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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Integrated Geologic and Geophysical Approach for Establishing Geothermal Play Fairways and Discovering Blind Geothermal Systems in the Great Basin Region, Western USA: A Progress Report

We have undertaken an integrated geologic, geochemical, and geophysical study of a broad 240-km-wide, 400-km-long transect stretching from west-central to eastern Nevada in the Great Basin region of the western USA. The main goal of this study is to produce a comprehensive geothermal potential map that incorporates up to 11 parameters and identifies geothermal play fairways that represent potential blind or hidden geothermal systems. Our new geothermal potential map incorporates: 1) heat flow; 2) geochemistry from springs and wells; 3) structural setting; 4) recency of faulting; 5) slip rates on Quaternary faults; 6) regional strain rate; 7) slip and dilation tendency on Quaternary faults; 8) seismologic data; 9) gravity data; 10) magnetotelluric data (where available); and 11) seismic reflection data (primarily from the Carson Sink and Steptoe basins). The transect is respectively anchored on its western and eastern ends by regional 3D modeling of the Carson Sink and Steptoe basins, which will provide more detailed geothermal potential maps of these two promising areas. To date, geological, geochemical, and geophysical data sets have been assembled into an ArcGIS platform and combined into a preliminary predictive geothermal play fairway model using various statistical techniques. The fairway model consists of the following components, each of which are represented in grid-cell format in ArcGIS and combined using specified weights and mathematical operators: 1) structural component of permeability; 2) regional-scale component of permeability; 3) combined permeability, and 4) heat source model. The preliminary model demonstrates that the multiple data sets can be successfully combined into a comprehensive favorability map. An initial evaluation using known geothermal systems as benchmarks to test interpretations indicates that the preliminary modeling has done a good job assigning relative ranks of geothermal potential. However, a major challenge is defining logical relative rankings of each parameter and how best to combine the multiple data sets into the geothermal potential/ permeability map. Ongoing feedback and data analysis are in use to revise the grouping and weighting of some parameters in order to develop a more robust, optimized, final model. The final product will incorporate more parameters into a geothermal potential map than any previous effort in the region and may serve as a prototype to develop comprehensive geothermal potential maps for other regions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Integrated Geologic and Geophysical Approach for Establishing Geothermal Play Fairways and Discovering Blind Geothermal Systems in the Great Basin Region, Western USA: A Progress Report

We have undertaken an integrated geologic, geochemical, and geophysical study of a broad 240-km-wide, 400-kmlong transect stretching from west-central to eastern Nevada in the Great Basin region of the western USA. The main goal of this study is to produce a comprehensive geothermal potential map that incorporates up to 11 parameters and identifies geothermal play fairways that represent potential blind or hidden geothermal systems. Our new geothermal potential map incorporates: 1) heat flow; 2) geochemistry from springs and wells; 3) structural setting; 4) recency of faulting; 5) slip rates on Quaternary faults; 6) regional strain rate; 7) slip and dilation tendency on Quaternary faults; 8) seismologic data; 9) gravity data; 10) magnetotelluric data (where available); and 11) seismic reflection data (primarily from the Carson Sink and Steptoe basins). The transect is respectively anchored on its western and eastern ends by regional 3D modeling of the Carson Sink and Steptoe basins, which will provide more detailed geothermal potential maps of these two promising areas. To date, geological, geochemical, and geophysical data sets have been assembled into an ArcGIS platform and combined into a preliminary predictive geothermal play fairway model using various statistical techniques. The fairway model consists of the following components, each of which are represented in grid-cell format in ArcGIS and combined using specified weights and mathematical operators: 1) structural component of permeability; 2) regional-scale component of permeability; 3) combined permeability, and 4) heat source model. The preliminary model demonstrates that the multiple data sets can be successfully combined into a comprehensive favorability map. An initial evaluation using known geothermal systems as benchmarks to test interpretations indicates that the preliminary modeling has done a good job assigning relative ranks of geothermal potential. However, a major challenge is defining logical relative rankings of each parameter and how best to combine the multiple data sets into the geothermal potential/permeability map. Ongoing feedback and data analysis are in use to revise the grouping and weighting of some parameters in order to develop a more robust, optimized, final model. The final product will incorporate more parameters into a geothermal potential map than any previous effort in the region and may serve as a prototype to develop comprehensive geothermal potential maps for other regions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2023

Beyond Expected Values Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

SPT-3G D1: Compton-$y$ maps using data from the SPT-3G and Planck surveys

We present thermal Sunyaev-Zel'dovich (tSZ) Compton-$y$ parameter maps constructed from two years (2019-2020) of observations with the South Pole Telescope (SPT) third-generation camera, SPT-3G, combined with data from the Planck satellite. Using a linear combination (LC) pipeline, we obtain a suite of reconstructions that explore different trade-offs between statistical sensitivity and suppression of astrophysical contaminants, including minimum-variance, CMB-deprojected, and CIB-deprojected $y$-maps. We validate these maps through different statistical techniques such as auto- and cross-power spectra with large-scale structure tracers as well as stacking on cluster locations. These tests are used to understand the balance between noise and astrophysical foreground residuals (such as the CIB) in combination with the recovery of the tSZ signal for different maps. For example, results from stacking at the location of clusters confirm the robustness of the recovered tSZ signal over the $\sim 1500\: {\rm deg}^2$ SPT-3G survey field used in this analysis. The high-resolution and low-noise maps produced here provide an important cosmological tool for future studies, including measurements of the Compton-$y$ map power spectrum, cross-correlations with other tracers of the large-scale structure, detailed modeling of cluster pressure profiles, and study of the thermodynamic state of the baryons in the Universe.

Maniyar, A. S. [Harvard-Smithsonian Ctr. Astrophys↗
NASA NTRS1989

Evaluating Statistical Process Control (SPC) techniques and computing the uncertainty of force calibrations

In recent years there has been a push within NASA to use statistical techniques to improve the quality of production. Two areas where statistics are used are in establishing product and process quality control of flight hardware and in evaluating the uncertainty of calibration of instruments. The Flight Systems Quality Engineering branch is responsible for developing and assuring the quality of all flight hardware; the statistical process control methods employed are reviewed and evaluated. The Measurement Standards and Calibration Laboratory performs the calibration of all instruments used on-site at JSC as well as those used by all off-site contractors. These calibrations must be performed in such a way as to be traceable to national standards maintained by the National Institute of Standards and Technology, and they must meet a four-to-one ratio of the instrument specifications to calibrating standard uncertainty. In some instances this ratio is not met, and in these cases it is desirable to compute the exact uncertainty of the calibration and determine ways of reducing it. A particular example where this problem is encountered is with a machine which does automatic calibrations of force. The process of force calibration using the United Force Machine is described in detail. The sources of error are identified and quantified when possible. Suggestions for improvement are made.

Navard, Sharon E.↗
NASA NTRS1993

Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

Wolf, S. F.↗
NASA NTRS2006

Statistical of a Characterization and the Simulation of a Reverberation Chamber Using Finite-Element Techniques

The statistical characterization of a simulation reverberation chamber is performed by considering a two-dimensional finite element model. This model includes a source to study the particular modal fields that couple into either a transverse electric or transverse magnetic configuration. The analysis includes a characterization of the basic field statistics, max-to-average ratio, normalized standard deviation, stirring ratio, and field uniformity. The shielding effectiveness of an aperture will be studied that will provide some insight into the nature of the fields coupled from a complex to a noncomplex environment.

Bunting, Charles F.↗
DOE OSTI2024

Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R 2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Techniques for improved statistical convergence in quantification of eddy diffusivity moments

While recent approaches, such as the macroscopic forcing method (MFM) or Green's function-based approaches, can be used to compute Reynolds-averaged Navier-Stokes closure operators using forced direct numerical simulations, MFM can also be used to directly compute moments of the effective nonlocal and anisotropic eddy diffusivities. The low-order spatial and temporal moments contain limited information about the eddy diffusivity but are often sufficient for quantification and modeling of nonlocal and anisotropic effects. However, when using MFM to compute eddy diffusivity moments, the statistical convergence can be slow for higher-order moments. In this work, we demonstrate that using the same direct numerical simulation (DNS) for all forced MFM simulations improves statistical convergence of the eddy diffusivity moments. We present its implementation in conjunction with a decomposition method that handles the MFM forcing semianalytically and allows for consistent boundary condition treatment, which we develop for both scalar and momentum transport. We demonstrate that for a two-dimensional Rayleigh-Taylor instability case study, using the same DNS for all forced MFM simulations results in convergence with 𝒪⁡(100) simulations rather than 𝒪⁡(1000) simulations. In conclusion, we then demonstrate the impacts of improved convergence on the quantification of the eddy diffusivity.

general physics↗
NASA NTRS1991

SSSFD manipulator engineering using statistical experiment design techniques

The Satellite Servicer System Flight Demonstration (SSSFD) program is a series of Shuttle flights designed to verify major on-orbit satellite servicing capabilities, such as rendezvous and docking of free flyers, Orbital Replacement Unit (ORU) exchange, and fluid transfer. A major part of this system is the manipulator system that will perform the ORU exchange. The manipulator must possess adequate toolplate dexterity to maneuver a variety of EVA-type tools into position to interface with ORU fasteners, connectors, latches, and handles on the satellite, and to move workpieces and ORUs through 6 degree of freedom (dof) space from the Target Vehicle (TV) to the Support Module (SM) and back. Two cost efficient tools were combined to perform a study of robot manipulator design parameters. These tools are graphical computer simulations and Taguchi Design of Experiment methods. Using a graphics platform, an off-the-shelf robot simulation software package, and an experiment designed with Taguchi's approach, the sensitivities of various manipulator kinematic design parameters to performance characteristics are determined with minimal cost.

Barnes, John↗
NASA NTRS2001

Accuracy Assessment of Response Surface Approximations for Supersonic Turbine Design

There is a growing trend to employ CFD tools to supply the necessary information for design optimization of fluid dynamics components/systems. Such results are prone to uncertainties due to reasons including discretization. errors, incomplete convergence of computational procedures, and errors associated with physical models such as turbulence closures. Based on this type of information, gradient-based optimization algorithms often suffer from the noisy calculations, which can seriously compromise the outcome. Similar problems arise from the experimental measurements. Global optimization techniques, such as those based on the response surface (RS) concept are becoming popular in part because they can overcome some of these barriers. However, there are also fundamental issues related to such global optimization technique such as RS. For example, in high dimensional design spaces, typically only a small number of function evaluations are available due to computational and experimental costs. On the other hand, complex features of the design variables do not allow one to model the global characteristics of the design space with simple quadratic polynomials. Consequently a main challenge is to reduce the size of the region where we fit the RS, or make it more accurate in the regions where the optimum is likely to reside. Response Surface techniques using either polynomials or and Neural Network (NN) methods offer designers alternatives to conduct design optimization. The RS technique employs statistical and numerical techniques to establish the relationship between design variables and objective/constraint functions, typically using polynomials. In this study, we aim at addressing issues related to the following questions: (1) How to identify outliers associated with a given RS representation and improve the RS model via appropriate treatments? (2) How to focus on selected design data so that RS can give better performance in regions critical to design optimization? (3) How to combine NN and polynomial techniques for improving the accuracy of the RS model?

Papila, Nilay↗
DOE OSTI2019

Method of resource-limited device and device class identification using system and function call tracing techniques, performance, and statistical analysis

Methods for cyber physical systems device classification are provided. A method can include receiving system and function calls and parameters and a device performance index from an unknown CPS device and a device performance index of similar class of CPS devices, calculating an autocorrelation value between different realizations of the system and function calls and parameters of the known CPS device, determining whether the autocorrelation value is greater than a threshold amount, and storing the system and function calls and parameters and the device performance characteristics of the known CPS device in the database. A method can also include calculating a correlation between system and function calls and parameters of an unknown CPS device and known CPS devices classes included in the database, as well as determining whether the maximum correlation is also greater than a threshold amount.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2024

A Physics-Based Antarctic Melt Detection Technique: Combining Advanced Microwave Scanning Radiometer 2, Radiative-Transfer Modeling, and Firn Modeling

Surface melt on ice shelves has been linked to hydrofracture and subsequent ice shelf breakup. Since the 1990s, scientists have been using microwave radiometers to detect melt on ice shelves and ice sheets by applying various statistical thresholding techniques to identify significant increases in brightness temperature that are associated with melt. In this study, instead of using a fixed threshold, we force the Snow Radiative Transfer model (SMRT) with outputs from the Community Firn Model (CFM) to create a dynamic, physics-based threshold for melt. In the process, we also combine our method with statistical thresholding techniques and produce microwave grain size information in the process. We run this “Hybrid Method” across the Larsen C ice shelf as well as thirteen sites on the Antarctic Ice Sheet. Melt and non-melt days from the Hybrid Method and three statistical thresholding techniques match with surface energy balance within 94±1%; the effect of melt on the passive microwave is mostly binary and thus largely detectable by statistical thresholding techniques as well as physics-based techniques. Rather than always replacing statistical thresholding techniques with the Hybrid Method, we recommend using the Hybrid Method in studies where melt volume or grain size is of interest. In this study, we show that the Hybrid Method can be used to (a) model dry snow brightness temperatures of Antarctic snow and (b) derive a measure of grain size; therefore, it is an important step forwards towards using firn and radiative transfer modeling to quantify melt rather than to simply detect melt days.

Marissa E Dattler↗
DOE OSTI2018

From Weakly Chaotic Dynamics to Deterministic Subdiffusion via Copula Modeling

Copula modeling consists in finding a probabilistic distribution, called copula, whereby its coupling with the marginal distributions of a set of random variables produces their joint distribution. The present work aims to use this technique to connect the statistical distributions of weakly chaotic dynamics and deterministic subdiffusion. More precisely, we decompose the jumps distribution of Geisel–Thomae map into a bivariate one and determine the marginal and copula distributions respectively by infinite ergodic theory and statistical inference techniques. We verify therefore that the characteristic tail distribution of subdiffusion is an extreme value copula coupling Mittag–Leffler distributions. We also present a method to calculate the exact copula and joint distributions in the case where weakly chaotic dynamics and deterministic subdiffusion statistical distributions are already known. Numerical simulations and consistency with the dynamical aspects of the map support our results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗