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A matrix solution for the simulation of magnetic fields with ideal current loops
A matrix formulation is presented for describing axisymmetric magnetic field data with ideal current loops. A computer program written in APL is used to invert the matrix and hence to solve for the coil strengths which are used to represent the field data. Examples are given of the coil representation for (1) measured magnetic data, (2) refocusing fields, and (3) PPM focusing fields.
Space simulation in the next 20 years
This is a brief overview of logically expected advancements in the area of space simulation over the next twenty years. Current NASA Space Shuttle simulations will be upgraded to support more complex payload and on-orbit tasks. This includes the ability to integrate various remote ground facilities with a real time space mission simulator and an expanded use of efficient part-task simulations. Software compatibilities between simulators will increase and each simulator will have a more combined training and engineering role. Software development processors will be increasingly internetted to an integrated data processing system.
Propulsion system ground testing
The objective is to provide management visibility relative to the roles of simulation and propulsion system testing for future development programs through assessment of current propulsion related simulation capabilities and review of contributions from propulsion system test programs. The presentation is represented by viewgraphs.
Hybrid simulations of whistler waves generation and current closure by a pulsed tether in the ionosphere
The dynamic response of a magnetized collisionless plasma to an externally driven, finite size, sudden switch-on current source across the magnetic field has been studied using a two dimensional hybrid code. It was found that the predominant plasma response was the excitation of whistler waves and the formation of current closure by induced currents in the plasma. The results show that the current closure path consists of: (a) two antiparallel field-aligned current channels at the end of the imposed current sheet; and (b) a cross-field current region connecting these channels. The formation of the current closure path occured in the whistler timescale much shorter than that of MHD and the closure region expanded continuously in time. The current closure process was accompanied by significant energy loss due to whistler radiation.
A Three-Dimensional MHD Simulation of the Solar Wind for a Tilted-Dipole Magnetic Field on the Sun
Using a three-dimensional MHD model, we simulate the global steady-state structure of the solar corona and solar wind for a dipole magnetic field on the Sun inclined by 30 degrees to the solar rotation axis. This represents the solar conditions typical for a declining phase of solar cycle. The computations can extend from the coronal base out to 100-AU and at large heliospheric distances includes the effects of interstellar neutral hydrogen and their interaction with solar wind protons. The simulations can model the formation of corotating interaction regions and the heliospheric current sheet. The simulations are also capable of describing very strong rarefaction regions that include embedded sub-Alfvenic regions that form on the trailing edge of a fast flows.
Efficiency Benefits Using the Terminal Area Precision Scheduling and Spacing System
NASA has developed a capability for terminal area precision scheduling and spacing (TAPSS) to increase the use of fuel-efficient arrival procedures during periods of traffic congestion at a high-density airport. Sustained use of fuel-efficient procedures throughout the entire arrival phase of flight reduces overall fuel burn, greenhouse gas emissions and noise pollution. The TAPSS system is a 4D trajectory-based strategic planning and control tool that computes schedules and sequences for arrivals to facilitate optimal profile descents. This paper focuses on quantifying the efficiency benefits associated with using the TAPSS system, measured by reduction of level segments during aircraft descent and flight distance and time savings. The TAPSS system was tested in a series of human-in-the-loop simulations and compared to current procedures. Compared to the current use of the TMA system, simulation results indicate a reduction of total level segment distance by 50% and flight distance and time savings by 7% in the arrival portion of flight (~200 nm from the airport). The TAPSS system resulted in aircraft maintaining continuous descent operations longer and with more precision, both achieved under heavy traffic demand levels.
Application of the NASCAP Spacecraft Simulation Tool to Investigate Electrodynamic Tether Current Collection in LEO
Recent interest in using electrodynamic tethers (EDTs) for orbital maneuvering in Low Earth Orbit (LEO) has prompted the development of the Marshall ElectroDynamic Tether Orbit Propagator (MEDTOP) model. The model is comprised of several modules which address various aspects of EDT propulsion, including calculation of state vectors using a standard orbit propagator (e.g., J2), an atmospheric drag model, realistic ionospheric and magnetic field models, space weather effects, and tether librations. The natural electromotive force (EMF) attained during a radially-aligned conductive tether results in electrons flowing down the tether and accumulating on the lower-altitude spacecraft. The energy that drives this EMF is sourced from the orbital energy of the system; thus, EDTs are often proposed as de-orbiting systems. However, when the current is reversed using satellite charged particle sources, then propulsion is possible. One of the most difficult challenges of the modeling effort is to ascertain the equivalent circuit between the spacecraft and the ionospheric plasma. The present study investigates the use of the NASA Charging Analyzer Program (NASCAP) to calculate currents to and from the tethered satellites and the ionospheric plasma. NASCAP is a sophisticated set of computational tools to model the surface charging of three-dimensional (3D) spacecraft surfaces in a time-varying space environment. The model's surface is tessellated into a collection of facets, and NASCAP calculates currents and potentials for each one. Additionally, NASCAP provides for the construction of one or more nested grids to calculate space potential and time-varying electric fields. This provides for the capability to track individual particles orbits, to model charged particle wakes, and to incorporate external charged particle sources. With this study, we have developed a model of calculating currents incident onto an electrodynamic tethered satellite system, and first results are shown here.
Current Capabilities of AFRL’s Spacecraft Simulation Tool
Assessment of spacecraft integration issues is typically accomplished with a combination of numerical tools developed to simulate different regions with different key physics. For instance, a detailed study of spacecraft with an electric propulsion device requires a device model, a plume model, and a spacecraft charging model. AFRL’s in-house spacecraft simulation tool, TURF, is now capable of performing all of these calculations in one simulation. In addition, the plume simulation capability has been expanded significantly to improve speed and accuracy. Other upgrades in TURF include adaptive mesh refinement (AMR) and dynamic load balancing. All of these upgrades are covered in this paper by providing detailed descriptions or pointing to relevant references. This paper also presents three example simulations demonstrating its multi-physics multi-scale capability.
Multiphysics simulations of a steady-state lower hybrid current drive antenna for the FSNF
The Fusion Nuclear Science Facility (FNSF) is a proposed tokamak reactor with the mission to investigate operation of a fusion reactor in a nuclear environment. The high neutron fluence component of the FNSF mission requires steady-state operation for extremely long pulses (t_{pulse} ∼ months) at full power. Plasma sustainment and current drive will be critical components of a successful FNSF. COMSOL Multiphysics software is used for combined radiofrequency (RF) and thermal simulations of the lower hybrid current drive (LHCD) antenna system. These simu- lations consider the resistive RF losses in the antenna including realistic surface roughness and a range of potential materials. The thermal analysis adds volumetric nuclear heating, plasma heat flux on leading edges, and electromagnetic radiation from the plasma to the RF heating calculated by COMSOL. Additional neutronics calculations have been performed to determine the impact of these antenna designs on activated waste disposal for the materials considered. The simulations show that it is technically feasible to implement a fully-active multi-junction (FAM) rather than a passive-active multi-junction (PAM) style of antenna if the septum between adjacent waveguides is sufficiently wide and the thermal conductivity of the structural material is sufficiently high. The FAM has the benefit of higher achievable power density with respect to the PAM, which results in a more compact antenna with potentially lower impact on neutron shielding and tritium breeding. These considerations point to tungsten rather than steel as the preferred structural material in constructing the antenna.
A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility
This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.
A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility
This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.
ALTSched: Improved Scheduling for Time-domain Science with LSST
Abstract Telescope scheduling is the task of determining the best sequence of observations (pointings and filter choices) for a survey system. Because it is computationally intractable to optimize over all possible multiyear sequences of observations, schedulers use heuristics to pick the best observation at a given time. A greedy scheduler selects the next observation by choosing whichever one maximizes a scalar merit function, which serves as a proxy for the scientific goals of the telescope. This sort of bottom-up approach for scheduling is not guaranteed to produce a schedule for which the sum of merit over all observations is maximized. As an alternative to greedy schedulers, we introduce ALTS ched, which takes a top-down approach to scheduling. Instead of considering only the next observation, ALTS ched makes global decisions about which area of sky and which filter to observe in, and then refines these decisions into a sequence of observations taken along the meridian to minimize airmass. We implement ALTS ched for the Large Synoptic Survey Telescope (LSST) and show that it equals or outperforms the baseline greedy scheduler in essentially all quantitative performance metrics. Due to its simplicity, our implementation is considerably faster than O p S im , the simulated greedy scheduler currently used by the LSST Project: a full 10-yr survey can be simulated in 4 minutes, as opposed to tens of hours for O p S im . LSST’s hardware is fixed, so improving the scheduling algorithm is one of the only remaining ways to optimize LSST’s performance. We see ALTS ched as a prototype scheduler that gives a lower bound on the performance achievable by LSST.
Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing
This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.
Analysis of Sample Acquisition Dynamics Using Discrete Element Method
The analysis presented in this paper is conducted in the framework of the Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) project, currently under development at NASA Ames Research Center. OceanWATERS aims at designing a simulation environment which allows for testing autonomy of scientific lander missions to the icy moons of our solar system. Mainly focused on reproducing the end effector interaction with the inherent terrain, this paper introduces a novel discrete element method (DEM)-based approach to determine forces and torques acting on the lander’s scoop during the sample acquisition process. An accurate force feedback from the terrain on the scoop is required by fault-detection and autonomous decision-making algorithms to identify when the requested torque on the robotic arm’s joints exceeds the maximum available torque. Knowledge of the terrain force feedback significantly helps evaluating the arm’s links structural properties and properly selecting actuators for the joints. Models available in literature constitute a partial representation of the dynamics of the interaction. As an example, Balovnev derived an analytical expression of the vertical and horizontal force acting on a bucket while collecting a sample as a function of its geometry and velocity, soil parameters and reached depth. Although the model represents an adequate approximation of the two force components, it ignores the direction orthogonal to the scoop motion and neglects the torque. This work relies on DEM analysis to compensate for analytical models’ deficiencies and inaccuracies, i. e. provide force and torque 3D vectors, defined in the moving reference (body) frame attached to the scoop, at each instant of the sample collection process. Results from the first presented analysis relate to the specific OceanWATERS sampling strategy, which consists of collecting the sample through five consecutive passes with increasing depth, each pass following the same circularlinear- circular trajectory. Data is collected given a specific scoop design interacting with two types of bulk materials, which may characterize the surface of icy planetary bodies: snow and ice. Although specifically concerned with the OceanWATERS design, this first analysis provides the expected force trends for similar sampling strategies and allows to deduce phenomenological information about the general scooping process. In order to further instruct the community on the use of DEM tools as a solution to the sampling collection problem, two more analyses have been carried out, mainly focused on reducing the DEM computation time, which increases with a decrease in particle size. After running a set of identical simulations, where the only changing parameter is the size of the spherical particle, it is observed that the resulting force trajectories, starting from a given particle size, converge to the true trend. It is deducible that a further decrease in size yields negligible improvements in the accuracy, while it sensibly increases computation time. A final analysis aims at discussing limitations of approximating bulk material particles having a complex shape, e. g. ice fragments, with spheres, by comparing force trends resulting in the two cases for the same simulation scenario.
Developments in the computation of turbulent boundary layers
Computational techniques applicable to turbulent boundary layers are classified into solutions of Reynolds-averaged equations, in which all the effects of the turbulence are modelled, and solutions of three-dimensional, time dependent Navier-Stokes equations, in which the large eddies are calculated and only the turbulence at scales smaller than the computational mesh spacings has to be modelled. Current computation costs place engineering computations in the first of these categories; large eddy simulations are appropriate currently for special studies of the dynamical processes of turbulence in idealized flow fields. It is shown that the two methods are interrelated and that each can gain from advances in the other. The degree of success of a pair of increasingly complex Reynolds stress models to broaden their range of applicability is examined through comparisons with experimental data for a variety of flow conditions. An example of a large-eddy simulation is presented, compared with experimental results, and used to evaluate the models for pressure rate-of-strain correlations and dissipation in the Reynolds-averaged equations.
The effect of different solar simulators on the measurement of short-circuit current temperature coefficients
Gallium arsenide solar cells are considered for several high temperature missions in space. Both near-Sun and concentrator missions could involve cell temperatures on the order of 200 C. Performance measurements of cells at elevated temperatures are usually made using simulated sunlight and a matched reference cell. Due to the change in bandgap with increasing temperature at portions of the spectrum where considerable simulated irradiance is present, there are significant differences in measured short circuit current at elevated temperatures among different simulators. To illustrate this, both experimental and theoretical data are presented for gallium arsenide cells.
Current and Future Performance of the CMS Simulation
The CMS full simulation using Geant4 has delivered billions of simulated events for analysis during Runs 1 and 2 of the LHC. However, the HL-LHC dataset will be an order of magnitude larger, with a similar increase in occupancy per event. In addition, the upgraded CMS detector will be considerably more complex, with an extended silicon tracker and a high granularity calorimeter in the endcap region. Increases in conventional computing resources are subject to both technological and budgetary limitations, so novel approaches are needed to improve software efficiency and to take advantage of new architectures and heterogeneous resources. Several projects are in development to address these needs, including the vectorized geometry library Vec-Geom and the GeantV transport engine, which uses track-level parallelization. The current computing performance of the CMS simulation will be presented as a baseline, along with an overview of the various optimizations already available for Geant4. Finally, the progress and outlook for integrating VecGeom and GeantV in the CMS software framework will be discussed.