[diss] Insinööritieteiden korkeakoulu / ENG

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    Numerical modeling of thermal stratification driven combustion regimes
    (Aalto University, 2024) Shahanaghi, Ali; Kaario, Ossi, Prof., Aalto University, Department of Mechanical Engineering, Finland; Karimkashi Arani, Shervin, Dr., Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Energy Conversion and Systems Research Group; Insinööritieteiden korkeakoulu; School of Engineering; Vuorinen, Ville, Prof., Aalto University, Department of Mechanical Engineering, Finland
    This dissertation is related to the research areas of computational physics and chemistry. The purpose of the study is to determine the role of temperature stratification in the secondary combustion of gasoline surrogates within the end-gas of spark ignition (SI) engines. Specifically, it highlights the influence of the Negative Temperature Coefficient (NTC) on the prevalence of various combustion regimes, including spontaneous, subsonic, and supersonic ignition, detonation, and deflagration (flame), within one and two-dimensional (1D/2D) scenarios. Gaining a deeper understanding of these phenomena facilitates understanding of the interaction between pressure oscillations, reaction front propagation, and fuel chemistry at SI engine-relevant conditions. Computational fluid dynamics (CFD) simulations of reacting flows, incorporating finite rate chemistry, efficient simulation methods, and high-performance computing, enable the investigation of the underlying physical and chemical processes in such reacting flows. This dissertation consists of three appended journal publications and their brief summary. In Publication I, a diagnostic approach distinguishes between secondary spontaneous ignition and flame of primary reference fuel (PRF) and PRF-ethanol (PRF-E) blends, in 1D setups. In Publication II, established 1D regime diagrams (detonation peninsula) are reconstructed for the PRF and PRF-E mixtures analyzing induced pressure levels from hotspot ignition (i.e. subsonic/supersonic ignition, and detonation modes). In Publication III, 2D phenomena are explored involving converging shock/detonation fronts and shockwave reflection-induced detonation, using the novel ARCFoam numerical framework. In essence, Publication I explores the prevalence of combustion modes at two extremes within the range of studied modes, namely flame and spontaneous ignition in a 1D setting. Publication II focuses on the pressure oscillations induced by hotspot ignition regimes within the 1D framework. Lastly, in Publication III, further geometrical considerations are introduced by investigation of hotspot ignition in 2D scenarios. The main conclusions of this dissertation are as follows: 1) NTC chemistry of the studied fuels is the dominant factor in manipulating the reactivity, inducing secondary combustion modes, and amplified pressure levels. 2) Given the dominance of auto-ignition in the presence of NTC and the impact of thermal stratification on ignition characteristics, density-based 1D/2D CFD simulations are preferred for analyzing underlying combustion regimes. 3) While the detonation peninsula predicts the initial ignition regime induced by hotspot ignition, NTC chemistry and 2D effects such as front curvature and shock reflection can significantly alter combustion dynamics. 4) Apart from the complexity of the flow field and the employed numerical techniques, the resourceintensive nature of finite rate chemistry solution remains the primary bottleneck in such reactive CFD simulations.
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    Drought in Water Abundant Finland - Data and Tools for Drought Management
    (Aalto University, 2024) Ahopelto, Lauri; Veijalainen, Noora, Dr., Finnish Environment Institute, Finland; Professor Varis, Olli, Prof., Aalto University, Department of Built Environment, Finland; Rakennetun ympäristön laitos; Department of Built Environment; Water and Development Research Group; Insinööritieteiden korkeakoulu; School of Engineering; Keskinen, Marko, Prof., Aalto University, Department of Built Environment, Finland
    Droughts pose a risk to all societies, even those with abundant water resources. Climate change will affect this risk, and societies should adapt accordingly. Though Finland has a low drought risk, recent droughts have had a clear impact, especially on agriculture and water supply, but also forestry, hydropower, and ecosystems. While Finland's water governance and water security are generally at a good level, drought has so far gained little attention and operative drought management plans and strategies are absent. This dissertation studies drought risks in Finland and provides recommendations on how to improve drought management. Drought risk can generally be understood as a combination of three factors: vulnerability, exposure, and hazard. Several drought indices, models, and weather data generation are used in the dissertation to better understand drought hazard and to quantify drought frequency, severity, and other characteristics of drought events in Finland. The dissertation also considers how drought hazard might change due to climate change. The results are discussed in relation to different sectors and within the broader water governance context in Finland. The results from the drought index analyses provide detailed information on drought characteristics in Finland. The findings show that choosing the best drought indices for different contexts is difficult, emphasizing the need to use several indices. For the Sirppujoki basin case study (a river basin in southwestern Finland), 2o different standardized drought indices were calculated for two drought events of 2002–2003 and 2018 as well as for the years 2040–2069. In addition, weather data generation coupled with hydrological modeling was tested for the basin. This dissertation reveals that drought risks will likely increase due to climate change, predominantly in the south and southwest Finland. Based on evapo-transpiration-dependent indices, drought events are predicted to increase especially during the growing season. This is particularly worrying for the agricultural sector, since only a few percent of fields have irrigation systems. However, the climate scenarios have a large variation, emphasizing the need for more research as well as flexible climate change adaptation. To address the growing drought risk in Finland, adaptation measures against drought impacts are suggested. A national drought strategy, together with bot-tom-up drought management plans, would mitigate the increasing drought risks. These should be accompanied with a systematic drought management process with an early warning system.
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    Utilization of short-term thermal energy storage for demand response and peak power reduction in district-heated buildings
    (Aalto University, 2024) Ju, Yuchen; Jokisalo, Juha, Senior Scientist, Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; HVAC Technology; Insinööritieteiden korkeakoulu; School of Engineering; Kosonen, Risto, Prof., Aalto University, Department of Mechanical Engineering, Finland
    The European Commission has set ambitious targets to cut at least 55% of greenhouse gas emissions from 1990 levels by 2030 and to realize carbon neutrality by 2050. In 2020, space heating consumed 28% of the total energy consumption in Germany while only 18% was produced by renewable sources. In Finland, district heating is the most common source of space heating. In 2020, it covered 45% of the market share of space heating for residential, commercial, and public buildings. Therefore, decarbonization strategies should be developed for district heating systems and the connected buildings. When renewable energies are utilized more in production, there is the demand to enhance the smart readiness of buildings. Demand side management is an approach to adjusting consumer energy use and power demand according to the production pattern. By utilizing short-term thermal energy storage, such as building thermal mass and thermal energy storage tanks, energy flexible strategies could be applied to buildings and their energy systems for peak power cutting and load shifting. This thesis investigated energy flexibility and the benefits of demand response based on dynamic district heat prices of space heating and a thermal storage tank for district-heated buildings. The meaning of building-level rule-based demand response control strategies on district heating production was also analyzed in the thesis. There were three different production scenarios. The first scenario utilized a biofuel CHP as the basic source and three gas boilers for backup. The second one had a biofuel CHP and a green-electricity heat pump as the basic source and two gas boilers as backup. The last one included a heat pump as the basic unit and an electric heater as backup used grid electricity. In addition, strategies were also developed for peak shaving and peak power limiting with a 5 m3 short-term thermal storage tank. Demand response of space heating cuts up to 9.6% of heating costs for building owners. The demand response control of the storage tank decreases the district heat energy cost by 3.4%. When employing the demand response control of space heating and the storage tank, it gains 12.8% of district heat energy cost savings. In addition, thermal energy storage provides the potential for peak shaving and peak power limiting. It reflects a higher peak shaving potential for colder days with a 31.5% maximum peak power decrease of a Finnish office building. The maximum heating power is limited by 43% and the power fee reduces by 41.2% without compromising room air and ventilation supply air temperatures. The large-scale demand response application decreases the total district heating demand from 3.6% to 3.9% with higher financial benefits and less CO2 emissions. Moreover, it increases the full load operation hours of renewable energy generation units, reducing emissions. Therefore, demand response effectively decreases fossil fuel usage and improves the energy resiliency of district heating systems.
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    Supporting agency for sustainability - Exploring the contributions of universities and workplaces to the sustainability competencies and agency of engineering graduates
    (Aalto University, 2024) Karvinen, Meeri; Rakennetun ympäristön laitos; Department of Built Environment; Water and Environmental Engineering; Insinööritieteiden korkeakoulu; School of Engineering; Keskinen, Marko, Ass. Prof., Aalto University, Department of Built Environment, Finland
    The societal sustainability transformation requires actions from all organizations. University graduates have the opportunity to catalyze the transformation already in the early career, provided they have adequate competencies from the education, and the workplaces ensure sufficient opportunities to influence. Particularly engineering graduates play a significant role through a solution-oriented approach. This dissertation investigates how universities support graduates in developing the required competencies and agency for sustainability using Nordic universities and the water and environmental engineering field in Finland as case examples. The thesis combines three research contexts, sustainability in higher education, engineering education and transition to working life, which together create a unique, broad theoretical framework for the explorations. The study utilizes surveys, interviews, and workshops to focus on the integration of sustainability in university operations, on the competencies needed for the early career ('employability') and for promoting sustainability, and on graduate role and agency in the workplaces. The findings show that sustainability is generally considered as important. The employers are also satisfied with graduate contributions. However, Nordic universities could take a stronger 'whole university approach' in integrating sustainability to better support graduate sustainability agency. Supporting teachers in sustainability education revealed to need particular emphasis. In engineering, employability competencies are prioritized over sustainability. In promoting sustainability, graduates are expected to take a knowledgeable, independent, even transgressive role. While they do bring new insights and 'green' values, the graduates have challenges to connect their work to sustainability and they feel lacking power to influence. A hybrid graduate competency profile is suggested that promotes both employability and sustainability competencies: substance knowledge, key sustainability competencies, and sustainability knowledge. Followingly, this dissertation encourages engineering educators to explore new pedagogical approaches that particularly develop the personal dispositions and agency of students and facilitate framing own work to a sustainability context. It further highlights the role of universities in supporting the teachers and workplaces in supporting the graduates. In addition, collaborative agency for sustainability among the graduates, workplaces and education is encouraged, as intensified collaboration around sustainability can clarify the role of the graduates in catalyzing the sustainability transformation in workplaces. It can also encourage teachers to try new approaches for teaching sustainability, students to develop adequate competencies, and workplaces to create practices that support graduates in contributing to sustainability.
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    Evaluation of Hydrogen Embrittlement Effect on Mechanical Strength of Modern Martensitic High-Strength Steels - Experimental Analysis and Artificial Neural Network-based Prediction
    (Aalto University, 2024) Fangnon, Eric A. K.; Malitckii, Evgenii, Dr., Aalto University, Department of Mechanical Engineering, Finland; Yagodzinskyy, Yuriy, Dr., Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Materials to Products; Insinööritieteiden korkeakoulu; School of Engineering; Vilaça, Pedro, Prof., Aalto University, Department of Mechanical Engineering, Finland
    Hydrogen embrittlement (HE) is a challenge affecting several engineering materials, with a significant impact on steels, targeting critical components in high-value industrial applications. To better understand the HE phenomenon and its impact on the mechanical performance of newly developed martensitic steels, this dissertation focuses on the following three key issues: (i) enhancement of experimental conditions for the accurate measurement of hydrogen concentration (CH) in metalic materials, (ii) assessment of the mechanical strength of steels under different hydrogenation and mechanical loading conditions, and (iii) a new artificial neural network (ANN)-based tool, applied initially to investigate the relationship between the hydrogen thermal desorption spectroscopy (TDS) and steel's susceptibility to H-induced damage, is further developed to predict the relation between CH and mechanical strength at failure, with reduced requisite experimental testing. A specimen cooling system was developed and integrated with the air-lock in a TDS apparatus with the objective of enhancing the accuracy of CH measurements in the studied steels. The application of the new specimen cooling system, enabling temperatures down to 213˚K, proved to provide a significant improvement in CH measurement, allowing more accurate analysis of obtained thermal desorption spectra, valuable for H-trapping analysis. The H-uptake and mechanical performance of four martensitic steel grades with varying prior austenite grain (PAG) morphology were studied by monotonic uniaxial tensile testing and TDS in different H-charging conditions. The results demonstrate that the H-uptake under the same Hcharging conditions, without external mechanical loading, does not vary between the steels. However, a variation in H-uptake was evident with external mechanical loading. This variation does not directly depend on, or correlate with the different PAG morphology. Furthermore, the results showed that CH in the steel has a greater influence on the H-enhanced creep rates leading to failure, than the magnitude of the applied loads, during constant load mechanical testing conditions. The developed dense ANN tools, encompassing three different models, were evaluated for the prediction of steel's susceptibility to HE and CH responsible for the H-induced failure with an approximate accuracy of about 98%. Enhancing the ANN models with training data may yield a powerful tool for the HE characterization of steels. This can be done with a reduced dependency on time-consuming experimental testing with hazardous and complex apparatus.
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    Out of the WASH box – Towards a wider contextualization of the water, sanitation, and hygiene sector
    (Aalto University, 2024) Juvakoski, Anni; Vahala, Riku, Dr., Finnish Water Utilities Association, Finland; Levchuk Golubtsova, Irina, Dr., University of Eastern Finland, Finland; Rakennetun ympäristön laitos; Department of Built Environment; Water and Environmental Engineering; Insinööritieteiden korkeakoulu; School of Engineering; Varis, Olli, Distinguished Prof., Aalto University, Deparment of Built Environment, Finland
    Water, sanitation, and hygiene (WASH) have perennially been recognized as a key approach to improved health in low-income areas. Whereas water sector proponents tend to emphasize it as the key approach, there are many other factors that are important and deeply interwoven with WASH. This interdisciplinary dissertation revisits this premise by attempting to provide "out-of-the-box" insight the water sector has been calling for with four contrasting studies. To generate such novel insight, we have expanded the WASH context to uncharted territory (impacts on mental health – Paper II, and functionality in new climates – Paper III). Additionally, we have turned WASH actors that are commonly research subjects (WASH professionals – Paper IV, and municipalities – Paper I) into research objects. In practice, the role of WASH was scrutinized with tools of quantitative analysis (Paper I), psychology frameworks (Paper II), empirical microbiology (Paper III), and qualitative interview analysis (Paper IV). Based on our results, the traditional thinking of the water field that adequate drinking water is the most essential need of people may be somewhat insufficient. We showed how waste management may be more strongly associated with severe diarrhea in the context of Brazil (Paper I). Moreover, if overall health equals "physical, mental, and social well-being" as defined by the WHO ever since 1948, then mental health impacts of suboptimal WASH also require attention. We found this to be essential in Paper II, especially in terms of drinking water service inequalities. Considering WASH in new contexts is also an important way to help improve health globally. The Russian full-scale war in Ukraine has made frugal point-of-use water treatment in Europe more relevant than in decades. In Paper III, we discovered that one of the most inexpensive drinking water treatment methods around, solar drinking water disinfection (SODIS), also works in cold climates and is hence a potential method for places such as Ukraine. Finally, we found that the unresearched views of WASH practitioners and innovators play significant roles in determining which WASH methods are used at a local level (Paper IV). In short, this dissertation showed how improving health especially in low- and middle-income areas would benefit from contextualizing WASH more widely than before and managing other equally important housing-related factors alongside it.
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    Renewable fuels for compression ignition engines in various transport modes: effect of fuel properties on end-use performance
    (Aalto University, 2024) Wojcieszyk, Michał; Kaario, Ossi, Prof., Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Research Group of Energy Conversion; Insinööritieteiden korkeakoulu; School of Engineering; Larmi, Martti, Prof., Aalto University, Department of Mechanical Engineering, Finland
    This doctoral dissertation belongs to the field of energy technology and focuses on the system level analysis of renewable liquid fuels for transportation purposes. Light-duty, heavy-duty and marine segments were in the scope of the study while compression ignition (CI) engine technology was the common powertrain. Based on statistical methods, the research linked engine performance with fuel properties, which has not been demonstrated yet. In this approach, data-driven black box modeling exploiting the multilinear regression method together with significance analysis and validations was successfully applied. The dissertation consists of four publications in peer-reviewed journals. Publication I concentrates on passenger cars and renewable drop-in fuels like hydrotreated vegetable oil (HVO) and traditional biodiesel (FAME). The experimental results from driving cycle test procedures are utilized in the model development. As an outcome, volumetric fuel consumption and carbon dioxide (CO2) emissions are predicted for light-duty fleet based exclusively on lower heating value, cetane number and density. In Publication II, the performance of heavy-duty vehicles is analyzed and predicted for various neat alternative fuels and their blends with fossil diesel. Simulations for new blending components are executed using heating value, density and cetane number. Publication III focuses on marine transport and suggests a model capable of predicting CO2 emissions from a medium-speed marine CI engine based on heating value, density and viscosity turned out to be significant properties. In Publication IV, the end-use challenges for the deployment of renewable fuels in the market are discussed and recommended interventions suggested. The novel approach presented in this doctoral dissertation enabled to link fuel properties with engine performance indicators like fuel consumption and tailpipe CO2 emissions. Three state-of-the-art models with high accuracy (coefficient of determination over 0.9 and all p-values below 0.05) were demonstrated in Publications I-III. The results from the modeling work represent the collective effect of fuel properties on end-use performance from the fleet perspective. Furthermore, all four publications support the deployment of renewable fuels in transportation by providing relevant modeling tools (Publications I-III) and recommendations (Publication IV) to decision makers. The outcomes of the dissertation serve for an unbiased comparison of the most promising fuel options that could be fitted to the existing infrastructure with minimum effort.
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    Understanding ice fracture using Digital Image Correlation - From microstructural crack arrest to comparison with the visco-elastic fictitious crack model
    (Aalto University, 2024) Ahmad, Waqas; Bossuyt, Sven, Prof., Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Marine and Arctic Technology; Insinööritieteiden korkeakoulu; School of Engineering; Tuhkuri, Jukka, Prof., Aalto University, Department of Mechanical Engineering, Finland
    Different parameters influence the fracture of ice. These include variation in microstructure of ice and experimental conditions such as loading rate and temperature etc. Conventionally fracture of ice has been studied using linear variable differential transducers (LVDTs) and lasers to record deformation and acoustic emissions to study the propagation of cracks in ice. This thesis discusses the use of Digital Image Correlation (DIC) in ice fracture mechanics to achieve higher spatial resolution and study the influence of the grains on a propagating crack. Analysis of S2 saline and freshwater ice experiments was done by developing a DIC postprocessing method that used cross-correlation of the Heaviside function to find a propagating crack tip. Moreover, a quantitative method was developed to find the size of the deformation zone ahead of the crack by using the decrease in the stiffness (slope of the force-COD plot) as a measure of deformation near the initial crack tip. Saline ice fracture experiment were conducted using load-control configuration. The thin section analysis coupled with crack propagation history obtained from DIC showed that the microstructure influenced the crack arrest events. Moreover, along with intermittent crack growth, localized stable crack growth was observed from the full field data which was also linked with the microstructure. Crack growth was intergranular during stable crack growth while transgranular growth was observed during unstable propagation. The upper bound of the fracture process zone (FPZ) ahead of the crack tip was also measured for floating freshwater ice experiments. This deformation zone (DZ) included both the permanent deformations in the FPZ and the elastic deformations. Comparison of the measured results with the visco-elastic fictitious crack model (VFCM) showed that the estimated FPZ size from VFCM depends on the nature of crack growth. The model overestimated the size of the FPZ if the specimen failed without intermittent crack growth. The specimens that failed with intermittent crack growth resulted in similar magnitude of lengths for the FPZ and DZ. However, VFCM underestimated the width of the FPZ compared to the critical crack opening displacement measured from DIC. Lastly, the accuracy of the calculated FPZ size using VFCM was found to be dependent on the accuracy of the crack tip opening displacement (CTOD). 
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    Performance of modern mechanical and natural ventilation systems in apartment buildings under a changing Nordic climate
    (Aalto University, 2024) Kravchenko, Ilia; Kilpeläinen, Simo, PhD., Aalto university, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; HVAC Team; Insinööritieteiden korkeakoulu; School of Engineering; Kosonen, Risto, Prof., Aalto university, Department of Mechanical Engineering, Finland
    Ventilation systems in new buildings and retrofitted ventilation systems in old buildings in Finland are designed to consistently provide a high level of indoor environment along with high energy efficiency. New buildings are implemented with balanced mechanical ventilation with kitchen boosting, which requires precise control of supply and exhaust airflows to preserve balance. Retrofitted buildings are equipped with self-regulating inlet devices to mitigate the natural ventilation dependency on outdoor conditions. The main objective of the study is to investigate the performance of these modern ventilation systems of apartment buildings in various operational conditions, such as occupant behaviour, possible maintenance shortages, microbial pollution resistance and urban microenvironment under changing climate. The performance analysis of the mechanical ventilation in the new buildings showed a significant imbalance between the supply and exhaust airflows during boosting conditions so buildings with high airtightness might encounter significant pressure difference over the envelope. Additionally, analysis of intermittent and continuous nighttime mechanical ventilation long-term operation under humid and cold with microbial pollution showed the extinction of colonies by the end of the experiment regardless of the chosen strategy. The performance analysis of a retrofitted apartment building with natural ventilation showed a significant effect of occupant behaviour, poor maintenance and the possibility of opening windows on the CO2 concentration besides the effect of outdoor conditions. The apartments on higher floors showed high levels of CO2 and risk for overheating, and small apartments tend to overheat more despite a higher air change rate. Improving the envelope airtightness does not benefit the indoor air quality. The effect of urban microenvironment parameters on the performance of large building stock was assessed to understand its ability to mitigate overheating during heatwaves. The most substantial influence of the urban microenvironment was observed during short heatwaves. The leading factors of indoor temperature decrement were low sea distance and high levels of greenery around buildings. The influence of urban microenvironment factors during the long midsummer heatwave was lower, but the green view index showed the most consistent temperature-reducing influence. This research can present the performance of modern ventilation systems in the climate of the Nordic region, emphasizing the need for a precise understanding of each new step in building energy-efficiency advisement to prevent shortcomings and ensure high indoor conditions.
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    Methanol production via carbon dioxide hydrogenation for the maritime sector - Techno-economic assessment and social acceptance
    (Aalto University, 2023) Nyári, Judit; Järvinen, Mika, Prof., Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Energy Conversion and Systems; Insinööritieteiden korkeakoulu; School of Engineering; Santasalo-Aarnio, Annukka, Assist. Prof., Aalto University, Department of Mechanical Engineering, Finland
    Interest in Power-to-X technologies, where X stands for various chemical molecules produced from renewable electricity via water electrolysis, has recently accelerated. Methanol is one of these X molecules, where, in addition to hydrogen, captured carbon dioxide also participates in the synthesis. Methanol is an excellent alternative fuel for the maritime industry due to its high energy density, ease of storage and distribution thanks to its liquid state at ambient conditions, biodegradability, and water miscibility. This research has investigated the utilisation of synthetic methanol and the techno-economics of its production. The techno-economics part has focused on assessing large-scale synthetic methanol plants, while the utilisation part investigated methanol usage as an alternative marine fuel from the social acceptance point of view. Aspen Plus® was utilised for the process modelling environment in the techno-economic part. The developed plants ranged from industrial-scale comparable in output to fossil methanol plants to smaller but still large-scale plants. The energy efficiency of these plants was around 80%, and the differences can be attributed mainly to the varying targets of the heat integration. Furthermore, a new parameter was introduced to the process simulation environment, the implemented kinetic model describing methanol synthesis. The selected three kinetic models were first compared in a simple one-pass reactor and later in full-scale synthetic methanol plants. The most recent model has outperformed the other two in all technical key performance indicators. The most recent kinetic model also predicts the lowest levelised cost of methanol, which was 801 €/tonne, 10% below the worst-performing model. Overall, the levelised cost of methanol was calculated to be around 700-900 €/tonne, which is around 75% higher than the current fossil methanol price at 395 €/tonne. Moreover, a series of sensitivity analyses were also conducted, which found that synthetic methanol's production cost is significantly influenced by the cost of electricity and the potential co-sale of the oxygen by-product from the electrolyser. In this research, the developed one-pass reactor model in Aspen Plus® was also used to verify a mathematical model in computational fluid dynamics describing synthetic methanol synthesis and the process conditions' effect. In the utilisation part of this research, passengers of roll-on/roll-off passenger vessels were questioned about their knowledge and preferences of alternative marine fuels and other emission mitigation tools. The research found that most passengers are willing to accept increased fare prices when the vessel runs on alternative marine fuels. Furthermore, passengers prefer lower-emitting fuels and fuel production technologies; however, they lack the knowledge to decide consciously.
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    Advancing safety in autonomous shipping through modern hazard analysis methods - A System-Theoretic Approach
    (Aalto University, 2023) Chaal, Meriam; Bahootoroody, Ahmad, Dr., Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Safe and Efficient Marine and Ship Systems; Insinööritieteiden korkeakoulu; School of Engineering; Valdez Banda, Osiris A., Prof., Aalto University, Department of Mechanical Engineering, Finland
    The maritime industry is currently undergoing a substantial transformation towards autonomous shipping, where human involvement in operational activities is diminishing, emphasizing safety and efficiency improvements. This transition, however, introduces new safety challenges that necessitate rigorous risk assessment and innovative safety frameworks. This thesis commences with an exploration of the historical development of risk, safety, and reliability considerations in autonomous shipping through a bibliometric review. Additionally, the future research directions and the potential risk assessment methods adequate for the complex autonomous ships are analysed. System Theoretic Process Analysis (STPA) is a key focus of this study. The thesis provides and investigate a model of the STPA organizational control structure within the maritime operational paradigm, seeking to reveal safety challenges of the transition to autonomy. An essential aspect of the work presented in this thesis involves integrating STPA with established marine risk assessment procedures, utilizing Bayesian Networks to quantify risks. The proposed framework scrutinizes the selection of Risk Control Options (RCOs) within Marine Risk Assessment (MRA) process and examines the potential incorporation of STPA-BN within the Formal Safety Assessment (FSA) process. Drawing upon conventional maritime practices, the thesis offers an approach to develop safety control structure of autonomous ship systems and provides an analysis of the control structure components of Autonomous Navigation Systems (ANS). Hence identifies unique safety challenges posed by these innovations. In summary, this doctoral thesis serves as a technical compass guiding the maritime industry towards enhanced safety in the age of autonomous shipping. By leveraging modern hazard analysis methods, particularly STPA, and integrating them into established risk assessment practices, this research seeks to catalyse a shift towards advanced system-theoretic risk assessment processes in the maritime industry, acknowledging the evolving regulatory landscape and the complexity of the challenges at hand.
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    Managing risks in maritime remote pilotage using the basis of the Formal Safety Assessment
    (Aalto University, 2023) Basnet, Sunil; BahooToroody, Ahmad, D.Sc., Aalto University, Marine and Arctic Technology, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Research group on Safe and Efficient Marine and Ship Systems; Insinööritieteiden korkeakoulu; School of Engineering; Valdez Banda, Osiris A., Prof. Aalto University, Department of Mechanical Engineering, Finland
    Maritime pilotage is conducted in congested areas, where the risk of collision and grounding accidents is high. Hence, the pilotage operation is safety critical and has been established as a mandatory service in many countries. However, with Remote Pilotage (RP) and related technological transformation, there is a need to adapt risk management methods to address emerging risks. This thesis aims to develop a framework to manage risks in RP by identifying gaps in the Formal Safety Assessment (FSA) framework and proposes novel solutions to fulfill them. The thesis investigates Model-Based Systems Engineering (MBSE) for creating unambiguous system description models for the risk management process. Furthermore, this thesis addresses the selection challenge in MBSE by proposing a framework that assists system developers in choosing suitable MBSE language. Building upon the model, the thesis combines, System-Theoretic Process Analysis (STPA) and Bayesian Network (BN) for hazard identification and risk analysis. To reduce the limitations of other STPA-BN studies, the thesis explores the application of complexity reduction techniques such as the Parent Divorcing Technique, Noisy-OR gates, and the sub-models. Moreover, the thesis extends the STPA-BN method with a cost-benefit analysis using Influence Diagrams (IDs) for selecting a cost-effective Risk Control Option (RCO). Lastly, the thesis provides a methodology for the automatic generation of a BN risk model using an incident database and programming language, which facilitates real-time risk monitoring. The proposed frameworks and solutions are then applied to RP for managing risks in early design phases. System description models, developed with selected MBSE language, are used together with STPA to identify the RP risk events such as losses, accidents, hazards, and causal factors. For each of these risk events, the occurrence probability is determined using a BN model. The model shows that the losses with high occurrence probability are loss of customer satisfaction, damage to the ship, injury to people, and damage to the environment. Furthermore, the model shows that collision and contact accidents have a higher occurrence probability than grounding during RP in Finnish fairways. For controlling these risk events in RP, an ID is developed and numerous RCOs are evaluated based on cost-benefit analysis. As a result, a cost-effective RCO for RP is proposed in the thesis. Finally, an automatic generation of BN risk models using a pilotage incident database and Python is demonstrated. The developed tool generates and updates the BN model providing the occurrence probability of risk events for real-time risk monitoring. The results of this thesis demonstrate the applicability and effectiveness of the proposed framework. Furthermore, this thesis provides an essential foundation for managing risks in RP and facilitates its development. Last but not least, the thesis provides tools and methods supporting stakeholders in making risk-based decisions involving advanced systems.
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    Verification of vessel resistance in old brash ice channels through model scale tests
    (Aalto University, 2023) Matala, Riikka; Suominen, Mikko, Dr., Aalto University, Department of Mechanical Engineering - Academy Research Fellow, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Marine and Arctic Technology; Insinööritieteiden korkeakoulu; School of Engineering; Kujala, Pentti, Prof. Emer., Aalto University, Department of Mechanical Engineering, Finland
    Winter navigation is vital for the societies and communities living close to the polar region to ensure the year-round security of supply. Winter navigation in the Baltic Sea is based on intergovernmental cooperation on icebreaker assistance and the Finnish-Swedish Ice Class Rules. The icebreaker fleet assists merchant ships with ice-classification by providing escort on request. The ship's eligibility for icebreaker assistance depends on the current traffic restrictions, which define the lowest allowed ice class and gross tonnage to acquire assistance. The ice class of the ship sets requirements for the minimum engine power for a ship, aiming to verify sufficient ice performance for the ship with specific ice class in an old brash ice channel, which is a typical operational condition for assisted ships. Model scale tests are an essential way to verify the ship's ice performance. Ship's performance in ice is one of the key factors in the winter navigation system, however, recent environmental standards have generated substantial changes in the merchant fleet bow shapes, meaning verifying model scale practices suitability in the new circumstances is crucial. This thesis investigates ship's resistance in frequently operated, old brash ice channels using experiments on brash ice and ship correlation tests in full scale and in model scale. Through analysing the processes forming the resistance and determining the forces contributing to the processes, it scrutinises the ice properties contributing to the forces. As the thesis shows, the current model scale test practices do not sufficiently simulate all substantial processes which contribute to ship's resistance in brash ice. The results indicate that the current practices are suboptimal for realistically and uniformly simulating ship's resistance: based on evidence from correlation tests, the model tests performed according to the current practices might overestimate the brash ice resistance of certain new bow types. To secure uniform and accurate ice performance predictions for all ice-classed ships, this thesis proposes a new approach for performing a model scale test in an unconsolidated old brash ice channel. The main discovery of the thesis is to show that realistic simulation of ship resistance in an old brash ice channel in physical model scale tests necessitates realistic simulation of brash ice fragment interaction. It does this through introducing a novel methodology for model scale simulations that improve the current problems of the modelling of ice-ice interaction. This leads to improved simulation of processes, which are related to displacing the brash ice mass sideways. The new scaling approach abandons the current practice of scaling down the ice flexural strength and proves that solid ice fragments more realistically model the interaction between the ice fragments when compared to traditional model ice with scaled-down strength. The understanding acquired within this thesis improves the performance predictions in brash ice channels.
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    Pakkolunastus ja eurooppalainen omaisuudensuoja - Tutkimus Suomen pakkolunastusinstituutiosta Euroopan ihmisoikeustuomioistuimen oikeuskäytännön valossa
    (Aalto University, 2023) Häkkänen, Martti; Ekroos, Ari, Prof., Aalto University, Department of Built Environment, Finland; Rakennetun ympäristön laitos; Department of Built Environment; Insinööritieteiden korkeakoulu; School of Engineering; Ekroos, Ari, Prof., Aalto University, Department of Built Environment, Finland
    Expropriation refers to the possibility of a public authority acquiring private property by force in order to carry out a project in the public interest. Expropriation is usually a last resort (ultimum remedum) means of carrying out a project when, for one reason or another, it is not possible to do so by agreement. In recent decades, the scope of expropriation has broadened from the implementation of roads or railway areas to the acquisition of areas necessary for urban development. Expropriation can also be used to implement various energy projects, such as electricity and gas distribution networks, nature conservation, and mining areas. Due to the last-resort nature of expropriation, its use may not be very common in practice. At the institutional level, however, the possibility of expropriation shapes the nature of ownership of real estate and the origin and content of contracts vis-à-vis the public authorities, since the conditions for expropriation and the compensation paid for it are reflected in contractual activities. Therefore, the existence and content of expropriation legislation have a very significant institutional impact on legal systems based on private real estate ownership. Expropriation is the most robust and profound way of interfering with private property. The use of expropriation, therefore, entails legal and political tensions, as well as economic, social, and moral dimensions. Its use must at the same time, meet the requirements of section 15 of the Constitution of Finland and the First Additional Protocol to the Council of Europe Convention on Human Rights concerning the protection of property. This study compares possible differences and similarities between the two sets of property protection standards concerning expropriation and assesses the need to revise national interpretations and practices. The Court of Human Rights, in its extensive case law on the protection of property, has developed a kind of general European principles of expropriation law. Comparing these Euro-pean principles with Finland's national legislative solutions and application practices reveals interesting similarities, but also clear differences. According to the research results, Finland's national legislation can be considered predominantly in line with the Convention on Human Rights at the level of basic legislative solutions and main principles. However, some individual regulatory solutions can be seen to be in tension with the latter. On the other hand, when examining Finland's national application practices, some more significant differences can be observed in relation to the Convention on Human Rights. In other words, the relationship is not without its legal problems in all respects. With regard to possible differences, it is essential that the Convention is a set of norms enforced by an act in Finland that constitutes a binding source of law both when enacting and applying laws. Any differences between Finland's national regulations and the Convention must, therefore, be taken into account in a binding manner in national activities. This is enhanced by the direct possibility for individuals to bring expropriation cases before the Court of Human Rights, which forms the cornerstone of international monitoring of the Convention.
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    Understanding the interplay of contextual factors affecting the integration of land use and transport planning - The Case of MAL 2019 planning process in Helsinki Metropolitan Region, Finland
    (Aalto University, 2023) Duman, Oya; Mäntysalo, Raine, Prof., Aalto University, Finland; Rakennetun ympäristön laitos; Department of Built Environment; Spatial Planning and Transportation Engineering; Insinööritieteiden korkeakoulu; School of Engineering; Mladenović, Miloš N., Assoc. Prof., Aalto University, Department of Built Environment, Finland
    Current policy challenges are complex as they are caused by an interplay of natural and anthropogenic phenomena, traversing environmental, social, financial and bureaucratic borders. A key problem in public policies is their fragmented approach to such challenges. The urgency to move away from fragmented public policies has been visible within land use planning and transport planning. Inability to respond to the global crises due to hierarchical and sectoral fragmentation creates new demands for the practices of land use planning and transport planning. An integrated land use and transport planning approach bringing together diverse forms of sectoral expertise, different planning levels and separate administrative units has been proposed to address issues contributing to the global crises. However, regardless of how widely recognised the need for land use and transport planning integration is, effective processes of such integration have proven difficult. There has been a lack of academic research which provides insights into the convoluted nature of conditions influencing the integration of land use and transport planning processes, and elucidates the conditions for their effective implementation from a perspective acknowledging the multi-faceted and situated nature of integrated planning processes. Accordingly, the objective of this research is to provide in-depth process knowledge into the integration of land use and transport planning, by identifying and discussing the interplay of contextual factors affecting integrated processes. This research examines the integration of transport planning and land use planning processes in MAL 2019 planning process in Helsinki Metropolitan Region, Finland. The MAL 2019 planning process is a special case as it is a process specifically designed for integrating land use planning and transport system planning processes. In order to study the lived experiences of planning actors, this research employed interviews and policy document analysis, with supporting validation and visualisation methods. The research also includes a systematic review of factors affecting the MAL 2019 planning process. The findings of this doctoral research shed light on how the context of an integrated land use and transport planning process emerges through the interdependencies between different factors making up the context. The findings emphasise the importance of situating integrated planning processes within their specific contexts, acknowledging the complexity and historical development of factors influencing these processes. The findings challenge the notion of applying "best practice" examples universally and highlight the need to understand what works within each unique context. The findings point towards the most influential contextual factors, providing insights for process design in the context of the MAL 2019 planning process, which can offer valuable lessons to other governance contexts, as well. This knowledge allows for targeted and context-specific recommendations to improve integrated planning processes, enabling planning organisations to enhance their governance capacity.
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    Learning from Futures: Utilising Scenario Thinking in Strategic Spatial Planning
    (Aalto University, 2023) Grišakov, Kristi; Ache, Peter, Prof., Radboud University Nijmegen, Netherlands; Rakennetun ympäristön laitos; Department of Built Environment; Insinööritieteiden korkeakoulu; School of Engineering; Mäntysalo, Raine, Prof., Aalto University, Department of Built Environment, Finland
    Strategic spatial planning has a specific commitment to future. It concerns the future transformation of place and constantly seeks ways to imagine different futures creatively and collectively (Hillier, 2011; Albrechts, 2005). However, much traditional planning has focused on preserving the existing order rather than challenging and transforming it (Albrechts, 2015). This, in combination with the need to address the 'radical' uncertainty (Zapata and Kaza, 2015) of the future, and to account for the multiplicity of communities that essentially shape the future (Hajer and Wagenaar, 2003), creates the need to rethink the praxis of strategic spatial planning (Hillier, 2013). While there is agreement that stra- tegic spatial planning should address the uncertainty of the future, there is less clarity about how exactly to deal with such a future. This research is a methodological inquiry into using futures studies techniques in the context of strategic spatial planning, more specifically the approach of 'scenario thinking'. It explores the potential contribution of scenario thinking to knowledge and capabilities needed in strategic spatial planning. In order to find opportunities for such a contribution, the dialogue between the disciplines of strategic spatial planning and scenario planning is explored, focusing specifically on the debates on knowledge needs. The research focuses on three core capabilities: 1) the capability to critically compare and learn from completed scenario planning documents; 2) the capability to design explorative scenario development projects in the context of strategic spatial planning, especially focusing on the aspects of re-framing, evidence and intuition; 3) the capability to create scenario stories, focusing on how the knowledge collected during the scenario project can be interpreted and mediated as scenario stories and story visuals. Finally, these core capabilities are interlinked, to discuss how scenario thinking as an iterative process can be connected with the wider practice of knowing in planning; not exclusively to be used for the purposes of strategic framing, but also to support reflective planning practice in general. Through the careful analysis of how knowledge is understood, gathered, used, and validated in scenario thinking, the research illustrates how various types of knowledge (episteme, techne, phronesis) are used not consecutively, but parallelly as an iterative process. For example, phronesis is used already in the beginning of the scenario thinking process in order to define re-framing needs. The practice of knowing through scenario thinking can and should be in dialogue with the practice of knowing in planning. This research proposes that planners can use scenario thinking to support collective learning and reflection for looking outwards in order to inform strategic framing but also for looking inwards to support reflective practice.
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    Hyperspectral imaging of tree stems
    (Aalto University, 2023) Juola, Jussi; Rautiainen, Miina, Prof., Aalto University, Finland; Hovi, Aarne, Dr., Aalto University, Finland; Rakennetun ympäristön laitos; Department of Built Environment; Geoinformatics; Insinööritieteiden korkeakoulu; School of Engineering; Rautiainen, Miina, Prof., Aalto University, Department of Built Environment, Finland
    With the recent development of portable hyperspectral imaging spectrometers, there is a unique opportunity to acquire detailed information on the spectral properties of individual forest canopy elements, such as tree stems. Information on the spectral properties of stem bark is important for remote sensing of forests, biodiversity mapping, and forestry applications. In remote sensing, information on the fine scale physical interactions between shortwave solar radiation and stem bark is needed to interpret remotely sensed signals of forests more accurately. For biodiversity mapping and forestry applications, information on the spectral properties of stem bark could be used to support accurate identification of tree species. The aim of this dissertation was to develop close-range imaging spectroscopy as a method to measure the reflectance of stem bark in laboratory and field conditions, explore the spectral characteristics of stem bark, and assess the use of spectral data on bark in the identification of boreal and temperate tree species. The results demonstrated that there is potential in utilizing close-range imaging spectroscopy as a novel data source for studying the spectral characteristics of stem bark in the laboratory and in the field. The reflectance spectra of the measured boreal and temperate tree species had a similar shape in the visible to near-infrared region, but the overall levels of reflectance varied substantially within-and between-species. In general, stem bark reflectance for the measured boreal and temperate tree species was highly variable and anisotropic. Stem bark reflectance was affected by the spatial location of the sample along the stem and by the angular effects associated with the view-illumination geometry. Greatest interspecific differences in stem bark reflectance were in the near-infrared region and varying absorption features were observed at around 670–700 nm. The spectral features of stem bark were robust for identifying tree species but combining them with the texture features extracted from the hyperspectral reflectance images improved results further. The results also underlined the importance of accounting for meteorological and radiation conditions when measuring the spectra of stem bark in field conditions with pushbroom sensor technology. This dissertation gave a unique perspective into the spectral characteristics of stem bark for boreal and temperate tree species. The results contributed towards understanding the spectral diversity of forests more comprehensively and the portable hyperspectral imaging spectrometer showed promising results as a new technology for developing tree species identification methods for the forest industry and biodiversity mapping applications.
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    Deserted Mining Regions in the Context of Chinese New-Type Urbanization: An Integrative Survey Framework for Managing Balanced Eco-social and Economic Development
    (Aalto University, 2023) Sun, Nan; Kyttä, Marketta, Prof., Aalto University, Finland; Rakennetun ympäristön laitos; Department of Built Environment; Insinööritieteiden korkeakoulu; School of Engineering; Mäntysalo, Raine, Prof., Aalto University, Department of Built Environment, Finland
    China is in a difficult transformation period, with both economic development and urbanization in high speed. The first point of departure of this research is the implementation of new-type urbanization, with social-economic-natural complexity on the one hand and unbalanced development on the other. The second point of departure is the urban-rural dual-structure contradictions and uneven regional development. While these two points have deeply affected China as a whole, in recent years the deserted mining regions have been among those most significantly affected. After years of rapid and resource-based economic development, these regions are now under complex pressure from economic transformation, resource depletion, social conflicts, and environmental pollution. This thesis takes the deserted mining region in Mentougou District, Beijing, as its case. As a broader perspective is required in resolving complex pressures, the conditions of urbanization are analysed on four administrative scales: the whole state, the Jing-Jin-Ji metropolitan region, Mentougou District, and its five case areas. Through the lens of these five case areas—two in urban districts, two in rural areas, and one located in between—the study develops an integrative survey framework for managing balanced urbanization while considering the social-economic-natural ecosystem, differences between rural and urban areas, and residents' perceptions of their living environment. To facilitate appropriate community planning and management, a broad scope of research methods and frameworks were adopted, including the ecosystem approach, social-economic-natural complex ecosystem (SENCE), Driver-Pressure-State Change-Impact-Response (DPSIR), cluster analysis, public participation GIS (PPGIS), geological hazard forecast and prevention by the public (GHFPP), and potential ecological risk assessment (PERA). This thesis offers four main contributions. The first is the integrative theoretical research approach, which lays the foundation of this research; the second is the outlining of the integrative indicator system corresponding to the theoretical integration; the third is the results of a comparative study of the case areas and cluster analysis of the residents' perceptions, addressing the role of the integrated framework in balanced development; and the fourth is development in public participation. The specific contribution of this thesis to SENCE theory is in adapting the theory from the complex objective rationality context to the bounded rationality context. Adaption means focusing on pragmatic solutions in the face of wicked and complex questions in regional planning and management.
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    Algorithmic Advancements in Drive-by Inspection Methods Towards Intelligent Bridge Monitoring
    (Aalto University, 2023) Lan, Yifu; Rakennustekniikan laitos; Department of Civil Engineering; Bridge Engineering; Insinööritieteiden korkeakoulu; School of Engineering; Lin, Weiwei, Assoc. Prof., Aalto University, Department of Civil Engineering, Finland
    Since conventional vibration-based structural health monitoring (SHM) methods typically require the installation of numerous sensors directly onto the bridge, the substantial costs associated with on-site sensor installation and maintenance have long rendered such technology an expensive option. Recently, an alternative approach referred to as the "drive-by bridge inspection method" has attracted scholarly attention. This method necessitates no instrumentation on the bridge; instead, it uses a few sensors positioned on the vehicle traversing the bridge, with the vehicle functioning as both an exciter and a receiver. It offers the possibility to efficiently monitor groups of bridges (particularly small and medium-sized ones), presenting an economically efficient solution to bridge health monitoring problems. While previous research on the drive-by method has yielded promising results, there are still some challenging problems and ample room for improvement before its engineering application. This thesis aims to propose algorithmic solutions to address the challenges faced by the current drive-by methods, successfully extracting bridge modal parameters and identifying damage. In terms of bridge modal parameters, two algorithms are proposed. Algorithm 1 extracts the bridge frequency as a common signal component in the responses of multiple sensors mounted on the vehicle. This method does not require specially designed vehicles or multiple cars, as in earlier studies, but instead utilizes a single ordinary vehicle, providing a practical solution. Algorithm 2 employs the Coherence-PPI (Prominent Peak Identification) method, which extracts the bridge frequency from the common vibrational components of multiple passes of the same vehicle. Rather than seeking to minimize differences, it encourages variability in drive-by measurements (e.g., varying vehicle parameters, avoiding traversing the same road surface) to filter bridge frequencies. It is particularly suitable for vehicles passing the same bridge multiple times (such as buses). In terms of damage identification, a data-driven algorithm based on an optimized AdaBoost-linear SVM is proposed (Algorithm 3), which accurately indicates bridge damage using only the raw vibration signals received from vehicles passing the bridge. To further improve damage identification accuracy and address certain limitations of drive-by measurements, such as noise and data redundancy, a time-domain signal processing algorithm for the raw vehicle accelerations is also proposed (Algorithm 4). The proposed algorithms have been validated through numerical simulations, laboratory experiments, and field tests on simply supported and continuous beam bridges using truck and bus models. The ultimate goal is to achieve a practical and intelligent bridge health monitoring system.
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    Deep learning applications for condition monitoring of rotating systems
    (Aalto University, 2023) Miettinen, Jesse; Tiainen, Tuomas, Dr., Aalto University, Department of Mechanical Engineering, Finland; Konetekniikan laitos; Department of Mechanical Engineering; Mechatronics Research Group; Insinööritieteiden korkeakoulu; School of Engineering; Viitala, Raine, Asst. Prof., Aalto University, Department of Mechanical Engineering, Finland
    Vibration-based condition monitoring can provide crucial information of the performance and health state of rotating machines for maintenance scheduling. Condition-based maintenance schedules can increase the reliability and useful lifetime of rotating machines and reduce maintenance downtime. Deep learning models show great promise for automating vibration-based condition monitoring systems. These models can be optimised for accurate and precise fault detection, fault diagnosis and virtual sensing functions, for example. Automating these functions can, for instance, reduce the manual labour required from experts, decrease the time from a fault occurring to the corrective maintenance action, and enable the condition monitoring of large machine fleets. To this end, the research improved the current deep learning-based condition monitoring models, and studied best practices for the application of these models for vibration analysis. A virtual sensor application based on long short-term memory (LSTM) and a training procedure for largely varied operating conditions were demonstrated. The virtual sensor application for a rotor system and the training procedure were evaluated with vibration data covering largely varied operating speeds and support stiffnesses. Fault diagnosis models based on one-dimensional convolutional neural networks (1D CNN) were optimised and compared with vibration data acquired with different sensors mounted on many locations on a drivetrain. The feature normalisation of 1D CNNs was investigated with vibration datasets acquired under laboratory and real operating conditions. The results demonstrate that deep learning models for vibration-based condition monitoring can learn to function over a large span of operating conditions. Simultaneously, the results also suggest that the training dataset should contain vibration samples from the desired operating condition range. The results imply that torsional vibration can be an effective data source for the fault diagnosis of rotating machines. Furthermore, the results show that the type, mounting location, and number of vibration sensors influence the model performance significantly. In addition, the results related to the feature normalisation experiments on 1D CNN-based models indicate that the current algorithms can still be improved. Overall, the findings in this research are relevant to the future research and development projects towards deep learning-based condition monitoring systems for rotating machines. Moreover, the developed applications and the findings related to the best optimisation practices can contribute to automatic condition monitoring systems providing timely information for maintenance planning. This in turn can reduce the downtime and maintenance costs of rotating machinery.