Laboratory measurements and computer simulations of highly curved flow after sluice gate

Sluice-gates are widely used for such purposes as the control of discharges and water levels in hydraulic engineering systems. It is important to understand the features of turbulent flow passing underneath a sluice-gate. Previously, a great deal of research attention has centred on such flow features as the head-discharge relationship and the pressure distribution over the gate surfaces, leading to impressive progress in those aspects of the turbulent flow problem. However, little attention has been paid to the curvature of flow profiles immediately downstream of the gate. This is in spite of its relevance to the optimal design and safe operations of sluice-gates. The purpose of this research work is to characterise the highly curved turbulent flow through laboratory flume experiments and to extend the experimental results by computer simulations. The experiments covered the conditions that the gate opening ranged from one to two inches and the ratio of the upstream depth to the gate opening ranged from four to 16. The computer simulations produced finite volume solutions to the Reynolds-averaged Navier-Stokes equations. Under the same conditions as the flume experiments, the computed flow profiles as well as pressure distributions from the simulations compare well with the experimental data. Much of the success in computations is attributable to the implementation of rigorous procedures to validate mesh convergence, the independence of numerical results on time step and initial conditions used, and the suitability of turbulence closure schemes. The shear stress transport k-ω model is shown to be a suitable model for turbulence closure. It is shown that the volume of fluid method works well for tracking the highly curved free water surface. This thesis reports further computational results of the flow and pressure fields for large gate openings up to 16 inches, which are close to field scales or prototype scales, and which are difficult and expensive to set up in laboratories. Using the new experimental and computational results, reliable relationships for flow curvature parameters, including the radius of the circle of curvature, the centre of the circle, and the angle of a tangent to the free surface with the channel-bottom, have been developed. The introduction of these new relationships to the permanent literature about sluice-gate flows represents a significant contribution from this research work. This thesis also provides an update of the contraction distance and coefficient, the results being consistent with the literature values. Moreover, corrections to some existing formulations of the sluice-gate flow problem are proposed

Securing Cyber-Physical Social Interactions on Wrist-worn Devices

Since ancient Greece, handshaking has been commonly practiced between two people as a friendly gesture to express trust and respect, or form a mutual agreement. In this article, we show that such physical contact can be used to bootstrap secure cyber contact between the smart devices worn by users. The key observation is that during handshaking, although belonged to two different users, the two hands involved in the shaking events are often rigidly connected, and therefore exhibit very similar motion patterns. We propose a novel key generation system, which harvests motion data during user handshaking from the wrist-worn smart devices such as smartwatches or fitness bands, and exploits the matching motion patterns to generate symmetric keys on both parties. The generated keys can be then used to establish a secure communication channel for exchanging data between devices. This provides a much more natural and user-friendly alternative for many applications, e.g., exchanging/sharing contact details, friending on social networks, or even making payments, since it doesn’t involve extra bespoke hardware, nor require the users to perform pre-defined gestures. We implement the proposed key generation system on off-the-shelf smartwatches, and extensive evaluation shows that it can reliably generate 128-bit symmetric keys just after around 1s of handshaking (with success rate >99%), and is resilient to different types of attacks including impersonate mimicking attacks, impersonate passive attacks, or eavesdropping attacks. Specifically, for real-time impersonate mimicking attacks, in our experiments, the Equal Error Rate (EER) is only 1.6% on average. We also show that the proposed key generation system can be extremely lightweight and is able to run in-situ on the resource-constrained smartwatches without incurring excessive resource consumption