710 research outputs found
Modal Testing And Analysis Techniques And Their Application On A Small Uas
This thesis focuses on experimental structural analysis using contemporary testing techniques. This includes modal testing topics such as data acquisition, data processing, sensor placement, and multiple excitation methods. It also presents a novel sensor placing procedure that uses a laser vibrometer to identify key sensor locations. These techniques are applied in a case study on a small unmanned aerial system, (UAS). The airframe, the BTE Super Hauler, is a small UAS used by the Unmanned Aircraft Systems Engineering (UASE) Laboratory at the University of North Dakota as a test platform for flight testing multiple payloads. An antenna system, designed for use in sense and avoid applications, was developed that requires the addition of wing pods to the current airframe to minimize electro-magnetic interference from the engine of the UAS. Modal testing is used to determine the effect of two wing pods on the structural dynamic behavior of the UAS. Flutter analysis is also performed to ensure that the surface bending and torsional modes of the UAS do not create an unstable airframe.
Data acquisition was performed using ModalVIEW, a structural analysis program supported by LabVIEW. ModalVIEW outputs a frequency response function to which various windowing methods can be applied. The aircraft was excited both by an impact hammer and a shaker.
The new sensor placement procedure was developed to assist in placing sensors in key locations in an efficient method to reduce the number of channels needed. It is also a fast, non-contact method implementing a laser vibrometer. A statistical method was used to determine appropriate sensor locations
Structural Response Evaluation Using Non-Uniform Sensor Arrays
Sensor arrays strategically deployed on various offshore structures may provide valuable information in addressing issues related to the complex dynamic response behavior due to varying environments, changing hydrodynamics and purposely attached engineering devices. The current work was devoted to developing techniques to (1) optimize the sensor array according to specific engineering goals, (2) use response data obtained from the sensors to evaluate structures‟ extreme responses, (3) extract modal parameters, and (4) analyze strength conditions. The computational tool developed in this study integrated genetic algorithms, modal recognition techniques, damage detection methods, time series and spectral analysis methods. Genetic algorithms, originally proposed for solving optimization problems based on natural selection, have demonstrated capabilities in obtaining the optimal sensor array configurations in extracting a single mode or two modes simultaneously. This finding laid the foundation for further modal recognition and damage analysis.
The first application discussed herein focused on response evaluation of long and flexible subsea transmission lines; specifically, evaluating the performance of flow-induced vibration suppression devices and buoyancy elements. With laboratory data, the study demonstrated that airfoil fairings, ribbon fairings and helical strakes can all effectively suppress the undesired vibrations in a uniform current; however, the first two devices were not quite effective, especially airfoil fairings, when the structures were subjected to combined loads of current and waves (though all devices significantly increased the damping). In addition, the study showed modal parameters extracted with optimized sensor arrays can help detect, locate and size damages in a structure via numerical simulation (though the performance of the methodology may decrease with localized non-uniform strength profiles and excessive marine growth).
The second application extended the methodologies from 1-D beam-like structures to 2-D plate-like structures. These studies focused on strength analyses of various ice sheet formations. The results illustrated, in spite of the exponentially increased computational volume, fine-tuned genetic algorithms can still locate near optimal sensor arrays regardless of boundary conditions and placement restrictions due to complicated Arctic environments. Furthermore, the damage detection methodology utilized herein proved to be able not only to detect weak regions but also to detect strengthened areas in ice sheets, for example an ice ridge, thus complete strength analyses of selected ice sheet formations can be conducted
Multivariable isoperformance methodology for precision opto-mechanical systems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2001.Includes bibliographical references (p. 277-285).Precision opto-mechanical systems, such as space telescopes, combine structures, optics and controls in order to meet stringent pointing and phasing requirements. In this context a novel approach to the design of complex, multi-disciplinary systems is presented in the form of a multivariable isoperformance methodology. The isoperformance approach first finds a point design within a given topology, which meets the performance requirements with sufficient margins. The performance outputs are then treated as equality constraints and the non-uniqueness of the design space is exploited by trading key disturbance, plant, optics and controls parameters with respect to each other. Three algorithms (branch-and-bound, tangential front following and vector spline approximation) are developed for the bivariate and multivariable problem. The challenges of large order models are addressed by presenting a fast diagonal Lyapunov solver, apriori error bounds for model reduction as well as a governing sensitivity equation for similarity transformed state space realizations. Specific applications developed with this technique are error budgeting and multiobjective design optimization. The goal of the multiobjective design optimization is to achieve a design which is pareto optimal, such that multiple competing objectives can be satisfied within the performance invariant set. Thus, situations are avoided where very costly and hard-to-meet requirements are levied onto one subsystem, while other subsystems hold substantial margins.(cont.) An experimental validation is carried out on the DOLCE laboratory testbed. The testbed allows verification of the predictive capability of the isoperformance technique on models of increasing fidelity. A comparison with experimental results, trading excitation amplitude and payload mass, is demonstrated. The predicted performance contours match the experimental data very well at low excitation levels, typical of the disturbance environment on precision opto-mechanical systems. The relevance of isoperformance to space systems engineering is demonstrated with a comprehensive NEXUS spacecraft dynamics and controls analysis. It is suggested that isoperformance is a useful concept in other fields of engineering science such as crack growth calculations in structures. The isoperformance approach enhances the understanding of complex opto-mechanical systems beyond the local neighborhood of a particular point design.by Olivier L. de Weck.Ph.D
The Fifth NASA/DOD Controls-Structures Interaction Technology Conference, part 1
This publication is a compilation of the papers presented at the Fifth NASA/DoD Controls-Structures Interaction (CSI) Technology Conference held in Lake Tahoe, Nevada, March 3-5, 1992. The conference, which was jointly sponsored by the NASA Office of Aeronautics and Space Technology and the Department of Defense, was organized by the NASA Langley Research Center. The purpose of this conference was to report to industry, academia, and government agencies on the current status of controls-structures interaction technology. The agenda covered ground testing, integrated design, analysis, flight experiments and concepts
Optimal sensor placement in structural health monitoring (SHM) with a field application on a RC bridge
Structural health monitoring (SHM) is a research field that targets detecting and locating damage in structures. The main objective of SHM is to detect damage at its onset and inform authorities about the type, nature and location of the damage in the structure. Successful SHM requires deploying optimal sensor networks. We present a probabilistic approach to identify optimal location of sensors based on a priori knowledge on damage locations while considering the need for redundancy in sensor networks. The optimal number of sensors is identified using a multi-objective optimization approach incorporating information entropy and cost of the sensor network. As the size of the structure grows, the advantage of the optimal sensor network in damage detection becomes obvious. We also present an innovative field application of SHM using Field Programmable Gate Array (FPGA) and wireless communication technologies. The new SHM system was installed to monitor a reinforced concrete (RC) bridge on interstate I-40 in Tucumcari, New Mexico. The new monitoring system is powered with renewable solar energy. The integration of FPGA and photovoltaic technologies make it possible to remotely monitor infrastructure with limited access to power. Using calibrated finite element (FE) model of the bridge with real data collected from the sensors installed on the bridge, we establish fuzzy sets describing different damage states of the bridge. Unknown states of the bridge performance are then identified using degree of similarity between these fuzzy sets. The proposed SHM system will reduce human intervention significantly and can save millions of dollars currently spent on prescheduled inspection by enabling performance based monitoring
Fourth NASA Workshop on Computational Control of Flexible Aerospace Systems, part 1
The proceedings of the workshop are presented. Some areas of discussion are as follows: modeling, systems identification, and control of flexible aircraft, spacecraft, and robotic systems
DESIGN OPTIMIZATION FOR A SUPPORT FOR THE STORAGE RING QUADRUPOLE MAGNET IN A SYNCHROTRON RADIATION FACILITY
High brilliance photon beam production requires high gradient magnets. High gradient magnets initiate large magnetic forces to be borne by supports to keep them in position. The objective of this study was to design a support for the CLS 2.0 quadrupole magnet that suppresses vibrations with the goals of the minimal amount of materials and low cost as compared to the existing system. The motivation of this study was associated with upgrading the CLS 2.0’s electron beam, specifically the beam size which will be more than a hundred times smaller than that of the current CLS. The optimization goals of the support design were : (1) Maximizing the natural frequency of the whole magnet system (magnet + supports) and (2) Minimizing the weight of the frame, while meeting the constraints: (1) Static deflection less than 10 microns. (2) Stress developed should be less than the yield stress of the frame material (3) Natural frequency of the system should be more than 50Hz. Such a problem, when translated to the optimization problem, is a large problem as too many design parameters are involved, which makes the “All-In-One (AIO)” strategy of optimization infeasible. This study adopted a divide-and-conquer strategy, i.e., to properly decompose the whole problem into a set of small problems and then optimize them separately. By applying this novel design process, the frame was successfully designed, and the verification showed satisfactory results. The contribution of this work lies in the field of computational design, and specifically, it provides a case demonstration of the divide-and-concur strategy usefulness while optimizing the design for large problems
Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes
The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors
Exploring resource/performance trade-offs for streaming applications on embedded multiprocessors
Embedded system design is challenged by the gap between the ever-increasing customer demands and the limited resource budgets. The tough competition demands ever-shortening time-to-market and product lifecycles. To solve or, at least to alleviate, the aforementioned issues, designers and manufacturers need model-based quantitative analysis techniques for early design-space exploration to study trade-offs of different implementation candidates. Moreover, modern embedded applications, especially the streaming applications addressed in this thesis, face more and more dynamic input contents, and the platforms that they are running on are more flexible and allow runtime configuration. Quantitative analysis techniques for embedded system design have to be able to handle such dynamic adaptable systems. This thesis has the following contributions: - A resource-aware extension to the Synchronous Dataflow (SDF) model of computation. - Trade-off analysis techniques, both in the time-domain and in the iterationdomain (i.e., on an SDF iteration basis), with support for resource sharing. - Bottleneck-driven design-space exploration techniques for resource-aware SDF. - A game-theoretic approach to controller synthesis, guaranteeing performance under dynamic input. As a first contribution, we propose a new model, as an extension of static synchronous dataflow graphs (SDF) that allows the explicit modeling of resources with consistency checking. The model is called resource-aware SDF (RASDF). The extension enables us to investigate resource sharing and to explore different scheduling options (ways to allocate the resources to the different tasks) using state-space exploration techniques. Consistent SDF and RASDF graphs have the property that an execution occurs in so-called iterations. An iteration typically corresponds to the processing of a meaningful piece of data, and it returns the graph to its initial state. On multiprocessor platforms, iterations may be executed in a pipelined fashion, which makes performance analysis challenging. As the second contribution, this thesis develops trade-off analysis techniques for RASDF, both in the time-domain and in the iteration-domain (i.e., on an SDF iteration basis), to dimension resources on platforms. The time-domain analysis allows interleaving of different iterations, but the size of the explored state space grows quickly. The iteration-based technique trades the potential of interleaving of iterations for a compact size of the iteration state space. An efficient bottleneck-driven designspace exploration technique for streaming applications, the third main contribution in this thesis, is derived from analysis of the critical cycle of the state space, to reveal bottleneck resources that are limiting the throughput. All techniques are based on state-based exploration. They enable system designers to tailor their platform to the required applications, based on their own specific performance requirements. Pruning techniques for efficient exploration of the state space have been developed. Pareto dominance in terms of performance and resource usage is used for exact pruning, and approximation techniques are used for heuristic pruning. Finally, the thesis investigates dynamic scheduling techniques to respond to dynamic changes in input streams. The fourth contribution in this thesis is a game-theoretic approach to tackle controller synthesis to select the appropriate schedules in response to dynamic inputs from the environment. The approach transforms the explored iteration state space of a scenario- and resource-aware SDF (SARA SDF) graph to a bipartite game graph, and maps the controller synthesis problem to the problem of finding a winning positional strategy in a classical mean payoff game. A winning strategy of the game can be used to synthesize the controller of schedules for the system that is guaranteed to satisfy the throughput requirement given by the designer
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