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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Impasse-Driven Tutoring for Reactive Skill Acquisition

We introduce a new approach to intelligent tutoring in performance-oriented training environments based on a method called situated plan attribution. The aim of this method is to provide contextualized tutoring for procedural tasks requiring reactive, goal-oriented skills. We use the term plan attribution instead of plan recognition because it does not assume that the problem solver is consciously executing plan. We avoid some of the pitfalls of other popularly used methods, i.e., model tracing and procedure net grammars, by selectively using an expert cognitive model to generate advice after detecting a problem solving impasse. The tutor attributes a set of plans to the student based on a task description. Each action is evaluated with respect to: the student's attributed plans, its actual effects on the training device, and the contextualized goals associated with the plans.

Johnson, W. Lewis↗
DOE OSTI2024

Transmission Operator Workflows for Real-Time Reliability Studies: A Review of Control Room Practices and Naturalistic Decision Making

This report provides an overview of real-time reliability study tools and their use by power system operators in the control room environment. After introducing some of the nuances of the control room environment and the differences in perspectives between power system engineers and operators, the roles and responsibilities of key entities involved in RTCA workflows are introduced. These are specifically the transmission system operator (TOP) and reliability coordinator (RC), which are required to run tools such as real-time contingency analysis (RTCA) as part of a real-time reliability assessment every 30 minutes, as dictated by a series of standards issued by the North American Electric Reliability Corporation (NERC). The process by which power systems operators operate the grid is discussed in terms of naturalistic decision making (NDM) and the recognition-primed decision-making (RPD) model. This cognitive model describe how experts working in high-risk, high-stress environments make safety-critical decisions under uncertainty and time pressure. For power system operators, the mental simulations involved in the traditional RPD model are supplemented by physics-based simulations using numerical tools, such as RTCA, to improve situational awareness and effectiveness of control actions. Next, a generic workflow is introduced to describe operator decision making for running RTCA tools and responding to system violations on a pre-contingent basis. The types of analysis performed and control actions chosen by power system operators are described in detail. The overall high-level workflow is then expanded in subsequent sections, with special attention given to high-voltage violations, low-voltage violations, and thermal overloads. Each type of violation is described in detail, with explanations of common causes, impacts on equipment and customers, and mitigation strategies. An additional workflow diagram is provided for each type of violation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2002

CATS-based Air Traffic Controller Agents

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.

Callantine, Todd J.↗
NASA NTRS2009

Human Research Program (HRP) Exploration Medical Capability (ExMC) Standing Review Panel (SRP)

The SRP believes strongly that regularly performed in-flight crew assessments are needed in order to identify a change in health status before a medical condition becomes clinically apparent. It is this early recognition in change that constitutes the foundation of the "occupational health model" expounded in the HRP Requirements Document as a key component of the HRP risk mitigation strategy that will enable its objective of "prevention and mitigation of human health and performance risks". A regular crew status examination of physiological and clinical performance is needed. This can be accomplished through instrumented monitoring of routine embedded tasks. The SRP recommends addition of a new gap to address this action under Category 3.0 Mitigate the Risk. This new gap is closely associated with Task 4.19 which addresses the lack of adequate biomedical monitoring capabilities for performing periodic clinical status evaluations and contingency medical monitoring. A corollary to these gaps is the critical emphasis on preventive medicine, not only during pre- and post-flight phases of a mission as is the current practice, but continued into the in-flight phases of exploration class missions.

Cintron, Nitza↗
NASA NTRS2006

Generating Control Commands From Gestures Sensed by EMG

An effort is under way to develop noninvasive neuro-electric interfaces through which human operators could control systems as diverse as simple mechanical devices, computers, aircraft, and even spacecraft. The basic idea is to use electrodes on the surface of the skin to acquire electromyographic (EMG) signals associated with gestures, digitize and process the EMG signals to recognize the gestures, and generate digital commands to perform the actions signified by the gestures. In an experimental prototype of such an interface, the EMG signals associated with hand gestures are acquired by use of several pairs of electrodes mounted in sleeves on a subject s forearm (see figure). The EMG signals are sampled and digitized. The resulting time-series data are fed as input to pattern-recognition software that has been trained to distinguish gestures from a given gesture set. The software implements, among other things, hidden Markov models, which are used to recognize the gestures as they are being performed in real time. Thus far, two experiments have been performed on the prototype interface to demonstrate feasibility: an experiment in synthesizing the output of a joystick and an experiment in synthesizing the output of a computer or typewriter keyboard. In the joystick experiment, the EMG signals were processed into joystick commands for a realistic flight simulator for an airplane. The acting pilot reached out into the air, grabbed an imaginary joystick, and pretended to manipulate the joystick to achieve left and right banks and up and down pitches of the simulated airplane. In the keyboard experiment, the subject pretended to type on a numerical keypad, and the EMG signals were processed into keystrokes. The results of the experiments demonstrate the basic feasibility of this method while indicating the need for further research to reduce the incidence of errors (including confusion among gestures). Topics that must be addressed include the numbers and arrangements of electrodes needed to acquire sufficient data; refinements in the acquisition, filtering, and digitization of EMG signals; and methods of training the pattern- recognition software. The joystick and keyboard simulations were chosen for the initial experiments because they are familiar to many computer users. It is anticipated that, ultimately, interfaces would utilize EMG signals associated with movements more nearly natural than those associated with joysticks or keyboards. Future versions of the pattern-recognition software are planned to be capable of adapting to the preferences and day-today variations in EMG outputs of individual users; this capability for adaptation would also make it possible to select gestures that, to a given user, feel the most nearly natural for generating control signals for a given task (provided that there are enough properly positioned electrodes to acquire the EMG signals from the muscles involved in the gestures).

Wheeler, Kevin R.↗
DOE OSTI2021

A contextual sensor system for non-intrusive machine status and energy monitoring

Event-driven contexts in manufacturing occur pervasively as a result of interactions among involved entities such as machines, workers, materials, and environment. One of the primary tasks in smart manufacturing is to derive a context-aware system conveniently incorporating worker knowledge for generating timely actionable intelligence for workers on factory floor and supervisors to respond. In this paper, we propose to design a human-and-machine interaction recognition framework by using a causality concept to collect contextual data for classifications of normal and abnormal machine operations. The causes and effects are between workers and machines for this initial research. To apply the causality to recognize worker interactions, initially a reliable way to identify the states of machines is necessary. The proposed contextual sensor system, consisting of a power meter for measuring machine operation conditions, a visual camera for capturing worker and machine interactions via a finite state machine model, and an algorithm for determining power signatures of individual components via energy disaggregation is implemented on semiconductor fabrication machines (manual or PLC controlled) each with multiple components. The experiment results demonstrate its context extraction capability such as components states and their corresponding energy usage in real time as well as its ability to identify anomalous operation conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Melatonin-Induced Modulation of Cholesterol-Enriched Model Neuronal Membranes

Melatonin, a hormone primarily produced by the brain’s pineal gland, not only regulates circadian rhythms, but also influences the structural and biophysical properties of neuronal membranes. Its amphiphilic nature enables direct incorporation into lipid bilayers and preferential interactions with cholesterol-rich lipid rafts, critical hubs for cellular signaling and membrane organization. Despite increasing recognition of its membrane activity, the molecular basis of melatonin’s interactions with coexisting liquid-ordered (L o ) and liquid-disordered (L d ) phases remains unclear. Here, in this study, we combine small-angle neutron scattering (SANS) and all-atom molecular dynamics simulations to examine model neuronal membranes composed of DSPC, DOPC, POPC, and cholesterol. Our results show that melatonin preserves domain morphology while adopting distinct orientations within the bilayer and at the membrane interface, allowing both lateral and transmembrane bridging across lipid phases. These findings establish the molecular underpinnings of melatonin’s modulation of membrane heterogeneity and provide strong support for its receptor-independent actions.

atomistic simulations↗
DOE OSTI2021

Comparison of human poly-N-acetyl-lactosamine synthase structure with GT-A fold glycosyltransferases supports a modular assembly of catalytic subsites

Poly-N-acetyl-lactosamine (poly-LacNAc) structures are composed of repeating [-Galβ(1,4)-GlcNAcβ(1,3)-]n glycan extensions. They are found on both N- and O-glycoproteins and glycolipids and play an important role in development, immune function, and human disease. The majority of mammalian poly-LacNAc is synthesized by the alternating iterative action of β1,3-N-acetylglucosaminyltransferase 2 (B3GNT2) and β1,4-galactosyltransferases. B3GNT2 is in the largest mammalian glycosyltransferase family, GT31, but little is known about the structure, substrate recognition, or catalysis by family members. Here we report the structures of human B3GNT2 in complex with UDP:Mg 2+ and in complex with both UDP:Mg 2+ and a glycan acceptor, lacto-N-neotetraose. The B3GNT2 structure conserves the GT-A fold and the DxD motif that coordinates a Mg 2+ ion for binding the UDP-GlcNAc sugar donor. The acceptor complex shows interactions with only the terminal Galβ(1,4)-GlcNAcβ(1,3)- disaccharide unit, which likely explains the specificity for both N- and O-glycan acceptors. Modeling of the UDP-GlcNAc donor supports a direct displacement inverting catalytic mechanism. Comparative structural analysis indicates that nucleotide sugar donors for GT-A fold glycosyltransferases bind in similar positions and conformations without conserving interacting residues, even for enzymes that use the same donor substrate. In contrast, the B3GNT2 acceptor binding site is consistent with prior models suggesting that the evolution of acceptor specificity involves loops inserted into the stable GT-A fold. These observations support the hypothesis that GT-A fold glycosyltransferases employ coevolving donor, acceptor, and catalytic subsite modules as templates to achieve the complex diversity of glycan linkages in biological systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Monitoring issues from a modeling perspective

Recognition that earth's climate and biogeophysical conditions are likely changing due to human activities has led to a heightened awareness of the need for improved long-term global monitoring. The present long-term measurement efforts tend to be spotty in space, inadequately calibrated in time, and internally inconsistent with respect to other instruments and measured quantities. In some cases, such as most of the biosphere, most chemicals, and much of the ocean, even a minimal monitoring program is not available. Recently, it has become painfully evident that emerging global change issues demand information and insights that the present global monitoring system simply cannot supply. This is because a monitoring system must provide much more than a statement of change at a given level of statistical confidence. It must describe changes in diverse parts of the entire earth system on regional to global scales. It must be able to provide enough input to allow an integrated physical characterization of the changes that have occurred. Finally, it must allow a separation of the observed changes into their natural and anthropogenic parts. The enormous policy significance of global change virtually guarantees an unprecedented level of scrutiny of the changes in the earth system and why they are happening. These pressures create a number of emerging challenges and opportunities. For example, they will require a growing partnership between the observational programs and the theory/modeling community. Without this partnership, the scientific community will likely fall short in the monitoring effort. The monitoring challenge before us is not to solve the problem now, but rather to set appropriate actions in motion so as to create the required framework for solution. Each individual piece needs to establish its role in the large problem and how the required interactions are to take place. Below, we emphasize some of the needs and opportunities that could and should be addressed through participation by the theoreticians and modelers in the global change monitoring effort.

Mahlman, Jerry D.↗
DOE OSTI2026

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Pantex Plant Ogallala Aquifer and Perched Groundwater Contingency Plan

The Pantex Plant Ogallala Aquifer and Perched Groundwater Contingency Plan has been developed in accordance with the requirements identified in the: • Interagency Agreement for the Pantex Superfund Site, Article 8.5 Work to be Performed, • Compliance Plan Provision of Hazardous Waste Permit No. 50284, and • Record of Decision for Groundwater, Soil, and Associated Media, Pantex Plant. A Long‐Term Monitoring System Design has been designed to monitor conditions in the perched groundwater including changes in the perched aquifer as a result of implementing the response actions. Monitoring is required for verifying the effectiveness of perched groundwater response actions (i.e., conditions in the perched aquifer are being affected as intended) and for confirming that the perched aquifer and Ogallala Aquifer characterization as defined in the Resource Conservation and Recovery Act Facility Investigation Report and the Corrective Measure Studies/Feasibility Study remains accurate. If monitoring results obtained through the monitoring network identify an unexpected condition or deviation, contingent actions will be considered and implemented as necessary to ensure continued protection of the Ogallala Aquifer and human health and the environment. Potential deviations to expected technology performance may be encountered for each of the four primary response actions that compose the selected remedy for perched groundwater; Playa 1 Pump and Treat System, Southeast Area Pump and Treat System, Southeast Area In‐Situ Bioremediation System (comprised of the Southeast In‐Situ Bioremediation System Original System, Southeast Area In‐Situ Bioremediation System Extension System, Offsite In‐Situ Bioremediation System, Perchlorate/Chromium ISB, Northeast ISB and County Road 8 ISB), and Zone 11 In‐Situ Bioremediation System. Monitoring will also be conducted to determine if there are deviations to the expected characterization, e.g., contaminants not expected as a result of the RCRA Facility Investigation characterization. Deviations to expected conditions in the Ogallala Aquifer could also be encountered if the response actions in the perched groundwater are not performing as expected, i.e., preventing contaminants from migrating to the Ogallala Aquifer. Currently, Pantex has begun investigation of detections of high explosives above groundwater protection standards in wells on the Texas Tech University property and a plume that is moving to the northeast from that area. Due to those detections, this Plan recognizes the fact that future detections in the Ogallala will be focused on first‐ time detections of analytes. After a remedy is determined, this Plan will require modification to address-deviations and contingent actions. This Plan was developed to identify the contingent actions necessary to mitigate impacts resulting from deviations to site conditions or response action performance. The Plan defines the environmental problem being addressed by the response actions, clarifies the expected conditions and objectives of the response actions, and identifies the potential deviations to the response actions (due to site conditions or technology performance) that could be encountered. The deviations were evaluated to determine the likelihood of occurrence, potential impact, and time to respond to avoid impact. The Plan also identifies the monitoring outlined in the Long‐Term Monitoring System Design Report (Consolidated Nuclear Security, 2024) and Sampling Analysis Plan (PanTeXas Deterrence, 2024) that will be used to detect the deviations. Lastly, the Plan specifies the contingent actions that could be implemented in response to the deviations. Because each response focuses on a discrete portion of the perched aquifer and contaminant plume, each response action has a different set of expected conditions, and therefore differing impacts from deviations to the site and technology expectations. As a result, the contingent actions are identified for each response action and potential deviation including specific constituents, location, and conditions. If deviations are encountered that impact the ability of the response action to meet performance objectives, the contingent actions will be focused on ensuring the response action can meet the performance objective. Contingent actions may be implemented as interim actions (ISMs/removal actions) in accordance with the Record of Decision, Interagency Agreement, and Hazardous Waste Permit‐50284, if warranted by the specific circumstances. For deviations to site characterization expected conditions, the contingent action will focus on determination of the source of the deviation, determination of the appropriate response, and evaluation of additional work to be completed. However, if the deviation to characterization impacts the performance of the response action, the contingent action will again focus on ensuring performance objectives can be met. Early source term removals and cleanup actions have been implemented to protect the Ogallala Aquifer. Because of these actions and based on modeling results, the expected conditions in the Ogallala Aquifer are that constituents of concern will not be detected above the Groundwater Protection Standards (GWPSs) nor will they reach potential points of exposure above the GWPS. The primary deviation of concern for the Ogallala is if constituents are detected in the Ogallala Aquifer near or above GWPSs. If it occurs, this change in expected conditions would require further evaluation of site and contaminant characteristics to determine an appropriate course of action. The evaluation would include additional monitoring, source identification, implementation of interim protective measures (if necessary), and delineation of extent. These evaluations are necessary to determine an appropriate response action for the Ogallala. The primary goal of the Plan is to provide for the continued protection of the Ogallala Aquifer and the health of its consumers. In recognition, this Plan presents a flexible and rational approach for making future decisions associated with confirming the change in perched and Ogallala aquifer conditions and identifying a response (technical activities, changes to response actions, regulatory oversight, and public involvement).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Workshop on Addressing Rigor and Reproducibility in Thermal, Heterogeneous Catalysis

Heterogeneous catalysis has long served as the bedrock of the manufacturing of energy carriers, fuels and chemicals, and various technologies for pollution abatement. The significant complexity and variability spanning the entire breadth of catalyst material properties, synthesis methods, characterization techniques, and evaluation procedures, has focused attention on the need to establish community-accepted best practices for ensuring high-quality, benchmarked, and reproducible data. In addition, increased societal urgency to transition to clean energy and reduce greenhouse gas concentrations has incentivized interdisciplinary, convergent, and translational approaches to catalysis research in recent years. Research engineers and scientists with expertise cutting broadly across materials science, chemical synthesis, interfacial science, spectroscopy, and methods of data science and computational simulation, all bring diverse and important perspectives to catalysis research, but often with little awareness of the complexity of catalytic systems, especially in their working environment. As has already occurred in other scientific fields, there has been growing recognition and consensus in the heterogeneous catalysis research community that mechanisms are needed to improve the rigor and reproducibility (R&R) of experimental measurements, to ensure alignment of the broader research community with a common core of best practices specific to the realization of high-quality catalysis research. Similarly, the field is moving rapidly toward computationally informed and data science-driven catalyst design, but the success of implementing such predictive tools hinges on model training and validation rooted in rigorously obtained and reproducible experimental data that are benchmarked to common specifications. As such, this workshop was convened to prepare a report summarizing best practices for reporting data and performing experiments that researchers can use to benchmark, validate, and reproduce data in specific sub-fields of thermal, heterogeneous catalysis. Additionally, we discussed recommendations for future actions that may improve R&R in this field. The workshop organizers and participants include a diverse range of catalysis researchers from various employment sectors (e.g., academia, industry, national laboratory), institutional mission and resources (e.g., PhD-granting research universities, non-PhD-granting teaching universities), career stage (e.g., early, mid and late-career), technical expertise, and demographic background. This diverse group was involved in the discussion of workshop agenda items, writing this report, and discussing possible future action items for the community to consider, which helped ensure that a broad range of perspectives were captured in the description of the problems at hand and the creation of actionable solutions that may be effectively adopted by the diverse practitioners in catalysis research. Importantly, this group of workshop participants also included very early career researchers (e.g., senior PhD students, postdoctoral scholars) who will become the next generation of scientific leaders in various sectors, thus capturing emerging perspectives of newcomers to the field to shape its future while positively impacting the development of its future workforce. We envision that this effort will help advance the field of catalysis science by improving the rigor and reproducibility of experimental data collected by current researchers and future newcomers to the field, which is of broad importance to health and vitality of any scientific discipline. Therefore, best practices identified in this endeavor for thermal heterogeneous catalysis can be translated to such efforts in other areas of catalysis and other scientific fields involving the study of materials, and vice versa. We also envision this to be an ongoing effort, with future workshops that are convened to discuss issues of rigor and reproducibility on technical topics that were unable to be covered in this workshop due to its scope limitations, and as emerging methods and materials become more prevalent in the research community.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accomplishments and Year-End Performance Report; Wind Energy Program: Fiscal Year 2021

The National Wind Technology Center (NWTC), located at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus, has been a driving force in advancing wind energy technology research worldwide since its designation as a DOE national research center in 1992. Enabled by the Flatirons Campus's world-class facilities, scientists, engineers, analysts, and researchers are pushing the frontiers of science to pursue wind energy innovation. In Fiscal Year (FY) 2021, NREL continued to provide the technical expertise, research capabilities, and industry understanding to support DOE's ambitious climate action and research goals by advancing technology, addressing market and deployment barriers, and driving down costs with more efficient, reliable, and predictable wind energy systems. One of several highlights, NREL received an R&D 100 Special Recognition Award for its Thermoplastic Resin System for Wind Turbine Blades. This breakthrough in the wind turbine manufacturing process will enable the production of recyclable blades that are stronger, longer, and less expensive, while increasing energy capture, decreasing energy and transportation costs, and increasing blade reliability. In a year when the entire U.S. economy struggled to address workforce gaps, an NREL study compared wind industry needs, training programs, and hiring practices with perspectives from students and recent college graduates. Researchers hope that, by pinpointing areas of disconnect, the expectations of employers who have difficulty filling entry-level jobs can better align with the preparation of the potential applicants who find it hard to break into the field. The lab also made numerous new data and modeling resources available in FY 2021. Recent NREL releases include a modeling tool for predicting the power performance and structural loads of wind turbines within a wind farm (FAST.Farm), a computational framework for modeling golden eagle behavior near wind farms, and 20 years of offshore wind data. Updates were also made to the widely used Wind Plant Integrated Systems Design and Engineering Model (WISDEM), which couples engineering and cost models to examine system-level trade-offs. Now, bolstered by a renewed national commitment to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in offshore wind energy - NREL stands poised to lead the way to a sustainable future that powers the United States with significant levels of reliable, low-cost, accessible wind energy. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during FY 2021 (between Oct. 1, 2020, and Sept. 30, 2021).

Flatirons Campus↗
DOE OSTI2023

LA100 Equity Strategies. Chapter 3: Community-Guided Energy Equity Strategies

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided strategies that aim to operationalize recognition and procedural justice. Chapters 1 and 2 target the problem space - the causal factors, impact areas, and values affecting LA's energy justice landscape. This chapter threads those themes through to begin focusing on the solution space. We examine community-identified problems and solutions through the lens of recognition and procedural justice, presenting analysis and strategies that form the basis for more equitable outcomes in LA's energy transition. In our listening sessions, underserved Angelenos highlighted the need to transition away from the status quo one participant described as "transactional extraction of information to check the box. To say yes, we engaged." She asked the LA Department of Water and Power (LADWP) to approach her community with respect and transparency, stating, "We consider you all to be experts in your community, and we'd like to authentically engage with you in the decision-making process. So, I do think there needs to be some intentional actions for that rapport building and that trust building." The community-informed analysis and strategies described in this chapter, which are foundational to the LA100 Equity Strategies project, rise to the challenge of engaging authentically to build rapport, establish relationships of respect, and meaningfully involve Angelenos in the decision-making process. LADWP is already making concerted efforts to redress a disproportionate distribution of investments in physical infrastructure and energy efficient technologies in Los Angeles. This chapter concentrates on the challenge to further rectify past and ongoing inequities in the social, cultural, and institutional scaffolding of Los Angeles. We examine community-guided strategies to tackle this challenge, informed by community input on how all Angelenos can equitably access green jobs and affordable, safe, and resilient energy services, technologies, and programs. These actionable strategies can help move energy equity programs from plans to applied practices, supporting LADWP in launching a just and equitable clean energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2017

Knowledge Base for Distributed Spacecraft Mission Design Using the Trade-Space Analysis Tool for Constellations (TAT-C)

Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.

Pattern Recognition↗
DOE OSTI2024

Bactericidal effectors of the Stenotrophomonas maltophilia type IV secretion system: functional definition of the nuclease TfdA and structural determination of TfcB

ABSTRACT Stenotrophomonas maltophilia expresses a type IV protein secretion system (T4SS) that promotes contact-dependent killing of other bacteria and does so partly by secreting the effector TfcB. Here, we report the structure of TfcB, comprising an N-terminal domain similar to the catalytic domain of glycosyl hydrolase (GH-19) chitinases and a C-terminal domain for recognition and translocation by the T4SS. Utilizing a two-hybrid assay to measure effector interactions with the T4SS coupling protein VirD4, we documented the existence of five more T4SS substrates. One of these was protein 20845, an annotated nuclease. A S. maltophilia mutant lacking the gene for 20845 was impaired for killing Escherichia coli , Klebsiella pneumoniae , and Pseudomonas aeruginosa . Moreover, the cloned 20845 gene conferred robust toxicity, with the recombinant E. coli being rescued when 20845 was co-expressed with its cognate immunity protein. The 20845 effector was an 899 amino-acid protein, comprised of a GHH-nuclease domain in its N-terminus, a large central region of indeterminant function, and a C-terminus for secretion. Engineered variants of the 20845 gene that had mutations in the predicted catalytic site did not impede E. coli , indicating that the antibacterial effect of 20845 involves its nuclease activity. Using flow cytometry with DNA staining, we determined that 20845, but not its mutant variants, confers a loss in DNA content of target bacteria. Database searches revealed that uncharacterized homologs of 20845 occur within a range of bacteria. These data indicate that the S. maltophilia T4SS promotes interbacterial competition through the action of multiple toxic effectors, including a potent, novel DNase. IMPORTANCE Stenotrophomonas maltophilia is a multi-drug-resistant, Gram-negative bacterium that is an emerging pathogen of humans. Patients with cystic fibrosis are particularly susceptible to S. maltophilia infection. In hospital water systems and various types of infections, S. maltophilia co-exists with other bacteria, including other pathogens such as Pseudomonas aeruginosa . We previously demonstrated that S. maltophilia has a functional VirB/D4 type VI protein secretion system (T4SS) that promotes contact-dependent killing of other bacteria. Since most work on antibacterial systems involves the type VI secretion system, this observation remains noteworthy. Moreover, S. maltophilia currently stands alone as a model for a human pathogen expressing an antibacterial T4SS. Using biochemical, genetic, and cell biological approaches, we now report both the discovery of a novel antibacterial nuclease (TfdA) and the first structural determination of a bactericidal T4SS effector (TfcB).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗