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Gdańsk University of Technology

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Publications from the year 2023

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  • Akademia Inżynierska w Polsce jako kontynuatorka tradycji przedwojennej Akademii Nauk Technicznych
    • Jerzy Barglik
    • Dariusz Świsulski
    2023

    Przedstawiono historię Akademii Nauk Technicznych i Polskiej Akademii Nauk Technicznych. Omówiono genezę i działalność Akademii Inżynierskiej w Polsce.

  • Aktualny stan wdrożenia BIM w polskich firmach budowlanych
    • Magdalena Apollo
    • Beata Grzyl
    2023 Full text Materiały Budowlane

    Celem artykułu jest określenie zakresu zastosowania technologii BIM przez inżynierów budownictwa. Wykorzystując badania ankietowe, zidentyfikowaliśmy m.in. zasadnicze bariery związane z wdrożeniem BIM. Przeprowadzone badanie potwierdziło, że stopień aplikacji technologii BIM w polskich firmach budowlanych nadal nie jest satysfakcjonujący, a jej tempo rozwoju w znacznej mierze zależy od wymagań, jakie stawiają zamawiający publiczni i inwestorzy prywatni.

  • Algorytmizacja tworzenia i dystrybucji treści medialnych a doświadczenie liminalne i zawodowa tożsamość dziennikarska
    • Jan Kreft
    2023

    W cyfrowym środowisku współczesnych mediów algorytmy mogą tworzyć tekstowe i wizualne treści dziennikarskie oraz wiele wersji tego samego artykułu z uwzględnieniem potrzeb poszczególnych odbiorców/użytkowników . Algorytmizacja dziennikarskiej pracy jest coraz chętniej wykorzystywana w zarządzaniu organizacjami mediów, a analizy danych o czytelnikach, widzach i słuchaczach decydują o podejmowanych tematach zastępując tradycyjnego dziennikarskiego „nosa” i ułatwiają reklamodawcom dostęp do odbiorców. Obecność dziennikarza w procesie powstawania i dystrybucji treści medialnej nie jest już niezbędna. Coraz powszechniejsza presja algorytmizacji dziennikarstwa skłania do badań nad zawodową tożsamością dziennikarzy i nad podejmowanymi przez nich strategiami w obliczu nowych technologii. W artykule sugeruję, że dogodną badawczą perspektywą pozwalającą uzyskać wzgląd w postawy wobec algorytmizacji tworzenia i dystrybucji dziennikarskiej treści jest koncepcja liminalności.

  • Ammonium and potassium vanadates: synthesis, physicochemical characterization, and applications
    • Małgorzata Nadolska-Dawidowska
    2023 Full text

    This doctoral thesis is devoted to the synthesis and investigation of ammonium/potassium vanadates, which constitute an interesting group of materials due to their potential applications in electrochemical devices and photocatalysis. The scope of the conducted experimental work included the synthesis of ammonium/potassium vanadates, their physicochemical characterization using various methods (spectroscopy, microscopy, thermal analysis and others), and evaluation of their use as cathode materials for Lithium-ion batteries (LIBs) or photocatalysts for the degradation of water contaminants. The main part of the thesis presents the conducted research and its analysis and consists of a collection of five articles [A1-A5] published in the following journals: Electrochimica Acta (IF 6.901, 100 pts. MEiN, 2020), Inorganic Chemistry (IF 5.436, 140 pts. MEiN, 2022), Materials (IF 3.057, 140 pts. MEiN, 2019), and Scientific Reports (IF 4.996, 140 pts MEiN, 2022 and 2023). This part is preceded by a brief introduction to the vanadate family, general motivation for the conducted research, and the current state of knowledge about ammonium/potassium vanadates, with special regard to their application as electrode materials for metal-ion batteries and photocatalysts. In the final section, the most significant achievements obtained within this thesis are summarized, and future research directions are presented. As part of the research, repeatable synthetic routes for uniform nanostructures of ammonium/potassium vanadates were developed. Notably, for the first time, the effect of precursor morphology and initial pressure on the hydrothermal synthesis of ammonium vanadates was studied. Furthermore, it has been proven that the obtained ammonium/potassium vanadates can be successfully used as efficient cathode materials for LIBs and as solar light-driven photocatalysts for decomposing water pollutants. In the case of the former application, hydrated vanadate compounds, i.e., (NH4)2V10O25∙nH2O and K2V6O16·nH2O were tested and described for the first time. For the latter, two new photocatalytic materials were proposed (KV3O8 and a composite based on NH4V4O10 and reduced graphene oxide). In addition, more detailed studies (kinetics and mechanism of the photocatalysis process) were presented for K2V6O16·nH2O and NH4V4O10.

  • An adaptive approach to non-destructive evaluation (NDE) of cast irons containing precipitated graphite particles with the help of magnetoacoustic emission
    • Leszek Piotrowski
    • J. Sertucha
    2023 NDT & E INTERNATIONAL

    Physical properties of cast irons strongly depend on both their microstructure and the presence of casting defects. The paper analyses the possibility of application of magnetoacoustic emission (MAE) for nondestructive detection of flawed cast iron components. The investigated samples containing dross, chunky graphite and lamellar graphite were compared with the reference, flawless, spheroidal cast iron sample. The optimisation adaptive procedure was applied for sensitivity enhancement. Application of five different acoustic emission sensors and filtering band optimisation enabled finding the optimum sensor/band configuration allowing not only for flawed samples identification, but also for discerning various kinds of flaws.

  • An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
    • Natalie Samhran
    • Jan Treur
    • Wioleta Kucharska
    • Anna Monika Wiewiora
    2023

    This paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects. Computational simulations of the introduced adaptive network were analyzed in different contexts varying in organization culture and leader characteristics. Statistical analysis results proved to be significant and supported the research hypotheses. Ultimately, this paper provides insight into how organizations that foster a mistake-tolerant attitude in alignment with the leader, can result in significantly better organizational learning on a team and individual level.

  • An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
    • S. Vettori
    • E. Di Lorenzo
    • Bart Peeters
    • Marcin Łuczak
    • E. Chatzi
    2023 Full text MECHANICAL SYSTEMS AND SIGNAL PROCESSING

    The establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical structure, the monitored response of the Digital Twin should match the one experienced by the actual system throughout the complete spectrum of its operational conditions. In most typical SHM configurations, it is only possible to rely on output-only measurements, acquired from finite positions within a structure, which naturally raises the challenge of recovering the full-field operational response, including unmeasured locations. This problem, also known as Virtual Sensing (VS), has been treated using different schemes, including Bayesian filtering and Modal Expansion (ME). In this paper, the Augmented Kalman Filter (AKF) is exploited to this end; a tool which allows for simultaneous full-field response and unmeasured input prediction. The common issue of Bayesian filtering relies on calibration of the filters defining parameters, namely the assumed measurement and process noise covariance levels. While the first is directly related to the accuracy of the employed physical sensors, the latter often acts as a tuning parameter for improving the reliability of the prediction. The process noise covariance adjustment is often performed in an offline fashion, either by making use of regularization methods, e.g., the L-curve method, or via trial and error. In this work, we propose a methodology for automated process noise covariance adaptation, relying on response estimates recovered by means of an improved ME approach. The method is validated on experimental data from a large scale research Wind Turbine (WT) blade made of glass fiber reinforced plastics.

  • An advanced synergy of partial denitrification-anammox for optimizing nitrogen removal from wastewater: A review
    • Hussein Al-Hazmi
    • Mojtaba Maktabifard
    • Dominika Grubba
    • Joanna Majtacz
    • Gamal K. Hassan
    • Xi Lu
    • Grzegorz Piechota
    • Giorgio Mannina
    • Charles B. Bott
    • Jacek Mąkinia
    2023 BIORESOURCE TECHNOLOGY

    Anammox is a widely adopted process for energy-efficient removal of nitrogen from wastewater, but challenges with NOB suppression and NO3− accumulation have led to a deeper investigation of this process. To address these issues, the synergy of partial denitrification and anammox (PD-anammox) has emerged as a promising solution for sustainable nitrogen removal in wastewater. This paper presents a comprehensive review of recent developments in the PD-anammox system, including stable performance outcomes, operational parameters, and mathematical models. The review categorizes start-up and recovery strategies for PD-anammox and examines its contributions to sustainable development goals, such as reducing N2O emissions and saving energy. Furthermore, it suggests future trends and perspectives for improving the efficiency and integration of PD-anammox into full-scale wastewater treatment system. Overall, this review provides valuable insights into optimizing PD-anammox in wastewater treatment, highlighting the potential of simultaneous processes and the importance of improving efficiency and integration into full-scale systems.

  • An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
    • Francesco Fatone
    • Bartosz Szeląg
    • Przemysław Kowal
    • Arthur McGarity
    • Adam Kiczko
    • Grzegorz Wałek
    • Ewa Wojciechowska
    • Michał Stachura
    • Nicolas Caradot
    2023 Full text HYDROLOGY AND EARTH SYSTEM SCIENCES

    An innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed from multiple runs of the US Environmental Protection Agency (EPA) Storm Water Management Model (SWMM). The extensions enable the inclusion of (1) the characteristics of the catchment and its stormwater network, calibrated model parameters expressing catchment retention, and the capacity of the sewer system; (2) extended sensitivity analysis; and (3) risk analysis. Sensitivity coefficients of calibrated model parameters include correction coefficients for percentage area, flow path, depth of storage, and impervious area; Manning roughness coefficients for impervious areas; and Manning roughness coefficients for sewer channels. Sensitivity coefficients were determined with respect to rainfall intensity and characteristics of the catchment and stormwater network. Extended sensitivity analysis enabled an evaluation of the variability in the specific flood volume and sensitivity coefficients within a catchment, in order to identify the most vulnerable areas threatened by flooding. Thus, the model can be used to identify areas particularly susceptible to stormwater network failure and the sections of the network where corrective action should be taken to reduce the probability of system failure. The simulator developed to determine the specific flood volume represents an alternative approach to the SWMM that, unlike current approaches, can be calibrated with limited topological data availability; therefore, the aforementioned simulator incurs a lower cost due to the lower number and lower specificity of data required.

  • An air-assisted dispersive liquid phase microextraction method based on a hydrophobic magnetic deep eutectic solvent for the extraction and preconcentration of melamine from milk and milk-based products
    • Adil Elik
    • Seçkin Fesliyan
    • Nevcihan Gürsoy
    • Hameed Haq
    • Roberto Castro Munoz
    • Nail Altunay
    2023 FOOD CHEMISTRY

    In the current research, a fast and sustainable air-assisted hydrophobic magnetic deep eutectic solvent-based dispersive liquid phase microextraction followed by UV–Vis spectrophotometry measurements was optimized for the extraction and determination of melamine in milk and milk-based products. The central composite design was applied for the optimization of factors affecting the recovery of melamine. Quantitative extraction of melamine was achieved using hydrophobic magnetic deep eutectic solvents prepared from a mixture of octanoic acid, aliquat-336, and cobalt(II) chloride. The optimum conditions for extraction were found as follows: 6 extraction cycles, pH 8.2, extraction solvent volume 260 µL, and acetone volume 125 µL. Interestingly, a centrifugation step was not required to achieve phase separation. Under the optimum conditions, melamine was determined in the linear range of 3–600 ng mL−1, the limit of detection (3Sblank/m) of 0.9 ng mL−1, and the enrichment factor of 144. The validation of the method was investigated by the analysis of reference materials. Consequently, the method was successfully applied for the analysis of melamine residues in milk and milk-based products.

  • An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
    • Bartosz Szeląg
    • Ewa Zaborowska
    • Jacek Mąkinia
    2023 Journal of Water Process Engineering

    This study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the most appropriate ML model: (i) fitting the results of model prediction to the measurements taking into account the range of variability of the input data, and (ii) model verification applying a reference MCM to identify the input-output relationship using the global sensitivity analysis (GSA). Using the k-means method, it was shown that the relative errors (%e) of N2O prediction by ML models depend on the range of variability of the input data (nitrogen compounds concentration in the bioreactor compartments, influent flowrate, air flowrate). The smallest relative errors of N2O prediction (%e = 0.13 for MARS, %e = 0.12 for SVM and %e=0.10 for XGboost) were found for the concentrations: NH4-N = 24.14 mg N/L (anaerobic compartment), NO3-N = 5.40 mg N/L (aerobic compartment), and the largest (%e > 0.35) for the concentrations: NH4-N = 29.43 mg N/L (anaerobic compartment), NO3-N = 7.90 mg N/L (aerobic compartment). Calculations using the GSA method confirmed that the XGboost model was the only one that showed identical relationships between all the considered input variables and N2O emission rate. The ML model obtained in this way can be used as an alternative to the MCM for estimating N2O emission as a significant contributor to the carbon footprint of WWTPs.

  • An automated, low-latency environment for studying the neural basis of behavior in freely moving rats
    • Maciej Jankowski
    • Ana Polterovich
    • Alex Kazakov
    • Johannes Niediek
    • Israel Nelken
    2023 Full text BMC BIOLOGY

    Background Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes). Results To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding areas, multiple sound sources, high-resolution behavioral tracking, and simultaneous electrophysiological recordings. The paper provides detailed information about the construction of the RIFF and the software used to control it. To illustrate the flexibility of the RIFF, we describe two complex tasks implemented in the RIFF, a foraging task and a sound localization task. Rats quickly learned to obtain rewards in both tasks. Neurons in the auditory cortex as well as neurons in the auditory field in the posterior insula had sound-driven activity during behavior. Remarkably, neurons in both structures also showed sensitivity to non-auditory parameters such as location in the arena and head-to-body angle. Conclusions The RIFF provides insights into the cognitive capabilities and learning mechanisms of rats and opens the way to a better understanding of how brains control behavior. The ability to do so depends crucially on the combination of wireless electrophysiology and detailed behavioral documentation available in the RIFF.

  • An electrochemical biosensor for the determination of hormone Human Chorionic Gonadotropin (hCG) in human serum
    • Adrian Koterwa
    • Magdalena Bojko
    • Jacek Ryl
    • Krzysztof Łukaszuk
    • Kornelia Kozłowska
    • Wiktor Sieklicki
    • Sylwia Rodziewicz-Motowidło
    • Pawel Niedzialkowski
    2023 Full text ELECTROANALYSIS

    This work describes the modification of a gold electrode to create an electrochemical biosensor capable of detecting human chorionic gonadotropin (hCG). The biosensor was obtained by modifying the gold electrode with cysteamine and oligopeptide (PPLRINRHILTR). The modification steps of the gold electrode were confirmed by cyclic voltammetry (CV) and impedance electrochemical spectroscopy (EIS) measurements. The conducted EIS experiments in 0.01 M PBS, pH 7.4 confirm that the biosensor exhibits sensitivity towards hCG in a range of concentrations from 1×10−12 to 1×10−7 M (0.5 mIU/mL – 50 000 mIU/mL) to solutions with a detection limit of 1. 91×10−14 M (0.0095 mIU/mL). The effectiveness of the investigated biosensor was also investigated in human serum. The EIS comparative investigations were performed in human serum containing a concentration of 1×10−12 M (0.5 mIU/mL) hCG and in human serum where the hCG was added. The obtained results indicate that the investigated biosensor is selective for the presence of hCG hormone in the human serum.

  • An experimental assessment on a diesel engine powered by blends of waste-plastic-derived pyrolysis oil with diesel
    • Katarzyna Januszewicz
    • Jacek Hunicz
    • Paweł Kazimierski
    • Arkadiusz Rybak
    • Tomasz Suchocki
    • Kamil Duda
    • Maciej Mikulski
    2023 Full text ENERGY

    The utilization of plastic solid wastes for sustainable energy production is a crucial aspect of the circular economy. This study focuses on pyrolysis as an effective method to convert this feedstock into renewable drop-in fuel. To achieve this, it is essential to have a comprehensive understanding of feedstock composition, pyrolysis process parameters, and the physicochemical characteristics of the resulting fuel, all correlated with engine combustion parameters. Considering this full value chain, this study provides the first unbiased and up-to-date benchmark of polypropylene and polystyrene pyrolysis oils (PPO and PSO) produced in an industrial-grade batch reactor. The pyrolysis process was optimized to achieve ultra-high liquid yield levels of 92% for PPO and 98% for PSO with minimum energy consumption. After post-processing, blending with diesel, and normative fuel analytics, combustion/emission tests involving 20 species preceded under fully controllable conditions using a stateof-the-art single-cylinder research engine. The fuel analysis results revealed significant disparities between the properties of PPO and PSO. PPO exhibited a diverse carbon structure, resulting in very low density and high volatility. On the other hand, PSO was predominantly composed of aromatics, leading to low viscosity and poor auto-ignition properties. Engine tests showed that PPO blends exhibited combustion characteristics similar to diesel, while PSO blends exhibited significant differences, particularly during the premixed combustion stage attributed to pilot injection. Following the combustion response, the addition of PPO had minimal impact on emissions, while PSO acted as an emission enhancer, resulting in over twofold increase in particulate matter at high loads. Consequently, PSO showed elevated carbon monoxide and hydrocarbon emissions due to the higher contribution of aromatics. Ultimately, this study challenges the prevailing perception of plastic-derived fuels as “dirty”. By implementing feedstock segregation to minimize polystyrene content, it is possible to achieve a fossil substitute level of 40% while meeting all emission and safety regulations for diesel engines with a minimum economic burden.

  • An influence of molecular weight, deacetylation degree of chitosan xerogels on their antimicrobial activity and cytotoxicity. Comparison of chitosan materials obtained using lactic acid and CO2 saturation.
    • Szymon Mania
    • Adrianna Banach-kopeć
    • Karol Staszczyk
    • Jolanta Kulesza
    • Ewa Augustin
    • Robert Tylingo
    2023 Full text CARBOHYDRATE RESEARCH

    This paper presents a comparison of the antimicrobial activity and cytotoxicity against L929 cells of chitosan xerogels prepared by dissolving the polymer in a solution of lactic acid (LA) or carbonic acid (CO2) and then freeze-drying. There was no simple relationship between the antimicrobial activity and cytotoxicity of the samples obtained using both techniques (LA and CO2). Chitosan materials obtained by the LA method in a 1:1 dilution were characterized by the highest cytotoxicity against L929 cells (~20%). For the same diluted samples prepared using the CO2 saturation method, the viability of L929 cells was approximately 2.5 times greater. Some of the tested chitosan materials obtained by the innovative method were characterized by significantly lower antimicrobial activity, for example, reduction of E. coli bacteria for MMW-LA and MMW-CO2 samples by 6.00 and 0.75 logarithmic order, respectively. This clearly indicates that in many applications, the presence of the acid necessary to dissolve chitosan is responsible for the antimicrobial activity of the polymer solution and its products.

  • An insight into the mixed quantum mechanical-molecular dynamics simulation of a ZnII-Curcumin complex with a chosen DNA sequence that supports experimental DNA binding investigations
    • Tanmoy Saha
    • Subrahmanyam Sappati
    • Saurabh Das
    2023 Full text INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES

    An important aspect of research pertaining to Curcumin (HCur) is the need to arrest its degradation in aqueous solution and in biological milieu. This may be achieved through complex formation with metal ions. For this reason, a complex of HCur was prepared with ZnII, that is not likely to be active in redox pathways, minimizing further complications. The complex is monomeric, tetrahedral, with one HCur, an acetate and a molecule of water bound to ZnII. It arrests degradation of HCur to a considerable extent that was realized by taking it in phosphate buffer and in biological milieu. The structure was obtained by DFT calculations. Stable adduct formation was identified between optimized structures of HCur and [Zn(Cur)] with DNA (PDB ID: 1BNA) through experiments validated with multiscale modeling approach. Molecular docking studies provide 2D and 3D representations of binding of HCur and [Zn(Cur)] through different non-covalent interactions with the nucleotides of the chosen DNA. Through molecular dynamics simulation, a detailed understanding of binding pattern and key structural characteristics of the generated DNA-complex was obtained following analysis by RMSD, RMSF, radius of gyration, SASA and aspects like formation of hydrogen bonds. Experimental studies provide binding constants for [Zn(Cur)] with calf thymus DNA at 25 °C that effectively helps one to realize its high affinity towards DNA. In the absence of an experimental binding study of HCur with DNA, owing to its tendency to degrade in solution, a theoretical analysis of the binding of HCur to DNA is extremely helpful. Besides, both experimental and simulated binding of [Zn(Cur)] to DNA may be considered as a case of pseudo-binding of HCur to DNA. In a way, such studies on interaction with DNA helps one to identify HCur's affinity for cellular target DNA, not realized through experiments. The entire investigation is an understanding of experimental and theoretical approaches that has been compared continuously, being particularly useful when a molecule's interaction with a biological target cannot realized experimentally.

  • An Integrated Approach to an Assessment of Bottlenecks for Navigation on Riverine Waterways
    • Marta Schoeneich
    • Michał Habel
    • Dawid Szatten
    • Damian Absalon
    • Jakub Montewka
    2023 Full text Water

    Water transport, both sea and inland, is the cheapest, least invasive, and safest option for non-standard loads; hence, it is important to increase the percentage share of inland waterway transport on the rivers of Central and Eastern Europe. Transporting cargo is particularly difficult on shallow waterways because rivers overloaded with sediment determine the vertical parameters on inland waterways. A ship’s safe manoeuvrability depends on the available water depth of the navigational area concerning the vessel’s draught. The draught is related to channel depth and sediments. The paper presents a model assessment of a new tool for studying limitations for ships carrying oversized cargo and the shallow channel bed inland waterways. Our analysis was carried out on the Vistula River lowland reach for the winter hydrological conditions. The Lower Vistula River in Poland is a clear example of a sedimentation problem. This waterway is also a zone of active sediment transport of sandy material; a massive volume of sediment reaches 1 million cubic meters per year. The results of this research could be helpful for inland transport management, risk assessment of ships entering waterways with shallow channel beds such as the Vistula River, and analysis for a new waterway project

  • An integrated geotechnical and geophysical investigation of landslide in Chira town, Ethiopia
    • Worku Firomsa Kabeta
    • Mulatu Tamiru
    • Damtew Tsige
    • Hashim Ware
    2023 Full text Heliyon

    Landslides pose a significant threat to infrastructure, property, and human lives in many regions worldwide, including Chira town in Ethiopia. This study presents an integrated geotechnical and geophysical investigation aimed at identifying the contributing factors to landslides in Chira town, Ethiopia, with a focus on a recent landslide event. The methodology employed a combination of geotechnical and geophysical techniques to comprehensively analyze the landslide problem. The geotechnical investigation involved a detailed analysis of the soil characteristics in the area, including the composition of fine-grained soil and the determination of cohesion and angle of internal friction through triaxial testing. The geophysical investigation utilized electrical resistivity tomography to assess the subsurface soil profile. The findings revealed the presence of a massive basaltic tertiary volcanic rock layer underlying a very low resistivity layer of sticky clay soil. Through this study, it was established that rainfall, soil type, land use, elevation, and proximity to streams, slopes, and aspects were the main factors contributing to the landslide, accounting for 22.03%, 18.89%, 15.75%, 15.46%, 10.87%, 9.7%, and 7.5% of the overall influence, respectively. Based on these findings, the study proposes a range of interventions to enhance resilience against landslides, including surface drainage, the implementation of appropriate land use management practices, and the introduction of vetiver vegetation. The integration of geotechnical and geophysical methodologies provided a comprehensive understanding of the landslide problem in Chira town. The proposed interventions aim to inform future land use planning, infrastructure development, and disaster risk reduction efforts in the region. By expanding our knowledge of the mechanisms driving landslides, this study offers valuable insights that can be utilized in similar regions facing comparable geotechnical and geophysical conditions.

  • An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
    • Tacjana Niksa-Rynkiewicz
    • Piotr Stomma
    • Anna Witkowska
    • Danuta Rutkowska
    • Adam Słowik
    • Krzysztof Cpałka
    • Joanna Jaworek-Korjakowska
    • Piotr Kolendo
    2023 Full text Journal of Artificial Intelligence and Soft Computing Research

    In this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent Unit), and H-MLP (Hierarchical Multilayer Perceptron). The DNN architectures are part of the Deep Learning Prediction (DLP) framework that is applied in the Deep Learning Power Prediction System (DLPPS). The system is trained based on data that comes from a real wind farm. This is significant because the prediction results strongly depend on weather conditions in specific locations. The results obtained from the proposed system, for the real data, are presented and compared. The best result has been achieved for the GRU network. The key advantage of the system is a high effectiveness prediction using a minimal subset of parameters. The prediction of wind power in wind farms is very important as wind power capacity has shown a rapid increase, and has become a promising source of renewable energies.

  • An investigation of microstructural basis for corrosion behavior of Al-CNT composites fabricated by SPS
    • Omid Ekhlasiosgouei
    • Reza Ebrahimi
    • Masood Hasheminiasari
    • Sebastian Molin
    2023 DIAMOND AND RELATED MATERIALS

    In this research effect of the addition of multi-wall carbon nanotubes (MWCNTs) as additive powder on microstructure and corrosion behavior of fabricated Al-CNT composites was studied. The aluminum powder and CNTs were mixed with high energy planetary ball-mill. It is observed that by increasing milling time, the uniformity of CNTs on aluminum matrix and consequently corrosion resistance of Al-CNT composite is increased. On the other hand, by increasing the volume percentage of CNTs, the uniformity of CNTs on aluminum matrix and corrosion resistance of fabricated Al-CNT composite is reduced. The value of polarization resistance, Rp, for fabricated composites with 2 % CNT is improved from 1.28 to 3.60 Ω/cm2 by increasing milling time. Also, the value of Rp for fabricated composites with 4 h milling time, is reduced from 3.60 to 2.76 Ω/cm2 by increasing the percentage of CNTs from 2 % up to 5 %. Moreover, Cyclic Polarization results showed that the pitting corrosion resistance improves by increasing milling time and deteriorates by increasing the percentage of CNTs. The electrochemical impedance spectroscopy (EIS) results showed that the corrosion mechanism of Al-CNT composites is a combination of uniform and pitting corrosion. Indeed, the CNTs act as preferred cathode regions and cause to formation of micro galvanic couples. The Al-2%CNT-4 h showed better uniformity and the highest corrosion resistance. The Al-5%CNT-2 h presented non-uniform distribution of CNTs and the lowest corrosion resistance.