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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

The development of multi-dimensional statistical methods has been demonstrated on variable contact time (VCT) 29 Si{ 1 H} cross-polarization magic angle spinning (CP/MAS) data sets collected using Carr–Purcell–Meiboom–Gill (CPMG) type acquisition. These methods utilize the transformation of the collected 2D VCT data set into a 3D data set and use tensor-rank decomposition to extract the spectral components that vary as a function of transverse relaxation time ( T 2 ) and CP contact time. The result is a data dense spectral set that can be used to reconstruct CP/MAS spectra at any contact time with a high signal to noise ratio and with an excellent agreement to 29 Si{ 1 H} CP/MAS spectra collected using conventional acquisition. These CPMG data can be collected in a fraction of time that would be required to collect a conventional VCT data set. Here, we demonstrate the method on samples of functionalized mesoporous silica materials and show that the method can provide valuable surface specific information about their functional chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reconstruction of effective potential from statistical analysis of dynamic trajectories

The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Improved Statistical Analysis for the Neutrinoless Double-Beta Decay Matrix Element of 136Xe

Neutrinoless double beta decay nuclear matrix element (M0ν) for 136Xe was recently analyzed using a statistical approach (Phys. Rev. C 107, 045501 (2023)). In the analysis, three initial shell model effective Hamiltonians were randomly altered, and their results for 23 measured observables were used to infer credibility for the M0ν nuclear matrix element (NME) based on a Bayesian Model Averaging approach. In that analysis, a reasonable Gamow-Teller quenching factor of 0.7 was assumed for each starting effective Hamiltonian. Given that the result of the statistical analysis was sensible to this choice, we are here improving that analysis by assuming that the Gamow-Teller quenching factor is also randomly chosen within reasonabe limits for all three starting Hamiltonians. The outcomes are slightly higher expectation values and uncertainties for the M0ν NME.

Astronomy & Astrophysics↗
DOE OSTI2015

Classification of Malaysia aromatic rice using multivariate statistical analysis

Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC–MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Rapid Characterization and Statistical Analysis of High-Volume Field-Harvested Photovoltaic Connectors

Photovoltaic (PV) installations heavily depend on connectors for efficient module and string interconnections without requiring skilled labor. Yet this seemingly innocuous component of PV systems is a leading cause of module failures, multiple high-profile fires, and lawsuits in the PV industry. This work aims to answer critical questions regarding why connectors fail and the contributing factors to their failure. The study involves collecting and analyzing more than 17,000 field-harvested connectors from various solar installations across the United States. The vast dataset, which includes connector metadata, visual inspections, and resistance measurements, provides unprecedented insight into the state of health of PV connectors across the US, including the geographic locations, connector types, and installation practices most prone to failures. The work presented here describes a novel rapid characterization method for processing large numbers of connectors and is supported by parallel forensic analysis to discern the root causes of failures as well as a levelized cost of lifetime model to determine the economic ramifications of connector failure. Ultimately, the findings may inform PV developers about the best practices to extend connector longevity and lead to more resilient and reliable PV systems.

connectors↗
DOE OSTI2021

Statistical analysis of correlations in the x-ray induced Coulomb explosion of iodopyridine

Coulomb explosion imaging is a promising experimental tool to study individual molecules. Here, in this work simulation data for the x-ray induced Coulomb explosion of 2-iodopyridine is analyzed and the involved fragmentation dynamics are described. It is found that particular final ion momenta show correlations that reflect a collision of two atoms during the explosion. Variations of the proton kinetic energies can be associated with variations in the charge build-up time. Covariances of the forces during the explosion can be utilized to simplify the description of the dynamics in reduced dimensionality using only four collective coordinates.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Statistical analysis of non-Maxwellian electron distribution functions measured with angularly resolved Thomson scattering

Angularly resolved Thomson scattering is a novel extension of Thomson scattering, enabling the measurement of the electron velocity distribution function over many orders of magnitude. Here, details of the theoretical basis of the technique and the instrument designed for this measurement are described. Angularly resolved Thomson-scattering data from several experiments are shown with descriptions of the corresponding distribution functions. A reduced model describing the distribution function is given and used to perform a Monte Carlo analysis of the uncertainty in the measurements. The electron density and temperature were determined to a precision of 12% and 21%, respectively, on average, while all other parameters defining the distribution function were generally determined to better than 20%. It was found that these uncertainties were primarily due to limited signal to noise and instrumental effects. Furthermore, measurements with this level of precision were sufficient to distinguish between Maxwellian and non-Maxwellian distribution functions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Parallel Hybrid Metaheuristics with Distributed Intensification and Diversification for Large-scale Optimization in Big Data Statistical Analysis

Important insights into many problems that are traditionally analyzed via statistical models can be obtained by re-formulating and evaluating within a large-scale optimization framework. The theoretical underpinnings of the statistical model often shift the goal of the solution space traversal from a traditional search for a single optimal solution to a traversal with the purpose of yielding a set of high quality, independent solutions. We examine statistical frameworks with astronomical solution spaces where the independence requirement constitutes a significant additional challenge for standard optimization methodologies. We design a hybrid metaheuristic with specialized intensification and diversification protocols in the base search algorithm. We extend our algorithm to the high-performance-computing realm using the Stampede2 supercomputer. We experimentally demonstrate the effectiveness of our algorithm to utilize multiple processors to collaboratively hill climb, broadcast messages to one another regarding landscape characteristics, diversify across the solution landscape, and request aid in climbing particularly difficult peaks.

Cho, Wendy K. Tam↗
DOE OSTI2014

Dose impact in radiographic lung injury following lung SBRT: Statistical analysis and geometric interpretation

Purpose: To demonstrate a new method of evaluating dose response of treatment-induced lung radiographic injury post-SBRT (stereotactic body radiotherapy) treatment and the discovery of bimodal dose behavior within clinically identified injury volumes. Methods: Follow-up CT scans at 3, 6, and 12 months were acquired from 24 patients treated with SBRT for stage-1 primary lung cancers or oligometastic lesions. Injury regions in these scans were propagated to the planning CT coordinates by performing deformable registration of the follow-ups to the planning CTs. A bimodal behavior was repeatedly observed from the probability distribution for dose values within the deformed injury regions. Based on a mixture-Gaussian assumption, an Expectation-Maximization (EM) algorithm was used to obtain characteristic parameters for such distribution. Geometric analysis was performed to interpret such parameters and infer the critical dose level that is potentially inductive of post-SBRT lung injury. Results: The Gaussian mixture obtained from the EM algorithm closely approximates the empirical dose histogram within the injury volume with good consistency. The average Kullback-Leibler divergence values between the empirical differential dose volume histogram and the EM-obtained Gaussian mixture distribution were calculated to be 0.069, 0.063, and 0.092 for the 3, 6, and 12 month follow-up groups, respectively. The lower Gaussian component was located at approximately 70% prescription dose (35 Gy) for all three follow-up time points. The higher Gaussian component, contributed by the dose received by planning target volume, was located at around 107% of the prescription dose. Geometrical analysis suggests the mean of the lower Gaussian component, located at 35 Gy, as a possible indicator for a critical dose that induces lung injury after SBRT. Conclusions: An innovative and improved method for analyzing the correspondence between lung radiographic injury and SBRT treatment dose has been demonstrated. Bimodal behavior was observed in the dose distribution of lung injury after SBRT. Novel statistical and geometrical analysis has shown that the systematically quantified low-dose peak at approximately 35 Gy, or 70% prescription dose, is a good indication of a critical dose for injury. The determined critical dose of 35 Gy resembles the critical dose volume limit of 30 Gy for ipsilateral bronchus in RTOG 0618 and results from previous studies. The authors seek to further extend this improved analysis method to a larger cohort to better understand the interpatient variation in radiographic lung injury dose response post-SBRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Structure retrieval from four-dimensional scanning transmission electron microscopy: Statistical analysis of potential pitfalls in high-dimensional data

Four-dimensional (4D) scanning transmission electron microscopy is one of the most rapidly growing modes of electron microscopy imaging. The advent of fast pixelated cameras and the associated data infrastructure have greatly accelerated this process. Yet conversion of the 4D datasets into physically meaningful structure images in real space remains an open issue. In this work, we demonstrate that it is possible to systematically create filters that will affect the apparent resolution or even qualitative features of the real-space structure image, reconstructing artificially generated patterns. As initial efforts, we explore statistical model selection algorithms, aiming for robustness and reliability of estimated filters. This statistical model selection analysis demonstrates the need for regularization and cross validation of inversion methods to robustly recover structure from high-dimensional diffraction datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Turbulence statistical analysis of the L-H transition and RMPs in KSTAR

Here, we investigate the turbulence statistics associated with low-to-high confinement (L-H) transitions and externally applied resonant magnetic perturbations (RMPs) in KSTAR. Time-series fluctuations of electron density n e , electron temperature T e , and the time derivative of the poloidal magnetic field dB θ /dt (Mirnov coils) are analysed using information-geometric measures (information rate Γ and information length $\mathcal{L}$ = ∫ Γ dt), together with kurtosis κ and variance σ 2 . In low-density upper single-null plasmas (n e ~ 1.2 x 10 19 m -3 ), a ~80 kHz magnetic mode coupling n e , T e , dB θ /dt and emerges prior to the L-H transition and persists into the edge-localised modes H-mode. Edge-localised RMPs (ERMPs) suppress this coherent mode but enhance intermittency, producing frequent bursts that abruptly reshape the time-dependent probability density functions (PDFs) and generate large spikes in Γ (with smaller changes in κ), signalling ERMP-driven departures from quasi-stationarity. The impact of ERMPs on background fluctuation levels depends on density, radial location, and the fluctuating variable itself ($\tilde{n}$, $\tilde{T}$, $\dot{B}$ θ ), whereas $\mathcal{L}$ provides a robust, regime-agnostic measure of cumulative statistical reorganisation and spatial decorrelation. In particular, at low density we observe weaker coupling between $\tilde{n}$ and $\tilde{T}$, along with a tendency toward decreased radial correlation-most clearly for $\tilde{T}$-under ERMPs. Overall, information geometry cleanly captures intermittent events, quantifies non-equilibrium PDF evolution, and offers a compact, cross-diagnostic metric for assessing resonant magnetic perturbation effects on edge transport and correlation across densities, radial locations, and confinement states.

Kim, Eun-jin [Coventry Univ. (United Kingdom); Seo↗
DOE OSTI2013

An experimental statistical analysis of stress projection factors in BCC tantalum

Crystallographic slip planes in body centered cubic (BCC) metals are not fully understood. In polycrystals, there are additional confounding effects from grain interactions. This paper describes an experimental investigation into the effects of grain orientation and neighbors on elastic–plastic strain accumulation. In situ strain fields were obtained by performing digital image correlation (DIC) on images from a scanning electron microscope (SEM) and from optical microscopy. These strain fields were statistically compared to the grain structure measured by electron backscatter diffraction (EBSD). Spearman rank correlations were performed between effective strain and six microstructural factors including four Schmid factors associated with the <111> slip direction, grain size, and Taylor factor. Modest correlations (~10%) were found for a polycrystal tension specimen. The influence of grain neighbors was first investigated by re-correlating the polycrystal data using clusters of similarly-oriented grains identified by low grain boundary misorientation angles. Second, the experiment was repeated on a tantalum oligocrystal, with through-thickness grains. Much larger correlation coefficients were found in this multicrystal due to the dearth of grain neighbors and subsurface microstructure. Finally, a slip trace analysis indicated (in agreement with statistical correlations) that macroscopic slip often occurs on {110}<111> slip systems and sometimes by pencil glide on maximum resolved shear stress planes (MRSSP). These results suggest that Schmid factors are suitable for room temperature, quasistatic, tensile deformation in tantalum as long as grain neighbor effects are accounted for.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Statistical analysis of an inter-laboratory comparison of small-scale safety and thermal testing of RDX

In this study, the Integrated Data Collection Analysis (IDCA) program has conducted a proficiency test for small-scale safety and thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results from this test for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Class 5 Type II standard. The material was tested as a well-characterized standard several times during the proficiency test to assess differences among participants and the range of results that may arise for well-behaved explosive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Statistical analysis of HAADF-STEM images to determine the surface coverage and distribution of immobilized molecular complexes

The surface immobilization of molecular catalysts is attractive because it combines the benefits of homogeneous and heterogeneous catalysis. However, determining the surface coverage and distribution of a molecular catalyst on a solid support is often challenging, inhibiting our ability to design improved catalytic systems. Here, in this work, we demonstrate that the combination of scanning transmission electron microscopy (STEM) and image analysis of the individual positions of heavy atoms in transition metal complexes via a convolutional neural network (CNN) allows statistically robust determination of the surface coverage and distribution of immobilized molecular catalysts. These observations provide information about how changes in the functionalization conditions, attachment group, and structure of the molecular catalyst affect the surface coverage and distribution, providing insight into the chemical mechanism of surface immobilization. The method could be generally valuable for correlating the surface coverage and distribution to the activity, selectivity, and stability of a catalytic system.

HAADF-STEM↗
DOE OSTI2017

Statistical Analysis of CO 2 Exposed Wells to Predict Long Term Leakage through the Development of an Integrated Neural-Genetic Algorithm

The objective of this project is to develop a computerized statistical model with the Integrated Neural-Genetic Algorithm (INGA) for predicting the probability of long-term leak of wells in CO 2 sequestration operations. This object has been accomplished by conducting research in three phases: 1) data mining of CO 2 -explosed wells, 2) INGA computer model development, and 3) evaluation of the predictive performance of the computer model with data from field tests. Data mining was conducted for 510 wells in two CO 2 sequestration projects in the Texas Gulf Coast region. They are the Hasting West field and Oyster Bayou field in the Southern Texas. Missing wellbore integrity data were estimated using an analytical and Finite Element Method (FEM) model. The INGA was first tested for performances of convergence and computing efficiency with the obtained data set of high dimension. It was concluded that the INGA can handle the gathered data set with good accuracy and reasonable computing time after a reduction of dimension with a grouping mechanism. A computerized statistical model with the INGA was then developed based on data pre-processing and grouping. Comprehensive training and testing of the model were carried out to ensure that the model is accurate and efficient enough for predicting the probability of long-term leak of wells in CO 2 sequestration operations. The Cranfield in the southern Mississippi was select as the test site. Observation wells CFU31F2 and CFU31F3 were used for pressure-testing, formation-logging, and cement-sampling. Tools run in the wells include Isolation Scanner, Slim Cement Mapping Tool (SCMT), Cased Hole Formation Dynamics Tester (CHDT), and Mechanical Sidewall Coring Tool (MSCT). Analyses of the obtained data indicate no leak of CO 2 cross the cap zone while it is evident that the well cement sheath was invaded by the CO 2 from the storage zone. This observation is consistent with the result predicted by the INGA model which indicates the well has a CO 2 leak-safe probability of 72%. This comparison implies that the developed INGA model is valid for future use in predicting well leak probability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same is for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for 4D-based clinical technologies, can be better controlled if nonlinear-based methodology, which reflects respiration characteristic, is applied. Funding provided by Varian Medical Systems via Investigator Initiated Research Project.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Mathematical and statistical analysis of the effect of boron on yield parameters of wheat

The main objective of this research is to investigate the effect of foliar applications of boron at different growth stages on yield and yield parameters of wheat. The contribution of boron in achieving yield parameters is described by second degree polynomial equations, with high statistical confidence (p<0.01; F theoretical < F calculated, according to ANOVA test, for Alfa = 0.05). Regression analysis, based on R{sup 2} values obtained, made it possible to evaluate the particular contribution of boron to the realization of yield parameters. This was lower for spike length (R{sup 2} = 0.812), thousand seeds weight (R{sup 2} = 0.850) and higher in the case of the number of spikelets (R{sup 2} = 0.936) and the number of seeds on a spike (R{sup 2} = 0.960). These results confirm that boron plays an important part in achieving the number of seeds on a spike in the case of wheat, as the contribution of this element to the process of flower fertilization is well-known. In regards to productivity elements, the contribution of macroelements to yield quantity is clear, the contribution of B alone being R{sup 2} = 0.868.

60 APPLIED LIFE SCIENCES↗