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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A survey study on arsenic speciation in coal fly ash and insights into the role of coal combustion conditions

Coal fly ashes (CFAs) are the low-density byproducts of the coal combustion process. Improper or uncontrolled CFA disposal poses significant environmental and health concerns due to the potential leaching of toxic heavy metals such as arsenic (As). Previous studies have investigated the content and speciation of As in different CFA samples, yet systematic information on As speciation in CFA with representative coal source and combustion conditions is still missing. Based on a recent survey study on the typical coal sources and combustion conditions across the U.S., this study selected 19 representative CFA samples to systematically investigate As speciation and potential correlations with these parameters. The composition, morphology, mineralogy, and As speciation of these CFA samples were characterized by complementary analytical, microscopic, and spectroscopic techniques. Synchrotron X-ray spectroscopy and microscopy analyses revealed the dominant As oxidation state to be As(V) and with strong associations to Ca, with the exception of 3 samples that had 19–51% As(III), likely due to the use of selective catalytic reduction (SCR) process. Principal component analysis was conducted to identify potential correlations of As concentration and oxidation state with parameters such as major element content, loss on ignition (LOI), average particle size, coal source, and combustion condition. Al 2 O 3 and FeO content were found to capture a majority of the variability. Further, results from this study provide fundamental basis for understanding the correlations between coal source, combustion conditions, CFA characteristics, and As speciation, and providing insights for downstream beneficial utilization or disposal management.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Modeling, control, and dynamic performance analysis of a reverse osmosis desalination plant integrated within hybrid energy systems

An RO (reverse osmosis) desalination plant is proposed as an effective, FLR (flexible load resource) to be integrated into HES (hybrid energy systems) to support various types of ancillary services to the electric grid, under variable operating conditions. To study the dynamic (transient) analysis of such system, among the various unit operations within HES, special attention is given here to the detailed dynamic modeling and control design of RO desalination process with a spiral-wound membrane module. The model incorporates key physical phenomena that have been investigated individually into a dynamic integrated model framework. In particular, the solution-diffusion model modified with the concentration polarization theory is applied to predict RO performance over a large range of operating conditions. Simulation results involving several case studies suggest that an RO desalination plant, acting as a FLR, can provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess electrical energy. Here, the incorporation of additional commodity (fresh water) produced from a FLR allows a broader range of HES operations for maximizing overall system performance and profitability. For the purpose of assessing the incorporation of health assessment into process operations, an online condition monitoring approach for RO membrane fouling supervision is addressed in the case study presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Sustainable Thorium Nuclear Fuel Cycles: A Comparison of Intermediate and Fast Neutron Spectrum Systems

This paper presents analyses of possible reactor representations of a nuclear fuel cycle with continuous recycling of thorium and produced uranium (mostly U-233) with thorium-only feed. The analysis was performed in the context of a U.S. Department of Energy effort to develop a compendium of informative nuclear fuel cycle performance data. The objective of this paper is to determine whether intermediate spectrum systems, having a majority of fission events occurring with incident neutron energies between 1 eV and 10 5 eV, perform as well as fast spectrum systems in this fuel cycle. The intermediate spectrum options analyzed include tight lattice heavy or light water-cooled reactors, continuously refueled molten salt reactors, and a sodium-cooled reactor with hydride fuel. All options were modeled in reactor physics codes to calculate their lattice physics, spectrum characteristics, and fuel compositions over time. Based on these results, detailed metrics were calculated to compare the fuel cycle performance. These metrics include waste management and resource utilization, and are binned to accommodate uncertainties. The performance of the intermediate systems for this selfsustaining thorium fuel cycle was similar to a representative fast spectrum system. However, the number of fission neutrons emitted per neutron absorbed limits performance in intermediate spectrum systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Phenomena Identification and Ranking Table (PIRT) for heat pipes

Heat pipes are advanced passive thermal management devices that utilize phase change and capillary action to achieve efficient heat transfer. However, due to the complexity of the phenomena coupled in heat pipes, including capillary, phase change, turbulence, and compressibility effects, there are high uncertainties in the predictability of their operational regimes and performance. This PIRT exercise, conducted as a collaborative effort involving the Department of Energy (DOE) Microreactor Program (MRP), the Nuclear Regulatory Commission (NRC), and university partners systematically identifies, reviews, and prioritizes critical phenomena affecting the operation of heat pipes based on their importance and knowledge levels. Additional analyses and discussion are provided for phenomena with high importance and low knowledge, such as wick de-wetting, critical heat flux, contact angles, and pressure dynamics. The discussions included the recognizing challenges and proposing future research directions for both modeling and simulation and experimental efforts. Additionally, the report addresses phenomena with medium importance and low knowledge that could impact heat pipe operation during non-normal or transient operation, including frozen startup, laminar to turbulent transition, geyser boiling, wick priming, underfilling conditions, surface roughness of the wick, NCGs trapped in the wick, and the timescales of startup and shutdown. In conclusion, this comprehensive evaluation serves as a valuable resource for guiding future research and development efforts, supporting the successful integration of heat pipes into critical applications such as nuclear reactors, and contributing to the advancement of heat pipe technologies in safety-critical industries.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2020

Brackish water desalination using reverse osmosis and capacitive deionization at the water-energy nexus

Here, we present a critical review of the reported performance of reverse osmosis (RO) and capacitive deionization (CDI) for brackish water (salinity < 5.0 g/L) desalination from the aspects of engineering, energy, economy and environment. We first illustrate the criteria and the key performance indicators to evaluate the performance of brackish water desalination. We then systematically summarize technological information of RO and CDI, focusing on the effect of key parameters on desalination performance, as well as energy-water efficiency, economic costs and environmental impacts (including carbon footprint). We provide in-depth discussion on the interconnectivity between desalination and energy, and the trade-off between kinetics and energetics for RO and CDI as critical factors for comparison. We also critique the results of technical-economic assessment for RO and CDI plants in the context of large-scale deployment, with focus on lifetime-oriented consideration to total costs, balance between energy efficiency and clean water production, and pretreatment/post-treatment requirements. Finally, we illustrate the challenges and opportunities for future brackish water desalination, including hybridization for energy-efficient brackish water desalination, co-removal of specific components in brackish water, and sustainable brine management with innovative utilization. Our study reveals that both RO and CDI should play important roles in water reclamation and resource recovery from brackish water, especially for inland cities or rural regions.

42 ENGINEERING↗
DOE OSTI2023

Ecological insights into soil health according to the genomic traits and environment-wide associations of bacteria in agricultural soils

Abstract Soil microbiomes are sensitive to current and previous soil conditions, and bacterial ‘bioindicators’ of biological, physical, and chemical soil properties have considerable potential for soil health assessment. However, the lack of ecological or physiological information for most soil microorganisms limits our ability to interpret the associations of bioindicators and, thus, their utility for guiding management. We identified bioindicators of tillage intensity and twelve soil properties used to rate soil health using a 16S rRNA gene-based survey of farmland across North America. We then inferred the genomic traits of bioindicators and evaluated their environment-wide associations (EWAS) with respect to agricultural management practice, disturbance, and plant associations with 89 studies from agroecosystems. Most bioindicators were either positively correlated with biological properties (e.g., organic matter) or negatively correlated with physical and chemical properties. Higher soil health ratings corresponded with smaller genome size and higher coding density, while lower ratings corresponded with larger genomes and higher rrn copy number. Community-weighted genome size explained most variation in health ratings. EWAS linked prominent bioindicators with the impacts of environmental disturbances. Our findings provide ecological insights into bioindicators of soil properties relevant to soil health management, illustrating the tight coupling of microbiome and soil function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Threshold-based queuing system for performance analysis of cloud computing system with dynamic scaling

Cloud computing is promising technology to manage and improve utilization of computing center resources to deliver various computing and IT services. For the purpose of energy saving there is no need to unnecessarily operate many servers under light loads, and they are switched off. On the other hand, some servers should be switched on in heavy load cases to prevent very long delays. Thus, waiting times and system operating cost can be maintained on acceptable level by dynamically adding or removing servers. One more fact that should be taken into account is significant server setup costs and activation times. For better energy efficiency, cloud computing system should not react on instantaneous increase or instantaneous decrease of load. That is the main motivation for using queuing systems with hysteresis for cloud computing system modelling. In the paper, we provide a model of cloud computing system in terms of multiple server threshold-based infinite capacity queuing system with hysteresis and noninstantanuous server activation. For proposed model, we develop a method for computing steady-state probabilities that allow to estimate a number of performance measures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Design of an Axial Flux Machine With an Integrated Hydraulic Pump for Off-Highway Vehicle Electrification

Axial flux machines offer an inherent torque density advantage over conventional radial flux machines and are increasingly being considered for transportation electrification applications. Electrification of off-highway vehicles is notoriously challenging due to extreme power density requirements. This paper investigates the use of axial flux machines for off-highway vehicle electrification. To maximize the power density, a hydraulic pump is integrated with the axial flux machine, resulting in a single modular, electric/hydraulic machine. This paper first compares three popular axial flux machine variants using an FEA-based design optimization approach. The single rotor, single stator variant is identified to be the most promising for integration with the hydraulic pump. Next, a multi-physics framework of the complete integrated hydraulic pump and axial flux machine is developed to search the design space. The results indicate promising potential for this concept to realize efficiency over 85% and power density over 5kW/kg for the complete machine (electric machine, hydraulic pump, and thermal management system), while utilizing conventional materials (thin gauge silicon steel, N45 magnets, and magnet wire)

Off-highway vehicles, Axial flux machines, Multi-p↗
DOE OSTI2024

Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules

Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.

Mehta, Kshitij↗
DOE OSTI2012

WESBES: A Wireless Embedded Sensor for Improving Human Comfort Metrics using Temporospatially Correlated Data

When utilized properly, energy management systems (EMS) can offer significant energy savings by optimizing the efficiency of heating, ventilation, and air-conditioning (HVAC) systems. However, difficulty often arises due to the constraints imposed by the need to maintain an acceptable level of comfort for a building’s occupants. This challenge is compounded by the fact that human comfort is difficult to define in a measurable way. One way to address this problem is to provide a building manager with direct feedback from the building’s users. Still, this data is relative in nature, making it difficult to determine the actions that need to be taken, and while some useful comfort correlations have been devised, such as ASHRAE’s Predicted Mean Vote index, they are rules of thumb that do not connect individual feedback with direct, diverse feedback sensing. As they are a correlation, quantifying effects of climate, age of buildings and associated defects such as draftiness, are outside the realm of this correlation. Therefore, the contribution of this paper is the Wireless Embedded Smart Block for Environment Sensing (WESBES); an affordable wireless sensor platform that allows subjective human comfort data to be directly paired with temporospatially correlated objective sensor measurements for use in EMS. The described device offers a flexible research platform for analyzing the relationship between objective and subjective occupant feedback in order to formulate more meaningful measures of human comfort. It could also offer an affordable and expandable option for real world deployment in existing EMS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Battery Equivalent Model for Residential HVAC

Flexible loads, especially heating, ventilation, and air-conditioning (HVAC) systems can be used to provide a battery-like service to the power grid by varying their demand up and down over a baseline. Recent work has reported that the round-trip efficiency for providing grid services with HVAC systems can be close to 1. Inspired by this promising result, in this work, we rigorously develop a battery equivalent model (BEM) for residential HVAC systems. Relying only on typically available data, the proposed BEM will bridge the observability and controllability gaps between utility companies and customers. The proposed BEM will enable the utility companies to manage the flexible HVAC devices as easy as charging/discharging the conventional energy storage devices. Validated physics-based models are used to train the BEM, whose prediction accuracy is illustrated through a simulation study.

Dong, Jin↗
DOE OSTI2024

Quantum/AI Topology-Aware Latency-Adaptive HPC Workflow Scheduling Optimization

The growing demand for more powerful high-performance computing (HPC) systems has led to a steady rise in energy consumption by supercomputing worldwide. This study is focused on comparing our Application-Topology Mapper (ATMapper) to the popular Simple Linux Utility for Resource Management (SLURM) for the purpose of exploring methods that can further optimize job-scheduling within HPC systems. ATMapper is an Artificial-Intelligence based approach to job-scheduling that is currently being enhanced with quantum annealing (QA) to generate optimal schedules faster. We are applying QA to speedup our ATMapper process to achieve higher computing efficiency, thereby reducing HPC energy consumption. Here, we examine how four job-scheduling approaches perform in processor node assignment when using an example network architecture of 4 interconnected nodes. Using a specialized script, we are assessing the schedule of a computation flow with 11 interdependent tasks. The data movements among nodes were tracked to count for the number of interactions (network hops) between nodes needed to complete the tasks. The total number of hops and the job completion time were then used to quantify the efficiency of the different mapping approaches. In addition to SLURM, we also compare our ATMapper to the QA-enabled LBNL TIGER and the D-Wave Distributed Computing processor assignment approaches. The preliminary results showed that our topology-aware, latency-adaptive ATMapper is significantly more efficient when compared to the other scheduling approaches due to its load-imbalance network allocation. The scheduler displayed a computing efficiency of 53% by performing significantly fewer network hops than its alternatives. By reducing the number of hops, ATMapper was able to perform all 11 tasks by using only 3 nodes out of given 4. This research indicates the potential to use QA/AI for HPC job-scheduling. Later, we will test a SLURM simulator program to draw further comparisons on the effectiveness of ATMapper's scheduling approach. The results of this comparison will serve as a baseline for later improving SLURM's performance using a QA-enhanced ATMapper approach.

Caraveo, Braulio [University of Huston - Clear Lak↗
DOE OSTI2022

Development of an Integrated Electro-Hydraulic Machine to Electrify Off-highway Vehicles

Electrification of off-highway vehicles is notoriously challenging due to extreme power density requirements. This paper proposes and develops an axial flux machine integrated with a hydraulic pump to realize a single modular, electro-hydraulic machine to electrify off-highway vehicle implements. This integrated machine eliminates redundant bearings, couplings, and shaft seals, re-uses surfaces, and enables direct cooling of the electric machine with the hydraulic fluid, to significantly increase power density. Three popular axial flux machine variants are first compared using an FEA-based design optimization approach. The single rotor, single stator variant is identified to be the most promising for integration with the hydraulic pump. Next, a multi-physics framework of the complete integrated hydraulic pump and axial flux machine is developed to characterize the design space. The results indicate promising potential for this concept to realize efficiency over 85% and power density over 5kW/kg for the complete machine (electric machine, hydraulic pump, and thermal management system), while utilizing conventional materials (thin gauge silicon steel, N45 magnets, and enamelled copper wire). Furthermore, a prototype axial flux machine has been experimentally characterized and integrated with a hydraulic pump to demonstrate the integrated electro-hydraulic machine concept.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Effect of Carbon Support Heat Treatment on the Performance of Ion-Pair High-Temperature PEM Fuel Cells

Heat treatment can significantly alter the physical and chemical properties of carbon supports, thereby influencing the performance of proton exchange membrane (PEM) fuel cells. This study explores how varying carbon heat treatment temperatures—from 1,000 °C to 2,200 °C—affect the structure and performance of platinum-based catalysts in high-temperature PEM fuel cells. Increasing the heat treatment temperature led to a notable decrease in surface area, along with increases in carbon grain size and hydrophobicity. Although the catalyst supported on carbon treated at 1,000 °C exhibited the highest catalyst activity, the MEA using carbon treated at 1,500 °C delivered the best overall fuel cell performance. This is attributed to an optimized balance between hydrophobicity and accessible surface area, which enhances water management and catalyst utilization. These findings underscore the importance of carbon support engineering in improving the efficiency of ion-pair high-temperature PEM fuel cells.

08 HYDROGEN↗
DOE OSTI2022

CityBES v2021

City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.

Hong, Tianzhen↗
DOE OSTI2012

Demand Response as a System Reliability Resource

The Demand Response as a System Reliability Resource project consists of six technical tasks: • Task 2.1. Test Plan and Conduct Tests: Contingency Reserves Demand Response (DR) Demonstration—a pioneering demonstration of how existing utility load-management assets can provide an important electricity system reliability resource known as contingency reserve. • Task 2.2. Participation in Electric Power Research Institute (EPRI) IntelliGrid—technical assistance to the EPRI IntelliGrid team in developing use cases and other high-level requirements for the architecture. • Task 2.3. Research, Development, and Demonstration (RD&D) Planning for Demand Response Technology Development—technical support to the Public Interest Energy Research (PIER) Program on five topics: Sub-task 1. PIER Smart Grid RD&D Planning Document; Sub-task 2. System Dynamics of Programmable Controllable Thermostats; Sub-task 3. California Independent System Operator (California ISO) DR Use Cases; Sub-task 4. California ISO Telemetry Requirements; and Sub-task 5. Design of a Building Load Data Storage Platform. • Task 2.4. Time Value of Demand Response—research that will enable California ISO to take better account of the speed of the resources that it deploys to ensure compliance with reliability rules for frequency control. • Task 2.5. System Integration and Market Research: Southern California Edison (SCE)—research and technical support for efforts led by SCE to conduct demand response pilot demonstrations to provide a contingency reserve service (known as non-spinning reserve) through a targeted sub-population of aggregated residential and small commercial customers enrolled in SCE’s traditional air conditioning (AC) load cycling program, the Summer Discount Plan. • Task 2.6. Demonstrate Demand Response Technologies: Pacific Gas and Electric (PG&E)—research and technical support for efforts led by PG&E to conduct a demand response pilot demonstration to provide non-spinning reserve through a targeted sub-population of aggregated residential customers enrolled in PG&E’s AC load curtailment program, the Smart AC™ Demand Response Program.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Kongiganak Wind Turbine Replacement and System Upgrade Project

The Native Village of Kongiganak, Alaska was awarded a grant to upgrade the braking systems on five wind turbines and upgrade the monitoring and data collection unit to insure that enough energy is available to power the utility. The project manager for this award is Intelligent Energy Systems, LLC located in Anchorage, Alaska. In addition to accomplishing these upgrades, it was the intent for a local wind tech crew to be trained in Kongiganak so that routine maintenance and future repairs will be made by local workers.

17 WIND ENERGY↗
DOE OSTI2017

An Early Survey of Best Practices for the Use of Small Unmanned Aerial Systems by the Electric Utility Industry

This technical manual is about doing things safely. It isn’t so much a how-to guide as it is a collection of best practices from unmanned aerial system (UAS) operators from all over the world. The desired end state is to provide a touchstone for utility businesses, directors, managers, and operators that will inform them as they begin to strategize, plan, and incorporate this technology into day-to-day operations.

99 GENERAL AND MISCELLANEOUS↗