration of hybrid quantum-classical algorithms and programming models on noisy near-term quantum hardware has begun. As hybrid programs scale towards classical intractability, validation and benchmarking are critical to understanding the utility of the hybrid computational model. In this paper, we demonstrate a newly developed quantum circuit simulator based on tensor network theory that enables intermediate-scale verification and validation of hybrid quantum-classical computing frameworks and programming models. We present our tensor-network quantum virtual machine (TNQVM) simulator which stores a multi-qubit wavefunction in a compressed (factorized) form as a matrix product state, thus enabling single-node simulations of larger qubit registers, as compared to brute-force statevector simulators. Our simulator is designed to be extensible in both the tensor network form and the classical hardware used to run the simulation (multicore, GPU, distributed). The extensibility of the TNQVM simulator with respect to the simulation hardware type is achieved via a pluggable interface for different numerical backends (e.g., ITensor and ExaTENSOR numerical libraries). We demonstrate the utility of our TNQVM quantum circuit simulator through the verification of randomized quantum circuits and the variational quantum eigensolver algorithm, both expressed within the eXtreme-scale ACCelerator (XACC) programming model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters

Popular HPC network interconnection simulators such as SST/macro provide a variety of configurable parameters to explore the design space of hardware components such as network interface cards (NIC), switches, and links among them. While such knobs provide flexibility to explore design trade-offs for novel hardware, manually configuring simulations for matching configurations of the existing hardware to focus on topology exploration can be cumbersome and error-prone, leading to widely inaccurate simulations. This challenge is compounded when specifications of various (proprietary) technologies are not readily available or intentionally omitted. In this work, we propose a framework to autotune the multiple network models’ simulation configurations within SST/macro using Tree-structured Parzen Estimator-based Bayesian optimization to observe the effect on simulation accuracy across different message regimes. These regimes consist of small to large message sizes and latency to bandwidth-bound messages. We provide a detailed analysis of the simulation error for four representative HPC systems. Our Bayesian optimization based autotuning framework for network models achieves a maximum of 5x improvement in accuracy over best-effort manual configurations based on available hardware specifications.

Simulation, autotuning↗
DOE OSTI2017

Percolation connectivity, pore size, and gas apparent permeability: Network simulations and comparison to experimental data: Connectivity, Pore Size, and Gas Permeability

We modeled single-phase gas flow through porous media using percolation networks. Gas permeability is different from liquid permeability. The latter is only related to the geometry and topology of the pore space, while the former depends on the specific gas considered and varies with gas pressure. As gas pressure decreases, four flow regimes can be distinguished as viscous flow, slip flow, transition flow, and free molecular diffusion. Here we use a published conductance model presumably capable of predicting the flow rate of an arbitrary gas through a cylindrical pipe in the four regimes. We incorporated this model into pipe network simulations. We considered 3-D simple cubic, body-centered cubic, and face-centered cubic lattices, in which we varied the pipe radius distribution and the bond coordination number. Gas flow was simulated at different gas pressures. The simulation results showed that the gas apparent permeability k app obeys an identical scaling law in all three lattices, k app ~ (z-z c ) β , where the exponent β depends on the width of the pipe radius distribution, z is the mean coordination number, and z c its critical value at the percolation threshold. Surprisingly, (z-z c ) had a very weak effect on the ratio of the apparent gas permeability to the absolute liquid permeability, k app /k abs , suggesting that the Klinkenberg gas slippage correction factor is nearly independent of connectivity. We constructed models of k app and k app /k abs based on the observed power law and tested them by comparison with published experimental data on glass beads and other materials.

58 GEOSCIENCES↗
NASA NTRS1991

Networked simulation for team training of Space Station astronauts, ground controllers, and scientists - A training and development environment

The purpose of this paper is to describe plans for the Space Station Training Facility (SSTF) which has been designed to meet the envisioned training needs for Space Station Freedom. To meet these needs, the SSTF will integrate networked simulators with real-world systems in five training modes: Stand-Alone, Combined, Joint-Combined, Integrated, and Joint-Integrated. This paper describes the five training modes within the context of three training scenaries. In addition, this paper describes an authoring system which will support the rapid integration of new real-world system changes in the Space Station Freedom Program.

Hajare, Ankur R.↗
DOE OSTI2017

Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Trace Replay and Network Simulation Tool

TraceR is a trace reply tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performances and understanding network behavior by simulating messaging in High Performance Computing applications on interconnection networks.

Acun, Bilge↗
DOE OSTI2017

Trace Replay and Network Simulation Tool

TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.

Jain, Nikhil↗
DOE OSTI2015

Trace Replay and Network Simulation Tool

TraceR is a trace reply tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performances and understanding network behavior by simulating messaging in High Performance Computing applications on interconnection networks.

Acun, Bilge↗
NASA NTRS1990

Prototyping distributed simulation networks

Durra is a declarative language designed to support application-level programming. The use of Durra is illustrated to describe a simple distributed application: a simulation of a collection of networked vehicle simulators. It is shown how the language is used to describe the application, its components and structure, and how the runtime executive provides for the execution of the application.

Doubleday, Dennis L.↗
NASA NTRSDate not supplied

Large-Scale Space Network Simulator for Performance-Optimized DTNs

High-rate Delay Tolerant Networking (HDTN) is a performance-optimized Delay Tolerant Networking (DTN) implementation that can provide multigigabit per second data rates in disruptive and high-latency space networks. Routing, especially in large-scale space networks, remains challenging due to network topologies that evolve over time. This paper presents a simulation tool that enables HDTN implementation testing at accelerated speeds, which is key for routing in large-scale space networks.

High data-rate Delay Tolerant Networking↗
DOE OSTI2015

Pore connectivity, electrical conductivity, and partial water saturation: Network simulations

Abstract The electrical conductivity of brine‐saturated rock is predominantly dependent on the geometry and topology of the pore space. When a resistive second phase (e.g., air in the vadose zone and oil/gas in hydrocarbon reservoirs) displaces the brine, the geometry and topology of the pore space occupied by the electrically conductive phase are changed. We investigated the effect of these changes on the electrical conductivity of rock partially saturated with brine. We simulated drainage and imbibition as invasion and bond percolation processes, respectively, in pipe networks assumed to be perfectly water‐wet. The simulations included the formation of a water film in the pipes invaded by the nonwetting fluid. During simulated drainage/imbibition, we measured the changes in resistivity index as well as a number of relevant microstructural parameters describing the portion of the pore space saturated with water. Except Euler topological number, all quantities considered here showed a significant level of “universality,” i.e., insensitivity to the type of lattice used (simple cubic, body‐centered cubic, or face‐centered cubic). Hence, the coordination number of the pore network appears to be a more effective measure of connectivity than Euler number. In general, the simulated resistivity index did not obey Archie's simple power law. In log‐log scale, the resistivity index curves displayed a substantial downward or upward curvature depending on the presence or absence of a water film. Our network simulations compared relatively well with experimental data sets, which were obtained using experimental conditions and procedures consistent with the simulations. Finally, we verified that the connectivity/heterogeneity model proposed by Bernabé et al. (2011) could be extended to the partial brine saturation case when water films were not present.

Li, M.↗
NASA NTRS2002

ESIM_DSN Web-Enabled Distributed Simulation Network

In this paper, the eSim(sup DSN) approach to achieve distributed simulation capability using the Internet is presented. With this approach a complete simulation can be assembled from component subsystems that run on different computers. The subsystems interact with each other via the Internet The distributed simulation uses a hub-and-spoke type network topology. It provides the ability to dynamically link simulation subsystem models to different computers as well as the ability to assign a particular model to each computer. A proof-of-concept demonstrator is also presented. The eSim(sup DSN) demonstrator can be accessed at http://www.jsc.draper.com/esim which hosts various examples of Web enabled simulations.

Bedrossian, Nazareth↗
NASA NTRS2008

Interfacing Space Communications and Navigation Network Simulation with Distributed System Integration Laboratories (DSIL)

NASA's planned Lunar missions will involve multiple NASA centers where each participating center has a specific role and specialization. In this vision, the Constellation program (CxP)'s Distributed System Integration Laboratories (DSIL) architecture consist of multiple System Integration Labs (SILs), with simulators, emulators, testlabs and control centers interacting with each other over a broadband network to perform test and verification for mission scenarios. To support the end-to-end simulation and emulation effort of NASA' exploration initiatives, different NASA centers are interconnected to participate in distributed simulations. Currently, DSIL has interconnections among the following NASA centers: Johnson Space Center (JSC), Kennedy Space Center (KSC), Marshall Space Flight Center (MSFC) and Jet Propulsion Laboratory (JPL). Through interconnections and interactions among different NASA centers, critical resources and data can be shared, while independent simulations can be performed simultaneously at different NASA locations, to effectively utilize the simulation and emulation capabilities at each center. Furthermore, the development of DSIL can maximally leverage the existing project simulation and testing plans. In this work, we describe the specific role and development activities at JPL for Space Communications and Navigation Network (SCaN) simulator using the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to simulate communications effects among mission assets. Using MACHETE, different space network configurations among spacecrafts and ground systems of various parameter sets can be simulated. Data that is necessary for tracking, navigation, and guidance of spacecrafts such as Crew Exploration Vehicle (CEV), Crew Launch Vehicle (CLV), and Lunar Relay Satellite (LRS) and orbit calculation data are disseminated to different NASA centers and updated periodically using the High Level Architecture (HLA). In addition, the performance of DSIL under different traffic loads with different mix of data and priorities are evaluated.

Traffic Measuring and Monitoring↗