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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Different CT slice thickness and contrast‐enhancement phase in radiomics models on the differential performance of lung adenocarcinoma

Abstract Background To investigate the effects of computed tomography (CT) reconstruction slice thickness and contrast‐enhancement phase on the differential diagnosis performance of radiomic signature in lung adenocarcinoma. Methods A total of 187 patients who had been pathologically confirmed with lung adenocarcinoma and nonadenocarcinoma were divided into a training cohort ( n = 149) and validation cohort ( n = 38). All the patients underwent contrast‐enhanced CT and the images were reconstructed with different slice thickness. The radiomic features were extracted from different slice thickness and scan phase. The logistic regression (LR) algorithm was used to build a machine learning model for each group. The area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve and DeLong test was used to evaluate its discriminating performance. Results Finally, 34 image features and five semantic features were selected to establish a radiomics model. Based on the three contrast‐enhanced CT phases and four reconstruction slice thickness, 12 groups of radiomics models showed good discrimination ability with the AUCs range from 0.9287 to 0.9631, sensitivity range from 0.8349 to 0.9083, specificity range from 0.825 to 0.925 in the training group. Similar results were observed in the validation group. However, there was no statistical significance between the different CT scan phase groups and different slice thickness ( p > 0.05). Conclusions The radiomic analysis of contrast‐enhanced CT can be used for the differential diagnosis of lung adenocarcinoma. Moreover, different slice thickness and contrast‐enhanced scan phase did not affect the discriminating ability in the radiomics models.

Wang, Yang↗
NASA NTRS1977

Depth-dose relations for heavy ion beams

Radiation transport of heavy ions in matter is of interest to radiological protection in space and high-altitude aircraft. In addition, heavy ion beams are expected to be of advantage in radiotherapy since their characteristic Bragg curve allows a relative reduction of the dose in reaching a tumor site and the near elimination of exposure beyond the tumor region as the beam exits the body. Furthermore, the radioresistance of tumorous cells due to their hypoxic state may be reduced or eliminated by the high specific ionization of heavy ion beams. The depth-dose distribution of heavy ion beams consists of energy deposited by the attenuated primary beam with its characteristic Bragg curve and a relatively unstructured background due to secondary radiations produced in nuclear reactions. As the ion mass increases, the secondary contribution becomes more structured and may add significantly to the Bragg peak of the primary ions. The result for heavy ions (z greater than 20) is a greatly broadened Bragg peak region, especially in comparison to straggling effects, which may prove to be of importance in radiotherapy and biomedical research.

Wilson, J. W.↗
NASA NTRS1981

A research program to reduce interior noise in general aviation airplanes. Influence of depressurization and damping material on the noise reduction characteristics of flat and curved stiffened panels

Some 20 x 20 aluminum panels were studied in a frequency range from 20 Hz to 5000 Hz. The noise sources used were a swept sine wave generator and a random noise generator. The effect of noise source was found to be negligible. Increasing the pressure differential across the panel gave better noise reduction below the fundamental resonance frequency due to an increase in stiffness. The largest increase occurred in the first 1 psi pressure differential. The curved, stiffened panel exhibited similar behavior, but with a lower increase of low frequency noise reduction. Depressurization on these panels resulted in decreased noise reduction at higher frequencies. The effect of damping tapes on the overall noise reduction values of the test specimens was small away from the resonance frequency. In the mass-law region, a slight and proportional improvement in noise reduction was observed by adding damping material. Adding sound absorbtion material to a panel with damping material beneficially increased noise reduction at high frequencies.

Navaneethan, R.↗
NASA NTRS1989

Performance characteristics of a curved-channel microchannel plate with a curved input face and a plane output face

The presently performance-evaluated format, in which a high-gain curved-channel microchannel plate (M2MCP) has a spherical concave input face and a plane output face, allows the input face of the MCP (1) to match such curved focal surfaces as that of a Rowland-circle spectrometer mounting, while (2) having a high-resolution plane readout array in proximity focus with the output face. This MCP has been evaluated in a discrete-anode multicathode microchannel array detector system. The saturated modal gain was found to be inversely proportional to the length/diameter ratio of the channels and directly proportional to the applied MCP voltage.

Slater, David C.↗
NASA NTRS1973

Design study of RL10 derivatives. Volume 2: Engine design characteristics, appendices

Calculations, curves, and substantiating data which support the engine design characteristics of the RL-10 engines are presented. A description of the RL-10 ignition system is provided. The performance calculations of the RL-10 derivative engines and the performance results obtained are reported. The computer simulations used to establish the control system requirements and to define the engine transient characteristics are included.

Source record↗
NASA NTRS2001

Nonlinear and Buckling Behavior of Curved Panels Subjected to Combined Loads

The results of an analytical study of the nonlinear and buckling response characteristics of curved panels subjected to combined loads are presented. Aluminum and laminated composite panels are considered in the study and a flat and shallow curved panel configurations are considered as well. The panels are subjected to combined axial compression and transverse tension or compression loads or combined axial compression and inplane shear loads. Results illustrating the effects of various combined load states on the buckling response of the panels are presented. In addition, results illustrating the effects of laminate orthotropy and anisotropy and panel curvature on the panel response are presented. The results indicate that panel curvature can have a significant effect on the nonlinear and buckling behavior of the panels subjected to combined loads. Results are included that show that geometrically perfect panels do not exhibit bifurcation points for some combined loads. Results are also presented that show the effects of laminate orthotropy and anisotropy on the interaction of combined loads.

Hilburger, Mark W.↗
NASA NTRS2016

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗
NASA NTRS1976

Comparison of chain sampling plans with single and double sampling plans

The efficiency of chain sampling is examined through matching of operating characteristics (OC) curves of chain sampling plans (ChSP) with single and double sampling plans. In particular, the operating characteristics of some ChSP-0, 3 and 1, 3 as well as ChSP-0, 4 and 1, 4 are presented, where the number pairs represent the first and the second cumulative acceptance numbers. The fact that the ChSP procedure uses cumulative results from two or more samples and that the parameters can be varied to produce a wide variety of operating characteristics raises the question whether it may be possible for such plans to provide a given protection with less inspection than with single or double sampling plans. The operating ratio values reported illustrate the possibilities of matching single and double sampling plans with ChSP. It is shown that chain sampling plans provide improved efficiency over single and double sampling plans having substantially the same operating characteristics.

Stephens, K. S.↗
NASA NTRS1975

Spectroscopic determination of the characteristics of precipitating auroral particles

A large data base obtained from NASA Convair auroral expeditions is used to illustrate the variability in 6300A/4278A and 5577A/4278A ratios in auroras. The variation is well bounded by theoretical curves for characteristic spectral energies between 0.3 and 10 keV, which are typical for auroral precipitation. Coordinated measurements with the OV1-18 satellite show good agreement between the parameters of the precipitating-proton and electron-energy spectra derived from photometric measurements and those measured directly.

Mende, S. B.↗
NASA NTRS1971

Supporting data package for TR 32-1541, effects of storage temperatures on silicon solar cell contacts

A series of summary curves is presented for cells having various contact systems, depicting the effects of temperature exposure as a function of time on the electrical and mechanical characteristics. Each curve represents the results obtained from a minimum of 32 and a maximum of 1104 individual data inputs and includes the 95% confidence limits associated with each time-temperature combination for which measurements were obtained. The curves are useful for detailed analysis and comparison of the behavior of the contact system as a function of the environmental conditions studied.

Berman, P. A.↗
NASA NTRS1984

Spectral response curve models applied to forest cover-type discrimination

The potential of remote sensing systems to provide a cost-effective inventory tool in the case of forest resources is currently of interest to a variety of natural resources management agencies. A number of studies have been performed regarding the use of Landsat data for mapping forest resources in Michigan. The present paper is concerned with current research, which has been directed toward the development and evaluation of computer-implemented classifications for the identification and characterization of coniferous forest types in Michigan's northern Lower Peninsula. Attention is given to the characteristic response curves from Landsat MSS data, spectral response curve models, and forest cover-type discrimination. It is found that spectral response curve models can be used to evaluate and explain the characteristic spectral responses of coniferous forest types on a snow-covered, winter Landsat scene.

Hudson, W. D.↗
NASA NTRS2011

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

Receiver Operator Characteristic (ROC) curves are commonly applied as metrics for quantifying the performance of binary fault detection systems. An ROC curve provides a visual representation of a detection system s True Positive Rate versus False Positive Rate sensitivity as the detection threshold is varied. The area under the curve provides a measure of fault detection performance independent of the applied detection threshold. While the standard ROC curve is well suited for quantifying binary fault detection performance, it is not suitable for quantifying the classification performance of multi-fault classification problems. Furthermore, it does not provide a measure of diagnostic latency. To address these shortcomings, a novel three-dimensional receiver operator characteristic (3D ROC) surface metric has been developed. This is done by generating and applying two separate curves: the standard ROC curve reflecting fault detection performance, and a second curve reflecting fault classification performance. A third dimension, diagnostic latency, is added giving rise to 3D ROC surfaces. Applying numerical integration techniques, the volumes under and between the surfaces are calculated to produce metrics of the diagnostic system s detection and classification performance. This paper will describe the 3D ROC surface metric in detail, and present an example of its application for quantifying the performance of aircraft engine gas path diagnostic methods. Metric limitations and potential enhancements are also discussed

Simon, Donald L.↗
NASA NTRS2004

Variable Stiffness Spar Wind-Tunnel Model Development and Testing

The concept of exploiting wing flexibility to improve aerodynamic performance was investigated in the wind tunnel by employing multiple control surfaces and by varying wing structural stiffness via a Variable Stiffness Spar (VSS) mechanism. High design loads compromised the VSS effectiveness because the aerodynamic wind-tunnel model was much stiffer than desired in order to meet the strength requirements. Results from tests of the model include stiffness and modal data, model deformation data, aerodynamic loads, static control surface derivatives, and fuselage standoff pressure data. Effects of the VSS on the stiffness and modal characteristics, lift curve slope, and control surface effectiveness are discussed. The VSS had the most effect on the rolling moment generated by the leading-edge outboard flap at subsonic speeds. The effects of the VSS for the other control surfaces and speed regimes were less. The difficulties encountered and the ability of the VSS to alter the aeroelastic characteristics of the wing emphasize the need for the development of improved design and construction methods for static aeroelastic models. The data collected and presented is valuable in terms of understanding static aeroelastic wind-tunnel model development.

Florance, James R.↗
DOE OSTI2019

The value of {sup 18}F-FDG PET/CT and carbohydrate antigen 19-9 in predicting lymph node micrometastases of pancreatic cancer

Purpose: This study aimed to assess the value of {sup 18}F-FDG PET/CT and carbohydrate antigen 19-9 (CA 19-9) levels in predicting lymph node micrometastases in patients with pancreatic cancer. Patients and methods: A total of 160 patients with pancreatic carcinoma were included in the study from 2012 to 2017. All patients underwent surgical treatment and PET/CT scans as well as tests to measure CA 19-9 levels before surgery. The PET/CT scans were evaluated by 2 nuclear medicine physicians who were blinded to the clinical information and were compared to the postsurgical pathological findings. Logistic regression analysis was performed to determine the variables that could predict lymph node micrometastases. Receiver operating characteristic (ROC) curves were utilized to find the best cutoff value of the variables related to predicting lymph node micrometastases. Results: The maximum standardized uptake value (SUV{sub max}) of the primary tumor and CA 19-9 level were potent predictors for determining the lymph node status. The best SUV{sub max} and CA 19-9 cutoff values for predicting lymph node micrometastases were 7.05 (sensitivity = 71.2%, specificity = 76.6%) and 240.55 U/ml (sensitivity = 62.1%, specificity = 79.8%), respectively. Conclusion: Patients with pancreatic cancer with a tumor SUV{sub max} ≥ 7.05 or a CA 19-9 value ≥ 240.55 are likely to have lymph node micrometastases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Analysis and prediction of intersection traffic violations using automated enforcement system data

We report that the automated enforcement system (AES) is an effective way of supplementing traditional traffic enforcement, and the traffic violation data from AES can also be effectively used for safety research. In this study, traffic violation data were used to analyze the influencing factors associated with traffic violations and to predict the probability of violations at intersections. The potential factors influencing violations include 24 independent factors related to time, space, traffic and weather. Results from a logistic model showed that the midday period, weekends, residential districts, collector roads, congested traffic conditions, high traffic flow, lower wind speed and low temperature would increase the probability of traffic violations. The probability of violations was predicted by the random forest algorithm, which was proven to be the best traffic violation prediction model among logistic regression, Gaussian naive Bayes, and support vector machine. Moreover, the proximity weighted synthetic oversampling technique (ProWSyn) method was applied to reduce the impact of the imbalance ratio (IR) and improve the model’s prediction performance. The receiver operating characteristics (ROC) curves and Precision-Recall (PR) curves illustrated that the random forest algorithm using oversampling data had the best classifier prediction performance than undersampling data. The area under curve (AUC) and out-of-bag (OOB) error with IR = 1 reached 0.914 and 0.0787, which showed the better performance of the random forest algorithm using ProWSyn in dealing with imbalanced traffic violation data.

42 ENGINEERING↗
DOE OSTI2020

Veridical data science

Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data science life cycle. The PCS workflow uses predictability as a reality check and considers the importance of computation in data collection/storage and algorithm design. It augments predictability and computability with an overarching stability principle. Stability expands on statistical uncertainty considerations to assess how human judgment calls impact data results through data and model/algorithm perturbations. As part of the PCS workflow, we develop PCS inference procedures, namely PCS perturbation intervals and PCS hypothesis testing, to investigate the stability of data results relative to problem formulation, data cleaning, modeling decisions, and interpretations. We illustrate PCS inference through neuroscience and genomics projects of our own and others. Moreover, we demonstrate its favorable performance over existing methods in terms of receiver operating characteristic (ROC) curves in high-dimensional, sparse linear model simulations, including a wide range of misspecified models. Finally, we propose PCS documentation based on R Markdown or Jupyter Notebook, with publicly available, reproducible codes and narratives to back up human choices made throughout an analysis. The PCS workflow and documentation are demonstrated in a genomics case study available on Zenodo.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects

In this paper we investigate how implementing machine learning could improve the efficiency of the search for Trans-Neptunian Objects (TNOs) within Dark Energy Survey (DES) data when used alongside orbit fitting. The discovery of multiple TNOs that appear to show a similarity in their orbital parameters has led to the suggestion that one or more undetected planets, an as yet undiscovered “Planet 9”, may be present in the outer solar system. DES is well placed to detect such a planet and has already been used to discover many other TNOs. Here, we perform tests on eight different supervised machine learning algorithms, using a data set consisting of simulated TNOs buried within real DES noise data. We found that the best performing classifier was the Random Forest which, when optimized, performed well at detecting the rare objects. We achieve an area under the receiver operating characteristic (ROC) curve, (AUC) = 0.996 ± 0.001. After optimizing the decision threshold of the Random Forest, we achieve a recall of 0.96 while maintaining a precision of 0.80. Finally, by using the optimized classifier to pre-select objects, we are able to run the orbit-fitting stage of our detection pipeline five times faster.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗