A decision support methodology for rehabilitation management of concrete bridges

Managing the existing bridge infrastructure has become a major social and economic concern in North America. This is due to the critical conditions of the deteriorated bridges and the limited funds available to repair their deficiencies. Most transportation agencies make bridge investment decisions based on a combination of some form of quantitative data analysis and the subjective judgments of decision and policy makers. The subjective nature of the decision making process easily raises questions about whether the investment decisions are being developed in a fair, equitable and systematic manner. This dissertation presents a decision support methodology developed for the rehabilitation management of concrete bridges in general, and for bridge decks in particular. A probabilistic bridge condition assessment method is developed. This method is consistent with the current practice in bridge inspection and the Markovian approach to model deterioration. A means to rank bridge projects is presented, which makes use of a hierarchy structure to represent the problem and rank the different bridge projects using the Multi Attribute Utility Theory (MAUT). A method to evaluate the available rehabilitation strategies is discussed. This method uses a modified Analytic Hierarchy Process (AHP) and the Monte Carlo simulation technique to evaluate the weights for the different rehabilitation strategies available for each project. A decision making technique to select a recommended work program that maximizes benefits to the network and to the users is developed. The developed methodology has the potential to be extended to other bridge components and to be the foundation for a comprehensive bridge management system. The significant features of this methodology can be summarized as follows: (1) It is consistent with the current practice in bridge management condition assessment and deterioration modeling. (2) It employs a multiple-criteria decision making process; (3) it has the flexibility to allow engineers to utilize their experience and judgment in the decision making process; and (4) It combines the network and the project levels of the bridge management process and performs effectively within a limited budget

GREEDY SINGLE USER AND FAIR MULTIPLE USERS REPLICA SELECTION DECISION IN DATA GRID

Replication in data grids increases data availability, accessibility and reliability. Replicas of datasets are usually distributed to different sites, and the choice of any replica locations has a significant impact. Replica selection algorithms decide the best replica places based on some criteria. To this end, a family of efficient replica selection systems has been proposed (RsDGrid). The problem presented in this thesis is how to select the best replica location that achieve less time, higher QoS, consistency with users' preferences and almost equal users' satisfactions. RsDGrid consists of three systems: A-system, D-system, and M-system. Each of them has its own scope and specifications. RsDGrid switches among these systems according to the decision maker

Urban Coastal Systems and Coastal Flooding. A GIS-based tool for planning climate-sensitive cities

In 2013, the "EU Strategy in adaptation to climate change" adopted by the European Commission stated the need of adaptation to climate impacts of European territories, including coastal areas. In fact, these areas are characterized by a higher concentration of buildings and people in comparison to inland areas. Furthermore, economic assets within 500 meters from the coastline have a value between €500 and €1,000 billion (EEA, 2016). Due to their several resources and the high degree of accessibility, these areas are very attractive for people and, hence, their population growth is expected to increase in the future (Neumann et al., 2015). Therefore, these characteristics make coastal cities particularly vulnerable to the impacts of climate change. One of the forecasted impacts of climate change in these areas is the increase of coastal floods due to rising sea level and storm surges. In this context, urban planning plays a key role in urban adaptation. However, even though the interest in this topic is increasing, operative support and tools for planning urban adaptation for cities are in short supply, especially for coastal cities. To date, urban adaptation has been mainly based on the concept of vulnerability and several vulnerability indices have been developed for supporting decision makers in the adaptation process of coastal areas, especially on the territorial level, grounding on a sectoral perspective. As a consequence, the adoption of this approach does not allow to take into account the complexity of the coastal urban system and, thus, all the features and their relationships that can affect the effectiveness of the urban measures to implement in the process of urban adaptation. Based on these observations, the purpose of this research was the development of a new decision support tool that allows the most suitable urban actions to be identified for increasing the capacity of cities to deal with coastal flooding events due to future rising sea level and storm surges. Besides the use of the most innovative GIS-based technologies, one of the novelties introduced with this work was the adoption of the holistic-system approach for the tool development, such as in the case of the definition of the new composite index based on the more holistic concept of urban resilience. For what concerns the development of the GIS-based tool, a four-phase methodology was defined. The first step was the definition and development of a novel composite index for a quantitative evaluation of the “urban coastal resilience” on the local level, named Coastal Resilience Index (or CoRI), by the Analytic Hierarchy Process (AHP) (Saaty, 1980), supported by the Delphi Method. In particular, the CoRI index allows the identification of four resilience levels (high, medium-high, medium-low and low). In the second step, since the urban adaptation measures should be defined in relation to physical and functional characteristics of the urban context, a classification of urban coastal areas was introduced, by specifying Urban Coastal Units (UCUs) depending on their urban density and land use. Considering the CoRI levels and the UCU classification and according to the coastal adaptation approaches defined by the IPCC (Nicholls et al., 2007), in the third phase, four classes of Urban Adaptation Actions were defined. In detail, a matrix that puts in relation the Urban Adaptation Actions classes with UCUs and CoRI levels has been developed. In relation to these three main phases and considering the potentialities of GIS applications in urban planning, in the last phase, a design workflow for developing the GIS-based tool was defined. Thanks to this workflow, the GIS-based tool was implemented and applied to a study area in the city of Naples. In particular, the identification of the potential coastal floodplains of Naples was useful for selecting the study area that includes five neighbourhoods - Barra, Mercato, Industrial Zone, Pendino and San Giovanni a Teduccio - localized in the eastern part of the city. Hence, the input data of the area chosen for the tool's implementation were collected. According to the methodology aforementioned, the GIS-based tool was realized considering three toolboxes: the “Coastal Resilience Index Tools” toolbox, the “Urban Coastal Units Tools” toolbox and, finally, the “Urban Adaptation Actions Tools” toolbox. From the application of the GIS-based tool to the study area, the main findings were the following ones. About the CoRI, the study area is characterized by a high presence of urban areas with medium-low resilience levels (61% of the study area) and by the absence of urban areas with high resilience levels. Concerning the UCU, the urban area is characterized by a high physical and functional complexity of the urban area. Therefore, the majority of the study area is classified as UCU 1 (i.e. high-density and mix-used developments) and UCU 2 (i.e. mono-functional zones, transport infrastructure, public facilities), while the absence of natural areas is noted. Regarding the identification of the Urban Adaptation Actions, all the UCUs need to enhance their resilience level through the implementation of fitting urban measures due to the absence of urban areas characterized by high resilience levels and the high urbanization degree of the study area. In particular, in the majority of the area (about 61%), it is necessary to implement a mix of “hardware” and “software” measures. Therefore, urban transformations should be addressed towards the realization or improvement of protection infrastructure systems, the use of resilient design standards at building scale and the reduction of land-use intensity through the delocalization of critical facilities from the coastline. From an urban planning perspective, the application of the GIS-based tool to the study area in Naples highlights how the urban layout and spatial organization can affect the urban capacity to deal with coastal flooding. Indicators that compose the CoRI enable the in-depth study of urban contexts, and identify areas where there are major shortcomings in terms of urban resilience. Whereas the Urban Coastal Units classification enables the categorization of coastal areas in relation to their land use and land-use intensity in order to better identify the most appropriate “palette” of urban adaptation actions to implement. The identification of a set of urban actions for different urban typologies can be useful for not only defining and programming new urban transformations but also for allowing decision-makers to monetize possible interventions to carry out. In conclusion, urban transformations will be more and more necessary in order to adapt urban areas to future impacts due to climate change. Therefore, in order to better deal with the forthcoming climate change impacts on cities, the novel methodology provided in this study sets the framework for the development of new urban planning tools capable to cope with other climate impacts and, eventually, for their integration in order to develop a comprehensive tool for urban adaptation to different possible impacts of climate change (Wardekker et al., 2010)

Multi-criteria suitability analysis and spatial interaction modeling of retail store locations in Ontario, Canada

GIS-based decision analysis is increasingly used by retailers to address the complexity and cost of investment in retail store location decisions. This study conceptualizes and represents nine criteria in a GIS-based multi-criteria decision analysis of 4.7 million potential retail store locations. From topographic statistics to spatial interaction modelling, the study utilizes criteria of varied complexity to analyze the statistical and spatial distribution of highly suitable locations for a retail store. The study further examines how the spatial representations of criteria based on the Huff model affects the distribution of suitable locations. The results show that although Toronto dominates the retail landscape in Ontario, key regions are found in Guelph, Kitchener-Waterloo and Cambridge. Results show that the incorporation of network-based spatial interaction costs in Huff’s model produces more spatially heterogeneous sales estimates than Euclidean-based spatial interactions. Future research efforts in improving various components of the suitability analysis, as well as the scaling and regional parameterization of spatial interaction models are also discussed

An Integrated Condition Assessment Model for Educational Buildings Using BIM

Building facilities compose a major part of any urban infrastructure. Despite their considerable economic, cultural and/or historic importance, several studies have shown that many buildings are sick, deteriorating and a major source of pollution. Maintaining a building is essential to keep it performing and functioning for a longer period of time as well as providing better quality of life for building occupants. Despite the importance of the condition assessment (CA) stage in the asset management process, literature review reveals that there is no building condition assessment framework that considers both physical and environmental conditions. Schools and educational facilities in Canada, which comprise a major component of the non-residential buildings sector, has passed 51% of their useful service life The primary objective of this research is to develop an Integrated Condition Assessment Model for Educational Buildings that considers both building physical and environmental conditions. This model will assist owners and facility managers in the condition assessment phase during the asset management process. As buildings are composed of spaces; this proposed model uses “space” as the principal element of evaluation. The Multi Attribute Utility Theory (MAUT) is used to calculate the physical and environmental conditions of each space, and the K-mean clustering is conducted to calculate the integrated condition of each one. Data are collected from experts via questionnaires to assign relative weights to models’ attributes using both the Analytical Network Process (ANP) and the Analytical Hierarchy Process (AHP) techniques. The proposed methodology upgrades the use of an object-oriented Building Information Model (BIM) so that it can be used as a platform and an advanced tool for storing, exchanging, and transferring assessment data inputs as well as serving in the assessment process. Integrated Condition Assessment model for Buildings (ICAB) is the developed automated tool that integrates with Revit© 2011. This integration allows the BIM model to be used as the data source and to provide any required graphical representation. The model is implemented and tested using data collected from experts and from field measurements taken from an educational building in Montreal. Finally, the model was validated by experts working in the facilities management field and they acknowledged having good potentials