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NASA NTRS1990

Determination of optimum fin profile for a zero-G capillary drained condenser

This paper presents the analytical formulation and numerical results for heat transfer in a high heat flux condenser that relies on capillary flow along shaped fins (Gregorig surfaces) and a drainage network embedded in the condenser walls. Results are shown for a variety of fin profile shapes in order to show the geometric trade-offs involved in seeking a maximum effective heat transfer coefficient for the fin. Predictions of the model show excellent agreement with previously reported measurements for steam. Based on this work, a profile has been selected for a 2 kW ammonia condenser currently under development for use in space. In that design the fin half width is 0.5 mm and the model predicts a heat transfer coefficient referred to the base of the fin of 9 W/sq cm deg C for a heat flux of 10/W sq cm at the base.

Mccormick, John A.↗

NASA NTRS2012

Strut Shaping of 34m Beam Waveguide Antenna for Reductions in Near-Field RF and Noise Temperature

Strut shaping of NASA's Deep Space Network (DSN) 34m Beam Waveguide (BWG) antenna has been implemented to reduce near-field RF exposure while improving the antenna noise temperature. Strut shaping was achieved by introducing an RF shield that does not compromise the structural integrity of the existing antenna. Reduction in the RF near-field level will compensate for the planned transmit power increase of the antenna from 20 kW to 80 kW while satisfying safety requirements for RF exposure. Measured antenna noise temperature was also improved by as much as 1.5 K for the low elevation angles and 0.5 K in other areas.

near-field↗

NASA NTRS1989

Neural networks for data compression and invariant image recognition

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

Gardner, Sheldon↗

NASA NTRS1972

Subsonic, transonic, and supersonic nozzle flow by the inverse technique.

The inverse technique is used to obtain a mathematically and physically consistent solution of the flowfield in a nozzle from the mass generation surface through the supersonic region. The inverse method employs an assumed centerline function which is of the Cauchy type in that the values and the derivatives of the function are known. Since the Cauchy boundary conditions can give rise to numerical instabilities, the governing gasdynamic equations for rotational steady flow were transformed into a form which puts the geometry into a rectangular shape, and which spaces the network of interior points more finely in regions of the greatest gradients of the dependent variables. For arbitrarily specified centerline data, the solution of the governing flow equations may not exist, and if it does it may not depend continuously on the data.

Norton, D. J.↗

NASA NTRS2000

Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks

Development of characteristic tissue patterns requires that individual cells be switched locally between different phenotypes or "fates;" while one cell may proliferate, its neighbors may differentiate or die. Recent studies have revealed that local switching between these different gene programs is controlled through interplay between soluble growth factors, insoluble extracellular matrix molecules, and mechanical forces which produce cell shape distortion. Although the precise molecular basis remains unknown, shape-dependent control of cell growth and function appears to be mediated by tension-dependent changes in the actin cytoskeleton. However, the question remains: how can a generalized physical stimulus, such as cell distortion, activate the same set of genes and signaling proteins that are triggered by molecules which bind to specific cell surface receptors. In this article, we use computer simulations based on dynamic Boolean networks to show that the different cell fates that a particular cell can exhibit may represent a preprogrammed set of common end programs or "attractors" which self-organize within the cell's regulatory networks. In this type of dynamic network model of information processing, generalized stimuli (e.g., mechanical forces) and specific molecular cues elicit signals which follow different trajectories, but eventually converge onto one of a small set of common end programs (growth, quiescence, differentiation, apoptosis, etc.). In other words, if cells use this type of information processing system, then control of cell function would involve selection of preexisting (latent) behavioral modes of the cell, rather than instruction by specific binding molecules. Importantly, the results of the computer simulation closely mimic experimental data obtained with living endothelial cells. The major implication of this finding is that current methods used for analysis of cell function that rely on characterization of linear signaling pathways or clusters of genes with common activity profiles may overlook the most critical features of cellular information processing which normally determine how signal specificity is established and maintained in living cells. Copyright 2000 Academic Press.

Review↗

NASA NTRS2012

Strut Shaping of 34m Beam Waveguide Antenna for Reductions in Near-Field RF and Noise Temeperature

Struts shaping of the NASA's Deep Space Network (DSN) 34m Beam Waveguide (BWG) antenna has been implemented to reduce near-field RF exposure while improving the antenna noise temperature. Strut shaping was achieved by introducing an RF shield that does not compromise the structural integrity of the existing structure. Reduction in the RF near-field exposure will compensate for the planned transmit power increase of the antenna from 20 kW to 80 kW while satisfying safety requirements for RF exposure. Antenna noise temperature was also improved by as much as 1.5 K for the low elevation angles and 0.5 K in other areas. Both reductions of RF near-field exposure and antenna noise temperature were verified through measurements and agree very well with calculated results.

reflector↗

NASA NTRS2007

Method for Constructing Composite Response Surfaces by Combining Neural Networks with Polynominal Interpolation or Estimation Techniques

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate mode

Rai, Man Mohan↗

NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗

NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

solar sail↗

NASA NTRS2011

ARC+(Registered Trademark) and ARC PC Welding Simulators: Teach Welders with Virtual Interactive 3D Technologies

123 Certification Inc., a Montreal based company, has developed an innovative hands-on welding simulator solution to help build the welding workforce in the most simple way. The solution lies in virtual reality technology, which has been fully tested since the early 90's. President and founder of 123 Certification Inc., Mr. Claude Choquet Ing. Msc. IWE. acts as a bridge between the welding and the programming world. Working in these fields for more than 20 years. he has filed 12 patents world-wide for a gesture control platform with leading edge hardware related to simulation. In the summer of 2006. Mr Choquet was proud to be invited to the annual IIW International Weld ing Congress in Quebec City to launch the ARC+ welding simulator. A 100% virtual reality system and web based training center was developed to simulate multi process. multi-materiaL multi-position and multi pass welding. The simulator is intended to train welding students and apprentices in schools or industries. The welding simulator is composed of a real welding e[eetrode holder (SMAW-GTAW) and gun (GMAW-FCAW). a head mounted display (HMD), a 6 degrees of freedom tracking system for interaction between the user's hands and head. as well as external audio speakers. Both guns and HMD are interacting online and simultaneously. The welding simulation is based on the law of physics and empirical results from detailed analysis of a series of welding tests based on industrial applications tested over the last 20 years. The simulation runs in real-time, using a local logic network to determine the quality and shape of the created weld. These results are based on the orientation distance. and speed of the welding torch and depth of penetration. The welding process and resulting weld bc.1d are displayed in a virtual environment with screenplay interactive training modules. For review. weld quality and recorded process values can be displayed and diagnosed after welding. To help in the le.tming process, a learning curve for each student and each Virtual Welding Class'" can be plotted, for an instructor's review or a required third party evaluation.

Choquet, Claude↗

NASA NTRS1999

A Neural Network Aero Design System for Advanced Turbo-Engines

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Sanz, Jose M.↗

NASA NTRS2000

Centrifugation of Cultured Osteoblasts And Macrophages as a Model To Study How Gravity Regulates The Function of Skeletal Cells

Mechanical loading helps define the architecture of weight-bearing bone via the tightly regulated process of skeletal turnover. Turnover occurs by the concerted activity of osteoblasts, responsible for bone formation. and osteoclasts, responsible for bone resorption. Osteoclasts are specialized megakaryon macrophages, which differentiate from monocytes in response to resorption stimuli, such as reduced weight-bearing. Habitation in space dramatically alters musculoskeletal loading, which modulates both cell function and bone structure. Our long-term objective is to define the molecular and cellular mechanisms that mediate skeletal adaptations to altered gravity environments. Our experimental approach is to apply hypergravity loads by centrifugation to rodents and cultured cells. As a first step, we examined the influence of centrifugation on the structure of cancellous bone in rats to test the ability of hypergravity to change skeletal architecture. Since cancellous bone undergoes rapid turnover we expected the most dramatic structural changes to occur in the shape of trabeculae of weight-bearing, cancellous bone. To define the cellular responses to hypergravity loads, we exposed cultured osteoblasts and macrophages to centrifugation. The intraosseous and intramedullary pressures within long bones in vivo reportedly range from 12-40 mm Hg, which would correspond to 18-59 gravity (g) in our cultures. We assumed that hydrostatic pressure from the medium above the cell layer is at least one major component of the mechanical load generated by centrifuging cultured cells. and therefore we exposed the cells to 10-50g. In osteoblasts, we examined the structure of their actin and microtubule networks, production of prostaglandin E2 (PGE2), and cell survival. Analysis of the shape of the cytoskeletal networks provides evidence for the ability of centrifugation to affect cell structure, while the production of PGE2 serves as a convenient marker for mechanical stimulation. We examined cell survival, reasoning that osteoblasts might mold skeletal structure in a hypergravity environment in part by regulating apoptosis and thus the duration of osteoblast productivity. Finally, we tested the influence of centrifugation on microbial activation of a macrophage cell line (RAW264.7). In response to the appropriate hormonal stimulation, this cell line is reportedly capable of undergoing differentiation to express osteoclast markers. In addition, a component of the cell wall of gram-negative bacteria, lipopolysaccaride (LPS), stimulates the formation of osteoclasts in vivo. Thus we tested the influence on centrifugation on RAW264.7 cells stimulated with LPS to provide an index of the function of osteoclast precursors.

Globus, Ruth K.↗

NASA NTRS1974

Dynamic behaviour of coastal sedimentation in the Lions Gulf

The author has identified the following significant results. A number of ERTS-1 images covering this geographical zone were studied and compared with cartographic maps, air photographs, and thermal-IR images. Old and recent sediments leave traces in the landscape which are decoded by interpreting the shapes of the clear zones forming a network against the black background representing water and humid zones. Current sedimentation and its mechanism were investigated. It had been hoped that a regular sequence of images would make it possible to follow the dynamics of the Rhone and the coastal rivers in relation to meteorological conditions. In any event only a small number of images spread over a wide period of time were obtained, and a complete study was therefore impossible. However, in comparing some of the ERTS-1 images certain thermal-IR images and information on the flow of the Rhone provided some clarification of mechanisms associated with river dynamics.

Guy, M.↗

NASA NTRS1999

Neural Networks Used to Compare Designed and Measured Time-Average Patterns

Electronic time-average holograms are convenient for comparing the measured vibration modes of fan blades with those calculated by finite-element models. At the NASA Lewis Research Center, neural networks recently were trained to perform what had been a simple visual comparison of the predictions of the design models with the measurements. Finite-element models were used to train neural networks to recognize damage and strain information encoded in subtle changes in the time-average patterns of cantilevers. But the design-grade finite element models were unable to train the neural networks to detect damage in complex blade shapes. The design-model-generated patterns simply did not agree well enough with the measured patterns. Instead, hybrid-training records, with measured time-average patterns as the input and model-generated strain information as the output, were used to effect successful training.

Decker, Arthur J.↗

NASA NTRS2004

Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation table in the presence of various sources of laboratory noise is shown. The output of the neural network is called the degradable classification index. The curve was generated by a simultaneous comparison of means, and it shows a peak-to-peak sensitivity of about 100 nm. The following graph uses model generated data from a compressor blade to show that much higher sensitivities are possible when the environment can be controlled better. The peak-to-peak sensitivity here is about 20 nm. The training procedure was modified for the second graph, and the data were subjected to an intensity-dependent transformation called folding. All the measurements for this approach to calibration were optical. The peak-to-peak amplitudes of the vibration modes were measured using heterodyne interferometry, and the modes themselves were recorded using television (electronic) holography.

Decker, Arthur J.↗

NASA NTRS2021

Collaborative Pose Estimation of An Unknown Target Using Multiple Spacecraft

A reliable method for pose estimation of an unknown and uncooperative space target using monocular vision remains an open problem. Vision-based pose determination can be challenging in case of unfavorable illumination, time-varying conditions due to rotational motion and relative orbit, and scale ambiguity resolution. To address these challenges, we propose a novel collaborative pose determination algorithm called Multi- Spacecraft Simultaneous Estimation of Pose and Shape algorithm or M-SEPS.Within M-SEPS, a team of chaser spacecraft, each equipped with a monocular camera, exchange information over a local network to jointly estimate the relative kinematic state of the target and its sparse shape landmarks. In this approach, each spacecraft processes its own images and observes particular target landmarks in parallel and in a distributed fashion. Then, the local network is exploited by the spacecraft to share their consensus proposals and aggregate them to achieve the joint estimate. We validate our algorithm using simulations of relative orbits and observations, captured by each chaser spacecraft. To the best of the authors’ knowledge, this is the first cooperative, vision-based algorithm for estimating the pose and shape of a space object for an arbitrary number of spacecraft.

Chung, Soon-Jo↗

NASA NTRS1982

Cassegrain dual reflector antenna design

A folded optics reflector system could mitigate problems associated with the pointability and controllability of the large UHF antenna for MSAT. Such a system is comprised of a parabolic main reflector and a hyperboloidal subreflector (Cassegrain arrangement) or an ellipsoidal subreflector (Gregorian arrangement), either of which brings the feed closer to the main reflector. By shaping the subreflector and the main reflector, an improved scan capability might be achieved and the size of the required feed aperture-per-beam could be reduced. In such a shaped dual reflector system, the need for overlapping cluster feed arrangement and its concomitant beam forming network could be removed. In this system, a relatively low gain feed element together with the shaped subreflector would be sufficient to produce the required high illumination taper that at the main reflector.

Source record↗

NASA NTRS1986

Near-field testing of the 5-meter model of the tetrahedral truss antenna

This report documents the technical results from near-field testing of the General Dynamics 5-meter model of the tetrahedral truss antenna at the Martin Marietta Denver Aerospace facility. A 5-meter square side of the tetrahedral served as the perimeter of the antenna, and a mesh surface and extensive surface contouring cord network was used to create a parabolic aperture shape to within an rms accuracy of 30 mils or better. Pattern measurements were made with offset feed systems radiating at frequencies of 7.73, 11.60, 2.27, and 4.26 (all in GHz). This report discusses the method of collecting the data, system measurement accuracy, the test data compiled, and diagostics and isolation of causes of pattern results. The technique of using near-field phase for measuring surface mechanical tolerances is included. Detailed far field antenna patterns and their implications are provided for all tests conducted.

Kefauver, Neill↗