232 research outputs found

    Sensing and control for fishlike propulsion in unsteady environments

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    Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 249-263).Fish are equipped with a unique and elaborate flow sensing system, the lateral line, that enables them to reconstruct the near-field three-dimensional flow around their bodies, and hence effect precise control for optimal propulsion and to achieve energy recovery from vortical flows. This is a capability that is not available to engineered underwater systems today. A paradigm example lies in the ability of fish to save energy when swimming in schools, through extracting energy from vortices generated by other fish. For a single fish modeled as an undulating, foil-shaped body at Reynolds number Re=5000, swimming directly behind another fish results in energy savings of 15-20%, compared with swimming alone. This is achieved by properly timing the interaction with vortices generated from the upstream fish, as they travel along its body and tail. Fish that have evolved for sustained fast swimming, such as tunas and dolphins, possess a stiff tail that is morphologically separate from their body. For such fish, the phasing of tail motion is known to be important, and we demonstrate that independent and precise control of the tail is even more critical for flow control in the presence of external vortices. With an independently pitching caudal fin, small variations in phase can alter the energy savings by 15% or more, and precise timing can allow the fish to swim behind another fish with less than 50% of the energy required in quiescent water. We explore the flow mechanisms that lead to this remarkable performance and provide detailed flow visualization documenting the vorticity control effected by the independently pitching tail. We also show that the precise feedback control required to achieve this remarkable swimming performance is feasible using the distributed flow sensing provided by the lateral line. A model-based observer is shown to be capable of extracting the positions of near-field vortices using distributed surface pressure measurements, within an error of less than 1% of the body length. With this precise feedback, we show that the fish can lock in to the frequency of an upstream wake at the correct phase, and fine-tune its tail motion to optimally exploit the wake. This demonstrates that, together, distributed flow sensing and vorticity control provide a powerful tool to control the flow for enhanced swimming performance.by Amy Ruiming Gao.Ph. D

    Three-dimensional joint kinematics of swimming using body-worn inertial and magnetic sensors

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    Wearable inertial and magnetic measurements units (IMMU) are an important tool for underwater motion analysis because they are swimmer-centric, they require only simple measurement set-up and they provide the performance results very quickly. In order to estimate 3D joint kinematics during motion, protocols were developed to transpose the IMMU orientation estimation to a biomechanical model. The aim of the thesis was to validate a protocol originally propositioned to estimate the joint angles of the upper limbs during one-degree-of-freedom movements in dry settings and herein modified to perform 3D kinematics analysis of shoulders, elbows and wrists during swimming. Eight high-level swimmers were assessed in the laboratory by means of an IMMU while simulating the front crawl and breaststroke movements. A stereo-photogrammetric system (SPS) was used as reference. The joint angles (in degrees) of the shoulders (flexion-extension, abduction-adduction and internal-external rotation), the elbows (flexion-extension and pronation-supination), and the wrists (flexion-extension and radial-ulnar deviation) were estimated with the two systems and compared by means of root mean square errors (RMSE), relative RMSE, Pearson’s product-moment coefficient correlation (R) and coefficient of multiple correlation (CMC). Subsequently, the athletes were assessed during pool swimming trials through the IMMU. Considering both swim styles and all joint degrees of freedom modeled, the comparison between the IMMU and the SPS showed median values of RMSE lower than 8°, representing 10% of overall joint range of motion, high median values of CMC (0.97) and R (0.96). These findings suggest that the protocol accurately estimated the 3D orientation of the shoulders, elbows and wrists joint during swimming with accuracy adequate for the purposes of research. In conclusion, the proposed method to evaluate the 3D joint kinematics through IMMU was revealed to be a useful tool for both sport and clinical contexts

    Aeronautical engineering: A continuing bibliography with indexes (supplement 237)

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    This bibliography lists 572 reports, articles, and other documents introduced into the NASA scientific and technical information system in February, 1989. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

    Aeronautical Engineering: A cumulative index to the 1984 issues of the continuing bibliography

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    This bibliography is a cumulative index to the abstracts contained in NASA SP-7037(171) through NASA SP-7037(182) of Aeronautical Engineering: A Continuing Bibliography. NASA SP-7037 and its supplements have been compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). This cumulative index includes subject, personal author, corporate source, foreign technology, contract, report number, and accession number indexes

    Path planning, flow estimation, and dynamic control for underwater vehicles

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    Underwater vehicles such as robotic fish and long-endurance ocean-sampling platforms operate in challenging fluid environments. This dissertation incorporates models of the fluid environment in the vehicles' guidance, navigation, and control strategies while addressing uncertainties associated with estimates of the environment's state. Coherent flow structures may be on the same spatial scale as the vehicle or substantially larger than the vehicle. This dissertation argues that estimation and control tasks across widely varying spatial scales, from vehicle-scale to long-range, may be addressed using common tools of empirical observability analysis, nonlinear/non-Gaussian estimation, and output-feedback control. As an application in vehicle-scale flow estimation and control, this dissertation details the design, fabrication, and testing of a robotic fish with an artificial lateral-line inspired by the lateral-line flow-sensing organ present in fish. The robotic fish is capable of estimating the flow speed and relative angle of the oncoming flow. Using symmetric and asymmetric sensor configurations, the robot achieves the primitive fish behavior called rheotaxis, which describes a fish's tendency to orient upstream. For long-range flow estimation and control, path planning may be accomplished using observability-based path planning, which evaluates a finite set of candidate control inputs using a measure related to flow-field observability and selects an optimizer over the set. To incorporate prior information, this dissertation derives an augmented observability Gramian using an optimal estimation strategy known as Incremental 4D-Var. Examination of the minimum eigenvalue of an empirical version of this Gramian yields a novel measure for path planning, called the empirical augmented unobservability index. Numerical experiments show that this measure correctly selects the most informative paths given the prior information. As an application in long-range flow estimation and control, this dissertation considers estimation of an idealized pair of ocean eddies by an adaptive Lagrangian sensor (i.e., a platform that uses its position data as measurements of the fluid transport, after accounting for its own control action). The adaptive sampling is accomplished using the empirical augmented unobservability index, which is extended to non-Gaussian posterior densities using an approximate expected-cost calculation. Output feedback recursively improves estimates of the vehicle position and flow-field states

    Machine Learning for Fluid Mechanics

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    The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from field measurements, experiments and large-scale simulations at multiple spatiotemporal scales. Machine learning offers a wealth of techniques to extract information from data that could be translated into knowledge about the underlying fluid mechanics. Moreover, machine learning algorithms can augment domain knowledge and automate tasks related to flow control and optimization. This article presents an overview of past history, current developments, and emerging opportunities of machine learning for fluid mechanics. It outlines fundamental machine learning methodologies and discusses their uses for understanding, modeling, optimizing, and controlling fluid flows. The strengths and limitations of these methods are addressed from the perspective of scientific inquiry that considers data as an inherent part of modeling, experimentation, and simulation. Machine learning provides a powerful information processing framework that can enrich, and possibly even transform, current lines of fluid mechanics research and industrial applications.Comment: To appear in the Annual Reviews of Fluid Mechanics, 202

    A comparison study of biologically inspired propulsion systems for an autonomous underwater vehicle

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    The field of Autonomous Underwater Vehicles (AUVs) has increased dramatically in size and scope over the past two decades. Application areas for AUVs are numerous and varied; from deep sea exploration, to pipeline surveillance to mine clearing. However, one limiting factor with the current technology is the duration of missions that can be undertaken and one contributing factor to this is the efficiency of the propulsion system, which is usually based on marine propellers. As fish are highly efficient swimmers greater propulsive efficiency may be possible by mimicking their fish tail propulsion system. The main concept behind this work was therefore to investigate whether a biomimetic fish-like propulsion system is a viable propulsion system for an underwater vehicle and to determine experimentally the efficiency benefits of using such a system. There have been numerous studies into biomimetic fish like propulsion systems and robotic fish in the past with many claims being made as to the benefits of a fish like propulsion system over conventional marine propulsion systems. These claims include increased efficiency and greater manoeuvrability. However, there is little published experimental data to characterise the propulsive efficiency of a fish like propulsive system. Also, very few direct experimental comparisons have been made between biomimetic and conventional propulsion systems. This work attempts to address these issues by directly comparing experimentally a biomimetic underwater propulsion system to a conventional propulsion system to allow for a better understanding of the potential benefits of the biomimetic system. This work is split into three parts. Firstly, the design and development of a novel prototype vehicle called the RoboSalmon is covered. This vehicle has a biomimetic tendon drive propulsion system which utilizes one servo motor for actuation and has a suite of onboard sensors and a data logger. The second part of this work focuses on the development of a mathematical model of the RoboSalmon vehicle to allow for a better understanding of the dynamics of the system. Simulation results from this model are compared to the experimental results and show good correlation. The final part of the work presents the experimental results obtained comparing the RoboSalmon prototype with the biomimetic tail system to the propeller and rudder system. These experiments include a study into the straight swimming performance, recoil motion, start up transients and power consumption. For forward swimming the maximum surge velocity of the RoboSalmon was 0.18ms-1 and at this velocity the biomimetic system was found to be more efficient than the propeller system. When manoeuvring the biomimetic system was found to have a significantly reduced turning radius. The thesis concludes with a discussion of the main findings from each aspect of the work, covering the benefits obtained from using the tendon drive system in terms of efficiencies and manoeuvring performance. The limitations of the system are also discussed and suggestions for further work are included

    Aeronautical Engineering: A Continuing Bibliography with indexes

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    This bibliography lists 426 reports, articles and other documents introduced into the NASA scientific and technical information system in August 1984. Reports are cited in the area of Aeronautical Engineering. The coverage includes documents on the engineering and theoretical aspects of design, construction, evaluation, testing operation and performance of aircraft (including aircraft engines) and associated components, equipment and systems
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