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At least 883 records · Page 49

Precision of Sensitivity in the Design Optimization of Indeterminate Structures

Design sensitivity is central to most optimization methods. The analytical sensitivity expression for an indeterminate structural design optimization problem can be factored into a simple determinate term and a complicated indeterminate component. Sensitivity can be approximated by retaining only the determinate term and setting the indeterminate factor to zero. The optimum solution is reached with the approximate sensitivity. The central processing unit (CPU) time to solution is substantially reduced. The benefit that accrues from using the approximate sensitivity is quantified by solving a set of problems in a controlled environment. Each problem is solved twice: first using the closed-form sensitivity expression, then using the approximation. The problem solutions use the CometBoards testbed as the optimization tool with the integrated force method as the analyzer. The modification that may be required, to use the stiffener method as the analysis tool in optimization, is discussed. The design optimization problem of an indeterminate structure contains many dependent constraints because of the implicit relationship between stresses, as well as the relationship between the stresses and displacements. The design optimization process can become problematic because the implicit relationship reduces the rank of the sensitivity matrix. The proposed approximation restores the full rank and enhances the robustness of the design optimization method.

Patnaik, Surya N.↗

UHF Relay Antenna Measurements on Phoenix Mars Lander Mockup

The Phoenix Lander, a NASA Discovery mission which lands on Mars in the spring of 2008, will rely entirely on UHF relay links between it and Mars orbiting assets, (Odyssey and Mars Reconnaissance Orbiter (MRO)), to communicate with the Earth. As with the Mars Exploration Rover (MER) relay system, non directional antennas will be used to provide roughly emispherical coverage of the Martian sky. Phoenix lander deck object pattern interference and obscuration are significant, and needed to be quantified to answer system level design and operations questions. This paper describes the measurement campaign carried out at the SPAWAR (Space and Naval Warfare Research) Systems Center San Diego (SSC-SD) hemispherical antenna range, using a Phoenix deck mockup and engineering model antennas. One goal of the measurements was to evaluate two analysis tools, the time domain CST, and the moment method WIPL-D software packages. These would subsequently be used to provide pattern analysis for configurations that would be difficult and expensive to model and test on Earth.

scattering↗

Arbitrary Shape Deformation in CFD Design

Sculptor(R) is a commercially available software tool, based on an Arbitrary Shape Design (ASD), which allows the user to perform shape optimization for computational fluid dynamics (CFD) design. The developed software tool provides important advances in the state-of-the-art of automatic CFD shape deformations and optimization software. CFD is an analysis tool that is used by engineering designers to help gain a greater understanding of the fluid flow phenomena involved in the components being designed. The next step in the engineering design process is to then modify, the design to improve the components' performance. This step has traditionally been performed manually via trial and error. Two major problems that have, in the past, hindered the development of an automated CFD shape optimization are (1) inadequate shape parameterization algorithms, and (2) inadequate algorithms for CFD grid modification. The ASD that has been developed as part of the Sculptor(R) software tool is a major advancement in solving these two issues. First, the ASD allows the CFD designer to freely create his own shape parameters, thereby eliminating the restriction of only being able to use the CAD model parameters. Then, the software performs a smooth volumetric deformation, which eliminates the extremely costly process of having to remesh the grid for every shape change (which is how this process had previously been achieved). Sculptor(R) can be used to optimize shapes for aerodynamic and structural design of spacecraft, aircraft, watercraft, ducts, and other objects that affect and are affected by flows of fluids and heat. Sculptor(R) makes it possible to perform, in real time, a design change that would manually take hours or days if remeshing were needed.

Landon, Mark↗

Constrained Reference Star Differential Imaging: Enabling High-fidelity Imagery of Highly Structured Circumstellar Disks

High-contrast imaging presents us with the opportunity to study circumstellar disks and the planets still embedded within them, providing key insights into the formation and evolution of planetary systems. However, the postprocessing techniques that are often needed to suppress stellar halo light typically result in significant and variable loss of circumstellar light, even when using relatively conservative approaches like reference star differential imaging (RDI). We introduce “constrained reference star differential imaging” (constrained RDI), a new class of RDI point-spread-function (PSF) subtraction techniques for systems with circumstellar disks. Constrained RDI utilizes either high-resolution polarized-intensity (PI) images or disk models to severely limit or even eliminate the signal loss due to oversubtraction that is common to RDI. We demonstrate the ability of constrained RDI utilizing polarimetric data to yield an oversubtraction-free detection of the AB Aurigae protoplanetary disk in total intensity. PI-constrained RDI allows us to decisively recover the spectral signature of the confirmed, recently discovered protoplanet, AB Aurigae b. We further demonstrate that constrained RDI can be a powerful analysis tool for soon-to-be-acquired James Webb Space Telescope coronagraphic imaging of disks. In both cases, constrained RDI provides analysis-ready products that enable more detailed studies of disks and more robust verification of embedded exoplanets.

Kellen Lawson↗

A Study on the Development of Service Quality Index for Incheon International Airport

The main purpose of this study is located at developing Ominibus Monitors System(OMS) for internal management, which will enable to establish standards, finding out matters to be improved, and appreciation for its treatment in a systematic way. It is through developing subjective or objective estimation tool with use importance, perceived level, and complex index at international airport by each principal service items. The direction of this study came towards for the purpose of developing a metric analysis tool, utilizing the Quantitative Second Data, Analysing Perceived Data through airport user surveys, systemizing the data collection-input-analysis process, making data image according to graph of results, planning Service Encounter and endowing control attribution, and ensuring competitiveness at the minimal international standards. It is much important to set up a pre-investigation plan on the base of existent foreign literature and actual inspection to international airport. Two tasks have been executed together on the base of this pre-investigation; one is developing subjective estimation standards for departing party, entering party, and airport residence and the other is developing objective standards as complementary methods. The study has processed for the purpose of monitoring services at airports regularly and irregularly through developing software system for operating standards after ensuring credibility and feasibility of estimation standards with substantial and statistical way.

Lee, Kang Seok↗

Boundary-Layer Transition Prediction Through Loose Coupling of OVERFLOW and LASTRAC

Transition prediction based on linear stability theory is expected to more accurately reflect the causality of transition onset than phenomenological transition models based on RANS-like transport equations. To help achieve the CFD vision 2030 aim of building a CFD tool chain with automated prediction of boundary layer transition, a technique to loosely tie the NASA OVERFLOW CFD solver with the LASTRAC stability analysis tool is described. The coupled solver is then used to compute transition over selected over a flat plate in a freestream with sufficiently low levels of turbulence, NLF(1)-0416 airfoil, the 6:1 prolate spheroid at an angle of attack, and a NASA juncture flow model with symmetric wing configuration. The findings show that the loosely coupled approach can reliably predict the transition location accurately in scenarios that are dominated by a single transition mechanism involving Tollmien-Schlichting instabilities, crossflow instabilities, or separation bubble-induced transition, or include a mixture of selected mechanisms. The toolset presents here appears to be robust to the prescription of the initial transition location, and it can lead to a converged solution in four or five rounds of the mean flow calculation and stability analysis, with minimal input from the user.

boundary layer transition↗

Tool Support for Parametric Analysis of Large Software Simulation Systems

The analysis of large and complex parameterized software systems, e.g., systems simulation in aerospace, is very complicated and time-consuming due to the large parameter space, and the complex, highly coupled nonlinear nature of the different system components. Thus, such systems are generally validated only in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. We have addressed the factors deterring such an analysis with a tool to support envelope assessment: we utilize a combination of advanced Monte Carlo generation with n-factor combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. Additional test-cases, automatically generated from models (e.g., UML, Simulink, Stateflow) improve the coverage. The distributed test runs of the software system produce vast amounts of data, making manual analysis impossible. Our tool automatically analyzes the generated data through a combination of unsupervised Bayesian clustering techniques (AutoBayes) and supervised learning of critical parameter ranges using the treatment learner TAR3. The tool has been developed around the Trick simulation environment, which is widely used within NASA. We will present this tool with a GN&C (Guidance, Navigation and Control) simulation of a small satellite system.

Schumann, Johann↗

Integrated Data Visualization and Virtual Reality Tool

The Integrated Data Visualization and Virtual Reality Tool (IDVVRT) Phase II effort was for the design and development of an innovative Data Visualization Environment Tool (DVET) for NASA engineers and scientists, enabling them to visualize complex multidimensional and multivariate data in a virtual environment. The objectives of the project were to: (1) demonstrate the transfer and manipulation of standard engineering data in a virtual world; (2) demonstrate the effects of design and changes using finite element analysis tools; and (3) determine the training and engineering design and analysis effectiveness of the visualization system.

Dryer, David A.↗

Simple Sensitivity Analysis for Orion GNC

The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch.We describe in this paper a sensitivity analysis tool (Critical Factors Tool or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.

Monte Carlo Simulation↗

SyReNN: A tool for analyzing deep neural networks

Deep Neural Networks (DNNs) are rapidly gaining popularity in a variety of important domains. Unfortunately, modern DNNs have been shown to be vulnerable to a variety of attacks and buggy behavior. This has motivated recent work in formally analyzing the properties of such DNNs. Furthermore, this paper introduces SyReNN, a tool for understanding and analyzing a DNN by computing its symbolic representation. The key insight is to decompose the DNN into linear functions. Our tool is designed for analyses using low-dimensional subsets of the input space, a unique design point in the space of DNN analysis tools. We describe the tool and the underlying theory, then evaluate its use and performance on three case studies: computing Integrated Gradients, visualizing a DNN’s decision boundaries, and repairing buggy DNNs.

97 MATHEMATICS AND COMPUTING↗

TX$^2$: Transformer eXplainability and eXploration

The Transformer eXplainability and eXploration (Martindale & Stewart, 2021), or TX 2 software package, is a library designed for artificial intelligence researchers to better understand the performance of transformer models (Vaswani et al., 2017) used for sequence classification. The tool is capable of integrating with a trained transformer model and a dataset split into training and testing populations to produce an ipywidget (Project Jupyter Contributors, 2021) dashboard with a number of visualizations to understand model performance with an emphasis on explainability and interpretability. The TX 2 package is primarily intended to integrate into a workflow centered around Jupyter Notebooks (Kluyver et al., 2016), and currently assumes the use of PyTorch (Paszke et al., 2019) and Hugging Face transformers library (Wolf et al., 2020). The dashboard includes visualization and data exploration features to aid researchers, including an interactive UMAP embedding graph (McInnes et al., 2018) to understand classification clusters, a word salience map that can be updated as researchers alter textual entries in near real time, a set of tools to understand word frequency and importance based on the clusters in the UMAP embedding graph, and a set of traditional confusion matrix analysis tools.

97 MATHEMATICS AND COMPUTING↗

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY202 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY2020 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time-separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗

ResStock: Annual Baseline Results with Component Loads

The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and high-performance computing. This combination achieves unprecedented granularity and accuracy in modeling the diversity of the housing stock and the distributional impacts of building technologies in different communities. The annual baseline energy results from a national-scale ResStock run use typical meteorological year 3 (TMY3) files for energy simulations. Results include heating and cooling loads for individual components of each building. Component loads describe the heating/cooling load that can be attributed to specific elements of a home, such as heat transfer through walls or internal gains. Additionally, these results include the standard ResStock outputs for housing characteristics and numerous energy outputs by end-use and fuel. A snapshot of the ResStock version used to produce this data, including a configuration file for the run can be found using the Source Code resource link.

Array↗

User's guide to the Mission Analysis Evaluation and Space Trajectory Operations program (MAESTRO)

The MAESTRO system is a mission analysis tool designed to present to the user information necessary to make the various decisions required in the design and execution of a spaceflight mission. The system was designed so that it can be used in both the pre-launch mission planning phase of a mission and during the flight as an in-flight decision making tool. A description of each of the following modes is presented: (1) trajectory propagation mode; (2) retro-fire determination mode; (3) midcourse analysis determination mode; (4) Monte Carlo mode; (5) verification mode; (6) orbit stability mode; and (7) post injection trim mode. A description of the inputs necessary to run the program mode is given along with a sample case.

Lutzky, D.↗

CFD Modeling of Turbulent Duct Flows for Coolant Channel Analysis

The design of modern liquid rocket engines requires the analysis of chamber coolant channels to maximize the heat transfer while minimizing the coolant flow. Coolant channels often do not remain at a constant cross section or at uniform curvature. New designs require higher aspect ratio coolant channels than previously used. To broaden the analysis capability and to complement standard analysis tools an investigation on the accuracy of CFD predictions for coolant channel flow has been initiated. Validation of CFD capabilities for coolant channel analysis will enhance the capabilities for optimizing design parameters without resorting to extensive experimental testing. The eventual goal is to use CFD to determine the flow fields of unique coolant channel designs and therefore determine critical heat transfer coefficients. In this presentation the accuracy of a particular CFD code is evaluated for turbulent flows. The first part of the presentation is a comparison of numerical results to existing cold flow data for square curved ducts (NASA CR-3367, 'Measurements of Laminar and Turbulent Flow in a Curved Duct with Thin Inlet Boundary Layers'). The results of this comparison show good agreement with the relatively coarse experimental data. The second part of the presentation compares two cases of higher aspect ratio channels (AR=2.5,10) to show changes in axial and secondary flow strength. These cases match experimental work presently in progress and will be used for future validation. The comparison shows increased secondary flow strength of the higher aspect ratio case due to the change in radius of curvature. The presentation includes a test case with a heated wall to demonstrate the program's capability. The presentation concludes with an outline of the procedure used to validate the CFD code for future design analysis.

Ungewitter, Ronald J.↗

Robot Manipulator Technologies for Planetary Exploration

NASA exploration missions to Mars, initiated by the Mars Pathfinder mission in July 1997, will continue over the next decade. The missions require challenging innovations in robot design and improvements in autonomy to meet ambitious objectives under tight budget and time constraints. The authors are developing design tools, component technologies and capabilities to address these needs for manipulation with robots for planetary exploration. The specific developments are: 1) a software analysis tool to reduce robot design iteration cycles and optimize on design solutions, 2) new piezoelectric ultrasonic motors (USM) for light-weight and high torque actuation in planetary environments, 3) use of advanced materials and structures for strong and light-weight robot arms and 4) intelligent camera-image coordinated autonomous control of robot arms for instrument placement and sample acquisition from a rover vehicle.

Das, H.↗

Visual Analysis of Air Traffic Data

In this paper, we present visual analysis tools to help study the impact of policy changes on air traffic congestion. The tools support visualization of time-varying air traffic density over an area of interest using different time granularity. We use this visual analysis platform to investigate how changing the aircraft separation volume can reduce congestion while maintaining key safety requirements. The same platform can also be used as a decision aid for processing requests for unmanned aerial vehicle operations.

Albrecht, George Hans↗