COMPARATIVE ANALYSIS OF EFFICIENCY AND OPERATING CHARACTERISTICS OF AUTOMOTIVE POWERTRAIN ARCHITECTURES THROUGH CHASSIS DYNAMOMETER TESTING

The thesis "COMPARATIVE ANALYSIS OF EFFICIENCY AND OPERATING CHARACTERISTICS OF AUTOMOTIVE POWERTRAIN ARCHITECTURES THROUGH CHASSIS DYNAMOMETER TESTING" was completed through a collaborative partnership between Michigan Technological University and Argonne National Laboratory under a contractual agreement titled "Advanced Vehicle Characterization at Argonne National Laboratory". The goal of this project was to investigate, understand and document the performance and operational strategy of several modern passenger vehicles of various architectures. The vehicles were chosen to represent several popular engine and transmission architectures and were instrumented to allow for data collection to facilitate comparative analysis. In order to ensure repeatability and reliability during testing, each vehicle was tested over a series of identical drive cycles in a controlled environment utilizing a vehicle chassis dynamometer. Where possible, instrumentation was preserved between vehicles to ensure robust data collection. The efficiency and fuel economy performance of the vehicles was studied. In addition, the powertrain utilization strategies, significant energy loss sources, tailpipe emissions, combustion characteristics, and cold start behavior were also explored in detail. It was concluded that each vehicle realizes different strengths and suffers from different limitations in the course of their attempts to maximize efficiency and fuel economy. In addition, it was observed that each vehicle regardless of architecture exhibits significant energy losses and difficulties in cold start operation that can be further improved with advancing technology. It is clear that advanced engine technologies and driveline technologies are complimentary aspects of vehicle design that must be utilized together for best efficiency improvements. Finally, it was concluded that advanced technology vehicles do not come without associated cost; the complexity of the powertrains and lifecycle costs must be considered to understand the full impact of advanced vehicle technology.

A Multi-Criteria GIS-Based Route Selection Tool for Hazardous Material Transport: Consideration of Environmental Consequence, Traffic Congestions and Costs

Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year. The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with identification of inhalation hazard impact zones and explosion protective areas around the location of hypothetical hazardous material releases, considering different parameters (i.e., chemicals characteristics, release quantities, atmospheric condition, etc.). Results showed that depending on the quantity of release, chemical, and atmospheric stability (a function of wind speed, meteorology, sky cover, time and location of accidents, etc.) the consequence of these incidents can differ. The study was extended by selection of other evaluation criteria for further investigation because health risk as an evaluation criterion would not be the only concern in selection of routes. Transportation difficulties (i.e., road blockage and congestion) were incorporated as important factor due to their indirect impact/cost on the users of transportation networks. Trucking costs were also considered as one of the primary criteria in selection of hazardous material paths; otherwise the suggested routes would have not been convincing for the shipping companies. The last but not least criterion was proximity of public places to the routes. The approach evolved from a simple framework to a complicated and efficient GIS-based tool able to investigate transportation networks of any given study area, and capable of generating best routing options for cargos. The suggested tool uses a multi-criteria-decision-making method, which considers the priorities of the decision makers in choosing the cargo routes. Comparison of the routing options based on each criterion and also the overall suitableness of the path in regards to all the criteria (using a multi-criteria-decision-making method) showed that using similar tools as the one proposed by this study can provide decision makers insights in the area of hazardous material transport. This tool shows the probable consequences of considering each path in a very easily understandable way; in the formats of maps and tables, which makes the tradeoffs of costs and risks considerably simpler, as in some cases slightly compromising on trucking cost may drastically decrease the probable health risk and/or traffic difficulties. This will not only be rewarding to the community by making cities safer places to live, but also can be beneficial to shipping companies by allowing them to advertise as environmental friendly conveyors.

New Rigorous Decomposition Methods for Mixed-integer Linear and Nonlinear Programming

Process systems design, operation and synthesis problems under uncertainty can readily be formulated as two-stage stochastic mixed-integer linear and nonlinear (nonconvex) programming (MILP and MINLP) problems. These problems, with a scenario based formulation, lead to large-scale MILPs/MINLPs that are well structured. The first part of the thesis proposes a new finitely convergent cross decomposition method (CD), where Benders decomposition (BD) and Dantzig-Wolfe decomposition (DWD) are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. A variant of CD, which includes multiple columns per iteration of DW restricted master problem and multiple cuts per iteration of BD relaxed master problem, called multicolumn-multicut CD is then developed to improve solution time. Finally, an extended cross decomposition method (ECD) for solving two-stage stochastic programs with risk constraints is proposed. In this approach, a CD approach at the first level and DWD at a second level is used to solve the original problem to optimality. ECD has a computational advantage over a bilevel decomposition strategy or solving the monolith problem using an MILP solver. The second part of the thesis develops a joint decomposition approach combining Lagrangian decomposition (LD) and generalized Benders decomposition (GBD), to efficiently solve stochastic mixed-integer nonlinear nonconvex programming problems to global optimality, without the need for explicit branch and bound search. In this approach, LD subproblems and GBD subproblems are systematically solved in a single framework. The relaxed master problem obtained from the reformulation of the original problem, is solved only when necessary. A convexification of the relaxed master problem and a domain reduction procedure are integrated into the decomposition framework to improve solution efficiency. Using case studies taken from renewable resource and fossil-fuel based application in process systems engineering, it can be seen that these novel decomposition approaches have significant benefit over classical decomposition methods and state-of-the-art MILP/MINLP global optimization solvers.

Stability and smoothness improvements for an underactuated biped with a tail

In this work we present an important improvement in our model of biped mechanism that allows the elevation in a stable form of the system's feet during the execution of trajectories. This improvement allows for simpler trajectory planning and also facilitates the reduction of losses in the collision between the feet and the ground. On the other hand, we add to the design phase the study of the displacement of the Zero Moment Point, as well as the variation of the normal component of the ground reaction force during the motion of the system. Consideration of the above mentioned magnitudes in the design phase allows us to design the necessary support area of the system. These magnitudes will be used as a smoothness criterion of the ground contact to facilitate the selection of robot parameters and trajectories.

Planning Processes for Transport Solutions An Application To the City of Bologna

Mathematical models and the involved methods applied to real contexts are essential tools for designing and evaluating solutions concerning physical elements and/or organizational components of transportation systems. To deal with this, the systems engineering approach is used, which considers the relationships among the transportation system elements and their performances. This approach allows quantifying the effects of transportation projects by taking into account the intrinsic complexity of the transportation system and then assessing the effects of solutions to solve – or mitigate – transportation problems. This thesis focuses on the application of the transport system engineering approach to a real city – Bologna, in northern Italy – in order to: 1. simulate the current transportation system conditions (status quo); 2. compare and assess the results obtained by two different approaches for simulating the link traffic flows on the road transportation network and their related impacts (externalities) 3. identify potential solutions to solve critical aspects, particularly in terms of traffic flow congestion and related environmental impacts (findings)

Reverse engineering in many-body quantum physics: Correspondence between many-body systems and effective single-particle equations

The mapping, exact or approximate, of a many-body problem onto an effective single-body problem is one of the most widely used conceptual and computational tools of physics. Here, we propose and investigate the inverse map of effective approximate single-particle equations onto the corresponding many-particle system. This approach allows us to understand which interacting system a given single-particle approximation is actually describing, and how far this is from the original physical many-body system. We illustrate the resulting reverse engineering process by means of the Kohn-Sham equations of density-functional theory. In this application, our procedure sheds light on the nonlocality of the density-potential mapping of density-functional theory, and on the self-interaction error inherent in approximate density functionals.

A systems biology framework for pathway level culture media engineering: pplication to Pichia pastoris cultures

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

Functional characterization and directed engineering of redox proteins for a rational improvement of Bioelectrochemical systems

In recent years, new methods of clean and environmentally friendly energy production have been the focus of intense research efforts. Microbial fuel cells (MFCs) are devices that utilize naturally occurring microorganisms that feed on organic matter, like waste water, while producing electrical energy. The natural habitats of bacteria thriving in microbial fuel cells are usually marine and freshwater sediments. These microorganisms are called dissimilatory metal reducing bacteria (DMRB), but in addition to metals like iron and manganese, they can use organic compounds like DMSO or TMAO, radionuclides and electrodes as terminal electron acceptors in their metabolic pathways.(...)

Prognostics health management: perspectives in engineering systems reliability prognostics

The Prognostic Health Management (PHM) has been asserting itself as the most promising methodology to enhance the effective reliability and availability of a product or system during its life-cycle conditions by detecting current and approaching failures, thus, providing mitigation of the system risks with reduced logistics and support costs. However, PHM is at an early stage of development, it also expresses some concerns about possible shortcomings of its methods, tools, metrics and standardization. These factors have been severely restricting the applicability of PHM and its adoption by the industry. This paper presents a comprehensive literature review about the PHM main general weaknesses. Exploring the research opportunities present in some recent publications, are discussed and outlined the general guide-lines for finding the answer to these issues.

Development of advanced cell/tissue culture systems, based on enhanced polymeric scaffolds and sophisticated bioreactors, for tissue engineering applications

Programa Doutoral em Engenharia Biomédica

Human fetal bone cells in delivery systems for bone engineering.

The aim of this study was to culture human fetal bone cells (dedicated cell banks of fetal bone derived from 14 week gestation femurs) within both hyaluronic acid gel and collagen foam, to compare the biocompatibility of both matrices as potential delivery systems for bone engineering and particularly for oral application. Fetal bone cell banks were prepared from one organ donation and cells were cultured for up to 4 weeks within hyaluronic acid (Mesolis(®)) and collagen foams (TissueFleece(®)). Cell survival and differentiation were assessed by cell proliferation assays and histology of frozen sections stained with Giemsa, von Kossa and ALP at 1, 2 and 4 weeks of culture. Within both materials, fetal bone cells could proliferate in three-dimensional structure at ∼70% capacity compared to monolayer culture. In addition, these cells were positive for ALP and von Kossa staining, indicating cellular differentiation and matrix production. Collagen foam provides a better structure for fetal bone cell delivery if cavity filling is necessary and hydrogels would permit an injectable technique for difficult to treat areas. In all, there was high biocompatibility, cellular differentiation and matrix deposition seen in both matrices by fetal bone cells, allowing for easy cell delivery for bone stimulation in vivo. Copyright © 2011 John Wiley & Sons, Ltd.

Competitive flexibility in systems supplier companies in mechanical engineering industry

Systems suppliers are focal actors in mechanical engineering supply chains, in between general contractors and component suppliers. This research concentrates on the systems suppliers’ competitive flexibility, as a competitive advantage that the systems supplier gains from independence from the competitive forces of the market. The aim is to study the roles that power, dependence relations, social capital, and interorganizational learning have on the competitive flexibility. Research on this particular theme is scarce thus far. The research method applied here is the inductive multiple case study. Interviews from four case companies were used as main source of the qualitative data. The literature review presents previous literature on subcontracting, supply chain flexibility, supply chain relationships, social capital and interorganizational learning. The result of this study are seven propositions and consequently a model on the effects that the dominance of sales of few customers, power of competitors, significance of the manufactured system in the end product, professionalism in procurement and the significance of brand products in the business have on the competitive flexibility. These relationships are moderated by either social capital or interorganizational learning. The main results obtained from this study revolve around social capital and interorganizational learning, which have beneficial effects on systems suppliers’ competitive flexibility, by moderating the effects of other constructs of the model. Further research on this topic should include quantitative research to provide the extent to which the results can be reliably generalized. Also each construct of the model gives possible focus for more thorough research.

A software engineering approach to distributed systems for composite modeling

The goal of this thesis is to define and validate a software engineering approach for the development of a distributed system for the modeling of composite materials, based on the analysis of various existing software development methods. We reviewed the main features of: (1) software engineering methodologies; (2) distributed system characteristics and their effect on software development; (3) composite materials modeling activities and the requirements for the software development. Using the design science as a research methodology, the distributed system for creating models of composite materials is created and evaluated. Empirical experiments which we conducted showed good convergence of modeled and real processes. During the study, we paid attention to the matter of complexity and importance of distributed system and a deep understanding of modern software engineering methods and tools.

Applying software performance engineering methods to development of IT device management systems

Ohjelmiston suorituskyky on kokonaisvaltainen asia, johon kaikki ohjelmiston elinkaaren vaiheet vaikuttavat. Suorituskykyongelmat johtavat usein projektien viivästymisiin, kustannusten ylittymisiin sekä joissain tapauksissa projektin täydelliseen epäonnistumiseen. Software performance engineering (SPE) on ohjelmistolähtöinen lähestysmistapa, joka tarjoaa tekniikoita suorituskykyisen ohjelmiston kehittämiseen. Tämä diplomityö tutkii näitä tekniikoita ja valitsee niiden joukosta ne, jotka soveltuvat suorituskykyongelmien ratkaisemiseen kahden IT-laitehallintatuotteen kehityksessä. Työn lopputuloksena on päivitetty versio nykyisestä tuotekehitysprosessista, mikä huomioi sovellusten suorituskykyyn liittyvät haasteet tuotteiden elinkaaren eri vaiheissa.

Applicability of Emergence Engineering to Distributed Systems Scenarios

Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.