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  • Open Access English
    Authors: 
    Tsering, Tenzin;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    Microplastics (MPs) are commonly considered pieces of plastic particles that are between 1 μm and 5 mm in size. It is an emerging contaminant and highly pervasive in different environmental compartment. Likewise, MPs have received huge attention from the scientific community, local citizens, and the media. Irrespective of drastic increases in the publications related to MPs, the data quality needs improvement. MPs studies in the remote regions of the globe are still lacking. The Indian Himalaya hosts large, glacier-fed perennial rivers and high-altitude mountainous lakes that serve the largest populated nations. Nevertheless, studies of MPs in the Indian Himalaya are scarce. In this thesis, MPs in the shore sediment of the freshwater sources including the Brahmaputra River, the Indus River, Pangong Lake, Tsomoriri Lake and Tsokar Lake were studied. Three sampling campaigns for shore sediment collection from the rivers and lakes of the Indian Himalaya were conducted during years 2018–2019. The samples of MPs were pretreated using density separation and digestion procedures. MPs within size range 20–5000 μm were detected in all the studied sites of the Brahmaputra and Indus rivers. Among the examined rivers, the highest concentration of MPs was detected in the Brahmaputra River, a concentration of 3505 MP/kg dw. In the studied remote lakes including the Pangong, Tsomoriri and Tsokar, MPs were detected within the size range 100–5000 μm. Among studied lakes, the highest concentration of MPs was detected in the Tsomoriri Lake with concentration of 3800 MP/kg dw. However, the reported MPs concentration should not be considered as an ideal value for MPs concentration in the studied area because MPs concentration varies depending upon the method of sampling, pretreatment, and analysis. Holistic understanding of MPs in freshwater sources is important. The intercomparison among MPs lacks reliability due to the lack of harmonisation of the utilised methods. Therefore, a means to move towards an understanding of the heterogeneity of MPs and the implications of different pretreatment methods on concentrations of MPs was assessed. Variation in MP concentrations was demonstrated in the lake samples by using different methods of digestion procedure including chemical degradation and/with enzymatic degradation. MPs concentration largely varies in samples pretreated with different pretreatment methods. Therefore, the study demonstrated the significance of different methods used in MPs handling on their reported concentrations and the heterogenous nature of MPs. The need for time-efficient and reliable analytical technique for MP analysis is crucial, especially for environmental samples consisting of various materials. In this context, an assessment for identification of MPs using Raman microspectroscopy was aimed particularly to minimize the analysis duration. The automatic selection features of the Raman imaging microscope were explored using spiked MPs in aquatic and solid samples. Strict contamination control measures, recovery tests and procedural blanks were utilised. The automatic particle selection features of the Raman imaging microscope significantly reduce the analysis duration compared to the pixel-based analysis. Therefore, Raman microspectroscopy has the potential to contribute to a reliable MPs identification. Nonetheless, the potential drawback of underestimation and overestimation due to the automatic selection features must be further improved in the future. Based on this thesis, it can be concluded and recommended that MPs in the Indian Himalaya require more in-depth good quality studies. Furthermore, practical steps must be taken to avoid improper disposal of waste that is the most prominent source of MPs in the studied freshwater sources. In the broader aspect of MPs research, the importance of reporting sufficient details of MPs is crucial to a reliable intercomparison of data and to be able to assess the possible impacts of pollution. The quality control and quality assurance measures are necessary for reliable MPs data. Moreover, it is recommended to report both MPs concentration with and without blank correction.

  • Open Access English
    Authors: 
    Mailagaha Kumbure, Mahinda;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    With the advancement of technology in many areas, an immense amount of data has currently become available, and discovering patterns and trends from this data is a core subject of interest in machine learning research. Machine learning, a form of artificial intelligence, provides a robust set of algorithms that iteratively learn from the data to understand and analyze data as well as predict future outcomes. The focus of this dissertation is on supervised machine learning techniques—classification and regression. In particular, the emphasis is on the fuzzy k-nearest neighbor (FKNN) algorithm that has received substantial attention in classification problems due to its efficacy and flexibility. In the context of classification, learning from data can be considered challenging for many algorithms due to uncertainties and inconsistencies in the data. In particular, a typical issue associated with most classification problems is that class distributions in the data are imbalanced—meaning that data points do not equally represent the classes in class variable, which can significantly affect classification performance. Along with class imbalance, it is apparent that a level of class overlapping, class noise, and outliers may also cause the degradation of the classifier’s performance. Given these issues, research has continued to make classification algorithms—particularly the nearest neighbor-based methods—more accurate and more competent. However, this has been a great challenge because the performance and efficiency of learning algorithms are heavily reliant on the correct choice of model features and data that often engages with many issues. In this context, this research seeks to develop solution techniques based on the FKNN algorithm, particularly for class imbalance problems. The multi-local power mean fuzzy k-nearest neighbor (MLPM-FKNN), which uses class prototype local mean vectors instead of individuals for creating memberships, is the first approach presented in this dissertation. It is demonstrated that the proposed MLPMFKNN classifier achieves better classification results than the classical methods in realworld data sets, often with high k (number of nearest neighbors chosen) values. In addition, the MLPM-FKNN classifier, in cooperation with feature selection, is applied to create a hybrid feature selection model to forecast the intraday return of the S&P index. Further, this work brings a feature selection and prediction (formed by classification) to a nexus wherein the feature selection can produce a significant impact with the help of MLPM-FKNN classification. The second approach proposed is the Bonferroni mean-based fuzzy k-nearest neighbor (BM-FKNN) classifier, which is an extension of the MLPM-FKNN method by the use of the Bonferroni mean instead of the Power mean. The findings with one artificial and six real-world data sets stress the capability and effectiveness of this method in solving class imbalance problems as compared to the original and several other competitive classifiers. The next contribution of this dissertation is a novel regression approach called the Minkowski distance-based fuzzy k-nearest neighbor regression (Md-FKNNreg) method. This is motivated by the fact that no one has investigated the ability of the FKNN method in regression settings, although it has gained broader attention in the classification context. Moreover, the principal advantage of this algorithm is that it attributes importance to the nearest neighbors using fuzzy weights considering their distances to the test instance and hence makes a more accurate prediction across a weighted average. Experimental results using real-world data show that the Md- FKNNreg outperformed the benchmark models and thus highlight its potential in terms of linear and non-linear regression problems.

  • Open Access English
    Authors: 
    Vehmaanperä, Paula;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    As the quality of raw materials decreases and legislation tightens, interest in various alternative materials has grown. For example, raw materials often contain iron as an impurity, which must be removed before the actual material can be utilized. Dissolution is a good option because it can be selective and can be used even at room temperature and in a normal atmospheric pressure. The dissolution of iron oxides has been extensively studied in individual acid systems, but a full understanding of the prevailing phenomena has not yet been achieved. In addition, dissolution in acid mixtures is a less understood phenomenon, but a two-acid system may offer advantages over a single acid system. An in-depth understanding of dissolution mechanisms and kinetics provides tools for manipulating various dissolution-based, i.e. leaching, processes. The aim of this thesis was to investigate how the addition of oxalic acid to sulphuric or nitric acid affects the dissolution kinetics, mechanisms and thermodynamics of magnetite and hematite. The work is based on solubility and kinetic experiments in different acid systems. It was hypothesised that mixing oxalic acid with sulphuric or nitric acid could accelerate dissolution. Pure synthetic magnetite and hematite were selected for this thesis in order to study the dissolution of iron. Industrial minerals often contain other impurities that can compete with iron dissolution reactions, but these substances were excluded from this thesis. The results showed that even low amounts of oxalic acid in sulphuric or nitric acid and at a higher temperature accelerated the dissolution but did not automatically lead to a higher level of solubility. The effect of temperature and acid mixtures can be preliminarily studied with special cube models. The dissolution kinetics of magnetite and hematite followed the Kabai model well throughout the extent of the reaction. The solid specific constant a of the Kabai model varied, which was not similar to the finding Kabai made. Therefore, it is suggested that the variation was due to changes in the solid phase during dissolution and that the constant is not solid-specific but is a dissolution-related constant describing changes in the dissolution mechanism. The dissolution mechanisms of magnetite and hematite in oxalic acid included theadsorption of oxalate on a solid surface, the reduction of Fe(III) to Fe(II), and finally the liberation of Fe(II) into a solution, which catalysed the rate of dissolution. In pure sulphuric acid, sulphate and bisulphate accelerated the rate of dissolution, while in nitric acid systems the rate was slowest because the dissolution occurred via a slow protonation mechanism. Dissolution mechanisms were more complex in acid mixtures, as was evidenced by the need for a more complex statistical model to describe the dissolution system compared to individual acid systems. The formation of humboldtine, Fe(II)(C2O4)∙2H2O, took place in pure oxalic acid. Density functional theory calculations (DFT) showed that the adsorption of oxalate on the surface of hematite and the reduction of Fe(III) to Fe(II) were the key steps in the formation of humboldtine. This finding can help improve practical applications where solid precipitates can be a real problem. An addition of even low amounts of sulphuric and nitric acid is sufficient to inhibit the formation of humboldtine. Another way is to gradually add oxalic acid to the system or shift the reaction to form carbon dioxide. Neither the specific surface area of BET or the oxalate and nitrate concentrations do not correlate with the dissolution mechanisms. However, the pH of the solution describedwell the dissolution degree. In addition, DFT calculations combined with experimental results provided additional information needed to visualize and rationalize the reaction steps during dissolution.

  • Open Access English
    Authors: 
    Karjunen, Hannu;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    Carbon dioxide (CO2) is an important chemical compound for life on earth, as it enables photosynthesis in plants and other organisms. It is also commonly utilized in many applications and products, such as carbonated drinks, welding gases, food preservatives, fire extinguishers, and coffee decaffeination. The concentration of carbon dioxide in the atmosphere has increased due to human activities related to the combustion of fossil fuels and other industrial activities. Because carbon dioxide contributes significantly to climate warming, its release into the atmosphere needs to be curbed in order to limit the harm done to the Earth’s ecosystem. In parallel with other climate change mitigation measures, carbon capture technologies could offer further pathways to reduce CO2 emissions. In principle, these may be divided into two subgroups: sequestration technologies and utilization concepts. Carbon capture and sequestration (CCS) aims to permanently store CO2 in underground formations and thus deny its climate warming impact. Carbon capture and utilization (CCU) instead targets different products and materials that could bind the carbon, either permanently or for a shorter time. To date, there are tens of different applications where CO2 is crucial, yet the global utilization volumes are still modest compared to what they are estimated to be in the future. This dissertation evaluates the challenges and opportunities related to CCU, focusing on fuels and chemicals due to their large utilization potential. The work addresses the volume and geographic availability of CO2 sources in Finland and presents possible scenarios for future CO2 utilization. Main infrastructural challenges and options related to the transportation and storage of CO2 are also evaluated. Dynamic simulations of different plant configurations and operation strategies are used to analyse system performance and to identify possible links to heat and power systems. Integration of CCU into a pulp mill is studied as an example case to evaluate the economical profitability of CO2 utilization. The analysis confirms that CCU holds great opportunities for reducing emissions and producing massive amounts of hydrocarbon products. Finland and Sweden both have exceptional volumes of biogenic CO2 available, to the extent that available electricity will be limiting the conversion processes. These feedstock challenges could partly be alleviated by significant investments into infrastructure development, which would level the resource discrepancies between regions. Challenges relating to CO2 transport, even in large volumes, are primarily related to legislation rather than technology. Dynamic operation of the production plants presents additional challenges, so intelligently designed buffer storage and flexible operation strategies could enable significant cost reductions. Residual heat from electrolysers and synthesis processes could be utilized to increase efficiency and profits, but the risk of local oversupply situations is also evident. Renewable premiums and other support systems for CCU are likely necessary in the short term to enable the forming of a mature market for CO2 and products derived from it.

  • Open Access English
    Authors: 
    Afkhami, Shahriar;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    Additive manufacturing has evolved over the last few decades from utilising a prototyping approach to favouring a fabrication method. Consequently, this technology has become recognised as a potential replacement for traditional fabrication methods employed in the processing of metals, polymers, and biomaterials. In particular, the additive manufacturing of metals can play a significant role in the future of manufacturing due to its capabilities for sustainable production and reducing material waste when compared to conventional methods. However, the additive manufacturing of metals has yet to reach its full potential due to technological drawbacks. Although laser powder-bed fusion technique is one of the most frequently used methods for metal additive manufacturing, the metallic components fabricated still suffer from associated inhomogeneities and weak points. Further research is needed, therefore, to identify factors causing these disadvantages. Acquiring this knowledge is necessary for expanding the applicability of metal additive manufacturing throughout contemporary industry and construction. On this basis, different aspects of the additive manufacturing of steel – one of the most economical alloy types – have been investigated in this research. This involved examining the microstructures and mechanical properties of two common types of steel – stainless steel 316L and tool steel 18Ni300 – in order to identify some of the effective parameters affecting their properties. Results show that the steels processed by laser powder-bed fusion suffer from the microstructural features associated with the intense thermal gradients present within manufacturing methods, e.g. segregation and cellular/dendritic subgrain structures. Nevertheless, mechanical properties were comparable to those of their conventional counterparts. Furthermore, parameters related to the manufacturing method, building orientation and surface quality were found to have a determining role in influencing the mechanical properties as material characteristics. This leads to the observation that an inappropriate building direction or surface quality can result in inferior mechanical performance. The interactions between external loads, geometrical notches, inherent defects, and surface features were investigated in 18Ni300 and processed by laser powder-bed fusion. The results showed that notch strengthening under uniaxial quasi-static loads is common in this ductile steel. However, the existence of geometrical notches reduced the specimens’ fatigue performance. Finally, the applicabilities of numerical/analytical approaches such as the Hall–Petch model, Ludwigson equation, Solberg–Berto equations, and Murakami approach were also evaluated for the investigated materials. These models and equations showed relatively good agreement with the experimental results in some cases but, on other occasions, required recalibration or modification to become suitable for metals processed by additive manufacturing.

  • Open Access English
    Authors: 
    Aghajanian, Soheil;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    Currently, a broad spectrum of decarbonisation efforts are ongoing in fundamental areas of human lifestyle to mitigate the global concerns materialising from climate-related transformations. Within the framework of carbon capture, utilisation, and storage (CCUS), the present study investigated the integration of two separation processes, namely, carbon dioxide (CO2) capture and the reactive crystallisation of calcium carbonate (CaCO3). In this work, aqueous sodium hydroxide solution was used for CO2 absorption. The scalable and economically feasible production route of micron-sized CaCO3 occurs by the direct addition of the CO2-loaded liquid solution to a crystalliser containing aqueous calcium chloride. The coupled processes eliminate the demand for high-temperature regeneration and promote high product purity. From the CO2 capture perspective, small-scale demonstration experiments were scaled-up by utilising a hollow fibre membrane contactor–based CO2 capture system developed in-house. The overall mass transfer enhancement due to reaction was investigated. The fast kinetic reactive crystallisation process was studied at two different scales and a range of operating conditions by utilising multiple process analytical tools. The employed image analysis–based in-line digital microscope camera provided real-time crystal size data and images from the crystal suspension. The in-line probe was utilised to develop an agitation–based feedback control for the CaCO3 precipitation process. The real-time control scheme influences the crystal formation process by manipulating the energy dissipation and spatial supersaturation distribution of the stirred tank reactor. The investigation provided preliminary insights into the challenges of real-time micron-sized reactive crystallisation measurement and control. A first of its kind framework was proposed to develop a real-time process fault detection and diagnostics utilising 1D electrical resistance tomography (ERT) measurements. The most sensitive measurement point was experimentally justified as a data transmitter position for process diagnostics. In parallel to the ERT, the application of a novel ultrasound tomography (UST) system was investigated in the reactive crystallisation process. The bulk crystal concentration and the reagent feeding region were successfully visualised using ultrasound tomographic reconstructions. Computational fluid dynamics (CFD) was used to perform 3D simulations of the mixing hydrodynamic and to visualise the spatio-temporal distribution of the chemical reaction in the stirred tank reactor. The experimentally validated CFD simulations deliver a framework that can be employed as a virtual tomography tool in parallel with ERT and UST measurements. The main idea was to directly utilise the crystal size distribution data of the small-scale experiments for model development. The empirical modelling approach inherently contains the effects of the operating conditions and the kinetics of the precipitation and uses less computational resources by reducing the design parameters.

  • Open Access English
    Authors: 
    Rumky, Jannatul;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    Wastewater sludge requires effective dewatering, lower metal content, retention of nutrients, and biological stability prior to use for other applications. This thesis presents a comprehensive sludge treatment study by chemical and electrochemical processes to develop alternative scope for sludge usage. Firstly, Fenton-ultrasonication was applied to treat anaerobically digested sludge (ADS) by optimizing three process variables (Fe2+, H2O2, and sonication time). 36 mM of Fe2+, 320 mM H2O2 with 30 min of sonication showed the best performance for total organic carbon (TOC), extracellular polymeric substances (EPS), and heavy metals. Secondly, pressure-driven electro-dewatering (EDW) was assessed by a lab-scale device 5, 15, and 25V. After EDW, dry solid content increased up to 56%, and EDW did not show remarkable effects on heavy metals and E.coli quantification. Thirdly, the effect of inorganic coagulant PTS combined with organic Ce-CTA was investigated on EPS, heavy metals, and nutrient contents in ADS at different levels of pH. pH 3 and 9 showed promising results after coagulation-flocculation and suggested the production of various sludge-based materials (adsorbents, catalysts, building materials, etc.). Finally, sludge beads were prepared for recovery of rare earth elements (REEs) from aqueous effluents. Among the REEs studied, Fenton and hydrochloric acid-treated sludge beads demonstrated a higher affinity towards Sc3+ and Sm3+ ions, displaying the maximum adsorption capacities of 2.80 to2.83 mg/g and 4.03 to 4.16 mg/g. To perform an economic evaluation of Fenton and electro-dewatering systems, chemical costs and required energy were calculated and the electrochemical system found them to be more appropriate for sludge treatment than Fenton.

  • Open Access English
    Authors: 
    Molinari, Andrea;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    This research focuses on re-designing the architecture of a Learning Management System (LMS) to facilitate and increase its usage inside an information system and achieve a more profound and better integration. LMSs offer many valuable services in various educational contexts. However, most of these services are typically inefficiently used because they are primarily redundant within other functionalities of an LMS or with services provided by other information systems. Services such as file sharing, forums, blogs, polling, voting, videoconferencing are often available within LMSs, but modern organizations also have access to these services via other systems. This thesis shows that with a deep re-design of the software architecture, LMSs can have broader application opportunities than only the educational setting and can be competitive compared to similar services provided in other formats. This thesis has followed two main research lines formulated as questions: a) how to intervene in an LMS’s architecture and functionalities to create a more generalized, collaborative environment not only devoted to the educational setting; b) how to facilitate the integration of LMSs into corporate information systems, while avoiding duplication of services for end-users and improving their Total Cost of Ownership (TCO). A central issue of this thesis has been identifying what these duplication and integration problems are based on. We observe that a central problem is found in the core architectural concepts of an LMS, the foundational metaphor underlying these platforms: LMS’s intimate structure is based on concepts such as “class”, “course”, “student”, and “teacher”. These concepts relate strictly to education, thus preventing LMSs from being used in a conceptually native way outside these contexts. Indeed, these concepts are unsuitable for collaborative settings, such as a meeting, a research group, a recreational community, a conference, a community of evaluators, a secretariat, a labor union association, etc. We cannot manage a research group the same way as a “class”, or assign the head of the research group to the role of a “teacher”. We should consider a research group as a community that uses digital services to support its activities, i.e., a virtual community. In this vein, this dissertation aims to demonstrate how a re-design of an LMS architecture around this thinking can potentially solve and improve the possibilities for an LMS to become central within modern information systems. Here the envisioned re-design places the concept of “virtual community” at the center of the architecture of the platform, replacing current concepts like "class" or "course". This novel approach represents a radical change to the internal architecture of an LMS, from the design of classes used in the code, to the persistence layer, to the services provided to the end-user. We could even talk about a new category of software platforms, i.e., a “Virtual Community Management System” or simply “Community Management Systems”, not to be confused with social media platforms. These systems provide their users with different services oriented toward education, communication, collaboration, multimedia management, videoconferencing, file sharing, project management, support to decision processes, time management, lifelong learning services etc. This thesis presents insights into the internal architectural changes of an LMS, the consequent new services developed, and how these changes can facilitate the integration of the new design for an LMS inside the information system stack of an organization. As a real-world test of the envisioned changes and as a partial validation for the applicability of the notions presented, artifacts created in the form of (primary) services within a software platform named “Online Communities” and the transformation of the platform to a virtual community are presented. The platform has been (re)designed according to the paradigmatic shift presented in this thesis. We also consider this re-design process successful because public and private organizations have adopted the platform. The platform has also enabled numerous fundraising activities, generating a spin-off company for the commercialization of the platform. The role of the author in this design process has initially been that of a designer, software architect, and partially software developer. During the process, due to the possible implications of the practical activities undertaken and the number of experiences collected, our role has become that of an external researcher looking at the phenomenon from the outside, and action researcher looking at the artifact creation from the inside.

  • Open Access English
    Authors: 
    Sousa de Sena, Arthur;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    Multiple-input multiple-output (MIMO) is an indispensable technology for deploying the pervasive connectivity sought for fifth-generation (5G) and beyond communication systems. By relying on a large number of antennas, massive MIMO schemes can implement space division multiple access (SDMA) to serve spatially separated users with a single frequency–time resource block, thus, leading to incredible spectral and latency enhancements. Nevertheless, there are certain communication scenarios, such as ultradense deployments or environments with users sharing overlapping angular positions, where spatial multiplexing becomes unrealizable through SDMA alone. These challenging scenarios motivate the exploitation of different domains and technologies. In particular, power-domain non-orthogonal multiple access (NOMA) and rate-splitting multiple access (RSMA) have appeared as strong candidates for extending the capabilities of MIMO systems and enabling resource-efficient simultaneous transmissions even to overlapping users. In parallel development, a disruptive concept of an intelligent reflecting surface (IRS) has arisen as a method to manipulate electromagnetic propagation through reconfigurable, low-power, subwavelength reflecting elements. As their main feature, the properties of IRSs can be dynamically tuned and harnessed to attack harsh phenomena of wireless channels and accomplish diverse objectives, enabling communication environments with optimized signal radiation. Driven by the promising capabilities of the above-mentioned technologies, this doctoral dissertation focuses on studying and developing novel transmission schemes based on the synergy between NOMA, RSMA, and IRSs, and their application to next-generation multiuser MIMO communication networks. This research work starts by investigating practical issues of imperfect successive interference cancellation (SIC) on a downlink multicluster massive MIMO-NOMA network. Through an in-depth theoretical analysis, exact closed-form expressions are derived for the outage probability and ergodic rates observed by each user. By exploiting the Karush– Kuhn–Tucker conditions, efficient dynamic power allocation strategies are also implemented for improving rate fairness within each cluster in the network. Motivated by the performance limitations identified in our seminal investigations, our research is continued on the MIMO-NOMA topic by exploiting the powerful capabilities of IRSs to tackle the interference issues of SIC. To broaden our optimization opportunities, a novel disruptive dual-polarized IRS is proposed to harness the additional degree of freedom offered by the polarization domain. By manipulating wave polarization with these promising IRSs through interior-point and conditional gradient methods, advanced dual-polarized transmission strategies are implemented, which can effectively mitigate SIC-related problems and remarkably improve the data rates of all users, both in the downlink and uplink of dual-polarized MIMO-NOMA networks. Among our contributions for the downlink, besides optimizing the IRS reflecting elements, a closed-form expression is derived for the ergodic rates considering large IRSs, whereas for the uplink, also a low-complexity alternate power allocation policy is proposed for balancing uplink data rates. Next, motivated by the impressive broader region of achievable rates possible with RSMA, this research is advanced and the advantages of the amalgamation between IRSs and MIMO-RSMA are investigated, showing that SIC issues can also degrade the performance of RSMA-based schemes. To solve the limitations introduced with SIC once and for all, in our last results, a novel high-performance dual-polarized massive MIMORSMA scheme is proposed that does not require SIC, thereby eliminating all associated problems. As a practical tool for assisting the design of the proposed system, a deep neural network (DNN) model is implemented for predicting the ergodic sum-rates observed in the network with high accuracy. Last, an intelligent DNN-aided adaptive power allocation strategy is developed, which maximizes the sum-rate of the dual-polarized MIMO-RSMA even under high levels of cross-polar interference and imperfect channel state information. Our contributions and all novel transmission schemes proposed in this doctoral dissertation are supported with extensive simulation results and fair performance comparisons with state-of-the-art baseline communication systems.

  • Open Access English
    Authors: 
    Lipiäinen, Satu;
    Publisher: Lappeenranta-Lahti University of Technology LUT
    Country: Finland

    The forest industry has increased its energy efficiency substantially in the 21st century, but higher improvement rates could be expected regarding targets set by the European Union and the Intergovernmental Panel on Climate Change. A variety of factors, i.e. technology development, structural changes and climate policies can drive energy efficiency improvement and decarbonization. This thesis looks how the Finnish and Swedish forest industries are developing towards energy efficient and low-carbon operation and evaluates the role of the sector in mitigating global change. These countries have long been forerunners in efficient operation and the decarbonization of the sector. The dependency on fossil fuels has decreased in the forest industry as energy efficiency has improved and fossil fuel use has been switching to biofuels. Potential opportunities to reduce CO2 emissions substantially exist: the Finnish and Swedish pulp mills have managed to operate lime kilns using a wide range of biofuels and their recovery boilers have been developed to produce significantly more renewable electricity and heat. New operating modes such as polysulphide cooking seem to provide a cost-effective way to produce pulp with higher material efficiency, but new solutions often cause changes in energy consumption and production. Structural changes, for example start-ups and closures of mills, have had a limited effect on energy efficiency improvement, which highlights the importance of maintaining efficient operation in existing mills. The forest industry can play a significant role in mitigating global change. The production of bioenergy and biofuels can be increased, notable energy savings can be expected and at least in comparison to other industrial sectors, the forest industry has good premises to achieve net zero industrial emissions before 2050. However, even though the forest industry has developed towards more sustainable operation and feasible technologies for improvement exist, the pace of evolution is slow in light of the urgent targets to mitigate global warming. The forest industry is the fourth largest industrial energy user and the fifth largest fossil CO2 emitter in the world. Investment cycles are long in the forest industry, and 2050 is only one cycle away. Thus, more research and political guidance are needed immediately to accelerate the evolution worldwide.

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