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At least 1,153 records · Page 64

Cantera Integration with the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS)

NASA Glenn Research Center (GRC) has recently developed a software package for modeling generic thermodynamic systems called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a library of building blocks that can be assembled to represent any thermodynamic system in the Simulink(Registered TradeMark) (The MathWorks, Inc.) environment. These elements, along with a Newton Raphson solver (also provided as part of the T-MATS package), enable users to create models of a wide variety of systems. The current version of T-MATS (v1.0.1) uses tabular data for providing information about a specific mixture of air, water (humidity), and hydrocarbon fuel in calculations of thermodynamic properties. The capabilities of T-MATS can be expanded by integrating it with the Cantera thermodynamic package. Cantera is an object-oriented analysis package that calculates thermodynamic solutions for any mixture defined by the user. Integration of Cantera with T-MATS extends the range of systems that may be modeled using the toolbox. In addition, the library of elements released with Cantera were developed using MATLAB native M-files, allowing for quicker prototyping of elements. This paper discusses how the new Cantera-based elements are created and provides examples for using T-MATS integrated with Cantera.

Systems Analysis↗

Cantera Integration with the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS)

NASA Glenn Research Center (GRC) has recently developed a software package for modeling generic thermodynamic systems called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a library of building blocks that can be assembled to represent any thermodynamic system in the Simulink (The MathWorks, Inc.) environment. These elements, along with a Newton Raphson solver (also provided as part of the T-MATS package), enable users to create models of a wide variety of systems. The current version of T-MATS (v1.0.1) uses tabular data for providing information about a specific mixture of air, water (humidity), and hydrocarbon fuel in calculations of thermodynamic properties. The capabilities of T-MATS can be expanded by integrating it with the Cantera thermodynamic package. Cantera is an object-oriented analysis package that calculates thermodynamic solutions for any mixture defined by the user. Integration of Cantera with T-MATS extends the range of systems that may be modeled using the toolbox. In addition, the library of elements released with Cantera were developed using MATLAB native M-files, allowing for quicker prototyping of elements. This paper discusses how the new Cantera-based elements are created and provides examples for using T-MATS integrated with Cantera.

Thermodynamics↗

Evaluating the Impact of Price-Responsive Load on Power Systems Using Integrated T&D Simulation

This paper explores the differences between simulating price-responsive load (PRL) interactions with power systems using integrated transmission and distribution (T&D) models and transmission-only (T-only) models. This analysis uses the Integrated Grid Modeling System (IGMS) software to capture 'ISO-to-appliance' simulations using a synthetic T&D model built on the PJM 5-Bus transmission network with multiple full-scale taxonomy feeders that include physics-based models of thousands of customers and PRLs. The results show important differences in the impacts of PRLs between integrated T&D and T-only models. Experiments with the synthetic integrated T&D dataset demonstrated that integrated T&D simulation revealed notably larger differences between the PRL and no-PRL cases for load, and prices compared to T-only simulation. Similarly, differences are observed between the price response of individual buildings and distribution feeders and the corresponding transmission bus in the integrated T&D simulations, which are difficult to capture in traditional T-only simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluating the Impact of Price-Responsive Load on Power Systems Using Integrated T&D Simulation: Preprint

This paper explores the advantages and challenges of simulating price-responsive load (PRL) interactions with large-scale power systems using integrated transmission and distribution (T&D) models. This analysis uses the Integrated Grid Modeling System (IGMS) software to capture 'ISO-to-appliance' simulations using a synthetic T&D model built on the PJM 5 Bus transmission network with multiple full-scale taxonomy feeders that include physics-based models of thousands of PRLs. The results show substantial differences in the impacts of PRLs between integrated T&D and transmission-only (T-only) models. Similarly differences are observed between the price response of individual distribution feeders and the corresponding transmission bus in the integrated T&D simulations, which cannot be captured in T-only simulations. Experiments include both traditional price responsive load reductions and price-driven load increases during low net demand periods driven by high daytime generation from distributed generation-based photovoltaics (DGPV).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Generating MCNP Input Files for Unstructured Mesh Geometries

Los Alamos National Laboratory's (LANL) Monte Carlo N-Particle (MCNP) transport code version 6 has the capability for tracking particles on unstructured mesh (UM) geometry models. The MCNP UM feature has been developed for performing calculations of complex geometry models. This capability tracks particles on hybrid geometries where finite element meshes are embedded into constructive solid geometry (CSG) cells. The MCNP UM feature was originally designed to read UM models created by Abaqus/CAE software suite. MCNP versions 6.2.0 and later can process UM models read from Abaqus input les or MCNPUM les converted from Abaqus input les. Sandia National Laboratory's Cubit Toolkit and other finite element analysis software packages may generate UM models and then convert these models into Abaqus input formats.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling Magnetic Properties in EZTB

A software module that calculates magnetic properties of a semiconducting material has been written for incorporation into, and execution within, the Easy (Modular) Tight-Binding (EZTB) software infrastructure. [EZTB is designed to model the electronic structures of semiconductor devices ranging from bulk semiconductors, to quantum wells, quantum wires, and quantum dots. EZTB implements an empirical tight-binding mathematical model of the underlying physics.] This module can model the effect of a magnetic field applied along any direction and does not require any adjustment of model parameters. The module has thus far been applied to study the performances of silicon-based quantum computers in the presence of magnetic fields and of miscut angles in quantum wells. The module is expected to assist experimentalists in fabricating a spin qubit in a Si/SiGe quantum dot. This software can be executed in almost any Unix operating system, utilizes parallel computing, can be run as a Web-portal application program. The module has been validated by comparison of its predictions with experimental data available in the literature.

Lee, Seungwon↗

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The development of the Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large complex systems engineering challenge being addressed in part by focusing on the specific subsystems handling of off-nominal mission and fault tolerance. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML), the Mission and Fault Management (M&FM) algorithms are crafted and vetted in specialized Integrated Development Teams composed of multiple development disciplines. NASA also has formed an M&FM team for addressing fault management early in the development lifecycle. This team has developed a dedicated Vehicle Management End-to-End Testbed (VMET) that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. The flexibility of VMET enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the algorithms utilizing actual subsystem models. The intent is to validate the algorithms and substantiate them with performance baselines for each of the vehicle subsystems in an independent platform exterior to flight software test processes. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test processes. Risk reduction is addressed by working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and detection and responses that can be tested in VMET and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM. The plan for VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗

Equivalent Test Bed in PSCAD and PSLF for Studying Advanced Power Systems Controller Performance

With increasing popularity of sustainable energy resources, research on power electronic-based renewable generation modeling is gaining impetus to enhance reliability of electric grids with high penetrations of renewable energy. A set of generic and public models for renewable energy are available in commercial positive sequence power system simulation software. However, advanced controller models applicable for renewable resources are typically not included in these tools. To ensure the integrity of the newly developed controller models for renewables in positive sequence simulators for large power systems, it is necessary to validate the dynamic performance of the proposed model with detailed electromagnetic models. This paper creates an equivalent test bed in PSCAD and PSLF for validating the performance of advanced controllers associated with renewable energy sources. To demonstrate the usefulness of the test-bed, a user-defined synthetic inertia (SI) controller model was developed in PSLF and validated through the proposed test bed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗

Simulation Software

Various NASA Small Business Innovation Research grants from Marshall Space Flight Center, Langley Research Center and Ames Research Center were used to develop the 'kernel' of COMCO's modeling and simulation software, the PHLEX finite element code. NASA needed it to model designs of flight vehicles; one of many customized commercial applications is UNISIM, a PHLEX-based code for analyzing underground flows in oil reservoirs for Texaco, Inc. COMCO's products simulate a computational mechanics problem, estimate the solution's error and produce the optimal hp-adapted mesh for the accuracy the user chooses. The system is also used as a research or training tool in universities and in mechanical design in industrial corporations.

Source record↗

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗

MCTrans++: a 0-D model for centrifugal mirrors

The centrifugal mirror confinement scheme incorporates supersonic rotation of a plasma into a magnetic mirror device. This concept has been shown experimentally to drastically decrease parallel losses and increase plasma stability as compared with prior axisymmetric mirrors. MCTrans++ is a dimensionless (0-D) scoping tool which rapidly models experimental operating points in the Centrifugal Mirror Fusion Experiment (CMFX) at the University of Maryland. In the low-collisionality regime, parallel losses can be modelled analytically. A confining potential is set up that is partially ambipolar and partially centrifugal. Due to the stabilizing effects of flow shear, the perpendicular losses can be modelled as classical. Radiation losses such as bremsstrahlung and cyclotron emission are taken into account. A neutrals model is included, and, in some circumstances, charge-exchange losses are found to exceed all other loss mechanisms. We use the SUNDIALS ARKODE library to solve the underlying equations of this model; the resulting software is suitable for scanning large parameter spaces, and can also be used to model time-dependent phenomena such as a capacitive discharge. MCTrans++ has been used to verify results from prior centrifugal mirrors, create an experimental plan for CMFX and find configurations for future reactor-scale fusion devices.

Schwartz, Nick R. (ORCID:0000000296846435)↗

Exhibit D modular design attitude control system study

A dynamically equivalent four body approximation of the NASTRAN finite element model supplied for hybrid deployable truss to support the digital computer simulation of the ten body model of the flexible space platform that incorporates the four body truss model were investigated. Coefficients for sensitivity of state variables of the linearized model of the three axes rotational dynamics of the prototype flexible spacecraft were generated with respect to the model's parameters. Software changes required to accommodate addition of another rigid body to the five body model of the rotational dynamics of the prototype flexible spacecraft were evaluated.

Chichester, F.↗

Graphical workstation capability for reliability modeling

In addition to computational capabilities, software tools for estimating the reliability of fault-tolerant digital computer systems must also provide a means of interfacing with the user. Described here is the new graphical interface capability of the hybrid automated reliability predictor (HARP), a software package that implements advanced reliability modeling techniques. The graphics oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault-tree gates, including sequence-dependency gates, or by a Markov chain. By using this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain, which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the graphical kernal system (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing stages.

Bavuso, Salvatore J.↗

SAO mission support software and data standards, version 1.0

This document defines the software developed by the SAO AXAF Mission Support (MS) Program and defines standards for the software development process and control of data products generated by the software. The SAO MS is tasked to develop and use software to perform a variety of functions in support of the AXAF mission. Software is developed by software engineers and scientists, and commercial off-the-shelf (COTS) software is used either directly or customized through the use of scripts to implement analysis procedures. Software controls real-time laboratory instruments, performs data archiving, displays data, and generates model predictions. Much software is used in the analysis of data to generate data products that are required by the AXAF project, for example, on-orbit mirror performance predictions or detailed characterization of the mirror reflection performance with energy.

Hsieh, P.↗

Centralized Planning for Multiple Exploratory Robots

A computer program automatically generates plans for a group of robotic vehicles (rovers) engaged in geological exploration of terrain. The program rapidly generates multiple command sequences that can be executed simultaneously by the rovers. Starting from a set of high-level goals, the program creates a sequence of commands for each rover while respecting hardware constraints and limitations on resources of each rover and of hardware (e.g., a radio communication terminal) shared by all the rovers. First, a separate model of each rover is loaded into a centralized planning subprogram. The centralized planning software uses the models of the rovers plus an iterative repair algorithm to resolve conflicts posed by demands for resources and by constraints associated with the all the rovers and the shared hardware. During repair, heuristics are used to make planning decisions that will result in solutions that will be better and will be found faster than would otherwise be possible. In particular, techniques from prior solutions of the multiple-traveling- salesmen problem are used as heuristics to generate plans in which the paths taken by the rovers to assigned scientific targets are shorter than they would otherwise be.

Estlin, Tara↗

Software forecasting as it is really done: A study of JPL software engineers

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

Griesel, Martha Ann↗

PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis

Abstract. This paper describes the new open-source framework PyFLEXTRKR (Python FLEXible object TRacKeR), a flexible atmospheric feature tracking software package with specific capabilities to track convective clouds from a variety of observations and model simulations. This software can track any atmospheric 2D objects and handle merging and splitting explicitly. The package has a collection of multi-object identification algorithms, scalable parallelization options, and has been optimized for large datasets including global high-resolution data. We demonstrate applications of PyFLEXTRKR on tracking individual deep convective cells and mesoscale convective systems from observations and model simulations ranging from large-eddy resolving (∼100s m) to mesoscale (∼10s km) resolutions. Visualization, post-processing, and statistical analysis tools are included in the package. New Lagrangian analyses of convective clouds produced by PyFLEXTRKR applicable to a wide range of datasets and scales facilitate advanced model evaluation and development efforts as well as scientific discovery.

54 ENVIRONMENTAL SCIENCES↗