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A comprehensive gust response analysis was performed on a complete model of an airplane using the NASTRAN aeroelastic package. The analysis investigated random response to atmospheric turbulence and transient response to a discrete gust, including control system dynamics in both cases. It is shown that NASTRAN is an effective tool for aeroelastic analysis and active control system design.
Four aspects of the Doppler lidar are discussed: (1) error analysis of the system; (2) design of the first field program; (3) potential areas of application; and (4) verification of Doppler lidar data by independent measurements.
A modified APQ-102 sidelooking array radar (SLAR) in a B-57 aircraft test bed is used, with other optical and infrared sensors, in remote sensing of Earth surface features for various users at NASA Johnson Space Center. The video from the radar is normally recorded on photographic film and subsequently processed photographically into high resolution radar images. Using a high speed sampling (digitizing) system, the two receiver channels of cross-and co-polarized video are recorded on wideband magnetic tape along with radar and platform parameters. These data are subsequently reformatted and processed into digital synthetic aperture radar images with the image data available on magnetic tape for subsequent analysis by investigators. The system design and results obtained are described.
Models for the analysis of photovoltaic (PV) systems' designs, implementation policies, and economic performance, have proliferated while keeping pace with rapid changes in basic PV technology and extensive empirical data compiled for such systems' performance. Attention is presently given to the results of a comparative assessment of ten well documented and widely used models, which range in complexity from first-order approximations of PV system performance to in-depth, circuit-level characterizations. The comparisons were made on the basis of the performance of their subsystem, as well as system, elements. The models fall into three categories in light of their degree of aggregation into subsystems: (1) simplified models for first-order calculation of system performance, with easily met input requirements but limited capability to address more than a small variety of design considerations; (2) models simulating PV systems in greater detail, encompassing types primarily intended for either concentrator-incorporating or flat plate collector PV systems; and (3) models not specifically designed for PV system performance modeling, but applicable to aspects of electrical system design. Models ignoring subsystem failure or degradation are noted to exclude operating and maintenance characteristics as well.
Results of the phase B study contract for the definition of the space station Electric Power System (EPS) are presented in detail along with backup information and supporting data. Systems analysis and trades, preliminary design, advanced development, customer accommodations, operations planning, product assurance, and design and development phase planning are addressed. The station design is a hybrid approach which provides user power of 25 kWe from the photovoltaic subsystem and 50 kWe from the solar dynamic subsystem. The electric power is distributed to users as a utility service; single phase at a frequency of 20 kHz and voltage of 440VAC. The solar array NiH2 batteries of the photovoltaic subsystem are based on commonality to those used on the co-orbiting and solar platforms.
Metal matrix composites (MMC) are the subject of intensive study and are receiving serious consideration for critical structural applications in advanced aerospace systems. MMC structural analysis and design methodologies are studied. Predicting the mechanical and thermal behavior and the structural response of components fabricated from MMC requires the use of a variety of mathematical models. These models relate stresses to applied forces, stress intensities at the tips of cracks to nominal stresses, buckling resistance to applied force, or vibration response to excitation forces. The extensive research in computational mechanics methods for predicting the nonlinear behavior of MMC are described. This research has culminated in the development of the METCAN (METal Matrix Composite ANalyzer) computer code.
Described is the development and use of a system to measure the Bidirectional Reflectance Distribution Function (BRDF) of various surfaces. The BRDF measurements are used in the analysis and design of optical measurement systems, such as laser anemometers. An argon ion laser (514 nm) is the light source. Preliminary results are presented for eight samples: two glossy black paints, two flat black paints, black glass, sand blasted aluminum, unworked aluminum, and a white paint. A BaSO4 white reflectance standard was used as the reference sample throughout the tests. The reflectance characteristics of these surfaces are compared.
A comparative study was made using 4 different computer codes for solving the compressible Navier-Stokes equations. Three different test problems were used, each of which has features typical of high speed internal flow problems of practical importance in the design and analysis of propulsion systems for advanced hypersonic vehicles. These problems are the supersonic flow between two walls, one of which contains a 10 deg compression ramp, the flow through a hypersonic inlet, and the flow in a 3-D corner formed by the intersection of two symmetric wedges. Three of the computer codes use similar recently developed implicit upwind differencing technology, while the fourth uses a well established explicit method. The computed results were compared with experimental data where available.
Changes in both software and hardware are rapidly bringing conceptual engineering tools like finite element analysis into mainstream mechanical design. Systems that integrate all phases of the manufacturing process provide the most cost benefits. The application of programming concepts like object oriented programming allow for the encapsulation of intelligent data within the design geometry. This combined with declining cost in per seat hardware bring new alternatives to the user.
Guaranteeing robustness has long been an important design objective of control system analysis. Stochastic robustness is a simple numerical procedure that can be used to measure and gain insight into robustness properties associated with linear control systems. In the realm of aircraft control systems, problems such as the effects of flight condition perturbations and model-order uncertainties on robustness are easily and effectively analyzed using stochastic robustness. The concept of stochastic robustness is reviewed and examples are presented demonstrating its use in flight control system analysis.
The Robust-Control Toolbox is a collection of 40 M-files which extend the capability of PC/PRO-MATLAB to do modern multivariable robust control system design. Included are robust analysis tools like singular values and structured singular values, robust synthesis tools like continuous/discrete H(exp 2)/H infinity synthesis and Linear Quadratic Gaussian Loop Transfer Recovery methods and a variety of robust model reduction tools such as Hankel approximation, balanced truncation and balanced stochastic truncation, etc. The capabilities of the toolbox are described and illustated with examples to show how easily they can be used in practice. Examples include structured singular value analysis, H infinity loop-shaping and large space structure model reduction.
Structural finite element models are often too large to be used in the design and analysis of control systems. Model reduction techniques must be applied to reduce the structural model to manageable size. In the past, engineers either performed the model order reduction by hand or used distinct computer programs to retrieve the data, to perform the significance analysis and to reduce the order of the model. To expedite this process, the latest version of INCA has been expanded to include an interactive graphical structural mode significance and model order reduction capability.
The chief goals of the summer project have been twofold - first, for my host group and myself to learn as much of the working details of Taguchi analysis as possible in the time allotted, and, secondly, to apply the methodology to a design problem with the intention of establishing a preliminary set of near-optimal (in the sense of producing a desired response) design parameter values from among a large number of candidate factor combinations. The selected problem is concerned with determining design factor settings for an automated approach program which is to have the capability of guiding the Shuttle into the docking port of the Space Station under controlled conditions so as to meet and/or optimize certain target criteria. The candidate design parameters under study were glide path (i.e., approach) angle, path intercept and approach gains, and minimum impulse bit mode (a parameter which defines how Shuttle jets shall be fired). Several performance criteria were of concern: terminal relative velocity at the instant the two spacecraft are mated; docking offset; number of Shuttle jet firings in certain specified directions (of interest due to possible plume impingement on the Station's solar arrays), and total RCS (a measure of the energy expended in performing the approach/docking maneuver). In the material discussed here, we have focused on single performance criteria - total RCS. An analysis of the possibility of employing a multiobjective function composed of a weighted sum of the various individual criteria has been undertaken, but is, at this writing, incomplete. Results from the Taguchi statistical analysis indicate that only three of the original four posited factors are significant in affecting RCS response. A comparison of model simulation output (via Monte Carlo) with predictions based on estimated factor effects inferred through the Taguchi experiment array data suggested acceptable or close agreement between the two except at the predicted optimum point, where a difference outside a rule-of-thumb bound was observed. We have concluded that there is most likely an interaction effect not provided for in the original orthogonal array selected as the basis for our experimental design. However, we feel that the data indicates that this interaction is a mild one and that inclusion of its effect will not alter the location of the optimum.
The objective of the Composite Load Spectra (CLS) project is to develop generic load models to simulate the composite load spectra that are included in space propulsion system components. The probabilistic loads thus generated are part of the probabilistic design analysis (PDA) of a space propulsion system that also includes probabilistic structural analyses, reliability, and risk evaluations. Probabilistic load simulation for space propulsion systems demands sophisticated probabilistic methodology and requires large amounts of load information and engineering data. The CLS approach is to implement a knowledge based system coupled with a probabilistic load simulation module. The knowledge base manages and furnishes load information and expertise and sets up the simulation runs. The load simulation module performs the numerical computation to generate the probabilistic loads with load information supplied from the CLS knowledge base.
An optical terrain analysis based sensor system specifically designed for landing hazard detection as required for NASA's autonomous planetary landers is introduced. This optical hazard detection and avoidance (HDA) sensor utilizes an optoelectronic wedge-and-ting (WRD) filter for Fourier transformed feature extraction and an electronic neural network processor for pattern classification. A fully implemented optical HDA sensor would assure safe landing of the planetary landers. Computer simulation results of a successful feasibility study is reported. Future research for hardware system implementation is also provided.
During the National Launch System design phase, a computer code (FEEDLINE) was written to analyze the feasibility of using passive recirculation propellant conditioning for the LH2 and LO2 feed systems. The FEEDLINE code was employed to provide temperature profiles to the STME design team. The team used the temperature profiles to determine if the required Space Transportation Main Engine net positive suction pressure was met. One desired outcome of the LH2 testing was to determine if modifications are required for the FEEDLINE code. The initial LN2 calibration tests indicate that the environmental heat into the system decreases with increasing heater input.
This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems.
The simulation of propulsive flows inherently involves chemical activity. Recent years have seen substantial strides made in the development of numerical schemes for reacting flowfields, in particular those involving finite-rate chemistry. However, finite-rate calculations are computationally intensive and require knowledge of the actual kinetics, which are not always known with sufficient accuracy. Alternatively, flow simulations based on the assumption of local chemical equilibrium are capable of obtaining physically reasonable results at far less computational cost. The present study summarizes the development of efficient numerical techniques for the simulation of flows in local chemical equilibrium, whereby a 'Black Box' chemical equilibrium solver is coupled to the usual gasdynamic equations. The generalization of the methods enables the modelling of any arbitrary mixture of thermally perfect gases, including air, combustion mixtures and plasmas. As demonstration of the potential of the methodologies, several solutions, involving reacting and perfect gas flows, will be presented. Included is a preliminary simulation of the SSME startup transient. Future enhancements to the proposed techniques will be discussed, including more efficient finite-rate and hybrid (partial equilibrium) schemes. The algorithms that have been developed and are being optimized provide for an efficient and general tool for the design and analysis of propulsion systems.