Search results for: reactive power optimization

Authors: Ali Rahnamoun, Adri van Duin

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The concept of high velocity particle impact on the spacecraft surface materials has been one of the important issues in the design of such materials. Among these particles, water clusters might be the most abundant and the most important particles to be studied. The importance of water clusters is that upon impact on the surface of the materials, they can cause damage to the material and also if they are sub-cooled water clusters, they can attach to the surface of the materials and cause ice accumulation on the surface which is very problematic in spacecraft and also aircraft operations. The dynamics of the collisions between amorphous silica structures and water clusters with impact velocities of 1 km/s to 10 km/s are studied using the ReaxFF reactive molecular dynamics simulation method. The initial water clusters include 150 water molecules and the water clusters are collided on the surface of amorphous fully oxidized and suboxide silica structures. These simulations show that the most abundant molecules observed on the silica surfaces, other than reflecting water molecules, are H3O+ and OH- for the water cluster impacts on suboxide and fully oxidized silica structures, respectively. The effect of impact velocity on the change of silica mass is studied. At high impact velocities the water molecules attach to the silica surface through a chemisorption process meaning that water molecule dissociates through the interaction with silica surface. However, at low impact velocities, physisorbed water molecules are also observed, which means water molecule attaches and accumulates on the silica surface. The amount of physisorbed waters molecules at low velocities is higher on the suboxide silica surfaces. The evolution of the temperatures of the water clusters during the collisions indicates that the possibility of electron excitement at impact velocities less than 10 km/s is minimal and ReaxFF reactive molecular dynamics simulation can predict the chemistry of these hypervelocity impacts. However, at impact velocities close to 10 km/s the average temperature of the impacting water clusters increase to about 2000K, with individual molecules oocasionally reaching temperatures of over 8000K and thus will be prudent to consider the concept of electron excitation at these higher impact velocities which goes beyond the current ReaxFF ability.

Keywords: spacecraft materials, hypervelocity impact, reactive molecular dynamics simulation, amorphous silica

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Authors: Krishnan Manickavasagam, Manikandan Shanmugam

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Clean and abundant renewable energy sources (RES) such as solar energy is seen as the best solution to replace conventional energy source. Unpredictable power generation is a major issue in the penetration of solar energy, as power generated is governed by the irradiance received. Controlling the power generated from solar PV (SPV) panels to battery and load is a challenging task. In this paper, power flow control from SPV to load and energy storage device (ESD) is controlled by a fuzzy decision support system (FDSS) on the availability of solar irradiation. The results show that FDSS implemented with the energy management system (EMS) is capable of managing power within the area, and if excess power is available, then shared with the neighboring area.

Keywords: renewable energy sources, fuzzy decision support system, solar photovoltaic, energy storage device, energy management system

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: L. Alejandro Cárdenas, Fernando Herrera, David Nova, Juan Ballesteros

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This paper presents a methodology to optimize the maintenance of grid-connected photovoltaic systems, considering the cleaning and module replacement periods based on an asset management strategy. The methodology is based on the analysis of the energy production of the PV plant, the energy feed-in tariff, and the cost of cleaning and replacement of the PV modules, with the overall revenue received being the optimization variable. The methodology is evaluated as a case study of a 5.6 kWp solar PV plant located on the Bogotá campus of the Universidad Nacional de Colombia. The asset management strategy implemented consists of assessing the PV modules through visual inspection, energy performance analysis, pollution, and degradation. Within the visual inspection of the plant, the general condition of the modules and the structure is assessed, identifying dust deposition, visible fractures, and water accumulation on the bottom. The energy performance analysis is performed with the energy production reported by the monitoring systems and compared with the values estimated in the simulation. The pollution analysis is performed using the soiling rate due to dust accumulation, which can be modelled by a black box with an exponential function dependent on historical pollution values. The pollution rate is calculated with data collected from the energy generated during two years in a photovoltaic plant on the campus of the National University of Colombia. Additionally, the alternative of assessing the temperature degradation of the PV modules is evaluated by estimating the cell temperature with parameters such as ambient temperature and wind speed. The medium-term energy decrease of the PV modules is assessed with the asset management strategy by calculating the health index to determine the replacement period of the modules due to degradation. This study proposes a tool for decision making related to the maintenance of photovoltaic systems. The above, projecting the increase in the installation of solar photovoltaic systems in power systems associated with the commitments made in the Paris Agreement for the reduction of CO2 emissions. In the Colombian context, it is estimated that by 2030, 12% of the installed power capacity will be solar PV.

Keywords: asset management, PV module, optimization, maintenance

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Authors: Ilya Kavalchuk, Mehdi Seyedmahmoudian, Ben Horan, Aman Than Oo, Alex Stojcevski

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The power electronic components within Electric Vehicles (EV) need to operate in several important modes. Some modes directly influence safety, while others influence vehicle performance. Given the variety of functions and operational modes required of the power electronics, it needs to meet efficiency requirements to minimize power losses. Another challenge in the control and construction of such systems is the ability to support bidirectional power flow. This paper considers the construction, operation, and feasibility of available converters for electric vehicles with feasible configurations of electrical buses and loads. This paper describes logic and control signals for the converters for different operations conditions based on the efficiency and energy usage bases.

Keywords: electric vehicles, electrical machines control, power electronics, powerflow regulations

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

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Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: load forecasting, artificial neural network, particle swarm optimization

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Authors: Ata Khorami, Mohammad Sharifkhani

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In the dynamic comparators, the pre-amplifier amplifies the input differential voltage and when the output Vcm of the pre-amplifier becomes larger than Vth of the latch input transistors, the latch is activated and finalizes the comparison. As a result, the pre-amplification delay is fixed to a value and cannot be set at the minimum required delay, thus, significant power and delay are imposed. In this paper, a novel structure is proposed through which the pre-amplification delay can be set at any low value saving power and time. Simulations show that using the proposed structure, by setting the pre-amplification delay at the minimum required value the power and comparison delay can be reduced by 55% and 100ps respectively.

Keywords: dynamic comparator, low power comparator, analog to digital converter, pre-amplification delay

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Authors: Kashmir Johal

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Within a wider context of improving whole-life effectiveness of gas and oil fields, we have been researching how to generate power local to the wellhead. (Provision of external power to a subsea wellhead can be prohibitively expensive and results in uneconomic fields. This has been an oil/gas industry challenge for many years.) We have been developing a possible approach to “local” power generation and have been conducting technical, environmental, (and economic) research to develop a viable approach. We sought to create a workable design for a new type of power generation system that makes use of differential pressure that can exist between the sea surface and a gas (or oil reservoir). The challenge has not just been to design a system capable of generating power from potential energy but also to design it in such a way that it anticipates and deals with the wide range of technological, environmental, and chemical constraints faced in such environments. We believe this project shows the enormous opportunity in deriving clean, economic, and zero emissions renewable energy from offshore sources. Since this technology is not currently available, a patent has been filed to protect the advancement of this technology.

Keywords: renewable, energy, power, offshore

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Authors: Sourabh Joshi, Geetinder Kaur, Sarabjit Kaur, Gulwatanpreet Singh, Geetika Mannan

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In this paper, we have use an algorithm that able to obtain an optimal solution to travelling salesman problem from a huge search space, quickly. This algorithm is based upon the ant colony optimization technique and employees roulette wheel selection mechanism. To illustrate it more clearly, a program has been implemented which is based upon this algorithm, that presents the changing process of route iteration in a more intuitive way. In the event, we had find the optimal path between hundred cities and also calculate the distance between two cities.

Keywords: ant colony, optimization, travelling salesman problem, roulette wheel selection

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Authors: Mohamed Abdelwahed

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We propose an optimization algorithm for the geometric control of fluid flow. The used approach is based on the topological sensitivity analysis method. It consists in studying the variation of a cost function with respect to the insertion of a small obstacle in the domain. Some theoretical and numerical results are presented in 2D and 3D.

Keywords: sensitivity analysis, topological gradient, shape optimization, stokes equations

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Authors: Muhammad Gillfran Samual, Rinaldy Dalimi, Fauzan Hanif Jufri, Budi Sudiarto, Ismi Rosyiana Fitri

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Solar energy is increasingly recognized as an important future energy source due to its abundant availability and renewable nature. However, the intermittent nature of solar energy can cause fluctuations in the electricity produced, making it difficult to guarantee a stable and reliable electricity supply. One solution that can be implemented is to use batteries in a photovoltaic solar power plant system with a Moving Average control algorithm, which can help smooth and reduce fluctuations in solar power output power. The parameter that can be adjusted in the Moving Average algorithm is the window size or the arithmetic average width of the photovoltaic output power over time. This research evaluates the effect of a change of window size parameter in the Moving Average algorithm on the resulting smoothed photovoltaic output power and the technical effects on batteries, i.e., power and energy usage. Based on the evaluation, it is found that the increase of window size parameter will slow down the response of photovoltaic output power to changes in irradiation and increase the smoothing quality of the intermittent photovoltaic output power. In addition, increasing the window size will reduce the maximum power received on the load side, and the amount of energy used by the battery during the power smoothing process will increase, which, in turn, increases the required battery capacity.

Keywords: battery, intermittent, moving average, photovoltaic, power smoothing

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Authors: Yue Hu, Xilu Zhao, Takao Yamaguchi, Manabu Sasajima, Yoshio Koike, Akira Hara

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This study tried optimization of design parameter of a cone loudspeaker unit as an example of the high flexibility of the products design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to each design the parameter of the loudspeaker. To overcome the limitation of the design problem in practice, this paper proposes a new an acoustic analysis algorithm to optimize design the parameter of the loudspeaker. The material character of cone paper and the loudspeaker edge was the design parameter, and the vibration displacement of the cone paper was the objective function. The results of the analysis were compared with the predicted value. They had high accuracy to the predicted value. These results suggest that, though the parameter design is difficult by experience and intuition, it can be performed comparatively easily using the optimization design by the developed acoustic analysis software.

Keywords: air viscosity, loudspeaker, cone paper, edge, optimization

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Authors: Hakim Aguedal, Abdelkader Iddou, Abdalla Aziz, Abdelhadi Bentouami, Ferhat Bensalah, Salah Bensadek

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The major environmental risk of soil pollution is the contamination of groundwater by infiltration of organic and inorganic pollutants that can cause a serious pollution. To prevent the migration of this pollution through this structure, many studies propose the installation of layers, which play a role of a barrier that inhibiting the contamination of groundwater by limiting or slowing the flow of rainwater carrying pollution through the layers of soil. However, it is practically impossible to build a barrier layer that let through only water, but it is possible to design a structure with low permeability, which reduces the infiltration of dangerous pollutant. In an environmental context of groundwater protection, the main objective of this study was to investigate the environmental and appropriate suitability method to preserve groundwater, by establishment of a permeable reactive barrier (PRB) intermediate in soil. Followed the influence of several parameters allow us to find the most effective materials and the most appropriate way to incorporate this barrier in the soil.

Keywords: Ground water, protection, permeable reactive Barrier, soil pollution.

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Authors: Lim Teck Beng, Thiha Kyaw, Poh Boon Kiat, Lee Ngai Meng

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This work presents discussion on the possibility of merging two emerging technologies in microwave; wireless power transfer (WPT) and RF energy harvesting. The current state of art of the two technologies is discussed and the strength and weakness of the two technologies is also presented. The equivalent circuit of wireless power transfer is modeled and explained as how the range and efficiency can be further increased by controlling certain parameters in the receiver. The different techniques of harvesting the RF energy from the ambient are also extensive study. Last but not least, we demonstrate that a low power wireless sensor network (WSN) can be power up by RF energy harvesting. The WSN is designed to transmit every 3 minutes of information containing the temperature of the environment and also the voltage of the node. One thing worth mention is both the sensors that are used for measurement are also powering up by the RF energy harvesting system.

Keywords: energy harvesting, wireless power transfer, wireless sensor network and magnetic coupled resonator

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Authors: Ersilio Tushaj

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The efficient solution that satisfies the optimal condition is an important issue in the structural engineering design problem. The new codes of structural design consist in design methodology that looks after the exploitation of the total resources of the construction material. In recent years some non-deterministic or meta-heuristic structural optimization algorithms have been developed widely in the research community. These methods search the optimum condition starting from the simulation of a natural phenomenon, such as survival of the fittest, the immune system, swarm intelligence or the cooling process of molten metal through annealing. Among these techniques the most known are: the genetic algorithms, simulated annealing, evolution strategies, particle swarm optimization, tabu search, ant colony optimization, harmony search and big bang crunch optimization. In this study, five of these algorithms are applied for the optimum weight design of a steel truss structure with variable geometry but fixed topology. The design process selects optimum distances and size sections from a set of commercial steel profiles. In the formulation of the design problem are considered deflection limitations, buckling and allowable stress constraints. The approach is repeated starting from different initial populations. The design problem topology is taken from an existing steel structure. The optimization process helps the engineer to achieve good final solutions, avoiding the repetitive evaluation of alternative designs in a time consuming process. The algorithms used for the application, the results of the optimal solutions, the number of iterations and the minimal weight designs, will be reported in the paper. Based on these results, it would be estimated, the amount of the steel that could be saved by applying structural analysis combined with non-deterministic optimization methods.

Keywords: structural optimization, non-deterministic methods, truss structures, steel truss

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Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

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Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

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Authors: Chandrashekara Krishnappa, Yogish Huchaiah

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The present work considers the importance of economic feasibility and financial viability of biodiesel production, and its use in the present context of prevailing Indian scenario. For this, costs involved in production of one litre of biodiesel from non-edible Jatropha and Pongamia oils Nano mix are considered. Biodiesel derived from the mix is blended with petrodiesel in various proportions and used in Compression Ignition (CI) Direct Injection (DI) engine. Performance and Emission characteristics were investigated. Optimization of the blends considering experimental results was carried out. To validate the experimental results and optimization, Multi-Functional Criteria Technique (MFCT) is used. Further, value additions in terms of INR due to increase in performance and reduction in emissions are investigated. Cost component of subsidy on petrodiesel is taken into consideration in the calculation of cost of one litre of it. Comparison of costs is with respect to the unit of power generated per litre of COME and petrodiesel. By the analysis it has been concluded that the amount saved with subsidy is INR 1.45 Lakh Crores per year and it is INR1.60 Lakh Crores per year without subsidy for petrodiesel.

Keywords: cap value addition, economic analysis, MFCT, NACOME, subsidy

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Authors: M. Celeska, K. Najdenkoski, V. Dimchev, V. Stoilkov

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Accurate determination of wind turbine performance is necessary for economic operation of a wind farm. At present, the procedure to carry out the power performance verification of wind turbines is based on a standard of the International Electrotechnical Commission (IEC). In this paper, nonparametric statistical inference is applied to designing a simple, inexpensive method of verifying the power performance of a wind turbine. A statistical test is explained, examined, and the adequacy is tested over real data. The methods use the information that is collected by the SCADA system (Supervisory Control and Data Acquisition) from the sensors embedded in the wind turbines in order to carry out the power performance verification of a wind farm. The study has used data on the monthly output of wind farm in the Republic of Macedonia, and the time measuring interval was from January 1, 2016, to December 31, 2016. At the end, it is concluded whether the power performance of a wind turbine differed significantly from what would be expected. The results of the implementation of the proposed methods showed that the power performance of the specific wind farm under assessment was acceptable.

Keywords: canonical correlation analysis, power curve, power performance, wind energy

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Authors: Oğuzhan Hasançebi, Saeid Kazemzadeh Azad

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Keywords: structural design optimization, optimal sizing, metaheuristics, self-adaptive step-size search, steel trusses, steel frames

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Authors: Annie B. V., Anu A. G., Harikumar R.

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Microgrid (MG) is a self-governing miniature section of the power system. Nowadays the majority of loads and energy storage devices are inherently in DC form. This necessitates a greater scope of research in the various types of energy storage devices in DC microgrids. In a modern power system, DC microgrid is a manageable electric power system usually integrated with renewable energy sources (RESs) and DC loads with the help of power electronic converters. The stability of the DC microgrid mainly depends on the power imbalance. Power imbalance due to the presence of intermittent renewable energy resources (RERs) is supplied by energy storage devices. Battery, supercapacitor, flywheel, etc. are some of the commonly used energy storage devices. Owing to the high energy density provided by the batteries, this type of energy storage system is mainly utilized in all sorts of hybrid energy storage systems. To minimize the stability issues, a Supercapacitor (SC) is usually interfaced with the help of a bidirectional DC/DC converter. SC can exchange power during transient conditions due to its high power density. This paper analyses the stability issues of DC microgrids with hybrid energy storage systems (HESSs) arises from a reduction in SC operating voltage due to self-discharge. The stability of DC microgrid and power management is analyzed with different control strategies.

Keywords: DC microgrid, hybrid energy storage system (HESS), power management, small signal modeling, supercapacitor

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Authors: S. Wakim, M. Nemer, B. Zeghondy, B. Ghannam, C. Bouallou

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Designing the optimal heat exchanger is still an essential objective to be achieved. Parametrical optimization involves the evaluation of the heat exchanger dimensions to find those that best satisfy certain objectives. This method contributes to an enhanced design rather than an optimized one. On the contrary, topology optimization finds the optimal structure that satisfies the design objectives. The huge development in metal additive manufacturing allowed topology optimization to find its way into engineering applications especially in the aerospace field to optimize metal structures. Using topology optimization in 3d heat and mass transfer problems requires huge computational time, therefore coupling it with CFD simulations can reduce this it. However, existed CFD models cannot be coupled with topology optimization. The CFD model must allow creating a uniform mesh despite the initial geometry complexity and also to swap the cells from fluid to solid and vice versa. In this paper, a porous media approach compatible with topology optimization criteria is developed. It consists of modeling the fluid region of the heat exchanger as porous media having high porosity and similarly the solid region is modeled as porous media having low porosity. The switching from fluid to solid cells required by topology optimization is simply done by changing each cell porosity using a user defined function. This model is tested on a plate and fin heat exchanger and validated by comparing its results to experimental data and simulations results. Furthermore, this model is used to perform a material reallocation based on local criteria to optimize a plate and fin heat exchanger under a constant heat duty constraint. The optimized fin uses 20% fewer materials than the first while the pressure drop is reduced by about 13%.

Keywords: computational methods, finite element method, heat exchanger, porous media, topology optimization

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Authors: Jun Yuan

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Shipping is a major transportation mode all over the world, and it has a significant contribution to global carbon emissions. Electrification of ships is one of the main strategies to reduce shipping carbon emissions. The number of electric ships has continued to grow in recent years. However, charging infrastructure is still scarce, which severely restricts the development of electric ships. Therefore, it is very important to design ship charging stations reasonably by comprehensively considering charging demand and investment costs. This study aims to minimize the full life cycle cost of charging stations, considering the uncertainty of charging demand. A mixed integer programming model is developed for this optimization problem. Based on the characteristics of the mathematical model, a simulation based optimization method is proposed to find the optimal number and rated power of chargers. In addition, the impact of renewable energy and storage systems is analyzed. The results can provide decision support and a reference basis for the design of ship charging stations.

Keywords: shipping emission, electricity ship, charging station, optimal design

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Authors: Pawel Sowa, Joachim Bargiel

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This paper presents modern solutions of distributed generation in rural communities aiming at the improvement of energy and environmental security, as well as power supply reliability to important customers (e.g. health care, sensitive consumer required continuity). Distributed sources are mainly gas and biogas cogeneration units, as well as wind and photovoltaic sources. Some examples of their applications in a selected Silesian community are given.

Keywords: energy security, mini energy centres , power engineering, power supply reliability

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Authors: Yuhan Lin, Rohan Kekatpure, Cassidy Yeung

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In Digital Marketing, robust quantification of View-through attribution (VTA) is necessary for evaluating channel effectiveness. VTA occurs when a product purchase is aided by an Ad but without an explicit click (e.g. a TV ad). A lack of a tracking mechanism makes VTA estimation challenging. Most prevalent VTA estimation techniques rely on post-purchase in-product user surveys. User surveys enable the calculation of channel multipliers, which are the ratio of the view-attributed to the click-attributed purchases of each marketing channel. Channel multipliers thus provide a way to estimate the unknown VTA for a channel from its known click attribution. In this work, we use Convex Optimization to compute channel multipliers in a way that enables a mathematical encoding of the expected channel behavior. Large fluctuations in channel attributions often result from overfitting the calculations to user surveys. Casting channel attribution as a Convex Optimization problem allows an introduction of constraints that limit such fluctuations. The result of our study is a distribution of channel multipliers across the entire marketing funnel, with important implications for marketing spend optimization. Our technique can be broadly applied to estimate Ad effectiveness in a privacy-centric world that increasingly limits user tracking.

Keywords: digital marketing, survey analysis, operational research, convex optimization, channel attribution

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Authors: Suleiman Aliyu

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Integrating IoT applications with Fog systems presents challenges in optimization due to diverse environments and conflicting objectives. This study explores achieving Pareto optimal deployments for Fog-based IoT systems to address growing QoS demands. We introduce Pareto optimality to balance competing performance metrics. Using the FogTorch optimization framework, we propose a hybrid approach (Backtracking search with branch and bound) for scalable IoT deployments. Our research highlights the advantages of Pareto optimality over single-objective methods and emphasizes the role of FogTorch in this context. Initial results show improvements in IoT deployment cost in Fog systems, promoting resource-efficient strategies.

Keywords: pareto optimality, fog application deployment, resource allocation, internet of things

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Authors: R. Rishi Jain, S. V. Viswanath, R. Naveen Vasanthan

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Generally all the IC engines, alternators, air conditioner compressors, oil pumps and coolant pumps are driven by a crankshaft utilizing V-belt drivers. An increase in the number of idle pulleys results in the increase of frictional power. Further, components like idler and belt tensioner are also needed to run the belt drive which adds to the frictional power. The aspiration of this paper is to minimize the friction power by introducing a new system that could combine all the accessories in one shaft within a single casing. This is conceptualized to minimize the friction power, service and maintenance cost, space and also time. The validation of this work can be executed through a simpler drive transmitting power from the crank shaft.

Keywords: single drive, idler pulley, belt tensioner, friction power, casing, space and cost

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Mahdi Golriz

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The aim of this work is to estimate the change in molecular structure of linear low-density polyethylene (LLDPE) during peroxide modification can be detected by a simple rheological method. For this purpose a commercial grade LLDPE (Exxon MobileTM LL4004EL) was reacted with different doses of dicumyl peroxide (DCP). The samples were analyzed by size-exclusion chromatography coupled with a light scattering detector. The dynamic shear oscillatory measurements showed a deviation of the δ-׀G ׀٭curve from that of the linear LLDPE, which can be attributed to the presence of long-chain branching (LCB). By the use of a simple rheological method that utilizes melt rheology, transformations in molecular architecture induced on an originally linear low density polyethylene during the early stages of reactive modification were indicated. Reasonable and consistent estimates are obtained, concerning the degree of LCB, the volume fraction of the various molecular species produced in peroxide modification of LLDPE.

Keywords: linear low-density polyethylene, peroxide modification, long-chain branching, rheological method

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Authors: Qasim Idrees, Gao Liangtian, Liu Bo, Miao Yiran

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In order to improve the efficiency and accuracy of the pressure hull structure, optimization of underwater vehicle based on response surface methodology, a method for optimizing the design of pressure hull structure was studied. To determine the pressure shell of five dimensions as a design variable, the application of thin shell theory and the Chinese Classification Society (CCS) specification was carried on the preliminary design. In order to optimize variables of the feasible region, different methods were studied and implemented such as Opt LHD method (to determine the design test sample points in the feasible domain space), parametric ABAQUS solution for each sample point response, and the two-order polynomial response for the surface model of the limit load of structures. Based on the ultimate load of the structure and the quality of the shell, the two-generation genetic algorithm was used to solve the response surface, and the Pareto optimal solution set was obtained. The final optimization result was 41.68% higher than that of the initial design, and the shell quality was reduced by about 27.26%. The parametric method can ensure the accuracy of the test and improve the efficiency of optimization.

Keywords: parameterization, response surface, structure optimization, pressure hull

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Authors: Alok Kumar Kamal, Vinod Kumar

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The trench gate MOSFET has shown itself as the most appropriate power device for low to medium voltage power applications due to its lowest possible ON resistance among all power semiconductor devices. In this research work a double-epilayer PSGT structure using a thin layer of N+ polysilicon as gate material. The total ON-state resistance (RON) of UMOSFET can be reduced by optimizing the epilayer thickness. The optimized structure of Double-Epilayer exhibits a 25.8% reduction in the ON-state resistance at Vgs=5V and improving the switching characteristics by reducing the Reverse transfer capacitance (Cgd) by 7.4%.

Keywords: Miller-capacitance, double-Epilayer;switching characteristics, power trench MOSFET (U-MOSFET), on-state resistance, blocking voltage

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