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At least 199 records · Page 11

Implementing Ordinary Differential Equation Solvers in Rust Programming Language for Modeling Vehicle Powertrain Systems: Preprint

Efficient and accurate ordinary differential equation (ODE) solvers are necessary for powertrain and vehicle dynamics modeling. However, current commercial ODE solvers can be financially prohibitive, leading to a need for accessible, effective, open-source ODE solvers designed for powertrain modeling. Rust is a compiled programming language that has the potential to be used for fast and easy-to-use powertrain models, given its exceptional computational performance, robust package ecosystem, and short time required for modelers to become proficient. However, of the three commonly used (>3,000 downloads) packages in Rust with ODE solver capabilities, only one has more than four numerical methods implemented, and none are designed specifically for modeling physical systems. Therefore, the goal of the Differential Equation System Solver (DESS) was to implement accurate ODE solvers in Rust designed for the component-based problems often seen in powertrain modeling. DESS is a text-based software package that provides a flexible framework for building and solving systems of ODEs. This allows DESS to be included as a dependency for automotive powertrain models that require a variety of solvers and solver configurations. Seven explicit ODE solver methods have been implemented in DESS: Euler’s, Heun’s, midpoint, Ralston’s, classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These represent five fixed-step methods and two adaptive-step methods. This paper shows that the solver implementations increase accuracy and computational efficiency compared to Euler's method when modeling a system of three thermal masses in Rust. DESS also includes features designed for modeling component-based physical systems. Users can define relationships between nodes in their system, which the package then translates into a system of equations, leading to simpler and more intuitive code. In the case of a three-thermal-mass system, the user can specify node thermal properties (e.g., thermal capacitance), how nodes are interconnected, and thermal conductance between nodes rather than providing a system of equations. The core contribution from this work is an open-source, text-based Rust package with ODE solvers for automotive powertrain modeling to support cost-free, fast, and accurate simulation.

ADVANCED PROPULSION SYSTEMS↗

The McDonald Accelerating Stars Survey (MASS): White Dwarf Companions Accelerating the Sun-like Stars 12 Psc and HD 159062

We present the discovery of a white dwarf companion to the G1 V star 12 Psc found as part of a Keck adaptive optics imaging survey of long-term accelerating stars from the McDonald Observatory Planet Search Program. Twenty years of precise radial-velocity monitoring of 12 Psc with the Tull Spectrograph at the Harlan J. Smith telescope reveals a moderate radial acceleration (≈10 m s{sup −1} yr {sup −1}), which together with relative astrometry from Keck/NIRC2 and the astrometric acceleration between Hipparcos and Gaia DR2 yields a dynamical mass of M {sub B} = 0.605{sub −0.022}{sup +0.021} M {sub ⊙} for 12 Psc B, a semimajor axis of 40{sub −4}{sup +2} au, and an eccentricity of 0.84 ± 0.08. We also report an updated orbital fit of the white dwarf companion to the metal-poor (but barium-rich) G9 V dwarf HD 159062 based on new radial-velocity observations from the High-Resolution Spectrograph at the Hobby–Eberly Telescope and astrometry from Keck/NIRC2. A joint fit of the available relative astrometry, radial velocities, and tangential astrometric acceleration yields a dynamical mass of M {sub B} = 0.609{sub −0.011}{sup +0.010} M {sub ⊙} for HD 159062 B, a semimajor axis of 60{sub −7}{sup +5} au, and preference for circular orbits (e < 0.42 at 95% confidence). 12 Psc B and HD 159062 B join a small list of resolved Sirius-like benchmark white dwarfs with precise dynamical mass measurements which serve as valuable tests of white dwarf mass–radius cooling models and probes of AGB wind accretion onto their main-sequence companions.

47 OTHER INSTRUMENTATION↗

Development and Flight Testing of a Neural Network Based Flight Control System on the NF-15B Aircraft

The Intelligent Flight Control System (IFCS) project at the NASA Dryden Flight Research Center, Edwards AFB, CA, has been investigating the use of neural network based adaptive control on a unique NF-15B test aircraft. The IFCS neural network is a software processor that stores measured aircraft response information to dynamically alter flight control gains. In 2006, the neural network was engaged and allowed to learn in real time to dynamically alter the aircraft handling qualities characteristics in the presence of actual aerodynamic failure conditions injected into the aircraft through the flight control system. The use of neural network and similar adaptive technologies in the design of highly fault and damage tolerant flight control systems shows promise in making future aircraft far more survivable than current technology allows. This paper will present the results of the IFCS flight test program conducted at the NASA Dryden Flight Research Center in 2006, with emphasis on challenges encountered and lessons learned.

Bomben, Craig R.↗

A design philosophy for multi-layer neural networks with applications to robot control

A system is proposed which receives input information from many sensors that may have diverse scaling, dimension, and data representations. The proposed system tolerates sensory information with faults. The proposed self-adaptive processing technique has great promise in integrating the techniques of artificial intelligence and neural networks in an attempt to build a more intelligent computing environment. The proposed architecture can provide a detailed decision tree based on the input information, information stored in a long-term memory, and the adapted rule-based knowledge. A mathematical model for analysis will be obtained to validate the cited hypotheses. An extensive software program will be developed to simulate a typical example of pattern recognition problem. It is shown that the proposed model displays attention, expectation, spatio-temporal, and predictory behavior which are specific to the human brain. The anticipated results of this research project are: (1) creation of a new dynamic neural network structure, and (2) applications to and comparison with conventional multi-layer neural network structures. The anticipated benefits from this research are vast. The model can be used in a neuro-computer architecture as a building block which can perform complicated, nonlinear, time-varying mapping from a multitude of input excitory classes to an output or decision environment. It can be used for coordinating different sensory inputs and past experience of a dynamic system and actuating signals. The commercial applications of this project can be the creation of a special-purpose neuro-computer hardware which can be used in spatio-temporal pattern recognitions in such areas as air defense systems, e.g., target tracking, and recognition. Potential robotics-related applications are trajectory planning, inverse dynamics computations, hierarchical control, task-oriented control, and collision avoidance.

Vadiee, Nader↗

Configurable Multi-Purpose Processor

Advancements in technology have allowed the miniaturization of systems used in aerospace vehicles. This technology is driven by the need for next-generation systems that provide reliable, responsive, and cost-effective range operations while providing increased capabilities such as simultaneous mission support, increased launch trajectories, improved launch, and landing opportunities, etc. Leveraging the newest technologies, the command and telemetry processor (CTP) concept provides for a compact, flexible, and integrated solution for flight command and telemetry systems and range systems. The CTP is a relatively small circuit board that serves as a processing platform for high dynamic, high vibration environments. The CTP can be reconfigured and reprogrammed, allowing it to be adapted for many different applications. The design is centered around a configurable field-programmable gate array (FPGA) device that contains numerous logic cells that can be used to implement traditional integrated circuits. The FPGA contains two PowerPC processors running the Vx-Works real-time operating system and are used to execute software programs specific to each application. The CTP was designed and developed specifically to provide telemetry functions; namely, the command processing, telemetry processing, and GPS metric tracking of a flight vehicle. However, it can be used as a general-purpose processor board to perform numerous functions implemented in either hardware or software using the FPGA s processors and/or logic cells. Functionally, the CTP was designed for range safety applications where it would ultimately become part of a vehicle s flight termination system. Consequently, the major functions of the CTP are to perform the forward link command processing, GPS metric tracking, return link telemetry data processing, error detection and correction, data encryption/ decryption, and initiate flight termination action commands. Also, the CTP had to be designed to survive and operate in a launch environment. Additionally, the CTP was designed to interface with the WFF (Wallops Flight Facility) custom-designed transceiver board which is used in the Low Cost TDRSS Transceiver (LCT2) also developed by WFF. The LCT2 s transceiver board demodulates commands received from the ground via the forward link and sends them to the CTP, where they are processed. The CTP inputs and processes data from the inertial measurement unit (IMU) and the GPS receiver board, generates status data, and then sends the data to the transceiver board where it is modulated and sent to the ground via the return link. Overall, the CTP has combined processing with the ability to interface to a GPS receiver, an IMU, and a pulse code modulation (PCM) communication link, while providing the capability to support common interfaces including Ethernet and serial interfaces boarding a relatively small-sized, lightweight package.

Valencia, J. Emilio↗

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗

Optimal Coordination of Distributed Energy Resources Using Deep Deterministic Policy Gradient

Recent studies showed that reinforcement learning (RL) is a promising approach for coordination and control of distributed energy resources (DER) under uncertainties. Many existing RL approaches, including Q-learning and approximate dynamic programming, are based on lookup table methods, which become inefficient when the problem size is large and infeasible when continuous states and actions are involved. In addition, when modeling battery energy storage system (BESS), the loss of life is not reasonably considered into the decision-making process. This paper proposes an innovative deep RL method for DER coordination considering BESS degradation. The proposed deep RL is designed based on an adaptive actor-critic architecture and employs an off-policy deterministic policy gradient method for determining the dispatch operation that minimizes the operation cost and BESS life loss. Case studies were performed to validate the proposed method and demonstrate the effects of incorporating degradation models into control design.

Das, Avijit↗

Usability and Optimization Improvements in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to MOOSE’s broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. Such improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work described in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities were implemented in the same order as they are covered in this report: multiple nonlinear systems in the same input file, implementation of generic field transfers and other transfer system enhancements, support for stateful material property redistribution for adaptivity and distributed meshes, and dynamic linking and loading of individually compiled applications. These four additions are fundamental capabilities that will be leveraged by many NEAMS applications.

97 MATHEMATICS AND COMPUTING↗

A systems engineering management approach to resource management applications

The author presents a program management response to the following question: How can the traditional practice of systems engineering management, including requirements specification, be adapted, enhanced, or modified to build future planning and scheduling systems for effective operations? The systems engineering management process, as traditionally practiced, is examined. Extensible resource management systems are discussed. It is concluded that extensible systems are a partial solution to problems presented by requirements that are incomplete, partially immeasurable, and often dynamic. There are positive indications that resource management systems have been characterized and modeled sufficiently to allow their implementation as extensible systems.

Hornstein, Rhoda Shaller↗

Real-time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter-vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop-and-go driving patterns. Here, by applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real-time on-vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

42 ENGINEERING↗

Concurrent extensions to the FORTRAN language for parallel programming of computational fluid dynamics algorithms

Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.

Weeks, Cindy Lou↗

Euler Technology Assessment for Preliminary Aircraft Design: Compressibility Predictions by Employing the Cartesian Unstructured Grid SPLITFLOW Code

The objective of the second phase of the Euler Technology Assessment program was to evaluate the ability of Euler computational fluid dynamics codes to predict compressible flow effects over a generic fighter wind tunnel model. This portion of the study was conducted by Lockheed Martin Tactical Aircraft Systems, using an in-house Cartesian-grid code called SPLITFLOW. The Cartesian grid technique offers several advantages, including ease of volume grid generation and reduced number of cells compared to other grid schemes. SPLITFLOW also includes grid adaption of the volume grid during the solution to resolve high-gradient regions. The SPLITFLOW code predictions of configuration forces and moments are shown to be adequate for preliminary design, including predictions of sideslip effects and the effects of geometry variations at low and high angles-of-attack. The transonic pressure prediction capabilities of SPLITFLOW are shown to be improved over subsonic comparisons. The time required to generate the results from initial surface data is on the order of several hours, including grid generation, which is compatible with the needs of the design environment.

Finley, Dennis B.↗

A Partitioned - Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a platform for multiscale modeling of composites which can perform analysis of materials with any arbitrary number of length scales. The platform supports modularity, scalability, and interoperability using recursive procedures and data structures. A Macro solver driven parallelization scheme often limits the capability of NASMAT to scale as it has access to limited memory and number of cores (often one core/thread) and often forces to implement macro solver specific changes to the platform. In this work, a partitioned task-parallel approach is adopted, where the parallelization strategy adopted for NASMAT is independent of the macro solver and the computational resources are managed independently. The programming architecture takes into account the hierarchy of multiple scales (task-dependence) and the heterogeneous nature (dynamic load balancing) of computation through implementation of a hierarchy-informed task parallel model. The partitioned nature of the framework further extends the “plug and play” capability of NASMAT. preCICE, an open-source library for coupling multiphysics solver in a partitioned manner, is adopted to integrate NASMAT with an external macro solver by implementing a NASMAT adapter for preCICE. Speedup and scalability of the framework is studied for micromechanical models of varying size.

task-parallel↗

Closed-Cycle Engine Program Used to Study Brayton Power Conversion

One form of power conversion under consideration in NASA Glenn Research Center's Thermal Energy Conversion Branch is the closed-Brayton-cycle engine. In the tens-of-kilowatts to multimegawatt class, the Brayton engine lends itself to potential space nuclear power applications such as electric propulsion or surface power. The Thermal Energy Conversion Branch has most recently concentrated its Brayton studies on electric propulsion for Prometheus. One piece of software used for evaluating such designs over a limited tradeoff space has been the Closed Cycle Engine Program (CCEP). The CCEP originated in the mid-1980s from a Fortran aircraft engine code known as the Navy/NASA Engine Program (NNEP). Components such as a solar collector, heat exchangers, ducting, a pumped-loop radiator, a nuclear heat source, and radial turbomachinery were added to NNEP, transforming it into a high-fidelity design and performance tool for closed-Brayton-cycle power conversion and heat rejection. CCEP was used in the 1990s in conjunction with the Solar Dynamic Ground Test Demonstration conducted at Glenn. Over the past year, updates were made to CCEP to adapt it for an electric propulsion application. The pumped-loop radiator coolant can now be n-heptane, water, or sodium-potassium (NaK); liquid-metal pump design tables were added to accommodate the NaK fluid. For the reactor and shield, a user can now elect to calculate a higher fidelity mass estimate. In addition, helium-xenon working-fluid properties were recalculated and updated.

Johnson, Paul K.↗

AthenaK: A Performance-portable Version of the Athena++ Adaptive Mesh Refinement Framework

We describe AthenaK: a new implementation of the Athena++ block-based adaptive mesh refinement framework using the Kokkos programming model. Finite volume methods for Newtonian, special relativistic, and general relativistic (GR) hydrodynamics and magnetohydrodynamics (MHD), and GR-radiation hydrodynamics and MHD, as well as a module for evolving Lagrangian tracer or charged test particles (e.g., cosmic rays) are implemented using the framework. In two companion papers, we describe (1) a new solver for the Einstein equations based on the Z4c formalism, and (2) a GRMHD solver in dynamical spacetimes also implemented using the framework, enabling new applications in numerical relativity. By adopting Kokkos, the code can be run on virtually any hardware, including CPUs, GPUs from multiple vendors, and emerging Advanced RISC Machine processors. AthenaK shows excellent performance and weak scaling, achieving over 1 billion cell updates per second for hydrodynamics in three dimensions on a single NVIDIA Grace Hopper processor. It does this with a typical parallel efficiency of 80% on 65,536 AMD GPUs on the OLCF Frontier system. Such performance portability enables AthenaK to leverage modern exascale computing systems for challenging applications in astrophysical fluid dynamics, numerical relativity, and multimessenger astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗

(abstract) Overview of NASA's Adaptive Structures Program

NASA's research program in Adaptive Structures was initiated seven years ago to provide the technology required for large (20-50 meters in dimension) precision (submicron) structures for observations from space. The current approach of designing thermally stable passive structures cannot meet the requirements and moreover the systems cannot be validated by ground tests. Adaptive Structures provides the capability to adjust the quasistatic dimensions of the structures, preload joints, add active damping, and provide the actuation forces necessary to attenuate the undesired dynamic motions. The technology is applicable to space platforms with various pointing instruments as well as for microspacecraft. This technology has been incorporated as part of a small Active Fold Mirror on the Wide Field Planetary Camera to be flown within the year to correct the optical errors in the Hubble Telescope. Highlights of NASA's Adaptive Structures research and applications will be presented along with future technology and research requirements for both small inexpensive spacecraft and large precision systems.

adaptive↗

Improved method for transonic airfoil design-by-optimization

An improved method for use of optimization techniques in transonic airfoil design is demonstrated. FLO6QNM incorporates a modified quasi-Newton optimization package, and is shown to be more reliable and efficient than the method developed previously at NASA-Ames, which used the COPES/CONMIN optimization program. The design codes are compared on a series of test cases with known solutions, and the effects of problem scaling, proximity of initial point to solution, and objective function precision are studied. In contrast to the older method, well-converged solutions are shown to be attainable in the context of engineering design using computational fluid dynamics tools, a new result. The improvements are due to better performance by the optimization routine and to the use of problem-adaptive finite difference step sizes for gradient evaluation.

Kennelly, R. A., Jr.↗

MultiSector Dynamics: 2023 Inaugural Workshop Report

Preface The MultiSector Dynamics (MSD) Community of Practice (CoP) hosted an inaugural workshop on October 3-5, 2023 at the University of California, Davis, to bring together members of the MSD community of practice to advance understanding of the co-evolution of human and natural systems, and to build the next generation of tools that bridge sectors, scales, and systems to realize a more resilient and equitable future. The theme of the workshop was "Advancing Complex Adaptive Human-Earth Systems Science in a World of Interconnected Risks". This document outlines the motivation for the workshop, its goals and objectives, the application process, the agenda, overviews of the training sessions offered to the workshop participants and a summary of each breakout session. The MSD workshop report further discusses the feedback from workshop participants and presents some reflections and next steps. The MSD Workshop organizers thank the DOE Office of Science, Earth and Environmental System Modeling, MultiSector Dynamics program area for financial support of its activities through the Integrated Multisector Multiscale Modeling (IM3) project. For more information related to the broader DOE MultiSector Dynamics Program please see https://climatemodeling.science.energy.gov/program-area/multisector-dynamics. D.L.M. and C.M.B. acknowledge support from the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (ORNL), managed by UT-Battelle, LLC, for the US Department of Energy (DOE). Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither theUnited States Government nor any agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, complete- ness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial products, process, or service by trade name,trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. Pacific Northwest National Laboratory operated by Battelle for the United States Department of Energy Available from:Office of Scientific and Technical Information http://www.OSTI.gov multisectordynamics.org This work is made available under the terms of the Creative Commons Attribution- NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommons.org/licenses/by-nc/4 Suggested citation: Monier, E., Reed, P.M., Vernon, C.R., Hadjimichael, A., Brelsford, C.M., Burleyson, C.B., Dyreson, A.R., Fletcher, S.M., Giang, A., Gupta, R.S., Jackson, N.D., Jones, A.D., Lamontagne, J.R., McCollum, D.L., Morris, J.F., Moss, R.H., Peng, W., Saari, R.K., Srikrishnan, V., Szinai, J.K., Yoon, J. (2024) MultiSector Dynamics: 2023 Inaugural Workshop Report. MSD-LIVE Data Repository. doi:10.57931/2371710.

Monier, Erwan↗