Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sensitivity study”

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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Atmospheric neutrinos in next-generation xenon and argon dark matter experiments

In this work, we study the sensitivity of future xenon- and argon-based dark matter and neutrino detection experiments to low-energy atmospheric neutrinos. Not accounting for experimental backgrounds, the primary obstacle for identifying nuclear recoils induced by atmospheric neutrinos in xenon is the tail of the electron recoil distribution due to pp solar neutrinos. We use the NEST code to model the solar and atmospheric neutrino signals in a xenon detector and find that an exposure of 700 tonne-years will produce a 5σ detection of atmospheric neutrinos. We explore the effect of different detector properties and find that a sufficiently long electron lifetime is essential to the success of such a measurement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Constraining neutrinophilic mediators at FASER ν , FLArE, and FASER ν 2

High energy collider neutrinos have been observed for the first time by the FASER ν experiment. The detected spectrum of collider neutrinos scattering off nucleons can be used to probe neutrinophilic mediators with GeV-scale masses. We find that constraints on the pseudoscalar (axial vector) neutrinophilic mediator are close to the scalar (vector) case since they have similar cross section in the neutrino massless limit. We perform an analysis on the measured muon spectra at FASER ν , and find that the bounds on the vector mediator from the current FASER ν data are comparable to the existing bounds at m Z ′ ≈ 0.2 GeV . We also study the sensitivities to a neutrinophilic mediator at future Forward Physics Facilities including FLArE and FASER ν 2 by using both the missing transverse momentum and the charge identification information. We find that FLArE and FASER ν 2 can impose stronger bounds on both the scalar and vector neutrinophilic mediators than the existing bounds. The constraints on the scalar mediator can reach 0.08 (0.1) for m ϕ ≲ 1 GeV with (without) muon charge identification at FASER ν 2 . Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Multiscale Monte Carlo equilibration: Two-color QCD with two fermion flavors

In this study, we demonstrate the applicability of a recently proposed multiscale thermalization algorithm to two-color quantum chromodynamics (QCD) with two mass-degenerate fermion flavors. The algorithm involves refining an ensemble of gauge configurations that had been generated using a renormalization group (RG) matched coarse action, thereby producing a fine ensemble that is close to the thermalized distribution of a target fine action; the refined ensemble is subsequently rethermalized using conventional algorithms. Although the generalization of this algorithm from pure Yang-Mills theory to QCD with dynamical fermions is straightforward, we find that in the latter case, the method is susceptible to numerical instabilities during the initial stages of rethermalization when using the hybrid Monte Carlo algorithm. We find that these instabilities arise from large fermion forces in the evolution, which are attributed to an accumulation of spurious near-zero modes of the Dirac operator. We propose a simple strategy for curing this problem, and demonstrate that rapid thermalization--as probed by a variety of gluonic and fermionic operators--is possible with the use of this solution. Also, we study the sensitivity of rethermalization rates to the RG matching of the coarse and fine actions, and identify effective matching conditions based on a variety of measured scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Performance of High-Convergence, Layered DT Implosions on Power-Scaling Experiments at National Ignition Facility

The radiation-driven, low-adiabat, cryogenic DT layered plastic capsule implosions were carried out on the National Ignition Facility (NIF) to study the sensitivity of performance to peak power and drive duration. An implosion with extended drive and at reduced peak power of 350 TW achieved the highest compression with fuel areal density of ~1.3±0.1 g/cm 2 , representing a significant step from previously measured ~1.0 g/cm 2 toward a goal of 1.5 g/cm 2 . Moreover, for future experiments will focus on understanding and mitigating hydrodynamic instabilities and mix, and improving symmetry required to reach the threshold for thermonuclear ignition on NIF.

42 ENGINEERING↗
DOE OSTI2016

Can Ab Initio Theory Explain the Phenomenon of Parity Inversion in Be 11 ?

The weakly bound exotic 11 Be nucleus, famous for its ground-state parity inversion and distinct n + 10 Be halo structure, is investigated from first principles using chiral two- and three-nucleon forces. An explicit treatment of continuum effects is found to be indispensable. We study the sensitivity of the 11 Be spectrum to the details of the three-nucleon force and demonstrate that only certain chiral interactions are capable of reproducing the parity inversion. With such interactions, the extremely large E 1 transition between the bound states is reproduced. We compare our photodisintegration calculations to conflicting experimental data and predict a distinct dip around the 3/2 – 1 resonance energy. Finally, we predict low-lying 3/2 + and 9/2 + resonances that are not or not sufficiently measured in experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Randomized low-rank decompositions of nuclear three-body interactions

First-principles simulations of many-fermion systems are commonly limited by the computational requirements of processing large data objects. As a remedy, we propose the use of low-rank approximations of three-body interactions, which are the dominant such limitation in nuclear physics. We introduce a randomized decomposition technique to handle the excessively large matrix dimensions and study the sensitivity of low-rank properties to interaction details. The developed low-rank three-nucleon interactions are benchmarked in ab initio simulations of few- and many-body systems. Exploiting low-rank properties provides a promising route to extend the microscopic description of atomic nuclei to large systems where storage requirements exceed the computational capacities of the most advanced high-performance computing facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Alignment of low-dose X-ray fluorescence tomography images using differential phase contrast

X-ray fluorescence nanotomography provides unprecedented sensitivity for studies of trace metal distributions in whole biological cells. Dose fractionation, in which one acquires very low dose individual projections and then obtains high statistics reconstructions as signal from a voxel is brought together (Hegerl & Hoppe, 1976), requires accurate alignment of these individual projections so as to correct for rotation stage runout. It is shown here that differential phase contrast at 10.2 keV beam energy offers the potential for accurate cross-correlation alignment of successive projections, by demonstrating that successive low dose, 3 ms per pixel, images acquired at the same specimen position and rotation angle have a narrower and smoother cross-correlation function (1.5 pixels FWHM at 300 nm pixel size) than that obtained from zinc fluorescence images (25 pixels FWHM). The differential phase contrast alignment resolution is thus well below the 700 nm × 500 nm beam spot size used in this demonstration, so that dose fractionation should be possible for reduced-dose, more rapidly acquired, fluorescence nanotomography experiments.

differential phase contrast↗
DOE OSTI2015

Photosynthetic leaf area modulates tiller bud outgrowth in sorghum

Abstract Shoot branches or tillers develop from axillary buds. The dormancy versus outgrowth fates of buds depends on genetic, environmental and hormonal signals. Defoliation inhibits bud outgrowth indicating the role of leaf‐derived metabolic factors such as sucrose in bud outgrowth. In this study, the sensitivity of bud outgrowth to selective defoliation was investigated. At 6 d after planting (6 DAP ), the first two leaves of sorghum were fully expanded and the third was partially emerged. Therefore, the leaves were selectively defoliated at 6 DAP and the length of the bud in the first leaf axil was measured at 8 DAP . Bud outgrowth was inhibited by defoliation of only 2 cm from the tip of the second leaf blade. The expression of dormancy and sucrose‐starvation marker genes was up‐regulated and cell cycle and sucrose‐inducible genes was down‐regulated during the first 24 h post‐defoliation of the second leaf. At 48 h, the expression of these genes was similar to controls as the defoliated plant recovers. Our results demonstrate that small changes in photosynthetic leaf area affect the propensity of tiller buds for outgrowth. Therefore, variation in leaf area and photosynthetic activity should be included when integrating sucrose into models of shoot branching.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗
DOE OSTI2014

SU-E-T-222: Investigation of Pre and Post Irradiation Fading of the TLD100 Thermoluminescence Dosimetry for Photon Beams

Purpose: The pre-irradiation and post-irradiation fading of the Thermoluminescense dosimeter signals were investigated in this study. Methods: Two groups of TLD chips with pre-determined ECC values were used in this study. The two groups were divided into 6 series, each composing of 5 TLD chips.The first group was used for pre-irradiation fading. 5 TLDs were exposed to a known amount of radiation from Cs-137 source, and were read out the next day. After seven days, the other 5 TLDs were exposed to the same amount of radiation and were read out after a day. The other series of 5 TLDs were also exposed after 7,19,28, 59, and 90 days, and were read out a day after irradiation. The loss in TLD signal were obtained for all the above cases. The second group, was used for postirradiation fading. All the TLDs of this group were exposed to a known amount of radiation from Cs-137 source. The 6 series composed of 5 TLDs were read out after 1,7,19,28,59, and 90 days. The above-mentioned procedures for obtaining pre-irradiation, and post-irradiation fading were performed for three storage temperatures (25°C, 4°C, and −18°C). Results: According to the results obtained in this study, in case of pre-irradiation fading study, the signal losses after 90 days are 12%, 24%, and 17% for 25°C, 4°C, and −18°C respectively. In case of post-irradiation fading study, the sensitivity losses after 90 days are 25%, 216%, and 20% for 25°C, 4°C, and −18°C respectively. Conclusion: The results indicate that the optimized time between exposing and reading out, and also the optimized time between annealing and exposing is 1 day.The reduction of Storage temperature will reduce the post-irradiation fading, While temperature reduction does not have any effect on pre-irradiation fading.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Characterization of the SARS-CoV-2 B.1.621 (Mu) variant

The SARS-CoV-2 B.1.621 (Mu) variant emerged in January 2021 and was categorized as a variant of interest by the World Health Organization in August 2021. This designation prompted us to study the sensitivity of this variant to antibody neutralization. In a live virus neutralization assay with serum samples from individuals vaccinated with the Pfizer/BioNTech or Moderna mRNA vaccines, we measured neutralization antibody titers against B.1.621, an early isolate (spike 614D), and a variant of concern (B.1.351, Beta variant). We observed reduced neutralizing antibody titers against the B.1.621 variant (3.4- to 7-fold reduction, depending on the serum sample and time after the second vaccination) compared to the early isolate and a similar reduction when compared to B.1.351. Likewise, convalescent serum from hamsters previously infected with an early isolate neutralized B.1.621 to a lower degree. Despite this antibody titer reduction, hamsters could not be efficiently rechallenged with the B.1.621 variant, suggesting that the immune response to the first infection is adequate to provide protection against a subsequent infection with the B.1.621 variant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Dispersive approaches for three-particle final state interaction

In this work, we presented different representations of Khuri-Treiman equation, the advantage and disadvantage of each representations are discussed. With a scattering amplitude toy model, we also studied the sensitivity of solution of KT equation to left-hand cut of toy model and to the different approximate methods. At last, we give a brief discussion of Watson's theorem when three particles in final states are involved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Fastlim: A fast LHC limit calculator

Fastlim is a tool to calculate conservative limits on extensions of the Standard Model from direct LHC searches without performing any Monte Carlo event generation. The program reconstructs the visible cross sections (cross sections after event selection cuts) from pre-calculated efficiency tables and cross section tables for simplified event topologies. As a proof of concept of the approach, we have implemented searches relevant for supersymmetric models with R-parity conservation. Fastlim takes the spectrum and coupling information of a given model point and provides, for each signal region of the implemented analyses, the visible cross sections normalised to the corresponding upper limit, reported by the experiments, as well as the CLs(Formula presented) value. To demonstrate the utility of the program we study the sensitivity of the recent ATLAS missing energy searches to the parameter space of natural SUSY models. The program structure allows the straightforward inclusion of external efficiency tables and can be generalised to R-parity violating scenarios and non-SUSY models. This paper serves as a self-contained user guide and indicates the conventions and approximations used.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

An Improved Convective Ice Parameterization for the NASA GISS Global Climate Model and Impacts on Cloud Ice Simulation

Partitioning of convective ice into precipitating and detrained condensate presents a challenge for GCMs since partitioning depends on the strength and microphysics of the convective updraft. It is an important issue because detrainment of ice from updrafts influences the development of stratiform anvils, impacts radiation, and can affect GCM climate sensitivity. Recent studies have shown that the CMIP5 configurations of the Goddard Institute for Space Studies (GISS) GCM simulated upper-tropospheric ice water content (IWC) that exceeded an estimated upper bound by a factor of 2. Partly in response to this bias, a new GCM parameterization of convective cloud ice has been developed that incorporates new ice particle fall speeds and convective outflow particle size distributions (PSDs) from the NASA African Monsoon Multidisciplinary Analyses (NAMMA), NASA Tropical Composition, Cloud and Climate Coupling (TC4), DOE ARM–NASA Midlatitude Continental Convective Clouds Experiment (MC3E), and DOE ARM Small Particles in Cirrus (SPARTICUS) field campaigns. The new parameterization assumes a normalized gamma PSD with two novel developments: no explicit assumption for particle habit in the calculation of mass distributions, and a formulation for translating ice particle fall speeds as a function of maximum diameter into fall speeds as a function of melted-equivalent diameter. Two parameters (particle volume– and projected area–weighted equivalent diameter) are diagnosed as a function of temperature and IWC in the convective plume, and these parameters constrain the shape and scale of the normalized gamma PSD. The diagnosed fall speeds and PSDs are combined with the GCM’s parameterized convective updraft vertical velocity to partition convective updraft condensate into precipitating and detrained components. A 5-yr prescribed sea surface temperature GCM simulation shows a 30%–50% decrease in upper-tropospheric deep convective IWC, bringing the tropical and global mean ice water path into closer agreement with CloudSat best estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Exploring the Sensitivity of Photosynthesis and Stomatal Resistance Parameters in a Land Surface Model

Abstract Land surface models, like the Common Land Model component of the ParFlow integrated hydrologic model (PF-CLM), are used to estimate transpiration from vegetated surfaces. Transpiration rates quantify how much water moves from the subsurface through the plant and into the atmosphere. This rate is controlled by the stomatal resistance term in land surface models. The Ball–Berry stomatal resistance parameterization relies, in part, on the rate of photosynthesis, and together these equations require the specification of 20 input parameters. Here, the active subspace method is applied to 2100 year-long PF-CLM simulations, forced by atmospheric data from California, Colorado, and Oklahoma, to identify which input parameters are important and how they relate to three quantities of interest: transpiration, stomatal resistance from the sunlit portion of the canopy, and stomatal resistance from the shaded portion. The slope (mp) and intercept (bp) parameters associated with the Ball–Berry parameterization are consistently important for all locations, along with five parameters associated with ribulose bisphosphate carboxylase/oxygenase (RuBisCO)- and light-limited rates of photosynthesis [CO2 Michaelis–Menten constant at 25°C (kc25), maximum ratio of oxygenation to carboxylation (ocr), quantum efficiency at 25°C (qe25), maximum rate of carboxylation at 25°C (vcmx25), and multiplier in the denominator of the equation used to compute the light-limited rate of photosynthesis (wj1)]. The importance of these input parameters, quantified by the active variable weight, and the relationship between the input parameters and quantities of interest vary seasonally and diurnally. Input parameter values influence transpiration rates most during midday, summertime hours when fluxes are large. This research informs model users about which photosynthesis and stomatal resistance parameters should be more carefully selected. Quantifying sensitivities associated with the stomatal resistance term is necessary to better understand transpiration estimates from land surface models.

54 ENVIRONMENTAL SCIENCES↗