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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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Testing HIADAC high impedance analyzer in Trento University laboratory on "unknown" object using 2-wire probe
Open Research DataThe dataset presents impedance spectrum of "black-box" object with interesting phase characteristics. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (1 Hz – 100 kHz) was selected in order to test the whole measureement...
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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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Morse decompositions for a two-dimensional discrete neuron model (low resolution)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Morse decompositions for a two-dimensional discrete neuron model (limited range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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Morse decompositions for a two-dimensional discrete neuron model (full range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
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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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Morse decompositions for a population model with harvesting. Case Ha-Se: Harvesting adults only, equal survival rates of juveniles and adults
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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Morse decompositions for a population model with harvesting. Case He-S1: Equal harvesting of juveniles and adults, survival rates of juveniles and adults add up to 1
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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Morse decompositions for a population model with harvesting. Case Ha-S1: Harvesting adults only, survival rates of juveniles and adults add up to 1
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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Morse decompositions for a population model with harvesting. Case He-Se: Equal harvesting and equal survival rates of juveniles and adults
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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Morse decompositions for a population model with harvesting. Case Hj-Se: Harvesting juveniles only, equal survival rates of juveniles and adults
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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Morse decompositions for a population model with harvesting. Case Hj-S1: Harvesting juveniles only, survival rates of juveniles and adults add up to 1
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "Global dynamics in a stage-structured discrete population model with harvesting" by E. Liz and P. Pilarczyk: Journal of Theoretical Biology, Vol. 297 (2012), pp. 148–165, doi: 10.1016/j.jtbi.2011.12.012.
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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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Morse decompositions for a non-linear Leslie population model with 2 varying parameters
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "A database schema for the analysis of global dynamics of multiparameter systems" by Z. Arai, W. Kalies, H. Kokubu, K. Mischaikow, H. Oka, P. Pilarczyk, published in SIAM Journal on Applied Dynamical Systems (SIADS),...
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Morse decompositions for a non-linear Leslie population model with 3 varying parameters
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper "A database schema for the analysis of global dynamics of multiparameter systems" by Z. Arai, W. Kalies, H. Kokubu, K. Mischaikow, H. Oka, P. Pilarczyk, published in SIAM Journal on Applied Dynamical Systems (SIADS),...
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Morse decompositions for a two-patch vaccination model
Open Research DataThis dataset contains selected results of rigorous numerical computations described in Section 5 of the paper "Rich bifurcation structure in a two-patch vaccination model" by D.H. Knipl, P. Pilarczyk, G. Röst, published in SIAM Journal on Applied Dynamical Systems (SIADS), Vol. 14, No. 2 (2015), pp. 980–1017, doi: 10.1137/140993934.
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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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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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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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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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Testing HIADAC high impedance analyzer in cooperation with Road and Bridge Research Institute on polyvinyl coating using 2-wire probe sample 1
Open Research DataThe dataset presents impedance spectrum of polyvinyl coating (code-name PW_2_2_1) sample 1. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole measureement...
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Testing HIADAC high impedance analyzer in cooperation with Road and Bridge Research Institute on polyvinyl coating using 2-wire probe sample 2
Open Research DataThe dataset presents impedance spectrum of polyvinyl coating (code-name PW_2_2_1) sample 2. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole measureement...
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Testing HIADAC high impedance analyzer in cooperation with Road and Bridge Research Institute on nano-nickel based coating using 2-wire probe sample 2
Open Research DataThe dataset presents impedance spectrum of nano-nickel based coating sample 2. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole measureement range of...
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Testing HIADAC high impedance analyzer in cooperation with Road and Bridge Research Institute on nano-nickel based coating using 2-wire probe sample 1
Open Research DataThe dataset presents impedance spectrum of nano-nickel based coating sample 1. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole measureement range of...
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Testing HIADAC high impedance analyzer in cooperation with Road and Bridge Research Institute on epoxy based coating using 2-wire probe sample 2
Open Research DataThe dataset presents impedance spectrum of epoxy based coating (code-name B2_B3) sample 2. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole measureement...
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Testing HIADAC high impedance analyzer in cooperation with Road and Bridge Research Institute on epoxy based coating using 2-wire probe sample 1
Open Research DataThe dataset presents impedance spectrum of epoxy based coating (code-name B2_B3) sample 1. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole measureement...
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Testing HIADAC high impedance analyzer in cooperation with Road and Bridge Research Institute on epoxy based coating using 2-wire probe sample 3
Open Research DataThe dataset presents impedance spectrum of epoxy based coating (code-name EPCS1) sample 3. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (0.1 Hz – 100 kHz) was selected in order to test the whole measureement...
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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...