Integration of micro- and macroscopic models for pedestrian evacuation simulation

Simulation of pedestrian evacuations of smart buildings in emergency is a powerful tool for building analysis, dynamic evacuation planning and real-time response to the evolving state of evacuations. Macroscopic pedestrian models are low-complexity models that are and well suited to algorithmic analysis and planning, but are quite abstract. Microscopic simulation models allow for a high level of simulation detail but can be computationally intensive. By combining micro- and macro- models we can use each to overcome the shortcomings of the other and enable new capability and applications for pedestrian evacuation simulation that would not be possible with either alone. We develop the EvacSim multi-agent pedestrian simulator and procedurally generate macroscopic flow graph models of building space, integrating micro- and macroscopic approaches to simulation of the same emergency space. By “coupling” flow graph parameters to microscopic simulation results, the graph model captures some of the higher detail and fidelity of the complex microscopic simulation model. The coupled flow graph is used for analysis and prediction of the movement of pedestrians in the microscopic simulation, and investigate the performance of dynamic evacuation planning in simulated emergencies using a variety of strategies for allocation of macroscopic evacuation routes to microscopic pedestrian agents. The predictive capability of the coupled flow graph is exploited for the decomposition of microscopic simulation space into multiple future states in a scalable manner. By simulating multiple future states of the emergency in short time frames, this enables sensing strategy based on simulation scenario pattern matching which we show to achieve fast scenario matching, enabling rich, real-time feedback in emergencies in buildings with meagre sensing capabilities.

Optimisation of Smart Grid performance using centralised and distributed control techniques

A massive change is currently taking place in the manner in which power networks are operated. Traditionally, power networks consisted of large power stations which were controlled from centralised locations. The trend in modern power networks is for generated power to be produced by a diverse array of energy sources which are spread over a large geographical area. As a result, controlling these systems from a centralised controller is impractical. Thus, future power networks will be controlled by a large number of intelligent distributed controllers which must work together to coordinate their actions. The term Smart Grid is the umbrella term used to denote this combination of power systems, artificial intelligence, and communications engineering. This thesis focuses on the application of optimal control techniques to Smart Grids with a focus in particular on iterative distributed MPC. A novel convergence and stability proof for iterative distributed MPC based on the Alternating Direction Method of Multipliers is derived. Distributed and centralised MPC, and an optimised PID controllers' performance are then compared when applied to a highly interconnected, nonlinear, MIMO testbed based on a part of the Nordic power grid. Finally, a novel tuning algorithm is proposed for iterative distributed MPC which simultaneously optimises both the closed loop performance and the communication overhead associated with the desired control.

A novel and miniaturized 433/868MHz multi-band wireless sensor platform for body sensor network applications

Body Sensor Network (BSN) technology is seeing a rapid emergence in application areas such as health, fitness and sports monitoring. Current BSN wireless sensors typically operate on a single frequency band (e.g. utilizing the IEEE 802.15.4 standard that operates at 2.45GHz) employing a single radio transceiver for wireless communications. This allows a simple wireless architecture to be realized with low cost and power consumption. However, network congestion/failure can create potential issues in terms of reliability of data transfer, quality-of-service (QOS) and data throughput for the sensor. These issues can be especially critical in healthcare monitoring applications where data availability and integrity is crucial. The addition of more than one radio has the potential to address some of the above issues. For example, multi-radio implementations can allow access to more than one network, providing increased coverage and data processing as well as improved interoperability between networks. A small number of multi-radio wireless sensor solutions exist at present but require the use of more than one radio transceiver devices to achieve multi-band operation. This paper presents the design of a novel prototype multi-radio hardware platform that uses a single radio transceiver. The proposed design allows multi-band operation in the 433/868MHz ISM bands and this, together with its low complexity and small form factor, make it suitable for a wide range of BSN applications.

Simulation of multigate SOI transistors with silicon, germanium and III-V channels

In this work by employing numerical three-dimensional simulations we study the electrical performance and short channel behavior of several multi-gate transistors based on advanced SOI technology. These include FinFETs, triple-gate and gate-all-around nanowire FETs with different channel material, namely Si, Ge, and III-V compound semiconductors, all most promising candidates for future nanoscale CMOS technologies. Also, a new type of transistor called “junctionless nanowire transistor” is presented and extensive simulations are carried out to study its electrical characteristics and compare with the conventional inversion- and accumulation-mode transistors. We study the influence of device properties such as different channel material and orientation, dimensions, and doping concentration as well as quantum effects on the performance of multi-gate SOI transistors. For the modeled n-channel nanowire devices we found that at very small cross sections the nanowires with silicon channel are more immune to short channel effects. Interestingly, the mobility of the channel material is not as significant in determining the device performance in ultrashort channels as other material properties such as the dielectric constant and the effective mass. Better electrostatic control is achieved in materials with smaller dielectric constant and smaller source-to-drain tunneling currents are observed in channels with higher transport effective mass. This explains our results on Si-based devices. In addition to using the commercial TCAD software (Silvaco and Synopsys TCAD), we have developed a three-dimensional Schrödinger-Poisson solver based on the non-equilibrium Green’s functions formalism and in the framework of effective mass approximation. This allows studying the influence of quantum effects on electrical performance of ultra-scaled devices. We have implemented different mode-space methodologies in our 3D quantum-mechanical simulator and moreover introduced a new method to deal with discontinuities in the device structures which is much faster than the coupled-mode-space approach.