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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

WPEC Subgroup-38 Final Report part II: Specifications for a new database structure

This is the revision of the specifications for the Generalised Nuclear Database Structure (GNDS), corresponding to GNDS version 1.9. GNDS is designed to serve as a replacement for the Evaluated Nuclear Data Format (ENDF). Although GNDS supersedes the ENDF6 format, GNDS should be viewed as a natural evolution of the ENDF-6 format, using modern computational tools to make nuclear data more accessible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2010

Risk Evaluation in the Pre-Phase A Conceptual Design of Spacecraft

Typically, the most important decisions in the design of a spacecraft are made in the earliest stages of its conceptual design the Pre-Phase A stages. It is in these stages that the greatest number of design alternatives is considered, and the greatest number of alternatives is rejected. The focus of Pre-Phase A conceptual development is on the evaluation and comparison of whole concepts and the larger-scale systems comprising those concepts. This comparison typically uses general Figures of Merit (FOMs) to quantify the comparative benefits of designs and alternative design features. Along with mass, performance, and cost, risk should be one of the major FOMs in evaluating design decisions during the conceptual design phases. However, risk is often given inadequate consideration in conceptual design practice. The reasons frequently given for this lack of attention to risk include: inadequate mission definition, lack of rigorous design requirements in early concept phases, lack of fidelity in risk assessment methods, and under-evaluation of risk as a viable FOM for design evaluation. In this paper, the role of risk evaluation in early conceptual design is discussed. The various requirements of a viable risk evaluation tool at the Pre-Phase A level are considered in light of the needs of a typical spacecraft design study. A technique for risk identification and evaluation is presented. The application of the risk identification and evaluation approach to the conceptual design process is discussed. Finally, a computational tool for risk profiling is presented and applied to assess the risk for an existing Pre-Phase A proposal. The resulting profile is compared to the risks identified for the proposal by other means.

Fabisinski, Leo L., III↗
DOE OSTI2024

Coupled Neutronics - Thermal-Hydraulics - Thermomechanics modeling of Molten Chloride Reactor

Molten Salt Reactors (MSRs) are innovative Generation-IV nuclear reactors known for their enhanced safety features, fuel economy, and fuel cycle advancements. However, designing and studying these reactors present unique safety and modeling challenges. The Department of Energy (DOE)'s Nuclear Energy Advanced Modeling and Simulation program addresses these challenges through the development of flexible multi-fidelity, multiphysics simulation tools. This study exemplifies NEAMS tools' capabilities by modeling a chloride-based micro-MSR: Griffin for neutronics simulations, Pronghorn for thermal-hydraulics simulations, and BISON for thermomechanics simulations. These tools are integrated into a comprehensive 3D multiphysics model, successfully capturing steady-state and transient reactor operations. A loss of flow accident is examined as an illustrative example of transient behavior. Additionally, this paper contributes to demonstrating the theoretical feasibility of micro-MSR concepts, which have received less attention compared to other designs. The subsequent sections provide a brief description of the MSR concept studied, an overview of the computational tools used, and present results for both steady-state operation and a loss of flow accident.

42 - ENGINEERING↗
NASA NTRS1992

Optimal parallel algorithms for problems modeled by a family of intervals

A family of intervals on the real line provides a natural model for a vast number of scheduling and VLSI problems. Recently, a number of parallel algorithms to solve a variety of practical problems on such a family of intervals have been proposed in the literature. Computational tools are developed, and it is shown how they can be used for the purpose of devising cost-optimal parallel algorithms for a number of interval-related problems including finding a largest subset of pairwise nonoverlapping intervals, a minimum dominating subset of intervals, along with algorithms to compute the shortest path between a pair of intervals and, based on the shortest path, a parallel algorithm to find the center of the family of intervals. More precisely, with an arbitrary family of n intervals as input, all algorithms run in O(log n) time using O(n) processors in the EREW-PRAM model of computation.

Olariu, Stephan↗
DOE OSTI2026

A roadmap toward scaling, reasoning and self-evolving foundation models for nuclear and particle physics

Foundation models have revolutionized artificial intelligence, with Large Language Models demonstrating unprecedented capabilities in multimodal understanding, reasoning and tool use. Nuclear and particle physics stands at a critical juncture where similar transformative potential awaits realization. The field generates exabytes of experimental data, exascale simulations, and decades of theoretical insights — yet these remain largely disconnected from modern Artifical Intelligence (AI) capabilities, with most physics AI applications confined to narrow, task-specific models that suffer from domain shifting when applied to real experimental data. We present a roadmap for FM4NPP (Foundation Model for Nuclear and Particle Physics), systematically scaling from current proof-of-concept models to trillion-parameter architectures capable of autonomous discovery. Our approach advances three critical frontiers: unified data infrastructure integrating detector data, scientific knowledge and computational tools across global facilities; multi-facility foundation models enabling cross-experiment knowledge transfer and accelerated discovery; and agentic AI capabilities for reasoning and autonomous tool use. The resulting self-evolving FM4NPP will transform physics research by converting time-intensive data analysis, theory derivation and computational bottlenecks into rapid AI–human collaborative discovery. This paradigm shift promises to fundamentally accelerate scientific progress in nuclear and particle physics, enabling researchers to focus on high-level insights while AI handles routine analysis and explores vast parameter spaces beyond human capacity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Fixed Source Sensitivity Calculations for Inertial Confinement Fusion Applications

A numerical code library was developed for the radiation transport code MCNP6.3 to calculate generalized response sensitivity coefficients for fixed source neutron transport problems with applications to inertial confinement fusion (ICF) experiments. The new MCNP6.3 dependency is used to generate a novel time convolution response that represents a neutron time-of-flight (nToF) signal. The traditional suite of macroscopic cross-section sensitivities and constrained fixed source probability distribution sensitivities are available for both the standard and the new response tallies in this library. However, novel sensitivity coefficients for the constrained hyperparameters of analytic fixed source probability distributions are emphasized in this work for their connection to ICF neutron transport models. Particularly, advanced Monte Carlo methods are developed for calculating the sensitivity of a nToF signal to perturbations in an ICF plasma’s ion temperature and burn history as well as perturbations in the target liner mass density and the shape parameters of the nToF detector’s impulse response function. Together, these capabilities form an advanced suite of computational tools that can be used to analyze and extract information from any ICF experimental platform.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1995

Fast Multipole Methods for Three-Dimensional N-body Problems

We are developing computational tools for the simulations of three-dimensional flows past bodies undergoing arbitrary motions. High resolution viscous vortex methods have been developed that allow for extended simulations of two-dimensional configurations such as vortex generators. Our objective is to extend this methodology to three dimensions and develop a robust computational scheme for the simulation of such flows. A fundamental issue in the use of vortex methods is the ability of employing efficiently large numbers of computational elements to resolve the large range of scales that exist in complex flows. The traditional cost of the method scales as Omicron (N(sup 2)) as the N computational elements/particles induce velocities at each other, making the method unacceptable for simulations involving more than a few tens of thousands of particles. In the last decade fast methods have been developed that have operation counts of Omicron (N log N) or Omicron (N) (referred to as BH and GR respectively) depending on the details of the algorithm. These methods are based on the observation that the effect of a cluster of particles at a certain distance may be approximated by a finite series expansion. In order to exploit this observation we need to decompose the element population spatially into clusters of particles and build a hierarchy of clusters (a tree data structure) - smaller neighboring clusters combine to form a cluster of the next size up in the hierarchy and so on. This hierarchy of clusters allows one to determine efficiently when the approximation is valid. This algorithm is an N-body solver that appears in many fields of engineering and science. Some examples of its diverse use are in astrophysics, molecular dynamics, micro-magnetics, boundary element simulations of electromagnetic problems, and computer animation. More recently these N-body solvers have been implemented and applied in simulations involving vortex methods. Koumoutsakos and Leonard (1995) implemented the GR scheme in two dimensions for vector computer architectures allowing for simulations of bluff body flows using millions of particles. Winckelmans presented three-dimensional, viscous simulations of interacting vortex rings, using vortons and an implementation of a BH scheme for parallel computer architectures. Bhatt presented a vortex filament method to perform inviscid vortex ring interactions, with an alternative implementation of a BH scheme for a Connection Machine parallel computer architecture.

Koumoutsakos, P.↗
NASA NTRS1993

A total variation diminishing finite difference algorithm for sonic boom propagation models

It is difficult to accurately model the rise phases of sonic boom waveforms with traditional finite difference algorithms because of finite difference phase dispersion. This paper introduces the concept of a total variation diminishing (TVD) finite difference method as a tool for accurately modeling the rise phases of sonic booms. A standard second order finite difference algorithm and its TVD modified counterpart are both applied to the one-way propagation of a square pulse. The TVD method clearly outperforms the non-TVD method, showing great potential as a new computational tool in the analysis of sonic boom propagation.

Sparrow, Victor W.↗
NASA NTRS2010

A Biomathematical Model of Lymphopoiesis and Its Application to Acute and Chronic Irradiation Assessment

After the events of September 11, 2001, there is an increasing concern of the occurrence of radiological terrorism that may result in significant casualties in densely populated areas. Much effort has been made to establish various biomarkers to rapidly assess radiation dose in mass-casualty and population-monitoring scenarios, which are demanded for effective medical management and treatment of the exposed victims. Among these the count of lymphocytes in peripheral blood and their depletion kinetics are the most important early indicators of the severity of the radiation injury. In this study, we examine a biomathematical model of lymphopoiesis which has been successfully utilized to simulate and interpret experimental data of acute and chronic irradiations on rodents [1]. With revised parameters for humans, we find this model can reproduce several sets of clinical lymphocyte data of accident victims over a wide range of absorbed doses. In addition, the absolute lymphocyte counts and the depletion rate constants calculated by this model also show good correlation with the Guskova formula and the Goans model, the two empirical tools which have been widely recognized for early estimation of the exposed dose after radiation accidents [2]. We also use the model to analyze the hematological data of the Techa River residents which were exposed to chronic low-dose irradiation during 1950-1956 [3]. This model can serve as a computational tool in radiation accident management, military operations involving nuclear warfare, radiation therapy, and space radiation risk assessment.

Hu, Shaowen↗
DOE OSTI2023

Implementation of a High-Speed Multichannel Data Acquisition System for Magnetic Diagnostics and Plasma Centroid Position Control in ISTTOK

In tokamak and other fusion devices, magnetic control is the main tool that allows to regulate the plasma current, position and shape; it is in charge of actuating the desired plasma current waveform, steering the plasma position to a given set point and maintain the plasma shape close to a prescribed plasma equilibrium. This work describes the application of several physics concepts and computational tools in order to obtain a novel optimal controller for the plasma centroid position, which has been implemented and tested in the real-time plasma control system at the ISTTOK tokamak. A key point for the development of the new control system was the installation of a recently upgraded hardware, that numerically integrates in real-time the magnetic probes signals.

poloidal field coils↗
DOE OSTI2018

STRESS AND DISTORTION SIMULATION OF ADDITIVE MANUFACTURING PROCESS BY HIGH PERFORMANCE COMPUTING

Numerical simulation is an efficient way to better understand the thermal and mechanical evolution during additive manufacturing (AM) and to design and optimize the process. However, with today’s computational tools, pass-by-pass thermal-mechanical numerical simulation of the AM process is extremely time-consuming. In this study, a new finite element code recently developed in house at Oak Ridge National Lab was used for additive manufacturing simulation. Our new code effectively utilizes GPU based high-performance computers to allow for realistic simulation of the transient thermal and mechanical response of materials during additive manufacturing. A benchmark study on a cylinder model by powder bed selective laser melting was carried out and distortion profile was compared to the experimental measurements. The accuracy and efficiency of the code was also demonstrated by analyzing a wire and arc additive manufacturing (WAAM) model which consists of a base plate and four deposited layers.

Huang, Hui↗
DOE OSTI2019

Sensitivity and Uncertainty Workflow of Full System SIERRA Models Supporting High Consequence Applications

Credibility of end-to-end CompSim (Computational Simulation) models and their agile execution requires an expressive framework to describe, communicate and execute complex computational tool chains representing the model. All stakeholders from system engineering and customers through model developers and V&V partners need views and functionalities of the workflow representing the model in a manner that is natural to their discipline. In the milestone and in this report we define workflow as a network of computation simulation activities executed autonomously on a distributed set of computational platforms. The FY19 ASC L2 Milestone (6802) for the Integrated Workflow (IWF) project was designed to integrate and improve existing capabilities or develop new functionalities to provide a wide range of stakeholders a coherent and intuitive platform capable of defining and executing CompSim modeling from analysis workflow definition to complex ensemble calculations. The main goal of the milestone was to advance the integrated workflow capabilities to support the weapon system analysts with a production deployment in FY20. Ensemble calculations supporting program decisions include sensitivity analysis, optimization and uncertainty quantification. The goal of the L2 milestone aligned with the ultimate goal of the IWF project is to foster cultural and technical shift toward and integrated CompSim capability based on automated workflows. Specific deliverables were defined in five broad categories: 1) Infrastructure, including development of distributed-computing workflow capability, 2) integration of Dakota (Sandia's sensitivity, optimization and UQ engine) with SAW (Sandia Analysis Workbench), 3) ARG (Automatic Report Generator introspecting analysis artifacts and generating human-readable extensible and archivable reports), 4) Libraries and Repositories aiding capability reuse, and 5) Exemplars to support training, capturing best practices and stress testing of the platform. A set of exemplars was defined to represent typical weapon system qualification CompSim projects. Analyzing the required capabilities and using the findings to plan implementation of required capabilities ensured optimal allocation of development resources focused on production deployment after the L2 is completed. It was recognized early that the end-to-end modeling applications pose a considerable number of diverse risks, and a formal risk tracking process was implemented. The project leveraged products, capabilities and development tasks of IWF partners. SAW, Dakota, Cubit, Sierra, Slycat, and NGA (NexGen Analytics, a small business) contributed to the integrated platform developed during this milestone effort. New products delivered include: a) NGW (Next Generation Workflow) for robust workflow definition and execution, b) Dakota wizards, editor and results visualization, and c) the automatic report generator ARG. User engagement was initiated early in the development process eliciting concrete requirements and actionable feedback to assure that the integrated CompSim capability will have high user acceptance and impact. The current integrated capabilities have been demonstrated and are continually being tested by a set of exemplars ranging from training scenarios to computationally demanding uncertainty analyses. The integrated workflow platform has been deployed on both SRN (Sandia Restricted Network) and SCN (Sandia Classified Network). Computational platforms where the system has been demonstrated span from Windows (Creo the CAD platform chosen by Sandia) to Trinity HPC (Sierra and CTH solvers). Follow up work will focus on deployment at SNL and other sites in the nuclear enterprise (LLNL, KCNSC), training and consulting support to democratize the analysis agility, process health and knowledge management benefits the NGW platform provides.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Developing And Scaling an OpenFOAM Model to Study Turbulent Flow in a HFIR Coolant Channel

Improving the understanding of how computational fluid dynamics (CFD) direct numerical simulations (DNS) of flows in the High Flux Isotope Reactor (HFIR) perform when run in parallel using the high performance computing (HPC) platform Summit at the Oak Ridge Leadership Computing Facility (OLCF) is of particular importance to boost the computational tools used to support HFIR conversion to low enriched fuel (LEU). Evaluation of scaling performance was driven by the increasing importance of graphics processing unit (GPU) usage in HPC, which is becoming the standard for modern supercomputers such as Summit. The desired results are to obtain a strong positive correlation between the computational resources dedicated to a problem and the relative speed-up of the simulation in comparison to a benchmark. This capability will allow substantially improvement in HFIR flow analytical capabilities, specifically when predicting turbulence properties at high Reynolds numbers. The study leverages previous simulation results performed with code PHASTA (finite element) on HPC platforms Cori (NERSC) and Theta (ALCF) [1] with computing options provided in the computing platform OpenFOAM (finite volume) at OLCF. Transitioning from PHASTA to OpenFOAM will (1) eliminate dependence on third-party software for mesh generation and manipulation, (2) reduce resource needs by employing modern architectures, and (3) build expertise for future modeling of HFIR-specific problems like heat transfer in involute geometry, entrance effects, flow structure in channel corners, and so on—all important issues when defining the available thermal margins in the transition to LEU. CPUs and GPUs differ significantly in their architecture and utilization, as discussed in the literature [2]. The most important differences are in the approach to computations and their memory. A single GPU contains a large quantity of cores, enabling it to perform with a much higher throughput than a CPU, but execution requires a different approach. GPU codes execute instructions using the Single-Instruction Multiple-Thread (SIMT) approach in which a single instruction is used for groups of threads called warps. A warp typically consists of 32 threads which must execute the same set of instructions, although on separate threads. Alternately, a CPU has far fewer cores that are much more flexible in their operation, excelling at quickly performing more complex serial computations. This is why GPUs have greater throughput when properly utilized. The second important difference is seen when comparing their memory spaces. Limited memory allocations and CPU–GPU communications cause a significant bottleneck in GPU-accelerated programs. Further study was required to properly take advantage of GPU resources. A comprehensive analysis of code performance and the model-specific features of turbulence constitutes the core of this work. In this study, a DNS simulation of HFIR channel turbulence was performed with the finite volume CFD code OpenFOAM v2112 and CUDA v11.0 on Red Hat Enterprise Linux v8.2. The OpenFOAM installation had AMGx integrated to enable GPU acceleration and utilizes the PETSc4FOAM library. The computational resources and the problem size were scaled on CPU and CPU + GPU architectures to gain a better understanding of the performance of a DNS problem on modern computing hardware. The study aimed to analyze the scaling of the code exclusively on CPUs and then to examine the scaling of the codes with GPU acceleration enabled. Scaling studies included CPU and GPU acceleration on a mesh of varying resolution to analyze the impact of problem size relative to computational resources. In the course of preparing the GPU configuration on Summit, mainly using the AMGX solvers, difficulties were encountered stemming from constant changes resulting from extensive ongoing development activities and the changing environment. This resulted in the inability to complete the GPU portion of the work. The code was compiled and tested, but production runs to assess acceleration were not performed because the used discretional compute time allocation expired as year-end approached. The Summit HPC platform is scheduled for decommissioning in 2024, making it unattractive for future use with Nvidia-based GPUs. Therefore, the work will be moved onto NERSC machines in FY24. An application was prepared and submitted, and sufficient node-hours were awarded to continue the research in the next calendar year. This report summarizes work performed thus far, which mostly focused on CPU OpenFOAM computing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Determination of interstellar He parameters using five years of data from the IBEX: Beyond closed form approximations

Interstellar He represents a key sample of interstellar matter that, due to its high first ionization potential, survives the journey from beyond our solar system’s heliospheric boundaries to Earth. Ongoing analysis of interstellar neutral (ISN) He atoms by the Interstellar Boundary Explorer (IBEX) has resulted in a growing sophistication in our understanding of the local interstellar flow. A key feature of the IBEX observations near perihelion of the ISN trajectories is a narrow “tube” of approximately degenerate interstellar parameters. These degenerate solutions provide a tightly coupled relationship between the interstellar flow longitude and latitude, speed, and temperature. However, the IBEX analysis resulting in a specific solution for the inflow longitude, inflow speed, temperature, and inflow latitude was accompanied by a sizeable uncertainty along the parameter tube. Here, we use the three-step method to find the interstellar parameters: (1) the ISN He peak rate in ecliptic longitude uniquely determines a relation (as part of the tube in parameter space) between the longitude λ{sub ISN∞} and the speed V{sub ISN∞} of the He ISN flow at infinity; (2) the ISN He peak latitude (on the great circle swept out in each spin) is compared to simulations to derive unique values for λ{sub ISN∞} and V{sub ISN∞} along the parameter tube; and (3) the angular width of the He flow distributions as a function of latitude is used to derive the interstellar He temperature. For simulated peak latitudes, we use a relatively new analytical tool that traces He atoms from beyond the termination shock into the position of IBEX and incorporates the detailed response function of IBEX-Lo. By varying the interstellar parameters along the IBEX parameter tube, we find the specific parameters that minimize the chi-square difference between observations and simulations. The new computational tool for simulating neutral atoms through the integrated IBEX-Lo response function makes no assumptions or expansions with respect to the spin-axis pointing or frame of reference. Thus, we are able to move beyond closed-form approximations and utilize observations of interstellar He during the complete five year period from 2009 to 2013 when the primary component of interstellar He is most prominent. Chi-square minimization of simulations compared to observations results in a He ISN flow longitude of 75.°6 ± 1.°4, latitude of −5.°12 ± 0.°27, speed of 25.4 ± 1.1 km s{sup −1}, and temperature of 8000 ± 1300 K, where the uncertainties are related and apply along the IBEX parameter tube. This paper also provides documentation for a new release of ISN data and associated model runs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

SBbadger: biochemical reaction networks with definable degree distributions

Abstract Motivation An essential step in developing computational tools for the inference, optimization and simulation of biochemical reaction networks is gauging tool performance against earlier efforts using an appropriate set of benchmarks. General strategies for the assembly of benchmark models include collection from the literature, creation via subnetwork extraction and de novo generation. However, with respect to biochemical reaction networks, these approaches and their associated tools are either poorly suited to generate models that reflect the wide range of properties found in natural biochemical networks or to do so in numbers that enable rigorous statistical analysis. Results In this work, we present SBbadger, a python-based software tool for the generation of synthetic biochemical reaction or metabolic networks with user-defined degree distributions, multiple available kinetic formalisms and a host of other definable properties. SBbadger thus enables the creation of benchmark model sets that reflect properties of biological systems and generate the kinetics and model structures typically targeted by computational analysis and inference software. Here, we detail the computational and algorithmic workflow of SBbadger, demonstrate its performance under various settings, provide sample outputs and compare it to currently available biochemical reaction network generation software. Availability and implementation SBbadger is implemented in Python and is freely available at https://github.com/sys-bio/SBbadger and via PyPI at https://pypi.org/project/SBbadger/. Documentation can be found at https://SBbadger.readthedocs.io. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

A decision-theoretic approach to the display of information for time-critical decisions: The Vista project

We describe a collaborative research and development effort between the Palo Alto Laboratory of the Rockwell Science Center, Rockwell Space Operations Company, and the Propulsion Systems Section of NASA JSC to design computational tools that can manage the complexity of information displayed to human operators in high-stakes, time-critical decision contexts. We shall review an application from NASA Mission Control and describe how we integrated a probabilistic diagnostic model and a time-dependent utility model, with techniques for managing the complexity of computer displays. Then, we shall describe the behavior of VPROP, a system constructed to demonstrate promising display-management techniques. Finally, we shall describe our current research directions on the Vista 2 follow-on project.

Horvitz, Eric↗