Calibration of Elastoplastic Constitutive Model Parameters from Full-Field Data with Automatic Differentiation-based Sensitivities.
Abstract not provided.
Seidl, Daniel↗
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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.
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IRAS observations of the Rho Ophiuchi infrared cluster - Spectral energy distributions and luminosity function
High-sensitivity IRAS coadded survey data, coupled with new high-sensitivity near-IR observations, are used to investigate the nature of embedded objects over an 4.3-sq-pc area comprising the central star-forming cloud of the Ophiuchi molecular complex; the area encompasses the central cloud of the Rho Ophiuchi complex and includes the core region. Seventy-eight members of the embedded cluster were identified; spectral energy distributions were constructed for 53 objects and were compared with theoretical models to gain insight into their evolutionary status. Bolometric luminosities could be estimated for nearly all of the association members, leading to a revised luminosity function for this dust-embedded cluster.
Wilking, Bruce A.↗
Infrared satellite-derived sea surface skin temperature sensitivity to aerosol vertical distribution ̶ Field data analysis and model simulations
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Bingkun Luo↗
SPND Sensitivity Calculations Using MCNP and Experimental Data from ACRR.
Abstract not provided.
King, Joseph↗
Sensitivity Tool Needs for Modern Nuclear Data Validation
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Rising, Michael Evan↗
Evaluation of thermal data for geologic applications
Sensitivity studies using thermal models indicated sources of errors in the determination of thermal inertia from HCMM data. Apparent thermal inertia, with only simple atmospheric radiance corrections to the measured surface temperature, would be sufficient for most operational requirements for surface thermal inertia. Thermal data does have additional information about the nature of surface material that is not available in visible and near infrared reflectance data. Color composites of daytime temperature, nighttime temperature, and albedo were often more useful than thermal inertia images alone for discrimination of lithologic boundaries. A modeling study, using the annual heating cycle, indicated the feasibility of looking for geologic features buried under as much as a meter of alluvial material. The spatial resolution of HCMM data is a major limiting factor in the usefulness of the data for geologic applications. Future thermal infrared satellite sensors should provide spatial resolution comparable to that of the LANDSAT data.
Kahle, A. B.↗
Application-driven Privacy-preserving Data Publishing with Correlated Attributes
Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN that offers privacy-preserving mechanism using generative adversarial networks. Given a target application, PR-GAN automatically modifies the data to hide sensitive attributes - which may be hidden and can be inferred by machine learning algorithms - while preserving the data utility in the target application. Unlike prior works, the public's possible knowledge of the correlation between the target application and sensitive attributes is built into our modeling. We formulate our problem as an optimization problem, show that an optimal solution exists and use generative adversarial networks (GAN) to create perturbations. We further show that our method provides privacy guarantees under the Pufferfish framework, an elegant generalization of the differential privacy that allows for the modeling of prior knowledge on data and correlations. Through experiments, we show that our method outperforms conventional methods in effectively hiding the sensitive attributes while guaranteeing high performance in the target application, for both property inference and training purposes. Finally, we demonstrate through further experiments that once our model learns a privacy-preserving task, such as hiding subjects' identity, on a group of individuals, it can perform the same task on a separate group with minimal performance drops.
97 MATHEMATICS AND COMPUTING↗
Sensitivity Analysis for the Component Design App: Analysis of Success Assured Data
A new tool has been developed to perform variance-based global sensitivity analysis (VBGSA) on data from a set-based concurrent engineering software called Success Assured (SA). The tool is part of a digital component design app, which is currently in production as an Accelerated Digital Engineering Pathfinder at Sandia National Laboratories. When working with complex digital models, it is important to understand relationships between inputs and outputs, i.e., how “sensitive” model outputs are to changes in model inputs. After extensive research and trials of various sensitivity analysis methods, it was determined that estimation of Sobol’ indices for VBGSA with Monte Carlo simulation, paired with simple surrogate models, produces the best results for SA data. This tool increases understanding of SA models and streamlines the creation of SA datasets. This report details the methodology and implementation of this sensitivity analysis tool so others can understand it and implement it.
97 MATHEMATICS AND COMPUTING↗
Sea ice-atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates
The application of multi-spectral satellite data to estimate polar surface energy fluxes is addressed. To what accuracy and over which geographic areas large scale energy budgets can be estimated are investigated based upon a combination of available remote sensing and climatological data sets. The general approach was to: (1) formulate parameterization schemes for the appropriate sea ice energy budget terms based upon the remotely sensed and/or in-situ data sets; (2) conduct sensitivity analyses using as input both natural variability (observed data in regional case studies) and theoretical variability based upon energy flux model concepts; (3) assess the applicability of these parameterization schemes to both regional and basin wide energy balance estimates using remote sensing data sets; and (4) assemble multi-spectral, multi-sensor data sets for at least two regions of the Arctic Basin and possibly one region of the Antarctic. The type of data needed for a basin-wide assessment is described and the temporal coverage of these data sets are determined by data availability and need as defined by parameterization scheme. The titles of the subjects are as follows: (1) Heat flux calculations from SSM/I and LANDSAT data in the Bering Sea; (2) Energy flux estimation using passive microwave data; (3) Fetch and stability sensitivity estimates of turbulent heat flux; and (4) Surface temperature algorithm.
Steffen, K.↗
Measurement of Local Differential Privacy Techniques for IoT-based Streaming Data
Various Internet of Things (IoT) devices generate complex, dynamically changed, and infinite data streams. Adversaries can cause harm if they can access the user’s sensitive raw streaming data. For this reason, protecting the privacy of the data streams is crucial. In this paper, we explore local differential privacy techniques for streaming data. We compare the techniques and report the advantages and limitations. We also present the effect on component (e.g., smoother, perturber) variations of distribution-based local differential privacy. We find that combining distribution-based noise during perturbation provides more flexibility to the interested entity.
Afrose, Sharmin↗
Constraints on mantle viscosity from relative sea level variations in Hudson Bay
Frechet kernels for the RSL data in Hunson Bay are computed to determine the detailed depth-dependent sensitivity of the data to variations in a viscosity profile which is consistent with the past inferences. The RSL data provide a robust constraint on the average viscosity in the top half of the lower mantle only (the average must be near 10 exp 21 Pa s). The data admit models whose average viscosity in the deep mantle (below 1800 km depth) and in the upper mantle can differ significantly from the value (near 10 exp 21 Pa s) estimated for the top half of the lower mantle. The total variation in the viscosity from the surface to the CMB can exceed an order of magnitude or more and still satisfy the constraint provided by the Hudson Bay RSL data set. The necessity of invoking an isoviscous mantle model in previous studies is a consequence of the limited class of viscosity model solutions employed in those studies.
Mitrovica, J. X.↗
The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040
Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.
Vision 2040↗
Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters [Slides]
Sensitivity coefficients of prompt neutron decay constant (α) and effective delayed neutron fraction (β eff ) to Pu-239 nuclear data were calculated using a newly available tool (ACEtk). Uncertainty calculations showed the following trends: (1) The prompt neutron decay constant can be used to reduce nuclear data-induced uncertainty in Pu-239(n,f) and (2) the effective delayed neutron fraction can be used to effectively reduce nuclear data-induced uncertainty in Pu-239 total fission $\tilde{v}$. Sensitivity/uncertainty analysis can be used to determine optimal experiment/detector setup to identify compensating errors in nuclear data. Upcoming work includes investigating other nuclide-reaction pairs and response sensitivities, such as Δ$\rho$, neutron leakage spectra, and reaction rate measurements to constrain nuclear data of interest.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
(U) Average Scattering Angle Cosine Sensitivities
The Evaluated Nuclear Data File (ENDF) provides covariances of the average scattering angle cosine $\overline{μ}$ for 117 nuclides, and the NJOY nuclear data processing code can process these covariances. To propagate them to the uncertainty of a response due to uncertainties in $\overline{μ}$ requires sensitivities of the response with respect to $\overline{μ}$. This report uses NJOY’s definition of $\overline{μ}$ and derives a relationship between the sensitivity of a response to $\overline{μ}$ and the sensitivity of the response to the anisotropic P 1 elastic scattering cross section. This relationship has been implemented in the multigroup neutron sensitivity code SENSMG, which relies on the discrete ordinates code PARTISN for the neutron transport calculations. Kodeli has also calculated sensitivities with respect to $\overline{μ}$ and associated uncertainties. However, the formal derivation of this paper shows that the definition of the sensitivity with respect to $\overline{μ}$ is ambiguous because there are multiple ways to change $\overline{μ}$ by changing scattering cross sections. Here we derive two such ways. Both are implemented in SENSMG. This report is organized as follows. Section II discusses $\overline{μ}$ and its significance. Section III presents the equations used for the sensitivity of a response with respect to $\overline{μ}$, and Section IV discusses how to compute these sensitivities with SENSMG and MCNP6.3. Section V is a fast-spectrum test problem, and Sec. VI is a thermal-spectrum problem. Section VII is a summary. The example problem inputs are listed in the appendix.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Criteria for site selection and frequency allocation (keynote paper), part 5
Technical aspects of mesosphere-stratosphere-troposphere (MST) Radar on site and frequency selection were discussed. Recommendations on site selections are presented. Tests of interference will be conducted before selecting a site. A small directional antenna may be suitable to simulate sidelobe sensitivity of radars however, sophisticated data-processing methods make system sensitivity extremely good. The use of the complete data system to look for interference is recommended. There is the difficulty of allocation of frequencies -- almost continuous use by these radars will be made when the band 40 to 60 MHz is allocated to other services.
Rottger, J.↗
Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities
Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Variational assimilation of VAS data into a mesoscale model Assimilation method and sensitivity experiments
The assimilation of temperature and moisture gradient information from the Visible IR Spin-Scan Radiometer's Atmospheric Sounder (VAS) into a mesoscale model is presently undertaken by means of a variational method and followed by tests of the sensitivity of both diabatic and adiabatic versions of the model to VAS data assimilations for the case of July 20-21, 1981. The synoptic scale effects of the assimilation of VAS data are noted to be negligible; the greatest impact was instead on mesoscale forecasts of convective instability patterns. The additional assimilation of relative humidity gradients did not significantly change the patterns of the forecast instabilities. The greatest improvements from assimilation resulted from the resolution of the strong mesoscale temperature gradients by the asynoptic VAS data.
Cram, J. M.↗
Polar motion results from GEOS 3 laser ranging
The observability of polar motion from laser range data has been investigated, and the contributions from the dynamical and kinematical effects have been evaluated. Using 2-day arcs with GEOS 3 laser data, simultaneous solutions for pole position components and orbit elements have been obtained for a 2-week interval spanning August 27 to September 10, 1975, using three NASA Goddard Space Flight Center stations located at Washington, D.C., Bermuda, and Grand Turk. The results for the y-component of pole position from this limited data set differenced with the BIH linearly interpolated values yield a mean of 39 cm and a standard deviation of 1.07 m. Consideration of the variance associated with each estimate yields a mean of 20 cm and a standard deviation of 81 cm. The results for the x-component of pole position indicate that the mean value is in fair agreement with the BIH; however, the x-coordinate determination is weaker than the y-coordinate determination due to the distribution of laser sites (all three are between 77 deg W and 65 deg W) which results in greater sensitivity to the data distribution. In addition, the sensitivity of these results to various model parameters is discussed.
Schutz, B. E.↗