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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Electric Drive Technology Trends, Challenges, and Opportunities for Future Electric Vehicles

The transition to electric road transport technologies requires electric traction drive systems to offer improved performances and capabilities, such as fuel efficiency (in terms of MPGe, i.e., miles per gallon of gasoline-equivalent), extended range, and fast-charging options. The enhanced electrification and transformed mobility are translating to a demand for higher power and more efficient electric traction drive systems that lead to better fuel economy for a given battery charge. To accelerate the mass-market adoption of electrified transportation, the U.S. Department of Energy (DOE), in collaboration with the automotive industry, has announced the technical targets for light-duty electric vehicles (EVs) for 2025. This article discusses the electric drive technology trends for passenger electric and hybrid EVs with commercially available solutions in terms of materials, electric machine and inverter designs, maximum speed, component cooling, power density, and performance. Additionally, the emerging materials and technologies for power electronics and electric motors are presented, identifying the challenges and opportunities for even more aggressive designs to meet the need for next-generation EVs. Some innovative drive and motor designs with the potential to meet the DOE 2025 targets are also discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Uncertainty-Proof Hosting Capacity with Surrogate Affine Policy

Physical constraints must be enforced when dis-tributed energy resources, such as PV, are integrated into distribution network. Hosting capacity (HC) is thus introduced to define the maximum renewable that distribution system can accommodate. When the grid is further pushed towards low-carbon, many research efforts are devoted to increasing HC. Security and cost-efficiency become even more important in determining HC. This work proposes an uncertainty-proof HC with surrogate affine policy. Flexible resources are leveraged to increase HC. We propose a novel hybrid two-stage AC model with variable uncertainty set. An iterative algorithm is designed to solve the problem. The proposed model and solution approach are validated in modified 141-node feeders, and HC performance is also analyzed.

hosting capacity↗
DOE OSTI2025

TrioSim: A Lightweight Simulator for Large-Scale DNN Workloads on Multi-GPU Systems

Deep Neural Networks (DNNs) have become increasingly capable of performing tasks ranging from image recognition to content generation. The training and inference of DNNs heavily rely on GPUs, as GPUs' massively parallel architecture delivers extremely high computing capability. With the growing complexity of DNNs and the size of training datasets, training DNNs with a large number of GPUs is becoming a prevalent strategy. Researchers have been exploring how to design software and hardware systems for GPU farms to achieve the best utilization, efficiency, and DNN accuracy during training or inference. However, when designing and deploying such systems, designers usually rely on testing on physical hardware platforms equipped with many GPUs, incurring high costs that are almost prohibitive for system designers to test different configurations and designs, even for highly resourceful companies. While an alternative solution is to test on GPU simulators, they are often too slow for these l

Li, Ying [William & Mary, Williamsburg, VA, USA] (↗
DOE OSTI2020

Technical Interface Coordination with SHINE (FY2020 Summary)

In FY20, Los Alamos National Laboratory (LANL) performed technical interface coordination with SHINE including coordination of SHINE CFD and thermal hydraulics conference calls, national laboratory conference calls, and program management activities such as reporting and tracking requirements for current FY20 activities. SHINE did not request any general technology consultation support for emergent issues. LANL has participated in the bi-weekly conference calls with SHINE and other national laboratories regarding LANL’s current activities. Activities discussed include the Supo 3-D CFD model geometry validation, releasing the CFD-MCNP coupled codes for the generic solution vessel simulations, and the ANL bubble experiment #2 design, preparation, and collaboration.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Performance Results for Sensor Assignment Problem as Solved on a Multi-Node Cluster

An earlier report described a procedure for optimal sensor set selection and its implementation on a computational cluster. This new and innovative capability was developed to facilitate a reduction in operations staffing levels to improve plant economics. By automating surveillance and maintenance tasks through early detection of degrading sensors and equipment, staff can be more efficiently deployed. The method uses automated reasoning and domain knowledge in the form of the conservation equations to infer from plant measurements the state of equipment health. Inclusion of domain knowledge addresses the problem that exists with pure data-driven methods that there are no rigorous guidelines for determining what constitutes an adequate sensor set. Formalizing the procedure for sensor set selection as we have done results in a more reliable and explainable diagnosis of plant equipment health. Importantly, from the standpoint of the plant owner, personnel are provided with an early and explicit diagnosis of an equipment problem. That in principle automates the process and eliminates having to send personnel into the plant to find the cause as typically occurs when a data-driven method detects an anomaly. In this report we describe first results obtained using a computational cluster to solve the sensor set selection problem as framed above. The case described addresses the problem of equipment health monitoring in the high-pressure (HP) feedwater system of a pressurized light water reactor as seen through the eyes of our collaborating utility partner. Maintenance of this system can amount to millions of dollars per year if equipment health issues go undiagnosed and lead to loss of function. On examining the potential that is inherent in the installed sensor set for diagnosing equipment health degradation, it was found that greater fault resolution capability can be achieved using a sensor set that is 20 percent fewer in number. The take-away is that compared to the installed sensor set there exists a more strategic assignment of sensors that will furnish better health monitoring capability and with fewer sensors. Where the problem defies solution by manual inspection, as is the case here, one can be found by an algorithm. The solution was obtained in four hours using 30 computational cores. The HP feedwater problem as posed above illustrates the added value of approaching the sensor selection problem as one amenable to algorithmic solution. This problem is of interest to advanced reactor designers and to utilities that are setting up remote monitoring and diagnostic centers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Power Sector Decarbonization in South Asia: Pathways for Research, Modeling, and Implementation

Decarbonization of the power sector has far-reaching impact into the further decarbonization of the economy. In many comprehensive decarbonization pathways proposed for the world and for India electrification of transportation, buildings, and industry is the principal solution to decarbonizing those sectors. Therefore, electricity grids are likely to grow as more and new loads are added to them, and this growth will necessarily be from non-carbon emitting resources. This report outlines several key challenges for the power sector in planning, research, and development towards a decarbonized electric power grid. While these challenges will continue to evolve, this report focuses on formulating the important questions for the next two decades to align planning timeframes of India's and South Asia's power sector stakeholders, and to offer near-term research solutions for preparing the datasets, building the models, and designing the studies to answer questions and prepare for these changes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Transversely Polarized Solid Target for Hall B at Jefferson Lab

The physics program for Hall B at Jefferson Lab includes multiple, high-impact experiments scattering electrons from transversely polarized protons. These experiments will measure, for example, the Transverse Momentum Distributions and the Generalized Parton Distribution for protons, using, respectively, semi-inclusive deep inelastic scattering and deeply virtual Compton scattering. In this talk I will discuss the technical challenges to implementing a polarized solid-state target in the Hall B experimental environment, examine potential solutions, and describe the current status of the target design.

Keith, Christopher↗
DOE OSTI2024

Research Priorities and Opportunities in U.S. Wholesale Electricity Markets: Market Design under Deep Decarbonization

This report contributes to the body of literature by reviewing key challenges for competitive wholesale electricity market design in deeply decarbonized power systems and establishing potential solutions and associated research needs. We provide a long-term perspective on ways in which competitive wholesale electricity markets can evolve to ensure that they still operate efficiently throughout the transition to a deeply decarbonized future. In this report, we use the term “deep decarbonization” to refer broadly to systems that generate nearly all their electricity from zero-carbon or carbon-neutral resources, while recognizing that there are many potential configurations of such systems. We also stress that many of these issues will arise to varying degrees as systems move toward full decarbonization, even if they are not truly 100% carbon-free.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Computationally-Guided ODS Refractory HEAs via Additive Manufacturing

This document is the final report for ARPA-E ULTIMATE project DE-AR0001422. To achieve higher efficiency turbine operation, the RTX Technology Research Center (RTRC) explored the use of additive manufacturing (AM) to produce test specimens of novel high entropy alloys (HEA) enhanced with oxide dispersion strengthening (ODS). HEAs, with multiple principal elements, offer a vast alloy design space rich with unique properties especially enhanced solid solution strengthening. ODS alloys historically are some of the best performing materials for high temperature applications. Leveraging AM enables near net shape part production and incorporation of ODS into the alloy. Density, melting temperature, and elevated temperature strength properties of several novel HEA compositions were found to meet or exceed program targets; however, obtaining sufficient room temperature ductility in these alloys proved challenging. In order to obtain an alloy with sufficient ductility, the team explored more conventional refractory alloy compositions, focusing on a niobium based alloy. This inherently ductile alloy also satisfied program metrics for cost, density, and fracture toughness. Results showed the oxide dispersions increased high temperature strength, and improved creep resistance compared to the conventional alloy, though the program creep metric was not met. Further tuning of the alloy chemistry, and optimization of the oxide dispersion, is likely required to improve creep resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Large-Scale CO2 Storage and Reservoir Management Strategies: Case Studies

This poster describes large-scale CO2 storage and reservoir management case studies for presentation at the AGU2024 conference. The analysis in this study provides a wealth of details on the designs and strategies that can lead to an optimal solution for pressure and CO2 plume management under critical constraints. These findings not only promise a reduction in the CO2 storage footprint but also hold the potential to create a more environmentally friendly ecosystem. Furthermore, this research offers valuable insights into the decision-making process when considering multi-project deployment in a shared basin for large-scale and gigatons of CO2 storage, paving the way for a more sustainable future. Poster presented (virtual) at the 2024 AGU Conference, December 9-13, 2024, Washington, D.C.

Liu, Guoxiang [NETL]↗
DOE OSTI2025

Shift Happens: Building Robust AI Models with Domain Adaptation

Artificial Intelligence (AI) is revolutionizing physics research—from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data—exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This summer school session will introduce students to common challenges in applying AI across domains and present solutions based on domain adaptation—a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery. The concepts discussed are broadly applicable across physics and other scientific disciplines, making this a valuable topic for anyone interested in building robust, transferable AI models for science.

Ciprijanovic, A. [Fermilab] (ORCID:000000031281719↗
DOE OSTI2025

AI in Astrophysics: Tackling Domain Shift, Model Robustness and Uncertainty

Artificial Intelligence (AI) is revolutionizing physics research from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This talk will introduce common challenges in applying AI across domains and present solutions based on domain adaptation a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery.

Ciprijanvoic, Aleksandra [Fermilab] (ORCID:0000000↗
DOE OSTI2020

Feasibility of Ocean-Based Renewable Energy in the Gulf of Mexico

This paper summarizes a comprehensive feasibility assessment of six offshore renewable energy sources in the Gulf of Mexico (GOM) to potentially provide utility-scale electricity from the Outer Continental Shelf (federal waters) and state waters to land-based grids. Overall, the primary objective is to inform future energy planning. The authors evaluated offshore wind, wave energy, tidal energy, ocean-based solar photovoltaics (PV), ocean current, and ocean thermal energy conversion. Of these energy resources, offshore wind was the most viable option and was the focus of the second part of the study. The technical challenges of developing offshore wind in the GOM are discussed including hurricane design for turbines and substructures, as well as turbine solutions to overcome lower wind regimes. In addition, advantages to offshore wind development in the GOM are described including proximity to oil and gas supply chains. Economic analysis using established cost models at the National Renewable Energy Laboratory identified hypothetical project locations where net value of offshore wind was the highest, and the levelized cost of energy (LCOE) was calculated for three sites: Port Isabel, Port Arthur, and Pensacola. Offshore wind LCOE in the GOM was found to be higher than those in sites along the north and mid-Atlantic coasts, but decreasing cost trajectories indicate the possibility of economic viability for locations in Texas and west Louisiana after 2030. The extrapolated 2030 LCOE values range from 73 dollars per MWh (Site 1, Port Isabel) and 79 dollars per MWh (Site 3, Port Arthur) to 91 dollars per MWh (Site 5, Pensacola).

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Residential Ventilation Systems

US homes are increasingly being provided with mechanical ventilation systems that are intended to comply with ASHRAE Standard 62.2. As mechanical ventilation is becoming more prevalent, the industry is gaining knowledge about measured installed performance of mechanical ventilation systems and guidance on how to avoid problem installations. Feedback from industry and research studies has led to several key improvements to the ASHRAE standard giving ventilation system designers more flexibility and providing more energy efficient ventilation solutions. This article summarizes some of the key advances in residential ventilation as well as the results of field investigations of residential ventilation system commissioning and operation/maintenance issues, much of which is from the USDOE Building America program.

Lubliner, Michael↗
DOE OSTI2023

OECD-NEA HTTF Benchmark Progress and Updates

General slides discussing High Temperature Test Facility benchmark progress, Prismatic HTGR deployment, modeling and simulation tools for validating systems, and verification and validation issues. Also discuss collaboration and conclusions of RELAP5-3D validation activities based on HTTF with trends in data and international impact to accelerate deployment of prismatic HTGR microreactors by providing an opportunity for designers to assess their codes against experimental data and solutions from other codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Optimizing the Fabrication of Electrospun Nanofibrous Membrane Using Fractional Factorial Design

Electrospinning, a simple and easily tunable technique that utilizes the force balance between the electrostatic force and the solution surface tension to fabricate membranes out of 1D nanostructured fibers, has garnered much interest especially from the nanotechnology community. Depending on the morphology of the fibers, electrospun membrane has found its way in a wide range of applications, such as oil-water separation, desalination, tissue engineering, and batteries. During an electrospinning process, many factors can affect the morphology of the products, such as viscosity of the solution, voltage supply, discharge distance, feed rate of the solution, and electrospinning time. In this work, we investigated the impacts of the most important parameters on the morphology of electrospun fibrous membrane based on the fractional factorial design. We evaluated the electrospun fibrous membrane morphology using scanning electron microscopy (SEM) and capillary flow porometry. Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) was chosen for the current study due to its interesting and versatile functionalities including superior hydrophobicity, high free volume, and piezoelectricity. This work provides valuable insight for the fabrication of electrospun membranes, especially for tailoring membrane properties in accordance with any targeted applications.

Zhao, Yajing↗
DOE OSTI2020

Application and Certification of Comparative Vacuum Monitoring Sensors for Structural Health Monitoring of 737 Wing Box Fittings

Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today's extensive fleet of aging aircraft and space vehicles. The use of in-situ sensors for real-time health monitoring of aircraft structures are a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. Prevention of unexpected flaw growth and structural failure can be improved if on-board health monitoring systems are used to continuously assess structural integrity. Such systems are able to detect incipient damage before catastrophic failures occurs. Condition-based maintenance practices could be substituted for the current time-based maintenance approach. Other advantages of on-board distributed sensor systems are that they can eliminate costly, and potentially damaging, disassembly, improve sensitivity by producing optimum placement of sensors and decrease maintenance costs by eliminating more time- consuming manual inspections. This report presents a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp. and the Federal Aviation Administration (FAA) carried out a certification program to formally introduce Comparative Vacuum Monitoring (CVM) as a structural health monitoring solution to a specific aircraft wing box application. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM into an airline maintenance program and the document revisions necessary to allow for routine use of CVM as an alternate means of performing periodic structural inspects. To carry out the validation process, knowledge of aircraft maintenance practices was coupled with an unbiased, independent evaluation. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically-relevant experimental effort to quantify the reliability of the CVM system applied to the Boeing 737 Wing Box fitting application. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for CVM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and also is acceptable to both the aviation industry and regulatory bodies. This report presents the use of several different statistical methods, some of them adapted from NDI performance assessments and some proposed to address the unique nature of damage detection via SHM systems, and discusses how they can converge to produce a confident quantification of SHM performance An important element in developing SHM validation processes is a clear understanding of the regulatory measures needed to adopt SHM solutions along with the knowledge of the structural and maintenance characteristics that may impact the operational performance of an SHM system. This report describes the major elements of an SHM validation approach and differentiates the SHM elements from those found in NDI validation. The activities conducted in this program demonstrated the feasibility of routine SHM usage in general and CVM in particular for the application selected. They also helped establish an optimum OEM-airline-regulator process and determined how to safely adopt SHM solutions. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM technology. It will also streamline the regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗
DOE OSTI2025

Spectroscopic investigation of cation effects in U(VI)-NO3- complexation in aqueous solutions

Understanding and manipulating uranyl speciation in aqueous solutions is critical for advancing chemical separation, sensing, and understanding environmental transport of uranyl. We report on the significant enhancement in the complexation of uranyl with nitrate in aqueous solutions containing quaternary ammonium cations leading to the formation of anionic complexes. We base this on the comparative study of the effect of monovalent cations (Na+, Li+, NH4+, and N(CH3)4+) on the complexation equilibria of uranyl-nitrate in solutions, probed by time-resolved laser induced fluorescence spectroscopy (TRLFS). Lifetime-corrected spectra, obtained by extrapolating the time-resolved spectra to t = 0, were used to study speciation to mitigate the effects of variations in the fluorescence lifetimes that depend on extraneous factors such as dynamic quenching. We demonstrate that the lifetime-corrected spectra can be used to determine uranyl speciation in aqueous solutions where the mono-nitrate complex forms, and in acetonitrile with N(CH3)4NO3 where di-nitrate and tris-nitrato species are formed. Aqueous solutions containing N(CH3)4+ are shown to promote the formation of higher complexes of uranyl compared to other inorganic nitrate salts based on the higher redshift in the spectra, poor fits to the two-component model, and the higher apparent formation constants. Comparing the trends in uranyl speciation in the presence of N(CH3)4+ in aqueous and acetonitrile solutions, it is proposed that the quaternary ammonium cations (quats) promote the formation of anionic complexes of uranyl by the ion-association mechanism. These results provide a basis for designing quat-assisted separation systems that target anionic actinide species in aqueous solutions.

Nayak, Srikanth (ORCID:0000000302135796)↗