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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 109 records · Page 6

Light Water Reactor Sustainability Program Plant Modernization Technical Program Plan for FY 2021

This report presents the Technical Program Plan for FY 2019 for the Department of Energy Light Water Reactor Sustainability Program – Plant Modernization research pathway. A summary of the vision and strategy is provided to explain how this program addresses key issues and barriers for modernizing instrumentation and control technologies and infrastructure in domestic nuclear power plants. The report describes the pilot projects that have been formulated to develop and validate enabling technologies over the next several years that will result in digital alternatives to the legacy analog II&C systems in place today. This will allow much needed modernization of these systems to address reliability and obsolescence problems, as well as serve as a platform for substantial operational improvement. The report further describes key project resources and cooperative relationships, including the Electric Power Research Institute, the Nuclear Energy Institute )NEI), the Institute of Nuclear Power Operations (INPO), the IFE Halden Reactor Project, the Nuclear Regulatory Commission, and industry suppliers, that are instrumental to the success of the program. The report also lists the schedule for all program products, including the titles and report numbers for all published reports under this program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

INVESTIGATION OF HUMAN RELIABILITY ANALYSIS METHODS FOR ANALYZING PRE-INITIATORS

As a type of human actions defined in human reliability analysis (HRA), pre-initiator refers to the human actions that may lead to the unavailability of systems, typically committed during maintenance, test, or calibration. This paper investigates representative HRA methods used for analyzing pre-initiators. The HRA methods are Technique for Human Error Rate Prediction (THERP), Korean Standard HRA (K-HRA) and Standard Plant Risk HRA (SPAR-H). In this paper, characteristics of each HRA method are compared for qualitative and quantification aspects. Two pre-initiators, i.e., a calibration task and a valve restoration task, are analyzed using the HRA methods to compare human error probabilities. Then, insights from the analysis and additional research requirements are discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗

Trustworthiness and Trust: Identifying Factors that Drive Successful Human-AI Interaction in Nuclear Power Plant Applications

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are rapidly evolving and considered a promising tool for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may support personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for tasks such as surveillances or completing work orders. This is a fundamental shift in the way operators currently perform their tasks today. The literature of human-automation interaction indicates that trust is a crucial factor that drives successful interaction between a human operator and an automated system, like an AI-infused NPP application. This work presents the results of a literature review on key factors that relate to trust in AI/LLM technologies for NPP applications. The relevant literature of human factors and cognitive engineering has identified various factors related to trust including trustworthiness, performance characteristics, operator skill and perceived risk. This preliminary literature review will guide development and evaluation of models involving the identified factors influencing trust in AI and develop a framework for human-centered design for interface between humans and AI. By addressing trust, this work supports developing a technical basis for designing key characteristics of AI/LLM to support calibrated trust, which will ultimately support wide-scale adoption of AI/LLM technologies, as well as ensure safe, effective, and reliable use.

99 - GENERAL AND MISCELLANEOUS↗

Design Philosophy for Accelerator Control Rooms

This report describes the foundational human factors principles needed to design user interfaces for accelerator control rooms. These principles are presented as recommendations for accelerator control system interface design and are illustrated with examples drawn from accelerator operations at Fermi National Accelerator Laboratory (Fermilab). These high-level principles are intended to serve as design objectives that apply generally across all control system interfaces developed for the accelerator complex. This design philosophy document is a high-level roadmap to approach the general interface design for the accelerator complex. This philosophy applies state-of-the-art human factors principles and evidence-based design standards to an accelerator environment, which will transform the next era of accelerator interfaces as outlined by the Accelerator Controls Operations Research Network (ACORN) Project. Further work will include mapping the general design principles included in this report to more specific guidance in the form of a user interface style guide.

43 PARTICLE ACCELERATORS↗

All-polymer nanocomposites having superior strength, toughness and ultralow energy dissipation

Toughening polymers has attracted significant interest. Traditionally, polymer toughness is enhanced by constructing polymer networks or introducing sacrificial bonds into the chains between crosslink points. These strategies, though, introduce pronounced energy dissipation and associated heat, both of which are undesirable under long-term cyclic loading, for example at the interface of implants in the human body. By incorporating single-chain nanoparticles (SCNPs) into linear polymer chains to generate all-polymer nanocomposites (APNCs), we have been able to achieve high strength, high toughness with low energy dissipation. Using a combination of simulation and experimental results, we are advancing a “SCNPs effect” where tightly cross-linked SCNPs produce a modulus contrast to achieve strengthening and toughening. Benefitting from the soft interface, the penetrable and deformable SCNPs cause the surrounding polymer chains to move in concert, significantly reducing the interfacial friction to achieve low energy dissipation. The intramolecular cross-linking of the SCNPs and adhesion between the SCNPs and polymer matrix are critical for realizing such high-performance systems. Based on a Gaussian regression model and back propagation (BP) neural network, the mechanical strength can be predicted and is supported by simulations. Finally, the APNC concept described can be applied to elastomers and gels, broadening its utilization in high-cycle and low-dissipation applications, like soft robots, flexible sensors and cartilage replacements, and artificial heart valves.

36 MATERIALS SCIENCE↗

Methods integrating innate and adaptive immune responses in human in vitro immunization assays

Rapid vaccine development and innovative immunotherapeutics are critical in the fight against emerging outbreaks and global pandemic threats, yet the high costs and prolonged timelines for developing new vaccines underscore the urgent need for robust, predictive pre-clinical testing platforms. The rapid down-selection of vaccine candidates and identification of optimal vaccine formulations can be performed using human in vitro immunization (IVI) assays that recapitulate the complex interactions of the innate and adaptive human immune response. In this review, we present a comprehensive evaluation of three key IVI platforms: the whole blood assay (WBA), monocyte-derived dendritic cell (MoDC) assay with dendritic cell-T cell interface assay (DTI), and the microphysiological human tissue construct assay (HTC). The WBA offers a cost-effective and straightforward approach, while the MoDC + DTI system represents the current gold standard for balancing experimental efficiency with immunological complexity. The HTC assay, by mimicking both spatial and temporal aspects of immune interactions, provides enhanced physiological relevance. We discuss the methodological advantages and limitations of each platform, explore their roles in rapid vaccine candidate screening, and propose strategies for integrating these assays with complementary in vivo models. These insights pave the way for refining IVI assays and accelerating the translational pipeline for next-generation vaccines and immunotherapies.

59 BASIC BIOLOGICAL SCIENCES↗

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗

Data Centers and Digital Assurance Workshop 2 – Prioritizing Digital Assurance Challenges, Session 2

The second session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 10, 2025, focused on prioritizing digital assurance challenges at the intersection of data centers and the electric grid. Building on the foundational concepts introduced in Workshop 1, this session deepened the application of the Threat–Vulnerability–Consequence (TVC) framework and emphasized the urgency of addressing cybersecurity, supply chain integrity, and operational reliability. Participants explored the growing convergence of digital and physical systems, the expanding attack surface due to global supply chain dependencies, and the implications of AI-driven load behavior. Real-world incidents—including the Volt Typhoon campaign and vulnerabilities in Solarman and Deye platforms—were analyzed to illustrate the risks of unpatched systems, insecure APIs, and inadequate vendor oversight. Key themes included architecture and interface weaknesses, governance gaps, and human and procedural shortcomings. The workshop also examined the evolving regulatory landscape, highlighting new federal mandates around Foreign Entity of Concern (FEOC) compliance and large-load reliability standards. Through interactive exercises, stakeholders ranked and mapped digital assurance risks from their respective perspectives—utilities, operators, and vendors—laying the groundwork for mitigation strategies and shared accountability models to be developed in Workshop 3. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Synergizing human expertise and AI efficiency with language model for microscopy operation and automated experiment design

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.

97 MATHEMATICS AND COMPUTING↗

Molecular determinants of pH sensing in the proton-activated chloride channel

In response to acidic pH, the widely expressed proton-activated chloride (PAC) channel opens and conducts anions across cellular membranes. By doing so, PAC plays an important role in both cellular physiology (endosome acidification) and diseases associated with tissue acidosis (acid-induced cell death). Despite the available structural information, how proton binding in the extracellular domain (ECD) leads to PAC channel opening remains largely unknown. Here, through comprehensive mutagenesis and electrophysiological studies, we identified several critical titratable residues, including two histidine residues (H130 and H131) and an aspartic acid residue (D269) at the distal end of the ECD, together with the previously characterized H98 at the transmembrane domain–ECD interface, as potential pH sensors for human PAC. Mutations of these residues resulted in significant changes in pH sensitivity. Some combined mutants also exhibited large basal PAC channel activities at neutral pH. By combining molecular dynamics simulations with structural and functional analysis, we further found that the β12 strand at the intersubunit interface and the associated “joint region” connecting the upper and lower ECDs allosterically regulate the proton-dependent PAC activation. Our studies suggest a distinct pH-sensing and gating mechanism of this new family of ion channels sensitive to acidic environment.

59 BASIC BIOLOGICAL SCIENCES↗

Assessment of Electric Grid Transmission System Simulator for Human Factors Research

Over the past decades, various technologies have been developed for electric grid operations to support clean energy, meet rising electricity demands, and address infrastructure concerns. However, the human factors aspect is often overlooked during rapid integration. Questions persist about how these technologies impact human performance. Simulators play a critical role in supporting investigation of human factors design concepts and conducting comprehensive usability testing to evaluate human performance and assess human reliability. This paper aims to address human factors research simulator requirements and conduct a comparative study of six different simulators. A detailed evaluation reveals that the evaluated simulators lack the ability to customize user interfaces. Additionally, their user interface designs do not fulfill the basic human factors design principles, potentially leading to increased response variability and reduced statistical power when conducting controlled experimental research. In the future, it is essential to develop scripting tools to integrate customizable user interfaces and simulation models, ensuring meeting research requirements.

Li, Ruixuan↗

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗

A Comparison of Three Types of Computer-Based Procedures: An Experiment Using the Rancor Microworld Simulator

The nuclear power industry has historically used paper-based procedures, but a shift towards computer-based procedures (CBPs) has the potential to reduce human errors, alleviate mental workload, and improve work performance. Twenty-seven participants were randomly assigned to one of three CBP types using the Rancor Microworld Simulator, and each performed two different types of operational scenarios (startup and loss of feedwater). The three CBP types varied in levels of digitalization. It was hypothesized that there would be less favorable impressions of the most basic procedures, and that these would demonstrate lower usability than types with greater digitalization. Overall, our predictions were partially supported with some interesting caveats, specifically with some performance benefits for CBPs that provided indicators but not embedded controls. We discuss our findings in terms of optimal levels of digitalization/automation within nuclear operations and suggest pathways for future directions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Energy-Flow-Environment Linkage Map

Understanding how flexibility in environmental requirements can facilitate co-optimization of hydropower production outcomes and environmental outcomes is critical for future grid decision-making and operations as renewable energy resources increase. The environmental and power system outcomes connectivity linkage maps presented here provide a framework for conceptually and quantitatively linking power system outcomes to environmental outcomes through hydropower flow decisions. The Executive Summary Map serves as a starting for exploring the links between hydropower system performance outcomes and environmental outcomes. The centralized topic is “Flow from Hydropower System,” and connects the hydropower operations through “Flow through turbines” and “Non-turbine flows”, and to environmental outcomes through Reservoir elevation” and “Flow downstream of the hydropower system”. To the left of these central topics, “Hydro-mechanical operations” are linked through “Hydro-electrical operations” to “Hydropower performance outcomes” (“Reliability”, “Resilience”, “Revenue”, “Emissions”). On the right, environmental outcomes are grouped together by their physical location: “Upstream Outcomes” (“Upstream geomorphology”, “Upstream recreation”, “Upstream habitat”, “Upstream biota and biodiversity”, “Upstream water quality and greenhouse gas”), Outcomes relevant to both “Upstream/downstream or dam interface” (“Navigation”, “Dam safety and maintenance", “Human health”, “Water supply”, “Flood control”, ”Fish passage”), and “Downstream outcomes“ (e.g., “Downstream geomorphology”, “Downstream recreations”, “Downstream habitat”, “Downstream biota and biodiversity”, “Downstream water quality and greenhouse gas”). Each of these subtopics (e.g., “Hydro-mechanical operations”, “Hydro-electrical operations”, “Upstream geomorphology”, “Upstream recreation”) is further explored through their corresponding submaps. The “Read Me” file provides more detail information on map navigation. The “Models and tools database” file provides detailed information of models and tools presented in the maps.

13 HYDRO ENERGY↗

Cardiac troponin T N-domain variant destabilizes the actin interface resulting in disturbed myofilament function

Missense variant Ile79Asn in human cardiac troponin T (cTnT-I79N) has been associated with hypertrophic cardiomyopathy and sudden cardiac arrest in juveniles. cTnT-I79N is located in the cTnT N-terminal (TnT1) loop region and is known for its pathological and prognostic relevance. A recent structural study revealed that I79 is part of a hydrophobic interface between the TnT1 loop and actin, which stabilizes the relaxed (OFF) state of the cardiac thin filament. Given the importance of understanding the role of TnT1 loop region in Ca 2+ regulation of the cardiac thin filament along with the underlying mechanisms of cTnT-I79N-linked pathogenesis, we investigated the effects of cTnT-I79N on cardiac myofilament function. Transgenic I79N (Tg-I79N) muscle bundles displayed increased myofilament Ca 2+ sensitivity, smaller myofilament lattice spacing, and slower crossbridge kinetics. These findings can be attributed to destabilization of the cardiac thin filament’s relaxed state resulting in an increased number of crossbridges during Ca 2+ activation. Additionally, in the low Ca 2+ -relaxed state (pCa8), we showed that more myosin heads are in the disordered-relaxed state (DRX) that are more likely to interact with actin in cTnT-I79N muscle bundles. Dysregulation of the myosin super-relaxed state (SRX) and the SRX/DRX equilibrium in cTnT-I79N muscle bundles likely result in increased mobility of myosin heads at pCa8, enhanced actomyosin interactions as evidenced by increased active force at low Ca 2+ , and increased sinusoidal stiffness. These findings point to a mechanism whereby cTnT-I79N weakens the interaction of the TnT1 loop with the actin filament, which in turn destabilizes the relaxed state of the cardiac thin filament.

59 BASIC BIOLOGICAL SCIENCES↗

Adaptive Cognitive Mechanisms to Maintain Calibrated Trust and Reliance in Automation

Trust calibration for a human–machine team is the process by which a human adjusts their expectations of the automation’s reliability and trustworthiness; adaptive support for trust calibration is needed to engender appropriate reliance on automation. Herein, we leverage an instance-based learning ACT-R cognitive model of decisions to obtain and rely on an automated assistant for visual search in a UAV interface. This cognitive model matches well with the human predictive power statistics measuring reliance decisions; we obtain from the model an internal estimate of automation reliability that mirrors human subjective ratings. The model is able to predict the effect of various potential disruptions, such as environmental changes or particular classes of adversarial intrusions on human trust in automation. Finally, we consider the use of model predictions to improve automation transparency that account for human cognitive biases in order to optimize the bidirectional interaction between human and machine through supporting trust calibration. The implications of our findings for the design of reliable and trustworthy automation are discussed.

60 APPLIED LIFE SCIENCES↗

Broad-spectrum CRISPR-mediated inhibition of SARS-CoV-2 variants and endemic coronaviruses in vitro

A major challenge in coronavirus vaccination and treatment is to counteract rapid viral evolution and mutations. Here we demonstrate that CRISPR-Cas13d offers a broad-spectrum antiviral (BSA) to inhibit many SARS-CoV-2 variants and diverse human coronavirus strains with >99% reduction of the viral titer. We show that Cas13d-mediated coronavirus inhibition is dependent on the crRNA cellular spatial colocalization with Cas13d and target viral RNA. Cas13d can significantly enhance the therapeutic effects of diverse small molecule drugs against coronaviruses for prophylaxis or treatment purposes, and the best combination reduced viral titer by over four orders of magnitude. Using lipid nanoparticle-mediated RNA delivery, we demonstrate that the Cas13d system can effectively treat infection from multiple variants of coronavirus, including Omicron SARS-CoV-2, in human primary airway epithelium air-liquid interface (ALI) cultures. Our study establishes CRISPR-Cas13 as a BSA which is highly complementary to existing vaccination and antiviral treatment strategies.

60 APPLIED LIFE SCIENCES↗