Langley Research Center

About: Langley Research Center is a facility organization based out in Hampton, Virginia, United States. It is known for research contribution in the topics: Mach number & Wind tunnel. The organization has 15945 authors who have published 37602 publications receiving 821623 citations. The organization is also known as: NASA Langley & NASA Langley Research Center.

A predictor-corrector technique for visualizing unsteady flow

Abstract: Presents a method for visualizing unsteady flow by displaying its vortices. The vortices are identified by using a vorticity-predictor pressure-corrector scheme that follows vortex cores. The cross-sections of a vortex at each point along the core can be represented by a Fourier series. A vortex can be faithfully reconstructed from the series as a simple quadrilateral mesh, or its reconstruction can be enhanced to indicate helical motion. The mesh can reduce the representation of the flow features by a factor of 1000 or more compared with the volumetric dataset. With this amount of reduction, it is possible to implement an interactive system on a graphics workstation to permit a viewer to examine, in 3D, the evolution of the vortical structures in a complex, unsteady flow. >

Needs and Opportunities for Uncertainty-Based Multidisciplinary Design Methods for Aerospace Vehicles

Abstract: This report consists of a survey of the state of the art in uncertainty-based design together with recommendations for a Base research activity in this area for the NASA Langley Research Center. This report identifies the needs and opportunities for computational and experimental methods that provide accurate, efficient solutions to nondeterministic multidisciplinary aerospace vehicle design problems. Barriers to the adoption of uncertainty-based design methods are identified. and the benefits of the use of such methods are explained. Particular research needs are listed.

Failure Criteria for Frp Laminates in Plane Stress

Abstract: A new set of six failure criteria for fiber reinforced polymer laminates is described. Derived from Dvorak's fracture mechanics analyses of cracked plies and from Puck's action plane concept, the physically-based criteria, denoted LaRC03, predict matrix and fiber failure accurately without requiring curve-fitting parameters. For matrix failure under transverse compression, the fracture plane is calculated by maximizing the Mohr-Coulomb effective stresses. A criterion for fiber kinking is obtained by calculating the fiber misalignment under load, and applying the matrix failure criterion in the coordinate frame of the misalignment. Fracture mechanics models of matrix cracks are used to develop a criterion for matrix in tension and to calculate the associated in-situ strengths. The LaRC03 criteria are applied to a few examples to predict failure load envelopes and to predict the failure mode for each region of the envelope. The analysis results are compared to the predictions using other available failure criteria and with experimental results. Predictions obtained with LaRC03 correlate well with the experimental results.

Bilevel Integrated System Synthesis for Concurrent and Distributed Processing

Abstract: The paper introduces a new version of the Bi-Level Integrated System Synthesis (BLISS) methods intended for optimization of engineering systems conducted by distributed specialty groups working concurrently and using a multiprocessor computing environment. The method decomposes the overall optimization task into subtasks associated with disciplines or subsystems where the local design variables are numerous and a single, system-level optimization whose design variables are relatively few. The subtasks are fully autonomous as to their inner operations and decision making. Their purpose is to eliminate the local design variables and generate a wide spectrum of feasible designs whose behavior is represented by Response Surfaces to be accessed by a system-level optimization. It is shown that, if the problem is convex, the solution of the decomposed problem is the same as that obtained without decomposition. A simplified example of an aircraft design shows the method working as intended. The paper includes a discussion of the method merits and demerits and recommendations for further research.

Method for Optimal Actuator and Sensor Placement for Large Flexible Structures

Abstract: A method of finding the optimal sensor and actuator locations for the control of flexible structures is presented. The method is based on the orthogonal projection of structural modes into the intersection subspace of the controllable and observable subspaces corresponding to an actuator/sensor pair. The controllability and observability grammians are then used to weight the projections to reflect the degrees of controllabili ty and observability. This method produces a three-dimensio nal design space wherein sets of optimal actuators and sensors may be selected. A novel parameter is introduced that is potentially useful for studying the problem of the number of actuators and sensors, in addition to their optimal locations. UPPOSE a specific number of actuators and sensors is given and they are placed at specific locations on a flexible structure such that the effectiveness of the chosen actuator and sensor locations could be analyzed. If it turns out that the a priori chosen number and locations for the actuators and sensors are not sufficiently effective, the question naturally arises as to how the locations could be changed to improve the system. Furthermore, it is possible that the a priori number of actuators and/or sensors used is insufficient or redundant. Thus, there is clearly a need for a computationall y feasible technique that is capable of determining an optimal set of locations and the minimal number of actuators and sensors. In general, there will be many more candidate locations (perhaps an order of magnitude more) than the number of actuators and sensors actually available. If the number of actuators and sensors is known a priori, all possible combina- tions could be evaluated, and in principle, the global optimum could then be found. Unfortunately, the number of possible combinations increases factorially, and therefore an exhaus- tive search for a global optimal is usually computationally infeasible, while nonlinear programming based techniques typically produce local minimums. In the past, various definitions of the degree of controllabil- ity and observability have been used in guiding the search for optimal actuator and sensor locations. Among these, the de- gree of controllabili ty defined by scalar measures of recovery regions appears useful for the purpose of actuator and sensor placement.1'3 A second approach4 uses the projection magni- tudes of eigenvectors into the input and output matrices to define gross measures of modal controllability and observabil- ity. However, only little attention is given to the development of a systematic search strategy for actually solving for an optimal set of actuators and sensors, and most attention has been directed toward defining what constitutes most suitable actuator and sensor locations. In this paper, the problem of defining and obtaining the optimal actuator and sensor locations is addressed. A method that is based on the controllability and observability of an actuator/sensor pair is introduced. An outline of the present paper follows. First, the model of actuator and sensor loca- tions for a linear, second-order dynamical system is presented. The basic assumption is that we are given a set of significant modes whose control is desired via feedback. In the next section, controllable, observable, and their intersection sub- spaces are presented, which forms the basis of the method presented in the sequel. The following section presents the main results of this paper. A cost function that is based on the weighted projection of structural modes into the intersection subspace of the controllable and observable subspaces is intro- duced, and a simple interpretation in terms of balanced coor- dinates is given. A novel method for selecting optimal sensor and actuator locations based on the preceding cost function is outlined. The weighted projections of the structural modes can be viewed as a scalar field in three-dimensi onal design space wherein a designer can easily select a set of actuators and sensors based on his or her own criteria without resorting to elaborate nonlinear programming strategies. The method also allows for the comparison of many actuator and sensor candi- date locations since the computational effort depends only on the product of the number of actuator and sensor location candidates rather than combinatorially based search strategies whpse computational effort is in the order of factorials. In the next section, the method of finding optimal locations is ap- plied to an existing laboratory structure to demonstrate the algorithm. Finally, a few concluding remarks are given.