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At least 775 records · Page 43

NASA Engineering and Safety Center Technical Bulletin No 12-01: Simulation Framework for Rapid Entry, Descent, and Landing Analysis

The NASA Engineering and Safety Center has archived a number of key historic Entry, Descent, and Landing (EDL) simulation models and developed several new models to enhance the capability of the Agency to evaluate a wide range of EDL systems for system analysis studies, preliminary design, mission development and execution, and time-critical assessments. The simulation models developed in this activity can be used to help define the required architectures and investment strategies for future robotic and human exploration missions.

Simulation Framework↗

Enhanced Models for the Simulation of Two-Phase Boiling Flow and Critical Heat Flux with the STAR-CCM+ and NEK-2P CFD Codes: Executive Summary (Final Report)

The goal of the project was to develop, verify and validate an advanced two-phase boiling flow modeling capability that enhances the existing two-phase flow modeling of the STAR-CCM+ Computational Fluid Dynamics (CFD) code. The project focused on the simulation of two phase flow and heat transfer phenomena that occur in Boiling Water Reactor (BWR) and Pressurized Water Reactor (PWR) fuel bundles under various operating conditions. The extended STAR-CCM+ two-phase flow models implemented during the project follow the approach similar to the Extended Boiling Framework [1-6] previously developed at Argonne but include more fundamental physical models of boiling phenomena. The development and validation of the extended two-phase models is supported by the U.S. DOE GAIN program and performed in collaboration with Framatome U.S. Inc.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Surface matching for correlation of virtual models: Theory and application

Virtual reality can enable a robot user to off line generate and test in a virtual environment a sequence of operations to be executed by the robot in an assembly cell. Virtual models of objects are to be correlated to the real entities they represent by means of a suitable transformation. A solution to the correlation problem, which is basically a problem of 3-dimensional adjusting, has been found exploiting the surface matching theory. An iterative algorithm has been developed, which matches the geometric surface representing the shape of the virtual model of an object, with a set of points measured on the surface in the real world. A peculiar feature of the algorithm is to work also if there is no one-to-one correspondence between the measured points and those representing the surface model. Furthermore the problem of avoiding convergence to local minima is solved, by defining a starting point of states ensuring convergence to the global minimum. The developed algorithm has been tested by simulation. Finally, this paper proposes a specific application, i.e., correlating a robot cell, equipped for biomedical use with its virtual representation.

Caracciolo, Roberto↗

The Satellite Flythrough and Reconstruction Softwares at CCMC

The next-generation of model data visualization to be offered at the Community Coordinated Modeling Center (CCMC) will be based on Kamodo, an open source python package. To increase the usefulness of our services, we are also developing new capabilities based on this software, called the satellite flythrough and the reconstruction tools, to be offered both as packages for offline analysis and through an online interface (coming soon). The satellite flythrough software ‘flies’ a satellite trajectory, whether real or imaginary, through either model data hosted at CCMC or on a personal machine. This service greatly simplifies the complexity of users’ access to model data, abstracting away the time-consuming details of model data formats and interpolation. We demonstrate execution times of a few seconds to a few minutes for several example flythroughs of a trajectory stretching over a few days, depending on the parameters chosen. We also demonstrate a reconstruction tool built on top of the satellite flythrough software, for use with mission planning and model-data comparisons. This tool, based on reconstructions provided for the GDC Science and Technology Definition Team, converts multiple, simultaneous satellite flythroughs into two-dimensional reconstructions. The reconstruction tool provides a software capability for satellite constellations to determine how many satellites are needed and in what configuration to resolve the desired features in the model data. Both tools are currently available through GitHub for a selection of CCMC-hosted ITM models. Finally, we present initial results from work in progress and plans for future work, including an expansion of the reconstruction tool to provide 3D reconstruction capabilities and a line-of-sight calculation tool.

software, python↗

The Trick Simulation Toolkit: A NASA/Opensource Framework for Running Time Based Physics Models

The Trick Simulation Toolkit is a simulation development environment used to create high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. Its purpose is to generate a simulation executable from a collection of user-supplied models and a simulation definition file. For each Trick-based simulation, Trick automatically provides job scheduling, numerical integration, the ability to write and restore human readable checkpoints, data recording, interactive variable manipulation, a run-time interpreter, and many other commonly needed capabilities. This allows simulation developers to concentrate on their domain expertise and the algorithms and equations of their models. Also included in Trick are tools for plotting recorded data and various other supporting utilities and libraries. Trick is written in C/C++ and Java and supports both Linux and MacOSX computer operating systems. This paper describes Trick's design and use at NASA Johnson Space Center.

Penn, John M.↗

Development of a model for predicting NASA/MSFC program success

Research conducted during the execution of a previous contract (NAS8-36955/0039) firmly established the feasibility of developing a tool to aid decision makers in predicting the potential success of proposed projects. The final report from that investigation contains an outline of the method to be applied in developing this Project Success Predictor Model. As a follow-on to the previous study, this report describes in detail the development of this model and includes full explanation of the data-gathering techniques used to poll expert opinion. The report includes the presentation of the model code itself.

Riggs, Jeffrey↗

Automated Environment Generation for Software Model Checking

A key problem in model checking open systems is environment modeling (i.e., representing the behavior of the execution context of the system under analysis). Software systems are fundamentally open since their behavior is dependent on patterns of invocation of system components and values defined outside the system but referenced within the system. Whether reasoning about the behavior of whole programs or about program components, an abstract model of the environment can be essential in enabling sufficiently precise yet tractable verification. In this paper, we describe an approach to generating environments of Java program fragments. This approach integrates formally specified assumptions about environment behavior with sound abstractions of environment implementations to form a model of the environment. The approach is implemented in the Bandera Environment Generator (BEG) which we describe along with our experience using BEG to reason about properties of several non-trivial concurrent Java programs.

Tkachuk, Oksana↗

VerifyIO: Ensuring Correctness of Consistency Semantics in Parallel I/O

Abstract—High-performance computing (HPC) applications generate and consume substantial amounts of data, typically managed by parallel file systems. These applications access file systems either through the POSIX interface or by using highlevel I/O libraries. While the POSIX consistency model remains dominant in HPC, emerging file systems and popular I/O libraries increasingly adopt alternative consistency models that relax semantics in various ways, creating significant challenges for correctness and portability. This paper addresses these challenges by proposing a trace-driven I/O consistency verification workflow, implemented in our open-source tool, VerifyIO, which collects execution traces, detects data conflicts, and verifies proper synchronization against specified consistency models. Our extensive evaluation of 91 test case executions across three widely used I/O libraries with four I/O consistency models reveals critical consistency issues at both application and implementation levels.

Consistency Semantics↗

Analysis of Asian Outflow over the Western Pacific using Observations from Trace-P

Our analysis of the TRACE-P data focused on answering the following questions: 1) How do anthropogenic sources in Asia contribute to chemical outflow over the western Pacific in spring? 2) How does biomass burning in southeast Asia contribute to this outflow? 3) How can the TRACE-P observations be used to better quantify the sources of environmentally important gases in eastern Asia? Our strategy drew on a combination of data analysis and global 3-D modeling, as described below. We also contributed to the planning and execution of TRACE-P through service as mission scientist and by providing chemical model forecasts in the field.

Jacob, Daniel J.↗

RELAP5-3D validation studies based on the High Temperature Test facility

In the spring and summer of 2019, experiments were conducted at the High Temperature Test Facility (HTTF) that form the basis of an upcoming high-temperature gas-cooled reactor (HTGR) thermal hydraulics (T/H) benchmark. HTTF is an integral effects test facility for HTGR T/H modeling validation. This paper presents RELAP5-3D models of two of those experiments: PG-27, a pressurized conduction cooldown (PCC); and PG-29, a depressurized conduction cooldown (DCC). These models used the RELAP5-3D model of HTTF originally developed by Paul Bayless as a starting point. The sensitivity analysis and uncertainty quantification code, RAVEN was used to perform calibration studies for the steady-state portion of PG-27. Here we developed four PG-27 calibrations based on steady-state conditions. These calibrations all used an effective thermal conductivity equal to 36 % of the measured thermal conductivity, but they differed with respect to the frictional pressure drops and radial conduction models. These models all captured the trends in steady-state temperature distributions and transient temperature behavior well. All four calibrations show room for improvement in predicting the transient temperature rise. The smallest error in temperature rise during the transient was a 21 % underprediction, and the largest was a 48 % underprediction. The errors in transient temperature rise are largely a result of a mismatch in power density between the RELAP5-3D model and the experiment due to the location of active heater rods along the boundary between heat structures in the model. The best of these calibrations was applied to PG-29 to model the DCC. Once again, temperatures during the transient were underpredicted but trends in temperature were captured. The RELAP5-3D model captured trends in the data but could not reproduce measured temperatures exactly. This result is not attributed to deficiencies in the experimental data or to RELAP5–3D itself. Rather, this result likely arises due to the some of the assumptions and decisions made when the RELAP5-3D model was first developed, prior to the execution of HTTF experiments. An agreement in prediction of temperature trends but challenges reproducing HTTF temperatures within measurement uncertainty is consistent with previous analyses of HTTF in the literature. Future RELAP5-3D validation activities centered around HTTF may be able to provide greater insight into the code’s capabilities for HTGR modeling with a more finely nodalized model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Calibr8 v.1.0

Calibr8 provides an application to rapidly prototype and perform material model calibration for complex plasticity models using advanced adjoint or forward sensitivity analyses for execution on massively parallel machines. These techniques can be orders of magnitude faster than traditional finite difference approaches for material model calibration. The underlying technology used in Calibr8 is automatic differentiation, which allows for the rapid implementation and testing of new plasticity models within its framework. Additionally, Calibr8 can perform adjoint-based error estimation to approximate discretization errors for user-implemented plasticity models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10630 O

Granzow, BrianN.↗

Multiprocessor performance modeling with ADAS

A graph managing strategy referred to as the Algorithm to Architecture Mapping Model (ATAMM) appears useful for the time-optimized execution of application algorithm graphs in embedded multiprocessors and for the performance prediction of graph designs. This paper reports the modeling of ATAMM in the Architecture Design and Assessment System (ADAS) to make an independent verification of ATAMM's performance prediction capability and to provide a user framework for the evaluation of arbitrary algorithm graphs. Following an overview of ATAMM and its major functional rules are descriptions of the ADAS model of ATAMM, methods to enter an arbitrary graph into the model, and techniques to analyze the simulation results. The performance of a 7-node graph example is evaluated using the ADAS model and verifies the ATAMM concept by substantiating previously published performance results.

Hayes, Paul J.↗

Modeling Social Influence via Combined Centralized and Distributed Planning Control

Real world events are driven by a mixture of both centralized and distributed control of individual agents based on their situational context and internal make up. For example, some people have partial allegiances to multiple, contradictory authorities, as well as to their own goals and principles. This can create a cognitive dissonance that can be exploited by an appropriately directed psychological influence operation (PSYOP). An Autonomous Dynamic Planning and Execution (ADP&E) approach is proposed for modeling both the unperturbed context as well as its reaction to various PSYOP interventions. As an illustrative example, the unrest surrounding the Iranian elections in the summer of 2009 is described in terms applicable to an ADP&E modeling approach. Aspects of the ADP&E modeling process are discussed to illustrate its application and advantages for this example.

Vaccaro, James↗

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗

Model for mapping settlements

A programmable media includes a graphical processing unit in communication with a memory element. The graphical processing unit is configured to detect one or more settlement regions from a high resolution remote sensed image based on the execution of programming code. The graphical processing unit identifies one or more settlements through the execution of the programming code that executes a multi-instance learning algorithm that models portions of the high resolution remote sensed image. The identification is based on spectral bands transmitted by a satellite and on selected designations of the image patches.

97 MATHEMATICS AND COMPUTING↗

Towards a Decision Support System for Space Flight Operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

Meshkat, Leila↗

Towards a decision support system for space flight operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The differences between the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the four increments of this vision. These increments include (1) the existing capabilities (2) hardware and software system components and interfaces with the NASA ground system, (3) uncertainty management and (4) re-planning and automated execution. Each of these increments provides value independently; but some may also enable building of a subsequent increment.

Ruszkowski, James↗

Operating executive for the DSIF tracking subsystem software

The advanced engineering model of the DSIF tracking subsystem (DTS) is being developed by the Deep Space Instrumentation Facility. The DTS will provide effective and reliable tracking and data acquisition support for the complex planetary and interplanetary space flight missions planned for the 1970's. The nucleus of the subsystem is a Honeywell H832 digital computer. The design and capabilities of the real-time operating executive software are described.

Poulson, P. L.↗