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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 OSTI2021

When to use rsync

We have endeavored to show, using a series of data transfer results obtained from two testbeds, when to use the popular data copying tool rsync and related tools. Tests have been conducted in local area network (LAN) and wide area network (WAN) environments. We conclude that for files in a certain size range and network latency ≦ 10 ms round trip time (RTT), rsync is still useful for data moving tasks in the category 4 of the U.S. DOE Technical Report “Data Movement Categories”. For more demanding data movement requirements, tools of different classes are suggested. Sample histograms from two DOE user facilities are provided to further support our conclusions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Modeling Hot Spot Experiments on Shocked Octahydro-1,3,5,7-Tetranitro-1,3,5,7-Tetrazocine

The cover picture shows a shock-induced reaction in a porous bed of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX). Our study shows compaction, reaction, and gas jetting during the initial stages of shock in the powder bed. Shock reflection at the glass window interface increases hot spot temperatures in HMX product gas in excess of 7000 K at higher impact speeds which is readily observable using pyrometry techniques. We extract a temperature histogram from simulations at discrete times, using it to calculate an effective emission spectrum and effective temperature, T eff , for comparison to data. Calculating T eff based on Planck's Law with a gray body assumption demonstrates good agreement with hot spot temperature data. The agreement with experimental results validates our mesoscale simulations as useful tools for elucidating the role of hot spot mechanisms in the shock initiation of heterogeneous explosives. Finally, more details can be found in the Full Paper by Harry Springer, Will Bassett, Sorin Bastea, Svjetlana Stekovic, and Craig Tarver on page 330 ff.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Image Distinguishability Analysis Testing Through Principal Components and Its Application to Hot Spot Scale Invariance

Hot spots are spatial regions of intense energy localization that govern initiation of secondary high explosives. Studies that characterize or compare simulated hot spots are frequently either qualitatively descriptive or resort to quantitative distribution functions that neglect stochastic variations and spatial correlations—effects that are also neglected in common comparison tests like the Kolmogorov–Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test based on principal component (PC) analysis that makes pixel-by-pixel comparisons between small, for example, O(<10), image data sets. The IDA test makes comparisons through a generalized distance metric in the PC space and a test statistic that is derived to calculate mathematical equation-values. Here, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations of hot spots from pore collapse in TATB to assess scale invariance in the complex patterns of hot spots that form in a representative high explosive crystal. The IDA test shows that TATB hot spot spatial temperature fields and their derived temperature histograms exhibit scale-invariant features over specific intervals of shock orientation, strength, and initial pore diameter. However, the IDA test also shows that qualitatively different conclusions regarding invariance can be reached depending on whether the hot spot is treated as a spatially correlated field as opposed to a distribution function that lacks spatial information.

organic↗
DOE OSTI2021

Parameter inference from event ensembles and the top-quark mass

One of the key tasks of any particle collider is measurement. In practice, this is often done by fitting data to a simulation, which depends on many parameters. Sometimes, when the effects of varying different parameters are highly correlated, a large ensemble of data may be needed to resolve parameter-space degeneracies. An important example is measuring the top-quark mass, where other physical and unphysical parameters in the simulation must be profiled when fitting the top-quark mass parameter. We compare four different methodologies for top-quark mass measurement: a classical histogram fit similar to one commonly used in experiment augmented by soft-drop jet grooming; a 2D profile likelihood fit with a nuisance parameter; a machine-learning method called DCTR; and a linear regression approach, either using a least-squares fit or with a dense linearly-activated neural network. Despite the fact that individual events are totally uncorrelated, we find that the linear regression methods work most effectively when we input an ensemble of events sorted by mass, rather than training them on individual events. Although all methods provide robust extraction of the top-quark mass parameter, the linear network does marginally best and is remarkably simple. For the top study, we conclude that the Monte-Carlo-based uncertainty on current extractions of the top-quark mass from LHC data can be reduced significantly (by perhaps a factor of 2) using networks trained on sorted event ensembles. More generally, machine learning from ensembles for parameter estimation has broad potential for collider physics measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Data-driven high-dimensional statistical inference with generative models

Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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 OSTI2019

Computed tomography-based texture analysis of bladder cancer: differentiating urothelial carcinoma from micropapillary carcinoma

Purpose: The purpose of the study is to determine the feasibility of using computed tomography-based texture analysis (CTTA) in differentiating between urothelial carcinomas (UC) of the bladder from micropapillary carcinomas (MPC) of the bladder. Methods: Regions of interests (ROIs) of computerized tomography (CT) images of 33 MPCs and 33 UCs were manually segmented and saved. Custom MATLAB code was used to extract voxel information corresponding to the ROI. The segmented tumors were input to a pre-existing radiomics platform with a CTTA panel. A total of 58 texture metrics were extracted using four different texture extraction techniques and statistically analyzed using a Wilcoxon rank-sum test to determine the differences between UCs and MPCs. Results: Of the 58 texture metrics extracted using the gray level co-occurrence matrix (GLCM) and gray level difference matrix (GLDM), 28 texture metrics were statistically significant (p < 0.05) for differences in tumor textures and 27 texture metrics were statistically significant (p < 0.05) for peritumoral fat textures. The remaining nine metrics extracted using histogram and fast Fourier transform analyses did not show significant differences between the textures of the tumors and their peritumoral fat. Conclusions: CTTA shows that MPC have a more heterogeneous texture compared to UC. As visual discrimination of MPC from UC from clinical CT scans are difficult, results from this study suggest that tumor heterogeneity extracted using GLCM and GLDM may be a good imaging aid in segregating MPC from UC. This tool can aid clinicians in further sub-classifying bladder cancers on routine imaging, a process which has potential to alter treatment and patient care.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?

Objective: To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC. Materials and methods: With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen’s kappa. Results: Tumor size was 24 ± 7 (13–39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5–100.0]) with low sensitivity (36.8% [21.8–54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94–1.0) with sensitivity/specificity 87.5%/100%. Conclusion: The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?

Purpose: To determine if texture analysis can differentiate placenta accreta spectrum (PAS) from normal placenta on MRI. Methods: We performed retrospective image analysis of 80 patients, comprised of 46 patients with PAS and 34 patients without PAS. Histopathology was used as the reference standard. Sagittal single shot fast spin echo T2-weighted MRI sequences acquired from a single institution were analyzed. Placental heterogeneity was quantified using in-house software on a Matlab platform, including the standard deviation of pixel intensity, coefficient of variation, gray-level co-occurrence matrices (GLCM), histogram-oriented gradients (HOG), and fractal analysis with box sizes from 2 to 512. Two-tailed unpaired Student’s t test was used with statistical significance of p < 0.05. Results: PAS was associated with higher values for standard deviation of pixel intensity and fractal analysis at every box size. Fractal analysis at box sizes 256 (p = 0.011) and 32 (p = 0.021), and standard deviation of pixel intensity (p = 0.023) were the most statistically significant. Fractal values at box size 256 for PAS was 0.13 versus 0.090 for patients without PAS, while standard deviation of pixel intensity was 3.7 for PAS versus 2.5 for patients without PAS. No statistically significant association between PAS and GLCM, coefficient of variation, and HOG was found. Conclusion: Statistically significant differences were found between normal and abnormal groups using standard deviation of pixel intensity and fractal analysis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Security enrichment of optical image cryptosystem based on superposition technique using fractional Hartley and gyrator transform domains deploying equal modulus decomposition

In this paper, a symmetric cryptosystem has been suggested to increase security of double random phase encoding using superposition technique in fractional Hartley transform (FrHT) and gyrator transform (GT) domains. It uses structured phase mask (SPM) and hybrid mask (HM) deploying equal modulus decomposition (EMD). Related to original phase truncated Fourier transform (PTFT) based cryptosystem, the security of encoding and decoding is upgraded by using the superposition technique. With the usage of SPM we can increase the key space while encoding and can also overcome the axis alignment difficulty. Decoding is just the reversal of the encoding method. The proposed scheme has robustness against common attacks like: noise and occlusion attacks. With the help of numerical simulation results we also show that our cryptosystem is vulnerable to various attacks. Performance of the suggested method is calculated in terms of Mean Square Error (MSE) between original and decoded image and also the sensitivity of the SPM parameters and rotational angles of GT is investigated. The competence of the suggested method includes analysis on EMD, histogram and correlation coefficient. The suggested cryptosystem is also open to the occlusion attack and noise attack to analyze its performance and evenness.

42 ENGINEERING↗
DOE OSTI2019

Image encryption and watermarking combined dynamic chaotic hopping pattern with double random phase encoding DRPE

In modern civilization information, security is a crucial problem. Image encryption and watermarking can effectively protect information from unauthorized access. This paper introduces a new vigorous symmetric optical image encryption and watermarking technique. This technique depends on a novel dynamic delay chaotic hopping pattern (DDCHP) combined with double random phase encoding (DRPE). To get a robust watermark image, the plain image is first watermarked with a binary secret message using a new chaotic hopping pattern (CHP) and then encrypted using a DRPE system that is controlled by double random independent keys generated with double DDCHP. In this symmetric cryptosystem, three different chaotic maps are used to enlarge the key space of the proposed cryptosystem against brute-force attack and overcome the linearity and vulnerable of the classical DRPE. The system keys are hypersensitive and their initial parameters are selected carefully. Security scrutiny proves the efficiency of the suggested cryptosystem. Therefore, the obtained simulation results prove that the cryptosystem is robust enough against the known attacks, such as statistical attack (uniform histograms of different encrypted images, correlation coefficients between the plain and the encrypted image is as low as 5.46 × 10{sup −6}), differential attack (99.99% NPCR and 38.6% UACI), brute force attack (large enough key space), and entropy attack. Moreover, the robustness of the watermark (secret message) is proved due to the solidity of CHP. The proposed approach can be used in different implementations like secure military communications, e-finance, e-healthcare, authenticated multimedia broadcasting, etc.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Study of the Thermomechanical Performance of FR-4 Laminates During the Reflow Process

The behavior of FR4 laminates for printed circuit boards (PCBs) during a double reflow process and the main factors associated with warpage are discussed. The microstructure, glass transition temperature (T{sub g}), decomposition temperature (T{sub d}), coefficient of thermal expansion (CTE), time to delamination and % water absorption were characterized, and the temperature profiles in the board during its pass through the reflow oven were recorded. Bow and twist measurements were taken on a set of 30 PCBs. Both T{sub d} and T{sub g} were found to be below their nominal values. The CTE is highly anisotropic and vary at different locations, and it is more than three times higher in the through thickness middle section with respect to the bottom and top locations. Temporary temperature gradients of more than 50 degrees between different locations were detected at the start of the reflow step as a result, the bow values were found to be strongly anisotropic, particularly after the first reflow, in which different sides can present bow values up to more than six times higher than others, with maxima values of 0.47 mm. The anisotropy of the CTE appears to affect only slightly the twist values. Compared with the first reflow, the bow and twist values are lower, exhibit less dispersion and are more homogeneous for the second reflow. The histograms of both bow and twist do not seem to follow a normal distribution, possibly as a result of the combined effect of spatial variations and anisotropy of properties as well as the temperature gradients during reflow.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An Algorithm to Generate Synthetic 3D Microstructures from 2D Exemplars

The inverse problem of constructing 3D microstructures from 2D data is an area of active research within the materials science community. This paper presents the implementation of a robust, computationally efficient algorithm, Hierarchical Algorithm for the Reconstruction of Exemplars (HARE), written in Python to reconstruct 3D features in a given microstructure from up to three orthogonal 2D exemplars using nearest neighbor matching to reproduce feature qualities, such as shape, size, and distribution. HARE’s feature sampling implements histogram reweighting to avoid both over- and undersampling. A neighborhood voting scheme allows each pixel to provisionally affect its neighbors according to its weight. Finally, the algorithm is presently configured for two-phase materials and is being extended to accommodate multiple phases. HARE is a convenient and robust base from which to generate statistically representative synthetic microstructures for use in multi-scale modeling or machine learning applications to support advanced manufacturing and materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Comparison of CZT SPECT and conventional SPECT for assessment of contractile function, mechanical synchrony and myocardial scar in patients with heart failure

Aim: The aim of this study was to compare CZT-SPECT (CZT SPECT) to conventional SPECT (C-SPECT) in the assessment of left ventricular myocardial scar, contractile function, and mechanical synchrony in patients with heart failure (HF). Methods: Fifty-nine patients with HF who were referred for myocardial perfusion/metabolism imaging were enrolled. All patients underwent resting {sup 99m}Tc-MIBI gated myocardial perfusion imaging using a CZT SPECT camera and a C-SPECT camera, respectively, and {sup 18}F-FDG PET myocardial metabolism imaging within three days. Summed rest score (SRS) and total perfusion defect (TPD) (as indices of perfusion abnormality), left ventricular (LV), end diastolic volume (EDV), end systolic volume (ESV), and ejection fraction (EF) (as indices of LV systolic function), and histogram band width (BW) and standard deviation (SD) (as indices of mechanical synchrony) were analyzed by automated software while the perfusion/metabolism patterns were analyzed visually. Results: There was a good correlation between CZT SPECT and C-SPECT for SRS and TPD. CZT SPECT tended to underestimate SRS and TPD compared to C-SPECT. CZT-SPECT and C-SPECT showed excellent agreement in assessing the perfusion/metabolism pattern though a small proportion of normal segments (6.6%) identified by CZT/PET exhibited mismatch pattern on C-SPECT/PET. CZT SPECT also showed excellent correlation with C-SPECT in measuring EDV, ESV, and EF. Finally, BW and SD measured by CZT SPECT correlated well with C-SPECT but CZT SPECT tended to overestimate BW and SD compared to C-SPECT. Conclusion: CZT SPECT provided comparable data to C-SPECT for measuring LV scar, function and synchrony at a considerable reduction in imaging time. CZT SPECT holds a promise for comprehensive evaluation of myocardial performance in patients with HF.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Physical Regime Sensitivity

Abstract This work presents a novel sensitivity approach that quantifies sensitivity to regimes of a model’s state variables rather than constitutive model parameters. This Physical Regime Sensitivity (PRS) determines which regimes of a model’s independent variables have the biggest influence on an experiment or application. PRS analysis is demonstrated on a strength model used in the simulation of a copper Taylor cylinder. In a series of simulations, the strength model was perturbed sequentially in local regimes of plastic strain, plastic strain rate, temperature and pressure, and then the prediction of cylinder shape was compared to unperturbed calculations. Results show, for example, that the deformed length of the cylinder was most sensitive to strength at a strain rate of 1.0 × 10 4 /sec., but the deformed footprint radius was most sensitive to strength at a strain rate of about 4.0 × 10 4 /sec. Compared to current histogram approaches, PRS can be used to design or interpret integrated experiments by identifying not just which regimes are accessed somewhere in the experiment but the causality question of which regimes actually affect the measured data. PRS should allow one to focus experimental and modeling efforts where they are most needed and to better interpret experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

GPU acceleration and performance of the particle-beam-dynamics code Elegant

Elegant is an accelerator physics and particle-beam dynamics code widely used for modeling and design of a variety of high-energy particle accelerators and accelerator-based systems. We discuss a recently developed version of the code that can take advantage of CUDA-enabled graphics processing units (GPUs) to achieve significantly improved performance for a large class of simulations that are important in practice. The GPU version is largely defined by a framework that simplifies implementations of the fundamental kernel types that are used by Elegant: particle operations, reductions, particle loss, histograms, array convolutions and random number generation. Accelerated performance on the Titan Cray XK-7 supercomputer is approximately 6–10 times better with the GPU than all the CPU cores associated with the same node count. In addition to performance, the maintainability of the GPU-accelerated version of the code was considered a key design objective. Accuracy with respect to the CPU implementation is also a core consideration. Finally, four different methods are used to ensure that the accelerated code faithfully reproduces the CPU results.

43 PARTICLE ACCELERATORS↗