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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development of Data-Driven Models for Performance Prediction and Chemical Dosing of a Full-Scale Controlled Phosphorus Precipitation Reactor

This study evaluated the use of data-driven models to improve control of a struvite precipitation reactor that removes phosphorus from wastewater while producing a fertilizer product. The researchers developed predictive models for influent orthophosphate concentration, effluent orthophosphate concentration, and phosphorus removal using operational data from a full-scale MagPrex™ reactor at a water resource recovery facility in Denver, Colorado. Model predictions were used to recommend magnesium chloride dosing adjustments needed to achieve a target effluent phosphorus concentration. Several machine learning approaches were tested, with ridge regression providing the best predictions for influent orthophosphate concentration and phosphorus removal, and XGBoost providing the best predictions for effluent orthophosphate concentration. Simulation results indicated that the decision-support approach could correctly identify dosing adjustments in most cases and reduce chemical use. Full-scale implementation achieved lower accuracy due to changing operating conditions and limited historical data in some operating ranges. Here, the results demonstrate the potential of data-driven tools to support phosphorus recovery process control while also identifying practical limitations that affect deployment in full-scale systems.

42 ENGINEERING↗
DOE OSTI2019

Tissue sampling in the era of precision medicine: comparison of percutaneous biopsies performed for clinical trials or tumor genomics versus routine clinical care

Purpose: The purpose of the study was to determine if patients undergoing percutaneous biopsy for genetic profiling are undergoing more biopsies (procedures, passes per procedure), or experiencing more procedure-related complications. Methods: 60 patients undergoing biopsy procedures for genetic profiling were retrospectively compared with 60 consecutive control patients undergoing routine biopsies. Procedural details and related complications were collected. Results were analyzed using t-tests and logistic regression. Results: Biopsied organs included mainly lung (n = 31), liver (n = 50), and lymph nodes (n = 18). The average number of core biopsy passes was 3.45 in the study group and 2.18 in the control group (0.73, 1.81; p = 0.0001). The average study patient underwent 1.44 biopsy procedures by radiology from 2016 to 2017, whereas the average control patient underwent 1.08 (0.1657, 0.5010, p = 0.0002). Results were similar when looking at the subset of patients undergoing liver biopsies. In our cohort of 120 patients total, only 6 complications were noted. There were 4 complications in the control patients and 2 complications in the study patients, all of which were pneumothoraces in patients undergoing lung biopsy; only 2 of these required treatment. The odds ratio for a complication occurring from an increase in one core biopsy is 1.07 (0.601, 1.573; p = 0.775), suggesting no significant relationship among the number of biopsies taken and the probability of complication in this cohort. Conclusions: Patients being biopsied for genetic profiling or clinical study enrollment are undergoing more biopsy procedures and more biopsy passes per procedure, but are not experiencing a detectable increased rate of complications in this small cohort, single-center study.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Can magnetic resonance imaging differentiate among transurethral bulking agent, urethral diverticulum, and periurethral cyst?

Purpose: To evaluate magnetic resonance imaging findings that differentiate among periurethral bulking agents (primarily collagen), urethral diverticulum, and periurethral cyst. Methods: We searched our radiologic database retrospectively from 2001 to 2017 for periurethral cystic lesions, identifying a total of 50 patients with 68 lesions. Final diagnoses in 68 lesions were bulking agents (27), urethral diverticula (29), and periurethral cysts (12). Two abdominal radiologists, blinded to clinical history, independently evaluated T1, T2, and post-contrast images. The readers assessed number, morphological features, location, connection to urethra and mass effect, signal intensity, and enhancement for each lesion. Fisher exact test and logistic regression analysis were performed for each univariate significant feature. The operative and pathologic reports were the reference standard. Results: Magnetic resonance imaging features found more often in bulking agents versus urethral diverticulum were multiple lesions (P = 0.011), upper or upper-mid-urethral location (P ≤ 0.0001), lack of internal fluid/fluid level (P = 0.002), no urethral connection (P = 0.005), T1 isointensity, and T2 mild hyperintensity compared to muscles but lower T2 signal than urine (P < 0.0001). Most cases of urethral diverticula and periurethral cysts were detected at mid- and lower urethra. Urethral diverticula were larger than bulking agents and periurethral cysts (P = 0.005 and P = 0.023) (mean diameter = 24, 16, 15 mm, respectively). Most bulking agents (93%) and urethral diverticula (90%) showed mass effect on urethra, while periurethral cysts (75%) did not (P < 0.0001). Conclusion: Signal intensity and lesion characterization on magnetic resonance imaging can significantly differentiate bulking agent from urethral diverticulum and periurethral cyst. Radiologists should consider differential diagnosis of a bulking agent, especially when distinguishing characteristics described here are present to prevent incorrect diagnosis and ultimately unnecessary surgical intervention.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Part-scale microstructure prediction for laser powder bed fusion Ti-6Al-4V using a hybrid mechanistic and machine learning model

Laser powder bed fusion (LPBF) Ti-6Al-4V is widely studied for use in structural applications in aerospace and medical industries, but mechanical anisotropy and microstructural inhomogeneity prohibits its wider adoption. Although successful microstructure prediction models have been developed, a remaining challenge is their limited integration across length/time scales and validation by experimental studies. Here, this work proposes a physics-augmented machine learning surrogate model to unite predictions of LPBF temperature, β phase morphology and texture, and α/α’ formation into a single framework that is calibrated and validated with experiments. First, a phase field (PF) model of the martensitic β→α’ transformation is developed and calibrated using data from in-situ synchrotron cyclic heating/cooling studies quantifying the variation of α phase fraction with time. In parallel, an established finite difference-Monte Carlo (FDMC) model predicts the part-scale temperature profile and β grain formation during solidification. A dataset is developed using LPBF cyclic temperature descriptors from the FDMC model as inputs and corresponding α/α’ phase fraction and width from the PF model as outputs. Five machine learning (ML) regression models are tested and optimized, having mean absolute error in testing ≤ 4 %, and the k-nearest neighbors (KNN) model is selected as the best performing. The KNN model is called at the nodal level during post-processing of the FDMC model to replace and downscale the response of the PF model. The combined agility and accuracy of the hybrid FDMC-ML model enables part-scale microstructure predictions that can be further used for property predictions to accelerate AM process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Perceptions of Seasonal Influenza Vaccine Among U.S. Army Civilians and Dependents in the Kaiserslautern Military Community: A Mixed-Methods Survey

ABSTRACT Introduction Influenza is a globally occurring viral respiratory infection that can lead to hospitalizations and death. An influenza outbreak can interfere with combat readiness in a military setting, as the infection can incapacitate soldiers. Vaccination remains the most effective tool to prevent and mitigate seasonal influenza. Although influenza vaccinations for U.S. Army soldiers can be monitored through military health systems, those systems cannot capture DoD civilians and Army dependents who may not use military health services. This study aims to gauge flu vaccine uptake and perceptions in U.S. Army civilians and dependents. Materials and Methods An online survey was e-mailed to civilian and dependent enrollees of Landstuhl Regional Medical Center. The survey contained 24 questions pertaining to demographics, vaccine history, history of the flu, and beliefs toward vaccines. Chi-square tests, t-tests, and logistic regressions were performed to investigate the association between demographic, behavior, and belief factors with vaccine uptake. Free-text answers were coded and categorized by themes. Results Over 70% of respondents were vaccinated for the flu. There were differences between vaccinated and unvaccinated respondents regarding their perceptions of barriers to vaccination, benefits of the flu vaccine, severity of flu symptoms, and personal risk of getting ill with the flu. After controlling for confounders, flu vaccination in the previous season and healthcare worker status were associated with increased vaccine uptake, while perceived barriers to influenza vaccination were associated with decreased vaccine uptake. Conclusions Flu vaccine uptake may be increased by increasing access to vaccination, promoting vaccination and addressing concerns at the provider level, and engaging positively framed public messaging. Increasing flu vaccine uptake is of particular importance as the flu season approaches during the COVID-19 (Coronavirus disease 2019) pandemic.

Burns, MSC, Veronica M.↗
DOE OSTI2024

Signatures of cysteine oxidation on muscle structural and contractile proteins are associated with physical performance and muscle function in older adults: Study of Muscle, Mobility and Aging (SOMMA)

Oxidative stress is considered a contributor to declining muscle function and mobility during aging; however, the underlying molecular mechanisms remain poorly described. We hypothesized that greater levels of cysteine (Cys) oxidation on muscle proteins are associated with decreased measures of mobility. Herein, we applied a novel redox proteomics approach to measure reversible protein Cys oxidation in vastus lateralis muscle biopsies collected from 56 subjects in the Study of Muscle, Mobility and Aging (SOMMA), a community-based cohort study of individuals aged 70 years and older. We tested whether levels of Cys oxidation on key muscle proteins involved in muscle structure and contraction were associated with muscle function (leg power and strength), walking speed, and fitness (VO 2 peak on cardiopulmonary exercise testing) using linear regression models adjusted for age, sex, and body weight. Higher oxidation levels of select nebulin Cys sites were associated with lower VO 2 peak, while greater oxidation of myomesin-1, myomesin-2, and nebulin Cys sites was associated with slower walking speed. Higher oxidation of Cys sites in key proteins such as myomesin-2, alpha-actinin-2, and skeletal muscle alpha-actin were associated with lower leg power and strength. We also observed an unexpected correlation (R = 0.48) between a higher oxidation level of eight Cys sites in alpha-actinin-3 and stronger leg power. Despite this observation, the results generally support the hypothesis that Cys oxidation of muscle proteins impairs muscle power and strength, walking speed, and cardiopulmonary fitness with aging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Crowd-based spatial risk assessment of urban flooding: Results from a municipal flood hotline in Detroit, MI

Climate change is increasing the frequency and intensity of extreme precipitation events, raising the risk of urban flood disasters. This study uses a crowd-sourced municipal call database to characterize the spatial distribution of flood risk in Detroit, MI. Call data including dates and addresses were obtained from the City of Detroit Department of Public Works for 2021. Calls were mapped and aggregated to census tract counts and merged with neighborhood-level data. Associations of predictors with flood calls were tested using spatial regression models. Flooding calls were located throughout the city but were concentrated in specific areas. Multivariate models of census tract level call counts indicated that increased poverty and Black, immigrant, and older residents were positively associated with flood calls, while increased elevation was associated with protective effects. Longer distances from waste water interceptors were associated with higher risk for calls. Crowd-sourced flood hotline call data can be used for effective spatial flood risk assessment. Though flooding occurs throughout the city of Detroit, infrastructural, neighborhood, and household factors influence flooding extent. Limitations included the self-reported nature of calls. Future modeling efforts might include input from local stakeholders to improve spatial risk assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Influence of amplitude-related perfusion parameters in the parotid glands by non-fat-saturated dynamic contrast-enhanced magnetic resonance imaging

Purpose: To verify whether quantification of parotid perfusion is affected by fat signals on non-fat-saturated (NFS) dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and whether the influence of fat is reduced with fat saturation (FS). Methods: This study consisted of three parts. First, a retrospective study analyzed DCE-MRI data previously acquired on different patients using NFS (n = 18) or FS (n = 18) scans. Second, a phantom study simulated the signal enhancements in the presence of gadolinium contrast agent at six concentrations and three fat contents. Finally, a prospective study recruited nine healthy volunteers to investigate the influence of fat suppression on perfusion quantification on the same subjects. Parotid perfusion parameters were derived from NFS and FS DCE-MRI data using both pharmacokinetic model analysis and semiquantitative parametric analysis. T tests and linear regression analysis were used for statistical analysis with correction for multiple comparisons. Results: NFS scans showed lower amplitude-related parameters, including parameter A, peak enhancement (PE), and slope than FS scans in the patients (all with P < 0.0167). The relative signal enhancement in the phantoms was proportional to the dose of contrast agent and was lower in NFS scans than in FS scans. The volunteer study showed lower parameter A (6.75 ± 2.38 a.u.), PE (42.12% ± 14.87%), and slope (1.43% ± 0.54% s{sup −1}) in NFS scans as compared to 17.63 ± 8.56 a.u., 104.22% ± 25.15%, and 9.68% ± 1.67% s{sup −1}, respectively, in FS scans (all with P < 0.005). These amplitude-related parameters were negatively associated with the fat content in NFS scans only (all with P < 0.05). Conclusions: On NFS DCE-MRI, quantification of parotid perfusion is adversely affected by the presence of fat signals for all amplitude-related parameters. The influence could be reduced on FS scans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP1-11: Predictors of Cardiac and Lung Dose Sparing in DIBH for Left Breast Treatment

Purpose: This retrospective study of left sided whole breast radiation therapy (RT) patients investigates possible predictive parameters correlating to cardiac and left lung dose sparing by deep inspiration breath-hold (DIBH) technique compared to free-breathing (FB). Methods: Thirty-one patients having both DIBH and FB CT scans were included in the study. All patients were planned with a standard step-and-shoot tangential technique using MV photons, with prescription of 50Gy or 50.4Gy. The displacement of the breath hold sternal mark during DIBH, the cardiac contact distances of the axial (CCDax) and parasagittal (CCDps) planes, and lateral-heart-to-chest (LHC) distance on FB CT scans were measured. Lung volumes, mean dose and dose-volume histograms (V5, V10 and V20) were analyzed and compared for heart and left lung for both FB and DIBH techniques. Correlation analysis was performed to identify the predictors for heart and left lung dose sparing. Two-tailed Student’s t-test and linear regression were used for data analysis with significance level of P≤0.05. Results: All dosimetric metrics for the heart and left lung were significantly reduced (P<0.01) with DIBH. Breath hold sternal mark displacement ranged from 0.4–1.8 cm and correlated with mean (P=0.05) and V5 (P=0.02) of heart dose reduction by DIBH. FB lung volume showed correlation with mean lung dose reduction by DIBH (P<0.01). The FB-CCDps and FB-LHC distance had strong positive and negative correlation with FB mean heart dose (P<0.01) and mean heart dose reduction by DIBH (P<0.01), respectively. FB-CCDax showed no correlation with dosimetric changes. Conclusion: DIBH technique has been shown to reduce dose to the heart and left lung. In this patient cohort, FB-CCDps, FB-LHC distance, and FB lung volume served as significant predictors for heart and left lung. These parameters can be further investigated to be used as a tool to better select patients who will benefit from DIBH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Sulfur TES ML [SWR-23-02]

Sulfur TES ML contains code originally created to develop surrogate ML models to mimic the utility of CFD simulations of Sulfur TES systems. It has been adapted to provide a comprehensive package for building, training, validating, testing, and optimizing regression models with customizable features and targets.

Menear, Kevin↗
DOE OSTI2020

BISON TRISO Modeling Advancements and Validation to AGR-1 Data

BISON is a finite element-based nuclear fuel performance code. Among its unique characteristics are its ability to model 1D, 2D, and 3D geometries and its applicability to a wide variety of nuclear fuels. For the last eight years, BISON has included a beginning capability to model tri-structural isotropic (TRISO) fuel. Recently, interest in TRISO fuel has grown, and a significant effort has been made to improve BISON’s capabilities in this area. Capability development has occurred for each material present in TRISO fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. New elastic, creep, swelling, thermal expansion, thermal conductivity, and fission gas release (FGR) models are available. New models for the graphite matrix are also now available. Another important addition is the ability to perform statistical failure analysis of large samples of fuel particles. This new capability, which continues to grow, enables evaluation of failure due to pressure or crack formation by analyzing many thousands of particles. This enables realistic calculations of fission product release from the many particles in a TRISO-fueled reactor. These capabilities were checked via regression and verification tests. A large number of code benchmarking problems were also run, showing that BISON’s results closely match those of other software tools. Finally, a significant validation effort was completed in which fission product release, measured as part of the AGR-1 capsule experiments, was compared to BISON outputs. BISON outputs compared very well to the experimental data and to PARFUME results. Interest in BISON’s TRISO capabilities is growing, with the U.S. Nuclear Regulatory Commission (NRC) and Westinghouse Electric Company receiving training during the past year. Multiple other entities have expressed interest in or are actively using BISON. Kairos Power, LLC, has a strong partnership with Idaho National Laboratory (INL) regarding the use of BISON for TRISO analysis. While its capabilities still continue to grow, BISON has already become a powerful tool for TRISO analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Supplemental Data for the Manuscript: Quantification of Manganese for ChemCam Mars and Laboratory Spectra Using a Multivariate Model

This dataset includes all of the data needed to validate and/or reproduce the manganese calibration model described in the manuscript. The reference database contains metadata for the new Mn-bearing standards, minerals, and mixtures that are > 2.9 wt.% MnO. In addition, the files include the MnO composition data for all standards used, non-normalized spectral data, mean peak area spectrum, results of outlier determination, RMSECV data, regression vectors, and Test Set predictions.

58 GEOSCIENCES↗
NASA NTRS1977

An empirical model for ocean radar backscatter and its application in inversion routine to eliminate wind speed and direction effects

Several regression models were tested to explain the wind direction dependence of the 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data. The models consider the radar backscatter as a harmonic function of wind direction. The constant term accounts for the major effect of wind speed and the sinusoidal terms for the effects of direction. The fundamental accounts for the difference in upwind and downwind returns, while the second harmonic explains the upwind-crosswind difference. It is shown that a second harmonic model appears to adequately explain the angular variation. A simple inversion technique, which uses two orthogonal scattering measurements, is also described which eliminates the effect of wind speed and direction. Vertical polarization was shown to be more effective in determining both wind speed and direction than horizontal polarization.

Dome, G. J.↗
NASA NTRS1983

Consistent Tolerance Bounds for Statistical Distributions

Assumption that sample comes from population with particular distribution is made with confidence C if data lie between certain bounds. These "confidence bounds" depend on C and assumption about distribution of sampling errors around regression line. Graphical test criteria using tolerance bounds are applied in industry where statistical analysis influences product development and use. Applied to evaluate equipment life.

Mezzacappa, M. A.↗
NASA NTRS1982

Tropical cyclone track and genesis forecasting using satellite microwave sounder data

Although many dynamical and statistical prediction schemes are available to forecasters, tropical cyclone track errors are still large. One primary difficulty is that tropical cyclones exist over the data-sparse tropical oceans. Satellite sounders, however, routinely provide numerous data over these areas. Mean layer temperatures from the Scanning Microwave Spectrometer on board the Nimbus 6 satellite are decomposed using empirical orthogonal functions, and the expansion coefficients are related to deviations from the persistence forecast location, to speed change, to direction change and to intensity change. The significance of the regression equations is tested by a null hypothesis of zero correlation coefficient. It appears that significant information about tropical cyclone motion exists in the satellite-estimated mean layer temperatures, especially at upper levels. A physical interpretation of the statistical results is offered, and a one-storm-out independent test is used to test the stability of the equations. Finally, some further work is suggested.

Kidder, S. Q.↗
NASA NTRS1990

Early experiences building a software quality prediction model

Early experiences building a software quality prediction model are discussed. The overall research objective is to establish a capability to project a software system's quality from an analysis of its design. The technical approach is to build multivariate models for estimating reliability and maintainability. Data from 21 Ada subsystems were analyzed to test hypotheses about various design structures leading to failure-prone or unmaintainable systems. Current design variables highlight the interconnectivity and visibility of compilation units. Other model variables provide for the effects of reusability and software changes. Reported results are preliminary because additional project data is being obtained and new hypotheses are being developed and tested. Current multivariate regression models are encouraging, explaining 60 to 80 percent of the variation in error density of the subsystems.

Agresti, W. W.↗
NASA NTRS1993

Effect of Malmquist bias on correlation studies with IRAS data base

The relationships between galaxy properties in the sample of Trinchieri et al. (1989) are reexamined with corrections for Malmquist bias. The linear correlations are tested and linear regressions are fit for log-log plots of L(FIR), L(H-alpha), and L(B) as well as ratios of these quantities. The linear correlations for Malmquist bias are corrected using the method of Verter (1988), in which each galaxy observation is weighted by the inverse of its sampling volume. The linear regressions are corrected for Malmquist bias by a new method invented here in which each galaxy observation is weighted by its sampling volume. The results of correlation and regressions among the sample are significantly changed in the anticipated sense that the corrected correlation confidences are lower and the corrected slopes of the linear regressions are lower. The elimination of Malmquist bias eliminates the nonlinear rise in luminosity that has caused some authors to hypothesize additional components of FIR emission.

Verter, Frances↗