Results for “scoring system” — Page 6

DOE OSTI2023

Suppressing Quantum Circuit Errors Due to System Variability

We present a quantum circuit optimization technique that takes into account the variability in error rates that is inherent across present-day noisy quantum computing platforms. This method can be run after qubit routing or postcompilation and consists of computing isomorphic subgraphs to input circuits and scoring each using heuristic cost functions derived from system calibration data. Using an independent standard algorithmic test suite, we show that it is possible to recover on average nearly 40% of missing fidelity using better qubit selection via efficient to compute cost functions. We demonstrate additional performance gains by considering qubit placement over multiple quantum processors. The overhead from these tools is minimal with respect to other compilation steps, such as qubit routing, as the number of qubits increases. As such, our method can be used to find qubit mappings for problems at the scale of quantum advantage and beyond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2018

FAIRness and Usability for Open-Access Omics Data Systems

Omics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems.

Berrios, Daniel C.↗

DOE OSTI2024

Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. To evaluate and quantify outcomes, the research team utilizes the mobility energy productivity (MEP) metric, which is a holistic accessibility measure, to analyze and compare the mobility of various transportation modes in Arlington, Texas. The MEP tool is applied to the ODT system in Arlington, Texas, as well as to five existing transportation modes (driving, transportation network company, transit, biking, and walking). Six ODT scenarios are also analyzed and compared. The analysis is focused on the opportunities that an ODT system presents for transportation disadvantaged communities (DACs) with low rates of car ownership. Although driving received the highest MEP score—a finding typical for a U.S.A. city— the results for the ODT system reveal that it serves those in DACs effectively, helping to achieve an equity design goal. ODT improved the average MEP score across the service area by 83% when considering only accessible, nonprivate vehicle modes (biking, transit, and ODT). For the ODT scenarios, decreasing the wait time by 50% compared with the baseline scenario led to a nearly 160% increase in the MEP score, whereas increasing the ODT travel speed by 21% led to an 80% improvement in the MEP score. As analyzed through the MEP tool, here this paper demonstrates how ODT can enhance mobility, particularly for DACs. The results of an MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems across a service area.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1991

Syntactic error modeling and scoring normalization in speech recognition

The objective was to develop the speech recognition system to be able to detect speech which is pronounced incorrectly, given that the text of the spoken speech is known to the recognizer. Research was performed in the following areas: (1) syntactic error modeling; (2) score normalization; and (3) phoneme error modeling. The study into the types of errors that a reader makes will provide the basis for creating tests which will approximate the use of the system in the real world. NASA-Johnson will develop this technology into a 'Literacy Tutor' in order to bring innovative concepts to the task of teaching adults to read.

Olorenshaw, Lex↗

DOE OSTI2023

Determining Catalytically Relevant Surfaces through Coverage-Dependent Lattice Gas Models: Carbon Adsorption on Fe(100)

Here, we have quantified the C–C lateral interactions on Fe(100) using a density functional theory (DFT)-parameterized lattice gas cluster expansion (LG CE) model trained using 265 unique configurations spanning a C coverage from 0 to 1 monolayer (ML). Our LG CE model shows high predictive accuracy with a leave-multiple-out cross-validation score of 10.2 and 16.6 meV/site for systems with and without the top two layers of Fe atoms fixed, respectively. Electronic ground-state structures identified from the lattice gas model (including the structures at 0 and 1 monolayers) were further used to generate ab initio phase diagrams under a range of temperatures and pressures. At low temperatures (<400 K), we found that the 1.0 monolayer structure is dominant, whereas at higher temperatures (>500 K), the 0.88 ML structure is most likely to form on the Fe surface. Interestingly, our model identified a c (2 × 2) ordered structure at 1/2 ML, which correlates well with previous DFT studies for carbon adsorption on iron surfaces and matches with the experimentally observed low-energy electron diffraction structure. Overall, the DFT-parameterized energies for the C/Fe system including effects of coverage and configurational space can further help in developing multiscale models for various heterogeneous reactions involving C–C and C–Fe interactions.

08 HYDROGEN↗

DOE OSTI2025

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Criticality Analysis of Wind Turbine Components - Intern Poster [Poster]

Wind turbines are an important part of critical energy infrastructure, with wind farms generating more than 10% of US energy in 2023. The goal of this project is to identify and analyze major, common components of wind turbines to reach a preliminary understanding of which should be considered most critical in terms of turbine operation and attack surface. At the time of this project, minimal data was available regarding component costs and lead times, so a qualitative risk assessment approach was used. Components were given a score of 1-5 in four categories– cost to repair, operational downtime, ease of physical attack, and ease of cyber attack. An overall component criticality score was assigned based on the sum of those scores, with a higher score indicating higher criticality. The turbine control system was identified as the most critical component, closely followed by the blades, structural components, and gearbox. This is ongoing project, and further research on the supply chain for wind turbine components will allow for a deeper and more concrete understanding of component criticality.

17 WIND ENERGY↗

NASA NTRSDate not supplied

Appetite and Food Intake During 11 Days of Mild Hypobaric Hypoxia

Introduction Reduced food consumption and loss of body mass and muscle mass have been observed during spaceflight. Hypoxic conditions that astronauts may encounter on exploration missions may further implicate satiety signals and dietary intake. Appetite, food intake, and satiety hormones were investigated under the conditions of mild hypoxia and high energy output during simulated extravehicular activity (EVA) to determine the adequacy of a mission relevant space food system to support energy balance and body composition. Methods Foods realistic to early Artemis missions was packed by meal for each subject for the 11-day test based on estimated energy requirements (EER) and estimated EVA caloric requirements. No hot water or food warmer was provided and only room temperature water was available to rehydrate food and beverages in-mission, mimicking plans for early Artemis missions. Measures included food records (pre-mission, in-mission); fasted body weight (pre-mission, in-mission); Dual-energy X-ray absorptiometry (DXA) (pre-mission, post-mission); subjective ratings and feedback of food acceptability, mealtime and meal preparation sufficiency, appetite, and nausea (in-mission); and circulating ghrelin and leptin concentration in fasted blood samples (pre-mission, in-mission: pre-post EVA). Results All subjects consumed fewer calories in-mission than predicted. On average, subjects consumed 341 calories less on EVA days compared to non-EVA days in-mission (p=0.0511). The total weight loss estimate from daily weight measurements (-1.1 kg, p=0.0028) is consistent with underconsumption and supported by DXA measurements (-1.3 kg total body mass, p=0.0123 and -1.6 kg fat mass, p=0.0016). In general, most foods that were consumed were given acceptable scores, but subject comments indicated that the most acceptable foods were those not intended to be heated. Comments also indicated that subjects found their favorite foods early in the mission and avoided the foods that they did not like throughout the mission. Habitability scores indicated that overall aspects of the food system were considered borderline or unacceptable over the length of this mission. Foods that caused gas were avoided pre-EVA to prevent discomfort during pressure changes. Average fruit and vegetable intake decreased during the mission, dropping from 4.8 servings/d pre-mission to 3.4 servings/d on non-EVA days in-mission (p=0.0872) and 2.3 servings on EVA days (p=0.0020). Fasting ghrelin concentrations tended to be lower pre-EVA and on non-EVA days when exposed to mild hypoxia compared to normoxic conditions pre-mission and post-EVA (p=0.0136). Fasting levels of leptin did not change. Discussion Food intake was reduced in-mission, resulting in a caloric deficit and weight loss for most subjects. Crew food and appetite ratings and comments indicated this was due to a combination of food choices, lack of preference, lack of preparation capability, lack of time for meal preparation, consumption, and cleanup, and physiological challenges with the changing pressure. The regulation of appetite stimulating hormone ghrelin, but not the appetite suppressor leptin, appeared to be sensitive to hypoxic conditions. Conclusions Food preparation capabilities and time for meals are important for promoting adequate food intake. Reduced appetite and food intake during missions may further be aggravated under hypoxic conditions through the suppression of ghrelin. Lack of time for meals on EVA days, and avoidance of potential gas-causing foods (e.g., health promoting fruits and vegetables) prior to EVAs, demonstrate the importance of scheduling ample recovery time between EVA days.

Grace L Douglas↗

NASA NTRS2023

Appetite and Food Intake During 11 Days of Mild Hypobaric Hypoxia

Introduction Reduced food consumption and loss of body mass and muscle mass have been observed during spaceflight. Hypoxic conditions that astronauts may encounter on exploration missions may further implicate satiety signals and dietary intake. Appetite, food intake, and satiety hormones were investigated under the conditions of mild hypoxia and high energy output during simulated extravehicular activity (EVA) to determine the adequacy of a mission relevant space food system to support energy balance and body composition. Methods Foods realistic to early Artemis missions was packed by meal for each subject for the 11-day test based on estimated energy requirements (EER) and estimated EVA caloric requirements. No hot water or food warmer was provided and only room temperature water was available to rehydrate food and beverages in-mission, mimicking plans for early Artemis missions. Measures included food records (pre-mission, in-mission); fasted body weight (pre-mission, in-mission); Dual-energy X-ray absorptiometry (DXA) (pre-mission, post-mission); subjective ratings and feedback of food acceptability, mealtime and meal preparation sufficiency, appetite, and nausea (in-mission); and circulating ghrelin and leptin concentration in fasted blood samples (pre-mission, in-mission: pre-post EVA). Results All subjects consumed fewer calories in-mission than predicted. On average, subjects consumed 341 calories less on EVA days compared to non-EVA days in-mission (p=0.0511). The total weight loss estimate from daily weight measurements (-1.1 kg, p=0.0028) is consistent with underconsumption and supported by DXA measurements (-1.3 kg total body mass, p=0.0123 and -1.6 kg fat mass, p=0.0016). In general, most foods that were consumed were given acceptable scores, but subject comments indicated that the most acceptable foods were those not intended to be heated. Comments also indicated that subjects found their favorite foods early in the mission and avoided the foods that they did not like throughout the mission. Habitability scores indicated that overall aspects of the food system were considered borderline or unacceptable over the length of this mission. Foods that caused gas were avoided pre-EVA to prevent discomfort during pressure changes. Average fruit and vegetable intake decreased during the mission, dropping from 4.8 servings/d pre-mission to 3.4 servings/d on non-EVA days in-mission (p=0.0872) and 2.3 servings on EVA days (p=0.0020). Fasting ghrelin concentrations tended to be lower pre-EVA and on non-EVA days when exposed to mild hypoxia compared to normoxic conditions pre-mission and post-EVA (p=0.0136). Fasting levels of leptin did not change. Discussion Food intake was reduced in-mission, resulting in a caloric deficit and weight loss for most subjects. Crew food and appetite ratings and comments indicated this was due to a combination of food choices, lack of preference, lack of preparation capability, lack of time for meal preparation, consumption, and cleanup, and physiological challenges with the changing pressure. The regulation of appetite stimulating hormone ghrelin, but not the appetite suppressor leptin, appeared to be sensitive to hypoxic conditions. Conclusions Food preparation capabilities and time for meals are important for promoting adequate food intake. Reduced appetite and food intake during missions may further be aggravated under hypoxic conditions through the suppression of ghrelin. Lack of time for meals on EVA days, and avoidance of potential gas-causing foods (e.g., health promoting fruits and vegetables) prior to EVAs, demonstrate the importance of scheduling ample recovery time between EVA days.

Lichar Dillon↗

NASA NTRS1977

The effect of a visual/motion display mismatch in a single axis compensatory tracking task

An experiment was performed to determine the effect of a performance mismatch between the visual and motion display systems on a real time piloted aircraft simulation. Pilots performed a compensatory roll tracking task with dynamics typical of medium jet transports. Between 0 and 10 rad/sec, visual and motion system responses were equivalent to either unity or a first order lag at 4.8 rad/sec. Pilot describing functions and error scores were calculated. Results show that the mismatch between visual and motion display systems has no significant effect. It is the absence of high frequency visual and/or motion cues which significantly affects pilot performance.

Shirachi, D. K.↗

NASA NTRS1985

Speech variability effects on recognition accuracy associated with concurrent task performance by pilots

In the present study of the responses of pairs of pilots to aircraft warning classification tasks using an isolated word, speaker-dependent speech recognition system, the induced stress was manipulated by means of different scoring procedures for the classification task and by the inclusion of a competitive manual control task. Both speech patterns and recognition accuracy were analyzed, and recognition errors were recorded by type for an isolated word speaker-dependent system and by an offline technique for a connected word speaker-dependent system. While errors increased with task loading for the isolated word system, there was no such effect for task loading in the case of the connected word system.

Simpson, C. A.↗

DOE OSTI2026

Resilience Metrics Framework for Solar Photovoltaics

This presentation was given at the Photovoltaic Specialist Conference (PVSC) 54 in New Orleans, Louisiana. Photovoltaic (PV) systems are routinely exposed to extreme weather, including wind and hail storms. Historically, most systems have proven to be resilient to such events, but some storms have damaged PV systems, leading to physical and financial loss. Storm hardening measures and specific system attributes can reduce this risk. This work introduces a set of resilience metrics and a framework for quantifying, comparing, and predicting PV system resilience. The framework is divided into two parts: 1) predictive, attribute metrics based on site and component characteristics, and 2) impact metrics that assess post-storm performance. Metrics are weighted and aggregated, producing hazard-specific resilience scores. We derive damage functions from storm-impacted PV systems, establishing a baseline against which post-storm performance can be compared. This damage was widely variable across hail and wind intensities, and field hail damage was less than predicted by laboratory tests, suggesting that system features - in addition to storm conditions - influence damage likelihood. Finally, the metrics framework is demonstrated using three case studies of storm damaged PV systems. Although additional data are needed to create attribute specific damage functions and establish metric weights, this study presents a methodology for evaluating PV resilience and contributes new damage functions to the literature.

14 SOLAR ENERGY↗

DOE OSTI2024

FEW questions, many answers: using machine learning to assess how students connect food–energy–water (FEW) concepts

There is growing support and interest in postsecondary interdisciplinary environmental education which integrate concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts. This work tests a text classification machine learning model as a tool to assess student systems thinking capabilities using two questions anchored by the Food-Energy-Water (FEW) Nexus phenomena by answering two questions (1) Can machine learning models be used to identify instructor-determined important concepts in student responses? (2) What do college students know about the interconnections between food, energy and water, and how have students assimilated systems thinking into their constructed responses about FEW? Reported here are a broad range of model performances across 26 text classification models associated with two different assessment items, with model accuracy ranging from 0.755 to 0.992. Expert-like responses were infrequent in our dataset compared to responses providing simpler, incomplete explanations of the systems presented in the question. For those students moving from describing individual effects to multiple effects, their reasoning about the mechanism behind the system indicates advanced systems thinking ability. Specifically, students exhibit higher expertise for explaining changing water usage than discussing tradeoffs for such changing usage. This research represents one of the first attempts to assess the links between foundational, discipline-specific concepts and systems thinking ability. These text classification approaches to scoring student FEW Nexus Constructed Responses (CR) indicate how these approaches can be used, in addition to several future research priorities for interdisciplinary, practice-based education research. Development of further complex question items using machine learning would allow evaluation of the relationship between foundational concept understanding and integration of those concepts as well as more nuanced understanding of student comprehension of complex interdisciplinary concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2026

Heat exposure and maternal stress: evidence from the GRAPHS pregnancy cohort in Ghana

Heat exposure has been linked to psychosocial stress, an established antecedent of perinatal depression; however, evidence on heat-related stress during pregnancy in sub-Saharan Africa remains limited. We analyzed psychosocial stress scores and covariate data from the Ghana Randomized Air Pollution and Health Study, linking daily maximum and minimum shaded wet bulb globe temperature (WBGT) metrics to participants’ stress scores derived from the Crisis in Family Systems-Revised Life Events Questionnaire. We evaluated associations using ordinal logistic regression of pregnancy-average and trimester-average exposures and distributed lag non-linear models (DLNMs) to assess time-varying associations across gestation. Higher average maximum WBGT exposure across pregnancy was associated with increased odds of higher psychosocial stress; each 1 °C increase in maximum WBGT was associated with 64% higher odds of belonging to a higher stress category (OR = 1.64; 95% CI = 1.17–2.31; p = 0.0040). In trimester-average models, higher first-trimester maximum WBGT was also associated with higher stress (OR = 1.44; 95% CI = 1.15–1.81; p = 0.0014). DLNMs suggested that relatively cooler daily maximum WBGT values (25th percentile) were associated with decreased odds of stress in early pregnancy, whereas extreme daily maximum WBGT values (99th percentile) showed a pattern consistent with increased odds of stress in mid-to-late gestation. These findings highlight gestational windows in which heat exposure may influence stress, emphasizing the need for further research into underlying mechanisms and effective interventions to protect maternal mental health in heat-vulnerable settings.

White, Lewis [Columbia University] (ORCID:00090005↗

NASA NTRS1977

Reliability measurement during software development

Measurement of software reliability was carried out during the development of data base software for a multi-sensor tracking system. Every run made during this project was scored as success or failure, and supporting data were collected on forms for further analysis. The failure ratio (number of failures per calendar interval divided by total number of runs) and failure rate (number of failures divided by CPU time for the interval) were found to be consistent measures, on a month-to-month basis as well as from module to module, and therefore considered valid indicators of reliability in this environment. Trend lines could be established from these measurements that provide good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the specific run submission rather than with the code proper.

Hecht, H.↗

NASA NTRS2008

Experimentation for the Maturation of Deep Space Cryogenic Refueling Technologies

This report describes the results of the "Experimentation for the Maturation of Deep Space Cryogenic Refueling Technology" study. This study identifies cryogenic fluid management technologies that require low-gravity flight experiments bring technology readiness levels to 5 to 6; examines many possible flight experiment options; and develops near-term low-cost flight experiment concepts to mature the core technologies. A total of 25 white papers were prepared by members of the project team in the course of this study. The full text of each white paper is included and 89 relevant references are cited. The team reviewed the white papers that provided information on new or active concepts of experiments to pursue and assessed them on the basis of technical need, cost, return on investment, and flight platform. Based on on this assessment the "Centaur Test Bed for Cryogenic Fluid Management" was rated the highest. "Computational Opportunities for Cryogenics for Cryogenic and Low-g Fluid Systems" was ranked second, based on its high scores in state of the art and return on investment, even though scores in cost and time were second to last. "Flight Development Test Objective Approach for In-space Propulsion Elements" was ranked third.

Chato, David J.↗

DOE OSTI2026

Towards Secure Autonomous Vehicles: An Integrated Edge and Multi-Modal Machine Learning Framework for Intrusion Detection

Autonomous vehicles (AVs) are vulnerable to cyberattacks targeting both internal communication networks and external perception sensors. While edge-based intrusion de- tection for Controller Area Network (CAN) buses offers real-time protection, it cannot detect cross-modal threats. Conversely, multi-modal fusion approaches improve coverage but often lack efficiency for in-vehicle deployment. This thesis integrates two complemen- tary solutions: (1) a lightweight, edge-deployable machine learning framework for CAN bus intrusion detection, and (2) a late-fusion system combining CAN FD and LiDAR data. Together, they form a hierarchical defense capable of handling single-modality and coordi- nated attacks. Simulations show that CAN-only models reach 93% accuracy on simulated DoS, spoofing, replay, and fuzzy attacks, while the fusion system achieves 0.87 AUC and 0.82 F1-score at 2 ms latency. This unified framework establishes a scalable, explainable, and field-ready strategy for AV cybersecurity.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Component Criticality in BESS for Cybersecurity

Battery energy storage systems (BESS), inverters, and associated digital equipment are integral pieces of interdependent energy delivery systems. When considering the supply chain security of such systems, there is often a misplaced focus on the origin of energy generation and storage materials like battery cells, overlooking the more significant cyber risks that stem from digital power electronics control systems. Part of this misplaced focus is due to the relative costs of these components, with more attention given to expensive raw materials rather than the impactful digital elements themselves. The Idaho National Laboratory (INL) is addressing this gap in supply chain security through a systems-of-systems approach that considers the impact various components in digital energy systems can have should misoperation occur. Therefore, INL assigns a cyber criticality score based on quantitative analysis, which enables informed prioritization of mitigations and allows operators to reduce risk in light of the prevalence of a BESS and associated systems foreign supply chain.

25 ENERGY STORAGE↗