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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Artificial Intelligence for Power Electronics in Electric Vehicles: Challenges and Opportunities

We report progress in the field of power electronics within electric vehicles has generally been driven by conventional engineering design principles and experiential learning. Power electronics is inherently a multidomain field where semiconductor physics and electrical, thermal, and mechanical design knowledge converge to achieve a practical realization of desired targets in the form of conversion efficiency, power density, and reliability. Due to the promising nature of artificial intelligence in delivering rapid results, engineers are starting to explore the ways in which it can contribute to making power electronics more compact and reliable. Here, we conduct a brief review of the foray of artificial intelligence in three distinct subtechnologies within a power electronics system in the context of electric vehicles: semiconductor devices, power electronics module design and prognostics, and thermal management design. The intent is not to report an exhaustive literature review, but to identify the state of the art and opportunities for artificial intelligence to play a meaningful role in power electronics design from a mechanical and thermal standpoint, as well as to discuss a few promising future research directions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Medium-duty Urban Range Extended Connected Powertrain (Final Scientific Technical Report)

The project goal is to develop and demonstrate a Class 4 delivery vehicle that reduces fuel consumption by 50% or more when compared to an equivalent vehicle with a conventional internal combustion engine (ICE) powertrain driven on a comparable duty cycle. This shall be achieved using a plug-in hybrid electric (PHEV) configuration that optimizes the efficiency of the ICE. The proposed solution aims to be commercially viable for fleets to procure the system without additional incentives. To accomplish this, commercialized light-duty vehicle electric drive components shall be used. A PHEV configuration for Class 4 MD/HD vocational vehicles using commercialized light-duty vehicle electric drive components will require the development of a new topology for the hybrid powertrain applicable to medium-duty vehicles. Prior research indicates that an identified novel power split device could provide a fuel economy improvement potential of up to 51%. Utilizing an advanced battery management algorithm that will allow operation closer to the battery limits, the project will minimize battery capacity to achieve the desired performance results while maintaining the cost target for high commercialization. The solution must be cost effective to purchase and integrate into a Class 4 delivery vehicle, deliver the intended fuel economy improvement, and perform as well, or better, than the current conventional ICE powertrain. MD/HD vehicles typically require higher power, which is one factor that results in high costs for the powerful electric machines typical in larger HEV/PHEV systems. A key element in the project is the use of commercially available Bosch electric drive components (e.g., motors, batteries, and power electronics) from the larger passenger vehicle segment. This leverages the economies of scale to decrease cost and improve reliability beyond current purpose-built low-volume commercial vehicle components. These innovations will result in a game-changing PHEV system that meets DOE’s 50% fuel consumption reduction target, grants the vehicle an uncompromised driving range, and achieves the cost point for widespread adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Digital engineering implementation in nuclear demonstration and nonproliferation projects at Idaho National Laboratory

Digital engineering and digital twins are increasingly being used in nuclear energy projects with important impacts. At Idaho National Laboratory, these approaches have been applied in a variety of nuclear energy research, development, and demonstration projects, with key lessons and evolutions occurring for each. In this paper, we describe the use of digital engineering and digital twins in the Versatile Test Reactor design, National Reactor Innovation Center test beds, and nonproliferation analysis of the AGN-201 reactor design. We share key lessons learned for these projects related to tool selection, adoption and training, and working with existing assets versus beginning at the design phase. We also share highlights of future potential uses of digital twins and digital engineering, including using artificial intelligence to perform repetitive design tasks and digital twins to move towards semiautonomous nuclear power plant operations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

A review on the application of machine learning for combustion in power generation applications

Abstract Although the world is shifting toward using more renewable energy resources, combustion systems will still play an important role in the immediate future of global energy. To follow a sustainable path to the future and reduce global warming impacts, it is important to improve the efficiency and performance of combustion processes and minimize their emissions. Machine learning techniques are a cost-effective solution for improving the sustainability of combustion systems through modeling, prediction, forecasting, optimization, fault detection, and control of processes. The objective of this study is to provide a review and discussion regarding the current state of research on the applications of machine learning techniques in different combustion processes related to power generation. Depending on the type of combustion process, the applications of machine learning techniques are categorized into three main groups: (1) coal and natural gas power plants, (2) biomass combustion, and (3) carbon capture systems. This study discusses the potential benefits and challenges of machine learning in the combustion area and provides some research directions for future studies. Overall, the conducted review demonstrates that machine learning techniques can play a substantial role to shift combustion systems towards lower emission processes with improved operational flexibility and reduced operating cost.

Engineering↗
DOE OSTI2024

Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C

Drainage structures are used to capture stormwater runoff in streets and highways in urban environments. These drainage structures, which typically consist of catch basins with grates, inlets, or combination grates/inlets, collect stormwater runoff and discharge through buried conveyance systems. They are strategically placed for public safety in curb and gutter systems to provide efficient drainage of water from roadways and thus reduce the risk of hydroplaning. The performance of drainage structures is measured in terms of hydraulic efficiency, which is defined as the percentage of flow captured by the basin as compared to the total flow drainage to the structure. Understanding of the performance of these drainage structures helps designers properly space inlets to promote an economic design that ensures the safety of the traveling public. The current design methodology used to determine drainage structure follows guidelines established in the current Michigan Department of Transportation (MDOT) Drainage Manual (2006). The guidelines in the MDOT Drainage Manual were modeled after the Federal Highway Administration’s (FHWA) Hydraulic Engineering Circular 22 “Urban Drainage Design” (HEC-22). HEC-22 includes empirically derived equations to calculate the interception capacity of drainage structures for several commonly used grate configurations, such as the parallel bar, curved vane and tilt bar grates, which are based on a research study performed by Burgi et al. in the 1970s. MDOT uses several drainage structures to capture runoff that are detailed as Standard Plans. Many of these drainage structures utilize sinusoidal type grates that are not described in HEC-22. Physical modeling of these structures has been limited, posing the need to have them analyzed to verify their capture efficiency. Current MDOT practice is to assume a similar sized reticuline grate, as described in HEC-22, for capture efficiencies. Until recently, evaluating the hydraulic performance of drainage structures was limited to physical modeling in a hydraulics laboratory. With advances in engineering software and computing power, computational fluid dynamics (CFD) modeling has become a more cost-effective alternative. The Federal Highway Administration (FHWA) provides states the option to evaluate their drainage structures using CFD through the Transportation Pooled Fund Program. This study, “Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C,” was carried out using the pooled fund. MDOT’s Cover C was chosen as the first test candidate, given its similar sinusoidal pattern to other MDOT grates, but it is typically used for high-volume, higher speed applications. A similar version, Cover CX, is used on interstate highways but does not have traverse bars for bicycle safety. Additional grates may be considered for evaluation in the future.

42 ENGINEERING↗
DOE OSTI2026

MOD-Amp System Design Spring: Spring 2026 – Georgetown University, SYSM–5620

High-energy lasers (HELs) play an important role in both national defense and scientific research. In defense applications, HELs are used for target detection, tracking, and engagement. In research environments, they support studies of extreme physical conditions relevant to fusion energy and plasma science. These systems depend on the amplification of light through stimulated emission of radiation, allowing optical energy to be increased to the levels required for operation. This amplification occurs when light passes through an energized gain medium that receives energy from an external optical or electrical source. To achieve the desired output, laser systems often use multiple amplification stages, including high-gain preamplifiers and lower-gain power or booster amplifiers. At Lawrence Livermore National Laboratory (LLNL) and other national laboratories, many large-aperture laser amplifier systems are aging and rely on system-specific hardware, obsolete technologies, and incomplete documentation. These legacy systems create challenges for maintenance, supportability, and long-term operation. Their lack of standardization also increases the difficulty of sustaining reliable performance over time. As this infrastructure continues to age, the likelihood of unplanned downtime grows, which can negatively affect both national security missions and scientific research programs that depend on dependable HEL capabilities. The purpose of this document is to demonstrate the application of systems engineering fundamentals and design thinking through the development of a laser amplifier case study. The proposed system concept is intended as an academic exercise and not as a finalized engineering design. As a result, the development presented in this document is incomplete and may contain technical assumptions or errors that would require further investigation before any real-world implementation.

42 ENGINEERING↗
DOE OSTI2020

LWRS 2019 Accomplishments Report

Nuclear energy is an important part of supplying our nation’s energy—safely, dependably, and economically—with reduced carbon dioxide emissions. The United States (U.S.) Department of Energy-Office of Nuclear Energy (DOE-NE) supports a strong and viable domestic nuclear industry. In collaboration with industry programs, the Light Water Reactor Sustainability (LWRS) Program supports the continued operation of the commercial fleet of nuclear power plants. DOE’s role in this program focuses on enhancing the safe, efficient, and economical performance of the nation’s nuclear fleet. This report describes the accomplishments of the LWRS Program during Fiscal Year 2019. DOE-NE’s0F primary mission is to advance nuclear power as a resource capable of making major contributions in meeting the nation’s energy supply, environmental, and energy security needs. Under the guidance of three research objectives, NE resolves barriers to technical, cost, safety, security, and proliferation resistance through early stage research, development, and demonstration (RD&D) to: • Enhance the long-term viability and competitiveness of the existing U.S. reactor fleet • Develop an advanced reactor pipeline • Implement and maintain national strategic fuel-cycle and supply-chain infrastructures.

42 ENGINEERING↗
DOE OSTI2022

Additive manufacturing of ceramic materials for energy applications: Road map and opportunities

Among engineering materials, ceramics are indispensable in energy applications such as batteries, capacitors, solar cells, smart glass, fuel cells and electrolyzers, nuclear power plants, thermoelectrics, thermoionics, carbon capture and storage, control of harmful emission from combustion engines, piezoelectrics, turbines and heat exchangers, among others. Advances in additive manufacturing (AM) offer new opportunities to fabricate these devices in geometries unachievable previously and may provide higher efficiencies and performance, all at lower costs. This article reviews the state of the art in ceramic materials for various energy applications. The focus of the review is on material selections, processing, and opportunities for AM technologies in energy related ceramic materials manufacturing. The aim of the article is to provide a roadmap for stakeholders such as industry, academia and funding agencies on research and development in additive manufacturing of ceramic materials toward more efficient, cost-effective, and reliable energy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Heavy-Duty Vehicle Activity Updates for MOVES Using NREL Fleet DNA and CE-CERT Data

The U.S. Environmental Protection Agency's (EPA's) Motor Vehicle Emission Simulator (MOVES) is a publicly available tool used by researchers and policymakers to help understand motor vehicle emission sources at a national, county, and project level. Estimates of heavy-duty activity in the most recent version of the model at the time this work was conducted, MOVES2014, was identified as an area in need of improvement. The start activity in MOVES2014 is based on a limited and dated data set. In addition, MOVES2014 relies on drive cycles that represent on-network activity but do not account for idling activity that occurs on off-network roads, such as at a distribution center, while the truck is queuing or during loading and unloading. As a result, MOVES2014 may currently underestimate the number of starts and idle and soak time for heavy-duty trucks in real-world operation. The National Renewable Energy Laboratory (NREL) has previously leveraged its expansive Fleet DNA database of heavy-duty vehicles to idle and start activity for six of the nine heavy-duty vehicle source types of classes in the MOVES model. The data available in Fleet DNA from 416 conventional, diesel-powered vehicles provided activity estimates from more than 120,000 hours of operation throughout 14,682 vehicle days between October 2006 and January 2016. NREL calculated start fraction, starts per day, soak fraction, and idle fraction by hour of the day for each vehicle type, state, and vocation, and provided results in .CSV files that can be translated to MOVES table inputs. The idle and start activity from this initial analysis of Fleet DNA data was used to develop default idle and start data for heavy-duty vehicles in MOVES3. Satisfied with the results from the Fleet DNA data used for MOVES3, the EPA asked NREL to extend this start/soak/idle analysis using additional data from a larger number of vehicles for a potential future update to the MOVES model. Such a data set was achieved from a project led by the University of California at Riverside, College of Engineering, Center for Environmental Research & Technology (CE-CERT) and funded by California Air Resources Board. Specifically, this data set consists of 90 heavy-duty vehicles operated mainly in California, which can be separated into five of the nine heavy-duty vehicle classes in the MOVES model. In addition, the heavy-duty activity database collected by CE-CERT provided activity estimates from more than 44,000 hours of operation throughout 4,724 vehicle days between November 2014 and September 2016. This report details the analysis of the heavy-duty activity database collected from the University of California at Riverside by providing graphical analysis and context for the start, soak, and idle distributions. The comparison of the related results from both the Fleet DNA and CE-CERT data sets are documented as well.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

High power ion beam generator systems and methods

Provided herein are high energy ion beam generator systems and methods that provide low cost, high performance, robust, consistent, uniform, low gas consumption and high current/high-moderate voltage generation of neutrons and protons. Such systems and methods find use for the commercial-scale generation of neutrons and protons for a wide variety of research, medical, security, and industrial processes.

42 ENGINEERING↗
DOE OSTI2024

Recent Progress of JT-60SA Project toward Plasma Operation

Superconducting tokamak JT-60SA plays an essential role in fusion research and development by supporting and complementing ITER project, providing directions to the DEMO design activity and fostering next generation scientists and engineers. Since the incident of the Equilibrium Field coil #1 during the Integrated Commissioning (IC) in March 2021, both EU and JA Implementing agencies (IAs) have examined how to ensure safety operation of JT-60SA by mitigating the risk of possible discharge occurrence inside the cryostat. Based on the experience of the Global Paschen tests, the IAs have established a strategy of risk mitigation measures, which is a combination of (i) reinforcement of insulation, (ii) avoiding unnecessary voltage application to the coil systems and (iii) immediate de-energization of the coils when deteriorated vacuum condition is detected. Thanks to the considerable efforts of the Integrated Project Team (IPT) members, the IC restarted in May 2023. After the confirmation of superconducting state of coil systems (TF, EF and CS), the coil energization test and the plasma operation (OP-1) starts. The first plasma was successfully achieved on 23 October 2023 with a limited value of applied voltage and current to the coils. The plasma configuration control will be also confirmed with low plasma current and low auxiliary heating power conditions. Based on the IO-F4E-QST collaboration, activities of JT-60SA have been shared with the IO and provided an important lesson learned for ITER assembly and commissioning, and will provide an outstanding contribution to fusion research at large. After OP-1, Maintenance & Enhancement phase 1 (M/E-1) starts from January 2024, in which in-vessel components are installed, and heating system and diagnostic system are extensively upgraded to allow high power heating experiment planned in OP-2. In order to make the best use of JT-60SA, newly organized JT-60SA experiment team will refine the research plan in the future high heating power operation phase.

Broader Approach activities↗
DOE OSTI2022

Triton Initiative: FY22 Communications, Outreach, and Engagement End-of-Year Report

The Department of Energy (DOE) Water Power Technologies Office (WPTO) Triton Initiative supports the advancement of the marine energy (ME) industry through environmental monitoring research and technology development. This report presents the results and analysis of the Triton Initiative’s communications, outreach, and engagement (TCOE) efforts in fiscal year 2022. The primary TCOE goals were to: (1) educate and raise awareness of ME and the role of Triton's environmental monitoring research in supporting the industry; (2) build trust with audiences through transparent communications and outreach; and (3) evaluate and refine TCOE tactics based on feedback and metrics. To support these goals, the TCOE team used multiple platforms and approaches. Notable achievements include: (1) 12 newsletter issues sent to 185 subscribers with an average open rate of 56.4%. (2) 10 Triton Stories, resulting in 2,871 collective views contributing to 46% of all Triton website views. (3) 78 Triton-specific social media posts, which generated a total of 81,896 impressions, 1,037 post-clicks, and 7,814 video views. (4) 6,320 Triton website views with increased search engine optimization ranking in several categories. (5) 3 Triton researchers interviewed as guests on two different podcasts, Water Women and Big Deep: An Ocean Podcast. (6) A Triton special issue of the Journal of Marine Science and Engineering (JMSE) featuring 10 peer reviewed publications. All articles ranked in the top 25%, and two in the top 5%, for digital attention of all research outputs scored by Altmetric. (7) A seven-part webinar series called Triton Talks to share and discuss research and results from the research published in the JMSE special issue. Triton leveraged unique opportunities, particularly the JMSE special issue, to disseminate research results to end users, educate stakeholders, and gain valuable feedback. These concerted communication efforts increased exposure across platforms ultimately resulting in greater reach and access across audiences. Based on audience analyses of webinar attendees and newsletter subscribers, the TCOE team was able to successfully engage with general audiences, research partners, and ME stakeholders, including subject matter experts from government agencies, research organizations, and the regulatory community. The TCOE task established channels to gather input and create opportunities for two-way communication with people engaged with Triton’s outreach efforts. The feedback received will enable the TCOE team to support its goals for ongoing evaluation of outreach and engagement tools while continuing to build trust in the ME community and educate diverse audiences about the impactful research conducted by the Triton Initiative. This report is a Triton Initiative Fiscal Year 2022 Quarter 4 Milestone Deliverable due to the DOE WPTO Sponsor on 9/30/2022. An updated version to include data through 9/30/2022 will be delivered in October 2022.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Exploring the binding properties and activities of ancestral expansins

Bacterial expansins are non-lytic proteins capable of loosening cellulose networks, offering promising applications in agriculture, biotechnology, and material science. Their ability to disrupt noncovalent interactions in biopolymer matrices such as cellulose and chitin positions them as valuable tools for upgrading abundant natural materials. However, their industrial use remains limited due to their relatively low wall-loosening activity compared to plant expansins. To address this limitation, we applied Ancestral Sequence Resurrection (ASR) to reconstruct and characterize ancient variants of the Bacillus subtilis expansin BsEXLX1. ASR is a powerful evolutionary tool that enables the inference and synthesis of ancestral proteins, allowing researchers to explore functional traits that may have been lost over time. This approach not only provides insights into protein evolution but also facilitates the design of proteins with enhanced properties, such as improved substrate affinity or structural stability. In this study, we combined biochemical and biophysical assays to evaluate the activity and binding behavior of ancestral expansins. Our results reveal that ancestral variants exhibit increased cellulose affinity, reduced binding to acidic polysaccharides, and greater salt resistance. Furthermore, these traits enhance their wall-loosening activity and demonstrate the utility of ASR in engineering surface-active proteins for industrial applications, particularly in biomass processing and cellulose modification.

09 BIOMASS FUELS↗
DOE OSTI2022

Regulatory Considerations for Nuclear Energy Applications of Digital Twin Technologies

Digital twins (DTs) in complex industrial and engineering applications have potential benefits that include increased operational efficiencies, enhanced safety and reliability, improved security engineering, reduced errors, faster information sharing, and better predictions. The interest in DT technologies continues to grow, and many of these advanced technologies are expected to experience rapid and wide industry adoption in the near future. Some of the potential application areas for DTs in the nuclear industry are design, licensing, plant construction, training simulators, predictive operations and maintenance, autonomous operation and control, failure and degradation prediction, physical protection modeling and simulation, and safety and reliability analyses. The Office of Nuclear Regulatory Research at the U.S. Nuclear Regulatory Commission (NRC) has initiated a future-focused research project to assess the regulatory viability of DTs for nuclear power plants and other NRC-regulated activities, such as fuel cycle facilities and operations. This report explores the potential impact of DT technologies in nuclear applications on NRC-regulated activities of interest. This report describes a nuclear DT system and its capabilities for nuclear power plant applications, followed by identification and discussion of some regulated activities that merit special consideration and present opportunities in implementing DT-enabling technologies and capabilities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Power and Wind Shear Implications of Large Wind Turbine Scenarios in the US Central Plains

Continued growth of wind turbine physical dimensions is examined in terms of the implications for wind speed, power and shear across the rotor plane. High-resolution simulations with the Weather Research and Forecasting model are used to generate statistics of wind speed profiles for scenarios of current and future wind turbines. The nine-month simulations, focused on the eastern Central Plains, show that the power scales broadly as expected with the increase in rotor diameter (D) and wind speeds at hub-height (H). Increasing wind turbine dimensions from current values (approximately H = 100 m, D = 100 m) to those of the new International Energy Agency reference wind turbine (H = 150 m, D = 240 m), the power across the rotor plane increases 7.1 times. The mean domain-wide wind shear exponent (α) decreases from 0.21 (H = 100 m, D = 100 m) to 0.19 for the largest wind turbine scenario considered (H = 168 m, D = 248 m) and the frequency of extreme positive shear (α > 0.2) declines from 48% to 38% of 10-min periods. Thus, deployment of larger wind turbines potentially yields considerable net benefits for both the wind resource and reductions in fatigue loading related to vertical shear.

17 WIND ENERGY↗
DOE OSTI2024

"Forward" Projects Boost U.S. Leadership in Advanced Computing and Artificial Intelligence

High-performance computing (HPC) has been an indispensable research tool for accessing physical realms difficult, or impossible, achieve with experiment alone. For several decades, the Department of Energy’s (DOE’s) Office of Science has deployed sophisticated HPC systems for solving the nation’s most pressing grand challenge problems in energy, climate change, and human health. In addition, DOE’s National Nuclear Security Administration (NNSA) has adeptly applied HPC in support of key national security objectives, such as nuclear science and stockpile modernization and stewardship. Over time, HPC systems have become increasingly more complex and capable, and as each new machine has come online, scientists and engineers have taken advantage of vast increases in compute power to accelerate scientific discoveries and engineering innovation.

42 ENGINEERING↗
DOE OSTI2024

A Survey of Open-Source Tools for Transmission and Distribution Systems Research

This work presents a review of open-source electric power transmission and distribution systems analysis tools suitable for use by industry professionals and academic researchers. Due to the high complexity of the electric grid, there exist numerous tools and extensive research pertaining to nearly every aspect of the design, operation, and control of transmission and distribution networks. In addition to the commercial tools, a wide range of free, open-source tools, models, and data usable by the scientific community for related research have been developed by different organizations, including both international and US universities and national laboratories. However, due to the absence of a catalog of available tools, models and data, researchers often lack a knowledge of existing capabilities and may develop duplicative software and tools. Increasing awareness of these available resources seeks to accelerate their broader use, leading to more efficient and standardized grid analysis. This review paper (which is part of a larger survey effort that studied over 400 tools in the transmission, distribution, buildings, and electric vehicles space) outlines selected open-source resources that have been developed in power transmission and distribution systems research. It is anticipated that this work can serve as a guide for industry and academic researchers alike, ensuring that research efforts are well-channeled.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Big Adaptive Rotor Phase I Final Report

The Big Adaptive Rotor (BAR) project was initiated by the U.S. Department of Energy (DOE) in 2018 with the goal of identifying novel technologies that can enable large (>100 meter [m]) blades for low-specific-power wind turbines. Five distinct tasks were completed to achieve this goal: 1. Assessed the trends, impacts, and value of low-specific-power wind turbines; 2. Developed a wind turbine blade cost-reduction road map study; 3. Completed research-and-development opportunity screening; 4. Performed detailed design and analysis; and, 5. Assessed low-cost carbon fiber. These tasks were completed by the national laboratory team consisting of Sandia National Laboratories (Sandia), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory.

17 WIND ENERGY↗