SEARCH · Search NASA

Results for “statistical comparison”

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.

SourceResearch connectionFrom yearThrough year

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

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2017

Inference of Transmission Network Structure from HIV Phylogenetic Trees

Phylogenetic inference is an attractive means to reconstruct transmission histories and epidemics. However, there is not a perfect correspondence between transmission history and virus phylogeny. Both node height and topological differences may occur, depending on the interaction between within-host evolutionary dynamics and between-host transmission patterns. To investigate these interactions, we added a within-host evolutionary model in epidemiological simulations and examined if the resulting phylogeny could recover different types of contact networks. To further improve realism, we also introduced patient-specific differences in infectivity across disease stages, and on the epidemic level we considered incomplete sampling and the age of the epidemic. Second, we implemented an inference method based on approximate Bayesian computation (ABC) to discriminate among three well-studied network models and jointly estimate both network parameters and key epidemiological quantities such as the infection rate. Our ABC framework used both topological and distance-based tree statistics for comparison between simulated and observed trees. Overall, our simulations showed that a virus time-scaled phylogeny (genealogy) may be substantially different from the between-host transmission tree. This has important implications for the interpretation of what a phylogeny reveals about the underlying epidemic contact network. In particular, we found that while the within-host evolutionary process obscures the transmission tree, the diversification process and infectivity dynamics also add discriminatory power to differentiate between different types of contact networks. We also found that the possibility to differentiate contact networks depends on how far an epidemic has progressed, where distance-based tree statistics have more power early in an epidemic. Finally, we applied our ABC inference on two different outbreaks from the Swedish HIV-1 epidemic.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Well Stimulation Treatment in California: Evaluation of Disclosure Data, May 2015 – October 2019

In this document, disclosure data from 1,228 well stimulations occurring May 2015 to October 2019 in California are evaluated. This evaluation updates a previous study that was based on 618 well stimulations occurring May 2015 to June 2016 (Stringfellow, W.T., Camarillo, M.K., and Jordan, P. 2017, Status of Well Stimulation in California Since Implementation of SB-4 Regulations, Berkeley National Laboratory, Berkeley, CA). While the goal of the previous study was to provide a summary of information obtained since passage of California Senate Bill No. 4—Oil and Gas, the goal of the current evaluation is to provide a basis for studying chemical indicators that could potentially be used to detect aquifer contamination. We evaluate chemical indicators is a separate document using the data contained herein as well as data from monitoring wells located within oil fields. Compared with the data used by Stringfellow et al. 2017, the current evaluation is based on a more diverse data set. While the previous study contained data for only two oil fields with more than 30 well stimulations, the current data set contains four oil fields with more than 30 well stimulations, making these data more ideal for comparisons using statistical tests. More producers and a new oil field, Buena Vista Nose, are represented in the current data set. Some well stimulation practices remain relatively unchanged since the previous study. Well stimulation is mostly occurring in Kern County with the exception of a single well stimulation in Orange County. Almost all well stimulations are hydraulic fracturing. The current data set contains two acid fracturing treatments and one matrix acidizing treatment. The median number of chemicals added per well stimulation—excluding water and proppant—was previously 21; the number in the expanded data set is 20. Median water added per well stimulation was previously 89,000 gallons and is now 98,000 gallons. While this water use represents a 10% increase, water use for hydraulic fracturing in California is still lower than water use in other oil and gas fields. Chemical formulations appear to have shifted since the previous study. This shift may be related to a change in the predominant service company. We identified 26 chemicals for which the frequency of use has changed by more than 30%. The total number of chemicals used has also expanded. Previously, 178 unique chemicals were identified as being added to well stimulation fluids. The total number of unique chemicals is now 205. Analytical data available for base and recovered fluids has expanded. The number of base fluid samples has increased from 12 to 35 and the number of recovered fluid samples has increased from 1,078 to 2,166. The expanded data set is more ideal for an evaluation of indicator chemicals and comparisons across different formations. The analytical data for recovered fluid samples indicates that many ions, radioactive constituents, and organics are consistently observed, making these chemicals ideal for consideration as potential indicators of aquifer contamination.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Comprehensive Performance Calibration Guidance for Perovskites and Other Emerging Solar Cells

Emerging photovoltaic (PV) technologies (e.g., organic, perovskite, and solution processed quantum dot) have attracted remarkable attention with the rapid growth of their efficiencies, and their transition toward commercialization. Accurate and reliable efficiency measurements of these PV technologies are crucial, yet much more complicated than for conventional PV technologies due to the former's pronounced dynamic responses to changes in measurement conditions (e.g., current–voltage (I–V) scan rate and preconditioning) and their susceptibility to degradation. Adjustments to the measurement procedures are therefore necessary so that a reproducible “steady state” is reached during measurement. Furthermore, given the small size of many emerging cells, inappropriate device area definition and solar simulator setup can lead to measurement errors. Here, comprehensive efficiency calibration guidance is offered for emerging solar cells, including area measurement; spectral irradiance translation to standard test conditions; and steady-state electrical performance. The necessity of reporting steady-state efficiency is justified with a statistical performance comparison between conventional and steady-state I–V scans over hundreds of cells the group has received globally for efficiency certifications. The procedures described here do not require specialized measurement instrumentation; what matters most are changes to the measurement protocols. These described changes aim to enable better comparisons between reported efficiencies.

14 SOLAR ENERGY↗

DOE OSTI2024

Constitutive model development of aluminum alloy 1100 for elevated temperature forming process

Commercially pure aluminum alloy, AA1100, presents good electrical and thermal conductivity, high formability, and low cost. Those favorable characteristics have the potential to enable bipolar plates with improved economics and enhanced performance compared to current stainless steel bipolar plates for proton exchange membrane fuel cells. An accurate constitutive model is essential to develop and optimize processing parameters and effectively control the forming process. Here, the objective of this work is to develop a constitutive model of AA1100 that is able to simulate stress-strain relation, formed geometry, and predict the onset of fracture strain to avoid forming failure. Initially, a set of tensile tests at temperature between 300 and 500°C and strain rate between 0.005 and 1.0/s were conducted to examine the deformation behavior. Then, a set of damage-based unified visco-plastic constitutive equations is proposed and calibrated based on the results of stress-strain data. A genetic algorithm optimization method is applied to search for best fitting material constants in constitutive equations. The proposed model shows good predictability of both the stress-strain relation and fracture strain at low strain rate and high temperature conditions. The accuracy of proposed model is also evaluated statistically. A comparison of the proposed model with three popular models (Arrhenius-type mode, Johnson-Cook model and Zerilli-Armstrong model) was made. The proposed model shows the best experimental agreement with correlation coefficient of 0.96 in contrast to 0.25, 0.38 and 0.75 for the popular models, respectively. The proposed model can help to optimize the elevated temperature forming process and guide die design to enable optimal geometric features in the formed components.

08 HYDROGEN↗

DOE OSTI2015

A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing

A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales, as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. Additionally, the importance of using DNS to calibrate and assess RANS type turbulence models is highlighted.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2023

Quantifying Pore Morphology in Spray-Formed Tantalum Using X-ray Micro-computed Tomography

In order to establish quantitative process–structure–property relationships in thermal spray coatings, a robust framework for defining (micro)structural characteristics is needed. Here, we present a quantitative characterization of the three-dimensional morphology of porosity in spray-formed tantalum samples based on high-resolution X-ray micro-computed tomography. Using synchrotron facilities, we acquired dozens of high-resolution scans, enabling a statistically meaningful comparison across multiple samples, different regions within samples, and spray processes. We quantify the spatial distribution, size, and topology of porous inclusions, with a significant focus on variability across samples and different spray processes (plasma and cold sprayed), as well as sensitivity to image segmentation and resolution. Based on a typical segmentation, we report porosities ranging from 0.9 to 1.7 pct for all samples tested, with significant sensitivity due to image segmentation resulting in estimates as low as 0.6 pct and as high as 4.8 pct. For the complex pore space morphology observed in these materials, we argue that a conventional analysis based on identifying individual pores is not well suited, and propose an alternative approach based on morphological metrics with a rich history in porous media literature, such as spatial correlations, local pore thickness, and scale-dependent sub-sampling. Spatial correlations indicate anisotropic splat structures, but only mildly anisotropic pores. Various measures of pore size show a wide distribution of sizes, ranging from sub-micron to 10-micron length scales. Scale-dependent variations in porosity suggest that representative volumes of several hundred microns are required for convergence of morphological metrics, with larger volumes for cold-spray materials. This work provides a robust quantitative basis for describing three-dimensional pore structure in thermal spray coatings.

36 MATERIALS SCIENCE↗

DOE OSTI2025

An update to the Sandia method for creating Typical Meteorological Years from a limited pool of calendar years

Typical Meteorological Years (TMYs) are essential for the efficient evaluation of energy system performance. Ideally, 30 years of weather data are required to generate TMYs, but significantly fewer years are typically available due to practical limitations. To address this issue, an update to the Sandia method was developed, referred to as the Argonne method, to create TMYs from a limited number of years. Furthermore, this method enhances candidate diversity by systematically shifting original candidate months forward or backward by specific days, creating an expanded pool of candidates. The effectiveness of the Argonne method was validated through statistical testing, comparison of monthly average weather parameters, and numerical simulations. The results demonstrate a high probability of identifying at least one shifted month whose cumulative distribution functions of weather parameters closely align with long-term distributions. In 67 % of all comparisons, the monthly average weather parameters in TMYs generated using the Argonne method exhibit better agreement with long-term averages than TMY3. Moreover, in 74 % of the 318 building simulation cases, the Argonne method outperforms TMY3 in estimating long-term average building heating and cooling demands. Therefore, the Argonne method effectively diversifies the candidate pool and produces typical years that provide more accurate estimations of long-term averages compared to TMY3 when only a limited pool of calendar years (10 years or fewer) is available.

Building energy modeling↗

DOE OSTI2016

International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station

Abstract The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward (Bowyer et al., 2013). Fission-based production of 99Mo for medical purposes also releases radioxenon isotopes to the atmosphere (Saey, 2009). One of the ways to mitigate the effect of emissions from medical isotope production is the use of stack monitoring data, if it were available, so that the effect of radioactive xenon emissions could be subtracted from the effect from a presumed nuclear explosion, when detected at an IMS station location. To date, no studies have addressed the impacts the time resolution or data accuracy of stack monitoring data have on predicted concentrations at an IMS station location. Recently, participants from seven nations used atmospheric transport modeling to predict the time-history of 133Xe concentration measurements at an IMS station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice. Some of the models predicted the highest measured concentrations quite well (a high composite statistical model comparison rank or a small mean square error with the measured values). The results suggest release data on a 15 min time spacing is best. The model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. Further research is needed to identify optimal methods for selecting ensemble members and those methods may depend on the specific transport problem. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. The one submission that best predicted small concentrations also included releases from nuclear power plants. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in discriminating those releases from releases from a nuclear explosion.

133Xe↗

DOE OSTI2017

Monte Carlo chord length sampling for d-dimensional Markov binary mixtures

The Chord Length Sampling (CLS) algorithm is a powerful Monte Carlo method that models the effects of stochastic media on particle transport by generating on-the-fly the material interfaces seen by the random walkers during their trajectories. This annealed disorder approach, which formally consists of solving the approximate Levermore–Pomraning equations for linear particle transport, enables a considerable speed-up with respect to transport in quenched disorder, where ensemble-averaging of the Boltzmann equation with respect to all possible realizations is needed. However, CLS intrinsically neglects the correlations induced by the spatial disorder, so that the accuracy of the solutions obtained by using this algorithm must be carefully verified with respect to reference solutions based on quenched disorder realizations. When the disorder is described by Markov mixing statistics, such comparisons have been attempted so far only for one-dimensional geometries, of the rod or slab type. In this work we extend these results to Markov media in two-dimensional (extruded) and three-dimensional geometries, by revisiting the classical set of benchmark configurations originally proposed by Adams, Larsen and Pomraning and extended by Brantley. In particular, we examine the discrepancies between CLS and reference solutions for scalar particle flux and transmission/reflection coefficients as a function of the material properties of the benchmark specifications and of the system dimensionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

An optimized posterior axillary boost technique in radiation therapy to supraclavicular and axillary lymph nodes: A comparative study

To assess the advantages of an optimized posterior axillary (AX) boost technique for the irradiation of supraclavicular (SC) and AX lymph nodes. Five techniques for the treatment of SC and levels I, II, and III AX lymph nodes were evaluated for 10 patients selected at random: a direct anterior field (AP); an anterior to posterior parallel pair (AP-PA); an anterior field with a posterior axillary boost (PAB); an anterior field with an anterior axillary boost (AAB); and an optimized PAB technique (OptPAB). The target coverage, hot spots, irradiated volume, and dose to organs at risk were evaluated and a statistical analysis comparison was performed. The AP technique delivered insufficient dose to the deeper AX nodes. The AP-PA technique produced larger irradiated volumes and higher mean lung doses than the other techniques. The PAB and AAB techniques originated excessive hot spots in most of the cases. The OptPAB technique produced moderate hot spots while maintaining a similar planning target volume (PTV) coverage, irradiated volume, and dose to organs at risk. This optimized technique combines the advantages of the PAB and AP-PA techniques, with moderate hot spots, sufficient target coverage, and adequate sparing of normal tissues. The presented technique is simple, fast, and easy to implement in routine clinical practice and is superior to the techniques historically used for the treatment of SC and AX lymph nodes.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

When will low-contrast features be visible in a STEM X-ray spectrum image?

When will a small or low-contrast feature, such as an embedded second-phase particle, be visible in a scanning transmission electron microscopy (STEM) X-ray map? This work illustrates a computationally inexpensive method to simulate X-ray maps and spectrum images (SIs), based upon the equations of X-ray generation and detection. To particularize the general procedure, an example of nanostructured ferritic alloy (NFA) containing nm-sized Y 2 Ti 2 O 7 embedded precipitates in ferritic stainless steel matrix is chosen. The proposed model produces physically appearing simulated SI data sets, which can either be reduced to X-ray dot maps or analyzed via multivariate statistical analysis. Comparison to NFA X-ray maps acquired using three different STEM instruments match the generated simulations quite well, despite the large number of simplifying assumptions used. A figure of merit of electron dose multiplied by X-ray collection solid angle is proposed to compare feature detectability from one data set (simulated or experimental) to another. The proposed method can scope experiments that are feasible under specific analysis conditions on a given microscope. As a result, future applications, such as spallation proton–neutron irradiations, core-shell nanoparticles, or dopants in polycrystalline photovoltaic solar cells, are proposed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Simulations of activities, solubilities, transport properties, and nucleation rates for aqueous electrolyte solutions

This article reviews recent molecular simulation studies of "collective" properties of aqueous electrolyte solutions, specifically free energies and activity coefficients, solubilities, nucleation rates of crystals, and transport coefficients. These are important fundamental properties for biology and geoscience, but also relevant for many technological applications. Their determination from molecular-scale calculations requires large systems and long sampling times, as well as specialized sampling algorithms. As a result, such properties have not typically been taken into account during optimization of force field parameters; thus, they provide stringent tests for the transferability and range of applicability of proposed molecular models. There has been significant progress on simulation algorithms to enable the determination of these properties with good statistical uncertainties. Comparisons of simulation results to experimental data reveal deficiencies shared by many commonly used models. Moreover, there appear to exist specific tradeoffs within existing modeling frameworks, so that good prediction of some properties is linked to poor prediction for specific other properties. For example, non-polarizable models that utilize full charges on the ions generally fail to predict accurately both activity coefficients and solubilities; the concentration dependence of viscosity and diffusivity for these models is also incorrect. Scaled-charge models improve the dynamic properties and could also perform well for solubilities, but fail in the prediction of nucleation rates. Even models that do well at room temperature for some properties generally fail to capture their experimentally observed temperature dependence. Finally, the main conclusion from the present review is that qualitatively new physics will need to be incorporated in future models of electrolyte solutions to allow description of collective properties for broad ranges of concentrations, temperatures, and solvent conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Modulation of ENSO teleconnections over North America by the Pacific decadal oscillation

In this study, we investigate whether the Pacific decadal oscillation (PDO) can enhance or diminish El Niño Southern Oscillation (ENSO) temperature and precipitation teleconnections over North America using five single model initial-condition large ensembles (SMILEs). The use of SMILEs facilitates a statistically robust comparison of ENSO events that occur during different phases of the PDO. We find that a positive PDO enhances winter and spring El Niño temperature and precipitation teleconnections and diminishes La Niña teleconnections. A negative PDO has the opposite effect. The modulation of ENSO by the PDO is mediated by differences in the location and strength of the Aleutian Low and Pacific Jet during ENSO events under different phases of the PDO. This modulation is a simple combination of the individual effects of the PDO and ENSO over North America. Finally, we show that ENSO and the PDO can be used to evaluate the likelihood of the occurrence of temperature and precipitation anomalies in different regions, but cannot be used as a deterministic predictor of these anomalies due to the large variability between individual events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Objective analysis of impressed chisel toolmarks

Historical and recent challenges to the practice of comparative forensic examination have created a driving force for the formation of objective methods for toolmark identification. In this study, fifty sequentially manufactured chisels were used to create impression toolmarks in lead (500 toolmarks total). An algorithm previously used to statistically separate known matching and nonmatching striated screwdriver marks and quasi-striated plier marks was used to evaluate the chisel marks. Impression toolmarks, a more complex form of toolmark, pose a more difficult test for the algorithm that was originally designed for striated toolmarks. Lastly, results show in this instance that the algorithm can separate matching and nonmatching impression marks, providing further validation of the assumption that toolmarks are identifiably unique.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

The importance of retaining a phylogenetic perspective in traits-based community analyses

1) Many environmental stressors manifest their effects via physiological processes (traits) that can differ significantly among species and species groups. We compiled available data for three traits related to the bioconcentration of the toxic metal cadmium (Cd) from 42 aquatic insect species representing orders Ephemeroptera (mayfly), Plecoptera (stonefly), and Trichoptera (caddisfly). These traits included the propensity to take up Cd from water (uptake rate constant, ku), the ability to excrete Cd (efflux rate constant, ke), and the net result of these two processes (bioconcentration factor, BCF). 2) Ranges in these Cd bioaccumulation traits varied in magnitude across lineages (some lineages had a greater tendency to bioaccumulate Cd than others). Overlap in the ranges of trait values among different lineages was common and highlights situations where species from different lineages can share a similar trait state, but represent the high end of possible physiological values for one lineage and the low end for another. 3) Variance around the mean trait state differed widely across clades, suggesting that some groups (e.g., Ephemerellidae) are inherently more variable than others (e.g., Perlidae). Thus, trait variability/lability is at least partially a function of lineage. 4) Akaike information criterion (AIC) comparisons of statistical models were more often driven by clade than by other potential biological or ecological explanation tested. Clade-driven models generally improved with increasing taxonomic resolution. 5) Altogether, these findings suggest that lineage provides context for the analysis of species traits, and that failure to consider lineage in community-based analysis of traits may obscure important patterns of species responses to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Primordial nucleosynthesis with non-extensive statistics

The conventional Big Bang model successfully anticipates the initial abundances of 2 H(D), 3 He, and 4 He, aligning remarkably well with observational data. However, a persistent challenge arises in the case of 7 Li, where the predicted abundance exceeds observations by a factor of approximately three. Despite numerous eﬀorts employing traditional nuclear physics to address this incongruity over the years, the enigma surrounding the lithium anomaly endures. In this context, we embark on an exploration of Big Bang nucleosynthesis (BBN) of light element abundances with the application of Tsallis non-extensive statistics. A comparison is made between the outcomes obtained by varying the non-extensive parameter q away from its unity value and both observational data and abundance predictions derived from the conventional big bang model. Here, a good agreement is found for the abundances of 4 He, 3 He and 7 Li, implying that the lithium abundance puzzle might be due to a subtle fine-tuning of the physics ingredients used to determine the BBN. However, the deuterium abundance deviates from observations.

Bertulani, Carlos A.↗

DOE OSTI2023

HopPyBar

HopPyBar is a python program to import, analyze, and export split-Hopkinson pressure bar (SHPB, also known as Kolsky bar) data. Traditional analysis offers a black box approach, where input data is converted to analyzed output by performing a series of calculations without user involvement. This program serves as a developmental platform to "white box" the data analysis process. Data streams can be captured (in-situ) to enable advanced or unconventional analyses, statistics, and comparisons. Additionally, the program is geared towards the standardized forms of input and output used at LANL to streamline analysis, but the open nature of the program makes additional input/output schemes straightforward to add. General workflow will import SHPB data in one of a number of formats, identify relevant portions of data signals, and convert to stress-strain-strain rate to show material behavior as a function of dynamic testing.

Morrow, Benjamin↗