A comprehensive review on the state-of-the-art of piezoelectric energy harvesting

This paper presents one of the first dedicated studies on mobile bed hydraulics of dam-break flow and the induced sediment transport and morphological evolution. A theoretical model is built upon the conservative laws of shallow water hydrodynamics, and a high-resolution numerical solution of the hyperbolic system is achieved using the total-variation-diminishing version of the second-order weighted average flux method in conjunction with the HLLC approximate Riemann solver and SUPERBEE limiter. It is found that a heavily concentrated and eroding wavefront first develops and then depresses gradually as it propagates downstream. In the early stage of the dam-break, a hydraulic jump is formed around the dam site due to rapid bed erosion, which attenuates progressively as it propagates upstream and eventually disappears. While the backward wave appears to migrate at the same speed as over a fixed bed, the propagation of the forward wavefront shows a complex picture compared to its fixed-bed counterpart as a result of the domination of rapid bed erosion initially, the density difference between the wavefront and the downstream ambient water in the intermediate period, and the pattern of the deformed bed profile in the long term. It is also found that the free surface profiles and hydrographs are greatly modified by bed mobility, which has considerable implications for flood prediction. The computed wave structure in the intermediate period exhibits great resemblance to available experiments qualitatively, and yet the existence of a shear wave is found in lieu of a secondary rarefaction postulated in an existing analysis. Finally, the use of the complete, rather than simplified, conservation equations is shown to be essential for correct resolution of the wave and bed structures, which suggests that previous models need reformulating.

Computational Dam-Break Hydraulics over Erodible Sediment Bed

In highly curved river bends, flow may separate at the inner bank to create a recirculation eddy with weak upstream flow. Very little is known about how recirculation eddies connect with the downstream flow or how the latter is affected by their presence. We investigate these questions using three-dimensional time-averaged computational fluid dynamics models of two natural bends with inner-bank separation. Test measurements of velocity in one bend agree well with the simulation. Common points in the two simulations are that (1) an outer-bank helix is only present in the upstream part of the bend, (2) maximum near-bank velocities are highest here rather than beyond the apex as in most bends, (3) reverse flow extends farther across the channel at the surface than the bed, and (4) flow within the recirculation eddy has a three-dimensional structure, linked with that in the outer-bank free stream. Substantial differences in detail between the two bends appear to be due to differences in upstream planform, manifested through the lateral distribution of inflow velocity.

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Flow in meander bends with recirculation at the inner bank

Neural network and neuro-fuzzy assessments for scour depth around bridge piers

The estimation of scour downstream of a ski-jump bucket has remained inconclusive, despite analysis of numerous prototypes as well as hydraulic model studies in the past. It is partly due to the complexity of the phenomenon involved and partly because of limitations of the traditional analytical tool of statistical regression. This paper addresses the latter part and presents an alternative to the regression in the form of neural networks. The depth of the scour hole developed along with its width and length is predicted using neural network models. A network architecture complete with trained values of connection weight and bias and requiring input of grouped parameters pertaining to discharge head, tail water channel depth, bucket radius, lip angle, and median sediment size is recommended in order to predict the depth, the location of maximum scour, as well as the width of scour hole. The neural network predictions have been compared with traditional statistical schemes. Although the common and simple feed forward back propagation network took a very long time to train as compared to some advanced schemes, it was found to impart equally reliable training as the latter. Use of causative variables in grouped forms was found to be more rewarding than that of their raw forms probably due to lesser scaling effect.

Neural Networks for Estimation of Scour Downstream of a Ski-Jump Bucket

Existing numerical river models are mostly built upon asynchronous solution of simplified governing equations. The strong coupling between water flow, sediment transport, and morphological evolution is thus ignored to a certain extent. An earlier study led to the development of a fully coupled model and identified the impacts of simplifications in the water-sediment mixture and global bed material continuity equations as well as of the asynchronous solution procedure for aggradation processes. This paper presents the results of an extended study along this line, highlighting the impacts on both aggradation and degradation processes. Simplifications in the continuity equations for the water-sediment mixture and bed material are found to have negligible effects on degradation. This is, however, in contrast to aggradation processes, in which the errors purely due to simplified continuity equations can be significant transiently. The asynchronous solution procedure is found to entail appreciable inaccuracy for both aggradation and degradation processes. Further, the asynchronous solution procedure can render the physical problem mathematically ill posed by invoking an extra upstream boundary condition in the supercritical flow regime. Finally, the impacts of simplified continuity equations and an asynchronous solution procedure are shown to be comparable with those of largely tuned friction factors, indicating their significance in calibrating numerical river models. It is concluded that the coupled system of complete governing equations needs to be synchronously solved for refined modeling of alluvial rivers.

Coupled and Decoupled Numerical Modeling of Flow and Morphological Evolution in Alluvial Rivers

Scour at culvert outlets is a phenomenon encountered world-wide. Research into the problem has mainly been of an experimental nature, with equations being derived for particular circumstances. These traditional scour prediction equations, although offering the engineer some guidance on the likely magnitude of maximum scour depth, are applicable only to a limited range of situations. A model for the prediction of scouring that is generally applicable to all circumstances is not currently available. However, there is a substantial amount of data available from research over many years in this area. This paper compares current prediction equations with results obtained from two Artificial Neural Network models (ANN). The development of a basic feed forward artificial neural network trained by back-propagation to model scour downstream of culvert outlets is described. A supervised training algorithm is used with data collected from published studies and the authors' own experimental work. The results show that the ANN can successfully predict the depth of scour with a greater accuracy than existing empirical formulae and over a wider range of conditions.

Prediction of scour depth at culvert outlets using neural networks

Performance analysis of a novel thermal management system with composite phase change material for a lithium-ion battery pack

Scouring downstream of culvert outlets is a common problem that can lead to damage to the culvert structure and neighbouring land. This paper presents measurements of the turbulent flow structure within scour holes downstream of pipe culvert outlets at different stages of development. Velocities have been recorded in scour holes at four stages of formation to enable changes in flow structure to be observed as the scour hole develops. The analysis of mean velocities, turbulence intensities, Reynolds stresses and near-bed bursting structure has led to a foundational understanding of the flow structure in scour holes. Initial scour hole development is a result of high velocities exceeding the critical velocity for sediment transport whilst further development results in a reduction in the magnitude of the near-bed velocities and an asymptotic increase in scour depth associated with the turbulent structure of the flow. Towards the downstream end of the scour holes the jet comes into contact with the bed and f...

Scour at culvert outlets as influenced by the turbulent flow structure

This is the peer reviewed version of the following article: Onoriu Puscasu, Nathan Counsell, Mohammad R. Herfatmanesh, Richard Peace, John Patsavellas, and Rodney Day, ‘Powering Lights with Piezoelectric Energy‐Harvesting Floors’, Energy Technology, Vol. 6 (5): 906-916, May 2018, which has been published in final form at https://doi.org/10.1002/ente.201700629. Under embargo until 6 March 2019. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

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Rodney Day

Papers

Coupled and Decoupled Numerical Modeling of Flow and Morphological Evolution in Alluvial Rivers

Prediction of scour depth at culvert outlets using neural networks

Performance analysis of a novel thermal management system with composite phase change material for a lithium-ion battery pack

Scour at culvert outlets as influenced by the turbulent flow structure

Powering Lights with Piezoelectric Energy-Harvesting Floors