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At least 307 records · Page 17

THE AGORA HIGH-RESOLUTION GALAXY SIMULATIONS COMPARISON PROJECT. II. ISOLATED DISK TEST

Using an isolated Milky Way-mass galaxy simulation, we compare results from nine state-of-the-art gravito-hydrodynamics codes widely used in the numerical community. We utilize the infrastructure we have built for the AGORA High-resolution Galaxy Simulations Comparison Project. This includes the common disk initial conditions, common physics models (e.g., radiative cooling and UV background by the standardized package Grackle) and common analysis toolkit yt, all of which are publicly available. Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production are carefully constrained across code platforms. With numerical accuracy that resolves the disk scale height, we find that the codes overall agree well with one another in many dimensions including: gas and stellar surface densities, rotation curves, velocity dispersions, density and temperature distribution functions, disk vertical heights, stellar clumps, star formation rates, and Kennicutt–Schmidt relations. Quantities such as velocity dispersions are very robust (agreement within a few tens of percent at all radii) while measures like newly formed stellar clump mass functions show more significant variation (difference by up to a factor of ∼3). Systematic differences exist, for example, between mesh-based and particle-based codes in the low-density region, and between more diffusive and less diffusive schemes in the high-density tail of the density distribution. Yet intrinsic code differences are generally small compared to the variations in numerical implementations of the common subgrid physics such as supernova feedback. Our experiment reassures that, if adequately designed in accordance with our proposed common parameters, results of a modern high-resolution galaxy formation simulation are more sensitive to input physics than to intrinsic differences in numerical schemes.

79 ASTRONOMY AND ASTROPHYSICS↗

A nonlinear propulsion system simulation technique for piloted simulators

A real time digital simulation technique providing the capabilities needed to evaluate propulsion system performance and aircraft system interaction on NASA manned flight simulators, is discussed. A parameter correlation technique is used with real and pseudo dynamics in a stable integration convergence loop. The cycle time reported was 2.0 ms on one computer and 5.7 ms on the simulator computer. The model was found to be stable and accurate with time up to 50 ms. It is concluded that the program has generated a valuable simulation technology and flight simulator experience by providing an adequate level of detail to evaluate propulsion systems in a simulated flight environment.

Mihaloew, J. R.↗

Materials Requirements for Standard Lunar Highlands Regolith Simulants as Defined by the NASA Simulant Development Program

The development of surface technologies for NASA's human and robotic lunar program beyond 2010 has begun. The multitude of projects underway and future ones will soon rely on the availability of lunar regolith simulant materials chosen to simulate the characteristics of lunar regoliths in order to design, test and qualify prototype hardware and flight equipment. The selection and development of standard lunar regolith simulants (SLRS) for the use of NASA technology programs was one of the main recommendations of the 2005 Workshop on Lunar Regolith Simulant Materials at Marshall Space Flight Center. The realization of that objective is now underway through the NASA simulant development program at the Marshall Space Flight Center. The approach adopted to define materials requirements for standard simulants of regolith from the Highlands regions of the Moon will be presented along with a discussion of limitations inherent to such an endeavor.

Sibille, Laurent↗

An Orion/Ares I Launch and Ascent Simulation: One Segment of the Distributed Space Exploration Simulation (DSES)

This paper describes the architecture and implementation of a distributed launch and ascent simulation of NASA's Orion spacecraft and Ares I launch vehicle. This simulation is one segment of the Distributed Space Exploration Simulation (DSES) Project. The DSES project is a research and development collaboration between NASA centers which investigates technologies and processes for distributed simulation of complex space systems in support of NASA's Exploration Initiative. DSES is developing an integrated end-to-end simulation capability to support NASA development and deployment of new exploration spacecraft and missions. This paper describes the first in a collection of simulation capabilities that DSES will support.

Chung, Victoria I.↗

Validation of Multibody Program to Optimize Simulated Trajectories II Parachute Simulation with Interacting Forces

A capability to simulate trajectories of multiple interacting rigid bodies has been developed, tested and validated. This capability uses the Program to Optimize Simulated Trajectories II (POST 2). The standard version of POST 2 allows trajectory simulation of multiple bodies without force interaction. In the current implementation, the force interaction between the parachute and the suspended bodies has been modeled using flexible lines, allowing accurate trajectory simulation of the individual bodies in flight. The POST 2 multibody capability is intended to be general purpose and applicable to any parachute entry trajectory simulation. This research paper explains the motivation for multibody parachute simulation, discusses implementation methods, and presents validation of this capability.

Raiszadeh, Behzad↗

Effect of Simulant Type on the Absorptance and Emittance of Dusted Thermal Control Surfaces in a Simulated Lunar Environment

During the Apollo program the effects of lunar dust on thermal control surfaces was found to be more significant than anticipated, with several systems overheating due to deposition of dust on them. In an effort to reduce risk to future missions, a series of tests has been initiated to characterize the effects of dust on these surfaces, and then to develop technologies to mitigate that risk. Given the variations in albedo across the lunar surface, one variable that may be important is the darkness of the lunar dust, and this study was undertaken to address that concern. Three thermal control surfaces, AZ-93 white paint and AgFEP and AlFEP second surface mirrors were dusted with three different lunar dust simulants in a simulated lunar environment, and their solar absorptivity and thermal emissivity values determined experimentally. The three simulants included JSC 1AF, a darker mare simulant, NU-LHT-1D, a light highlands simulant, and 1:1 mixture of the two. The response of AZ-93 was found to be slightly more pronounced than that of AgFEP. The increased with fractional dust coverage in both types of samples by a factor of 1.7 to 3.3, depending on the type of thermal control surface and the type of dust. The of the AZ-93 decreased by about 10 percent when fully covered by dust, while that of AgFEP increased by about 10 percent. It was found that alpha/epsilon varied by more than a factor of two depending on the thermal control surface and the darkness of the dust. Given that the darkest simulant used in this study may be significantly lighter than the darkest dust that could be encountered on the lunar surface, it becomes apparent that the performance degradation of thermal control surfaces due to dust on the moon will be strongly dependent on the and of the dust in the specific locality.

Gaier, James R.↗

Effect of Simulant Type on the Absorptance and Emittance of Dusted Thermal Control Surfaces in a Simulated Lunar Environment

During the Apollo program the effects of lunar dust on thermal control surfaces was found to be more significant than anticipated, with several systems overheating due to deposition of dust on them. In an effort to reduce risk to future missions, a series of tests has been initiated to characterize the effects of dust on these surfaces, and then to develop technologies to mitigate that risk. Given the variations in albedo across the lunar surface, one variable that may be important is the darkness of the lunar dust, and this study was undertaken to address that concern. Three thermal control surfaces, AZ-93 white paint and AgFEP and AlFEP second surface mirrors were dusted with three different lunar dust simulants in a simulated lunar environment, and their integrated solar absorptance ( ) and thermal emittance ( ) values determined experimentally. The three simulants included JSC-1AF, a darker mare simulant, NU-LHT-1D, a light highlands simulant, and 1:1 mixture of the two. The response of AZ-93 was found to be slightly more pronounced than that of AgFEP. The increased with fractional dust coverage in both types of samples by a factor of 1.7 to 3.3, depending on the type of thermal control surface and the type of dust. The of the AZ-93 decreased by about 10 percent when fully covered by dust, while that of AgFEP increased by about 10 percent. It was found that / varied by more than a factor of two depending on the thermal control surface and the darkness of the dust. Given that the darkest simulant used in this study may be lighter than the darkest dust that could be encountered on the lunar surface, it becomes apparent that the performance degradation of thermal control surfaces due to dust on the Moon will be strongly dependent on the and of the dust in the specific locality

Gaier, James R.↗

Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators in Climate Models

The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This work examines the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. We focus on the stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15% of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.

Pincus, Robert↗

Physics-Based Simulator for NEO Exploration Analysis & Simulation

As part of the Space Exploration Analysis and Simulation (SEAS) task, the National Aeronautics and Space Administration (NASA) is using physics-based simulations at NASA's Jet Propulsion Laboratory (JPL) to explore potential surface and near-surface mission operations at Near Earth Objects (NEOs). The simulator is under development at JPL and can be used to provide detailed analysis of various surface and near-surface NEO robotic and human exploration concepts. In this paper we describe the SEAS simulator and provide examples of recent mission systems and operations concepts investigated using the simulation. We also present related analysis work and tools developed for both the SEAS task as well as general modeling, analysis and simulation capabilites for asteroid/small-body objects.

Dshell↗

Molecular Simulations Probing the Adsorption and Diffusion of Ammonia, Nitrogen, Hydrogen, and Their Mixtures in Bulk MFI Zeolite and MFI Nanosheets at High Temperature and Pressure

Recent advances in the synthesis of MFI zeolite nanosheets have led to highly selective membranes that are promising candidates for small-scale ammonia separation from ammonia/nitrogen/hydrogen mixtures in distributed green ammonia production plants. Using force-field-based molecular simulations, we evaluate the performance of bulk all-silica MFI zeolite and a 3 nm thick all-silica MFI nanosheet for ammonia/nitrogen/hydrogen separations at moderate temperature and pressure conditions (T = 373 K, p = 5 bar) as well as conditions relevant for a membrane-based reactor–separator process (T = 523 or 623 K, p = 80 bar). Isobaric–isothermal Gibbs ensemble Monte Carlo (GEMC) simulations were carried out to understand the selective adsorption behavior for these mixtures. Molecular dynamics simulations in the canonical ensemble were performed to examine the transport behavior of ammonia in a mixture with nitrogen or hydrogen at loadings obtained from the GEMC simulations. Our results show that both bulk MFI and the nanosheet with explicit surface silanols are highly selective toward ammonia adsorption, but the adsorption selectivity decreases by factors of 4 and 10 for ammonia/nitrogen and ammonia/hydrogen mixtures as the temperature is increased from 373 to 623 K. Conversely, the diffusion selectivities toward ammonia are more favorable at process-relevant temperatures and for the MFI nanosheet. Here, at T = 523 K and p = 80 bar, our simulations predict overall separation factors of 3.8 ± 0.2 and 4.5 ± 0.3 for ammonia/nitrogen and ammonia/hydrogen mixtures, respectively, in the bulk MFI zeolite, and separation factors of 8.6 ± 0.4 and 12.5 ± 0.8, respectively, for the MFI nanosheet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel Approach to PV Inverter Modeling and Simulation Leveraging Experiments, Learning Based Modeling and Co-Simulation: Preprint

Photovoltaic inverter (PV) inverter manufacturers use custom, proprietary control approaches and topologies in their inverter design. Due to this proprietary nature, it is not possible to share EMT domain models for system studies. This research work presents a novel approach in experimental design, high fidelity data collection, use of learning-based modeling, and co-simulation to enhance the PV inverter modeling. We used a 20 kW off-the-shelf grid following PV inverter and subjected the inverter to controlled tests including voltage and frequency step changes, as well as solar irradiance variations. The recorded high frequency data was used in learning-based model training. This learning-based model was imported into an Electromagnetic Transient (EMT) simulation tool using co-simulation techniques to complete the modeling effort and integrate the model into an EMT simulation tool. The three key components in this research work are the design of experimental setup, use of learning-based approach for model development and use of co-simulation to complete the approach. The proposed approach will allow users to develop a model in a really short period of time and achieve reasonable inverter models.

artificial intelligence↗

A new coupling of a GPU-resident large-eddy simulation code with a multiphysics wind turbine simulation tool

The development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large-eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross-verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large-scale meteorological models as boundary conditions.

17 WIND ENERGY↗

Finite time step and spatial grid effects in δf simulation of warm plasmas

This paper introduces a technique for analyzing time integration methods used with the particle weight equations in δf method particle-in-cell (PIC) schemes. The analysis applies to the simulation of warm, uniform, periodic or infinite plasmas in the linear regime and considers the collective behavior similar to the analysis performed by Langdon for full-f PIC schemes [1,2]. We perform both a time integration analysis and spatial grid analysis for a kinetic ion, adiabatic electron model of ion acoustic waves. An implicit time integration scheme is studied in detail for δf simulations using our weight equation analysis and for full-f simulations using the method of Langdon. It is found that the δf method exhibits a CFL-like stability condition for low temperature ions, which is independent of the parameter characterizing the implicitness of the scheme. The accuracy of the real frequency and damping rate due to the discrete time and spatial schemes is also derived using a perturbative method. The theoretical analysis of numerical error presented here may be useful for the verification of simulations and for providing intuition for the design of new implicit time integration schemes for the δf method, as well as understanding differences between δf and full-f approaches to plasma simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification

We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute atomic interactions. Our approach quantifies the sensitivity of the quantities of interest with respect to the input functions as opposed to its parameters as is done in typical uncertainty quantification methods. We show that the functional sensitivity of the average potential energy and pressure in isothermal, isochoric MD simulations using Lennard–Jones two-body interactions can be used to accurately predict those properties for other interatomic potentials (with different functional forms) without re-running the simulations. This is demonstrated under three different thermodynamic conditions, namely a crystal at room temperature, a liquid at ambient pressure, and a high pressure liquid. The method provides accurate predictions as long as the change in potential can be reasonably described to first order and does not significantly affect the region in phase space explored by the simulation. The functional uncertainty quantification approach can be used to estimate the uncertainties associated with constitutive models used in the simulation and to correct predictions if a more accurate representation becomes available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Predicting Reaction Products and Automating Reactive Trajectory Characterization in Molecular Simulations with Support Vector Machines

A machine learning-based methodology for the prediction of chemical reaction products, along with automated elucidation of mechanistic details via phase space analysis of reactive trajectories, is introduced using low-dimensional heuristic models and then applied to ab initio computer simulations of the photodissociation of acetaldehyde, an important chemical system in atmospheric chemistry. Our method is centered around training Support Vector Machines (SVMs) to identify optimal separatrices that delineate the regions of phase space that lead to different chemical reaction products. In contrast to the more common “black box” type machine learning methodologies for analyzing chemical simulation data, this SVM-based methodology allows for mechanistic insight to be gleaned from further analysis of the positioning of the phase space points used to train the SVM with respect to the separatrices. For example, a pair of phase space points that are in close proximity to each other but on opposite sides of a separatrix may be situated on opposite sides of a transition state, while phase space points occurring early in a simulation that are distant from a separatrix are likely to belong to trajectories that are highly biased toward the product state associated with the basin of attraction to which they belong. In addition to inferring mechanistic details about multiple-pathway chemical reactions, our method can also be used to increase reactive trajectory sampling efficiency in molecular simulations via rejection sampling, with trajectories leading to undesired product states being identified and terminated early in the simulation rather than being carried to completion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic and simulation-free coarse graining of homopolymer melts: A structure-based study

We propose a systematic and simulation-free strategy for coarse graining of homopolymer melts, where each chain of N{sub m} monomers is uniformly divided into N segments, with the spatial position of each segment corresponding to the center-of-mass of its monomers. We use integral-equation theories suitable for the study of equilibrium properties of polymers, instead of many-chain molecular simulations, to obtain the structural and thermodynamic properties of both original and coarse-grained (CG) systems, and quantitatively examine how the effective pair potentials between CG segments and the thermodynamic properties of CG systems vary with N. Our systematic and simulation-free strategy is much faster than those using many-chain simulations, thus effectively solving the transferability problem in coarse graining, and provides the quantitative basis for choosing the appropriate N-values. It also avoids the problems caused by finite-size effects and statistical uncertainties in many-chain simulations. Taking the simple hard-core Gaussian thread model [K. S. Schweizer and J. G. Curro, Chem. Phys. 149, 105 (1990)] as the original system, we demonstrate our strategy applied to structure-based coarse graining, which is quite general and versatile, and compare in detail the various integral-equation theories and closures for coarse graining. Our numerical results show that the effective CG potentials for various N and closures can be collapsed approximately onto the same curve, and that structure-based coarse graining cannot give thermodynamic consistency between original and CG systems at any N < N{sub m}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Particle-in-cell simulations of electron beam control using an inductive current divider

Kinetic, time-dependent, electromagnetic, particle-in-cell simulations of the inductive current divider are presented. The inductive current divider is a passive method for controlling the trajectory of an intense, hollow electron beam using a vacuum structure that inductively splits the beam’s return current. The current divider concept was proposed and studied theoretically in a previous publication [Phys. Plasmas 22, 023107 (2015)] A central post carries a portion of the return current (I 1 ) while the outer conductor carries the remainder (I 2 ) with the injected beam current given by I b =I 1 +I 2 . The simulations are in agreement with the theory which predicts that the total force on the beam trajectory is proportional to (I 2 -I 1 ) and the force on the beam envelope is proportional to I b . For a fixed central post, the beam trajectory is controlled by varying the outer conductor radius which changes the inductance in the return-current path. The simulations show that the beam emittance is approximately constant as the beam propagates through the current divider to the target. As a result, independent control over both the current density and the beam angle at the target is possible by choosing the appropriate return-current geometry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Coupling of CTF and RELAP5-3D Within an Enhanced Fidelity Nuclear Power Plant Simulator

A robust and accurate multiphysics engineering simulator is being developed to model the core behavior and system response of pressurized water reactors. This simulator relies on the NESTLE and CTF computer codes to model the neutronics and thermal hydraulics (TH), respectively, inside the core on a nodal scale and on the Reactor Excursion and Leak Analysis Program—Three Dimensional (RELAP5-3D) to model the entire nuclear steam supply system. The RELAP5-3D model includes highly detailed nodalization and multidimensional flow modeling throughout the vessel. Previously, pin-resolved data generated via the Virtual Environment for Reactor Analysis core simulator were used to improve the accuracy of the NESTLE core predictions. The engineering simulator being developed as part of this work uses the 3KEYMASTER platform to couple the enhanced NESTLE model to a nodal-fidelity CTF model to balance run time with accuracy; NESTLE provides node-dependent powers to CTF, and CTF provides node-dependent coolant densities and fuel temperatures to NESTLE.An overlapping domain approach is used for the core TH in which RELAP5-3D provides core boundary conditions based on the system response and CTF provides a node-dependent coolant heating rate to the RELAP5-3D core solution. In the preliminary TH demonstration discussed in this paper, CTF and RELAP5-3D provided similar steady-state core predictions, indicating the hydraulic compatibility between the codes, as well as reasonable and expected behavior under hypothetical transient conditions. This provides an initial step in ongoing efforts toward a robust, multiscale TH/neutronics engineering simulator capability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗