SEARCH · Search NASA

Results for “Performance Tools”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2016

TU-FG-209-07: Medical Physics 1.0 Versus Medical Physics 2.0: A Case Study

Purpose: To illustrate how performance analytics can identify performance decrement in digital radiography systems. Methods: Subsequent to a radiologist’s image quality complaint, four different advanced methods contributed to root cause analysis. Our system was a GE Revolution XQi digital radiography unit. Initially, we reviewed weekly GE Quality Assurance Procedures (QAP) results in a database dating from 2001. Next, we evaluated objective image quality metrics of individual PA Chest radiographs acquired. These images were anonymized, securely transferred, and analyzed by the Duke University Clinical Imaging Physics Group with software previously described{sup 1} and validated{sup 2}. Third, we compared the exposure-dependent SNR{sup 2} (NEQ) of the unit with previously established confidence limits{sup 3}. Finally, we explored our service database to reveal events that might affect detector performance. Results: QAP reported a decrease in CNR reflected in a significant increase in lung noise(Ln), mediastinum noise(Mn), and subdiaphragm-lung contrast(Slc) with a significant decrease in lung grey level(Lgl) after detector replacement. Most change occurred during week 1, before the QAP indicated one-half the ultimate decrease in CNR. After detector recalibration, QAP CNR improved, but was not restored to previous levels. Lgl and Slc were no longer significantly different from before, however Ln and Mn remained significantly different. Exposure-dependent SNR2 show the detector to be operating within limits in October 2006 but subsequently became miscalibrated sometime before acquisition of the 2011–2014 data. Service records revealed catastrophic failure of the Image Detection Controller that contained the 2007 calibration. Traditional metrics did not indicate that the system was performing outside of normal limits. Conclusion: Performance analytics are powerful tools whose proper application could allow early intervention in degraded system performance. The image-quality metrics appear to be highly sensitive to system performance and are reported with every acquisition rather than at arbitrary intervals. Confidence intervals may require customization for individual systems or detectors.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1989

Experiences with hypercube operating system instrumentation

The difficulties in conceptualizing the interactions among a large number of processors make it difficult both to identify the sources of inefficiencies and to determine how a parallel program could be made more efficient. This paper describes an instrumentation system that can trace the execution of distributed memory parallel programs by recording the occurrence of parallel program events. The resulting event traces can be used to compile summary statistics that provide a global view of program performance. In addition, visualization tools permit the graphic display of event traces. Visual presentation of performance data is particularly useful, indeed, necessary for large-scale parallel computers; the enormous volume of performance data mandates visual display.

Reed, Daniel A.↗

NASA NTRS1994

Task network models in the prediction of workload imposed by extravehicular activities during the Hubble Space Telescope servicing mission

In a joint effort with Brooks AFB, Texas, the Flight Crew Support Division at JSC has begun a computer simulation and performance modeling program directed at establishing the predictive validity of software tools for modeling human performance during spaceflight. This paper addresses the utility of task network modeling for predicting the workload that astronauts are likely to encounter in extravehicular activities (EVA) during the Hubble Space Telescope (HST) repair mission. The intent of the study was to determine whether two EVA crewmembers and one intravehicular activity (IVA) crewmember could reasonably be expected to complete HST Wide Field/Planetary Camera (WFPC) replacement in the allotted time. Ultimately, examination of the points during HST servicing that may result in excessive workload will lead to recommendations to the HST Flight Systems and Servicing Project concerning (1) expectation of degraded performance, (2) the need to change task allocation across crewmembers, (3) the need to expand the timeline, and (4) the need to increase the number of EVA's.

Diaz, Manuel F.↗

DOE OSTI2023

Slicing with deep learning models at ProtoDUNE-SP

DUNE is a cutting-edge experiment aiming to study neutrinos in detail, with a special focus on the flavor oscillation mechanism. The prototype of the DUNE Far Detector Single Phase TPC (ProtoDUNE-SP) was built and operated at CERN with a full set of reconstruction tools. To implement these reconstruction tools, Pandora, a multi-algorithm framework, has been developed. A large number of these algorithms, some of them being exploiting traditional clustering, detector physics and deep learning approaches, have been applied to images to gradually build up a picture out of singular events. One of such algorithms is the Pandora slicing algorithm which aims to partition the detector hits of an event in sets called slices. Each slice represents a single interaction in the detector and should identify all the hits related to the interacting particle and its subsequent decay products. We expect the order of tens of slices per event in ProtoDUNE-SP. In this paper we present a deep learning approach to the problem, designing a model able to outperform the state-of-the-art slicing algorithm which is currently implemented within Pandora. We assess the performance of our tool in terms of efficiency and accuracy, while exploiting hardware accelerating setups. The ultimate goal is to incorporate this deep learning approach in the Pandora reconstruction tool.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1997

Robotic Assisted Microsurgery - RAMS FY'97

JPL and Microdexterity Systems collaborated to develop new surgical capabilities. They developed a Robot Assisted Microsurgery (RAM) tool for surgeons to use for operating on the eye, ear, brain, and blood vessels with unprecedented dexterity. A surgeon can hold the surgical instrument with motions of 6 degrees of freedom with an accuracy of 25 microns in a 70 cu cm workspace. In 1996 a demonstration was performed to remove a microscopic particle from a simulated eyeball. In 1997, tests were performed at UCLA to compare telerobotics with mechanical operations. In 5 out of 7 tests, the RAM tool performed with a significant improvement of preciseness over mechanical operation. New design features include: (1) amplified forced feedback; (2) simultaneous slave robot instrumentation; (3) index control switch on master handle; and (4) tool control switches. Upgrades include: (1) increase in computational power; and (2) installation of hard disk memory storage device for independent operation and independent operation of forceps. In 1997 a final demonstration was performed using 2 telerobotics simultaneously in a microsurgery suture procedure to close a slit in a thin sheet of latex rubber which extended the capabilities of microsurgery procedures. After completing trials and demonstrations for the FDA the potential benefits for thousands of operations will be exposed.

Source record↗

DOE OSTI2024

High-Fidelity Multiphysics Modeling of a Heat Pipe Microreactor Using BlueCrab

Researchers who are actively developing nuclear microreactors are planning to employ innovative designs and features using traditional commercial modeling tools that may be inadequate for their design and licensing activities. The codes developed under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program provide flexibility in terms of geometry modeling and multiphysics coupling and are particularly well suited for modeling novel microreactor concepts. To test the maturity of these codes, this paper introduces a conceptual heat pipe microreactor (HP-MR) designed to gather various technologies of interest to microreactor developers such as control drums, heat pipes, and hydride moderators. Here, the objective of this effort is to demonstrate NEAMS tools capability to perform high-fidelity multiphysics simulations, using coupled neutronics (via the Griffin code), heat conduction (via the BISON code), heat pipe modeling (via the Sockeye code), and hydrogen redistribution in hydride metal moderator (via the SWIFT code). Codes are coupled in-memory through the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which permits flexible multiphysics data transfer schemes. The analysis confirmed two key aspects of the HP-MR concept: (1) its ability to follow the power load requested from the heat pipe and (2) its ability to avoid heat pipe cascading failure unless designed with high power close to operating failure limits of its heat pipes. The developed computational model was distributed publicly on the Virtual Test Bed for training purposes to accelerate adoption by industry and to provide a high-fidelity multiphysics solution for benchmarking against other tools. Additional multiphysics analyses including other transients and coupled physics were identified as necessary future work, together with a focus on validating multiphysics behavior against experiments.

Microreactor↗

DOE OSTI2014

Standard Energy Efficiency Data Platform

The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.

Cheifetz, D.Magnus↗

DOE OSTI2014

Standard Energy Efficiency Data Platform

Cheifetz, D. Magnus↗

DOE OSTI2022

CTF: A modernized, production-level, thermal hydraulic solver for the solution of industry-relevant challenge problems in pressurized water reactors

CTF is a thermal hydraulic (T/H) subchannel tool that has been extensively developed over the past ten years as part of the Consortium for Advanced Simulation of Light Water Reactors (CASL) program. The code was selected early in the CASL program for support of high-impact challenge problems that were found to be relevant to the nuclear industry and its currently operating fleet of pressurized water reactors (PWRs), including issues such as departure from nucleate boiling (DNB), crud-induced power shifts (CIPSs), and reactivity-insertion accidents (RIAs). By incorporating CTF into the multiphysics Virtual Environment for Reactor Application (VERA) core simulator software developed by CASL, CTF has become the primary means of providing fluid and fuel thermal feedback, as well as T/H figure-of-merits (FOMs) in large-scale reactor simulations. With the goal of solving industry challenge problems, CASL placed great emphasis on developing high-quality, high-performance, validated software tools that offer higher fidelity than what is currently possible with current industry methods. In support of this effort, CTF was developed from a research tool into an nuclear quality assurance (NQA-1)–compliant, production-level software tool that is capable of addressing the stated challenge problems and goals of CASL. This work presents a review of the major technological achievements that were realized in developing CTF over the past decade of the CASL program and presents an overview of the code solution approach and closure models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Economic Model for Estimation of GDP Losses in the MACCS Offsite Consequence Analysis Code

The MACCS (MELCOR Accident Consequence Code System) code is the U.S. Nuclear Regulatory Commission (NRC) tool used to perform probabilistic health and economic consequence assessments for atmospheric releases of radionuclides. It is also used by international organizations, both reactor owners and regulators. It is intended and most commonly used for hypothetical accidents that could potentially occur in the future rather than to evaluate past accidents or to provide emergency response during an ongoing accident. It is designed to support probabilistic risk and consequence analyses and is used by the NRC, U.S. nuclear licensees, the Department of Energy, and international vendors, licensees, and regulators. This report describes the modeling framework, implementation, verification, and benchmarking of a GDP-based model for economic losses that has recently been developed as an alternative to the original cost-based economic loss model in MACCS. The GDP-based model has its roots in a code developed by Sandia National Laboratories for the Department of Homeland Security to estimate short-term losses from natural and manmade accidents, called the Regional Economic Accounting analysis tool (REAcct). This model was adapted and modified for MACCS and is now called the Regional Disruption Economic Impact Model (RDEIM). It is based on input-output theory, which is widely used in economic modeling. It accounts for direct losses to a disrupted region affected by an accident, indirect losses to the national economy due to disruption of the supply chain, and induced losses from reduced spending by displaced workers. RDEIM differs from REAcct in its treatment and estimation of indirect loss multipliers, elimination of double counting associated with inter-industry trade in the affected area, and that it is designed to be used to estimate impacts for extended periods that can occur from a major nuclear reactor accident, such as the one that occurred at the Fukushima Daiichi site in Japan. Most input-output models do not account for economic adaptation and recovery, and in this regard RDEIM differs from its parent, REAcct, because it allows for a user-definable national recovery period. Implementation of a recovery period was one of several recommendations made by an independent peer review panel to ensure that RDEIM is state-of-practice. For this and several other reasons, RDEIM differs from REAcct. Both the original and the RDEIM economic loss models account for costs from evacuation and relocation, decontamination, depreciation, and condemnation. Where the original model accounts for an expected rate of return, based on the value of property, that is lost during interdiction, the RDEIM model instead accounts for losses of GDP based on the industrial sectors located within a county. The original model includes costs for disposal of crops and milk that the RDEIM model currently does not, but these costs tend to contribute insignificantly to the overall losses. This document discusses three verification exercises to demonstrate that the RDEIM model is implemented correctly in MACCS. It also describes a benchmark study at five nuclear power plants chosen to represent the spectrum of U.S. commercial sites. The benchmarks provide perspective on the expected differences between the RDEIM and the original cost-based economic loss models. The RDEIM model is shown to consistently predict larger losses than the original model, probably in part because it accounts for national losses by including indirect and induced losses; whereas, the original model only accounts for regional losses. Nonetheless, the RDEIM model predicts losses that are remarkably consistent with the original cost-based model, differing by 16% at most for the five sites combined with three source terms considered in this benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2016

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix and Polymer Matrix Composite Structures

Stochastic-based, discrete-event progressive damage simulations of ceramic-matrix composite and polymer matrix composite material structures have been enabled through the development of a unique multiscale modeling tool. This effort involves coupling three independently developed software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/ Life), and (3) the Abaqus finite element analysis (FEA) program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating unit cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC. Abaqus is used at the global scale to model the overall composite structure. An Abaqus user-defined material (UMAT) interface, referred to here as "FEAMAC/CARES," was developed that enables MAC/GMC and CARES/Life to operate seamlessly with the Abaqus FEA code. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events, which incrementally progress and lead to ultimate structural failure. This report describes the FEAMAC/CARES methodology and discusses examples that illustrate the performance of the tool. A comprehensive example problem, simulating the progressive damage of laminated ceramic matrix composites under various off-axis loading conditions and including a double notched tensile specimen geometry, is described in a separate report.

composite structures↗

DOE OSTI2024

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Chemistry↗

NASA NTRS1994

Utilizing inheritance in requirements engineering

The scope of this paper is the utilization of inheritance for requirements specification, i.e., the tasks of analyzing and modeling the domain, as well as forming and defining requirements. Our approach and the tool supporting it are named RETH (Requirements Engineering Through Hypertext). Actually, RETH uses a combination of various technologies, including object-oriented approaches and artificial intelligence (in particular frames). We do not attempt to exclude or replace formal representations, but try to complement and provide means for gradually developing them. Among others, RETH has been applied in the CERN (Conseil Europeen pour la Rechereche Nucleaire) Cortex project. While it would be impossible to explain this project in detail here, it should be sufficient to know that it deals with a generic distributed control system. Since this project is not finished yet, it is difficult to state its size precisely. In order to give an idea, its final goal is to substitute the many existing similar control systems at CERN by this generic approach. Currently, RETH is also tested using real-world requirements for the Pastel Mission Planning System at ESOC in Darmstadt. First, we outline how hypertext is integrated into a frame system in our approach. Moreover, the usefulness of inheritance is demonstrated as performed by the tool RETH. We then summarize our experiences of utilizing inheritance in the Cortex project. Lastly, RETH will be related to existing work.

Kaindl, Hermann↗

NASA NTRS2011

NASA Tech Briefs, November 2011

The topics include: 1) Flight Test Results from the Rake Airflow Gage Experiment on the F-15B; 2) Telemetry and Science Data Software System; 3) CropEx Web-Based Agricultural Monitoring and Decision Support; 4) High-Performance Data Analysis Tools for Sun-Earth Connection Missions; 5) Experiment in Onboard Synthetic Aperture Radar Data Processing; 6) Microfabrication of a High-Throughput Nanochannel Delivery/Filtration System; 7) Improved Design and Fabrication of Hydrated-Salt Pills; 8) Monolithic Flexure Pre-Stressed Ultrasonic Horns; 9) Cryogenic Quenching Process for Electronic Part Screening; 10) Broadband Via-Less Microwave Crossover Using Microstrip-CPW Transitions; 11) Wheel-Based Ice Sensors for Road Vehicles; 12) G-DYN Multibody Dynamics Engine; 13) Multibody Simulation Software Testbed for Small-Body Exploration and Sampling; 14) Propulsive Reaction Control System Model; 15) Licklider Transmission Protocol Implementation; 16) Core Recursive Hierarchical Image Segmentation; 17) Two-Stage Centrifugal Fan; 18) Combined Structural and Trajectory Control of Variable-Geometry Planetary Entry Systems; 19) Pressure Regulator With Internal Ejector Circulation Pump, Flow and Pressure Measurement Porting, and Fuel Cell System Integration Options; 20) Temperature-Sensitive Coating Sensor Based on Hematite; 21) Standardization of a Volumetric Displacement Measurement for Two-Body Abrasion Scratch Test Data Analysis; 22) Detection of Carbon Monoxide Using Polymer-Carbon Composite Films; 23) Substituted Quaternary Ammonium Salts Improve Low-Temperature Performance of Double-Layer Capacitors; 24) Sustainably Sourced, Thermally Resistant, Radiation Hard Biopolymer; 25) Integrated Lens Antennas for Multi-Pixel Receivers; 26) 180-GHz Interferometric Imager; 27) Maturation of Structural Health Management Systems for Solid Rocket Motors; 28) Validating Phasing and Geometry of Large Focal Plane Arrays; 29) Transverse Pupil Shifts for Adaptive Optics Non-Common Path Calibration; 30) Qualification of Fiber Optic Cables for Martian Extreme Temperature Environments; 31) Solid-State Spectral Light Source System; 32) Multiple-Event, Single-Photon Counting Imaging Sensor; 33) Surface Modeling to Support Small-Body Spacecraft Exploration and Proximity Operations; and 34) Achieving Exact and Constant Turnaround Ratio in a DDS-Based Coherent Transponder.

Source record↗

DOE OSTI2017

Accurate Holdup Calculations with Predictive Modeling & Data Integration

In facilities that process special nuclear material (SNM) it is important to account accurately for the fissile material that enters and leaves the plant. Although there are many stages and processes through which materials must be traced and measured, the focus of this project is material that is “held-up” in equipment, pipes, and ducts during normal operation and that can accumulate over time into significant quantities. Accurately estimating the holdup is essential for proper SNM accounting (vis-à-vis nuclear non-proliferation), criticality and radiation safety, waste management, and efficient plant operation. Usually it is not possible to directly measure the holdup quantity and location, so these must be inferred from measured radiation fields, primarily gamma and less frequently neutrons. Current methods to quantify holdup, i.e. Generalized Geometry Holdup (GGH), primarily rely on simple source configurations and crude radiation transport models aided by ad hoc correction factors. This project seeks an alternate method of performing measurement-based holdup calculations using a predictive model that employs state-of-the-art radiation transport codes capable of accurately simulating such situations. Inverse and data assimilation methods use the forward transport model to search for a source configuration that best matches the measured data and simultaneously provide an estimate of the level of confidence in the correctness of such configuration. In this work the holdup problem is re-interpreted as an inverse problem that is under-determined, hence may permit multiple solutions. A probabilistic approach is applied to solving the resulting inverse problem. This approach rates possible solutions according to their plausibility given the measurements and initial information. This is accomplished through the use of Bayes’ Theorem that resolves the issue of multiple solutions by giving an estimate of the probability of observing each possible solution. To use Bayes’ Theorem, one must have a model y(x) that maps the state variables x (the solution in this case) to the measurements y. In this case, the unknown state variables are the configuration and composition of the heldup SNM. The measurements are the detector readings. Thus, the natural model is neutral-particle radiation transport where a wealth of computational tools exists for performing these simulations accurately and efficiently. The combination of predictive model and Bayesian inference forms the Data Integration with Modeled Predictions (DIMP) method that serves as foundation for this project. The cost functional describing the model-to-data misfit is computed via a norm created by the inverse of the covariance matrix of the model parameters and responses. Since the model y(x) for the holdup problem is nonlinear, a nonlinear optimization on Q is conducted via Newton-type iterative methods to find the optimal values of the model parameters x. This project comprised a collaboration between NC State University (NCSU), the University of South Carolina (USC), and Oak Ridge National Laboratory (ORNL). The project was originally proposed in seven main tasks with an eighth contingency task to be performed if time and funding permitted; in fact time did not permit commencement of the contingency task and it was not performed. The remaining tasks involved holdup analysis with gamma detection strategies and separately with neutrons based on coincidence counting. Early in the project, and upon consultation with experts in coincidence counting it became evident that this approach is not viable for holdup applications and this task was replaced with an alternative, but valuable investigation that was carried out by the USC partner. Nevertheless, the experimental 4 measurements at ORNL of both gamma and neutron sources for the purpose of constructing Detector Response Functions (DRFs) with the associated uncertainties were indeed completed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2005

Using CFD as a Rocket Injector Design Tool: Recent Progress at Marshall Space Flight Center

New programs are forcing American propulsion system designers into unfamiliar territory. For instance, industry s answer to the cost and reliability goals set out by the Next Generation Launch Technology Program are engine concepts based on the Oxygen- Rich Staged Combustion Cycle. Historical injector design tools are not well suited for this new task. The empirical correlations do not apply directly to the injector concepts associated with the ORSC cycle. These legacy tools focus primarily on performance with environment evaluation a secondary objective. Additionally, the environmental capability of these tools is usually one-dimensional while the actual environments are at least two- and often three-dimensional. CFD has the potential to calculate performance and multi-dimensional environments but its use in the injector design process has been retarded by long solution turnaround times and insufficient demonstrated accuracy. This paper has documented the parallel paths of program support and technology development currently employed at Marshall Space Flight Center in an effort to move CFD to the forefront of injector design. MSFC has established a long-term goal for use of CFD for combustion devices design. The work on injector design is the heart of that vision and the Combustion Devices CFD Simulation Capability Roadmap that focuses the vision. The SRL concept, combining solution fidelity, robustness and accuracy, has been established as a quantitative gauge of current and desired capability. Three examples of current injector analysis for program support have been presented and discussed. These examples are used to establish the current capability at MSFC for these problems. Shortcomings identified from this experience are being used as inputs to the Roadmap process. The SRL evaluation identified lack of demonstrated solution accuracy as a major issue. Accordingly, the MSFC view of code validation and current MSFC-funded validation efforts were discussed in some detail. The objectives of each effort were noted. Issues relative to code validation for injector design were discussed in some detail. The requirement for CFD support during the design of the experiment was noted and discussed in terms of instrumentation placement and experimental rig uncertainty. In conclusion, MSFC has made significant progress in the last two years in advancing CFD toward the goal of application to injector design. A parallel effort focused on program support and technology development via the SCIT Task have enabled the progress.

Tucker, Kevin↗

NASA NTRS1991

SSSFD manipulator engineering using statistical experiment design techniques

The Satellite Servicer System Flight Demonstration (SSSFD) program is a series of Shuttle flights designed to verify major on-orbit satellite servicing capabilities, such as rendezvous and docking of free flyers, Orbital Replacement Unit (ORU) exchange, and fluid transfer. A major part of this system is the manipulator system that will perform the ORU exchange. The manipulator must possess adequate toolplate dexterity to maneuver a variety of EVA-type tools into position to interface with ORU fasteners, connectors, latches, and handles on the satellite, and to move workpieces and ORUs through 6 degree of freedom (dof) space from the Target Vehicle (TV) to the Support Module (SM) and back. Two cost efficient tools were combined to perform a study of robot manipulator design parameters. These tools are graphical computer simulations and Taguchi Design of Experiment methods. Using a graphics platform, an off-the-shelf robot simulation software package, and an experiment designed with Taguchi's approach, the sensitivities of various manipulator kinematic design parameters to performance characteristics are determined with minimal cost.

Barnes, John↗

DOE OSTI2016

Coupling the System Analysis Module with SAS4A/SASSYS-1

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced reactors, with an emphasis on sodium fast reactors. SAS4A/SASSYS-1 has been under development and in active use for nearly forty-five years, and is currently maintained by the U.S. Department of Energy under the Office of Advanced Reactor Technology. Although SAS4A/SASSYS-1 contains a very capable primary and intermediate system modeling component, PRIMAR-4, it also has some shortcomings: outdated data management and code structure makes extension of the PRIMAR-4 module somewhat difficult. The user input format for PRIMAR-4 also limits the number of volumes and segments that can be used to describe a given system. The System Analysis Module (SAM) is a fairly new code development effort being carried out under the U.S. DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM is being developed with advanced physical models, numerical methods, and software engineering practices; however, it is currently somewhat limited in the system components and phenomena that can be represented. For example, component models for electromagnetic pumps and multi-layer stratified volumes have not yet been developed. Nor is there support for a balance of plant model. Similarly, system-level phenomena such as control-rod driveline expansion and vessel elongation are not represented. This report documents fiscal year 2016 work that was carried out to couple the transient safety analysis capabilities of SAS4A/SASSYS-1 with the system modeling capabilities of SAM under the joint support of the ART and NEAMS programs. The coupling effort was successful and is demonstrated by evaluating an unprotected loss of flow transient for the Advanced Burner Test Reactor (ABTR) design. There are differences between the stand-alone SAS4A/SASSYS-1 simulations and the coupled SAS/SAM simulations, but these are mainly attributed to the limited maturity of the SAM development effort. The severe accident modeling capabilities in SAS4A/SASSYS-1 (sodium boiling, fuel melting and relocation) will continue to play a vital role for a long time. Therefore, the SAS4A/SASSYS-1 modernization effort should remain a high priority task under the ART program to ensure continued participation in domestic and international SFR safety collaborations and design optimizations. On the other hand, SAM provides an advanced system analysis tool, with improved numerical solution schemes, data management, code flexibility, and accuracy. SAM is still in early stages of development and will require continued support from NEAMS to fulfill its potential and to mature into a production tool for advanced reactor safety analysis. The effort to couple SAS4A/SASSYS-1 and SAM is the first step on the integration of these modeling capabilities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗