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NASA NTRS1994

Data assimilation and model evaluation experiment datasets

The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

Lai, Chung-Cheng A.↗

DOE OSTI2023

Improving and Assessing the Quality of Uncertainty Quantification in Deep Learning

Deep learning (DL) models have enjoyed increased attention in recent years because of their powerful predictive capabilities. While many successes have been achieved, standard deep learning methods suffer from a lack of uncertainty quantification (UQ). While the development of methods for producing UQ from DL models is an active area of current research, little attention has been given to the quality of the UQ produced by such methods. In order to deploy DL models to high-consequence applications, high-quality UQ is necessary. This report details the research and development conducted as part of a Laboratory Directed Research and Development (LDRD) project at Sandia National Laboratories. The focus of this project is to develop a framework of methods and metrics for the principled assessment of UQ quality in DL models. This report presents an overview of UQ quality assessment in traditional statistical modeling and describes why this approach is difficult to apply in DL contexts. An assessment on relatively simple simulated data is presented to demonstrate that UQ quality can differ greatly between DL models trained on the same data. A method for simulating image data that can then be used for UQ quality assessment is described. A general method for simulating realistic data for the purpose of assessing a model’s UQ quality is also presented. A Bayesian uncertainty framework for understanding uncertainty and existing metrics is described. Research that came out of collaborations with two university partners are discussed along with a software toolkit that is currently being developed to implement the UQ quality assessment framework as well as serve as a general guide to incorporating UQ into DL applications.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

TransFit: Finite element analysis data fitting software

The Advanced X-Ray Astrophysics Facility (AXAF) mission support team has made extensive use of geometric ray tracing to analyze the performance of AXAF developmental and flight optics. One important aspect of this performance modeling is the incorporation of finite element analysis (FEA) data into the surface deformations of the optical elements. TransFit is software designed for the fitting of FEA data of Wolter I optical surface distortions with a continuous surface description which can then be used by SAO's analytic ray tracing software, currently OSAC (Optical Surface Analysis Code). The improved capabilities of Transfit over previous methods include bicubic spline fitting of FEA data to accommodate higher spatial frequency distortions, fitted data visualization for assessing the quality of fit, the ability to accommodate input data from three FEA codes plus other standard formats, and options for alignment of the model coordinate system with the ray trace coordinate system. TransFit uses the AnswerGarden graphical user interface (GUI) to edit input parameters and then access routines written in PV-WAVE, C, and FORTRAN to allow the user to interactively create, evaluate, and modify the fit. The topics covered include an introduction to TransFit: requirements, designs philosophy, and implementation; design specifics: modules, parameters, fitting algorithms, and data displays; a procedural example; verification of performance; future work; and appendices on online help and ray trace results of the verification section.

Freeman, Mark↗

DOE OSTI2022

MPACT Software Management Plan (V.4.3)

The MPACT code solves a discretized form of the Boltzmann transport equation on a wide variety of geometries and is distributed with a multigroup neutron cross section library. MPACT provides an advanced geometrically resolved neutral-particle transport capability to solve the flux distribution throughout the entire problem geometry, and it can model the isotopic depletion, decay, and activation of materials. The flux solution in MPACT is provided using a 2D/1D synthesis method within the framework of the 3D coarse mesh finite difference (CMFD) method for which axial and radial correction factors are obtained from 2D method of characteristics (MOC) and 1D nodal expansion method (NEM), PN, or SN. Other key characteristics of the MPACT code include the subgroup method and the embedded self-shielding method (ESSM) for resonance treatment, depletion capability based on the ORIGEN exponential matrix method, and a simplified thermal-hydraulics method for temperature/fluid feedback. The sole purpose of the simplified feedback model is to provide a mechanism for testing during code development and to provide a limited capability for educational applications. Work performed at the code level supports the VERA-QA-001, quality assurance program plan (QAPP) and VERA-QA-002, VERA Software Quality Assurance Plan.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2011

Human Thermal Model Evaluation Using the JSC Human Thermal Database

The human thermal database developed at the Johnson Space Center (JSC) is used to evaluate a set of widely used human thermal models. This database will facilitate a more accurate evaluation of human thermoregulatory response using in a variety of situations, including those situations that might otherwise prove too dangerous for actual testing--such as extreme hot or cold splashdown conditions. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models. Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality.

Cognata, T.↗

NASA NTRS2010

Kepler Mission's Focal Plane Characterization Models Implementation

The Kepler Mission photometer is an unusually complex array of CCDs. A large number of time-varying instrumental and systemic effects must be modeled and removed from the Kepler pixel data to produce light curves of sufficiently high quality for the mission to be successful in its planet-finding objective. After the launch of the spacecraft, many of these effects are difficult to remeasure frequently, and various interpolations over a small number of sample measurements must be used to determine the correct value of a given effect at different points in time. A library of software modules, called Focal Plane Characterization (FC) Models, is the element of the Kepler Science Data Pipeline (hereafter "pipeline") that handles this. FC, or products generated by FC, are used by nearly every element of the SOC processing chain. FC includes Java components: database persistence classes, operations classes, model classes, and data importers; and MATLAB code: model classes, interpolation methods, and wrapper functions. These classes, their interactions, and the database tables they represent, are discussed. This paper describes how these data and the FC software work together to provide the pipeline with the correct values to remove non-photometric effects caused by the photometer and its electronics from the Kepler light curves. The interpolation mathematics is reviewed, as well as the special case of the sky-to-pixel,pixel-to-sky coordinate transformation code, which incorporates a compound model that is unique in the SOC software.

mission↗

DOE OSTI2021

CERES : a cryo-EM re-refinement system for continuous improvement of deposited models

The field of electron cryomicroscopy (cryo-EM) has advanced quickly in recent years as the result of numerous technological and methodological developments. This has led to an increase in the number of atomic structures determined using this method. Recently, several tools for the analysis of cryo-EM data and models have been developed within the Phenix software package, such as phenix.real_space_refine for the refinement of atomic models against real-space maps. Also, new validation metrics have been developed for low-resolution cryo-EM models. To understand the quality of deposited cryo-EM structures and how they might be improved, models deposited in the Protein Data Bank that have map resolutions of better than 5 Å were automatically re-refined using current versions of Phenix tools. The results are available on a publicly accessible web page (https://cci.lbl.gov/ceres). The implementation of a Cryo-EM Re-refinement System ( CERES ) for the improvement of models deposited in the wwPDB, and the results of the re-refinements, are described. Based on these results, contents are proposed for a `cryo-EM Table 1', which summarizes experimental details and validation metrics in a similar way to `Table 1' in crystallography. The consistent use of robust metrics for the evaluation of cryo-EM models and data should accompany every structure deposition and be reported in scientific publications.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2023

An Enabling Platform for Achieving Multiscale Multiphysics Analysis of Multiphase Materials

This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT) which address technical gaps in three of the Vision 2040 key discipline areas. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials and is available free through the NASA software catalog. It 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. The resulting anisotropic, evolving nonlinear, thermomechanical constitutive model can also be coupled with external software and used to perform multiscale analyses of more complex structures. A recent application 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 will be discussed. Since typical NASMAT analyses can be completed on the order of seconds to minutes, a second example will demonstrate the ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on implementing NASMAT within a multiscale digital thread/digital twin framework will also be addressed. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Multiscale↗

NASA NTRS1990

Systems Engineering and Integration (SE and I)

The issue of technology advancement and future space transportation vehicles is addressed. The challenge is to develop systems which can be evolved and improved in small incremental steps where each increment reduces present cost, improves, reliability, or does neither but sets the stage for a second incremental upgrade that does. Future requirements are interface standards for commercial off the shelf products to aid in the development of integrated facilities; enhanced automated code generation system slightly coupled to specification and design documentation; modeling tools that support data flow analysis; and shared project data bases consisting of technical characteristics cast information, measurement parameters, and reusable software programs. Topics addressed include: advanced avionics development strategy; risk analysis and management; tool quality management; low cost avionics; cost estimation and benefits; computer aided software engineering; computer systems and software safety; system testability; and advanced avionics laboratories - and rapid prototyping. This presentation is represented by viewgraphs only.

Chevers, ED↗

DOE OSTI2021

Reproducibility of protein x-ray diffuse scattering and potential utility for modeling atomic displacement parameters

Protein structure and dynamics can be probed using x-ray crystallography. Whereas the Bragg peaks are only sensitive to the average unit-cell electron density, the signal between the Bragg peaks—diffuse scattering—is sensitive to spatial correlations in electron-density variations. Although diffuse scattering contains valuable information about protein dynamics, the diffuse signal is more difficult to isolate from the background compared to the Bragg signal, and the reproducibility of diffuse signal is not yet well understood. We present a systematic study of the reproducibility of diffuse scattering from isocyanide hydratase in three different protein forms. Both replicate diffuse datasets and datasets obtained from different mutants were similar in pairwise comparisons (Pearson correlation coefficient ≥0.8). The data were processed in a manner inspired by previously published methods using custom software with modular design, enabling us to perform an analysis of various data processing choices to determine how to obtain the highest quality data as assessed using unbiased measures of symmetry and reproducibility. The diffuse data were then used to characterize atomic mobility using a liquid-like motions (LLM) model. This characterization was able to discriminate between distinct anisotropic atomic displacement parameter (ADP) models arising from different anisotropic scaling choices that agreed comparably with the Bragg data. Our results emphasize the importance of data reproducibility as a model-free measure of diffuse data quality, illustrate the ability of LLM analysis of diffuse scattering to select among alternative ADP models, and offer insights into the design of successful diffuse scattering experiments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

EI_MS_ML

The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation. Substructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit. Determining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.

Mitchell, Joshua↗

DOE OSTI2020

DNA Sequencing Optimizer v0.1

This is a software utility used to maximize next-generation sequencing data output without compromising quality values. The DNA Sequencing Optimizer is used to determine the optimal amount of library to load. To do this a supervised machine learning model predicts cluster density, a measure of how much DNA is bound to the sequence, from the concentration of DNA loaded. The output is a plot that is used by experimentalists to determine the best DNA library concentration to load onto the sequencer.

Costello, Zachary↗

NASA NTRS1991

Quality and security - They work together

This paper describes the importance of considering computer security as part of software quality assurance practice. The intended audience is primarily those professionals involved in the design, development, and quality assurance of software. Many issues are raised which point to the need ultimately for integration of quality assurance and computer security disciplines. To address some of the issues raised, the NASA Automated Information Security program is presented as a model which may be used for improving interactions between the quality assurance and computer security community of professionals.

Carr, Richard↗

NASA NTRS2012

Analytical and Experimental Evaluation of Digital Control Systems for the Semi-Span Super-Sonic Transport (S4T) Wind Tunnel Model

An important objective of the Semi-Span Super-Sonic Transport (S4T) wind tunnel model program was the demonstration of Flutter Suppression (FS), Gust Load Alleviation (GLA), and Ride Quality Enhancement (RQE). It was critical to evaluate the stability and robustness of these control laws analytically before testing them and experimentally while testing them to ensure safety of the model and the wind tunnel. MATLAB based software was applied to evaluate the performance of closed-loop systems in terms of stability and robustness. Existing software tools were extended to use analytical representations of the S4T and the control laws to analyze and evaluate the control laws prior to testing. Lessons were learned about the complex windtunnel model and experimental testing. The open-loop flutter boundary was determined from the closed-loop systems. A MATLAB/Simulink Simulation developed under the program is available for future work to improve the CPE process. This paper is one of a series of that comprise a special session, which summarizes the S4T wind-tunnel program.

Wieseman, Carol D.↗

DOE OSTI2025

Status of SPCA-ANL Software Development, Software Quality Assurance, and Application (FY2025)

SPCA-ANL is a simulation tool used to perform deterministic analyses of sodium spray and pool fires. Development of the SPCA-II (Spray Pool Combustion Analysis) code began in the mid- 1980s as part of the Clinch River Breeder Reactor (CRBR) Project. At that time, development of SPCA-II, which was led by Rockwell International, was focused on treatment of large-scale sodium spray, stream, and pool fires that were anticipated to be prototypic of the steam generator building cells in CRBR. Under more recent DOE NE programmatic activities, the SPCA-II code was recovered from existing literature and underwent minor modifications to generate a stable executable. This recovered version of the code was not formally released. As part of the Versatile Test Reactor (VTR) Project in the 2010s, the SPCA-II code underwent key modifications to improve stability, address modeling deficiencies, improve consistency between the code manual and software, and address numerous bugs. At this point, SPCA-II was renamed SPCA-ANL. Given that SPCA-II served as the original basis for SPCA-ANL, both codes share an integrated history. Following termination of the VTR Project, the DOE NE Fast Reactor Program resumed support of the software with the goal of building and maintaining software infrastructure that can enable commercial-grade dedication of SPCA-ANL by an end user. Version 1.0, the first external release of SPCA-ANL, was generated in June 2024. This report summarizes the development and maintenance activities completed for SPCAANL in FY2025. This year’s work was focused on improving quality and usability of the code. The provisional Software Quality Assurance (SQA) program has been established and was used to test the procedures for infrastructure improvements, code development, bug fixes, and code releases, as described in the following sections of this report. A code Version 1.0.1 was released in FY25, as described in Chapter 4.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

pnnl/emp-gnn

Efficient Graph Neural Network for Predicting Molecular Properties software can compare the prediction quality with ab initio DFT results reported by the high-performance state-of-theart NWChem quantum chemistry package [1] through Mean Absolute Error (MAE) obtained by the fitting between DFT and model predictions i.e, MPNN [2]. We also demonstrated the performance benefits by grouping large molecules by atom sizes, and executing GNN models on different types of resources. Since the training times depend on the number of atoms, we demonstrate the impact of distributing the workloads on two GPUs with varying capabilities (e.g., NVIDIA A100 vs. GeForce RTX 2080 Ti) to optimize the efficiency. We are at the precipice of broad adoption of GNNs for molecular property prediction tasks; hence, our work is timely by comparing model prediction against classical approaches with the intent of providing initial screening for specific classes of molecules.

Lee, Hyungro↗

NASA NTRS1982

A wake traverse technique for use in a 2 dimensional transonic flexible walled test section

Reported two dimensional validation data from the Transonic Self-Streamlining Wind Tunnel (TSWT) concerns model lift. The models tested provided data on their pressure distributions. This information was numerically integrated over the model surface to determine lift, pressure drag and pitching moment. However, the pressure drag is only a small component of the total drag at nominal angles of attack and cannot be used to assess the quality of flow simulation. An intrusive technique for obtaining information on the total drag of a model in TSWT is described. The technique adopted is the wake traverse method. The associated tunnel hardware and control and data reduction software are outlined and some experimental results are presented for discussion.

Wolf, S. W. D.↗

DOE OSTI2024

Software Quality Assurance Plan ANSYS LSDYNA Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic and electromagnetic simulation capabilities. ANSYS LS-DYNA is the most used explicit simulation program capable of simulating the response of materials to short periods of severe loading. Its many elements, contact formulations, material models, and other controls can be used to simulate complex models with control over all the details of the problem. ANSYS LS-DYNA has a vast array of capabilities to simulate extreme deformation problems using its explicit solver. Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times. In addition, many consulting firms and hundreds of universities use ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. ANSYS has successfully passed over 100 customer quality system audits against American Society of Mechanical Engineers (ASME) NQA-1 and 10 CFR Part 50, Appendix B, since the company was founded, over 60 of which have been since 1997. ANSYS has successfully passed over 100 International Organization for Standardization (ISO) 9001 assessments. ANSYS design analysis software is the first created within a quality system with ISO 9001 certification, which is the internationally accepted quality standard. Product development, testing, maintenance, and support processes also meet the US Nuclear Regulatory Commission’s (NRC’s) quality requirements, as they have for nearly four decades. ANSYS staff perform more than 60,000 software verification tests before releasing each new product. ASME NQA-1-2012 (Subpart 2.7 is specific to software) is the industry- and NRC-accepted approach (consensus standard) for meeting 10 CFR Part 50, Appendix B, requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗