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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Automated Classification and Analysis of Non-metallic Inclusion Data Sets

The aim of this study is to utilize principal component analysis (PCA), clustering methods, and correlation analysis to condense and examine large, multivariate data sets produced from automated analysis of non-metallic inclusions. Non-metallic inclusions play a major role in defining the properties of steel and their examination has been greatly aided by automated analysis in scanning electron microscopes equipped with energy dispersive X-ray spectroscopy. The methods were applied to analyze inclusions on two sets of samples: two laboratory-scale samples and four industrial samples from a near-finished 4140 alloy steel components with varying machinability. The laboratory samples had well-defined inclusions chemistries, composed of MgO-Al{sub 2}O{sub 3}-CaO, spinel (MgO-Al{sub 2}O{sub 3}), and calcium aluminate inclusions. The industrial samples contained MnS inclusions as well as (Ca,Mn)S + calcium aluminate oxide inclusions. PCA could be used to reduce inclusion chemistry variables to a 2D plot, which revealed inclusion chemistry groupings in the samples. Clustering methods were used to automatically classify inclusion chemistry measurements into groups, i.e., no user-defined rules were required.

36 MATERIALS SCIENCE↗
NASA NTRS2001

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

Aires, Filipe↗
DOE OSTI2021

Gaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control

Abstract Advances in hyperspectral imaging including electron energy loss spectroscopy bring forth the challenges of exploratory and physics-based analysis of multidimensional data sets. The multivariate linear unmixing methods generally explore similarities in the energy dimension, but ignore correlations in the spatial domain. At the same time, Gaussian process (GP) explicitly incorporate spatial correlations in the form of kernel functions but is computationally intensive. Here, we implement a GP method operating on the full spatial domain and reduced representations in the energy domain. In this multivariate GP, the information between the components is shared via a common spatial kernel structure, while allowing for variability in the relative noise magnitude or image morphology. We explore the role of kernel constraints on the quality of the reconstruction, and suggest an approach for estimating them from the experimental data. We further show that spatial information contained in higher-order components can be reconstructed and spatially localized.

36 MATERIALS SCIENCE↗
DOE OSTI2019

MRI of pancreatic ductal adenocarcinoma: texture analysis of T2-weighted images for predicting long-term outcome

Purpose: To assess the association between T2-weighted imaging (T2WI) texture-analysis parameters and the pathological aggressiveness or long-term outcomes in pancreatic ductal adenocarcinoma (PDAC) patients. Methods: A total of 66 patients (mean age 65.3 ± 9.0 years) who underwent preoperative MRI followed by pancreatectomy for PDAC between 2013 and 2015 were included in this study. A radiologist performed a texture analysis twice on one axial image using commercial software. Differences in the tex parameters, according to pathological factors, were analyzed using a Student’s t test or an ANOVA with Tukey’s test. Univariate and multivariate Cox proportional hazards regression analyses were used to evaluate the association between tex parameters and recurrence-free survival (RFS) or overall survival (OS). Results: The mean follow-up time was 18.5 months, and there were 58 recurrences and 39 deaths. The mean of the positive pixel (MPP)-related factors was significantly lower in poorly differentiated tumors than in well-differentiated tumors as well as in cases with perineural invasion. The univariate Cox proportional hazards analysis showed a significant association between the tex parameters and RFS or OS. However, only tumor size was statistically significant after the multivariate analysis. Only tumor size and entropy with medium texture were significantly associated with OS after the multivariate analysis. Conclusions: Tumor size was a significant predictive factor for RFS and OS in PDAC patients. Although entropy with medium texture analysis was significantly associated with OS, there were also limitations in the texture analysis; thus, further study is necessary.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Biochemical Control With Radiotherapy Improves Overall Survival in Intermediate and High-Risk Prostate Cancer Patients Who Have an Estimated 10-Year Overall Survival of >90%

Purpose: To identify subgroups of patients with carcinoma of the prostate treated with radical radiotherapy that have improved overall survival when disease is biochemically controlled. Methods and Materials: A cohort of 1,060 prostate cancer patients treated with radical radiotherapy was divided into nine subgroups based on National Comprehensive Cancer Network risk category and estimated 10-year overall survival (eOS 10y) derived from the age adjusted Charlson Comorbidity Index. Patients with and without biochemical control were compared with respect to overall survival. Actuarial estimates of overall survival were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of overall survival. Results: Median follow-up was 125 months (range, 51-176 months). Only the subgroups with high or intermediate risk disease and an eOS 10y of >90% had a statistically significantly improved overall survival when prostate cancer was biochemically controlled. In all other groups, biochemical control made no significant difference to overall survival. In the subgroup with high-risk disease and eOS 10y >90%, actuarial overall survival was 86.3% (95% confidence interval [CI] 78.5%-94.1%) and 62.1% (95% CI 52.9%-71.3%) for patients with biochemical control and biochemical relapse respectively (p = 0.002). In the intermediate risk group with eOS >90%, actuarial overall survival was 95.3% (95% CI 89.0%-100%) and 79.8% (95% CI 68.0%-91.6%) for biochemically controlled and biochemically relapsed patients (p = 0.033). On multivariate analysis, National Comprehensive Cancer Network risk group (p = 0.005), biochemical control (p = 0.033) and eOS 10y (p < 0.001) were statistically significant. Conclusion: Biochemical control translates into improved overall survival in patients with high or intermediate risk disease and an estimated 10-year overall survival of >90%.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

MR texture analysis: potential imaging biomarker for predicting the chemotherapeutic response of patients with colorectal liver metastases

Purpose: The purpose of the study was to determine whether the pre-treated MR texture features of colorectal liver metastases (CRLMs) are predictive of therapeutic response after chemotherapy. Methods: The study included twenty-six consecutive patients (a total of 193 liver metastasis) with unrespectable CRLMs at our institution from August 2014 to February 2016. Lesions were categorized into either responding group or non-responding group according to changes in size. Texture analysis was quantified on T2-weighted images by two radiologists with consensus on regions of interest which were manually drawn on the largest cross-sectional area of the lesions. Five histogram features (mean, variance, skewness, kurtosis, and entropy{sup 1}) and five gray level co-occurrence matrix features (GLCM; angular second moment (ASM), entropy{sup 2}, contrast, correlation, and inverse difference moment (IDM)) were extracted. The texture parameters were statistically analyzed to identify the differences between the two groups, and the potential predictive parameters to differentiate the responding group from the non-responding group were subsequently tested using multivariable logistic regression analysis. Results: A total of 107 responding and 86 non-responding lesions were evaluated. A higher variance, entropy{sup 1}, contrast, entropy{sup 2} and a lower ASM, correlation, IDM were independently (P < 0.05) associated with a good response to chemotherapy with the areas under the ROC curves (AUCs) of 0.602–0.784. Variance (P < 0.001) and ASM (P = 0.001) remained potential predictive values to discriminate responding lesions from non-responding lesions when tested using multivariable logistic regression analysis. The highest AUC of the predictors from the association of variance and ASM was 0.814. Conclusion: MR texture features on pre-treated T2 images have the potential to predict the therapeutic response of colorectal liver metastases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Evaluation of image guided motion management methods in lung cancer radiotherapy

Purpose: To evaluate the accuracy and reliability of three target localization methods for image guided motion management in lung cancer radiotherapy. Methods: Three online image localization methods, including (1) 2D method based on 2D cone beam (CB) projection images, (2) 3D method using 3D cone beam CT (CBCT) imaging, and (3) 4D method using 4D CBCT imaging, have been evaluated using a moving phantom controlled by (a) 1D theoretical breathing motion curves and (b) 3D target motion patterns obtained from daily treatment of 3 lung cancer patients. While all methods are able to provide target mean position (MP), the 2D and 4D methods can also provide target motion standard deviation (SD) and excursion (EX). For each method, the detected MP/SD/EX values are compared to the analytically calculated actual values to calculate the errors. The MP errors are compared among three methods and the SD/EX errors are compared between the 2D and 4D methods. In the theoretical motion study (a), the dependency of MP/SD/EX error on EX is investigated with EX varying from 2.0 cm to 3.0 cm with an increment step of 0.2 cm. In the patient motion study (b), the dependency of MP error on target sizes (2.0 cm and 3.0 cm), motion patterns (four motions per patient) and EX variations is investigated using multivariant linear regression analysis. Results: In the theoretical motion study (a), the MP detection errors are −0.2 ± 0.2, −1.5 ± 1.1, and −0.2 ± 0.2 mm for 2D, 3D, and 4D methods, respectively. Both the 2D and 4D methods could accurately detect motion pattern EX (error < 1.2 mm) and SD (error < 1.0 mm). In the patient motion study (b), MP detection error vector (mm) with the 2D method (0.7 ± 0.4) is found to be significantly less than with the 3D method (1.7 ± 0.8,p < 0.001) and the 4D method (1.4 ± 1.0, p < 0.001) using paired t-test. However, no significant difference is found between the 4D method and the 3D method. Based on multivariant linear regression analysis, the variances of MP error in SI direction explained by target sizes, motion patterns, and EX variations are 9% with the 2D method, 74.4% with the 3D method, and 27% with the 4D method. The EX/SD detection errors are both < 1.0 mm for the 2D method and < 2.0 mm for the 4D method. Conclusions: The 2D method provides the most accurate MP detection regardless of the motion pattern variations, while its performance is limited by the accuracy of target identification in the projection images. The 3D method causes the largest error in MP determination, and its accuracy significantly depends on target sizes, motion patterns, and EX variations. The 4D method provides moderate MP detection results, while its accuracy relies on a regular motion pattern. In addition, the 2D and 4D methods both provide accurate measurement of the motion SD/EX, providing extra information for motion management.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Chapter 12 - Laser-Induced Breakdown Spectroscopy: Advanced Analytical Technique

Application of laser-induced breakdown spectroscopy (LIBS) to analyze solid samples and food materials is described in this chapter. A comparative study of the quantitative and qualitative analysis of atomic and molecular emission from LIBS spectra was performed using a mixture of SrCl 2 and Al 2 O 3 in powder form as a sample. The atomic emission from Sr and molecular emission from SrCl and SrO observed in LIBS spectra were analyzed. Calibration data collected at optimum experimental conditions were used to develop calibration curves, which can be used to predict the Sr concentration. Limits of detection for selected atomic and molecular emission spectra were determined. To showcase an application of LIBS technique in food science, analysis of wheat flour tortillas and comparison of organic and conventional vegetables are described. For the comparative study of organic and conventional vegetables, cauliflowers and broccolis were taken as working samples. Presence of the major elemental nutrients in these vegetables was detected by identifying emission lines of those elements in the LIBS spectra obtained from them. Both multivariate and univariate analyses were employed for comparison. Finally, principal component analysis was performed for multivariate analysis, whereas intensities of emission lines of elements were compared in univariate analysis.

47 OTHER INSTRUMENTATION↗
NASA NTRS1997

Analysis of Forest Foliage Using a Multivariate Mixture Model

Data with wet chemical measurements and near infrared spectra of ground leaf samples were analyzed to test a multivariate regression technique for estimating component spectra which is based on a linear mixture model for absorbance. The resulting unmixed spectra for carbohydrates, lignin, and protein resemble the spectra of extracted plant starches, cellulose, lignin, and protein. The unmixed protein spectrum has prominent absorption spectra at wavelengths which have been associated with nitrogen bonds.

Hlavka, C. A.↗
DOE OSTI2013

Preliminary Toxicity Analysis of 3-Dimensional Conformal Radiation Therapy Versus Intensity Modulated Radiation Therapy on the High-Dose Arm of the Radiation Therapy Oncology Group 0126 Prostate Cancer Trial

Purpose: To give a preliminary report of clinical and treatment factors associated with toxicity in men receiving high-dose radiation therapy (RT) on a phase 3 dose-escalation trial. Methods and Materials: The trial was initiated with 3-dimensional conformal RT (3D-CRT) and amended after 1 year to allow intensity modulated RT (IMRT). Patients treated with 3D-CRT received 55.8 Gy to a planning target volume that included the prostate and seminal vesicles, then 23.4 Gy to prostate only. The IMRT patients were treated to the prostate and proximal seminal vesicles to 79.2 Gy. Common Toxicity Criteria, version 2.0, and Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer late morbidity scores were used for acute and late effects. Results: Of 763 patients randomized to the 79.2-Gy arm of Radiation Therapy Oncology Group 0126 protocol, 748 were eligible and evaluable: 491 and 257 were treated with 3D-CRT and IMRT, respectively. For both bladder and rectum, the volumes receiving 65, 70, and 75 Gy were significantly lower with IMRT (all P<.0001). For grade (G) 2+ acute gastrointestinal/genitourinary (GI/GU) toxicity, both univariate and multivariate analyses showed a statistically significant decrease in G2+ acute collective GI/GU toxicity for IMRT. There were no significant differences with 3D-CRT or IMRT for acute or late G2+ or 3+ GU toxicities. Univariate analysis showed a statistically significant decrease in late G2+ GI toxicity for IMRT (P=.039). On multivariate analysis, IMRT showed a 26% reduction in G2+ late GI toxicity (P=.099). Acute G2+ toxicity was associated with late G3+ toxicity (P=.005). With dose–volume histogram data in the multivariate analysis, RT modality was not significant, whereas white race (P=.001) and rectal V70 ≥15% were associated with G2+ rectal toxicity (P=.034). Conclusions: Intensity modulated RT is associated with a significant reduction in acute G2+ GI/GU toxicity. There is a trend for a clinically meaningful reduction in late G2+ GI toxicity with IMRT. The occurrence of acute GI toxicity and large (>15%) volumes of rectum >70 Gy are associated with late rectal toxicity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

An improved Method for Determining Transient Fuel Dilution of Oil in an Internal-Combustion Engine Using Laser-Induced Florescence and Multivariate Least Square Calibration

An optical diagnostic, based on laser-induced fluorescence (LIF), has been developed for on-engine measurements of real-time fuel dilution of engine oil or fuel in oil (FIO). Fuel dilution of oil is broadly relevant to advancing engine technology including durability, calibration, and catalyst-system management, and believed to promote destructive stochastic pre-ignition (SPI) during high-load engine operations. While standard (e.g., ASTM D3524-90) methods are not capable of real-time transient measurements, the LIF technique resolves transient dilution on the minutes time scale. We have expanded on our original FIO instrument development by introducing an improved analysis based on multivariate least square chemometrics analysis. The measurement uses a fuel dye (180–1300 parts per million, by mass) and monitors for its presence in the oil using 532 nm excitation and LIF. While the original FIO instrument utilized a two-color ratio method for analysis, the improved chemometric analysis uses the fully resolved LIF dye spectra to provide better predictive FIO accuracy (>92%) over a wide FIO range (1.5–14%) typical of engine application. We also investigate the effect of oil temperature on the LIF signal. Limited engine applications for demonstrating and validating the improved FIO instrument are shown, and the related data used to quantify practical detection limit and sensitivity. The improved analysis is insensitive to laser power fluctuation and change in detector integration time, providing an excellent FIO sensitivity (1–2%) and detection limit (0.01 %FIO) over a wide range of loads and injection timings, illustrating this updated approach to be a promising tool for advancing engine technology.

42 ENGINEERING↗
DOE OSTI2020

Reimagining pH Measurement: Utilizing Raman Spectroscopy for Enhanced Accuracy in Phosphoric Acid Systems

Measurement of pH is an integral component of chemical studies and process control; however traditional pH probes are difficult to utilize in harsh or complex chemical systems. Optical spectroscopy-based on-line monitoring offers a powerful and novel route for characterizing system parameters, such as pH, and is well adapted to deployment in harsh environments or chemically complex systems. Specifically, Raman spectroscopy combined with chemometric analysis can provide an improved method of on-line pH measurement. Therefore, multivariate curve resolution analysis of Raman spectra can be utilized to determine speciation as a function of pH and subsequent chemometric modeling can be used to correlate spectral response to pH. This was demonstrated with phosphoric acid, a chemical system known to challenge traditional pH probes. Raman spectra exhibit clear changes with pH due to changing speciation, and chemometric modeling can be successfully utilized to correlate those fingerprints to pH. Using this approach, true pH of the phosphoric acid system can be measured with greater accuracy than with traditional pH probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

High-Dose Radiotherapy With or Without Androgen Deprivation Therapy for Intermediate-Risk Prostate Cancer: Cancer Control and Toxicity Outcomes

Purpose: To evaluate the impact of short-course androgen deprivation therapy (ADT) on cancer control outcomes and toxicity in intermediate-risk prostate cancer treated with dose-escalated external beam radiotherapy (high-dose radiotherapy [HDRT]). Methods and Materials: Demographic, disease, and treatment characteristics of prostate cancer patients at 2 institution consortiums were charted. Of 296 men with intermediate-risk prostate cancer (defined as {>=}T2b, prostate-specific antigen level >10 ng/mL, or Gleason score [GS] of 7, with none of the following: {>=}T3, prostate-specific antigen level >20 ng/mL, GS {>=}8, or positive nodes) treated with HDRT to a dose of 72 Gy or greater, 123 received short-course ADT and 173 did not. Univariate and multivariate analyses on biochemical failure-free survival (BFFS) (including subset analysis by disease factors) and on overall survival (OS) were performed, as were comparisons of gastrointestinal (GI) and genitourinary (GU) toxicity rates. Results: For the whole group, the median dose was 75.6 Gy; the minimum follow-up was 2 years, and the median follow-up was 47.4 months. For ADT vs. no ADT, the 5-year BFFS rate was 86% vs. 79% (p = 0.138) and the 5-year OS rate was 87% vs. 80% (p = 0.159). On multivariate analysis, percent positive cores (PPC) (p = 0.002) and GS (p = 0.008) were significantly associated with BFFS, with ADT showing a trend (p = 0.055). The impact of ADT was highest in the subsets with PPC greater than 50% (p = 0.019), GS 4+3 (p = 0.078), and number of risk factors greater than 1 (p = 0.022). Only intensity-modulated radiotherapy use (p = 0.012) and GS (p = 0.023) reached significance for OS, and there were no significant differences in GU or GI toxicity. Conclusions: Although the use of ADT with HDRT did not influence BFFS, our study suggests a benefit in patients with PPC greater than 50%, GS 4+3, or multiple risk factors. No OS benefit was shown, and ADT was not associated with additional radiotherapy-related GI or GU toxicity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2012

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Roberts, Yolanda↗
DOE OSTI2013

STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS

This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Simulation of the output power of copper bromide lasers by the MARS method

The dependence of the output power of CuBr lasers (operating at wavelengths of 510.6 and 578.2 nm) on ten input physical parameters has been statistically analysed based on a large amount of experimental data accumulated for these lasers. Regression models have been built using the flexible nonparametric method of multivariate adaptive regression splines (MARS) to describe both linear and nonlinear local dependences. These models cover more than 97% initial data with an error comparable with the experimental error; they are applied to estimate and predict the output powers of both existing and future lasers. The advantage of the models constructed for estimating laser parameters over the standard parametric methods of multivariate factor and regression analysis is demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗