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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Numerical Investigation of a Fuselage Boundary Layer Ingestion Propulsion Concept

In the present study, a numerical assessment of the performance of fuselage boundary layer ingestion (BLI) propulsion techniques was conducted. This study is an initial investigation into coupling the aerodynamics of the fuselage with a BLI propulsion system to determine if there is sufficient potential to warrant further investigation of this concept. Numerical simulations of flow around baseline, Boundary Layer Controlled (BLC), and propelled boundary layer controlled airships were performed. Computed results showed good agreement with wind tunnel data and previous numerical studies. Numerical simulations and sensitivity analysis were then conducted on four BLI configurations. The two design variables selected for the parametric study of the new configurations were the inlet area and the inlet to exit area ratio. Current results show that BLI propulsors may offer power savings of up to 85% over the baseline configuration. These interim results include the simplifying assumption that inlet ram drag is negligible and therefore likely overstate the reduction in power. It has been found that inlet ram drag is not negligible and should be included in future analysis.

Elmiligui, Alaa A.↗
DOE OSTI2022

A comparison of neural network architectures for data-driven reduced-order modeling

The popularity of deep convolutional autoencoders (CAEs) has engendered new and effective reduced-order models (ROMs) for the simulation of large-scale dynamical systems. Despite this, it is still unknown whether deep CAEs provide superior performance over established linear techniques or other network-based methods in all modeling scenarios. To elucidate this, the effect of autoencoder architecture on its associated ROM is studied through the comparison of deep CAEs against two alternatives: a simple fully connected autoencoder, and a novel graph convolutional autoencoder. Through benchmark experiments, it is shown that the superior autoencoder architecture for a given ROM application is highly dependent on the size of the latent space and the structure of the snapshot data, with the proposed architecture demonstrating benefits on data with irregular connectivity when the latent space is sufficiently large.

42 ENGINEERING↗
NASA NTRS1993

Discrimination of poorly exposed lithologies in AVIRIS data

One of the advantages afforded by imaging spectrometers such as AVIRIS is the capability to detect target materials at a sub-pixel scale. This paper presents several examples of the identification of poorly exposed geologic materials - materials which are either subpixel in scale or which, while having some surface expression over several pixels, are partially covered by vegetation or other materials. Sabol et al. (1992) noted that a primary factor in the ability to distinguish sub-pixel targets is the spectral contrast between the target and its surroundings. In most cases, this contrast is best expressed as an absorption feature or features present in the target but absent in the surroundings. Under such circumstances, techniques such as band depth mapping (Clark et al., 1992) are feasible. However, the only difference between a target material and its surroundings is often expressed solely in the continuum. We define the 'continuum' as the reflectance or radiance spanning spectral space between spectral features. Differences in continuum slope and shape can only be determined by reduction techniques which considers the entire spectral range; i.e., techniques such as spectral mixture analysis (Adams et al., 1989) and recently developed techniques which utilize an orthogonal subspace projection operator (Harsanyi, 1993). Two of the three examples considered herein deal with cases where the target material differs from its surroundings only by such a subtle continuum change.

Farrand, William H.↗
DOE OSTI2025

Hybrid data-driven cement-stabilized soil design: An integration of machine learning, multi-objective optimization, and life cycle assessment

Soil stabilization is crucial in geotechnical engineering, yet conventional methods are often time-consuming, resource-intensive, and environmentally unsustainable. Despite growing interest in Machine Learning (ML) and optimization tools for mix design, few studies integrate these methods with decision-making techniques and environmental assessment to support practical implementation. This study proposes a hybrid data-driven framework for predicting strength, optimizing mix compositions, and evaluating environmental impacts via life cycle assessment of cement-stabilized soft soils. Six ML models were evaluated, and the top-performing eXtreme Gradient Boosting (XGB) model was further improved using the Grey Wolf Optimizer (GWO). The optimized XGB-GWO model, integrated with a polynomial cost function, served as the objective function in a multi-objective optimization problem solved via the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), with final mix selection guided by the entropy-weighted TOPSIS method. Validation through a case study produced mix designs offering superior strength-cost trade-offs, with the optimal mix achieving 2243.2 kPa unconfined compressive strength and a 16.07 % reduction in carbon emissions compared to the highest-cost design. In conclusion, this study offers a sustainable, scalable approach to soil stabilization and supports informed decision-making in construction.

Life cycle assessment↗
DOE OSTI2015

Spectral and Spatial Classification of Hyperspectral Images Based on ICA and Reduced Morphological Attribute Profiles

The availability of hyperspectral images with improved spectral and spatial resolutions provides the opportunity to obtain accurate land-cover classification. In this paper, a novel methodology that combines spectral and spatial information for supervised hyperspectral image classification is proposed. A feature reduction strategy based on independent component analysis is the main core of the spectral analysis, where the exploitation of prior information coupled to the evaluation of the reconstruction error assures the identification of the best class-informative subset of independent components. Reduced attribute profiles (APs), which are designed to address well-known issues related to information redundancy that affect the common morphological APs, are then employed for the modeling and fusion of the contextual information. Four real hyperspectral data sets, which are characterized by different spectral and spatial resolutions with a variety of scene typologies (urban, agriculture areas), have been used for assessing the accuracy and generalization capabilities of the proposed methodology. The obtained results demonstrate the classification effectiveness of the proposed approach in all different scene typologies, with respect to other state-of-the-art techniques.

42 ENGINEERING↗
NASA NTRS1990

Computer vision research at Marshall Space Flight Center

Orbital docking, inspection, and sevicing are operations which have the potential for capability enhancement as well as cost reduction for space operations by the application of computer vision technology. Research at MSFC has been a natural outgrowth of orbital docking simulations for remote manually controlled vehicles such as the Teleoperator Retrieval System and the Orbital Maneuvering Vehicle (OMV). Baseline design of the OMV dictates teleoperator control from a ground station. This necessitates a high data-rate communication network and results in several seconds of time delay. Operational costs and vehicle control difficulties could be alleviated by an autonomous or semi-autonomous control system onboard the OMV which would be based on a computer vision system having capability to recognize video images in real time. A concept under development at MSFC with these attributes is based on syntactic pattern recognition. It uses tree graphs for rapid recognition of binary images of known orbiting target vehicles. This technique and others being investigated at MSFC will be evaluated in realistic conditions by the use of MSFC orbital docking simulators. Computer vision is also being applied at MSFC as part of the supporting development for Work Package One of Space Station Freedom.

Vinz, Frank L.↗
NASA NTRSDate not supplied

Effect of Electronic Shot Noise on Dynamic Measurements using Optical Techniques: Examples from Rayleigh Scattering and Unsteady PSP

Electronic shot noise is an unavoidable reality in all optical techniques that depend on measuring light intensity. For steady-state, time-averaged measurements the impact of shot noise can be easily reduced by increasing the exposure time, or by averaging over multiple-exposures. That is not the case for unsteady measurements, where time histories of light intensity variations need to be created either by high-speed photography (unsteady PSP) or via photoelectron counting (spectrally resolved Rayleigh scattering) over short time durations using a photo-multiplier tube (PMT) and photon counting electronics. Electronic shot noise introduces a fixed amount of random error, which can overwhelm the light intensity variation caused by turbulent fluctuations. Spectrum computed from such time series shows a fixed noise floor that is independent of the number of data points in the time series. For a fixed optical system, where the collected power of the luminescent light (uPSP), or the scattered light (Rayleigh) is fixed, one needs to resort to special techniques to obtain enough signal-to noise ratio (SNR). For the uPSP application it is shown that averaging of the adjacent pixels improves SNR; although this may lead to a sacrifice of spatial resolution. A second means is to increase the exposure time, which leads to a lowering of the frequency range. For the Rayleigh application, improvements of SNR can be achieved via two different cross-correlation based approaches. The first involves measuring the light intensity using two PMTs using short, contiguous gates; thereby, creating two time-series of data. The second one involves collecting one long time-series of data using one set of measurement device, followed by an odd-even splitting into two time series. When the two time-series are cross-correlated, and a power spectrum is calculated, a significant reduction in the shot noise floor can be achieved. Examples from measurements of density and velocity fluctuations spectra from two different Rayleigh setup are presented to demonstrate the process.

uPSP↗
DOE OSTI2025

Signatures of enhanced superconducting properties in niobium cavities

Superconducting radio-frequency (SRF) niobium cavities are critical for modern particle accelerators, as well as for advancing superconducting quantum systems and enabling ultrasensitive searches for new physics. In this work, we report a systematic observation of an anomalous frequency dip in Nb cavities, which occurs at temperatures just below the critical temperature (𝑇𝑐 ), indicative of enhanced superconducting properties at 𝑇 ≪ 𝑇 𝑐 . The magnitude of this dip is strongly correlated with the rf surface resistance, impurity distribution near the surface, and 𝑇𝑐 . Additionally, we report measurements of the coherence peak in the ac conductivity of two Nb SRF cavities processed using distinct methods. By comparing recent theories developed to model this experimental data, we show that the frequency-dip feature, larger coherence peak height, and reduction in the temperature-dependent surface resistance with rf current occur at minimal but finite levels of disorder.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗
DOE OSTI2021

Discovery of Energy Storage Molecular Materials Using Quantum Chemistry-Guided Multiobjective Bayesian Optimization

Redox flow batteries (RFBs) are a promising technology for stationary energy storage applications due to their flexible design, scalability, and low cost. In RFBs, energy is carried in flowable redoxactive materials (redoxmers) which are stored externally and pumped to the cell during operation. Further improvements in the energy density of RFBs necessitates redoxmer designs with wider redox potential windows and higher solubility. Additionally, designing redoxmers with a fluorescence-enabled self-reporting functionality allows monitoring of the state of health of RFBs. To accelerate the discovery of redoxmers with desired properties, state-of-the- art machine learning ( ML) methods, such as multiobjective Bayesian optimization (MBO), are useful. Here, we first employed density functional theory calculations to generate a database of reduction potentials, solvation free energies, and absorption wavelengths for 1400 redoxmer molecules based on a 2,1,3-benzothiadiazole (BzNSN) core structure. From the computed properties, we identified 22 Pareto-optimal molecules that represent best trade-off among all of the desired properties. We further utilized these data to develop and benchmark an MBO approach to identify candidates quickly and efficiently with multiple targeted properties. With MBO, optimal candidates from the 1400-molecule data set can be identified at least 15 times more efficiently compared to the brute force or random selection approach. Importantly, we utilized this approach for discovering promising redoxmers from an unseen database of 1 million BzNSN-based molecules, where we discovered 16 new Pareto-optimal molecules with significant improvements in properties over the initial 1400 molecules. Furthermore, we anticipate that this active learning technique is general and can be utilized for the discovery of any class of functional materials that satisfies multiple desired property criteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Technical Note: Phantom study to evaluate the dose and image quality effects of a computed tomography organ-based tube current modulation technique

Purpose: This technical note quantifies the dose and image quality performance of a clinically available organ-dose-based tube current modulation (ODM) technique, using experimental and simulation phantom studies. The investigated ODM implementation reduces the tube current for the anterior source positions, without increasing current for posterior positions, although such an approach was also evaluated for comparison. Methods: Axial CT scans at 120 kV were performed on head and chest phantoms on an ODM-equipped scanner (Optima CT660, GE Healthcare, Chalfont St. Giles, England). Dosimeters quantified dose to breast, lung, heart, spine, eye lens, and brain regions for ODM and 3D-modulation (SmartmA) settings. Monte Carlo simulations, validated with experimental data, were performed on 28 voxelized head phantoms and 10 chest phantoms to quantify organ dose and noise standard deviation. The dose and noise effects of increasing the posterior tube current were also investigated. Results: ODM reduced the dose for all experimental dosimeters with respect to SmartmA, with average dose reductions across dosimeters of 31% (breast), 21% (lung), 24% (heart), 6% (spine), 19% (eye lens), and 11% (brain), with similar results for the simulation validation study. In the phantom library study, the average dose reduction across all phantoms was 34% (breast), 20% (lung), 8% (spine), 20% (eye lens), and 8% (brain). ODM increased the noise standard deviation in reconstructed images by 6%–20%, with generally greater noise increases in anterior regions. Increasing the posterior tube current provided similar dose reduction as ODM for breast and eye lens, increased dose to the spine, with noise effects ranging from 2% noise reduction to 16% noise increase. At noise equal to SmartmA, ODM increased the estimated effective dose by 4% and 8% for chest and head scans, respectively. Increasing the posterior tube current further increased the effective dose by 15% (chest) and 18% (head) relative to SmartmA. Conclusions: ODM reduced dose in all experimental and simulation studies over a range of phantoms, while increasing noise. The results suggest a net dose/noise benefit for breast and eye lens for all studied phantoms, negligible lung dose effects for two phantoms, increased lung dose and/or noise for eight phantoms, and increased dose and/or noise for brain and spine for all studied phantoms compared to the reference protocol.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Determining Reduced Order Models for Optimal Stochastic Reduced Order Models

The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better represent the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

NASA Tech Briefs, October 2013

Topics include: A Short-Range Distance Sensor with Exceptional Linearity; Miniature Trace Gas Detector Based on Microfabricated Optical Resonators; Commercial Non-Dispersive Infrared Spectroscopy Sensors for Sub-Ambient Carbon Dioxide Detection; Fast, Large-Area, Wide-Bandgap UV Photodetector for Cherenkov Light Detection; Mission Data System Java Edition Version 7; Adaptive Distributed Environment for Procedure Training (ADEPT); LEGEND, a LEO-to-GEO Environment Debris Model; Electronics/Computers; Millimeter-Wave Localizers for Aircraft-to-Aircraft Approach Navigation; Impedance Discontinuity Reduction Between High-Speed Differential Connectors and PCB Interfaces; SpaceCube Version 1.5; High-Pressure Lightweight Thrusters; Non-Magnetic, Tough, Corrosion- and Wear-Resistant Knives From Bulk Metallic Glasses and Composites; Ambient Dried Aerogels; Applications for Gradient Metal Alloys Fabricated Using Additive Manufacturing; Passivation of Flexible YBCO Superconducting Current Lead With Amorphous SiO2 Layer; Propellant-Flow-Actuated Rocket Engine Igniter; Lightweight Liquid Helium Dewar for High-Altitude Balloon Payloads; Method to Increase Performance of Foil Bearings Through Passive Thermal Management; Unibody Composite Pressurized Structure; JWST Integrated Science Instrument Module Alignment Optimization Tool; Radar Range Sidelobe Reduction Using Adaptive Pulse Compression Technique; Digitally Calibrated TR Modules Enabling Real-Time Beamforming SweepSAR Architectures; Electro-Optic Time-to-Space Converter for Optical Detector Jitter Mitigation; Partially Transparent Petaled Mask/Occulter for Visible-Range Spectrum; Educational NASA Computational and Scientific Studies (enCOMPASS); Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network; Detection of Moving Targets Using Soliton Resonance Effect; High-Efficiency Nested Hall Thrusters for Robotic Solar System Exploration; High-Voltage Clock Driver for Photon-Counting CCD Characterization; Development of the Code RITRACKS; and Enabling Microliquid Chromatography by Microbead Packing of Microchannels.

Source record↗
NASA NTRS2016

Further Development and Assessment of a Broadband Liner Optimization Process

The utilization of advanced fan designs (including higher bypass ratios) and shorter engine nacelles has highlighted a need for increased fan noise reduction over a broader frequency range. Thus, improved broadband liner designs must account for these constraints and, where applicable, take advantage of advanced manufacturing techniques that have opened new possibilities for novel configurations. This work focuses on the use of an established broadband acoustic liner optimization process to design a variable-depth, multi-degree of freedom liner for a high speed fan. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design a liner aimed at producing impedance spectra that most closely match the predicted optimum values. The multi-degree of freedom design is carried through design, fabrication, and testing. In-duct attenuation predictions compare well with measured data and the multi-degree of freedom liner is shown to outperform a more conventional liner over a range of flow conditions. These promising results provide further confidence in the design tool, as well as the enhancements made to the overall design process.

Nark, Douglas M.↗
NASA NTRSDate not supplied

Dynamic Stability Analysis Using Free-Flight CFD

Blunt body probes are the primary design for atmospheric entry. The blunted capsule shape, while desirable for the decreased forebody heating, typically experiences dynamic instability at low supersonic and transonic flight. At moderate to low supersonic conditions, the unsteady wake begins to adversely interact with the vehicle in free-flight resulting in attitude oscillations which can grow in time and result in tumbling. Understanding vehicle dynamics is thus important when considering vehicle entry design and guidance navigation and control (GN&C) considerations. Historically, dynamic stability has been carried out exclusively using experimental techniques. The wide range of experimental approaches provide reasonable coverage in Mach and dynamic pressure space for a given trajectory, however achieving flight similitude is often difficult or impossible. Advancements in Computational Fluid Dynamics (CFD) techniques allow for dynamic motion of the vehicle surface during the simulation with either forced/prescribed motion or free motion in response to fluid forces. Several examples of CFD software with the ability to simulate fluid dynamics and vehicle motion are available in literature. The Free-Flight CFD (FF-CFD) capability developed by NASA Ames within the US3D flow solver has shown extensive validation and verification (V&V) efforts from moderate to low supersonic flow across a range of vehicle architectures. The solver is able to simulate full rotational and translation motion resulting in full 6 degrees-of-freedom (DoF) motion. The validation and verification efforts the solver's ability to predict the motion of a ballistic range model as compared to experimental results. Similar to other computational capabilities in literature, FF-CFD relied on heritage data reduction methodologies and processes for reducing dynamic data into aerodynamic coefficients intended for use in design and trajectory codes. These heritage approaches, initially developed with the assumptions (and restrictions) of ground test facilities, resulted in the significant culling of the full 6-DoF dynamic data set to discrete values which are then fit using an aerodynamic model. Recent development of simulation and data reduction methodologies has resulted in an improved approach to FF-CFD simulations of vehicle dynamics which leverage the control of dynamic constraints within a simulation set-up. The presentation of this work will cover the constrained dynamic simulation approach for deriving dynamic coefficients for a Genesis capsule. The methodology will be outlined and a discussion of implications in motion restriction will be discussed. Finally, reconstructed vehicle trajectories using FF-CFD derived aerodynamic coefficients will be presented.

Joseph M Brock↗
DOE OSTI2022

Solvent-Induced Swelling Behaviors of Microphase-Separated Polystyrene- block -Poly(ethylene oxide) Thin Films Investigated Using In Situ Spectroscopic Ellipsometry and Single-Molecule Fluorescence Microscopy

Block copolymers have attracted considerable interest in the fields of nanoscience and nanotechnology, because these polymers afford well-defined nanostructures via self-assembly. An in-depth understanding of solvent effects on the physicochemical properties of these microdomains is crucial for their preparation and utilization. Herein, we employed in situ spectroscopic ellipsometry and single-molecule fluorescence techniques to gain detailed insights into microdomain properties in polystyrene-block-poly(ethylene oxide) (PS-b-PEO) films exposed to ethanol- and water-saturated N 2 . We observed a quick increase and a subsequent gradual decrease in the ellipsometric thickness of PS-b-PEO films upon exposure to ethanol-saturated N 2 . This observation was unexpected because ethanol-saturated N 2 induced negligible thickness change for PS and PEO homopolymer films. The similarity in maximum thickness gain observed under ethanol- and water-saturated N 2 implied the swelling of PEO microdomains. Ethanol vapor permeation through the PEO microdomains was supported by the red-shift of the ensemble and single-molecule fluorescence emission of Nile red in PS-b-PEO films. Single-molecule tracking data showed the initial enhancement and subsequent reduction of the diffusion of hydrophilic sulforhodamine B molecules in PS-b-PEO films upon exposure to ethanol-saturated N 2 , consistent with the spectroscopic ellipsometry results. Furthermore, the higher ethanol susceptibility of the PEO microdomains was attributable to their amorphous nature, as shown by FTIR data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Development of a Two-fluid Drag Law for Clustered Particles using Direct Numerical Simulation and Validation through Experiments

This study presents a new drag model, based on the cohesive inter-particle forces, implemented in the MFIX code. This new drag model combines an existing standard model in MFIX with a particle-based drag model based on a switching principle. Switches between the models in the computational domain occur where strong particle-to-particle cohesion potential is detected. Three versions of the new model were obtained by using one standard drag model in each version. Later, performance of each version was compared against available experimental data for a fluidized bed, published in the literature and used extensively by other researchers for validation purposes. In our analysis of the results, we first observed that standard models used in this research were incapable of producing closely matching results. Then, we showed for a simple case that a threshold is needed to be set on the solid volume fraction. This modification was applied to avoid non-physical results for the clustering predictions, when governing equation of the solid granular temperate was solved. Later, we used our hybrid technique and observed the capability of our approach in improving the numerical results significantly; however, improvement of the results depended on the threshold of the cohesive index, which was used in the switching procedure. Our results showed that small values of the threshold for the cohesive index could result in significant reduction of the computational error for all the versions of the proposed drag model. In addition, we redesigned an existing circulating fluidized bed (CFB) test facility in order to create validation cases for clustering regime of Geldart A type particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2006

A low cost imaging displacement measurement system for spacecraft thermal vacuum testing

A low cost imaging displacement technique suitable for use in thermal vacuum testing was built and tested during thermal vacuum testing of the space infrared telescope facility (SIRTF, later renamed Spitzer infrared telescope facility). The problem was to measure the relative displacement of different portions of the spacecraft due to thermal expansion or contraction. Standard displacement measuring instrumentation could not be used because of the widely varying temperatures on the spacecraft and for fear of invalidating the thermal vacuum testing. The imaging system was conceived, designed, purchased, and installed in approximately 2 months at very low cost. The system performed beyond expectations proving that sub millimeter displacements could be measured from over 2 meters away. Using commercial optics it was possible to make displacement measurements down to 10 (mu)m. An automated image processing tool was used to process the data, which not only speeded up data reduction, but showed that velocities and accelerations could also be measured. Details of the design and capabilities of the system are discussed along with the results of the test on the observatory. Several images from the actual test are presented.

thermal vacuum↗