Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Statistical techniques”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Statistical chronometry of Meteorites: II. Initial abundances and homogeneity of short-lived radionuclides

Astrophysical models of planet formation require accurate radiometric dating of meteoritic components by short-lived (Al-Mg, Mn-Cr, Hf-W) and long-lived (U-Pb) chronometers, to develop a timeline of such events in the solar nebula as formation of Ca-rich, Al-rich Inclusions (CAIs), chondrules, planetesimals, etc. CAIs formed mostly around a time (“t=0”) when the short-lived radionuclide 26 Al (t 1/2 = 0.72 Myr) was present and presumably homogeneously distributed at a known level we define as ( 26 Al/ 27 Al) SS = 5.23 × 10 -5 . The time of formation after t=0 of another object can be found by determining its initial ( 26 Al/ 27 Al) 0 ratio and comparing it to ( 26 Al/ 27 Al) SS . Dating of meteoritic objects using the Mn-Cr or Hf-W systems is hindered because the abundances ( 53 Mn/ 55 Mn) SS and ( 182 Hf/ 180 Hf) SS at t=0 are not known precisely. To constrain these quantities, we compile literature Al-Mg, Mn-Cr, Hf-W and Pb-Pb data for 13 achondrites and use novel statistical techniques to minimize the discrepancies between their times of formation across these systems. We find that for ( 53 Mn/ 55 Mn) SS = (7.80±0.36)×10 -6 , ( 182 Hf/ 180 Hf) SS = (10.41 ± 0.12) × 10-5, t SS = 4568.65 ± 0.10 Myr, and a 53 Mn half-life of 3.98 ± 0.22 Myr, these four free parameters make concordant 18 formation times recorded by the different systems in all six known volcanic achondrites (the quenched angrites D’Orbigny, Sahara 99555, Northwest Africa 1670; the psuedo-eucrites Asuka 881394 and Ibitira; and the basaltic achondrite Northwest Africa 7325). These parameters also make concordant the ages derived for chondrules from CB/CH achondrites, formed simultaneously in an impact. The other seven achondrites are not quite concordant, but are plutonic angrites or ‘carbonaceous achondrites’ for which simultaneous closure of the isotopic systems might not be expected. Our findings provide very strong support for homogeneity of 26 Al, 53 Mn, and 182 Hf in the solar nebula, and our approach offers a path for more precise chronometry

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Metallic Metal–Organic Frameworks Predicted by the Combination of Machine Learning Methods and Ab Initio Calculations

Emerging applications of metal–organic frameworks (MOFs) in electronic devices will benefit from the design and synthesis of intrinsically, highly electronically conductive MOFs. However, very few are known to exist. It is a challenging task to search for electronically conductive MOFs within the tens of thousands of reported MOF structures. Using a new strategy (i.e., transfer learning) of combining machine learning techniques, statistical multivoting, and ab initio calculations, we screened 2932 MOFs and identified 6 MOF crystal structures that are metallic at the level of semilocal DFT band theory: Mn 2 [Re 6 X 8 (CN) 6 ] 4 (X = S, Se,Te), Mn[Re 3 Te 4 (CN) 3 ], Hg[SCN] 4 Co[NCS] 4 , and CdC 4 . Five of these structures have been synthesized and reported in the literature, but their electrical characterization has not been reported. In conclusion, our work demonstrates the potential power of machine learning in materials science to aid in down-selecting from large numbers of potential candidates and provides the information and guidance to accelerate the discovery of novel advanced materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
DOE OSTI2024

Atomic resolution coherent x-ray imaging with physics-based phase retrieval

Coherent x-ray imaging and scattering from accelerator based sources such as synchrotrons continue to impact biology, medicine, technology, and materials science. Many synchrotrons around the world are currently undergoing major upgrades to increase their available coherent x-ray flux by approximately two orders of magnitude. The improvement of synchrotrons may enable imaging of materials in operando at the atomic scale which may revolutionize battery and catalysis technologies. Current algorithms used for phase retrieval in coherent x-ray imaging are based on the projection onto sets method. These traditional iterative phase retrieval methods will become more computationally expensive as they push towards atomic resolution and may struggle to converge. Additionally, these methods do not incorporate physical information that may additionally constrain the solution. In this work, we present an algorithm which incorporates molecular dynamics into Bragg coherent diffraction imaging (BCDI). This algorithm, which we call PRAMMol (Phase Retrieval with Atomic Modeling and Molecular Dynamics) combines statistical techniques with molecular dynamics to solve the phase retrieval problem. We present several examples where our algorithm is applied to simulated coherent diffraction from 3D crystals and show convergence to the correct solution at the atomic scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

The geostatistical approach for structural and stratigraphic framework analysis of offshore NW Bonaparte Basin, Australia

Geostatistics or statistical approach is based on the studies of temporal and spatial trend, which depend upon spatial relationships to model known information of variable(s) at unsampled locations. The statistical technique known as kriging was used for petrophycial and facies analysis, which help to assume spatial relationship to model the geological continuity between the known data and the unknown to produce a single best guess of the unknown. Kriging is also known as optimal interpolation technique, which facilitate to generate best linear unbiased estimation of each horizon. The idea is to construct a numerical model of the lithofacies and rock properties that honor available data and further integrate with interpreting seismic sections, techtonostratigraphy chart with sea level curve (short term) and regional tectonics of the study area to find the structural and stratigraphic growth history of the NW Bonaparte Basin. By using kriging technique the models were built which help to estimate different parameters like horizons, facies, and porosities in the study area. The variograms were used to determine for identification of spatial relationship between data which help to find the depositional history of the North West (NW) Bonaparte Basin.

58 GEOSCIENCES↗
DOE OSTI2018

Correlation electron cyclotron emission diagnostic and improved calculation of turbulent temperature fluctuation levels on ASDEX Upgrade

A newly upgraded correlation electron cyclotron emission (CECE) diagnostic has been installed on the ASDEX Upgrade tokamak and has begun to perform experimental measurements of electron temperature fluctuations. CECE diagnostics measure small amplitude electron temperature fluctuations by correlating closely spaced heterodyne radiometer channels. This upgrade expanded the system from six channels to thirty, allowing simultaneous measurement of fluctuation level radial profiles without repeat discharges, as well as opening up the possibility of measuring radial turbulent correlation lengths. Newly refined statistical techniques have been developed in order to accurately analyze the fluctuation data collected from the CECE system. This paper presents here the hardware upgrades for this system and the analysis techniques used to interpret the raw data, as well as measurements of fluctuation spectra and fluctuation level radial profiles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

EVIDENCE FOR (AND AGAINST) PROGENITOR BIAS IN THE SIZE GROWTH OF COMPACT RED GALAXIES

Most massive, passive galaxies are compact at high redshifts, but similarly compact massive galaxies are rare in the local universe. The most common interpretation of this phenomenon is that massive galaxies have grown in size by a factor of about five since redshift z = 2. An alternative explanation is that recently quenched massive galaxies are larger (a {sup p}rogenitor bias{sup )}. In this paper, we explore the importance of progenitor bias by looking for systematic differences in the stellar populations of compact early-type galaxies in the DEEP2 survey as a function of size. Our analysis is based on applying the statistical technique of bootstrap resampling to constrain differences in the median ages of our samples and to begin to characterize the distribution of stellar populations in our co-added spectra. The light-weighted ages of compact early-type galaxies at redshifts 0.5 < z < 1.4 are compared to those of a control sample of larger galaxies at similar redshifts. We find that massive compact early-type galaxies selected on the basis of red color and high bulge-to-total ratio are younger than similarly selected larger galaxies, suggesting that size growth in these objects is not driven mainly by progenitor bias, and that individual galaxies grow as their stellar populations age. However, compact early-type galaxies selected on the basis of image smoothness and high bulge-to-total ratio are older than a control sample of larger galaxies. Progenitor bias will play a significant role in defining the apparent size changes of early-type galaxies if they are selected on the basis of the smoothness of their light distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Testing averaged cosmology with type Ia supernovae and BAO data

An important problem in precision cosmology is the determination of the effects of averaging and backreaction on observational predictions, particularly in view of the wealth of new observational data and improved statistical techniques. In this paper, we discuss the observational viability of a class of averaged cosmologies which consist of a simple parametrized phenomenological two-scale backreaction model with decoupled spatial curvature parameters. We perform a Bayesian model selection analysis and find that this class of averaged phenomenological cosmological models is favored with respect to the standard ΛCDM cosmological scenario when a joint analysis of current SNe Ia and BAO data is performed. In particular, the analysis provides observational evidence for non-trivial spatial curvature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression

Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. Further, we provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Interpolating between small- and large-$\mathscr{g}$ expansions using Bayesian model mixing

Bayesian model mixing (BMM) is a statistical technique that can be used to combine models that are predictive in different input domains into a composite distribution that has improved predictive power over the entire input space. We explore the application of BMM to the mixing of two expansions of a function of a coupling constant $\mathscr{g}$ that are valid at small and large values of $\mathscr{g}$ respectively. This type of problem is quite common in nuclear physics, where physical properties are straightforwardly calculable in strong and weak interaction limits or at low and high densities or momentum transfers, but difficult to calculate in between. Interpolation between these limits is often accomplished by a suitable interpolating function, e.g., Padé approximants, but it is then unclear how to quantify the uncertainty of the interpolant. We address this problem in the simple context of the partition function of zero-dimensional Φ 4 theory, for which the (asymptotic) expansion at small $\mathscr{g}$ and the (convergent) expansion at large $\mathscr{g}$ are both known. We consider three mixing methods: linear mixture BMM, localized bivariate BMM, and localized multivariate BMM with Gaussian processes. Here, we find that employing a Gaussian process in the intermediate region between the two predictive models leads to the best results of the three methods. The methods and validation strategies we present here should be generalizable to other nuclear physics settings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

α -decay energies of superheavy nuclei: Systematic trends

Background: New superheavy nuclei are often identified through their characteristic α -decay energies, which requires accurate calculations of Q α values. While many Q α predictions are available, little is known about their uncertainties, and this makes it difficult to carry out extrapolations to as-yet-unknown systems. Purpose: This work aims to analyze several models, compare their predictions to available experimental data, and study their performance for the unobserved α-decay chains of 296 120 and 298 120, which are of current experimental interest. Our quantified results will also serve as a benchmark for future, more sophisticated statistical studies. Methods: We use nuclear superfluid density functional theory (DFT) with several Skyrme energy density functionals (EDFs). To estimate systematic model uncertainties, we employ uniform model averaging. Results: We investigated the Q α values for even-even nuclei from Fm to Z = 120 . For well-deformed nuclei between Fm and Ds, we find excellent consistency between different model predictions, and a good agreement with experimental results. For transitional nuclei beyond Ds, intermodel differences grow, resulting in an appreciable systematic error. In particular, our models underestimate Q α for the heaviest nucleus 294 Og. Conclusions The robustness of DFT predictions for well-deformed superheavy nuclei supports the idea of using experimental Q α values, together with theoretical predictions, as reasonable ( Z, A ) indicators. Unfortunately, this identification method is not projected to work well in the region of deformed-to-spherical shape transition as one approaches N = 184 . The use of Q α values in the identification of new superheavy nuclei will benefit greatly from progress in developing both new spectroscopic-quality EDFs and more sophisticated statistical techniques of uncertainty quantification.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Lattice quantum chromodynamics at large isospin density

We present an algorithm to compute correlation functions for systems with the quantum numbers of many identical mesons from lattice quantum chromodynamics (QCD). The algorithm is numerically stable and allows for the computation of n-pion correlation functions for n ϵ {1, … , N} using a single N × N matrix decomposition, improving on previous algorithms. We apply the algorithm to calculations of correlation functions with up to 6144 charged pions using two ensembles of gauge field configurations generated with quark masses corresponding to a pion mass m π = 170 MeV and spacetime volumes of (4.4 3 × 8.8) fm 4 and (5.8 3 × 11.6) fm 4 . We also discuss statistical techniques for the analysis of such systems, in which the correlation functions vary over many orders of magnitude. In particular, we observe that the many-pion correlation functions are well-approximated by log-normal distributions, allowing the extraction of the energies of these systems. Using these energies, the large-isospin-density, zero-baryon-density region of the QCD phase diagram is explored. A peak is observed in the energy density at an isospin chemical potential μ I ~ 1.5m π , signaling the transition into a Bose-Einstein condensed phase. The isentropic speed of sound, c s , in the medium is seen to exceed the ideal-gas (conformal) limit ($c^{2}_{s} ≤ 1/3)$ over a wide range of chemical potential before falling towards the asymptotic expectation at μ I ~ 15m π . These, and other thermodynamic observables, indicate that the isospin chemical potential must be large for the system to be well described by an ideal gas or perturbative QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Dark matter constraints from a joint analysis of dwarf Spheroidal galaxy observations with VERITAS

We present constraints on the annihilation cross section of weakly interacting massive particles dark matter based on the joint statistical analysis of four dwarf galaxies with VERITAS. These results are derived from an optimized photon weighting statistical technique that improves on standard imaging atmospheric Cherenkov telescope (IACT) analyses by utilizing the spectral and spatial properties of individual photon events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Constraining the equation of state of superhadronic matter from heavy-ion collisions

The equation of state of QCD matter for temperatures near and above the quark-hadron transition (~165 MeV) is inferred within a Bayesian framework through the comparison of data from the Relativistic Heavy Ion Collider and from the Large Hadron Collider to theoretical models. State-of-the-art statistical techniques are applied to simultaneously analyze multiple classes of observables while varying 14 independent model parameters. Thus, the resulting posterior distribution over possible equations of state is consistent with results from lattice gauge theory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

A Framework for Counterfeit Smart Grid Device Detection

The core vision of the smart grid concept is the realization of reliable two-­way communications between smart devices (e.g., IEDs, PLCs, PMUs). The benefits of the smart grid also come with tremendous security risks and new challenges in protecting the smart grid systems from cyber threats. Particularly, the use of untrusted counterfeit smart grid devices represents a real problem. Consequences of propagating false or malicious data, as well as stealing valuable user or smart grid state information from counterfeit devices are costly. Hence, early detection of counterfeit devices is critical for protecting smart grid’s components and users. To address these concerns, in this poster, we introduce our initial design of a configurable framework that utilize system call tracing, library interposition, and statistical techniques for monitoring and detection of counterfeit smart grid devices. In our framework, we consider six different counterfeit device scenarios with different smart grid devices and adversarial seZings. Our initial results on a realistic testbed utilizing actual smart-­grid GOOSE messages with IEC-­61850 communication protocol are very promising. Our framework is showing excellent rates on detection of smart grid counterfeit devices from impostors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Time-of-flight neutron spectrum unfolding for mixed-oxide nuclear fuel and plutonium metal using a dual-particle imager

A dual-particle imager with sensitivity to both neutrons and photons has been developed for the detection of special nuclear material. This system has the capability to provide spectral information on detected sources that is useful for safeguard applications. In nuclear facilities with high photon background rates, neutron detection can aid in identification and verification capabilities. The dual-particle imager creates a reconstructed neutron spectrum by correlating neutron counts in pairs of liquid scintillators. The reconstructed spectrum, a combination of energy deposited and time-of-flight, contains resolution effects that blur the true, emitted source-spectrum. To reduce the impact of resolution effects, the reconstructed spectrum can be unfolded to create an estimated source spectrum. A statistical technique, maximum-likelihood expectation-maximization, has been shown to produce an unfolded result for Cf-252 and Am-Be. This technique requires a system response-matrix that contains reconstructed spectra for single neutron energies. Since measuring mono-energetic neutrons is difficult, the system-response-matrix is simulated. Monte Carlo modeling with MCNPX-PoliMi has been show to produce an accurate system response. This work expands on previous neutron unfolding results by showing results for mixed-oxide fuel and plutonium metal measured with the dual-particle imager. Furthermore these results also demonstrate the ability of the dual-particle imager to discrimination between spontaneous fission neutrons and (α,n) reaction neutrons.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Characterization and differentiation of aluminum powders used in improvised explosive devices. Part 2: Micromorphometric method refinement and preliminary statistical analysis

Abstract Aluminum (Al) powder is commonly encountered in improvised explosive devices (IEDs) as a metallic fuel due to its availability and low cost. Although available commercially in powder form, amateur bomb‐makers also produce their own Al powder via simple methods found online. In order to provide investigative leads and forensic intelligence, it is important to evaluate not only the composition of homemade devices, but also to distinguish between the various forms of Al powder they contain. To achieve this goal, a method using automated microscopy in combination with statistical techniques has been demonstrated to have the potential to provide source discrimination and investigative leads in source attribution of Al powders in IEDs. The present research refined this method and investigated 59 industrially and amateurly produced Al powder sources with seven subsamples per source using two traditional linear discriminant analyses (LDA), one with a standard data split for training and testing, and another using leave‐one‐out cross‐validation. Averaging the classification accuracies for the two LDA‐based analyses, LDA has the ability to correctly classify 59.26%, 83.35%, and 80.69% of the samples based on their powder source, type, and production method, respectively. This classification accuracy represents a 3407%, 317%, and 61.38% increase in accuracy from random class assignment, respectively. Further, in most instances of incorrect data attribution to a particular source, the subsample has been misidentified with another sample of the same powder type or production method.

Ommen, Danica M.↗
DOE OSTI2016

Effects of sample design and landscape features on a measure of environmental heterogeneity

Environmental heterogeneity, an important influence on organisms and ecological processes, can be quantified by the variance of an environmental characteristic over all locations within a study extent. However on landscapes with autocorrelation and gradient patterns, estimating this variance from a sample of locations may lead to errors that cannot be corrected with statistical techniques. We analytically derived the relative expected sampling error of sample designs on landscapes with particular gradient pattern and autocorrelation features. We applied this closed-form approach to temperature observations from an existing study. The expected heterogeneity differed, both in magnitude and direction, amongst sample designs over the study site's likely range of autocorrelation and gradient features. We conducted a simulation study to understand the effects of (i) landscape variability and (ii) design variability on an average sampling error. On 10 000 simulated landscapes with varying gradient and autocorrelation features, we compared estimates of variance from a variety of structured and random sample designs. While gradient patterns and autocorrelation cause large errors for some designs, others yield near-zero average sampling error. Sample location spacing is a key factor in sample design performance. Random designs have larger range of possible sampling errors than structured designs due to the potential for sample arrangements that over- and under-sample certain areas of the landscape. Furthermore, when implementing a new sample design to quantify environmental heterogeneity via variance, we recommend using a simple structured design with appropriate sample spacing. For existing designs, we recommend calculating the relative expected sampling error via our analytical derivation.

54 ENVIRONMENTAL SCIENCES↗