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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

EV Champion Training Webinar 2: ZEV and EV Charging Planning [Slides]

The Electric Vehicle (EV) Champion Training Series, hosted by the National Renewable Energy Laboratory (NREL), is tailored for fleet managers, facility managers, and other stakeholders involved in the deployment of EVs and charging stations. This series equips participants with the skills and knowledge necessary to become subject matter experts in EV implementation. This is the second training in a four-part series and serves as an intermediate training. This training covers the first four steps in the ZEV Ready Center process, including how to identify and train your zero-emission vehicle (ZEV) team, align headquarters strategy with site-level planning, identify ZEV opportunities, and identify charging needs for your project sites. Participants will gain a solid foundation to support the effective deployment and management of EVs and their infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Development of PNNL’s Plutonium Metallography Capability

The goal of this project was to develop plutonium metallography capabilities and establish workflows for characterization at PNNL’s Radiological Processing Facility (RPL). Developing and expanding on this capability opens more opportunities for PNNL to better support science through collaborations with other labs, plants, and sites withing the Department of Energy Complex and through programs within the National Nuclear Security Administration. This project established metallography equipment in an air glovebox, polishing protocols, as well as radiological and facility controls and procedures so that gram quantities of plutonium metal could be analyzed on multiple characterization tools. Data was collected and analyzed on two different delta phase plutonium - Gallium samples and a calciothermically reduced alpha plutonium metal using a combination of optical and electron microscopy, powder X-ray diffraction, and atom probe tomography. This report highlights the metallography capabilities, some preliminary data collections, and plans at PNNL to support plutonium material science.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Integrating Resilience Planning in Distribution System Planning

Electric utilities, regulators, and stakeholders face increasing risks of severe storms, freezes, floods, and heat waves damaging grid infrastructure and causing power outages—and increasing risks of utility equipment igniting wildfires. At the same time, customer electricity rates have risen substantially in recent years, due in part to replacing aging infrastructure and improving resilience to natural hazards and physical threats. To address these challenges, utilities are beginning to move beyond traditional, siloed planning processes to balance resilience with other fundamental grid objectives such as affordability, reliability, safety, and serving new loads. This study presents a framework for states and utilities that want to advance integration of resilience and distribution planning processes to improve planning efficiency, better prioritize cost-effective grid expenditures, and balance planning objectives. The framework includes 7 key integration points between these planning processes: -Strategy process -Data -Threat assessments -Solution identification and prioritization -Optimization opportunities -Consideration of other grid needs -Metrics Lawrence Berkeley National Laboratory reviewed utility distribution system plans and interviewed subject matter experts to identify emerging practices for each of the 7 integration points. This report presents these practices, which can be used as a guide toward more holistic planning and cohesive investment strategies. It also includes 3 case studies to provide practical examples of how utilities apply such integrated planning processes: two pole hardening programs and one microgrid planning effort. The report concludes by identifying opportunities for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Electrochemical Nutrient Recovery for the Food–Energy–Water Nexus at Municipal Wastewater Facilities: Multivariate Analyses of Seasonal Sampling and Reactor Performance

Digester-equipped municipal wastewater facilities generate recycle streams with high nutrient loads that increase energy consumption and can cause environmental pollution. The reduction of these loads through electrochemical nutrient recovery (ENR) could enhance the food–energy–water nexus by producing fertilizer (struvite). This study investigated the recovery process through a 1 year sampling of recycle streams and the implementation of nutrient recovery. Time series analyses showed that P (as orthophosphate) concentration was time-variant in digester effluent streams, while N (as ammonia) concentration was time-variant in only the aerobic system. Furthermore, these two nutrient concentrations did not correlate in any of the recycle streams. Subsequent multivariate screening analyses identified anode type, NH 4 + concentration, cathodic potential, P concentration, and temperature as most significant for ENR. Finally, the optimum conditions of cathodic potential, anode area-to-volume ratio, and temperature applied to a real recycle stream resulted in 95% P recovery with 0.03 kWh/kg P. This energy consumption is significantly lower than process energy for conventional P fertilizers (1.1 kWh/kg P) and chemical recovery processes at scale (1.7–12.9 kWh/kg P). Overall, this study recommended specific process controls for nutrient recovery, expanded the variables evaluated for ENR, and demonstrated the ability to significantly impact energy demand associated with P-based fertilizers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture

This work presents a two-stage adaptive framework for progressively developing deep neural network (DNN) architectures that generalize well for a given training data set. In the first stage, a layerwise training approach is adopted where a new layer is added each time and trained independently by freezing parameters in the previous layers. We impose desirable structures on the DNN by employing manifold regularization, sparsity regularization, and physics-informed terms. We introduce a ε – δ – stability-promoting concept as a desirable property for a learning algorithm and show that employing manifold regularization yields a ε – δ stability-promoting algorithm. Further, we also derive the necessary conditions for the trainability of a newly added layer and investigate the training saturation problem. In the second stage of the algorithm (post-processing), a sequence of shallow networks is employed to extract information from the residual produced in the first stage, thereby improving the prediction accuracy. Numerical investigations on prototype regression and classification problems demonstrate that the proposed approach can outperform fully connected DNNs of the same size. Moreover, by equipping the physics-informed neural network (PINN) with the proposed adaptive architecture strategy to solve partial differential equations, we numerically show that adaptive PINNs not only are superior to standard PINNs but also produce interpretable hidden layers with provable stability. As a result, we also apply our architecture design strategy to solve inverse problems governed by elliptic partial differential equations.

42 ENGINEERING↗
DOE OSTI2025

Time-tagging data acquisition system for testing superconducting electronics based on an RFSoC and custom analog frontend

Novel electronic devices can often be operated in a plethoraof ways, which makes testing circuits comprised of them difficult.Often, no single tool can simultaneously analyze the operatingmargins, maximum speed, and failure modes of a circuit, particularlywhen the intended behavior of subcomponents of the circuit is notstandardized. This work demonstrates a cost-effective time-domaindata acquisition system for electronic circuits that enables moreintricate verification techniques than are practical withconventional experimental setups. We use high-speeddigital-to-analog converters and real-timemulti-gigasample-per-second waveform processing to push experimentalcircuits beyond their maximum operating speed. Our customtime-tagging data capture firmware reduces memory requirements andcan be used to determine when errors occur. The firmware iscombined with a thermal-noise-limited analog frontend with50 dB of dynamic range. Compared to currentlyavailable commercial test equipment that is seven times moreexpensive, this data acquisition system was able to operate asuperconducting shift register at a nearly three-times-higher clockfrequency (200 MHz vs. 80 MHz).

Foster, Reed A. [MIT] (ORCID:0000000231002127)↗
DOE OSTI2024

Cybersecurity Considerations for the Liquified Natural Gas Sector

Due to the highly volatile nature of Liquified Natural Gas (LNG) and the systems required for generation and safe containment, it is likely a targeted cyber-attack on LNG control and safety systems will have a significant economic impact on energy supplies and prices. Moreover, if the interconnected operational technology (OT) devices within LNG systems are exploited to malfunction, the repair and recertification process will almost certainly be longer than for natural gas (NG) systems.

03 NATURAL GAS↗
DOE OSTI2025

COnfirmation using Gamma-ray Non-Imaging Zero-knowledge ANti-mask Time-encoding (COGNIZANT) Final Summary Report

In potential future arms reduction treaties in which the numbers of nuclear warheads may approach small numbers, using delivery systems as a proxy for the warheads themselves may be insufficient. Therefore, a technical means of verifying the presence of a nuclear warhead may become necessary. Verifying that a declared item actually is a warhead is technically challenging within a verification regime: providing assurance to the monitoring party that a presented item is a warhead while protecting sensitive information about that warhead may be required. It is generally believed that strong assurance will require the confirmation of key attributes that may reveal closely-guarded critical design information. This provides high confidence to the monitoring party, but presents a risk of information loss to the host. A verification system must overcome this hurdle. Over the last several decades, systems have been developed that balance host and monitoring partner needs by using sensitive information to confirm treaty accountable items (TAI) as warheads while sequestering that information behind an information barrier (1). These are designed to meet the needs of the host but places the onus on the monitor to authenticate the hardware, firmware, and software. Authentication requires that the monitor confirm that all components of the system have not been modified and work as intended. In 2014, Glaser et al. proposed applying the concept of “zero knowledge protocols” (ZKP) from the field of cryptography to the problem of warhead verification (2). In mathematical cryptography, ZKP is accomplished by challenging one party to solve a problem that is only possible if that party possesses the information being authenticated. After repeated challenges, the party provides confidence that it possesses this information without revealing any details about the information itself. Systems have been in development based on this idea at both Princeton and MIT (2) (3) (4). The final measurement results produced by these systems can be viewed by both the host and the monitoring party without the worry of revealing sensitive information. However, in both of these physical implementations, there remains an information barrier within the system. The need for a digital information barrier to protect a measurement result is eliminated, but it has been replaced with the need to sequester physical components of the system, potentially obfuscating the measurement process itself. Both implementations physically insert information into the system that requires protection to prevent undesired disclosure of sensitive information: in the Princeton method, one must physically load the complement of the expected image of a true warhead into the system, and in the MIT technique, one loads a collection of spectator foils whose thicknesses physically encrypt a measured spectrum. This complicates authentication of the hardware and measurement process. The CONFIDANTE/COGNIZANT concept developed in this project do not load sensitive information into the system at any time, and could therefore open the possibility of allowing the inspector to not only view the final data but also the measurement as it is being performed and all associated equipment.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2025

Embracing Uncertainty and Perseverance. A Brief Perspective on Conducting On-Site NDT Research

Dr. Judi E. See, a Systems Analyst and Human Factors Engineer at Sandia National Laboratories, reflects on her experience conducting NDT research in a male-dominated environment. She emphasizes the importance of persistence, flexibility, and persuasive skills in overcoming challenges, ranging from gaining access to test sites and equipment to building trust with inspectors. She shares her personal experience of navigating professional situations where gender disparities were evident, highlighting the need for women to adapt and overcome obstacles in traditionally male-dominated settings. See's journey demonstrates that perseverance and ingenuity can lead to significant contributions, process improvements, and recognition in the NDT field.

42 ENGINEERING↗
DOE OSTI2025

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Picasso: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing

A coloring of a graph is an assignment of colors to vertices such that no two neighboring vertices have the same color. The need for memory-efficient coloring algorithms is motivated by their application in computing clique partitions of graphs arising in quantum computations where the objective is to map a large set of Pauli strings into a compact set of unitaries. We present Picasso, a randomized memory-efficient iterative parallel graph coloring algorithm with theoretical sublinear space guarantees under practical assumptions. The parameters of our algorithm provide a trade-off between coloring quality and resource consumption. To assist the user, we also propose a machine learning model to predict the coloring algorithm’s parameters considering these trade-offs. We provide a sequential and a parallel implementation of the proposed algorithm. We perform an experimental evaluation on a 64-core AMD CPU equipped with 512 GB of memory and an Nvidia A100 GPU with 40GB of memory. For a small dataset where existing coloring algorithms can be executed within the 512 GB memory budget, we show up to 68× memory savings. On massive datasets we demonstrate that GPU-accelerated Picasso can process inputs with 49.5× more Pauli strings (vertex set in our graph) and 2,478× more edges than state-of-the-art parallel approaches.

artificial intelligence, quantum computing↗
DOE OSTI2025

Engineering Services in a Mission Critical Environment: Engineering Services - Science and Technology Operations’ Infrastructure Support at Los Alamos National Laboratory

As an engineering team within a facilities-driven organization, Engineering Services – Science and Technology Operations (ES-STO), supports Los Alamos National Laboratory (LANL), playing a pivotal role in the U.S. nuclear stockpile mission. This report outlines ES-STO’s contributions through the installation of crucial systems such as HVAC units, compressors, and scientific specialty equipment, as well as providing expert consultation to optimize laboratory operations. ES-STO’s goal is to ensure that LANL's infrastructure and research facilities are aligned with mission-critical needs, supporting both operational efficiency and safety in the nuclear stockpile management and maintenance. This report discusses the installation processes, ongoing consultations, and the significant impact of our efforts on national security objectives.

42 ENGINEERING↗
DOE OSTI2024

NMPC for Mode-Switching Operation of Reversible Solid Oxide Cell Systems

Solid oxide cells (SOCs) are a promising dual-mode technology that generates hydrogen through high-temperature water electrolysis and generates power through a fuel cell reaction that consumes hydrogen. Reversible operation of SOCs requires a transition between these two modes for hydrogen production setpoints as the demand and price of electricity fluctuate. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional integral (PI) control strategies, while ramping between the modes of hydrogen and power production. While both control methods provide similar performance in many metrics, NMPC significantly reduces cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives) during mode switching. A dynamic process flowsheet of the reversible SOC system was developed in the open-source, equation-based IDAES modeling framework. Our IDAES dynamic simulation results show that NMPC can ramp the SOC system between hydrogen and power production targets within short mode-switching times. Moreover, NMPC can comply with operating limits in the SOC system more effectively than PI, and only NMPC can directly enforce user-specified limits for mixed spatial-temporal partial derivatives of temperature. This allows for management of the trade-off be-tween operating efficiency and cell degradation, which is dependent on these temperature curvatures.

Li, Mingrui↗
DOE OSTI2025

Laser powder bed fusion parameter estimation with k-NN

Abstract Laser powder bed fusion (L-PBF) is a technique within additive manufacturing that uses a high power density laser to build parts from fused powdered metal alloy. This technology is well equipped to produce complex parts with otherwise impossible features, such as hidden voids or lattice structures. Alongside capability, reliability and quality are key characteristics considered when choosing a manufacturing method, and these are gaining attention as this method becomes more prevalent in industry. One main indicator of a stable L-PBF process is consistent melt pool geometry, and the properties of which are likely to determine the quality of the part produced. As computing power and sensing technologies become more advanced, this melt pool geometry could be studied in real time. This work addresses the challenge by leveraging a k-nearest neighbor (k-NN) model to identify key features within melt pool imagery and predict the energy density. The k-NN model was trained on data provided by the National Institute of Standards and Technology (NIST). Data preprocessing was performed on the images to extract features that were used in the k-NN model. This approach was used to accurately infer the energy density of unseen layers within the same part. The algorithm was subsequently tested with unique scan strategies and found to reasonably estimate the energy density of different parts. A fivefold cross validation found the algorithm to be consistently predicting the class of 91.4% of the in situ melt pool images.

Jung, Patrick (ORCID:0000000267890859)↗
DOE OSTI2025

Chemical Recycling of Polycaprolactones via Reactive Melt Processing

Chemical recycling is a promising technology for the deconstruction of waste plastics into monomers or other chemical intermediates, which can be converted into other value-added products or repolymerized into polymers. In this work, polycaprolactone and poly(4-propylcaprolactone) were chemically recycled by exploiting ring-closing depolymerization (RCD). To demonstrate the utility of this approach, reactive distillation experiments were initially conducted in a heated round-bottom flask with a distillation head to explore the effect of temperature and catalyst loading on RCD. Inspired by industrial devolatilization equipment, analogous experiments were conducted using a twin-screw melt compounder that was modified to simultaneously heat and mix polymer in the presence of a catalyst while continuously removing the evolved monomer vapors with a vacuum system and collecting them in a cold trap. Yield and selectivity of the recovered monomer were characterized by 1 H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry. Importantly, the more scalable twin-screw melt compounder approach produced values of monomer selectivity (∼90%) and yield (∼80%) similar to those of the round-bottom flask experiments. The recovered monomers were also successfully repolymerized into the same neat polymer with comparable molar masses without purification steps or adding initiator. Here, the results of this study promote the use of reactive devolatilization extrusion as a scalable approach to polyester depolymerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

ORNL Package Testing Program Overview

When transporting radioactive or hazardous materials, safety and security are top priorities. Packaging and transportation regulations require reliable evidence that containers have passed rigorous performance tests to ensure that the public and the environment are protected from the hazardous nature of the cargo. Because of its long history in energy and security research, Oak Ridge National Laboratory (ORNL) has needed to ship hazardous packages for the past 65 years. Since the 1940s, ORNL has made significant contributions to transportation regulations and has been at the forefront of regulatory testing development. Today, ORNL is a leader in standards development and testing of designs of radioactive material packages. ORNL plays a critical role in ensuring the safe transportation of radioactive materials across the United States by executing rigorous testing campaigns of packages that contain radioactive materials. Early testing activities focused on supporting the development of transportation regulations established by both the International Atomic Energy Agency (IAEA) and the United States. Currently, all package testing activities are performed under the Package Testing Program (PTP) at the Package Evaluation Facility (PEF) located at the National Transportation Research Center (NTRC), which is about 10 miles from the main ORNL campus. The PTP develops and evaluates testing solutions, ensuring that they are safe efficient, and in compliance with regulatory requirements. The vision for the PTP is to be a world-class leader in the evaluation and testing of radioactive and hazardous material packages. The key elements necessary to fulfill this mission are an experienced and professional staff; state-of-the-art facilities, equipment, and instrumentation; and completion of challenging programs and projects important to package transportation. Collaborations with other internal and external organizations play a significant role in building stronger teams and achieving this vision. By adhering to and advancing regulatory standards, ORNL’s PTP supports development of safe and compliant packaging, safeguarding the transportation process from potential risks associated with radioactive material logistics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Filtration of Hanford Tank 241-AN-107 Supernatant at 16 °C

Approximately 9 liters of supernatant from Hanford waste tank 241-AN-107 was delivered by Washington River Protection Solutions to the Radiochemical Processing Laboratory (RPL) at Pacific Northwest National Laboratory. The thirty-six AN-107 sample bottles consisted of six sets of six samples, with each set pulled from a unique tank sampling level. Prior to testing, samples from each level were composited to provide nominally level-independent feed for dead end filtration and ion exchange testing. The composited 241-AN-107 supernatant was chilled to 16 °C for 1 week prior to testing. Filtration testing was then conducted using a backpulse dead-end filter (BDEF) system equipped with a feed vessel and a Mott inline filter Model 6610 (Media Grade 5) in the hot cells of the RPL. The purpose of this testing is to a) demonstrate dead-end filtration (DEF) of AN-107 feed at reduced temperature to obtain prototypic tank side cesium removal (TSCR) flux rates and identify issues that may impact filtration after dilution to 5.5M Na, and b) provide feed for a follow on ion exchange unit operation. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft 2 . During filtration the differential pressure required to effect filtration at 0.065 gpm/ft 2 was slow to increase for most of the filtration campaign. After all the feed bottles had been pumped into the slurry reservoir, the bottoms of the bottles were added to the reservoir and transmembrane pressure (TMP) reached 2.0 psid (the TSCR action limit). The prototypic filter cleaning process was unable to effectively restore filter performance, and cleaning with oxalic acid was required before flow through the filter could be restored. This indicates that the Media Grade 5 filter may require an alternative cleaning protocol when processing AN-107 supernatant. After completing filtration of the AN-107 feed, the filter was cleaned. Solids concentrated from the backpulse solutions were composed of natrophosphate, Mn-Fe phases, and fluoro-natrophosphate that occurred as particle agglomerates. The individual particles were in some cases 100s of micrometers across which is consistent with prior observations from AN-107 supernate waste characterizations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗