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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Design of Power Hardware-in-the-Loop Simulations for Integrated Starter–Generator Systems

The integrated starter-generator system (ISGS) is a combination of starter and generator for independent power systems in transportation. It replaces both a conventional starter and generator with a single set of highly integrated devices. A power hardware in the loop simulation that is flexible and can include the hardware under test is used to test the ISGS under representative field conditions. This paper utilizes the special structure of the ISGS and proposes an ISGS emulator (ISGSE) to develop and test the converter. The proposed ISGSE can be used to test a variety of motor drives or rectifiers including dynamic capabilities without necessitating a connection to a large motor load. To emulate the ISGS, the structure and operation principle in different modes are introduced in detail. Also, the issue of stability and accuracy is discussed in this paper. Furthermore, detailed simulation and experimental comparisons are carried out between the ISGS and the ISGSE, which validates the proposed ISGSE as an effective tool for designing and testing new motor drives.

42 ENGINEERING↗
DOE OSTI2017

Evaluation of CO 2 -Fluid-Rock Interaction in Enhanced Geothermal Systems: Field-Scale Geochemical Simulations

Recent studies suggest that using supercritical CO 2 (scCO 2 ) instead of water as a heat transmission fluid in Enhanced Geothermal Systems (EGS) may improve energy extraction. While CO 2 -fluid-rock interactions at “typical” temperatures and pressures of subsurface reservoirs are fairly well known, such understanding for the elevated conditions of EGS is relatively unresolved. Geochemical impacts of CO 2 as a working fluid (“CO 2 -EGS”) compared to those for water as a working fluid (H 2 O-EGS) are needed. The primary objectives of this study are (1) constraining geochemical processes associated with CO 2 -fluid-rock interactions under the high pressures and temperatures of a typical CO 2 -EGS site and (2) comparing geochemical impacts of CO 2 -EGS to geochemical impacts of H 2 O-EGS. The St. John’s Dome CO 2 -EGS research site in Arizona was adopted as a case study. A 3D model of the site was developed. Net heat extraction and mass flow production rates for CO 2 -EGS were larger compared to H 2 O-EGS, suggesting that using scCO 2 as a working fluid may enhance EGS heat extraction. More aqueous CO 2 accumulates within upper- and lower-lying layers than in the injection/production layers, reducing pH values and leading to increased dissolution and precipitation of minerals in those upper and lower layers. Dissolution of oligoclase for water as a working fluid shows smaller magnitude in rates and different distributions in profile than those for scCO 2 as a working fluid. It indicates that geochemical processes of scCO 2 -rock interaction have significant effects on mineral dissolution and precipitation in magnitudes and distributions.

58 GEOSCIENCES↗
DOE OSTI2024

Impact of refrigerant undercharge faults on building indoor conditions and HVAC system operation in residential Buildings: A simulation study

This study investigates the impact of refrigerant undercharge on indoor temperature and HVAC system performance in residential buildings. Simulation models for typical residential buildings in Orlando, FL and Indianapolis, IN were developed using the ResStock database. A refrigerant undercharge fault model was then applied to the simulations with varying levels of fault intensity. The paper offers an extensive analysis, revealing that variations in supply air temperature, equipment runtime, and cooling energy consumption due to the level of refrigerant undercharge faults are notably significant on a summer representative day. Similarly, on a winter representative day, changes in supply air temperature and runtime are significant as well as changes in supplemental heat energy consumption. We find that occupants may remain oblivious to these faults during the cooling season, particularly when the HVAC system is oversized; in that case, supply air temperature data could help detect a fault. Another challenge is that during the heating season, when the supplemental heater operates, it is difficult to identify a refrigerant undercharge fault using only indoor and supply air temperature data. Finally, this study finds that supply air temperature, equipment runtime, and supplemental heater energy consumption data can help in detecting refrigerant undercharge faults.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes' rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle these challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A numerical method for simulating variable density flows in membrane desalination systems

Here, we present a novel method for simulating unsteady, variable density, fluid flows in membrane desalination systems. By assuming the density varies only with concentration and temperature, the scheme decouples the solution of the governing equations into two sequential blocks. The first solves the governing equations for the temperature and concentration fields, which are used to compute all thermophysical properties. The second block solves the conservation of mass and momentum equations for the velocity and pressure. We show that this is computationally more efficient than schemes that iterate over the full coupled equations in one block. We verify that the method achieves second-order spatial-temporal accuracy, and we use the method to investigate buoyancy-driven convection in a desalination process called vacuum membrane distillation. Specifically, we show that with gravity properly oriented, variations in temperature and concentration can trigger a double-diffusive instability that enhances mixing and improves water recovery. We also show that the instability can be strengthened by providing external heating.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SURVEY SIMULATIONS OF A NEW NEAR-EARTH ASTEROID DETECTION SYSTEM

We have carried out simulations to predict the performance of a new space-based telescopic survey operating at thermal infrared wavelengths that seeks to discover and characterize a large fraction of the potentially hazardous near-Earth asteroid (NEA) population. Two potential architectures for the survey were considered: one located at the Earth–Sun L1 Lagrange point, and one in a Venus-trailing orbit. A sample cadence was formulated and tested, allowing for the self-follow-up necessary for objects discovered in the daytime sky on Earth. Synthetic populations of NEAs with sizes as small as 140 m in effective spherical diameter were simulated using recent determinations of their physical and orbital properties. Estimates of the instrumental sensitivity, integration times, and slew speeds were included for both architectures assuming the properties of newly developed large-format 10 μm HgCdTe detector arrays capable of operating at ∼35 K. Our simulation included the creation of a preliminary version of a moving object processing pipeline suitable for operating on the trial cadence. We tested this pipeline on a simulated sky populated with astrophysical sources such as stars and galaxies extrapolated from Spitzer Space Telescope and Wide-field Infrared Explorer data, the catalog of known minor planets (including Main Belt asteroids, comets, Jovian Trojans, planets, etc.), and the synthetic NEA model. Trial orbits were computed for simulated position-time pairs extracted from the synthetic surveys to verify that the tested cadence would result in orbits suitable for recovering objects at a later time. Our results indicate that the Earth–Sun L1 and Venus-trailing surveys achieve similar levels of integral completeness for potentially hazardous asteroids larger than 140 m; placing the telescope in an interior orbit does not yield an improvement in discovery rates. This work serves as a necessary first step for the detailed planning of a next-generation NEA survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

CFD Evaluation of Pressure Change Along Coolant Passages in Sodium-Cooled Fast Reactor with Nek5000

To support the design efforts of advanced sodium-cooled fast reactors (SFRs), a series of computational fluid dynamics (CFD) simulations are performed to investigate the pressure change along various flow passages in the proposed SFR system. The simulations are carried out with the state-of-the-art spectral element flow solver, Nek5000. Two specific case studies are presented in this paper: the flow exiting the axial neutron reflector channels and the flow entering the fuel pin bundle. Due to the high Reynolds numbers expected, a Reynolds-averaged Navier-Stokes (RANS) approach is necessary to model the turbulence. A newly developed regularized k-omega RANS model is adopted in the related CFD calculations. The first case study explores the effect of Reynolds number on the pressure change when flow exits the reflector channels. The pressure change in this case has two major contributors: the change due to wall friction and the Bernoulli effect. It is noted that the nondimensional pressure loss follows a log-linear trend up to Re = 10 5 , and then the trend is flattened. In the second case study, the advanced NekNek coupling capability is tested where an integral domain can be divided into multiple subdomains with coupling interfaces, which would greatly ease the meshing process of complex engineering geometries and potentially save computational resources. The preliminary results obtained so far confirm the consistency between the NekNek results and those produced by regular Nek5000 simulation. The presented work demonstrates the readiness and flexibility of the related CFD techniques, which is part of the broader effort to leverage cutting-edge CFD to inform the advanced nuclear reactor designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Data-driven Distributed Learning of Multi-agent Systems: A Koopman Operator Approach

Koopman operator theory provides a model-free technique for studying nonlinear dynamical systems purely from data. Since the Koopman operator is infinite-dimensional, researchers have developed several methods that provide a finite-dimensional approximation of the Koopman operator so that it can be applied for practical use cases. One common thing with most of the methods is that their solutions are obtained by solving a centralized minimization problem. In this work, we treat the dynamical system to be a multi-agent system and propose an algorithm to compute the finite-dimensional approximation of the Koopman operator in a distributed manner using the knowledge of the topology of the underlying multi-agent system. The proposed distributed approach is shown to be equivalent to the centralized learning problem and results in a sparse Koopman whose block structure mimics the Laplacian of the multi-agent system. Extensive simulation studies illustrate the proposed framework on the network of oscillators and the IEEE 68 bus system.

Nandanoori, Sai Pushpak↗
DOE OSTI2016

DERHCAT (Distributed Energy Resource Hosting Capacity Analysis Tool) [SWR-16-32]

NREL's advanced hosting capacity analysis and System Analysis Reports can help utilities, policymakers, and solar developers better understand the impact of adding new distributed photovoltaic (DPV) systems to the electrical distribution system. Advanced hosting capacity analysis considers the thresholds at which new DPV systems will trigger upgrades or changes to the electrical distribution system and evaluates the cost of different options for expanding the hosting capacity. It is one part of NREL's work to help stakeholders better understand the distribution system costs associated with integrating new DPV systems at different penetration levels. NREL's analysis uses a bottom-up methodology that involves simulating distribution systems. The analysis considers sequential increases in hosting capacity and corresponding upgrade costs from a baseline scenario with no DPV up to penetration levels greater than 100% of peak load.

Ding, Fei↗
DOE OSTI2019

Evolution of Ocean Heat Content Related to ENSO

As the strongest interannual perturbation to the climate system, El Niño–Southern Oscillation (ENSO) dominates the year-to-year variability of the ocean energy budget. Here we combine ocean observations, reanalyses, and surface flux data with Earth system model simulations to obtain estimates of the different terms affecting the redistribution of energy in the Earth system during ENSO events, including exchanges between ocean and atmosphere and among different ocean basins, and lateral and vertical rearrangements. This comprehensive inventory allows better understanding of the regional and global evolution of ocean heat related to ENSO and provides observational metrics to benchmark performance of climate models. Results confirm that there is a strong negative ocean heat content tendency (OHCT) in the tropical Pacific Ocean during El Niño, mainly through enhanced air–sea heat fluxes Q into the atmosphere driven by high sea surface temperatures. In addition to this diabatic component, there is an adiabatic redistribution of heat both laterally and vertically (0–100 and 100–300 m) in the tropical Pacific and Indian oceans that dominates the local OHCT. Heat is also transported and discharged from 20°S–5°N into off-equatorial regions within 5°–20°N during and after El Niño. OHCT and Q changes outside the tropical Pacific Ocean indicate the ENSO-driven atmospheric teleconnections and changes of ocean heat transport (i.e., Indonesian Throughflow). The tropical Atlantic and Indian Oceans warm during El Niño, partly offsetting the tropical Pacific cooling for the tropical oceans as a whole. While there are distinct regional OHCT changes, many compensate each other, resulting in a weak but robust net global ocean cooling during and after El Niño.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

A Comparative Study on the Environmental Impact of CO2 Supermarket Refrigeration Systems

Supermarket refrigeration systems have high environmental impact due to their large refrigerant charge and high leak rates. Accordingly, the interest in using natural refrigerants, such as carbon dioxide (CO2), and new refrigerant blends with low GWP in such systems is increasing. In this paper, an open-source Life Cycle Climate Performance (LCCP) framework is presented and used to compare the environmental impact of three supermarket refrigeration systems. These systems include a transcritical CO2 booster system, a cascade CO2/N-40 system, and a baseline R-404A multiplex direct expansion system. The study is performed for cities representing different climates within the USA using EnergyPlus to simulate the systems' hourly performance. Finally, a parametric analysis is performed to study the impact of annual leak rate on the systems' LCCP.

LCCP↗
DOE OSTI2026

Potential of Data Center Controls in Grid Services

The rapid proliferation of large data centers brings both challenges and opportunities for grid reliability. The data center resources and their potential flexibility have the potential to contribute resources to grid operations. Through capabilities like energy shifting and resource coordination, data centers can help reduce their net demand on the transmission network, as well as provide additional grid services to support reliable operation on the grid. While transient and long-term grid planning and operations are the scenarios that draw most attention, the quasi-steady state timeseries (QSTS) operation of data centers and grid bring interesting scenarios that can help evaluate the data center controls to aid grid services. This work is focused on modeling data centers for QSTS applications – incorporating the AI data center load profiles and building on the PNNL digital twin model for the thermal management loads to enable simulation studies to reveal the impact of data center controls on grid performance. This includes the integration of a QSTS battery and natural gas generator model to incorporate local resource impacts to the system. The simulation study is performed with a modified IEEE 24-Bus transmission system. Scenarios are focused on evaluating the data center load impacts on the transmission system and leveraging both data center and local generation controls to mitigate those impacts and provide additional grid services. The data center controls revealed the ability to contribute to two main kinds of grid services: preventing congestion on a weak grid by coordinating the data center resources with the collocated BESS and onsite generation; and the ability to help the grid operations during stressed times of operation like during a contingency. Leveraging these and other capabilities has the potential to help data centers become grid responsive assets, aiding in both their integration into the power system and grid reliability.

power grid simulation↗
DOE OSTI2015

Microcalcification detectability using a bench-top prototype photon-counting breast CT based on a Si strip detector

Purpose: To investigate the feasibility of detecting breast microcalcification (μCa) with a dedicated breast computed tomography (CT) system based on energy-resolved photon-counting silicon (Si) strip detectors. Methods: The proposed photon-counting breast CT system and a bench-top prototype photon-counting breast CT system were simulated using a simulation package written in MATLAB to determine the smallest detectable μCa. A 14 cm diameter cylindrical phantom made of breast tissue with 20% glandularity was used to simulate an average-sized breast. Five different size groups of calcium carbonate grains, from 100 to 180 μm in diameter, were simulated inside of the cylindrical phantom. The images were acquired with a mean glandular dose (MGD) in the range of 0.7–8 mGy. A total of 400 images was used to perform a reader study. Another simulation study was performed using a 1.6 cm diameter cylindrical phantom to validate the experimental results from a bench-top prototype breast CT system. In the experimental study, a bench-top prototype CT system was constructed using a tungsten anode x-ray source and a single line 256-pixels Si strip photon-counting detector with a pixel pitch of 100 μm. Calcium carbonate grains, with diameter in the range of 105–215 μm, were embedded in a cylindrical plastic resin phantom to simulate μCas. The physical phantoms were imaged at 65 kVp with an entrance exposure in the range of 0.6–8 mGy. A total of 500 images was used to perform another reader study. The images were displayed in random order to three blinded observers, who were asked to give a 4-point confidence rating on each image regarding the presence of μCa. The μCa detectability for each image was evaluated by using the average area under the receiver operating characteristic curve (AUC) across the readers. Results: The simulation results using a 14 cm diameter breast phantom showed that the proposed photon-counting breast CT system can achieve high detection accuracy with an average AUC greater than 0.89 ± 0.07 for μCas larger than 120 μm in diameter at a MGD of 3 mGy. The experimental results using a 1.6 cm diameter breast phantom showed that the prototype system can achieve an average AUC greater than 0.98 ± 0.01 for μCas larger than 140 μm in diameter using an entrance exposure of 1.2 mGy. Conclusions: The proposed photon-counting breast CT system based on a Si strip detector can potentially offer superior image quality to detect μCa with a lower dose level than a standard two-view mammography.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

$\mathrm{DRAGON}$: A multi-GPU orbital-free density functional theory molecular dynamics simulation package for modeling of warm dense matter

As progress in electronic structure theoretical methods is made, ab initio molecular dynamics (MD) based on orbital-free density functional theory (OF-DFT) is becoming increasingly more successful at substituting the traditional, very accurate but computationally costly Kohn–Sham (KS) approach for simulations of matter at the challenging warm dense matter (WDM) regime. However, despite the significant cost alleviation of eliminating the dependence on the KS orbitals, OF-DFT MD runs require ~10 2 to 10 3 CPU cores running for days, or even weeks, for simulations of systems comprised of 10 2 to 10 3 atoms, depending on thermodynamic conditions. Here we present DRAGON, a multi-GPU OF-DFT MD code for fast and efficient simulations of WDM. With a relatively small allocation of resources (4 to 8 GPU devices) it can provide an order of magnitude speedup for simulations containing $\mathscr{O}$(10 4 ) atoms and target systems composed of $\mathscr{O}$(10 5 ) atoms at conditions within the WDM regime, which is currently outside the capabilities of CPU codes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗
DOE OSTI2016

TH-CD-207A-11: Sensitivity Analysis of Action Limits for Real-Time EPID-Based Delivery Verification System Using Artificial Clinical Relevant Error Simulations

Purpose: A real-time patient treatment delivery verification system using EPID (Watchdog) has been developed as an advanced patient safety tool. In a pilot study data was acquired for 119 prostate and head and neck (HN) IMRT patient deliveries to generate body-site specific action limits using statistical process control. The purpose of this study is to determine the sensitivity of Watchdog to detect clinically significant errors during treatment delivery. Methods: Watchdog utilizes a physics-based model to generate a series of predicted transit cine EPID images as a reference data set, and compares these in real-time to measured transit cine-EPID images acquired during treatment using chi comparison (4%, 4mm criteria) after the initial 2s of treatment to allow for dose ramp-up. Four study cases were used; dosimetric (monitor unit) errors in prostate (7 fields) and HN (9 fields) IMRT treatments of (5%, 7%, 10%) and positioning (systematic displacement) errors in the same treatments of (5mm, 7mm, 10mm). These errors were introduced by modifying the patient CT scan and re-calculating the predicted EPID data set. The error embedded predicted EPID data sets were compared to the measured EPID data acquired during patient treatment. The treatment delivery percentage (measured from 2s) where Watchdog detected the error was determined. Results: Watchdog detected all simulated errors for all fields during delivery. The dosimetric errors were detected at average treatment delivery percentage of (4%, 0%, 0%) and (7%, 0%, 0%) for prostate and HN respectively. For patient positional errors, the average treatment delivery percentage was (52%, 43%, 25%) and (39%, 16%, 6%). Conclusion: These results suggest that Watchdog can detect significant dosimetric and positioning errors in prostate and HN IMRT treatments in real-time allowing for treatment interruption. Displacements of the patient require longer to detect however incorrect body site or very large geographic misses will be detected rapidly.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Open-source framework for power system transmission and distribution dynamics co-simulation

The promise of the smart grid entails more interactions between the transmission and distribution networks, and there is an immediate need for tools to provide the comprehensive modelling and simulation required to integrate operations at both transmission and distribution levels. Existing electromagnetic transient simulators can perform simulations with integration of transmission and distribution systems, but the computational burden is high for large-scale system analysis. For transient stability analysis, currently there are only separate tools for simulating transient dynamics of the transmission and distribution systems. In this paper, we introduce an open source co-simulation framework “Framework for Network Co-Simulation” (FNCS), together with the decoupled simulation approach that links existing transmission and distribution dynamic simulators through FNCS. FNCS is a middleware interface and framework that manages the interaction and synchronization of the transmission and distribution simulators. Preliminary testing results show the validity and capability of the proposed open-source co-simulation framework and the decoupled co-simulation methodology.

Huang, Renke↗