Master Theses

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The sustainable future of insects as food and feed
Sekertzi, Rea
The pressure for new protein sources is turning our attention to insects. They are rich in protein, good fats, and micronutrients, while being less demanding on land, water, and feed compared to livestock. The European Union has already approved some species as animal feed and "novel foods", but acceptance issues remain and further research on safety and legislation is needed. The work aims to explore the use of insects as a sustainable source of protein for either animal feed or human nutrition. A systematic review of the literature will be conducted to highlight the nutritional characteristics of insects, the impacts on the economy and the environment, as well as the social and legislative parameters that determine their acceptance in the market. Particular emphasis will be placed on their potential within the circular economy and sustainable agriculture, while the prospects for implementation both in Greece and in Europe will be examined. Through a comparison of recent studies, this analysis captures how insect farming can enhance the sustainability of agriculture and reduce the environmental footprint of nutrition.
Nature-based solutions for soil erosion control in Mediterranean soils: A review
Gatsis, Evangelos
This dissertation explores scientific sources concerning the effectiveness of nature-based solutions for soil erosion control in agroecosystems with a Mediterranean climate. The research paper divides methods used in soil conservation into five groups, namely vegetation-based practices, organic amendments, conservation tillage, structural measures, and land-use change. In general, vegetation-based practices including cover crops, shrubs, spontaneous vegetation, and mosses proved to be highly effective due to the reduction of rain drop impact, improvement of soil structure, and enhanced infiltration. On the one hand, use of organic amendments (biochar and mulch) also contributes to soil erosion control through higher soil stability and water retention. However, their effectiveness significantly varies depending on application rates and environment. At the same time, the implementation of conservation tillage measures like no-tillage reduces soil disturbance and erosion in case of the presence of continuous vegetative cover and crop rotations. Moreover, implementation of some structural measures (terracing) and land-use changes such as afforestation and riparian restoration lead to increased soil stabilization despite high costs and long-term results. The analysis reveals that there is no single measure capable of solving the problem of soil erosion and, therefore, it is necessary to combine several soil conservation methods for the best possible results.
The Impact of COVID-19 on the Financial System of Middle Eastern Countries
Rahmeh, Merwad
This dissertation was written as part of the MSc in International Accounting, Auditing and Taxation at the International Hellenic University. The COVID-19 pandemic, declared by the World Health Organization (WHO) in March 2020, created an unprecedented global crisis that affected health systems, financial structures, and economic activities worldwide. For the Middle East and North Africa (MENA) region, where economic stability is closely tied to oil revenues, trade flows, and migrant labor, the pandemic produced a dual shock: a health emergency and a dramatic collapse in oil demand. Oil prices fell to historic lows in April 2020, intensifying fiscal pressure on both Gulf Cooperation Council (GCC) economies and non-GCC oil-importing countries. Government and regulatory responses became central to managing this instability. Across the region, authorities introduced fiscal stimulus programs, monetary easing, liquidity support initiatives, and regulatory adjustments to preserve financial system resilience. These measures were critical in restoring market confidence and limiting the broader socioeconomic fallout. This dissertation examines these policy responses through a qualitative comparative approach, identifying how governments and regulatory institutions shaped financial stability during the crisis. Drawing on literature related to oil price volatility, exchange rate movements, risk transmission, and labor market conditions, the study highlights the role of institutional agility and the ability of policymakers to react rapidly in times of disruption. The research ultimately establishes a conceptual pathway showing how government action mediates market behavior and financial resilience during systemic shocks. This dissertation was completed under the supervision of Dr. Antonios Chantziaras, whose guidance, academic insight, and constructive feedback were essential throughout the research process. I also acknowledge the scholars and researchers whose published work informed this study, as well as colleagues and peers who offered valuable discussions and support during its development. Their contributions helped strengthen the analysis and overall quality of this research.
Design and development of a modular, multi-purpose bicycle for sustainable mobility
Karalioki, Evangelia
After reviewing recent market trends and consumer behaviours, this dissertation examines the design of a modular bike, enabling multifunctional utility. By maintaining the core parts and allowing the integration of different components and accessories, the design empowers consumers to configure their bike according to their needs. The dissertation also addresses the essential pillars to design and develop a modular bicycle. The main objective was to identify the core modular features that enable a single universal frame to accommodate multiple components, in order to create different configurations, while maintaining structural integrity and ergonomics. The research focused on the development of a main bike frame and the engineering of three different fastening concepts. A novel fastening system was developed based on its superior performance compared to the conventional ones and its ability to secure the modular components successfully. The main material selected for the further simulations of the bike, was Aluminum 6061 and 6061-T6, after carefully reviewing the material properties of the most common materials used for bicycle construction. The design of the modular bike was based on four main bike types, the city bike, the mountain bike, the cargo bike and the family bike, that were digitally designed and examined for their assembly attachment. The family bike configuration, which is the bike type with the highest risk of safety as it receives multiple loads and strains, was evaluated for its design effectiveness and safety, exhibiting a safety factor of 5.04.
Stablecoins and the Cryptocurrency Market Volatility
Sofidis, Ioannis
This thesis examines the short-run dynamic relationships between stablecoins and cryptocurrency market capitalizations. VAR models, IRFs, local projections, forecast error variance decomposition and dynamic connectedness measures are employed to trace how shocks from stablecoins, equity indices and gold transmit to the cryptocurrency market. The results, based on weekly frequency data, highlight the cryptocurrency market's substantial independence in the short to medium term. Stablecoins appear to serve mainly as liquidity and infrastructure tools within the crypto ecosystem rather than as drivers of aggregate market capitalization dynamics. These findings add to the understanding of spillovers in digital asset markets and carry implications for investors and regulators regarding the limited systemic role of stablecoins in cryptocurrency fluctuations.
From Freelancer to Founder: The Rise of Solo Digital Entrepreneurs in Europe
Preusch, Marco
Digital solo entrepreneurship has become an increasingly visible part of Europe’s digital economy, driven by the growing accessibility of digital platforms, tools and digitally enabled business models that have made it easier to launch one-person ventures. However, it remains unclear how these ventures emerge and which factors contribute to their success. This thesis examines this issue through an exploratory survey of digital solopreneurs in Europe, focusing on founder pathways, digital capabilities, business model design and external conditions. Given the small sample size, the analysis was exploratory and the findings should be interpreted cautiously. Nevertheless, several patterns emerged. Survey participants with prior freelancing experience appeared to reach a MVP more quickly. Frequent use of digital tools alone appeared less informative than the ability to integrate them into productive routines and workflows. The findings further suggest that ventures with higher automation and clearer niche focus tended to report greater revenue stability, although both overall economic stability and personal sustainability remained inconsistent. The study therefore suggests that digital opportunity alone is insufficient; instead, greater importance appears to lie in how solo founders transform digital possibilities into structured and manageable business practices.
The use of artificial intelligence in the management of digital communities: opportunities,limitations and ethical issues/systematic literature review
Almalioti, Aliki
This dissertation explores the use of Artificial Intelligence (AI) in the management of digital communities, focusing on its opportunities, limitations, and ethical challenges. Through a systematic literature review, the study examines how AI technologies such as machine learning, natural language processing, and automated moderation systems are used to support online community governance and content moderation. The findings show that AI can improve efficiency, scalability, and detection of harmful content, while also reducing moderators’ workload. However, significant concerns remain regarding algorithmic bias, transparency, privacy, and freedom of expression. The study concludes that AI should support, rather than replace, human judgment in digital community management. Responsible and ethical implementation requires transparency, fairness, and continuous human oversight.
Optimization Techniques in React and Movie Finder Application
Tsianakas, Dimitrios
As user expectations for web speed intensify, optimizing data-intensive Single-Page Applications (SPAs) has become critical. This research addresses common React performance bottlenecks such as unnecessary re-renders and large JavaScript payloads through the development of a "Movie Finder" case study. By systematically implementing component memoization, route-based code splitting, list virtualization, client-side caching, and responsive image loading, the study achieved significant measurable improvements. The initial JavaScript bundle was reduced by approximately 84% (from ~416 kB to 67.5 kB), Total Blocking Time (TBT) was eliminated (0 ms), and the overall Lighthouse performance score rose from 85 to 99. These findings confirm that a holistic architectural approach is essential for delivering production-grade user experiences.
Stock Market Prediction Using Multi-Source Data: A Comparative Analysis Across Feature Sets and Prediction Horizons
Deda, Antonios
This dissertation explores whether combining multiple sources of financial information like technical indicators, market sentiment, company fundamentals, and macroeconomic factors, can improve stock market prediction across different forecasting horizons. Using major U.S. stocks such as AAPL, MSFT, AMZN, and TSLA, a range of machine learning and statistical models were evaluated to compare the contribution of each data source. The results show that technical indicators consistently provide the strongest predictive power, especially for short-term forecasts, while sentiment, fundamental, and macroeconomic data offer more limited and context-dependent benefits. The study also finds that more complex models do not necessarily outperform simpler ones, as they are often more susceptible to overfitting. Overall, the findings suggest that successful stock market prediction depends less on using larger amounts of data or increasingly sophisticated algorithms and more on selecting the right information and model for the specific forecasting horizon.
Human Vs AI Marketing
Tsitsiou, Anna
This dissertation examines the relationship between artificial intelligence and human capability in contemporary marketing, focusing on the central question of whether AI can replace, outperform, or productively complement human marketers in theory and practice. The study is structured around six chapters that move from the historical evolution of marketing and the rise of digital marketing to the role of artificial intelligence, machine learning, big data analytics, and automation in modern business environments. It then turns to the human factor in marketing, emphasizing creativity, emotional intelligence, empathy, consumer psychology, storytelling, brand identity formation, market understanding, and intuition as essential dimensions of effective marketing practice. The analysis demonstrates that AI offers substantial advantages in areas such as personalization, predictive analytics, recommendation systems, programmatic advertising, chatbot communication, campaign optimization, and large-scale data processing. These capabilities make AI especially effective in digital environments where speed, scalability, and data-driven responsiveness are critical. At the same time, the study argues that human marketers remain indispensable in tasks involving symbolic interpretation, ethical judgment, emotional sensitivity, strategic originality, and culturally meaningful brand communication. Through the comparative discussion of human and machine capabilities, the dissertation shows that marketing cannot be reduced to computational efficiency alone, since trust, authenticity, and emotional resonance continue to depend heavily on human-centered insight. The dissertation also includes a case-based discussion of Coca-Cola and Netflix in order to illustrate how AI is applied in real marketing settings through generative creativity, recommendation systems, interface personalization, and brand-level innovation. The broader conclusion is that the future of marketing does not lie in a simple opposition between AI and humans, but in a collaborative model where intelligent systems enhance efficiency and analytical power while human marketers provide interpretation, ethical control, and creative direction. The study concludes that businesses should adopt AI strategically and responsibly, with strong human oversight, and that future research should further explore workforce transformation, consumer trust, ethical governance, and the long-term implications of human–AI collaboration in marketing.
Evaluating the Performance of Large Language Models (LLMs): a Comparative Analysis of LLAMA and BERT in News Article Summarization and Sentiment Analysis of Social Media Posts.
Gorokhov, Sergei
ABSTRACT This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. The research study titled “A Comparative Analysis of LLaMA and BERT in News Article Summarisation and Sentiment Analysis of Social Media Posts” seeks to evaluate and compare the effectiveness of LLaMA 2 7B and BERT base in two different applications of NLP. The two primary goals were to establish how well they performed for various types of textual data and offer guidelines on the best ways to harness them in practical applications. The study utilised two datasets: The dataset used for summarisation is a news articles dataset and the second set is the TweetEval dataset for sentiment analysis. Hence, the results of both models were assessed on accuracy, resource uses, and time required for training. The outcomes established showed that BERT scored better on both tasks than LLaMA with a validation accuracy of 94 % for news summarisation and 64 % for sentiment analysis in contrast to LLaMA which scored only 79% and 54% respectively. Lacking LLaMA’s additional complexity did not penalize BERT for not attaining the same level of performance as the original tasks. The analysis pointed out the need to select which model to use for each task, while it emerged that BERT was more appropriate for classifying tasks that involve contextual information. Recommendations for BERT are to adapt BERT models to fit into your specific industry or niche and for LLaMA, it is advised for the more intricate, generative tasks. I would like to express my gratitude to my supervisor for their valuable insights and guidance throughout the project. I want to say special thanks to my collaborators and colleagues for their constructive feedback and support, which enriched this work making it easier to complete.
Strategic asset allocation for energy transition portfolios: a long-term view
Massaras, Ioannis
The rapid growing shift towards a low-carbon economy, presents both challenges and opportunities for long-term investors who are willing to align their portfolios with this energy transition. This dissertation examines how strategic asset allocation can be optimized for investment portfolios that incorporate environmental, social, as well as and governance (ESG) considerations, while maintaining an effective long-term financial performance. The study adopts a Conditional Value at Risk (CVaR) optimization framework in order to construct diversified, ESG-constrained portfolios using an investment asset selection of exchange-traded funds (ETFs), representing green energy (ICLN), fossil fuels (IXC), global equities (URTH) and green bonds (BGRN). Through comparative analysis, the performance of a benchmark equal-weighted portfolio is evaluated against the portfolios optimized for downside risk and ESG alignment. The final portfolio optimization integrates ESG score constraints, CVaR minimization at the 95% confidence level, as well as and asset weight boundaries (10%–50%). Moreover, the ESG-constrained portfolio exhibits lower CVaR (–7.62%) and higher ESG performance (score of 7.76) with only a marginal reduction in expected return compared to the benchmark. In addition, a 24-month rolling CVaR analysis illustrates that the optimized portfolio maintains effectively lower tail risk over time. Furthermore, Johansen cointegration tests are conducted in order to reveal any significant long-run equilibrium relationships among the selected assets. The findings suggest that portfolios should not only rely on long-term co-movement assumptions across green and traditional energy sectors. These results further support prior findings that ESG integration, when incorporated with effective risk optimization, enhances downside protection without sacrificing significantly any return potential. The dissertation contributes a practical framework for institutional investors who seek to balance financial objectives with sustainability commitments. It further highlights the value of CVaR-based portfolio construction under ESG and diversification constraints, offering insights for asset managers and policymakers navigating the financial implications of the global energy transition.
Switching Costs and Ecosystem Effects in iPhone Customer Retention
Koutalidi, Ismini
Switching costs are one of the most discussed contemporary issues in marketing in an attempt to explain consumer behaviour, as they have been considered the main forces that penetrate market competition. Depending on their type, brands have been leveraging them to establish higher prices, ecosystem dependencies, emotional attachments and as a consequence of all this, create significant entry barriers to alternative brands (Maicas et al., 2009). The aim of this research project is to investigate the factors that sustain iPhone users’ loyalty in Apple and the Apple ecosystem, and to illustrate the relationship between switching costs, emotional branding, and customer retention. For getting more concrete, this study breaks down emotional branding strategies into specific dimensions identified in prior literature, while considering the different types of switching costs, such as learning, procedural, complementary and compatibility costs, with a particular focus on their relevance within the mobile device industry and, where applicable, the Apple ecosystem. These were chosen based on their frequent identification in literature. At the end, I used PSPP- a platform for statistical analysis of sampled data- to perform relevant statistical tests and test our hypotheses around our objectives. The mean scores of each construct was separately calculated in relation to participant’s retention levels, thereby revealing which factor exerted the strongest influence. The survey results were statistically proven by performing quantitative methods, including descriptive analytics, cross-tabulations, Chi-square tests, Analysis of Variance (ANOVA) and Pearson correlation. This research employs a thorough literature review and later, a quantitative approach with online questionnaires distributed involving 52 iPhone users as respondents. The target population is exclusively past or current iPhone users of all ages and genders. The results demonstrate that switching costs have a positive, moderate effect on iPhone users’ retention, and their relationship is statistically significant. These findings were al-so closely linked to Apple’s ecosystem effects, as identified in the literature. In contrary, emotional branding only showed a weak relationship with customer retention. Out of all types of switching costs, learning and procedural switching costs emerged as the most influential factor in driving iPhone repurchase intentions. The contribution of this re-search is expected to be a consideration and input for Apple to consider the factors that influence not only Apple's customer satisfaction but also retention levels and long-term loyalty. The insights also suggest a deeper probing into Apple’s ecosystem strategies extending beyond cross-device functionalities, but including features within the operating system and platform-specific services, such as iCloud, AirDrop, and iMessage that reinforce switching costs and therefore, user retention.
Risk Management and Financing Instruments in Agriculture Challenges, Mechanisms and Policy Implimications – The case of Greece
Sallis, Christos
This dissertation was written as part of the MSc in Sustainable agriculture and business at the International Hellenic University. I gratefully acknowledges the valuable guidance, constant support and constructive comments of the supervisor throughout the course of this work. The agricultural sector is one of the major pillars of economic, social and environmental development, but operates under severe structural limitations, high exposure to natural, market and financial risks, and heavy reliance on institutional interventions (FAO, 2019–2022; OECD, 2020–2021; World Bank, 2018–2022; EC, 2022–2023). Here we present a systematic assessment of factors influencing income stability and sustainability of agricultural production with reference to both traditional and innovative financial instruments and to the role of the Common Agricultural Policy and mechanisms of insurance coverage. Our methodological approach integrated critical evaluation of international and national literature with a detailed case study of agricultural conditions in Greece, enabling comparison of systems of risk and of policies applied (FAO, 2019–2022; OECD, 2020–2021; World Bank, 2018–2022; EC, 2022–2023). Major limitations included high rates of land fragmentation, an aging rural population, uncertainty of commodity prices and limited availability of financial resources. These conditions underscore the need to increase the capacity for institutional and technological adaptation to natural and market risks. We evaluated conventional methods of risk management, as well as innovative systems of financial support, including environmentally friendly loans, combined mechanisms of financial support, application of digital technologies and strategies of adaptation to climate change. In addition, we proposed measures to strengthen the capacity for institutional control, increase levels of financial inclusion and integrate digital technologies into systems of agricultural production. Overall, our results confirm that increases in the sustainability and competitiveness of agriculture in Greece will be achieved only through comprehensive and integrated systems of financial, institutional and technological intervention.
Process Mining in Operational Data of an Organisation
Diamantis, Georgios
This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. The current dissertation provides a complete study of Process mining in operational data of an Organisation. By using different Techniques and methodology of Process mining is presented, with classical and more modern techniques and approaches. These techniques are applied in log files provided by a public sector Organisation where financial transactions and administration processes were studied on the purpose to discover bottlenecks and suggest improvements that will support efficiency in the procedures. In specific expense requests log files were provided and process mining cycle was applied to the dataset. By using open software as ProM, a tool primary developed at Eindhoven University of Technology, Anaconda Python Jupyter as programing language and platform with library PM4py, KNIME with process mining Community Nodes extension and limited access to Disco commercial tool, a thorough evaluation of the tool capabilities was preformed. The steps of process mining were followed side by side with the use of the tools on the given public sector data sets. Following visualisations and metrics on the event logs of the Organisations were created and supported the understanding of the workflow and discover bottlenecks in the given use case. Deviations from the intended process models were determined and suggestion to enhance operational performance, ensure compliance, and drive continuous improvement initiatives are provided. Finally the strong and weak points of each tool are mentioned and improvement points for the expense request process are provided. I would like to express my appreciation to my supervisor professor Christos Berberidis for his support and guidance through this study. Furthermore I would like to thank Assoc. Prof. Vassilios Peristeras and Assist. Prof. Ioannis Magnisalis for their support and knowledge sharing. Finally I would like to thank O.T.S. S.A. company for providing sanitized log files of a financial Organisation transactions.
Morphological Biomimicry: Strategies for the Structural Abstraction of Biological Systems
Papafilippou, Georgios
This dissertation investigates how morphological biomimicry can contribute to the de-sign of an outdoor structure through the translation of biological principles observed in corals, fungi, and marine organisms into a conceptual design proposal. As contempo-rary design increasingly turns to nature for adaptive and sustainable strategies, biolog-ical growth patterns such as branching, lattice formation, and curvature are explored as a creative framework for design. This research adopts a Research through Design (RtD) methodology, integrated with biomimetic frameworks such as the biomimetic design spiral, beginning with the bio-logical analysis of natural organisms and progressing through iterative sketching, digi-tal modelling, and environmental visualisation. Two complementary digital workflows are employed. The first consists of a manually controlled modeling process based on idea exploration and hands on creation, includ-ing sculpting and material experimentation in Blender. The second introduces a rule-based generative approach using Geometry Nodes, enabling the development of emergent forms through parameter-driven systems. The comparison of these work-flows allows for the evaluation of differences in control, adaptability and morphologi-cal expression. The design process that is followed integrates organic geometries with functional con-siderations, demonstrating how characteristics such as porosity and controlled irregu-larity contribute to both structural behavior and experiential quality. The outcomes of this research are the development of a biomimetic outdoor structure, the establish-ment of a reflective digital workflow for translating biological morphologies into de-sign strategies and the demonstration of morphological biomimicry as a methodologi-cal approach. The study contributes to the understanding of how nature-inspired principles can support adaptable, sustainable, and experience-driven design solutions.
Exploring the Role of Lean Production and Digital Traceability in Achieving Social License to Operate: A Systematic Literature Review
Prifti, Antonio
This dissertation was written as part of the MSc in Environmental Management and Sustainability at the International Hellenic University. Social License to Operate (SLO) is the informal, ongoing acceptance that stakeholders grant to an organisation's activities beyond formal regulatory permits. It has become an increasingly critical concern for manufacturing organisations operating in global supply chains. This dissertation examines how two approaches, lean production and digital traceability, contribute to achieving SLO. A systematic literature review following the PRISMA 2020 framework was conducted, applying six search strings across Scopus and Google Scholar for the period 2010 to 2025. Of the 256 records identified across both databases, 57 peer reviewed studies were included following screening and full-text assessment, and were synthesised thematically around four research questions. The findings show that lean production builds organisational legitimacy through tools such as Kaizen, Total Productive Maintenance, standardised work, and Value Stream Mapping, which positively affect worker well-being, safety, and empowerment when implementation is deliberately designed to serve social objectives. Digital traceability, particularly blockchain-based systems, builds informational credibility by reducing information asymmetry and enabling independent verification of sustainability claims. While the Lean 4.0 paradigm demonstrates operational synergies between the two, their combined effect on SLO remains virtually unexamined, only two of 57 studies address all three pillars simultaneously. To address this gap, the dissertation proposes an original conceptual framework mapping pathways from lean (legitimacy) and traceability (credibility) to stakeholder trust, grounded in the three-component SLO model. It establishes a research agenda for future empirical investigation at this intersection.
Parametric design and fabrication of modular façade systems
Pappos, Angelos
This thesis investigates how fabrication constraints can be integrated into the early stages of architectural design to reduce the gap between digital geometric intent and robotic subtractive fabrication. Focusing on modular marble façade systems, the study proposes a fabrication-aware framework in which pattern generation, expected material simulation, robotic movement and CAM preparation were developed as interconnected stages. The workflow embeds parameters such as toolpath continuity, depth modulation, feedrate logic and tool inclination directly into the design process. This approach moves beyond traditional linear CAD/CAM workflows, treating machining parameters as primary drivers of formal expression rather than post-design technical hurdles. The methodology was developed in Grasshopper, evaluated trough robotic simulation in KUKA|prc and CAM preparation in SprutCAM and validated through two series of physical marble prototypes using a 6-axis robot. The results demonstrated that encoding fabrication constraints into parametric patterns significantly reduced machining time and non-cutting motions while enhancing surface quality. The first prototype series confirmed the importance of controlling depth, feedrate and engagement strategy, while the second series validated the use of tool inclination as both a fabrication and a design parameter. The research therefore suggests that toolpaths and robotic traces can become part of the architectural expression of carved stone surfaces, contributing to a more coherent and efficient approach to contemporary digital stereotomy.
A design research approach to sustainable furniture: redesigning the monobloc chair using innovative materials and processes
Lanara, Stamatia Kleopatra
The present dissertation investigates the redesign of the generic plastic monobloc chair through sustainable design principles, use of alternative materials and additive manufacturing technologies. The chair is one of the most widely used objects in everyday life, reflecting social, cultural and technological developments. The monobloc chair’s global presence due to its affordability and industrial efficiency established it as the most democratic seating. However, this typology is also associated with throwaway culture, mass production and reliance on petroleum based plastic products, leading to environmental concerns and waste considerations. Beginning with the historical analysis of chair design, the study examines the interpretation of seatings from ceremonial and symbolic objects into accessible industrial products. It investigates key innovations in furniture design and manufacturing, such as bentwood construction, tubular steel and plastic. Following that, the development of plastic materials, their environmental impacts and the sustainable alternatives as potential substitutes of conventional plastics are reviewed. In this approach, additive manufacturing technologies are analyzed as methods for efficient and environmentally responsible production processes with reduced material waste, energy consumption and on-demand manufacturing. Based on that theoretical framework, a redesigned model of the monobloc chair is proposed, using biodegradable material and 3d printing fabrication techniques. Two prototypes were produced in 1:5 physical scale, using polylactic acid (PLA) filament for the evaluation of the redesigned chair, testing structure, stackability and aesthetic qualities. The redesigned chair maintains the visual connection with the traditional monobloc typology while introducing refined geometry, smoother curves and improved aesthetics. Overall, the project shows how intentional design, sustainable materials and additive manufacturing methods can contribute to the reduction of environmental impact in furniture design, while rethinking everyday objects through responsible design strategies.
Development of a Computational Tool for the Thermal Design of a Cross Flow Heat Exchanger for Efficient Waste Heat Utilization on a Brayton Cycle Gas Turbine.
Kyziridis, Leonidas
This dissertation was written as part of the MSc in Energy Systems at the International Hellenic University. The growing demand for improved energy efficiency in industrial power generation underscores the importance of recovering waste heat from gas turbine exhaust streams. This dissertation presents the development and application of an integrated computational framework for the thermal and economic design of a cross-flow heat exchanger intended for waste-heat recovery from a Brayton-cycle industrial gas turbine. A detailed gas turbine model was first constructed and calibrated in COCO Simulator to replicate the performance of a 25 MW-class unit. The thermodynamic validation ensured consistency with manufacturer data in terms of power output, exhaust temperature, efficiency, and mass flow rate. Building upon this validated turbine model, a custom Excel-based heat exchanger tool was implemented, allowing full control over geometric parameters, empirical heat- transfer correlations (including theZukauskas correlation for crossflow tube banks), NTU-effectiveness analysis, and pressure-drop calculations. A structured parametric study was performed by varying the number of tube rows and columns, tube length, and tube pitch across four compactness levels. A thermo-economic screening criterion, expressed as cost per recovered kilowatt (€/kW), while also cost per Cubic meter (€/m2), enabled objective comparison of design alternatives. The analysis identified an optimal configuration achieving approximately 60-63% Heat exchanger effectiveness while minimizing capital cost per unit of recovered thermal power. The final design was integrated with the turbine exhaust stream, demonstrating substantial heat recovery with acceptable hydraulic impact. The author would like to express sincere gratitude to the supervising Professor Dr. Dimitrios Misirlis for the guidance, constructive feedback, and continuous support throughout the development of this research. His guidance and encouragement were instrumental in shaping both the technical depth and the methodological rigor of this dissertation. Keywords: Gas Turbine Modelling, Waste Heat Recovery, NTU-Effectiveness Method, Crossflow Heat Exchanger, Thermo-Economic Optimization.

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