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DOE OSTI2015

STRONG LENS TIME DELAY CHALLENGE. I. EXPERIMENTAL DESIGN

The time delays between point-like images in gravitational lens systems can be used to measure cosmological parameters. The number of lenses with measured time delays is growing rapidly; the upcoming Large Synoptic Survey Telescope (LSST) will monitor ∼10{sup 3} strongly lensed quasars. In an effort to assess the present capabilities of the community, to accurately measure the time delays, and to provide input to dedicated monitoring campaigns and future LSST cosmology feasibility studies, we have invited the community to take part in a ''Time Delay Challenge'' (TDC). The challenge is organized as a set of ''ladders'', each containing a group of simulated data sets to be analyzed blindly by participating teams. Each rung on a ladder consists of a set of realistic mock observed lensed quasar light curves, with the rungs' data sets increasing in complexity and realism. The initial challenge described here has two ladders, TDC0 and TDC1. TDC0 has a small number of data sets, and is designed to be used as a practice set by the participating teams. The (non-mandatory) deadline for completion of TDC0 was the TDC1 launch date, 2013 December 1. The TDC1 deadline was 2014 July 1. Here we give an overview of the challenge, we introduce a set of metrics that will be used to quantify the goodness of fit, efficiency, precision, and accuracy of the algorithms, and we present the results of TDC0. Thirteen teams participated in TDC0 using 47 different methods. Seven of those teams qualified for TDC1, which is described in the companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1975

Simulator studies and psychophysical ride comfort models

An elementary psychophysical model to predict ride comfort was developed using flight and simulator data where subjects were exposed to six degrees of freedom. The model presumes that the comfort response is proportional to the logarithm of the stimulus above some threshold stimulus. In order to verify this concept of comfort modeling, it was necessary to obtain ride comfort data for single degree of freedom random motions and for combinations of random motions. Accordingly, a simulator program was performed at the NASA Langley Research Center to measure subjective comfort response ratings using one degree of freedom, two degrees of freedom, three degrees of freedom, and six degrees of freedom. An analysis of the single degree of freedom and two degrees of freedom data is presented. Preliminary models of ride comfort response for single degree of freedom random motions and for certain combinations of two degrees of freedom random motions were developed.

Stone, R. W., Jr.↗

DOE OSTI2022

Biomass sorghum production in Iowa, USA

This dataset includes field measurement and model simulation data from Josh Bendorf's (former MS student with Drs. VanLoocke & Heaton, ISU Dept. of Agronomy) thesis project focusing on the simulation of biomass sorghum ( Sorghum bicolor L. Moench) in the state of Iowa. Measured field data are provided in CSV file format for 2019 & 2020. Model output files are provided as NetCDF file format for the state of Iowa (1998-2007) & the larger US region (1969-2018).

Agricultural production systems simulation↗

DOE OSTI2020

Lorentz and CPT violation in partons

A framework is presented for the factorization of high-energy hadronic processes in the presence of Lorentz and CPT violation. The comprehensive effective field theory describing Lorentz and CPT violation, the Standard-Model Extension, is used to demonstrate factorization of the hadronic tensor at leading order in electroweak interactions for deep inelastic scattering and for the Drell-Yan process. Effects controlled by both minimal and nonminimal coefficients for Lorentz violation are explored, and the equivalent parton-model description is derived. The methodology is illustrated by determining cross sections and studying estimated attainable sensitivities to Lorentz violation using real data collected at the Hadronen-Elektronen Ring Anlage and the Large Hadron Collider and simulated data for the future US-based electron-ion collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2014

The SACADA database for human reliability and human performance

Lack of appropriate and sufficient human performance data has been identified as a key factor affecting human reliability analysis (HRA) quality especially in the estimation of human error probability (HEP). The Scenario Authoring, Characterization, and Debriefing Application (SACADA) database was developed by the U.S. Nuclear Regulatory Commission (NRC) to address this data need. An agreement between NRC and the South Texas Project Nuclear Operating Company (STPNOC) was established to support the SACADA development with aims to make the SACADA tool suitable for implementation in the nuclear power plants' operator training program to collect operator performance information. The collected data would support the STPNOC's operator training program and be shared with the NRC for improving HRA quality. This paper discusses the SACADA data taxonomy, the theoretical foundation, the prospective data to be generated from the SACADA raw data to inform human reliability and human performance, and the considerations on the use of simulator data for HRA. Each SACADA data point consists of two information segments: context and performance results. Context is a characterization of the performance challenges to task success. The performance results are the results of performing the task. The data taxonomy uses a macrocognitive functions model for the framework. At a high level, information is classified according to the macrocognitive functions of detecting the plant abnormality, understanding the abnormality, deciding the response plan, executing the response plan, and team related aspects (i.e., communication, teamwork, and supervision). The data are expected to be useful for analyzing the relations between context, error modes and error causes in human performance.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Causal network inference using biochemical kinetics

Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems. Results: We present a general framework for network inference and dynamical prediction using time course data that is rooted in nonlinear biochemical kinetics. This is achieved by considering a dynamical system based on a chemical reaction graph with associated kinetic parameters. Both the graph and kinetic parameters are treated as unknown; inference is carried out within a Bayesian framework. This allows prediction of dynamical behavior even when the underlying reaction graph itself is unknown or uncertain. Results, based on (i) data simulated from a mechanistic model of mitogen-activated protein kinase signaling and (ii) phosphoproteomic data from cancer cell lines, demonstrate that non-linear formulations can yield gains in causal network inference and permit dynamical prediction and uncertainty quantification in the challenging setting where the reaction graph is unknown. Availability and implementation: MATLAB R2014a software is available to download from warwick.ac.uk/chrisoates.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Nonperturbative Guiding Center Model for Magnetized Plasmas

Perturbative guiding center theory adequately describes the slow drift motion of charged particles in the strongly magnetized regime characteristic of thermal particle populations in various magnetic fusion devices. However, it breaks down for particles with large-enough energy. Here, we report on a data-driven method for learning a nonperturbative guiding center model from full-orbit particle simulation data. We show the data-driven model significantly outperforms traditional asymptotic theory in magnetization regimes appropriate for fusion-born α particles in stellarators, thus opening the door to nonperturbative guiding center calculations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1991

Software reliability report

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Unfortunately, the models appear to be unable to account for the random nature of the data. If the same code is debugged multiple times and one of the models is used to make predictions, intolerable variance is observed in the resulting reliability predictions. It is believed that data replication can remove this variance in lab type situations and that it is less than scientific to talk about validating a software reliability model without considering replication. It is also believed that data replication may prove to be cost effective in the real world, thus the research centered on verification of the need for replication and on methodologies for generating replicated data in a cost effective manner. The context of the debugging graph was pursued by simulation and experimentation. Simulation was done for the Basic model and the Log-Poisson model. Reasonable values of the parameters were assigned and used to generate simulated data which is then processed by the models in order to determine limitations on their accuracy. These experiments exploit the existing software and program specimens which are in AIR-LAB to measure the performance of reliability models.

Wilson, Larry↗

NASA NTRSDate not supplied

In-Tunnel Simulations of the NASA Juncture Flow Model

The effect of wind tunnel walls on the development of flow separation in the wing-fuselage juncture area is assessed using FUN3D’s overset and wind tunnel controller capabilities. The simulation data obtained from the in-tunnel runs are compared with the free-air simulations. The simulation results are also evaluated using measurements from the Juncture Flow Experiment.

Nash'at N. Ahmad↗

DOE OSTI2015

LEM-CF Premixed Tool Kit

The purpose of LEM-CF Premixed Tool Kit is to process premixed flame simulation data from the LEM-CF solver (https://fileshare.craft-tech.com/clusters/view/lem-cf) into a large-eddy simulation (LES) subgrid model database. These databases may be used with a user-defined-function (UDF) that is included in the Tool Kit. The subgrid model UDF may be used with the ANSYS FLUENT flow solver or other commercial flow solvers.

Source record↗

DOE OSTI2021

A Multi-Analysis Approach for Estimating Regional Health Impacts from the 2017 Northern California Wildfires

In the evening of October 8 and early hours of October 9, 2017, high winds in Northern California downed trees and power lines, igniting some of the most devastating wildfires the state had seen, and within hours unhealthy air quality impacted millions of people. We simulated these air quality conditions using fire detection information from the MODIS, VIIRS, and GOES-16 ABI satellite instruments, and applying a set of three WRF–CMAQ simulations, one data fusion, and three machine learning methods. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ air quality modeling system. Interestingly, this approach did not necessarily improve results compared to the baseline case, which used a default time profile. However, this approach was key to simulating the initial 12-hr explosive fire activity and smoke impacts. The WRF-CMAQ simulations compared well with observational data for the October 8-15 time period and tended to overestimate concentrations October 16-20. To improve these results, we applied three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across the WRF-CMAQ, data fusion, and machine learning datasets, the best Pearson correlation was 0.5. The data fusion and machine learning results were biased low and WRF-CMAQ results were biased high. Finally, we applied the optimized PM2.5 exposure estimate in a short-term exposure-response function. Total estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to wildland fire smoke.

O'Neill, Susan↗

NASA NTRS1983

Edge discrimination as applied to Thematic Mapper data

An evaluation of suitable edge discrimination techniques and their application to image segmentation is reported. From an analysis of Thematic Mapper Simulator data, it is concluded that segmentation by automated edge discrimination is a valuable technique which can be used in the development of per-field classifiers. A Laplacian convolution operator appears to be the most cost-effective high-pass filter. Spatial frequency domain filtering is more versatile in its ability to enhance different edge types. A simple global gray value threshold can produce good edge discrimination from an enhanced image which may be improved by using a local thresholding technique. A gap-fill postprocessing technique is necessary for useful segmentation. Gradient and other directionally dependent techniques are unsuitable for segmentation.

Hall, J. R.↗

DOE OSTI2016

The impact of non-uniform thermal structure on the interpretation of exoplanet emission spectra

The determination of atmospheric structure and molecular abundances of planetary atmospheres via spectroscopy involves direct comparisons between models and data. While varying in sophistication, most model spectra comparisons fundamentally assume one-dimensional (1D) model physics. However, knowledge from general circulation models and of solar system planets suggests that planetary atmospheres are inherently three-dimensional in their structure and composition. We explore the potential biases resulting from standard “1D” assumptions within a Bayesian atmospheric retrieval framework. Specifically, we show how the assumption of a single 1D thermal profile can bias our interpretation of the thermal emission spectrum of a hot Jupiter atmosphere that is composed of two thermal profiles. We retrieve spectra of unresolved model planets as observed with a combination of the Hubble Space Telescope Wide Field Camera 3 (WFC3)+Spitzer Infrared Array Camera (IRAC) as well as the James Webb Space Telescope (JWST) under varying differences in the two thermal profiles. For WFC3+IRAC, there is a significantly biased estimate of CH{sub 4} abundance using a 1D model when the contrast is 80%. For JWST, two thermal profiles are required to adequately interpret the data and estimate the abundances when contrast is greater than 40%. We also apply this preliminary concept to the recent WFC3+IRAC phase curve data of the hot Jupiter WASP-43b. We see similar behavior as present in our simulated data: while the H{sub 2}O abundance determination is robust, CH{sub 4} is artificially well-constrained to incorrect values under the 1D assumption. Our work demonstrates the need to evaluate model assumptions in order to extract meaningful constraints from atmospheric spectra and motivates exploration of optimal observational setups.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Frequency Nadir Constrained Unit Commitment for High Renewable Penetration Island Power Systems

The process of energy decarbonization in island power systems is accelerated due to the swift integration of inverter-based renewable energy resources (IBRs). The unique features of such systems, including rapid frequency changes resulting from potential generation outages or imbalances due to the unpredictability of renewable power, pose a significant challenge in maintaining the frequency nadir without external support. This paper presents a unit commitment (UC) model with data-driven frequency nadir constraints, including either frequency nadir or minimum inertia requirements, helping to limit frequency deviations after significant generator outages. The constraints are formulated using a linear regression model that takes advantage of real-world, year-long generation scheduling and dynamic simulation data. The efficacy of the proposed UC model is verified through a year-long simulation in an actual island power system using historical weather data. The alternative minimum inertia constraint, derived from actual system operation assumptions, is also evaluated. Findings demonstrate that the proposed frequency nadir constraint notably improves the system's frequency nadir under high photovoltaic (PV) penetration levels, albeit with a slight increase in generation costs, when compared to the alternative minimum inertia constraint.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Frequency-Nadir-Constrained Unit Commitment for Low-Inertia, High-IBR Island Power Systems [Slides]

14 SOLAR ENERGY↗

NASA NTRS2011

Soft-Decision-Data Reshuffle to Mitigate Pulsed Radio Frequency Interference Impact on Low-Density-Parity-Check Code Performance

This presentation briefly discusses a research effort on mitigation techniques of pulsed radio frequency interference (RFI) on a Low-Density-Parity-Check (LDPC) code. This problem is of considerable interest in the context of providing reliable communications to the space vehicle which might suffer severe degradation due to pulsed RFI sources such as large radars. The LDPC code is one of modern forward-error-correction (FEC) codes which have the decoding performance to approach the Shannon Limit. The LDPC code studied here is the AR4JA (2048, 1024) code recommended by the Consultative Committee for Space Data Systems (CCSDS) and it has been chosen for some spacecraft design. Even though this code is designed as a powerful FEC code in the additive white Gaussian noise channel, simulation data and test results show that the performance of this LDPC decoder is severely degraded when exposed to the pulsed RFI specified in the spacecraft s transponder specifications. An analysis work (through modeling and simulation) has been conducted to evaluate the impact of the pulsed RFI and a few implemental techniques have been investigated to mitigate the pulsed RFI impact by reshuffling the soft-decision-data available at the input of the LDPC decoder. The simulation results show that the LDPC decoding performance of codeword error rate (CWER) under pulsed RFI can be improved up to four orders of magnitude through a simple soft-decision-data reshuffle scheme. This study reveals that an error floor of LDPC decoding performance appears around CWER=1E-4 when the proposed technique is applied to mitigate the pulsed RFI impact. The mechanism causing this error floor remains unknown, further investigation is necessary.

Ni, Jianjun David↗