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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Verification of a Modeling Toolkit for the Design of Building Electrical Distribution Systems

DC electrical distribution systems offer many potential advantages over their AC counterparts. They can facilitate easier integration with distributed energy resources, improve system energy efficiency by eliminating AC/DC converters at end-use devices (e.g., laptop chargers), and reduce installation material, time, and cost. However, DC electrical distribution systems present additional design considerations, largely resulting from potentially greater magnitude and variation in cable losses. Modeling and simulation are rarely used to design such systems. However, the greater dependency of DC system energy efficiency on design choices such as distribution voltages, architecture, and integration of PV and BESS suggests that modeling and simulation may be required. Such system performance analysis is currently not a standard practice, in part due to limited availability and validation of capable software tools. This paper characterizes the accuracy of a Modelica-based Building Electrical Efficiency Analysis Model (BEEAM) toolkit, as a precursor for validating its use to perform system performance analysis and inform design decisions. The study builds upon previous verification research by characterizing complete systems comprised of commercially available equipment, and providing a more detailed analysis of simulation results. Five lighting systems with varying electrical distribution architectures were designed using market-available equipment, installed in a laboratory environment, modeled using BEEAM, and simulated using three Modelica integrated development environments (IDEs). Simulated and measured results were compared to characterize toolkit accuracy. Initial results revealed that simulated performance was mostly within ±5% of measured system-level and device-level performance. While simulation results were not found to be dependent on the IDE, some Modelica compiler interoperability issues were identified. Although the BEEAM toolkit showed promise for the targeted use case, further work is needed to determine whether the demonstrated 5% accuracy is sufficient for making real-world design decisions, and for BEEAM to advance from an interesting research tool to one that can impact real-world building projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2014

Development of a Twin-Spool Turbofan Engine Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS)

The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) is a tool that has been developed to allow a user to build custom models of systems governed by thermodynamic principles using a template to model each basic process. Validation of this tool in an engine model application was performed through reconstruction of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) (v2) using the building blocks from the T-MATS (v1) library. In order to match the two engine models, it was necessary to address differences in several assumptions made in the two modeling approaches. After these modifications were made, validation of the engine model continued by integrating both a steady-state and dynamic iterative solver with the engine plant and comparing results from steady-state and transient simulation of the T-MATS and C-MAPSS models. The results show that the T-MATS engine model was accurate within 3% of the C-MAPSS model, with inaccuracy attributed to the increased dimension of the iterative solver solution space required by the engine model constructed using the T-MATS library. This demonstrates that, given an understanding of the modeling assumptions made in T-MATS and a baseline model, the T-MATS tool provides a viable option for constructing a computational model of a twin-spool turbofan engine that may be used in simulation studies.

numerical simulation↗
DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Towards Digital and Performance-Based Supervisory HVAC Control Delivery

Upgrading supervisory HVAC control in commercial buildings is one of the most attractive decarbonization tools at our disposal. Modern controls are software programs and can in theory be deployed at scale and with a low up-front carbon "pulse". In practice, however, control delivery is a disjointed and inefficient process, dominated by manual handoffs of imprecise English language documents. A particularly high barrier exists between control implementation and building energy modeling (BEM) which results in control sequences typically not being tested for correctness or performance before implementation. Together with industry partners, DOE and the national labs are developing an ecosystem of tools and standards that can support fully digital performance-based control delivery workflows. This paper describes this ecosystem, which consists of three mutually supportive efforts. Semantic models of buildings and their systems enable automatic configuration and installation of control software. Platform-neutral control descriptions separate control algorithms from control platforms and enable the creation of libraries of reference control implementations. Dynamic whole-building energy-control simulation that can execute physically realistic control sequences makes it possible to test and evaluate the performance of control sequences and then directly compile them for installation and execution in control systems. In addition to digitizing and streamlining project-level control delivery, these standards and related software support benchmarking of control algorithms, both rule-based and optimization-based, and help to both advance the state of the art and to implement ratings and programs that encourage the adoption of high-performance control.

building controls↗
DOE OSTI2026

A prototype cooling blanket for mitigating occupant overheating risk in a hot indoor environment: Modeling and assessments

Conventional ways of cooling a room or an entire house for occupant thermal comfort during summer consume a significant amount of energy and are vulnerable to overheating risk during power outages that lead to loss of cooling system operations. This study investigates a low-power cooling blanket, as a Personal Cooling System (PCS), that covers the upper human body for direct cooling during a five-day heat wave in a single-family house. A modeling framework is developed for evaluating the thermal and energy performance of the cooling blanket, which builds upon the co-simulation of three models: a house energy model, a personal thermal comfort model, and a cooling blanket model. Simulation results show that under the power outage scenario, the cooling blanket can greatly reduce the occupant heat stress with a reduction of daily hours of exceedance (discomfort hours defined as TSV>2) by up to 17.2 h (a 95.3 % improvement from the baseline power outage without the blanket). The cooling blanket, equipped with an innovative electrocaloric heat pump (COP as high as 10.1) consumes 6.31 W and can be operated by a portable battery for several days. The cooling blanket consumes only 0.28 % of the electricity of a central air-conditioning system running to provide cooling for the whole house during the five-day heatwave period. The findings justify further research of electrocaloric wearable PCS as low-power effective cooling to ensure thermal survivability of occupants during extreme indoor environments.

Electrocaloric heat pump↗
DOE OSTI2025

Artificial Intelligence/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)

This collaborative project integrated an improved version of the Artificial Intelligence/Deep Learning FRNN prediction and control software into the real-time DIII-D PCS (plasma control system). A key AI/DL software challenge is to build a modern high-performance computing (HPC) enabled “synthetic plasma simulator” capable of carrying out HPC-driven real-time plasma control applications. This involves development of a deep learning framework to train the surrogate model for a first-principles-based instability analysis simulator (“SGTC”) derived from the global gyrokinetic code GTC. The role of SGTC is to provide accurate and detailed plasma instability information from a real-time AI-based simulator capability to complement the deep learning prediction and control from experimentally-measured signals, such as ECE Imaging, supplemented by synthetic SGTC-ECEI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1998

Development and Testing of Automatically Generated ACS Flight Software for the MAP Spacecraft

By integrating the attitude determination and control system (ACS) analysis and design, flight software development, and flight software testing processes, it is possible to improve the overall spacecraft development cycle, as well as allow for more thorough software testing. One of the ways to achieve this integration is to use code-generation tools to automatically generate components of the ACS flight software directly from a high-fidelity (HiFi) simulation. In the development of the Microwave Anisotropy Probe (MAP) spacecraft, currently underway at the NASA Goddard Space Flight Center, approximately 1/3 of the ACS flight software was automatically generated. In this paper, we will examine each phase of the ACS subsystem and flight software design life cycle: analysis, design, and testing. In the analysis phase, we scoped how much software we would automatically generate and created the initial interface. The design phase included parallel development of the HiFi simulation and the hand-coded flight software components. Everything came together in the test phase, in which the flight software was tested, using results from the HiFi simulation as one of the bases of comparison for testing. Because parts of the spacecraft HiFi simulation were converted into flight software, more care needed to be put into its development and configuration control to support both the HiFi simulation and flight software. The components of the HiFi simulation from which code was generated needed to be designed based on the fact that they would become flight software. This process involved such considerations as protecting against mathematical exceptions, using acceptable module and parameter naming conventions, and using an input/output interface compatible with the rest of the flight software. Maintaining good configuration control was an issue for the HiFi simulation and the flight software, and a way to track the two systems was devised. Finally, an integrated test approach was devised to support flight software testing at both the unit- and build-test levels using the HiFi simulation to generate data for performance verification. Another benefit of the simulation and code-generation application used on the MAP project is that it supported bringing flight software and test data into the HiFi simulation environment. It was possible to integrate parts of the hand-coded flight software into the HiFi simulation, and also possible to import flight software test data for comparison and performance verification. This capability was used to incorporate the flight software Kalman filter into the HiFi simulation. This enabled us to greatly increase the amount of testing that could be done on the filter, because we could exert a greater degree of control over the software-only simulation than over the flight software test environment. Also, since the simulation could be used to run the Kalman filter faster than real time, our testing efficiency was greatly increased. We will conclude our discussion with a summary of the lessons learned thus far using automatically- generated code for the MAP project, and the spacecraft status as we work towards our scheduled launch in the year 2000.

ODonnell, James R., Jr.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-20739-DND

Overview of LaRC's Comprehensive Digital Transformation strategy. Includes foundational items such as modeling & simulation, big data analytics, high performance computing, and advanced information technology. Builds upon the foundation to recommend advanced "virtual capabilities," such as a virtual flight test capability to complement flight testing and wind tunnels.

Ed McLarney↗
NASA NTRSDate not supplied

In-Depth Modeling and Simulation Analysis of Artemis Missions Using the Impact Probabilistic Risk Assessment Tool

BACKGROUND The Artemis campaign is a Moon exploration program with a series of six planned missions, five of which will be crewed. These five crewed missions will contain a single mission segment (space flight), or multiple mission segments involving space flight (Orion), lunar landing (LTV) and/or space habitat (Gateway). Each crewed segment faces the risk of unique medical conditions, necessitating medical sets/kits tailored to those specificities. To support and enable a data-driven and evidence-based decision-making process through out a mission’s life cycle, a software tool called IMPACT was developed. Using probabilistic risk assessment (PRA) methodologies, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool built for analyzing the possibility of encountering complex medical risks during space flight, and for identifying the medical resources and capabilities needed to treat those potential at-risk medical conditions. IMPACT achieves this by performing hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. During an extended simulation modeling phase, IMPACT generated analytical results for medical risks, and the medical resources and capabilities to address those risks, for every segment of every crewed Artemis mission. This presentation will highlight the reliability, consistency and validity of IMPACT’s computational modeling techniques and will showcase the library of analytical outcomes generated for the Artemis missions. OVERVIEW During the early stages of IMPACT’s design, architecture and technical requirements collection, “scenarios” (use cases) - achievement goals required for acceptance testing, were identified by stakeholders. IMPACT successfully completed the scenario testing requirements and undertook an extensive operational run phase utilizing a wide range of input combinations with a goal of delivering a cohesive, trustworthy, reliable, vast, and diverse body of evidence. The intent of these modeling runs was to validate consistency in output, ensure solidity of executable operations and to streamline processes by identifying areas requiring efficiency improvements. Using the many missions of Artemis, IMPACT ran variations of operational runs to assess the output for acceptable, as well as unusual characteristics. This rigorous long-term “shakedown” analysis was implemented to help build a collective body of evidence to aid in securing a high level of confidence, reliability, and validity in the output, whether from the applicational components of IMPACT, or the entirety of the operational process. ANTICIPATED ANALYSIS AND CONCLUSION This presentation will discuss the various categories of input criteria; the comparisons in the application of these input criteria to various Artemis missions; the preparation and collection of the body of evidence, and reliability of the computational modeling techniques. This paper serves as an initial analytical overview of IMPACT’s probabilistic risk assessment (PRA) medical risk outputs covering Artemis missions and is not intended to be deemed the official medical response for the Artemis campaign.

Crew Composition↗
DOE OSTI2022

An Interactive Visualization Tool for Large-Scale Building Stock Modeling: Preprint

Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.

big data↗
NASA NTRS2007

A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues

Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.

Tucker, David A.↗
DOE OSTI2022

Defining and applying an electricity demand flexibility benchmarking metrics framework for grid-interactive efficient commercial buildings

Building demand flexibility (DF) research has recently gained attention. To unlock building DF as a predictable grid resource, we must establish a quantitative understanding of the resource size, performance variability, and predictability based on large empirical datasets. Researchers have proposed various sets of theoretical metrics to measure this performance. Some metrics have been applied to simulation results, but most fall short of exploring the complexities in real building applications. There are practical metrics used in individual demand response field studies but they alone cannot fulfil the job of DF benchmarking across a diverse group of buildings. The electrical grid's geographically diverse and changing nature presents challenges to comparing building DF performance measured under different conditions (i.e., benchmarking DF). To address this challenge, a novel DF benchmarking framework focused on load shedding and shifting is presented; the foundation is a set of simple, proven single-event metrics with attributes describing event conditions. These enable benchmarking and visualization in different dimensions for identifying trends that represent how these attributes influence DF. To test its feasibility and scalability, the DF framework was applied to two case studies of 11 office buildings and 121 big-box retail buildings with demand response participation data. Furthermore, these examples provided a pathway for using both building level benchmarking and aggregation to extract insights into building DF about magnitude, consistency, and influential factors. Potential applications of the framework and real-world values have been identified for grid and building stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2006

Propulsion IVHM Technology Experiment

The Propulsion IVHM Technology Experiment (PITEX) successfully demonstrated real-time fault detection and isolation of a virtual reusable launch vehicle (RLV) main propulsion system (MPS). Specifically, the PITEX research project developed and applied a model-based diagnostic system for the MPS of the X-34 RLV, a space-launch technology demonstrator. The demonstration was simulation-based using detailed models of the propulsion subsystem to generate nominal and failure scenarios during captive carry, which is the most safety-critical portion of the X-34 flight. Since no system-level testing of the X-34 Main Propulsion System (MPS) was performed, these simulated data were used to verify and validate the software system. Advanced diagnostic and signal processing algorithms were developed and tested in real time on flight-like hardware. In an attempt to expose potential performance problems, the PITEX diagnostic system was subjected to numerous realistic effects in the simulated data including noise, sensor resolution, command/valve talkback information, and nominal build variations. In all cases, the PITEX system performed as required. The research demonstrated potential benefits of model-based diagnostics, defined performance metrics required to evaluate the diagnostic system, and studied the impact of real-world challenges encountered when monitoring propulsion subsystems.

Chicatelli, Amy K.↗
DOE OSTI2025

OpenFerro v0.1.0

OpenFerro is a Python package for on-lattice atomistic dynamics simulation of ferroic materials. OpenFerro is based on JAX, a high-performance linear algebra package supporting auto-differentiation and GPU acceleration. OpenFerro is designed to minimize the effort required to build on-lattice Hamiltonian models, and to perform molecular dynamics (MD) and Landau-Lifshitz-Gilbert simulations. Unlike existing codes, OpenFerro provides a unified interface to model different types of local order parameters.

Xie, Pinchen [Lawrence Berkeley National Laborator↗
NASA NTRS1976

Numerical simulation of tornado wind loading on structures

A numerical simulation of a tornado interacting with a building was undertaken in order to compare the pressures due to a rotational unsteady wind with that due to steady straight winds used in design of nuclear facilities. The numerical simulations were performed on a two-dimensional compressible hydrodynamics code. Calculated pressure profiles for a typical building were then subjected to a tornado wind field and the results were compared with current quasisteady design calculations. The analysis indicates that current design practices are conservative.

Maiden, D. E.↗
NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity (Pilot Egress Fitness)

As NASA prepares for exploration missions, it will be critical to understand and build upon known crew capabilities. Specifically, we need to know the functional capacities of crew at different stages of a mission and characterize these profiles so that the appropriate vehicle requirements and mission concepts of operations (ConOps) can be developed. One of the most complex phases of any missions is when there is a transition between gravity environments. For instance, both physiological adaptation to microgravity and subsequent re-entry into a gravity environment result in reduced functional capacity, even with rigorous adherence to inflight countermeasures. Quantification of the astronauts’ post-landing functional performance is necessary to design ConOps for exploration missions. Specifically, these two high-risk tasks may have to be performed soon after gravity transitions: •Unassisted capsule egress task after return to Earth •Planetary extravehicular activity (EVA) soon after landing on Mars or the Moon This study has been broken down into two phases. A pilot phase to assess the overall feasibility and demonstrate the capability to do these tasks shortly after landing and the full Egress Fitness study, which will be part of the CIPHER complement. This study uses a functional task approach to characterize performance of these high-risk tasks in long-duration ISS crewmembers before flight and shortly after return to Earth. Prior to any testing, each astronaut subject completes a suit fit check to ensure adequate sizing and mobility to be able to complete the EVA tasks. Pilot Egress Fitness pre-flight and post-flight testing includes an Earth based emergency egress out of a functional capsule mockup, and a short Mars gravity EVA simulation including suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. Pre-flight testing can occur almost anytime pre-flight, but post-flight scheduling is much more critical with the capsule egress test occurring 1-4 hours after landing and the planetary EVA approximately 18-36 hours after landing. Data collected for both tasks includes task completion time, photo, and video. The EVA portion also includes collection of metabolic and heart rate. Pilot Egress Fitness study has completed baseline pre-flight testing on 3 astronaut subjects. Post-flight testing of the first two subjects will be completed in November 2021 and the final subject around March 2022. Results and lessons learned from this pilot study will inform the full Egress Fitness study, which will incorporate additional pre-flight sessions, longer EVA tasks, and post-flight testing on R+1, 4, and 7 to characterize the timeframe of recovery

J R Norcross↗
DOE OSTI2022

Home energy management under realistic and uncertain conditions: A comparison of heuristic, deterministic, and stochastic control methods

We report home energy management systems (HEMS) have been shown to reduce energy bills and to provide grid services including peak demand reduction and demand flexibility. However, uncertainty in residential energy systems is a significant issue and can reduce the benefits of a HEMS to the homeowner or grid operator. Sources of uncertainty include weather forecasts, predictions of energy-related occupant activities (e.g., hot water draws), and parameter estimation for the building envelope and energy-consuming equipment. This paper tackles the problem of uncertainty by developing a framework that simulates HEMS in uncertain conditions and evaluates the performance of multiple control strategies. A linear, reduced-order residential building model for model predictive control applications is derived and compared to a full-order model. Stochastic model predictive control is shown to perform better than deterministic and heuristic methods when considering realistic forecasts with uncertainty. The framework can evaluate the performance of HEMS in real-world applications, which can help de-risk HEMS deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

The hygrothermal performance of continuous and cavity wood fiber insulation

Wood fiber insulation is an emerging material known for its effective thermal performance and moisture management properties, making it a compelling alternative to conventional insulation. Its vapor permeability and ability to regulate indoor humidity contribute to improved building durability and comfort, particularly in varying climate conditions. The goal of this project is to characterize the hygrothermal performance of a new wood fiber insulation product line in U.S. climate zones and to facilitate the design and construction of the product in residential and light commercial building envelopes. This study investigates the thermal and hygrothermal performance of wood fiber insulation, both as continuous and cavity insulation. The research employs an exhaustive simulation task and an environmental chamber test of a wood fiber insulation. Over 400 simulations were conducted to study the hygrothermal characteristics of bio-based wood fiber insulation in various building envelope configurations across four climate zones. Environmental chamber tests were conducted under controlled winter conditions representative of Climate Zone 5A (Chicago, IL) to complement the simulation results. The chamber tests focused on the hygrothermal performance of the wood fiber insulation and the sheathing board to assess the insulation's ability to manage moisture in a cold climate. Simulation and environmental chamber test results were analyzed to evaluate the insulation's consistency and efficacy across diverse climatic zones. Results show that with a proper moisture control strategy, both cavity and continuous wood fiber insulation can work properly in both new and retrofit constructions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗