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At least 1,477 records · Page 82

Translational Vestibulo-Ocular Reflex and Motion Perception During Interaural Linear Acceleration: Comparison of Different Motion Paradigms

The neural mechanisms to resolve ambiguous tilt-translation motion have been hypothesized to be different for motion perception and eye movements. Previous studies have demonstrated differences in ocular and perceptual responses using a variety of motion paradigms, including Off-Vertical Axis Rotation (OVAR), Variable Radius Centrifugation (VRC), translation along a linear track, and tilt about an Earth-horizontal axis. While the linear acceleration across these motion paradigms is presumably equivalent, there are important differences in semicircular canal cues. The purpose of this study was to compare translation motion perception and horizontal slow phase velocity to quantify consistencies, or lack thereof, across four different motion paradigms. Twelve healthy subjects were exposed to sinusoidal interaural linear acceleration between 0.01 and 0.6 Hz at 1.7 m/s/s (equivalent to 10 tilt) using OVAR, VRC, roll tilt, and lateral translation. During each trial, subjects verbally reported the amount of perceived peak-to-peak lateral translation and indicated the direction of motion with a joystick. Binocular eye movements were recorded using video-oculography. In general, the gain of translation perception (ratio of reported linear displacement to equivalent linear stimulus displacement) increased with stimulus frequency, while the phase did not significantly vary. However, translation perception was more pronounced during both VRC and lateral translation involving actual translation, whereas perceptions were less consistent and more variable during OVAR and roll tilt which did not involve actual translation. For each motion paradigm, horizontal eye movements were negligible at low frequencies and showed phase lead relative to the linear stimulus. At higher frequencies, the gain of the eye movements increased and became more inphase with the acceleration stimulus. While these results are consistent with the hypothesis that the neural computational strategies for motion perception and eye movements differ, they also indicate that the specific motion platform employed can have a significant effect on both the amplitude and phase of each.

Beaton, K. H.↗

Uncertainty Due to Unsteady Fluid/Structure Interaction for the Ares I Vehicle Traversing the Transonic Regime

Rapid reduced-order numerical models are being investigated as candidates to simulate the dynamics of a flexible launch vehicle during atmospheric ascent. There has also been the extension of these new approaches to include gust response. These methods are used to perform aeroelastic and gust response analyses at isolated Mach numbers. Such models require a method to time march through a succession of ascent Mach numbers. An approach is presented for interpolating reduced-order models of the unsteady aerodynamics at successive Mach numbers. The transonic Mach number range is considered here since launch vehicles can suffer the highest dynamic loads through this range. Realistic simulations of the flexible vehicle behavior as it traverses this Mach number range are presented. The response of the vehicle due to gusts is computed. Uncertainties in root mean square and maximum bending moment and crew module accelerations are presented due to assumed probability distributions in design parameters, ascent flight conditions, gusts. The primary focus is on the uncertainty introduced by modeling fidelity. It is found that an unsteady reduced order model produces larger excursions in the root mean square loading and accelerations than does a quasi-steady reduced order model.

Bartels, Robert E.↗

Advancing Open Science through Public-Private Partnerships

Rapid technology developments are changing the way data-driven research is performed within the science community. With the emergence of cloud computing, this has quickly become a viable approach for enabling “science at scale”. Researchers are no longer hindered by obstacles of data management and data wrangling, allowing them to quickly discover, access and perform analysis on extremely large datasets. Infrastructures that move data out of institutional silos and into a computational platform, will ensure that data and tools are accessible to all users. NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) seeks to address these rapid technology developments by establishing Space Act Agreements with selected partners from the public-private sector working in the area of cloud computing. These agreements aim to explore new opportunities with commercial cloud providers to accelerate open science and enable discovery, access and use of data sets on the cloud. In addition, they will also help establish training workshops for the science community to help researchers utilize the cloud for science. In this talk, we will present an overview of current and new partnerships we are developing to support open science and open data initiatives.

Elizabeth Fancher↗

Global-to-local air quality forecasts using the NASA GEOS Composition Forecast System

Since 2019, the NASA Global Earth Observing System (GEOS) model has been used to generate global, near-real-time estimates and daily five-day forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). Because GEOS-CF includes atmospheric levels up through the stratosphere, this system has been leveraged to support the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite mission and provide stratospheric intrusion alerts to ground-based monitoring stations. We will present recent advances to GEOS-CF which target increased computational efficiency and accuracy. These include the incorporation of simplified chemistry mechanisms to accelerate model forecasts, use of model-observation data fusion techniques to provide highly localized forecasts, and assimilation of satellite observations to produce more accurate model analyses. We further discuss our attempts to make these tools publicly available on platforms outside the NASA domain, such as Google Earth Engine and Amazon Web Services with the goal to facilitate the integration of state-of-the-science air quality information onto platforms used by stakeholders, air quality managers, and the public.

Emma Knowland↗

NMDQi Nuclear Materials Discovery and Qualification Initiative Conference Overview

The Nuclear Materials Discovery and Qualification Initiative (NMDQi) is designed to accelerate nuclear materials qualification to fulfill the promises of early and advanced reactor technologies as a safe, clean, and low-cost baseload energy. Materials development and qualification in the nuclear industry is by definition challenging due to stringent safety requirements, limited availability of specialized facilities for materials irradiation and testing, and the challenging high-temperature, high-radiation environment. NMDQi will establish tools and capabilities that will greatly accelerate the nuclear fuels and materials development process. These tools will provide both computationally informed insights and high-throughput infrastructure with the goal of completing qualification in a single pass. In this approach, materials must be fabricated with a range of properties of interest so that materials performance can be examined in parallel, rather than with multiple discrete specimens. Advanced manufacturing (AM) techniques, which can produce complex component geometries, microstructures, and compositions, are ideal. The improved process monitoring and control that AM can provide are ideal for ensuring and reducing material variability, which will be particularly important as standards committees pursue regulations for AM components. However, gaining these benefits requires overcoming the substantial barrier of qualifying AM processes and the resulting materials and components for supporting research campaigns and eventually nuclear service.

36 MATERIALS SCIENCE↗

Comparison of advanced reduced-basis methods for transient structural analysis

Two advanced reduced-basis methods for linear, transient structural analysis, the force-derivative method and the Lanczos method, are compared to two widely-used modal methods, the mode-displacement method and the mode-acceleration method. Comparisons are made for two linear example problems: a proportionally-damped cantilevered beam subject to a discrete tip load which varies linearly with time, and a discretely-damped multispan beam subject to a uniformly distributed load which varies as a quintic function of time. Results from the methods are compared in terms of the number of basis vectors required to obtain a desired level of accuracy and the associated computational times. The results are problem dependent, and it is shown that for the cantilevered beam problem, the mode-acceleration and force-derivative methods are the most efficient in terms of the number of basis vectors and computational time. The force-derivative method is shown to be the most effective method for solving the multispan beam problem with closely-spaced frequencies. In general, the force-derivative method is shown to produce an accurate solution using very few basis vectors and to require less computational time as compared to the other methods studied.

Mcgowan, David M.↗

Premixed shock-induced combustion studies in the hypulse facility

Engine performance calculations strongly suggest that the oblique detonation-wave engine can outperform the diffusive-burning scramjet engine in the high hypervelocity flight regime; i.e., at flight Mach numbers exceeding about 14. Research is described that examines and characterizes the behavior of oblique detonation waves (ODW). The effort is both computational and experimental, the latter utilizing the NASA Hypulse expansion tube. The experimental work is hampered by preignition of the hydrogen-oxygen-helium mixtures in either the intermediate or acceleration sections of the facility. The experiments are described and possible causes of this preignition are discussed. Initial results obtained from a parallel computation effort indicate that temporally steady ODW are achievable in the Hypulse facility.

Chinitz, W.↗

Sloshing dynamics modulated angular momentum fluctuations actuated by gravity gradient acceleration associated with spacecraft slew motion

The mathematical formulation of orbital spacecraft sloshing dynamics for a partially filled cryogenic superfluid liquid helium II in a dewar container actuated by the gravity gradient acceleration associated with slew motion is studied. The Advanced X-Ray Astrophysics Facility-Spectroscopy (AXAF-S) spacecraft is chosen as a practical example in this study. Explicit mathematical expressions which manage orbital galaxy gradient acceleration with slew motion which is acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics is based on the non-inertia frame spacecraft bound coordinates and the solution of time-dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. This study discloses the capillary effect of sloshing dynamics governed liquid-vapor interface fluctuations, angular momentum and moment fluctuations of fluid system, and also buble mass center fluctuations driven by the gravity gradient acceleration associated with slew motion which affects the stability of the orbital spacecraft fluid system in a microgravity environment.

Hung, R. J.↗

Investigation into Scalable and Detection-Enhanced Satellite Conjunction Assessment

Imaging opportunities (viewable conjunctions) of Resident Space Objects (RSOs) by satellites are not continuously discovered. We propose to continuously produce and report viewable conjunctions among objects in orbit. Viewable conjunctions are events in space and time when a satellite may favorably view a Resident Space Object (RSO). Favorability is defined by a set of constraints, e.g., solar illumination, distance between observer and target, orbital location for viewable event. Computing viewable conjunctions requires calculation of orbital propagation while considering constraints based on the state vectors of position, velocity, with covariance for both satellite and RSO. We propose two parallel lanes of effort: acceleration and research. The objective of acceleration is to avoid missed opportunities and reduce latency for satellite maneuver requests through continuous prediction and reporting of viewable conjunctions. The effort will begin by deploying currently available software on dedicated systems and continue with optimizing the code for high performance computing hardware. The research lane aims to expand RSO inspection and modeling capabilities. Among our current research ideas are spectral characterization of RSO materials and planning multiple observations to recover RSO 3D form. Computing resources at Oak Ridge National Laboratory (ORNL) are available for the acceleration work. Laika, Maxar conjunction prediction dashboard software, and Bluesim, Maxar orbital propagation software, are expected to be the first software in the acceleration lane. Laike and Bluesim are to be provided by the sponsor, and output will be made accessible through its dashboard. Deliverables will follow a gated schedule to the sponsor. ORNL will provide progressively more robust viewable conjunction assessments from both modelled and actual ephemerides.

97 MATHEMATICS AND COMPUTING↗

Electron Target Cooling Analyses of the KIPT ADS Using MCNP and Ansys Fluent

This study presents multiphysics analyses of the electron target cooling system of the accelerator-driven system (ADS) of the Kharkiv Institute of Physics and Technology (KIPT) using MCNP and Fluent computer programs. MCNP has been used to transport electrons, gammas, and neutrons, and to calculate the energy deposition in the target materials. The MCNP mesh-tally data have been imported into Fluent by a C subroutine that has been compiled and linked to Fluent as a user-defined function.The KIPT ADS is located in Ukraine and was in operation until February 2022. The Fluent model is based on the computer-aided design files from the manufacturing process of the target assembly. Here, the Fluent results for the reference case match very well the literature results obtained by STAR-CCM+ during the design phase. Other cases that differ from the reference one have been analyzed; in these cases, it is assumed a malfunction of the electron accelerator or of the water cooling system. The target cooling system operates normally for all the analyzed cases except when the inlet water mass flow rate is decreased. The transient analysis showed that the target cooling system can operate for 180 s with full power when the inlet water mass flow rate is decreased down by 75%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Visual analysis of fluid dynamics at NASA's numerical aerodynamic simulation facility

A study aimed at describing and illustrating visualization tools used in Computational Fluid Dynamics (CFD) and indicating how these tools are likely to change by showing a projected resolution of the human computer interface is presented. The following are outlined using a graphically based test format: the revolution of human computer environments for CFD research; comparison of current environments; current environments with the ideal; predictions for the future CFD environments; what can be done to accelerate the improvements. The following comments are given: when acquiring visualization tools, potential rapid changes must be considered; environmental changes over the next ten years due to human computer interface cannot be fathomed; data flow packages such as AVS, apE, Explorer and Data Explorer are easy to learn and use for small problems, excellent for prototyping, but not so efficient for large problems; the approximation techniques used in visualization software must be appropriate for the data; it has become more cost effective to move jobs that fit on workstations and run only memory intensive jobs on the supercomputer; use of three dimensional skills will be maximized when the three dimensional environment is built in from the start.

Watson, Velvin R.↗

Developing a complete AI-accelerated workflow for superconductor discovery

The quest to identify new superconducting materials with enhanced properties is hindered by the prohibitive cost of computing electron-phonon spectral functions, severely limiting the materials space that can be explored. Here, we introduce a Bootstrapped Ensemble of Equivariant Graph Neural Networks (BEE-NET), a machine-learning model trained to predict the Eliashberg spectral function and superconducting critical temperature with a mean-absolute-error of 0.87 K relative to DFT-based Allen-Dynes calculations. Intriguingly, BEE-NET achieves a true-negative-rate of 99.4%, enabling highly efficient screening for the rare property of superconductivity. Integrated into a multi-stage, AI-accelerated discovery pipeline that incorporates elemental-substitution strategies and machine-learned interatomic potentials, our workflow reduced over 1.3 million candidate structures to 741 dynamically and thermodynamically stable compounds with DFT-confirmed T c > 5 K. We report the successful synthesis and experimental confirmation of superconductivity in two of these previously unreported compounds. This study establishes a data-driven framework that integrates machine learning, quantum calculations, and experiments to systematically accelerate superconductor discovery.

Gibson, Jason B. [Quantum Formatics, Cambridge, MA↗

Assessing entropy for catalytic processes at complex reactive interfaces

When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.

Kollias, Loukas↗

FPGA-based HPC accelerators: An evaluation on performance and energy efficiency

Hardware specialization is a promising direction for the future of digital computing. Reconfigurable technologies enable hardware specialization with modest non-recurring engineering cost, but their performance and energy efficiency compared to state-of-the-art processor architectures remain an open question. In this article, we use FPGAs to evaluate the benefits of building specialized hardware for numerical kernels found in scientific applications. In order to properly evaluate performance, we not only compare Intel Arria 10 and Xilinx U280 performance against Intel Xeon, Intel Xeon Phi, and NVIDIA V100 GPUs, but we also extend the Empirical Roofline Toolkit (ERT) to FPGAs in order to assess our results in terms of the Roofline model. We show design optimization and tuning techniques for peak FPGA performance at reasonable hardware usage and power consumption. As FPGA peak performance is known to be far less than that of a GPU, we also benchmark the energy efficiency of each platform for the scientific kernels comparing against microbenchmark and technological limits. Results show that while FPGAs struggle to compete in absolute terms with GPUs on memory- and compute-intensive kernels, they require far less power and can deliver nearly the same energy efficiency.

97 MATHEMATICS AND COMPUTING↗

Acceleration of FDNS flow simulations using initial flowfields generated with a parabolized Navier-Stokes method

The capability of computational fluid dynamics (CFD) analysis to predict complex flowfields has been greatly advanced by the widespread use of flow simulation programs based on the Navier-Stokes (NS) equations. The flow physics are theoretically well represented, and with proper care the numerical solution should not introduce appreciable uncertainties. However, the computational cost of a typical simulation in terms of both memory and execution time are large by current standards. Therefore, the efficiency of the numerical algorithm in solving the set of model equations is one factor determining the usefulness of CFD tools. The objective of the present study is to reduce the execution time of the FDNS flow simulation code by using the parabolized Navier-Stokes (PNS) equations to provide a 'good' starting condition. The technique is not universal, however the PNS model can be applied to convection dominated flows with moderate deflection in geometries that are free of large obstructions.

Tenpas, Peter W.↗

Heavy ion beams in extended materials - Computational methods and experiment

The transport of heavy ion beams in extended materials is a problem of interest in accelerator and space shielding, radiation therapy, and astrophysical and radiobiological studies. The beam particles change their energy and direction of motion through atomic/molecular collisions and undergo occasional radical transformation in nuclear collision. In health physics applications, a heavy ion beam of initially well defined radiation quality is transformed into a complex mixture of diverse quality components after passing through a modest amount of material. This transformation of radiation quality must be understood to adequately explain the biological response of tissue to heavy ion radiation. A theoretical/experimental program to define an ion beam and its products in extended matter is described.

Wilson, J. W.↗

Software Tool for Computing Maximum Von Mises Stress

The maximum Van Mises stress and stress direction are of interest far analyzing launch accelerations such as with the Mass Acceleration Curves developed by JPL. Maximum launch stresses can be combined with appropriate load cases at consistent locations with resulting stress tensors. Maximum Van Mises stress is also of interest for understanding maximum operational loading such as traverse events. - For example, planetary traversing simulations may prescribe bounding acceleration values during traverse for a rover such as Mars Science Lab (MSL) in (X,Y,Z) of the rover. - Such accelerations can be really in any directions for many parts such as a mast or head mounted components which can be in numerous configurations and orientations when traversing a planet surface.

software↗