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NASA NTRS1992

Validating a large geophysical data set: Experiences with satellite-derived cloud parameters

We are validating the global cloud parameters derived from the satellite-borne HIRS2 and MSU atmospheric sounding instrument measurements, and are using the analysis of these data as one prototype for studying large geophysical data sets in general. The HIRS2/MSU data set contains a total of 40 physical parameters, filling 25 MB/day; raw HIRS2/MSU data are available for a period exceeding 10 years. Validation involves developing a quantitative sense for the physical meaning of the derived parameters over the range of environmental conditions sampled. This is accomplished by comparing the spatial and temporal distributions of the derived quantities with similar measurements made using other techniques, and with model results. The data handling needed for this work is possible only with the help of a suite of interactive graphical and numerical analysis tools. Level 3 (gridded) data is the common form in which large data sets of this type are distributed for scientific analysis. We find that Level 3 data is inadequate for the data comparisons required for validation. Level 2 data (individual measurements in geophysical units) is needed. A sampling problem arises when individual measurements, which are not uniformly distributed in space or time, are used for the comparisons. Standard 'interpolation' methods involve fitting the measurements for each data set to surfaces, which are then compared. We are experimenting with formal criteria for selecting geographical regions, based upon the spatial frequency and variability of measurements, that allow us to quantify the uncertainty due to sampling. As part of this project, we are also dealing with ways to keep track of constraints placed on the output by assumptions made in the computer code. The need to work with Level 2 data introduces a number of other data handling issues, such as accessing data files across machine types, meeting large data storage requirements, accessing other validated data sets, processing speed and throughput for interactive graphical work, and problems relating to graphical interfaces.

Kahn, Ralph↗

NASA NTRS1999

"Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation.

Wilhelms, Jane↗

NASA NTRS1999

User's Manual for LINER: FORTRAN Code for the Numerical Simulation of Plane Wave Propagation in a Lined Two-Dimensional Channel

LINER is a system of Fortran 77 codes which performs a 2D analysis of acoustic wave propagation and noise suppression in a rectangular channel with a continuous liner at the top wall. This new implementation is designed to streamline the usage of the several codes making up LINER, resulting in a useful design tool. Major input parameters are placed in two main data files, input.inc and nurn.prm. Output data appear in the form of ASCII files as well as a choice of GNUPLOT graphs. Section 2 briefly describes the physical model. Section 3 discusses the numerical methods; Section 4 gives a detailed account of program usage, including input formats and graphical options. A sample run is also provided. Finally, Section 5 briefly describes the individual program files.

Reichert, R, S.↗

NASA NTRS2013

Memory Circuit Fault Simulator

Spacecraft are known to experience significant memory part-related failures and problems, both pre- and postlaunch. These memory parts include both static and dynamic memories (SRAM and DRAM). These failures manifest themselves in a variety of ways, such as pattern-sensitive failures, timingsensitive failures, etc. Because of the mission critical nature memory devices play in spacecraft architecture and operation, understanding their failure modes is vital to successful mission operation. To support this need, a generic simulation tool that can model different data patterns in conjunction with variable write and read conditions was developed. This tool is a mathematical and graphical way to embed pattern, electrical, and physical information to perform what-if analysis as part of a root cause failure analysis effort.

Sheldon, Douglas J.↗

NASA NTRSDate not supplied

Agent-based modeling of microbes in space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal microgravity; however, much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER results agree with experimental data indicating that indirect effects of radiation (reactive oxygen species generation, metabolic impairment) have a greater impact on microorganisms than direct effects (DNA damage).

Jessica A Lee↗

DOE OSTI2018

A Decision-Based Iterative Modeling Framework for Probabilistic Performance Assessments - 18441

Radiological probabilistic performance assessments (PPAs) employ highly complex computer models to simulate the release of radionuclides from wastes in an engineered disposal facility, migration of these radionuclides over time, and resulting radiological dose to potentially exposed individuals. An iterative approach to PPA modeling is described to help define the appropriate complexity of the computer model. An initial model is developed that addresses all relevant processes and media, but that employs preliminary statistical parameter distributions to minimize the initial effort expended. Where appropriate, transport and exposure submodels with simplifying assumptions are also used in the initial model. Different assumptions and boundaries may be explored with the initial model to assess their importance in constraining model results. Exploration of the results of the initial model are used to determine the benefits of model refinements, and to guide such refinements to focus on specific areas of the model that most influence the model outputs of interest. This approach promotes efficiency and model parsimony, but does not compromise defensibility when performed in a transparent manner. Key model boundaries for a PPA include the time frame of the modeling (temporal boundaries), where future human receptors may be located (spatial boundaries), and what types of land uses and activities may exist in the future (exposure scenarios). Simplified transport and exposure models can be useful in helping decision makers and stakeholders establish such boundaries by analyzing the consequences of selecting different bounds and understanding which assumptions and boundaries have the greatest influence on the magnitude and distribution of model results. Pathway analysis and parameter sensitivity analysis performed on PPA model results are key components of the iterative modeling approach. The objective of pathway analysis is to identify the critical radionuclides and pathways contributing to radiation dose during the modeling performance period. An environmental 'pathway' is described by the connections from a waste package or cell in the disposal facility to a future human exposure event. These connections are commonly visualized using graphical means. A simple example of a potentially complete pathway for radon-222 is: radium-containing waste → radon emanation → upwards diffusion in cap material → diffusion/advection into a future building → inhalation exposure to a building occupant Parameter sensitivity analysis is conducted on the results of a PPA to identify those specific model input parameters whose distribution of values contributes the most to the distribution of target model output, such as annual radiation dose. Pathway and sensitivity analyses on initial modeling results provide information for guiding subsequent model development, and possibly interim decisions, by informing questions tied to the modeling objectives and performance criteria. For example, questions related to radiological doses from existing disposals may include: 1. Is radiation dose from radiological exposures either obviously negligible or obviously unacceptable based on initial modeling results? 2. If dose is not obviously negligible or unacceptable relative to applicable performance criteria, what model refinements would reduce uncertainty in the results to better inform decisions? (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

SU-F-R-44: Modeling Lung SBRT Tumor Response Using Bayesian Network Averaging

Purpose: The prediction of tumor control after a patient receives lung SBRT (stereotactic body radiation therapy) has proven to be challenging, due to the complex interactions between an individual’s biology and dose-volume metrics. Many of these variables have predictive power when combined, a feature that we exploit using a graph modeling approach based on Bayesian networks. This provides a probabilistic framework that allows for accurate and visually intuitive predictive modeling. The aim of this study is to uncover possible interactions between an individual patient’s characteristics and generate a robust model capable of predicting said patient’s treatment outcome. Methods: We investigated a cohort of 32 prospective patients from multiple institutions whom had received curative SBRT to the lung. The number of patients exhibiting tumor failure was observed to be 7 (event rate of 22%). The serum concentration of 5 biomarkers previously associated with NSCLC (non-small cell lung cancer) was measured pre-treatment. A total of 21 variables were analyzed including: dose-volume metrics with BED (biologically effective dose) correction and clinical variables. A Markov Chain Monte Carlo technique estimated the posterior probability distribution of the potential graphical structures. The probability of tumor failure was then estimated by averaging the top 100 graphs and applying Baye’s rule. Results: The optimal Bayesian model generated throughout this study incorporated the PTV volume, the serum concentration of the biomarker EGFR (epidermal growth factor receptor) and prescription BED. This predictive model recorded an area under the receiver operating characteristic curve of 0.94(1), providing better performance compared to competing methods in other literature. Conclusion: The use of biomarkers in conjunction with dose-volume metrics allows for the generation of a robust predictive model. The preliminary results of this report demonstrate that it is possible to accurately model the prognosis of an individual lung SBRT patient’s treatment.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1981

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

A new experimental climatological model/variable termed the sponge, a measure of moisture availability based on daily temperature maxima and minima and precipitation, is tested for potential biogeographic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic from, suggest that, as a generalized climatic index, sponge's simplicity and sensitivity make particularly appropriate for trans-regional biogeographic studies (e.g., large-area and global vegetation monitoring). The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

Greegor, D. H.↗

NASA NTRS1989

Combining high performance simulation, data acquisition, and graphics display computers

Issues involved in the continuing development of an advanced simulation complex are discussed. This approach provides the capability to perform the majority of tests on advanced systems, non-destructively. The controlled test environments can be replicated to examine the response of the systems under test to alternative treatments of the system control design, or test the function and qualification of specific hardware. Field tests verify that the elements simulated in the laboratories are sufficient. The digital computer is hosted by a Digital Equipment Corp. MicroVAX computer with an Aptec Computer Systems Model 24 I/O computer performing the communication function. An Applied Dynamics International AD100 performs the high speed simulation computing and an Evans and Sutherland PS350 performs on-line graphics display. A Scientific Computer Systems SCS40 acts as a high performance FORTRAN program processor to support the complex, by generating numerous large files from programs coded in FORTRAN that are required for the real time processing. Four programming languages are involved in the process, FORTRAN, ADSIM, ADRIO, and STAPLE. FORTRAN is employed on the MicroVAX host to initialize and terminate the simulation runs on the system. The generation of the data files on the SCS40 also is performed with FORTRAN programs. ADSIM and ADIRO are used to program the processing elements of the AD100 and its IOCP processor. STAPLE is used to program the Aptec DIP and DIA processors.

Hickman, Robert J.↗

DOE OSTI2021

Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

Abstract Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

Sehnal, David↗

DOE OSTI2015

Evaluating the Impact of Road Grade on Simulated Commercial Vehicle Fuel Economy Using Real-World Drive Cycles

Commercial vehicle fuel economy is known to vary significantly with both positive and negative road grade. Medium- and heavy-duty vehicles operating at highway speeds require incrementally larger amounts of energy to pull heavy payloads up inclines as road grade increases. Non-hybrid vehicles are then unable to recapture energy on descent and lose energy through friction braking. While the on-road effects of road grade are well understood, the majority of standard commercial vehicle drive cycles feature no climb or descent requirements. Additionally, existing literature offers a limited number of sources that attempt to estimate the on-road energy implications of road grade in the medium- and heavy-duty space. This study uses real-world commercial vehicle drive cycles from the National Renewable Energy Laboratory's Fleet DNA database to simulate the effects of road grade on fuel economy across a range of vocations, operating conditions, and locations. Drive-cycles are matched with vocation-specific vehicle models and simulated with and without grade. Fuel use due to grade is presented, and variation in fuel consumption due to drive cycle and vehicle characteristics is explored through graphical and statistical comparison. The results of this study suggest that road grade accounts for 1%-9% of fuel use in commercial vehicles on average and up to 40% on select routes.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2007

GVIPS Models and Software

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

Arnold, Steven M.↗

DOE OSTI2023

Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry

Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. Here, this work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline k–τ turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

A lightweight approach to performance portability with targetDP

Leading high performance computing systems achieve their status through use of highly parallel devices such as NVIDIA graphics processing units or Intel Xeon Phi many-core CPUs. The concept of performance portability across such architectures, as well as traditional CPUs, is vital for the application programmer. In this paper we describe targetDP, a lightweight abstraction layer which allows grid-based applications to target data parallel hardware in a platform agnostic manner. We demonstrate the effectiveness of our pragmatic approach by presenting performance results for a complex fluid application (with which the model was co-designed), plus separate lattice quantum chromodynamics particle physics code. For each application, a single source code base is seen to achieve portable performance, as assessed within the context of the Roofline model. TargetDP can be combined with Message Passing Interface (MPI) to allow use on systems containing multiple nodes: we demonstrate this through provision of scaling results on traditional and graphics processing unit-accelerated large scale supercomputers.

Computer Science↗

DOE OSTI2023

Exploring model complexity in machine learned potentials for simulated properties

Abstract Machine learning (ML) enables the development of interatomic potentials with the accuracy of first principles methods while retaining the speed and parallel efficiency of empirical potentials. While ML potentials traditionally use atom-centered descriptors as inputs, different models such as linear regression and neural networks map descriptors to atomic energies and forces. This begs the question: what is the improvement in accuracy due to model complexity irrespective of descriptors? We curate three datasets to investigate this question in terms of ab initio energy and force errors: (1) solid and liquid silicon, (2) gallium nitride, and (3) the superionic conductor Li $$_{10}$$ 10 Ge(PS $$_{6}$$ 6 ) $$_{2}$$ 2 (LGPS). We further investigate how these errors affect simulated properties and verify if the improvement in fitting errors corresponds to measurable improvement in property prediction. By assessing different models, we observe correlations between fitting quantity (e.g. atomic force) error and simulated property error with respect to ab initio values. Graphical abstract

Rohskopf, A. (ORCID:0000000227128296)↗

NASA NTRS1975

Investigation of Skylab imagery for regional planning

The author has identified the following significant results. It is feasible to use earth terrain camera imagery to detect four land uses (vacant land, developed land, streets, and water) for general regional planning purposes. Multispectral imagery is suitable for detecting, mapping, and measuring water bodies as small as two acres. Sufficient information can be extracted to prepare graphic and pictorial representations of the general growth and development patterns, but cannot be incorporated into an inventory file for predictive models.

Harting, W.↗

NASA NTRS1977

An application of interactive computer graphics technology to the design of dispersal mechanisms

Interactive computer graphics technology is combined with a general purpose mechanisms computer code to study the operational behavior of three guided bomb dispersal mechanism designs. These studies illustrate the use of computer graphics techniques to discover operational anomalies, to assess the effectiveness of design improvements, to reduce the time and cost of the modeling effort, and to provide the mechanism designer with a visual understanding of the physical operation of such systems.

Richter, B. J.↗

NASA NTRS1977

An application of interactive computer graphics technology to the design of dispersal mechanisms

Richter, B. J.↗