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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

MO-E-17A-06: Organ Dose in Abdomen-Pelvis CT: Does TG 111 Equilibrium Dose Concept Better Accounts for KVp Dependence Than Conventional CTDI?

Purpose: In CT imaging, a desirable quality assurance (QA) dose quantity should account for the dose variability across scan parameters and scanner models. Recently, AAPM TG 111 proposed to use equilibrium dose-pitch product, in place of CT dose index (CTDI100), for scan modes involving table translation. The purpose of this work is to investigate whether this new concept better accounts for the kVp dependence of organ dose than the conventional CTDI concept. Methods: The adult reference female extended cardiac-torso (XCAT) phantom was used for this study. A Monte Carlo program developed and validated for a 128-slice CT system (Definition Flash, Siemens Healthcare) was used to simulate organ dose for abdomenpelvis scans at five tube voltages (70, 80, 100, 120, 140 kVp) with a pitch of 0.8 and a detector configuration of 2x64x0.6 mm. The same Monte Carlo program was used to simulate CTDI100 and equilibrium dose-pitch product. For both metrics, the central and peripheral values were used together with helical pitch to calculate a volume-weighted average, i.e., CTDIvol and (Deq)vol, respectively. Results: While other scan parameters were kept constant, organ dose depended strongly on kVp; the coefficient of variation (COV) across the five kVp values ranged between 70–75% for liver, spleen, stomach, pancreas, kidneys, colon, small intestine, bladder, and ovaries, all of which were inside the primary radiation beam. One-way analysis of variance (ANOVA) for the effect of kVp was highly significant (p=3e−30). When organ dose was normalized by CTDIvol, the COV across the five kVp values reduced to 7–16%. The effect of kVp was still highly significant (p=4e−4). When organ dose was normalized by (Deq)vol, the COV further reduced to 4−12%. The effect of kVp was borderline significant (p=0.04). Conclusion: In abdomen-pelvis CT, TG 111 equilibrium dose concept better accounts for kVp dependence than the conventional CTDI. This work is supported by a faculty startup fund from the Cleveland State University.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-C-12A-05: Repeatability Study of Reduced Field-Of-View Diffusion-Weighted MRI On Human Thyroid Gland

Purpose: To investigate the repeatability of reduced field-of-view diffusion-weighted imaging (rFOV DWI) in quantifying apparent diffusion coefficients (ADCs) for human thyroid glands in a clinical setting. Methods: Nine healthy human volunteers were enrolled and underwent 3T MRI exams. For each volunteer, 3 longitudinal exams (2 weeks apart) with 2 repetitive sessions within each exam, including rFOV and conventional full field-of-view (fFOV) DWI scans, were performed. In the acquired DWI images, a fixed-size region of interest (ROI; diameter=8mm) was placed on thyroid glands to calculate ADC. ADC was calculated using a monoexponential function with a noise correction scheme. The repeatability of ADC was assessed by using coefficient variation (CV) across sessions or exams, which was defined to be: r = 1-CV, 0 < r < 1, where CV=STD/m, STD is the standard deviation of ADC, and m is the average of ADC across sessions or exams. An experienced radiologist assessed and scored rFOV and fFOV DW images based on image characteristics (1, nondiagnostic; 2, poor; 3, satisfactory; 4, good; and 5, excellent).Analysis of variance (ANOVA) was performed to compare ADC values, CV of ADC, repeatability of ADC across sessions and exams, and radiologic scores between rFOV and fFOV DWI techniques. Results: There was no significant difference in ADC values across sessions and exams either in rFOV or fFOV DWI. The average CVs of both rFOV and fFOV DWI were less than 13%. The repeatability of ADC measurement between rFOV and fFOV DWI was not significantly different. The overall image quality was significantly higher with rFOV DWI than with fFOV DWI. Conclusion: This study suggested that ADCs from both rFOV and fFOV DWI were repeatable, but rFOV DWI had superior imaging quality for human thyroid glands in a clinical setting.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

4D-CT scans reveal reduced magnitude of respiratory liver motion achieved by different abdominal compression plate positions in patients with intrahepatic tumors undergoing helical tomotherapy

Purpose: While abdominal compression (AC) can be used to reduce respiratory liver motion in patients receiving helical tomotherapy for hepatocellular carcinoma, the nature and extent of this effect is not well described. The purpose of this study was to evaluate the changes in magnitude of three-dimensional liver motion with abdominal compression using four-dimensional (4D) computed tomography (CT) images of several plate positions. Methods: From January 2012 to October 2015, 72 patients with intrahepatic carcinoma and divided into four groups underwent 4D-CT scans to assess respiratory liver motion. Of the 72 patients, 19 underwent abdominal compression of the cephalic area between the subxiphoid and umbilicus (group A), 16 underwent abdominal compression of the caudal region between the subxiphoid area and the umbilicus (group B), 11 patients underwent abdominal compression of the caudal umbilicus (group C), and 26 patients remained free breathing (group D). 4D-CT images were sorted into ten-image series, according to the respiratory phase from the end inspiration to the end expiration, and then transferred to treatment planning software. All liver contours were drawn by a single physician and confirmed by a second physician. Liver relative coordinates were automatically generated to calculate the liver respiratory motion in different axial directions to compile the 10 ten contours into a single composite image. Differences in respiratory liver motion were assessed with a one-way analysis of variance test of significance. Results: The average respiratory liver motion in the Y axial direction was 4.53 ± 1.16, 7.56 ± 1.30, 9.95 ± 2.32, and 9.53 ± 2.62 mm in groups A, B, C, and D, respectively, with a significant change among the four groups (p < 0.001). Abdominal compression was most effective in group A (compression plate on the subxiphoid area), with liver displacement being 2.53 ± 0.93, 4.53 ± 1.16, and 2.14 ± 0.92 mm on the X-, Y-, and Z-axes, respectively. There was no significant difference in respiratory liver motion between group C (displacement: 3.23 ± 1.47, 9.95 ± 2.32, and 2.92 ± 1.10 mm on the X-, Y-, and Z-axes, respectively) and group D (displacement: 3.35 ± 1.55, 9.53 ± 2.62, and 3.35 ± 1.73 mm on the X-, Y-, and Z-axes, respectively). Abdominal compression was least effective in group C (compression on caudal umbilicus), with liver motion in this group similar to that of free-breathing patients (group D). Conclusions: 4D-CT scans revealed significant liver motion control via abdominal compression of the subxiphoid area; however, this control of liver motion was not observed with compression of the caudal umbilicus. The authors, therefore, recommend compression of the subxiphoid area in patients undergoing external radiotherapy for intrahepatic carcinoma.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-201-09: Predicting Accelerator Dysfunction

Purpose: To develop an integrated statistical process control (SPC) framework using digital performance and component data accumulated within the accelerator system that can detect dysfunction prior to unscheduled downtime. Methods: Seven digital accelerators were monitored for twelve to 18 months. The accelerators were operated in a ‘run to failure mode’ with the individual institutions determining when service would be initiated. Institutions were required to submit detailed service reports. Trajectory and text log files resulting from a robust daily VMAT QA delivery were decoded and evaluated using Individual and Moving Range (I/MR) control charts. The SPC evaluation was presented in a customized dashboard interface that allows the user to review 525 monitored parameters (480 MLC parameters). Chart limits were calculated using a hybrid technique that includes the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. The individual (I) grand mean values and control limit ranges of the I/MR charts of all accelerators were compared using statistical (ranked analysis of variance (ANOVA)) and graphical analyses to determine consistency of operating parameters. Results: When an alarm or warning was directly connected to field service, process control charts predicted dysfunction consistently on beam generation related parameters (BGP)– RF Driver Voltage, Gun Grid Voltage, and Forward Power (W); beam uniformity parameters – angle and position steering coil currents; and Gantry position accuracy parameter: cross correlation max-value. Control charts for individual MLC – cross correlation max-value/position detected 50% to 60% of MLCs serviced prior to dysfunction or failure. In general, non-random changes were detected 5 to 80 days prior to a service intervention. The ANOVA comparison of BGP determined that each accelerator parameter operated at a distinct value. Conclusion: The SPC framework shows promise. Long term monitoring coordinated with service will be required to definitively determine the effectiveness of the model. Varian Medical System, Inc. provided funding in support of the research presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Load Deflection Data (LDDATA)

The current data set is load deflection data (Stress vs strain for compression stress and stress vs elongation for tension stress) from a material test. The goal of the test was to characterize this rubber-like material by looking at different variables: sample creation process, anisotropy, temperature, etc. The data will be used with the Texas A&M Online Research Experience for Undergraduates (O-REU) program. This program is joint with LANL. The student is not an official LANL student so they will not be able to access data and documents on the yellow. The load deflection data set is unclassified and will be sent to the student for analysis. Analysis will include curve fitting, scalar value analysis (stiffness, toughness, etc.) and analysis of variance to determine what variables statistically affect the response while correcting for covariates (temperature soak time and humidity). Data will be stored as Matlab structs and as HDF5 files. Same data, different formats.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Near-Efficient and Non-Asymptotic Multiway Inference

We establish non-asymptotic efficiency guarantees for tensor decomposition–based inference in count data models. Under a Poisson framework, we consider two related goals: (i) parametric inference , the estimation of the full distributional parameter tensor, and (ii) multiway analysis , the recovery of its canonical polyadic (CP) decomposition factors. Our main result shows that in the rank-one setting, a rank-constrained maximum-likelihood estimator achieves multiway analysis with variance matching the Cramér–Rao Lower Bound (CRLB) up to absolute constants and logarithmic factors. This provides a general framework for studying “near-efficient” multiway estimators in finite-sample settings. For higher ranks, we illustrate that our multiway estimator may not attain the CRLB; nevertheless, CP-based parametric inference remains nearly minimax optimal, with error bounds that improve on prior work by offering more favorable dependence on the CP rank. Numerical experiments corroborate near-efficiency in the rank-one case and highlight the efficiency gap in higher-rank scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Experimental Studies on Wood Pellets Combustion in a Fixed Bed Combustor Using Taguchi Method

The combustion of wood pellets in a fixed bed combustor of a 20 kW capacity domestic pellet boiler was tested according to several factors including Power, Excess Air (EA), Primary/Secondary air Split Ratio (SR) and Grate Area (GA). The Taguchi method was applied to program the experimental design. Several parameters were measured, including gas emissions (CO), fuel bed temperature (measured at 4 different heights), and efficiency. The experimental results show that the lower CO emission and the higher efficiency were obtained at medium thermal loads and the highest temperature on the fuel bed was obtained at about ¼ of its height (15 mm). The results obtained from the analysis of variance (ANOVA) show that the SR and the Power are the most important factors contributing to the CO reduction and also increase the fuel bed temperature.

Castro, Carlos↗
DOE OSTI2020

Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data

High-throughput phenotyping using high spatial, spectral, and temporal resolution remote sensing (RS) data has become a critical part of the plant breeding chain focused on reducing the time and cost of the selection process for the “best” genotypes with respect to the trait(s) of interest. In this paper, the potential of accurate and reliable sorghum biomass prediction using visible and near infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data as well as light detection and ranging (LiDAR) data acquired by sensors mounted on UAV platforms is investigated. Predictive models are developed using classical regression-based machine learning methods for nine experiments conducted during the 2017 and 2018 growing seasons at the Agronomy Center for Research and Education (ACRE) at Purdue University, Indiana, USA. The impact of the regression method, data source, timing of RS and field-based biomass reference data acquisition, and the number of samples on the prediction results are investigated. R2 values for end-of-season biomass ranged from 0.64 to 0.89 for different experiments when features from all the data sources were included. Geometry-based features derived from the LiDAR point cloud to characterize plant structure and chemistry-based features extracted from hyperspectral data provided the most accurate predictions. Evaluation of the impact of the time of data acquisition during the growing season on the prediction results indicated that although the most accurate and reliable predictions of final biomass were achieved using remotely sensed data from mid-season to end-of-season, predictions in mid-season provided adequate results to differentiate between promising varieties for selection. The analysis of variance (ANOVA) of the accuracies of the predictive models showed that both the data source and regression method are important factors for a reliable prediction; however, the data source was more important with 69% significance, versus 28% significance for the regression method.

09 BIOMASS FUELS↗
DOE OSTI2021

A Comprehensive Open-Source R Software For Statistical Metrology Calculations: From Uncertainty Evaluation To Risk Analysis

Whether calibrating equipment or inspecting products on the factory floor, metrology requires many complicated statistical calculations to achieve a full understanding and evaluation of measurement uncertainty and quality. In order to assist its workforce in performing these calculations in a consistent and rigorous way, the Primary Standards Lab at Sandia National Laboratories (SNL) has developed a free and open-source software package for computing various metrology calculations from uncertainty propagation to risk analysis. In addition to propagating uncertainty through a measurement model using the well-known Guide to Expression of Uncertainty in Measurement or Monte Carlo approaches, evaluating the individual Type A and Type B uncertainty components that go into the measurement model often requires other statistical methods such as analysis of variance or determining uncertainty in a fitted curve. Once the uncertainty in a measurement has been calculated, it is usually evaluated from a risk perspective to ensure the measurement is suitable for making a particular conformance decision. Finally, SNL’s software can perform all these calculations in a single application via an easy-to-use graphical interface, where the different functions are integrated so the results of one calculation can be used as inputs to another calculation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Large-Scale Inference of Multivariate Regression for Heavy-Tailed and Asymmetric Data

Large-scale multivariate regression is a fundamental statistical tool with a wide range of applications. Here, this study considers the problem of simultaneously testing a large number of general linear hypotheses, encompassing covariate-effect analysis, analysis of variance, and model comparisons. The challenge that accompanies a large number of tests is the ubiquitous presence of heavy-tailed and/or highly skewed measurement noise, which is the main reason for the failure of conventional least squares-based methods. For large-scale multivariate regression, we develop a set of robust inference methods to explore data features such as heavy tailedness and skewness, which are not visible to least squares methods. The new testing procedure is based on the data-adaptive Huber regression and a new covariance estimator of regression estimates. Under mild conditions, we show that our methods produce consistent estimates of the false discovery proportion. Extensive numerical experiments and an empirical study on quantitative linguistics demonstrate the advantage of the proposed method over many state-of-the-art methods when the data are generated from heavy-tailed and/or skewed distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Experimental trials of species-specific bat flight responses to an ultrasonic deterrent

Unintended consequences of increasing wind energy production include bat mortalities from wind turbine blade strikes. Ultrasonic deterrents (UDs) have been developed to reduce bat mortalities at wind turbines. Our goal was to experimentally assess the species-specific effectiveness of three emission treatments from the UD developed by NRG Systems. We conducted trials in a flight cage measuring approximately 60 m × 10 m × 4.4 m (length × width × height) from July 2020 to May 2021 in San Marcos, Texas, USA. A single UD was placed at either end of the flight cage, and we randomly selected one for each night of field trials. Trials focused on a red bat species group (Lasiurus borealis and Lasiurus blossevillii; n = 46) and four species: cave myotis (Myotis velifer; n = 57), Brazilian free-tailed bats (Tadarida brasiliensis; n = 73), evening bats (Nycteceius humeralis; n = 53), and tricolored bats (Perimyotis subflavus; n = 17). The trials occurred during three treatment emissions: low (emissions from subarrays at 20, 26, and 32 kHz), high (emissions from subarrays at 38, 44, and 50 kHz), and combined (all six emission frequencies). We placed one wild-captured bat into the flight cage for each trial, which consisted of an acclimation period, a control period with the UD powered off, and the three emission treatments (order randomly selected), each interspersed with a control period. We tracked bat flight using four thermal cameras placed outside the flight cage. We quantified the effectiveness of each treatment by comparing the distances each bat flew from the UD during each treatment vs. the control period using quantile regression. Additionally, we conducted an exploratory analysis of differences between sex and season and sex within season using analysis of variance. Broadly, UDs were effective at altering the bats’ flight paths as they flew farther from the UD during treatments than during controls; however, results varied by species, sex, season, and sex within season. For the red bat group, bats flew farther from the UD during all treatments than during the control period at all percentiles (p < 0.001), and treatments were comparable in effectiveness. For cave myotis, all percentile distances were farther from the UD during each of the treatments than during the control, except the 90th percentile distance during high, and low was most effective. For evening bats and Brazilian free-tailed bats, results were inconsistent, but high and low were most effective, respectively. For tricolored bats, combined and low were significant at the 10th–75th percentiles, high was significant at all percentiles, and combined was most effective. Results suggest UDs may be an effective means of reducing bat mortalities due to wind turbine blade strikes. We recommend that continued research on UDs focus on low emission treatments, which have decreased sound attenuation and demonstrated effectiveness across the bat species evaluated in this study.

17 WIND ENERGY↗
NASA NTRS1972

An improved multiple linear regression and data analysis computer program package

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Sidik, S. M.↗
NASA NTRS1972

Vestibular adaptation in man - Effects of increased acceleration during different phases of adaptation.

The purpose of this study was to investigate the course of vestibular adaptation following a temporary increase in angular acceleration (A). Eight normal subjects, who were rotated in a precision rotation device, gave periodic magnitude estimates of their perceived velocity throughout a prolonged 1 deg per sec per sec acceleration, which was briefly increased to either 2 or 3 deg per sec per sec at four points in the adaptation cycle. The data, tested with analysis of variance, showed that the size of the magnitude estimates was influenced by the magnitude and position of the altered A. The duration of subjective response was affected only by the position of the altered A.

Luster, T.↗
NASA NTRS1973

Alfven wave refraction by interplanetary inhomogeneities.

Pioneer 6 magnetic data reveal that the propagation direction of Alfven waves in the interplanetary medium is strongly oriented along the ambient field. Magnetic fluctuations of frequencies up to 1/30 sec in the spacecraft frame are shown to satisfy a necessary condition for Alfven waves, and a variance matrix analysis is used to determine the Alfven wave normal. It appears from this analysis that geometrical hydromagnetics may satisfactorily describe deviation of the wave normal from the background field. The rotational discontinuity is likely also to propagate along the field lines.

Daily, W. D.↗
NASA NTRS1975

On hemispheric differences in evoked potentials to speech stimuli

Confirmation is provided for the belief that evoked potentials may reflect differences in hemispheric functioning that are marginal at best. Subjects were right-handed and audiologically normal men and women, and responses were recorded using standard EEG techniques. Subjects were instructed to listen for the targets while laying in a darkened sound booth. Different stimuli, speech and tone signals, were used. Speech sounds were shown to evoke a response pattern that resembles that to tone or clicks. Analysis of variances on peak amplitude and latency measures showed no significant differences between hemispheres, however, a Wilcoxon test showed significant differences in hemispheres for certain target tasks.

Galambos, R.↗
NASA NTRS1976

Analysis and application of minimum variance discrete time system identification

An on-line minimum variance parameter identifier was developed which embodies both accuracy and computational efficiency. The new formulation resulted in a linear estimation problem with both additive and multiplicative noise. The resulting filter is shown to utilize both the covariance of the parameter vector itself and the covariance of the error in identification. It is proven that the identification filter is mean square covergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Kotob, S.↗