DEVELOPMENT OF ION EXCHANGE MODELS FOR WATER TREATMENT AND APPLICATION TO THE INTERNATIONAL SPACE STATION WATER PROCESSOR

The International Space Station (ISS) requires a substantial amount of potable water for use by the crew. The economic and logistic limitations of transporting the vast amount of water required onboard the ISS necessitate onboard recovery and reuse of the aqueous waste streams. Various treatment technologies are employed within the ISS water processor to render the waste water potable, including filtration, ion exchange, adsorption, and catalytic wet oxidation. The ion exchange resins and adsorption media are combined in multifiltration beds for removal of ionic and organic compounds. A mathematical model (MFBMODEL™) designed to predict the performance of a multifiltration (MF) bed was developed. MFBMODEL consists of ion exchange models for describing the behavior of the different resin types in a MF bed (e.g., mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins) and an adsorption model capable of predicting the performance of the adsorbents in a MF bed. Multicomponent ion exchange ii equilibrium models that incorporate the water formation reaction, electroneutrality condition, and degree of ionization of weak acids and bases for mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins were developed and verified. The equilibrium models developed use a tanks-inseries approach that allows for consideration of variable influent concentrations. The adsorption modeling approach was developed in related studies and application within the MFBMODEL framework was demonstrated in the Appendix to this study. MFBMODEL consists of a graphical user interface programmed in Visual Basic and Fortran computational routines. This dissertation shows MF bed modeling results in which the model is verified for a surrogate of the ISS waste shower and handwash stream. In addition, a multicomponent ion exchange model that incorporates mass transfer effects was developed, which is capable of describing the performance of strong acid cation (SAC) and strong base anion (SBA) exchange resins, but not including reaction effects. This dissertation presents results showing the mass transfer model's capability to predict the performance of binary and multicomponent column data for SAC and SBA exchange resins. The ion exchange equilibrium and mass transfer models developed in this study are also applicable to terrestrial water treatment systems. They could be applied for removal of cations and anions from groundwater (e.g., hardness, nitrate, perchlorate) and from industrial process waters (e.g. boiler water, ultrapure water in the semiconductor industry).

A cautionary tale of two ‘tigers’: Industrial policy ‘lessons’ from Ireland and Hungary?

This paper draws industrial policy lessons for small Central and Eastern European states through a critical evaluation of recent Irish and Hungarian experiences. The paper outlines a ‘holistic view’ of industrial policy before exploring the experiences of the two economies. Whilst both have managed to ‘do’ policy well in some regards, substantial challenges remain in making FDI attraction the centrepiece of industrial policy, as has been highlighted recently. Overall, the paper suggests that wholesale emulation of the Irish and Hungarian approach is problematic for small open CEE states, and that more balanced approaches to development - and hence industrial policy – are warranted.

Deindustrialisation and industrial communities: the Lanarkshire coalfields c.1947-1983

This thesis examines deindustrialisation, the declining contribution of industrial activities to economic output and employment, in Lanarkshire, Scotland’s largest coalfield between the early nineteenth and mid-twentieth century. It focuses on contraction between the National Coal Board’s (NCB) vesting in 1947 and the closure of Lanarkshire’s last colliery, Cardowan, in 1983. Deindustrialisation was not the natural outcome of either market forces or geological exhaustion. Colliery closures and falling coal employment were the result of policy-makers’ decisions. The thesis consists of four thematic chapters: political economy, moral economy, class and community, and generation and gender. The analysis is based on archival sources including Scottish Office reports and correspondence relating to regional policy, and NCB records. These are supported by National Union of Mineworkers Scottish Area and STUC meeting minutes, and oral history testimonies from over 30 men and women with Lanarkshire coalfield backgrounds, as well as two focus groups. The first two chapters analyse the process of deindustrialisation, with the first offering a top-down perspective and the second a bottom-up viewpoint. In chapter one deindustrialisation is analysed through changes in political economy. Shifts in labour market structure are examined through the development of regional policy and its administration by the Scottish Office. The analysis centres upon a policy network of Scottish business elites and civil servants who shaped a vision of modernisation via industrial diversification through attracting inward investment. In chapter two the perspective shifts to community and workforce. It analyses responses to coalfield contraction through a moral economy of customary rights to colliery employment. A detailed investigation of Lanarkshire colliery closures between the 1940s and 1980s emphasises the protracted nature of deindustrialisation. Chapters three and four consider the social and cultural structures which shaped the moral economy but were heavily altered by deindustrialisation. Chapter three focuses on the dense networks that linked occupation, community, and class consciousness. Increasing coalfield centralisation and remote control of pits from NCB headquarters in London, and mounting hostility to coal closures, contributed to an accentuated sense of Scottish-ness. Chapter four illuminates gender and generational dimensions. The differing experiences of cohorts of men who faced either early retirement, redundancy or transfer to alternative sectors, or those who never attained anticipated industrial employment due to final closures, are analysed in terms of constructions of masculinity and the endurance of cultural as well as material losses. This is counterpoised to women who gained industrial work in assembly plants and the perceived gradual attainment of an improved economic and social position whilst continuing to navigate structures of patriarchy.

Design and Technology: A Historical Perspective on the Mediating Role of Technology Between Industrial Design and Engineering

The interdisciplinary relationship between industrial design and mechanical engineering is sensitive. This research focuses on understanding how one can positively mediate this relation, in order to foster innovation. In this paper, technology is considered for this role since it has, in some historical moments, served as an integrator of these two disciplines, in processes that led to innovation. By means of an extensive literature review, covering three different periods of technological development, both disciplines’ positioning in society and their link with technology are analyzed and compared. The three case studies selected help to illustrate, precisely, the technology positioning between both disciplines and society. Literature assumes that industrial design is rooted in the rise of criticism against both the machine and the mechanized production. This is an opposing approach to the current paradigm, in which design plays a fundamental role in adapting technology to society. Also, the social problems caused by the mechanized and massive production triggered the mechanical engineering emergence, as a professionalized discipline. Technology was intrinsically connected with both industrial design and mechanical engineering emergence and subsequent evolution. In the technology conflict with society lays the reform and regulation for design practice, in its broadest sense.

Computational Models Development and Demand Response Application for Smart Grids

This paper focuses on computational models development and its applications on demand response, within smart grid scope. A prosumer model is presented and the corresponding economic dispatch problem solution is analyzed. The prosumer solar radiation production and energy consumption are forecasted by artificial neural networks. The existing demand response models are studied and a computational tool based on fuzzy clustering algorithm is developed and the results discussed. Consumer energy management applications within the InovGrid pilot project are presented. Computation systems are developed for the acquisition, monitoring, control and supervision of consumption data provided by smart meters, allowing the incorporation of consumer actions on their electrical energy management. An energy management system with integration of smart meters for energy consumers in a smart grid is developed.

Development and experimental validation of a knock induced damage model and real-time implementation of model-based strategies to control knock intensity in boosted gasoline engines

This PhD thesis reports the main activities carried out during the 3 years long “Mechanics and advanced engineering sciences” course, at the Department of Industrial Engineering of the University of Bologna. The research project title is “Development and analysis of high efficiency combustion systems for internal combustion engines” and the main topic is knock, one of the main challenges for boosted gasoline engines. Through experimental campaigns, modelling activity and test bench validation, 4 different aspects have been addressed to tackle the issue. The main path goes towards the definition and calibration of a knock-induced damage model, to be implemented in the on-board control strategy, but also usable for the engine calibration and potentially during the engine design. Ionization current signal capabilities have been investigated to fully replace the pressure sensor, to develop a robust on-board close-loop combustion control strategy, both in knock-free and knock-limited conditions. Water injection is a powerful solution to mitigate knock intensity and exhaust temperature, improving fuel consumption; its capabilities have been modelled and validated at the test bench. Finally, an empiric model is proposed to predict the engine knock response, depending on several operating condition and control parameters, including injected water quantity.

Essays in Long-run Development and Spatial Economics

This thesis tries to further our understanding for why some countries today are more prosperous than others. It establishes that part of today's observed variation in several proxies such as income or gender inequality have been determined in the distant past. Chapter one shows that 450 years of (Catholic) Portuguese colonisation had a long-lasting impact in India when it comes to education and female emancipation. Furthermore I use a historical quasi-experiment that happened 250 years ago in order to show that different outcomes have different degrees of persitence over time. Educational gaps between males and females seemingly wash out a few decades after the public provision of schools. The male biased sex-ratios on the other hand stay virtually unchanged despite governmental efforts. This provides evidence that deep rooted son preferences are much harder to overcome, suggesting that a differential approach is needed to tackle sex-selective abortion and female neglect. The second chapter proposes improvements for the execution of Spatial Regression Discontinuity Designs. These suggestions are accompanied by a full-fledged spatial statistical package written in R. Chapter three introduces a quantitative economic geography model in order to study the peculiar evolution of the European urban system on its way to the Industrial Revolution. It can explain the shift of economic gravity from the Mediterranean towards the North-Sea ("little divergence"). The framework provides novel insights on the importance of agricultural trade costs and the peculiar geography of Europe with its extended coastline and dense network of navigable rivers.

Development and Validation of a Model-Based Combustion Controller for Water Injection Management

This manuscript reports the overall development of a Ph.D. research project during the “Mechanics and advanced engineering sciences” course at the Department of Industrial Engineering of the University of Bologna. The project is focused on the development of a combustion control system for an innovative Spark Ignited engine layout. In details, the controller is oriented to manage a prototypal engine equipped with a Port Water Injection system. The water injection technology allows an increment of combustion efficiency due to the knock mitigation effect that permits to keep the combustion phasing closer to the optimal position with respect to the traditional layout. At the beginning of the project, the effects and the possible benefits achievable by water injection have been investigated by a focused experimental campaign. Then the data obtained by combustion analysis have been processed to design a control-oriented combustion model. The model identifies the correlation between Spark Advance, combustion phasing and injected water mass, and two different strategies are presented, both based on an analytic and semi-empirical approach and therefore compatible with a real-time application. The model has been implemented in a combustion controller that manages water injection to reach the best achievable combustion efficiency while keeping knock levels under a pre-established threshold. Three different versions of the algorithm are described in detail. This controller has been designed and pre-calibrated in a software-in-the-loop environment and later an experimental validation has been performed with a rapid control prototyping approach to highlight the performance of the system on real set-up. To further make the strategy implementable on an onboard application, an estimation algorithm of combustion phasing, necessary for the controller, has been developed during the last phase of the PhD Course, based on accelerometric signals.

Essays in Economic Geography and Long-Term Development

This dissertation has two main themes: first, the economic impact of tourism on cities and, secondly, the determinants of European long-run development, with a focus on the pre-Industrial era. The common thread is the attempt to develop economic geography models that incorporate spatial frictions and are liable to be given empirical content. Chapter 1, written in conjunction with G. Alfredo Minerva, provides an empirical analysis of the relationship between tourism and economic activity across Italian municipalities, and lays down the basic elements of an urban theory of tourism in an a-spatial setting. Chapter 2 extends these ideas to a quantitative urban framework to study the economic impact and the welfare consequences of tourism into the city of Venice. The model is given empirical content thanks to a large collection of data at the Census tract level for the Municipality of Venice, and then used to perform counterfactual policty analysis. In chapter 3, with Matteo Santacesaria, we consider a setting where agents are continuously distributed over a two-dimensional heterogeneous geography, and are allowed to do business at a finite set of markets. We study the equilibrium partition of the economic space into a collection of mutually-exclusive market areas, and provide condition for this equilibrium partition to exist and to be unique. Finally, chapter 4 "The rise of (urban) Europe: a Quantitative-Spatial analysis", co-authored with Matteo Cervellati and Alex Lehner, sets up a quantitative economic geography model to understand the roots of the Industrial Revolution, in an attempt to match the evolution of the European urban network, and the corresponding city-size distribution, over the period A.D. 1000-1850. It highlights the importance of agricultural trade across cities for the emergence of large manufacturing hubs.

Environmental assessment of industrial chemical and primary sector processes from a life cycle perspective

During the PhD program in chemistry at the University of Bologna, the environmental sustainability of some industrial processes was studied through the application of the LCA methodology. The efforts were focused on the study of processes under development, in order to assess their environmental impacts to guide their transfer on an industrial scale. Processes that could meet the principles of Green Chemistry have been selected and their environmental benefits have been evaluated through a holistic approach. The use of renewable sources was assessed through the study of terephthalic acid production from biomass (which showed that only the use of waste can provide an environmental benefit) and a new process for biogas upgrading (whose potential is to act as a carbon capture technology). Furthermore, the basis for the development of a new methodology for the prediction of the environmental impact of ionic liquids has been laid. It has already shown good qualities in identifying impact trends, but further research on it is needed to obtain a more reliable and usable model. In the context of sustainable development that will not only be sector-specific, the environmental performance of some processes linked to the primary production sector has also been evaluated. The impacts of some organic farming practices in the wine production were analysed, the use of the Cereal Unit parameter was proposed as a functional unit for the comparison of different crop rotations, and the carbon footprint of school canteen meals was calculated. The results of the analyses confirm that sustainability in the industrial production sector should be assessed from a life cycle perspective, in order to consider all the flows involved during the different phases. In particular, it is necessary that environmental assessments adopt a cradle-to-gate approach, to avoid shifting the environmental burden from one phase to another.

Design, development and characterization of DHA-based emulsion for Nutrilipidomics strategies

The industrial PhD project presented here is part of the R&D strategies of the Lipinutragen company. The innovation brought by the company concerns nutrilipidomics, i.e. the correlation between the lipid composition (in fatty acids) of the cell membrane and lipid-based nutraceuticals, especially starting from the well-known dependence of the lipid composition on the intake of essential fats, omega- 6 and omega-3 polyunsaturated fatty acids. Among the results obtained from the membrane lipidomic profiles, the case of autistic subjects is here highlighted, showing the significant deficiency of docosahexaenoic acid (DHA). The activity during the PhD was devoted to the nutrilipidomic approach. Part of the activities were devoted to scientific research in lipidomics: a) the study of lipidomic profiles in the frame of two collaboration projects: one with the group of Dr. I. Tueros at AZTI, Bilbao, regading obese population, and the other one regarding seed germination with the changes of the fatty acid profiles with the group of prof. A. Balestrazzi of the University of Parma; b) the liposome preparation for protection and lifetime prolongation of the peptide somatostatin, which was an important premise to the formulation of the DHA-containing microemulsion. The activities was also focused on the development of DHA-containing nutraceutical formulations in the form of emulsion, overcoming the difficulty of the capsule ingestion, to be administered orally. The work pointed to study the combination of active ingredients, based on the previous know-how regarding the bioavailability for the cell membrane incorporation. The ingredients of the formulation were studied and tested in vitro for the bioavailability of DHA to be incorporated in the cell membranes of different types of cultured cells. Part of this study is covered by non-disclosure agreement since it belongs to the know-how of Lipinutragen.

Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of the global warming. In this context, the transportation sector plays a vital role, since it is responsible for a large part of carbon dioxide production. In order to address these issues, the present thesis deals with the development of advanced control strategies for the energy efficiency optimization of plug-in hybrid electric vehicles (PHEVs), supported by the prediction of future working conditions of the powertrain. In particular, a Dynamic Programming algorithm has been developed for the combined optimization of vehicle energy and battery thermal management. At this aim, the battery temperature and the battery cooling circuit control signal have been considered as an additional state and control variables, respectively. Moreover, an adaptive equivalent consumption minimization strategy (A-ECMS) has been modified to handle zero-emission zones, where engine propulsion is not allowed. Navigation data represent an essential element in the achievement of these tasks. With this aim, a novel simulation and testing environment has been developed during the PhD research activity, as an effective tool to retrieve routing information from map service providers via vehicle-to-everything connectivity. Comparisons between the developed and the reference strategies are made, as well, in order to assess their impact on the vehicle energy consumption. All the activities presented in this doctoral dissertation have been carried out at the Green Mobility Research Lab} (GMRL), a research center resulting from the partnership between the University of Bologna and FEV Italia s.r.l., which represents the industrial partner of the research project.

Development of a colorimetric indicator label for food oxidation based on hexanal detection

In this work, a colorimetric indicator for food oxidation based on the detection of hexanal in gas-phase, has been developed. In fact, in recent years, the food packaging industry has evolved towards new generation of packaging, like active and intelligent. According to literature (Pangloli P. et al. 2002), hexanal is the main product of a fatty acid oxidation: the linoleic acid. So, it was chosen to analyse two kinds of potato chips, fried in two different oils with high concentration of linoleic acid: olive oil and sunflower oil. Five different formulas were prepared and their colour change when exposed to hexanal in gas phase was evaluated. The formulas evaluations were first conducted on filter paper labels. The next step was to select the thickener to add to the formula, in order to coat a polypropylene film, more appropriate than the filter paper for a production at industrial scale. Three kinds of thickeners were tested: a cellulose derivative, an ethylene vinyl-alcohol and a polyvinyl alcohol. To obtain the final labels with the autoadhesive layer, the polypropylene film with the selected formula and thickener was coat with a water based adhesive. For both filter paper and polypropylene labels, with and without autoadhesive layer, the detection limit and the detection time were measured. For the selected formula on filter paper labels, the stability was evaluated, when conserved on the dark or on the light, in order to determine the storage time. Both potato chips samples, stocked at the same conditions, were analysed using an optimised Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) method, in order to determine the concentration of volatilized hexanal. With the aim to establish if the hexanal can be considered as an indicator of the end of potato chips shelf life, sensory evaluation was conducted each day of HS-SPME-GC-MS analysis.

A distributed middleware for IT/OT convergence in modern industrial environments

The modern industrial environment is populated by a myriad of intelligent devices that collaborate for the accomplishment of the numerous business processes in place at the production sites. The close collaboration between humans and work machines poses new interesting challenges that industry must overcome in order to implement the new digital policies demanded by the industrial transition. The Industry 5.0 movement is a companion revolution of the previous Industry 4.0, and it relies on three characteristics that any industrial sector should have and pursue: human centrality, resilience, and sustainability. The application of the fifth industrial revolution cannot be completed without moving from the implementation of Industry 4.0-enabled platforms. The common feature found in the development of this kind of platform is the need to integrate the Information and Operational layers. Our thesis work focuses on the implementation of a platform addressing all the digitization features foreseen by the fourth industrial revolution, making the IT/OT convergence inside production plants an improvement and not a risk. Furthermore, we added modular features to our platform enabling the Industry 5.0 vision. We favored the human centrality using the mobile crowdsensing techniques and the reliability and sustainability using pluggable cloud computing services, combined with data coming from the crowd support. We achieved important and encouraging results in all the domains in which we conducted our experiments. Our IT/OT convergence-enabled platform exhibits the right performance needed to satisfy the strict requirements of production sites. The multi-layer capability of the framework enables the exploitation of data not strictly coming from work machines, allowing a more strict interaction between the company, its employees, and customers.

Development of advanced methods for the simulation of the reacting mixture formation in internal combustion engines with the use of machine learning algorithms

Besides increasing the share of electric and hybrid vehicles, in order to comply with more stringent environmental protection limitations, in the mid-term the auto industry must improve the efficiency of the internal combustion engine and the well to wheel efficiency of the employed fuel. To achieve this target, a deeper knowledge of the phenomena that influence the mixture formation and the chemical reactions involving new synthetic fuel components is mandatory, but complex and time intensive to perform purely by experimentation. Therefore, numerical simulations play an important role in this development process, but their use can be effective only if they can be considered accurate enough to capture these variations. The most relevant models necessary for the simulation of the reacting mixture formation and successive chemical reactions have been investigated in the present work, with a critical approach, in order to provide instruments to define the most suitable approaches also in the industrial context, which is limited by time constraints and budget evaluations. To overcome these limitations, new methodologies have been developed to conjugate detailed and simplified modelling techniques for the phenomena involving chemical reactions and mixture formation in non-traditional conditions (e.g. water injection, biofuels etc.). Thanks to the large use of machine learning and deep learning algorithms, several applications have been revised or implemented, with the target of reducing the computing time of some traditional tasks by orders of magnitude. Finally, a complete workflow leveraging these new models has been defined and used for evaluating the effects of different surrogate formulations of the same experimental fuel on a proof-of-concept GDI engine model.