Search results for: wind turbine performance optimization

Authors: Mohammad Ali Farrokhpour

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In the current decade and sustainable transportation systems, scooter sharing has attracted widespread attention as an environmentally-friendly means of public transportation which can help develop public transportation. The combination of scooters and subway in the area of sustainable transportation systems can provide a great many opportunities for developing access to public transportation. Of the challenges which have arisen and initiated discussions of interest about the implementation of a scooter-subway system to replace personal vehicles is the issue of routing in the aforementioned system. This has been chosen as the main subject of the present paper. Thus, the present paper provides an account for routing in this system. Because the issue of routing includes multiple factors such as time, costs, traffic, green spaces, etc., the above-mentioned problem is considered to be a multi-objective NP-hard optimization problem. For this purpose, the hybrid optimization approach of PSO-GA has been put forward in the present paper for the provided answers to be of higher accuracy and validity than those of normal optimization methods. The results obtained from modeling and problem solving for the case study in the MATLAB software are indicative of the efficiency and desirability of the model and the proposed approach for solving the model

Keywords: route planning, scooter sharing, public transportation, sharing system

Procedia PDF Downloads 78

Authors: Younghyun Jeon, Seungjoo Maeng

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In the Ad-hoc network, the great interests regarding MIMO scheme leads to their combination, which is also utilized into its applicable network. We manage the field of the problem into Reverse-link MIMO Ad-hoc Network (RMAN) and propose the methodology to maximize the data rate with its power consumption using Node-Cooperative beamforming technique. Based on the result of mathematical optimization formulation, we design the algorithm to construct optimal orthogonal weight vector according to channel feedback and control its transmission power according to QoS-pricing value level. In simulation results, we show the validity of the proposed mathematical optimization result and algorithm which mean that the sum-rate of each link is converged into some point.

Keywords: ad-hoc network, MIMO, cooperative beamforming, transmit power

Procedia PDF Downloads 391

Authors: Agord M. Pinto Jr., Yuzo Iano, Leandro T. Manera, Raphael R. N. Souza

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This paper describes an optimization tool-based design strategy for a Current Mode Logic CML divide-by-2 circuit. Representing a building block for output frequency generation in a RFID protocol based-frequency synthesizer, the circuit was designed to minimize the power consumption for driving of multiple loads with unbalancing (at transceiver level). Implemented with XFAB XC08 180 nm technology, the circuit was optimized through MunEDA WiCkeD tool at Cadence Virtuoso Analog Design Environment ADE.

Keywords: divide-by-2 circuit, CMOS technology, PLL phase locked-loop, optimization tool, CML current mode logic, RF transceiver

Procedia PDF Downloads 458

Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Hanlin Liu, Hua Li, Yintan AI

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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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Authors: Camila Lima, Murilo Andrade Valle, Patrícia Teixeira Leite Asano

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The growth in demand for electricity, caused by human development, depletion and environmental impacts caused by traditional sources of electricity generation have made new energy sources are increasingly encouraged and necessary for companies in the electricity sector. Based on this scenario, this paper assesses the negative environmental impacts associated with thermoelectric power plants in Brazil, pointing out the importance of using renewable energy sources, reducing environmental aggression. This article points out the existence of an energy alternative, wind energy, of the municipalities of São Paulo, represented by georeferenced maps with the help of GIS, using as a premise the indicators of sustainability and multicriteria analysis in the decision-making process.

Keywords: GIS (geographic information systems), multicriteria analysis, sustainability, wind energy

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Authors: Badache Messaoud

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Geothermal thermosyphons (GTs) are increasingly used in many heating and cooling geothermal applications owing to their high heat transfer performance. This paper proposes a response surface methodology (RSM) to investigate and optimize the performance of a CO2 geothermal thermosyphon. The filling ratio (FR), temperature, and flow rate of the heat transfer fluid are selected as the designing parameters, and heat transfer rate and effectiveness are adopted as response parameters (objective functions). First, a dedicated experimental GT test bench filled with CO2 was built and subjected to different test conditions. An RSM was used to establish corresponding models between the input parameters and responses. Various diagnostic tests were used to assess evaluate the quality and validity of the best-fit models, which explain respectively 98.9% and 99.2% of the output result’s variability. Overall, it is concluded from the RSM analysis that the heat transfer fluid inlet temperatures and the flow rate are the factors that have the greatest impact on heat transfer (Q) rate and effectiveness (εff), while the FR has only a slight effect on Q and no effect on εff. The maximal heat transfer rate and effectiveness achieved are 1.86 kW and 47.81%, respectively. Moreover, these optimal values are associated with different flow rate levels (mc level = 1 for Q and -1 for εff), indicating distinct operating regions for maximizing Q and εff within the GT system. Therefore, a multilevel optimization approach is necessary to optimize both the heat transfer rate and effectiveness simultaneously.

Keywords: geothermal thermosiphon, co2, Response surface methodology, heat transfer performance

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Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization

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Authors: Mukul Anand

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Quality oriented affordable shelter for all has always been the key issue in the housing sector of our country. Homelessness is the acute form of housing need. It is a paradox that in spite of innumerable government initiated programmes for affordable housing, certain section of society is still devoid of shelter. About nineteen million (18.78 million) households grapple with housing shortage in Urban India in 2012. In Indian scenario there is major mismatch between the people for whom the houses are being built and those who need them. The prime force faced by public authorities in facilitation of quality housing for all is high cost of construction. The present paper will comprehend executable techniques for dilution of cost factor in housing the homeless. The key actors responsible for delivery of cheap housing stock such as capacity building, resource optimization, innovative low cost building material and indigenous skeleton housing system will also be incorporated in developing these techniques. Time performance, which is an important angle of above actors, will also be explored so as to increase the effectiveness of low cost housing. Along with this best practices will be taken up as case studies where both conventional techniques of housing and innovative low cost housing techniques would be cited. Transportation consists of approximately 30% of total construction budget. Thus use of alternative local solutions depending upon the region would be covered so as to highlight major components of low cost housing. Government is laid back regarding base line information on use of innovative low cost method and technique of resource optimization. Therefore, the paper would be an attempt to bring to light simpler solutions for achieving low cost housing.

Keywords: construction, cost, housing, optimization, shelter

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Authors: G. Rajyalakhmi, C. Karthik, Gerson Desouza, Rimmie Duraisamy

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In this present work, metal matrix composites with combination of aluminium with (Sic/Al2O3) were fabricated using stir casting technique. The objective of the present work is to optimize the process parameters of Wire Electric Discharge Machining (WEDM) composites. Pulse ON Time, Pulse OFF Time, wire feed and sensitivity are considered as input process parameters with responses Material Removal Rate (MRR), Surface Roughness (SR) for optimization of WEDM process. Taguchi L18 Orthogonal Array (OA) is used for experimentation. Grey Relational Analysis (GRA) is coupled with Taguchi technique for multiple process parameters optimization. ANOVA (Analysis of Variance) is used for finding the impact of process parameters individually. Finally confirmation experiments were carried out to validate the predicted results.

Keywords: parametric optimization, particulate reinforced metal matrix composites, Taguchi-grey relational analysis, WEDM

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Authors: Ibrahim Isa Ali (Pantami), Abdu Jaafaru Bambale, Abimbola Alale, Danjuma Ibrahim Ndihgihdah, Muhammad Alkali, Adamu Idris Umar, Babadoko Dantala Mohammed, Moshood Kareem Olawole

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This paper dwells on the risk management required for High throughput Satellite (HTS) project, and major subsystems that pertains to the improved performance and reliability of the spacecraft. The paper gives a clear picture of high‐throughput satellites (HTS) and the associated technologies with performances as they align and differ with the traditional geostationary orbit or Geosynchronous Equatorial Orbit (GEO) Communication Satellites. The paper also highlights critical subsystems and processes in project conceptualization and execution. The paper discusses the configuration of the payload. The need for optimization of resources for the HTS project and successful integration of critical subsystems for spacecraft requires implementation of risk analysis and mitigation from the preliminary design stage; Assembly, Integration and Test (AIT); Launch and in-orbit- Management stage.

Keywords: AIT, HTS, in-orbit management, optimization

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Authors: Li Dan, Zhao Junsuo, Zhang Wenjun

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Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.

Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Santhosh Kumat T., Priya E.

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The control of a doubly fed induction generator by fuzzy is described. The active and reactive power can be controlled by rotor and grid side converters with fuzzy controller. The main objective is to maintain constant voltage and frequency at the output of the generator. However the Line Side Converter (LSC) can be controlled to supply up to 50% of the required reactive current. When the crowbar is not activated the DFIG can supply reactive power from the rotor side through the machine as well as through the LSC.

Keywords: Doubly Fed Induction Generator (DFIG), Rotor Side Converter (RSC), Grid Side Converter (GSC), Wind Energy Conversion Systems (WECS)

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Authors: Masato Koizumi, Yuya Oshio, Ikkoh Funaki

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Magnetoplasma Sail (MPS) is a future spacecraft propulsion that generates high levels of thrust by inducing an artificial magnetosphere to capture and deflect solar wind charged particles in order to transfer momentum to the spacecraft. By injecting plasma in the spacecraft’s magnetic field region, the ring current azimuthally drifts on the equatorial plane about the dipole magnetic field generated by the current flowing through the solenoid attached on board the spacecraft. This ring current results in magnetosphere inflation which improves the thrust performance of MPS spacecraft. In this present study, the ring current was experimentally measured using three Rogowski Current Probes positioned in a circular array about the laboratory model of MPS spacecraft. This investigation aims to determine the detailed structure of ring current through physical experimentation performed under two different magnetic field strengths engendered by varying the applied voltage on the solenoid with 300 V and 600 V. The expected outcome was that the three current probes would detect the same current since all three probes were positioned at equal radial distance of 63 mm from the center of the solenoid. Although experimental results were numerically implausible due to probable procedural error, the trends of the results revealed three pieces of perceptive evidence of the ring current behavior. The first aspect is that the drift direction of the ring current depended on the strength of the applied magnetic field. The second aspect is that the diamagnetic current developed at a radial distance not occupied by the three current probes under the presence of solar wind. The third aspect is that the ring current distribution varied along the circumferential path about the spacecraft’s magnetic field. Although this study yielded experimental evidence that differed from the original hypothesis, the three key findings of this study have informed two critical MPS design solutions that will potentially improve thrust performance. The first design solution is the positioning of the plasma injection point. Based on the implication of the first of the three aspects of ring current behavior, the plasma injection point must be located at a distance instead of at close proximity from the MPS Solenoid for the ring current to drift in the direction that will result in magnetosphere inflation. The second design solution, predicated by the third aspect of ring current behavior, is the symmetrical configuration of plasma injection points. In this study, an asymmetrical configuration of plasma injection points using one plasma source resulted in a non-uniform distribution of ring current along the azimuthal path. This distorts the geometry of the inflated magnetosphere which minimizes the deflection area for the solar wind. Therefore, to realize a ring current that best provides the maximum possible inflated magnetosphere, multiple plasma sources must be spaced evenly apart for the plasma to be injected evenly along its azimuthal path.

Keywords: Magnetoplasma Sail, magnetosphere inflation, ring current, spacecraft propulsion

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Authors: Ekin Nurbaş

Abstract:

One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

Procedia PDF Downloads 139

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Mahdi Mottahedi, Peter Zahn, Armin Lechler, Alexander Verl

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Optimal topology of components leads to the maximum stiffness with the minimum material use. For the generation of these topologies, normally algorithms are employed, which tackle manufacturing limitations, at the cost of the optimal result. The global optimum result with penalty factor one, however, cannot be fabricated with conventional methods. In this article, an additive manufacturing method is introduced, in order to enable the production of global topology optimization results. For a benchmark, topology optimization with higher and lower penalty factors are performed. Different algorithms are employed in order to interpret the results of topology optimization with lower factors in many microstructure layers. These layers are then joined to form the final geometry. The algorithms’ benefits are then compared experimentally and numerically for the best interpretation. The findings demonstrate that by implementation of the selected algorithm, the stiffness of the components produced with this method is higher than what could have been produced by conventional techniques.

Keywords: topology optimization, additive manufacturing, 3D-printer, laminated object manufacturing

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Azadeh Jafari, Farzin Ghanadi, Matthew J. Emes, Maziar Arjomandi, Benjamin S. Cazzolato

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The turbulence within the atmospheric boundary layer induces highly unsteady aerodynamic loads on structures. These loads, if not accounted for in the design process, will lead to structural failure and are therefore important for the design of the structures. For an accurate prediction of wind loads, understanding the correlation between atmospheric turbulence and the aerodynamic loads is necessary. The aim of this study is to investigate the effect of turbulence within the atmospheric boundary layer on the surface pressure on a flat plate over a wide range of turbulence intensities and integral length scales. The flat plate is chosen as a fundamental geometry which represents structures such as solar panels and billboards. Experiments were conducted at the University of Adelaide large-scale wind tunnel. Two wind tunnel boundary layers with different intensities and length scales of turbulence were generated using two sets of spires with different dimensions and a fetch of roughness elements. Average longitudinal turbulence intensities of 13% and 26% were achieved in each boundary layer, and the longitudinal integral length scale within the three boundary layers was between 0.4 m and 1.22 m. The pressure distributions on a square flat plate at different elevation angles between 30° and 90° were measured within the two boundary layers with different turbulence intensities and integral length scales. It was found that the peak pressure coefficient on the flat plate increased with increasing turbulence intensity and integral length scale. For example, the peak pressure coefficient on a flat plate elevated at 90° increased from 1.2 to 3 with increasing turbulence intensity from 13% to 26%. Furthermore, both the mean and the peak pressure distribution on the flat plates varied with turbulence intensity and length scale. The results of this study can be used to provide a more accurate estimation of the unsteady wind loads on structures such as buildings and solar panels.

Keywords: atmospheric boundary layer, flat plate, pressure coefficient, turbulence

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Authors: Emery A. Coppola Jr., Suna Cinar, Ferenc Szidarovszky

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Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions.

Keywords: numerical groundwater flow modeling, water management optimization, groundwater overdraft, streamflow depletion

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Authors: Ehsan Atash Zaban, Mehdi Beyk

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In recent years, concerns over the depletion of non-renewable fuels and environmental pollution have led countries around the world to look for alternative energy sources for these fuels. An energy source that can have the necessary reliability, be a suitable alternative to fossil fuels, be technologically achievable, comply with environmental standards to the maximum, and at the same time cause countries to meet domestic consumption for electricity production. Iran is one of the richest countries in the world in terms of various energy sources because, on the one hand, it has extensive sources of fossil and non-renewable fuels such as oil and gas, and on the other hand, it has great potential for renewable energy. In this paper, the potential of renewable energy in Iran, which includes solar, wind, geothermal, hydrogen technology, and biomass, has been reviewed and analyzed.

Keywords: renewable energy, solar stations, wind, biomass, hydropower

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Syed Hassan Raza Shah, Mohammad Mohammad Ali

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The flow over a smoothly profiled airfoil at a low Reynolds number is highly susceptible to separate even at a very low angle of attack. An investigation was made to study the effect of leading-edge and trailing-edge corrugation with the spanwise change in the ridges resulted due to the change in the chord length for an infinite wing. The wind tunnel results using NACA0018 wings revealed that leading and trailing edge corrugation did not have any benefit in terms of aerodynamic efficiency or delayed stall. The leading edge and trailing edge corrugation didn't change the lift curve slope, with the leading edge corrugation wing stalling first in the range of Reynolds number of 50,000 to 125,000.

Keywords: leading and trailing edge corrugations, low reynolds number, wind tunnel testing, NACA0018

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Authors: Ebert Brea

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We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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Authors: Bakr Gomaa

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Wind driven Cross ventilation is achieved when air moves indoors due to the pressure difference on the building envelope. This is especially important in breezy moderate to humid settings in which fast air flow can promote thermal comfort. Studies have shown that the use of simple building forms or ignoring the urban context when studying natural ventilation can lead to inaccurate results. In this paper, the impact of the urban form of a regular array of buildings is investigated to define the impact of this urban setting on cross ventilation potential. The objective of this paper is to provide the necessary tools to achieve natural ventilation for cooling purposes in an array of building blocks context. The array urban form has been studied before for natural ventilation purposes yet to the best of our knowledge no study has considered the relationship between the urban form and the pressure patterns that develop on the buildings envelope for cross ventilation. For this we use detailed weather data for a case study city of Alexandria (Egypt), as well as a validated CFD simulations to investigate the cross ventilation potential in terms of pressure patterns in waterfront as well as in-city wind flows perpendicular to the buildings array. it was found that for both waterfront and in-city wind speeds the windows needed for cross ventilation in rear raws of the array are significantly larger than those needed for front raw.

Keywords: Alexandria, CFD, cross ventilation, pressure coefficient

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Authors: Wenbo Duan, Hossein Habibi, Vassilios Kappatos, Cem Selcuk, Tat-Hean Gan

Abstract:

Ultrasonic guided waves are often used to remove ice or fouling in different structures, such as ship hulls, wind turbine blades and so on. To achieve maximum sound power output, it is important that multiple transducers are arranged in a particular way so that a desired mode can be excited. The objective of this paper is thus to provide a theoretical basis for generating a particular mode in a finite width rectangular plate which can be used for removing potential ice or fouling on the plate. The number of transducers and their locations with respect to a particular mode will be investigated, and the link between dispersion curves and practical applications will be explored. To achieve this, a semi-analytical finite element (SAFE) method is used to study the dispersion characteristics of all the modes in the ultrasonic frequency range. The detailed modal shapes will be revealed, and from the modal analysis, the particular mode with the strongest yet continuous transverse and axial displacements on the surfaces of the plate will be chosen for the purpose of removing potential ice or fouling on the plate. The modal analysis is followed by providing information on the number, location and amplitude of transducers needed to excite this particular mode. Modal excitation is then implemented in a standard finite element commercial package, namely COMSOL Multiphysics. Wave motion is visualized in COMSOL, and the mode shapes generated in SAFE is found to be consistent with the mode shapes generated in COMSOL.

Keywords: dispersion analysis, finite width plate, guided wave, modal excitation

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Authors: R. Dariani, S. Schmidt, R. Kasper

Abstract:

Based on a non-linear single track model which describes the dynamics of vehicle, an optimal path planning strategy is developed. Real time optimization is used to generate reference control values to allow leading the vehicle alongside a calculated lane which is optimal for different objectives such as energy consumption, run time, safety or comfort characteristics. Strict mathematic formulation of the autonomous driving allows taking decision on undefined situation such as lane change or obstacle avoidance. Based on position of the vehicle, lane situation and obstacle position, the optimization problem is reformulated in real-time to avoid the obstacle and any car crash.

Keywords: autonomous driving, obstacle avoidance, optimal control, path planning

Procedia PDF Downloads 365

Authors: Shraddha Srivastava, N. K. Painuly, S. P. Mishra, Navin Singh, Muhsin Punchankandy, Kirti Srivastava, M. L. B. Bhatt

Abstract:

Various optimization methods used in interstitial brachytherapy are based on dwell positions and dwell weights alteration to produce dose distribution based on the implant geometry. Since these optimization schemes are not anatomy based, they could lead to deviations from the desired plan. This study was henceforth carried out to compare anatomy-based Inverse Planning Simulated Annealing (IPSA) optimization technique with graphical and geometrical optimization methods in interstitial high dose rate brachytherapy planning of cervical carcinoma. Six patients with 12 CT data sets of MUPIT implants in HDR brachytherapy of cervical cancer were prospectively studied. HR-CTV and organs at risk (OARs) were contoured in Oncentra treatment planning system (TPS) using GYN GEC-ESTRO guidelines on cervical carcinoma. Three sets of plans were generated for each fraction using IPSA, graphical optimization (GrOPT) and geometrical optimization (GOPT) methods. All patients were treated to a dose of 20 Gy in 2 fractions. The main objective was to cover at least 95% of HR-CTV with 100% of the prescribed dose (V100 ≥ 95% of HR-CTV). IPSA, GrOPT, and GOPT based plans were compared in terms of target coverage, OAR doses, homogeneity index (HI) and conformity index (COIN) using dose-volume histogram (DVH). Target volume coverage (mean V100) was found to be 93.980.87%, 91.341.02% and 85.052.84% for IPSA, GrOPT and GOPT plans respectively. Mean D90 (minimum dose received by 90% of HR-CTV) values for IPSA, GrOPT and GOPT plans were 10.19 ± 1.07 Gy, 10.17 ± 0.12 Gy and 7.99 ± 1.0 Gy respectively, while D100 (minimum dose received by 100% volume of HR-CTV) for IPSA, GrOPT and GOPT plans was 6.55 ± 0.85 Gy, 6.55 ± 0.65 Gy, 4.73 ± 0.14 Gy respectively. IPSA plans resulted in lower doses to the bladder (D₂

Keywords: cervical cancer, HDR brachytherapy, IPSA, MUPIT

Procedia PDF Downloads 179