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At least 1,657 records · Page 92

Estimating Uncertainties in the Multi-Instrument SBUV Profile Ozone Merged Data Set

The MOD data set is uniquely qualified for use in long-term ozone analysis because of its long record, high spatial coverage, and consistent instrument design and algorithm. The estimated MOD uncertainty term significantly increases the uncertainty over the statistical error alone. Trends in the post-2000 period are generally positive in the upper stratosphere, but only significant at 1-1.6 hPa. Remaining uncertainties not yet included in the Monte Carlo model are Smoothing Error ( 1 from 10 to 1 hPa) Relative calibration uncertainty between N11 and N17Seasonal cycle differences between SBUV records.

Uncertainties↗

Efficient method for estimating the time evolution of the proto-neutron star mass and radius from a supernova neutrino signal

In this paper, we present a novel method to estimate the time evolution of the proto-neutron star (PNS) structure from the neutrino signal in a core-collapse supernova (CCSN). Employing recent results from multidimensional CCSN simulations, we delve into a relation between the total emitted neutrino energy (TONE) and PNS mass/radius, and we find that they are strongly correlated with each other. We fit the relation by simple polynomial functions connecting the TONE to the mass and radius of the PNS as a function of time. By combining another fitting function representing the correlation between the TONE and the cumulative number of events at each neutrino observatory, the PNS mass and radius can be retrieved from purely observed neutrino data. We demonstrate retrievals of PNS mass and radius from mock data of the neutrino signal, and we assess the capability of our proposed method. While underlining the limitations of the method, we also discuss the importance of the joint analysis with the gravitational wave signal. This would reduce uncertainties of parameter estimations in our method, and may narrow down the possible neutrino oscillation model. The proposed method is a very easy and inexpensive computation, which will be useful in real data analysis of the CCSN neutrino signal.

79 ASTRONOMY AND ASTROPHYSICS↗

Null Space Monte Carlo Evaluation of the Plateau to River Model

The Plateau to River Groundwater Model (P2R Model) is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by CH2M HILL Plateau Remediation Company at the Hanford Site in Washington State. Figure 1-1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model provides a computational framework to simulate the F&T of contaminants in groundwater associated with the 200-PO-1, 200-UP-1, 200-BP-5, and 200-ZP-1 Groundwater Operable Units (OUs) in the Hanford Site Central Plateau. In addition, the model includes adjacent areas and facilities (e.g., the State Approved Land Disposal Site). Intended and anticipated uses of the model include calculating water levels, hydraulic gradients, and groundwater flows throughout the model domain (encompassing the 200 West and 200 East Areas) for use in subsequent F&T calculations for contaminants of concern and developing scale-appropriate, telescopic-mesh refinement models for detailed evaluation of areas within the model domain where required. The overall objective of the modeling effort is to provide a basis for making informed remedial action decisions based on descriptions of current and expected future contaminant concentrations in groundwater at decision points within the OU boundaries. The objective for the model development phase is to create a common modeling platform that can be used for investigations of the Central Plateau groundwater OUs and areas downgradient toward the Columbia River. The P2R Model calibration to historical data observed at the Hanford Site is documented in CP-57037, Model Package Report for the Plateau to River Model Version 8.3. The purpose of this environmental calculation is to describe a null space Monte Carlo (NSMC) evaluation was conducted with the historic calibration of the P2R model. Use of numerical groundwater models is always accompanied with uncertainty in the results produced by a model because models are approximations of reality. Thus, by definition, lack the detail to fully represent observed behavior. Use of numerical techniques, such as a NSMC analysis, can help in identifying and quantifying the potential uncertainties associated with a numerical model such as the P2R Model. Use of the NSMC approach results in 100 groundwater flow models that are variants of the calibrated P2R Model. These variant models can be used to evaluate uncertainty in model predictions made by the calibrated P2R Model for other analyses. A secondary purpose of the environmental calculation is to establish these variant models for use with other applications.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Non-Technical Barriers to Geothermal Development in California and Nevada

Geothermal project development in the United States may be subject to numerous permits, authorizations, and other regulatory requirements at the federal, state, and local level, which are necessary to address potential environmental and resource impacts at geothermal project sites. This report presents the findings of our study, including an analysis of federal, state, and local geothermal regulatory and permitting processes, case studies analyzing site-specific attributes that may impact project development at four selected geothermal project sites, an analysis of cost and timeline implications for geothermal project development, and the results of a qualitative study focused on inter-agency coordination and collaboration efforts between federal, state, and/or local agencies for geothermal projects located in California and Nevada. Our analysis found that development timelines may be impacted by multiple federal and state environmental review processes and duplicative permitting requirements as well as coordination efforts between numerous federal, state, and local agencies involved in issuing authorizations and permits necessary for project development. In addition, projects in California and Nevada may face site-specific environmental challenges due to the presence of sensitive resources (e.g., biological species and species habitat, cultural resources) that may result in project construction delays. Our study results also indicate that protracted geothermal development timelines caused by delays in acquiring necessary permits and environmental reviews may result in loss of generated electricity revenue and additional financing costs, which may increase economic uncertainty associated with project development. Through our qualitative analysis, we found that utilization of best practices, including tiering to existing environmental review documents and developing memoranda of understanding, which clearly delineate agency roles and responsibilities may reduce overall project timelines, costs, and uncertainties associated with geothermal project development in California and Nevada.

15 GEOTHERMAL ENERGY↗

Non-Technical Barriers to Geothermal Development in California and Nevada [Slides]

This presentation presents the findings of our study, including an analysis of federal, state, and local geothermal regulatory and permitting processes, case studies analyzing site-specific attributes that may impact project development at four selected geothermal project sites, an analysis of cost and timeline implications for geothermal project development, and the results of a qualitative study focused on inter-agency coordination and collaboration efforts between federal, state, and/or local agencies for geothermal projects located in California and Nevada. Our analysis found that development timelines may be impacted by multiple federal and state environmental review processes and duplicative permitting requirements as well as coordination efforts between numerous federal, state, and local agencies involved in issuing authorizations and permits necessary for project development. In addition, projects in California and Nevada may face site-specific environmental challenges due to the presence of sensitive resources (e.g., biological species and species habitat, cultural resources) that may result in project construction delays. Our study results also indicate that protracted geothermal development timelines caused by delays in acquiring necessary permits and environmental reviews may result in loss of generated electricity revenue and additional financing costs, which may increase economic uncertainty associated with project development. Through our qualitative analysis, we found that utilization of best practices, including tiering to existing environmental review documents and developing memoranda of understanding, which clearly delineate agency roles and responsibilities may reduce overall project timelines, costs, and uncertainties associated with geothermal project development in California and Nevada.

15 GEOTHERMAL ENERGY↗

Valuation of Wind Energy Turbines Using Volatility of Wind and Price

The limitedness of the nonrenewable local energy resources in Israel, even in the background of the later gas fields’ findings, continues to force the state to devote various efforts towards ‘green’ energy development. These efforts include installations, both for the solar and for wind energy, thus improving the diversity of energy sources. While the standard discounted cash flow (DCF) method using the net present value (NPV) criterion is extensively adopted to evaluate investments, the standard DCF method is inappropriate for the rapidly changing investment climate and for the managerial flexibility in investment decisions. In recent years, the real options analysis (ROA) technique has been widely applied in many studies for the valuation of renewable energy investment projects. Taking into account the above background, we apply, in this study, the real options analysis approach for the valuation of wind energy turbines and apply it to the analysis of wind energy economic potential in Israel, which is the context of our work. We hypothesize that due to nature of wind energy production uncertainties, the ROA method is better than the alternative. The novelty of this paper includes the following: real world wind statistics of the Merom Golan site in Israel (velocity 3.73 m/s, with a standard deviation of 2.03 m/s), a realistic power generation estimation (power generation of 1205.84 kW with a standard deviation of about 0.5% in annual value which is worth about 1.3 M$ per annum), and an economic model to evaluate the profitability of such a project. We thus discuss the existing challenges of diversifying renewable energy sources in Israel by adding wind installations. Our motivation is to introduce a method which will allow investors and officials to take into account uncertainties when deciding in investing in such wind installations. The outcomes of the paper, which are obtained using the method of Weibull statistics and the Black–Scholes ROA technique, include the result that market price volatility adds to the uncertainties much more than any wind fluctuations, provided that the analysis is integrated over a long enough time.

17 WIND ENERGY↗

Improving air leakage prediction of buildings using the fan pressurization method with the Weighted Line of Organic Correlation

In many countries, the fan pressurization method is the most frequently chosen approach for measuring the air leakage of houses. The measurements are usually performed at pressures that far exceed pressures to which buildings are exposed to under normal conditions. A fit of these tests to the power-law formulation allows an extrapolation to data points outside the measured pressure range. With the Ordinary Least Square (OLS) fitting method, the pressure exponent and flow coefficient can be determined. However, the measurement results are highly sensitive to uncertainties induced by external factors like changing wind conditions during the tests, which is neglected by OLS. This may lead to errors in the prediction of flows at lower pressures. The Weighted Line of Organic Correlation (WLOC) is an alternative approach and takes measurement uncertainty into account. In this paper, a statistical analysis of an extensive data set of pressurization measurements has been performed. Both regression techniques have been compared for almost 7500 fan pressurization measurements of six houses in 109 different house leak configurations. The variability in predicting pressure exponent and flow coefficient for both WLOC and OLS regression was analyzed using probability density functions. It was found that the Weighted Line of Organic Correlation significantly decreases the uncertainty in predicting pressure exponent, flow coefficient, and other low-pressure air leakage metrics compared to the Ordinary Least Square fitting. Here, the authors highly recommend the implementation of WLOC in current measurement standards and test equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Recent developments of the NESSUS probabilistic structural analysis computer program

The NESSUS probabilistic structural analysis computer program combines state-of-the-art probabilistic algorithms with general purpose structural analysis methods to compute the probabilistic response and the reliability of engineering structures. Uncertainty in loading, material properties, geometry, boundary conditions and initial conditions can be simulated. The structural analysis methods include nonlinear finite element and boundary element methods. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. The scope of the code has recently been expanded to include probabilistic life and fatigue prediction of structures in terms of component and system reliability and risk analysis of structures considering cost of failure. The code is currently being extended to structural reliability considering progressive crack propagation. Several examples are presented to demonstrate the new capabilities.

Millwater, H.↗

Measurement of Electron Neutrino and Antineutrino Appearance with the NO{$\nu$}A Experiment

As a long-baseline neutrino oscillation experiment, the NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment aims at studying neutrino physics by measuring neutrino oscillation parameters using the neutrino flux from the Main Injector (NuMI) beam. It has two functionally identical detectors. The near detector is onsite at Fermi National Accelerator Laboratory. The far detector is 810 km away from the source of neutrinos and antineutrinos, at Ash River, Minnesota. At the near detector, muon neutrinos or antineutrinos, before significant oscillations take place, are used to correct the Monte Carlo simulation. At the far detector, the neutrino and antineutrino fluxes after significant oscillations have happened are measured and analyzed to study neutrino oscillation. The NOvA experiment is sensitive to the values of $\sin^2{\theta_{23}}$, $\Delta m^2_{32}$, and $\delta_{CP}$. The latest values from the NOvA 2020 analysis are as follows: $\sin^2{\theta_{23}}= 0.57^{+0.03}_{-0.04}$, $\Delta m^2_{32} = (2.41 \pm 0.07)\times 10^{-3}$\,eV$^2/c^4$, and $\delta_{CP}=0.82\pi$ with a wide 1$\sigma$ interval of uncertainty. My study is focused on the neutrino oscillation analysis with NOvA, including detector light model tuning, particle classification with convolutional neural network, electron neutrino and antineutrino energy reconstruction, and oscillation background estimation. Most of my studies have been used in the latest NOvA publication and the NOvA 2020 analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A framework for quantitative analysis of spectral data in two channels

Simultaneous acquisition of emission intensity from two channels in dual-color fluorescence measurements can be used to determine the spectral properties of an emitter. We detail a method to extract quantitative information from dual-color measurements by considering two models: a single spectral component model for peak wavelength determination and a dual spectral component model for relative strength determination. The former model is useful for spectral characterization and establishing heterogeneity within an emitter species, while the latter model is useful for analyzing energy transfer efficiency. Both models are formalized to yield probability distributions that reflect uncertainties due to shot noise. We applied these analysis tools to single-particle measurements of CdSe/CdS quantum dots. Isolated emitters had narrow spectral-intensity distributions that reflected their static emission profiles and fluorescence stability. Small assemblies of mixed donor/acceptor particles exhibited dynamic behavior where emission configuration changes reveal different spectral characteristics due to energy transfer.

36 MATERIALS SCIENCE↗

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks [Slides]

This presentation discusses Nuclear Criticality Safety (NCS) and how designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear experiments. The presentation poses the question of how this analysis can be performed and states that the answer lies in matching new nuclear experiments with existing benchmark experiments using similarity metrics. By increasing the criticality safety of the application in this work, higher mass limits could be used in PF-4 operations. Additionally, the presentation discusses MCNP6.2®, Whisper-1.1, the software that can be used in this analysis. Also discussed is the fact that International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks rarely match new nuclear applications and that there are significant differences in given set of materials and/or geometry. If there are no benchmarks that match the application, the presentation discusses the possibility of creating new benchmarks. In conclusion, this work presents a Gaussian process (GP) optimization scheme that was used to generate new benchmarks with the highest sensitivity-based similarity metrics to user-defined nuclear applications. The Gaussian process optimization successfully designed 3 new experimental benchmarks that were highly correlated to the application of interest and had k eff values near critical. Optimization over c k,i-r has shown that investigating specific isotope reactions for different applications is crucial to designing benchmark experiments. Partial contribution from Pu dominates c k similarity metric. Future work includes testing new stand-alone similarity metrics or new combinations of similarity metrics as the design criterion of this optimization – design criterion is application dependent.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Error studies for ground tracking of synchronous satellites

The results of various sets of tracking error analysis studies of the ability of ground stations to determine the position and velocity of synchronous satellites are summarized. The effects of varying: (1) the ground station configuration from 1 to 6 tracking stations in differing locations; (2) the ground station measurement type such as S-Band, C-Band, VHF, and lasers and (3) the uncertainties in ground station location are investigated. The linear error analysis computer program used includes the effects of ground tracking station location uncertainties, measurement noise and biases, and station timing bias. Results show that two ground trackers are needed if at least 2000 meters position accuracy is desired, with a favorable two-station solution giving less than 500 meters position accuracy. Under favorable circumstances, a multi-station laser solution gives a synchronous satellite position accuracy of less than 100 meters. The various cases illustrate features of synchronous satellite tracking from ground stations.

Cooley, J. L.↗

The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support

Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society.

54 ENVIRONMENTAL SCIENCES↗

Wavefront-Error Performance Characterization for the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM) Science Instruments

The science instruments (SIs) comprising the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM) were tested in three cryogenic-vacuum test campaigns in the NASA Goddard Space Flight Center (GSFC)'s Space Environment Simulator (SES) test chamber. In this paper, we describe the results of optical wavefront-error performance characterization of the SIs. The wavefront error is determined using image-based wavefront sensing, and the primary data used by this process are focus sweeps, a series of images recorded by the instrument under test in its as-used configuration, in which the focal plane is systematically changed from one image to the next. High-precision determination of the wavefront error also requires several sources of secondary data, including 1) spectrum, apodization, and wavefront-error characterization of the optical ground-support equipment (OGSE) illumination module, called the OTE Simulator (OSIM), 2) F-number and pupil-distortion measurements made using a pseudo-nonredundant mask (PNRM), and 3) pupil geometry predictions as a function of SI and field point, which are complicated because of a tricontagon-shaped outer perimeter and small holes that appear in the exit pupil due to the way that different light sources are injected into the optical path by the OGSE. One set of wavefront-error tests, for the coronagraphic channel of the Near-Infrared Camera (NIRCam) Longwave instruments, was performed using data from transverse translation diversity sweeps instead of focus sweeps, in which a sub-aperture is translated and/or rotated across the exit pupil of the system. Several optical-performance requirements that were verified during this ISIM-level testing are levied on the uncertainties of various wavefront-error-related quantities rather than on the wavefront errors themselves. This paper also describes the methodology, based on Monte Carlo simulations of the wavefront-sensing analysis of focus-sweep data, used to establish the uncertainties of the wavefront-error maps.

image analysis↗

Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. Here this article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

42 ENGINEERING↗

The sensitivity to parametric variation in direct minimization techniques

Solutions of some objective analysis techniques are known to depend upon the subjective values of internal parameters. The change in the solution per change in the parameter is the sensitivity. Parameters with low sensitivity can be varied with large increments during preliminary searches for near-optimal parameter values. Only terms with high sensitivity must be thoroughly investigated once the parameters are determined to be close to optimal. Both absolute and relative sensitivities are discussed and a sensitivity-based definition of the solution uncertainty is proposed. The sensitivity of direct minimization analysis to parametric variation is evaluated using a set of 'response functions' that characterize different aspects of the solution. It is shown that solutions of direct minimization techniques have low absolute sensitivity. Two examples are used to illustrate the usefulness of the technique. Both involved measurements of air-sea quantities (e.g., wind stress and latent heat flux) from a variety of data sources using a direct minimization technique. The examples demonstrate that sensitivity analysis is capable of quantifying regional sensitivities as well as indicating the magnitude and relationship between the various parameters.

Meyers, S. D.↗

Estimating the Properties of Hard X-Ray Solar Flares by Constraining Model Parameters

We wish to better constrain the properties of solar flares by exploring how parameterized models of solar flares interact with uncertainty estimation methods. We compare four different methods of calculating uncertainty estimates in fitting parameterized models to Ramaty High Energy Solar Spectroscopic Imager X-ray spectra, considering only statistical sources of error. Three of the four methods are based on estimating the scale-size of the minimum in a hypersurface formed by the weighted sum of the squares of the differences between the model fit and the data as a function of the fit parameters, and are implemented as commonly practiced. The fourth method is also based on the difference between the data and the model, but instead uses Bayesian data analysis and Markov chain Monte Carlo (MCMC) techniques to calculate an uncertainty estimate. Two flare spectra are modeled: one from the Geostationary Operational Environmental Satellite X1.3 class flare of 2005 January 19, and the other from the X4.8 flare of 2002 July 23.We find that the four methods give approximately the same uncertainty estimates for the 2005 January 19 spectral fit parameters, but lead to very different uncertainty estimates for the 2002 July 23 spectral fit. This is because each method implements different analyses of the hypersurface, yielding method-dependent results that can differ greatly depending on the shape of the hypersurface. The hypersurface arising from the 2005 January 19 analysis is consistent with a normal distribution; therefore, the assumptions behind the three non- Bayesian uncertainty estimation methods are satisfied and similar estimates are found. The 2002 July 23 analysis shows that the hypersurface is not consistent with a normal distribution, indicating that the assumptions behind the three non-Bayesian uncertainty estimation methods are not satisfied, leading to differing estimates of the uncertainty. We find that the shape of the hypersurface is crucial in understanding the output from each uncertainty estimation technique, and that a crucial factor determining the shape of hypersurface is the location of the low-energy cutoff relative to energies where the thermal emission dominates. The Bayesian/MCMC approach also allows us to provide detailed information on probable values of the low-energy cutoff, Ec, a crucial parameter in defining the energy content of the flare-accelerated electrons. We show that for the 2002 July 23 flare data, there is a 95% probability that Ec lies below approximately 40 keV, and a 68% probability that it lies in the range 7-36 keV. Further, the low-energy cutoff is more likely to be in the range 25-35 keV than in any other 10 keV wide energy range. The low-energy cutoff for the 2005 January 19 flare is more tightly constrained to 107 +/- 4 keV with 68% probability.

X-rays↗

Wavefront-Error Performance Characterization for the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM) Science Instruments

The science instruments (SIs) comprising the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM) were tested in three cryogenic-vacuum test campaigns in the NASA Goddard Space Flight Center (GSFC)'s Space Environment Simulator (SES). In this paper, we describe the results of optical wavefront-error performance characterization of the SIs. The wavefront error is determined using image-based wavefront sensing (also known as phase retrieval), and the primary data used by this process are focus sweeps, a series of images recorded by the instrument under test in its as-used configuration, in which the focal plane is systematically changed from one image to the next. High-precision determination of the wavefront error also requires several sources of secondary data, including 1) spectrum, apodization, and wavefront-error characterization of the optical ground-support equipment (OGSE) illumination module, called the OTE Simulator (OSIM), 2) plate scale measurements made using a Pseudo-Nonredundant Mask (PNRM), and 3) pupil geometry predictions as a function of SI and field point, which are complicated because of a tricontagon-shaped outer perimeter and small holes that appear in the exit pupil due to the way that different light sources are injected into the optical path by the OGSE. One set of wavefront-error tests, for the coronagraphic channel of the Near-Infrared Camera (NIRCam) Longwave instruments, was performed using data from transverse translation diversity sweeps instead of focus sweeps, in which a sub-aperture is translated andor rotated across the exit pupil of the system.Several optical-performance requirements that were verified during this ISIM-level testing are levied on the uncertainties of various wavefront-error-related quantities rather than on the wavefront errors themselves. This paper also describes the methodology, based on Monte Carlo simulations of the wavefront-sensing analysis of focus-sweep data, used to establish the uncertainties of the wavefront error maps.

wavefront error↗