Structural and operational optimisation : applications in energy systems

In this work mathematical programming models for structural and operational optimisation of energy systems are developed and applied to a selection of energy technology problems. The studied cases are taken from industrial processes and from large regional energy distribution systems. The models are based on Mixed Integer Linear Programming (MILP), Mixed Integer Non-Linear Programming (MINLP) and on a hybrid approach of a combination of Non-Linear Programming (NLP) and Genetic Algorithms (GA). The optimisation of the structure and operation of energy systems in urban regions is treated in the work. Firstly, distributed energy systems (DES) with different energy conversion units and annual variations of consumer heating and electricity demands are considered. Secondly, district cooling systems (DCS) with cooling demands for a large number of consumers are studied, with respect to a long term planning perspective regarding to given predictions of the consumer cooling demand development in a region. The work comprises also the development of applications for heat recovery systems (HRS), where paper machine dryer section HRS is taken as an illustrative example. The heat sources in these systems are moist air streams. Models are developed for different types of equipment price functions. The approach is based on partitioning of the overall temperature range of the system into a number of temperature intervals in order to take into account the strong nonlinearities due to condensation in the heat recovery exchangers. The influence of parameter variations on the solutions of heat recovery systems is analysed firstly by varying cost factors and secondly by varying process parameters. Point-optimal solutions by a fixed parameter approach are compared to robust solutions with given parameter variation ranges. In the work enhanced utilisation of excess heat in heat recovery systems with impingement drying, electricity generation with low grade excess heat and the use of absorption heat transformers to elevate a stream temperature above the excess heat temperature are also studied.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Applications of augmented reality for sales in apparel industry in Russia

The sustainable growth of video interactivity technologies on different platforms in the lasts years opens good prospects for augmented reality technology adoption on different markets. In the end of 2011 there was an improvement in technology which allows building the 3D model of human body. Such an improvement could be used in apparel industry. The main goal of the study is to understand the level of acceptance of augmented reality as a technology on the Russian apparel market. For a more accurate investigation, a new model accounting for augmented reality characteristics, as well as for similarities and differences between online and offline customer behavior in apparel industry, was developed. As a result of the survey, the weights of different purchase intention factors for Russian consumer were found, and the information about Russian consumers’ preferences towards the augmented reality features in apparel market, especially in fitting time, real-time interaction and fitting quality peculiarities, was presented.

Particle model for simulating limestone reactions in novel fluidised bed energy applications

The development of carbon capture and storage (CCS) has raised interest towards novel fluidised bed (FB) energy applications. In these applications, limestone can be utilized for S02 and/or CO2 capture. The conditions in the new applications differ from the traditional atmospheric and pressurised circulating fluidised bed (CFB) combustion conditions in which the limestone is successfully used for SO2 capture. In this work, a detailed physical single particle model with a description of the mass and energy transfer inside the particle for limestone was developed. The novelty of this model was to take into account the simultaneous reactions, changing conditions, and the effect of advection. Especially, the capability to study the cyclic behaviour of limestone on both sides of the calcination-carbonation equilibrium curve is important in the novel conditions. The significances of including advection or assuming diffusion control were studied in calcination. Especially, the effect of advection in calcination reaction in the novel combustion atmosphere was shown. The model was tested against experimental data; sulphur capture was studied in a laboratory reactor in different fluidised bed conditions. Different Conversion levels and sulphation patterns were examined in different atmospheres for one limestone type. The Conversion curves were well predicted with the model, and the mechanisms leading to the Conversion patterns were explained with the model simulations. In this work, it was also evaluated whether the transient environment has an effect on the limestone behaviour compared to the averaged conditions and in which conditions the effect is the largest. The difference between the averaged and transient conditions was notable only in the conditions which were close to the calcination-carbonation equilibrium curve. The results of this study suggest that the development of a simplified particle model requires a proper understanding of physical and chemical processes taking place in the particle during the reactions. The results of the study will be required when analysing complex limestone reaction phenomena or when developing the description of limestone behaviour in comprehensive 3D process models. In order to transfer the experimental observations to furnace conditions, the relevant mechanisms that take place need to be understood before the important ones can be selected for 3D process model. This study revealed the sulphur capture behaviour under transient oxy-fuel conditions, which is important when the oxy-fuel CFB process and process model are developed.

Developing usability evaluation heuristics for augmented reality applications

There is no generic usability heuristics for Augmented Reality (AR) applications, thus, the aim of this thesis was to develop one. The development of the heuristics was carried out in phases. Based on a literature review, a preliminary version of the heuristics was developed, which was evaluated by four experts. As a result, six evaluation criteria were formed: 1) interaction methods and controls, 2) presentation of virtual objects, 3) relationship between virtual objects and real world, 4) information related to virtual objects, 5) suitability for the usage context and 6) physical comfort of use. The heuristics should be used with Nielsen's (1995) generic usability evaluation heuristics. The heuristics are not ready to be used as such, since it must still be tested in practice.

New methods for controlling twin configurations and characterizing twin boundaries in 5M Ni-Mn-Ga for the development of applications

Traditional methods for studying the magnetic shape memory (MSM) alloys Ni-Mn-Ga include subjecting the entire sample to a uniform magnetic field or completely actuating the sample mechanically. These methods have produced significant results in characterizing the MSM effect, the properties of Ni-Mn-Ga and have pioneered the development of applications from this material. Twin boundaries and their configuration within a Ni-Mn-Ga sample are a key component in the magnetic shape memory effect. Applications that are developed require an understanding of twin boundary characteristics and, more importantly, the ability to predictably control them. Twins have such a critical role that the twinning stress of a Ni-Mn-Ga crystal is the defining characteristic that indicates its quality and significant research has been conducted to minimize this property. This dissertation reports a decrease in the twinning stress, predictably controlling the twin configuration and characterizing the dynamics of twin boundaries. A reduction of the twinning stress is demonstrated by the discovery of Type II twins within Ni-Mn-Ga which have as little as 10% of the twinning stress of traditional Type I twins. Furthermore, new methods of actuating a Ni-Mn-Ga element using localized unidirectional or bidirectional magnetic fields were developed that can predictably control the twin configuration in a localized area of a Ni-Mn-Ga element. This method of controlling the local twin configuration was used in the characterization of twin boundary dynamics. Using a localized magnetic pulse, the velocity and acceleration of a single twin boundary were measured to be 82.5 m/s and 2.9 × 107 m/s2, and the time needed for the twin boundary to nucleate and begin moving was less than 2.8 μs. Using a bidirectional magnetic field from a diametrically magnetized cylindrical magnet, a highly reproducible and controllable local twin configuration was created in a Ni-Mn-Ga element which is the fundamental pumping mechanism in the MSM micropump that has been co-invented and extensively characterized by the author.

Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

Development and characterization of thin printed films for gas sensing applications

The monitoring and control of hydrogen sulfide (H2S) level is of great interest for a wide range of application areas including food quality control, defense and antiterrorist applications and air quality monitoring e.g. in mines. H2S is a very poisonous and flammable gas. Exposure to low concentrations of H2S can result in eye irritation, a sore throat and cough, shortness of breath, and fluid retention in the lungs. These symptoms usually disappear in a few weeks. Long-term, low-level exposure may result in fatigue, loss of appetite, headache, irritability, poor memory, and dizziness. Higher concentrations of 700 - 800 ppm tend to be fatal. H2S has a characteristic smell of rotten egg. However, because of temporary paralysis of olfactory nerves, the smelling capability at concentrations higher than 100 ppm is severely compromised. In addition, volatile H2S is one of the main products during the spoilage of poultry meat in anaerobic conditions. Currently, no commercial H2S sensor is available which can operate under anaerobic conditions and can be easily integrated in the food packaging. This thesis presents a step-wise progress in the development of printed H2S gas sensors. Efforts were made in the formulation, characterization and optimization of functional printable inks and coating pastes based on composites of a polymer and a metal salt as well as a composite of a metal salt and an organic acid. Different processing techniques including inkjet printing, flexographic printing, screen printing and spray coating were utilized in the fabrication of H2S sensors. The dispersions were characterized by measuring turbidity, surface tension, viscosity and particle size. The sensing films were characterized using X-ray photoelectron spectroscopy, X-ray diffraction, atomic force microscopy and an electrical multimeter. Thin and thick printed or coated films were developed for gas sensing applications with the aim of monitoring the H2S concentrations in real life applications. Initially, a H2S gas sensor based on a composite of polyaniline and metal salt was developed. Both aqueous and solvent-based dispersions were developed and characterized. These dispersions were then utilized in the fabrication of roll-to-roll printed H2S gas sensors. However, the humidity background, long term instability and comparatively lower detection limit made these sensors less favourable for real practical applications. To overcome these problems, copper acetate based sensors were developed for H2S gas sensing. Stable inks with excellent printability were developed by tuning the surface tension, viscosity and particle size. This enabled the formation of inkjet-printed high quality copper acetate films with excellent sensitivity towards H2S. Furthermore, these sensors showed negligible humidity effects and improved selectivity, response time, lower limit of detection and coefficient of variation. The lower limit of detection of copper acetate based sensors was further improved to sub-ppm level by incorporation of catalytic gold nano-particles and subsequent plasma treatment of the sensing film. These sensors were further integrated in an inexpensive wirelessly readable RLC-circuit (where R is resistor, L is inductor and C is capacitor). The performance of these sensors towards biogenic H2S produced during the spoilage of poultry meat in the modified atmosphere package was also demonstrated in this thesis. This serves as a proof of concept that these sensors can be utilized in real life applications.

Functionalisation of spruce O-acetyl-galactoglucomannans for barrier and composite applications

The increasing use of energy, food, and materials by the growing population in the world is leading to the situation where alternative solutions from renewable carbon resources are sought after. The growing use of plastics depends on the raw-oil production while oil refining are politically governed and required for the polymer manufacturing is not sustainable in terms of carbon footprint. The amount of packaging is also increasing. Packaging is not only utilising cardboard and paper, but also plastics. The synthetic petroleum-derived plastics and inner-coatings in food packaging can be substituted with polymeric material from the renewable resources. The trees in Finnish forests constitute a huge resource, which ought to be utilised more effectively than it is today. One underutilised component of the forests is the wood-derived hemicelluloses, although Spruce Oacetyl-galactoglucomannans (GGMs) have previously shown high potential for material applications and can be recovered in large scale. Hemicelluloses are hydrophilic in their native state, which restrains the use of them for food packaging as non-dry item. To cope with this challenge, we intended to make GGMs more hydrophobic or amphiphilic by chemical grafting and consequently with the focus of using them for barrier applications. Methods of esterification with anhydrides and cationic etherification with a trimethyl ammonium moiety were established. A method of controlled synthesis to obtain the desired properties by the means of altering temperature, reaction time, the quantity of the reagent, and even the solvent for purification of the products was developed. Numerous analytical tools, such as NMR, FTIR, SEC-MALLS/RI, MALDI-TOF-MS, RP-HPLC and polyelectrolyte titration were used to evaluate the products from different perspectives and to acquire parallel proofs of their chemical structure. Modified GGMs with different degree of substitution and the correlating level of hydrophobicity was applied as coatings on cartonboard and on nanofibrillated cellulose-GGM films to exhibit barrier functionality. The water dispersibility in processing was maintained with GGM esters with low DS. The use of chemically functionalised GGM was evaluated for the use as barriers against water, oxygen and grease for the food packaging purposes. The results show undoubtedly that GGM derivatives exhibit high potential to function as a barrier material in food packaging.

Blue and Uv-Emitting Upconversion Nanoparticles: Synthesis and (Bio) Analytical Applications.

Rare-earth based upconverting nanoparticles (UCNPs) have attracted much attention due to their unique luminescent properties. The ability to convert multiple photons of lower energy to ones with higher energy through an upconversion (UC) process offers a wide range of applications for UCNPs. The emission intensities and wavelengths of UCNPs are important performance characteristics, which determine the appropriate applications. However, insufficient intensities still limit the use of UCNPs; especially the efficient emission of blue and ultraviolet (UV) light via upconversion remains challenging, as these events require three or more near-infrared (NIR) photons. The aim of the study was to enhance the blue and UV upconversion emission intensities of Tm3+ doped NaYF4 nanoparticles and to demonstrate their utility in in vitro diagnostics. As the distance between the sensitizer and the activator significantly affect the energy transfer efficiency, different strategies were explored to change the local symmetry around the doped lanthanides. One important strategy is the intentional co-doping of active (participate in energy transfer) or passive (do not participate in energy transfer) impurities into the host matrix. The roles of doped passive impurities (K+ and Sc3+) in enhancing the blue and UV upconversions, as well as in influencing the intense UV upconversion emission through excess sensitization (active impurity) were studied. Additionally, the effects of both active and passive impurity doping on the morphological and optical performance of UCNPs were investigated. The applicability of UV emitting UCNPs as an internal light source for glucose sensing in a dry chemistry test strip was demonstrated. The measurements were in agreement with the traditional method based on reflectance measurements using an external UV light source. The use of UCNPs in the glucose test strip offers an alternative detection method with advantages such as control signals for minimizing errors and high penetration of the NIR excitation through the blood sample, which gives more freedom for designing the optical setup. In bioimaging, the excitation of the UCNPs in the transparent IR region of the tissue permits measurements, which are free of background fluorescence and have a high signal-to-background ratio. In addition, the narrow emission bandwidth of the UCNPs enables multiplexed detections. An array-in-well immunoassay was developed using two different UC emission colours. The differentiation between different viral infections and the classification of antibody responses were achieved based on both the position and colour of the signal. The study demonstrates the potential of spectral and spatial multiplexing in the imaging based array-in-well assays.

Adopting the Vaadin Java framework to rebuild VTT’s Web Interfaces and Database Applications

With the growth in new technologies, using online tools have become an everyday lifestyle. It has a greater impact on researchers as the data obtained from various experiments needs to be analyzed and knowledge of programming has become mandatory even for pure biologists. Hence, VTT came up with a new tool, R Executables (REX) which is a web application designed to provide a graphical interface for biological data functions like Image analysis, Gene expression data analysis, plotting, disease and control studies etc., which employs R functions to provide results. REX provides a user interactive application for the biologists to directly enter the values and run the required analysis with a single click. The program processes the given data in the background and prints results rapidly. Due to growth of data and load on server, the interface has gained problems concerning time consumption, poor GUI, data storage issues, security, minimal user interactive experience and crashes with large amount of data. This thesis handles the methods by which these problems were resolved and made REX a better application for the future. The old REX was developed using Python Django and now, a new programming language, Vaadin has been implemented. Vaadin is a Java framework for developing web applications and the programming language is extremely similar to Java with new rich components. Vaadin provides better security, better speed, good and interactive interface. In this thesis, subset functionalities of REX was selected which includes IST bulk plotting and image segmentation and implemented those using Vaadin. A code of 662 lines was programmed by me which included Vaadin as the front-end handler while R language was used for back-end data retrieval, computing and plotting. The application is optimized to allow further functionalities to be migrated with ease from old REX. Future development is focused on including Hight throughput screening functions along with gene expression database handling

Metal oxides prepared through the nanocasting approach-mechanistic study, surface interactions and applications in separation

Mesoporous metal oxides are nowadays widely used in various technological applications, for instance in catalysis, biomolecular separations and drug delivery. A popular technique used to synthesize mesoporous metal oxides is the nanocasting process. Mesoporous metal oxide replicas are obtained from the impregnation of a porous template with a metal oxide precursor followed by thermal treatment and removal of the template by etching in NaOH or HF solutions. In a similar manner to the traditional casting wherein the product inherits the features of the mold, the metal oxide replicas are supposed to have an inverse structure of the starting porous template. This is however not the case, as broken or deformed particles and other structural defects have all been experienced during nanocasting experiments. Although the nanocasting technique is widely used, not all the processing steps are well understood. Questions over the fidelity of replication and morphology control are yet to be adequately answered. This work therefore attempts to answer some of these questions by elucidating the nanocasting process, pin pointing the crucial steps involved and how to harness this knowledge in making wholesome replicas which are a true replication of the starting templates. The rich surface chemistry of mesoporous metal oxides is an important reason why they are widely used in applications such as catalysis, biomolecular separation, etc. At times the surface is modified or functionalized with organic species for stability or for a particular application. In this work, nanocast metal oxides (TiO2, ZrO2 and SnO2) and SiO2 were modified with amino-containing molecules using four different approaches, namely (a) covalent bonding of 3-aminopropyltriethoxysilane (APTES), (b) adsorption of 2-aminoethyl dihydrogen phosphate (AEDP), (c) surface polymerization of aziridine and (d) adsorption of poly(ethylenimine) (PEI) through electrostatic interactions. Afterwards, the hydrolytic stability of each functionalization was investigated at pH 2 and 10 by zeta potential measurements. The modifications were successful except for the AEDP approach which was unable to produce efficient amino-modification on any of the metal oxides used. The APTES, aziridine and PEI amino-modifications were fairly stable at pH 10 for all the metal oxides tested while only AZ and PEI modified-SnO2 were stable at pH 2 after 40 h. Furthermore, the functionalized metal oxides (SiO2, Mn2O3, ZrO2 and SnO2) were packed into columns for capillary liquid chromatography (CLC) and capillary electrochromatography (CEC). Among the functionalized metal oxides, aziridinefunctionalized SiO2, (SiO2-AZ) showed good chemical stability, and was the most useful packing material in both CLC and CEC. Lastly, nanocast metal oxides were synthesized for phosphopeptide enrichment which is a technique used to enrich phosphorylated proteins in biological samples prior to mass spectrometry analysis. By using the nanocasting technique to prepare the metal oxides, the surface area was controlled within a range of 42-75 m2/g thereby enabling an objective comparison of the metal oxides. The binding characteristics of these metal oxides were compared by using samples with different levels of complexity such as synthetic peptides and cell lysates. The results show that nanocast TiO2, ZrO2, Fe2O3 and In2O3 have comparable binding characteristics. Furthermore, In2O3 which is a novel material in phosphopeptide enrichment applications performed comparably with standard TiO2 which is the benchmark for such phosphopeptide enrichment procedures. The performance of the metal oxides was explained by ranking the metal oxides according to their isoelectric points and acidity. Overall, the clarification of the nanocasting process provided in this work will aid the synthesis of metal oxides with true fidelity of replication. Also, the different applications of the metal oxides based on their surface interactions and binding characteristics show the versatility of metal oxide materials. Some of these results can form the basis from which further applications and protocols can be developed.

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).