Identifying strategies for mitigating the global warming impact of the EU-25 economy using a multi-objective input-output approach

Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.

Efficient image mosaicing for multi-robot visual underwater mapping

Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

Dual inhibitors of beta-amyloid aggregation and acetylcholinesterase as multi-target anti-Alzheimer drug candidates

Notwithstanding the functional role that the aggregates of some amyloidogenic proteins can play in different organisms, protein aggregation plays a pivotal role in the pathogenesis of a large number of human diseases. One of such diseases is Alzheimer"s disease (AD), where the overproduction and aggregation of the β-amyloid peptide (Aβ) are regarded as early critical factors. Another protein that seems to occupy a prominent position within the complex pathological network of AD is the enzyme acetylcholinesterase (AChE), with classical and non-classical activities involved at the late (cholinergic deficit) and early (Aβ aggregation) phases of the disease. Dual inhibitors of Aβ aggregation and AChE are thus emerging as promising multi-target agents with potential to efficiently modify the natural course of AD. In the initial phases of the drug discovery process of such compounds, in vitro evaluation of the inhibition of Aβ aggregation is rather troublesome, as it is very sensitive to experimental assay conditions, and requires expensive synthetic Aβ peptides, which makes cost-prohibitive the screening of large compound libraries. Herein, we review recently developed multi-target anti-Alzheimer compounds that exhibit both Aβ aggregation and AChE inhibitory activities, and, in some cases also additional valuable activities such as BACE-1 inhibition or antioxidant properties. We also discuss the development of simplified in vivo methods for the rapid, simple, reliable, unexpensive, and high-throughput amenable screening of Aβ aggregation inhibitors that rely on the overexpression of Aβ42 alone or fused with reporter proteins in Escherichia coli.

Effect of hydrodynamics on modelling, monitoring and control of crystallization

Crystallization is a purification method used to obtain crystalline product of a certain crystal size. It is one of the oldest industrial unit processes and commonly used in modern industry due to its good purification capability from rather impure solutions with reasonably low energy consumption. However, the process is extremely challenging to model and control because it involves inhomogeneous mixing and many simultaneous phenomena such as nucleation, crystal growth and agglomeration. All these phenomena are dependent on supersaturation, i.e. the difference between actual liquid phase concentration and solubility. Homogeneous mass and heat transfer in the crystallizer would greatly simplify modelling and control of crystallization processes, such conditions are, however, not the reality, especially in industrial scale processes. Consequently, the hydrodynamics of crystallizers, i.e. the combination of mixing, feed and product removal flows, and recycling of the suspension, needs to be thoroughly investigated. Understanding of hydrodynamics is important in crystallization, especially inlargerscale equipment where uniform flow conditions are difficult to attain. It is also important to understand different size scales of mixing; micro-, meso- and macromixing. Fast processes, like nucleation and chemical reactions, are typically highly dependent on micro- and mesomixing but macromixing, which equalizes the concentrations of all the species within the entire crystallizer, cannot be disregarded. This study investigates the influence of hydrodynamics on crystallization processes. Modelling of crystallizers with the mixed suspension mixed product removal (MSMPR) theory (ideal mixing), computational fluid dynamics (CFD), and a compartmental multiblock model is compared. The importance of proper verification of CFD and multiblock models is demonstrated. In addition, the influence of different hydrodynamic conditions on reactive crystallization process control is studied. Finally, the effect of extreme local supersaturation is studied using power ultrasound to initiate nucleation. The present work shows that mixing and chemical feeding conditions clearly affect induction time and cluster formation, nucleation, growth kinetics, and agglomeration. Consequently, the properties of crystalline end products, e.g. crystal size and crystal habit, can be influenced by management of mixing and feeding conditions. Impurities may have varying impacts on crystallization processes. As an example, manganese ions were shown to replace magnesium ions in the crystal lattice of magnesium sulphate heptahydrate, increasing the crystal growth rate significantly, whereas sodium ions showed no interaction at all. Modelling of continuous crystallization based on MSMPR theory showed that the model is feasible in a small laboratoryscale crystallizer, whereas in larger pilot- and industrial-scale crystallizers hydrodynamic effects should be taken into account. For that reason, CFD and multiblock modelling are shown to be effective tools for modelling crystallization with inhomogeneous mixing. The present work shows also that selection of the measurement point, or points in the case of multiprobe systems, is crucial when process analytical technology (PAT) is used to control larger scale crystallization. The thesis concludes by describing how control of local supersaturation by highly localized ultrasound was successfully applied to induce nucleation and to control polymorphism in reactive crystallization of L-glutamic acid.

A study of combustion phenomena in circulating fluidized beds by developing and applying experimental and modelling methods for laboratory-scale reactors

The results shown in this thesis are based on selected publications of the 2000s decade. The work was carried out in several national and EC funded public research projects and in close cooperation with industrial partners. The main objective of the thesis was to study and quantify the most important phenomena of circulating fluidized bed combustors by developing and applying proper experimental and modelling methods using laboratory scale equipments. An understanding of the phenomena plays an essential role in the development of combustion and emission performance, and the availability and controls of CFB boilers. Experimental procedures to study fuel combustion behaviour under CFB conditions are presented in the thesis. Steady state and dynamic measurements under well controlled conditions were carried out to produce the data needed for the development of high efficiency, utility scale CFB technology. The importance of combustion control and furnace dynamics is emphasized when CFB boilers are scaled up with a once through steam cycle. Qualitative information on fuel combustion characteristics was obtained directly by comparing flue gas oxygen responses during the impulse change experiments with fuel feed. A one-dimensional, time dependent model was developed to analyse the measurement data Emission formation was studied combined with fuel combustion behaviour. Correlations were developed for NO, N2O, CO and char loading, as a function of temperature and oxygen concentration in the bed area. An online method to characterize char loading under CFB conditions was developed and validated with the pilot scale CFB tests. Finally, a new method to control air and fuel feeds in CFB combustion was introduced. The method is based on models and an analysis of the fluctuation of the flue gas oxygen concentration. The effect of high oxygen concentrations on fuel combustion behaviour was also studied to evaluate the potential of CFB boilers to apply oxygenfiring technology to CCS. In future studies, it will be necessary to go through the whole scale up chain from laboratory phenomena devices through pilot scale test rigs to large scale, commercial boilers in order to validate the applicability and scalability of the, results. This thesis shows the chain between the laboratory scale phenomena test rig (bench scale) and the CFB process test rig (pilot). CFB technology has been scaled up successfully from an industrial scale to a utility scale during the last decade. The work shown in the thesis, for its part, has supported the development by producing new detailed information on combustion under CFB conditions.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Fraud detection in the banking sector : a multi-agent approach

Fraud is an increasing phenomenon as shown in many surveys carried out by leading international consulting companies in the last years. Despite the evolution of electronic payments and hacking techniques there is still a strong human component in fraud schemes. Conflict of interest in particular is the main contributing factor to the success of internal fraud. In such cases anomaly detection tools are not always the best instruments, since the fraud schemes are based on faking documents in a context dominated by lack of controls, and the perpetrators are those ones who should control possible irregularities. In the banking sector audit team experts can count only on their experience, whistle blowing and the reports sent by their inspectors. The Fraud Interactive Decision Expert System (FIDES), which is the core of this research, is a multi-agent system built to support auditors in evaluating suspicious behaviours and to speed up the evaluation process in order to detect or prevent fraud schemes. The system combines Think-map, Delphi method and Attack trees and it has been built around audit team experts and their needs. The output of FIDES is an attack tree, a tree-based diagram to ”systematically categorize the different ways in which a system can be attacked”. Once the attack tree is built, auditors can choose the path they perceive as more suitable and decide whether or not to start the investigation. The system is meant for use in the future to retrieve old cases in order to match them with new ones and find similarities. The retrieving features of the system will be useful to simplify the risk management phase, since similar countermeasures adopted for past cases might be useful for present ones. Even though FIDES has been built with the banking sector in mind, it can be applied in all those organisations, like insurance companies or public organizations, where anti-fraud activity is based on a central anti-fraud unit and a reporting system.

Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Chromatographic recovery of chemicals from acidic biomass hydrolysates

Lignocellulosic biomasses (e.g., wood and straws) are a potential renewable source for the production of a wide variety of chemicals that could be used to replace those currently produced by petrochemical industry. This would lead to lower greenhouse gas emissions and waste amounts, and to economical savings. There are many possible pathways available for the manufacturing of chemicals from lignocellulosic biomasses. One option is to hydrolyze the cellulose and hemicelluloses of these biomasses into monosaccharides using concentrated sulfuric acid as catalyst. This process is an efficient method for producing monosaccharides which are valuable platforn chemicals. Also other valuable products are formed in the hydrolysis. Unfortunately, the concentrated acid hydrolysis has been deemed unfeasible mainly due to high chemical consumption resulting from the need to remove sulfuric acid from the obtained hydrolysates prior to the downstream processing of the monosaccharides. Traditionally, this has been done by neutralization with lime. This, however, results in high chemical consumption. In addition, the by-products formed in the hydrolysis are not removed and may, thus, hinder the monosaccharide processing. In order to improve the feasibility of the concentrated acid hydrolysis, the chemical consumption should be decreased by recycling of sulfuric acid without neutralization. Furthermore, the monosaccharides and the other products formed in the hydrolysis should be recovered selectively for efficient downstream processing. The selective recovery of the hydrolysis by-products would have additional economical benefits on the process due to their high value. In this work, the use of chromatographic fractionation for the recycling of sulfuric acid and the selective recovery of the main components from the hydrolysates formed in the concentrated acid hydrolysis was investigated. Chromatographic fractionation based on the electrolyte exclusion with gel type strong acid cation exchange resins in acid (H+) form as a stationary phase was studied. A systematic experimental and model-based study regarding the separation task at hand was conducted. The phenomena affecting the separation were determined and their effects elucidated. Mathematical models that take accurately into account these phenomena were derived and used in the simulation of the fractionation process. The main components of the concentrated acid hydrolysates (sulfuric acid, monosaccharides, and acetic acid) were included into this model. Performance of the fractionation process was investigated experimentally and by simulations. Use of different process options was also studied. Sulfuric acid was found to have a significant co-operative effect on the sorption of the other components. This brings about interesting and beneficial effects in the column operations. It is especially beneficial for the separation of sulfuric acid and the monosaccharides. Two different approaches for the modelling of the sorption equilibria were investigated in this work: a simple empirical approach and a thermodynamically consistent approach (the Adsorbed Solution theory). Accurate modelling of the phenomena observed in this work was found to be possible using the simple empirical models. The use of the Adsorbed Solution theory is complicated by the nature of the theory and the complexity of the studied system. In addition to the sorption models, a dynamic column model that takes into account the volume changes of the gel type resins as changing resin bed porosity was also derived. Using the chromatography, all the main components of the hydrolysates can be recovered selectively, and the sulfuric acid consumption of the hydrolysis process can be lowered considerably. Investigation of the performance of the chromatographic fractionation showed that the highest separation efficiency in this separation task is obtained with a gel type resin with a high crosslinking degree (8 wt. %); especially when the hydrolysates contain high amounts of acetic acid. In addition, the concentrated acid hydrolysis should be done with as low sulfuric acid concentration as possible to obtain good separation performance. The column loading and flow rate also have large effects on the performance. In this work, it was demonstrated that when recycling of the fractions obtained in the chromatographic fractionation are recycled to preceding unit operations these unit operations should included in the performance evaluation of the fractionation. When this was done, the separation performance and the feasibility of the concentrated acid hydrolysis process were found to improve considerably. Use of multi-column chromatographic fractionation processes, the Japan Organo process and the Multi-Column Recycling Chromatography process, was also investigated. In the studied case, neither of these processes could compete with the single-column batch process in the productivity. However, due to internal recycling steps, the Multi-Column Recycling Chromatography was found to be superior to the batch process when the product yield and the eluent consumption were taken into account.

Additional revenue opportunities in pulp mills and their impacts on the kraft process

Although the concept of multi-products biorefinery provides an opportunity to meet the future demands for biofuels, biomaterials or chemicals, it is not assured that its implementation would improve the profitability of kraft pulp mills. The attractiveness will depend on several factors such as mill age and location, government incentives, economy of scale, end user requirements, and how much value can be added to the new products. In addition, the effective integration of alternative technologies is not straightforward and has to be carefully studied. In this work, detailed balances were performed to evaluate possible impacts that lignin removal, hemicelluloses recovery prior to pulping, torrefaction and pyrolysis of wood residues cause on the conventional mill operation. The development of mill balances was based on theoretical fundamentals, practical experience, literature review, personal communication with technology suppliers and analysis of mill process data. Hemicelluloses recovery through pre-hydrolysis of chips leads to impacts in several stages of the kraft process. Effects can be observed on the pulping process, wood consumption, black liquor properties and, inevitably, on the pulp quality. When lignin is removed from black liquor, it will affect mostly the chemical recovery operation and steam generation rate. Since mineral acid is used to precipitate the lignin, impacts on the mill chemical balance are also expected. A great advantage of processing the wood residues for additional income results from the fact that the pulping process, pulp quality and sales are not harmfully affected. For pulp mills interested in implementing the concept of multi-products biorefinery, this work has indicated possible impacts to be considered in a technical feasibility study.

Computational studies for the design of process equipment with complex geometries

This study combines several projects related to the flows in vessels with complex shapes representing different chemical apparata. Three major cases were studied. The first one is a two-phase plate reactor with a complex structure of intersecting micro channels engraved on one plate which is covered by another plain plate. The second case is a tubular microreactor, consisting of two subcases. The first subcase is a multi-channel two-component commercial micromixer (slit interdigital) used to mix two liquid reagents before they enter the reactor. The second subcase is a micro-tube, where the distribution of the heat generated by the reaction was studied. The third case is a conventionally packed column. However, flow, reactions or mass transfer were not modeled. Instead, the research focused on how to describe mathematically the realistic geometry of the column packing, which is rather random and can not be created using conventional computeraided design or engineering (CAD/CAE) methods. Several modeling approaches were used to describe the performance of the processes in the considered vessels. Computational fluid dynamics (CFD) was used to describe the details of the flow in the plate microreactor and micromixer. A space-averaged mass transfer model based on Fick’s law was used to describe the exchange of the species through the gas-liquid interface in the microreactor. This model utilized data, namely the values of the interfacial area, obtained by the corresponding CFD model. A common heat transfer model was used to find the heat distribution in the micro-tube. To generate the column packing, an additional multibody dynamic model was implemented. Auxiliary simulation was carried out to determine the position and orientation of every packing element in the column. This data was then exported into a CAD system to generate desirable geometry, which could further be used for CFD simulations. The results demonstrated that the CFD model of the microreactor could predict the flow pattern well enough and agreed with experiments. The mass transfer model allowed to estimate the mass transfer coefficient. Modeling for the second case showed that the flow in the micromixer and the heat transfer in the tube could be excluded from the larger model which describes the chemical kinetics in the reactor. Results of the third case demonstrated that the auxiliary simulation could successfully generate complex random packing not only for the column but also for other similar cases.

Towards multi bibliographic format support in Invenio

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Analysis and modelling of chemical looping combustion process with and without oxygen uncoupling

Effective control and limiting of carbon dioxide (CO₂) emissions in energy production are major challenges of science today. Current research activities include the development of new low-cost carbon capture technologies, and among the proposed concepts, chemical combustion (CLC) and chemical looping with oxygen uncoupling (CLOU) have attracted significant attention allowing intrinsic separation of pure CO₂ from a hydrocarbon fuel combustion process with a comparatively small energy penalty. Both CLC and CLOU utilize the well-established fluidized bed technology, but several technical challenges need to be overcome in order to commercialize the processes. Therefore, development of proper modelling and simulation tools is essential for the design, optimization, and scale-up of chemical looping-based combustion systems. The main objective of this work was to analyze the technological feasibility of CLC and CLOU processes at different scales using a computational modelling approach. A onedimensional fluidized bed model frame was constructed and applied for simulations of CLC and CLOU systems consisting of interconnected fluidized bed reactors. The model is based on the conservation of mass and energy, and semi-empirical correlations are used to describe the hydrodynamics, chemical reactions, and transfer of heat in the reactors. Another objective was to evaluate the viability of chemical looping-based energy production, and a flow sheet model representing a CLC-integrated steam power plant was developed. The 1D model frame was succesfully validated based on the operation of a 150 kWth laboratory-sized CLC unit fed by methane. By following certain scale-up criteria, a conceptual design for a CLC reactor system at a pre-commercial scale of 100 MWth was created, after which the validated model was used to predict the performance of the system. As a result, further understanding of the parameters affecting the operation of a large-scale CLC process was acquired, which will be useful for the practical design work in the future. The integration of the reactor system and steam turbine cycle for power production was studied resulting in a suggested plant layout including a CLC boiler system, a simple heat recovery setup, and an integrated steam cycle with a three pressure level steam turbine. Possible operational regions of a CLOU reactor system fed by bituminous coal were determined via mass, energy, and exergy balance analysis. Finally, the 1D fluidized bed model was modified suitable for CLOU, and the performance of a hypothetical 500 MWth CLOU fuel reactor was evaluated by extensive case simulations.

Time to volume through efficient multi-site ramp-up

The aim of this thesis was to create a process for all multi-site ramp-up (MSRU) projects in the case company in order to have simultaneous ramp-ups early in the market. The research was done through case study in one company and semi-structured interviews. There are already processes, which are now in use in MSRU-cases. Interviews of 20 ramp-up specialists revealed topics to be improved. Those were project team set up, roles and responsibilities and recommended project organization, communication, product change management practices, competence and know how transfer practices and support model. More R&D support and involvement is needed in MSRU-projects. DCM’s role is very important in the MSRU-projects among PMT-team; he should be the business owner of the project. Recommendation is that product programs could take care of the product and repair training of new products in volume factories. R&D’s participation in competence transfers is essential important in MSRU-projects. Communication in projects could be shared through special intranet commune. Blogging and tweeting could be considered in the communication plan. If hundreds of change notes are open in ramp-up phase, it should be considered not to approve the product into volume ramp-up. PMTs’ supports are also important and MSRU-projects should be planned, budgeted and executed together. Finally a new MSRU-process is presented in this thesis to be used in all MSRU-projects.