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Expedited Re-Design of Multi-Band Passive Microwave Circuits Using Orthogonal Scaling Directions and Gradient-Based Tuning
PublicationGeometry scaling of microwave circuits is an essential but challenging task. In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates utilization of numerical optimization methods. Nonetheless, if the intended frequencies are distant from the ones at the starting point,...
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Method of earth fault loop impedance measurement without nuisance tripping of RCDs in 3-phase low-voltage circuits
PublicationVerification of electrical safety in low-voltage power systems includes the measurement of earth fault loop impedance. This measurement is performed to verify the effectiveness of protection against indirect contact. The widespread classic methods and meters use a relatively high value of the measuring current (5–20) A, so that they are a source of nuisance tripping of residual current devices (RCDs). The meters dedicated to circuits...
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An Efficient Framework For Fast Computer Aided Design of Microwave Circuits Based on the Higher-Order 3D Finite-Element Method
PublicationIn this paper, an efficient computational framework for the full-wave design by optimization of complex microwave passive devices, such as antennas, filters, and multiplexers, is described. The framework consists of a computational engine, a 3D object modeler, and a graphical user interface. The computational engine, which is based on a finite element method with curvilinear higher-order tetrahedral elements, is coupled with built-in...
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Adrian Bekasiewicz dr hab. inż.
PeopleAdrian Bekasiewicz received the MSc, PhD, and DSc degrees in electronic engineering from Gdansk University of Technology, Poland, in 2011, 2016, and 2020, respectively. In 2014, he joined Engineering Optimization & Modeling Center where he held a Research Associate and a Postdoctoral Fellow positions, respectively. Currently, he is an Associate Professor with Gdansk University of Technology, Poland. His research interests include...
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Towards Carbon Neutral Settlements. The Importance of Early-Stage Urban and Energetic Optimizations
PublicationThe aim of the research was to verify the essence of interdisciplinary energy optimizations in earlystage urban design process. A further aim was to the find most optimal design variant and scenario in terms of urban energy efficiency for the future development in Nowy Port, located in Gdansk, Poland - a place requiring complex revitalization. The research combined qualitative and quantitative approaches; an urban design layer...
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Assessment, optimisation and working fluid comparison of organic rankine cycle combined with negative CO2 gas power plant system
PublicationThis study aims to investigate the application of the Organic Rankine Cycle (ORC) as an alternative to low-pressure expansion in the negative CO2 power plant (nCO2PP). The reason for this study is that a detailed analysis of nCO2PP indicates a certain amount of waste heat present in the exhaust gas from the high-to-intermediate pressure gas turbine. Some of this energy can be used by the application of the expansion in a low-pressure...
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Reduced-cost electromagnetic-driven optimisation of antenna structures by means of trust-region gradient-search with sparse Jacobian updates
PublicationNumerical optimisation plays more and more important role in the antenna design. Because of lack of design-ready theoretical models, electromagnetic (EM)-simulation-driven adjustment of geometry parameters is a necessary step of the design process. At the same time, traditional parameter sweeping cannot handle complex topologies and large number of design variables. On the other hand, high computational cost of the conventional...
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Editorial for the special issue on advances in forward and inverse surrogate modeling for high-frequency design
PublicationThe design of modern‐day high‐frequency devices and circuits, including microwave/RF, antenna and photonic components, historically has relied on full‐wave electromagnetic (EM) simulation tools. Initially used for design verification, EM simulations are nowadays used in the design process itself, for example, for finding optimum values of geometry and/or material parameters of the structures of interest. In a growing number of...
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IEEE Journal on Emerging and Selected Topics in Circuits and Systems
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublicationRecent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction...
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Optimization of hydrodynamic vortex separator for removal of sand particles from storm water by computational fluid dynamics
PublicationStorm water treatment has been gradually acknowledged for the removal of pollutants from urban areas using the hydro cyclone separation technique. The separation efficiency of the hydrodynamic vortex separator (HDVS) is a complex phenomenon. With the aim enhance the separation potency of HDVS for storm runoff to get rid of sand particles, the HDVS with different structural configurations was studied by computational fluid dynamics....
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The Maximum Power Point Tracking (MPPT) of a Partially Shaded PV Array for Optimization Using the Antlion Algorithm
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Space Mission Risk, Sustainability and Supply Chain: Review, Multi-Objective Optimization Model and Practical Approach
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Optimization and validation of a multiplex assay for microsatellite loci analysis in the field cricket, Gryllus campestris (Orthoptera: Gryllidae)
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Multivariable optimization of ultrasound-assisted solvent extraction of bee pollen prior to its element analysis by FAAS
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Optimization of Self-Organized TiO2 Nanotube Geometry on Ti and Ti Alloys Using Fuzzy Logic Reasoning
PublicationThe geometry of self-organized TiO2 nanotubes, obtained by electrochemicalanodization, has been determined by using fuzzy reasoning approach. The efficiency of TiO2nanotubular layer in biomedical applications depends on geometry and available surface area ofnanotubes, which can be determined by their diameter and length. The structure of nanotubesdepends on processing parameters of electrochemical anodization, like applied potential,anodization...
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Fast Multi-Objective Optimization of Narrow-Band Antennas Using RSA Models and Design Space Reduction
PublicationComputationally efficient technique for multi-objective design optimization of narrow-band antennas is presented. In our approach, the corrected low-fidelity antenna model (obtained through coarse-discretization EM simulations) is enhanced using frequency scaling and response correction, sampled, and utilized to obtain a fast response surface approximation (RSA) antenna surrogate. The RSA model is constructed in the reduced design space....
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Optimization of Chemical Functionalities of Indole-2-carboxamides To Improve Allosteric Parameters for the Cannabinoid Receptor 1 (CB1)
Publication5-Chloro-3-ethyl-N-(4-(piperidin-1-yl)phenethyl)-1H-indole-2-carboxamide (1; ORG27569) is a prototypical allosteric modulator for the cannabinoid type 1 receptor (CB1). Here, we reveal key structural requirements of indole-2-carboxamides for allosteric modulation of CB1: a critical chain length at the C3-position, an electron withdrawing group at the C5-position, the length of the linker between the amide bond and the phenyl ring...
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Application of multicriteria decision analysis in solvent type optimization for chlorophenols determination with a dispersive liquid–liquid microextraction
PublicationThis study presents a novel support tool for the optimization and development of analytical methods. The tool is based on multi-criteria decision analysis (MCDA), namely the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS), that allows users to rank possible solutions according to their requirements. In this study, we performed rankings of pairs of eight extraction and three dispersive solvents used...
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On Decomposition-Based Surrogate-Assisted Optimization of Leaky Wave Antenna Input Characteristics for Beam Scanning Applications
PublicationRecent years have witnessed a growing interest in reconfigurable antenna systems. Travelling wave antennas (TWAs) and leaky wave antennas (LWAs) are representative examples of structures featuring a great level of flexibility (e.g., straightforward implementation of beam scanning), relatively simple geometrical structure, low profile, and low fabrication cost. Notwithstanding, the design process of TWAs/LWAs is a challenging endeavor...
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Performance evaluation and model-based optimization of the mainstream deammonification in an integrated fixed-film activated sludge reactor
PublicationThis study aimed to model and optimize mainstream deammonification in an integrated fixed-film activated sludge (IFAS) pilot plant under natural seasonal temperature variations. The effect of gradually decreasing temperature on the performance was evaluated during a winter season and a transition period to summer conditions, and the correlation of the performance parameters was investigated using principal component analysis (PCA)....
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Analyzing Wind Energy Potential Using Efficient Global Optimization: A Case Study for the City Gdańsk in Poland
PublicationWind energy (WE), which is one of the renewable energy (RE) sources for generating electricity, has been making a significant contribution to obtaining clean and green energy in recent years. Fitting an appropriate statistical distribution to the wind speed (WS) data is crucial in analyzing and estimating WE potential. Once the best suitable statistical distribution for WS data is determined, WE potential and potential yield could...
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Maximizing SDN resilience to node‐targeted attacks through joint optimization of the primary and backup controllers placements
PublicationIn Software Defined Networks (SDN) packet data switches are configured by a limited number of SDN controllers, which respond to queries for packet forwarding decisions from the switches. To enable optimal control of switches in real time the placement of controllers at network nodes must guarantee that the controller-to-controller and switch-to-controller communications delays are bounded. Apart from the primary controllers that...
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Computational Bar Size Optimization of Single Layer Dome Structures Considering Axial Stress and Shape Disturbance
PublicationA computational method is proposed in this paper to minimize the material usage in the construction of modern spatial frame structures by prestressing a minimal number of members. The computational optimization is conducted in two steps. Firstly, a numerical model of a single-layer dome structure is used to minimize the cross-sectional area through several iterations. Different assumed ratios (r) ranging from 0.95 to 0.75 are multiplied...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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PLC-based Implementation of Stochastic Optimization Method in the Form of Evolutionary Strategies for PID, LQR, and MPC Control
PublicationProgrammable logic controllers (PLCs) are usually equipped with only basic direct control algorithms like proportional-integral-derivative (PID). Modules included in engineering software running on a personal computer (PC) are usually used to tune controllers. In this article, an alternative approach is considered, i.e. the development of a stochastic optimizer based on the (μ,λ) evolution strategy (ES) in a PLC. For this purpose,...
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublicationAbstract: Recent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction...
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Low-Cost Quasi-Global Optimization of Expensive Electromagnetic Simulation Models by Inverse Surrogates and Response Features
PublicationConceptual design of contemporary high-frequency structures is typically followed by a careful tuning of their parameters, predominantly the geometry ones. The process aims at improving the relevant performance figures, and may be quite expensive. The reason is that conventional design methods, e.g., based on analytical or equivalent network models, often only yield rough initial designs. This is especially the case for miniaturized...
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Modeling and optimization of chemical-treated torrefaction of wheat straw to improve energy density by response surface methodology
PublicationToday, torrefaction is important technique for extending the potential of biomass for improvement of energy density. The independent variables investigated for torrefaction study were temperature, retention time, acid concentration, and particle size. The experiment was designed by central composite design (CCD) method using design expert (version 11). The three dependent variables were higher heating value (HHV), energy enhancement...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublicationAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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Tuning Electrochemical Performance by Microstructural Optimization of the Nanocrystalline Functional Oxygen Electrode Layer for Solid Oxide Cells
PublicationFurther development of solid oxide fuel cell (SOFC) oxygen electrodes can be achieved through improvements in oxygen electrode design by microstructure miniaturisation alongside nanomaterials implementation. In this work, improved electrochemical performance of an La0.6Sr0.4Co0.2Fe0.8O3-d (LSCF) cathode was achieved by the controlled modification of the La0.6Sr0.4CoO3-d (LSC) nanocrystalline interlayer introduced between a porous...
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Multipath routing for quality of service differentiation and network capacity optimization in broadband low-earth orbit systems
PublicationThis paper shows the importance of employing multiple different paths for routing in Inter-Satellite Link (ISL) networks in broadband Low-Earth Orbit (LEO) satellite systems. A theoretical analysis is presented and a routing concept is proposed to demonstrate three facts that make multipath routing especially important in broadband LEO networks: (1) differences in the propagation delays have a much greater impact on end-to-end...
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Implementation of multicriteria decision analysis in design of experiment for dispersive liquid-liquid microextraction optimization for chlorophenols determination
PublicationA novel and efficient approach to optimization of extraction step prior the chromatographic determination of nine chlorinated phenols is described. It is based on the combination of design of experiments and multicriteria decision analysis. Such an approach is used to optimize dispersive liquid-liquid microextraction procedure for the determination of 9 chlorophenols in water samples. Three parameters are optimized – sample volume,...
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Inverse modeling for fast design optimization of small-size rat-race couplers incorporating compact cells
PublicationIn the paper, a framework for computationally-efficient design optimization of compact rat-race couplers (RRCs) is discussed. A class of hybrid RRCs with variable operating conditions is investigated, whose size reduction is obtained by replacing ordinary transmission lines with compact microstrip resonant cells (CMRCs). Our approach employs a bottom-up design strategy leading to the development of compact RRCs through rapid design...
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Importance of the combined effects of dissolved oxygen and pH on optimization of nitrogen removal in anammox-enriched granular sludge
PublicationThe combined effects of dissolved oxygen (DO) and pH on nitrogen removal were investigated in a laboratory-scale sequencing batch reactor (SBR) with anammox-enriched granular sludge obtained from a nitritation/anammox system. The highest specific nitrogen removal rate (SNRR) (1.1 gN gVSS−1 d−1) was observed under non-aerated conditions, resulting in the nitrogen removal efficiency of 81.6%. Although nitrogen removal was readily...
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublicationAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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Optimization of the Aeration Strategies in a Deammonification Sequencing Batch Reactor for Efficient Nitrogen Removal and Mitigation of N2O Production
PublicationIn deammonification systems, nitrite-oxidizing bacteria (NOB) suppression and nitrous oxide (N2O) mitigation are two important operational objectives. To carry out this multivariable analysis of response, a comprehensive model for the N cycle was developed and evaluated against experimental data from a laboratory-scale deammonification granular sludge sequencing batch reactor. Different aeration strategies were tested, and the manipulated...
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Multicriteria Optimization Approach to Design and Operation of District Heating Supply System over its Life Cycle
PublicationDistrict Heating (DH) systems are commonly supplied using local heat sources. Nowadays, modern insulation materials allow for effective and economically viable heat transportation over long distances (over 20 km). In the paper a method for optimized selection of design and operating parameters of long distance Heat Transportation System (HTS) is proposed. The method allows for evaluation of feasibility and effectivity of heat transportation...
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EM-Driven Multi-Objective Optimization of a Generic Monopole Antenna by Means of a Nested Trust-Region Algorithm
PublicationAntenna structures for modern applications are characterized by complex and unintuitive topologies that are difficult to develop when conventional experience-driven techniques are of use. In this work, a method for automatic generation of antenna geometries in a multi-objective setup has been proposed. The approach involves optimization of a generic spline-based radiator with adjustable number of parameters using a nested trust-region-based...
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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublicationSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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Optimization of the Hardware Layer for IoT Systems using a Trust Region Method with Adaptive Forward Finite Differences
PublicationTrust-region (TR) algorithms represent a popular class of local optimization methods. Owing to straightforward setup and low computational cost, TR routines based on linear models determined using forward finite differences (FD) are often utilized for performance tuning of microwave and antenna components incorporated within the Internet of Things systems. Despite usefulness for design of complex structures, performance of TR methods...
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublicationThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...
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Low-cost multi-criterial design optimization of compact microwave passives using constrained surrogates and dimensionality reduction
PublicationDesign of contemporary microwave circuits is a challenging task. Typically, it has to take into account several performance requirements and constraints. The design objectives are often conflicting and their simultaneous improvement may not be possible; instead, compromise solutions are to be sought. Representative examples are miniaturized microwave passives where reduction of the circuit size has a detrimental effect on its electrical...
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Application of MARKAL model to optimisation of electricity generation structure in Poland in the long-term time horizon Part I - concept of the model
PublicationIn this paper, which inaugurates a series of papers on this subject, a concept is proposed of a power system development model with regard to the technological structure of electricity generation in Poland, in the long-term time perspective – until 2060. The model is based on the mathematical structure of the MARKAL optimization package. The paper presents a brief description of the tool used in the model research. In addition,...
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Bandwidth-size design trade-offs for compact spline-parameterised patch couplers by means of electromagnetic-driven multi-objective optimisation
PublicationBroad bandwidth and small size are the key performance figures for contemporary microwave couplers. These requirements are conflicting, i.e. improvement of one generally leads to degradation of the other assuming fixed topology of the circuit at hand. From a designer's perspective, the knowledge about available design trade-offs is indispensable as it permits for tailoring the circuit for particular applications as well as comparing...