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At least 1,423 records · Page 79

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NASA NTRS1988

Three-dimensional self-adaptive grid method for complex flows

A self-adaptive grid procedure for efficient computation of three-dimensional complex flow fields is described. The method is based on variational principles to minimize the energy of a spring system analogy which redistributes the grid points. Grid control parameters are determined by specifying maximum and minimum grid spacing. Multidirectional adaptation is achieved by splitting the procedure into a sequence of successive applications of a unidirectional adaptation. One-sided, two-directional constraints for orthogonality and smoothness are used to enhance the efficiency of the method. Feasibility of the scheme is demonstrated by application to a multinozzle, afterbody, plume flow field. Application of the algorithm for initial grid generation is illustrated by constructing a three-dimensional grid about a bump-like geometry.

Djomehri, M. Jahed↗

NASA NTRS1991

The ACTS propagation program

The purpose of the Advanced Communications Technology Satellite (ACTS) is to demonstrate the feasibility of the Ka-band (20 and 30 GHz) spectrum for satellite communications, as well as to help maintain U.S. leadership in satellite communications. ACTS incorporates such innovative schemes as time division multiple access (TDMA), microwave and baseband switching, onboard regeneration, and adaptive application of coding during rain-fade conditions. The success or failure of the ACTS experiment will depend on how accurately the rain-fade statistics and fade dynamics can be predicted in order to derive an appropriate algorithm that will combat weather vagaries, specifically for links with small terminals, such as very small aperture terminals (VSAT's) where the power margin is a premium. This article describes the planning process and hardware development program that will comply with the recommendations of the ACTS propagation study groups.

Chakraborty, Dayamoy↗

NASA NTRS1994

Laminar and turbulent flow computations of Type 4 shock-shock interference aerothermal loads using unstructured grids

This report presents computations for the Type 4 shock-shock interference flow under laminar and turbulent conditions using unstructured grids. Mesh adaptation was accomplished by remeshing, refinement, and mesh movement. Two two-equation turbulence models were used to analyze turbulent flows. The mean flow governing equations and the turbulence governing equations are solved in a coupled manner. The solution algorithm and the details pertaining to its implementation on unstructured grids are described. Computations were performed at two different freestream Reynolds numbers at a freestream Mach number of 11. Effects of the variation in the impinging shock location are studied. The comparison of the results in terms of wall heat flux and wall pressure distributions is presented.

Vemaganti, Gururaja R.↗

NASA NTRS1995

An efficient implementation of Forward-Backward Least-Mean-Square Adaptive Line Enhancers

An efficient implementation of the forward-backward least-mean-square (FBLMS) adaptive line enhancer is presented in this article. Without changing the characteristics of the FBLMS adaptive line enhancer, the proposed implementation technique reduces multiplications by 25% and additions by 12.5% in two successive time samples in comparison with those operations of direct implementation in both prediction and weight control. The proposed FBLMS architecture and algorithm can be applied to digital receivers for enhancing signal-to-noise ratio to allow fast carrier acquisition and tracking in both stationary and nonstationary environments.

Yeh, H.-G.↗

NASA NTRS1999

Parallel Tetrahedral Mesh Adaptation with Dynamic Load Balancing

The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D_TAG. using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However. performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region., creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D_TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines.

Oliker, Leonid↗

NASA NTRS2009

Neural Network Target Identification System for False Alarm Reduction

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗

NASA NTRS2016

Trajectories for Flyby Sample Return at Saturn's Moons

Ballistic trajectories are computed which would enable a sample return mission to Titan or Enceladus without capturing, descending, or landing. The low-cost mission concept utilizes a free return trajectory that also involves a close flyby of the moon. This work extends the concept, and related trajectory analysis methodology, previously applied to a Europa mission. Specifically, a broad search algorithm is employed to systematically locate potentially feasible itineraries over an entire Saturn period. High-quality approximate solutions are then optimized to be continuous using high-fidelity dynamics. Techniques and software from the Europa analysis, were readily adapted and able to find numerous mission enabling trajectories. A direct mission to Titan is possible with flight time under 16 years and Earth-relative speeds below 11.0 km/sec. The VEEGA option is shown to substantially reduce launch C3, but flight times exceed 21 years. Unfortunately, an Enceladus mission requires a flight time of 25 years or more, and incurs fairly high relative speeds. Nevertheless, an optimized reference mission is computed.

Jones, Drew Ryan↗

NASA NTRS2022

A New Machine Learning Based Analysis for Improving Satellite Retrieved Atmospheric Composition Data: OMI SO2 as an Example

Despite recent progress, satellite retrievals of anthropogenic SO2 still suffer from relatively low signal-tonoise ratios. In this study, we demonstrate a new machine learning data analysis method to improve the quality of satellite SO2 products. In the absence of large ground-truth datasets for SO2, we start from SO2 slant column densities (SCDs) retrieved from the Ozone Monitoring Instrument (OMI) using a data-driven, physically based algorithm and calculate the ratio between the SCD and the root mean square (rms) of the fitting residuals for each pixel. To build the training data, we select presumably clean pixels with small SCD / rms ratios (SRRs) and set their target SCDs to zero. For polluted pixels with relatively large SRRs, we set the target to the original retrieved SCDs. We then train neural networks (NNs) to reproduce the target SCDs using predictors including SRRs for individual pixels, solar zenith, viewing zenith and phase angles, scene reflectivity, and O3 column amounts, as well as the monthly mean SRRs. For data analysis, we employ two NNs: (1) one trained daily to produce analyzed SO2 SCDs for polluted pixels each day and (2) the other trained once every month to produce analyzed SCDs for less polluted pixels for the entire month. Test results for 2005 show that our method can significantly reduce noise and artifacts over background regions. Over polluted areas, the monthly mean NN-analyzed and original SCDs generally agree to within ±15 %, indicating that our method can retain SO2 signals in the original retrievals except for large volcanic eruptions. This is further confirmed by running both the NN-analyzed and original SCDs through a topdown emission algorithm to estimate the annual SO2 emissions for ∼ 500 anthropogenic sources, with the two datasets yielding similar results. We also explore two alternative approaches to the NN-based analysis method. In one, we employ a simple linear interpolation model to analyze the original SCD retrievals. In the other, we develop a PCA–NN algorithm that uses OMI measured radiances, transformed and dimension-reduced with a principal component analysis (PCA) technique, as inputs to NNs for SO2 SCD retrievals. While the linear model and the PCA–NN algorithm can reduce retrieval noise, they both underestimate SO2 over polluted areas. Overall, the results presented here demonstrate that our new data analysis method can significantly improve the quality of existing OMI SO2 retrievals. The method can potentially be adapted for other sensors and/or species and enhance the value of satellite data in air quality research and applications.

Can Li↗

NASA NTRSDate not supplied

A Parallelized Oxidation-Driven Surface Recession Framework in DSMC Code, SPARTA

Spacecrafts rely on ablative thermal protection systems (TPS) made of composites consisting of a carbon-based reinforcement and a polymeric matrix. These materials are designed to withstand high-temperature oxidation and surface recession during re-entry into the Earth's atmosphere. However, ablation occurs due to a complex interplay of thermal, mechanical, and chemical factors, making it challenging to determine the individual impact of each on the TPS's overall degradation. In this study, we have developed an ablation model that can leverage a finite rate carbon oxidation model to predict material recession and surface states more accurately. Stochastic PArallel Rarified-gas Time-accurate Analyzer (SPARTA), a direct-simulation Monte Carlo (DSMC) code, is modified to allow oxidation-driven ablation of implicitly defined carbon surfaces. In SPARTA, implicit surfaces are generated from the grid corner point values via a marching cubes algorithm, therefore creating a new set of surface elements every time ablation is performed. The finite-rate oxidation model developed by Gopalan et. al can perform both gas-surface and pure-surface reactions and is now adapted to tally surface data on a per grid cell basis. The ablation functionality was also adjusted so once the reactions have occurred, the number of reactions leading to CO formation can be converted to corner point reduction values; therefore, carbon removal is directly proportional to surface recession. We also briefly discuss some unique challenges associated with parallelizing this dynamic surface state and geometry. Finally, we analyze the performance of this parallelized implicit chemistry model with simple 2D and 3D benchmark cases by producing surface state statistics, area changes over time, and visualization across a range of surface temperatures and processors with and without load-balancing.

DSMC↗

NASA NTRS1981

Adaptive filtering of radar images for autofocus applications

Autofocus techniques are being designed at the Jet Propulsion Laboratory to automatically choose the filter parameters (i.e., the focus) for the digital synthetic aperture radar correlator; currently, processing relies upon interaction with a human operator who uses his subjective assessment of the quality of the processed SAR data. Algorithms were devised applying image cross-correlation to aid in the choice of filter parameters, but this method also has its drawbacks in that the cross-correlation result may not be readily interpretable. Enhanced performance of the cross-correlation techniques of JPL was hypothesized given that the images to be cross-correlated were first filtered to improve the signal-to-noise ratio for the pair of scenes. The results of experiments are described and images are shown.

Stiles, J. A.↗

NASA NTRS1974

Optimal space communications techniques

The encoding of video signals using the Song Adaptive Delta Modulator (Song ADM) is discussed. The video signals are characterized as a sequence of pulses having arbitrary height and width. Although the ADM is suited to tracking signals having fast rise times, it was found that the DM algorithm (which permits an exponential rise for estimating an input step) results in a large overshoot and an underdamped response to the step. An overshoot suppression algorithm which significantly reduces the ringing while not affecting the rise time is presented along with formuli for the rise time and the settling time. Channel errors and their effect on the DM encoded bit stream were investigated.

Schilling, D. L.↗

NASA NTRS1975

Autonomous navigation preparations for future unmanned space missions

In order to prepare for the era of autonomous navigation, this paper first examines existing techniques for spacecraft navigation by describing the basic elements of the Mark-I and II navigation technologies. The remainder of the paper deals with identification of criteria which necessitate onboard navigation, and with promising solutions now under consideration. An attractive solution possibility is proposed which utilizes narrow-angle optics, a charge-coupled device area-array image sensor, a small advanced onboard flight computer, and a simplified set of software algorithms. Onboard commands would be derived and sent to the appropriate spacecraft attitude control, propulsion, and science platform pointing subsystems. The proposed autonomous navigation system does not address all mission options, but focuses primarily on precision approach trajectory control and adaptive science instrument pointing for asteroid, cometary, and outer planet satellite missions.

Kohlhase, C. E.↗

NASA NTRS1984

Yaw Attitude Estimation for the Tracking and Data Relay Satellite System

The Tracking and Data Relay Satellite System (TDRSS) uses a groundbased attitude determination algorithm to open loop point the satellite's high data rate antennas. The spacecraft is able to measure its pitch and roll attitude, but its yaw attitude is periodically unobservable. The ground software uses a state-space estimator, an adaptation of a Luenberger observer, to predict the spacecraft yaw angle during these unobservable periods. It contains states associated with the roll/yaw dynamics and the on-board control law. The accuracy is limited by the modeling fidelity of the disturbance torques acting on the spacecraft. After initial operating problems were cleared up, the operation of the estimator has converged to predicted performance.

Staich, S.↗

NASA NTRS1989

Prototype architecture for a VLSI level zero processing system

The prototype architecture and implementation of a high-speed level zero processing (LZP) system are discussed. Due to the new processing algorithm and VLSI technology, the prototype LZP system features compact size, low cost, high processing throughput, and easy maintainability and increased reliability. Though extensive control functions have been done by hardware, the programmability of processing tasks makes it possible to adapt the system to different data formats and processing requirements. It is noted that the LZP system can handle up to 8 virtual channels and 24 sources with combined data volume of 15 Gbytes per orbit. For greater demands, multiple LZP systems can be configured in parallel, each called a processing channel and assigned a subset of virtual channels. The telemetry data stream will be steered into different processing channels in accordance with their virtual channel IDs. This super system can cope with a virtually unlimited number of virtual channels and sources. In the near future, it is expected that new disk farms with data rate exceeding 150 Mbps will be available from commercial vendors due to the advance in disk drive technology.

Shi, Jianfei↗

NASA NTRS1991

Application of the boundary element method to transient heat conduction

An advanced boundary element method (BEM) is presented for the transient heat conduction analysis of engineering components. The numerical implementation necessarily includes higher-order conforming elements, self-adaptive integration and a multiregion capability. Planar, three-dimensional and axisymmetric analyses are all addressed with a consistent time-domain convolution approach, which completely eliminates the need for volume discretization for most practical analyses. The resulting general purpose algorithm establishes BEM as an attractive alternative to the more familiar finite difference and finite element methods for this class of problems. Several detailed numerical examples are included to emphasize the accuracy, stability and generality of the present BEM. Furthermore, a new efficient treatment is introduced for bodies with embedded holes. This development provides a powerful analytical tool for transient solutions of components, such as casting moulds and turbine blades, which are cumbersome to model when employing the conventional domain-based methods.

Dargush, G. F.↗

NASA NTRS1992

Adaptive methods in computational fluid dynamics

A review is conducted of the basic components of adaptive methods applicable to very complex problems in fluid dynamics. Attention is given to ways of changing the structure of an approximation to reduce error, techniques for estimating the evolution of error in a CFD calculation, and the range of algorithms that are currently available for mesh-changing functions. Available numerical results which demonstrate the viability of these approaches are discussed.

Oden, J. T.↗

NASA NTRS1996

Finite Element Simulation of Smart Structures

Finite element equations representing the behavior of piezoelectric materials when bounded to a typical structure and used as sensors and actuators were developed. Emphasis was placed on generating sensor output equations of piezoelectric sensors and responses of a typical structure bonded with piezoelectric sensors and actuators on the basis of finite element formulation. The model can predict not only structural responses due to both mechanical and electrical loading but also electrical potential due to mechanical or thermal effects. The resulted finite element equations were then used for simple control design and performance evaluation. In the control algorithm, voltages coming out from piezoelectric sensors, which are proportional to strains at sensing locations, are taken as input. The voltages applied to the piezoelectric actuators are used as output. The feasibility of integrating control algorithm with the element routine developed herein and FEAP was demonstrated. In particular, optimal independent modal space control was implemented in a software package on the basis of finite element formulation. A rudimentary finite element-control algorithm package was also developed to evaluate the performance of candidate control laws. A few numerical simulations using the software package developed herein were given. The integrated software package will provide a design tool to address issues such as how adaptive smart systems will scale to a full size aircraft, the amount of piezoelectric materials and the powers needed to actuate it for desired performance. It will also provide a viable new structural control design concept for practical applications in large flexible structures such as aerospace vehicles and aircraft.

Cui, Y. Lawrence↗

NASA NTRS1999

Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines

Dynamic load balancing is central to adaptive mesh-based computations on large-scale parallel computers. The principal investigator has investigated various issues on the dynamic load balancing problem under NASA JOVE and JAG rants. The major accomplishments of the project are two graph partitioning algorithms and a load balancing framework. The S-HARP dynamic graph partitioner is known to be the fastest among the known dynamic graph partitioners to date. It can partition a graph of over 100,000 vertices in 0.25 seconds on a 64- processor Cray T3E distributed-memory multiprocessor while maintaining the scalability of over 16-fold speedup. Other known and widely used dynamic graph partitioners take over a second or two while giving low scalability of a few fold speedup on 64 processors. These results have been published in journals and peer-reviewed flagship conferences.

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