Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data fitting”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

From Event Data to Wind Power Plant DQ Admittance and Stability Risk Assessment

This paper presents a dynamic event data-based stability risk assessment method for power grids with high penetrations of inverter-based resources (IBRs). This method relies on obtaining the IBRs' DQ admittance through dynamic event data and computing the system's eigenvalues based on the admittance models. Two critical technologies are employed in this research, including time-domain and frequency-domain data fitting and dq-frame voltage and current signal derivation. The first technology is key to obtaining the s-domain expressions from the transient response data, and the s-domain DQ admittance model from the frequency-domain measurements. The second technology is key to obtaining the dq-frame voltage and current signals from either the three-phase instantaneous measurements or the phasor measurement unit (PMU) data. The method is illustrated using data generated from a Type-4 wind power plant modeled in PSCAD. This paper demonstrates the technical feasibility of the proposed approach.

17 WIND ENERGY↗
DOE OSTI2021

Large-scale Genetic Characterization of a Model Sulfate-Reducing Bacterium

ABSTRACTSulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources, and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

Trotter, Valentine V↗
DOE OSTI2023

Large-scale genetic characterization of the model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough

Sulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Modeling Calcium Loss from Bones During Space Flight

Calcium loss from bones during space flight creates a risk for astronauts who travel into space, and may prohibit space flights to other planets. The problem of calcium loss during space flight has been studied using animal models, bed rest (as a ground-based model), and humans in-flight. In-flight studies have typically documented bone loss by comparing bone mass before and after flight. To identify changes in metabolism leading to bone loss, we have performed kinetic studies using stable isotopes of calcium. Oral (Ca-43) and intravenous (Ca-46) tracers were administered to subjects (n=3), three-times before flight, once in-flight (after 110 days), and three times post-flight (on landing day, and 9 days and 3 months after flight). Samples of blood, saliva, urine, and feces were collected for up to 5 days after isotope administration, and were analyzed for tracer enrichment. Tracer data in tissues were analyzed using a compartmental model for calcium metabolism and the WinSAAM software. The model was used to: account for carryover of tracer between studies, fit data for all studies using the minimal number of changes between studies, and calculate calcium absorption, excretion, bone calcium deposition and bone calcium resorption. Results showed that fractional absorption decreased by 50% during flight and that bone resorption and urinary excretion increased by 50%. Results were supported by changes in biochemical markers of bone metabolism. Inflight bone loss of approximately 250 mg Ca/d resulted from decreased calcium absorption combined with increased bone resorption and excretion. Further studies will assess the time course of these changes during flight, and the effectiveness of countermeasures to mitigate flight-induced bone loss. The overall goal is to enable human travel beyond low-Earth orbit, and to allow for better understanding and treatment of bone diseases on Earth.

Wastney, Meryl E.↗
NASA NTRS2022

Comparison of U.S. and Russian Slow Crack Growth Data and Models

Both the US and Russian space programs use similar predictive models for design of fused silica windows on the International space station. The Russian model can be derived from the power expression for slow crack growth (SCG) or “static fatigue.” The US uses both power and exponential models. Despite the similarity of models and data fitting approach (linear regression and right censoring), different SCG parameters have been derived by US and Russian parties for the same material (Russian fused silica) tested in a similar manner. The difference appears to be related to the use of short-term strength data along with the longer-term static fatigue data, with the power law parameter n being very sensitive to the conversion of strength data into equivalent static data. This hybrid approach is feasible if strength data is measured with a constant stress rate and is appropriately converted to a static equivalent. More research into the approach is needed. However, because of the nonlinear behavior of fused silica in log(v) – log(K(I) ) space and the sensitivity of parameter estimation to fit range, the exponential model is a better choice regardless of test method. Functions are given to convert parameters from the Russian model to those in the US model. However, accurate conversion is hampered by the lack of inert strength data. When the same test technique is used, US and Russian materials exhibit very similar parameters.

Silica, strength, impact, crack growth, windows, I↗
DOE OSTI2021

Parameter inference from event ensembles and the top-quark mass

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

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1987

Use of inelastic strain as a basis for analyzing thermomechanical test data

It was shown that the proposed data analysis method, based on inelastic strain-time response, can be used effectively to represent cyclic response at elevated temperatures for Hastelloy-X. A high level of confidence in this method was built by making comparisons of the experimental and fitted data in two forms. Because of this level of confidence, the analysis was taken one step further and inelastic strain rates were calculated from the derivatives of the fit equations.

Bartolotta, P. A.↗
DOE OSTI2015

Structural and electronic properties of GaAs and GaP semiconductors

The Structural and Electronic properties of Zinc Blende phase of GaAs and GaP compounds are studied using self consistent SIESTA-code, pseudopotentials and Density Functional Theory (DFT) in Local Density Approximation (LDA). The Lattice Constant, Equillibrium Volume, Cohesive Energy per pair, Compressibility and Band Gap are calculated. The band gaps calcultated with DFT using LDA is smaller than the experimental values. The P-V data fitted to third order Birch Murnaghan equation of state provide the Bulk Modulus and its pressure derivatives. Our Structural and Electronic properties estimations are in agreement with available experimental and theoretical data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Predictive models of the genetic bases underlying budding yeast fitness in multiple environments

Abstract The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitness and genotype-by-environment interactions hinder our understanding of the genetic basis of fitness. Here, we established fitness prediction models for 35 environments using machine learning and existing fitness data and different genetic variant types for a Saccharomyces cerevisiae population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.

DNA copy number variations↗
NASA NTRSDate not supplied

Analysis of the Pioneer Venus Large Probe Neutral Mass Spectrometer Data Yields New Insights into the Composition of Venus’ Atmosphere

We present a new analysis of mass spectral data obtained by the Pioneer Venus (PV) Large Probe Neutral Mass Spectrometer (LNMS). To analyze the LNMS data, we constructed an analytical model that accounts for spectrometer performance at each altitude, provides CO2 abundances in units of density (kg/m3), and retains the resolving power of the LNMS through use of a targeted data-fitting routine. Our results provide new insights into the composition of Venus’ atmosphere and show that densities for CO2 increase towards the surface, which is suggestive of surface outgassing. Additionally, the data reveal partial obstructions of the LNMS inlet at <17 km, which is an likely important consideration for future missions. Re-analysis of the LNMS data may assist in revealing the past, present and/or future habitability of Venus’ clouds.

mass spectral data↗
DOE OSTI2015

Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons

Transposon mutagenesis with next-generation sequencing (TnSeq) is a powerful approach to annotate gene function in bacteria, but existing protocols for TnSeq require laborious preparation of every sample before sequencing. Thus, the existing protocols are not amenable to the throughput necessary to identify phenotypes and functions for the majority of genes in diverse bacteria. Here, we present a method, random bar code transposon-site sequencing (RB-TnSeq), which increases the throughput of mutant fitness profiling by incorporating random DNA bar codes into Tn5 and mariner transposons and by using bar code sequencing (BarSeq) to assay mutant fitness. RB-TnSeq can be used with any transposon, and TnSeq is performed once per organism instead of once per sample. Each BarSeq assay requires only a simple PCR, and 48 to 96 samples can be sequenced on one lane of an Illumina HiSeq system. We demonstrate the reproducibility and biological significance of RB-TnSeq with Escherichia coli , Phaeobacter inhibens , Pseudomonas stutzeri , Shewanella amazonensis , and Shewanella oneidensis . To demonstrate the increased throughput of RB-TnSeq, we performed 387 successful genome-wide mutant fitness assays representing 130 different bacterium-carbon source combinations and identified 5,196 genes with significant phenotypes across the five bacteria. In P. inhibens , we used our mutant fitness data to identify genes important for the utilization of diverse carbon substrates, including a putative D-mannose isomerase that is required for mannitol catabolism. RB-TnSeq will enable the cost-effective functional annotation of diverse bacteria using mutant fitness profiling. A large challenge in microbiology is the functional assessment of the millions of uncharacterized genes identified by genome sequencing. Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach to assign phenotypes and functions to genes. However, the current strategies for TnSeq are too laborious to be applied to hundreds of experimental conditions across multiple bacteria. Here, we describe an approach, random bar code transposon-site sequencing (RB-TnSeq), which greatly simplifies the measurement of gene fitness by using bar code sequencing (BarSeq) to monitor the abundance of mutants. We performed 387 genome-wide fitness assays across five bacteria and identified phenotypes for over 5,000 genes. RB-TnSeq can be applied to diverse bacteria and is a powerful tool to annotate uncharacterized genes using phenotype data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

An efficient parallel sampling technique for Multivariate Poisson-Lognormal model: Analysis with two crash count datasets

Our study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and takes account of the over dispersion in the data that leads to a superior data fitting. But, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chain Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Moreover, the correlations among the latent effects of different severity levels are found significant in both datasets that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Efficiency and mechanisms of Sb(III/V) removal by Fe-modified biochars using X-ray absorption spectroscopy

Fe-modified biochars (FeBC) are effective antimony (Sb) removal materials; however, the removal mechanisms require further investigation. In this study, aqueous Sb(III) and Sb(V) removal by FeBC (300, 600, and 900 °C) was evaluated, with the adsorption mechanisms investigated using X-ray absorption spectroscopy (XAS). Screening results (based on removal efficiencies) using different types of FeBC indicated the 900 °C FeCl3- modified biochar (FeCl3BC900) achieved the best Sb(III/V) removal performance. The kinetics of the Sb(III/V) removal process were best fitted by a pseudo-second-order model. Additionally, the isothermal results were described by Langmuir and Redlich-Peterson models. Aqueous analysis and X-ray absorption near-edge structure data fitting indicated Sb(III) was oxidized to Sb(V) in the Sb(III)-spiked system, and the oxidation extent increased with increasing pyrolysis temperature. The oxidation process rapidly occurred in both the solution and biochar. No Sb(V) was reduced to Sb(III) in the Sb(V)-spiked system. The XAS results of the isothermal experiment indicated the oxidation capacity of FeCl3BC900 was limited for high initial Sb(III) concentrations. The SbFe1 and Sb-Fe2 bonding distances were 3.05–3.10 and 3.47–3.54 Å, respectively, indicating inner-sphere complexes were formed during the Sb(III/V) removal processes. The Sb(III/V) removal mechanisms included electrostatic adsorption, inner-sphere complexes, and coprecipitation. Oxidation was also involved in Sb(III) removal.

Antimony↗
DOE OSTI2025

Deriving Stable Peak Models to Fit Complex XPS Data From Cu Contaminated Pt Electrocatalysts

X-ray Photoelectron Spectroscopy spectra peak models, designed to partition photoemission signals emanating from different elements or chemical states within an atom, are fitted to data limited to an energy interval over which inelastically scattered photoemission signal can be estimated. While the choice of background approximation and line shapes of components to the peak model requires careful consideration, the energy interval used to define the data to which the peak model is optimized has a significant impact on the final peak model. The relationship between the background intensity and data intensity at the start and end of the energy interval dictates the line shapes used in the peak model. In this work, we devise a method to peak fit a complex overlapping Cu 3p and Pt 4f XPS peak structure to perform the elemental quantification. We first use an Al 2s peak to illustrate how background curves approach data at the limits of the energy interval over which the background is defined, influencing the analysis of XPS spectra. Next, we demonstrate the nature of interactions between specific line shapes (Voigt and pseudo-Voigt profiles) suitable for photoemission peaks and a specific background curve (Shirley) and a peak model is presented that includes components to the peak model that accommodates background intensity during fitting of the peak model to data. The peak model allowed for quantification of the contributions of Pt 4f peaks emanating from the substrate that exhibits strong asymmetry in the presence of the inhomogeneously distributed Cu species, mostly of Lorentzian character.

XPS↗
DOE OSTI2022

More Tools for Visualization and Analysis of Small-Angle Neutron Scattering Data: Descriptions and Examples

With the adoption of drtsans as the data reduction software for the GP-SANS, Bio-SANS and EQ-SANS instruments at ORNL, tools for data visualization and analysis that can be integrated into drtsans scripts are needed to further improve the user experience. New tools that do not need to be incorporated directly into data reduction scripts can also positively impact users during their experiments. In this report, a new set of tools is presented that complements the previous set released. The set includes tools for both fitting data and for visualizing data.

42 ENGINEERING↗
DOE OSTI2024

High-throughput genetics enables identification of nutrient utilization and accessory energy metabolism genes in a model methanogen

Archaea are widespread in the environment and play fundamental roles in diverse ecosystems; however, characterization of their unique biology requires advanced tools. This is particularly challenging when characterizing gene function. Here, we generate randomly barcoded transposon libraries in the model methanogenic archaeon Methanococcus maripaludis and use high-throughput growth methods to conduct fitness assays (RB-TnSeq) across over 100 unique growth conditions. Using our approach, we identified new genes involved in nutrient utilization and response to oxidative stress. We identified novel genes for the usage of diverse nitrogen sources in M. maripaludis including a putative regulator of alanine deamination and molybdate transporters important for nitrogen fixation. Furthermore, leveraging the fitness data, we inferred that M. maripaludis can utilize additional nitrogen sources including $\tiny{L}$-glutamine, $\tiny{D}$-glucuronamide, and adenosine. Under autotrophic growth conditions, we identified a gene encoding a domain of unknown function (DUF166) that is important for fitness and hypothesize that it has an accessory role in carbon dioxide assimilation. Finally, comparing fitness costs of oxygen versus sulfite stress, we identified a previously uncharacterized class of dissimilatory sulfite reductase-like proteins (Dsr-LP; group IIId) that is important during growth in the presence of sulfite. When overexpressed, Dsr-LP conferred sulfite resistance and enabled use of sulfite as the sole sulfur source. The high-throughput approach employed here allowed for generation of a large-scale data set that can be used as a resource to further understand gene function and metabolism in the archaeal domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Amplitude analysis of resonant production in three pions

We present some results on the analysis of three pion resonances. The analyses are motivated by the recent release of the largest data set on diffractively produced three pions by the COMPASS collaboration. We construct reaction amplitudes that satisfy fundamental $S$-matrix principles, which allows the use of models that have physical constraints to be used in fitting data. The models are motivated by the isobar model that satisfy unitarity constraints. The model consist of a Deck production amplitude with which final state interactions are constrained by unitarity. We employ the isobar model where two of the pions form a quasi-stable particle. The analysis is performed in the high-energy, single Regge limit. We specifically discuss the examples of the three pion $J^{PC}=2^{-+}$ resonance in the $\rho\pi$ and $f_2\pi$ channels.

Jackura, Andrew↗