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Search results for: PWR BLACK-BOX MODEL
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CONTROL OF THE WAVES IN A TOWING TANK WITH THE USE OF A BLACK-BOX MODEL
PublicationThe paper describes an adaptive control system of the waves, implemented in the Ship Design and Research Centre, CTO S.A. The purpose of generating the waves in the towing tank is the modelling of the environmental conditions during hydrodynamic model tests. The tests are performed on scale models of towed or free running ships, anchored structures like oil rigs or bottommounted structures, e.g. wind turbines. In the towing tank...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublicationA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Krótkoterminowe prognozowanie
PublicationNowoczesne algorytmy i techniki sterowania, zwłaszcza te oparte na sterowaniu predykcyjnym, pracują na modelu obiektu bądź procesu, który podlega sterowaniu. W przypadku zintegrowanego, inteligentnego sterowania systemem ściekowym korzystamy z modelu oczyszczalni ścieków. Przydatność takiego modelu do celów sterowania predykcyjnego niezależnie od tego, czy mówimy o modelu typu white-box, grey-box czy black-box, jest uwarunkowana...
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Automotive Validation Functions for On-line Test Evaluation of Hybrid Real-time Systems
PublicationThe aim of this paper is to present the means of black-box on-line test evaluation for hybrid real-time systems. The described procedures can be used for the model-based testing process so as to improve its effectiveness. In particular, intelligent automotive validation functions are considered, which are divided into different types depending on the nature of the evaluated issue. All provided definitions are specified on the meta-model...
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The behavioural model of graphene field-effect transistor
PublicationThe behavioural model of a graphene field-effect transistor (GFET) is proposed. In this approach the GFET element is treated as a “black box” with only external terminals available and without considering the physical phenomena directly. The presented circuit model was constructed to reflect steady-states characteristics taking also into account GFET capacitances. The authors’ model is defined by a relatively small number of equations...
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Adversarial attack algorithm for traffic sign recognition
PublicationDeep learning suffers from the threat of adversarial attacks, and its defense methods have become a research hotspot. In all applications of deep learning, intelligent driving is an important and promising one, facing serious threat of adversarial attack in the meanwhile. To address the adversarial attack, this paper takes the traffic sign recognition as a typical object, for it is the core function of intelligent driving. Considering...
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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Robustness Analysis of a Distributed MPC Control System of a Turbo-Generator Set of a Nuclear Plant – Disturbance Issues
PublicationTypically, there are two main control loops with PI controllers operating at each turbo-generator set. In this paper, a distributed model predictive controller with local quadratic model predictive controllers for the turbine generator is proposed instead of a set of classical PI controllers. The local quadratic predictive controllers utilize step-response models for the controlled system components. The parameters of these models...
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The distributed model predictive controller for the nuclear power plant turbo-generator set
PublicationTypically there are two main control loops with PI controllers operating at each turbo-generator set. In this paper a distributed model predictive controller DMPC, with local QDMC controllers for the turbine generator, is proposed instead of a typical PI controllers. The local QDMC controllers utilize step-response models for the controlled system components. These models parameters are determined based on the proposed black-box...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublicationNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublicationModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
PublicationML algorithms are very effective tools for medical data analyzing, especially at image recognition. Although they cannot be considered as a stand-alone diagnostic tool, because it is a black-box, it can certainly be a medical support that minimize negative effect of human-factors. In high-risk domains, not only the correct diagnosis is important, but also the reasoning behind it. Therefore, it is important to focus on trustworthiness...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublicationA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublicationIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Multi-nodal PWR reactor model — Methodology proposition for power distribution coefficients calculation
PublicationIn the paper the multi-nodal Pressurized Water Reactor (PWR) model called Mann’s model is presented. This models is used for modelling purposes of the heat transfer from fuel to coolant in reactor core. The authors expand widely used in literature approach by defining additional coefficients for the heat transfer model. These parameters approximate the power generation distribution in the PWR reactor core according to the to the...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Sieci neuronowe oparte na prawach fizyki
PublicationWiele fizycznie nieuzasadnionych sieci neuronowych, mimo zadowalają- cej wydajności, generuje sprzeczności z logiką i prowadzi do rozbieżno- ści wyników z rzeczywistością. Jedną z metod poprawy funkcjonowania typowego modelu typu “black-box” na etapie uczenia, jest rozszerzenie jego funkcji kosztu o zależność bezpośrednio inspirowaną wzorem fizycz- nym. Niniejszy rozdział wyjaśnia koncepcję budowy sieci neuronowych opartych na...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
PublicationDesign of modern antenna structures is a challenging endeavor. It is laborious, and heavily reliant on engineering insight and experience, especially at the initial stages oriented towards the devel-opment of a suitable antenna architecture. Due to its interactive nature and hands-on procedures (mainly parametric studies) for validating suitability of particular geometric setups, typical antenna development requires many weeks...
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Rapid and simple multi-analyte LC–MS/MS method for the determination of benzodiazepines and Z-hypnotic drugs in blood samples: Development, validation and application based on three years of toxicological analyses
PublicationBenzodiazepines (BZDs) and Z-drugs have been particularly important treatments for sleeping and anxiety disorders for many years. However, recently, a number of new benzodiazepines (named designer benzodiazepines, DBZDs) were synthesised, but some of them have never been used in the clinic; they reached the black drug market as new psychoactive substances and are used for recreational purposes. The abuse of these substances has...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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A grey box model of glucose fermentation and syntrophic oxidation in microbial fuel cells
PublicationIn this work, the fermentative and oxidative processes taking place in a microbial fuel cell (MFC) fed with glucose were studied and modeled. The model accounting for the bioelectrochemical processes was based on ordinary, Monod-type differential equations. The model parameters were estimated using experimental results obtained from three H-type MFCs operated at open or closed circuits and fed with glucose or ethanol. The experimental...
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Analiza sterowania ułamkowego PIλDμ mocą reaktora jądrowego
PublicationW artykule przedstawiono syntezę regulatora PIλDμ niecałkowitego rzędu dla potrzeb sterowania mocą reaktora jądrowego lekko wodnego określanego, jako typu PWR (Pressurized Water Reactor). W tym celu wykorzystano nieliniowy model matematyczny reaktora PWR o parametrach skupionych obejmujący procesy generacji i wymiany ciepła oraz termicznych efektów reaktywnościowych. Nastawy regulatora PIλDμ niecałkowitego rzędu dobrano w sposób...
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Wieloobszarowa rozmyta regulacja PID mocy reaktora jądrowego
PublicationW artykule przedstawiono wieloobszarowy regulator rozmyty z lokalnymi regulatorami PID dla sterowania mocą reaktora jądrowego typu PWR. Wykorzystano model matematyczny o parametrach skupionych reaktora PWR obejmujący procesy generacji i wymiany ciepła oraz efektów reaktywnościowych. Nastawy lokalnych regulatorów PID zostały dobrane w sposób optymalny, minimalizując całkowy wskaźnik jakości ISE. Na przykładzie pokazano że zastosowane...
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Wieloobszarowa rozmyta regulacja PIλDµ mocy reaktora jądrowego
PublicationWartykule przedstawiono wieloobszarowy regulator rozmyty z lokalnymi regulatorami PIλDµ niecałkowitego rzędu. Regulator ten ostał zaprojektowany do sterowania mocą reaktora jądrowego typu PWR (Pressurized Water Reactor). Do syntezy wieloobszarowego regulatora PIλDµ wykorzystano model matematyczny reaktora PWR o parametrach skupionych obejmujący procesy generacji i wymiany ciepła oraz efektów reaktywnościowych. Nastawy lokalnych...
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Wieloobszarowa rozmyta regulacja PIλDμ mocy reaktora jądrowego
PublicationW artykule przedstawiono wieloobszarowy regulator rozmyty z lokalnymi regulatorami PIλDμ niecałkowitego rzedu. Regulator ten został zaprojektowany do sterowania mocą reaktora jądrowego typu PWR (Pressurized Water Reactor). Do syntezy wieloobszarowego regulatora PIDμ wykorzystano model matematyczny reaktora PWR o parametrach skupionych obejmujący procesy generacji i wymiany ciepła oraz efektów reaktywnościowych. Nastawy lokalnych...
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Nodal models of Pressurized Water Reactor core for control purposes – A comparison study
PublicationThe paper focuses on the presentation and comparison of basic nodal and expanded multi-nodal models of the Pressurized Water Reactor (PWR) core, which includes neutron kinetics, heat transfer between fuel and coolant, and internal and external reactivity feedback processes. In the expanded multi-nodal model, the authors introduce a novel approach to the implementation of thermal power distribution phenomena into the multi-node...
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The hybrid estimation algorithm for wastewater treatment plant robust model predictive control purposes at medium time scale
PublicationThe paper proposes an approach to designing the hybrid estimation algorithm/module (HEA) with moving measurements window for Wastewater Treatment Plant (WWTP) Robust Model Predictive Control (RMPC) purposes at medium time scale. The RMPC uses a dedicated grey-box model of biological reactor for the system outputs prediction purposes. The grey-box model parameters are dependant on the plant operating point. Hence, these parameters...
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Fuzzy Multi-Regional Fractional PID controller for Pressurized Water nuclear Reactor
PublicationThe paper presents the methodology for the synthesis of a Fuzzy Multi-Regional Fractional Order PID controller (FMR-FOPID) used to control the average thermal power of a PWR nuclear reactor in the load following mode. The controller utilizes a set of FOPID controllers and the fuzzy logic Takagi-Sugeno reasoning system. The proposed methodology is based on two optimization parts. The first part is devoted to finding the optimal...
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Tailoring optical constants of few-layer black phosphorus coatings: Spectroscopic ellipsometry approach supported by ab-initio simulation
Publication2D black phosphorus (BP) has attracted extensive attention as an anisotropic platform for novel optoelectronic and polarizing optics applications. Insight into the factors that tune the optical and polarizing properties of 2D BP reveals their essential influence on BP-based photonic and optoelectronic devices. In this work, studies of the optical constants of few-layer black phosphorus coatings are studied and discussed, with particular...
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Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant
PublicationIn the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR) working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller...
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Implementation of the FOPID Algorithm in the PLC Controller - PWR Thermal Power Control Case Study
PublicationIn the paper authors describe proposition of design and verification procedures of the discrete Fractional Order PID (FOPID) algorithm for control of the Pressurized Water Reactor (PWR) thermal power near its nominal operating point. The FOPID algorithm synthesis consists of: off-line optimal tunning of its parameters in continuous time-domain with LQ (Linear Quadratic) performance index and simplified models of nuclear reactor...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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NO-BROADCASTING OF NON-SIGNALLING BOXES VIA OPERATIONS WHICH TRANSFORM LOCAL BOXES INTO LOCAL ONES
PublicationWe deal with families of probability distributions satisfying non-signalling condition, called non-signalling boxes and consider a class of operations that transform local boxes into local ones (the one that admit LHV model). We prove that any operation from this class cannot broadcast a bipartite non-local box with 2 binary inputs and outputs. We consider a function called anti-Robustness which can not decrease under these operations....
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Symulator szybkich procesów dynamiki reaktora jądrowego wodno ciśnieniowego
PublicationArtykuł przedstawia symulator dynamiki reaktora jądrowego (RJ) zbudowany w oparciu o punktowe modele matematyczne procesów reaktora typu wodnego ciśnieniowego (ang. Pressurized Water Reactor – PWR) i zaimplementowany w środowisku MATLAB/Simulink. Symulator wykorzystywany jest obecnie jako narzędzie pomocne w dydaktyce i wstępnych badaniach w zakresie energetyki jądrowej na Politechnice Gdańskiej. W pierwszej części artykuł Autorzy...
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Influence of an applied bearing system on behaviour of multi-span footbridge
PublicationThe cycle overpass in Gdynia is a box structure over 300 metres long, 10-span. It was opened for bicycle traffic in the second half of 2013. At the end of its construction, there was failure due to excessive horizontal displacement of the system. A number of bearings exceeded the range of permissible transverse shifts thus it was necessary to temporarily protect the spans from slipping. The FEM analysis of the original solution...
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Automated anonymization of sensitive data on production unit
PublicationThe article presents an approach to data anonymization with the use of generally available tools. The focus is put on the practical aspects of using open-source tools in conjunction with programming libraries provided by suppliers of industrial control systems. This universal approach shows the possibilities of using various operating systems as a platform for process data anonymization. An additional advantage of the described...
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Modele typu szara skrzynka dla potrzeb estymacji zmiennych i sterowania predykcyjnego z zastosowaniem w zintegrowanych systemach ściekowych - doktoratData obrony (14.12.2004)Promotor: prof. dr hab. inż. Mieczysław Brdyś
PublicationEfektywne sterowanie zintegrowanym systemem ściekowym za pomocą zaawansowanych technologii sterowania, mające na celu utrzymanie jego wysokiej technologicznej wydajności przy relatywnie niskich kosztach, wymaga bogatej informacji o jego stanie. Nie jest jednak możliwe ze względów fizycznych i ekonomicznych, uzyskanie wystarczających informacji o stanie systemu wyłącznie na podstawie bezpośrednich pomiarów. Niezbędne jest wykorzystanie...
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Hierarchical predictive control of integrated wastewater treatment systems
PublicationThe paper proposes an approach to designing the control structure and algorithms for optimising control of integrated wastewater treatment plant-sewer systems (IWWTS) under a full range of disturbance inputs. The optimised control of IWWTS allows for significant cost savings, fulfilling the effluent discharge limits over a long period and maintaining the system in sustainable operation. Due to the specific features of a wastewater...
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Influence of selected CO2 absorption promoters on the characteristics of calcium carbonate particles produced by carbonation of the post-distillation liquid from the Solvay process
PublicationThe aim of this work is to compare the effect of selected process parameters, gas flow rate, CO2 absorption promoter concentration and its pKa, on the precipitation of CaCO3 by the gas-liquid method using a model post-distillation liquid from the Solvay process. To ensure effective capture of CO2, the absorption promoters used were ammonia, triethanolamine and triethylamine. The Box-Behnken Design was applied to plan the experiments....
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Determination of Thermophysical Parameters Involved in The Numerical Model to Predict the Temperature Field of Cast-In-Place Concrete Bridge Deck
PublicationThe paper dealswith a concept of a practical computationmethod to simulate the temperature distribution in an extradosed bridge deck. The main goal of the study is to develop a feasible model of hardening of concrete consistent with in-situ measurement capabilities. The presented investigations include laboratory tests of high performance concrete, measurements of temperature evolution in the bridge deck and above all, numerical...
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Dependence of Housing Real Estate Prices on Inflation as One of the Most Important Factors: Poland’s Case
PublicationThe study aimed to examine the impact of inflation on the real estate market using Polish panel data for the last 13 years. It is based on a panel model, where price changes of one square meter of housing are determined as a function in changes of inflation, the central bank's base rate, dwellings built, as well as new mortgage loans. The quarterly dynamics of the average price of 1 square meter of housing in...
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The Dynamics of Trade Relations between Ukraine and Romania: Modelling and Forecasting
PublicationThe article examines the monthly dynamics of exports, imports and balance of trade between Ukraine and Romania in the period from 2005 to 2021. Time series from 2015 to 2021 were used for modelling and forecasting (since the date the European Union–Ukraine Association Agreement took effect). Adequate models of the dynamics series of the Box-Jenkins methodology were built: additive models with seasonal component ARIMA (Autoregressive...
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Shear band evolution phenomena in direct shear test modelled with DEM.
PublicationA direct shear test is widely used in the geotechnical engineering field. It is an easy and quick test to measure the shear properties of soil. This test often replaces more expensive and difficult tri-axial shear test. Despite that the direct shear test is known and used for a long time, it is still not well investigated at the grain scale. This paper deals with the micro behaviour of the cohesionless sand inside the direct shear...
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Studying the Effect of Working Conditions on WEDM Machining Performance of Super Alloy Inconel 617
PublicationWire electrical discharge machining (WEDM) has been for many years a precise and efficient non-conventional manufacturing solution in various industrial applications, mostly involving the use of hard-to machine materials like, among other, the Inconel super alloys. The focus of the present study is on exploring the effect of selected control parameters, including pulse duration, pulse-off time and the dielectric flow pressure on...
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Numerical model for thin liquid film with evaporation and condensation on solid surfaces in systems with conjugated heat transfer
PublicationCondensation and evaporation processes from wetted surfaces are of utmost importance in many technological or industrial applications. In many devices such as home-appliances and air conditioning systems just to name a few, condensation and evaporation processes greatly impact their performance and energy efficiency; The physics of these processes is quite complex, involving conjugate heat transfer among solid–liquid film-gaseous...
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Magnetic superhydrophobic melamine sponges for crude oil removal from water
PublicationThis paper proposes the preparation of a new sorbent material based on melamine sponges (MS) with superhydrophobic, superoleophilic, and magnetic properties. This study involved impregnating the surface of commercially available MS with eco-friendly deep eutectic solvents (DES) and Fe3O4 nanoparticles. The DES selection was based on the screening of 105 eutectic mixtures using COSMO-RS modeling. Other parameters affecting the efficiency...
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In Vitro and In Vivo Imaging-Based Evaluation of Doxorubicin Anticancer Treatment in Combination with the Herbal Medicine Black Cohosh
PublicationAs a substitution for hormone replacement therapy, many breast cancer patients use black cohosh (BC) extracts in combination with doxorubicin (DOX)-based chemotherapy. In this study, we evaluated the viability and survival of BC- and DOX-treated MCF-7 cells. A preclinical model of MCF-7 xenografts was used to determine the influence of BC and DOX administration on tumor growth and metabolism. The number of apoptotic cells after...