Non-auditory Influences on the Auditory Periphery

Once thought to be predominantly the domain of cortex, multisensory integration has now been found at numerous sub-cortical locations in the auditory pathway. Prominent ascending and descending connection within the pathway suggest that the system may utilize non-auditory activity to help filter incoming sounds as they first enter the ear. Active mechanisms in the periphery, particularly the outer hair cells (OHCs) of the cochlea and middle ear muscles (MEMs), are capable of modulating the sensitivity of other peripheral mechanisms involved in the transduction of sound into the system. Through indirect mechanical coupling of the OHCs and MEMs to the eardrum, motion of these mechanisms can be recorded as acoustic signals in the ear canal. Here, we utilize this recording technique to describe three different experiments that demonstrate novel multisensory interactions occurring at the level of the eardrum. 1) In the first experiment, measurements in humans and monkeys performing a saccadic eye movement task to visual targets indicate that the eardrum oscillates in conjunction with eye movements. The amplitude and phase of the eardrum movement, which we dub the Oscillatory Saccadic Eardrum Associated Response or OSEAR, depended on the direction and horizontal amplitude of the saccade and occurred in the absence of any externally delivered sounds. 2) For the second experiment, we use an audiovisual cueing task to demonstrate a dynamic change to pressure levels in the ear when a sound is expected versus when one is not. Specifically, we observe a drop in frequency power and variability from 0.1 to 4kHz around the time when the sound is expected to occur in contract to a slight increase in power at both lower and higher frequencies. 3) For the third experiment, we show that seeing a speaker say a syllable that is incongruent with the accompanying audio can alter the response patterns of the auditory periphery, particularly during the most relevant moments in the speech stream. These visually influenced changes may contribute to the altered percept of the speech sound. Collectively, we presume that these findings represent the combined effect of OHCs and MEMs acting in tandem in response to various non-auditory signals in order to manipulate the receptive properties of the auditory system. These influences may have a profound, and previously unrecognized, impact on how the auditory system processes sounds from initial sensory transduction all the way to perception and behavior. Moreover, we demonstrate that the entire auditory system is, fundamentally, a multisensory system.

Experimental detection of sudden stiffness change in a structural system employing Laser Doppler Vibrometry

Sudden changes in the stiffness of a structure are often indicators of structural damage. Detection of such sudden stiffness change from the vibrations of structures is important for Structural Health Monitoring (SHM) and damage detection. Non-contact measurement of these vibrations is a quick and efficient way for successful detection of sudden stiffness change of a structure. In this paper, we demonstrate the capability of Laser Doppler Vibrometry to detect sudden stiffness change in a Single Degree Of Freedom (SDOF) oscillator within a laboratory environment. The dynamic response of the SDOF system was measured using a Polytec RSV-150 Remote Sensing Vibrometer. This instrument employs Laser Doppler Vibrometry for measuring dynamic response. Additionally, the vibration response of the SDOF system was measured through a MicroStrain G-Link Wireless Accelerometer mounted on the SDOF system. The stiffness of the SDOF system was experimentally determined through calibrated linear springs. The sudden change of stiffness was simulated by introducing the failure of a spring at a certain instant in time during a given period of forced vibration. The forced vibration on the SDOF system was in the form of a white noise input. The sudden change in stiffness was successfully detected through the measurements using Laser Doppler Vibrometry. This detection from optically obtained data was compared with a detection using data obtained from the wireless accelerometer. The potential of this technique is deemed important for a wide range of applications. The method is observed to be particularly suitable for rapid damage detection and health monitoring of structures under a model-free condition or where information related to the structure is not sufficient.

Wind Shear, Gust, and Yaw-Induced Dynamic Stall on Wind-Turbine Blades

This study examined the effect of a spanwise angle of attack gradient on the growth and stability of a dynamic stall vortex in a rotating system. It was found that a spanwise angle of attack gradient induces a corresponding spanwise vorticity gradient, which, in combination with spanwise flow, results in a redistribution of circulation along the blade. Specifically, when modelling the angle of attack gradient experienced by a wind turbine at the 30% span position during a gust event, the spanwise vorticity gradient was aligned such that circulation was transported from areas of high circulation to areas of low circulation, increasing the local dynamic stall vortex growth rate, which corresponds to an increase in the lift coefficient, and a decrease in the local vortex stability at this point. Reversing the relative alignment of the spanwise vorticity gradient and spanwise flow results in circulation transport from areas of low circulation generation to areas of high circulation generation, acting to reduce local circulation and stabilise the vortex. This circulation redistribution behaviour describes a mechanism by which the fluctuating loads on a wind turbine are magnified, which is detrimental to turbine lifetime and performance. Therefore, an understanding of this phenomenon has the potential to facilitate optimised wind turbine design.

Essays in dynamic optimal taxation: working experience, unemployment scarring and poverty

This thesis investigates the design of optimal tax systems in dynamic environments. The first essay characterizes the optimal tax system where wages depend on stochastic shocks and work experience. In addition to redistributive and efficiency motives, the taxation of inexperienced workers depends on a second-best requirement that encourages work experience, a social insurance motive and incentive effects. Calibrations using U.S. data yield higher expected optimal marginal income tax rates for experienced workers for most of the inexperienced workers. They confirm that the average marginal income tax rate increases (decreases) with age when shocks and work experience are substitutes (complements). Finally, more variability in experienced workers' earnings prospects leads to increasing tax rates since income taxation acts as a social insurance mechanism. In the second essay, the properties of an optimal tax system are investigated in a dynamic private information economy where labor market frictions create unemployment that destroys workers' human capital. A two-skill type model is considered where wages and employment are endogenous. I find that the optimal tax system distorts the first-period wages of all workers below their efficient levels which leads to more employment. The standard no-distortion-at-the-top result no longer holds due to the combination of private information and the destruction of human capital. I show this result analytically under the Maximin social welfare function and confirm it numerically for a general social welfare function. I also investigate the use of a training program and job creation subsidies. The final essay analyzes the optimal linear tax system when there is a population of individuals whose perceptions of savings are linked to their disposable income and their family background through family cultural transmission. Aside from the standard equity/efficiency trade-off, taxes account for the endogeneity of perceptions through two channels. First, taxing labor decreases income, which decreases the perception of savings through time. Second, taxation on savings corrects for the misperceptions of workers and thus savings and labor decisions. Numerical simulations confirm that behavioral issues push labor income taxes upward to finance saving subsidies. Government transfers to individuals are also decreased to finance those same subsidies.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.

IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Dynamic Workload Parallelization and System Calibration on Single-Chip Cloud Computer

Many-core systems are emerging from the need of more computational power and power efficiency. However there are many issues which still revolve around the many-core systems. These systems need specialized software before they can be fully utilized and the hardware itself may differ from the conventional computational systems. To gain efficiency from many-core system, programs need to be parallelized. In many-core systems the cores are small and less powerful than cores used in traditional computing, so running a conventional program is not an efficient option. Also in Network-on-Chip based processors the network might get congested and the cores might work at different speeds. In this thesis is, a dynamic load balancing method is proposed and tested on Intel 48-core Single-Chip Cloud Computer by parallelizing a fault simulator. The maximum speedup is difficult to obtain due to severe bottlenecks in the system. In order to exploit all the available parallelism of the Single-Chip Cloud Computer, a runtime approach capable of dynamically balancing the load during the fault simulation process is used. The proposed dynamic fault simulation approach on the Single-Chip Cloud Computer shows up to 45X speedup compared to a serial fault simulation approach. Many-core systems can draw enormous amounts of power, and if this power is not controlled properly, the system might get damaged. One way to manage power is to set power budget for the system. But if this power is drawn by just few cores of the many, these few cores get extremely hot and might get damaged. Due to increase in power density multiple thermal sensors are deployed on the chip area to provide realtime temperature feedback for thermal management techniques. Thermal sensor accuracy is extremely prone to intra-die process variation and aging phenomena. These factors lead to a situation where thermal sensor values drift from the nominal values. This necessitates efficient calibration techniques to be applied before the sensor values are used. In addition, in modern many-core systems cores have support for dynamic voltage and frequency scaling. Thermal sensors located on cores are sensitive to the core's current voltage level, meaning that dedicated calibration is needed for each voltage level. In this thesis a general-purpose software-based auto-calibration approach is also proposed for thermal sensors to calibrate thermal sensors on different range of voltages.

Sistemas auxiliares de desinfeção em Endodontia

Introdução: O objetivo da terapia endodôntica é eliminar a infeção presente nos canais radiculares e prevenir a reinfeção dos mesmos, criando assim as condições para a manutenção da peça dentária em função e livre de patologia pulpar ou peri-apical. A complexa anatomia dos canais faz com que seja impossível uma limpeza completa dos mesmos. Para se conseguir um bom resultado clínico é de extrema importância utilizarmos técnicas e procedimentos que visem uma utilização combinada de instrumentação mecânica e desinfeção com soluções de irrigação. Objetivo: Revisão bibliográfica sobre sistemas auxiliares de desinfeção em Endodontia, abordando as suas principais vantagens e limitações e apresentando estudos que provam a sua importância para o sucesso do tratamento endodôntico. Materiais e métodos: Realizou-se uma pesquisa eletrónica nos principais motores de busca online tais como PubMed, B-On, Scielo e Science Direct e em livros científicos sobre a temática, utilizando palavras-chave em inglês tais como “irrigation techniques”, “sonic irrigation”, “EndoVac”, “EDTA”, “hypoclorite sodium”, “passive ultrasonic irrigation”, “apical negative pressure irrigation”, “root canal irrigation”, “EndoAtivator”, e ainda alguns termos em português tais como “insucesso em endodontia”, “hipoclorito de sódio” “ácido cítrico” e “irrigação sónica e ultrasónica”. Da pesquisa efectuada entre Junho e Novembro de 2015 e cujo critério de inclusão foram artigos datados de 2001 a 2015, escolheu-se 65 artigos em inglês, 4 em português e 1 em espanhol, dos quais se utilizaram 44 artigos. Além dos artigos analisou-se 2 livros, dos quais se utilizou 1. Resultados: Os artigos analisados apresentam como principais resultados que a combinação de instrumentação mecânica e a irrigação reduz mas não elimina totalmente as bactérias. Até à data não existem soluções de irrigação ideais. Têm-se desenvolvido técnicas capazes de combater as dificuldades encontradas e aumentar as potencialidades da irrigação, cada uma apresentando suas vantagens e desvantagens. Dos resultados constatados, a literatura científica aparenta reconhecer o Sistema EndoVac como o melhor em termos de biossegurança e o sistema de irrigação ultrasónica passiva como o melhor em termos de desinfecção e limpeza. Conclusão: Uma combinação de soluções com uma sequência específica é aparentemente necessária para atingir o sucesso endodôntico, bem como uma escolha adequada da técnica. As novas técnicas desenvolvidas tais como a ativação dinâmica manual, irrigação ultrasónica passiva, ativação sónica e sistemas de pressão apical negativa apresentam melhores resultados quando associados a irrigantes adequados como o hipoclorito, EDTA, ácido cítrico, clorohexidina e álcool. No entanto, concluiu-se que mais investigação é necessária para melhorar o sucesso do tratamento endodôntico não-cirúrgico.

Non-contact test set-up for aeroelasticity in a rotating turbomachine combining a novel acoustic excitation system with tip-timing

Due to trends in aero-design, aeroelasticity becomes increasingly important in modern turbomachines. Design requirements of turbomachines lead to the development of high aspect ratio blades and blade integral disc designs (blisks), which are especially prone to complex modes of vibration. Therefore, experimental investigations yielding high quality data are required for improving the understanding of aeroelastic effects in turbomachines. One possibility to achieve high quality data is to excite and measure blade vibrations in turbomachines. The major requirement for blade excitation and blade vibration measurements is to minimize interference with the aeroelastic effects to be investigated. Thus in this paper, a non-contact-and thus low interference-experimental set-up for exciting and measuring blade vibrations is proposed and shown to work. A novel acoustic system excites rotor blade vibrations, which are measured with an optical tip-timing system. By performing measurements in an axial compressor, the potential of the acoustic excitation method for investigating aeroelastic effects is explored. The basic principle of this method is described and proven through the analysis of blade responses at different acoustic excitation frequencies and at different rotational speeds. To verify the accuracy of the tip-timing system, amplitudes measured by tip-timing are compared with strain gage measurements. They are found to agree well. Two approaches to vary the nodal diameter (ND) of the excited vibration mode by controlling the acoustic excitation are presented. By combining the different excitable acoustic modes with a phase-lag control, each ND of the investigated 30 blade rotor can be excited individually. This feature of the present acoustic excitation system is of great benefit to aeroelastic investigations and represents one of the main advantages over other excitation methods proposed in the past. In future studies, the acoustic excitation method will be used to investigate aeroelastic effects in high-speed turbomachines in detail. The results of these investigations are to be used to improve the aeroelastic design of modern turbomachines.

Garbage collection optimization for non uniform memory access architectures

Cache-coherent non uniform memory access (ccNUMA) architecture is a standard design pattern for contemporary multicore processors, and future generations of architectures are likely to be NUMA. NUMA architectures create new challenges for managed runtime systems. Memory-intensive applications use the system’s distributed memory banks to allocate data, and the automatic memory manager collects garbage left in these memory banks. The garbage collector may need to access remote memory banks, which entails access latency overhead and potential bandwidth saturation for the interconnection between memory banks. This dissertation makes five significant contributions to garbage collection on NUMA systems, with a case study implementation using the Hotspot Java Virtual Machine. It empirically studies data locality for a Stop-The-World garbage collector when tracing connected objects in NUMA heaps. First, it identifies a locality richness which exists naturally in connected objects that contain a root object and its reachable set— ‘rooted sub-graphs’. Second, this dissertation leverages the locality characteristic of rooted sub-graphs to develop a new NUMA-aware garbage collection mechanism. A garbage collector thread processes a local root and its reachable set, which is likely to have a large number of objects in the same NUMA node. Third, a garbage collector thread steals references from sibling threads that run on the same NUMA node to improve data locality. This research evaluates the new NUMA-aware garbage collector using seven benchmarks of an established real-world DaCapo benchmark suite. In addition, evaluation involves a widely used SPECjbb benchmark and Neo4J graph database Java benchmark, as well as an artificial benchmark. The results of the NUMA-aware garbage collector on a multi-hop NUMA architecture show an average of 15% performance improvement. Furthermore, this performance gain is shown to be as a result of an improved NUMA memory access in a ccNUMA system. Fourth, the existing Hotspot JVM adaptive policy for configuring the number of garbage collection threads is shown to be suboptimal for current NUMA machines. The policy uses outdated assumptions and it generates a constant thread count. In fact, the Hotspot JVM still uses this policy in the production version. This research shows that the optimal number of garbage collection threads is application-specific and configuring the optimal number of garbage collection threads yields better collection throughput than the default policy. Fifth, this dissertation designs and implements a runtime technique, which involves heuristics from dynamic collection behavior to calculate an optimal number of garbage collector threads for each collection cycle. The results show an average of 21% improvements to the garbage collection performance for DaCapo benchmarks.

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

Multiple solutions and numerical analysis to the dynamic and stationary models coupling a delayed energy balance model involving latent heat and discontinuous albedo with a deep ocean

We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration.

Use of BARD scoring system in non-alcoholic fatty liver disease patients and its correlation with ultrasonographic grading in Gizan, Saudi Arabia

Purpose: To assess the efficacy of the BARD scoring system in Saudi non‐alcoholic fatty liver disease (NAFLD) patients attending Gizan General Hospital and to identify the clinical variables associated with advanced fibrosis. . Methods: The cross-sectional study involved 120 patients aged ≥ 18 years who attended the Ultrasound Department of Gizan General Hospital, Gizan, Saudi Arabia, during January – June 2013. BARD scoring system comprised the following variables: body mass index (BMI) ≥ 28 = 1 point, aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio ≥ 0.8 = 2 points, and type 2 diabetes mellitus = 1 point. Results: Patients with advanced fibrosis were older (55.0 years) than patients with no/mild fibrosis (48.6 years), albeit not significantly so. A higher BMI was associated with advanced fibrosis in males, females and all study participants (p = 0.013, 0.016 and 0.001, respectively). Advanced fibrosis was more common in older patients with a higher weight to height ratio. Logistic regression suggested that age ≥ 50 years was associated with a 2.52-fold increase in the risk of advanced fibrosis, but this did not have a significant clinical impact (p = 0.087). BMI > 28 was associated with a 26.73-fold increased risk of advanced fibrosis, while AST/ALT ≥ 0.8 was associated with an 18.46-fold increased risk of advanced liver fibrosis (p = 0.002 and 0.006, respectively). Conclusion: The major risk factors for advanced fibrosis using BARD scoring system in patients with NAFLD were old age, BMI > 28, and AST/ALT ≥ 0.8. In addition, grade 3 ultrasonographic fatty liver significantly correlated with advanced fibrosis.

A non-conventional five piston double.-acting Stirling Engine filling system CFD simulation and experimental validation

Análisis mediante CFD y validación experimental de un sistema de carga para un motor Stirling. Validado y analizado experimentalmente en un motor de 5 pistones de doble acción.

SYSTEM DYNAMICS MODELING AS A QUANTITATIVE-QUALITATIVE FRAMEWORK FOR SUSTAINABLE WATER RESOURCES MANAGEMENT: INSIGHTS FOR WATER QUALITY POLICY IN THE GREAT LAKES REGION

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.