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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Analysis of Factors Affecting Successful Clinical Trial Enrollment in the Context of Three Prospective, Randomized, Controlled Trials

Purpose: Challenges can arise when attempting to maximize patient enrollment in clinical trials. There have been limited studies focusing on the barriers to enrollment and the efficacy of alternative study design to improve accrual. We analyzed barriers to clinical trial enrollment, particularly the influence of timing, in context of three prospective, randomized oncology trials where one arm was considered more aggressive than the other. Methods and Materials: From June 2011 to March 2015, patients who were enrolled on 3 prospective institutional protocols (an oligometastatic non-small cell lung cancer [NSCLC] trial and 2 proton vs intensity modulated radiation therapy trials in NSCLC and esophageal cancer) were screened for protocol eligibility. Eligible candidates were approached about trial participation, and patient characteristics (age, sex, T/N categorization) were recorded along with details surrounding trial presentation (appointment number). Fisher's exact test, Student's t tests, and multivariate analysis were performed to assess differences between enrolled and refusal patients. Results: A total of 309 eligible patients were approached about trial enrollment. The enrollment success rate during this time span was 52% (n=160 patients). Enrolled patients were more likely to be presented trial information at an earlier appointment (oligometastatic protocol: 5 vs 3 appointments [P<.001]; NSCLC protocol: 4 vs 3 appointments [P=.0018]; esophageal protocol: 3 vs 2 appointments [P=.0086]). No other factors or patient characteristics significantly affected enrollment success rate. Conclusion: Improvement in enrollment rates for randomized control trials is possible, even in difficult accrual settings. Earlier presentation of trial information to patients is the most influential factor for success and may help overcome accrual barriers without compromising trial design.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1984

Prediction of the space adaptation syndrome

The univariate and multivariate relationships of provocative measures used to produce motion sickness symptoms were described. Normative subjects were used to develop and cross-validate sets of linear equations that optimally predict motion sickness in parabolic flights. The possibility of reducing the number of measurements required for prediction was assessed. After describing the variables verbally and statistically for 159 subjects, a factor analysis of 27 variables was completed to improve understanding of the relationships between variables and to reduce the number of measures for prediction purposes. The results of this analysis show that none of variables are significantly related to the responses to parabolic flights. A set of variables was selected to predict responses to KC-135 flights. A series of discriminant analyses were completed. Results indicate that low, moderate, or severe susceptibility could be correctly predicted 64 percent and 53 percent of the time on original and cross-validation samples, respectively. Both the factor analysis and the discriminant analysis provided no basis for reducing the number of tests.

Reschke, M. F.↗
DOE OSTI2019

Effect of Stress States on Twinning Behavior in Twinning-Induced Plasticity Steel

The effects of stress state on the twin structures and kinetics in twinning-induced plasticity (TWIP) steel have been investigated to understand the twinning behaviors in more detail. Twinning behaviors of tension, compression, wire drawing, and caliber rolling were evaluated and compared using the EBSD technique, TEM measurement, and Schmid factor analysis. Twin structures, such as twin thickness, twin variant, twin shape, and twin kinetics were different with stress states. The specimen under compressive stress had wavy-shaped twins, less twin variant, lower twin thickness, and more twin volume fraction in comparison with the specimen under tensile stress. The different structures and kinetics of deformation twin with stress state were highly related to the grain rotation during plastic deformation. Under tensile stress, the grain rotation to <111> orientation, twinning-favored regions by Schmid factor analysis, encouraged the lateral growth of twins, more twin variants, and straight-type twins, while the grain rotation to <110> orientation under compressive stress suppressed the twin growth and twin variant and developed wavy-shaped twins. Drawn wire and caliber-rolled wire had both twin features under tensile and compressive stress states and higher twin volume fraction since complex stress state that combined tension and compression was applied in these processes. The hardness values were strongly related to the twin volume fraction with strain and stress state.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Analysis of Factors Affecting the Performance of RLV Thrust Cell Liners

The reusable launch vehicle (RLV) thrust cell liner, or thrust chamber, is a critical component of the Space Shuttle Main Engine (SSME). It is designed to operate in some of the most severe conditions seen in engineering practice. This requirement, in conjunction with experimentally observed 'dog-house' failure modes characterized by bulging and thinning of the cooling channel wall, provides the motivation to study the factors that influence RLV thrust cell liner performance. Factors or parameters believed to be directly related to the observed characteristic deformation modes leading to failure under in-service loading conditions are identified, and subsequently investigated using the cylindrical version of the higher-order theory for functionally graded materials in conjunction with the Robinson's unified viscoplasticity theory and the power-law creep model for modeling the response of the liner s constituents. Configurations are analyzed in which specific modifications in cooling channel wall thickness or constituent materials are made to determine the influence of these parameters on the deformations resulting in the observed failure modes in the outer walls of the cooling channel. The application of thermal barrier coatings and functional grading are also investigated within this context. Comparison of the higher-order theory results based on the Robinson and power-law creep model predictions has demonstrated that, using the available material parameters, the power-law creep model predicts more precisely the experimentally observed deformation leading to the 'dog-house' failure mode for multiple short cycles, while also providing much improved computational efficiency. However, for a single long cycle, both models predict virtually identical deformations. Increasing the power-law creep model coefficients produces appreciable deformations after just one long cycle that would normally be obtained after multiple cycles, thereby enhancing the efficiency of the analysis. This provides a basis for the development of an accelerated modeling procedure to further characterize dog-house deformation modes in RLV thrust cell liners. Additionally, the results presented herein have demonstrated that the mechanism responsible for deformation leading to 'dog-house' failure modes is driven by pressure, creep/relaxation and geometric effects.

Arnold, Steven M.↗
DOE OSTI2016

A Parametric Analysis of Factors Affecting Calculations of Estimated Dose Rates from Spent Nuclear Fuel Shipments - 16458

Planning for transportation of SNF requires estimation of the radiation dose to the members of the public associated with the transportation. This dose is expected to be very low compared to natural background radiation because dose rates and exposure durations are minimal. A preliminary investigation was performed to estimate the dose rate from a SNF transportation package as a function of distance and evaluate factors affecting the estimated dose rate, such as local environment modeling. Effects on the dose rate are determined for changes in temperature and relative humidity of the air surrounding a transportation package and for different compositions of the ground underneath it. The impact of different vapor content in air was evaluated to be small, within the statistical uncertainty of the dose rate estimates. The neutron dose rate contributions from scattering interactions within different soil/pavement materials were from approximately 20% to 70% at 25 cm from the ground and from approximately 10% to 40% at 175 cm from the ground. The effect of photon scattering interactions within different soil/pavement materials was an increase in photon dose rate of less than 20% at 25 cm from the ground and less than 10% at 175 cm from the ground. The impact of different ground materials on the total dose rate would depend on the relative contributions of photon and neutron dose rates to the total dose rate. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Report on PTT Imaging of Defects in AM Metallic Materials-Part 2

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Virtual reality as a human factors design analysis tool: Macro-ergonomic application validation and assessment of the Space Station Freedom payload control area

A virtual reality (VR) Applications Program has been under development at MSFC since 1989. Its objectives are to develop, assess, validate, and utilize VR in hardware development, operations development and support, missions operations training, and science training. A variety of activities are under way within many of these areas. One ongoing macro-ergonomic application of VR relates to the design of the Space Station Freedom Payload Control Area (PCA), the control room from which onboard payload operations are managed. Several preliminary conceptual PCA layouts have been developed and modeled in VR. Various managers and potential end users have virtually 'entered' these rooms and provided valuable feedback. Before VR can be used with confidence in a particular application, it must be validated, or calibrated, for that class of applications. Two associated validation studies for macro-ergonomic applications are under way to help characterize possible distortions of filtering of relevant perceptions in a virtual world. In both studies, existing control rooms and their 'virtual counterparts will be empirically compared using distance and heading estimations to objects and subjective assessments. Approaches and findings of the PCA activities and details of the studies are presented.

Hale, Joseph P.↗
NASA NTRS2011

Advanced Electrocardiography Can Identify Occult Cardiomyopathy in Doberman Pinschers

Recently, multiple advanced resting electrocardiographic (A-ECG) techniques have improved the diagnostic value of short-duration ECG in detection of dilated cardiomyopathy (DCM) in humans. This study investigated whether 12-lead A-ECG recordings could accurately identify the occult phase of DCM in dogs. Short-duration (3-5 min) high-fidelity 12-lead ECG recordings were obtained from 31 privately-owned, clinically healthy Doberman Pinschers (5.4 +/- 1.7 years, 11/20 males/females). Dogs were divided into 2 groups: 1) 19 healthy dogs with normal echocardiographic M-mode measurements: left ventricular internal diameter in diastole (LVIDd . 47mm) and in systole (LVIDs . 38mm) and normal 24-hour ECG recordings (<50 ventricular premature complexes, VPCs); and 2) 12 dogs with occult DCM: 11/12 dogs had increased M-mode measurements (LVIDd . 49mm and/or LVIDs . 40mm) and 5/11 dogs had also >100 VPCs/24h; 1/12 dogs had only abnormal 24-hour ECG recordings (>100 VPCs/24h). ECG recordings were evaluated via custom software programs to calculate multiple parameters of high-frequency (HF) QRS ECG, heart rate variability, QT variability, waveform complexity and 3-D ECG. Student's t-tests determined 19 ECG parameters that were significantly different (P < 0.05) between groups. Principal component factor analysis identified a 5-factor model with 81.4% explained variance. QRS dipolar and non-dipolar voltages, Cornell voltage criteria and QRS waveform residuum were increased significantly (P < 0.05), whereas mean HF QRS amplitude was decreased significantly (P < 0.05) in dogs with occult DCM. For the 5 selected parameters the prediction of occult DCM was performed using a binary logistic regression model with Chi-square tested significance (P < 0.01). ROC analyses showed that the five selected ECG parameters could identify occult ECG with sensitivity 89% and specificity 83%. Results suggest that 12-lead A-ECG might improve diagnostic value of short-duration ECG in earlier detection of canine DCM as five selected ECG parameters can with reasonable accuracy identify occult DCM in Doberman Pinschers. Future extensive clinical studies need to clarify if 12-lead A-ECG could be useful as an additional screening test for canine DCM.

Spiljak, M.↗