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At least 1,063 records · Page 59

Post-Flight Estimation of Motion of Space Structures: Part 1

A computer program estimates the relative positions and orientations of two space structures from data on the angular positions and distances of fiducial objects on one structure as measured by a target tracking electronic camera and laser range finders on another structure. The program is written specifically for determining the relative alignments of two antennas, connected by a long truss, deployed in outer space from a space shuttle. The program is based partly on transformations among the various coordinate systems involved in the measurements and on a nonlinear mathematical model of vibrations of the truss. The program implements a Kalman filter that blends the measurement data with data from the model. Using time series of measurement data from the tracking camera and range finders, the program generates time series of data on the relative position and orientation of the antennas. A similar program described in a prior NASA Tech Briefs article was used onboard for monitoring the structures during flight. The present program is more precise and designed for use on Earth in post-flight processing of the measurement data to enable correction, for antenna motions, of scientific data acquired by use of the antennas.

Brugarolas, Paul↗

Symbolic Processing Combined with Model-Based Reasoning

A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

James, Mark↗

Modeling and Simulation of the Second-Generation Orion Crew Module Air Bag Landing System

Air bags were evaluated as the landing attenuation system for earth landing of the Orion Crew Module (CM). An important element of the air bag system design process is proper modeling of the proposed configuration to determine if the resulting performance meets requirements. Analysis conducted to date shows that airbags are capable of providing a graceful landing of the CM in nominal and off-nominal conditions such as parachute failure, high horizontal winds, and unfavorable vehicle/ground angle combinations. The efforts presented here surround a second generation of the airbag design developed by ILC Dover, and is based on previous design, analysis, and testing efforts. In order to fully evaluate the second generation air bag design and correlate the dynamic simulations, a series of drop tests were carried out at NASA Langley's Landing and Impact Research (LandIR) facility. The tests consisted of a full-scale set of air bags attached to a full-scale test article representing the Orion Crew Module. The techniques used to collect experimental data, construct the simulations, and make comparisons to experimental data are discussed.

Timmers, Richard B.↗

Modeling and Simulation of the Second-Generation Orion Crew Module Air Bag Landing System

Air bags were evaluated as the landing attenuation system for earth landing of the Orion Crew Module (CM). Analysis conducted to date shows that airbags are capable of providing a graceful landing of the CM in nominal and off-nominal conditions such as parachute failure, high horizontal winds, and unfavorable vehicle/ground angle combinations, while meeting crew and vehicle safety requirements. The analyses and associated testing presented here surround a second generation of the airbag design developed by ILC Dover, building off of relevant first-generation design, analysis, and testing efforts. In order to fully evaluate the second generation air bag design and correlate the dynamic simulations, a series of drop tests were carried out at NASA Langley s Landing and Impact Research (LandIR) facility in Hampton, Virginia. The tests consisted of a full-scale set of air bags attached to a full-scale test article representing the Orion Crew Module. The techniques used to collect experimental data, develop the simulations, and make comparisons to experimental data are discussed.

Timmers, Richard B.↗

Propulsion Flight-Test Fixture

NASA Dryden Flight Research Center s new Propulsion Flight Test Fixture (PFTF), designed in house, is an airborne engine-testing facility that enables engineers to gather flight data on small experimental engines. Without the PFTF, it would be necessary to obtain such data from traditional wind tunnels, ground test stands, or laboratory test rigs. Traditionally, flight testing is reserved for the last phase of engine development. Generally, engines that embody new propulsion concepts are not put into flight environments until their designs are mature: in such cases, either vehicles are designed around the engines or else the engines are mounted in or on missiles. However, a captive carry capability of the PFTF makes it possible to test engines that feature air-breathing designs (for example, designs based on the rocket-based combined cycle) economically in subscale experiments. The discovery of unknowns made evident through flight tests provides valuable information to engine designers early in development, before key design decisions are made, thereby potentially affording large benefits in the long term. This is especially true in the transonic region of flight (from mach 0.9 to around 1.2), where it can be difficult to obtain data from wind tunnels and computational fluid dynamics. In January 2002, flight-envelope expansion to verify the design and capabilities of the PFTF was completed. The PFTF was flown on a specially equipped supersonic F-15B research testbed airplane, mounted on the airplane at a center-line attachment fixture, as shown in Figure 1. NASA s F-15B testbed has been used for several years as a flight-research platform. Equipped with extensive research air-data, video, and other instrumentation systems, the airplane carries externally mounted test articles. Traditionally, the majority of test articles flown have been mounted at the centerline tank-attachment fixture, which is a hard-point (essentially, a standardized weapon-mounting fixture). This hard-point has large weight margins, and, because it is located near the center of gravity of the airplane, the weight of equipment mounted there exerts a minimal effect on the stability and controllability of the airplane. The PFTF (see Figure 2) includes a one-piece aluminum structure that contains space for instrumentation, propellant tanks, and feed-system components. The PFTF also houses a force balance, on which is mounted the subscale engine or other experimental apparatus that is to be the subject of a flight test. The force balance measures a combination of inertial and aerodynamic forces and moments acting on the experimental apparatus.

Palumbo, Nate↗

Upper Limits on a Stochastic Gravitational-Wave Background Using LIGO and Virgo Interferometers at 600-1000 Hz

A stochastic background of gravitational waves is expected to arise from a superposition of many incoherent sources of gravitational waves, of either cosmological or astrophysical origin. This background is a target for the current generation of ground-based detectors. In this article we present the first joint search for a stochastic background using data from the LIGO and Virgo interferometers. In a frequency band of 600-1000 Hz, we obtained a 95% upper limit on the amplitude of omega(sub GW)(f) = omega(sub 3) (f/900Hz)3, of omega(sub 3) < 0.33, assuming a value of the Hubble parameter of h(sub 100) = 0.72. These new limits are a factor of seven better than the previous best in this frequency band.

Abadie, J.↗

Fiber-Optic Strain-Based Deflection and Twist Sensing for a High-Aspect-Ratio Swept Wing

Designs of aircraft structures have been moving toward leaner, lightweight designs for increased fuel efficiency. The Passive Aeroelastic Tailored (PAT) wing developed under the NASA Advanced Air Transport Technology (AATT) project is an example of a swept-wing design with high aspect ratio that incorporates lightweight highly-flexible tailored composite construction. The passive aeroelastic tailored structural design has explored the design space to enable aeroelastically tailored wing structures to increase aspect ratios (from 9 to 14) and ultimately reduce weight by 20 percent to 25 percent without impacting aeroelastic performance. To further study the aeroelastic performance of such a wing, the NASA Armstrong Flight Research Center (AFRC) (Edwards, California) has developed efficient real-time structural algorithms that are used in conjunction with a fiber-optic measurement system for lightweight vehicle applications. The AFRC Fiber Optic Sensing System (FOSS) provides up to 8,000 distributed surface strain measurements at one-half-inch increments and can be used to estimate a variety of structural parameters such as shape and load. This report discusses the implementation of strain-based displacement and twist-sensing techniques applied to the PAT wing test article tested at the NASA AFRC Flight Loads Laboratory. Empirical FOSS strain data are collected under varying loading conditions. Strain data are processed with the displacement and twist-sensing algorithms and independently verified by comparison to conventional ground-based instrumentation.

Pena, Francisco↗

Dynamic Characterization of the Crew Module Uprighting System for NASA’s Orion Crew Module

The Orion Crew Module Uprighting System is a set of five airbag that are responsible for the uprighting of the crew module in the case of an inverted splashdown. A series of tests during the Underway Recovery Test 7 (URT-7) were run in preparation for the Artemis I mission, where the dynamic characterization of the CMUS in an ocean wave environment was performed. A Datawell Waverider DWR-G4 wave buoy was deployed to the characterize the wave environment during these tests. The heave measurements from this buoy were projected to the Orion Crew Module Buoyancy Test Article location by two different methods: (1) directly time-shifting the data, and (2) performing a frequency-domain, phase-shifting operation. Results demonstrate that the phase-shifting operation led to better correlation with the true crew module response to wave excitation as compared with the purely time-shifted method. Additionally, a novel approach to localize an object in a bidirectional wave field based on its heave response is presented and validated with URT- 7 data. Given a wave measurement device at a known location, one can estimate the relative distance to another object based solely off its heave response. Results show that if signals have sufficiently good correlation, this method can be used to estimate the relative separation between two objects in the same wave field.

Vertaska, Ivan Bertaska↗

Microwave Radiometer RFI Detection Using Deep Learning

Radio frequency interference (RFI) is a risk for microwave radiometers due to their requirement of very high sensitivity. The Soil Moisture Active Passive (SMAP) mission has an aggressive approach to RFI detection and filtering using dedicated spaceflight hardware and ground processing software. As more sensors push to observe at larger bandwidths in unprotected or shared spectrum, RFI detection continues to be essential. This article presents a deep learning approach to RFI detection using SMAP spectrogram data as input images. The study utilizes the benefits of transfer learning to evaluate the viability of this method for RFI detection in microwave radiometers. The well-known pretrained convolutional neural networks, AlexNet, GoogleNet, and ResNet-101 were investigated. ResNet-101 provided the highest accuracy with respect to validation data (99%), while AlexNet exhibited the highest agreement with SMAP detection (92%).

Microwave radiometry↗

Validation of Transient Spacecraft Refueling Model with Gateway Breadboard Test Data

The ability to refuel spacecraft on-orbit is a key enabling technology for deep space human exploration. On-orbit refueling requires priming a pressurized liquid propellant from a source tank into fluid transfer lines at vacuum conditions, which could result in excessive surge pressures beyond the system’s qualified operating limits and potentially damage hardware. Another source of potentially damaging surge pressures is the water hammer transient that occurs when the isolation valves are closed to pause or end the refueling operation. Therefore, it is imperative to employ numerical models during the development of flight hardware to parametrically characterize system performance over a wide range of operating conditions to minimize the risk of exceeding pressure limits during flight. Since rapid pressure transients can be difficult to model accurately, it is important to validate those models with test data. As part of the Gateway bipropellant refueling system development, a simplified fluidic breadboard system was created using water as a simulant for fuel to support early program risk reduction of refueling operations. The objectives of breadboard testing were to gather performance data to characterize and demonstrate critical refueling operations and to validate numerical models that can be extended to predicting flight system performance. A description of the breadboard test article and the results of numerical model validation is presented. The model is shown to have very good agreement with test data.

Refueling↗

Capability Improvements at Marshall Space Flight Center's X-Ray and Cryogenic Facility

The X-Ray & Cryogenic Facility (XRCF) at Marshall Space Flight Center is the world’s largest x-ray optic calibration facility and NASA’s premier cryogenic optical test facility. Built specifically to calibrate the Chandra telescope, the facility contributed to several other x-ray missions until 2005 when it became dedicated to normal incidence optical testing at cryogenic temperatures. Recently the facility’s x-ray test capability has been returned to service and updated. New beam monitors, focal plane detectors, and test article and instrument positioning systems have been added. The x-ray data acquisition system has been updated. A real-time position monitoring metrology system is being developed that will enable calibration of large diameter optics via partial illumination in a diverging beam. The newly expanded x-ray test capabilities of the facility will be discussed.

XRCF↗

Systems and methods for generating a molecular dynamic graded lattice structure and their application to additive manufacturing

Systems and methods for generating molecular dynamic graded lattice structures that can be used as infill for additively manufactured articles. Molecular dynamically generated lattice infill is based on force balancing a node distribution instead of a circle packing. Field data can be utilized to adjust the spacing of the node distribution according to a force balance equilibrium model that accounts for the field expected to be experienced by the article being additively manufactured. The resultant non-uniform honeycomb structures from force-balancing robustly and efficiently address the connection issues with traditional non-uniform lattice structures.

Kim, Seokpum↗

Making sense of uncertain nuclear data

At its core, and in an imperfect world, the scientific method relies heavily on the concept of uncertain knowledge. Understanding the nature and magnitude of our lack of knowledge on nuclear data has important ramifications on a wide range of nuclear technologies that encompass defense, energy, medicine, astrophysics, among others. Over the span of a long and fruitful carrier, Dr. Massimo Salvatores has made significant contributions to the fields of nuclear reactor physics, nuclear data, and uncertainty quantification and propagation. Advances in machine learning techniques and computational capabilities are enabling a new level of confidence in our ability to predict key nuclear metrics as well as their associated uncertainties across many applications. Here this short article reviews some of those concepts with an eye towards developing a new paradigm to provide nuclear data libraries of benefit to various applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Hybrid FEA/SEA Assessment for an Orthogrid Cylindrical Panel Section and Periodic Subsystem Modeling Evaluation

In the lower frequency range, where particular boundary conditions can make a significant difference to panel response characteristics Statistical Energy Analysis (SEA) has never been the analytical tool of choice. In addition to boundary condition effects, SEA is not well suited in frequency bands where no modes or less than a few modes exist. The advent of the Hybrid Module has enabled integration of Finite Element Analysis to expand and enhance the capability for response calculations within VA One into the lower frequency range. Exploration of several additional modeling approaches was completed for the cylindrical orthogrid panel test article that was examined in Reference 1. Comparison of the new analytical response predictions with the measured response data from ground test and the pure SEA results from the reference will be presented. One approach that is considered promising is the periodic subsystem capability. Initially, a detailed FEM of just one region of the test article is defined. After evaluating this small region using symmetric boundary conditions, the FEM may be expanded to determine the properties of the entire system using similar connected regions that map over the entire test article. Another approach is the direct use of a very detailed finite element model of the entire panel, explicitly modeling pocket and rib details of the structure. A third approach is to approximate localized structure geometry details with a smeared property generalization using a PCOMP (NASTRAN card used to define layered composite structures) to define skin layer and ribbed layer for the orthogrid panel. The authors expect to demonstrate that the integrated Hybrid/FEM approach increases confidence in response prediction in the lower frequency range (for example from 20-300 Hz for the test article under consideration). In addition the strength and weakness of each additional approach will be highlighted and compared to those reported with those reported in an earlier paper

Smith, Andrew M.↗

The Planetary Data System Distributed Inventory System

The advent of the World Wide Web (Web) and the ability to easily put data repositories on-line has resulted in a proliferation of digital libraries. The heterogeneity of the underlying systems, the autonomy of the individual sites, and distributed nature of the technology has made both interoperability across the sites and the search for resources within a site major research topics. This article will describe a system that addresses both issues using standard Web protocols and meta-data labels to implement an inventory of on-line resources across a group of sites. The success of this system is strongly dependent on the existence of and adherence to a standards architecture that guides the management of meta-data within participating sites.

Hughes, J. Steven↗

Co-Simulation of Building Energy and Control Systems with the Building Controls Virtual Test Bed

This article describes the implementation of the Building Controls Virtual Test Bed (BCVTB). The BCVTB is a software environment that allows connecting different simulation programs to exchange data during the time integration, and that allows conducting hardware in the loop simulation. The software architecture is a modular design based on Ptolemy II, a software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. The BCVTB provides additions to Ptolemy II that allow the run-time coupling of different simulation programs for data exchange, including EnergyPlus, MATLAB, Simulink and the Modelica modelling and simulation environment Dymola. The additions also allow executing system commands, such as a script that executes a Radiance simulation. In this article, the software architecture is presented and the mathematical model used to implement the co-simulation is discussed. The simulation program interface that the BCVTB provides is explained. The article concludes by presenting applications in which different state of the art simulation programs are linked for run-time data exchange. This link allows the use of the simulation program that is best suited for the particular problem to model building heat transfer, HVAC system dynamics and control algorithms, and to compute a solution to the coupled problem using co-simulation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Protein subcellular location pattern classification in cellular images using latent discriminative models

Motivation: Knowledge of the subcellular location of a protein is crucial for understanding its functions. The subcellular pattern of a protein is typically represented as the set of cellular components in which it is located, and an important task is to determine this set from microscope images. In this article, we address this classification problem using confocal immunofluorescence images from the Human Protein Atlas (HPA) project. The HPA contains images of cells stained for many proteins; each is also stained for three reference components, but there are many other components that are invisible. Given one such cell, the task is to classify the pattern type of the stained protein. We first randomly select local image regions within the cells, and then extract various carefully designed features from these regions. This region-based approach enables us to explicitly study the relationship between proteins and different cell components, as well as the interactions between these components. To achieve these two goals, we propose two discriminative models that extend logistic regression with structured latent variables. The first model allows the same protein pattern class to be expressed differently according to the underlying components in different regions. The second model further captures the spatial dependencies between the components within the same cell so that we can better infer these components. To learn these models, we propose a fast approximate algorithm for inference, and then use gradient-based methods to maximize the data likelihood. Results: In the experiments, we show that the proposed models help improve the classification accuracies on synthetic data and real cellular images. The best overall accuracy we report in this article for classifying 942 proteins into 13 classes of patterns is about 84.6%, which to our knowledge is the best so far. In addition, the dependencies learned are consistent with prior knowledge of cell organization.

59 BASIC BIOLOGICAL SCIENCES↗

An open-access simulated earthquake ground-motion database for an M7 Hayward Fault earthquake in the San Francisco Bay Region

Comprehensive understanding of earthquake ground motions, particularly in the near-fault region of large-magnitude events, is limited by gaps in strong-motion data. This challenge is prominent in areas with high seismic hazard but infrequent large earthquakes where data is sparse and difficult to interpret. These data limitations lead to uncertainties in the development of site-specific ground motions, which are crucial for engineering risk assessments. To address these challenges, physics-based regional-scale ground-motion simulations have been developed. With the emergence of exaflop-scale computing ecosystems, it is now possible to simulate regional earthquake processes at unprecedented fidelity and generate the large number of fault rupture realizations necessary to characterize both intra- and inter-event ground-motion variability. This article introduces a new database of simulated earthquake ground motions, created for applications in earthquake engineering, earthquake planning, and emergency response. The inaugural version of the database features simulated ground motions for a magnitude 7 Hayward Fault earthquake in the San Francisco Bay Region (SFBR), using the EarthQuake SIMulation (EQSIM) simulation framework and the Graves–Pitarka kinematic rupture model. The aim is to provide high-fidelity, spatially dense, three-component motions generated on the Department of Energy’s (DOE) newest generation of graphics processing unit (GPU)-accelerated supercomputers. These motions are being made openly available to the engineering, scientific, and disaster planning communities. In addition, this work develops protocols for the efficient dissemination of these large data sets and emphasizes community engagement to build confidence in their application. This article discusses the methodology behind the data, underlying software verification and validation, scalable data management, and a user interface for data access. The goal is to facilitate widespread use and elicit expert feedback to maximize the utility and exploitation of simulated motions. While the initial focus is on the San Francisco Region, simulations for additional regions will be added as the DOE program progresses.

Simulated ground-motion database↗