New doctoral dissertation

June 11, 2025

VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Investigation of operating modes of a variable circuit volume heat pump in a mechanical ventilation system“  („Kintamo kontūro tūrio šilumos siurblio veikimo režimų tyrimas mechaninio vėdinimo sistemoje“) prepared by VILNIUS TECH, Anton Frik. The dissertation was prepared in 2019–2025. Scientific Consultant – Prof. Dr Habil. Vytautas Martinaitis.

The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Mechanical Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 10 a.m. on 11 June 2025.

The dissertation investigates the thermodynamic operating cycle and parameter control of a heat pump integrated into a mechanical ventilation system through analytical, experimental research, and numerical modelling. The research explores how variations in the heat pump circuit volume influence system efficiency under changing outdoor air conditions. The primary aim is to develop a control method to enhance the seasonal operating efficiency of a heat pump integrated into a building ventilation system. The dissertation addresses several key objectives: developing an analytical thermodynamic model and performing parametric analysis; designing and constructing an experimental test bench, followed by experimental investigations under various operating conditions; creating a mechanism for adjusting the heat pump circuit volume and evaluating its impact on system parameters and seasonal efficiency. The dissertation consists of an introduction, three chapters, general conclusions, references, the author’s publications on the topic, and two appendices. The introduction discusses the research problem and relevance, describes the object of investigation, formulates the aim and specific objectives, outlines the methodology, highlights the scientific novelty and practical significance, and presents defendable statements. It concludes with an overview of the author’s publications and conference presentations related to the topic, and a description of the dissertation structure. The First Chapter provides a literature review on heat pump applications in ventilation systems, their control principles, and technological solutions. It identifies key research directions and refines objectives. The Second Chapter describes the research methodology, the design of the experimental setup, and the procedure for conducting the tests. Additionally, the chapter outlines the operating algorithm of the numerical heat pump model and seasonal efficiency evaluation principles. The Third Chapter presents the results of analytical, experimental, and numerical modelling studies. It evaluates the impact of circuit volume adjustment on the performance and efficiency of the heat pump under varying operating conditions and provides a comparative analysis of heat pump operation in European regions with different climates. Nine scientific publications related to the dissertation have been published, including two in peer-reviewed journals indexed in Web of Science with citation indices. The results have been presented at four international scientific conferences in Lithuania and abroad.

Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.

Related news

New doctoral dissertation
New doctoral dissertation
VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Research and application of machine learning methods for migraine attack prediction“ prepared at VILNIUS TECH by Viroslava Kapustynska. The dissertation was prepared in 2021–2026. Scientific consultant – Prof. Dr Šarūnas Paulikas. The dissertation was defended at the public meeting of the Dissertation Defense Council of the Scientific Field of Electrical and Electronic Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 2 p.m. on 9 June 2026. Migraine is a complex neurological disorder characterized by strong inter- and intra-individual variability, which makes early forecasting difficult using only clinical observations. Wearable biosensors combined with machine learning offer new opportunities to detect subtle physiological changes that may precede migraine attacks and to develop individualized prediction models. This dissertation investigates migraine analysis and next-day prediction using physiological recordings collected under real-life monitoring conditions. Data were obtained with the Empatica Embrace Plus wearable device and include electrodermal activity, pulse rate, skin temperature, and movement-related signals. The analysis focuses on nocturnal recordings, since the night period provides a more stable physiological context with fewer external disturbances. Nights were standardized using sleep-based contextual selection and consistent night-level rules. The experimental framework is organized in two stages. In the first stage, a window-level binary classification task is used as an exploratory methodological analysis to examine how design choices influence model performance. Night recordings are segmented into analysis frames ranging from 5 to 120 minutes, statistical features are extracted, and the influence of signal preprocessing and feature representation is evaluated across several classifier families, including Random Forest, XGBoost, histogram-based gradient boosting, support vector machines, and k-nearest neighbors. In the second stage, the research evaluates next-day migraine prediction based on whole-night recordings. This stage refines the experimental methodology to obtain more reliable estimates of predictive performance under a stricter validation framework. The analysis focuses on the effect of temporal aggregation while comparing the same classifier families under consistent evaluation conditions. The results demonstrate considerable variability across participants in achievable prediction performance and optimal modeling configurations. Shorter analysis frames generally preserve informative short-term physiological changes, whereas longer windows tend to smooth these variations. Signal preprocessing shows a window-dependent effect and does not consistently improve performance. Overall, the results highlight the importance of temporal resolution, rigorous validation, and individualized modeling for wearable-based migraine prediction systems. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.
More
Expert Evaluation: VILNIUS TECH’s Progress Exceeded Expectations
Expert Evaluation: VILNIUS TECH’s Progress Exceeded Expectations
VILNIUS TECH has received a highly positive assessment from international experts. In their recently published conclusions, it is noted that since the 2022 institutional evaluation, the university has achieved significant, evidence-based progress across all four evaluation areas: governance, quality assurance, studies and research activities, and impact on regional and national development. In 2022, VILNIUS TECH was granted a seven-year accreditation. At that time, the expert panel provided the university with 19 recommendations for further improvement. The latest progress review concludes that the university responded to these recommendations responsibly, systematically, and constructively, and that the implemented changes have become part of long-term institutional development. „We are pleased that external experts have highly evaluated the progress achieved by VILNIUS TECH across all four assessment areas. It was noted that the university demonstrates a mature quality culture, a strategic vision, and the ability to consistently sustain growth and increase its impact on society. This ensures that we are entering the next institutional evaluation period with a strong position,“ says Nora Skaburskienė, Director of the Studies Directorate. International experts particularly highlighted the consistently strengthened system of strategic management, the quality culture, active collaboration with business and alumni, leadership within the ATHENA European Universities Alliance, the development of new interdisciplinary study programmes, and significant progress in innovation and technology transfer. The rapid expansion of lifelong learning activities was also noted — VILNIUS TECH has broadened its micro-credential offerings, strengthened partnerships with social and business partners, and is creating favourable conditions for knowledge commercialization and startup development. According to the expert panel, the university has already moved beyond the stage of merely responding to recommendations and is now ready to purposefully leverage its accumulated potential to achieve even higher performance results. In summarizing the evaluation, the experts concluded that VILNIUS TECH is entering the next phase of institutional assessment with a solid foundation for continued successful development.
More