Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “FIT”

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 379 records · Page 21

Impact of high invariant-mass Drell-Yan forward-backward asymmetry measurements on SMEFT fits

We study the impact of LHC forward-backward asymmetry (AFB) measurements at high invariant mass in the Drell-Yan process on probes of semileptonic four-fermion operators in the Standard Model effective field theory (SMEFT). In particular, we study whether AFB measurements can resolve degeneracies in the Wilson coefficient parameter space that appear when considering invariant-mass and rapidity measurements alone. We perform detailed fits of the available high-energy and high-luminosity ATLAS and CMS data for both invariant-mass distributions and AFB. While each type of measurement separately exhibits degeneracies, combining them removes these blind spots in some cases. In other situations, it does not, highlighting the importance of incorporating future datasets from other experiments to fully explore this sector of the SMEFT. We investigate the impact of contributions quadratic in the Wilson coefficients on the description of Drell-Yan data and discuss when such terms are important in joint fits of the AFB and invariant-mass data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Cosmic distance inference from purely geometric BAO methods: Linear point standard ruler and correlation function model fitting

Leveraging the baryon acoustic oscillations (BAO) feature present in clustering 2-point statistics, we aim to measure cosmological distances independently of the underlying background cosmological model. However this inference is complicated by late-time nonlinearities that introduce model and tracer dependencies in the clustering correlation function and power spectrum, which must be properly accounted for. With this in mind, we introduce the “purely geometric-BAO,” which provides a rigorous tool to measure cosmological distances without assuming a specific background cosmology. We focus on the 2-point clustering correlation function monopole, and show how to implement such an inference scheme employing two different methodologies: the linear point standard ruler (LP) and correlation-function model-fitting (CF-MF). For the first time we demonstrate how, by means of the CF-MF, we can measure very precisely the sound-horizon/isotropic-volume-distance ratio, r d /DV(z¯), while correctly propagating all the uncertainties. Using synthetic data, we compare the outcomes of the two methodologies, and find that the LP provides up to 50% more precise measurements than the CF-MF. Finally, we test a procedure widely employed in BAO analyses: fitting the 2-point function while fixing the cosmological and the non-linear-damping parameters at fiducial values. We find that this underestimates the distance errors by nearly a factor of 2. Furthermore, we recommend that this practice be reconsidered, whether for parameter determination or model selection.

79 ASTRONOMY AND ASTROPHYSICS↗

Practical guide to understanding goodness-of-fit metrics used in chemical state modeling of x-ray photoelectron spectroscopy data by synthetic line shapes using nylon as an example

Chemical state analysis of a sample surface through fitting bell-shaped curves to x-ray photoelectron spectroscopic polymer data is reviewed using nylon to introduce and discuss aspects of data analysis. Different strategies for modeling chemistry in nylon spectra are presented and in so doing, a case is made to include in published science the design logic and implementation in terms of line shapes and optimization parameter constraints between components in a peak model. Imperfections in line shape relative to the true shape for photoemission lines, when compensated for using constraints to optimization parameters, are shown to provide chemical state information about a sample that justify, for peak models constructed with these limitations, metrics for goodness-of-fit different from those expected for pulse-counted data.

Materials Science↗

Reevaluation of XPS Pt 4f peak fitting: Ti 3s plasmon peak interference and Pt metallic peak asymmetry in Pt@TiO2 system

The structural, electronic, and electrochemical properties of noble metals supported on transition metal oxides, such as Pt nanoparticles (NPs) supported on TiO2 (Pt@TiO2), have been extensively studied for their relevance to energy technologies, including photocatalysis, electrocatalysis, and electrochemical energy conversion. As the need to lower the amount of Pt and other noble metals used in energy conversion systems becomes urgent, it is essential to accurately quantify the loading of these metals and electronic density redistribution between them and their supports. X-ray photoelectron spectroscopy (XPS) is widely used for the identification and quantification of chemical species. In particular, fitting of the Pt 4f spectra for Pt@TiO2 is frequently performed to determine the chemical environment and oxidation state of Pt, which strongly affect the physical behavior and catalytic performance of this system. Here, we show that neglecting contributions due to the Pt surroundings and the asymmetry of the Pt metal peak in the line shape fitting can lead to severe mischaracterization of the oxidation state of Pt. We quantify the effects of background contributions that stem from the TiO2 support and discuss how factoring in the strong asymmetry of Pt 4f doublets, which stems from the shake-up type processes, affects the interpretation of Pt 4f XPS line shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SU-F-I-63: Relaxation Times of Lipid Resonances in NAFLD Animal Model Using Enhanced Curve Fitting

Purpose: The objective of this study is to evaluate the relaxation time of methylene resonance in comparison with other lipid resonances. Methods: The examinations were performed on a 3.0T MRI scanner using a four-channel animal coil. Eight more Sprague-Dawley rats in the same baseline weight range were housed with ad libitum access to water and a high-fat (HF) diet (60% fat, 20% protein, and 20% carbohydrate). In order to avoid large blood vessels, a voxel (0.8×0.8×0.8 cm{sup 3}) was placed in a homogeneous area of the liver parenchyma during free breathing. Lipid relaxations in NC and HF diet rats were estimated at a fixed repetition time (TR) of 6000 msec, and multi echo time (TEs) of 40–220 msec. All spectra for data measurement were processed using the Advanced Method for Accurate, Robust, and Efficient Spectral (AMARES) fitting algorithm of the Java-based Magnetic Resonance User Interface (jMRUI) package. Results: The mean T2 relaxation time of the methylene resonance in normal-chow diet was 37.1 msec (M{sub 0}, 2.9±0.5), with a standard deviation of 4.3 msec. The mean T2 relaxation time of the methylene resonance was 31.4 msec (M{sub 0}, 3.7±0.3), with a standard deviation of 1.8 msec. The T2 relaxation times of methylene protons were higher in normal-chow diet rats than in HF rats (p<0.05), and the extrapolated M{sub 0} values were higher in HF rats than in NC rats (p<0.005). The excellent linear fit with R{sup 2}>0.9971 and R{sup 2}>0.9987 indicates T2 relaxation decay curves with mono-exponential function. Conclusion: In in vivo, a sufficient spectral resolution and a sufficiently high signal-to-noise ratio (SNR) can be achieved, so that the data measured over short TE values can be extrapolated back to TE = 0 to produce better estimates of the relative weights of the spectral components. In the short term, treating the effective decay rate as exponential is an adequate approximation.

60 APPLIED LIFE SCIENCES↗

Impact of Polymicrobial Infection on Fitness of Streptococcus gordonii In Vivo

Pathogenic microbial ecosystems are often polymicrobial, and interbacterial interactions drive emergent properties of these communities. In the oral cavity, Streptococcus gordonii is a foundational species in the development of plaque biofilms, which can contribute to periodontal disease and, after gaining access to the bloodstream, target remote sites such as heart valves. Here, we used a transposon sequencing (Tn-Seq) library of S. gordonii to identify genes that influence fitness in a murine abscess model, both as a monoinfection and as a coinfection with an oral partner species, Porphyromonas gingivalis. In the context of a monoinfection, conditionally essential genes were widely distributed among functional pathways. Coinfection with P. gingivalis almost completely changed the nature of in vivo gene essentiality. Community-dependent essential (CoDE) genes under the coinfection condition were primarily related to DNA replication, transcription, and translation, indicating that robust growth and replication are required to survive with P. gingivalis in vivo. Interestingly, a group of genes in an operon encoding streptococcal receptor polysaccharide (RPS) were associated with decreased fitness of S. gordonii in a coinfection with P. gingivalis. Individual deletion of two of these genes (SGO_2020 and SGO_2024) resulted in the loss of RPS production by S. gordonii and increased susceptibility to killing by neutrophils. P. gingivalis protected the RPS mutants by inhibiting neutrophil recruitment, degranulation, and neutrophil extracellular trap (NET) formation. These results provide insight into genes and functions that are important for S. gordonii survival in vivo and the nature of polymicrobial synergy with P. gingivalis. Furthermore, we show that RPS-mediated immune protection in S. gordonii is dispensable and detrimental in the presence of a synergistic partner species that can interfere with neutrophil killing mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli

There is an urgent need for strategies to discover secondary drugs to prevent or disrupt antimicrobial resistance (AMR), which is causing >700,000 deaths annually. Here, we demonstrate that tetracycline-resistant (Tet R ) Escherichia coli undergoes global transcriptional and metabolic remodeling, including downregulation of tricarboxylic acid cycle and disruption of redox homeostasis, to support consumption of the proton motive force for tetracycline efflux. Using a pooled genome-wide library of single-gene deletion strains, at least 308 genes, including four transcriptional regulators identified by our network analysis, were confirmed as essential for restoring the fitness of Tet R E. coli during treatment with tetracycline. Targeted knockout of ArcA, identified by network analysis as a master regulator of this new compensatory physiological state, significantly compromised fitness of Tet R E. coli during tetracycline treatment. A drug, sertraline, which generated a similar metabolome profile as the arcA knockout strain, also resensitized Tet R E. coli to tetracycline. We discovered that the potentiating effect of sertraline was eliminated upon knocking out arcA, demonstrating that the mechanism of potential synergy was through action of sertraline on the tetracycline-induced ArcA network in the Tet R strain. Our findings demonstrate that therapies that target mechanistic drivers of compensatory physiological states could resensitize AMR pathogens to lost antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗

HERAFitter: Open source QCD fit project

HERAFitter is an open-source package that provides a framework for the determination of the parton distribution functions (PDFs) of the proton and for many different kinds of analyses in Quantum Chromodynamics (QCD). It encodes results from a wide range of experimental measurements in lepton-proton deep inelastic scattering and proton-proton (proton-antiproton) collisions at hadron colliders. These are complemented with a variety of theoretical options for calculating PDF-dependent cross section predictions corresponding to the measurements. The framework covers a large number of the existing methods and schemes used for PDF determination. The data and theoretical predictions are brought together through numerous methodological options for carrying out PDF fits and plotting tools to help visualise the results. While primarily based on the approach of collinear factorisation, HERAFitter also provides facilities for fits of dipole models and transverse-momentum dependent PDFs. The package can be used to study the impact of new precise measurements from hadron colliders. This paper describes the general structure of HERAFitter and its wide choice of options.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Rossi-alpha Uncertainty Quantification by Analytic, Bootstrap, and Sample Methods to Inform Fitting Best Practices

The prompt neutron period (the negative reciprocal of the prompt neutron decay constant) can be estimated using the Rossi-alpha technique that is predicated on fitting Rossi alpha histograms and of interest in nuclear criticality safety and nonproliferation. The histograms are traditionally fit with a one-exponential model; however, recent work has proposed a two-exponential model to account for reflector induced phenomenon. Until recently, the uncertainty quantification for either model was inadequate (inaccurate and demanded large measurement times). Measurement uncertainty quantification by sample and analytic methods was developed and validated in Ref. The purpose of this transaction is to (i) validate a new bootstrap method by comparing bin-by-bin error bar estimates and (ii) demonstrate how to choose bin widths and reset times to optimize precision and accuracy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hybrid time–frequency domain dual-probe coherent anti-Stokes Raman scattering for simultaneous temperature and pressure measurements in compressible flows via spectral fitting

We demonstrate a hybrid time–frequency spectroscopic method for simultaneous temperature/pressure measurements in nonreacting compressible flows with known gas composition. Hybrid femtosecond–picosecond, pure-rotational coherent anti-Stokes Raman scattering (CARS), with two independent, time-delayed probe pulses, is deployed for single-laser-shot measurements of temperature and pressure profiles along an ∼ <#comment/> 5 -mm line. The theory of dual-probe CARS is presented, along with a discussion of the iterative fitting of experimental spectra. Temperature is obtained from spectra acquired with an early, near-collision-free probe time delay ( τ <#comment/> 1 = 0 p s ) and pressure from spectra obtained at probe delays of τ <#comment/> 2 = 150 − <#comment/> 1000 p s , where collisions significantly impact the spectral profile. Unique solutions for temperature and pressure are obtained by iteratively fitting the two spectra to account for small collisional effects observed for the near zero probe delay spectrum. A dual-probe pure-rotational CARS system, in a 1D line-imaging configuration, is developed to demonstrate effectively the simultaneous temperature and pressure profiles recorded along the axial centerline of a highly underexpanded jet. The underexpanded air jet permits evaluation of this hybrid time–frequency domain approach for temperature and pressure measurements across a wide range of low-temperature–low-pressure conditions of interest in supersonic ground-test facilities. Single-laser-shot measurement precisions in both quantities and pressure measurement accuracy are systematically evaluated in the quiet zone upstream of the Mach disk. Precise thermometry approaching 1%−2% is observed in regions of high CARS signal-to-noise ratios. Pressure measurements are optimized at probe time delays where the ratio of the late probe delay to the Raman lifetime exceeds four ( τ <#comment/> 2 / τ <#comment/> R > <#comment/> 4 ). The impact of low-temperature Raman linewidths on CARS pressure measurements is evaluated, and comparisons of CARS pressures obtained with our recent low-temperature pure-rotational Raman linewidth data and extrapolated high-temperature Q -branch linewidths are presented. Considering all measurements with τ <#comment/> 2 / τ <#comment/> R ≥ <#comment/> 4.0 , measured pressures were on average 7.9% of the computed isentropic values with average shot-to-shot deviations representing a combination of instrument noise and fluid fluctuations of 5.0%.

Retter, Jonathan E.↗

Evaluating E. coli genome‐scale metabolic model accuracy with high‐throughput mutant fitness data

Abstract The Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

59 BASIC BIOLOGICAL SCIENCES↗

AK112: Full Waveform Inversion Tomography of Alaska Improves Waveform Fits While Imaging Crustal, Mantle, and Slab Structure

We report a full waveform inversion tomography model of Alaska and the surrounding regions, inferring radially anisotropic shear and isotropic compressional wavespeeds by fitting complete waveforms from 120 regional earthquakes. Our multiscale approach inverted time–frequency phase misfits (maximum period of 100 s), starting with a minimum period of 40 s and ending at 20 s in 7 stages and 112 total iterations. The model (AK112) was evaluated by computing the misfits for 36 independent validation events. We find that misfit reductions were large and equal (∼55%) for both the inversion and validation data sets, providing confidence in the model. AK112 also provides much better waveform fits compared to other reported models for the region, including an isotropic version of itself, highlighting the importance of anisotropy. The model resolves known crustal, upper mantle, and slab structure to depths of 100 km with new detail: sedimentary basins in the Alaskan Shelf, Cook Inlet, and Colville basins, among others; discontinuous lithospheric structure across major terrane boundaries; and subducting slab geometry and back‐arc volcanic sources. In addition to tectonic interpretations, the model enables full waveform simulations for long‐period earthquake ground motions and source characterization (e.g., moment tensor and finite‐fault inversion).

Rodgers, Arthur [Lawrence Livermore National Labor↗

Averaging cross section data so we can fit it

The 56 Fe cross section we are interested in have a lot of fluctuations. We would like to fit the average of the cross section with cross sections calculated within EMPIRE. EMPIRE is a Hauser-Feshbach theory based nuclear reaction code, requires cross sections to be smoothed using a Lorentzian profile. The plan is to fit EMPIRE to these cross sections in the fast region (say above 500 keV).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Hunt for Green Every April: Factors Affecting Fitness in Switchgrass

This grant funded work was undertaken to develop fundamental biological knowledge of the factors affecting the complex plant trait “fitness” in switchgrass (Panicum virgatum L.), a plant being developed as a biomass crop. Using a diverse range of latitudinally-adapted switchgrass plants, genomic, molecular and physiological studies were performed to track a number of different aspects of plant genetics and physiology over the course of the growing season. Work was performed on both genetically unrelated and genetically related plants. Plants were established in the field from seedlings raised in a greenhouse, or from clones present in other field nurseries. Field grown plants were used as the source of all tissues. The three objectives of this proposal were:(1) Transcript Profiling, Metabolomics, and C and N Partitioning and Recycling in Crowns and Rhizomes of Switchgrass over two growing seasons; (2) Gene Profiling During Regreening and Dormancy of Bulked Segregants; (3) Extent of Linkage Disequilibrium in Populations for Adaptation and Fitness Traits Being Developed for Central and Northern USA, that Show Significant Heterosis. Objective 1 results: Plants were labeled using 13 CO2 (a stable isotope) using an acrylic chamber constructed specifically for this purpose. Plants became labeled with 13 C and label decayed in aerial tissues over the course of the growing season. Varying amounts of 13 C were recovered in the rhizomes. These data are being analyzed. Plants were also labeled with 15 N-urea. Plants absorbed significant amounts of label that was remobilized to the growing shoots. N-dynamics would suggest that a portion of the 15 N absorbed into the crowns and rhizomes is sequestered below ground. Variable amounts of 15 N were translocated from the shoots to the roots over the course of the growing season. Polar metabolites extracted from a diverse array of rhizomes were analyzed using GCMS. Data indicated that there was a significant shift in metabolite pools over the course of the growing season, and differences in the levels of specific metabolites could be linked to the progression of dormancy. Several metabolites that accumulate in dormant rhizomes were identified. Some of these metabolites could be potentially linked to winter-survival of switchgrass. Extensive high-throughput sequencing was conducted on crown and rhizome samples collected from field grown plants. Initial work was performed on a Roche 454 system. All later work was performed on an Illumina sequencing-by-synthesis system. Some of these datasets have been published as peer-reviewed papers, other data are currently being analyzed and being readied for publication. Objective 2 results: Genetically related but phenotypically divergent plants from an octaploid switchgrass population were grown in a replicated field nursery. Rhizomes were harvested at four different times over the course of the growing season from plants with high winter survival and those with lower winter survival. RNA-Seq was performed on harvested materials. Initial analysis suggests that plants with lowered winter survival experience a greater level of cellular stress in dormant tissues. This aspect of plant function is being probed in greater depth. Objective 3 results: A total of 592 individual clones with three clonal replications in a randomized complete block design from each of five populations used in Objective 1 studies were rated for heading date in 2012 and 2014, green-up day of year in 2013, anthesis date in 2012, and yield in 2012, they were also subjected to NIR spectroscopy to derive cell wall composition estimates based on prior NIR calibrations. Plants were genotyped via a genotyping by sequencing (GBS) approach from reduced representation libraries constructed with adaptors that identified each individual. Libraries generated with the restriction enzyme PstI and called SNPs using Samtools after alignment to version 1.1 of the switchgrass genome sequence. A total of approximately 40,000 SNPs were found. These were then further filtered to eliminate markers with a minor allele frequency of < 0.05. The results of population analysis using STRUCTURE with expected population sizes or cluster numbers (K), clearly shows the hybrid composition of the KxS population and discriminated easily between upland (Summer) and lowland (Kanlow) populations. Under an assumption of 5 distinct populations there were detectable differences in allele frequencies between subpopulations within the three Kanlow populations particularly with respect to Kanlow EM and Kanlow base. We detected 110 SNPs with an allele frequency difference of ≥ 0.2 between Kanlow EM and Kanlow base populations, while 120 SNPs showed an allele frequency difference of ≥ 0.15 between Kanlow N1 and Kanlow base populations. These data are being readied for publication.

59 BASIC BIOLOGICAL SCIENCES↗

Neutron Multiplicity: LANL W Covariance Matrix for Curve Fitting

In neutron multiplicity counting one may fit a curve by minimizing an objective function, χ$2\atop{n}$. The objective function includes the inverse of an n by n matrix of covariances, W. The inverse of the W matrix has a closed form solution. In addition W -1 is a tri-diagonal matrix. The closed form and tridiagonal nature allows for a simpler expression of the objective function χ$2\atop{n}$. Minimization of this simpler expression will provide the optimal parameters for the fitted curve.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fitness Tracker for Weight Lifting Style Workouts

This document proposes an early, high level design for a fitness tracking system which can automatically log weight lifting style workouts. The system will provide an easy to use interface both physically through the use of several wireless wristband style motion trackers worn on the limbs, and graphically through a smartphone application. Exercise classification will be accomplished by calibration of the user’s specific motions. The system will accurately track a user’s workout, miscounting no more than one repetition in every 20, have sufficient battery life to last several hours, work with existing smartphones and have a cost similar to those of current fitness tracking devices. This document presents the mission background, current state-of-theart, stakeholders and their expectations, the proposed system’s context and concepts, implementation concepts, system requirements, first sublevel function decomposition, possible risks for the system, and a reflection on the design process.

42 ENGINEERING↗

Extraction of Neutrino Oscillation Parameters using a Simultaneous Fit of $\nu_{\mu}$ Disappearance and $\nu_{e}$ Appearance data with the NOvA Experiment

This thesis presents the analyses and results of the $\nu_{\mu} \rightarrow \nu_{\mu}$ disappearance and $\nu_{\mu} \rightarrow \nu_{e}$ appearance due to neutrino oscillations using 8.85 $\times$ 10$^{20}$ protons on target (POT) equivalent of data collected by the NOvA experiment. The data analyzed in this thesis was collected from February 06, 2014 to February 20, 2017. NOvA is an accelerator-based, long-baseline neutrino oscillation experiment and uses the two detector set-up to study the phenomenon of neutrino oscillation using a beam of muon neutrinos produced at Fermilab. One NOvA detector is placed within the Fermilab campus, 100 m underground, at a distance of 1 km from the neutrino source and is called the Near Detector (ND). The ND is 300 ton in mass and smaller in size than the Far Detector (FD) which is 14 kton in mass and is placed 810 km away from the neutrino source in Ash River, Minnesota (MN). Both ND and FD are made of the same material and are functionally identical. The ND being closer to the neutrino source, analyzes the neutrino beam before the neutrinos oscillate and the FD analyzes the neutrinos after oscillations. The ND is used to predict the signal and background expectations in the FD. The similarity in the ND and FD help to reduce the systematic uncertainties in the FD prediction. The combined oscillation fit to the $\nu_{\mu} \rightarrow \nu_{\mu}$ disappearance and $\nu_{\mu} \rightarrow \nu_{e}$ appearance gives the best fit values of the $\Delta m^{2}_{32}$, $\sin^{2}{\theta_{32}}$ and $\delta_{CP}$ oscillation parameters and are presented in this thesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗