Yes / The coupling of thermal (Multi Stage Flash, MSF) and membrane processes (Reverse Osmosis, RO) in desalination systems has been widely presented in the literature to achieve an improvement of performance compared to an individual process. However, very little study has been made to the combined Multi Effect Distillation (MED) and Reverse Osmosis (RO) processes. Therefore, this research investigates several design options of MED with thermal vapor compression (MED_TVC) coupled with RO system. To achieve this aim, detailed mathematical models for the two processes are developed, which are independently validated against the literature. Then, the integrated model is used to investigate the performance of several configurations of the MED_TVC and RO processes in the hybrid system. The performance indicators include the fresh water productivity, energy consumption, fresh water purity, and recovery ratio. Basically, the sensitivity analysis for each configuration is conducted with respect to seawater conditions and steam supply variation. Most importantly, placing the RO membrane process upstream in the hybrid system generates the overall best configuration in terms of the quantity and quality of fresh water produced. This is attributed to acquiring the best recovery ratio and lower energy consumption over a wide range of seawater salinity.

It is a common practice when designing a system to apply safety factors to the critical failure load or event. These safety factors provide a buffer against failure due to the random or un-modeled behavior, which may lead the system to exceed these limits. However these safety factors are not directly related to the likelihood of a failure event occurring. If the safety factors are poorly chosen, the system may fail unexpectedly or it may have a design which is too conservative. Reliability-Based Design Optimization (RBDO) is an alternative approach which directly considers the likelihood of failure by incorporating a reliability analysis step such as the First-Order Reliability Method (FORM). The FORM analysis requires the solution of an optimization problem however, so implementing this approach into an RBDO routine creates a double-loop optimization structure. For large problems such as Reliability-Based Topology Optimization (RBTO), numeric sensitivity analysis becomes computationally intractable. In this thesis, a general approach to the sensitivity analysis of nested functions is developed from the Lagrange Multiplier Theorem and then applied to several Reliability-Based Design Optimization problems, including topology optimization. The proposed approach is computationally efficient, requiring only a single solution of the FORM problem each iteration. / Master of Science / It is a common practice when designing a system to apply safety factors to the critical failure load or event. These safety factors provide a buffer against failure due to the random or unmodeled behavior, which may lead the system to exceed these limits. However these safety factors are not directly related to the likelihood of a failure event occurring. If the safety factors are poorly chosen, the system may fail unexpectedly or it may have a design which is too conservative. Reliability-Based Design Optimization (RBDO) is an alternative approach which directly considers the likelihood of failure by incorporating a reliability analysis step such as the First-Order Reliability Method (FORM). The FORM analysis requires the solution of an optimization problem however, so implementing this approach into an RBDO routine creates a double-loop optimization structure. For large problems such as Reliability-Based Topology Optimization (RBTO), numeric sensitivity analysis becomes computationally intractable. In this thesis, a general approach to the sensitivity analysis of nested functions is developed from the Lagrange Multiplier Theorem and then applied to several Reliability-Based Design Optimization problems, including topology optimization. The proposed approach is computationally efficient, requiring only a single solution of the FORM problem each iteration.

Yes / Smart city development is gaining considerable recognition in the systematic literature and international policies throughout the world. The study aims to identify the key barriers of smart cities from a review of existing literature and views of experts in this area. This work further makes an attempt on the prioritisation of barriers to recognise the most important barrier category and ranking of specific barriers within the categories to the development of smart cities in India. Through the existing literature, this work explored 31 barriers of smart cities development and divided them into six categories. This research work employed fuzzy Analytic Hierarchy Process (AHP) technique to prioritise the selected barriers. Findings reveal that ‘Governance’ is documented as the most significant category of barriers for smart city development followed by ‘Economic; ‘Technology’; ‘Social’; ‘Environmental’ and ‘Legal and Ethical’. In this work, authors also performed sensitivity analysis to validate the findings of study. This research is useful to the government and policymakers for eradicating the potential interferences in smart city development initiatives in developing countries like India.

Understanding the dynamics of agricultural basins has been difficult for decision-makers when developing cost-effective plans. An uncertainty analysis evaluates the impact of information gaps on hydrologic model’s output and performance. The Agricultural Policy/Environmental Extender (APEX v1501) was used to predict runoff, crop yield, sediment load, total phosphorus, and total nitrogen from agricultural fields in the Mississippi Delta to investigate the impact of using different input variables (climate, soils, and management practices) on mechanistic models. Results indicated that the use of surrogate information such as weather data from close weather stations, a predominant soil series, and simulated irrigation schedules, could be considered when available in situ information is restricted. Overall results provided information on model setup and output interpretation that may be useful to Mississippi Delta decision-makers.

This thesis applies the theory of uncertainty quantification and sensitivity analysis on the SIR-model and SEIR-model for the spread of diseases. We attempt to determine if we can apply this theory to estimate the model parameters to an acceptable degree of accuracy.  Using sensitivity analysis we determine which parameters of the models are the most significant for some quantity of interest. We apply forward uncertainty quantification to determine how the uncertainty of the model parameters propagates to the quantities of interests. And lastly, we apply uncertainty quantification based on the maximum likelihood method to estimate the model parameters. To easily verify the results, we use synthetic data when estimating the parameters. After applying these methods we see that the importance of the model parameters heavily depend on the choice of quantity of interest. We also note that the uncertainty method reduces the uncertainty in the quantities of interests, although there are a lot of sources of errors that still needs to be considered.

Sensitivity analysis quantifies the effect that of perturbations of the model inputs have on the model's outputs. Some of the key insights gained using sensitivity analysis are to understand the robustness of the model with respect to perturbations, and to select the most important parameters for the model. MATLODE is a tool for sensitivity analysis of models described by ordinary differential equations (ODEs). MATLODE implements two distinct approaches for sensitivity analysis: direct (via the tangent linear model) and adjoint. Within each approach, four families of numerical methods are implemented, namely explicit Runge-Kutta, implicit Runge-Kutta, Rosenbrock, and single diagonally implicit Runge-Kutta. Each approach and family has its own strengths and weaknesses when applied to real world problems. MATLODE has a multitude of options that allows users to find the best approach for a wide range of initial value problems. In spite of the great importance of sensitivity analysis for models governed by differential equations, until this work there was no MATLAB ordinary differential equation sensitivity analysis toolbox publicly available. The two most popular sensitivity analysis packages, CVODES [8] and FATODE [10], are geared toward the high performance modeling space; however, no native MATLAB toolbox was available. MATLODE fills this need and offers sensitivity analysis capabilities in MATLAB, one of the most popular programming languages within scientific communities such as chemistry, biology, ecology, and oceanogra- phy. We expect that MATLODE will prove to be a useful tool for these communities to help facilitate their research and fill the gap between theory and practice. / Master of Science / Sensitivity analysis is the study of how small changes in a model?s input effect the model’s output. Sensitivity analysis provides tools to quantify the impact that small, discrete changes in input values have on the output. The objective of this research is to develop a MATLAB sensitivity analysis toolbox called MATLODE. This research is critical to a wide range of communities who need to optimize system behavior or predict outcomes based on a variety of initial conditions. For example, an analyst could build a model that reflects the performance of an automobile engine, where each part in the engine has a set of initial characteristics. The analyst can use sensitivity analysis to determine which part effects the engine’s overall performance the most (or the least), without physically building the engine and running a series of empirical tests. By employing sensitivity analysis, the analyst saves time and money, and since multiple tests can usually be run through the model in the time needed to run just one empirical test, the analyst is likely to gain deeper insight and design a better product. Prior to MATLODE, employing sensitivity analysis without significant knowledge of computational science was too cumbersome and essentially impractical for many of the communities who could benefit from its use. MATLODE bridges the gap between computational science and a variety of communities faced with understanding how small changes in a system’s input values effect the systems output; and by bridging that gap, MATLODE enables more large scale research initiatives than ever before.

Barrier islands serve as valuable resources for coastal communities by reducing backbarrier flooding, providing wildlife habitat, and creating local economic activity through opportunities for recreation and tourism. Because the benefits of these islands are linked to their morphology, coastal resource planners must consider what management alternatives will maximize these benefits, considering both short- and long-term goals. Recent advances in long-term computational modeling of barrier island, marsh, and lagoon systems have created opportunities for gaining additional insights into the morphodynamics of these systems, which may help planners make better-informed coastal management decisions. In this series of studies, a recently developed long-term barrier-marsh-lagoon model is evaluated to better understand system morphodynamics and applied to a real barrier island system in the mid-Atlantic to understand its vulnerabilities and the potential impacts of management alternatives. In the first study, a comprehensive review of advances in barrier island morphodynamic modeling was presented. In the second study, a global sensitivity analysis method, the Sobol method, was used to explore the parameter space of the barrier-marsh-lagoon model. The significant influence of initial barrier geometry, the combination of parameters required for short-term drowning to occur, and the significant role of tidal dispersion on backbarrier sediment dynamics were morphodynamic insights drawn from this study. In the third study, five global sensitivity analysis methods were evaluated based on their ability to rank parameters, converge to stable results, and their reliability. Groups of the most significant parameters were generally identified by all methods; however, the Morris method exceeded all others in terms of performance, especially its ability to converge and its reliability. VARS performed second best, on average, with better convergence and reliability results than the Sobol method, and with lower simulation counts. In the fourth study, the long-term model was applied to a mid-Atlantic barrier island and used to assess the island's vulnerabilities to sea level rise, overwash, and the impact of coastal management alternatives. Thin-layer placement and beach nourishment were found to be effective at sustaining the marsh and minimizing island retreat, respectively. / Doctor of Philosophy / Barrier islands help coastal communities by reducing flooding, providing wildlife habitat, and creating local economic activity through opportunities for recreation and tourism. Because the benefits of these islands are linked to their form, decision-makers must think about how to manage these islands to help the community both now and in the future. Recent advances in computer modeling of barrier islands, and the adjacent marshes and lagoons, over decades to hundreds of years, have created opportunities for us to learn more about how these systems behave over time, which may help planners make better-informed coastal management decisions. In this series of studies, a recently developed computer model of the barrier island, marsh, and lagoon is evaluated to learn how the system changes over time and applied to a real barrier island system in the mid-Atlantic to understand its vulnerabilities and the potential impacts of management alternatives. In the first study, a comprehensive review of advances in computer modeling of barrier island changes over time was presented. In the second study, the impact of the model parameters and their combinations with one another was explored using the Sobol global sensitivity analysis method, which is widely considered to be the standard method in practice. The significant influence of initial barrier geometry, the combination of parameters required for the barrier to be overcome by sea level in the short-term, and the significant role of sediment delivered behind the island through tidal inlets were significant insights into the system behavior that were drawn from this study. In the third study, five global sensitivity analysis methods were evaluated based on their ability to rank parameters, the number of computer simulations that were required, the ability of a method to arrive at a conclusive answer, and the consistency of a method in providing an answer. Groups of the most significant parameters were generally identified by all methods; however, the Morris method exceeded all others in terms of its ability to find conclusive and consistent answers due to its ability to identify unimportant parameters. VARS performed second best, on average, with better ability to find conclusive and consistent answers with fewer computer simulations than Sobol. In the fourth study, the long-term computer model was applied to a mid-Atlantic barrier island and used to assess the island's vulnerabilities to sea level rise, overwash (when water flows over the dunes), and the impact of coastal management alternatives. Placing thin layers of additional sediment on top of the marsh platforms and extending the shoreline toward the ocean by placing additional sediment on the beach were found to be effective at sustaining the marsh and minimizing movement of the barrier island landward, respectively.

Water infrastructures have been implemented to support the vital activities of human society. The infrastructure developments at the same time have interrupted the natural catchment response characteristics, challenging society to implement effective water resources planning and management strategies. The Telemark area in southern Norway has seen a large number of water infrastructure developments, particularly hydropower, over more than a century. Recent developments in decision support tools for flood control and reservoir operation has raised the need to compute inflows from local catchments, most of which are regulated or have no observed data. This has contributed for the motivation of this PhD thesis work, with an aim of improving runoff estimation at ungauged catchments, and the research results are presented in four manuscript scientific papers.  The inverse distance weighting, inverse distance squared weighting, ordinary kriging, universal kriging and kriging with external drift were applied to analyse precipitation variability and estimate daily precipitation in the study area. The geostatistical based univariate and multivariate map-correlation concepts were applied to analyse and physically understand regional hydrological response patterns. The Sobol variance based sensitivity analysis (VBSA) method was used to investigate the HBV hydrological model parameterization significances on the model response variations and evaluate the model’s reliability as a prediction tool. The HBV hydrological model space transferability into ungauged catchments was also studied.  The analyses results showed that the inverse distance weighting variants are the preferred spatial data interpolation methods in areas where relatively dense precipitation station network can be found.  In mountainous areas and in areas where the precipitation station network is relatively sparse, the kriging variants are the preferred methods. The regional hydrological response correlation analyses suggested that geographic proximity alone cannot explain the entire hydrological response correlations in the study area. Besides, when the multivariate map-correlation analysis was applied, two distinct regional hydrological response patterns - the radial and elliptical-types were identified. The presence of these hydrological response patterns influenced the location of the best-correlated reference streamgauges to the ungauged catchments. As a result, the nearest streamgauge was found the best-correlated in areas where the radial-type hydrological response pattern is the dominant. In area where the elliptical-type hydrological response pattern is the dominant, the nearest reference streamgauge was not necessarily the best-correlated. The VBSA verified that varying up to a minimum of four to six influential HBV model parameters can sufficiently simulate the catchments' responses characteristics when emphasis is given to fit the high flows. Varying up to a minimum of six influential model parameters is necessary to sufficiently simulate the catchments’ responses and maintain the model performance when emphasis is given to fit the low flows. However, varying more than nine out of the fifteen HBV model parameters will not make any significant change on the model performance.  The hydrological model space transfer study indicated that estimation of representative runoff at ungauged catchments cannot be guaranteed by transferring model parameter sets from a single donor catchment. On the other hand, applying the ensemble based model space transferring approach and utilizing model parameter sets from multiple donor catchments improved the model performance at the ungauged catchments. The result also suggested that high model performance can be achieved by integrating model parameter sets from two to six donor catchments. Objectively minimizing the HBV model parametric dimensionality and only sampling the sensitive model parameters, maintained the model performance and limited the model prediction uncertainty.

Made available in DSpace on 2015-03-04T18:50:29Z (GMT). No. of bitstreams: 1 Apresentacao.pdf: 103220 bytes, checksum: c76acce6b0debd619e9db9533aa20f11 (MD5) Previous issue date: 2003-02-13 / Conselho Nacional de Desenvolvimento Cientifico e Tecnologico / The Topological Sensitivity Analysis results in a scalar function, denoted as Topological Derivative, that supplies for each point of the domain of definition of the problem the sensitivity of a given cost function when a small hole is created. However, when a hole is introduced, it is no longer possible to stablish a homeomorphism between the domains. Due to this mathematical difficulty the Topological Derivative may become restrictive, nevertheless be extremely general. Thus, in the present work it is proposed a new method to calculte the Topological Derivative via Shape Sensitivity Analysis. This result, formally proved through a theorem, leads to a simpler and more general methodology than the others found in the literature. The Topological Sensitivity Analysis is performed for several Engineering problems, and the obtained results are used to improve the design of mechanical devices by introducing holes. The same theory developed to calculate the Topological Derivative is used to determine the sensitivity of the cost function when a small incrustation is introduced in each position of the domain, resulting in a novel concept denoted as Configurational Sensitivity Analysis, being discussed some possible applications in the context of Inverse Problems and modelling of phenomena that experiment changes in the physical properties of the medium. Thus, the methodology developed in the present work results in a framework with potential applications in Topology Optimization, Inverse Problems and Mechanical Modelling, which may be seen, from now on, not only as a method to calculate the Topological Derivative, but as a promising research area in Computational Modelling. / A análise de Sensibilidade Topológica resulta em uma função escalar, denominada Derivada Topológica, que fornece para cada ponto do domínio de definição do problema a sensibilidade de uma dada função custo quando um pequeno furo é criado. No entanto, ao introduzir um furo, não é mais possível estabelecer um homeomorfismo entre os domínios envolvidos. Devido a essa dificuldade matemática a Derivada Topológica pode se tornar restritiva, não obstante seja extremamente geral. No presente trabalho, portanto, é proposto um novo método de cálculo da Derivada Topológica via Análise de Sensibilidade à Mudança de Forma. Este resultado, formalmente demonstrado através de um teorema, conduz a uma metodologia mais simples e geral do que as demais encontradas na literatura. A Análise de Sensibilidade Topológica é então realizada em diversos problemas da Engenharia e os resultados obtidos são empregados para melhorar o projeto de componentes mecânicos mediante a introdução de furos. A mesma teoria desenvolvida para calcular a Derivada Topológica é utilizada para determinar a sensibilidade da função custo ao introduzir uma pequena incrustação numa dada posição do domínio, resultando em um novo conceito denominado Análise de Sensibilidade Configuracional, sendo discutidas suas possíveis aplicações no contexto de Problemas Inversos e de modelagem de fenômenos que experimentam mudanças nas propriedades físicas do meio. Assim, a metodologia aqui desenvolvida é uma ferramenta em potencial tanto de Otimização Topológica quanto de Problemas Inversos e de Modelagem Mecânica, podendo ser vista, a partir de agora, não somente como um método de cálculo da Derivada Topológica, mas como uma promissora área de pesquisa em Modelagem Computacional.

The Topological Sensitivity Analysis results in a scalar function, denoted as Topological Derivative, that supplies for each point of the domain of definition of the problem the sensitivity of a given cost function when a small hole is created. However, when a hole is introduced, it is no longer possible to stablish a homeomorphism between the domains. Due to this mathematical difficulty the Topological Derivative may become restrictive, nevertheless be extremely general. Thus, in the present work it is proposed a new method to calculte the Topological Derivative via Shape Sensitivity Analysis. This result, formally proved through a theorem, leads to a simpler and more general methodology than the others found in the literature. The Topological Sensitivity Analysis is performed for several Engineering problems, and the obtained results are used to improve the design of mechanical devices by introducing holes. The same theory developed to calculate the Topological Derivative is used to determine the sensitivity of the cost function when a small incrustation is introduced in each position of the domain, resulting in a novel concept denoted as Configurational Sensitivity Analysis, being discussed some possible applications in the context of Inverse Problems and modelling of phenomena that experiment changes in the physical properties of the medium. Thus, the methodology developed in the present work results in a framework with potential applications in Topology Optimization, Inverse Problems and Mechanical Modelling, which may be seen, from now on, not only as a method to calculate the Topological Derivative, but as a promising research area in Computational Modelling. / A análise de Sensibilidade Topológica resulta em uma função escalar, denominada Derivada Topológica, que fornece para cada ponto do domínio de definição do problema a sensibilidade de uma dada função custo quando um pequeno furo é criado. No entanto, ao introduzir um furo, não é mais possível estabelecer um homeomorfismo entre os domínios envolvidos. Devido a essa dificuldade matemática a Derivada Topológica pode se tornar restritiva, não obstante seja extremamente geral. No presente trabalho, portanto, é proposto um novo método de cálculo da Derivada Topológica via Análise de Sensibilidade à Mudança de Forma. Este resultado, formalmente demonstrado através de um teorema, conduz a uma metodologia mais simples e geral do que as demais encontradas na literatura. A Análise de Sensibilidade Topológica é então realizada em diversos problemas da Engenharia e os resultados obtidos são empregados para melhorar o projeto de componentes mecânicos mediante a introdução de furos. A mesma teoria desenvolvida para calcular a Derivada Topológica é utilizada para determinar a sensibilidade da função custo ao introduzir uma pequena incrustação numa dada posição do domínio, resultando em um novo conceito denominado Análise de Sensibilidade Configuracional, sendo discutidas suas possíveis aplicações no contexto de Problemas Inversos e de modelagem de fenômenos que experimentam mudanças nas propriedades físicas do meio. Assim, a metodologia aqui desenvolvida é uma ferramenta em potencial tanto de Otimização Topológica quanto de Problemas Inversos e de Modelagem Mecânica, podendo ser vista, a partir de agora, não somente como um método de cálculo da Derivada Topológica, mas como uma promissora área de pesquisa em Modelagem Computacional.