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At least 1,261 records · Page 70

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Zaychik, Kirill B.↗

Modeling Microgravity Induced Fluid Redistribution Autoregulatory and Hydrostatic Enhancements

Space flight induces a marked cephalad (headward) redistribution of blood and interstitial fluid potentially resulting in a loss of venous tone and reduction in heart muscle efficiency upon introduction into the microgravity environment. Using various types of computational models, we are investigating how this fluid redistribution may induce intracranial pressure changes, relevant to reported reductions in astronaut visual acuity, part of the Visual Impairment and Intracranial Pressure (VIIP) syndrome. Methods: We utilize a lumped parameter cardiovascular system (CVS) model, augmented by compartments comprising the cerebral spinal fluid (CSF) space, as the primary tool to describe how microgravity, and the associated lack of hydrostatic gradient, impacts fluid redistribution. Models of ocular fluid pressures and biomechanics then accept the output of the above model as boundary condition input to allow more detailed, local analysis (see IWS Abstract by Ethier et al.). Recently, we enhanced the capabilities our previously reported CVS model through the implementation of robust autoregulatory mechanisms and a more fundamental approach to the implementation of hydrostatic mechanisms. Modifying the approach of Blanco et al., we implemented auto-regulation in a quasi-static manner, as an averaged effect across the span of one heartbeat. This approach reduced the higher frequency perturbations from the regulatory mechanism and was intended to allow longer simulation times (days) than models that implement within-beat regulatory mechanisms (minutes). A more fundamental approach to hydrostatics was implemented by a quasi-1D approach, in which compartment descriptions include compartment length, orientation and relative position, allowed for modeling of body orientation, relative body positioning and, in the future, alternative gravity environments. At this time the inclusion of hydrostatic mechanisms supplies additional capabilities to train and validate the CVS model with terrestrial data. Results and Conclusions: With the implementation of auto-regulation and hydrostatic modeling capabilities, the model performs as expected in the maintaining the CA (Central Artery) compartment pressure when simulating orientations ranging from supine to standing. The model appears to generally overpredict heart rate and thus cardiac output, possibly indicating sensitivity to the nominal heart rate, which is used as an initial set point of the regulation mechanisms. Despite this sensitivity, the model performs consistently for many hours of simulation time, indicating the success of our quasi-static implementation approach.

biomechanics↗

Water tunnel flow visualization study of a 4.4 percent scale X-31 forebody

A water-tunnel test of a 4.4 percent-scale, forebody-only model of the X-31 aircraft with different forebody strakes and nosebooms has been performed in the Flow Visualization Facility at the NASA Dryden Flight Research Center. The focus of the study was to determine the relative effects of the different configurations on the stability and symmetry of the high-angle-of-attack forebody vortex flow field. The clean, noseboom-off configuration resisted the development of asymmetries in the primary vortices through 70 deg angle of attack. The wake of the X-31 flight test noseboom configuration significantly degraded the steadiness of the primary vortex cores and promoted asymmetries. An alternate L-shaped noseboom mounted underneath the forebody had results similar to those seen with the configuration, enabling stable, symmetrical vortices up to 70 deg angle of attack. The addition of strakes near the radome tip along the waterline increased the primary vortex strength while it simultaneously caused the vortex breakdown location co move forward. Forebody strakes did not appear to significantly reduce the asymmetries in the forebody vortex field in the presence of the flight test noseboom.

Cobleigh, Brent R.↗

Strictly Enforcing Invertibility and Conservation in CNN-Based Super Resolution for Scientific Datasets

Abstract Recently, deep convolutional neural networks (CNNs) have revolutionized image “super resolution” (SR), dramatically outperforming past methods for enhancing image resolution. They could be a boon for the many scientific fields that involve imaging or any regularly gridded datasets: satellite remote sensing, radar meteorology, medical imaging, numerical modeling, and so on. Unfortunately, while SR-CNNs produce visually compelling results, they do not necessarily conserve physical quantities between their low-resolution inputs and high-resolution outputs when applied to scientific datasets. Here, a method for “downsampling enforcement” in SR-CNNs is proposed. A differentiable operator is derived that, when applied as the final transfer function of a CNN, ensures the high-resolution outputs exactly reproduce the low-resolution inputs under 2D-average downsampling while improving performance of the SR schemes. The method is demonstrated across seven modern CNN-based SR schemes on several benchmark image datasets, and applications to weather radar, satellite imager, and climate model data are shown. The approach improves training time and performance while ensuring physical consistency between the super-resolved and low-resolution data. Significance Statement Recent advancements in using deep learning to increase the resolution of images have substantial potential across the many scientific fields that use images and image-like data. Most image super-resolution research has focused on the visual quality of outputs, however, and is not necessarily well suited for use with scientific data where known physics constraints may need to be enforced. Here, we introduce a method to modify existing deep neural network architectures so that they strictly conserve physical quantities in the input field when “super resolving” scientific data and find that the method can improve performance across a wide range of datasets and neural networks. Integration of known physics and adherence to established physical constraints into deep neural networks will be a critical step before their potential can be fully realized in the physical sciences.

54 ENVIRONMENTAL SCIENCES↗

PyARC Status Report: New Integrations and Upgrades to the Fast Reactor Analysis Workflow Management Tool

PyARC was initially developed as an open source tool to support fast reactor analyses using the Argonne Reactor Computation (ARC) code suite as a part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench initiative in FY17. The goal of this initiative is to provide a common user interface for model generation, real-time validation, execution, output processing, and visualization for all integrated codes. This is accomplished through the reliance on tools available in the Workbench framework and runtime environment. While initially developed to support the ARC codes, PyARC was extended in FY22 to wrap other NEAMS and non-ARC codes, including Griffin and OpenMC, in the supported other neutronics workflows, and support users in the adoption of NEAMS-supported high fidelity analysis codes. Most recently, NUBOW-3D, a recently adopted ARC code, was integrated to support reactor bowing calculations as well. Integration of these codes into the NEAMS Workbench directly benefits the advanced reactor modeling community by: • Providing a set of controlled, maintained, documented and validated scripts to generate inputs, which promotes best practices, reduces the learning curve, and facilitates project collaboration. • Improving the user experience: the Workbench interface provides assistance for building an input through auto-completion, real-time validation, document navigation, and geometry and results visualization. • Automating complex calculations and workflows for reactor analysis. • Helping users transition to using high-fidelity NEAMS codes along-side the ARC codes. In FY22, a progress report was published that described the state of each of the tools integrated into PyARC. Since then, there have been many enhancements and upgrades to the existing integrations as well as entirely new code integrations as well. This report details all new integrations and major developments in PyARC since the version 2.0.0 release highlighted in the FY22 report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tracking Magnetic Perturbations, dB/dt and Geomagnetic Indices for Geospace Storms on a Routine Basis at the CCMC

The first comprehensive assessment of geospace model skill to specify magnetic perturbations (delta-B) on the ground and their time derivative (dB/dt) was performed at the Community Coordinated Modeling Center starting in 2010. This study resulted in the addition of the Space Weather Modling Framework to the suite of operational models run by the NOAA Space Weather Prediction Center (SWPC). Since then, magnetic pertubations have been made available on a larger scale for Run-on-Request simulations in geospace at the CCMC. We will demonstrate recent additions to the suite of analysis tools and model results including magnetic perturbations at more stations and on a grid of positions from both, original model outputs (SWMF using preset run configurations) and post-processed calculations using CalcDeltaB and their analysis and visualization using the open-source Kamodo data access and analysis suite and the Comprehensive Assessment of Models and Events using Library tools (CAMEL) application.

Lutz Rastaetter↗

Far-infrared emission in the Rho Ophiuchi region - A comparison with molecular gas emission and visual extinction

The dust characteristics of a 40 arcmin x 40 arcmin section of the Rho Ophiuchi molecular clouds complex revealed by the IRAS satellite are compared with both molecular line and deep star count data for the region. The data reveal the cloud to be clearly visible at 12 and 25 microns, as well as at 60 and 100 microns. Modeling the infrared emission from the cloud as being due to two populations of dust grains, the short-wavelength emission is found not to reflect the internal structure of the molecular cloud. The 60 micron opacity determined using a single grain emission model correlates reasonably well with (C-13)O column density and visual extinction up to roughly 5 mag. The cloud edges appear to be heated by the interstellar radiation field. The far-infrared luminosity to mass ratio for the region is determined to be 0.9 solar luminosity/solar mass, a value much smaller than the average ratio for the inner Galaxy.

Jarrett, T. H.↗

A Julia Framework for Graph-Structured Nonlinear Optimization

Graph theory provides a convenient framework for modeling and solving structured optimization problems. Under this framework, the modeler can arrange/assemble the components of an optimization model (variables, constraints, objective functions, and data) within nodes and edges of a graph, and this representation can be used to visualize, manipulate, and solve the problem. In this work, we present a Julia framework for modeling and solving graph-structured nonlinear optimization problems. Our framework integrates the modeling package Plasmo.jl (which facilitates the construction and manipulation of graph models) and the nonlinear optimization solver MadNLP.jl (which provides capabilities for exploiting graph structures to accelerate solution). We illustrate with a simple example how model construction and manipulation can be performed in an intuitive manner using Plasmo.jl and how the model structure can be exploited by MadNLP.jl. We also demonstrate the scalability of the framework by targeting a large-scale, stochastic gas network problem that contains over 1.7 million variables.

Cole, David↗

A Global, Multi-Waveband Model for the Zodiacal Cloud

This recently completed three-year project was undertaken by the PI at the University of Florida, NASA Goddard and JPL, and by the Co-I and Collaborator at the University of Florida. The funding was used to support a continuation of research conducted at the University of Florida over the last decade which focuses on the dynamics of dust particles in the interplanetary environment. The main objectives of this proposal were: To produce improved dynamical models of the zodiacal cloud by performing numerical simulations of the orbital evolution of asteroidal and cometary dust particles. To provide visualizations of the results using our visualization software package, SIMUL, simulating the viewing geometries of IRAS and COBE and comparing the model results with archived data. To use the results to provide a more accurate model of the brightness distribution of the zodiacal cloud than existing empirical models. In addition, our dynamical approach can provide insight into fundamental properties of the cloud, including but not limited to the total mass and surface area of dust, the size-frequency distribution of dust, and the relative contributions of asteroidal and cometary material. The model can also be used to provide constraints on trace signals from other sources, such as dust associated with the "Plutinos" , objects captured in the 2:3 resonance with Neptune.

Grogan, Keith↗

Common Methodology for Efficient Airspace Operations

Topics include: a) Developing a common methodology to model and avoid disturbances affecting airspace. b) Integrated contrails and emission models to a national level airspace simulation. c) Developed capability to visualize, evaluate technology and alternate operational concepts and provide inputs for policy-analysis tools to reduce the impact of aviation on the environment. d) Collaborating with Volpe Research Center, NOAA and DLR to leverage expertise and tools in aircraft emissions and weather/climate modeling. Airspace operations is a trade-off balancing safety, capacity, efficiency and environmental considerations. Ideal flight: Unimpeded wind optimal route with optimal climb and descent. Operations degraded due to reduction in airport and airspace capacity caused by inefficient procedures and disturbances.

Sridhar, Banavar↗

Hot gas ingestion test results of a two-poster vectored thrust concept with flow visualization in the NASA Lewis 9- x 15-foot low speed wind tunnel

A 9.2 percent scale Short Takeoff and Vertical Landing (STOVL) hot gas ingestion model was designed and built by McDonnell Douglas Corporation (MCAIR) and tested in the Lewis Research Center 9 x 15 foot Low Speed Wind Tunnel (LSWT). Hot gas ingestion, the entrainment of heated engine exhaust into the inlet flow field, is a key development issure for advanced short takeoff and vertical landing aircraft. Flow visualization from the Phase 1 test program, which evaluated the hot ingestion phenomena and control techniques, is covered. The Phase 2 test program evaluated the hot gas ingestion phenomena at higher temperatures and used a laser sheet to investigate the flow field. Hot gas ingestion levels were measured for the several forward nozzle splay configurations and with flow control/life improvement devices (LIDs) which reduced the hot gas ingestion. The model support system had four degrees of freedom - pitch, roll, yaw, and vertical height variation. The model support system also provided heated high-pressure air for nozzle flow and a suction system exhaust for inlet flow. The test was conducted at full scale nozzle pressure ratios and inlet Mach numbers. Test and data analysis results from Phase 2 and flow visualization from both Phase 1 and 2 are documented. A description of the model and facility modifications is also provided. Headwind velocity was varied from 10 to 23 kn. Results are presented over a range of nozzle pressure ratios at a 10 kn headwind velocity. The Phase 2 program was conducted at exhaust nozzle temperatures up to 1460 R and utilized a sheet laser system for flow visualization of the model flow field in and out of ground effects. The results reported are for nozzle exhaust temperatures up to 1160 R. These results will contain the compressor face pressure and temperature distortions, the total pressure recovery, the inlet temperature rise, and the environmental effects of the hot gas. The environmental effects include the ground plane contours, the model airframe heating, and the location of the ground flow separation.

Johns, Albert L.↗

Geometric Interpretation of the Cluster Location Problem Part I: Theory

We present a new framing of the seismic location problem using principles drawn from differential geometry. Our interpretation relies upon the common assumption that travel times observed across a network are continuous, differentiable functions of source location. In consequence, travel‐time functions constitute a differentiable map between the source region and a Riemannian manifold. The manifold is said to be the image of the source region embedded in a generally high‐dimension travel‐time vector space. A cluster of events in the source region has an image of discrete points on the manifold, that, except in the simplest cases, cannot be viewed directly. However, it is possible to project the image of a cluster into a tangent space of the manifold for direct visualization. The projection operator can be computed directly from the data without a velocity model, but produces a distorted rendering of the cluster geometry. With a model we can predict the distortions and correct them to estimate cluster geometry. We develop these points with the simplest possible example, one for which direct visualization of the manifold is possible, using the example as an introduction to the relevant concepts from differential geometry in a familiar setting. The tangent space, a local linearization of the manifold, plays a key role. We develop a metric to estimate the limits of linearization, that is, to determine when the curvature of the manifold invalidates the linear assumption. We also examine the interplay of model error, inadequate network geometry, and pick error. We then generalize our results from the simple case to the general case of 3D source regions observed by general networks. Although we do suggest a new “project and correct” method for location, we do not develop it into a practical algorithm. In conclusion, our intention rather is to highlight new analytical methods grounded in differential geometry.

East Pacific Ocean Islands↗

Block Island Noise Modeling Data

Noise propagation near Block Island was simulated to assess environmental impacts of impact pile driving during wind turbine construction. Computational models complement field-recorded acoustic data, providing insights into sound attenuation, spectral variability, and propagation dynamics. The dataset includes: 1. Propagation Models: Simulated underwater sound fields documenting sound pressure and directional variability across frequency bands and distances. 2. Spectral Analysis (LTSA): Long-term averages and processed outputs calculating acoustic intensity over time. 3. Visualization Files: Graphs, 2D/3D simulation results, and reference calculations used in sound modeling.

17 WIND ENERGY↗

Mathematical Modeling of an Oscillating Droplet

Oscillating droplets are of interest in a number of disciplines. A practical application is the oscillating drop method, which is a technique for measuring surface tension and viscosity of liquid metals. It is especially suited to undercooled and highly reactive metals, because it is performed by electromagnetic levitation. The natural oscillation frequency of the droplets is related to the surface tension of the material, and the decay of oscillations is related to its viscosity. The fluid flow inside the droplet must be laminar in order for this technique to yield good results. Because no experimental method has yet been developed to visualize flow in electromagnetically-levitated oscillating metal droplets, mathematical modeling is required to determine whether or not turbulence occurs. Three mathematical models of the flow: (1) assuming laminar conditions, (2) using the k-epsilon turbulence model, and (3) using the RNG turbulence model, respectively, are compared and contrasted to determine the physical characteristics of the flow. It is concluded that the RNG model is the best suited for describing this problem. The goal of the presented work was to characterize internal flow in an oscillating droplet of liquid metal, and to verify the accuracy of the characterization by comparing calculated surface tension and viscosity.

Berry, S.↗

Effects of simulator variations on the fidelity of a UH-60 Black Hawk simulation

The validity of the vertical motion simulator used to simulate the UH-60A Black Hawk helicopter is evaluated. Aircraft simulation of bob-up, hover turn, and dash/quick stop manuevers are compared to actual flight data. The effects of variations in the simulator's visual and motion characteristics on the simulation data are investigated. Data obtained with the nonintrusive parameter identification procedure and optimal control measures are applied to the helicopter math model used for real-time aircraft simulation. Analysis of the model reveals that the simulated aircraft is underdamped, and the changes in the visual reference have the greatest effect on the ability of the pilot to perform the maneuvers.

Cleveland, W. B.↗

Some Observations on the Current Status of Performing Finite Element Analyses

Aerospace structures are complex high-performance structures. Advances in reliable and efficient computing and modeling tools are enabling analysts to consider complex configurations, build complex finite element models, and perform analysis rapidly. Many of the early career engineers of today are very proficient in the usage of modern computers, computing engines, complex software systems, and visualization tools. These young engineers are becoming increasingly efficient in building complex 3D models of complicated aerospace components. However, the current trends demonstrate blind acceptance of the results of the finite element analysis results. This paper is aimed at raising an awareness of this situation. Examples of the common encounters are presented. To overcome the current trends, some guidelines and suggestions for analysts, senior engineers, and educators are offered.

Raju, Ivatury S.↗

VTK-m User's Guide (V.1.6)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures.

97 MATHEMATICS AND COMPUTING↗