Search NASA⌕ Search

SEARCH · Search NASA

Results for “Simulation System”

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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Agent-based simulation and child protection systems: Rationale, implementation, and verification

Simulation models are an important tool used in health care and other disciplines to support operational research and decision-making. In the child protection literature, simulation models are an under-utilized source of research evidence. Here, in this paper, we describe the rationale for and the development of an agent-based simulation of a child protection system in the US. Using the investigation, prevention service, and placement histories of 600,000 children served in an urban child welfare system, we walk the reader through the development of a prototype known as OSPEDALE. The governing equations built into OSPEDALE probabilistically simulate the onset of investigations. Then, drawing from empirical survival distributions, the governing equations trace the probability of subsequent interactions with the system (recurrence of maltreatment, service referrals, and placement) conditional on the characteristics of children, their assessed risk level, and prior child protection system involvement. As an initial test of OSPEDALE's utility, we compare empirical admission counts with counts generated from OSPEDALE. Though the verification step is admittedly simple, the comparison shows that OSPEDALE replicates the empirical count of new admissions closely enough to justify further investment in OSPEDALE. Management of public child protection systems is increasingly research evidence-dependent. The emphasis on research evidence as a decision-support tool has elevated evidence acquired through randomized clinical trials. Though important, the evidence from clinical trials represents only one type of research evidence. Properly specified, simulation models are another source of evidence with real-world relevance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Comprehensive Simulation Study to Evaluate Future Vehicle Energy and Cost Reduction Potential

Under the umbrella of EERE’s Office of Sustainable Transportation, the U.S. Department of Energy’s (DOE) Vehicle Technologies Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) seek to develop sustainable, affordable, and efficient technologies for transportation of goods and people. Translating investments in advanced transportation component technologies and powertrains to estimate the potential for vehicle-level fuel savings is critical to understanding DOE’s impact and success in this mission For this study, Argonne National Laboratory (Argonne) simulated technologies funded by VTO and HFTO for light-duty vehicles across the following: Powertrain configurations (conventional, power-split hybrid electric vehicle, extended-range electric vehicle, battery electric drive, and fuel-cell vehicles); Vehicle classes (compact car, mid-size car, small sport utility vehicle [SUV], mid-size SUV, and pickup truck); Fuels (gasoline, diesel, natural gas, hydrogen, and battery electricity). We assessed each technology for five different timeframes: laboratory years 2015 (reference), 2020, 2025, 2030, and 2045. We assumed a delay of 5 years between laboratory year and model year (i.e., the year the technology is introduced into production). Finally, we included uncertainties for both technology performance and cost by considering two cases (note that these cases are not intended as predictions of future performance): Low case , aligned with DOE technology manager estimates of expected original equipment manufacturer (OEM) improvements based on business as usual regulatory and market environments; High case , aligned with aggressive technology advancements based on research and development (R&D) targets developed through support by VTO and HFTO. We estimated the energy and cost impact of different technologies using Autonomie (Argonne undated), a state-of-the-art vehicle system simulation tool developed by Argonne and used to assess the energy consumption, performance, and cost of multiple advanced vehicle technologies. The tool comprises a complete set of vehicle models to assess impacts across a wide range of classes (from light- to heavy-duty), powertrain configurations (from conventional to hybrid electric vehicles [HEVs], fuel cell electric vehicles [FCEVs], plug-in hybrid electric vehicles [PHEVs], and battery electric vehicles [BEVs]), components, and control strategies, including vehicle-level and component-level controls developed and calibrated using dynamometer test data. Autonomie has been used to support a wide range of studies: analyzing various component technologies, sizing powertrain components to meet different vehicle requirements, comparing the benefits of powertrain configurations, optimizing both heuristic and route-based vehicle energy control, and predicting transportation energy use when paired with a traffic modeling tool such as POLARIS. This report documents the assumptions made and the vehicle-level energy consumption benefits and associated technology costs estimated for various types of light-duty vehicles. Details regarding vehicle assumptions and simulation results are available in the spreadsheets accompanying this report.

08 HYDROGEN↗
DOE OSTI2017

Modeling for Stellar Feedback in Galaxy Formation Simulations

Various heuristic approaches to model unresolved supernova (SN) feedback in galaxy formation simulations exist to reproduce the formation of spiral galaxies and the overall inefficient conversion of gas into stars. Some models, however, require resolution-dependent scalings. We present a subresolution model representing the three major phases of supernova blast wave evolution—free expansion, energy-conserving Sedov–Taylor, and momentum-conserving snowplow—with energy scalings adopted from high-resolution interstellar-medium simulations in both uniform and multiphase media. We allow for the effects of significantly enhanced SN remnant propagation in a multiphase medium with the cooling radius scaling with the hot volume fraction, f{sub hot}, as (1−f{sub hot}){sup −4/5}. We also include winds from young massive stars and AGB stars, Strömgren sphere gas heating by massive stars, and a mechanism that limits gas cooling that is driven by radiative recombination of dense H ii regions. We present initial tests for isolated Milky Way-like systems simulated with the Gadget-based code SPHgal with improved SPH prescription. Compared to pure thermal SN input, the model significantly suppresses star formation at early epochs, with star formation extended both in time and space in better accord with observations. Compared to models with pure thermal SN feedback, the age at which half the stellar mass is assembled increases by a factor of 2.4, and the mass-loading parameter and gas outflow rate from the galactic disk increase by a factor of 2. Simulation results are converged for a variation of two orders of magnitude in particle mass in the range (1.3–130) × 10{sup 4} solar masses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Data assimilation in a solar dynamo model using Ensemble Kalman Filters: sensitivity and robustness in reconstruction of meridional flow speed

We implement an Ensemble Kalman Filter procedure using the Data Assimilation Research Testbed for assimilating “synthetic” meridional flow-speed data in a Babcock–Leighton-type flux-transport solar dynamo model. By performing several “observing system simulation experiments,” we reconstruct time variation in meridional flow speed and analyze sensitivity and robustness of reconstruction. Using 192 ensemble members including 10 observations, each with 4% error, we find that flow speed is reconstructed best if observations of near-surface poloidal fields from low latitudes and tachocline toroidal fields from midlatitudes are assimilated. If observations include a mixture of poloidal and toroidal fields from different latitude locations, reconstruction is reasonably good for ⩽40% error in low-latitude data, even if observational error in polar region data becomes 200%, but deteriorates when observational error increases in low- and midlatitude data. Solar polar region observations are known to contain larger errors than those in low latitudes; our forward operator (a flux-transport dynamo model here) can sustain larger errors in polar region data, but is more sensitive to errors in low-latitude data. An optimal reconstruction is obtained if an assimilation interval of 15 days is used; 10- and 20-day assimilation intervals also give reasonably good results. Assimilation intervals <5 days do not produce faithful reconstructions of flow speed, because the system requires a minimum time to develop dynamics to respond to flow variations. Reconstruction also deteriorates if an assimilation interval >45 days is used, because the system’s inherent memory interferes with its short-term dynamics during a substantially long run without updating.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Decentralized State Estimation and Remedial Control Action for Minimum Wind Curtailment Using Distributed Computing Platform

Intermittency of wind energy poses a great challenge for power system operation and control. Wind curtailment might be necessary at the certain operating condition to keep the line flow within the limit. Remedial Action Scheme (RAS) offers quick control action mechanism to keep reliability and security of the power system operation with high wind energy integration. In this paper, a new RAS is developed to maximize the wind energy integration without compromising the security and reliability of the power system based on specific utility requirements. A new Distributed Linear State Estimation (DLSE) is also developed to provide the fast and accurate input data for the proposed RAS. A distributed computational architecture is designed to guarantee the robustness of the cyber system to support RAS and DLSE implementation. The proposed RAS and DLSE is validated using the modified IEEE-118 Bus system. Simulation results demonstrate the satisfactory performance of the DLSE and the effectiveness of RAS. Real-time cyber-physical testbed has been utilized to validate the cyber-resiliency of the developed RAS against computational node failure.

17 WIND ENERGY↗
DOE OSTI2017

Analysis of the Effects of Connected–Automated Vehicle Technologies on Travel Demand

Connected–automated vehicle (CAV) technologies are likely to have significant effects not only on how vehicles operate in the transportation system, but also on how individuals behave and use their vehicles. While many CAV technologies—such as connected adaptive cruise control and ecosignals—have the potential to increase network throughput and efficiency, many of these same technologies have a secondary effect of reducing driver burden, which can drive changes in travel behavior. Such changes in travel behavior—in effect, lowering the cost of driving—have the potential to increase greatly the utilization of the transportation system with concurrent negative externalities, such as congestion, energy use, and emissions, working against the positive effects on the transportation system resulting from increased capacity. To date, few studies have analyzed the potential effects on CAV technologies from a systems perspective; studies often focus on gains and losses to an individual vehicle, at a single intersection, or along a corridor. However, travel demand and traffic flow constitute a complex, adaptive, nonlinear system. Therefore, in this study, an advanced transportation systems simulation model—POLARIS—was used. POLARIS includes cosimulation of travel behavior and traffic flow to study the potential effects of several CAV technologies at the regional level. Various technology penetration levels and changes in travel time sensitivity have been analyzed to determine a potential range of effects on vehicle miles traveled from various CAV technologies.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

NREL's Advanced Distribution Management System (ADMS) Test Bed

NREL's advanced distribution management system (ADMS) test bed is a vendor-neutral resource for evaluating existing and future ADMS functionalities in a realistic laboratory setting. The test bed uses Opal-RT's ePHASORsim and eMEGAsim products interfaced with an OpenDSS power system simulation through the HELICS cosimulation platform developed by multiple DOE laboratories; and with power and controller hardware. NREL will present an overview of the test bed and the technologies included within it, and also some examples of how the test bed has been used to address industry challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Risk-Constrained Reinforcement Learning for Inverter-Dominated Power System Controls

Here, this paper develops a risk-aware controller for grid-forming inverters (GFMs) to minimize large frequency oscillations in GFM inverter-dominated power systems. To tackle the high variability from loads/renewables, we incorporate a mean-variance risk constraint into the classical linear quadratic regulator (LQR) formulation for this problem. The risk constraint aims to bound the time-averaged cost of state variability and thus can improve the worst-case performance for large disturbances. The resulting risk-constrained LQR problem is solved through the dual reformulation to a minimax problem, by using a reinforcement learning (RL) method termed as stochastic gradient-descent with max-oracle (SGDmax). In particular, the zero-order policy gradient (ZOPG) approach is used to simplify the gradient estimation using simulated system trajectories. Numerical tests conducted on the IEEE 68-bus system have validated the convergence of our proposed SGDmax for GFM model and corroborate the effectiveness of the risk constraint in improving the worst-case performance while reducing the variability of the overall control cost.

Frequency control↗
DOE OSTI2022

RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)

RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.

Zhang, Xiangyu↗
DOE OSTI2019

Ongoing solution reproducibility of earth system models as they progress toward exascale computing

We present a methodology for solution reproducibility for the Energy Exascale Earth System Model during its ongoing software infrastructure development to prepare for exascale computers. The nonlinear chaotic nature of climate system simulations precludes traditional model verification approaches since machine precision differences—resulting from code refactoring, changes in software environment, and so on—grow exponentially to a different weather state. Here, we leverage the nature of climate as a statistical description of the atmosphere in order to establish model reproducibility. We evaluate the degree to which two-sample equality of distribution tests can confidently detect the change in climate from minor tuning parameter changes on model output variables in order to establish the level of difference that indicates a new climate. To apply this (baselined test), we target a section of the model’s development cycle wherein no intentional science changes have been applied to its source code. We compare an ensemble of short simulations that were conducted using a verified model configuration against a new ensemble with the same configuration but with the latest software infrastructure (Common Infrastructure for Modeling the Earth, CIME5.0), compiler versions, and software libraries. We also compare these against ensemble simulations conducted using the original version of the software infrastructure (CIME4.0) of the earlier model configuration, but with the latest compilers and software libraries, to test the impact of new compilers and libraries in isolation from additional software infrastructure. The two-sample equality of distribution tests indicates that these ensembles indeed represent the same climate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Impact of Distributed Wind on Bulk Power System Operations in ISO-NE: Preprint

The work presented in this paper aims to study the impact of a range of penetration levels of distributed wind on the operation of the electric power system at the transmission level. This paper presents a case study on the power system in Independent System Operator New England. It is analyzed using PLEXOS, a commercial power system simulation tool. The results show that increasing the integration of distributed wind reduces total variable electricity generation costs, coal- and gas-fired electricity generation, electricity imports, and CO2 emissions, and increases wind curtailment. The variability and uncertainty of wind power also increases the start-up and shutdown costs and ramping of most conventional power plants.

17 WIND ENERGY↗
DOE OSTI2020

A Strategy for Forced Oscillation Suppression

Wide-area time-synchronized measurements have recently revealed troublesome forced oscillations (FOs) within modern synchronized power grids. In some cases, these FOs represent a dangerous hazard to the system. Recent research has focused on locating the source of FOs to provide operators with knowledge for mitigating their impact locally. This paper presents a complementary mitigation strategy, which is to purposely induce a second oscillation into the grid which cancels the impact of the FO. Such a strategy is complementary in that it may provide valuable time to operators attempting to locate the FOs source and to determine how to rectify it. This paper presents a suppression control strategy which modulates controllable devices to automatically cancel the impact of the FO without the need for locating the source of the original FO. The strategy is based upon tuned feedback control. In this study, the approach is demonstrated on a simulation system via modulation of inverter-based generation.

42 ENGINEERING↗
DOE OSTI2014

Impact of Distributed Wind on Bulk Power System Operations in ISO-NE

The work presented in this paper aims to study the impact of a range of penetration levels of distributed wind on the operation of the electric power system at the transmission level. This paper presents a case study on the power system in Independent System Operator New England. It is analyzed using PLEXOS, a commercial power system simulation tool. The results show that increasing the integration of distributed wind reduces total variable electricity generation costs, coal- and gas-fired electricity generation, electricity imports, and CO2 emissions, and increases wind curtailment. The variability and uncertainty of wind power also increases the start-up and shutdown costs and ramping of most conventional power plants.

17 WIND ENERGY↗
DOE OSTI2022

Optically connected memory for disaggregated data centers

Recent advances in integrated photonics enable the implementation of reconfigurable, high-bandwidth, and low energy-per-bit interconnects in next-generation data centers. We propose and evaluate an Optically Connected Memory (OCM) architecture that disaggregates the main memory from the computation nodes in data centers. OCM is based on micro-ring resonators (MRRs), and it does not require any modification to the DRAM memory modules. We calculate energy consumption from real photonic devices and integrate them into a system simulator to evaluate performance. Here, our results show that (1) OCM is capable of interconnecting four DDR4 memory channels to a computing node using two fibers with 1.02 pJ energy-per-bit consumption and (2) OCM performs up to 5.5× faster than a disaggregated memory with 40G PCIe NIC connectors to computing nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Engineering Analysis Baseline Model Requirements

The purpose of this document is to set requirements for the development, documentation, implementation, and maintenance of engineering analysis baseline models used by the Advanced Engineering and Analysis group to model and simulate systems. The intended audience of this document is the Engineering Technology and Design division Advanced Engineering and Analysis group—in particular the baseline model owners and users—and the Group Leaders and members of the Systems Engineering groups. Section 1 presents a discussion of general concepts related to engineering analysis models and baseline models, including definitions of common terms used in this requirements document. It also presents the purpose and intentions of creating and using baseline models and exposes some underlying assumptions about what baseline models are supposed to be. Section 2 presents requirements on the general categories of: the Advanced Engineering and Analysis Group Leader and the baseline model owner; parts, materials, and load cases; the process of generating and using the model; and how the baseline model will be stored, maintained, and documented. This document presents requirements on the baseline model as well as some aspects of the development process and the people responsible for the development; it does not address how the results of simulations utilizing these models will be used to make assessments

42 ENGINEERING↗
DOE OSTI2017

Electric train energy consumption modeling

For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error of 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗