226 research outputs found
Design of an endoscopic 3-D Particle-Tracking Velocimetry system and its application in flow measurements within a gravel layer
In this thesis a novel method for 3-D flow measurements within a permeable gravel layer is developed. Two fiberoptic endoscopes are used in a stereoscopic arrangement to acquire image sequences of the flow field within a single gravel pore. The images are processed by a 3-D Particle-Tracking Velocimetry (3-D PTV) algorithm, which yields the three-dimensional reconstruction of Lagrangian particle trajectories. The underlying image processing algorithms are significantly enhanced and adapted to the special conditions of endoscopic imagery. This includes methods for image preprocessing, robust camera calibration, image segmentation and particle-tracking. After a performance and accuracy analysis, the measurement technique is applied in extensive systematic investigations of the flow within a gravel layer in an experimental flume at the Federal Waterways Engineering and Research Institute in Karlsruhe. In addition to measurements of the pore flow within three gravel pores, an extended experimental setup enables the simultaneous observation of the near-bed 3-D flow field in the turbulent open-channel flow above the gravel layer and of grain motions in a sand layer beneath the gravel layer. The interaction of the free surface flow and the pore flow can be analyzed for the first time with a high temporal and spatial resolution. The experiments are part of a research project initiated by an international cooperation called Filter and Erosion Research Club (FERC). The longterm goal of this project is to quantify the influence of turbulent velocity and pressure fluctuations on the bed stability of waterways. The obtained experimental data provide new insight into the damping behaviour of a gravel bed and can be used for comparison with numerical, analytical and phenomenological models
Flood dynamics derived from video remote sensing
Flooding is by far the most pervasive natural hazard, with the human impacts of floods expected to worsen in the coming decades due to climate change. Hydraulic models are a key tool for understanding flood dynamics and play a pivotal role in unravelling the processes that occur during a flood event, including inundation flow patterns and velocities. In the realm of river basin dynamics, video remote sensing is emerging as a transformative tool that can offer insights into flow dynamics and thus, together with other remotely sensed data, has the potential to be deployed to estimate discharge. Moreover, the integration of video remote sensing data with hydraulic models offers a pivotal opportunity to enhance the predictive capacity of these models.
Hydraulic models are traditionally built with accurate terrain, flow and bathymetric data and are often calibrated and validated using observed data to obtain meaningful and actionable model predictions. Data for accurately calibrating and validating hydraulic models are not always available, leaving the assessment of the predictive capabilities of some models deployed in flood risk management in question. Recent advances in remote sensing have heralded the availability of vast video datasets of high resolution. The parallel evolution of computing capabilities, coupled with advancements in artificial intelligence are enabling the processing of data at unprecedented scales and complexities, allowing us to glean meaningful insights into datasets that can be integrated with hydraulic models. The aims of the research presented in this thesis were twofold. The first aim was to evaluate and explore the potential applications of video from air- and space-borne platforms to comprehensively calibrate and validate two-dimensional hydraulic models. The second aim was to estimate river discharge using satellite video combined with high resolution topographic data. In the first of three empirical chapters, non-intrusive image velocimetry techniques were employed to estimate river surface velocities in a rural catchment. For the first time, a 2D hydraulicvmodel was fully calibrated and validated using velocities derived from Unpiloted Aerial Vehicle (UAV) image velocimetry approaches. This highlighted the value of these data in mitigating the limitations associated with traditional data sources used in parameterizing two-dimensional hydraulic models. This finding inspired the subsequent chapter where river surface velocities, derived using Large Scale Particle Image Velocimetry (LSPIV), and flood extents, derived using deep neural network-based segmentation, were extracted from satellite video and used to rigorously assess the skill of a two-dimensional hydraulic model. Harnessing the ability of deep neural networks to learn complex features and deliver accurate and contextually informed flood segmentation, the potential value of satellite video for validating two dimensional hydraulic model simulations is exhibited. In the final empirical chapter, the convergence of satellite video imagery and high-resolution topographical data bridges the gap between visual observations and quantitative measurements by enabling the direct extraction of velocities from video imagery, which is used to estimate river discharge. Overall, this thesis demonstrates the significant potential of emerging video-based remote sensing datasets and offers approaches for integrating these data into hydraulic modelling and discharge estimation practice. The incorporation of LSPIV techniques into flood modelling workflows signifies a methodological progression, especially in areas lacking robust data collection infrastructure. Satellite video remote sensing heralds a major step forward in our ability to observe river dynamics in real time, with potentially significant implications in the domain of flood modelling science
Power Distribution System Event Classification Using Fuzzy Logic
This dissertation describes an on-line, non-intrusive, classification system for identifying and reporting normal and abnormal power system events occurring on a distribution feeder based on their underlying cause, using signals acquired at the distribution substation. The event classification system extracts features from acquired signals using signal processing and shape analysis techniques. It then analyzes features and classifies events based on their cause using a fuzzy logic expert system based classifier. The classification system also extracts and reports parameters to assist utilities in locating faulty components. A detailed illustration of the classifier design process is presented.
Power distribution system event classification problem is shown to be a large scale classification problem. The reasoning behind the choice of a fuzzy logic based hierarchical expert system classifier to solve this problem is explained in detail. The fuzzy logic based expert system classifier uses generic features, shape based features and event specific features extracted from acquired signals. The design of feature extractors for each of these feature categories is explained. A new, fuzzy logic based, modified Dynamic Time Warping (DTW) algorithm was developed for extracting shape based features. Design of event specific feature extractors for capacitor problems, arcing and overcurrent events are discussed in detail. The fuzzy logic based hierarchical expert system classifier required a new fuzzy inference engine that could efficiently handle a large number of rules and rule chaining. A new fuzzy inference engine was designed for this purpose and the design process is explained in detail. To avoid information overload, an intelligent reporting framework that processes raw classification information generated by the fuzzy classifier and reports events of interest in a timely and user friendly manner was developed.
Finally, performance studies were carried out to validate the performance of the designed fuzzy logic based expert system classifier and the intelligent reporting system. The data needed to design and validate the classification system were obtained through the Distribution Fault Anticipation (DFA) data collection plat- form developed by Power System Automation Laboratory (PSAL) at Texas A&M University, sponsored by the Electric Power Research Institute (EPRI) and multiple partner utilities
Field-based measurement of hydrodynamics associated with engineered in-channel structures: the example of fish pass assessment
The construction of fish passes has been a longstanding measure to improve
river ecosystem status by ensuring the passability of weirs, dams and other in-
channel structures for migratory fish. Many fish passes have a low biological
effectiveness because of unsuitable hydrodynamic conditions hindering fish to
rapidly detect the pass entrance. There has been a need for techniques to
quantify the hydrodynamics surrounding fish pass entrances in order to identify
those passes that require enhancement and to improve the design of new
passes. This PhD thesis presents the development of a methodology for the
rapid, spatially continuous quantification of near-pass hydrodynamics in the
field. The methodology involves moving-vessel Acoustic Doppler Current
Profiler (ADCP) measurements in order to quantify the 3-dimensional water
velocity distribution around fish pass entrances. The approach presented in this
thesis is novel because it integrates a set of techniques to make ADCP data
robust against errors associated with the environmental conditions near
engineered in-channel structures. These techniques provide solutions to
(i) ADCP compass errors from magnetic interference, (ii) bias in water velocity
data caused by spatial flow heterogeneity, (iii) the accurate ADCP positioning in
locales with constrained line of sight to navigation satellites, and (iv) the
accurate and cost-effective sensor deployment following pre-defined sampling
strategies. The effectiveness and transferability of the methodology were
evaluated at three fish pass sites covering conditions of low, medium and high
discharge. The methodology outputs enabled a detailed quantitative
characterisation of the fish pass attraction flow and its interaction with other
hydrodynamic features. The outputs are suitable to formulate novel indicators of
hydrodynamic fish pass attractiveness and they revealed the need to refine
traditional fish pass design guidelines
Downstream suspended sediment dynamics of reservoir sediment flushing.
PhDReservoir sediment flushing is increasingly considered beneficial to reduce sedimentation of reservoirs and maintain sediment supply downstream of impounded rivers. Nevertheless, flushing of the accumulated sediments downstream of the dam also bears numerous negative impacts. In this study, first the most important downstream impacts of fine sediment releases of flushing were identified based on previously published research of twenty case studies in eleven countries. The results showed that the long-term as well as short term biological and physical impacts decreased with distance from the dam. The temporal scale of impacts on macro-invertebrates could span from few weeks or a month to several months while the effect on fish could last for a number of years. The impacts on downstream vegetation dynamics is driven by many years of flushing activities. The study also enabled proposing generic management strategies aimed to reduce the impacts.
Second, fine sediment transport in coarse immobile bed, which is a common phenomenon downstream of dams during flushing releases, dam removal and also in many mountain and canyon rivers, was investigated. Particularly, the dynamics of the downstream erosion and transport of fine sediments released during sediment flushing was investigated based on a series of flume experiments that were carried out in immobile gravel bed and using a one-dimensional (1-D) suspended sediment transport model developed in the present study. In the framework of the flume experiment, firstly gravel bed roughness, porosity and roughness density were exclusively extracted from gravel surface elevation data in which developing a spatial filter to overcome elevation errors was carried out. Secondly a new technique to acquire fine sediment erosion in immobile coarse bed in running water condition was developed. The method proved to be the back bone of all fine sediment erosion experiments conducted in the present study and could be used for similar studies. This study presents a first work of direct measurement of erosion rate and characterizing its spatial heterogeneity in gravel bed. The experimental data of erosion rate of fine sediments showed that it varied spatially with high erosion rate on the stoss side of gravels and less on the lee side conforming to sweeps and ejections characteristics in coherent flow structure of gravel bed flows. Erosion rate was significantly affected by increase in roughness of immobile gravel bed with high erosion rate noticed when sand level was reduced although the effect on stream-wise velocity was not significant. The vertical profile of erosion rate was found to decrease linearly and showed an exponential decay in time in the gravel matrix.
Third, a new non-equilibrium erosion rate relation is proposed. Drag force profile in the interfacial sublayer of clean gravel bed was found to be scaled well with roughness density and allowed predicting the effective shear stress distribution available for fine sediment entrainment with an empirical equation.
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The new relation is a modified version of the pick-up rate function of van Rijn (1984b) in which the predicted shear stress in the roughness layer was implemented. The most important finding was that if the shear stress distribution in the interfacial sublayer is predicted, a relation for sand bed condition can be applied to predict fine sediment erosion rate in immobile gravel bed. This approach is conceptually superior to previous approaches where erosion rate in sand bed condition was scaled empirically for various fine sediment bed level within the interfacial sublayer.
Finally, the effect of the interaction between hydrodynamic and sediment wave dynamics of sediment flushing on spatial pattern of sediment deposition was investigated. The 1-D model was developed to include major processes observed in sediment flushing: sediment wave celerity correction, variable bed roughness, bed exchange in immobile bed, hindered settling velocity and rough bed porosity. The proposed erosion rate relation showed encouraging results when implemented in the 1-D model. The wave celerity factor did not show significant effect on the spatial lag in immobile bed condition although was significant in sand bed condition. Variable bed roughness modified both the flow field and sediment deposition in which larger length of sediment deposit was noted. The immobile bed porosity allowed modelling clogged depth of fine sediments. The model was also found to be very valuable to investigate flushing scenarios that reduce significant deposition through the analysis of the dependence of deposition on peak-to-base flow and intermittence of releases. The highest peak-to-base flows produced the longest and thickest region of deposition while those with the lowest ratio produced the shortest and thinnest. A single flushing release followed by clear water release reduced area or length of sediment deposition more than intermittent flushing followed by inter- and post-flushing clear water releases. In the latter case, the peak of concentration reduced but remained higher for longer duration than the former, which suggests that a large quantity of clear water release has to be available.
Overall, the present research represents a step forward in understanding relevant processes involved in the downstream transport of fine sediments released during sediment flushing and the associated impacts that can help the development of better management strategies and predictive tools.This project has been funded with support from the European Commission
BioMEMS
As technological advancements widen the scope of applications for biomicroelectromechanical systems (BioMEMS or biomicrosystems), the field continues to have an impact on many aspects of life science operations and functionalities. Because BioMEMS research and development require the input of experts who use different technical languages and come from varying disciplines and backgrounds, scientists and students can avoid potential difficulties in communication and understanding only if they possess a skill set and understanding that enables them to work at the interface of engineering and biosciences. Keeping this duality in mind throughout, BioMEMS: Science and Engineering Perspectives supports and expedites the multidisciplinary learning involved in the development of biomicrosystems. Divided into nine chapters, it starts with a balanced introduction of biological, engineering, application, and commercialization aspects of the field. With a focus on molecules of biological interest, the book explores the building blocks of cells and viruses, as well as molecules that form the self-assembled monolayers (SAMs), linkers, and hydrogels used for making different surfaces biocompatible through functionalization. The book also discusses: Different materials and platforms used to develop biomicrosystems Various biological entities and pathogens (in ascending order of complexity) The multidisciplinary aspects of engineering bioactive surfaces Engineering perspectives, including methods of manufacturing bioactive surfaces and devices Microfluidics modeling and experimentation Device level implementation of BioMEMS concepts for different applications. Because BioMEMS is an application-driven field, the book also highlights the concepts of lab-on-a-chip (LOC) and micro total analysis system (μTAS), along with their pertinence to the emerging point-of-care (POC) and point-of-need (PON) applications
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