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DOE OSTI2020

LANL studies of ESD spark energy discharge through September 2019

Two concentric-sphere apparatuses were used to measure the energies deposited by electric sparks through air to calibrated loads. Both sets of spheres had clean, uninsulated metal surfaces. The 127-mm diameter pair of spheres had a gap of 10 mm and a capacitance of 52 pF. The maximum energy stored on these spheres was 12 mJ and the maximum energy delivered to the 50-mΩ load was 11 µJ, with or without inductance. This load energy amounted to 0.09% of the available input energy; the remainder of the input energy was expended in forming the spark. The second set of spheres was 330 mm in diameter with a gap of 14 mm and a capacitance of 240 pF. The maximum energy stored on these spheres was 71 mJ and the maximum energy delivered to the 50-mΩ load was 150 µJ without added inductance. This load energy was 0.27% of the input energy; again, the remainder of the input energy was expended in forming the spark. The inclusion of 250 nH and 500 nH inductances in the discharge path of the smaller spheres caused the current discharges to resonate, but had little effect on the maximum energies deposited in the loads. At the time of writing, inductances had not yet been added to the larger spheres. The magnitudes of the observed spark discharges were stochastic, so more than 1200 tests were required to develop the statistical bounds of the spark behavior, i.e., to estimate the worst case (highest likely) energy depositions in the loads. The action integrals of the current discharges $∫ i^2dt$ were found to be approximately independent of the load resistances for loads of less than ~1 Ω. Hence the energy deposition scaled with resistance as 207 µJ/Ω and 2.93 mJ/Ω for the two apparatuses.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2020

Interpenetrating Plasma Simulations

This project investigated multifluid models for simulating interpenetrating plasmas. These models solve the Euler equations for each plasma stream along with an appropriate model for electron dynamics. The project developed a novel code, Euclid, that simulates these models using high-order conservative spatial discretization methods and explicit and semi-implicit time integration methods. Euclid was used to solve several multifluid test cases representative of plasma dynamics in high-energy density physics experiments. Kinetic simulations of interpenetrating flows using the LOKI code revealed novel physical effects of the ion-ion streaming instability. A new multi-flow collision operator was developed for the LOKI code. A simple model of the ion-ion streaming instability was also developed. Several presentations were given on the project results; three journal articles have been published, one has been submitted, and two are planned.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Explainable Artificial Intelligence Technology for Predictive Maintenance

The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Scaling Outlooks on Integrated Energy Systems

The report provides research summaries of two developed theories: data projection to enable multi-scale facility digital interactions and introducing the Evaluation Model Development and Assessment Process (EMDAP) approach to Integrated Energy Systems (IES) design. For the data projection, a two-system scaling case including interactions between thermal storage and hydrogen production is provided. The corresponding facilities are the thermal energy distribution system (TEDS) facility and high temperature steam electrolysis (HTSE) facility at the Dynamic Energy Transport and Integration Laboratory (DETAIL) in Idaho National Laboratory (INL). For the EMDAP adaption to system design, a modified process of the EMDAP was developed and applied to indirect two-tank heat storage system design. System phenomena were identified, ranked, and scaled to discover helpful key relations that would determine the ideal component geometry.

08 HYDROGEN↗

DOE OSTI2025

Coal to Carbon Fiber (C2CF) Continuous Processing for High Value Composites (Final Report)

Coal tar is a condensed and recovered by-product of the coking of metallurgical coal for steel production. The heaviest fraction of distilled coal tar is an isotropic pitch largely used as a binder in the manufacturing of carbonaceous electrodes for primary aluminum smelting and in electric arc furnaces. Coal tar pitch offers high carbon yield upon carbonization. In this project, a process to convert the domestically sourced isotropic coal tar pitch, containing very low particulates (QI = 0.32 wt.%), to form flow-domain mesophase pitch amenable for melt spinning into precursor (green) fibers for carbon fiber, was developed and optimized. The final reproducible processing developed is reviewed in this report, along with several characterizations of the mesophase pitch. A final definition of the characteristics of a ‘spinnable’ mesophase pitch is presented. With this mesophase pitch, reproducible and stable multifilament melt spinning was developed, producing green fiber tows with filament diameters of approximately 20 m. The multifilament melt spinning was the most challenging aspect of the project and required the most effort. The best practices learned from this project for melt spinning are reviewed in this report. Once spun, the green fibers were oxidatively stabilized, carbonized and graphitized under inert gas atmosphere to form the final carbon fibers. Given the relatively high softening point of the mesophase pitch, no issues of interfilament fusion were observed during batch oxidation, and subsequent batch carbonization and graphitization went smoothly in all cases. An ~ 80 wt.% conversion of the green fiber mass to final carbon fiber was achieved. After graphitization, the carbon fibers showed high tensile moduli (most were ~ 600 GPa, or 87 Msi) consistent with commercially-available high-performance pitch-based carbon fiber. However, tensile strength and strain to failure were comparatively low. Further work to reduce defects in and on the fiber surfaces would increase these properties. SEM imaging of the graphitic fiber textures is presented herein. Rudimentary composites were fabricated from the carbon fibers and characterized showing similar modulus to baseline composites fabricated with commercial carbon fiber. Finally, a basic economic analysis was done showing the potential to increase the value of the isotropic coal tar pitch by up to 13.6 to 136 times based on a carbon fiber value of $\$$5/lb to $\$$50/lb, respectively. Moreover, the site case study suggests that the coal tar from the single integrated steel mill could supply production of up to 16 kt/yr of carbon fiber. Finally, a technological gap analysis was done which shed light on remaining technical challenges. These challenges included: recovery and utilization of condensates from the mesophase pitch processing, further advancing and increasing stability of the multifilament melt spinning processing, optimization of the oxidation processing, defect reduction for increased carbon fiber strength, and the development of a weaving process towards carbon fiber fabrics. To maximize the coal value chain, the primary objectives of this project were to (a) develop and scale efficient processing technology for producing melt-spinnable mesophase pitch from isotropic coal tar pitch, (b) clarify and simplify tedious continuous fiber processing technologies (particularly multifilament melt spinning of mesophase pitch) towards the efficient production of high performance carbon fiber, and (c) demonstrate and characterize representative composite parts derived from the final carbon fiber. Immense progress was made on all 3 objectives and is detailed in this report.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Voices from Rural Electric Cooperatives: A Call for a DER Integration Playbook for Rural and Agricultural Income & Savings from Renewable Energy (RAISE)

Rural-serving electric utilities (RSEUs)—including electric cooperatives, municipal systems, and small investor-owned utilities—are essential players in the evolving energy landscape. These community-focused entities are increasingly being asked to consider distributed energy resources (DERs) such as rooftop and ground-mounted solar, wind, battery storage, smart water heaters, and demand response programs (NRECA 2025; Lenhart et al. 2020). Yet the path to DER adoption is far from straightforward in the rural context. This report is based on in-depth interviews with managers of rural electric cooperatives across the United States. These conversations offer a grounded, unvarnished look at how DERs are perceived, what barriers exist, and what conditions might enable integration and adoption. While the utilities interviewed vary in geography, size, and DER experience, several clear and common themes emerged across electric cooperatives such that the report recommends the development of a DER Integration Runbook to help utilities assess readiness, define local use cases, engage stakeholders, pilot projects, and iterate, expanding over time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Technology Feasibility of High-Temperature Heat Pumps for Industrial Drying Process in the US

High-temperature heat pumps are a prospective technology for electrifying and decarbonizing industrial drying processes. This study investigates the technological potential of HTHPs in replacing fossil-fuel burners or steam boilers in industrial spray dryers. The performance of HTHPs with three configurations was investigated, including high high-temperature heat pump boosted with an electric air heater, a steam-generating high-temperature heat pump with multi-stage mechanical vapor compressions, and transcritical high-temperature heat pumps. R1336mzz(Z) is used as the refrigerant in both subcritical and transcritical high-temperature heat pumps, and R717 is used as the working fluid in the mechanical vapor recompression and the heat transfer fluids. Thermodynamic models are built to evaluate the energy efficiency of HTHPs. A case study was carried out on an industrial spray dryer integrated with a waste heat recuperator, where the HTHPs are used to recover precooled air with a dew point of 40℃ and supply heat for drying air at 200℃. For a high-temperature heat pump boosted with an electric air heater, a higher system-level COP is achieved with a high supply temperature from high-temperature heat pump. For a high-temperature heat pump with mechanical vapor recompressions, larger temperature drops in the flashing tank provide higher heat capacities but almost constant values of the coefficient of performance. For a transcritical high-temperature heat pump, an optimum discharge pressure exists for the temperature profiles within the gas cooler and the coefficient of performance. The transcritical high-temperature heat pump provides the best energy efficiency among the three configurations. The theoretical results prove the technical feasibility of high-temperature heat pumps in industrial air-drying applications. .

Wang, Pengtao↗

DOE OSTI2025

Adapting Grid Criticality for Data Centers

This presentation explores the evolving definition of “critical load” in the electric grid, emphasizing the growing importance of digital infrastructure—particularly data centers—in grid resilience, restoration, and modernization. As utilities increasingly rely on AI-driven analytics and software-defined control systems, data centers have shifted from passive electricity consumers to essential computational hubs that enable National Critical Functions (NCFs) and support real-time grid operations. The deck examines the scale and impact of digital loads, the need for grid modernization to manage rapid load growth, and the diverse computing paradigms required for AI deployment. It introduces a tiered taxonomy for classifying critical loads, highlights operational dependencies between the grid and digital infrastructure, and discusses policy implications for integrating data centers into emergency planning and restoration protocols. Through case studies and practical frameworks, the presentation provides actionable insights for utilities, regulators, and planners navigating the digital transformation of the power sector.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2025

Hawaii Threat Brief

The Digital Energy Transformation is redefining how power systems operate, integrating physical infrastructure with digital technologies to enhance efficiency, visibility, and resilience. For islanded and digitally modernizing systems like Hawai‘i’s, this shift presents both new opportunities and evolving challenges in cybersecurity, supply chain assurance, and environmental resilience. This brief provides an overview of critical infrastructure dependencies and systemic risks associated with increasing digital integration. It summarizes recent energy-sector threat activity and case studies that illustrate adversary tactics and supply chain vulnerabilities, and identifies pathways to strengthen resilience.

25 - ENERGY STORAGE↗

DOE OSTI2022

A Fast and Accurate Transient Stability Assessment Method Based on Deep Learning: WECC Case Study

Transient stability is one of the critical aspects of power system stability assessment. The increasing integration of inverter-based resources and the retirement of conventional synchronous generators result in the decreasing system inertia and growing complexity of system operating conditions. Using a few selected typical operating conditions cannot guarantee system transient stability in all operating conditions, and the time-domain simulation of all operating conditions requires tremendous time and is often infeasible. This paper proposes a more efficient transient stability assessment method based on deep learning. The binary search method is used to determine the critical clearing time (CCT) in creating training databased by time-domain simulation. This method is fast and accurate with 1 ms resolution. The buses whose CCTs are lower than 200 ms are considered critical buses. Buses close to each other are grouped based on their mutual admittance matrix to reduce the search space of the critical buses. This paper also proposes the generator feature normalization based on the physical model. Case study on the reduced 240-bus WECC system model demonstrates that the proposed method can predict CCT accurately and efficiently.

critical clearing time↗

DOE OSTI2021

Design for Remanufacturing

The objective of this project was to develop relationships between published scholarship, industry experience, and remanufacturing design rules and identify a clear path for integrating remanufacturing design rules into CAD tools and design practices. To accomplish this, remanufacturing knowledge was compiled, and then the relationships between this knowledge and a prioritized set of product design guidelines was developed. Next, a process to create rules out of guidelines was developed by first defining life extension as a primary function, and remanufacturing as effective tasks to control the failure modes that would restrict the product life. The reliability centered maintenance (RCM) process was used to identify proactive tasks and default actions to mitigate the effects of failure modes. These tasks were developed into expert system rules. The impact of design on remanufacturing was then validated through implementing a prioritized set of design rules for a Heavy Duty Off-Road (HDOR) techno-economic case study. Finally, detailed steps on how to define, develop, and integrate these rules into CAD were created.

42 ENGINEERING↗

DOE OSTI2024

Chaotic roots of the modular multiplication dynamical system in Shor's algorithm

Shor's factoring algorithm, believed to provide an exponential speedup over classical computation, relies on finding the period of an exactly periodic quantum modular multiplication operator. This exact periodicity is the hallmark of an integrable system, which is paradoxical from the viewpoint of quantum chaos, given that the classical limit of the modular multiplication operator is a highly chaotic system that occupies the “maximally random” Bernoulli level of the classical ergodic hierarchy. In this work, we approach this apparent paradox from a quantum dynamical systems viewpoint, and consider whether signatures of ergodicity and chaos may indeed be encoded in such an “integrable” quantization of a chaotic system. We show that Shor's modular multiplication operator, in specific cases, can be written as a superposition of quantized 𝐴-baker's maps exhibiting more typical signatures of quantum chaos and ergodicity. This work suggests that the integrability of Shor's modular multiplication operator may stem from the interference of other “chaotic” quantizations of the same family of maps, and paves the way for deeper studies on the interplay of integrability, ergodicity, and chaos in and via quantum algorithms.

Dynamical systems↗

DOE OSTI2023

Boosting the performances of protonic solid oxide fuel cells for co-production of propylene and electricity from propane by integrating thermo- and electro- catalysis

Protonic solid oxide fuel cells (p-SOFC) integrated with clean thermal energy sources are promising platforms for decarbonized chemical production in addition to power generation, such as on-purpose propylene production from propane dehydrogenation (PDH). The catalytic performance of the conventional nickel-cermet-based anode materials in p-SOFC for propane conversion is restrained by their low active surface area and proneness to coking. In this work, by integration of a highly efficient industry-relevant thermal catalyst PtGa/ZSM-5 for PDH reaction, we demonstrate that both the electrochemical and catalytic performance of the propane-fueled p-SOFC can be effectively enhanced. The PtGa catalyst integrated p-SOFC exhibits a peak power density of 93 mW cm -2 at 600°C, which is greater by about 100% and 50% than that without catalyst or with a perovskite-based (Pr 0.3 Sr 0.7 ) 0.9 Ni 0.1 Ti 0.9 O 3 (PSNT) catalyst layer, respectively. The PDH activity and olefin selectivity of the PtGa catalyst is also significantly higher than that of the PSNT catalyst. In addition, much improved coke tolerance and propylene selectivity (over 90%) compared to the catalyst-free Ni-cermet anode materials were achieved by integrating the industrial catalyst layer. The propane conversion can be further improved by an applied current density, whereas the olefin selectivity is almost unaltered. The excellent performance of the PtGa catalyst integrated p-SOFC is attributed to the high surface area, intrinsically high catalytic activity, selectivity, and anti-coking properties of the catalytic layer for propane conversion. In conclusion, this work provides a general approach and a case study for boosting the performances of p-SOFCs in chemical production by integrating thermo- and electro- catalysis.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

Unified wavefront singularity characterization of three-dimensional elastodynamic time-domain half-space Green's function under impulsive boundary and internal loads

Founded on a novel analytical formulation that led to a rigorous yet compact path-integral representation of the time-domain elastodynamic half-space Green's function, a unified analysis of the possible occurrence of different singular wavefront behaviour in the response under arbitrary impulsive internal or surface point loads at arbitrary source-receiver locations is presented. With the decomposition of the general solution into distinct initiating and reflected wave group integrals that share a common factored format and simple contour definitions, the mathematical framework is shown to allow a straightforward identification of the specific conditions and the particular wave groups that are responsible for the singular wavefront phenomena without resorting to advanced analytic function theories or asymptotic methods. Analytic characterizations of the nature, strength and direction of all intrinsic singular wavefront behaviours of the three-dimensional Green's function in three canonical cases of source-receiver configurations are given in a dual integral-closed form format to facilitate their theoretical understanding as well as computational applications. Graphical illustrations of their variation with the source-receiver configuration and the medium's Poisson's ratio together with relevant comparison and clarifications of some classical treatments are included.

Green’s functions↗

DOE OSTI2021

Integrability, normal forms, and magnetic axis coordinates

Integrable or near-integrable magnetic fields are prominent in the design of plasma confinement devices. Such a field is characterized by the existence of a singular foliation entirely consisting of invariant submanifolds. A compact regular leaf (a flux surface) of this foliation must be diffeomorphic to the two-torus. In a neighborhood of a flux surface, it is known that the magnetic field admits several exact smooth normal forms in which the field lines are straight. However, these normal forms break down near singular leaves, including elliptic and hyperbolic magnetic axes. In this work, the existence of exact smooth normal forms for integrable magnetic fields near elliptic and hyperbolic magnetic axes is established. In the elliptic case, smooth near-axis Hamada and Boozer coordinates are defined and constructed. Ultimately, these results establish previously conjectured smoothness properties for smooth solutions of the magnetohydrodynamic equilibrium equations. The key arguments are a consequence of a geometric reframing of integrability and magnetic fields: they are presymplectic systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Progress Towards a Comprehensive Approach for Habitat Restoration in the Columbia Basin: Case Study in the Grande Ronde River

Abstract Despite immense resources directed towards habitat restoration, recovering fish populations remains a daunting and perplexing issue. In 2015, recommendations for a comprehensive approach to habitat restoration in the Columbia River basin were published in Fisheries, which included elements of landscape ecology and resilience, broad public support, governance for collaboration and integration, and capacity for learning and adaptation. Using the Grande Ronde River basin as a case study, we convened a working group consisting of local restoration practitioners, managers, and researchers involved in habitat restoration research, monitoring, and evaluation to assess progress towards meeting these recommendations. We concluded that partnerships and collaborations in governance have been formed and research using a landscape perspective has been integrated into decision making, but efforts would benefit from gaining broader public support, formalizing an adaptive management strategy, and defining objectives and indicators for biological and ecological diversity. Continued progress will require consistent policy and funding support from the broader region. We envision this self-assessment at the 5-year milestone would be helpful to other groups facing similar challenges.

White, Seth M. (ORCID:0000000349186865)↗

DOE OSTI2025

A Design for Remanufacturing Framework Incorporating Identification, Evaluation, and Validation: A Case Study of Hydraulic Manifold

In recent years, academic researchers and engineers in the industry have widely recognized the necessity of integrating remanufacturing considerations into product design iterations to advance sustainability objectives. Acknowledging the importance of design for remanufacturing (DfRem), efforts were made to develop tools and guidelines that could be implemented in practice. However, such methods largely rely upon experiential insights and qualitative assessments, leaving a gap in the ability to quantitatively assess the economic and environmental impacts of design choices. To bridge this gap, we investigate existing efforts and present a framework for DfRem that integrates established design and remanufacturing practices into a cohesive workflow with quantitative assessments. To demonstrate its efficacy for making practical design changes for remanufacturing, we apply the framework to a hydraulic manifold in a transmission system for heavy-duty tractors. Through this industry-relevant case study, we focus on showcasing the practical utility of our framework. Based on the identified design modifications from remanufacturability analysis, we estimate the reductions in life cycle costs, energy consumption, and emissions. Afterward, the modifications are tested using physical experiments with plans for integration into future iterations of the hydraulic manifold design and production. Here, we anticipate this framework can illustrate the process of remanufacturing that ensures improvements in sustainability while maintaining performance and reliability standards.

design for X↗

DOE OSTI2021

Holo-omics for deciphering plant-microbiome interactions

Host-microbiome interactions are recognized for their importance to host health. An improved understanding of the molecular underpinnings of host-microbiome relationships will advance our capacity to accurately predict host fitness and manipulate interaction outcomes. Within the plant microbiome research field, unlocking the functional relationships between plants and their microbial partners is the next step to effectively using the microbiome to improve plant fitness. We propose that strategies that pair host and microbial datasets—referred to here as holo-omics—provide a powerful approach for hypothesis development and advancement in this area. We discuss several experimental design considerations and present a case study to highlight the potential for holo-omics to generate a more holistic perspective of molecular networks within the plant microbiome system. In addition, we discuss the biggest challenges for conducting holo-omics studies; specifically, the lack of vetted analytical frameworks, publicly available tools, and required technical expertise to process and integrate heterogeneous data. Finally, we conclude with a perspective on appropriate use-cases for holo-omics studies, the need for downstream validation, and new experimental techniques that hold promise for the plant microbiome research field. We argue that utilizing a holo-omics approach to characterize host-microbiome interactions can provide important opportunities for broadening system-level understandings and significantly inform microbial approaches to improving host health and fitness.

59 BASIC BIOLOGICAL SCIENCES↗