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Gdańsk University of Technology

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  • Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
    • Kawsar Nassereddine
    • Marek Turzyński
    • Mykola Lukianov
    • Ryszard Strzelecki
    2024

    This research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting in solar power. This transition offers a broader and more detailed perspective for power system operators. The core of this research lies in applying and comparing three distinct Machine Learning algorithms for forecasting photovoltaic power output. The primary aim is to evaluate each method's accuracy and to identify the algorithm with the lowest prediction error. This comparative analysis is crucial for determining the most effective machine learning forecasting method, significantly contributing to the more reliable and efficient integration of renewable energy into power systems.

  • Advancing sustainable hybrid bitumen systems: A compatibilization solution by functionalized polyolefins for enhanced crumb rubber content in bitumen
    • Mateusz Malus
    • Joanna Bojda
    • Maciej Sienkiewicz
    • Wojciech Szot
    • Miloud Bouyahyi
    • Lanti Yang
    • Francisco Javier Navarro
    • Maha AlSayegh
    • Rasha Daadoush
    • Maria Soliman
    • Rob Duchateau
    • Lidia Jasinska-Walc
    2024 JOURNAL OF CLEANER PRODUCTION

    Polymer waste pollution has a profound effect on the environment and, consequently, on the lifestyle of hu- mankind. The massive production and disposal of cross-linked polymers clearly exemplify the challenges of recycling. Increasing efforts are being undertaken to introduce recycled polymers, especially crumb rubber (CR), into asphalt formulations. Due to the rather poor processability and phase separation associated with CR- modified bitumen (CRMB) compositions, a broader implementation of such concept is challenging unless an efficient compatibilizer is applied. Results from the study on usage of In-Reactor-Functionalized Polyolefins viz. poly(propylene-co-hex-1-ene-co-hex-5-en-1-ol) (FPP), demonstrated excellent compatibilizing ability in CRMB, allowing incorporation of up to 10 wt% of CR. This represents a significant improvement when compared to the best-in-class solutions. The FPP-containing products exhibit superior bulk, nanomechanical and rheological properties, as well as stability during binder annealing. Furthermore, the bitumen surface morphology is significantly improved. The polar groups present in the FPP create a thermo-reversible interpenetrating cross- linked network that provides mechanical integrity and contributes to the adhesion to different components of the modified bitumen at service temperatures, enhancing its processability. The exceptional compatibility of FPP in CRMB resulted in a significant increase in the Performance Grade of the hybrid system by 5 classes (88) compared to neat bitumen (58). Moreover, the best-performing composition fulfilled the low-temperature ductility specifications, withstanding deformation without fracturing or breaking up to a 400 mm elongation.

  • Advancing sustainable wastewater management: A comprehensive review of nutrient recovery products and their applications
    • Bogna Śniatała
    • Hussein Al-Hazmi
    • Dominika Sobotka
    • Jun Zhai
    • Jacek Mąkinia
    2024 SCIENCE OF THE TOTAL ENVIRONMENT

    Wastewater serves as a vital resource for sustainable fertilizer production, particularly in the recovery of nitrogen (N) and phosphorus (P). This comprehensive study explores the recovery chain, from technology to final product reuse. Biomass growth is the most cost-effective method, valorizing up to 95 % of nutrients, although facing safety concerns. Various techniques enable the recovery of 100 % P and up to 99 % N, but challenges arise during the final product crystallization due to the high solubility of ammonium salts. Among these techniques, chemical precipitation and ammonia stripping/ absorption have achieved full commercialization, with estimated recovery costs of 6.0–10.0 EUR kgP-1 and 4.4-4.8 £ kgN-1, respectively. Multiple technologies integrating biomass thermo-chemical processing and P and/or N have also reached technology readiness level TRL = 9. However, due to maturing regulatory of waste-derived products, not all of their products are commercially available. The non-homogenous nature of wastewater introduces impurities into nutrient recovery products. While calcium and iron impurities may impact product bioavailability, some full-scale P recovery technologies deliver products containing this admixture. Recovered mineral nutrient forms have shown up to 60 % higher yield biomass growth compared to synthetic fertilizers. Life cycle assessment studies confirm the positive environmental outcomes of nutrient recycling from wastewater to agricultural applications. Integration of novel technologies may increase wastewater treatment costs by a few percent, but this can be offset through renewable energy utilization and the sale of recovered products. Moreover, simultaneous nutrient recovery and energy production via bio-electrochemical processes contributes to carbon neutrality achieving. Interdisciplinary cooperation is essential to offset both energy and chemicals inputs, increase their cos-efficiency and optimize technologies and understand the nutrient release patterns of wastewater-derived products on various crops. Addressing non-technological factors, such as legal and financial support, infrastructure redesign, and market-readiness, is crucial for successfully implementation and securing the global food production.

  • Advancing Urban Transit: Gepard and CAR projects - Innovations in Trolleybus Technology
    • Mikołaj Bartłomiejczyk
    • Leszek Jarzębowicz
    • Slobodan Mirchevski
    • Marcin Połom
    2024

    The Gepard project in Gdynia, Poland, revolutionized the city's trolleybus network with the introduction of “Trolleybus 2.0” vehicles and an innovative charging system. “Trolleybus 2.0” vehicles combine features of traditional trolleybuses and electric buses boasting traction batteries for autonomous driving and dual legal approval. Statistical analysis of energy consumption informed the development of a hybrid charging concept, balancing overhead contact line (OHL) coverage with additional fast charging stations. This hybrid In Motion Charhing (IMC) system reduces costs while ensuring reliable operation, even in adverse weather conditions. Moreover, as part of the CAR project, a fast charging station for trolleybuses was constructed, allowing for the additional extension of trolleybus routes.

  • AGREEMIP: The Analytical Greenness Assessment Tool for Molecularly Imprinted Polymers Synthesis
    • Mariusz Marć
    • Wojciech Wojnowski
    • Francisco Pena-Pereira
    • Marek Tobiszewski
    • Antonio Martín-Esteban
    2024 ACS Sustainable Chemistry & Engineering

    Molecular imprinting technology is well established in areas where a high selectivity is required, such as catalysis, sensing, and separations/sample preparation. However, according to the Principles of Green Chemistry, it is evident that the various steps required to obtain molecularly imprinted polymers (MIPs) are far from ideal. In this regard, greener alternatives to the synthesis of MIPs have been proposed in recent years. However, although it is intuitively possible to design new green MIPs, it would be desirable to have a quantitative measure of the environmental impact of the changes introduced for their synthesis. In this regard, this work proposes, for the first time, a metric tool and software (termed AGREEMIP) to assess and compare the greenness of MIP synthesis procedures. AGREEMIP is based on 12 assessment criteria that correspond to the greenness of different reaction mixture constituents, energy requirements, and the details of MIP synthesis procedures. The input data of the 12 criteria are transformed into individual scores on a 0−1 scale that in turn produce an overall score through the calculation of the weighted average. The assessment can be performed using user-friendly open-source software, freely downloadable from mostwiedzy.pl/agreemip. The assessment result is an easily interpretable pictogram and visually appealing, showing the performance in each of the criteria, the criteria weights, and overall performance in terms of greenness. The application of AGREEMIP is presented with selected case studies that show good discrimination power in the greenness assessment of MIP synthesis pathways.

  • Agri-food waste biosorbents for volatile organic compounds removal from air and industrial gases – A review
    • Patrycja Makoś-Chełstowska
    • Edyta Słupek
    • Jacek Gębicki
    2024 Full text SCIENCE OF THE TOTAL ENVIRONMENT

    Approximately 1.3 billion metric tons of agricultural and food waste is produced annually, highlighting the need for appropriate processing and management strategies. This paper provides an exhaustive overview of the utilization of agri-food waste as a biosorbents for the elimination of volatile organic compounds (VOCs) from gaseous streams. The review paper underscores the critical role of waste management in the context of a circular economy, wherein waste is not viewed as a final product, but rather as a valuable resource for innovative processes. This perspective is consistent with the principles of resource efficiency and sustainability. Various types of waste have been described as effective biosorbents, and methods for biosorbents preparation have been discussed, including thermal treatment, surface activation, and doping with nitrogen, phosphorus, and sulfur atoms. This review further investigates the applications of these biosorbents in adsorbing VOCs from gaseous streams and elucidates the primary mechanisms governing the adsorption process. Additionally, this study sheds light on methods of biosorbents regeneration, which is a key aspect of practical applications. The paper concludes with a critical commentary and discussion of future perspectives in this field, emphasizing the need for more research and innovation in waste management to fully realize the potential of a circular economy. This review serves as a valuable resource for researchers and practitioners interested in the potential use of agri-food waste biosorbents for VOCs removal, marking a significant first step toward considering these aspects together.

  • AI-Powered Cleaning Robot: A Sustainable Approach to Waste Management
    • Johan Carcamo Pineda
    • Ahmad M.A. Shehada
    • Arda Candas
    • Nirav Vaghasiya
    • Murad Abdullayev
    • Jacek Rumiński
    2024

    The world is producing a massive amount of single use waste, especially plastic waste made from polymers. Such waste is usually distributed in large areas within cities, near roads, parks, forests, etc. It is a challenge to collect them efficiently. In this work, we propose a Cleaning Robot as an autonomous vehicle for waste collection, utilizing the Nvidia Jetson Nano platform for precise arm movements guided by computer vision capabilities. Integrated with the Raspberry Pi platform for mobility control, the robot employs the YOLO (You Only Look Once) framework for efficient waste detection and classification. The model was trained, implemented in the robot prototype, and tested on preprocessed waste images, resulting in mean average precision (mAP) above 80 percent. Our design emphasizes singular-object focus, enabling real-time detection of waste with accurate distance (83.7-95.6%) and direction (84.7 97.3%) information. The robot autonomously navigates towards detected waste, halting at a predefined distance for collection and disposal into a designated bin. This work contributes to advancements in waste management systems using small robots.

  • AI-powered Customer Relationship Management – GenerativeAI-based CRM – Einstein GPT, Sugar CRM, and MS Dynamics 365
    • Edyta Gołąb-Andrzejak
    2024 Full text Procedia Computer Science

    Generative artificial intelligence (GenAI) and its implementation in successive business management support systems is a rapidly growing area of theoretical consideration, ongoing research, discourse and application in practice. Recently, the implementation of of GenAI in customer relationship management (CRM) systems has been observed. Accordingly, the aim of this article is to identify areas where GenAI can enhance CRM systems, using Einstain GPT, Sugar CRM or Microsoft Dynamics 365 as examples. To this end, a research question was formulated: how can GenAI improve the effective use of CRM systems? Accordingly, a preliminary study based on secondary data analysis as well as software analysis was conducted to identify areas of GenAI use in CRM systems where we see an increase in the effective application of CRM. The results of the analysis showed that GenAI-powered CRM systems support the effectiveness and efficiency of marketing, sales, commerce, service and system user success. This is because they provide numerous advantages in terms of developing, expanding and strengthening customer relationships through highly advanced personalisation, closely linked to customer segmentation, which allows unique experiences to be provided to individual segments. As a result, this translates into building a company's competitive advantage and increasing the profitability of its CRM efforts.

  • Airport Runoff Water: State-of-the-Art and Future Perspectives
    • Anna Maria Sulej-Suchomska
    • Danuta Szumińska
    • Miguel de la Guardia
    • Piotr Przybyłowski
    • Żaneta Polkowska
    2024 Sustainability

    The increase in the quantity and variety of contaminants generated during routine airport infrastructure maintenance operations leads to a wider range of pollutants entering soil and surface waters through runoff, causing soil erosion and groundwater pollution. A significant developmental challenge is ensuring that airport infrastructure meets high-quality environmental management standards. It is crucial to have effective tools for monitoring and managing the volume and quality of stormwater produced within airports and nearby coastal areas. It is necessary to develop methodologies for determining a wide range of contaminants in airport stormwater samples and assessing their toxicity to improve the accuracy of environmental status assessments. This manuscript aims to showcase the latest advancements (2010–2024 update) in developing methodologies, including green analytical techniques, for detecting a wide range of pollutants in airport runoff waters and directly assessing the toxicity levels of airport stormwater effluent. An integrated chemical and ecotoxicological approach to assessing environmental pollution in airport areas can lead to precise environmental risk assessments and well-informed management decisions for sustainable airport operations. Furthermore, this critical review highlights the latest innovations in remediation techniques and various strategies to minimize airport waste. It shifts the paradigm of soil and water pollution management towards nature-based solutions, aligning with the sustainable development goals of the 2030 Agenda

  • Algebraic periods and minimal number of periodic points for smooth self-maps of 1-connected 4-manifolds with definite intersection forms
    • Haibao Duan
    • Grzegorz Graff
    • Jerzy Jezierski
    • Adrian Myszkowski
    2024 Full text Journal of Fixed Point Theory and Applications

    Let M be a closed 1-connected smooth 4-manifolds, and let r be a non-negative integer. We study the problem of finding minimal number of r-periodic points in the smooth homotopy class of a given map f: M-->M. This task is related to determining a topological invariant D^4_r[f], defined in Graff and Jezierski (Forum Math 21(3):491–509, 2009), expressed in terms of Lefschetz numbers of iterations and local fixed point indices of iterations. Previously, the invariant was computed for self-maps of some 3-manifolds. In this paper, we compute the invariants D^4_r[f] for the self-maps of closed 1-connected smooth 4-manifolds with definite intersection forms (i.e., connected sums of complex projective planes). We also present some efficient algorithmic approach to investigate that problem.

  • Alginate-based sorbents in miniaturized solid phase extraction techniques - Step towards greenness sample preparation
    • Natalia Jatkowska
    2024 Full text TRAC-TRENDS IN ANALYTICAL CHEMISTRY

    In response to growing concerns about environmental degradation, one of the main areas of research activity in recent years has been to make sample preparation methods more sustainable and eco-friendly. The increasing greenness of this step can be achieved by minimizing the usage of reagents, automating individual stages, saving energy and time, and using non-toxic, biodegradable substances. Therefore, the use of natural materials as sorbents in miniaturized extraction techniques is becoming a main trend. One of the natural material that is increasingly being used, not only due to eco-friendly nature but also because of their easy applicability to various sample preparation techniques, is alginate hydrogel. Following this trend, this review discusses the recent application of alginate-based sorbents in various microextraction techniques, focusing on functionalization approaches that enhance extraction performance. Additionally, the green profile of alginate-based sorbent microextraction approaches, along with the sorbent synthesis, were investigated.

  • Algorithmic Human Resources Management
    • Łukasz Sienkiewicz
    2024

    The rapid evolution of Digital Human Resources Management has introduced a transformative era where algorithms play a pivotal role in reshaping the landscape of workforce management. This transformation is encapsulated in the concepts of algorithmic management and algorithmic Human Resource Management (HRM). The integration of advanced analytics, predictive and prescriptive analytics and the power of Artificial Intelligence (AI) has given rise to algorithmic approaches that go beyond traditional human-centric decision-making. This paradigm shift is marked by comprehensive data collection, real-time responses to data influencing management decisions and automated decision-making processes. The culmination of algorithmic management is illustrated in a scheme where human-configured management processes are automated, leading to autonomous decision-making by an information system. The ongoing development of AI-driven algorithms, adapting and becoming self-learning, raises the prospect of increased automation, potentially leading to the displacement of human managers. This chapter provides a comprehensive overview of the evolution of algorithmic management and algorithmic HRM, setting the stage for a deeper exploration of their implications on organisational decision-making, employee management and the future of algorithm-supported management. While algorithmic HRM brings benefits to organisations it also poses risks, such as hidden errors and ethical concerns, emphasising the need for transparency and responsible application. Unconscious system errors, especially in fully automated systems, can lead to detrimental personnel decisions. Organisations must actively counteract potential negative consequences, striking a balance between technology and human decision-making, fostering organisational culture that embraces digital transformation while prioritising the human element. Enterprises should view technology as a tool to enhance work processes, focusing on connecting people and technology to create an innovative and inclusive work environment.

  • Alphitobius diaperinus larvae (lesser mealworm) as human food – An approval of the European Commission – A critical review
    • Shahida Anusha Siddiqui
    • Y.s. Wu
    • K. Vijeepallam
    • K. Batumalaie
    • M.h.m. Hatta
    • H. Lutuf
    • Roberto Castro Munoz
    • I. Fernando
    • S.a. Ibrahim
    2024 Full text Journal of Insects as Food and Feed

    Due to the increasing threat of climate change and the need for sustainable food sources, human consumption of edible insects or entomophagy has gained considerable attention globally. The larvae of Alphitobius diaperinus Panzer (Coleoptera: Tenebrionidae), also known as the lesser mealworm, have been identified as a promising candidate for mass-rearing as a food source based the on evaluation on several aspects such as the production process, the microbiological and chemical composition, and the potential allergenicity to humans. As a consequence, the European Commission has recently approved the utilization of lesser mealworms as human foods. Lesser mealworms are considered a good source of protein, with a protein content ranging from 50-65% of their dry weight and containing various essential amino acids. Lesser mealworms are also rich in other essential nutrients such as iron, calcium, and vitamins B12 and B6. Furthermore, the hydrolysates of lesser mealworms are known to contain antioxidants, suggesting the therapeutic properties of the insects. To enable and ensure a continuous supply of lesser mealworms, various rearing procedures of the insects and information on optimal environmental rearing conditions have been reported. However, like other edible insects, lesser mealworms are still not commonly consumed in Western countries because of various consumer- and product-related factors. Ultimately, the European Commission’s approval of lesser mealworms as a novel food is a key milestone in the development of the insect food industry. Embracing the consumption of edible insects can help address the challenges of feeding a growing population, mitigate the environmental impact of food production, and promote a more sustainable and resilient food system for the future.

  • An absorbing set for the Chialvo map
    • Paweł Pilarczyk
    • Grzegorz Graff
    2024 Communications in Nonlinear Science and Numerical Simulation

    The classical Chialvo model, introduced in 1995, is one of the most important models that describe single neuron dynamics. In order to conduct effective numerical analysis of this model, it is necessary to obtain a rigorous estimate for the maximal bounded invariant set. We discuss this problem, and we correct and improve the results obtained by Courbage and Nekorkin (2010). In particular, we provide an explicit formula for an absorbing set for the Chialvo neuron model. We also introduce the notion of a weakly absorbing set, outline the methodology for its construction, and show its advantage over an absorbing set by means of numerical computations.

  • An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
    • Mojgan Hosseini
    • Jan Treur
    • Wioleta Kucharska
    2024

    Although making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss also strongly believe that mistakes usually have negative consequences but in addition they believe that the boss never makes mistakes, it is often believed that only those who never make mistakes can be bosses and hold power. That’s the problem, such kinds of bosses do not learn. So, on the one hand, we have bosses who select simple tasks to be always seen as perfect. Therefore, also they believe they should avoid mistakes. On the other hand, there exists a mindset of a boss who is not limited to simple tasks, he/she accepts more complex tasks and therefore in the end has better general performance by learning from mistakes. This then also affects the mindset and actions of employees in the same direction. This paper investigates the consequences of both attitudes for the organizations. It does so by computational analysis based on an adaptive dynamical systems modeling approach represented in a network format using the self-modeling network modeling principle.

  • An Adversarial Machine Learning Approach on Securing Large Language Model with Vigil, an Open-Source Initiative
    • Kushal Pokhrel
    • Cesar Sanín
    • Md Rafiqul Islam
    • Edward Szczerbicki
    2024 Full text Procedia Computer Science

    Several security concerns and efforts to breach system security and prompt safety concerns have been brought to light as a result of the expanding use of LLMs. These vulnerabilities are evident and LLM models have been showing many signs of hallucination, repetitive content generation, and biases, which makes them vulnerable to malicious prompts that raise substantial concerns in regard to the dependability and efficiency of such models. It is vital to have a complete grasp of the complex behaviours of malicious attackers in order to build effective strategies for protecting modern artificial intelligence (AI) systems through the development of effective tactics. The purpose of this study is to look into some of these aspects and propose a method for preventing devastating possibilities and protecting LLMs from potential threats that attackers may pose. Vigil is an open-source LLM prompt security scanner, that is accessible as a Python library and REST API, specifically to solve these problems by employing a sophisticated adversarial machine-learning algorithm. The entire objective of this study is to make use of Vigil as a security scanner. and asses its efficiency. In this case study, we shed some light on Vigil, which effectively recognises and helps LLM prompts by identifying two varieties of threats: malicious and benign.

  • An Analysis of Airline GRI and SDG Reporting
    • Eljas Johansson
    2024 Full text

    This study aims to increase our understanding of the Global Reporting Initiative’s (GRI) topic-specific disclosures and the sustainable development goals (SDGs) addressed in the global passenger airline industry’s sustainability reporting (SR). Based on a quantitative content analysis of the industry’s sustainability reports from the financial year 2019 (FY19), this study reveals that airlines focused more on reporting environmental issues, especially emissions, than economic or social dimensions, demonstrating this emission-intensive industry’s responsiveness to stakeholders’ information needs. However, a closer look at the reported impacts shows that many topic-specific disclosures and SDGs, which industry associations have not identified as relevant to the industry, were also mentioned across the reports. Moreover, the results indicated a broader use of SDGs in Asia-Pacific reports than in European. The results are expected to interest practitioners and academics in assessing and developing the industry’s SR.

  • An analytical approach to determine the health benefits and health risks of consuming berry juices
    • Magdalena Fabjanowicz
    • Anna Rożańska
    • Nada S. Abdelwahab
    • Marina Pereira-Coelho
    • Isabel Cristina da Silva Haas
    • Luiz Augusto dos Santos Madureira
    • Justyna Płotka-Wasylka
    2024 Full text FOOD CHEMISTRY

    Food products composition analysis is a prerequisite for verification of product quality, fulfillment of regulatory enforcements, checking compliance with national and international food standards, contracting specifications, and nutrient labeling requirements and providing quality assurance for use of the product for the supplemen- tation of other foods. These aspects also apply to the berry fruit and berry juice. It also must be noted that even though fruit juices are generally considered healthy, there are many risks associated with mishandling both fruits and juices themselves. The review gathers information related with the health benefits and risk associated with the consumption of berry fruit juices. Moreover, the focus was paid to the quality assurance of berry fruit juice. Thus, the analytical methods used for determination of compounds influencing the sensory and nutritional characteristics of fruit juice as well as potential contaminants or adulterations.

  • An ANN-Based Method for On-Load Tap Changer Control in LV Networks with a Large Share of Photovoltaics—Comparative Analysis
    • Klara Janiga
    • Piotr Miller
    • Robert Małkowski
    • Michał Izdebski
    2024 ENERGIES

    The paper proposes a new local method of controlling the on-load tap changer (OLTC) of a transformer to mitigate negative voltage phenomena in low-voltage (LV) networks with a high penetration of photovoltaic (PV) installations. The essence of the method is the use of the load compensation (LC) function with settings determined via artificial neural network (ANN) algorithms. The proposed method was compared with other selected local methods recommended in European regulations, in particular with those currently required by Polish distribution system operators (DSOs). Comparative studies were performed using the model of the 116-bus IEEE test network, taking into account the unbalance in the network and the voltage variation on the medium voltage (MV) side.

  • An annotated timeline of sensitivity analysis
    • Marta Kuc-Czarnecka
    • Stefano Tarantolo
    • Federico Ferretti
    • Samuele Lo Piano
    • Mariia Kozlova
    • Alesio Lachi
    • Rosana Rosati
    • Arnald Puy,
    • Pamphile Roy
    • Giulia Vannucci
    • Andrea Saltelli,
    2024 Full text ENVIRONMENTAL MODELLING & SOFTWARE

    The last half a century has seen spectacular progresses in computing and modelling in a variety of fields, applications, and methodologies. Over the same period, a cross-disciplinary field known as sensitivity analysis has been making its first steps, evolving from the design of experiments for laboratory or field studies, also called ‘in-vivo’, to the so-called experiments ‘in-silico’. Some disciplines were quick to realize the importance of sensitivity analysis, whereas others are still lagging behind. Major tensions within the evolution of this discipline arise from the interplay between local vs global perspectives in the analysis as well as the juxtaposition of the mathematical complexification and the desire for practical applicability. In this work, we retrace these main steps with some attention to the methods and through a bibliometric survey to assess the accomplishments of sensitivity analysis and to identify the potential for its future advancement with a focus on relevant disciplines, such as the environmental field.

  • An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
    • Sasirekha Natarajan
    • Smitha Kurian
    • Parameshachari Bidare Divakarachari
    • Przemysław Falkowski-Gilski
    2024 EXPERT SYSTEMS

    Sentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO) to classify sentiment of tweets. Initially, data is obtained from Twitter API, Sentiment 140 and Stanford Sentiment Treebank-2 (SST-2). The raw data is pre-processed and it is subjected to feature extraction which is performed using Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF). The feature selection is performed using Gazelle Optimization Algorithm (GOA) which removes the irrelevant or redundant features that maximized model performance and classification is performed using Bi LSTM–RAO. The RAO optimizes the loss function of Bi-LSTM model that maximized accuracy. The classification accuracy of proposed method for Twitter API, Sentiment 140 and SST 2 dataset is obtained as 909.44%, 99.71% and 99.86%, respectively. These obtained results are comparably higher than ensemble framework, Robustly Optimized BERT and Gated Recurrent Unit (RoBERTa-GRU), Logistic Regression-Long Short Term Memory (LR-LSTM), Convolutional Bi-LSTM, Sentiment and Context Aware Attention-based Hybrid Deep Neural Network (SCA-HDNN) and Stochastic Gradient Descent optimization based Stochastic Gate Neural Network (SGD-SGNN).

  • An Efficient PEEC-Based Method for Full-Wave Analysis of Microstrip Structures
    • Jinyan Ma
    • Da Li
    • Hanzhi Ma
    • Ruifeng Li
    • Ling Zhang
    • Michał Mrozowski
    • Erping Li
    2024 IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY

    This article introduces an efficient method for the equivalent circuit characterization and full-wave analysis of microstrip structures, leveraging the full-wave partial element equivalent circuit (PEEC). In particular, the multilayered Green's function is evaluated using the discrete complex-image method (DCIM) and employed to establish the mixed potential integral equations. The proposed strategy considers time delays for the retarded electric and magnetic couplings, offering a new efficient full-wave approach to extract equivalent circuit components, which encapsulate the contributions of the quasi-static, surface-wave, and complex images. It is noted that the proposed full-wave PEEC strategy allows each component contribution derived from DCIM to be efficiently represented as frequency-independent lumped circuit elements and corresponding frequency factors, thereby simplifying the extraction process of the entire frequency-dependent lumped elements in the traditional PEEC method. Moreover, the proposed PEEC model, equipped with full-wave equivalent circuits, offers clear physical insight into electromagnetic behaviors, thereby facilitating design and optimization. Finally, the accuracy and efficiency of the proposed PEEC model are fully demonstrated through various examples and experiments.

  • An Example of Using Low-Cost LiDAR Technology for 3D Modeling and Assessment of Degradation of Heritage Structures and Buildings
    • Piotr Kędziorski
    • Marcin Jagoda
    • Paweł Tysiąc
    • Jacek Katzer
    2024 Materials

    This article examines the potential of low-cost LiDAR technology for 3D modeling and assessment of the degradation of historic buildings, using a section of the Koszalin city walls in Poland as a case study. Traditional terrestrial laser scanning (TLS) offers high accuracy but is expensive. The study assessed whether more accessible LiDAR options, such as those integrated with mobile devices such as the Apple iPad Pro, can serve as viable alternatives. This study was conducted in two phases—first assessing measurement accuracy and then assessing degradation detection—using tools such as the FreeScan Combo scanner and the Z+F 5016 IMAGER TLS. The results show that, while low-cost LiDAR is suitable for small-scale documentation, its accuracy decreases for larger, complex structures compared to TLS. Despite these limitations, this study suggests that low-cost LiDAR can reduce costs and improve access to heritage conservation, although further development of mobile applications is recommended.

  • An Extremely Compact Frequency Reconfigurable Antenna Diplexer Employing Dielectric Liquids
    • Rusan Kumar Barik
    • Xiaohu Wu
    • Xiaoguang Liu
    • Sławomir Kozieł
    2024 IEEE Antennas and Wireless Propagation Letters

    The letter presents an extremely compact frequency reconfigurable antenna diplexer based on fluidic channels for sub6 GHz applications. The proposed antenna diplexer is modelled by employing half-mode (HM) and quarter-mode (QM) substrateintegrated rectangular cavities, two slots, orthogonal feed lines, and fluidic vias. To comprehend the radiation mechanism, the equivalent circuit, electric field distributions, and frequency responses are analyzed. Utilization of HM and QM cavities that are loaded with slots results in an extremely compact antenna diplexer. Three fluidic vias are bored from the bottom plane of each cavity and filled with different dielectric liquids to enable frequency reconfigurability. For validation of the concept, an antenna diplexer is built and demonstrated. The constructed antenna prototype has a small footprint 0.078lg2 with 15% and 16% of reconfigurability in lower and upper frequency bands, respectively. The proposed antenna offers high-isolation exceeding 28 dB, realized gain better than > 3.8 dBi, front-to-back-ratio of > −18 dB, and cross-polarization level of > −18 dB. A good consistency is obtained in between full-wave simulations and measurement.

  • An image processing approach for fatigue crack identification in cellulose acetate replicas
    • Krzysztof Pałczyński
    • Jan Seyda
    • Dariusz Skibicki
    • Łukasz Pejkowski
    • Wojciech Macek
    2024 ENGINEERING FAILURE ANALYSIS

    The cellulose acetate replication technique is an important method for studying material fatigue. However, extracting accurate information from pictures of cellulose replicas poses challenges because of distortions and numerous artifacts. This paper presents an image processing procedure for effective fatigue crack identification in plastic replicas. The approach employs thresholding, adaptive Gaussian thresholding, and Otsu binarization to convert gray-scale images into binary ones, enhancing crack visibility. Morphological operations refine object shapes, and Connected Components Analysis facilitates crack identification. Despite limited data, the handcrafted feature extraction algorithm proves robust, addressing challenges. The algorithm shows efficacy in detecting cracks as small as 30 μm, even in the presence of cellulose replication artifacts. The results highlight ability to capture significant cracks’ orientation, length, and growth stages, essential for understanding fatigue mechanisms. Analysis of results, especially evaluation metrics encompassing false positives and false negatives, provides a comprehensive understanding of the algorithm’s strengths and limitations. The proposed tool is available on GitHub.

  • An improved methodology for accelerated marine immersed corrosion testing of ship structural components
    • Krzysztof Wołoszyk
    • Emil Roch
    • Beata Zima
    • Yordan Garbatov
    2024 Ships and Offshore Structures

    Corrosion degradation is a prominent ageing mechanism in engineering structures (e.g. ships and offshore structures), leading to safety concerns and significant economic expenses. This study presents an improved methodology for indoor accelerated corrosion testing of structural components. The method involves controlling natural factors (oxygen saturation, temperature, salinity, and flow rate) to accelerate the corrosion in a controlled environment. The study uses small coupons, medium specimens, and stiffened plates made of steel with different thicknesses. Significant degradation acceleration was achieved compared to natural conditions (approx. twenty times faster). The mean corrosion equals 3.3 mm/year with a maximum 10% variation for different specimen sizes and thicknesses. A novel approach to account for the mass of corrosion products during periodical measurements was proposed and validated. The improved methodology offers an efficient and accurate way to simulate marine immersed corrosion, enabling further research on corrosion degradation behaviour and resistance in ship structures.

  • An improvement of body surface area formulas using the 3D scanning technique
    • Grzegorz Redlarski
    • Sławomir Kozieł
    • Marek Krawczuk
    • Janusz Siebert
    • Marek Tałałaj
    • Aleksander Pałkowski
    • Piotr Tojza
    • Zuzanna Cieślikowska
    • Leszek Litzbarski
    2024 Full text International Journal of Occupational Medicine and Environmental Health

    Objectives: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. Material and Methods: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the majority of known BSA formulas. Furthermore, it was supplement with a comparison with the authors' propositions of enhanced formulas coefficients for known formulas models as well as with new power models based on an increased number of anthropometric data. Results: Introduction of the enhanced formulas coefficients cause a reduction of at least 30.5% in mean absolute error and 21.1% in maximum error in comparison with their known counterparts. Conclusions: In the context of the analysis presented it can be stated that the development of a single universal body surface area formula, based on a small number of state variables, is not possible. Therefore, it is necessary and justified to search for new estimation models that allow for quick and accurate calculation of body surface area for the entire population, regardless of individual body variations. The new formulas presented are such an alternative, which achieves better results than the previously known methods. Int J Occup Med Environ Health 2024;37(2)

  • An Innovative Floating System with a Savonius Rotor as a Horizontal-Axis Wind Turbine
    • Joanna Grzelak
    • Lara Guijarro Carrillo
    • Jacek Nakielski
    • Michał Piotrowicz
    • Krzysztof Doerffer
    2024 Full text Polish Maritime Research

    In this project, an innovative wind turbine was designed for a floating plant. A large Savonius rotor was replaced with a double-rotor wind turbine implemented as a horizontal-axis turbine. This double rotor was positioned on the tip of a thrust plate and fixed to the deck of a catamaran. Simple 2D numerical simulations were performed to confirm the effectiveness of the concept. An analysis of the floating system configuration was carried out, and the loads and stresses on the system components were verified. Next, floating supports with appropriate sizes were selected to counteract the forces on the wind turbine system. Finally, an anchoring system with full rotational freedom was selected for the f loating platform. The present work was conducted as part of a Master’s thesis.

  • An Innovative New Approach to Light Pollution Measurement by Drone
    • Katarzyna Bobkowska
    • Paweł Burdziakowski
    • Paweł Tysiąc
    • Mariusz Pulas
    2024 Drones

    The study of light pollution is a relatively new and specific field of measurement. The current literature is dominated by articles that describe the use of ground and satellite data as a source of information on light pollution. However, there is a need to study the phenomenon on a microscale, i.e., locally within small locations such as housing estates, parks, buildings, or even inside buildings. Therefore, there is an important need to measure light pollution at a lower level, at the low level of the skyline. In this paper, the authors present a new drone design for light pollution measurement. A completely new original design for an unmanned platform for light pollution measurement is presented, which is adapted to mount custom sensors (not originally designed to be mounted on a unmanned aerial vehicles) allowing registration in the nadir and zenith directions. The application and use of traditional photometric sensors in the new configuration, such as the spectrometer and the sky quality meter (SQM), is presented. A multispectral camera for nighttime measurements, a calibrated visible-light camera, is used. The results of the unmanned aerial vehicle (UAV) are generated products that allow the visualisation of multimodal photometric data together with the presence of a geographic coordinate system. This paper also presents the results from field experiments during which the light spectrum is measured with the installed sensors. As the results show, measurements at night, especially with multispectral cameras, allow the assessment of the spectrum emitted by street lamps, while the measurement of the sky quality depends on the flight height only up to a 10 m above ground level.

  • An intelligent cellular automaton scheme for modelling forest fires
    • Joan Boters Pitarch
    • María Signes-Pont
    • Julian Szymański
    • Higinio Mora-Mora
    2024 Full text Ecological Informatics

    Forest fires have devastating consequences for the environment, the economy and human lives. Understanding their dynamics is therefore crucial for planning the resources allocated to combat them effectively. In a world where the incidence of such phenomena is increasing every year, the demand for efficient and accurate computational models is becoming increasingly necessary. In this study, we perform a revision of an initial proposal which consists of a two-dimensional propagation model based on cellular automata (2D-CA), which aims to understand the dynamics of these phenomena. We identify the key theoretical weaknesses and propose improvements to address these limitations. We also assess the effectiveness and accuracy of the model by evaluating improvements using real forest fire data (Beneixama, Alicante 2019). Moreover, as a result of the theoretical modifications performed, we introduce a novel intelligent architecture that seeks to capture relationships between system cells from the data. This new architecture has the ability to advance our understanding of forest fire dynamics, contributing to both the evaluation of existing protocols and more efficient firefighting resource management.

  • An inverse algorithm for contact heat conduction problems with an interfacial heat source based on a first-order thermocouple model
    • Oleksii Nosko
    2024 Full text INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER

    Inverse problems of contact heat conduction with an interfacial heat source are common in various fields of science, engineering and technology. In this study, an algorithm for their solution is developed based on an inverse parametric optimisation method with an impulse response function describing the heat partition and contact heat transfer. A first-order thermocouple model with a time constant parameter is embedded in the impulse response function. The specific power of the heat source is sought in the form of a polynomial from the condition of least-squares deviation of the simulated temperature from the temperature samples obtained by a thermocouple. Compared to the classical methods of simple inverse convolution and sequential function specification, the algorithm proves to be accurate in a substantially larger region of variation of the heating duration and time constant, covering slow-response thermocouple measurements. Additionally, the algorithm is significantly more robust against noise with a sufficient number of temperature samples. The applicability of the algorithm is demonstrated by solving inverse problems of contact heat conduction typical for sliding friction, laser and electric resistance welding at different thermal contact conditions and ratios of the time constant to the heating duration.

  • An optimized dissolved oxygen concentration control in SBR with the use of adaptive and predictive control schemes
    • Tomasz Zubowicz
    • Tomasz Ujazdowski
    • Zuzanna Klawikowska
    • Robert Piotrowski
    2024 Full text

    This paper addresses the problem of optimizing control of the aeration process in a water resource recovery facility (WRRF) using sequencing batch reactor (SBR), one that affects the efficiency of wastewater treatment by stimulating metabolic reactions of microorganisms through dissolved oxygen (DO) level control, and accounts for the predominant part of operating costs. Two independent approaches to DO control algorithm design based on nonlinear model-based predictive control (NMPC) with constraints and direct model reference adaptive control (DMRAC) are proposed and compared. Both algorithms were developed on the basis of utility models obtained by cognitive model simplification, however, both algorithms are characterized by a distinct mechanism to achieve control optimality and incorporate uncertainty. The NMPCbased algorithm solves an online optimization task by reducing the impact of uncertainty through feedback and estimating its influence by evaluating the differences between the internal model and measurements on a sliding prediction window. In contrast, DMRAC reduces the impact of uncertainty through the adaptation of control law parameters. Meanwhile, optimality is encoded in the reference model parameters reflecting the operation of the closed-loop system and in the independent parameters of the adaptation mechanism. Illustrations of the algorithms’ operation were provided by simulation experiments using a three-layer SBR model of the Swarzewo wastewater treatment plant with ASM3e-based reactions.

  • An Optimized Ka-Band Low Profile Dual-Polarized Transmitarray Antenna With 2D Beam Switching
    • Seyed Hashem Ramazannia Tuloti
    • Adam Lamęcki
    • Michał Mrozowski
    2024 Full text IEEE Access

    This article presents an optimized dual-polarized transmitarray antenna (TA) designed for MIMO applications at the Ka-band, capable of switching beams in two directions. The antenna aperture uses a small unit cell with three layers of Taconic RF-35 dielectric substrates, which can be easily fabricated using PCB technology. The unit cell achieved a 360-degree phase shift and a transmission magnitude exceeding –0.4 dB at 28 GHz. We used nine dual-polarized patch antennas in a cross shape, each with a 10.5 dBi gain at 28 GHz, to switch the beams in two directions without changing the feed location. We optimized the phase distribution in the TA aperture and adjusted the feed antenna’s F/D and tilt to achieve a high-gain antenna with low-gain roll-off during beam switching. The fabricated TA exhibited excellent agreement with the full-wave simulation results. It achieved ±15 degrees and ±30 degrees beam tilts in the x- and y- directions, with less than 0.8 dB gain roll-off for both polarizations

  • An optimized system for sensor ontology meta-matching using swarm intelligent algorithm
    • Abdul Lateef Haroon P S
    • Sujata N. Patil
    • Parameshachari Bidare Divakarachari
    • Przemysław Falkowski-Gilski
    • M. D. Rafeeq
    2024 Internet Technology Letters

    It is beneficial to annotate sensor data with distinct sensor ontologies in order to facilitate interoperability among different sensor systems. However, for this interoperability to be possible, comparable sensor ontologies are required since it is essential to make meaningful links between relevant sensor data. Swarm Intelligent Algorithms (SIAs), namely the Beetle Swarm Optimisation Algorithm (BSO), present a possible answer to ontology matching problems. This research focuses on a method for optimizing ontology alignment that employs BSO. A novel method for effectively controlling memory use and striking a balance between algorithm exploration and exploitation is proposed: the Simulated Annealing-based Beetle Swarm Optimisation Algorithm (SA-BSO). Utilizing Gray code for solution encoding, two compact operators for exploitation and exploration, and Probability Vectors (PVs) for swarming choosing exploitation and exploration, SA-BSO combines simulated annealing with the beetle search process. Through inter-swarm communication in every generation, SA-BSO improves search efficiency in addressing sensor ontology matching. Three pairs of real sensor ontologies and the Conference track were used in the study to assess SA-BSO's efficacy. Statistics show that SA-BSO-based ontology matching successfully aligns sensor ontologies and other general ontologies, particularly in conference planning scenarios.

  • An Overview of Sport and the Future Smart Cities
    • Aleksander Orłowski
    • Narek Parsamyan
    2024

    One of the main challenges for future cities is to strengthen the role of people and their activities. Therefore, sport provides an opportunity to engage in physical activity, connecting citizens to the city. The question of how sport influences the development of cities and the concept of future smart cities arises. The aim of this study is to examine the relationship between sport and the concept of smart cities by identifying sport factors in the literature. The article highlights different areas of influence of sport on the smart city concept through specific examples of the contribution of sport to urban development and the well-being of citizens. The study states that the consideration of sport in the context of smart cities is relevant and multidimensional, since sport is a factor for the development of city solutions using in “hard” projects such as infrastructural and technological ones, and “soft” projects relating to improving social inclusion and healthcare. Including sport as a building component of the smart city concept is a new perspective of city governance, which is so far rarely discussed and, therefore, important. Sport has a broad influence on the social, technological, and environmental evolution of cities, therefore, sport appears to be a relevant factor that should contribute to the debate on future city agendas. The research delivers the links between sport and smart cities, which is important for further scientific considerations on the insights of smart city, and explores the subject of the influence of sport on the evolution of cities of tomorrow.

  • Analiza czasochłonności docierania jednotarczowego powierzchni płaskich elementów ceramicznych - studium przypadku
    • Adam Barylski
    2024

    Przedstawiono analizę czasochłonności docierania elementów ceramicznych. Badano czasochłonność obróbki na dwóch docierarkach jednotarczowych o znacząco różniących się średnicach tarcz docierających. Porównano czasy jednostkowe docierania elementów płaskich z ceramiki technicznej Al2O3

  • Analiza doświadczalna wpływu długości zakotwienia pręta na zachowanie przyczepności w teście pull-out
    • Marcin Burdziński
    • Maciej Niedostatkiewicz
    2024 Full text Inżynieria i Budownictwo

    Artykuł prezentuje badania przyczepności przeprowadzone przy użyciu testu pull-out. Eksperymenty miały na celu ocenę wpływu długości zakotwienia na przyczepność w tym teście. Z przeprowadzonej analizy wynika, że długość styku pręt-beton znacząco wpływa na zachowanie przyczepności. Określa ona typ zniszczenia połączenia, wpływa na rozkład i wartość naprężeń w pręcie oraz rzutuje na przebieg krzywej przyczepność-poślizg, która jest kluczowym rezultatem testu pull-out.

  • Analiza numeryczna wpływu długości zakotwienia pręta na zachowanie przyczepności w teście pull-out
    • Marcin Burdziński
    • Maciej Niedostatkiewicz
    2024

    Artykuł przedstawia symulacje numeryczne testu pull-out przeprowadzone w programie ABAQUS. Celem analizy była ocena wpływu długości zakotwienia pręta żebrowanego na przyczepność. Interakcję pręta z betonem odwzorowano za pomocą kohezyjnej powierzchni kontaktu, wykorzystując skalibrowane krzywe zależności przyczepność-poślizg, otrzymane z badań własnych. W obliczeniach numerycznych wykorzystano parametry mechaniczne betonu i stali wykorzystanych w eksperymentach. Analiza wykazała istotny wpływ długości zakotwienia na zachowanie przyczepności. Wyniki symulacji numerycznych charakteryzują się wysoką zbieżnością z rezultatami eksperymentów, m.in. pod względem krzywej przyczepność-poślizg czy pracy materiałów.

  • Analiza numeryczna wpływu długości zakotwienia pręta na zachowanie przyczepności w teście pull-out
    • Marcin Burdziński
    • Maciej Niedostatkiewicz
    2024 Full text Inżynieria i Budownictwo

    W artykule przedstawiono symulacje numeryczne testu pull-out w programie ABAQUS. Symulacje miały na celu ocenienie wpływu długości zakotwienia pręta żebrowanego na przyczepność w tym teście, opierając się na wynikach przeprowadzonych eksperymentów. Interakcję pręta z betonem odwzorowano za pomocą kohezyjnej powierzchni kontaktu, wykorzystując skalibrowane krzywe przyczepność-poślizg, otrzymane z doświadczeń wykonanych w ramach badań własnych. Do zdefiniowania modeli materiałowych użyto parametrów mechanicznych betonu i stali wykorzystanych w testach. Przeprowadzona analiza wykazała, że długość zakotwienia znacząco wpływa na zachowanie przyczepności. Rezultaty symulacji numerycznych charakteryzują się dużą zbieżnością z badaniami laboratoryjnymi, zarówno pod kątem krzywej przyczepność-poślizg, jak i pracy materiałów.

  • ANALIZA POSTACI SYGNAŁU SYNCHRONIZACYJNEGO NPSS W NB-IOT
    • Olga Błaszkiewicz
    • Jarosław Sadowski
    • Piotr Rajchowski
    2024 Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

    W artykule zaprezentowane zostały możliwości zmiany postaci sekwencji Zadoff-Chu używanej do wygenerowania sygnału synchronizacyjnego NPSS w interfejsie radiowym NB-IoT. Modyfikacji poddano elementy charakterystyczne sekwencji z uwzględnieniem: root index, ciągu binarnego czy składnika funkcji wykładniczej w celu poprawy właściwości korelacyjnych na potrzeby synchronizacji pracy terminali użytkowników.

  • Analiza stateczności skarpy klifu w ciągubrzegu morskiego w miejscowości Rozewie
    • Witold Tisler
    • Wiktoria Pałasz
    • Tomasz Pierzchliński
    • Natalia Piórkowska
    • Kacper Szulc
    2024 Builder

    W opracowaniu przedstawiono wariantową analizę stateczności wykonaną dla klifu znajdującego się w miejscowości Rozewie. Na zboczu z uwagi na gęstą roślinność oraz wysokie nachylenie zachodzą procesy osuwiskowe i wymaga ono wzmocnienia. W porównaniu przeprowadzonych analiz szczególną uwagę zwrócono na sposób modelowania poziomu wody gruntowej oraz wartości parametrów przyjmowanych dla modelu van Genuchtena, odpowiedzialnego za analizę przepływu w strefie nienasyconej.

  • Analiza techniczno-ekonomiczna zastosowania systemu magazynowania energii zasilanego z instalacji fotowoltaicznej
    • Blanka Jakubowska
    • Aleksandra Sierdzińska
    2024 Rynek Energii

    W artykule dokonano oceny celowości implementacji magazynu energii do instalacji fotowoltaicznej o mocy zainstalowanej 39,3 kW. W analizowanym przypadku prąd produkowany jest na potrzeby gospodarstwa sadowniczego oraz mieszkańców domu jednorodzinnego. Analiza, oparta na realnych danych rocznej eksploatacji systemu fotowoltaicznego, uwzględnia ilość wyprodukowanej energii nadwyżki energii przekazywanej do sieci i z niej pobieranej. Zebrane dane umożliwiły odpowiedni dobór pojemności akumulatorów. W ramach prowadzonej analizy określono ilość energii jaka możliwa jest do zmagazynowania, liczbę cykli pracy, koszty eksploatacyjne i inwestycyjne oraz koszt zaoszczędzonej energii. Przeprowadzona analiza opiera się na dwóch wariantach, wykorzystujących technologie baterii litowo-jonowych i kwasowo-ołowiowych.

  • ANALYSIS AND OPTIMIZATION OF ELECTRIC VEHICLE CHARGING PROCESSES IN TRANSACTIVE ENERGY SYSTEMS
    • Halyna Bielokha
    • Ryszard Strzelecki
    • Denys Derevianko
    • Ihor Radysh
    2024 Full text POWER ENGINEERING

    The implementation of smart charging of electric vehicles allows operators of local power networks and electricity suppliers to implement new business models for the interaction of electric vehicles with the network. In addition to the optimal selection of Microgrid capacities when charging electric vehicles, it is also important to use different charging methods. To satisfy the interests of all participants of local systems from an economic and technical point of view, the concept of transactional energy was chosen. The effect of different charge management methods on EV battery efficiency, such as two-stage charging (CC-CV), accelerated charging (AC) and alternative multi-level MSCC charging, has been investigated. The optimization of charging processes aims not only to increase the profit from the sale of electricity, but also to minimize charging costs by means of an optimal flow of electricity from the network to the car. The proposed objective function depends on the generation capacity of all sources included in the system, the state of charge of the storage systems, the time of day, the charging time of electric vehicles, the charging speed, and the price of electricity. The control system, solving the objective function, itself chooses and offers the consumer and the aggregator a charging method that, given the system parameters, will be optimal for all participants of the transactional system. Three charge methods were investigated by digital simulation for four different types of electric vehicles, all considered charge methods have high energy efficiency indicators that can be used as control methods for charging electric vehicles from local systems

  • Analysis of cyclone separator solutions depending on spray ejector condenser conditions
    • Milad Amiri
    • Paweł Ziółkowski
    • Jaroslaw Mikielewicz
    • Michał Klugmann
    • Dariusz Mikielewicz
    2024 APPLIED THERMAL ENGINEERING

    The core design strategy for minimizing CO2 emissions in gas power plant entails combining a spray ejector condenser (SEC) and separator to accomplish steam condensation and CO2 purification. This innovative process involves direct-contact condensation of steam with CO2, facilitated by interaction with a subcooled water spray, along with a cyclone separator mechanism intended for generating pure CO2. The investigation of the SEC section, both experimentally and analytically, provides crucial insights into its operational dynamics. Given the susceptibility of cyclone efficiency to fluctuations in SEC conditions, this research endeavors to examine the impacts of CO2 volumetric flow rate and droplet break-up within the SEC on the separation efficacy of the cyclone separator. Additionally, the impact of cone size on the performance of the cyclone has been investigated. Here, a three-dimensional, transient, and turbulent cyclone separator is numerically simulated using Ansys Fluent 2021 R1. The Reynolds Stress Model is employed to simulate turbulent flow, while a mixture model is utilized to replicate swirl two-phase flow within the separators. The findings revealed that reductions in steam and CO2 flow rates were associated with a decrease in outlet temperature but an increase in SEC inlet temperature, leading to a rise in temperature difference and heat transfer rate. Furthermore, an augmentation in cyclone cone size (from 0.2 to 0.5 m) resulted in enhanced separation efficiency (from 77.30% to 80.98%) alongside an elevation in pressure drop (from 6.08 Pa to 10.91 Pa), suggesting a compromise between CO2 purification and energy consumption. Additionally, elevated CO2 flow rates induced a rise in pressure drop and separation efficiency, ultimately achieving maximum efficiency at a rate of 24 g/s. Moreover, the exploration into droplet breakup manifesting in a boost in separation efficiency from 50.98% to 100% across droplet diameters ranging from 1 to 20 μm.

  • Analysis of dynamics of a map-based neuron model via Lorenz maps
    • Piotr Bartłomiejczyk
    • Frank Llovera Trujillo
    • Justyna Signerska-Rynkowska
    2024 Full text CHAOS

    Modeling nerve cells can facilitate formulating hypotheses about their real behavior and improve understanding of their functioning. In this paper, we study a discrete neuron model introduced by Courbage et al. [Chaos 17, 043109 (2007)], where the originally piecewise linear function defining voltage dynamics is replaced by a cubic polynomial, with an additional parameter responsible for varying the slope. Showing that on a large subset of the multidimensional parameter space, the return map of the voltage dynamics is an expanding Lorenz map, we analyze both chaotic and periodic behavior of the system and describe the complexity of spiking patterns fired by a neuron. This is achieved by using and extending some results from the theory of Lorenz-like and expanding Lorenz mappings.

  • Analysis of Ferroresonance Mitigation Effectiveness in Auxiliary Power Systems of High-Voltage Substations
    • Rafał Tarko
    • Wiesław Nowak
    • Jakub Gajdzica
    • Stanisław Czapp
    2024 Full text ENERGIES

    Ferroresonance in power networks is a dangerous phenomenon, which may result in overcurrents and overvoltages, causing damage to power equipment and the faulty operation of protection systems. For this reason, the possibility of the occurrence of ferroresonance has to be identified, and adequate methods need to be incorporated to eliminate or reduce its effects. The aim of this paper is to evaluate the effectiveness of ferroresonance damping in auxiliary power systems of high-voltage substations by selected damping devices. Laboratory experiments, the results of which created bases for the development of models of selected damping devices, are presented. These models were used to simulate the effectiveness of ferroresonance damping in an auxiliary power system of a 220/110 kV substation in the EMTP-ATP program. The analyses showed that control systems with different algorithms of operation are used in damping devices. This knowledge is important when selecting parameters and settings of the applied damping devices for a given network and the disturbances in it. The presented research results have proved the effectiveness of commercially available damping devices, provided their parameters are correctly coordinated with the settings of the power system protection.

  • Analysis of friction ridge evidence for trace amounts of paracetamol in various pharmaceutical industries by Raman spectroscopy
    • Martyna Czarnomska
    • Aneta Lewkowicz
    • Mattia Pierpaoli
    • Emilia Gruszczyńska
    • Magdalena Kasprzak
    • Zygmunt Gryczyński
    • Piotr Bojarski
    • Sławomir Steinborn
    • Krzysztof Woźniewski
    2024 Full text JOURNAL OF FORENSIC SCIENCES

    The detection of potentially harmful substances presents a multifaceted challenge. On one hand, it can directly save lives, on the other, it can significantly aid and enhance police work, thereby increasing the effectiveness of investigations. The research conducted in this study primarily aims to identify paracetamol in fingerprints, considering situations involving direct contact of a person with paracetamol either chronically or in a single dose. The identification procedure presented, utilizing Raman spectroscopy, aims to rapidly detect the xenobiotic following ingestion by an individual, which involves touching the tablet with their fingers—this can be termed as touch evidence in forensic science investigations. Additionally, the authors focus on assessing the impact of additives present in drugs containing paracetamol as the main active ingredient. The screening results obtained will enable us to analyze the composition of drugs in terms of potentially toxic substances, and their influence on the physicochemical activity of the active substance. We successfully identified the paracetamol molecule using a noninvasive forensic trace detection method. Samples in the form of common drugs containing 500 mg of paracetamol were studied. Throughout the study, comprehensive validation of the method was ensured through the utilization of a statistical model, which excluded sensitivity to the presence of other substances, whether additives or from the external environment. The proposed approach to trace the content of substances in fingerprint using Raman scattering analysis provides a useful starting point to enhance current analytical methods not only in forensic science but also in toxicology.

  • Analysis of regulations regarding transport of dangerous goods by road in Poland and in Europe
    • Bartłomiej Kobus
    • Joanna Wachnicka
    2024 Full text Przegląd Komunikacyjny

    The subject of the article are regulations regarding transport of hazardous materials in road transportation. In Poland, as well as in most European countries, these regulations are mainly governed by the ADR Agreement, which is a supra-national legal act. The article contains an analysis of the mentioned legal act. Despite the fact that the ADR Agreement harmonizes regulations concerning the transport of hazardous materials, there are domestic standards that diff er slightly from the provisions of this agreement. The article also describes parking facilities for vehicles carrying hazardous materials in Poland and presents statistical data regarding parking spaces for this type of vehicles.

  • Analysis of Roughness, the Material Removal Rate, and the Acoustic Emission Signal Obtained in Flat Grinding Processes
    • Piotr Sender
    • Irene Buj - Corral
    • Jesús Álvarez-Flórez
    2024 Full text Machines

    In this work, the analysis of the acoustic emission (AE) signal in grinding processes is addressed. The proposed analysis method decomposes the acoustic signal into three frequency ranges. The total energy of each range is determined, as well as the highest frequency. Different grinding experiments were carried out, according to a full factorial design of experiments (DOE), in which feed speed, depth of cut, and transversal step (table cross feed) were varied. Arithmetic average roughness Ra and the material removal rate (MRR) were determined. It was observed that Ra depends mainly on the transversal step, followed by feed speed and the interaction between the transversal step and depth of cut, while MRR is greatly influenced by the transversal step. According to multi-objective optimization with the Derringer–Suich function, in order to simultaneously minimize Ra and maximize MRR, a transversal step of 9 mm per longitudinal pass, feed speed of 20 m/min, and depth of cut of 0.020 mm should be selected.

  • Analysis of the influence of geometrical imperfections on the equivalent load stabilizing roof truss with lateral bracing system
    • Marcin Krajewski
    2024 Full text Journal of Theoretical and Applied Mechanics

    The paper is focused on the numerical analysis of the stability and load bearing capacity of a flat steel truss. The structure was supported by elastic lateral braces. The translational and rotational brace stiffness was taken into account. The linear buckling analysis were performed for the beam and shell model of the truss. The nonlinear static analysis were conducted for the structure initial geometric imperfections. As a result the buckling load and the limit load depended on brace stiffness was obtained. The reactions in elastic braces were compared to the stabilizing forces calculated on the basis of actual code requirements.