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Innovative approach for the determination of a DC motor’s and drive’s parameters using evolutionary methods and different measured current and angular speed responses
Marko Jesenik, Miha Ravber, Mislav Trbušić, 2024, izvirni znanstveni članek

Opis: The determination is presented of seven parameters of a DC motor’s drive. The determination was based on a comparison between the measured and simulated current and speed responses. For the parameters’ determination, different evolutionary methods were used and compared to each other. The mathematical model presenting the DC drives model was written using two coupled differential equations, which were solved using the Runge–Kutta first-, second-, third- and fourth-order methods. The approach allows determining the parameters of controlled drives in such a way that the controller is taken into account with the measured voltage. Between the tested evolutionary methods, which were Differential Evolution with three strategies, Teaching-Learning Based Optimization and Artificial Bee Colony, the Differential Evolution (DE/rand/1/exp) can be suggested as the most appropriate for the presented problem. Measurements with different sampling times were used, and it was found out that at least some measuring points should be at the speed-up interval. Different lengths of the measured signal were tested, and it is sufficient to use a signal consisting of the drive’s acceleration and a short part of the stationary operation. The analysis showed that the procedure has good repeatability. The biggest deviation of calculated parameters considering 10 repeated measurements was 6% in case of the La calculation. The deviations of all the other parameters’ calculations were less than 2%.
Ključne besede: differential evolution, artificial bee colony, teaching-learning based optimization, DC motors, electric drive
Objavljeno v DKUM: 26.01.2024; Ogledov: 76; Prenosov: 7
.pdf Celotno besedilo (5,41 MB)

Optimal positioning of mobile cranes on construction sites using nonlinear programming with discontinuous derivatives
Matjaž Hozjan, Uroš Klanšek, 2023, izvirni znanstveni članek

Opis: Mobile cranes represent conventional construction machinery that is indispensable for the erection of most prefabricated buildings, especially those containing heavy components. However, it is also common knowledge that the engagement of these machines has a significant influence on the environment, various social aspects of the construction process, and its economic benefits. Optimal positioning of the mobile crane on the construction site, primarily driven by the contractor’s interest to perform assembly operations with expensive machinery as effectively as possible, considerably reduces not only the costs of engaging such a machine but indirectly also its negative impacts on construction sustainability. This paper discusses an exact nonlinear model for the optimization task. The optimization model consists of a cost objective function that is subject to various duration and positioning constraints for the mobile crane, including bounds on its degrees of freedom of movement and stop positions. Because the model formulation includes discontinuous and non-smooth expressions, nonlinear programming with discontinuous derivatives (DNLP) was employed to ensure the optimal solution was reached. The model provides the mobile crane operator with exact key information that enables the complete and optimal assembly of the building structure under consideration. Additionally, the information gained on the optimal distribution of the mobile crane rental period to assembly operations allows for a detailed duration analysis of the entire process of building structure erection, which can be used for its further improvement. An application example is given in this study to demonstrate the advantages of the proposed approach.
Ključne besede: construction sustainability, mobile crane, nonlinear programming with discontinuous derivatives, optimization, positioning
Objavljeno v DKUM: 18.12.2023; Ogledov: 184; Prenosov: 7
.pdf Datoteka (877,26 KB)
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Managing the complexity of empty container movements through repositioning strategies and routing practices under certain demand and supply : doctoral dissertation
Alaa Abdelshafie, 2023, doktorska disertacija

Opis: Over the past decades, container transportation management has become an important part of the global maritime industry. Due to an ever-increasing movement of containers across the globe in line with the economic boom, the trade imbalance and issues related to empty containers have become inevitable. The accumulation of empty containers in specific ports not only causes a waste of money but also increases the environmental footprint. Accordingly, the urgent need for empty container management has been gaining more attention than ever before, as the shipping companies recognized that more revenues are always derived from a good repositioning strategy. In this respect, this thesis described state-of-the-art of empty container management, focusing on the practices concerning the movement of empty containers that are varied between organizational policies, technical solutions, and optimization applications. With the development of computer-aided systems, the combination of optimization and simulation models has been proposed to tackle the maritime empty container problem. The thesis shows how the strengths of optimization-based simulation can be integrated to provide high-quality solutions with low computational costs. Agent-based modelling was developed to model the global movements of empty containers, providing realistic details of interactions among entities and characteristics of components within the system. The model was applied between ports in the Middle East and Asia for one of the biggest shipping lines worldwide. By using simulated annealing (SA), the best sequence for moving containers can be determined. The results comparison demonstrate that the proposed optimised repositioning strategy can significantly reduce the shipping line’s costs and make full use of empty containers in the planning horizon.
Ključne besede: shipping industry, container transportation management, empty container repositioning, simulation, optimization, agent-based modelling
Objavljeno v DKUM: 08.12.2023; Ogledov: 272; Prenosov: 13
.pdf Celotno besedilo (3,38 MB)

Frequency range optimization for continuous wave Terahertz imaging
Blaž Pongrac, Andrej Sarjaš, Dušan Gleich, izvirni znanstveni članek

Opis: S krajšimi valovnimi dolžinami kot mikrovalovi in večjo globino prodora v material kot infrardeča svetloba, valovi v TeraHertz-nem (THz) spektru ponujajo edinstvene možnosti testiranja materialov. THz tehnologija ponuja neinvazivna in nedestruktivna testiranja v obliki spektroskopije in slikanja. Najbolj uporabljeni sistemi za THz slikanje so sistemi spektroskopije v časovni domeni. Vendar sistemi spektroskopije frekvenčne domene ponujajo odlično frekvenčno ločljivost in so primerni za biomedicinske aplikacije. THz-no slikanje na podlagi spektroskopije v frekvenčnem prostoru je časovno kompleksno in ima pomanjkljivosti zaradi napak pri generiranju THz valov. V tem članku je predstavljen nov princip enodimenzionalnega zajemanja s THz valovi. Predlagana optimizacija frekvenčnega območja temelji na konvolucijski nevronski omreži. Predstavljena je frekvenčna optimizacija za določitev optimalnega frekvenčnega območja za zajem podatkov. Optimalno frekvenčno območje ali pasovna širina morata biti dovolj široka za učinkovito zaznavanje faze in morata biti na presečišču več spektralnih odtisov v opazovanem mediju. Presek spektralnih odtisov je ocenjen z uporabo predlaganega algoritma za optimizacijo frekvenčnega območja, ki temelji na konvolucijski nevronski mreži in algoritmu za občutljivost okluzije. Predlagani algoritem izbira samodejno najobčutljivejši frekvenčni pas THz spektra in omogoča zelo hitre zajeme za pregled in klasifikacijo objektov.
Ključne besede: terahertz, spectroscopy, imaging, convolutional neural network, occlusion sensitivity, optimization
Objavljeno v DKUM: 07.12.2023; Ogledov: 210; Prenosov: 9
.pdf Celotno besedilo (8,82 MB)
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Response surface method-based optimization of outer rotor permanent magnet synchronous motor
Vahid Rafiee, Jawad Faiz, 2019, izvirni znanstveni članek

Opis: The Finite Element Method (FEM) is a prominent analysis approach. Although it is applicable for simulation and optimization of electrical machines, FEM is a very time-consuming technique. One of the approaches to shorten the optimization runtime is the use of surrogate models instead of FEM. In this paper, the design and optimization of an outer rotor permanent magnet synchronous motor for a hybrid vehicle are investigated. Response surface methodology (RSM) with four input variables is integrated with a sequential quadratic programming algorithm for optimization. Before the optimization, the performance of the surrogate model in the prediction of untried points is validated. Finally, the optimal motor is simulated by FEM to verify the results of RSM-based optimization, and the outputs of both models are compared.
Ključne besede: response surface surrogate method, outer rotor permanent magnet synchronous motor, sequential quadratic programming optimization
Objavljeno v DKUM: 05.12.2023; Ogledov: 274; Prenosov: 3
.pdf Celotno besedilo (683,42 KB)
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The Influence of Increased Moderator Temperature on the Nuclear Characteristics of the NPP Krško
Marjan Kromar, Bojan Kurinčič, 2019, objavljeni znanstveni prispevek na konferenci

Opis: NPP Krško safety analysis has been performed in such a way to allow operation with primary system average coolant temperature - Tavg inside a prescribed range, which constitute the socalled operating window. The Tavg window enables certain flexibility to select an optimum value within the Tavg range taking into account safety, operational and economical considerations. Increase of the reactor coolant temperature in general improves thermodynamic efficiency of the Pressurized Water Reactor (PWR) plant yielding to increase in the electricity production. However, higher temperature causes lower water density in the reactor core altering the neutron moderation and consequently neutron transport in the reactor. This impact on the nuclear core characteristics is investigated for the NPP Krško reactor core.
Ključne besede: pressurized water reactor, nuclear design calculations, reactor coolant temperature optimization, critical boron concentration, Nuclear Powe Plant Krško
Objavljeno v DKUM: 05.12.2023; Ogledov: 168; Prenosov: 7
.pdf Celotno besedilo (18,06 MB)
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Accuracy is not enough: optimizing for a fault detection delay
Matej Šprogar, Domen Verber, 2023, izvirni znanstveni članek

Opis: This paper assesses the fault-detection capabilities of modern deep-learning models. It highlights that a naive deep-learning approach optimized for accuracy is unsuitable for learning fault-detection models from time-series data. Consequently, out-of-the-box deep-learning strategies may yield impressive accuracy results but are ill-equipped for real-world applications. The paper introduces a methodology for estimating fault-detection delays when no oracle information on fault occurrence time is available. Moreover, the paper presents a straightforward approach to implicitly achieve the objective of minimizing fault-detection delays. This approach involves using pseudo-multi-objective deep optimization with data windowing, which enables the utilization of standard deep-learning methods for fault detection and expanding their applicability. However, it does introduce an additional hyperparameter that needs careful tuning. The paper employs the Tennessee Eastman Process dataset as a case study to demonstrate its findings. The results effectively highlight the limitations of standard loss functions and emphasize the importance of incorporating fault-detection delays in evaluating and reporting performance. In our study, the pseudo-multi-objective optimization could reach a fault-detection accuracy of 95% in just a fifth of the time it takes the best naive approach to do so.
Ključne besede: artificial neural networks, deep learning, fault detection, accuracy, multi-objective optimization
Objavljeno v DKUM: 30.11.2023; Ogledov: 209; Prenosov: 10
.pdf Celotno besedilo (478,93 KB)
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Proportional-integral controllers performance of a grid-connected solar PV system with particle swarm optimization and Ziegler-Nichols tuning method
Klemen Deželak, Peter Braciník, Klemen Sredenšek, Sebastijan Seme, 2021, izvirni znanstveni članek

Opis: This paper deals with photovoltaic (PV) power plant modeling and its integration into the medium-voltage distribution network. Apart from solar cells, a simulation model includes a boost converter, voltage-oriented controller and LCL filter. The main emphasis is given to the comparison of two optimization methods-particle swarm optimization (PSO) and the Ziegler-Nichols (ZN) tuning method, approaches that are used for the parameters of Proportional-Integral (PI) controllers determination. A PI controller is commonly used because of its performance, but it is limited in its effectiveness if there is a change in the parameters of the system. In our case, the aforementioned change is caused by switching the feeders of the distribution network from an open-loop to a closedloop arrangement. The simulation results have claimed the superiority of the PSO algorithm, while the classical ZN tuning method is acceptable in a limited area of operation.
Ključne besede: photovoltaic power plant, optimization, PI controllers, distribution system
Objavljeno v DKUM: 10.11.2023; Ogledov: 186; Prenosov: 8
.pdf Celotno besedilo (3,36 MB)
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