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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Photometric redshifts for the S-PLUS Survey: Is machine learning up to the task?

The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for important stellar features in the local universe. In this paper we use the photometry and morphological information from the first S-PLUS data release (S-PLUS DR1) cross-matched to unWISE data and spectroscopic redshifts from Sloan Digital Sky Survey DR15. We explore three different machine learning methods (Gaussian Processes with GPz and two Deep Learning models made with TensorFlow) and compare them with the currently used template-fitting method in the S-PLUS DR1 to address whether machine learning methods can take advantage of the twelve filter system for photometric redshift prediction. Using tests for accuracy for both single-point estimates such as the calculation of the scatter, bias, and outlier fraction, and probability distribution functions (PDFs) such as the Probability Integral Transform (PIT), the Continuous Ranked Probability Score (CRPS) and the Odds distribution, we conclude that a deep-learning method using a combination of a Bayesian Neural Network and a Mixture Density Network offers the most accurate photometric redshifts for the current test sample. In conclusion, it achieves single-point photometric redshifts with scatter (σ NMAD ) of 0.023, normalized bias of -0.001, and outlier fraction of 0.64% for galaxies with r_auto magnitudes between 16 and 21.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Powering the Blue Economy - Ocean Observing Use Cases Report

The "Powering the Blue Economy" (PBE) Report identified ocean observing and autonomous underwater vehicle (AUV) recharge as near-term markets with significant potential for marine energy integration when specified qualitative and quantitative assessment criteria were used. The ocean observing market (including AUVs) scored high relative to other markets analyzed in the PBE Report with respect to market size, marine renewable energy (MRE) compatibility with functional requirements, competitive positioning (i.e., MRE versus other power sources), path to market, and alignment to the Department of Energy Water Power Technologies Office (WPTO) and other agencies' objectives. Based on this scoring, Pacific Northwest National Laboratory (PNNL) and the National Renewable Energy Laboratory (NREL) pursued the development of five use cases that represent a spectrum of ocean observation platforms, fixed and mobile, to explore the present and future power needs that might be satisfied by marine energy. The use cases were described and analyzed for this potential by examining current missions and future needs, evaluating the mix of renewable energy sources that might satisfy those needs at sea, and understanding the overall cost drivers that might enable this application.

14 SOLAR ENERGY↗
NASA NTRS2003

Simple Math is Enough: Two Examples of Inferring Functional Associations from Genomic Data

Non-random features in the genomic data are usually biologically meaningful. The key is to choose the feature well. Having a p-value based score prioritizes the findings. If two proteins share a unusually large number of common interaction partners, they tend to be involved in the same biological process. We used this finding to predict the functions of 81 un-annotated proteins in yeast.

Liang, Shoudan↗
NASA NTRS2001

Space Shuttle RTOS Bayesian Network

With shrinking budgets and the requirements to increase reliability and operational life of the existing orbiter fleet, NASA has proposed various upgrades for the Space Shuttle that are consistent with national space policy. The cockpit avionics upgrade (CAU), a high priority item, has been selected as the next major upgrade. The primary functions of cockpit avionics include flight control, guidance and navigation, communication, and orbiter landing support. Secondary functions include the provision of operational services for non-avionics systems such as data handling for the payloads and caution and warning alerts to the crew. Recently, a process to selection the optimal commercial-off-the-shelf (COTS) real-time operating system (RTOS) for the CAU was conducted by United Space Alliance (USA) Corporation, which is a joint venture between Boeing and Lockheed Martin, the prime contractor for space shuttle operations. In order to independently assess the RTOS selection, NASA has used the Bayesian network-based scoring methodology described in this paper. Our two-stage methodology addresses the issue of RTOS acceptability by incorporating functional, performance and non-functional software measures related to reliability, interoperability, certifiability, efficiency, correctness, business, legal, product history, cost and life cycle. The first stage of the methodology involves obtaining scores for the various measures using a Bayesian network. The Bayesian network incorporates the causal relationships between the various and often competing measures of interest while also assisting the inherently complex decision analysis process with its ability to reason under uncertainty. The structure and selection of prior probabilities for the network is extracted from experts in the field of real-time operating systems. Scores for the various measures are computed using Bayesian probability. In the second stage, multi-criteria trade-off analyses are performed between the scores. Using a prioritization of measures from the decision-maker, trade-offs between the scores are used to rank order the available set of RTOS candidates.

Morris, A. Terry↗
DOE OSTI2021

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗
DOE OSTI2025

Implementation of disruptive designs for gas turbine components using direct energy deposition additive manufacturing

This research aims to develop a framework for establishing the correlation between in-situ monitoring data, process parameters, and microstructure evolution in blown-powder laser-directed energy deposition (DED) additive manufacturing (AM). To achieve this, a comprehensive manufacturing framework has been developed, spanning from in-situ data acquisition, melt-pool simulation, microstructure modeling, and statistical microstructure quantification. A machine learning-based surrogate model is constructed to predict melt pool geometry directly from in-situ coaxial camera data. The surrogate model is trained using outputs from a high-fidelity melt pool simulation, which provides accurate melt pool dimension data under varying process conditions. The predicted melt pool geometry is then used as input to a microstructure model to predict microstructural features. To rigorously compare and analyze microstructures, the project introduces statistical metrics that quantify differences based on key features such as morphology and texture. Microstructures are represented using advanced statistical descriptors including angular chord length distribution, two-point spatial statistics, orientation distribution function, and global spherical harmonic. These representations are used to compute four distinct “dissimilarity scores” that quantitatively capture differences in texture and morphology. This framework is demonstrated to enable automated calibration of simulation parameters by minimizing discrepancies between simulated and target microstructures. The technology developed in this project enables direct correlation between in-situ monitoring data and resulting microstructure, paving the way for adaptive microstructure control in metal AM. This capability strengthens the connection between process parameters and final material properties, facilitating more precise and reliable material design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simultaneous inhibition of ATM, ATR, and DNA-PK causes synergistic lethality

Here, in this paper, we report that simultaneous inhibition of the three primary DNA damage recognition PI3 kinase-like kinases (PIKKs) —ATM, ATR, and DNA-PK— induces severe combinatorial synthetic lethality in mammalian cells. Utilizing Chinese hamster cell lines CHO and V79 and their respective PIKK mutants, we evaluated effects of inhibiting these three kinases on cell viability, DNA damage response, and chromosomal integrity. Our results demonstrate that while single or dual kinase inhibition increased cytotoxicity, inhibition of all three PIKKs results in significantly higher synergistic lethality, chromosomal aberrations, and DNA double-strand break (DSB) induction as calculated by their synergy scores. These findings suggest that the overlapping redundancy of ATM, ATR, and DNA-PK functions is critical for cell survival, and their combined inhibition greatly disrupts DNA damage signaling and repair processes, leading to cell death. This study provides insights into the potential of multi-targeted DDR kinase inhibition as an effective anticancer strategy, necessitating further research to elucidate underlying mechanisms and therapeutic applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An implicit solution for Asay foil trajectories generated by separable, sustained-production ejecta source models

We present a simple implicit solution for the time-dependent trajectory of a thin Asay foil ejecta diagnostic for the general case where the impinging ejecta cloud is generated by a source function characterized by an arbitrary (sustained) time dependence and a time-independent (stationary) particle velocity distribution. In the limit that the source function time dependence becomes a delta function, this solution—which is amenable to rapid numerical calculations of arbitrary accuracy—exactly recovers a previously published solution for the special case of instantaneous ejecta production. We also derive simple expressions for the free-surface arrival (catch-up) time as well as the true ejecta areal mass accumulation on the accelerating foil and place bounds on the level of error incurred when applying instant-production mass solutions to a sustained-production trajectory. We demonstrate these solutions with example calculations for hypothetical source functions spanning a wide range of ejecta production durations, velocity distributions, and temporal behaviors. These calculations demonstrate how the foil trajectory is often insensitive to the temporal dependence of the source function, instead being dominated by the velocity distribution. We quantify this insensitivity using a “compatibility score” metric. Under certain conditions, one may capitalize upon this insensitivity to obtain a good approximation of the second integral of the velocity distribution from the observed foil trajectory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Clinical effects of 3D printing-assisted posterolateral incision in the treatment of ankle fractures involving the posterior malleolus

Objective To explore the clinical outcomes of a 3D printing-assisted posterolateral approach for the treatment of ankle fractures involving the posterior malleolus. Methods A total of 51 patients with ankle fractures involving the posterior malleolus admitted to our hospital from January 2018 to December 2019 were selected. The patients were divided into 3D printing group (28 cases) and control group (23 cases). 3D printing was performed for ankle fractures, followed by printing of a solid model and simulation of the operation on the 3D model. The operation was then performed according to the preoperative plan, including open reduction and internal fixation via the posterolateral approach with the patient in the prone position. Routine x-ray and CT examinations of the ankle joint were performed, and ankle function was evaluated using the American Foot and Ankle Surgery Association (AOFAS) ankle-hindfoot score. Results All patients underwent x-ray and CT examinations. All fractures healed clinically, without loss of reduction or failure of internal fixation. Good clinical effects were achieved in both groups of patients. The operation time, intraoperative blood loss and intraoperative fluoroscopy frequency in the 3D printing group were significantly less than those in the control group ( p < 0.05). There was no significant difference between the two groups in the anatomical reduction rate of fractures or the incidence of surgical complications ( p > 0.05). Conclusion The 3D printing-assisted posterolateral approach is effective in the treatment of ankle fractures involving the posterior malleolus. The approach can be well planned before the operation, is simple to perform, yields good fracture reduction and fixation, and has good prospects for clinical application.

Zheng, Hongming↗
DOE OSTI2025

Structure-Based Design of Small-Molecule Inhibitors of Human Interleukin-6

Human Interleukin-6 (hIL-6) is a pro inflammatory cytokine that binds to its receptor, IL-6Rα followed by binding to gp130 and subsequent dimerization to form a hexamer signaling complex. As a critical inflammation mediator, hIL-6 is associated with a diverse range of diseases and monoclonal antibodies in clinical use that either target IL-6Rα or hIL-6 to inhibit signaling. Here, we perform high-throughput structure-based computational screening using ensemble docking for small-molecule antagonists for which the target conformations were taken from 600 ns long molecular dynamics simulations of the apo protein. Prior knowledge of the contact sites from binary complex studies and experimental work was incorporated into the docking studies. The top 20 scoring ligands from the in silico studies after post analysis were subjected to in vitro functional assays. Among these compounds, the ligand with the second-highest calculated binding affinity experimentally showed an ~84% inhibitory effect on IL6-induced STAT3 reporter activity at 10 μM concentration. This finding may pave the way for designing small-molecule inhibitors of hIL-6 of therapeutic significance.

Human Interleukin-6↗
NASA NTRS1972

Visual motor response of crewmen during a simulated 90 day space mission as measured by the critical task battery

In order to test various components of a regenerative life support system and to obtain data on the physiological and psychological effects of long-duration exposure to confinement in a space station atmosphere, four carefully screened young men were sealed in space station simulator for 90 days. A tracking test battery was administered during the above experiment. The battery included a clinical test (critical instability task) related to the subject's dynamic time delay, and a conventional steady tracking task, during which dynamic response (describing functions) and performance measures were obtained. Good correlation was noted between the clinical critical instability scores and more detailed tracking parameters such as dynamic time delay and gain-crossover frequency. The comprehensive data base on human operator tracking behavior obtained in this study demonstrate that sophisticated visual-motor response properties can be efficiently and reliably measured over extended periods of time.

Allen, R. W.↗
NASA NTRS1973

Visual-motor response of crewmen during a simulated 90-day space mission as measured by the critical task battery

In order to test various components of a regenerative life support system and to obtain data on the physiological and psychological effects of long duration exposure to confinement in a space station atmosphere, four carefully screened young men were sealed in a space station simulator for 90 days and administered a tracking test battery. The battery included a clinical test (Critical Instability Task) designed to measure a subject's dynamic time delay, and a more conventional steady tracking task, during which dynamic response (describing functions) and performance measures were obtained. Good correlation was noted between the clinical critical instability scores and more detailed tracking parameters such as dynamic time delay and gain-crossover frequency. The levels of each parameter span the range observed with professional pilots and astronaut candidates tested previously. The chamber environment caused no significant decrement on the average crewman's dynamic response behavior, and the subjects continued to improve slightly in their tracking skills during the 90-day confinement period.

Allen, R. W.↗
NASA NTRS1988

Steady-state evoked potentials possibilities for mental-state estimation

The use of the human steady-state evoked potential (SSEP) as a possible measure of mental-state estimation is explored. A method for evoking a visual response to a sum-of-ten sine waves is presented. This approach provides simultaneous multiple frequency measurements of the human EEG to the evoking stimulus in terms of describing functions (gain and phase) and remnant spectra. Ways in which these quantities vary with the addition of performance tasks (manual tracking, grammatical reasoning, and decision making) are presented. Models of the describing function measures can be formulated using systems engineering technology. Relationships between model parameters and performance scores during manual tracking are discussed. Problems of unresponsiveness and lack of repeatability of subject responses are addressed in terms of a need for loop closure of the SSEP. A technique to achieve loop closure using a lock-in amplifier approach is presented. Results of a study designed to test the effectiveness of using feedback to consciously connect humans to their evoked response are presented. Findings indicate that conscious control of EEG is possible. Implications of these results in terms of secondary tasks for mental-state estimation and brain actuated control are addressed.

Junker, Andrew M.↗
NASA NTRS1997

Sequence information signal processor for local and global string comparisons

A sequence information signal processing integrated circuit chip designed to perform high speed calculation of a dynamic programming algorithm based upon the algorithm defined by Waterman and Smith. The signal processing chip of the present invention is designed to be a building block of a linear systolic array, the performance of which can be increased by connecting additional sequence information signal processing chips to the array. The chip provides a high speed, low cost linear array processor that can locate highly similar global sequences or segments thereof such as contiguous subsequences from two different DNA or protein sequences. The chip is implemented in a preferred embodiment using CMOS VLSI technology to provide the equivalent of about 400,000 transistors or 100,000 gates. Each chip provides 16 processing elements, and is designed to provide 16 bit, two's compliment operation for maximum score precision of between -32,768 and +32,767. It is designed to provide a comparison between sequences as long as 4,194,304 elements without external software and between sequences of unlimited numbers of elements with the aid of external software. Each sequence can be assigned different deletion and insertion weight functions. Each processor is provided with a similarity measure device which is independently variable. Thus, each processor can contribute to maximum value score calculation using a different similarity measure.

Peterson, John C.↗
DOE OSTI2025

Impacts of benchmarking choices on inferred model skill of the Arctic–Boreal terrestrial carbon cycle

Abstract Land surface models require continuous validation against observations to improve and reduce simulation uncertainty. However, inferred model performance can be heavily influenced by subjective choices made in the selection and application of observational data products. A key area often misrepresented by models is the Arctic–Boreal region, which is a potential tipping point region in Earth’s climate system due to large permafrost carbon stocks that are vulnerable to release with climate warming. We use the International Land Model Benchmarking (ILAMB) framework to evaluate how the model skill of TRENDY-v9 models varies based on the choice of observational-based benchmark and how benchmarks are applied in model evaluation. This analysis uses global datasets integrated into ILAMB and new, regionally-specific observational products from the Arctic–Boreal Vulnerability Experiment. Our results cover the overall time period of 1979–2019 and show that model scores can vary substantially depending on the data product applied, with higher model scores indicating better model performance against observations. The lowest model scores occur when benchmarked against regional, compared to global, datasets. We also evaluate observed and modeled functional relationships between ecosystem respiration and air temperature and between gross primary production and precipitation. Here, we find that the magnitude and shape of the responses are strongly impacted by the choice of observational dataset and the approach used to construct the functional relationship benchmark. These results suggest that model evaluation studies could conclude a false sense of model skill if only using a single benchmark data product or if not applying regional data products when performing a regional model analysis. Collectively, our findings highlight the influence of benchmarking choices on model evaluation and point to the need for benchmarking guidelines when assessing model skill.

Poe, Jeralyn (ORCID:0000000318495278)↗
NASA NTRS1974

Video requirements for remote medical diagnosis

Minimal television system requirements for medical telediagnosis were studied. The experiment was conducted with the aid of a simulated telemedicine system. The first step involved making high quality videotape recordings of actual medical examinations conducted by a skilled nurse under the direction of a physician watching on closed circuit television. These recordings formed the baseline for the study. Next, these videotape recordings were electronically degraded to simulate television systems of less than broadcast quality. Finally, the baseline and degraded video recordings were shown (via a statistically randomized procedure) to a large number of physicians who attempted to reach a correct medical diagnosis and to visually recognize key physical signs for each patient. By careful scoring and analysis of the results of these viewings, the pictorial and diagnostic limitations as a function of technical video characteristics were to be defined.

Davis, J. G.↗
NASA NTRS2007

Artificial Gravity as a Multi-System Countermeasure: Effects on Cognitive Function

The Space Flight Cognitive Assessment Tool for Windows (WinSCAT) is a medical requirement on the International Space Station, and its purpose is to evaluate cognitive functioning after physical insult (e.g., head trauma, decompression sickness, exposure to toxic gases, medication side effects). The current objective is to assess cognitive functioning in a long duration space mission analog environment where Artificial Gravity is being applied as a countermeasure in a Bed Rest study. Methods: Fifteen male subjects (8 treatment and 7 control) who participated in 21 days of -6 degree head-down bed rest were assessed. Three practice and three baseline WinSCAT test sessions were administered during the pre-bed rest phase of study participation. During the bed rest phase, the WinSCAT test was scheduled every other day, following the centrifuge, for a total of 10 test sessions. (The treatment group received 60 minutes of centrifugation each day during the 21 days of bed rest. The control subjects were strapped to the centrifuge for the same length of time as the treatment group but were not spun.) During the post-bed rest (reconditioning) phase, the test was administered 4 times. Results: Individual differences were found both within and between the treatment and control groups. After controlling for the number of subjects in each group, the treatment group accounted for more off-nominal WinSCAT scores than the control group. Conclusions:There is some preliminary evidence that centrifuge spinning might negatively impact cognitive functioning. However, due to sample size limitations, it cannot be ascertained whether there were significant differences in cognitive performance between the treatment and control groups. If centrifugation had a negative effect on cognitive functioning, consistent decrements would be expected to be found with all treatment subjects across time. Individual differences in underlying cognitive ability and motivation level are other possible explanations for the results found in this study.

Sipes, Walter E.↗
NASA NTRS1994

Stochastic decision analysis

Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given amount of the best score. Formulas are also derived for the probability that one concept's total score is within a given amount of a second concept's total score. These probabilistic calculations provide more realistic data entry and output information for designers, enabling designers to better determine which concepts to eliminate and which concepts to retain at the decision points of each design phase.

Lacksonen, Thomas A.↗