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Gdańsk University of Technology

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Publications from the year 2024

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  • Design and Performance Evaluation of the Energy Subsystem of a Hybrid Light andWave Energy Harvester
    • Marcin Drzewiecki
    • Piotr Kołodziejek
    • Jarosław Guziński
    2024 Full text ENERGIES

    The paper presents the design and performance of an energy subsystem (ES) dedicated to hybrid energy harvesters (HEHs): wave energy converters (WECs) combined with photovoltaic panels (PVPs). The considered ES is intended for compact HEHs powering autonomous end-node devices in distributed IoT networks. The designed ES was tested experimentally and evaluated in relation to the mobile and wireless distributed communication use case. The numerical evaluation was based on the balance of the harvested energy versus the energy consumed in the considered use case. The evaluation results proved that the ES ensured energy surplus over the considered IoT node consumption. It confirmed the proposed solution as convenient to the compact HEHs applied for sustainable IoT devices to power them with renewable energy harvested from light and sea waves. It was found that the proposed ES can provide the energy autonomy of the IoT end node and increase its reliability through a hybrid energy-harvesting approach.

  • DESIGN ERRORS CAUSE AN EMERGENCY OF THE REINFORCED CONCRETE TANK FOR COKE
    • Tomasz Majewski
    • Maciej Niedostatkiewicz
    2024

    The quality of the developed design documentation and the maintenance of the technological regime during construction works have a decisive impact on the subsequent safety of the structure, as well as the safety of use of the building. The paper describes the defects and damages of an open, rectangular reinforced concrete tank for hot process water, which failed during a short period of operation. The article also presents the proposed solution to remove the existing damage to the tank structure.

  • Design of a Cellular Dual-Band Sticker Antenna for Thickness-Independent 3D-Printed Substrates
    • Adrian Bekasiewicz
    • Khadijeh Askaripour
    • Marek Wójcikowski
    • Tuan-Vu Cao
    2024 Full text

    Additive manufacturing technology provides high flexibility in designing custom enclosures for prototype devices such as nodes of distributed sensor networks. Although integration of components is desired from the perspective of sensor mobility, it might negatively affect the performance of radio-connectivity due to couplings between the antenna and system peripherals, as well as other unaccounted effects of the 3D printed enclosure. In this work, a design of a dual-band cellular antenna is considered. The structure is optimized to work on plastic substrates characterized by thicknesses ranging from 1 mm to 5 mm, respectively. The antenna features a –10 dB bandwidth within frequencies from 0.74 GHz to 1.05 GHz and 1.49 GHz to 1.92 GHz. Owing to a simple topology the structure can be implemented in the form of a copper-based sticker and attached on a 3D printed material (e.g., the enclosure of the device). The radiator has been compared against the state-of-the-art antennas in terms of bandwidth and gain.

  • Design of a Shape-Memory-Alloy-Based Carangiform Robotic Fishtail with Improved Forward Thrust
    • Mithilesh Kumar Koiri
    • Dubey Vineet
    • Kumar Anuj Sharma
    • Daniel Chuchała
    2024 Full text SENSORS

    Shape memory alloys (SMAs) have become the most common choice for the development of mini- and micro-type soft bio-inspired robots due to their high power-to-weight ratio, ability to be installed and operated in limited space, silent and vibration-free operation, biocompatibility, and corrosion resistance properties. Moreover, SMA spring-type actuators are used for developing different continuum robots, exhibiting high degrees of freedom and flexibility. Spring- or any elasticmaterial- based antagonistic or biasing force is mostly preferred among all other biasing techniques to generate periodic oscillation of SMA actuator-based robotic body parts. In this model-based study, SMA-based spring-type actuators were used to develop a carangiform-type robotic fishtail. Fin size optimization for the maximization of forward thrust was performed for the developed system by varying different parameters, such as caudal fin size, current through actuators, pulse-width modulation signal (PWM), and operating depth. A caudal fin with a mixed fin pattern between the Lunate and Fork “Lunafork” and a fin area of approximately 5000 mm2 was found to be the most effective for the developed system. The maximum forward thrust developed by this fin was recorded as 40 gmf at an operation depth of 12.5 cm in a body of still water.

  • Design of Compact and Wideband Groove Gap Waveguide-Based Directional Couplers
    • Mahdieh Rabbanifard
    • Davood Zarifi
    • Ali Farahbakhsh
    • Michał Mrozowski
    2024 IEEE Access

    This paper proposes a compact cross-shaped groove gap waveguide structure for creating wideband and compact directional couplers with different coupling levels. Groove gap waveguide technology is applied to overcome fabrication challenges of printed and hollow waveguide structures in high frequency bands. The validity of the novel concept is demonstrated through the design and evaluation of several compact broadband directional couplers, featuring 3-, 4.5-, 6-, and 10- dB coupling levels, alongside the fabrication and testing of a compact, wideband 3-dB directional coupler prototype. In addition, an equivalent circuit is proposed to present the behavior of the 3-dB coupler. The comparison of simulation and experimental results for the prototype shows good agreement. The measured transmission coefficients in the output ports are −3±0.5 dB with a phase imbalance of ±2.5∘ over 17.9-24 GHz frequency band. The findings confirm the suitability of the proposed directional coupler structure as a compact and self-packaged solution for high-frequency applications.

  • Designing a high-sensitivity dual-band nano-biosensor based on petahertz MTMs to provide a perfect absorber for early-stage non-melanoma skin cancer diagnostic
    • Musa Hamza
    • Mohammad Islam
    • Sunil Lavadiya
    • Sławomir Kozieł
    • Iftikhar Din Ud
    • Bruno Sanches
    2024 Full text IEEE SENSORS JOURNAL

    The purpose of this study is development of a novel high-performance low-Petahertz (PHz) biosensor for non-melanoma skin cancer (NMSC) diagnosis. The presented device is designed to work within a microwave imaging regime, which is a promising alternative to conventional diagnostic methods such as visual examination, dermoscopy, and biopsy. The suggested biosensor incorporates a dual-band perfect absorber (operating bands at 0.909 PHz and 1.215 PHz) constructed using aluminum layers separated by a dielectric material. Numerical studies confirm its suitability for NMSC diagnosis, enabling discrimination between healthy and cancerous skin tissues and precise visualization of affected areas. Compared to existing THz devices, the proposed biosensor offers improved sensitivity, a smaller size, and enhanced resolution, attributed partially to the transition to the petahertz band. Moreover, our research highlights the potential of PHz spectroscopy for biomarker detection, advancing non-invasive microwave imaging techniques for NMSC and other skin cancers. The proposed biosensor boasts higher sensitivity, figure of merit (FOM), and quality factor (Q-factor), while its insensitivity to polarization angle ensures superior signal-to-noise ratio and high-resolution imaging, instilling confidence in specialists.

  • Designing a High-sensitivity Microscale Triple-band Biosensor based on Terahertz MTMs to provide a perfect absorber for Non-Melanoma Skin Cancer diagnostic
    • Musa Hamza
    • Mohammad Islam
    • Sławomir Kozieł
    • Muhammad Hamad
    • Iftikhar Din Un
    • Ali Farmani
    • Sunil Lavadiya
    • Mohammad Alibakhshikenari
    2024 Full text IEEE Photonics Journal

    Non-melanoma skin cancer (NMSC) is among the most prevalent forms of cancer originating in the top layer of the skin, with basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) being its primary categories. While both types are highly treatable, the success of treatment hinges on early diagnosis. Early-stage NMSC detection can be achieved through clinical examination, typically involving visual inspection. An alternative, albeit invasive, method is a skin biopsy. Microwave imaging has gained prominence for non-invasive early detection of various cancers, leveraging distinct dielectric properties of healthy and malignant tissues to discriminate tumors and categorize them as benign or malignant. Recent studies demonstrate the potential of terahertz (THz) spectroscopy for detecting biomarkers by aligning electromagnetic wave frequencies in the low THz range (0.1 to 10 THz) with resonant frequencies of biomolecules, such as proteins. This study proposes an innovative microscale biosensor designed to operate in the THz range for the high-sensitivity and efficient diagnosis of non-melanoma skin cancer. By incorporating meticulously designed metamaterial layers, the sensor's absorption properties can be controlled, a critical aspect for discriminating between normal and NMSC-affected skin. In particular, the interaction between skin and THz waves, influenced by dielectric properties and unique vibrational resonances of molecules within tissue, is crucial for wave propagation and scattering. Extensive numerical studies showcased the suitability of the proposed biosensor for NMSC diagnosis, illustrated through specific case studies. These findings hold the potential to pave the way for further development of non-invasive microwave-imaging-based techniques for detecting NMSC and other types of skin cancer.

  • Designing learning spaces through international and interdisciplinary collaborative design studio: The case of engineer architects and pedagogic students
    • Dorota Wojtowicz-Jankowska
    • Einat Gil
    • Ziemowit Belter
    2024 World Transactions on Engineering and Technology Education

    The study explores the dynamics and outcomes of an international interdisciplinary design studio focusing on innovative learning spaces. Conducted over two years between students of Faculty of Architecture at Gdansk Tech and pedagogic students from Kibbutzim College in Tel Aviv, this design-based study examines the contributions of unique educational program to student learning, the evolution of the design process, collaboration, and the challenges and opportunities that arose from the complex context. Students tackled real-world design challenges and employed digital collaboration tools. The analysis utilized two structured questionnaires to evaluate design process key aspects, with a significant self-reported value of acquired knowledge and skills for both courses and increase in maximum satisfaction ratings in the second year, suggesting a more engaging and rewarding experience for dedicated students.

  • Desirability-based optimization of dual-fuel diesel engine using acetylene as an alternative fuel
    • Van Giao Nguyen
    • Dager Brijesh
    • Ajay Chhillar
    • Sharma Prabhakar
    • M. Sameh Osman
    • Duc. T. Nguyen
    • Jerzy Kowalski
    • Hai Thanh Truong
    • Prem Shanker Yadav
    • Dao Nam Cao
    • Viet Dung Tran
    2024 Full text Case Studies in Thermal Engineering

    he study examined the dual-fuel engine performance employing acetylene gas as primary fuel and diesel as pilot fuel. The engine's operational parameters were adjusted using the Box-Behnken design, and the results were recorded. The best operating settings were yielded as 81.25 % engine load, 4.48 lpm acetylene gas flow rate and the compression ratio were 18. At this optimized setting the BTE was 27.1 % and the engine emitted 360 ppm of NOx, 56.2 ppm of HC, 104 ppm of CO. The experimental data at optimized setting was compared to the optimized results, and the percentage of errors was within 7 %. Two advanced machine learning methods, LightGBM and Tweedie, were used to predict engine efficiency and emissions. Tweedie-based models had an R2 value of 0.89–1, while LightGBM-based models had an R2 value of 0.38–1. The mean squared error was 0.24–45.04 for Tweedie-based models and 8.5 to 153.89 for LightGBM-based models. On the basis of R2 and MSE, it was observed that Tweedie was superior at making predictions than LightGBM. The study demonstrated the efficient functioning of a dual-fuel engine using acetylene as an alternative fuel for increased performance and lower emissions.

  • Detailed studies of superconducting properties of Y2Pd1.25Ge2.75
    • Hanna Świątek
    • Szymon Królak
    • Leszek Litzbarski
    • Ihor Oshchapovskyy
    • Michał Winiarski
    • Tomasz Klimczuk
    2024 Full text JOURNAL OF ALLOYS AND COMPOUNDS

    We report a successful synthesis of a high-purity intermetallic germanide Y2Pd1.25Ge2.75, crystallizing in the disordered variant of the AlB2-type structure. A single-phase sample was obtained via arc-melting by deliberately tuning the composition out of the ideal 2:1:3 ratio. Specific heat, electrical resistivity and magnetization measurements show that the compound is a weakly-coupled (λ e-p = 0.58) type-II superconductor with a superconducting transition at Tc = 2.72 K. Additional magnetization measurements conducted under pressure up to 0.55 GPa show suppression of Tc, at a rate of − 0.17 K/GPa. Electronic structure calculations reveal the deep similarity between Y2Pd1.25Ge2.75 and other AlB2-type germanide superconductors, especially the ordered YGa2 phase.

  • Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
    • Aleksander Madajczak
    • Marcin Ciecholewski
    2024

    The effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The recognition of small and overlapping objects is often very problematic. The highest valued classifiers are universal ones that help accurately detect objects of various categories. This research project compared the efficiency of detecting objects of various categories, such as airports, helicopters, planes, fuel tanks and warships, using various modern neural network architectures in the public remote-sensing dataset for geospatial object detection (RSD-GOD). The results presented in this paper are better than the results of detecting objects of the same categories in the RSD-GOD dataset produced by previous studies.

  • Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
    • Praveena Ganesan
    • G. P. Ramesh
    • Przemysław Falkowski-Gilski
    • Bożena Falkowska-Gilska
    2024 Full text Frontiers in Physiology

    Introduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because it efficiently reflects the brain variations. Methods: Machine learning and deep learning models are widely applied on sMRI images for AD detection to accelerate the diagnosis process and to assist clinicians for timely treatment. In this article, an effective automated framework is implemented for early detection of AD. At first, the Region of Interest (RoI) is segmented from the acquired sMRI images by employing Otsu thresholding method with Tunicate Swarm Algorithm (TSA). The TSA finds the optimal segmentation threshold value for Otsu thresholding method. Then, the vectors are extracted from the RoI by applying Local Binary Pattern (LBP) and Local Directional Pattern variance (LDPv) descriptors. At last, the extracted vectors are passed to Deep Belief Networks (DBN) for image classification. Results and Discussion: The proposed framework achieves supreme classification accuracy of 99.80% and 99.92% on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarker and Lifestyle flagship work of ageing (AIBL) datasets, which is higher than the conventional detection models.

  • Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
    • Krzysztof Pastuszak
    • Michał Sieczczyński
    • Marta Dzięgielewska
    • Rafał Wolniak
    • Agata Drewnowska
    • Marcel Korpal
    • Laura Zembrzuska
    • Anna Supernat
    • Anna J. Żaczek
    2024 Full text Scientific Reports

    Circulating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically comprises thousands of gene expression reads per cell, which artificial intelligence algorithms can accurately analyze. This work presents machine-learning-based classifiers that differentiate CTCs from peripheral blood mononuclear cells (PBMCs) based on single cell RNA sequencing data. We developed four tree-based models and we trained and tested them on a dataset consisting of Smart-Seq2 sequenced data from primary tumor sections of breast cancer patients and PBMCs and on a public dataset with manually annotated CTC expression profiles from 34 metastatic breast patients, including triple-negative breast cancer. Our best models achieved about 95% balanced accuracy on the CTC test set on per cell basis, correctly detecting 133 out of 138 CTCs and CTC-PBMC clusters. Considering the non-invasive character of the liquid biopsy examination and our accurate results, we can conclude that our work has potential application value.

  • Detection of Closing Crack in Beam Based on Responses Induced by Harmonic Excitation
    • Samrawit Alemayehu Tewelde
    • Marek Krawczuk
    2024 Full text SENSORS

    The non-linear contact model was chosen to simulate the closed crack in the cantilever beam. The study examines the shape and characteristics of the phase diagram of a cantilever beam with closed cracks. It investigates how various crack properties influence the geometry of the phase diagram and proposes a method for identifying cracks based on their features. The area of each closed curve in the phase diagram is determined using the pixel method. Based on the results, the contact model proves effective in simulating closed cracks and is sensitive to nonlinear closing cracks. The vibration responses of beams with different damage severity and positions exhibit distinct geometric features. The crack parameter is identified by locating the intersection of contour lines on the maps. According to numerical calculations, the phase diagrams for superharmonic resonance seem to be more susceptible to changes in closed cracks with varied damage locations and severity. The wavelet transform is also employed to identify closed cracks using RMS signals, and the results are compared with those obtained from the phase diagram.

  • Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
    • Jakub Konert
    • Adam Dradrach
    • Jacek Rumiński
    2024

    Every year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and machine learning. Two types of cameras, RGB and thermal, were integrated and calibrated to form a multimodal imaging system. The system was designed and implemented to acquire real-world data for bathing people in swimming pools. The EfficientDet models were adapted and trained on collected data reaching at least 94% detection accuracy, with the highest result equal to 97.47%. The best accuracy obtained for the thermal data was lower and equal to 94.85%. However, thermal imaging allows observing scenes in low-light conditions or darkness. This could potentially highly improve the effectiveness of rescue missions, decreasing the death rates or improving the health of early rescued people. Thermal imaging could also be more acceptable regarding privacy, as high-frequency biometric features are not as easy to extract from thermal images as from high-resolution RGB images.

  • Determination of safety indicators of the freight wagons by mobile systems
    • Oleksij Fomin
    • P. Prokopenko
    • Ievgen Medvediev
    • L. Degtyareva
    2024 Procedia Structural Integrity

    The organization of the movement of freight trains in Ukraine is an important factor in integrating the country’s railway transport into the European system. A situation that requires a significant renewal of the freight wagon park with modern wagons to meet the freight transportation requirements has arisen. Also, a significant drawback of railway transport in Ukraine is the limitation of the speed of trains, which include freight wagons with a reduced container in an empty state, therefore, at the moment, the issue of improving the methodological and software and instrumental testing tools for evaluating the quality and safety indicators of the movement of such wagons is relevant at the moment. At present, laboratory wagons are used during field tests related to the evaluation of traffic quality indicators, acceptance and admission to operation of railway rolling stock, but the modern state of development of measuring equipment allows in most cases to abandon the use of such wagons during running tests of units rolling stock in favor of mobile hardware and software complexes.

  • Determination of Sodium Ion Diffusion Coefficient in Tin Sulfide@Carbon Anode Material Using GITT and EIS Techniques
    • Andrzej Nowak
    • Paweł Rutecki
    • Mariusz Szkoda
    • Konrad Trzciński
    2024 ENERGIES

    The electroanalytical behavior of SnSx (x = 1, 2) encapsulated into a carbon phase was studied using the galvanostatic intermittent titration technique (GITT) and electrochemical impedance spectroscopy (EIS). These techniques are widely utilized in battery systems to investigate the diffusion of alkali metal cations in anode and cathode materials depending on the concentration of ions in the host material. Here, we report different calculation methods showing how the applied model affects the derived diffusion coefficient. The calculated value of the apparent chemical diffusion coefficient of sodium ions ((Formula presented.)) is in the range of 1 × 10−10 to 1 × 10−15 cm2/s depending on the technique, mathematical protocol, geometry of the electrode material, and applied potential.

  • Determination of the shape of the CFGFT cylindrical column based on laboratory tests
    • Eligiusz Mieloszyk
    • Marcin Abramski
    • Anita Milewska
    2024 Full text MEASUREMENT

    Analyses were carried out on glass-fibre-reinforced polymer tube columns with reference to laboratory tests. The angles of the glass fibre beams were 20◦, 55◦ and 85◦. The study employed non-classical operational calculus. Various modulated harmonic signal shapes were considered for columns and tubes at buckling. The buckling loads were assessed and compared for different models.

  • Determining an Architectural Character for Durban Residential Streetscapes
    • Louis du Plessis
    2024 Full text

    In the current global context and in consideration of the Sustainable Development Goals, there is a strong need for urban densification. However, this development is also driven by processes linked to the idea of capitalism and 'economic growth'. Such development often leads to the loss of the 'genius loci' of a place and sometimes even overlooks the fact that the quality of the built environment greatly influences the health and well-being of city dwellers. An important element of the quality of an urban structure is its urban landscape - referred to in this thesis as 'streetscape character'. At present, decision-makers involved in urban development unfortunately perceive little value in the quality aspects of this element and are poorly equipped to maintain or improve the existing streetscape character. The thesis research, using the example of an inner city neighbourhood in Durban, showed that a gap in current research and practical approaches is the recognition of the importance of the architectural details of buildings that define the appearance of the street. The paper shows how key these elements are to the construction of the streetscape and how they allow the context of a place to be described. The work concludes by demonstrating how these elements can support the process of maintaining a distinctive townscape. These findings can be translated into practical aspects and can be used in urban development management decisions to maintain or improve the character of the streetscape, which will ultimately contribute to the creation of a unique 'genius loci'.

  • Development and experimental validation of a novel double-stage yield steel slit damper-buckling restrained brace
    • Farzin Kazemi
    • Neda Asgarkhani
    • Natalia Lasowicz
    • Robert Jankowski
    2024 ENGINEERING STRUCTURES

    This research is focused on the development and experimental validation of a novel double-stage yield steel slit damper-buckling restrained brace (SSD-DYB) system designed for seismic resistance of steel structures. The SSD-DYB integrates the energy dissipation capability of a steel slit damper (SSD) in its initial segment, enhancing performance in the case of lower seismic intensities levels while employing a larger segment for higher load resistance to maintain structural stability. The results of the study show that the proposed SSD-DYB is capable to reduce the weight of similar all-steel buckling restrained braces (BRBs) successfully addressing critical points through stiffeners and top and bottom plates. Additionally, the U-shaped element exhibits resilience during seismic loads, indicating its potential for replacing cores without failure which would be beneficial for seismic retrofitting of buildings. Experimental tests show that varying the number and shape of SSD strips significantly impacts the hysteresis curve's maximum load and dissipated energy (i.e., adding strips increased energy dissipation by 33.48 % for SSD-DYB-1), which can be used to control the proposed device for a specific performance target. Stopper mechanisms within the SSD-DYB regulate load distribution between segments and can be used to control the device and its transmitting capacities. Finally, an optimized SSD-DYB has been proposed with promising performance to be used by researchers for designing new structures or retrofit old ones.