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At least 631 records · Page 35

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NASA NTRS2013

Sensitivity of Downward Longwave Surface Radiation to Moisture and Cloud Changes in a High-elevation Region

Several studies have suggested enhanced rates of warming in high-elevation regions since the latter half of the twentieth century. One of the potential reasons why enhanced rates of warming might occur at high elevations is the nonlinear relationship between downward longwave radiation (DLR) and specific humidity (q). Using ground-based observations at a high-elevation site in southwestern Colorado and coincident satellite-borne cloud retrievals, the sensitivity of DLR to changes in q and cloud properties is examined and quantified using a neural network method. It is also used to explore how the sensitivity of DLR to q (dDLR/dq) is affected by cloud properties. When binned by season, dDLR/dq is maximum in winter and minimum in summer for both clear and cloudy skies. However, the cloudy-sky sensitivities are smaller, primarily because (1) for both clear and cloudy skies dDLR/dq is proportional to 1/q, for q>0.5 g/kg, and (2) the seasonal values of q are on average larger in the cloudy-sky cases than in clear-sky cases. For a given value of q, dDLR/dq is slightly reduced in the presence of clouds and this reduction increases as q increases. In addition, DLR is found to be more sensitive to changes in cloud fraction when cloud fraction is large. In the limit of overcast skies, DLR sensitivity to optical thickness decreases as clouds become more opaque. These results are based on only one high-elevation site, so the conclusions here need to be tested at other high-elevation locations.

cloud physics↗

NASA NTRS2014

Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice.

Antarctic Ocean↗

NASA NTRSDate not supplied

How Well Satellite Remote Sensing Can Inform Surface Level Ozone Production Sensitivity to Precursor Trace Gas Emissions?

Surface-level ozone (O3) pollution mitigation strategies rely on a clear understanding of the atmospheric chemical processes involving O3, NOx (nitric oxide (NO) + nitrogen dioxide (NO2)) and volatile organic compounds (VOCs). A robust spatiotemporal classification of O3 photochemical regimes with relative chemical sensitivity of local O3 formation to emission reductions of NOx (NOx-limited regime) versus VOCs (radical-limited regime) is required to design anthropogenic emission reduction policies in order to improve surface air quality. Numerous studies found that the ratio of satellite-retrieved Vertical Column Densities (VCDs) of formaldehyde (HCHO) to NO2 can diagnose O3 production sensitivity. However, uncertainty still remains about the accuracy of such estimates using satellite-based retrievals. This study conducts an investigation to identify how well satellite data can inform surface-level O3 sensitivity by validating satellite-based estimates against aircraft-based retrievals taken during the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) and Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaigns. For this study, we use HCHO and NO2 retrievals from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite, and high spatiotemporal resolution TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The Community Multiscale Air Quality (CMAQ) modelling system is used to provide trace gas vertical profiles to recalculate air mass factor for deriving consistent satellite-based VCDs. To demonstrate the ability of satellites to diagnose O3 production regimes, we validate satellite-derived O3 sensitivity regimes, along with the OMI and TROPOMI products applied, using HCHO and NO2 retrievals from the aircraft-based instruments: Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) spectrometer and Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instruments deployed during the LISTOS-2018 and OWLETS-2 campaigns. The results of this work will advance our fundamental knowledge of the spatiotemporal evolution of the complex O3-NOx-VOC chemistry, and will advance our understanding about the quality of remote-sensing, suborbital, and satellite data for accurately observing surface-level O3 production sensitivity.

Satellite↗

NASA NTRSDate not supplied

Genomic and Phenotypic Associations to Predict Human Sensitivity to SpaceRadiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350MeV/n 28Si, 350MeV/n 40Ar and 600MeV/n 56Fe particles, at 1.1 and 3 particles/100 sq.m fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1+ radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radio sensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radio sensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radio sensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS radiation human↗

NASA NTRSDate not supplied

Holey Silicon-based Thermopiles for High-Sensitivity Broadband Thermal Detection in Space

Future planetary missions call for thermal detectors with high sensitivity over a wide range of temperature or wavelength. Conventional approaches based upon photon detectors are limited to a narrow and material-selective range of wavelength, and they often require cryogenic cooling for measurements of far-infrared (FIR) radiation or very low-temperature objects, which result in a significant increase in the system’s size, weight, and power (SWaP). While thermal detectors based upon thermopiles are uncooled and sensitive to a wide range of wavelengths including FIR radiation, their sensitivity, limited by the material’s thermoelectric response and heat losses, is an order of magnitude lower than photon detectors. To address the sensitivity requirements for future planetary science missions that target very cold objects such as ice giant planets, icy regoliths, planetary satellites, and primitive bodies, we introduce a high-sensitive broadband thermopile concept using holey silicon – a thin membrane of silicon with a microfabricated arrangement of pores that can be optimized to minimize heat losses and enable breakthrough thermoelectric performance. In this paper, we present our analytical model for the holey silicon-based thermopile, its performance expectations, and its performance comparisons with the state-of-the-art thermopile technology. We will investigate the roles of thermal conductance in holey silicon-based thermopile performance, the impact of thermal conduction and thermal radiation at different temperature limits, and the performance trade-off between the responsivity and noises.

thermopiles↗

DOE OSTI2019

Sensitivity Analysis of an LCC-LCC Compensated 20-kW Bidirectional Wireless Charging System for Medium-Duty Vehicles

In this paper, sensitivity analysis of an LCC-LCC compensated bidirectional wireless charging system is presented. In a wireless charging system for electric vehicle applications, the effective load impedance varies significantly with the state-of-charge (SOC)of the battery. Due to the change in system parameters, resonant frequency, and transferred power, the efficiency of the system varies significantly. Sensitivity analysis of the system characteristics reveals the optimal operating region and required control strategy to operate within that region. Sensitivity analysis is even more important for a bidirectional system with mismatched input and output voltage levels. In this paper, the sensitivity of a bidirectional 20 kW wireless charging system is investigated analytically and the results are validated experimentally. The experimental results for a geometrically matched Double-D (DD) coil-based LCC-LCC tuned bidirectional WCS with asymmetric voltage levels show that the voltage gains and input impedance of the system are highly sensitive near the resonant frequency.

Mostak, Mostak Mohammad↗

DOE OSTI2020

Method for lithograghic patterning of sensitive materials

Methods for patterning highly sensitive materials, such as organic materials, organic semiconductors, biomolecular materials, and the like, with photolithographic resolution are disclosed. In some embodiments, a germanium mask (304) is formed on the surface of the sensitive material (302), thereby protecting it from subsequent processes that employ harsh chemicals that would otherwise destroy the sensitive material (302). A microlithography mask (306) is patterned on the germanium mask layer (304), after which the germanium exposed by the microlithography mask (306) is removed by dissolving it in water. After transferring the pattern of the germanium mask (304) into the sensitive material (302), the germanium and microlithography masks (304, 306) are completely removed by immersing the substrate in water, which dissolves the remaining germanium and lifts off the microlithography mask material. As a result, the only chemical to which the sensitive material (302) is exposed during the patterning process is water, thereby mitigating or avoiding damage to the material (302).

36 MATERIALS SCIENCE↗

DOE OSTI2022

Reactivity Coefficient Measurements and Sensitivity Studies [Abstract]

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor (k eff ). K eff is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while k eff is a well-documented parameter with detailed sensitivity and uncertainty analysis, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific nuclear data by optimally designing experiments that are sensitive to a suite of measurement parameters beyond k eff . By identifying how each parameter's nuclear data sensitivity differs from others, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes reactivity coefficient sensitivities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

A Bayesian approach to the long-baseline neutrino oscillation sensitivity of DUNE

The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is evaluated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. This analysis uses the same underlying sensitivity inputs as previous DUNE studies [Eur. Phys. J. C 80, 978 (2020)], and therefore does not present updated DUNE sensitivities, but instead explores the additional inferences accessible using a Bayesian approach. We present four-dimensional posterior probability distributions of the oscillation parameters, highlighting the breadth of correlation in the parameter space of interest, especially between $\sin^2 θ_{23}$ and $\sin^2 θ_{13}$. We exploit the flexibility of the Bayesian framework to incorporate parameter constraints post hoc and assess the impact of applying a reactor short-baseline $θ_{13}$ constraint. A significant increase in the sensitivity to the $θ_{23}$ octant is found when including the constraint. Posterior distributions of derived quantities can be easily constructed from MCMC results. This work presents the first study of DUNE's sensitivity to the Jarlskog invariant, $J$, a quantity that provides a parametrisation-independent measure of charge-parity violation in the leptonic sector.

Abbaslu, Saeed [IPM, Tehran] (ORCID:00000003356771↗

DOE OSTI2017

PDE 5 inhibitor improves insulin sensitivity by enhancing mitochondrial function in adipocytes

Adipocytes are involved in many metabolic disorders. It was recently reported that phosphodiesterase type 5 (PDE5) is expressed in human adipose tissue. In addition, PDE5 inhibitors have been shown to improve insulin sensitivity in humans. However, the mechanism underlying the role of PDE5 inhibitors as an insulin sensitizer remains largely unknown. The present study was undertaken to investigate the role of the PDE5 inhibitor udenafil in insulin signaling in adipocytes and whether this is mediated through the regulation of mitochondrial function. To study the mechanism underlying the insulin sensitizing action of PDE5 inhibitors, we evaluated quantitative changes in protein or mRNA levels of mitochondrial oxidative phosphorylation (OxPhos) complex, oxygen consumption rate (OCR), and fatty acid oxidation with varying udenafil concentrations in 3T3-L1 cells. Our cell study suggested that udenafil enhanced the insulin signaling pathway in 3T3-L1 cells. Following udenafil treatment, basal mitochondrial OCR, maximal OxPhos capacity, and OxPhos gene expression significantly increased. Finally, we examined whether udenafil can affect the fatty acid oxidation process. Treatment of 3T3-L1 cells with udenafil (10 and 20 μM) significantly increased fatty acid oxidation rate in a dose-dependent manner. In addition, the expression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) significantly increased. We demonstrated that the PDE5 inhibitor udenafil enhances insulin sensitivity by improving mitochondrial function in 3T3-L1 cells. This might be the mechanism underlying the PDE5 inhibitor-enhanced insulin signaling in adipocytes. This also suggests that udenafil may provide benefit in the treatment of type 2 diabetes and other related cardiovascular diseases. - Highlights: • Udenafil enhanced the insulin signaling pathway. • Udenafil improved mitochondrial function by increasing oxygen consumption rate (OCR). • Udenafil upregulated mitochondrial OxPhos gene expression. • Udenafil was involved in increasing fatty acid oxidation (FAO).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Physics and Criticality Safety Applications

Many new reactor designs, such as advanced reactors and micro reactors, have materials that lack nuclear data validation. This is also true for many other applications in criticality safety and global security. Both differential and integral experiments are needed to validate cross-section data. Without this, a user cannot have confidence in the predicted results of a radiation-transport code. This work describes an approach called ARCHIMEDES (Application Relevant Critical/Subcritical HEU/Pu-based Integral Measurements for Enhancing Data and Evaluating Sensitivities) to design new criticality experiments that have similar k eff cross-section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. Recently, there has been a great deal of interest in the reactor physics community on advanced reactors, micro reactors, and accelerator driven systems (ADS). This work will apply the described method to specific examples in this area. The focus of this work will be on the sensitivity study and gap analysis, while future work will include experiment design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

Efficient simulation strategies are crucial for the development and evaluation of high resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity and computational efficiency of the constrained simulations depend strongly on 3 factors: the detailed implementation of nudging, the mechanism through which the perturbed parameter affects precipitation and cloud, and the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature and/or wind nudging with a 6-hour relaxation time scale leads to non-negligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while a 1-year free running simulation can satisfactorily capture the annual mean precipitation sensitivity in terms of both global average and geographical distribution. In the case of a relatively weak perturbation the large-scale condensation scheme, results from 1-year free-running simulations are strongly affected by noise associated with internal variability, while nudging winds effectively reduces the noise, and reasonably reproduces the response of precipitation and cloud forcing to parameter perturbation. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

In‐Silico Device Performance Prediction of Cosensitizer Dye Pairs for Dye‐Sensitized Solar Cells

Abstract Endeavors in the field of dye‐sensitized solar cells (DSCs) have shown great promise when adopting a data‐driven approach to materials discovery, such as successful molecular‐scale predictions of light‐harvesting chromophores. However, predictions of DSC dyes would become much more sophisticated if a molecular‐to‐macroscopic DSC device prediction methodology existed. Thereby, a fully computational pipeline is presented that predicts device‐performance parameters of DSCs which contain varying dye combinations. Optimal pairing of complementary dyes is identified via a data‐driven workflow that affords cosensitized DSCs with maximum power‐conversion efficiencies. Six high‐performing DSC dyes are paired with partner dyes that are screened from a database of 8488 compounds using sequential heuristic filters. Existing models that predict short‐circuit‐current density ( J SC ) and open‐circuit voltage ( V OC ) parameters are adapted to predict singly sensitized and cosensitized DSC performance. The predictions for J sc values of singly sensitized devices match experimental literature values with comparable accuracy to more computationally costly methods. Five out of six dye pairings are predicted to have greater J SC values when cosensitized compared to their corresponding singly sensitized devices, including two pairs that show strong J sc boosts of +13% and +12% when cosensitized. Thus, the prospect of an entirely in‐silico prediction pipeline for DSC performance that can be used to realize the fully automated design of optimized cosensitized DSCs is demonstrated.

14 SOLAR ENERGY↗

DOE OSTI2014

TRAJECTORY SENSITIVITY ANALYSIS FOR DYNAMIC SECURITY ASSESSMENT AND OTHER APPLICATIONS IN POWER SYSTEMS

Real time stability evaluation and preventive scheduling in power systems offer many challenges in a stressed power system. Trajectory sensitivity analysis (TSA) is a useful tool for this and other applications in the emerging smart grid area. In this chapter we outline the basic approach of TSA, to extract suitable information from the data and develop reliable metrics or indices to evaluate proximity of the system to an unstable condition. Trajectory sensitivities can be used to compute critical parameters such as clearing time of circuit breakers, tie line flow, etc. in a power system by developing suitable norms for ease of interpretation. The TSA technique has the advantage that model complexity is not a limitation, and the sensitivities can be computed numerically. Suitable metrics are developed from these sensitivities. The TSA technique can be extended to do preventive rescheduling. A brief discussion of other applications of TSA in placement of distributed generation is indicated.

critical parameter computation↗

DOE OSTI2019

Highly sensitive SPR PCF biosensors based on Ag/TiN and Ag/ZrN configurations

We numerically present and analyze a surface plasmon resonance (SPR) bimetallic photonic crystal fiber (PCF) biosensor using full vectorial finite element method. The bimetallic configuration is based on Silver and (TiN or ZrN) as alternative plasmonic materials. The reported design relies on PCF with an external channel to house the analyte. The inner surface of the channel is coated by a silver layer followed by TiN or ZrN to protect the silver layer from oxidation. The proposed biosensor can be implemented to detect the unknown analytes, organic chemicals, biological analytes, and biomolecules via the sensitive resonant peaks to the analyte refractive index variations for both polarized modes with high linearity. In this study, a comparison is made between the Ag/TiN configuration and the Ag/ZrN counterpart in terms of sensitivity, losses, and linearity. The geometrical parameters are optimized to achieve high refractive index sensitivities of 7000 nm/RIU for quasi-transverse electric (TE) mode and 6900 nm/RIU for quasi-transverse magnetic (TM) mode, respectively for the Ag/TiN configuration. However, the quasi TE and quasi TM modes achieve high sensitivity of 5300 and 5400 nm/RIU, respectively using the Ag/ZrN configuration. The standard PCF fabrication technologies can be used to fabricate the proposed SPR PCF biosensors.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Notch Sensitivity and Failure Behavior of TiAl and K418 Alloys

The notch sensitivity of tensile specimens of TiAl and K418 alloys has been investigated, and the notch strength has been quantitatively analyzed. The fracture surface of the specimens has also been observed and analyzed by scanning electron microscopy (JEOL-6700F). By comparing notch rod tensile specimens and special notch rod tensile specimens, it was found that the basic nature, fracture driving force, and fracture criteria of the brittle TiAl alloy and the ductile K418 alloy are different. The final fracture of the K418 alloy is controlled by strain and not by stress, and the specimens do not exhibit notch sensitivity. However, the final fracture of the TiAl alloy is controlled by stress, and the specimens exhibit small notch sensitivity. For the special notch rod tensile specimens, the K418 specimens do not exhibit notch sensitivity. However, for the TiAl alloy, when the notch depth reaches 10% of the specimen diameter, the tensile strength decreases, and when the notch depth reaches 20% of the specimen diameters, the tensile strength sharply decreases.

36 MATERIALS SCIENCE↗

DOE OSTI2024

On the Strain Rate Sensitivity Measured by Nanoindentation at High Strain Rates

The flow stress of a material can be strongly dependent on the rate of applied strain. Measuring the strain rate sensitivity can reveal key insights into the mechanisms that drive plastic deformation. Indentation techniques have been developed to measure the strain rate sensitivity at quasistatic strain rates, but accessing higher strain rate regimes has been saddled with experimental and technical challenges. With state-of-the-art indentation instrumentation now capable of recording load and displacement at data acquisition rates in excess of 1.25 MHz, we report how strain rate sensitivity testing methodologies, especially those aimed for higher indentation strain rates, may be validated using the well-studied time-dependent deformation behavior of tungsten. Here, the strain rate sensitivity for a (110) single crystal is shown to be consistent (m = 0.023 at 2 µm depth) across all tested strain rates and methods ranging from 10 -2 - 10 4 1/s.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Uncertainty quantification and sensitivity analysis with CASL Core Simulator VERA-CS

Uncertainty quantification and sensitivity analysis are important for nuclear reactor safety design and analysis. A 2x2 fuel assembly core design was developed and simulated by the Virtual Environment for Reactor Applications, Core Simulator (VERA-CS) coupled neutronics and thermal-hydraulics code under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). An approach to uncertainty quantification and sensitivity analysis with VERA-CS was developed and a new toolkit was created to perform uncertainty quantification and sensitivity analysis with fourteen uncertain input parameters. Furthermore, the minimum departure from nucleate boiling ratio (MDNBR), maximum fuel center-line temperature, and maximum outer clad surface temperature were chosen as the selected figures of merit. Pearson, Spearman, and partial correlation coefficients were considered for all of the figures of merit in sensitivity analysis and coolant inlet temperature was consistently the most influential parameter. We used parameters as inputs to the critical heat flux calculation with the W-3 correlation were shown to be the most influential on the MDNBR, maximum fuel center-line temperature, and maximum outer clad surface temperature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗