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Airports are fast-growing dynamic infrastructure assets. For example, the Canadian airport industry is growing by 5% annually and generates about $8 billion yearly. Since the 9/11 tragedy, airport security has been of paramount importance both in Canada and worldwide. Consequently, in 2002, in the wake of the attacks, the International Civil Aviation Organization (ICAO) put into force revised aviation security standards and recommended practices, and began a Universal Security Audit Program (USAP), in order to insure the worldwide safeguarding of civil aviation in general, and of airports in particular, against unlawful interference. To improve aviation security at both the national level and for individual airport, airport authorities in North America have initiated extensive programs to help quantify, detect, deter, and mitigate security risk. At the research level, a number of studies have examined scenarios involving threats to airports, the factors that contribute to airport vulnerability, and decision support systems for security management. However, more work is still required in the area of developing decision support tools that can assist airport officials in meeting the challenges associated with decision about upgrades; determining the status of their security systems and efficiently allocating financial resources to improve them to the level required. To help airport authorities make cost-effective decisions about airport security upgrades, this research has developed a risk-based optimization framework. The framework assists airport officials in quantitatively assessing the status of threats to their airports, the vulnerability to their security systems, and the consequences of security breaches. A key element of this framework is a new quantitative security metric ; the aim of which is to assist airport authorities self-assess the condition of their security systems, and to produce security risk indices that decision makers can use as prioritizing criteria and constraints when meeting decisions about security upgrades. These indices have been utilized to formulate an automated decision support system for upgrading security systems in airports. Because they represent one of the most important security systems in an airport, the research focuses on passenger and cabin baggage screening systems. Based on an analysis of the related threats, vulnerabilities and consequences throughout the flow of passengers, cabin baggage, and checked-in luggage, the proposed framework incorporates an optimization model for determining the most cost-effective countermeasures that can minimize security risks. For this purpose, the framework first calculates the level of possible improvement in security using a new risk metric. Among the important features of the framework is the fact that it allows airport officials to perform multiple “what-if” scenarios, to consider the limitations of security upgrade budgets, and to incorporate airport-specific requirements. Based on the received positive feedback from two actual airports, the framework can be extended to include other facets of security in airports, and to form a comprehensive asset management system for upgrading security at both single and multiple airports. From a broader perspective, this research contributes to the improvement of security in a major transportation sector that has an enormous impact on economic growth and on the welfare of regional, national and international societies.

Airports are fast-growing dynamic infrastructure assets. For example, the Canadian airport industry is growing by 5% annually and generates about $8 billion yearly. Since the 9/11 tragedy, airport security has been of paramount importance both in Canada and worldwide. Consequently, in 2002, in the wake of the attacks, the International Civil Aviation Organization (ICAO) put into force revised aviation security standards and recommended practices, and began a Universal Security Audit Program (USAP), in order to insure the worldwide safeguarding of civil aviation in general, and of airports in particular, against unlawful interference. To improve aviation security at both the national level and for individual airport, airport authorities in North America have initiated extensive programs to help quantify, detect, deter, and mitigate security risk. At the research level, a number of studies have examined scenarios involving threats to airports, the factors that contribute to airport vulnerability, and decision support systems for security management. However, more work is still required in the area of developing decision support tools that can assist airport officials in meeting the challenges associated with decision about upgrades; determining the status of their security systems and efficiently allocating financial resources to improve them to the level required. To help airport authorities make cost-effective decisions about airport security upgrades, this research has developed a risk-based optimization framework. The framework assists airport officials in quantitatively assessing the status of threats to their airports, the vulnerability to their security systems, and the consequences of security breaches. A key element of this framework is a new quantitative security metric ; the aim of which is to assist airport authorities self-assess the condition of their security systems, and to produce security risk indices that decision makers can use as prioritizing criteria and constraints when meeting decisions about security upgrades. These indices have been utilized to formulate an automated decision support system for upgrading security systems in airports. Because they represent one of the most important security systems in an airport, the research focuses on passenger and cabin baggage screening systems. Based on an analysis of the related threats, vulnerabilities and consequences throughout the flow of passengers, cabin baggage, and checked-in luggage, the proposed framework incorporates an optimization model for determining the most cost-effective countermeasures that can minimize security risks. For this purpose, the framework first calculates the level of possible improvement in security using a new risk metric. Among the important features of the framework is the fact that it allows airport officials to perform multiple “what-if” scenarios, to consider the limitations of security upgrade budgets, and to incorporate airport-specific requirements. Based on the received positive feedback from two actual airports, the framework can be extended to include other facets of security in airports, and to form a comprehensive asset management system for upgrading security at both single and multiple airports. From a broader perspective, this research contributes to the improvement of security in a major transportation sector that has an enormous impact on economic growth and on the welfare of regional, national and international societies.

This work describes the design and implementation of the Disease Control System DiCon (pronounced [ˈdaɪkɒn]), providing a general framework for solving optimization problems on distributed computer systems. The central aspects of DiCon are discussed, as are decisions made while realizing the system. Several implementation-specific details are highlighted. Real-world applications show the system's flexibility and demonstrate the potential impact DiCon has on public-health decision making. / text

Truely optimal solutions to system design can only be obtained if the entire system is considered. In this research we consider design of commercial aircraft, but we expand the system to include a family of planes. A multidisciplinary design optimization framework is developed in which multiple aircraft, each with different missions, can be optimized simultaneously. Results are presented for a two-member family whose individual missions differ significantly. We show that both missions can be satisfied with common designs, and that by optimizing both planes simultaneously rather than following the traditional baseline plus derivative approach, the common solution is vastly improved. The new framework is also used to gain insight to the effect of design variable scaling on the optimization algorithm. / Singapore-MIT Alliance (SMA)

Wireless Mesh Networks are increasingly becoming popular as low cost alternatives to wired networks for providing broadband access to users (the last mile connectivity). A key challenge in deploying wireless mesh networks is designing networks with sufficient capacity to meet user demands. Accordingly, researchers have explored various schemes in an effort to build high throughput mesh networks. One of the key technologies that is often employed by researchers to build high throughput wireless mesh networks (WMN) is equipping nodes with smart antennas. By exploiting the advantages of reduced interference and longer transmission paths, smart antennas have been shown to significantly increase network throughput in WMN. However, there is a need to identify and establish an upper-bound on the maximum throughput that is achievable by using smart antennas equipped WMN. Such a bound on throughput is important for several reasons, the most important of which is identifying the services that can be supported by these technologies. This thesis begins with a focus on establishing this bound. Clearly, it is evident that smart-antennas cannot increase network throughput beyond a certain limit for various reasons including the limitations imposed by existing smart an- tenna technology itself. However with the spiralling demand for broadband access, schemes must be explored that can increase network throughput beyond the limit imposed by smart antennas. An interesting and robust method to achieve this increased throughput is by en- abling multiple gateways within the network. Since, the position of these gateways within the network bears a significant influence on network performance, techniques to “opti- mally” place these gateways within the network must be evolved. The study of multiple gateway placement in multi-hop mesh networks forms the next focus of this study. This thesis ends with a discussion on further work that is necessary in this domain.

Wireless Mesh Networks are increasingly becoming popular as low cost alternatives to wired networks for providing broadband access to users (the last mile connectivity). A key challenge in deploying wireless mesh networks is designing networks with sufficient capacity to meet user demands. Accordingly, researchers have explored various schemes in an effort to build high throughput mesh networks. One of the key technologies that is often employed by researchers to build high throughput wireless mesh networks (WMN) is equipping nodes with smart antennas. By exploiting the advantages of reduced interference and longer transmission paths, smart antennas have been shown to significantly increase network throughput in WMN. However, there is a need to identify and establish an upper-bound on the maximum throughput that is achievable by using smart antennas equipped WMN. Such a bound on throughput is important for several reasons, the most important of which is identifying the services that can be supported by these technologies. This thesis begins with a focus on establishing this bound. Clearly, it is evident that smart-antennas cannot increase network throughput beyond a certain limit for various reasons including the limitations imposed by existing smart an- tenna technology itself. However with the spiralling demand for broadband access, schemes must be explored that can increase network throughput beyond the limit imposed by smart antennas. An interesting and robust method to achieve this increased throughput is by en- abling multiple gateways within the network. Since, the position of these gateways within the network bears a significant influence on network performance, techniques to “opti- mally” place these gateways within the network must be evolved. The study of multiple gateway placement in multi-hop mesh networks forms the next focus of this study. This thesis ends with a discussion on further work that is necessary in this domain.

Indiana University-Purdue University Indianapolis (IUPUI) / Powder bed fusion (PBF) process is a metal additive manufacturing process, which can build parts with any complexity from a wide range of metallic materials. Research in the PBF process predominantly focuses on the impact of a few parameters on the ultimate properties of the printed part. The lack of a systematic approach to optimizing the process parameters for a better performance of given material results in a sub-optimal process limiting the potential of the application. This process needs a comprehensive study of all the influential parameters and their impact on the mechanical and microstructural properties of a fabricated part. Furthermore, there is a need to develop a quantitative system for mapping the material properties and process parameters with the ultimate quality of the fabricated part to achieve improvement in the manufacturing cycle as well as the quality of the final part produced by the PBF process. To address the aforementioned challenges, this research proposes a framework to optimize the process for 316L stainless steel material. This framework characterizes the influence of process parameters on the microstructure and mechanical properties of the fabricated part using a series of experiments. These experiments study the significance of process parameters and their variance as well as study the microstructure and mechanical properties of fabricated parts by conducting tensile, impact, hardness, surface roughness, and densification tests, and ultimately obtain the optimum range of parameters. This would result in a more complete understanding of the correlation between process parameters and part quality. Furthermore, the data acquired from the experiments are employed to develop an intelligent parameter suggestion multi-layer feedforward (FF) backpropagation (BP) artificial neural network (ANN). This network estimates the fabrication time and suggests the parameter setting accordingly to the user/manufacturers desired characteristics of the end-product. Further, research is in progress to evaluate the framework for assemblies and complex part designs and incorporate the results in the network for achieving process repeatability and consistency.

<p>  </p> <p>In the last years, lithium-ion batteries (LIBs) have become the most important energy storage system for consumer electronics, electric vehicles, and smart grids. The development of lithium-ion batteries (LIBs) based on current practice allows an energy density increase estimated at 10% per year. However, the required power for portable electronic devices is predicted to increase at a much faster rate, namely 20% per year. Similarly, the global electric vehicle battery capacity is expected to increase from around 170 GWh per year today to 1.5 TWh per year in 2030--this is an increase of 125% per year. Without a breakthrough in battery design technology, it will be difficult to keep up with the increasing energy demand. To that end, a design methodology to accelerate the LIB development is needed. This can be achieved through the integration of electro-chemical numerical simulations and machine learning algorithms.</p> <p><br></p> <p>To help this cause, this study develops a design methodology and framework using Simcenter Battery Design Studio® (BDS) and Bayesian optimization for design and optimization of cylindrical cell type 18650. The materials of the cathode are Nickel-Cobalt-Aluminum (NCA)/Nickel-Manganese-Cobalt-Aluminum (NMCA), anode is graphite, and electrolyte is Lithium hexafluorophosphate (LiPF6). Bayesian optimization has emerged as a powerful gradient-free optimization methodology to solve optimization problems that involve the evaluation of expensive black-box functions. The black-box functions are simulations of the cyclic performance test in Simcenter Battery Design Studio. </p> <p>The physics model used for this study is based on full system model described by Fuller and Newman. It uses Butler-Volmer Equation for ion-transportation across an interface and solvent diffusion model (Ploehn Model) for Aging of Lithium-Ion Battery Cells. The BDS model considers effects of SEI, cell electrode and microstructure dimensions, and charge-discharge rates to simulate battery degradation. Two objectives are optimized: maximization of the specific energy and minimization of the capacity fade. We perform global sensitivity analysis and see that thickness and porosity of the coating of the LIB electrodes that affect the objective functions the most. As such the design variables selected for this study are thickness and porosity of the electrodes. The thickness is restricted to vary from 22 micron to 240 microns and the porosity varies from 0.22 to 0.54. </p> <p>Two case studies are carried out using the above-mentioned objective functions and parameters. In the first study, cycling tests of 18650 NCA cathode Li-ion cells are simulated. The cells are charged and discharged using a constant 0.2C rate for 500 cycles. In the second case study a cathode active material more relevant to the electric vehicle industry, Nickel-Manganese-Cobalt-Aluminum (NMCA), is used. Here, the cells are cycled for 5 different charge-discharge scenarios to replicate charge-discharge scenario that an EVs battery module experiences. The results show that the design and optimization methodology can identify cells to satisfy the design objective that extend and improve the pareto front outside the original sampling plan for several practical charge-discharge scenarios which maximize energy density and minimize capacity fade. </p>

Les activités de transport jouent un rôle crucial autant dans le domaine de la production que dans celui des services. En particulier, elles permettent d’assurer la distribution de biens et de services entre fournisseurs, unités de production, entrepôts, distributeurs, et clients finaux. Plus spécifiquement, les problèmes de tournées de véhicules (VRP) considèrent la mise au point d’un ensemble de tournées de coût minimal servant la demande en biens ou en services d’un ensemble de clients distribués géographiquement, tout en vérifiant un ensemble de contraintes opérationnelles. Alors qu’il s’agissait d’un problème statique, des avancées technologiques récentes permettent aux organisations de gérer leur flotte de véhicules en temps réel. Cependant, ces nouvelles technologies introduisent également une plus grande complexité dans les tâches de gestion de flotte, révélant une demande pour des outils d’aide à la décision dédiés aux problèmes de tournées de véhicules dynamiques. Dans ce contexte, les contributions de la présente thèse de doctorat s’organisent autour de trois axes : (i) elle présente un état de l’art détaillé des problèmes de tournées dynamiques; (ii) elle introduit des frameworks d’optimisation génériques adaptés à une grande variété de problèmes ; (iii) elle définit un problème de tournées novateur et aux nombreuses applications. / Within the wide scope of logistics management,transportation plays a central role and is a crucialactivity in both production and service industry.Among others, it allows for the timely distributionof goods and services between suppliers, productionunits, warehouses, retailers, and final customers.More specifically, Vehicle Routing Problems(VRPs) deal with the design of a set of minimal costroutes that serve the demand for goods orservices of a set of geographically spread customers,satisfying a group of operational constraints.While it was traditionally a static problem, recenttechnological advances provide organizations withthe right tools to manage their vehicle fleet in realtime. Nonetheless, these new technologies alsointroduce more complexity in fleet managementtasks, unveiling the need for decision support systemsdedicated to dynamic vehicle routing. In thiscontext, the contributions of this Ph.D. thesis arethreefold : (i) it presents a comprehensive reviewof the literature on dynamic vehicle routing ; (ii)it introduces flexible optimization frameworks thatcan cope with a wide variety of dynamic vehiclerouting problems ; (iii) it defines a new vehicle routingproblem with numerous applications.