Search NASA⌕ Search

SEARCH · Search NASA

Results for “Discrete Event Simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Object oriented studies into artificial space debris

A prototype simulation is being developed under contract to the Royal Aerospace Establishment (RAE), Farnborough, England, to assist in the discrimination of artificial space objects/debris. The methodology undertaken has been to link Object Oriented programming, intelligent knowledge based system (IKBS) techniques and advanced computer technology with numeric analysis to provide a graphical, symbolic simulation. The objective is to provide an additional layer of understanding on top of conventional classification methods. Use is being made of object and rule based knowledge representation, multiple reasoning, truth maintenance and uncertainty. Software tools being used include Knowledge Engineering Environment (KEE) and SymTactics for knowledge representation. Hooks are being developed within the SymTactics framework to incorporate mathematical models describing orbital motion and fragmentation. Penetration and structural analysis can also be incorporated. SymTactics is an Object Oriented discrete event simulation tool built as a domain specific extension to the KEE environment. The tool provides facilities for building, debugging and monitoring dynamic (military) simulations.

Adamson, J. M.↗
DOE OSTI2017

Concurrent conversation modeling and parallel simulation of the naming game in social networks

The Naming Game is an effective self-organization model to understand the emergence of linguistic consensus and to investigate the system dynamics in a variety of phenomena over social networks of autonomous agents. The Naming Game is an effective description for the evolution of consensus despite the absence of any central coordination or specialized initialization even in large-scale networks. While the classical game is effective in description, it was defined with inherently sequential evaluation semantics over the entire network. Here, we develop a new concurrent model as a relaxation of the classical formulation and express it in a discrete event style of evaluation. Further, with the uncovered concurrency that was absent in the classical algorithm, we map the concurrent model to parallel discrete event simulation. Using a prototype implementation, we present an initial parallel performance study on networks containing hundreds of thousands of individuals, with a decrease in simulation time in the best-observed case from 4800 seconds down to 1400 seconds.

Perumalla, Kalyan↗
DOE OSTI2024

Exploring the benefits of using co-packaged optics in data center and AI supercomputer networks: a simulation-based analysis [Invited]

We investigate the advantages of using co-packaged optics in next-generation data center and AI supercomputer networks. The increased escape bandwidth offered by co-packaged optics provides multiple possibilities for building 50T switches and beyond, expanding the opportunities in both the data center and supercomputing domains. Furthermore, this provides network architects with the opportunity to expand their design space and develop simplified networks with enhanced network locality properties. Co-packaging at the switch and server points enables networks with double capacity while reducing the switch count by 64% compared to state-of-the-art systems. We evaluate these concepts through discrete-event simulations using all-to-all and all-reduce traffic patterns that simulate collective communications commonly found in network-bound applications. Initially, we investigate the all-to-all overhead involved in distributing the virtual machines of the applications across multiple leaf switches and compare it to the scenario in which all VMs are placed under a single switch. Subsequently, we evaluate the performance of an AI supercomputing cluster by simulating both patterns for different message sizes, while also varying the number of participating nodes. The results suggest that networks with improved locality properties become increasingly important as the network stack operates at higher speeds; for a stack latency of 1.25 µs, placing the applications under multiple switches can result in up to 68% higher completion times than placing them under a single switch. For AI supercomputers, significant improvements are observed in the mean server throughput, reaching more than 90% for configurations involving 256 nodes and message sizes of at least 128 KiB.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2015

Deep Space Storm Shelter Simulation Study

Missions outside of Earth's magnetic field are impeded by the presence of radiation from galactic cosmic rays and solar particle events. To overcome this issue, NASA's Advanced Exploration Systems Radiation Works Storm Shelter (RadWorks) has been studying different radiation protective habitats to shield against the onset of solar particle event radiation. These habitats have the capability of protecting occupants by utilizing available materials such as food, water, brine, human waste, trash, and non-consumables to build short-term shelters. Protection comes from building a barrier with the materials that dampens the impact of the radiation on astronauts. The goal of this study is to develop a discrete event simulation, modeling a solar particle event and the building of a protective shelter. The main hallway location within a larger habitat similar to the International Space Station (ISS) is analyzed. The outputs from this model are: 1) the total area covered on the shelter by the different materials, 2) the amount of radiation the crew members receive, and 3) the amount of time for setting up the habitat during specific points in a mission given an event occurs.

Dugan, Kathryn↗
DOE OSTI2016

Operational Excellence through Schedule Optimization and Production Simulation of Application Specific Integrated Circuits.

Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performance evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

Career Development through Discreet Simulation Modeling - 19009

The cleanup mission of the Department of Energy (DOE) Office of River Protection (ORP) at the Hanford Site is to immobilize 212,000 m3 (56 million gallons) of nuclear waste, currently stored in 177 underground tanks, at the Waste Treatment and Immobilization Plant (WTP) and associated supplemental treatment facilities. Waste transfers to and from the WTP utilize the intricate Hanford Waste Feed Delivery (WFD) system, a network composed of: double-shell tanks (DSTs), single shell tanks (SSTs), the effluent treatment facility (ETF), a large number of pumps, valves, and leak detectors, and thousands of feet of underground transfer lines. This equipment must be prepared to safely and reliably transfer waste to the WTP. This study used discrete event simulation modeling to explore the behavior of the waste transfer system to identify areas of improvement. Two models and their subsequent results are presented: the Effluent Treatment Facility and the next-to-be-retrieved single-shell tanks (A/AX Farms). This study focused on identifying throughput bottlenecks, operational constraints, choke-point analysis, and redundancy in equipment, process design, and operational strategy. Analysis performed on the ETF OR Model indicated that the existing facility operation strategy will not result in a sufficient throughput to prevent WTP melter idling. Furthermore, in the absence of equipment failures, the facility was still shown to be unable to reach the required throughput to prevent melter idling. It is concluded that ETF system maintenance events are currently the main bottlenecks in the ETF facility. Analysis performed on the SST (A/AX) OR model indicate that the main drivers of the retrieval schedule are the hard retrieval start dates for each SST tank. In addition, it was concluded that operating the ventilation trains in parallel results in 15 times less retrieval interruptions and shortens the retrieval durations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Comparison of Two Models for Damage Accumulation in Simulations of System Performance

A comprehensive simulation study of system performance needs to address variations in component behavior, variations in phenomenology, and the coupling between phenomenology and component failure. This paper discusses two models of this: 1. damage accumulation is modeled as a random walk process in each time history, with component failure occurring when damage accumulation reaches a specified threshold; or 2. damage accumulation is modeled mechanistically within each time history, but failure occurs when damage reaches a time-history-specific threshold, sampled at time zero from each component’s distribution of damage tolerance. A limiting case of the latter is classical discrete-event simulation, with component failure times sampled a priori from failure time distributions; but in such models, the failure times are not typically adjusted for operating conditions varying within a time history. Nowadays, as discussed below, it is practical to account for this. The paper compares the interpretations and computational aspects of the two models mentioned above.

42 ENGINEERING↗
NASA NTRS2016

The Exploration of Mars Launch and Assembly Simulation

Advancing human exploration of space beyond Low Earth Orbit, and ultimately to Mars, is of great interest to NASA, other organizations, and space exploration advocates. Various strategies for getting to Mars have been proposed. These include NASA's Design Reference Architecture 5.0, a near-term flyby of Mars advocated by the group Inspiration Mars, and potential options developed for NASA's Evolvable Mars Campaign. Regardless of which approach is used to get to Mars, they all share a need to visualize and analyze their proposed campaign and evaluate the feasibility of the launch and on-orbit assembly segment of the campaign. The launch and assembly segment starts with flight hardware manufacturing and ends with final departure of a Mars Transfer Vehicle (MTV), or set of MTVs, from an assembly orbit near Earth. This paper describes a discrete event simulation based strategic visualization and analysis tool that can be used to evaluate the launch campaign reliability of any proposed strategy for exploration beyond low Earth orbit. The input to the simulation can be any manifest of multiple launches and their associated transit operations between Earth and the exploration destinations, including Earth orbit, lunar orbit, asteroids, moons of Mars, and ultimately Mars. The simulation output includes expected launch dates and ascent outcomes i.e., success or failure. Running 1,000 replications of the simulation provides the capability to perform launch campaign reliability analysis to determine the probability that all launches occur in a timely manner to support departure opportunities and to deliver their payloads to the intended orbit. This allows for quantitative comparisons between alternative scenarios, as well as the capability to analyze options for improving launch campaign reliability. Results are presented for representative strategies.

Cates, Grant↗
NASA NTRS2016

The Exploration of Mars Launch and Assembly Simulation

Advancing human exploration of space beyond Low Earth Orbit, and ultimately to Mars, is of great interest to NASA, other organizations, and space exploration advocates. Various strategies for getting to Mars have been proposed. These include NASA's Design Reference Architecture 5.0, a near-term flyby of Mars advocated by the group Inspiration Mars, and potential options developed for NASA's Evolvable Mars Campaign. Regardless of which approach is used to get to Mars, they all share a need to visualize and analyze their proposed campaign and evaluate the feasibility of the launch and on-orbit assembly segment of the campaign. The launch and assembly segment starts with flight hardware manufacturing and ends with final departure of a Mars Transfer Vehicle (MTV), or set of MTVs, from an assembly orbit near Earth. This paper describes a discrete event simulation based strategic visualization and analysis tool that can be used to evaluate the launch campaign reliability of any proposed strategy for exploration beyond low Earth orbit. The input to the simulation can be any manifest of multiple launches and their associated transit operations between Earth and the exploration destinations, including Earth orbit, lunar orbit, asteroids, moons of Mars, and ultimately Mars. The simulation output includes expected launch dates and ascent outcomes i.e., success or failure. Running 1,000 replications of the simulation provides the capability to perform launch campaign reliability analysis to determine the probability that all launches occur in a timely manner to support departure opportunities and to deliver their payloads to the intended orbit. This allows for quantitative comparisons between alternative scenarios, as well as the capability to analyze options for improving launch campaign reliability. Results are presented for representative strategies.

Cates, Grant↗
NASA NTRS2006

Simulation Modeling and Performance Evaluation of Space Networks

In space exploration missions, the coordinated use of spacecraft as communication relays increases the efficiency of the endeavors. To conduct trade-off studies of the performance and resource usage of different communication protocols and network designs, JPL designed a comprehensive extendable tool, the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE). The design and development of MACHETE began in 2000 and is constantly evolving. Currently, MACHETE contains Consultative Committee for Space Data Systems (CCSDS) protocol standards such as Proximity-1, Advanced Orbiting Systems (AOS), Packet Telemetry/Telecommand, Space Communications Protocol Specification (SCPS), and the CCSDS File Delivery Protocol (CFDP). MACHETE uses the Aerospace Corporation s Satellite Orbital Analysis Program (SOAP) to generate the orbital geometry information and contact opportunities. Matlab scripts provide the link characteristics. At the core of MACHETE is a discrete event simulator, QualNet. Delay Tolerant Networking (DTN) is an end-to-end architecture providing communication in and/or through highly stressed networking environments. Stressed networking environments include those with intermittent connectivity, large and/or variable delays, and high bit error rates. To provide its services, the DTN protocols reside at the application layer of the constituent internets, forming a store-and-forward overlay network. The key capabilities of the bundling protocols include custody-based reliability, ability to cope with intermittent connectivity, ability to take advantage of scheduled and opportunistic connectivity, and late binding of names to addresses. In this presentation, we report on the addition of MACHETE models needed to support DTN, namely: the Bundle Protocol (BP) model. To illustrate the use of MACHETE with the additional DTN model, we provide an example simulation to benchmark its performance. We demonstrate the use of the DTN protocol and discuss statistics gathered concerning the total time needed to simulate numerous bundle transmissions

network protocols↗
DOE OSTI2021

Evaluating MPI resource usage summary statistics

The Message Passing Interface (MPI) remains the dominant programming model for scientific applications running on today’s high-performance computing (HPC) systems. This dominance stems from MPI’s powerful semantics for inter-process communication that has enabled scientists to write applications for simulating important physical phenomena. MPI does not, however, specify how messages and synchronization should be carried out. Those details are typically dependent on low-level architecture details and the message characteristics of the application. Therefore, analyzing an application’s MPI resource usage is critical to tuning MPI’s performance on a particular platform. The result of this analysis is typically a discussion of the mean message sizes, queue search lengths and message arrival times for a workload or set of workloads. While a discussion of the arithmetic mean in MPI resource usage might be the most intuitive summary statistic, it is not always the most accurate in terms of representing the underlying data. In this paper, we analyze MPI resource usage for a number of key MPI workloads using an existing MPI trace collector and discrete-event simulator. Our analysis demonstrates that the average, while easy and efficient to calculate, is a useful metric for characterizing latency and bandwidth measurements, but may not be a good representation of application message sizes, match list search depths, or MPI inter-operation times. Additionally, we show that the median and mode are superior choices in many cases. We also observe that the arithmetic mean is not the best representation of central tendency for data that are drawn from distributions that are multi-modal or have heavy tails. Furthermore, the results and analysis of our work provide valuable guidance on how we, as a community, should discuss and analyze MPI resource usage data for scientific applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Discrete Event Execution with One-Sided and Two-Sided GVT Algorithms on 216,000 Processor Cores

Global virtual time (GVT) computation is a key determinant of the efficiency and runtime dynamics of parallel discrete event simulations (PDES), especially on large-scale parallel platforms. Here, three execution modes of a generalized GVT computation algorithm are studied on high-performance parallel computing systems: (1) a synchronous GVT algorithm that affords ease of implementation, (2) an asynchronous GVT algorithm that is more complex to implement but can relieve blocking latencies, and (3) a variant of the asynchronous GVT algorithm to exploit one-sided communication in extant supercomputing platforms. Performance results are presented of implementations of these algorithms on up to 216,000 cores of a Cray XT5 system, exercised on a range of parameters: optimistic and conservative synchronization, fine- to medium-grained event computation, synthetic and non-synthetic applications, and different lookahead values. Performance of up to 54 billion events executed per second is registered. Detailed PDES-specific runtime metrics are presented to further the understanding of tightly-coupled discrete event dynamics on massively parallel platforms.

Perumalla, Kalyan S↗
DOE OSTI2016

Model-based Dynamic Control of Speculative Forays in Parallel Computation

In simulations running in parallel, the processors would have to synchronize with other processors to maintain correct global order of computations. This can be done either by blocking computation until correct order is guaranteed, or by \textit{speculatively} proceeding with the best guess (based on local information) and later correcting errors if/as necessary. Since the gainful lengths of speculative forays depend on the dynamics of the application software and hardware at runtime, an online control system is necessary to dynamically choose and/or switch between the blocking and speculative strategies. In this paper, we formulate the reversible speculative computing in large-scale parallel computing as a dynamic linear feedback control (optimization) system model and evaluate its performance in terms of time and cost savings as compared to the traditional (forward) computing. We illustrate with an exact analogy in the form of vehicular travel under dynamic, delayed route information. The objective is to assist in making the optimal decision on what computational approach is to be chosen, by predicting the amount of time and cost savings (or losing) under different environments represented by different parameters and probability distribution functions. We consider the cases of Gaussian, exponential and log-normal distribution functions. The control system is intended for incorporating into speculative parallel applications such as optimistic parallel discrete event simulations to decide at runtime when and to what extent speculative execution can be performed gainfully.

Perumalla, Kalyan↗
DOE OSTI2017

Analysis of Operating Strategies Using Different Target Designs For 238Pu Production

An engineering effort is underway to re-establish capability to produce 238Pu oxide at the kilogram scale in the United States. A multi-step batch process is being developed to produce this important material. Recently, a portion of this process was studied using discrete-event simulation tools to determine whether the conceptual process might achieve its yearly production goal. The study showed the conceptual process can meet the yearly production goal under some circumstances, but process improvements would be needed to ensure greater likelihood of success. This study extends the work performed previously by examining the effects of changing the reactor target design on the yearly process output. Two new reactor target configurations are considered an aluminum-clad reactor target containing 50% greater 237Np oxide content than the original target, and a zirconium alloy-clad target using no aluminum. The results indicate that use of the new aluminum-clad target configuration may allow the process to achieve the same yearly production goal in less time using fewer targets. If the zirconium alloy-clad target is used, then even fewer targets would be needed to reach the production goal, but some process changes would be required to handle the zirconium cladding. The number of days needed to process a target batch to completion, and the steady state 238Pu oxide production rate, for each configuration are compared to the results from the initial simulation study.

campaign↗
DOE OSTI2024

Power System Operational Impacts of Electric Vehicle Dynamic Wireless Charging

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts.

dynamic wireless power transfer↗
DOE OSTI2024

Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues

Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.

09 - BIOMASS FUELS↗
DOE OSTI2023

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Estimating value of information for heliostat washing operations at solar thermal plants

Concentrating solar power (CSP) plants depend on thousands of heliostats whose reflectance declines as dust accumulates. Operators routinely measure reflectance to estimate soiling and, in turn, inform cleaning schedules, but the value of collecting more frequent or more accurate data has not been formally quantified. This study introduces a Monte Carlo discrete event simulation framework that integrates stochastic models of soiling, weather, and measurement error with a dynamic cleaning dispatch policy to estimate annual energy production and operations costs. Applied to two representative central-receiver field configurations, the results show that both the frequency and accuracy of reflectance measurements can meaningfully impact plant performance. In both case studies, reducing measurement intervals yields significant returns, with the energy gains greatly exceeding the cost of more frequent data collection. The simulation framework serves as a decision-support tool for CSP operators, allowing them to input site-specific soiling conditions, measurement accuracy, and survey frequency to evaluate the tradeoffs between data collection cost and energy recovery, and to identify measurement strategies that maximize plant profit.

14 SOLAR ENERGY↗