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DOE OSTI2025

Dark Energy Survey Year 6 Results: Point-Spread Function Modeling

We present the point-spread function (PSF) modeling for weak lensing shear measurement using the full six years of the Dark Energy Survey (DES Y6) data. We review the PSF estimation procedure using the PIFF (PSFs In the Full FOV) software package and describe the key improvements made to PIFF and modeling diagnostics since the DES year three (Y3) analysis: (i) use of external Gaia and infrared photometry catalogs to ensure higher purity of the stellar sample used for model fitting, (ii) addition of color-dependent PSF modeling, the first for any weak lensing analysis, and (iii) inclusion of model diagnostics inspecting fourth-order moments, which can bias weak lensing measurements to a similar degree as second-order modeling errors. Through a comprehensive set of diagnostic tests, we demonstrate the improved accuracy of the Y6 models evident in significantly smaller systematic errors than those of the Y3 analysis, in which all g band data were excluded due to insufficiently accurate PSF models. For the Y6 weak lensing analysis, we include g band photometry data in addition to the riz bands, providing a fourth band for photometric redshift estimation. Looking forward to the next generation of wide-field surveys, we describe several ongoing improvements to PIFF, which will be the default PSF modeling software for weak lensing analyses for the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1991

Model-based diagnostics for Space Station Freedom

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

Fesq, Lorraine M.↗

DOE OSTI2024

Qualitative and quantitative enhancement of parameter estimation for model-based diagnostics using automatic differentiation with an application to inertial fusion

Parameter estimation using observables is a fundamental concept in the experimental sciences. Mathematical models that represent the physical processes can enable reconstructions of the experimental observables and greatly assist in parameter estimation by turning it into an optimization problem which can be solved by gradient-free or gradient-based methods. In this work, the recent rise in flexible frameworks for developing differentiable scientific computing programs is leveraged in order to dramatically accelerate data analysis of a common experimental diagnostic relevant to laser–plasma and inertial fusion experiments, Thomson scattering. A differentiable Thomson-scattering data analysis tool is developed that uses reverse-mode automatic differentiation (AD) to calculate gradients. By switching from finite differencing to reverse-mode AD, three distinct outcomes are achieved. First, gradient descent is accelerated dramatically to the extent that it enables near real-time usage in laser–plasma experiments. Second, qualitatively novel quantities which require $\mathcal{O}(10^3)$ parameters can now be included in the analysis of data which enables unprecedented measurements of small-scale laser–plasma phenomena. Third, uncertainty estimation approaches that leverage the value of the Hessian become accurate and efficient because reverse-mode AD can be used for calculating the Hessian.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Predictive Modeling and Diagnostic Monitoring of Extreme Science Workflows (Final Report)

This proposal addresses a critical issue of performance prediction identified in the report from the ASCR \Computational Modeling of Big Networks (COMBINE)" workshop: "end-to-end performance is not predictable due to a variety of factors. Even when some performance forecasts or predictions can be made, they often cannot explain the reasons why some predictions fail." We will develop new analytical models to predict the end-to-end performance of scientific workflows on DOE computing infrastructures, and use simulations and experimentation to validate and refine these models, as well as to pinpoint the sources of model inaccuracy. We will also use these models to help diagnose application and infrastructure problems, and to adapt the system based on this diagnosis. This section provides background in the areas relevant to the proposed work. RPI’s specific tasks within the Panorama project are as follows: (1) Develop Aspen-Simulation interface for Workflow Model Driven Simulation. (2) Validate manual performance models of two target workflow scenarios with empirical measurement and simulation. (3) Extend ROSS-Aspen API to simulate workflow descriptions when required. (4) Validate Aspen performance models of two target workflow scenarios with automatic performance model empirical measurement and simulation. (5) Design and implement final system to automatically generate Aspen performance models from workflow descriptions (including methods to compensate for limitations of Aspen analytical models). (6) Validate improved Aspen performance models with target workflow on production infrastructure. To date, all the project milestones assigned to us where reached within the best of our abilities over the course of the project performance period. Below describes the key outcome from our collaborative research in a system named, Durango .

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). Here, we also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135 × 10 4 km 2 ) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101 ×10 4 km 2 ). However the uncertainty (1 to 128 × 10 4 km 2 ) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0°C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2011

X-Ray Reflected Spectra from Accretion Disk Models. II. Diagnostic Tools for X-Ray Observations

We present a comprehensive study of the emission spectra from accreting sources. We use our new reflection code to compute the reflected spectra from an accretion disk illuminated by X-rays. This set of models covers different values of ionization parameter, solar iron abundance and photon index for the illuminating spectrum. These models also include the most complete and recent atomic data for the inner-shell of the iron and oxygen isonuclear sequences. We concentrate our analysis to the 2 - 10 keV energy region, and in particular to the iron K-shell emission lines. We show the dependency of the equivalent width (EW) of the Fe Ka with the ionization parameter. The maximum value of the EW is approx. 800 eV for models with log Epsilon approx. 1.5, and decreases monotonically as Epsilon increases. For lower values of Epsilon the Fe K(alpha) EW decreases to a minimum near log Epsilon approx. 0.8. We produce simulated CCD observations based on our reflection models. For low ionized, reflection dominated cases, the 2 -10 keV energy region shows a very broad, curving continuum that cannot be represented by a simple power-law. We show that in addition to the Fe K-shell emission, there are other prominent features such as the Si and S L(alpha) lines, a blend of Ar VIII-XI lines, and the Ca x K(alpha) line. In some cases the S xv blends with the He-like Si RRC producing a broad feature that cannot be reproduced by a simple Gaussian profile. This could be used as a signature of reflection.

Garcia, J.↗

NASA NTRS2010

Stage Separation Failure: Model Based Diagnostics and Prognostics

Safety of the next-generation space flight vehicles requires development of an in-flight Failure Detection and Prognostic (FD&P) system. Development of such system is challenging task that involves analysis of many hard hitting engineering problems across the board. In this paper we report progress in the development of FD&P for the re-contact fault between upper stage nozzle and the inter-stage caused by the first stage and upper stage separation failure. A high-fidelity models and analytical estimations are applied to analyze the following sequence of events: (i) structural dynamics of the nozzle extension during the impact; (ii) structural stability of the deformed nozzle in the presence of the pressure and temperature loads induced by the hot gas flow during engine start up; and (iii) the fault induced thrust changes in the steady burning regime. The diagnostic is based on the measurements of the impact torque. The prognostic is based on the analysis of the correlation between the actuator signal and fault-induced changes in the nozzle structural stability and thrust.

Luchinsky, Dmitry↗

NASA NTRS2020

Model Based Diagnostics and Prognostics Framework for Systems Health Management

In order to tackle and solve the system health prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. This presentation will cover a physics based-modeling approach implemented for case-studies in battery and composite structures for prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Banerjee, Portia↗

DOE OSTI2019

Diagnostics and Models for Birthing Stress

Understanding the stress development in fluids as they transition to solids is not well-understood. Computational models are needed to represent "birthing stress" for multiphysics applications such as polymer encapsulation around sensitive electronics and additive manufacturing where these stresses can lead to defects such as cracking and voids. The local stress state is also critical to understand and predict the net shape of parts formed in the liquid phase. In this one-year exploratory LDRD, we have worked towards a novel experimental diagnostic to measure the fluid rheology, degree of solidification, and the solid stress development simultaneously. We debugged and made viable a "first-generation" Rheo-Raman system and used it to characterize two types of solidifying systems: paraffin wax, which crystalizes as it solidifies, and thermoset polymers, which form a network of covalent bonds. We used the paraffin wax as a model system to perform flow visualization studies and did some preliminary modeling of the experiment, to demonstrate the inadequacy of the current modeling approaches. This work will inform an advanced fluid constitutive equation that includes a yield stress, temperature dependence, and an evolving viscosity when we pursue the full proposal, which was funded for FY20.

36 MATERIALS SCIENCE↗

DOE OSTI2014

X-ray spectroscopic diagnostics and modeling of polar-drive implosion experiments on the National Ignition Facility

A series of experiments featuring laser-imploded plastic-shell targets filled with hydrogen or deuterium were performed on the National Ignition Facility. The shells (some deuterated) were doped in selected locations with Cu, Ga, and Ge, whose spectroscopic signals (indicative of local plasma conditions) were collected with a time-integrated, 1-D imaging, spectrally resolved, and absolute-intensity calibrated instrument. The experimental spectra compare well with radiation hydrodynamics simulations post-processed with a non-local thermal equilibrium atomic kinetics and spectroscopic-quality radiation-transport model. The obtained degree of agreement between the modeling and experimental data supports the application of spectroscopic techniques for the determination of plasma conditions, which can ultimately lead to the validation of theoretical models for thermonuclear burn in the presence of mix. Furthermore, the use of a lower-Z dopant element (e.g., Fe) is suggested for future experiments, since the ∼2 keV electron temperatures reached in mixed regions are not high enough to drive sufficient H-like Ge and Cu line emissions needed for spectroscopic plasma diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

On the application of betweenness centrality in chemical network analysis: Computational diagnostics and model reduction

Here, the concept of shortest path and betweenness centrality (BC) is introduced in combustion systems, with its application demonstrated in chemical network analysis and skeletal mechanism generation. After establishing the graphical representation of a chemical network for given pressure, temperature, and species concentrations, a metric BC is defined to rank the shortest paths passed by other nodes between the pair of source and target node, and as such captures the dominant indirect kinetic pathways between any pair of nodes in the network for computational diagnostics. As a result, the controlling pathways are retained by collecting the species with larger BC values. Such a notion then indicates that the index of importance of species could then be assigned based on their BC values to further guide skeletal mechanism generation. Unlike existing methods, the betweenness centrality approach takes into account of both the fluxes between species and their relative positioning within the chemical network. To demonstrate its potential utility to combustion studies, the approach was applied to the GRI-3.0, LLNL and USC-Mech II mechanisms to identify the important pathways in the chemical network at each local reaction state, and develop skeletal mechanisms from all reaction state samples in auto-ignition and perfectly stirred reactor (PSR) simulations. The performance of the BC ranking is compared to the methods of directed relation graph (DRG), DRG with error propagations (DRGEP) and sensitivity analysis (SA), and is shown to possess sufficient utility in producing skeletal mechanisms with good accuracy and flexibility for the cases studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Model-Based Diagnostics and Mitigation of Cyber Threats

The report summarizes key tasks performed to develop a toolkit for detecting cyber-attack events in instrumentation and control (I&C) systems of nuclear power plants. The toolkit connects the state-of-the-art GPWR Simulator with the RELAP5 code providing best-estimate nuclear steam supply system (NSSS) analyses, via the application programming interface (API), and allows users to introduce potential cyber-attack scenarios into power plant operational simulation. This summary for the project reflects topical reports submitted during the project as well as a journal paper published in 2022. The focus areas of the summary include: (1) modeling I&C systems for the AP1000 Generation III+ nuclear plant and GPWR simulator, (2) simulation and monitoring of plant response to cyber-attack events, (3) API structure for the toolkit interfacing the GPWR simulator and RELAP5 code, and (4) restructuring of the three-loop NSSS software of GPWR to model the two-loop AP1000 structure. Discussed in some details are (a) the attack tree analysis assessing the susceptibility of the AP1000 I&C system, resulting in reactor trips, in terms of the attack possibility and component sensitivity and (b) realistic estimation of the time to steam generator trip due to cyber-intrusions in the GPWR Simulator. Finally, sample demonstrations of the cyber-security tool kit, in the form of the GPWR-RELAP5 API, are summarized.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Plasma diagnostics and modeling of lithium-containing plasmas

Thin-film deposition from chemically reactive multi-component plasmas is complex, and the lack of electron collision cross-sections for even the most common metalorganic precursors and their fragments complicates their modeling based on fundamental plasma physics. This study focuses on understanding the plasma physics and chemistry in argon (Ar) plasmas containing lithium bis (trimethylsilyl) amide used to deposit Li x Si y thin films. These films are emerging as potential solid electrolytes for lithium-ion batteries, and the Li-to-Si ratio is a crucial parameter to enhance their ionic conductivity. We deposited Li x Si y films in an axial flow-through plasma reactor and studied the factors that determine the variation of the Li-to-Si ratio in films deposited at various points on a substrate spanning the entire reactor axis. While the Li-to-Si ratio is 1:2 in the precursor, the Li-to-Si ratio is as high as 3:1 in films deposited near the plasma entrance and decreases to 1:1 for films deposited downstream. Optical emission from the plasma is dominated by Li emission near the entrance, but Li emission disappears downstream, which we attribute to the complete consumption of the precursor. We hypothesized that the axially decreasing precursor concentration affects the electron energy distribution function in a way that causes different dissociation efficiencies for the production of Li and Si. We used Li line intensities to estimate the local precursor concentration and Ar line ratios to estimate the local reduced electric field to test this hypothesis. This analysis suggests that the mean electron energy increases along the reactor axis with decreasing precursor concentration. As a result, the decreasing Li-to-Si ratio with axially decreasing precursor concentration may be explained by Li release from the precursor having lower threshold energy than Si release.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Development of advanced diagnostic tools, models, and technoeconomic analyses for high-temperature heat transfer coefficient heat exchangers

This is a final technical report of a system designed to image fall particle receivers. High temperature heat is hard to store and move and using low cost materials, similar to sand, are ideal. However, particle-to-particle interactions can impact heat transfer mechanisms in these classes of materials. This report highlights our effects to utilize x-ray imaging to understand these dynamics.

14 SOLAR ENERGY↗

NASA NTRS1984

Physics of the inner heliosphere 1-10R sub O plasma diagnostics and models

The physics of solar wind flow in the acceleration region and impulsive phenomena in the solar corona is studied. The study of magnetohydrodynamic wave propagation in the corona and the solutions for steady state and time dependent solar wind equations gives insights concerning the physics of the solar wind acceleration region, plasma heating and plasma acceleration processes and the formation of shocks. Also studied is the development of techniques for placing constraints on the mechanisms responsible for coronal heating.

Withbroe, G. L.↗

NASA NTRS1988

Knowledge-based diagnosis for aerospace systems

The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

Atkinson, David J.↗

NASA NTRS1988

Knowledge-based diagnosis for aerospace systems

Atkinson, David↗

NASA NTRS2001

Physics of the Inner Heliosphere 1-10 R(sub s): Plasma Diagnostics and Models

While the mechanisms responsible for heating the solar corona and accelerating the fast and slow solar wind streams are still unknown, model computations offer the only means for exploring and predicting the properties of such mechanisms in light of the empirical constraints currently available. During the time covered by this grant, modeling and data analysis efforts were aimed at: 1) the study of the propagation and damping of ion-cyclotron waves in the fast solar wind 2) the exploration of the role of instabilities in the development of temperature anisotropies in the inner corona 3) the coupling of neutral hydrogen and protons in the fast solar wind 4) the morphology of the source region of the solar wind. Summarized are some of the highlights of these studies. Two PhD theses by Xing Li and Lorraine Allen were partially supported by this grant.

Habbal, Shadia R.↗