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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This project (1) developed and demonstrated data-driven process controls at full-scale facilities for five promising WRRF process technologies that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) created a Machine Learning (ML) Toolkit and an implementation guide of new process control approaches that walks users through each step of the ML workflow and illustrates the steps through case study examples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High power density compact drive integrated motor for electric transportation

This project, initially part of OPEN 2018, and subsequently the ASCEND effort, targeted demonstration of significant enhancements in internal permanent magnet (IPM) motor torque and power density for current and future ground and air electric transportation applications. These were achieved through: (1) embedded two-phase system thermal management, (2) coupled, multi-scale electrical-electromagnetic-thermal-mechanical co-design and optimization, (3) size and weight reduction of motor and drive electronics through elimination of redundant cooling and coupling hardware, and (4) higher efficiency operation of SiC wide bandgap power electronics packaging through high temperature operation (200 oC). The proposed approach utilizes a single dielectric coolant for closed loop two-phase thermal management, and a combined heat rejection unit for the IPM and drive. Wick assisted liquid delivery for evaporative thermal management is utilized for the motor, and the drive electronics utilize the same coolant in flow boiling within the cold plate structures. Through the use of three-dimensional packaging for SiC, and novel drive topologies with reduced switching losses, significant increases in power density and compactness were targeted.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Bioreactor Optimization through Multi-Phase Flow Models (CRADA Final Report)

Chemical manufacturing uses 29% of energy in the United States and produces 925 million metric tons of CO2 annually. Biomanufacturing offers the potential to leverage America’s rich agricultural resources to produce critical chemicals such as lubricants, pharmaceutical precursors, and components of energetic materials that today are sourced extensively from overseas. The bioreactors used in biomanufacturing applications, such as one developed by Capra Biosciences, involve multiphase flow of biofilm-coated solid support particles that are continuously circulated in a fluidized state within the reactor along with a constant supply of oxygen via an aeration mechanism. In this project, Capra Biosciences and LBNL developed a multiscale modeling framework to simulate the multiphase flows of solid particles in a liquid-gas bubble mixture that occurs in the bioreactor using the current MFIX-Exa software, an opensource multiphase flow solver developed and maintained at LBNL and NETL. By leveraging HPC capabilities, this high-fidelity multiscale model was used to inform design decisions for bioreactor architecture to make them operationally efficient.

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

Laser calibration system at ProtoDUNE-HD

The Deep Underground Neutrino Experiment (DUNE) is a full experiment consisting of multiple detectors separated by a near and far site. DUNE will study long-baseline neutrino oscillations, which will provide insight into CP-violation, neutrino mass ordering, and the matter/antimatter asymmetry. Additionally, DUNE will search for nucleon decay and observe neutrinos from supernovae. DUNE relies on liquid argon time projection chambers (LAr TPCs), an excellent technology for tracking particles and reconstructing their interactions with high precision. To achieve its goals, DUNE is supported by the ProtoDUNE experiments at CERN, which serve as large-scale prototypes to validate detector technologies and calibration systems. The precise calibration of the electric field within the detector is vital for accurate 3D reconstruction of particle tracks, particularly in maintaining the consistency of charge measurements along the drift path. This work presents the development and implementation of a laser calibration system designed for ProtoDUNE-II. This poster involved the physical installation and commissioning of the laser system. The commissioning process included extensive testing to ensure alignment and operational efficiency, such as rotating the laser to observe behavior of tracks. The groundwork established during these steps is crucial for future data analysis, aiming to measure the electron lifetime (in the active volume) and map the electric field inside the detector with high precision.

Campanelli, Wallison [LIP]↗
DOE OSTI2025

Advancing Conduction-Cooled 650 MHZ SRF Technology for Industrial Accelerators at Fermilab S IARC

The National Nuclear Security Administration (NNSA) funds the Illinois Accelerator Research Center (IARC) at Fermilab in developing a high-power, conduction-cooled Superconducting Radio Frequency (SRF) accelerator tailored for industrial applications requiring robust and efficient operation. A 650 MHz, 1.6 MeV, 20 kW SRF accelerator is currently under development, employing a conduction cooling approach to simplify cryogenic requirements and enhance accessibility for industrial use. The accelerator's control system is implemented on the Blinky Lite platform, selected for its open-source architecture, secure remote access capabilities, and operational flexibility attributes advantageous for industrial deployment and sustained operation. A dedicated beamline is designed to measure essential beam parameters and test the integrated performance of the accelerator and control systems, thereby validating their operational readiness for intended applications.

Ji, Yichen [Fermilab]↗
DOE OSTI2025

Feasibility and Compatibility of Alternative Fuels in the U.S. Rail Sector: Technoeconomic, Lifecycle, and Supply Chain Analysis

The U.S. rail sector is a cornerstone of the United States’ freight transportation system, responsible for moving approximately 40% of long-distance freight ton-miles each year (AAR, 2025). Freight demand is projected to grow over time (BTS, 2017) thereby necessitating the investigation of alternative fuels that can sustain operational efficiency while reducing emissions and cost impacts. At the same time, it is important to explore alternative fuels as new sources of energy that can increase energy security and resilience for this sector. This report investigates the feasibility and compatibility of seven alternative fuels in the U.S. rail sector, focusing on biofuels and fuels from other renewable energy sources. The study evaluates alternative fuel pathways, considering their technical, economic, and environmental aspects to provide stakeholders with a comprehensive understanding of potential solutions.

09 BIOMASS FUELS↗
DOE OSTI2025

Advanced Reactor Designs Security Analysis, Risk, and Recommendations: Risks, Consequences, and Possible by-Design Mitigation Approaches Associated with Select Advanced Reactors

Next-generation advanced reactors (ARs) incorporate enhanced safety systems, have smaller source terms, and feature compact modular designs, which should lessen their collective risk profiles. However, to fully evaluate risk, security needs to be a part of the equation. Without taking security into consideration, safety systems and components in the new ARs may be vulnerable to sabotage. These base attributes, coupled with enhanced security features specific to AR design through sound engineering and security-by-design (SeBD), should provide developers and operators with lower inherent security risk profiles. Building security early into the AR design may remove or passively secure potential critical targets from an adversary’s reach , thereby increasing overall safety and security. An integrated approach and diverse design team that includes engineering, operations, and security experts are fundamental to building security into the design without sacrificing fundamental operational efficiencies and principles. The objective of this project was to evaluate the security and safety interfaces for five classes of reactors, identify potential security vulnerabilities of structures, systems, and components (SSC), and underscore the need to consider security alongside safety in the design o f these concepts. The five reactor classes evaluated in this project and presented in this report are molten-salt reactors (MSR), high temperature gas reactors (HTGR), sodium-fast reactors (SFR), advanced light-water reactors (ALWR), and microreactors. These designs were selected because they reflect the concepts that are closest to market deployment and have received significant resource investments from the public and private sector. This project assesses the inherent security risks posed by common classes of ARs, provides a methodology and framework to assess security along with safety, and offers an analysis of potential mitigation strategies that could be incorporated. For each AR technology, the SSCs that relate to radionuclide source safety functions are discussed to understand the SSC contribution to safety and relative importance in the protective strategy for the design. The assumptions that went into evaluating each reactor concept originated from generic publicly available nonproprietary information and should not directly be used to qualify an absolute risk profile nor to rank specific AR designs. Instead, the purpose of the analysis is to understand and compare the generic inherent security risks of different AR technologies.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2026

Product Defect Detection System: SYSM- 5620 Final Project

Retail sales is a growing market estimated to up to seven percent year over year. With this growing market there is also a trend in growing rate of retail returns, estimated just last year at $\$$850 billion. Retail stores must ensure that products available for purchase remain safe, undamaged, and acceptable to customers throughout their time in the store. This job exists regardless of the specific solution used because stores are always responsible for preventing damaged or defective products from reaching customers and when they fail to this is categorized under operation inefficiencies which accounts for an estimated $\$$12 billion in returns. When defective items remain on the sales floor, stores may experience increased returns, reduced customer satisfaction, loss of customer trust, and potential safety concerns depending on the product type. As a result, the core job to be done is to identify defective products quickly, remove them from the sales floor before they are purchased, and preserve useful information about the defect so that the store can improve its handling, stocking, and supplier coordination over time. The need for a more reliable process is especially important in high volume retail environments where employees manage large numbers of products across many aisles, shelves, and storage areas. In these settings, manual inspection alone can be inconsistent and difficult to sustain at the individual item level. At the same time, broader retail trends continue to emphasize operational efficiency, product visibility, and improved customer experience, creating an opportunity for more automated and data driven defect detection methods.

42 ENGINEERING↗
DOE OSTI2026

ARCH Technology Snapshot Autonomous Robot Control Hierarchy (ARCH): A universal software system that removes the need to rebuild robotic software for every new platform or task

Robots are increasingly used to perform repetitive, hazardous, and time-sensitive tasks, improving safety and operational efficiency. However, most robotic systems remain difficult to adapt because they are tightly tied to specific hardware and require extensive reprogramming for each new configuration.

42 ENGINEERING↗
DOE OSTI2021

Data-Driven Probabilistic Anomaly Detection for Electricity Market under Cyber Attacks

Information and communication technologies have been widely used in smart grid for efficient operation. However, these technologies are vulnerable to malicious cyber attacks, which may lead to severe reliability and economic issues. Recently, a variety of data-driven anomaly detection approaches have been explored to detect potential cyber attacks in smart grids. In this paper, we researched on the electricity market data aiming to identify anomalies from the locational marginal prices (LMPs) and provide a new indicator for potential cyber attacks in power grids. Specifically, a novel data-driven probabilistic anomaly detection framework is proposed for electricity market, which consists of three major components: long short-term memory (LSTM) based deterministic electricity price forecasting, probabilistic electricity price forecasting and anomaly detection. This framework is tested on a model-based electricity market simulator under two types of cyber attacks, i.e., load redistribution attack (LRA) and price responsive attack (PRA). Numerical results on the simulated LMPs show that the proposed framework is capable of detecting data anomalies over these attacks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Sink or Swim: A Tutorial on the Control of Floating Wind Turbines: Preprint

Within the rapidly growing wind energy sector, floating offshore wind turbines are expected to be the fastest growing portion. This is largely driven by the immense offshore wind resources that are mostly over deep water, where fixed-bottom concepts become cost prohibitive. However, compared to fixed-bottom wind turbines, floating wind turbines are more dynamic and exhibit potential instabilities, which requires advanced control technologies to ensure a safe and efficient operation. Beyond their existing objectives of maximizing power production while minimizing structural loads, floating wind turbine controllers must also avoid large platform oscillations and accommodate wave disturbances. This paper provides an overview of the challenges and opportunities in the control of floating offshore wind energy systems.

control↗
DOE OSTI2021

Error-Level-Controlled Synthetic Forecasts for Renewable Generation

Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the importance of short-term (hours ahead) renewable generation forecasting in power systems operation, it becomes crucial to address the potential inaccuracies in these forecasts. To systematically evaluate the performance of controllers in the presence of imperfect forecasts, we generate synthetic forecasts using actual renewable generation profiles (one from solar and one from wind). These synthetic forecasts incorporate different levels of statistical error, allowing us to control and manipulate the accuracy of the predictions. The primary objective is to employ synthetic forecasts with controlled yet realistic error levels to systematically investigate how controllers adapt to variations in forecast accuracy, providing valuable insights into their robustness and effectiveness under real-world conditions.

Array↗
DOE OSTI2026

Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions

Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.

artificial intelligence↗
DOE OSTI2024

Integrated Transmission and Distribution Co-Simulation Platform for Demonstration of Bulk Grid Services Using Distributed Energy Resources

In September 2020, the Federal Energy Regulatory Commission (FERC) released Order 2222, which opens wholesale markets to small-capacity distributed energy resources (DERs), recognizing their potential in improving operational efficiency by providing bulk grid services. Therefore, a co-simulation capability that can connect transmission and distribution (T&D) simulations and evaluate the impacts of DER provision of bulk grid services is needed. In this paper, we present a new integrated T&D co-simulation platform that incorporates T&D system simulators, DER aggregator/group strategies, and a co-simulation coordinator. Industry-standard communication protocols are employed to mimic real-world conditions. Secondary frequency regulation is selected as the representative bulk grid service, and we simulate the responses of DERs to the frequency regulation signals. The simulation results for a solar-rich distribution feeder in Colorado, USA, demonstrate how the T&D co-simulation setup is used to evaluate the contributions of DERs to minimize the bulk grid frequency deviation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Leveraging Optimal Sparse Sensor Placement to Aggregate a Network of Digital Twins for Nuclear Subsystems

Nuclear power plants (NPPs) require continuous monitoring of various systems, structures, and components to ensure safe and efficient operations. The critical safety testing of new fuel compositions and the analysis of the effects of power transients on core temperatures can be achieved through modeling and simulations. They capture the dynamics of the physical phenomenon associated with failure modes and facilitate the creation of digital twins (DTs). Accurate reconstruction of fields of interest (e.g., temperature, pressure, velocity) from sensor measurements is crucial to establish a two-way communication between physical experiments and models. Sensor placement is highly constrained in most nuclear subsystems due to challenging operating conditions and inherent spatial limitations. This study develops optimized data-driven sensor placements for full-field reconstruction within reactor and steam generator subsystems of NPPs. Optimized constrained sensors reconstruct field of interest within a tri-structural isotropic (TRISO) fuel irradiation experiment, a lumped parameter model of a nuclear fuel test rod and a steam generator. The optimization procedure leverages reduced-order models of flow physics to provide a highly accurate full-field reconstruction of responses of interest, noise-induced uncertainty quantification and physically feasible sensor locations. Accurate sensor-based reconstructions establish a foundation for the digital twinning of subsystems, culminating in a comprehensive DT aggregate of an NPP.

42 ENGINEERING↗
DOE OSTI2025

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗
DOE OSTI2023

Removal of Iron from Pyrite-Rich Coal Refuse by Calcination and Magnetic Separation for Hydrometallurgical Extraction of Rare Earth Elements

In the metallurgical extraction of rare earth elements (REEs), the ratio of contaminant ions to REEs in the leachate dictates the cost and operational efficiency of the downstream processes. The current study investigated the potential iron contamination removal from the feed to the hydrometallurgical process by calcination followed by magnetic separation. The 2.20 specific gravity sink fraction of Baker coal seam coarse refuse was pulverized to finer than 180 μm, calcined at various temperatures, and separated into magnetic and non-magnetic fractions using a wet high-intensity magnetic separator at different field strengths. The untreated feed, calcined products, and their subsequent magnetic and non-magnetic fractions were subjected to acid leaching tests with 1.2 M sulfuric acid at 75 °C and 1% w/v solids concentration. The recovery of light and heavy rare earth elements (LREEs and HREEs, respectively) along with the concentration of common contaminant ions (Al, Ca, and Fe) were measured as output variables. The weight percent of magnetic material was maximized at approximately 29% by calcination at a temperature of 400 °C. Magnetic removal of this fraction using a field strength of 1.15 Tesla resulted in the rejection of 81% of the iron. Leaching of the magnetic fraction provided significantly higher Fe recovery relative to untreated feed material and the non-magnetic fraction. The non-magnetic fraction was subsequently calcined at 600 °C to dehydroxylate the clays and released the REE minerals in the same manner as the treatment of the original coarse refuse material. A comparison of the leachate elemental concentrations resulting from the leaching of both the calcined non-magnetic and original coarse refuse showed only a slight reduction in the iron content from the non-magnetic material. This finding combined with the REE loss in the magnetic fraction resulted in the conclusion that the magnetic removal step was unfavorable.

58 GEOSCIENCES↗