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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Evaluation of the Impact of Slab Foundation Heat Transfer on Heating and Cooling in Florida

During the last three decades of energy-efficiency research, there has been limited study of heat transfer to slab-on-grade foundations in cooling-dominated climates. Most experimental research has focused on the impact of slab-on-grade foundations and insulation schemes on heat losses in heating-dominated climates. This is surprising because the floor area in single-family homes is generally equal to wall area, window area, or attic area, all of which have been extensively evaluated for heat-transfer properties. Moreover, slab foundations are the most common foundation type in cooling-dominated climates. Slab-on-grade construction is very popular in southern states, accounting for 77% of new home floors according to 2014 U.S. Census data. There is a widespread perception that tile flooring, as opposed to carpet, provides a cooler home interior in warm climates. Empirical research is needed because building energy simulation software programs running DOE-2 and EnergyPlus engines often rely on simplified models to evaluate the influence of flooring on interior temperature, even though in some cases more detailed models exist. The U.S. Department of Energy Building America Partnership for Improved Residential Construction (BA-PIRC) performed experiments in the Florida Solar Energy Center’s Flexible Residential Test Facility intended to assess for the first time (1) how slab-on-grade construction influences interior cooling in a cooling-dominated climate and (2) how the difference in a carpeted versus uncarpeted building might influence heating and cooling energy use. Two nominally identical side-by-side residential buildings were evaluated during the course of 1 year, from 2014 to 2015: the east building with a pad and carpet floor and the west building with a bare slab floor. A detailed grid shows temperature measurements taken on the slab surface at various locations as well as at depths of 1.0 ft, 2 ft, 5.0 ft, 10.0 ft, and 20.0 ft below the surface. Temperature measurements were taken at both buildings for more than 3 years prior to the experiments to ensure that the ground and foundation temperatures had fully come into equilibrium.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Evaluation of the Impact of Slab Foundation Heat Transfer on Heating and Cooling in Florida

During the last three decades of energy-efficiency research, there has been limited study of heat transfer to slab-on-grade foundations in cooling-dominated climates. Most experimental research has focused on the impact of slab-on-grade foundations and insulation schemes on heat losses in heating-dominated climates. This is surprising because the floor area in single-family homes is generally equal to wall area, window area, or attic area, all of which have been extensively evaluated for heat-transfer properties. Moreover, slab foundations are the most common foundation type in cooling-dominated climates. Slab-on-grade construction is very popular in southern states, accounting for 77% of new home floors according to 2014 U.S. Census data. There is a widespread perception that tile flooring, as opposed to carpet, provides a cooler home interior in warm climates. Empirical research is needed because building energy simulation software programs running DOE-2 and EnergyPlus engines often rely on simplified models to evaluate the influence of flooring on interior temperature, even though in some cases more detailed models exist. The U.S. Department of Energy Building America Partnership for Improved Residential Construction (BA-PIRC) performed experiments in the Florida Solar Energy Center’s Flexible Residential Test Facility intended to assess for the first time (1) how slab-on-grade construction influences interior cooling in a cooling-dominated climate and (2) how the difference in a carpeted versus uncarpeted building might influence heating and cooling energy use. Two nominally identical side-by-side residential buildings were evaluated during the course of 1 year, from 2014 to 2015: the east building with a pad and carpet floor and the west building with a bare slab floor. A detailed grid shows temperature measurements taken on the slab surface at various locations as well as at depths of 1.0 ft, 2 ft, 5.0 ft, 10.0 ft, and 20.0 ft below the surface. Temperature measurements were taken at both buildings for more than 3 years prior to the experiments to ensure that the ground and foundation temperatures had fully come into equilibrium.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota.

Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically, it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. This manual offers Consortium for Advanced Simulation of Light Water Reactors (LWRs) (CASL) partners a guide to conducting Dakota-based VUQ studies for CASL problems. It motivates various classes of Dakota methods and includes examples of their use on representative application problems. On reading, a CASL analyst should understand why and how to apply Dakota to a simulation problem.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota.

Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota

Sandia’s Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a physics-based computational model. This can lend efficiency and rigor to manual parameter perturbation studies already being conducted by analysts. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. Dakota algorithms enrich complex science and engineering models, enabling an analyst to answer crucial questions of - Sensitivity: Which are the most important input factors or parameters entering the simulation, and how do they influence key outputs?; Uncertainty: What is the uncertainty or variability in simulation output, given uncertainties in input parameters? How safe, reliable, robust, or variable is my system? (Quantification of margins and uncertainty, QMU); Optimization: What parameter values yield the best performing design or operating condition, given constraints? Calibration: What models and/or parameters best match experimental data? In general, Dakota is the Consortium for Advanced Simulation of Light Water Reactors (CASL) delivery vehicle for verification, validation, and uncertainty quantification (VUQ) algorithms. It permits ready application of the VUQ methods described above to simulation codes by CASL researchers, code developers, and application engineers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

New Design Methods and Algorithms for Energy Efficient Multicomponent Distillation Column Trains (Final Report)

The major objectives of this project are to; first develop new methods and tools, and then incorporate them in a user-friendly software that will readily generate low-energy solutions for a large class of multicomponent distillation applications found in typical chemical and petrochemical plants. Having such methods and corresponding software at the disposal of the process engineers will allow chemical manufacturers of all sizes to reduce energy consumption of their grassroots as well as existing separation plants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗
DOE OSTI2014

Reducing EnergyPlus Run Time For Code Compliance Tools

Integration of the EnergyPlus ™ simulation engine into performance-based code compliance software raises a concern about simulation run time, which impacts timely feedback of compliance results to the user. EnergyPlus annual simulations for proposed and code baseline building models, and mechanical equipment sizing result in simulation run times beyond acceptable limits. This paper presents a study that compares the results of a shortened simulation time period using 4 weeks of hourly weather data (one per quarter), to an annual simulation using full 52 weeks of hourly weather data. Three representative building types based on DOE Prototype Building Models and three climate zones were used for determining the validity of using a shortened simulation run period. Further sensitivity analysis and run time comparisons were made to evaluate the robustness and run time savings of using this approach. The results of this analysis show that the shortened simulation run period provides compliance index calculations within 1% of those predicted using annual simulation results, and typically saves about 75% of simulation run time.

energyplus, simulation, runtime, run time, comchec↗
DOE OSTI2013

Roof Savings Calculator Suite

The software options currently supported by the simulation engine can be seen/experienced at www.roofcalc.com. It defaults all values to national averages with options to test a base-case (residential or commercial) building versus a comparison building with inputs for building type, location, building vintage, conditioned area, number of floors, and window-to-wall ratio, cooling system efficiency, type of heating, heating system efficiency, duct location, roof/ceiling insulation level, above-sheathing ventilation, radiant barrier, roof thermal mass, roof solar reflectance, roof thermal emittance, utility costs, roof pitch. The Roof Savings Caculator Suite adds utilities and website/web service and the integration of AtticSim with DOE-2.1E, with the end-result being Roof Savings Calculator.

New, Joshua R↗
DOE OSTI2017

ExaMPM

ExaMPM is a mini-application for the Material Point Method (MPM) for studying the application of MPM to future exascale computing systems. MPM is a general method for computational mechanics and fluids and is used in a wide variety of science and engineering disciplines to study problems with large deformations, phase change, fracture, and other phenomena. ExaMPM provides a reference implementation of MPM as described in the 1994 work of Sulsky et.al. (Sulsky, Deborah, Zhen Chen, and Howard L. Schreyer. "A particle method for history-dependent materials." Computer methods in applied mechanics and engineering 118.1-2 (1994): 179-196.). The software can solve basic MPM problems in solid mechanics using the original algorithm of Sulsky with explicit time integration, basic geometries, and free-slip and no-slip boundary conditions as described in the reference. ExaMPM is intended to be used as a starting point to design new parallel algorithms for the next generation of DOE supercomputers.

Slattery, Stuart R↗
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗
DOE OSTI2023

BEopt™ (Building Energy Optimization Tool) version 3.0.1 3/16/2023 [SWR-05-41]

The BEopt™ (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy. The BEopt software can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations. The BEopt software provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated. The BEopt software uses EnergyPlus®, the Department of Energy's flagship simulation engine. Simulation assumptions are based on ANSI/RESNET/ICC Standards and the Building America Housing Simulation Protocols. The sequential search optimization technique used by the BEopt software: Finds minimum-cost building designs at different target energy-savings levels Identifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference. Download A BEopt™ Version 3.0.1 Beta release (Mar. 16, 2023) is now available. Download the BEopt 3.0.1 Beta setup file.

Christensen, Craig↗
DOE OSTI2015

Traileka Glacier X-Stack. Final Scientific/Technical Report

The XStack Traleika Glacier (XSTG) project was a three-year research award for exploring a revolutionary exascale-class machine software framework. The XSTG program, including Intel, UC San Diego, Pacific Northwest National Lab, UIUC, Rice University, Reservoir Labs, ET International, and U. Delaware, had major accomplishments, insights, and products resulting from this three-year effort.

42 ENGINEERING↗
DOE OSTI2015

RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Diversified Therapeutic Phage Cocktails from Close Relatives of the Target Bacterium

This project tackles the antibiotic resistance crisis, developing a new method for discovering numerous efficacious bacteriophages for therapeutic cocktails against bacterial pathogens. The phage therapy approach to infectious disease, recently rekindled in U.S. medicine, requires numerous phages for each bacterial pathogen. Our approach 1) uses Sandia-unique software to identify dormant phages (prophages) integrated into bacterial chromosomes, 2) identifies prophage-laden bacteria that are close relatives of the target pathogenic strain to be killed, and 3) engineers away properties of these phages that are undesirable for therapy. We have perfected our phage-finding software, implemented our phage therapy strategy by targeting the pathogen Pseudomonas aeruginosa, and prepared new software to assist the phage engineering. We then turned toward Burkholderia pathogens, aiming to overcome the difficulty to transform these bacteria with a novel phage conjugation approach. Our work demonstrates the validity of a new approach to phage therapy for killing antibiotic resistant pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Exploring Sustainability in Scientific Software through Code Quality & Test Coverage Metrics

Context: Scientific open-source software (SciOSS) plays a foundational role in research and engineering, yet its long-term sustainability has often been overlooked and remains a significant concern. Objective: This study investigates the long-term sustainability of SciOSS through code and test quality metrics. Method: We analyze CASS Software Portfolio projects, classifying them by sustainability and comparing their code structure, test coverage, and links between code quality and testing across the dataset. Results: Sustainable projects show higher, more consistent test coverage and clearer code-test correlations, while unsustainable ones show weaker patterns. Overall, test coverage is low in scientific software, and high complexity and coupling reduce testability. Conclusion: In this study, we present a practical, data-driven approach for assessing sustainability in scientific software, offering a foundation for evaluating long-term software health and supporting future efforts in quality assurance and sustainability monitoring.

Md mushfiqur rahman, Sheikh [University of Tenness↗
DOE OSTI2020

Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency

Neuromorphic computing offers one path forward for AI at the edge. However, accessing and effectively utilizing a neuromorphic hardware platform is non-trivial. In this work, we present a complete pipeline for neuromorphic computing at the edge, including a small, inexpensive, low-power, FPGA-based neuromorphic hardware platform, a training algorithm for designing spiking neural networks for neuromorphic hardware, and a software framework for connecting those components. We demonstrate this pipeline on a real-world application, engine control for a spark-ignition internal combustion engine. We illustrate how we connect engine simulations with neuromorphic hardware simulations and training software to produce hardware-compatible spiking neural networks that perform engine control to improve fuel efficiency. We present initial results on the performance of these spiking neural networks and illustrate that they outperform open-loop engine control. We also give size, weight, and power estimates for a deployed solution of this type.

Schuman, Catherine↗
DOE OSTI2014

Narrowing the gap between the promise and reality of polyketide synthases as a synthetic biology platform

Engineering modular polyketide synthases (PKSs) has the potential to be an effective methodology to produce existing and novel chemicals. However, this potential has only just begun to be realized. We propose the adoption of an iterative design-build-test-learn paradigm to improve PKS engineering. We suggest methods to improve engineered PKS design by learning from laboratory-based selection; adoption of DNA design software and automation to build constructs and libraries more easily; tools for the expression of engineered proteins in a variety of heterologous hosts; and mass spectrometry-based high-throughput screening methods. Finally, lessons learned during iterations of the design-build-test-learn cycle can serve as a knowledge base for the development of a single retrosynthesis algorithm usable by both PKS experts and non-experts alike.

Poust, S↗