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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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The Balloon-Borne Ultraviolet Stellar Spectrometer (BUSS) Science Data Docummutation Program (BAPS48) is a pulse code modulation docummutation program that will format the BUSS science data contained on a one inch PCM tracking tape into a seven track serial bit stream formatted digital tape.
Key components of CEED software development involve fast finite element operator storage and evaluation, architecture optimizations, performant algorithms for all orders, global kernels for finite element operators, efficient use of the memory sub-system, optimal data locality and motion, enhanced scalability and parallelism, and fast tensor contractions. As ultimate goals of the project, CEED is exploring and identifying the best algorithms for the full range of discretizations and applying algorithmic and software development to support ECP applications’ needs. In this milestone, we initiated the development and implementation of a common CEED API consisting of two main components: low-level and high-level APIs. We accomplished the goal of having the low-level component ready for the release of CEED v1.0 in the next quarter, see CEED-MS13. In this report we also provide a highlight from CEED’s integration with the MARBL app and the corresponding Laghos miniapp. A main theme in this work has been the systematic transition of advanced algorithms, developed and tested in Laghos, to the large-scale multi-physics settings of the MARBL code. The low-level CEED API provides a set of FE kernels and components for writing new low-level kernels. Examples include: vector and sparse linear algebra, element matrix assembly over a batch of elements, partial assembly and action for efficient high-order operators like mass, diffusion, advection, etc. The main goal of the low-level API is to establish the basis for the high-level API. Also, identifying such low-level kernels and providing a reference implementation for them serves as the basis for collaboration with vendors and STs. Another goal for the low-level API is to make it easy for applications with their own discretization infrastructure, who do not want to switch directly to using the high-level CEED API, to still evaluate and use the core operations provided by the low-level API. One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. Thus, another important question we tried to address while developing the low-level API is: is it possible to abstract out in a natural and efficient way the different implementations and data structures that arise when dealing with various computational device types: CPUs, GPUs, etc. Fully answering this question is beyond the scope of this particular milestone, since that requires longer time as we develop and expand the devices we support. The future high-level API will be the frontend provided by CEED consisting of high-level abstractions such as meshes, finite element spaces and solutions, bilinear forms, solvers, etc. At this high-level, an important aspect of the API will be to provide a uniform abstraction layer for writing code in a portable manner. To achieve that, we plan to utilize the MPI programming model combined with a device abstraction layer (DAL) for finite element computations that we will develop. The DAL will serve as the bridge between the low- and the high-level APIs, allowing a variety of programming models to be used for the low-level kernel implementations. The software artifacts delivered as part of this milestone include an initial CEED API software implementation (libCEED) provided through the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q1 of FY18, including: the Nek5000 v17.0 MFEM v3.3.2 and PETSc v3.8 releases, collaborations with ECP/ST and SciDAC projects, the inaugural Nek5000 hackathon and various outreach activities.
The requirements for United States nuclear power plants to maintain a large onsite physical security force contribute to their large operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability Program Physical Security Pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. This pathway will analyze and minimize the conservatisms built into current security postures in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within this pathway has successfully developed a dynamic force-on-force (FOF) modeling framework using various computer simulation tools and integrated them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an overview of lessons learned in applying a dynamic computational framework that links results from a commercially available FOF simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework. Previous reports described how a user could integrate their plant-specific FOF models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as Computer Aided Fault Tree Analysis System or Systems Analysis Programs for Hands-on Integrated Reliability Evaluations, and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance of the use of the framework. Such an assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants. NOTE: The work performed in this report is based on a generic EMRALD model with actual plant data used for the analysis. However, only the generic model and general results of the analysis are in the report. No plant’s sensitive information is discussed in this report. The discussion shows examples of insights that can be obtained from the MASS-DEF methodology.
The piping in a liquid rocket can assume complex configurations due to multiple tanks, multiple engines, and structures that must be piped around. The capability to handle some of these complex configurations have been incorporated into the SSFREQ code. The capability to modify the input on line has been implemented. The configurations allowed include multiple tanks, multiple engines, the splitting of a pipe into equal segments going to different (or the same) engines. This program will handle the following type elements: straight pipes, bends, inline accumulators, tuned stub accumulators, Helmholtz resonators, parallel resonators, pumps, split pipes, multiple tanks, and multiple engines.
What is UME? UME extracts an important computational kernel from a large computational physics application, which is based on an unstructured mesh representation. The memory layout, indexing, data management, and communication patterns are as close to the original application as possible. The original application is a long-lived Fortran program, with ~750K source lines of code (sloc). UME is a C++17 implementation of a zone gradient operator, with about ~3K sloc.
In order to conservatively apply burnup credit in spent fuel pool criticality safety analyses, Westinghouse has developed a software tool, ISOCRIT, for generating depletion isotopics. This tool is used to create isotopics data based on specific reactor input parameters, such as design basis assembly type; bounding power/burnup profiles; reactor specific moderator temperature profiles; pellet percent theoretical density; burnable absorbers, axial blanket regions, and bounding ppm boron concentration. ISOCRIT generates burnup dependent isotopics using PARAGON; Westinghouse's state-of-the-art and licensed lattice physics code. Generation of isotopics and passing the data to the subsequent 3D KENO calculations are performed in an automated fashion, thus reducing the chance for human error. Furthermore, ISOCRIT provides the means for responding to any customer request regarding re-analysis due to changed parameters (e.g., power uprate, exit temperature changes, etc.) with a quick turnaround.
Aperiodic variability is a characteristic feature of young stars, massive stars, and active galactic nuclei. With the recent proliferation of time-domain surveys, it is increasingly essential to develop methods to quantify and analyze aperiodic variability. We develop three timescale metrics that have been little used in astronomy—Δm-Δt plots, peak-finding, and Gaussian process regression—and present simulations comparing their effectiveness across a range of aperiodic light curve shapes, characteristic timescales, observing cadences, and signal to noise ratios. We find that Gaussian process regression is easily confused by noise and by irregular sampling, even when the model being fit reflects the process underlying the light curve, but that Δm-Δt plots and peak-finding can coarsely characterize timescales across a broad region of parameter space. We make public the software we used for our simulations, both in the spirit of open research and to allow others to carry out analogous simulations for their own observing programs.
Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo, and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.
The NEAMS IPSC's are developing multidimensional, multiphysics, multiscale simulation codes based on first principles that will be capable of predicting all aspects of current and future nuclear reactor systems. These new breeds of simulation codes will include rigorous verification, validation and uncertainty quantification checks to quantify the accuracy and quality of the simulation results. The resulting NEAMS IPSC simulation codes will be an invaluable tool in designing the next generation of Nuclear Reactors and also contribute to a more speedy process in the acquisition of licenses from the NRC for new Reactor designs. Due to the high resolution of the models, the complexity of the physics and the added computational resources to quantify the accuracy/quality of the results, the NEAMS IPSC codes will require large HPC resources to carry out the production simulation runs.
A simplified method is presented for computing the installation losses of aircraft gas turbine propulsion systems. The method has been programmed for use in computer aided conceptual aircraft design studies that cover a broad range of Mach numbers and altitudes. The items computed are: inlet size, pressure recovery, additive drag, subsonic spillage drag, bleed and bypass drags, auxiliary air systems drag, boundary-layer diverter drag, nozzle boattail drag, and the interference drag on the region adjacent to multiple nozzle installations. The methods for computing each of these installation effects are described and computer codes for the calculation of these effects are furnished. The results of these methods are compared with selected data for the F-5A and other aircraft. The computer program can be used with uninstalled engine performance information which is currently supplied by a cycle analysis program. The program, including comments, is about 600 FORTRAN statements long, and uses both theoretical and empirical techniques.
The input data and execution control statements for the ATLAS integrated structural analysis and design system are described. It is operational on the Control Data Corporation (CDC) 6600/CYBER computers in a batch mode or in a time-shared mode via interactive graphic or text terminals. ATLAS is a modular system of computer codes with common executive and data base management components. The system provides an extensive set of general-purpose technical programs with analytical capabilities including stiffness, stress, loads, mass, substructuring, strength design, unsteady aerodynamics, vibration, and flutter analyses. The sequence and mode of execution of selected program modules are controlled via a common user-oriented language.
The propagation of the charge-exchange plasma from an electrostatic ion thruster is crucial in determining the interaction of that plasma with the associated spacecraft. A model that describes this plasma and its propagation is described, together with a computer code based on this model. The structure and calling sequence of the code, named PLASIM, is described. An explanation of the program's input and output is included, together with samples of both. The code is written in ASNI Standard FORTRAN.
Theoretical studies of the electronic structure of metal clusters, in particular clusters of Group IIA and IIB atoms were conducted. Early in the project it became clear that electron correlation involving d orbitals plays a more important role in the binding of these clusters than had been previously anticipated. This necessitated that computer codes for calculating two electron integrals and for constructing the resulting CI Hamiltonions be replaced with newer, more efficient procedures. Program modification, interfacing and testing were performed. Results of both plans are reported.
The evolutionary process of combining analysis and optimization codes was traced with a view toward providing insight into the long term goal of developing the methodology for an integrated, multidisciplinary software system for the concurrent analysis and optimization of aerospace structures. It was traced along the lines of strength sizing, concurrent strength and flutter sizing, and general optimization to define a near-term goal for combining analysis and optimization codes. Development of a modular software system combining general-purpose, state-of-the-art, production-level analysis computer programs for structures, aerodynamics, and aeroelasticity with a state-of-the-art optimization program is required. Incorporation of a modular and flexible structural optimization software system into a state-of-the-art finite element analysis computer program will facilitate this effort. This effort results in the software system used that is controlled with a special-purpose language, communicates with a data management system, and is easily modified for adding new programs and capabilities. A 337 degree-of-freedom finite element model is used in verifying the accuracy of this system.
The propagation of the charge exchange plasma for an electrostatic ion thruster is crucial in determining the interaction of that plasma with the associated spacecraft. A model that describes this plasma and its propagation is described, together with a computer code based on this model. The structure and calling sequence of the code, named PLASIM, is described. An explanation of the program's input and output is included, together with samples of both. The code is written in ANSI Standard FORTRAN.
An investigation of the capability of two computer programs to simulate transonic and supersonic flows about representative fighter aircraft forebodies has been carried out for purpose of predicting flow fields in the vicinity of typical inlet locations. Each computer program is described as to its features and usage, and results are compared with comprehensive wind tunnel data. Although both computer codes were inviscid, results show that the gross aerodynamic effects of the forebody, with and without a wing, can be simulated fairly well. Further work is needed to include the effects of viscosity including vortex shedding.
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.
The piping in a liquid rocket can assume complex configurations due to multiple tanks, multiple engines, and structures that must be piped around. The capability to handle some of these complex configurations have been incorporated into the NYQUIST code. The capability to modify the input on line has been implemented. The configurations allowed include multiple tanks, multiple engines, and the splitting of a pipe into unequal segments going to different (or the same) engines. This program will handle the following type elements: straight pipes, bends, inline accumulators, tuned stub accumulators, Helmholtz resonators, parallel resonators, pumps, split pipes, multiple tanks, and multiple engines. The code is too large to compile as one program using Microsoft FORTRAN 5; therefore, the code was broken into two segments: NYQUIST1.FOR and NYQUIST2.FOR. These are compiled separately and then linked together. The final run code is not too large (approximately equals 344,000 bytes).