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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Semi-Empirical Density Law for Ternary, Homogeneous PuCl 3 /HCl/H 2 O Solutions

Nuclear material operations pose unique hazards that are not encountered in other chemical, energy, or manufacturing industries. One of these hazards is the potential for a nuclear criticality accident when handling fissile isotopes such as 235 U and 239 Pu. These hazards are particularly high when fissile material is dissolved in solution as the neutron behaviors of the system can change rapidly with the physical and chemical changes accessible in solution. Current estimates of solution density used for criticality safety are outdated and hinder fissile material handling. Developing new estimates for these safety calculations requires experimental characterization and the derivation of empirical density models. We have derived a density law describing PuCl 3 /HCl/H 2 O solutions from experimental data characterizing solution density. Density data was treated using a Pitzer-derived eight-parameter equation, defining density as a function of analyte concentrations, temperature, and interactions between these variables. The model is predictive across the concentration and temperature ranges from which it was derived. The potential effects of varying oxidation states of plutonium, which are easily accessible in aqueous media, on the bulk solution density of the ternary system were also investigated. The resulting Pitzer-derived density law was applied to a nuclear criticality safety model, and the impact of the experimental characterization of solution density relative to previous estimates was demonstrated to be significant and suggest that the current approach to estimating density in nuclear criticality safety calculations may lead to overly conservative controls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Self-Aware Local Autonomous and Semi-Cooperative Control for Cross-Layered Resilience (SLAC3R)

The objective of this work is to develop and demonstrate novel, adaptive, lightweight algorithms that enable the decision-making agents in a large cyber-physical network to act both autonomously and in collaborative harmony to enforce assured resilience across spatiotemporal layers, even under unforeseen adversarial scenarios (e.g., high- impact-low-probability events). Towards this end, the proposed solution will serve as minimally invasive add-on layers that bridge the existing (faster, reactive) local myopic controls and (slower, predictive) centralized optimization. Importantly, the proposed algorithms will enable the multi-agent network to autonomously and collaboratively enforce resilient operation under no or limited communication environment typical of severe cyber- physical adversarial events. The expected outcome of this effort is a suite of prototype, open-source, software algorithms for safety-aware local autonomous and semi-cooperative control (SLAC3R), demonstrated on networked microgrids (via RD2C/Thrust-1 OPAL-RT testbed).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Quantum prediction of ultra-low thermal conductivity in lithium intercalation materials

Lithium-intercalated layered transition-metal oxides, Li x TMO 2, brought about a paradigm change in rechargeable batteries in recent decades and show promise for use in memristors, a type of device for future neural computing and on-chip storage. Thermal transport properties, although being a crucial element in limiting the charging/discharging rate, package density, energy efficiency, and safety of batteries as well as the controllability and energy consumption of memristors, are poorly managed or even understood yet. Here, for the first time, we employ quantum calculations including high-order lattice anharmonicity and find that the thermal conductivity κ of Li x TMO 2 materials is significantly lower than hitherto believed. More specifically, the theoretical upper limit of κ of LiCoO 2 is 6 W/m-K, 2–6 times lower than the prior theoretical predictions. Delithiation further reduces κ by 40–70% for LiCoO 2 and LiNbO 2 . Grain boundaries, strain, and porosity are yet additional causes of thermal-conductivity reduction, while Li-ion diffusion and electrical transport are found to have only a minor effect on phonon thermal transport. The results elucidate several long-standing issues regarding the thermal transport in lithium-intercalated materials and provide guidance toward designing high-energy-density batteries and controllable memristors.

25 ENERGY STORAGE↗
DOE OSTI2024

Gut enterotype-dependent modulation of gut microbiota and their metabolism in response to xanthohumol supplementation in healthy adults

Xanthohumol (XN), a polyphenol found in the hop plant (Humulus lupulus), has antioxidant, anti-inflammatory, prebiotic, and anti-hyperlipidemic activity. Preclinical evidence suggests the gut microbiome is essential in mediating these bioactivities; however, relatively little is known about XN’s impact on human gut microbiota in vivo. We conducted a randomized, triple-blinded, placebo-controlled clinical trial (ClinicalTrials.gov NCT03735420) to determine safety and tolerability of XN in healthy adults. Thirty healthy participants were randomized to 24 mg/day XN or placebo for 8 weeks. As secondary outcomes, quantification of bacterial metabolites and 16S rRNA gene sequencing were utilized to explore the relationships between XN supplementation, gut microbiota, and biomarkers of gut health. Although XN did not significantly change gut microbiota composition, it did re-shape individual taxa in an enterotype-dependent manner. High levels of inter-individual variation in metabolic profiles and bioavailability of XN metabolites were observed. Moreover, reductions in microbiota-derived bile acid metabolism were observed, which were enterotype-dependent. These results suggest interactions between XN and gut microbiota in healthy adults are highly inter-individualized and potentially indicate that XN elicits effects on gut health in an enterotype-dependent manner.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference

Large-scale battery energy storage systems (BESS) have found ever-increasing use across industry and society to accelerate clean energy transition and improve energy supply reliability and resilience. However, their optimal power management poses significant challenges: the underlying high-dimensional nonlinear nonconvex optimization lacks computational tractability in real-world implementation, and the uncertainty of the exogenous power demand makes exact optimization difficult. This paper presents a new solution framework to address these bottlenecks. The solution pivots on introducing power-sharing ratios to specify each cell’s power quota from the output power demand. To find the optimal power-sharing ratios, we formulate a nonlinear model predictive control (NMPC) problem to achieve power-loss-minimizing BESS operation while complying with safety, cell balancing, and power supply-demand constraints. We then propose a parameterized control policy for the power-sharing ratios, which utilizes only three parameters, to reduce the computational demand in solving the NMPC problem. This policy parameterization allows us to translate the NMPC problem into a Bayesian inference problem for the sake of 1) computational tractability, and 2) overcoming the nonconvexity of the optimization problem. We leverage the ensemble Kalman inversion technique to solve the parameter estimation problem. Concurrently, a low-level control loop is developed to seamlessly integrate our proposed approach with the BESS to ensure practical implementation. This low-level controller receives the optimal power-sharing ratios, generates output power references for the cells, and maintains a balance between power supply and demand despite uncertainty in output power. We conduct extensive simulations and experiments on a 20-cell prototype to validate the proposed approach.

Battery energy storage systems (BESSs)↗
DOE OSTI2025

Three‐trophic level food webs support the safety of a biocontrol agent 3 years after release

Biological control (biocontrol) is a powerful tool for managing invasive alien species and assisting the restoration of native ecosystems. Rigorous post‐release monitoring of biocontrol agents is critical to evaluate the success of biocontrol programs; however, this is still rarely implemented. Here, we combined the use of species interaction networks with a Before‐After Control‐Impact design to evaluate the target and non‐target, direct and indirect effects of the Australian gall wasp Trichilogaster acaciaelongifoliae , released to control the invasive plant Acacia longifolia in Portugal. We compared the structure of plant‐galling insect‐parasitoid food webs before and 3 years after the release of the biocontrol agent. Exhaustive sampling did not detect any non‐target effects, either direct (on non‐target plants) or indirect (on other galling insects via shared plants). Additionally, no significant changes were detected in network structure that could be related to the establishment of the biocontrol agent. This study shows that monitoring biocontrol at the community level is possible and that, when carefully planned, biocontrol poses minimal risk of non‐target effects.

López‐Núñez, Francisco A. [Centre for Functional E↗
DOE OSTI2020

Fissionable Materials Handlers Operators-Initial Training

These courses were designed for all Initial Fissionable Material Handlers Operators and Supervisors whose job activities will require the performance of Fissile Material Operations located within the Plutonium Facility (PF-4). The course requirements are based on DOE order 426.2, Personnel Section, Qualification, and Training Requirements for Fissionable Material Handlers. These courses are required training for all initial Fissionable Material Handlers and is specific to TA-55 FMH Certification. It covers the core areas and topics in Criticality Safety, Material-at-Risk, Nuclear Material Control and Accountability, Radiological Protection, TA-55 Material Handling and Movement.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Boiler Health Monitoring Using a Hybrid First Principles-Artificial Intelligence Model

Due to increased penetration of the intermittent renewables to the grid, pulverized coal (PC) plants are being forced to cycle their load frequently and rapidly, operate at low load condition for sustained period, and start up and shut down several hundred times in a year in the worst case. These severe operations are causing substantial damage to the boiler components compromising the reliability of PC plants. An online health monitoring tool can be instrumental in understanding the impacts of load-following and can eventually help PC plants to develop advanced process control strategies for improved flexibility without compromising safety nor reliability.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Simulation-Based Recovery Action Analysis Using the EMRALD Dynamic Risk Assessment Tool

A recovery action is defined as the action that prevents deviant conditions from producing unwanted effects. It generally indicates a kind of countermeasure performed in response to a failure of human action. The recovery actions especially play an important role in complex systems like nuclear power plants (NPPs), which consist of highly sophisticated controllers to ensure that desired performance and safety must be achieved and maintained. This is because a combination of human error and its recovery failure may be able to cause a catastrophic effect on a system. Analyzing recovery actions has been a critical part of HRA, which is a technique to evaluate human errors and provide human error probabilities (HEPs) for application in probabilistic safety assessment (PSA). If recovery actions are not adequately analyzed and applied to PSA models, the PSA results may be under-estimated or be not able to reasonably account for the failure of human actions in the context of PSA. For this reason, some regulatory documents such as ASME/ANS RA-Sb-2013 by the American Society for Mechanical Engineers and the American Nuclear Society and NUREG-1792 by U.S. Nuclear Regulatory Commission have emphasized the importance of recovery analysis within the HRA. A couple of existing HRA methods, such as the Technique for Human Error-Rate Prediction (THERP), the Cause-Based Decision Tree (CBDT), and the Korean Standard HRA (K-HRA), have respectively suggested their own approaches to the HRA recovery analysis. However, there are a couple of limitations to treating recovery actions using only the current HRA methods available. The biggest limitation is that the existing recovery analysis does not explicitly consider a variety of recovery action types and recovery sequences as they occur in actual NPPs. To handle the limitations of existing recovery analysis, this study proposes a simulation-based recovery analysis method using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. The EMRALD software is a dynamic simulation tool for PSA. It supports realistic and dynamic modeling of human actions as they would be performed at NPPs. It is also favorable to simultaneously model the specific moment at which an action is performed, the time it takes to perform the action, and the failure probability of that action. In this paper, a detailed methodology for modeling recovery actions in the simulation platform is proposed with a couple of examples. Then, outputs from the simulation are discussed as reviewing if this novel approach can complement the challenges of existing recovery analyses.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Implementation of a System of Gamma Imagers for Measuring Plutonium Holdup

The Surplus Plutonium Disposition (SPD) project is an effort to dilute and dispose of many tonsof weapons grade plutonium. This work will take place in a shielded glovebox to protect workers fromradiological dose. Accurate measurements of the holdup, or material left behind, in the gloveboxes is im-portant for Nuclear Material Control and Accountancy, worker dose minimization, criticality safety, andprocess monitoring. Shielding around the gloveboxes presents an obstacle for the traditional GeneralizedGamma Holdup (GGH) method. The uncertainties associated with that method, at around 28%, arealso detrimental since the amount of holdup must be kept below an established limit with a high level ofconfidence.Passive gamma-ray imaging provides a more complete depiction of the distribution of radioactivematerials. Recent refinement of the method has demonstrated that quantitative information can beextracted from the images with a well-characterized system. A permanently installed system of gamma-ray imagers is currently being developed to measure plutonium holdup in the SPD gloveboxes. Thispaper will report on progress with the development of this system.This application requires that the features of current commercially available instruments from H3Dand PHDS, optimized for measurement performance in a mobile application, be translated into theconstraints of the operational environment with fixed installations. The interaction between facilityconstraints and measurement capabilities will be addressed.A series of measurements with plutonium sources in a mocked-up glovebox geometry with imagersmounted above the ceiling of the glovebox have been taken. Imager performance with respect to angularresolution, minimum measurement time for quantification, and signal-to-noise ratio with a multitudeof sources will be evaluated for those measurements. A series of prototypes of user interfaces will bepresented for display of the data to its various consumers for the purposes of Nuclear Material Controland Accountancy, worker dose minimization, criticality safety, and process monitoring.

Schmitt, Kyle↗
DOE OSTI2026

MARVEL Lessons Learned – 2026 Edition Fabrication, Fuel Procurement, Quality Assurance, and Safety Basis

The Microreactor Applications Research Validation and Evaluation (MARVEL) project is intended to be among the first U.S. advanced reactor demonstrations in four decades. By virtue of being sponsored directly by the U.S. Department of Energy (DOE), the reactor is expected to benefit the broader nuclear community by exercising design processes, safety reviews, and supply chains. This project is committed to publicly documenting key lessons learned along the way toward demonstration. Building on a 2025 report that focused on lessons learned from guard vessel fabrication and Primary Coolant Apparatus Test (PCAT) testing (Abou-Jaoude et al. 2025), this 2026 edition captures findings spanning structural fabrication, quality assurance (QA), reactivity control system (RCS) assembly, fuel fabrication and shipment, safety basis development, balance-of-plant design, and overall reactor design.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees

We present differentiable predictive control (DPC), a method for offline learning of constrained neural control policies for nonlinear dynamical systems with performance guarantees. We show that the sensitivities of the parametric optimal control problem can be used to obtain direct policy gradients. Specifically, we employ automatic differentiation (AD) to efficiently compute the sensitivities of the model predictive control (MPC) objective function and constraints penalties. To guarantee safety upon deployment, we derive probabilistic guarantees on closed-loop stability and constraint satisfaction based on indicator functions and Hoeffding’s inequality. We empirically demonstrate that the proposed method can learn neural control policies for various parametric optimal control tasks. In particular, we show that the proposed DPC method can stabilize systems with unstable dynamics, track time-varying references, and satisfy nonlinear state and input constraints. Our DPC method has practical time savings compared to alternative approaches for fast and memory-efficient controller design. Specifically, DPC does not depend on a supervisory controller as opposed to approximate MPC based on imitation learning. We demonstrate that, without losing performance, DPC is scalable with greatly reduced demands on memory and computation compared to implicit and explicit MPC while being more sample efficient than model-free reinforcement learning (RL) algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Optimal Distribution System Voltage Regulation using State Estimation and DER Grid-Support Functions

Increasing solar energy penetrations may create challenges for distribution system operations because production variability can lead to large voltage deviations or protection system miscoordination. Instituting advanced management systems on distribution systems is one promising method for combating these challenges by intelligently controlling distribution assets to regulate voltage and ensure protection safety margins. While it is generally not the case today, greater deployment of power system sensors and interoperable distributed energy resources (DER)e.g., photovoltaic (PV) inverters, energy storage systems (ESS), electric vehicles (EVs)will enable situational awareness, control, and optimization of distribution systems. In this work, a control system was created which measures power system parameters to estimate the status of a feeder, forecasts the distribution state over a short-term horizon, and issues optimal set point commands to distribution-connected equipment to regulate voltage and protect the system. This two-year project integrated multiple research innovations into a management system designed to safely allow PV penetrations of 50% or greater. The integrated software was demonstrated through extensive real-time (RT) and power hardware-in-the-loop studies and a field demonstration on a live power system with a 684 kVA PV system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Model predictive control for demand flexibility: Real-world operation of a commercial building with photovoltaic and battery systems

Hundreds of studies have investigated Model Predictive Control (MPC) for the optimal operation of building energy systems in the past two decades. However, MPC field tests are still uncommon, especially for small- and medium-sized commercial buildings and for buildings integrated with onsite renewables. This paper describes the implementation and the long-term performance evaluation of an MPC controller in a small commercial building equipped with behind-the-meter photovoltaics and electrochemical batteries. MPC controls space conditioning, commercial refrigeration, and the battery system. We tested two types of demand flexibility applications in the field: electricity bill minimization under time-of-use tariffs and responses to grid flexibility events. Results show that the proposed controller achieves 12% of annual electricity cost savings and 34% peak demand reduction against the baseline, while respecting thermal comfort and food safety. The field tests also demonstrate the ability of the MPC controller to provide a multitude of grid services including real-time pricing, demand limiting, load shedding, load shifting, and load tracking, using the same optimization framework.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Extremum-Seeking-Based Ultra-local Model Predictive Control and Its Application to Electric Motor Speed Regulation

Electric vehicle (EV) market is rapidly expanding. As a critical component of EV, an electric motor needs to accurately follow a reference speed signal while respecting the electrical current constraint for safety. Those requirements are usually formulated as a model predictive control (MPC) problem. However, the performance of traditional model-based MPC depends on the accuracy of the system model, which may not always be guaranteed in reality. Therefore, we utilize a data-driven, model-free predictive control strategy, called ultra-local MPC (ULMPC), to control the speed of an electric motor. To further enhance the control performance of ULMPC, we employ the extremum-seeking control (ESC) to tune the control gain of the ULMPC online. Simulation and hardware experiments demonstrate the enhancement of the extremum-seeking-based ULMPC over a constant-gain ULMPC.

Zhou, Yujing↗
DOE OSTI2022

Stress-Controlled Creep–Fatigue of an Advanced Austenitic Stainless Steel at Elevated Temperatures

Creep–fatigue interaction occurs in many structural components of high-temperature systems operating under cyclic and steady-state service conditions, such as in nuclear power plants, aerospace, naval, and other industrial applications. Thus, understanding micromechanisms governing high-temperature creep–fatigue behavior is essential for safety and design considerations. In this work, stress-controlled creep–fatigue tests of advanced austenitic stainless steel (Alloy 709) were performed at a 400 MPa stress range and 750 °C with tensile hold times of 0, 60, 600, 1800, and 3600 s, followed by microstructural examinations. The creep–fatigue lifetime of the Alloy 709 was found to decrease with increasing hold time until reaching a saturation level where the number of cycles to failure did not exhibit a significant decrease. Softening behavior was observed at the beginning of the test, possibly due to the recovery of entangled dislocations and de-twining. In addition, hysteresis loops showed ratcheting behavior, although the mean stress was zero during creep–fatigue cycling, which was attributed to activity of partial dislocations. Microstructural examination of the fracture surfaces showed that fatigue failure dominated at small hold times where the cracks initiated at the surface of the sample. Larger creep cracks were found for longer hold times with a lower probability of dimpled cavities, indicating the dominance of creep deformation. The results were compared with other commonly used stainless steels, and plausible reasons for the observed responses were described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

System Health and Status Reporting is Used to Improve Infrastructure Systems at the Hanford Site - 20449

Reliable physical infrastructure systems are vital to completing the clean-up mission and the start-up and commissioning of new nuclear waste processing facilities at the Hanford Site. Key infrastructure systems at Hanford include water, sewer, and electrical utilities, roads, telecommunications/network systems, and fire systems. All of the infrastructure systems are non-nuclear, General Service systems that are being maintained under formal engineering configuration control and none are specifically credited in any documented safety analysis (DSA). Starting in calendar year 2017, the Hanford Site's infrastructure and services contractor started producing system health and status reports for a total of 15 critical infrastructure systems as means to get a better understanding of each system's health and how it could be improved to ensure better and more reliable service delivery. As the reporting, tracking, and use of the metrics has matured, the number of systems for which reports are being developed has been expanded to a total of 23. Each of the critical infrastructure systems are assigned primary and alternate design authorities that complete qualifications on each assigned system. The design authorities actively manage and maintain configuration control on each of their systems and track metrics associated with availability, maintenance (corrective and preventive), and configuration of the technical baseline. The metrics are based on the principles established in Chapter V of DOE O 420.1C, Facility Safety, [1] and have been tailored as appropriate to each of the key infrastructure systems. An overall assessment of system health is performed and documented on a routine basis (e.g., quarterly). Included in this documentation is a quantitative score for each of the metrics (i.e., availability, maintenance, configuration management) along with results of system walk-downs, description of any permanent design modifications, identification of new or emerging issues and vulnerabilities affecting the system, and an assessment by the design authority of actions necessary to improve the system health score. The overall status scores are calculated using a formula and based on a pre-determined grading scale, a color is assigned for simple presentation. The information gained from developing the reports is being used to (1) assist with making timely and better informed decisions through the use of solid technical bases that are increasing the overall reliability and capabilities of the Site's infrastructure systems as new expense and capital projects in the Reliability Projects Investment Portfolio (RPIP) are prioritized and executed; (2) feed the risk management program, and (3) integrate the technical content of Master Plans that describe the Site's needs for the system and the system's capabilities to meet those future needs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗