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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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DOE OSTI2022

Wabash CarbonSAFE: Detailed Site Characterization Plan, Task 11.0, Technical Report

Wabash CarbonSAFE established that commercial-scale CO 2 storage in the Potosi Dolomite –Maquoketa Group storage complex associated with the Wabash Valley Resources (WVR) plant site near Terre Haute, IN is highly feasible. The CarbonSAFE project team performed this evaluation through extensive data acquisition and analysis including 2D seismic reflection data, wireline logs, well testing, and core/cuttings from the Wabash #1 stratigraphic test well (now plugged and abandoned). This document summarizes work detailed in separate Wabash CarbonSAFE reports and consolidates the geologic characterization, well testing, and storage complex modeling results for the Mt. Simon Sandstone and Potosi Dolomite, two distinct reservoirs characterized at the Wabash CarbonSAFE project site. The report then presents recommendations for the next steps for site characterization, identifies data gaps for future activities, and provides an overall assessment of site potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1997

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

This final report has four sections. We first describe the actual scientific results attained by our research team, followed by a description of the high performance computing research enhancing those results and prompted by the scientific tasks being undertaken. Next, we describe our research in data and program visualization motivated by the scientific research and also enabling it. Last, we comment on the indirect effects this research effort has had on our work, in terms of follow up or additional funding, student training, etc.

Schwan, Karsten↗

NASA NTRS2023

IMPACTing Medical System Design with a Risk Analysis Tool [“IMPACT” sur la Conception du Système Médical avec un Outil d'Analyse des Risques]

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗

NASA NTRSDate not supplied

IMPACTing Medical System Design with a Risk Analysis Tool

K A Shair↗

DOE OSTI2021

Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach

Explore the source record for details and available documents.

Computer Science↗

NASA NTRS2011

Evaluating Suit Fit Using Performance Degradation

The Mark III suit has multiple sizes of suit components (arm, leg, and gloves) as well as sizing inserts to tailor the fit of the suit to an individual. This study sought to determine a way to identify the point an ideal suit fit transforms into a bad fit and how to quantify this breakdown using mobility-based physical performance data. This study examined the changes in human physical performance via degradation of the elbow and wrist range of motion of the planetary suit prototype (Mark III) with respect to changes in sizing and as well as how to apply that knowledge to suit sizing options and improvements in suit fit. The methods implemented in this study focused on changes in elbow and wrist mobility due to incremental suit sizing modifications. This incremental sizing was within a range that included both optimum and poor fit. Suited range of motion data was collected using a motion analysis system for nine isolated and functional tasks encompassing the elbow and wrist joints. A total of four subjects were tested with motions involving both arms simultaneously as well as the right arm only. The results were then compared across sizing configurations. The results of this study indicate that range of motion may be used as a viable parameter to quantify at what stage suit sizing causes a detriment in performance; however the human performance decrement appeared to be based on the interaction of multiple joints along a limb, not a single joint angle. The study was able to identify a preliminary method to quantify the impact of size on performance and to develop a means to gauge tolerances around optimal size. More work is needed to improve the assessment of optimal fit and to compensate for multiple joint interactions.

Margerum, Sarah E.↗

DOE OSTI2019

Parameter inference with deep jointly informed neural networks

Abstract A common challenge in modeling inertial confinement fusion (ICF) experiments with computer simulations is that many of the simulation inputs are unknown and cannot be directly measured. Often, parameters that are measured in the experiment are used to infer the unknown inputs by solving the inverse problem: finding the set of simulation inputs that result in outputs consistent with the experimental observations. In ICF, this process is often referred to as a “post‐shot analysis.” Post‐shot analyses are challenging as the inverse problem is often highly degenerate, the input parameter space is vast, and simulations are computationally expensive. In this work, deep neural network models equipped with model uncertainty estimates are used to train inverse models, which map directly from output to input space, to find the distribution of post‐shot simulations that are consistent with experimental observations. The inverse model approach is compared to Markov chain Monte Carlo (MCMC) sampling of the forward model, which maps from input to output space, for parameter inference tasks of varying complexity. The inverse models perform best when searching vast parameter spaces for post‐shot simulations that are consistent with a large number of observables, where MCMC sampling can be prohibitively expensive. We demonstrate how augmenting inverse models with autoencoders enable the inclusion of several dozen observables in the inverse mapping, reducing the degeneracy of the model and improving the accuracy of the post‐shot analysis.

Humbird, Kelli D.↗

NASA NTRS2015

Subsonic Ultra Green Aircraft Research: Phase 2: Hybrid Electric Design Exploration - Volume 2

This report summarizes the hybrid electric concept design, analysis, and modeling work accomplished by the Boeing Subsonic Ultra Green Aircraft Research (SUGAR) team, consisting of Boeing Research and Technology, Boeing Commercial Airplanes, General Electric, and Georgia Tech.Performance and sizing tasks were conducted for hybrid electric versions of a conventional tube-and-wing aircraft and a hybrid wing body. The high wing Truss Braced Wing (TBW) SUGAR Volt was updated based on results from the TBW work (documented separately) and new engine performance models. Energy cost and acoustic analyses were conducted and technology roadmaps were updated for hybrid electric and battery technology. NOx emissions were calculated for landing and takeoff (LTO) and cruise. NPSS models were developed for hybrid electric components and tested using an integrated analysis of superconducting and non-superconducting hybrid electric engines. The hybrid electric SUGAR Volt was shown to produce significant emissions and fuel burn reductions beyond those achieved by the conventionally powered SUGAR High and was able to meet the NASA goals for fuel burn. Total energy utilization was not decreased but reduced energy cost can be achieved for some scenarios. The team was not able to identify a technology development path to meet NASA's noise goals

Bradley, Marty K.↗

NASA NTRS1993

Performance analysis of a robotic system for space-based assembly

A dual arm system for space-based assembly has been under development and experimentation at the Center of Intelligent Robotic Systems for Space Exploration. This paper will describe the components of this system and will then focus on the specific problem of predicting response time of the integrated system. This hierarchical system consists of a task representation and planning level, a coordination level, and an execution level to carry out the desired assembly task. A common modeling methodology based on Petri nets was used to model the various subtasks throughout the levels of the hierarchy. The Petri net model can then be analyzed for liveness and boundedness that, in turn, are used to detect the existence of deadlock or conflict in the system. The model can also be used to calculate the time it will take to complete an assembly task once an operator issues a command. These modeling results are compared with the actual experimental results obtained from carrying out the assembly task.

Desrochers, Alan↗

NASA NTRS2002

Examining the Pilot and Controller Performance Data When in a Free Flight with Weather Phenomenon

The present study investigated effects of weather related factors on the performance of pilots under free flight. A weather scenario was defined by a combination of precipitation factors (light rain, moderate rain, and heavy rain or snow), visibility (1,4,8 miles), wind conditions (light, medium, or heavy), cloud ceiling (800ft. below, 1800ft above, and 4000ft horizontal). The performance of the aircraft self-separation was evaluated in terms of detection accuracy and detection times for student- and commercial (expert) pilots. Overall, the results obtained from a behavioral analysis showed that in general, the ability to recognize intruder aircraft conflict incidents, followed by the ability to acquire the spatial location of the intruder aircraft relative to ownership aircraft were judged to be the major cognitive tasks as perceived by the participants during self-separation. Further, the participants rarely used cockpit display of traffic information (CDTI) during conflict management related to aircraft separation, but used CDTI highly during decision-making tasks. In all weather scenarios, there were remarkable differences between expert and student pilots in detection times. In summary, weather scenarios were observed to affect intruder aircraft detection performance accuracies. There was interaction effects between weather Scenario-1 and Scenario-2 for climbing task data generated by both expert- and student- pilots at high traffic density. Scenario-3 weather condition provided an opportunity for poor detection accuracy as well as detection time increase. This may be attributed to low visibility. The intruder aircraft detection times were not affected by the weather conditions during climbing and descending tasks. The decision of pilots to fly into certain weather condition was dependent in part on the warning distance to the location of the weather. When pilots were warned of the weather conditions, they were more likely to fly their aircraft into it, but mostly when the warning was not close to the weather location.

Nituen, Celestine A.↗

DOE OSTI2023

Large Language Models (LLMs) for Energy Systems Research

The integration of Large Language Models (LLMs) in energy systems research promises transformative results, as demonstrated in this work, particularly in the realms of information retrieval and legal document analysis. We have developed a chat-based interface, specifically designed to query an extensive corpus of technical reports from the National Renewable Energy Laboratory (NREL). This interface capitalizes on the natural language processing capabilities of LLMs, providing future consumers of NREL research with a user-friendly platform to access and extract valuable information from technical documents, thus enhancing the dissemination of research to the public. In addition to information retrieval, we have employed LLMs to extract renewable energy siting ordinances from a variety of legal documents, a task traditionally driven by significant human labor. This automated extraction not only supports the ongoing development of the high-impact NREL siting ordinance database but also ensures the database's accuracy and comprehensiveness. Crucially, we have augmented the performance of LLMs through the integration of a decision tree framework, resulting in a substantial improvement in extraction accuracy. Comparative analysis with manual efforts has shown that this approach not only rivals but also significantly surpasses human accuracy, heralding increased reliability in legal document analysis for energy systems research. To democratize access to these advancements and foster collaborative research, we introduce the "Energy Language Model" (ELM), an open-source software package. ELM encapsulates the methodologies and tools developed in this work, providing researchers and practitioners with a robust toolkit to conduct similar analyses within their respective domains. Through these contributions, this work underscores the immense potential of LLMs in revolutionizing energy systems research, improving accuracy, efficiency, and accessibility in the field.

automation↗

NASA NTRS2015

Analysis of Human-Spacesuit Interaction

Astronauts sustain injuries of various natures such as finger delamination, joint pain, and redness due to their interaction with the space suit. The role of the Anthropometry and Biomechanics Facility is to understand the biomechanics, environmental variables, and ergonomics of the suit. This knowledge is then used to make suggestions for improvement in future iterations of the space suit assembly to prevent injuries while allowing astronauts maneuverability, comfort, and tactility. The projects I was involved in were the Extravehicular Mobility Unit (EMU) space suit stiffness study and the glove feasibility study. The EMU project looked at the forces exerted on the shoulder, arm, and wrist when subjects performed kinematic tasks with and without a pressurized suit. The glove study consisted of testing three conditions - the Series 4000 glove, the Phase VI glove, and the no glove condition. With more than forty channels of sensor data total, it was critical to develop programs that could analyze data with basic descriptive statistics and generate relevant graphs to help understand what happens within the space suit and glove. In my project I created a Graphical User Interface (GUI) in MATLAB that would help me visualize what each sensor was doing within a task. The GUI is capable of displaying overlain plots and can be synchronized with video. This was helpful during the stiffness testing to visualize how the forces on the arm acted while the subject performed tasks such as shoulder adduction/abduction and bicep curls. The main project of focus, however, was the glove comparison study. I wrote MATLAB programs which generated movies of the strain vectors during specific tasks. I also generated graphs that summarized the differences between each glove for the strain, shear and FSR sensors. Preliminary results indicate that the Phase VI glove places less strain and shear on the hand. Future work includes continued data analysis of surveys and sensor data. In the end, the ideal glove is one that provides more tactility for the astronauts but lessens injuries. Often times, a more tactile glove transmits forces better to the hand; thus, achieving a balance of both a tactile and safe glove is the main challenge present.

Thomas, Neha↗

DOE OSTI2018

IEA Wind TCP Task 26–Wind Technology, Cost, and Performance Trends in Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States: 2008-2016

The International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) Task 26 - The Cost of Wind Energy represents an international collaboration dedicated to exploring the past, present, and future cost of wind energy. The countries that are currently represented by participating organizations in IEA Wind TCP Task 26 included in this report are Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States. This report discusses trends from 2008 through 2016 that affected the cost of land-based wind energy in each country. The cost of wind energy during this period is compared with the market value of wind energy in the respective electricity market for each country. This report builds from previous analysis conducted since the inception of Task 26 in 2009. Schwabe et al. (2011) explored differences in the cost of wind energy in 2008 among countries participating in Task 26 at that time. Vitina et al. (2015) presented turbine- and project-level trends in the wind industry from 2008 to 2012, including wind project size, turbine size, specific power and hub height, project performance, investment costs, operation and maintenance (O&M) costs, and project financing. These inputs are used to calculate the levelized cost of energy (LCOE), a widely recognized metric for understanding how technology performance, capital investment, operations, and financing impact the life cycle cost of building and operating a wind project. Both prior reports - as well as this report - used this metric to estimate the cost of wind energy.

17 WIND ENERGY↗

DOE OSTI2022

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Detecting dynamic causal inference in nonlinear two-phase fracture flow

Identifying dynamic causal inference involved in flow and transport processes in complex fractured-porous media is generally a challenging task, because nonlinear and chaotic variables may be positively coupled or correlated for some periods of time, but can then become spontaneously decoupled or non-correlated. In his 2002 paper (Faybishenko, 2002), the author performed a nonlinear dynamical and chaotic analysis of time-series data obtained from the fracture flow experiment conducted by Persoff and Pruess (1995), and, based on the visual examination of time series data, hypothesized that the observed pressure oscillations at both inlet and outlet edges of the fracture result from a superposition of both forward and return waves of pressure propagation through the fracture. In the current paper, the author explores an application of a combination of methods for detecting nonlinear chaotic dynamics behavior along with the multivariate Granger Causality (G-causality) time series test. Based on the G-causality test, the author infers that his hypothesis is correct, and presents a causation loop diagram of the spatial-temporal distribution of gas, liquid, and capillary pressures measured at the inlet and outlet of the fracture. The causal modeling approach can be used for the analysis of other hydrological processes, for example, infiltration and pumping tests in heterogeneous subsurface media, and climatic processes, for example, to find correlations between various meteorological parameters, such as temperature, solar radiation, barometric pressure, etc.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

North American Board of Certified Energy Practitioners Final Report

The U.S. DOE’s Office of EERE National Solar Energy Technology Program (SETP) calls for a “National Accreditation and Certification Program for Installation and Acceptance of Photovoltaic Systems.” A near-term goal listed in the U.S. Photovoltaic Industry’s Roadmap, 2000 - 2020 is to work to establish standards, codes, and certifications which are essential for consumer protection and acceptance as part of the goal of building toward a viable future PV industry. This program paves the way for a voluntary national certification program for PV system practitioners and installers, initiation of the first steps toward certification of hardware, and reinforcement of all five of the technical objectives in the Systems category of SETPs Multi-Year technical Plan. Through this project, NABCEP will direct the continued initiation of and sustained implementation and administration of the NABCEP Solar PV Installer Certification Program (hereafter the “Program”). The NABCEP Program is a national, voluntary program designed to provide certification for those PV installers who demonstrate the requisite skills, abilities and knowledge typically required to install and maintain PV systems. The core document upon which the Program was developed and upon which the national exam is based, is referred to as the (Program) Task Analysis. It is a thorough descriptive document containing specific psychomotor and cognitive tasks for the purposes of identifying the types of training/assessment methods that apply. Psychomotor skills require measuring, assembling, fastening and related activities. Cognitive skills require knowledge processing, decision-making and computations. NABCEP effectively evaluates an applicant’s psychomotor skills through review of a candidate’s PV installations and hands-on training received. NABCEP evaluates the candidate’s cognitive skills through administration of its national Program exam. By first qualifying for and then obtaining the required passing score, NABCEP certificants receive an accreditation that upholds NABCEP’s standards of quality, compliance to applicable codes and safety in PV installation. The objectives of DOE’s National Solar Energy Technology Program (SETP) are intrinsic to NABCEP. As detailed in the PV Roadmap, the lifespan of a PV system is a function of reliability and value. PV system reliability is directly dependent upon the quality of components and, design, installation and maintenance of a system. The latter three are all core components of the NABCEP Task Analysis - accordingly NABCEP certified installers will be instrumental in improving reliability of systems through safe, code and manufacturer-compliant installation and necessary post-installation maintenance of PV systems. This will have the effect of ensuring and increasing the performance of installed systems and, as consumers realize the benefits of well-installed and maintained systems, increased demand will follow and manufacturers will respond - supporting further growth in the PV industry. Furthermore, as more NABCEP certified installers perform these installations and maintenance competently, additional installations (whole system re-installations) and unnecessary repairs can be avoided. This will drive down system costs. This combined with creation/enhancement of the DE-FG36-04GO14348/005 NABCEP Central Data Base of Installers – providing consumers with installation/maintenance service options will further reduce system costs and help meet the overall goal of reducing life cycle costs. As consumers receive more value from PV systems which are providing longer, trouble free, renewable energy, they will join the ranks of professionals and enthusiasts calling for reduced technological barriers to installation (particularly for grid-tied systems). States and utilities will react to pressure and begin easing onerous net-metering and other technological restrictions. The benefits of NABCEP’s Program will be evident to consumers, manufacturers, distributors, state energy officials and solar academic institutions. Consumers benefit through increased system performance and reduced costs. Manufacturers of PV and balance of system components as well as distributors support and benefit from NABCEP because of assurances that systems are installed in accordance to code (i.e., NEC) and their specifications, resulting in longer life. Collaborators including state energy officials (i.e., New York State Energy Research and Development Authority) benefit by knowing that rebate funds are spent on systems whose benefits will far exceed system costs. Program Objectives The improvements and advantages offered by a national voluntary certification program can only expand the horizons for photovoltaic applications.

14 SOLAR ENERGY↗

DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Criteria for assessing problem solving and decision making in complex environments

Training crews to cope with unanticipated problems in high-risk, high-stress environments requires models of effective problem solving and decision making. Existing decision theories use the criteria of logical consistency and mathematical optimality to evaluate decision quality. While these approaches are useful under some circumstances, the assumptions underlying these models frequently are not met in dynamic time-pressured operational environments. Also, applying formal decision models is both labor and time intensive, a luxury often lacking in operational environments. Alternate approaches and criteria are needed. Given that operational problem solving and decision making are embedded in ongoing tasks, evaluation criteria must address the relation between those activities and satisfaction of broader task goals. Effectiveness and efficiency become relevant for judging reasoning performance in operational environments. New questions must be addressed: What is the relation between the quality of decisions and overall performance by crews engaged in critical high risk tasks? Are different strategies most effective for different types of decisions? How can various decision types be characterized? A preliminary model of decision types found in air transport environments will be described along with a preliminary performance model based on an analysis of 30 flight crews. The performance analysis examined behaviors that distinguish more and less effective crews (based on performance errors). Implications for training and system design will be discussed.

Orasanu, Judith↗