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DOE OSTI2024

Assessing and benchmarking the fidelity of posterior inference methods for astrophysics data analysis

In this era of large and complex astronomical survey data, interpreting, validating, and comparing inference techniques becomes increasingly difficult. This is particularly critical for emerging inference methods like Simulation-Based Inference (SBI), which offer significant speedup potential and posterior modeling flexibility, especially when deep learning is incorporated. We present a study to assess and compare the performance and uncertainty prediction capability of Bayesian inference algorithms – from traditional MCMC sampling of analytic functions to deep learning-enabled SBI. We focus on testing the capacity of hierarchical inference modeling in those scenarios. Before we extend this study to cosmology, we first use astrophysical simulation data to ensure interpretability. We demonstrate a probabilistic programming implementation of hierarchical and non-hierarchical Bayesian inference using simulations derived from the DeepBench software library, a benchmarking tool developed by our group that generates simple and controllable astrophysical objects from first principles. This study will enable astronomers and physicists to harness the inference potential of these methods with confidence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗

DOE OSTI2016

Evaluation of Deep Subsurface Resistivity Imaging for Hydrofracture Monitoring

This report describes the results of the first of its kind monitoring of a hydrofracture operation with electromagnetic measurements. The researchers teamed with oil and gas producer Encana Corporation to design and execute a borehole to surface monitoring of three fracture stages at a well pad in central Colorado. The field project consisted of an equipment upgrade, a survey design and modeling phase, several weeks of data collection, and data processing and interpretation. Existing Depth to Surface Resistivity (DSR) instrumentation was upgraded to allow for continuous high precision recording from downhole sources. The full system can now collect data continuously for up to 72 hours, which is sufficient to measure data for 10 frac stages. Next we used numerical modeling and frac treatment data supplied by Encana to design a field survey to detect EM signal from induced fractures. Prior to modeling we developed a novel technique for using well casing as an antenna for a downhole source. Modeling shows that 1) a measurable response for an induced fracture could be achieved if the facture fluid was of high salinity 2) an optimum fracture response is created when the primary source field is parallel to the well casing but perpendicular to the fracture direction. In mid-July, 2014 we installed an array of more than 100 surface sensors, distributed above the treatment wells and extending for approximately 1 km north and 750 m eastward. We applied a 0.6 Hz square wave signal to a downhole current electrode located in a horizontal well 200 m offset from the treatment well with a return electrode on the surface. The data were transmitted to a recording trailer via Wi-Fi where we monitored receiver and transmitter channels continuously in a 72-hour period which covered 7 frac stages, three of which were high salinity. Although the background conditions were very noisy we were able to extract a clear signal from the high salinity stages. Initial data interpretation attempts consisting of trying to directly invert collected data using a simple background starting model did not produce reasonable models. We next used a simulated data set to develop a constrained inversion workflow that places the downhole fracture in the correct location. Finally, we used a combination of forward and inverse models to fit the collected data to a model that incorporated 3 frac stages. This project provided a first-of-its-kind application of EM technology to map an induced fracture. The results demonstrated a clear anomaly during the operation that can be fit to a reasonable model of an induced fracture.

42 ENGINEERING↗

DOE OSTI2025

Data-Driven Method for Groundwater-Level Mapping and Monitoring-Well Network Optimization at Hanford

This report summarizes the initial results and outcomes of a physics-informed, data-driven groundwater level (GWL) mapping capability for the Hanford Site. GWL mapping at Hanford is typically conducted annually and requires a significant amount of computational and expert resources, and it does not allow assessment of the informational value of specific monitoring wells. The proposed method produces spatially and temporally resolved fields consistent with sparse, irregularly sampled, and nonuniformly distributed well measurements. Implemented successfully, this capability will allow rapid mapping of groundwater levels and provide an opportunity to optimize monitoring activities (both location and sampling frequency) based on data information value evaluation. The approach integrates a diffusion-based generative model – trained on MODFLOW simulation data from the Plateau-to-River (P2R) model – with score-based data assimilation (SDA), allowing observation-conditioned mapping without retraining for each monitoring-network layout.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1986

Quality indicators for trace gas concentrations determined from earthlimb emission spectra

Different techniques which can be used to indicate the quality of the mixing ratios retrieved from spectral radiance measurements made by the CLAES instrument for 11 different atmospheric gases are discussed. A key to retrieval from noisy data is the Singular Value Decomposition (SVD), which is described. The use of the SVD with simulated data and radiance measurements from a balloon floating at 30 km is discussed.

Uplinger, W. G.↗

NASA NTRS1989

Aerodynamic parameters of an advanced fighter aircraft estimated from flight data. Preliminary results

Preliminary estimates of aerodynamic parameters of an advanced fighter aircraft were obtained from flight data of different values of the angle of attack from 8 to 54 deg. The data were analyzed by a stepwise regression with the ordinary least squares technique. The estimated stability and control derivatives are plotted against the angle of attack and compared with wind tunnel measurement and previous flight results. Also included is the data compatibility check of measured data. The effect of various input forms on the estimates is demonstrated in two examples using simulated data.

Klein, Vladislav↗

NASA NTRS2008

Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results

Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.

Morelli, Eugene A.↗

NASA NTRS2010

Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results

Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors, prediction cases, and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.

Morelli, Eugene A.↗

NASA NTRS1990

Improved evaluation of optical depth components from Langley plot data

A simple, iterative procedure to determine the optical depth components of the extinction optical depth measured by a solar radiometer is presented. Simulated data show that the iterative procedure improves the determination of the exponent of a Junge law particle size distribution. The determination of the optical depth due to aerosol scattering is improved as compared to a method which uses only two points from the extinction data. The iterative method was used to determine spectral optical depth components for June 11-13, 1988 during the MAC III experiment.

Biggar, S. F.↗

NASA NTRS1989

Six-degree-of-freedom aircraft simulation with mixed-data structure using the applied dynamics simulation language, ADSIM

A realistic simulation of an aircraft in the flight using the AD 100 digital computer is presented. The implementation of three model features is specifically discussed: (1) a large aerodynamic data base (130,00 function values) which is evaluated using function interpolation to obtain the aerodynamic coefficients; (2) an option to trim the aircraft in longitudinal flight; and (3) a flight control system which includes a digital controller. Since the model includes a digital controller the simulation implements not only continuous time equations but also discrete time equations, thus the model has a mixed-data structure.

Savaglio, Clare↗

NASA NTRS2000

Identification of Low Order Equivalent System Models From Flight Test Data

Identification of low order equivalent system dynamic models from flight test data was studied. Inputs were pilot control deflections, and outputs were aircraft responses, so the models characterized the total aircraft response including bare airframe and flight control system. Theoretical investigations were conducted and related to results found in the literature. Low order equivalent system modeling techniques using output error and equation error parameter estimation in the frequency domain were developed and validated on simulation data. It was found that some common difficulties encountered in identifying closed loop low order equivalent system models from flight test data could be overcome using the developed techniques. Implications for data requirements and experiment design were discussed. The developed methods were demonstrated using realistic simulation cases, then applied to closed loop flight test data from the NASA F-18 High Alpha Research Vehicle.

Morelli, Eugene A.↗

DOE OSTI2013

Multiphysics Integrated Coupling Environment (MICE) User Manual

The complex, multi-part nature of waste glass melters used in nuclear waste vitrification poses significant modeling challenges. The focus of this project has been to couple a 1D MATLAB model of the cold cap region within a melter with a 3D STAR-CCM+ model of the melter itself. The Multiphysics Integrated Coupling Environment (MICE) has been developed to create a cohesive simulation of a waste glass melter that accurately represents the cold cap. The one-dimensional mathematical model of the cold cap uses material properties, axial heat, and mass fluxes to obtain a temperature profile for the cold cap, the region where feed-to-glass conversion occurs. The results from Matlab are used to update simulation data in the three-dimensional STAR-CCM+ model so that the cold cap is appropriately incorporated into the 3D simulation. The two processes are linked through ModelCenter integration software using time steps that are specified for each process. Data is to be exchanged circularly between the two models, as the inputs and outputs of each model depend on the other.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2012

Simulated Wake Characteristics Data for Closely Spaced Parallel Runway Operations Analysis

A simulation experiment was performed to generate and compile wake characteristics data relevant to the evaluation and feasibility analysis of closely spaced parallel runway (CSPR) operational concepts. While the experiment in this work is not tailored to any particular operational concept, the generated data applies to the broader class of CSPR concepts, where a trailing aircraft on a CSPR approach is required to stay ahead of the wake vortices generated by a lead aircraft on an adjacent CSPR. Data for wake age, circulation strength, and wake altitude change, at various lateral offset distances from the wake-generating lead aircraft approach path were compiled for a set of nine aircraft spanning the full range of FAA and ICAO wake classifications. A total of 54 scenarios were simulated to generate data related to key parameters that determine wake behavior. Of particular interest are wake age characteristics that can be used to evaluate both time- and distance- based in-trail separation concepts for all aircraft wake-class combinations. A simple first-order difference model was developed to enable the computation of wake parameter estimates for aircraft models having weight, wingspan and speed characteristics similar to those of the nine aircraft modeled in this work.

Guerreiro, Nelson M.↗

DOE OSTI2021

Coupling particle scale model and SuperDEM–CFD for multiscale simulation of biomass pyrolysis in a packed bed pyrolyzer

An efficient biomass pyrolysis process requires a comprehensive understanding of the chemical and physical phenomena that occur at multi-length and time scales. In this study, a multiscale computational approach was developed and validated for biomass pyrolysis in a packed-bed reactor by integrating pyrolysis kinetics, a particle scale model, and SuperDEM-CFD in open-source code MFiX. A one-dimensional particle-scale model that discretizes the characteristic length of biomass particle into layers was developed to predict the intraparticle phenomena inside a single particle. The 1D model was validated by comparing it with a single biomass particle pyrolysis experiment. Here, a recently developed SuperDEM-CFD model was employed to simulate the non-spherical particle-particle contact and fluid-particle interaction. The coupled model was applied to simulate the pyrolysis of cubic biomass particles in a packed bed and validated by comparing with experimental data. Simulation with and without particle-scale model was compared, and the effect of the gas-solid heat transfer models was also investigated.

09 BIOMASS FUELS↗

DOE OSTI2015

Testing the Ge detectors for the MAJORANA DEMONSTRATOR

High purity germanium (HPGe) crystals will be used for the MAJORANA DEMONSTRATOR, where they serve as both the source and the detector for neutrinoless double beta decay. It is crucial for the experiment to understand the performance of the HPGe crystals. A variety of crystal properties are being investigated, including basic properties such as energy resolution, efficiency, uniformity, capacitance, leakage current and crystal axis orientation, as well as more sophisticated properties, e.g. pulse shapes and dead layer and transition layer distributions. In this talk, we will present our measurements that characterize the HPGe crystals. We will also discuss the our simulation package for the detector characterization setup, and show that additional information can be extracted from data-simulation comparisons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Molecular dynamics and charge transport in organic semiconductors: a classical approach to modeling electron transfer

Organic photovoltaics (OPVs) are a promising carbon-neutral energy conversion technology, with recent improvements pushing power conversion efficiencies over 10%. A major factor limiting OPV performance is inefficiency of charge transport in organic semiconducting materials (OSCs). Due to strong coupling with lattice degrees of freedom, the charges form polarons, localized quasi-particles comprised of charges dressed with phonons. These polarons can be conceptualized as pseudo-atoms with a greater effective mass than a bare charge. Here we propose that due to this increased mass, polarons can be modeled with Langevin molecular dynamics (LMD), a classical approach with a computational cost much lower than most quantum mechanical methods. Here we present LMD simulations of charge transfer between a pair of fullerene molecules, which commonly serve as electron acceptors in OSCs. We find transfer rates consistent with experimental measurements of charge mobility, suggesting that this method may provide quantitative predictions of efficiency when used to simulate materials on the device scale. Our approach also offers information that is not captured in the overall transfer rate or mobility: in the simulation data, we observe exactly when and why intermolecular transfer events occur. In addition, we demonstrate that these simulations can shed light on the properties of polarons in OSCs. In conclusion, much remains to be learned about these quasi-particles, and there are no widely accepted methods for calculating properties such as effective mass and friction. Lastly, our model offers a promising approach to exploring mass and friction as well as providing insight into the details of polaron transport in OSCs.

14 SOLAR ENERGY↗

DOE OSTI2018

NaCl nucleation from brine in seeded simulations: Sources of uncertainty in rate estimates

This work reexamines seeded simulation results for NaCl nucleation from a supersaturated aqueous solution at 298.15 K and 1 bar pressure. We present a linear regression approach for analyzing seeded simulation data that provides both nucleation rates and uncertainty estimates. Our results show that rates obtained from seeded simulations rely critically on a precise driving force for the model system. The driving force vs. solute concentration curve need not exactly reproduce that of the real system, but it should accurately describe the thermodynamic properties of the model system. We also show that rate estimates depend strongly on the nucleus size metric. We show that the rate estimates systematically increase as more stringent local order parameters are used to count members of a cluster and provide tentative suggestions for appropriate clustering criteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Effect of resistive wall on thermal quench in JET disruptions

In this paper, experimental data, simulations and theory are presented of a JET tokamak thermal quench. The emphasis is on the timescale of the bulk plasma thermal energy loss. The simulations suggest that the thermal energy loss is caused by a resistive wall tearing mode, and experimental data is consistent with this conclusion. The time scale of the thermal quench is the inverse of the mode growth rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗