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At least 163 records · Page 9

The NASA/industry design analysis methods for vibrations (DAMVIBS) program: Accomplishments and contributions

A NASA Langley-sponsored rotorcraft structural dynamics program, known as Design Analysis Methods for VIBrationS (DAMVIBS), has been under development since 1984. The objective of this program was to establish the technology base needed by the industry to develop an advanced finite-element-based dynamics design analysis capability for vibrations. Under the program, teams from the four major helicopter manufacturers have formed finite-element models, conducted ground vibration tests, made test/analysis comparisons of both metal and composite airframes, performed 'difficult components' studies on airframes to identify components which need more complete finite-element representation for improved correlation, and evaluated industry codes for computing coupled rotor-airframe vibrations. Studies aimed at establishing the role that structural optimization can play in airframe vibrations design work have also been initiated. Five government/industry meetings were held in connection with these activities during the course of the program. Because the DAMVIBS Program is coming to an end, the fifth meeting included a brief assessment of the program and its benefits to the industry.

Kvaternik, Raymond G.↗

The NASA/industry design analysis methods for vibrations (DAMVIBS) program - Accomplishments and contributions

A NASA Langley-sponsored rotorcraft structural dynamics program, known as Design Analysis Methods for VIBrationS (DAMVIBS), has been under development since 1984. The objective of this program was to establish the technology base needed by the industry to develop an advanced finite-element-based dynamics design analysis capability for vibrations. Under the program, teams from the four major helicopter manufacturers have formed finite-element models, conducted ground vibration tests, made test/analysis comparisons of both metal and composite airframes, performed 'difficult components' studies on airframes to identify components which need more complete finite-element representation for improved correlation, and evaluated industry codes for computing coupled rotor-airframe vibrations. Studies aimed at establishing the role that structural optimization can play in airframe vibrations design work have also been initiated. Five government/industry meetings were held in connection with these activities during the course of the program. Because the DAMVIBS Program is coming to an end, the fifth meeting included a brief assessment of the program and its benefits to the industry.

Kvaternik, Raymond G.↗

A Government/Industry Summary of the Design Analysis Methods for Vibrations (DAMVIBS) Program

The NASA Langley Research Center in 1984 initiated a rotorcraft structural dynamics program, designated DAMVIBS (Design Analysis Methods for VIBrationS), with the objective of establishing the technology base needed by the rotorcraft industry for developing an advanced finite-element-based dynamics design analysis capability for vibrations. An assessment of the program showed that the DAMVIBS Program has resulted in notable technical achievements and major changes in industrial design practice, all of which have significantly advanced the industry's capability to use and rely on finite-element-based dynamics analyses during the design process.

Kvaternik, Raymond G.↗

Flexible Aircraft Takeoff and Landing Analysis

Flexible Aircraft Takeoff and Landing Analysis Program, FATOLA, simulates aircraft takeoff and landing dynamics. Program includes maneuver logic and autopilots for glide slope, flare, landing, and takeoff and is modular so performance of aircraft in flight and during landing and ground maneuvers can be studied separately or in combination.

Carden, H. D.↗

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Davis, Larry S.↗

A self-learning rule base for command following in dynamical systems

In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

Tsai, Wei K.↗

Overview of the solar dynamic ground test demonstration program

The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the availability of SD technologies in a simulated space environment at the NASA Lewis Research Center (LeRC) vacuum facility. An aerospace industry/ government team is working together to design, fabricate, build, and test a complete SD system. This paper reviews the goals and status of the SD GTD program. A description of the SD system includes key design features of the system, subsystems, and components as reported at the Critical Design Review (CDR).

Shaltens, Richard K.↗

Update of the 2 Kw Solar Dynamic Ground Test Demonstration Program

The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the operation of a complete 2 kW, SD system in a simulated space environment at a NASA Lewis Research Center (LeRC) thermal-vacuum facility. This paper reviews the goals and status of the SD GTD program. A brief description of the SD system identifying key design features of the system, subsystems, and components is included. An aerospace industry/government team is working together to design, fabricate, assemble, and test a complete SD system.

Shaltens, Richard K.↗