2024 - Repozytorium publikacji - Politechnika Gdańska

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A probabilistic-driven framework for enhanced corrosion estimation of ship structural components
- Krzysztof Wołoszyk
- Yordan Garbatov
2024 Pełny tekst RELIABILITY ENGINEERING & SYSTEM SAFETY
The work proposes a probabilistic-driven framework for enhanced corrosion estimation of ship structural components using Bayesian inference and limited measurement data. The new approach for modelling measurement uncertainty is proposed based on the results of previous corrosion tests that incorporate the non-uniform character of the corroded surface of structural components. The proposed framework's basic features are outlined, and the detailed algorithm is presented. Further, the proposed framework is validated by comparison with the classical statistical approach and mass measurements, considering previous experimental work results. Notably, the impact of the number of measuring points is investigated, and the accuracy index is proposed to identify the optimum number of measurements. The developed framework has a significant advantage over the classical approach since measuring uncertainty is incorporated. Additionally, the confidence intervals of both mean value corrosion depth and standard deviation could be gathered due to the probabilistic character of the framework. Thus, the presented approach can potentially be used in the structural health monitoring of ship structural components and reliability analysis.
A procedure for the identification of effective mechanical parameters of additively manufactured elements using integrated ultrasonic bulk and guided waves
- Erwin Wojtczak
- Magdalena Rucka
- Angela Andrzejewska
2024 Pełny tekst MEASUREMENT
The subject of the current work was a simple but robust novel two-stage procedure for the non-destructive determination of effective elastic constants using ultrasonic wave propagation. First, ultrasonic bulk wave velocities measured on cubic samples were used to calculate most of the elements of the stiffness matrix. Secondly, the remaining elements were determined using the dispersion curves of elastic guided waves measured on plate samples. Based on the complete stiffness matrix it was possible to calculate the complete set of effective elastic constants. The algorithm was verified for AM elements produced from PLA filament satisfying the conditions of transversely isotropic and orthotropic material models. For the transversely isotropic samples, Young’s moduli (E) varied from 2.6 to 2.9 GPa, shear moduli (G) equalled between 0.9 and 1.2 GPa, whereas Poisson’s ratios (ν) ranged between 0.20 and 0.32. In orthotropic sample the corresponding values were: E = 1.3–2.8 GPa, G = 0.6–1.2 GPa, and ν = 0.07–0.59. The results of the current study have been compared with references from the literature, giving satisfactory agreement.
A procedure for the visualization of fingerprint traces on standard and thermal paper using the electron excitation energy of 1,8-diazafluoren-9- one aggregates in a polyvinylpyrrolidone polymer
- Aneta Lewkowicz
- Martyna Czarnomska
- Emilia Gruszczyńska
- Katarzyna Karpienko
- Maciej Wróbel
- Michalina Chabowska
- Piotr Bojarski
2024 Pełny tekst Z Zagadnień Nauk Sądowych
The scope of this study is a new procedure for visualizing dactyloscopic traces on an absorbent surface using a solution based on aggregates of 1,8-diazafluoren-9-one (DFO) in a polyvinylpyrrolidone polymer (PVP). An absorbent surface is defined as a plain or thermal paper, which is considered to be a difficult surface due to its varying chemical composition. In the case of the thermal paper surface, the procedure can be further improved by the addition of Au/Ag nanoparticles, which cause an enhancement of the fluorescence phenomenon from the surface of the fingerprint. The procedure requires the use of forensic illuminators and filters to reveal traces at the crime scene. Regarding the visualization of fingerprint prints in the forensic laboratory, the use of a stereo fluorescence microscope provides higher-resolution images when analyzing single patterns in the form of minutiae. The presented procedure is competitive with known, highly toxic current methods for revealing dactyloscopic traces using the DFO molecule. It also represents a key contribution to the development of methods for visualizing traces on thermal paper using fluorescent dyes and suitable control of their spectroscopic properties.
A prototype information system for managing and pricing e-waste
- Krystian Jandy
- Paweł Weichbroth
2024 Pełny tekst
There is no doubt that innovation drives development in all areas of human activity, including electrical and electronic equipment. However, the production of new equipment has a significant impact on the natural environment and a relatively high consumption of natural resources. To address these issues, the circular economy has been implemented in recent years by promoting and introducing numerous measures to facilitate the recycling of used goods. However, it has been found that there are many obstacles and difficulties currently faced by decision and policy makers. In this paper, we try to fill the research gap by presenting the prototype of an information system (IS) that could help not only these stakeholders, but also other interested parties, to move towards a circular economy through the efficient management of used electrical and electronic equipment (e-waste). In this context, we present the prototype of the system and elaborate on its two main components, namely functionality and user interface. Furthermore, we discuss the future research directions regarding the development of existing and new system features, followed by a comprehensive usability testing.
A Residential Building Extension Prototype to face Post-Pandemic Needs: Foreseen Challenges and Impacts
- Anna Stefańska
- Carlos C. Duarte
- Katarzyna Zielonko-Jung
- Nuno D. Cortiços
- Daniel Mateus
2024 Green Energy & Environment
The COVID-19 pandemic highlighted the importance of outdoor spaces for maintaining physical and mental well-being. However, many urban residents lack private outdoor areas, which led to harmful health consequences during lockdowns. The research project aims to address and solve this issue by developing a physical/digital prototype called “X-TEND” that extends living space outdoors by attaching it to existing multi-story residential building facades. This prototype intends to promote healthier lifestyles, improving the well-being of individuals and positively impacts the urban surroundings aesthetics. X-TEND prototype uses a light, modular, and prefabricated approach for cost-effectiveness and environmental sustainability. It incorporates generative processes for structural and bioclimatic optimisation complemented by green building strategies to reduce environmental impact while maximising thermal and energy performance. Ultimately, X-TEND prototype contributes to a more sustainable built environment, fostering healthier and more liveable cities for current and future generations.
A review of explainable fashion compatibility modeling methods
- Karolina Selwon
- Julian Szymański
2024 ACM COMPUTING SURVEYS
The paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general characteristics of publicly available datasets that are related to the fashion compatibility recommendation task. Finally, we analyzed the representation bias of datasets, fashion-based algorithms’ sustainability, and explainable model assessment. The paper describes practical problem explanations, methodologies, and published datasets that may serve as an inspiration for further research. The proposed structure of the survey organizes knowledge in the fashion recommendation domain and will be beneficial for those who want to learn the topic from scratch, expand their knowledge, or find a new field for research. Furthermore, the information included in this paper could contribute to developing an effective and ethical fashion-based recommendation system.
A Review of Recent Advances in Human-Motion Energy Harvesting Nanogenerators, Self-Powering Smart Sensors and Self-Charging Electronics
- Justyna Gołąbek
- Michał Strankowski
2024 Pełny tekst SENSORS
In recent years, portable and wearable personal electronic devices have rapidly developed with increasing mass production and rising energy consumption, creating an energy crisis. Using batteries and supercapacitors with limited lifespans and environmental hazards drives the need to find new, environmentally friendly, and renewable sources. One idea is to harness the energy of human motion and convert it into electrical energy using energy harvesting devices—piezoelectric nanogenerators (PENGs), triboelectric nanogenerators (TENGs) and hybrids. They are characterized by a wide variety of features, such as lightness, flexibility, low cost, richness of materials, and many more. These devices offer the opportunity to use new technologies such as IoT, AI or HMI and create smart self-powered sensors, actuators, and self-powered implantable/wearable devices. This review focuses on recent examples of PENGs, TENGs and hybrid devices for wearable and implantable self-powered systems. The basic mechanisms of operation, micro/nano-scale material selection and manufacturing processes of selected examples are discussed. Current challenges and the outlook for the future of the nanogenerators are also discussed.
A review on analytical models of brushless permanent magnet machines
- Ahmed Abbas
- Atif Iqbal
- Arkadiusz Lewicki
- Reddy B. Prathap
- M Mnzool
2024 Pełny tekst INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS
This study provides an in-depth investigation of the use of analytical and numerical methods in analyzing electrical machines. Although numerical models such as the finite-element method (FEM) can handle complex geometries and saturation effects, they have significant computational burdens, are time-consuming, and are inflexible when it comes to changing machine geometries or input values. Analytical models based on magnetic equivalent circuits (MEC) or solving Maxwell's equations can be faster and more flexible, but less accurate for complex machine structures. The paper focuses on the recent development of analytical models for brushless permanent-magnet (PM) machines that have become increasingly popular in low and medium- power applications. The literature review covers the recent developments in analytical models for PM machines with respect to various machine quantities such as magnetic flux density components, induced voltage, inductances, electromagnetic force/torque, efficiency, or unbalanced magnetic force (UMF). It outlines the advantages and disadvantages of different analytical models such as the zero-dimensional (0-D), one-dimensional (1-D), two-dimensional (2-D), and three-dimensional (3-D) analytical methods, as well as the Maxwell and basic mathematical analysis. Although the MEC models are faster than the numerical model, they are not as accurate for various structures of electrical machines including a great magnetic air gap. They also note that the analytical models based on the Maxwell equations are faster than the numerical ones and have the potential to obtain acceptable accuracy similar to the numerical models in electrical machines. Overall, this literature review provides valuable insights for researchers and engineers in selecting appropriate analytical models for PM machines. It highlights the trade-offs between accuracy and computational efficiency when choosing between numerical and analytical models, and the flexibility of analytical models to address changes in machine geometries or input values. Additionally, this helps researchers save time in determining appropriate references regarding the analytical models of brushless PM machines.
A review on carbon storage via mineral carbonation: Bibliometric analysis, research advances, challenge, and perspectives
- Xiaodan Lin
- Xingyang Li
- Hongwen Liu
- Grzegorz Boczkaj
- Yijun Cao
- Chongqing Wang
2024 SEPARATION AND PURIFICATION TECHNOLOGY
Mineral carbonation as a way of carbon storage has received a particular attention in the reduction of carbon dioxide (CO2) emission . This work gives a comprehensive description of the research trends and hotspots in the field of mineral carbonation for carbon storage based on bibliometric analysis. A total of 1507 articles were collected from the Web of Science database from 2010 to 2022 and analyzed in details, using a Citepace and VOSviewer software. Keyword cluster analysis indicates that research on mineral carbonation mainly involves natural minerals, industrial wastes, and cement-based materials. Research advances on carbon storage via mineral carbonation are summarized from the aspects of magnesium-based feedstocks and calcium-based feedstocks. Direct aqueous carbonation and indirect carbonation are the most promising methods. Mining tailings and industrial wastes are promising feedstocks for mineral carbonation. The slow kinetics and low carbonation capacity of feedstocks are the main obstacles for industrial application. Finally, challenges and prospects in mineral carbonation are put forward, which is conducive to its rapid and balanced development. This work provides the basis for the future development of cheap, efficient, and green large-scale mineral carbonation processes for carbon storage.
A review on fungal-based biopesticides and biofertilizers production
- Dante Ferreyra-Suarez
- Octavio García-Depraect
- Roberto Castro Munoz
2024 ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
The escalating use of inorganic fertilizers and pesticides to boost crop production has led to the depletion of natural resources, contamination of water sources, and environmental crises. In response, the scientific community is exploring eco-friendly alternatives, such as fungal-based biofertilizers and biopesticides, which have proven effectiveness in enhancing plant health and growth while sustainably managing plant diseases and pests. This review article examines the production methodologies of these bioproducts, highlighting their role in sustainable agriculture and advancing our understanding of soil microorganisms. Despite their increasing demand, their global market presence remains limited compared to traditional chemical counterparts. The article addresses: 1) the production of biofertilizers and biopesticides, 2) their contribution to crop productivity, 3) their environmental impact and regulations, and 4) current production technologies. This comprehensive approach aims to promote the transition towards more sustainable agricultural practices.
A review on homogeneous and heterogeneous catalytic microalgal lipid extraction and transesterification for biofuel production
- Vinoth Kumar Ponnumsamy
- Hussein Al-Hazmi
- Sutha Shobana
- Jeyaprakash Dharmaraja
- Dipak Ashok Jadhav
- Rajesh Banu J
- Grzegorz Piechota
- Bartłomiej Igliński
- Vinod Kumar
- Amit Bhatnagar
- Kyu-Jung Chae
- Gopalakrishnan Kumar
2024 Pełny tekst CHINESE JOURNAL OF CATALYSIS
Extracting lipids from microalgal biomass presents significant potential as a cost-effective approach for clean energy generation. This can be achieved through the chemical conversion of lipids to produce fatty acid methyl esters via transesterification. The extraction mainly involves free fatty acids, phospholipids, and triglycerides, and requires less energy, making it an attractive option for satisfying the growing demand for fossil-derived energies. Several approaches have been explored for sustainable bioenergy production from microalgal species via catalytic, non-catalytic, and enzymatic transesterification. This review discusses recent insights into microalgal lipid extraction via solvent, Soxhlet, Bligh and Dyer’s, supercritical CO2, and ionic liquids solvent methods and lipid conversion by transesterification and homo/heterogeneous acid/base catalyzed, enzymatic, non-catalytic, and mechanically/chemically catalyzed in-situ techniques towards algal bioenergy production. Technical advances in both extraction and conversion are necessary for the commercialization of renewable energy sources.
A Review on Machine Learning Deployment Patterns and Key Features in the Prediction of Preeclampsia
- Louise Pedersen
- Magdalena Mazur-Milecka
- Jacek Rumiński
- Stefan Rahr Wagner
2024 Machine Learning and Knowledge Extraction
Previous reviews have investigated machine learning (ML) models used to predict the risk of developing preeclampsia. However, they have not addressed the intended deployment of these models throughout pregnancy, nor have they detailed feature performance. This study aims to provide an overview of existing ML models and their intended deployment patterns and performance, along with identified features of high importance. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The search was performed in January and February 2024. It included all papers published before March 2024 obtained from the scientific databases: PubMed, Engineering Village, the Association for Computing Machinery, Scopus, and Web of Science. Of a total of 198 identified studies, 18 met the inclusion criteria. Among these, 11 showed the intent to use the ML model as a single-use tool, two intended a dual-use, and two intended multiple-use. Ten studies listed the features of the highest importance, with systolic and diastolic blood pressure, mean arterial pressure, and hypertension frequently mentioned as critical predictors. Notably, three of the four studies proposing dual or multiple-use models were conducted in 2023 and 2024, while the remaining study is from 2009. No single ML model emerged as superior across the subgroups of PE. Incorporating body mass index alongside hypertension and either mean arterial pressure, diastolic blood pressure, or systolic blood pressure as features may enhance performance. The deployment patterns mainly focused on single use during gestational weeks 11+0 to 14+1.
A Review on Metal–Organic Framework as a Promising Catalyst for Biodiesel Production ENERGY & FUELS
- Giao Van Nguyen
- Prabhakar Sharma
- Marek Dzida
- Van Hung Bui
- Huu Son Le
- Ahmed Shabana El-Shafay
- Huu Cuong Le
- Duc Trong Nguyen Le
- Viet Dung Tran
2024 ENERGY & FUELS
The rapid depletion of fossil-derived fuels along with rising environmental pollution have motivated academics and manufacturers to pursue more environmentally friendly and sustainable energy options in today’s globe. Biodiesel has developed as an ecologically favorable alternative. However, the mass manufacturing of biodiesel on an industrial scale confronts substantial cost and pricing challenges. To address this issue, high-efficiency catalysts with a large number of active sites are needed, resulting in increased biodiesel output and quality. Metal–organic frameworks (MOFs) have received a lot of interest as a catalyst for converting oils/fats or fatty acids into biodiesel. MOFs are polyporous materials that can alter pore size as well as topological structure. They serve as a versatile foundation for designing active sites to satisfy the unique needs of catalytic reactions and conversion pathways. The purpose of this current work is to shed light on the underlying mechanisms and essential properties of MOF-based catalysts used in biodiesel synthesis. In addition, several methods for connecting active sites inside MOFs are scrutinized, while the properties and usability of MOF-based catalysts for the biodiesel production process are completely compared to other catalysts. More importantly, limits and future research directions about the utilization of MOFs in the biodiesel synthesis route are also critically presented. In general, this review contributes to improved awareness about the potential of MOFs in the biodiesel production sector by investigating the primary mechanism and characteristics of MOF-based catalysts.
A Review: Structural Shape and Stress Control Techniques and their Applications
- Ahmed Manguri
- Najmadeen Saeed
- Robert Jankowski
2024 Pełny tekst ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
This review article presents prior studies on controlling shape and stress in flexible structures. The study offers a comprehensive survey of literature concerning the adjustment and regulation of shape, stress, or both in structures and emphasizes such control’s importance. The control of systems is classified into three primary classes: nodal movement control, axial force control, and controlling the two classes concurrently. Each class is thoroughly assessed, showcasing diverse methods anticipated by various scholars. Furthermore, the paper discusses methods to reduce the number of devices (actuators) to adjust and optimize actuators’ placement to achieve optimal structural control, considering the cost implications of numerous actuators. Additionally, various actuators are presented in detail, their advantages and disadvantages are also discussed. Moreover, the applications of the presented techniques are reviewed in detail, the essential recommendations for future work are also suggested.
A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
- Sayed Mohammad Kameli
- Abdelaziz Abuelrub
- Mohammad AlShaikh Saleh
- Shady S. Refaat
- Marek Olesz
- Jarosław Guziński
2024
Partial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency domain, introducing new spectral features that may be beneficial in certain circumstances. Consequently, time delays are introduced, due to the high utilization of computational resources within the signal processing pipeline. Moreover, some microprocessors struggle with the excess computational burden demanded by resource-heavy mathematical transformations. To rectify these issues, an alternative approach is utilized, where Machine learning (ML) algorithms are directly used for the classification of PD severity. Cylindrically-shaped air cavities with lengths ranging from 1mm–6mm are introduced to a resin-based polyethylene terephthalate (PET) insulation material. The cavities are partitioned based on size, to obtain different classes of PD severity. A comparative analysis is performed on various ML algorithms, to determine which algorithm correctly determined the severity of PDs, with highest efficacy. Random Forest was determined to be the most performant, with an accuracy of 98.33%. The high performance illustrates the model’s potential success in accurately determining the hazard level of PDs in real-time, based on merely time-domain signals.
A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
- Jarosław Sadowski
- Jacek Stefański
2024 Pełny tekst SENSORS
This article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the neural network and how the FNN is used in 2D and 3D position estimation process are presented. The most important results of the work are the parameters of various FNN network structures that resulted in a 100% probability of convergence of iterative position estimation algorithms in the exemplary TDoA positioning network, as well as the average and maximum number of iterations, which can give a general idea about the effectiveness of using neural networks to support the position estimation process. In all simulated scenarios, simple networks with a single hidden layer containing a dozen non-linear neurons turned out to be sufficient to solve the convergence problem.
A semiempirical model for low energy electron–atom transport cross sections: The case of noble gases
- Felipe Arretche
- Eliton Popovicz Seidel
- Wagner Tenfen
2024 JOURNAL OF ELECTRON SPECTROSCOPY AND RELATED PHENOMENA
A semiempirical approach to describe low energy electron–atom transport cross sections of easy implementation and reproduction is presented. The heart of the model is an energy independent two-parameter potential that was adjusted to reproduce the accurate total cross sections for He, Ne, Ar and Kr, measured with a threshold photoelectron source technique from meV up to 20 eV. Once the potential was conceived, the model was validated by comparing the values obtained for the calculated scattering lengths and phase shifts with the respective quantities previously reported in the literature. We close the article by presenting the momentum transfer and viscosity cross sections. Good agreement is found when compared to the similar data obtained from swarm experiments, from phase shifts according to differential cross section measurements and to the cross sections reported by sophisticated ab initio relativistic many-body calculations. Tables for the phase shifts and cross sections are provided for direct use and applications.
A simple and efficient hybrid discretization approach to alleviate membrane locking in isogeometric thin shells
- Roger Sauer
- Zhihui Zou
- T.j.r. Hughes
2024 COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
This work presents a new hybrid discretization approach to alleviate membrane locking in isogeometric finite element formulations for Kirchhoff–Love shells. The approach is simple, and requires no additional dofs and no static condensation. It does not increase the bandwidth of the tangent matrix and is effective for both linear and nonlinear problems. It combines isogeometric surface discretizations with classical Lagrange-based surface discretizations, and can thus be run with existing isogeometric finite element codes. Also, the stresses can be recovered straightforwardly. The effectiveness of the proposed approach in alleviating, if not eliminating, membrane locking is demonstrated through the rigorous study of the convergence behavior of several classical benchmark problems. Accuracy gains are particularly large in the membrane stresses. The approach is formulated here for quadratic NURBS, but an extension to other discretization types can be anticipated. The same applies to other constraints and associated locking phenomena.
A simple route of providing a soft interface for PEDOT: PSS film metallic electrodes without loss of their electrical interface parameters
- Karolina Cysewska
- Sylwia Pawłowska
2024 ELECTROCHIMICA ACTA
The work presents the development of a soft interface at PEDOT:PSS film without changing its electrical interface parameters. In the first step, PEDOT:PSS is electrodeposited on the commercial platinum electrode under the state-of-the-art conditions desirable for different electrochemical electrodes. Secondly, a pure hydrogel layer is deposited on the top of the electrodeposited PEDOT:PSS film under conditions that provide desirable mechanical properties (Young's modulus ∼10–20 kPa) and high permeability to ions from the solution. As a result, a PEDOT:PSS electrode with a soft interface desirable for different electrode applications is fabricated. The electrode exhibits electrical parameters at the same level as the state-of-the-art PEDOT:PSS film applied already for electrode applications. Moreover, the hydrogel layer additionally supports the polymeric film's electrochemical stability by inhibiting its oxidative degradation. The thickness of PEDOT film does not affect the overall electrochemical properties of the hydrogel electrode. The work shows that the specific choice of the hydrogel type and fabrication conditions allows to synthesis of the hydrogel interface on a stiff polymeric film, which does not block the ionic and electrical transfer. Moreover, the fabricated PEDOT:PSS electrode with hydrogel interface reveals interfacial impedance and potential window comparable or even better to the already published studies on PEDOT:PSS hydrogels.
A simplified channel estimation procedure for NB-IoT downlink
- Jarosław Magiera
2024 Pełny tekst
This paper presents a low-complexity channel estimation procedure which is suitable for use in energy-efficient NB-IoT user equipment devices. The procedure is based on the well-established least squares scheme, followed by linear interpolation in the time domain and averaging in the frequency domain. The quality of channel estimation vs. signal-to-noise ratio is evaluated for two channel models and compared with the performance of channel estimation function implemented in the Matlab LTE Toolbox. The computational complexities of both implementations are assessed by measuring the average processing times required to obtain channel estimates for a given number of consecutive downlink frames. The results indicate that the proposed method provides a similar quality of channel estimation with considerably shorter processing time compared to its counterpart.