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Ioanna Aslanidou
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Preprint content
Published: 16 July 2021
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ACS Style

Ioanna Aslanidou; Aggelos Gaitanis; Anestis Kalfas. Introduction of a Smartphone Application in an Aeroengine Technology Course. 2021, 1 .

AMA Style

Ioanna Aslanidou, Aggelos Gaitanis, Anestis Kalfas. Introduction of a Smartphone Application in an Aeroengine Technology Course. . 2021; ():1.

Chicago/Turabian Style

Ioanna Aslanidou; Aggelos Gaitanis; Anestis Kalfas. 2021. "Introduction of a Smartphone Application in an Aeroengine Technology Course." , no. : 1.

Preprint content
Published: 16 July 2021
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Ioanna Aslanidou; Valentina Zaccaria; Amare Fentaye; Konstantinos Kyprianidis. Development of Web-Based Short Courses on Control, Diagnostics, and Instrumentation. 2021, 1 .

AMA Style

Ioanna Aslanidou, Valentina Zaccaria, Amare Fentaye, Konstantinos Kyprianidis. Development of Web-Based Short Courses on Control, Diagnostics, and Instrumentation. . 2021; ():1.

Chicago/Turabian Style

Ioanna Aslanidou; Valentina Zaccaria; Amare Fentaye; Konstantinos Kyprianidis. 2021. "Development of Web-Based Short Courses on Control, Diagnostics, and Instrumentation." , no. : 1.

Review article
Published: 01 June 2021 in Frontiers in Mechanical Engineering
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The energy generation landscape is changing, pushed by stricter regulations for emissions control and green energy generation. The limitations of renewable energy sources, however, require flexible energy production sources to supplement them. Micro gas turbine based combined heat and power plants, which are used for domestic applications, can fill this gap if they become more reliable. This can be achieved with the use of an engine monitoring and diagnostics system: real-time engine condition monitoring and fault diagnostics results in reduced operating and maintenance costs and increased component and engine life. In order to allow the step change in the connection of small engines to the grid, a fleet monitoring system for micro gas turbines is required. A proposed framework combines a physics-based model and a data-driven model with machine learning capabilities for predicting system behavior, and includes a purpose-developed diagnostic tool for anomaly detection and classification for a multitude of engines. The framework has been implemented on a fleet of micro gas turbines and some of the lessons learned from the demonstration of the concept as well as key takeaways from the general literature are presented in this paper. The extension of fleet monitoring to optimal operation and production planning in relation to the needs of the grid will allow the micro gas turbines to fit in the future green energy system, connect to the grid, and trade in the energy market. The requirements on the system level for the widespread use of micro gas turbines in the energy system are addressed in the paper. A review of the current solutions in fleet monitoring and diagnostics, generally developed for larger engines, is included, with an outlook into a sustainable future.

ACS Style

Ioanna Aslanidou; Moksadur Rahman; Valentina Zaccaria; Konstantinos G. Kyprianidis. Micro Gas Turbines in the Future Smart Energy System: Fleet Monitoring, Diagnostics, and System Level Requirements. Frontiers in Mechanical Engineering 2021, 7, 1 .

AMA Style

Ioanna Aslanidou, Moksadur Rahman, Valentina Zaccaria, Konstantinos G. Kyprianidis. Micro Gas Turbines in the Future Smart Energy System: Fleet Monitoring, Diagnostics, and System Level Requirements. Frontiers in Mechanical Engineering. 2021; 7 ():1.

Chicago/Turabian Style

Ioanna Aslanidou; Moksadur Rahman; Valentina Zaccaria; Konstantinos G. Kyprianidis. 2021. "Micro Gas Turbines in the Future Smart Energy System: Fleet Monitoring, Diagnostics, and System Level Requirements." Frontiers in Mechanical Engineering 7, no. : 1.

Journal article
Published: 16 November 2020 in Energies
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Subcooled flow boiling occurs in many industrial applications where enormous heat transfer is needed. Boiling is a complex physical process that involves phase change, two-phase flow, and interactions between heated surfaces and fluids. In general, boiling heat transfer is usually predicted by empirical or semiempirical models, which are horizontal to uncertainty. In this work, a data-driven method based on artificial neural networks has been implemented to study the heat transfer behavior of a subcooled boiling model. The proposed method considers the near local flow behavior to predict wall temperature and void fraction of a subcooled minichannel. The input of the network consists of pressure gradients, momentum convection, energy convection, turbulent viscosity, liquid and gas velocities, and surface information. The outputs of the models are based on the quantities of interest in a boiling system wall temperature and void fraction. To train the network, high-fidelity simulations based on the Eulerian two-fluid approach are carried out for varying heat flux and inlet velocity in the minichannel. Two classes of the deep learning model have been investigated for this work. The first one focuses on predicting the deterministic value of the quantities of interest. The second one focuses on predicting the uncertainty present in the deep learning model while estimating the quantities of interest. Deep ensemble and Monte Carlo Dropout methods are close representatives of maximum likelihood and Bayesian inference approach respectively, and they are used to derive the uncertainty present in the model. The results of this study prove that the models used here are capable of predicting the quantities of interest accurately and are capable of estimating the uncertainty present. The models are capable of accurately reproducing the physics on unseen data and show the degree of uncertainty when there is a shift of physics in the boiling regime.

ACS Style

Jerol Soibam; Achref Rabhi; Ioanna Aslanidou; Konstantinos Kyprianidis; Rebei Bel Fdhila. Derivation and Uncertainty Quantification of a Data-Driven Subcooled Boiling Model. Energies 2020, 13, 5987 .

AMA Style

Jerol Soibam, Achref Rabhi, Ioanna Aslanidou, Konstantinos Kyprianidis, Rebei Bel Fdhila. Derivation and Uncertainty Quantification of a Data-Driven Subcooled Boiling Model. Energies. 2020; 13 (22):5987.

Chicago/Turabian Style

Jerol Soibam; Achref Rabhi; Ioanna Aslanidou; Konstantinos Kyprianidis; Rebei Bel Fdhila. 2020. "Derivation and Uncertainty Quantification of a Data-Driven Subcooled Boiling Model." Energies 13, no. 22: 5987.

Review
Published: 29 August 2020 in Sustainability
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In a world of fast technological advancements, it is increasingly important to see how hydrocracking applications can benefit from and adapt to digitalization. A review of hydrocracking processes from the perspective of modeling and characterization methods is presented next to an investigation on digitalization trends. Both physics-based and data-based models are discussed according to their scope of use, needs, and capabilities based on open literature. Discrete and continuous lumping, structure-oriented lumping, and single event micro-kinetic models are reported as well as artificial neural networks, convolutional neural networks, and surrogate models. Infrared, near-infrared, ultra-violet and Raman spectroscopic methods are given with their examples for the characterization of feed or product streams of hydrocracking processes regarding boiling point curve, API, SARA, sulfur, nitrogen and metal content. The critical points to consider while modeling the system and the soft sensor are reported as well as the problems to be addressed. Optimization, control, and diagnostics applications are presented together with suggested future directions of interdisciplinary studies. The links required between the models, soft sensors, optimization, control, and diagnostics are suggested to achieve the automation goals and, therefore, a sustainable operation.

ACS Style

Esin Iplik; Ioanna Aslanidou; Konstantinos Kyprianidis. Hydrocracking: A Perspective towards Digitalization. Sustainability 2020, 12, 7058 .

AMA Style

Esin Iplik, Ioanna Aslanidou, Konstantinos Kyprianidis. Hydrocracking: A Perspective towards Digitalization. Sustainability. 2020; 12 (17):7058.

Chicago/Turabian Style

Esin Iplik; Ioanna Aslanidou; Konstantinos Kyprianidis. 2020. "Hydrocracking: A Perspective towards Digitalization." Sustainability 12, no. 17: 7058.

Research article
Published: 16 January 2020 in International Journal of Mechanical Engineering Education
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The main outcomes of an engineering course should be for the students to achieve the educational goals, enhance their problem solving capabilities and develop essential skills for their future career. In that context, it is important to understand what motivates the students and what helps them develop an engineering mind-set. This paper discusses the improvement of a course with the use of student feedback to motivate students and help them develop essential skills. The purpose of the paper is to provide insight into how different aspects of the course are linked to the students’ growth. Different activities have been integrated in the course over the past years. The effect these have on the student motivation to follow the course and develop skills, knowledge and interest in the subject is discussed through the analysis of student performance, student feedback and the experience of the lecturers. The improvements in the course based on the student feedback were received positively by the students, whose learning experience improved, even though the workload of the course was high. Their motivation to successfully complete the course has also increased through the changes in the delivery of the course and the support by the teachers. The combination of student feedback and teacher experience is key for the improvement of a course, while ensuring that the students develop their engineering knowledge. Therefore, the teachers should strike a balance between helping the students find the solution and encouraging them to think on their own in order to develop essential skills.

ACS Style

Ioanna Aslanidou; Nathan Zimmerman; Evangelia Pontika; Anestis I Kalfas; Konstantinos G Kyprianidis. Reforming heat and power technology course using student feedback to enhance learning experience. International Journal of Mechanical Engineering Education 2020, 1 .

AMA Style

Ioanna Aslanidou, Nathan Zimmerman, Evangelia Pontika, Anestis I Kalfas, Konstantinos G Kyprianidis. Reforming heat and power technology course using student feedback to enhance learning experience. International Journal of Mechanical Engineering Education. 2020; ():1.

Chicago/Turabian Style

Ioanna Aslanidou; Nathan Zimmerman; Evangelia Pontika; Anestis I Kalfas; Konstantinos G Kyprianidis. 2020. "Reforming heat and power technology course using student feedback to enhance learning experience." International Journal of Mechanical Engineering Education , no. : 1.

Review
Published: 06 November 2019 in Sustainability
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The correct and early detection of incipient faults or severe degradation phenomena in gas turbine systems is essential for safe and cost-effective operations. A multitude of monitoring and diagnostic systems were developed and tested in the last few decades. The current computational capability of modern digital systems was exploited for both accurate physics-based methods and artificial intelligence or machine learning methods. However, progress is rather limited and none of the methods explored so far seem to be superior to others. One solution to enhance diagnostic systems exploiting the advantages of various techniques is to fuse the information coming from different tools, for example, through statistical methods. Information fusion techniques such as Bayesian networks, fuzzy logic, or probabilistic neural networks can be used to implement a decision support system. This paper presents a comprehensive review of information and decision fusion methods applied to gas turbine diagnostics and the use of probabilistic reasoning to enhance diagnostic accuracy. The different solutions presented in the literature are compared, and major challenges for practical implementation on an industrial gas turbine are discussed. Detecting and isolating faults in a system is a complex problem with many uncertainties, including the integrity of available information. The capability of different information fusion techniques to deal with uncertainty are also compared and discussed. Based on the lessons learned, new perspectives for diagnostics and a decision support system are proposed.

ACS Style

Valentina Zaccaria; Moksadur Rahman; Ioanna Aslanidou; Konstantinos Kyprianidis. A Review of Information Fusion Methods for Gas Turbine Diagnostics. Sustainability 2019, 11, 6202 .

AMA Style

Valentina Zaccaria, Moksadur Rahman, Ioanna Aslanidou, Konstantinos Kyprianidis. A Review of Information Fusion Methods for Gas Turbine Diagnostics. Sustainability. 2019; 11 (22):6202.

Chicago/Turabian Style

Valentina Zaccaria; Moksadur Rahman; Ioanna Aslanidou; Konstantinos Kyprianidis. 2019. "A Review of Information Fusion Methods for Gas Turbine Diagnostics." Sustainability 11, no. 22: 6202.

Journal article
Published: 16 April 2018 in Journal of Turbomachinery
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In gas turbines with can combustors, the trailing edge (TE) of the combustor transition duct wall is found upstream of every second vane. This paper presents an experimental and numerical investigation of the effect of the combustor wall TE on the aerothermal performance of the nozzle guide vane. In the measurements carried out in a high-speed experimental facility, the wake of this wall is shown to increase the aerodynamic loss of the vane. On the other hand, the wall alters secondary flow structures and has a protective effect on the heat transfer in the leading edge-endwall junction, a critical region for component life. The different clocking positions of the vane relative to the combustor wall are tested experimentally and are shown to alter the aerothermal field. The experimental methods and processing techniques adopted in this work are used to highlight the differences between the different cases studied.

ACS Style

Ioanna Aslanidou; Budimir Rosic. Effect of the Combustor Wall on the Aerothermal Field of a Nozzle Guide Vane. Journal of Turbomachinery 2018, 140, 051010 .

AMA Style

Ioanna Aslanidou, Budimir Rosic. Effect of the Combustor Wall on the Aerothermal Field of a Nozzle Guide Vane. Journal of Turbomachinery. 2018; 140 (5):051010.

Chicago/Turabian Style

Ioanna Aslanidou; Budimir Rosic. 2018. "Effect of the Combustor Wall on the Aerothermal Field of a Nozzle Guide Vane." Journal of Turbomachinery 140, no. 5: 051010.

Journal article
Published: 19 July 2017 in Journal of Turbomachinery
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This paper presents an experimental investigation of the concept of using the combustor transition duct wall to shield the nozzle guide vane leading edge. The new vane is tested in a high-speed experimental facility, demonstrating the improved aerodynamic and thermal performance of the shielded vane. The new design is shown to have a lower average total pressure loss than the original vane, and the heat transfer on the vane surface is overall reduced. The peak heat transfer on the vane leading edge–endwall junction is moved further upstream, to a region that can be effectively cooled as shown in previously published numerical studies. Experimental results under engine-representative inlet conditions showed that the better performance of the shielded vane is maintained under a variety of inlet conditions.

ACS Style

Ioanna Aslanidou; Budimir Rosic. Aerothermal Performance of Shielded Vane Design. Journal of Turbomachinery 2017, 139, 111003 .

AMA Style

Ioanna Aslanidou, Budimir Rosic. Aerothermal Performance of Shielded Vane Design. Journal of Turbomachinery. 2017; 139 (11):111003.

Chicago/Turabian Style

Ioanna Aslanidou; Budimir Rosic. 2017. "Aerothermal Performance of Shielded Vane Design." Journal of Turbomachinery 139, no. 11: 111003.