Characterisation of Large Disturbance Rotor Angle and Voltage Stability in Interconnected Power Networks with Distributed Wind Generation

Wind generation in highly interconnected power networks creates local and centralised stability issues based on their proximity to conventional synchronous generators and load centres. This paper examines the large disturbance stability issues (i.e. rotor angle and voltage stability) in power networks with geographically distributed wind resources in the context of a number of dispatch scenarios based on profiles of historical wind generation for a real power network. Stability issues have been analysed using novel stability indices developed from dynamic characteristics of wind generation. The results of this study show that localised stability issues worsen when significant penetration of both conventional and wind generation is present due to their non-complementary characteristics. In contrast, network stability improves when either high penetration of wind and synchronous generation is present in the network. Therefore, network regions can be clustered into two distinct stability groups (i.e. superior stability and inferior stability regions). Network stability improves when a voltage control strategy is implemented at wind farms, however both stability clusters remain unchanged irrespective of change in the control strategy. Moreover, this study has shown that the enhanced fault ride-through (FRT) strategy for wind farms can improve both voltage and rotor angle stability locally, but only a marginal improvement is evident in neighbouring regions.

Restoring function after neuromuscular trauma: novel paradigms for enhancing volitional control of neural activity in untethered environments and vHAB, a gamified therapy platform

Thesis (Ph.D.)--University of Washington, 2016-08

Hospitality Management Accounting: Current Problems and Future Opportunities

This paper discusses areas for future research opportunities by addressing accounting issues faced by management accountants practicing in hospitality organizations. Specifically, the article focuses on the use of the uniform system of accounts by operating properties, the usefulness of allocating support costs to operated departments, extending our understanding of operating costs and performance measurement systems and the certification of practicing accountants.

Zombie pedagogies: the problems with using the undead in public pedagogies for emergencies

The well-known Hollywood ‘zombie’ genre has recently begun to invade programs and training courses in disaster control and emergency prevention. The author explores the consequences of a transfer of an entertainment metaphor into real US military policies. Is it possible that this implies attuning the populace to catastrophies by means of edutainment? And does this, as Preston argues, in some ways ‘de-humanize’ one’s adversaries? The article points to a fatal dialectics and disturbing elements of a post-ethical disposition. This results not only in some sort of inevitable legitimation of the ‘war on terror’ leaving behind all tenets of civil society. It also permits, subcutaneously, to act without restrictions against certain groups as if they were ‘undeads’.

Preschoolers’ Executive Control and Diurnal Cortisol as Mediators of the Relations of Prenatal Stress to Child Adjustment

Thesis (Ph.D.)--University of Washington, 2016-08

A generic strategy for dynamic load balancing of distributed memory parallel computational mechanics using unstructured meshes

A large class of computational problems are characterised by frequent synchronisation, and computational requirements which change as a function of time. When such a problem is solved on a message passing multiprocessor machine [5], the combination of these characteristics leads to system performance which deteriorate in time. As the communication performance of parallel hardware steadily improves so load balance becomes a dominant factor in obtaining high parallel efficiency. Performance can be improved with periodic redistribution of computational load; however, redistribution can sometimes be very costly. We study the issue of deciding when to invoke a global load re-balancing mechanism. Such a decision policy must actively weigh the costs of remapping against the performance benefits, and should be general enough to apply automatically to a wide range of computations. This paper discusses a generic strategy for Dynamic Load Balancing (DLB) in unstructured mesh computational mechanics applications. The strategy is intended to handle varying levels of load changes throughout the run. The major issues involved in a generic dynamic load balancing scheme will be investigated together with techniques to automate the implementation of a dynamic load balancing mechanism within the Computer Aided Parallelisation Tools (CAPTools) environment, which is a semi-automatic tool for parallelisation of mesh based FORTRAN codes.

Business Signage Control in Seattle's Chinatown International District, Pursuing Healthy Balance of Preservation and Commercial Vitalization in a Historic Commercial Districts

Thesis (Master's)--University of Washington, 2016-06

Synergistic nisin-polymyxin combinations for the control of Pseudomonas biofilm formation

The emergence and dissemination of multi-drug resistant pathogens is a global concern. Moreover, even greater levels of resistance are conferred on bacteria when in the form of biofilms (i.e., complex, sessile communities of bacteria embedded in an organic polymer matrix). For decades, antimicrobial peptides have been hailed as a potential solution to the paucity of novel antibiotics, either as natural inhibitors that can be used alone or in formulations with synergistically acting antibiotics. Here, we evaluate the potential of the antimicrobial peptide nisin to increase the efficacy of the antibiotics polymyxin and colistin, with a particular focus on their application to prevent biofilm formation of Pseudomonas aeruginosa. The results reveal that the concentrations of polymyxins that are required to effectively inhibit biofilm formation can be dramatically reduced when combined with nisin, thereby enhancing efficacy, and ultimately, restoring sensitivity. Such combination therapy may yield added benefits by virtue of reducing polymyxin toxicity through the administration of significantly lower levels of polymyxin antibiotics.

Context-awareness privacy in data communications

Internet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed through data mining techniques and put to use by enabling personalized and tailored services as well as business intelligence practices, fueling the digital economy. However, the ever-expanding information gathering and use undermines the privacy conceptions of the past. Natural social practices of managing privacy in daily relations are overridden by socially-awkward communication tools, service providers struggle with security issues resulting in harmful data leaks, governments use mass surveillance techniques, the incentives of the digital economy threaten consumer privacy, and the advancement of consumergrade data-gathering technology enables new inter-personal abuses. A wide range of fields attempts to address technology-related privacy problems, however they vary immensely in terms of assumptions, scope and approach. Privacy of future use cases is typically handled vertically, instead of building upon previous work that can be re-contextualized, while current privacy problems are typically addressed per type in a more focused way. Because significant effort was required to make sense of the relations and structure of privacy-related work, this thesis attempts to transmit a structured view of it. It is multi-disciplinary - from cryptography to economics, including distributed systems and information theory - and addresses privacy issues of different natures. As existing work is framed and discussed, the contributions to the state-of-theart done in the scope of this thesis are presented. The contributions add to five distinct areas: 1) identity in distributed systems; 2) future context-aware services; 3) event-based context management; 4) low-latency information flow control; 5) high-dimensional dataset anonymity. Finally, having laid out such landscape of the privacy-preserving work, the current and future privacy challenges are discussed, considering not only technical but also socio-economic perspectives.

Dynamic load balancing of distributed memory parallel computational mechanics using unstructured meshes for multi-physical modelling

As the complexity of parallel applications increase, the performance limitations resulting from computational load imbalance become dominant. Mapping the problem space to the processors in a parallel machine in a manner that balances the workload of each processors will typically reduce the run-time. In many cases the computation time required for a given calculation cannot be predetermined even at run-time and so static partition of the problem returns poor performance. For problems in which the computational load across the discretisation is dynamic and inhomogeneous, for example multi-physics problems involving fluid and solid mechanics with phase changes, the workload for a static subdomain will change over the course of a computation and cannot be estimated beforehand. For such applications the mapping of loads to process is required to change dynamically, at run-time in order to maintain reasonable efficiency. The issue of dynamic load balancing are examined in the context of PHYSICA, a three dimensional unstructured mesh multi-physics continuum mechanics computational modelling code.

Security and Trust in Distributed Computation

We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.

Large eddy simulation of shock boundary layer interaction control using micro-vortex generators

The performance of supersonic engine inlets and external aerodynamic surfaces can be critically affected by shock wave / boundary layer interactions (SBLIs), whose severe adverse pressure gradients can cause boundary layer separation. Currently such problems are avoided primarily through the use of boundary layer bleed/suction which can be a source of significant performance degradation. This study investigates a novel type of flow control device called micro-vortex generators (µVGs) which may offer similar control benefits without the bleed penalties. µVGs have the ability to alter the near-wall structure of compressible turbulent boundary layers to provide increased mixing of high speed fluid which improves the boundary layer health when subjected to flow disturbance. Due to their small size,µVGs are embedded in the boundary layer which provide reduced drag compared to the traditional vortex generators while they are cost-effective, physically robust and do not require a power source. To examine the potential of µVGs, a detailed experimental and computational study of micro-ramps in a supersonic boundary layer at Mach 3 subjected to an oblique shock was undertaken. The experiments employed a flat plate boundary layer with an impinging oblique shock with downstream total pressure measurements. The moderate Reynolds number of 3,800 based on displacement thickness allowed the computations to use Large Eddy Simulations without the subgrid stress model (LES-nSGS). The LES predictions indicated that the shock changes the structure of the turbulent eddies and the primary vortices generated from the micro-ramp. Furthermore, they generally reproduced the experimentally obtained mean velocity profiles, unlike similarly-resolved RANS computations. The experiments and the LES results indicate that the micro-ramps, whose height is h≈0.5δ, can significantly reduce boundary layer thickness and improve downstream boundary layer health as measured by the incompressible shape factor, H. Regions directly behind the ramp centerline tended to have increased boundary layer thickness indicating the significant three-dimensionality of the flow field. Compared to baseline sizes, smaller micro-ramps yielded improved total pressure recovery. Moving the smaller ramps closer to the shock interaction also reduced the displacement thickness and the separated area. This effect is attributed to decreased wave drag and the closer proximity of the vortex pairs to the wall. In the second part of the study, various types of µVGs are investigated including micro-ramps and micro-vanes. The results showed that vortices generated from µVGs can partially eliminate shock induced flow separation and can continue to entrain high momentum flux for boundary layer recovery downstream. The micro-ramps resulted in thinner downstream displacement thickness in comparison to the micro-vanes. However, the strength of the streamwise vorticity for the micro-ramps decayed faster due to dissipation especially after the shock interaction. In addition, the close spanwise distance between each vortex for the ramp geometry causes the vortex cores to move upwards from the wall due to induced upwash effects. Micro-vanes, on the other hand, yielded an increased spanwise spacing of the streamwise vortices at the point of formation. This resulted in streamwise vortices staying closer to the wall with less circulation decay, and the reduction in overall flow separation is attributed to these effects. Two hybrid concepts, named “thick-vane” and “split-ramp”, were also studied where the former is a vane with side supports and the latter has a uniform spacing along the centerline of the baseline ramp. These geometries behaved similar to the micro-vanes in terms of the streamwise vorticity and the ability to reduce flow separation, but are more physically robust than the thin vanes. Next, Mach number effect on flow past the micro-ramps (h~0.5δ) are examined in a supersonic boundary layer at M=1.4, 2.2 and 3.0, but with no shock waves present. The LES results indicate that micro-ramps have a greater impact at lower Mach number near the device but its influence decays faster than that for the higher Mach number cases. This may be due to the additional dissipation caused by the primary vortices with smaller effective diameter at the lower Mach number such that their coherency is easily lost causing the streamwise vorticity and the turbulent kinetic energy to decay quickly. The normal distance between the vortex core and the wall had similar growth indicating weak correlation with the Mach number; however, the spanwise distance between the two counter-rotating cores further increases with lower Mach number. Finally, various µVGs which include micro-ramp, split-ramp and a new hybrid concept “ramped-vane” are investigated under normal shock conditions at Mach number of 1.3. In particular, the ramped-vane was studied extensively by varying its size, interior spacing of the device and streamwise position respect to the shock. The ramped-vane provided increased vorticity compared to the micro-ramp and the split-ramp. This significantly reduced the separation length downstream of the device centerline where a larger ramped-vane with increased trailing edge gap yielded a fully attached flow at the centerline of separation region. The results from coarse-resolution LES studies show that the larger ramped-vane provided the most reductions in the turbulent kinetic energy and pressure fluctuation compared to other devices downstream of the shock. Additional benefits include negligible drag while the reductions in displacement thickness and shape factor were seen compared to other devices. Increased wall shear stress and pressure recovery were found with the larger ramped-vane in the baseline resolution LES studies which also gave decreased amplitudes of the pressure fluctuations downstream of the shock.

A Pyramidal Genetic Algorithm for Multiple-Choice Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence, higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.