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Politechniki Gdańskiej

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  • Computational Bar Size Optimization of Single Layer Dome Structures Considering Axial Stress and Shape Disturbance
    • Ahmed Manguri
    • Najmadeen Saeed
    • Farzin Kazemi
    • Neda Asgarkhani
    • Marcin Szczepański
    • Robert Jankowski
    2024

    A computational method is proposed in this paper to minimize the material usage in the construction of modern spatial frame structures by prestressing a minimal number of members. The computational optimization is conducted in two steps. Firstly, a numerical model of a single-layer dome structure is used to minimize the cross-sectional area through several iterations. Different assumed ratios (r) ranging from 0.95 to 0.75 are multiplied by the designed cross-sectional area, and the optimal actual ratio (R) is determined through multiple steps using MATLAB. The selection of the optimum ratio is based on ensuring structural stability and considering various constraints. Secondly, a computational optimization is performed using the fmincon function in MATLAB, which employs an interior-point optimization algorithm to search for the minimum summation of the function. The algorithm is designed to exclude actuators with negligible actuation, thereby minimizing the number of actuators. Constraints are set on the stress of all members and the nodal displacements to maintain the desirable shape of the optimized structure. The obtained results demonstrate that the cross-sectional area of the numerical dome structure can be reduced by up to 18% by prestressing only nine members. The validity of the results is confirmed by comparing them with those obtained from MATLAB and SAP2000 software.

  • Computational modelling of historic masonry railroad arch bridges
    • Bartosz Sobczyk
    • Łukasz Pyrzowski
    • Mikołaj Miśkiewicz
    2024 COMPUTERS & STRUCTURES

    The problems encountered during the analyzes of structural response of historic masonry railroad arch bridges are described in this paper. The attention is mainly focused on the stiffness of the masonry arches, their strengths and appropriate estimation of railroad load intensity. Issues related to computational modelling of two, existing, almost 130 years old masonry arch railroad bridges are presented in this context. The main properties and results of detailed inspection of the structures are shown. Computational models that were created in the finite element method environment in order to efficiently describe the responses of the bridges under typical loading conditions and estimate their load carrying abilities are presented. The outcomes of several nonlinear static analyses that were conducted for this purpose are discussed. What is more the results of finite element analyses are reviewed against the inspected bridge condition and final conclusions are formulated on that basis. All the analyses allowed to find the possible causes of the deterioration of the bridges condition.

  • Computational Study of Molecular Interactions in ZnCl2(urea)2 Crystals as Precursors for Deep Eutectic Solvents
    • Adrian Malinowski
    • Maciej Śmiechowski
    2024 Crystals

    Deep eutectic solvents (DESs) are now enjoying an increased scientific interest due to their interesting properties and growing range of possible applications. Computational methods are at the forefront of deciphering their structure and dynamics. Type IV DESs, composed of metal chloride and a hydrogen bond donor, are among the less studied systems when it comes to their understanding at a molecular level. An important example of such systems is the zinc chloride–urea DES, already used in chemical synthesis, among others. In this paper, the ZnCl2(urea)2 crystal is studied from the point of view of its structure, infrared spectrum, and intermolecular interactions using periodic density functional theory and non-covalent interactions analysis. The two main structural motifs found in the crystal are a strongly hydrogen-bonded urea dimer assisted by chloride anions and a tetrahedral Zn(II) coordination complex. The crystal is composed of two interlocking parallel planes connected via the zinc cations. The infrared spectrum and bond lengths suggest a partially covalent character of the Zn–Cl bonds. The present analysis has far-reaching implications for the liquid ZnCl2–urea DES, explaining its fluidity, expected microstructure, and low conductivity, among others.

  • Concept of Multifactor Method and Non-Functional Requirements Solution to Increase Resilience through Functional Safety with Cybersecurity Analysis
    • Emilian Piesik
    • Marcin Śliwiński
    • Narayanan Subramanian
    • Janusz Zalewski
    2024 Pełny tekst Eksploatacja i Niezawodność - Maintenance and Reliability

    In the process of designing safety systems, an integrated approach in safety and cybersecurity analysis is necessary. The paper describes a new technique of increasing resilience through integrated analysis of functional safety and cybersecurity. It is a modeling methodology based on the combination of the multifactor method utilizing modified risk graphs, used previously for Safety Integrity Level (SIL) assessment, and the Non-Functional Requirements (NFR) approach. The NFR approach, based on the analysis of graphical representation of conceptual and physical components of the system, contributes a technique to include cybersecurity through the Softgoal Interdependency Graph. The assessment methodology is outlined in detail and applied to a case study involving an industrial control system. The analysis turns out to be effective in both aspects: confirming the findings of the multifactor approach based on modified risk graphs and complementing the traditional analysis to increase resilience in discovering and mitigating security vulnerabilities for SIL assessment by the use of NFR

  • Consideration of Pseudo Strain Energy in Determination of Fatigue Life and Microdamage Healing of Asphalt Mastics
    • Dawid Ryś
    • Cezary Szydłowski
    2024 INTERNATIONAL JOURNAL OF FATIGUE

    Rest periods between cyclic loads can lead to recovery of damage and extension of fatigue life. This phenomenon is referred to as healing. Healing is clearly observed in bituminous materials, such as asphalt mastics, which belong to the components of asphalt mixtures. Due to the nature of road pavement traffic loading, which is characterized by series of intermittent pulses with rest periods, consideration of healing is necessary for accurate fatigue life estimation. Nevertheless, the vast majority of existing methods relies on relationships established using continuous load conditions. The paper presents a new approach to fatigue life determination, based on pseudo strain energy density. Two components of energy released in fatigue test are considered: the energy responsible for damage growth and the energy consumed to counteract the healing effect. Theoretical derivations were verified in experimental tests, which were performed on asphalt mastics using the Dynamic Shear Rheometer (DSR). It was shown that fatigue life increases with the duration of rest periods on a linear-log scale. Moreover, fatigue life and healing abilities of the analysed asphalt mastics were affected by the type of bitumen and filler, as well as the ageing process.

  • Contemporary and Conventional Passive Methods of Intensifying Convective Heat Transfer—A Review
    • Ewa Kozłowska
    • Marek Szkodo
    2024 ENERGIES

    The ever-increasing demand for effective heat dissipation and temperature control in industrial and everyday applications highlights a critical research problem. The need for development is not only in terms of providing thermal comfort to humans but also forms the basis for the efficient operation of machines and equipment. Cooling of industrial machinery and household electronic equipment is a crucial element in any manufacturing process, and the planning and design of appropriate cooling systems continues to be an integral part of the machine design and construction process. Manufacturers aim to maximize performance while minimizing size and weight. This article reviews widely used passive methods to enhance heat transfer, focusing on their effectiveness in improving convective heat transfer. The techniques examined include surface modifications and advanced materials like foamed metals and nanostructured coatings, which influence turbulence and heat transfer coefficients. The key findings demonstrate that surface roughness, perforated fins, and twisted tapes enhance fluid mixing but may increase flow resistance. The review underscores the significance of these passive methods in optimizing cooling system efficiency across various applications. Despite the variety of techniques available, many areas, especially those involving laser beam modifications, remain underexplored, indicating a need for further research in this field.

  • Continuum contact model for friction between graphene sheets that accounts for surface anisotropy and curvature
    • Aningi Mokhalingam
    • Shakti Gupta
    • Roger Sauer
    2024 Pełny tekst PHYSICAL REVIEW B

    Understanding the interaction mechanics between graphene layers and co-axial carbon nanotubes (CNTs) is essential for modeling graphene and CNT-based nanoelectromechanical systems. This work proposes a new continuum contact model to study interlayer interactions between curved graphene sheets. The continuum model is calibrated and validated using molecular dynamics (MD) simulations. These are carried out employing the reactive empirical bond order (REBO)+Lennard-Jones (LJ) potential to model the interactions within a sheet, while the LJ, Kolmogorov-Crespi (KC), and Lebedeva potentials are used to model the interactions between sheets. The continuum contact model is formulated for separation distances greater than 0.29 nm, when sliding contact becomes non-dissipative and can be described by a potential. In this regime, sheet deformations are sufficiently small and do not affect the sheet interactions substantially. This allows to treat the master contact surface as rigid, thus simplifying the contact formulation greatly. The model calibration is conducted systematically for a sequence of different stackings using existing and newly proposed ansatz functions. The calibrated continuum model is then implemented in a curvilinear finite element (FE) shell formulation to investigate the pull-out and twisting interactions between co-axial CNTs. The resisting pull-out forces and torques depend strongly on the chirality of the considered CNTs. The absolute differences between FE and MD results are very small, and can be attributed to model assumptions and loading conditions.

  • Controlling nodal displacement of pantographic structures using matrix condensation and interior-point optimization: A numerical and experimental study
    • Ahmed Manguri
    • Najmadeen Saeed
    • Robert Jankowski
    2024 ENGINEERING STRUCTURES

    This study presents an innovative approach for the precise control of nodal displacements in pantographic structures. The method is founded on the Matrix Condensation of Force Method, seamlessly integrated with an Interior Point Optimization algorithm. This combination offers a unique advantage by allowing users to manipulate displaced nodes within a defined coordination domain. Furthermore, this approach introduces the Interior Point Optimization algorithm as an indispensable tool to eliminate inactive turnbuckles and minimize overall actuation requirements. Traditional control methods typically demand a substantial number of turnbuckles and extensive actuation efforts to attain the desired nodal coordinates. The interconnected nature of node movements, wherein changes in one node affect others, adds complexity to determining the impact of bar length alterations on each node. To address this challenge, precisely control power of the Interior Point Optimization algorithm systematically explores numerous scenarios to identify solutions that minimize both actuation and turnbuckle usage. The current technique's effectiveness is validated through rigorous comparisons with established methods, experimental modeling, and rigorous testing using SAP 2000 software. Notably, the current approach yields remarkable results, requiring a staggering 60% less actuation and reducing the reliance on turnbuckles by up to 40% compared to previous methods. This innovation promises to significantly enhance the efficiency and cost-effectiveness of controlling pantographic structures, marking a substantial advancement in this field.

  • Controlling the europium oxidation state in diopside through flux concentration
    • N. Górecka
    • Tadeusz Lesniewski
    • Sebastian Mahlik
    • Marcin Łapiński
    • Y.-T. Tsai
    • Aleksandra Bielicka-giełdoń
    • Karol Szczodrowski
    2024 DALTON TRANSACTIONS

    This paper explores the connection between the H3BO3 flux concentration and the co-existence of Eu2+ and Eu3+ dopants within CaMgSi2O6 crystals (diopside). The samples were synthesised using a solid-state synthesis method under varying atmospheric conditions, including oxidative (air), neutral (N2), and reductive (H2/N2 mixture) environments. Additionally, some materials underwent chemical modification by partially substituting Si4+ with Al3+ ions acting as charge compensation defects stabilizing Eu3+ luminescence. Depending on the specific synthesis conditions, the materials predominantly displayed either the orange-red luminescence of Eu3+ (under oxidising conditions) or the blue luminescence of Eu2+; however, the comprehensive results confirmed the co-existence of Eu3+/Eu2+ luminescence in both cases. This work shows that varying flux concentrations added during synthesis significantly affect the relative strength of Eu2+ and Eu3+ emissions in a manner dependent on the synthesis atmosphere. The emission of Eu2+ increases with a higher flux concentration in materials synthesised under oxidative and neutral atmospheres independent of the chemical modification. In contrast, for materials obtained under a reductive atmosphere, the changes in the Eu3+ emission intensity depended on the presence or absence of Al3+ ions namely the increase of flux increased the Eu3+ intensity in the case of unmodified materials and decreased in the Al-modified ones. All observed effects were qualitatively explained considering the double role of the flux in the studied system, which besides facilitating the diffusion of chemical species during synthesis acts as a charge compensating agent by creating B′Si centres stabilizing Eu3+ emission.

  • Convenient and efficient N-methylation of secondary amines under solvent-free ball milling conditions
    • Mikołaj Walter
    • Olga Ciupak
    • Karol Biernacki
    • Janusz Rachoń
    • Dariusz Witt
    • Sebastian Demkowicz
    2024 Pełny tekst Scientific Reports

    In the present work, we report the development of a rapid, efcient, and solvent-free procedure for the N-methylation of secondary amines under mechanochemical conditions. After optimization of the milling parameters, a vibrational ball mill was used to synthesize 26 tertiary N-methylated amine derivatives in a short time of 20 min (30 Hz frequency) and high yields ranging from 78 to 95%. An exception was compounds having a hydroxyl group in their structure, for which a decrease in reaction efciency was observed. During our research, we investigated alternate reaction selectivity occurring in compounds able to form ring closure products that are 3,4-dihydro-2H-1,3-benzoxazine derivatives instead of N-methylated products. The liquid-assisted grinding technique has been applied using formalin as a methylating agent and sodium triacetoxyborohydride as a reducing agent in a reductive amination reaction.

  • Corncob-supported calcium oxide nanoparticles from hen eggshells for cadmium (Cd-II) removal from aqueous solutions; Synthesis and characterization
    • Werkne Sorsa Muleta
    • Sultan Mulisa Denboba
    • Abreham Bayu
    2024 Pełny tekst Heliyon

    This study investigated the efficient removal of cadmium ions from aqueous solutions using calcium oxide nanoparticles (CaO NPs) synthesized from waste hen eggshells using a Sol-gel method and supported on corncob bio-adsorbent. The synthesized CaO NPs were characterized using FT-IR, XRD, specific surface area, and TGA. Batch adsorption experiments were conducted to examine the influence of process parameters such as adsorbent dosages, initial Cd (II) concentrations, pH values, and contact times. XRD analysis revealed that the synthesized CaO nanoparticles had a size of 24.34 nm and a specific surface area of 77.4 m2 g. The optimal conditions for achieving the highest percent removal of cadmium (99.108%) were found to be an initial concentration of 55 ppm, pH 7, adsorbent dose of 0.75 g, and contact time of 50 min. The experimental removal efficiency closely matched the predicted value (99.0%), indicating the suitability of the method used in optimizing the removal of Cd (II) ions from aqueous solutions. These findings, corroborated by predicted values, underscore the efficacy of our method in optimizing cadmium removal. Based on these findings, it can be concluded that corncob-supported CaO NPs are optimized for their highest efficiency and hold great promise as a cost-effective and environmentally friendly solution for wastewater treatment with a focus on cadmium removal.

  • Corporate social responsibility and forward default risk under firm and industry heterogeneity
    • Muhammad Mushafiq
    • Błażej Prusak
    • Magdalena Markiewicz
    2024 Pełny tekst Entrepreneurial Business and Economics Review

    Objective: This study aims to evaluate the impact of corporate social responsibility on forward default risk (FDR) under the setting of firm and industry heterogeneity. Research Design & Methods: This study evaluated the impact of corporate social responsibility (CSR) on FDR using the data of 497 companies from 2007-2021 in the S&P 500 index, taking into account firm and industry heterogeneity aspects. This study utilized instrumental variable regression using the generalized method of moments (IV-GMM) estimation technique which is robust for controlling the pertinent issue of endogeneity. Findings: This study found a negative relationship between CSR and FDR in the full sample. From the firm size aspect, this study found that CSR is more effective in mitigating FDR in large-cap firms than in mid-cap firms. Firm age heterogeneity exhibited a distinct behaviour, as young and middle-aged firms had a stronger impact on FDR management in comparison to old firms. Industry heterogeneity showed that industries with higher customer interaction have a higher impact on corporate social responsibility to control FDR. Industries with lower customer interaction have a lower impact on corporate social responsibility and FDR. Implications & Recommendations: We proposed some policy recommendations based on the findings in the context of firm and industry heterogeneity. Especially the management of mid-cap and young corporations should improve the CSR policy to enhance CSR performance which would lead to stabilized protection against FDR. Similarly, consumer-intensive industries should also focus on enhancing CSR initiatives to decrease FDR. Non-consumer-intensive industries should focus on enhancing CSR policy and at the same time pay particular attention to communicating CSR results to end consumers to reduce FDR. Contribution & Value Added: This study is the first to explore CSR’s impact on financial parameters under heterogeneity.

  • Correlations of structural, thermal and electrical properties of sodium doped complex borophosphosilicate glass
    • Zuzanna Milewczyk
    • Sharafat Ali
    • Piotr Okoczuk
    • Jacek Ryl
    • Ryszard Barczyński
    • Natalia Wójcik
    2024 Pełny tekst CERAMICS INTERNATIONAL

    Borophosphosilicate glasses with varying sodium ion concentrations were investigated for their, structural, thermal, and electrical properties. All the obtained glasses were transparent except the glass with the highest sodium content, which exhibited translucency due to inhomogeneities. Increasing sodium content led to reduced boron and silicon content while maintaining a constant B/Si ratio, indicating progressive depolymerization of the glass network. Confocal microscopy, scanning electron microscopy, and atomic force microscopy showed homogeneous and granular structure for samples with lower sodium content, but higher sodium content resulted in visible agglomeration/nanocrystallization. X-ray diffractograms showed amorphous nature for most samples, with samples doped with the highest concentrations of Na2O showing several broad reflections suggesting nanoscale crystallinity. Fourier-transform infrared spectroscopy revealed shifts in dominant bands with increasing sodium content, indicating depolymerization of the borate network. An observed decrease in glass transition temperature and thermal stability with increasing sodium content was attributed to depolymerization and formation of non-bridging oxygens. Impedance spectroscopy revealed two relaxation processes associated with the transport of Na+ ions through two different regions. DC conductivity and activation energy predominantly increased with the sodium ion content at high temperatures.

  • Corrigendum to “An investigation on residual stress and fatigue life assessment of T-shape welded joints” [Eng. Fail. Anal. 141 (2022) 106685]
    • Jeetendra Mourya
    • Greg Wheatley
    • Mohammed Nizam Khan
    • Reza Masoudi Nejad
    • Ricardo Branco
    • Wojciech Macek
    2024 ENGINEERING FAILURE ANALYSIS

    This paper aims to quantitatively evaluate the residual stress and fatigue life of T-type welded joints with a multi-pass weld in different direction. The main research objectives of the experimental test were to test the residual stress by changing direction along with multiple wielding passes and determine the fatigue life of the welded joints. The result shows that compressive residual stress increases in the sample gradually from single-pass weld to double and triple-pass weld. Moreover, the fatigue life of the specimen also gradually improves with an increasing number of welding passes. Performing multi-pass welding in different directions affects the material’s residual stress and fatigue life, which is an essential factor to consider for assuring the strength of the welded joint.

  • Corrigendum to “Fatigue life improvement using low transformation temperature weld material with measurement of residual stress” [Int. J. Fatigue 164 (2022) 107137]
    • Jordan Franks
    • Greg Wheatley
    • Pedram Zamani
    • Reza Masoudi Nejad
    • Wojciech Macek
    • Ricardo Branco
    2024 INTERNATIONAL JOURNAL OF FATIGUE

    Welding processes often produce high levels of tensile residual stress. Low transformation temperature (LTT) welding wires utilise phase transformation strains to overcome the thermal contraction of a cooling weld. In this paper, the residual stress within each weld was quantified using the milling/strain gauge method, being the strain change measured as the weldment was milled away. The fatigue tests were conducted under uniaxial loading considering two types of LTT materials. The results show that the crack propagation of all samples was similar in cycles although both LTT materials extended the crack initiation, and, therefore, the overall life of the part. It was found that both LTT materials reduced the residual tensile stresses, increased the residual compressive stresses, leading to increase in fatigue life about 30%.

  • Corrigendum to “The influence of α,ω-diols and SiO2 particles on CO2 absorption and NH3 escaping during carbon dioxide capture in ammonia solutions” [J. CO2 Util. 80 (2024) 102698]
    • Temesgen Amibo
    • Donata Konopacka-Łyskawa
    2024 Pełny tekst Journal of CO2 Utilization

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  • Corrosion damage identification based on the symmetry of propagating wavefield measured by a circular array of piezoelectric transducers: Theoretical, experimental and numerical studies
    • Beata Zima
    • Jochen Moll
    2024 Pełny tekst MECHANICAL SYSTEMS AND SIGNAL PROCESSING

    The article investigates the results obtained from numerical simulations and experimental tests concerning the propagation of guided waves in corroded steel plates. Developing innovative methodologies for assessing corrosion-induced degradation is crucial for accurately diagnosing offshore and ship structures exposed to harsh environmental conditions. The main aim of the research is to analyze how surface irregularities affect wave propagation characteristics. An investigation was conducted for antisymmetric fundamental mode A0. Specifically, the study examines the asymmetrical wavefronts generated by nonuniform thickness in damaged specimens. Initially, numerical analysis explores the impact of thickness variation on wave field symmetry. Corroded plates with varying levels of degradation are modeled using the random fields approach, with degradation levels ranging from 0 % to 60 %. Subsequently, the research investigates how the standard deviation of thickness distribution (from 5 % to 20 % of the initial thickness) and excitation frequency (from 50 to 150 kHz) influence recorded signals and the shape of reconstructed wavefronts. Each scenario compares wavefront symmetry levels estimated using rotational and bilateral symmetry degrees as indicative parameters. The numerical simulations are complemented by experimental tests conducted on plates with three different degradation levels. The results demonstrate the efficacy of the proposed wave field analysis approach for assessing structural integrity, as evidenced by the agreement between numerical predictions and experimental observations.

  • Corrosion Monitoring in Petroleum Installations—Practical Analysis of the Methods
    • Juliusz Orlikowski
    • Agata Jazdzewska
    • Iwona Łuksa
    • Michał Szociński
    • Kazimierz Darowicki
    2024 Pełny tekst Materials

    This paper presents the most typical corrosion mechanisms occurring in the petroleum industry. The methods of corrosion monitoring are described for particular corrosion mechanisms. The field and scope of the application of given corrosion-monitoring methods are provided in detail. The main advantages and disadvantages of particular methods are highlighted. Measurement difficulties and obstacles are identified and widely discussed based on actual results. Presented information will allow the corrosion personnel in refineries to extract more reliable data from corrosion-monitoring systems.

  • Corrosion of AISI1018 and AISI304 steel exposed to sulfates
    • Ginneth Millan Ramirez
    • Miguel Angel Baltazar-Zamora
    • Ce Tochtli Méndez Ramírez
    • Maciej Niedostatkiewicz
    • Hubert Byliński
    2024 Inżynieria Bezpieczeństwa Obiektów Antropogenicznych

    This research analyses the behavior of corrosion, durability, and quality of reinforced concrete samples coated with two different materials when exposed to contaminated soil with sulfates. The initial assessment involved evaluating the water absorption rate of the coating materials before and after exposure to a solution containing 3%푁푎2푆푂4+3%푀푔푆푂4+3%퐾2푆푂4+3%퐶푎푆푂4to determine their durability. the corrosion potential and linear polarization resistance technique were employed to measure the corrosion rate. Carbon steel and AISI 304 steel bars were tested alongside a stainless counter electrode. The findings indicate that the solvent-based coating exhibited superior performance, demonstrating reduced corrosion and water absorption rates. Additionally, the presence of sulfates led to the formation of a surface layer on the concrete, initially aiding in limiting waterpenetration. However, over time, this layer eventually causes damage to the concrete from the inside out.

  • Cost-effective methods of fabricating thin rare-earth element layers on SOC interconnects based on low-chromium ferritic stainless steel and exposed to air, humidified air or humidified hydrogen atmospheres
    • Łukasz Mazur
    • Paweł Winiarski
    • Bartosz Kamecki
    • Justyna Ignaczak
    • Sebastian Molin
    • Tomasz Brylewski
    2024 INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

    Most oxidation studies involving interconnects are conducted in air under isothermal conditions, but during real-life solid oxide cell (SOC) operation, cells are also exposed a mixture of hydrogen and water vapor. For this study, an Fe–16Cr low-chromium ferritic stainless steel was coated with different reactive element oxides – Gd2O3, CeO2, Ce0.9Y0.1O2 – using an array of methods: dip coating, electrodeposition and spray pyrolysis. The samples underwent oxidation experiments carried out over 100 h in three different atmospheres at 800 °C: air, an air/H2O mixture, and an Ar/H2/H2O mixture. The influence of different atmospheres on the corrosion of the Fe–16Cr steel was determined via oxidation kinetics studies; the corrosion product was evaluated using X-ray diffraction, scanning electron microscopy and area-specific resistance (ASR) measurements. All coated samples exhibited lower parabolic oxidation rate constants than bare steel and most also had lower ASR. The applied modifications were found to be sufficiently effective to allow the investigated low-chromium steel to be considered for application as an interconnect material for SOCs.

  • Cost-Effective Piggyback Forward dc-dc Converter
    • Oleksandr Matiushkin
    • Oleksandr Husev
    • Hossein Afshari
    • Dmitri Vinnikov
    • Ryszard Strzelecki
    2024

    The novel piggyback dc-dc converter as a cost-effective solution is presented in this work. It provides a wide input voltage range of regulation with a low component count. The novel solution is an advanced forward dc-dc converter with an additional clamp output capacitor. The idea of such a type of converter is to transfer magnetizing energy of transformer to the output side, instead of using input clamp circuit. The design guidelines of the passive component of the proposed solution are discussed. A digital domain proportional integral controller is designed for the off-grid system validation, and it provides a stable output voltage in a wide range of the input voltage and power. Experimental prototype of the proposed piggyback converter along with experimental results of critical points are presented. The efficiency study of the proposed solution is done.

  • Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
    • Anna Pietrenko-Dąbrowska
    • Sławomir Kozieł
    • Łukasz Gołuński
    2024 Pełny tekst IEEE Access

    Design of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters is commonly performed utilizing EM simulation software. As EM analysis is computationally heavy, parametric optimization entails significant costs, also for local algorithms. The expenses generated by global search procedures are incomparably higher, and often prohibitive. Still, global optimization is more and more often necessary, for example, when re-designing a structure over extended ranges of operating conditions (bandwidth, power split ratios, etc.), when more than a single local optimum exists (e.g., optimization of frequency selective surfaces), or simply due to the absence of quality initial design (e.g., compact circuits obtained using the slow-wave phenomenon). A possible workaround is surrogate-assisted optimization, yet a construction of accurate replacement models is a challenge by itself. This paper offers an innovative approach to a rapid globalized optimization of passive microwave components. It combines a machine learning procedure, specifically, an iterative construction and refinement of fast surrogates (with infill criterion being a minimization of the predictor-yielded objective improvement) with a response feature technology, where the metamodel targets suitably appointed characteristic points of the circuit outputs. These so-called response features are in a nearly linear relationship with the geometry parameters, which facilitates the search process and reduces the expenditures associated with surrogate model construction. Identification of the infill points is executed using a particle swarm optimization algorithm. Numerical experiments carried out using two microstrip circuits demonstrate the capability for a global search of the proposed algorithm, and its superior performance over direct nature-inspired-based optimization and surrogate-assisted search at the level of complete circuit characteristics.

  • Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
    • Anna Pietrenko-Dąbrowska
    • Sławomir Kozieł
    • Marek Wójcikowski
    • Bogdan Pankiewicz
    • Artur Rydosz
    • Tuan-Vu Cao
    • Krystian Wojtkiewicz
    2024 MEASUREMENT

    Air quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung diseases. Notwithstanding, precise NO2 detection typically demands complex and costly equipment. This paper explores NO2 monitoring using low-cost platforms, meticulously calibrated for reliability. An integrated measurement unit is first presented that contains primary and supplementary nitrogen dioxide sensors, as well as auxiliary detectors for evaluating outside and inside temperature and humidity. The calibration process utilizes data acquired over the period of five months from various reference stations. Employing machine learning with an artificial neural network (ANN)-based and kriging interpolation surrogate models, the correction strategy integrates additive and multiplicative enhancement, predicted by the ANN through auxiliary sensor data such as temperature, humidity, and the sensor-detected NO2 levels. Extensive verification studies showcase that this calibration approach notably enhances monitoring precision (r2 correlation coefficient surpassing 0.85 concerning reference data, and RMSE of less than four g/m3), rendering low-cost NO2 detection practical and dependable.

  • Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    • Leifur Leifsson
    2024

    Designing microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective MO technique for microwave passive components utilizing a machine learning (ML) framework with artificial neural network (ANN) surrogates as the primary prediction tool. In this approach, mul-tiple candidate solutions are extracted from the Pareto set via optimization using a multi-objective evolutionary algorithm (MOEA) applied to the current ANN model. These solutions expand the dataset of available (EM-simulated) parameter vectors and refine the surrogate model iteratively. To enhance computational effi-ciency, we employ variable-resolution EM models. Tested on two microstrip cir-cuits, our methodology competes effectively against several surrogate-based ap-proaches. The average computational cost of the algorithm is below three hundred EM analyses of the circuit, with the quality of generated Pareto sets surpassing those produced by the benchmark methods.

  • Coupled DEM/CFD analysis of impact of free water on the static and dynamic response of concrete in tension regime
    • Marek Krzaczek
    • Andrzej Tejchman-Konarzewski
    • Michał Nitka
    2024 Pełny tekst COMPUTERS AND GEOTECHNICS

    W tym artykule zbadano numerycznie quasi-statyczne i dynamiczne zachowanie częściowo nasyconego płynem betonu w warunkach dwuwymiarowego (2D) jednoosiowego rozciągania w mezoskali. Obliczono, jaki wpływ ma zawartość wolnego płynu porowego (gazu i wody) na proces pękania i wytrzymałość betonu w rozciąganiu. Do symulacji zachowania betonu całkowicie i częściowo nasyconego płynem w warunkach quasi-statycznych i dynamicznych wykorzystano ulepszony model hydromechaniczny w skali porów, oparty na DEM/CFD. Podstawą koncepcji przepływu płynu była sieć kanałów na ciągłym obszarze pomiędzy dyskretnymi elementami. W bardzo porowatym, częściowo nasyconym betonie przyjęto dwufazowy laminarny przepływ płynu. Aby śledzić zawartość cieczy/gazu, wzięto pod uwagę położenie i objętość porów i rys. Symulacje numeryczne spójnych próbek ziarnistych o uproszczonej mezostrukturze sferycznej przypominającej beton przeprowadzono w warunkach suchych i mokrych dla dwóch różnych szybkości odkształcenia. Przeprowadzono badania wpływu ciśnienia porów płynu, nasycenia płynu i lepkości płynu na wytrzymałość i proces pękania betonu. Kwasi-statyczna wytrzymałość na rozciąganie spadała nieliniowo wraz ze wzrostem nasycenia płynu i lepkości płynu podczas migracji płynu przez pory i pęknięcia wskutek przyspieszenia procesu pękania. Jednakże podczas szybkiego dynamicznego odkształcenia przy rozciąganiu proces pękania został osłabiony z powodu ograniczenia migracji płynu wynikającego z niewystarczającego czasu płynu na opuszczenie porów. Spowodowało to nieliniowy wzrost dynamicznej wytrzymałości na rozciąganie wraz ze wzrostem nasycenia płynu i lepkości płynu.

  • Crack monitoring in concrete beams under bending using ultrasonic waves and coda wave interferometry: the effect of excitation frequency on coda
    • Magdalena Knak
    • Erwin Wojtczak
    • Magdalena Rucka
    2024 Pełny tekst

    Concrete is one of the most widely used construction materials in the world. In recent years, various non-destructive testing (NDT) and structural health monitoring (SHM) techniques have been investigated to improve the safety and control of the current condition of concrete structures. This study focuses on micro-crack monitoring in concrete beams. The experimental analysis was carried out on concrete elements subjected to three-point bending in a testing machine under monotonic quasi-static loading. During the tests, the fracture process was characterized using ultrasonic waves. The recorded signals were further processed by coda wave interferometry (CWI). This technique allowed the detection of cracks using the decorrelation between ultrasonic wave signals collected at different stages of degradation. Different values of excitation frequencies in the range from 100 kHz to 400 kHz were used to investigate the influence of frequency selection on the effectiveness of the damage indication based on the decorrelation of coda waves. The results obtained from the experiments were intended to highlight the effect of the applied frequencies on the coda wave interferometry.

  • Crank–Nicolson FDTD Method in Media Described by Time-Fractional Constitutive Relations
    • Damian Trofimowicz
    • Tomasz Stefański
    • Jacek Gulgowski
    2024

    In this contribution, we present the Crank-Nicolson finite-difference time-domain (CN-FDTD) method, implemented for simulations of wave propagation in media described by time-fractional (TF) constitutive relations. That is, the considered constitutive relations involve fractional-order (FO) derivatives based on the Grünwald-Letnikov definition, allowing for description of hereditary properties and memory effects of media and processes. Therefore, the TF constitutive relations make it possible to include, in a dielectric response, diffusion processes which are modelled mathematically by the diffusion-wave equation. We formulate fundamental equations of the proposed CN-FDTD method, and then we execute simulations which confirm its accuracy and applicability. Additionally, we perform numerical tests of stability, which confirm unconditional stability of the method. The proposed method is useful for researchers investigating numerical techniques in media described by FO derivatives.

  • Creating private and public value in data-related management projects: a cross-border case study from Switzerland and Italy
    • Elide Garbani-Nerini
    • Elena Marchiori
    • Nadzeya Sabatini
    • Lorenzo Cantoni
    2024 Pełny tekst

    The literature in the field of smart cities shows a continuous emphasis and interest in the topic of big data due to the extensive use of Information and Communication Technologies by public and private institutions within each city. There is undoubtedly value in big data: in data lie insights on the city, its stakeholders, citizens, products, and services. Challenges, though, lie in data’s variety, volume, and velocity, but also in managing them, considering the complex interplay between stakeholders inside a city or a country. Another layer of complexity is added when we consider a smart city as a smart destination where the visitor - often an international tourist - becomes an additional stakeholder of a smart city bringing in additional data. Such challenges, though, are even stronger when tourists do not stop at geographical borders: smart destinations become cross-border destinations. While there is a physical border between them, but most importantly, a legal difference in how data should be collected, stored, managed, and re-used [56, 59], data flows do not stop at this border. This complexity has to be managed both by governmental and tourism agencies. However, the literature between eGovernment and tourism is often theoretical in nature, and while it highlights the potential benefits of smart destinations and data-management processes, it does not provide detailed guidelines on how to implement these concepts in practice [41], especially in the context of cross-border smart destinations. With regards to this, not only has the need for guidelines risen to help tourism destinations tackle smart data- and technology-related projects, but also to define how stakeholders can come together to determine data policies and governance in order to create private as well as public value [60]. This paper responds to such a need by presenting the results of a cross-border research project conducted in Switzerland and Italy, where the model of a smart destination’s structure proposed by Ivars-Baidal et al. [35] has been applied, and its dimensions have been operationalized in a data-related management project. This allowed the authors to understand how to create public and private value managing data flows in a cross-border context, while also elaborating on the model reflecting on data’s dual role as a starting point but also as a central component impacting other dimensions.

  • Cryptocurrencies as a Speculative Asset: How Much Uncertainty is Included in Cryptocurrency Price?
    • Tayyaba Ahsan
    • Krystian Zawadzki
    • Khan Mubashir
    2024 Pełny tekst SAGE Open

    The aim of this paper is to examine the relationship between uncertainty indices (Geopolitical Uncertainty Index and Global Economic Policy Uncertainty Index) and cryptocurrencies. This study evaluated the behavior of cryptocurrencies with the evolution of uncertainties (GPU, EPU) on returns and volatility in terms of safe heaven as in traditional specualtive assets it increases their volaitility and reduces risk. For this purpose, this study examines the relationship between uncertanities indices, gold returns and crptocurrency by using the OLS regression for the monthly data from April 2017 to April 2022. The findings of this study indicate that the return and volatility of cryptocurrency increases. In particular, we note that the cryptocurrency market could serve as a weak hedge and safe against GEPU during a bull market; It could be considered a strong hedge, but in most cases could not serve as a safety against GPR. However, in case of Gold it is found that it serves as weak hedge against uncertainity indices and is not considered as safe heaven against GEPU and GPR. This study expands the current research on uncertainity indices and provides unique insight about the speculative nature of cryptocurrencies and safe heaven.

  • Current advances in membrane processing of wines: A comprehensive review
    • Youssef El Rayess
    • Roberto Castro Munoz
    • Alfredo Cassano
    2024 Pełny tekst TRENDS IN FOOD SCIENCE & TECHNOLOGY

    Background Membrane-based operations, especially pressure-driven membrane operations, are today well-established procedures for various applications in the wine industry thanks to their intrinsic properties and undoubted advantages over traditional methods. Emerging membrane processes, such as pervaporation, electrodialysis and osmotic distillation, forward osmosis, membrane contactors, offer new and interesting perspectives to improve quality and develop new products without compromising organoleptic properties. Scope and approach This review provides a comprehensive overview on the use of membrane operations in wine processing. A bibliometric and scientometric analysis has been done to provide the current advances dealing with the application of these operations in different steps of wine manufacture, including clarification, stabilization, concentration, acidification, deacidification and dealcoholization. The current challenges and perspectives are highlighted to guide further advancements of membrane technology in this field. Key findings and conclusions The use of conventional and emerging membrane systems offers interesting opportunities to improve and optimize current practices of the wine processing industry. Considerable progress has been done concerning the development of low-fouling materials, identification of wine molecules responsible for membrane fouling and methods to mitigate such phenomenon in the clarification of wines by microfiltration membranes. Technological progress in electrodialysis makes this process a very attractive method for tartrate stabilization, acidification and deacidification of wines. Different conventional and emerging membrane processes offer valid post-fermentation strategies to remove ethanol in wines while preserving their original characteristics. The global results provide interesting perspectives for a wider implementation of membrane processes in the winemaking industry and to redesign the traditional vinification process under the process intensification strategy.

  • Cyclic behaviour modelling of additively manufactured Ti-6Al-4V lattice structures
    • Michał Doroszko
    • Andrzej Seweryn
    2024 INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES

    The present work is concerned with the numerical modelling of the cyclic behaviour of Ti-6Al-4V lattice structures. In the study, diamond structures of titanium alloy produced by the additive laser powder bed fusion (LPBF) method with different degrees of relative density were used. Realistic geometric models of the studied mesostructures were generated using computed microtomography, taking into account the imperfections of the material resulting from the manufacturing process. The numerical calculations also took into account the actual material hardening curve in the elastic-plastic strain range. One of the achievements of this work is the numerical modelling of cyclic loading of realistic mesostructures with their imperfections. The areas of the mesostructures most susceptible to fatigue cracking have been identified and analysed. True hysteresis loops and values of local stress and strain amplitude were determined at the locations of highest stress concentration in cyclically loaded diamond structures. The main achievement of the present work was the modelling of the macroscopic fatigue life of the investigated mesostructures based on the true values of stress and strain at the locations most exposed to fatigue cracking. For this purpose, a stress criterion for fatigue cracking of Ti-6Al-4V lattice structures fabricated by the additive LPBF method was proposed.

  • Cyclic deformation and fracture behaviour of additive manufactured maraging steel under variable-amplitude loading
    • Zbigniew Marciniak
    • Ricardo Branco
    • Wojciech Macek
    • Michał Dobrzyński
    • C. Malça
    2024 THEORETICAL AND APPLIED FRACTURE MECHANICS

    The cyclic deformation and fracture behaviour of 18Ni300 maraging steel produced by laser beam powder bed fusion is studied under variable-amplitude loading. The tests were conducted under fully-reversed strain-controlled conditions with a loading sequence comprising three ascending cycles and three descending cycles repeated sequentially until failure. After the tests, fracture surfaces were examined using height and volume surface topography parameters to characterise the fractographic features. Fracture surfaces were also analysed through scanning electron microscopy to identify the main failure modes. Fatigue life was predicted by using the Smith-Watson-Topper and the Basquin-Coffin-Manson models with the Palmgren-Miner damage rule. The former approach was more accurate leading to mean errors close to zero. The values of the kurtosis parameter obtained from both sides of the fracture surfaces correlated well with the fatigue life. SEM analysis showed a mixed ductile-brittle mode of fracture with a predominance of brittle fracture. Crack initiation occurred from manufacturing defects located at the surface or near-surface.

  • Cytocompatibility, antibacterial, and corrosion properties of chitosan/polymethacrylates and chitosan/poly(4‐vinylpyridine) smart coatings, electrophoretically deposited on nanosilver‐decorated titania nanotubes
    • Łukasz Pawłowski
    • Michał Bartmański
    • Anna Ronowska
    • Adrianna Banach-Kopeć
    • Szymon Mania
    • Bartłomiej Cieślik
    • Aleksandra Mielewczyk-Gryń
    • Jakub Karczewski
    • Andrzej Zieliński
    2024 JOURNAL OF BIOMEDICAL MATERIALS RESEARCH PART B-APPLIED BIOMATERIALS

    The development of novel implants subjected to surface modification to achieve high osteointegration properties at simultaneous antimicrobial activity is a highly current problem. This study involved different surface treatments of titanium surface, mainly by electrochemical oxidation to produce a nanotubular oxide layer (TNTs), a subsequent electrochemical reduction of silver nitrate and decoration of a nanotubular surface with silver nanoparticles (AgNPs), and finally electrophoretic deposition (EPD) of a composite of chitosan (CS) and either polymethacrylate-based copolymer Eudragit E 100 (EE100) or poly(4-vinylpyridine) (P4VP) coating. The effects of each stage of this multi-step modification were examined in terms of morphology, roughness, wettability, corrosion resistance, coating-substrate adhesion, antibacterial properties, and osteoblast cell adhesion and proliferation. The results showed that the titanium surface formed nanotubes (inner diameter of 97 ± 12 nm, length of 342 ± 36 nm) subsequently covered with silver nanoparticles (with a diameter of 88 ± 8 nm). Further, the silver-decorated nanotubes were tightly coated with biopolymer films. Most of the applied modifications increased both the roughness and the surface contact angle of the samples. The deposition of biopolymer coatings resulted in reduced burst release of silver. The coated samples revealed potent antimicrobial activity against both Gram-positive and Gram-negative bacteria. Total elimination (99.9%) of E. coli was recorded for a sample with CS/P4VP coating. Cytotoxicity results using hFOB 1.19, a human osteoblast cell line, showed that after 3 days the tested modifications did not affect the cellular growth according to the titanium control. The proposed innovative multilayer antibacterial coatings can be successful for titanium implants as effective postoperative anti-inflammation protection.

  • Damage detection in 3D printed plates using ultrasonic wave propagation supported with weighted root mean square calculation and wavefield curvature imaging
    • Erwin Wojtczak
    • Magdalena Rucka
    • Angela Andrzejewska
    2024 Pełny tekst

    3D printing (additive manufacturing, AM) is a promising approach to producing light and strong structures with many successful applications, e.g., in dentistry and orthopaedics. Many types of filaments differing in mechanical properties can be used to produce 3D printed structures, including polymers, metals or ceramics. Due to the simplicity of the manufacturing process, biodegradable polymers are widely used, e.g., polylactide (polylactide – PLA) with a practical application for manufacturing complex-shaped elements. The current work dealt with the application of ultrasonic guided waves for non-destructive damage detection and imaging in AM plates. Two specimens with defects were manufactured from PLA filament. Different sizes of damage areas were considered. The specimens were tested using the guided wave propagation technique. The waves were excited using a PZT actuator and recorded contactless with the scanning laser Doppler vibrometry (SLDV) in a set of points located at one surface of the sample. The collected signals were processed with two methods. The first was the weighted root mean square (WRMS) algorithm. Different values of the calculation parameters, namely, averaging time and weighting factor were considered. The WRMS damage maps for both samples were prepared to differentiate between intact and damaged areas. The second approach was wavefield curvature imaging (WCI) which allowed the determination of damage maps based on the curvature of the wavefront. The compensation of wave signals was performed to enhance the quality of results. It was observed that the size of the defect strongly influenced the efficiency of imaging with both methods. The limitations of the proposed approaches were characterized. The presented results confirmed that guided waves are promising for non-destructive damage imaging in AM elements.

  • Damage of a post-tensioned concrete bridge – Unwanted cracks of the girders
    • Bartosz Sobczyk
    • Łukasz Pyrzowski
    • Mikołaj Miśkiewicz
    2024 ENGINEERING FAILURE ANALYSIS

    The cracking of a post-tensioned T-beam superstructure, which was built using the incremental launching method, is analyzed in the paper. The problem is studied in detail, as specific damage was observed in the form of longitudinal cracks, especially in the mid-height zone of the girder at the interface of two assembly sections. The paper is a case study. A detailed inspection is done and non-destructive testing results of the girders are briefly discussed. The attention is especially focused on advanced and comprehensive numerical simulations of the bridge mechanical behavior. Linear and nonlinear static calculations are performed employing the Finite Element Method at global and local levels of precision, enabling deep insight into the bridge response during all the stages of bridge construction and after it is opened to traffic. The crack propagation process in local analyses is described by the application of the Concrete Damage Plasticity law, the parameters of which were carefully chosen. The predicted damage patterns closely resemble those observed at the site. The results reveal, that the girder damage process was initiated when centric prestressing was applied, because vertical reinforcement of the assembly section front-end surface was not designed. However, the damage did not compromise the safety of the bridge. Finally, the repair methods employed are described and also a discussion is presented on how to prevent the occurrence of such cracking.

  • Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
    • Wiktor Oczkoś
    • Bartosz Podgórski
    • Wiktoria Szczepańska
    • Tomasz Maria Boiński
    2024 Pełny tekst Data in Brief

    The dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail prices for Poland, prices from aftermarket transactions). The data was merged based on the official LEGO set ID. With high granularity of the data (averaged monthly prices per LEGO set) the dataset permits the computation of variables at the set level and could support both aggregate and time-series analyses whereas the sparseness of the data permits the analysis of collector behavior allowing pinpointing of expected qualities from the purchased products and their resale potential. This may be useful to a broad range of researchers and data scientists using statistical methods and machine-learning techniques for price prediction.

  • Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
    • Farzin Kazemi
    • Torkan Shafighfard
    • Doo-Yeol Yoo
    2024 ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

    Fiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required for design criteria, has been a challenge because of their high uncertainties. Statistical and empirical models have been extensively utilized. However, such models require extensive experimental work and can produce incorrect outcomes when there are complicated interactions among the qualities of concrete, the makeup of the blend, and the curing environment. To address this issue, machine learning (ML) methods have been increasingly applied in recent years to solve complex structural engineering problems. Predictive models can provide a strong solution for time-consuming numerical simulations and expensive experiments. This study explores the ML techniques applied in this context and provides a comprehensive analysis of artificial intelligence methods used for predicting the mechanical properties of FRCs. It also highlights the key observations, challenges, and future trends in this field. This study serves as a valuable resource for researchers in selecting accurate models that match their applications. It also encourages material engineers to become familiar with and employ ML methods to design FRC mixtures appropriately.

  • Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
    • Piotr Januszewski
    • Dominik Grzegorzek
    • Paweł Czarnul
    2024 Pełny tekst

    The Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results demonstrate that NeuraLCB can learn from various datasets, while Neural Greedy necessitates extensive coverage of the action-space for effective learning. Moreover, the way data is collected significantly affects offline methods’ efficiency. This underscores the critical role of dataset quality in offline policy learning.

  • Dc Leakage Current in Isolated Grid-Connected dc Nanogrid - Origins and Elimination Methods
    • Mohammadreza Azizi
    • Oleksandr Husev
    • Oleksandr Veligorskyi
    • Marek Turzyński
    • Ryszard Strzelecki
    2024

    The LV dc system is a relatively new trend in the distribution sector, which seems to grow widely in the near future due to its promising advantages. In this context, LV dc protection and grounding are challenging issues. Although the galvanically isolated connection mode of dc nanogrid to the ac grid has high reliability, the leakage current can still be injected into the ac grid through the interwinding capacitors and the insulation resistance between the primary and secondary windings of the transformer. The way of grounding the dc nanogrid can also be a determining factor in the leakage current and its dc components. This study deals with the leakage current in the galvanically isolated dc nanogrid. Then, it examines the dc leakage current and its relationship with the dc nanogrid grounding and finally provides solutions to remove the dc components in the leakage current.

  • Dead time effects compensation strategy by third harmonic injection for a five-phase inverter
    • Krzysztof Łuksza
    • Dmytro Kondratenko
    • Arkadiusz Lewicki
    2024 Pełny tekst Archives of Electrical Engineering

    This paper proposes a method for compensation of dead-time effects for a fivephase inverter. In the proposed method an additional control subsystem was added to the field-oriented control (FOC) scheme in the coordinate system mapped to the third harmonic. The additional control loop operates in the fixed, orthogonal reference frame ( α - β coordinates) without the need for additional Park transformations. The purpose of this method is to minimize the dead-time effects by third harmonic injection in two modes of operation of the FOC control system: with sinusoidal supply and with trapezoidal supply. The effectiveness of the proposed control method was verified experimentally on a laboratory setup with a prototype five-phase interior permanent magnet synchronous machine (IPMSM). All experimental results were presented and discussed in the following paper.

  • Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects
    • Syed Imran Shafiq
    • Cesar Sanin
    • Edward Szczerbicki
    2024 Pełny tekst CYBERNETICS AND SYSTEMS

    Digital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data analytics for product and process control. Conventional manufacturing setups are still widely used all around the world for the fabrication of large-scale production. This article proposes a general DT implementation architecture for engineering objects/artifacts used in conventional manufacturing. It will empower manufacturers to leverage DT for real-time decision-making, control, and prediction for efficient production. An application scenario of Decisional-DNA based anomaly detection for conventional manufacturing tools is demonstrated as a case study to explain the architecture.

  • Deep eutectic solvent-based shaking-assisted extraction for determination of bioactive compounds from Norway spruce roots
    • Alina Kalyniukova
    • Alica Varfalvyová
    • Justyna Płotka-Wasylka
    • Tomasz Majchrzak
    • Patrycja Makoś-Chełstowska
    • Ivana Tomášková
    • Vítězslava Pešková
    • Filip Pastierovič
    • Anna Jirošová
    • Vasil Andruch
    2024 Pełny tekst Frontiers in Chemistry

    Polyphenolic compounds play an essential role in plant growth, reproduction, and defense mechanisms against pathogens and environmental stresses. Extracting these compounds is the initial step in assessing phytochemical changes, where the choice of extraction method significantly influences the extracted analytes. However, due to environmental factors, analyzing numerous samples is necessary for statistically significant results, often leading to the use of harmful organic solvents for extraction. Therefore, in this study, a novel DESbased shaking-assisted extraction procedure for the separation of polyphenolic compounds from plant samples followed by LC-ESI-QTOF-MS analysis was developed. The DES was prepared from choline chloride (ChCl) as the hydrogen bond acceptor (HBA) and fructose (Fru) as the hydrogen bond donor (HBD) at various molar ratios with the addition of 30% water to reduce viscosity. Several experimental variables affecting extraction efficiency were studied and optimized using one-variable-at-a-time (OVAT) and confirmed by response surface design (RS). Nearly the same experimental conditions were obtained using both optimization methods and were set as follows: 30 mg of sample, 300 mg of ChCl:Fru 1:2 DES containing 30% w/w of water, 500 rpm shaking speed, 30 min extraction time, 10°C extraction temperature. The results were compared with those obtained using conventional solvents, such as ethanol, methanol and water, whereby the DES-based shaking-assisted extraction method showed a higher efficiency than the classical procedures. The greenness of the developed method was compared with the greenness of existing procedures for the extraction of polyphenolic substances from solid plant samples using the complementary green analytical procedure index (ComplexGAPI) approach, while the results for the developed method were better or comparable to the existing ones. In addition, the practicability of the developed procedure was evaluated by application of the blue applicability grade index (BAGI) metric. The developed procedure was applied to the determination of spruce root samples with satisfactory results and has the potential for use in the analysis of similar plant samples.

  • Deep eutectic solvents with solid supports used in microextraction processes applied for endocrine-disrupting chemicals
    • Jose Grau
    • Aneta Chabowska
    • Justyna Werner
    • Agnieszka Zgoła-Grześkowiak
    • Magdalena Fabjanowicz
    • Natalia Jatkowska
    • Alberto Chisvert
    • Justyna Płotka-Wasylka
    2024 TALANTA.The International Journal of Pure and Applied Analytical Chemistry

    The determination of endocrine-disrupting chemicals (EDCs) has become one of the biggest challenges in Analytical Chemistry. Due to the low concentration of these compounds in different kinds of samples, it becomes necessary to employ efficient sample preparation methods and sensitive measurement techniques to achieve low limits of detection. This issue becomes even more struggling when the principles of the Green Analytical Chemistry are added to the equation, since finding an efficient sample preparation method with low damaging properties for health and environment may become laborious. Recently, deep eutectic solvents (DESs) have been proposed as the most promising green kind of solvents, but also with excellent analytical properties due to the possibility of custom preparation with different components to modify their polarity, viscosity or aromaticity among others. However, conventional extraction techniques using DESs as extraction solvents may not be enough to overcome challenges in analysing trace levels of EDCs. In this sense, combination of DESs with solid supports could be seen as a potential solution to this issue allowing, in different ways, to determine lower concentrations of EDCs. In that aim, the main purpose of this review is the study of the different strategies with solid supports used along with DESs to perform the determination of EDCs, comparing their advantages and drawbacks against conventional DES-based extraction methods.

  • Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
    • Kashif Shaheed
    • Piotr Szczuko
    • Munish Kumar
    • Imran Qureshi
    • Qaisar Abbas
    • Ihsan Ullah
    2024 ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

    Biometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with pre- sentation attacks (PAs) being prevalent and easily executed. PAs involve displaying videos, images, or full-face masks to trick biometric systems and gain unauthorized access. Many authors are currently focusing on detecting these presentation attacks (PAD) and have developed several methods, particularly those based on deep learning (DL), which have shown superior performance compared to other techniques. This survey article focuses on manuscripts related to deep learning presentation attack detection, spoof attack detection using deep learning, and anti-spoofing deep learning methods for biometric finger vein, fingerprint, iris, and face recognition. The studies were primarily sourced from four digital research libraries: ACM, Science Direct, Springer, and IEEE Xplore. The article presents a comprehensive review of DL-based PAD systems, examining recent literature on DL-based PAD methods in finger vein, fingerprint, iris, and face detection systems. Through extensive research of the literature, recent algorithms and their solutions for relevant PAD approaches are thoroughly analyzed. Additionally, the article provides a performance analysis and highlights the most promising research findings. The discussion section addresses current issues, opportunities for advancement, and potential solutions associ- ated with deep learning-based PAD methods. This study is valuable to various community users seeking to understand the significance of this technology and its recent applicability in the development of biometric technology for deep learning.

  • Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
    • Maksym Albin Jopek
    • Krzysztof Pastuszak
    • Sebastian Cygert
    • Myron G Best
    • Thomas Würdinger
    • Jacek Jassem
    • Anna Żaczek
    • Anna Supernat
    2024 Pełny tekst IEEE Journal of Translational Engineering in Health and Medicine-JTEHM

    The field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and therapy personalization. This study presents a multiclass approach based on deep learning to analyze and classify diseases based on blood platelet RNA. Its primary objective is to enhance cancer-type diagnosis in clinical settings by leveraging the power of deep learning combined with high-throughput sequencing of liquid biopsy. Ultimately, the study demonstrates the potential of this approach to accurately identify the patient’s type of cancer. Methods: The developed method classifies patients using heatmap images, generated based on gene expression arranged according to the Kyoto Encyclopedia of Genes and Genomes pathways. The images represent samples of patients with ovarian cancer, endometrial cancer, glioblastoma, non-small cell lung cancer, and sarcoma, as well as cancer patients with brain metastasis. Results: Our deep learning-based models reached 66.51% balanced accuracy when distinguishing between those 6 sites of cancer origin and 90.5% balanced accuracy on a location-specific dataset where cancer types from close locations were grouped. The developed models were further investigated with an explainable artificial intelligence-based approach (XAI) - SHAP. They returned a set of 60 genes with the highest impact on the models’ decision-making process. Conclusions: Our results show that deep-learning methods are a promising opportunity for cancer detection and could support clinicians’ decision-making process in finding the solution for the black-box problem. Clinical and Translational Impact Statement— Utilizing TEPs-based liquid biopsies and deep learning, our study offers a novel approach to early cancer detection, highlighting cancer origin. The integration of Explainable AI reinforces trust in predictive outcomes. Category: Early/Pre-Clinical Research.

  • Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
    • Munusamy Arun
    • Thanh Tuan Le
    • Debabrata Barik
    • Prabhakar Sharma
    • Sameh M. Osman
    • Van Kiet Huynh
    • Jerzy Kowalski
    • Van Huong Dong
    • Viet Vinh Le
    2024 Case Studies in Thermal Engineering

    Installing photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based systems, necessitating innovative solutions. The research proposes a deep learning-based optimal energy management system designed specifically for home micro-grids that incorporate PV systems with battery energy storage, Enhanced Long Short-Term Memory (LSTM)-Based Optimal Home Micro-Grid Energy Management (OHM-GEM). Integrating an improved type of LSTM neural network called LSTM into the energy management system improves the reliability of PV power output predictions. The dependability of PV power production forecasts is increased by including a refined version of the LSTM neural network in the energy management system. The efficiency of the OHM-GEM system in maximizing PV system integration into buildings is shown by the authors using simulated data. With considerable gains in energy efficiency, cost savings, and decreased reliance on non-renewable energy sources, the results highlight the possibility of this approach to forward sustainable energy practices.

  • Defected Ag/Cu-MOF as a modifier of polyethersulfone membranes for enhancing permeability, antifouling properties and heavy metal and dye pollutant removal
    • Vahid Vatanpour
    • Rabia Ardic
    • Berk Esenli
    • Bahriye Eryildiz-Yesir
    • Parisa Yaqubnezhad Pazoki
    • Atefeh Jarahiyan
    • Firouz Matloubi Moghaddam
    • Roberto Castro Munoz
    • Ismail Koyuncu
    2024 SEPARATION AND PURIFICATION TECHNOLOGY

    In this study, a novel bimetallic metal-organic framework (MOF) i.e. Ag/Cu-MOF was synthesized using a solvothermal method and later incorporated at different concentrations (0.1–2 wt%) using a phase inversion method for modification and antifouling property improvement of polyethersulfone (PES) membranes. The resulting Ag/Cu-MOF characteristics were investigated using different techniques, such as FTIR, XRD, FE-SEM and EDX. The membranes were characterized by FE-SEM, contact angle, porosity, mean pore size, surface roughness and zeta potential. Furthermore, membrane performance was examined using pure water flux, BSA, Pb(II), dye removal and fouling properties. In particular, the results showed that the addition of 1.0 wt% of the Ag/Cu-MOF decreased the water contact angle from 68.5° to 59.6° while enhancing overall porosity from 45.1 % to 56.0 %. The maximum water permeability was obtained with 1.0 wt% Ag/Cu-MOF (ca. 100 L/m2.h.bar) representing 1.9 times higher flux than that of the bare PES membrane due to the hydrophilic nature of the bimetallic MOF. As for the rejection performance, high Pb(II), BSA, reactive black 5 and reactive red 120 rejections values were observed as 92.6 %, 99.5 %, 96.4 % and 98.4 %, respectively. The Ag/Cu-MOF embedded membrane showed antibacterial behavior against Escherichia coli and antifouling properties, causing a considerable decrease in fouling resistance parameters and significant improvement in the antifouling properties of the PES membrane. The results of this study demonstrated that the Ag/Cu-MOF could be a promising material for boosting the polymeric membrane properties.

  • Deformation mitigation and twisting moment control in space frames
    • Ahmed Manguri
    • Najmadeen Saeed
    • Robert Jankowski
    2024 Pełny tekst Structures

    Over the last five decades, space frames have centered on the modernization of touristic zones in view of architectural attractions. Although attempts to control joint movement and minimize axial force and bending moment in such structures were made sufficiently, twisting moments in space frames have been underestimated so far. In space frames, external load or restoring the misshapen shape may cause twisting in members. We herein developed a robust computational algorithm to reduce the induced torsional moment through shape restoration within a desired limit by changing the length of active bars that are placed in space frames. Applying optimization algorithms like interior-point and Sequential quadratic programming (SQP), a direct correlation was pursued between bar length alteration and twisting in structural members. A numerical model of a single-layer space frame resembling an egg captures the twisting moment in all members, achieving a specified limit. The overall length change of the active members using an iterative process based on a heuristic that considers a threshold on the minimum length change of the active members.

  • Degradacja i uszkodzenia podbudowy jako przyczyny awarii betonowych posadzek przemysłowych
    • Sylwia Świątek-Żołyńska
    • Maciej Niedostatkiewicz
    • Władysław Ryżyński
    2024

    Posadzki i nawierzchnie betonowe doznają podczas użytkowania zróżnicowanych w swojej skali i czasie degradacji takich jak spękania, zarysowania i klawiszowanie płyt. Część z tych uszkodzeń jest spowodowana wadami wykonania, niską jakością betonu lub błędami projektowymi płyty konstrukcyjnej, ale w znacznej części jest to związane z wadliwą podbudową. Podbudowa jest bowiem istotnym elementem składowym posadzki, zapewniającym wymaganą nośność i sztywność całego układu

  • DEM modelling of concrete fracture based on its structure micro-CT images
    • Michał Nitka
    • Andrzej Tejchman-Konarzewski
    2024

    W rozdziale książki zawarto numeryczne wyniki mezoskopowe dotyczące postępującego pękania betonu na poziomie kruszywa. Do badania procesu pękania belki betonowej z karbem w trzech (3D) i dwóch (2D) wymiarach zastosowano metodę elementów dyskretnych (DEM). Niejednorodność betonu uwzględniono stosując czterofazowy opis: kruszywo, zaprawa, makropustki i międzyfazowe strefy przejściowe. W obliczeniach DEM na podstawie zdjęć rentgenowskich mikro-CT przyjęto rzeczywistą postać i rozmieszczenie kruszywa w betonie. Osiągnięto dobry poziom zgodności w odniesieniu do siły pionowej wpływającej na ewolucję przemieszczenia otworu wylotowego pęknięcia i kształtu pęknięcia pomiędzy analizą DEM a pomiarami laboratoryjnymi. Ewolucja zerwanych styków, sił normalnych kontaktu, rotacji cząstek, energii wewnętrznych, kształtu kruszywa oraz porowatości i szerokości ITZ były szeroko zbadane numerycznie na poziomie agregatów. Wyniki 3D również mocno kontrastowały z wynikami 2D. Pokazano, że model 3D DEM jest potencjalnym narzędziem do modelowania umożliwiającym przewidywanie i zrozumienie pękania betonu na poziomie mezoskopowym i makroskopowym.