A robust position control for induction machines

ICEM 2010

Decision support systems optimising effluent release in sub tropical estuarine environment - An Australian case study

Gold Coast Water is responsible for the management of the water and wastewater assets of the City of the Gold Coast on Australia’s east coast. Treated wastewater is released at the Gold Coast Seaway on an outgoing tide in order for the plume to be dispersed before the tide changes and renters the Broadwater estuary. Rapid population growth over the past decade has placed increasing demands on the receiving waters for the release of the City’s effluent. The Seaway SmartRelease Project is designed to optimise the release of the effluent from the City’s main wastewater treatment plant in order to minimise the impact of the estuarine water quality and maximise the cost efficiency of pumping. In order to do this an optimisation study that involves water quality monitoring, numerical modelling and a web based decision support system was conducted. An intensive monitoring campaign provided information on water levels, currents, winds, waves, nutrients and bacterial levels within the Broadwater. These data were then used to calibrate and verify numerical models using the MIKE by DHI suite of software. The decision support system then collects continually measured data such as water levels, interacts with the WWTP SCADA system, runs the models in forecast mode and provides the optimal time window to release the required amount of effluent from the WWTP. The City’s increasing population means that the length of time available for releasing the water with minimal impact may be exceeded within 5 years. Optimising the release of the treated water through monitoring, modelling and a decision support system has been an effective way of demonstrating the limited environmental impact of the expected short term increase in effluent disposal procedures. (PDF contains 5 pages)

Synthetic molecular machines for active self-assembly : prototype algorithms, designs, and experimental study

Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast–all while remaining functional.

This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context of “active self-assembly” of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology’s numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules.

One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved.

One might think that because a system is Turing-complete, capable of computing “anything,” that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not “computations” in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface.

Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors “energetically incomplete” programmable behaviors. This class of behaviors includes any behavior where a passive physical system simply does not have enough physical energy to perform the specified tasks in the requisite amount of time.

As we will demonstrate and prove, a sufficiently expressive implementation of an “active” molecular self-assembly approach can achieve these behaviors. Using an external source of fuel solves part of the the problem, so the system is not “energetically incomplete.” But the programmable system also needs to have sufficient expressive power to achieve the specified behaviors. Perhaps surprisingly, some of these systems do not even require Turing completeness to be sufficiently expressive.

Building on a large variety of work by other scientists in the fields of DNA nanotechnology, chemistry and reconfigurable robotics, this thesis introduces several research contributions in the context of active self-assembly.

We show that simple primitives such as insertion and deletion are able to generate complex and interesting results such as the growth of a linear polymer in logarithmic time and the ability of a linear polymer to treadmill. To this end we developed a formal model for active-self assembly that is directly implementable with DNA molecules. We show that this model is computationally equivalent to a machine capable of producing strings that are stronger than regular languages and, at most, as strong as context-free grammars. This is a great advance in the theory of active self- assembly as prior models were either entirely theoretical or only implementable in the context of macro-scale robotics.

We developed a chain reaction method for the autonomous exponential growth of a linear DNA polymer. Our method is based on the insertion of molecules into the assembly, which generates two new insertion sites for every initial one employed. The building of a line in logarithmic time is a first step toward building a shape in logarithmic time. We demonstrate the first construction of a synthetic linear polymer that grows exponentially fast via insertion. We show that monomer molecules are converted into the polymer in logarithmic time via spectrofluorimetry and gel electrophoresis experiments. We also demonstrate the division of these polymers via the addition of a single DNA complex that competes with the insertion mechanism. This shows the growth of a population of polymers in logarithmic time. We characterize the DNA insertion mechanism that we utilize in Chapter 4. We experimentally demonstrate that we can control the kinetics of this re- action over at least seven orders of magnitude, by programming the sequences of DNA that initiate the reaction.

In addition, we review co-authored work on programming molecular robots using prescriptive landscapes of DNA origami; this was the first microscopic demonstration of programming a molec- ular robot to walk on a 2-dimensional surface. We developed a snapshot method for imaging these random walking molecular robots and a CAPTCHA-like analysis method for difficult-to-interpret imaging data.

Design support for turbomachinery

From the steam turbines which provide most of our electricity to the jet engines which have shrunk our World, turbomachines undoubtedly play a major role in life today. Competition in the turbomachinery industry is fiercely strong [Wisler, 1998], hence good aerodynamic design is vital. However, with efficiency levels already close to their theoretical maxima, companies are increasingly looking to reduce costs and increase reliability through improved design practice. Computational Fluid Dynamics (CFD) can make a strong contribution to assisting this process as it has the potential to increase performance while reducing cost. The situation is, however, complicated by an ever decreasing number of engineers with sufficient design experience to reap the full benefits offered by CFD. With the large risks involved, novice designers of today are increasingly confined to refining old designs rather than gaining experience, like their forebears, through 'clean sheet' exercises. Hence it is desirable to capture the knowledge and experience of older designers, before it is lost, to assist the engineers of tomorrow. It is therefore the aim of this project to produce a design support tool which will not only store the appropriate CFD codes, but also provide a dynamic signpost (based on elicited knowledge and experience) to advise the engineer in their use. The signposting methodology developed for the aerospace industry [Clarkson and Hamilton, 1997] will provide the basic framework for the tool. This paper reviews current turbomachinery design practice (including an examination of the relevant CFD) in order to establish the important issues which a support tool must address. Current design support methodologies and their propriety are then reviewed, followed by a detailed description of the signposting concept. It then sets out a clear statement of the objectives for the research and the methods proposed to meet them. The paper concludes with a timetable of the work.