Search results for: memory optimization
3379 Conversion of HVAC Lines into HVDC in Transmission Expansion Planning
Authors: Juan P. Novoa, Mario A. Rios
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This paper presents a transmission planning methodology that considers the conversion of HVAC transmission lines to HVDC as an alternative of expansion of power systems, as a consequence of restrictions for the construction of new lines. The transmission expansion planning problem formulates an optimization problem that minimizes the total cost that includes the investment cost to convert lines from HVAC to HVDC and possible required reinforcements of the power system prior to the conversion. The costs analysis assesses the impact of the conversion on the reliability because transmission lines are out of service during the conversion work. The presented methodology is applied to a test system considering a planning a horizon of 10 years.Keywords: transmission expansion planning, HVDC, cost optimization, energy non-supplied
Procedia PDF Downloads 3923378 Application of GA Optimization in Analysis of Variable Stiffness Composites
Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani
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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.Keywords: beam structures, layerwise, optimization, variable stiffness
Procedia PDF Downloads 1493377 Historical Memory and Social Representation of Violence in Latin American Cinema: A Cultural Criminology Approach
Authors: Maylen Villamanan Alba
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Latin America is marked by its history: conquest, colonialism, and slavery left deep footprints in most Latin American countries. Also, the past century has been affected by wars, military dictatorships, and political violence, which profoundly influenced Latin American popular culture. Consequently, reminiscences of historical crimes are frequently present in daily life, media, public opinion, and arts. This legacy is remembered in novels, paintings, songs, and films. In fact, Latin American cinema has a trend which refers to the verisimilitude with reality in fiction films. These films about historical violence are narrated as fictional characters, but their stories are based on real historical contexts. Therefore, cultural criminology has considered films as a significant field to understand social representations of violence related to historical crimes. The aim of the present contribution is to analyze the legacy of past and historical memory in social representations of violence in Latin American cinema as a critical approach to historical crimes. This qualitative research is based on content analysis. The sample is seven multi-award winning films of the International Festival of New Latin American Cinema of Havana. The films selected are Kamchatka, Argentina (2002); Carandiru, Brazil (2003); Enlightened by fire, Argentina (2005); Post-mortem, Chile (2010); No, Chile (2012) Wakolda; Argentina (2013) and The Clan, Argentina (2015). Cultural criminology highlights that cinema shapes meanings of social practices such as historical crimes. Critical criminology offers a critical theory framework to interpret Latin American cinema. This analysis reveals historical conditions deeply associated with power relationships, policy, and inequality issues. As indicated by this theory, violence is characterized as a structural process based on social asymmetries. These social asymmetries are crossed by social scopes, including institutional and personal dimensions. Thus, institutions of the states are depicted through personal stories of characters involved with human conflicts. Intimacy and social background are linked in the personages who simultaneously perform roles such as soldiers, policemen, professionals or inmates and they are at the same time depict as human beings with family, gender, racial, ideological or generational issues. Social representations of violence related to past legacy are a portrait of historical crimes perpetrated against Latin American citizens. Thereby, they have contributed to political positions, social behaviors, and public opinion. The legacy of these historical crimes suggests a path that should never be taken again. It means past legacy is a reminder, a warning, and a historic lesson for Latin American people. Social representations of violence are permeated by historical memory as denunciation under a critical approach.Keywords: Latin American cinema, historical memory, social representation, violence
Procedia PDF Downloads 1543376 Optimal Placement of the Unified Power Controller to Improve the Power System Restoration
Authors: Mohammad Reza Esmaili
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One of the most important parts of the restoration process of a power network is the synchronizing of its subsystems. In this situation, the biggest concern of the system operators will be the reduction of the standing phase angle (SPA) between the endpoints of the two islands. In this regard, the system operators perform various actions and maneuvers so that the synchronization operation of the subsystems is successfully carried out and the system finally reaches acceptable stability. The most common of these actions include load control, generation control and, in some cases, changing the network topology. Although these maneuvers are simple and common, due to the weak network and extreme load changes, the restoration will be associated with low speed. One of the best ways to control the SPA is to use FACTS devices. By applying a soft control signal, these tools can reduce the SPA between two subsystems with more speed and accuracy, and the synchronization process can be done in less time. Meanwhile, the unified power controller (UPFC), a series-parallel compensator device with the change of transmission line power and proper adjustment of the phase angle, will be the proposed option in order to realize the subject of this research. Therefore, with the optimal placement of UPFC in a power system, in addition to improving the normal conditions of the system, it is expected to be effective in reducing the SPA during power system restoration. Therefore, the presented paper provides an optimal structure to coordinate the three problems of improving the division of subsystems, reducing the SPA and optimal power flow with the aim of determining the optimal location of UPFC and optimal subsystems. The proposed objective functions in this paper include maximizing the quality of the subsystems, reducing the SPA at the endpoints of the subsystems, and reducing the losses of the power system. Since there will be a possibility of creating contradictions in the simultaneous optimization of the proposed objective functions, the structure of the proposed optimization problem is introduced as a non-linear multi-objective problem, and the Pareto optimization method is used to solve it. The innovative technique proposed to implement the optimization process of the mentioned problem is an optimization algorithm called the water cycle (WCA). To evaluate the proposed method, the IEEE 39 bus power system will be used.Keywords: UPFC, SPA, water cycle algorithm, multi-objective problem, pareto
Procedia PDF Downloads 723375 The Optimization Design of Sound Absorbing for Automotive Interior Material
Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park
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Nonwoven fabric such as an automobile interior material becomes consists of several material layers required for the sound-absorbing function. Because several material layers, many experimental tuning is required to achieve the target of sound absorption. Therefore, a lot of time and money is spent in the development of the car interior materials. In this study, we present the method to predict the sound-absorbing performance of the various layers with physical properties of each material. and we will verify it with the measured value of a prototype. If the sound absorption can be estimated, it can be optimized without a number of tuning tests of the interiors. So, it can reduce the development cost and time during developmentKeywords: automotive interior material, sound absorbing, optimization design, nonwoven fabric
Procedia PDF Downloads 8423374 A Lightweight Pretrained Encrypted Traffic Classification Method with Squeeze-and-Excitation Block and Sharpness-Aware Optimization
Authors: Zhiyan Meng, Dan Liu, Jintao Meng
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Dependable encrypted traffic classification is crucial for improving cybersecurity and handling the growing amount of data. Large language models have shown that learning from large datasets can be effective, making pre-trained methods for encrypted traffic classification popular. However, attention-based pre-trained methods face two main issues: their large neural parameters are not suitable for low-computation environments like mobile devices and real-time applications, and they often overfit by getting stuck in local minima. To address these issues, we developed a lightweight transformer model, which reduces the computational parameters through lightweight vocabulary construction and Squeeze-and-Excitation Block. We use sharpness-aware optimization to avoid local minima during pre-training and capture temporal features with relative positional embeddings. Our approach keeps the model's classification accuracy high for downstream tasks. We conducted experiments on four datasets -USTC-TFC2016, VPN 2016, Tor 2016, and CICIOT 2022. Even with fewer than 18 million parameters, our method achieves classification results similar to methods with ten times as many parameters.Keywords: sharpness-aware optimization, encrypted traffic classification, squeeze-and-excitation block, pretrained model
Procedia PDF Downloads 383373 A Novel PSO Based Decision Tree Classification
Authors: Ali Farzan
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Classification of data objects or patterns is a major part in most of Decision making systems. One of the popular and commonly used classification methods is Decision Tree (DT). It is a hierarchical decision making system by which a binary tree is constructed and starting from root, at each node some of the classes is rejected until reaching the leaf nods. Each leaf node is a representative of one specific class. Finding the splitting criteria in each node for constructing or training the tree is a major problem. Particle Swarm Optimization (PSO) has been adopted as a metaheuristic searching method for finding the best splitting criteria. Result of evaluating the proposed method over benchmark datasets indicates the higher accuracy of the new PSO based decision tree.Keywords: decision tree, particle swarm optimization, splitting criteria, metaheuristic
Procedia PDF Downloads 4133372 Synergy Effect of Energy and Water Saving in China's Energy Sectors: A Multi-Objective Optimization Analysis
Authors: Yi Jin, Xu Tang, Cuiyang Feng
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The ‘11th five-year’ and ‘12th five-year’ plans have clearly put forward to strictly control the total amount and intensity of energy and water consumption. The synergy effect of energy and water has rarely been considered in the process of energy and water saving in China, where its contribution cannot be maximized. Energy sectors consume large amounts of energy and water when producing massive energy, which makes them both energy and water intensive. Therefore, the synergy effect in these sectors is significant. This paper assesses and optimizes the synergy effect in three energy sectors under the background of promoting energy and water saving. Results show that: From the perspective of critical path, chemical industry, mining and processing of non-metal ores and smelting and pressing of metals are coupling points in the process of energy and water flowing to energy sectors, in which the implementation of energy and water saving policies can bring significant synergy effect. Multi-objective optimization shows that increasing efforts on input restructuring can effectively improve synergy effects; relatively large synergetic energy saving and little water saving are obtained after solely reducing the energy and water intensity of coupling sectors. By optimizing the input structure of sectors, especially the coupling sectors, the synergy effect of energy and water saving can be improved in energy sectors under the premise of keeping economy running stably.Keywords: critical path, energy sector, multi-objective optimization, synergy effect, water
Procedia PDF Downloads 3643371 Protein Tertiary Structure Prediction by a Multiobjective Optimization and Neural Network Approach
Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares
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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network
Procedia PDF Downloads 2093370 Modeling Visual Memorability Assessment with Autoencoders Reveals Characteristics of Memorable Images
Authors: Elham Bagheri, Yalda Mohsenzadeh
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Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception
Procedia PDF Downloads 953369 Increasing Performance of Autopilot Guided Small Unmanned Helicopter
Authors: Tugrul Oktay, Mehmet Konar, Mustafa Soylak, Firat Sal, Murat Onay, Orhan Kizilkaya
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In this paper, autonomous performance of a small manufactured unmanned helicopter is tried to be increased. For this purpose, a small unmanned helicopter is manufactured in Erciyes University, Faculty of Aeronautics and Astronautics. It is called as ZANKA-Heli-I. For performance maximization, autopilot parameters are determined via minimizing a cost function consisting of flight performance parameters such as settling time, rise time, overshoot during trajectory tracking. For this purpose, a stochastic optimization method named as simultaneous perturbation stochastic approximation is benefited. Using this approach, considerable autonomous performance increase (around %23) is obtained.Keywords: small helicopters, hierarchical control, stochastic optimization, autonomous performance maximization, autopilots
Procedia PDF Downloads 5843368 Revising Australia’s Collective Memory through Post-Colonial Storytelling
Authors: Linda Jane Wells
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In 1914 Topsy Smith, a woman of the First Nations Arabana tribe arrived in Alice Springs with her seven children and a herd of goats. They had come in from the goldfields at Arltunga where they had been living, and Topsy’s husband, Welsh-born Bill Smith, had recently died. Sergeant Stott, the local policeman and sub-protector of Aborigines for the region, erected a tin shed for Topsy and the children to live in, which became known as the Bungalow for half-castes. Over the years that followed many more children of mixed descent were removed from their families and brought to live at the Bungalow until, a decade later, sixty children were growing up there, cared for predominantly by Topsy Smith; Ida Standley who was the first, white schoolteacher for the town; and Sergeant Stott. The story of the Bungalow is pivotal to the foundations of social relations in the town of Alice Springs and beyond. At the same time, it is little known, recognised or understood locally, let alone more broadly. This is typical of the dominant historic narratives that have emerged out of the Australian colonial project and led to ‘the Great Australian Silence.’ The term was coined by Australian anthropologist WEH Stanner in his 1968 Boyer Lectures, in reference to the omission of the Aboriginal experience from the dominant narratives of the nation’s history. In his lecture, he attributed this silence to something that may have begun as a simple forgetting of other possible views which turned, under habit and over time, into something like a cult of forgetfulness practised on a national scale. This doctoral project, underpinned by a methodology of practice-led research, engages a bricolage of methods including archival research, ethnography, and oral histories to research the bungalow and the context in which it operated. Techniques of fictocriticism, speculative biography, autoethnography, and archival poetics are then engaged to write the research outcomes into a post-colonial, multi-genre work of creative non-fiction that speaks into the silences in the archives. The overall intent of this doctoral work is to explore and demonstrate how techniques of creative non-fiction can be used to rewrite narratives of Australian colonial history that resonate beyond the academy, thus contributing to the bank of post-colonial stories and working towards a more just, honest and inclusive national ‘memory’ and identity.Keywords: Australian history, collective memory, creative non-fiction, postcolonialism
Procedia PDF Downloads 1203367 Supply Chain Optimization for Silica Sand in a Glass Manufacturing Company
Authors: Ramon Erasmo Verdin Rodriguez
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Many has been the ways that historically the managers and gurus has been trying to get closer to the perfect supply chain, but since this topic is so vast and very complex the bigger the companies are, the duty has not been certainly easy. On this research, you are going to see thru the entrails of the logistics that happens at a glass manufacturing company with the number one raw material of the process that is the silica sand. After a very quick passage thru the supply chain, this document is going to focus on the way that raw materials flow thru the system, so after that, an analysis and research can take place to improve the logistics. Thru Operations Research techniques, it will be analyzed the current scheme of distribution and inventories of raw materials at a glass company’s plants, so after a mathematical conceptualization process, the supply chain could be optimized with the purpose of reducing the uncertainty of supply and obtaining an economic benefit at the very end of this research.Keywords: inventory management, operations research, optimization, supply chain
Procedia PDF Downloads 3303366 Optimization of the Production Processes of Biodiesel from a Locally Sourced Gossypium herbaceum and Moringa oleifera
Authors: Ikechukwu Ejim
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This research project addresses the optimization of biodiesel production from gossypium herbaceum (cottonseed) and moringa oleifera seeds. Soxhlet extractor method using n-hexane for gossypium herbaceum (cottonseed) and ethanol for moringa oleifera were used for solvent extraction. 1250 ml of oil was realized from both gossypium herbaceum (cottonseed) and moringa oleifera seeds before characterization. In transesterification process, a 4-factor-3-level experiment was conducted using an optimal design of Response Surface Methodology. The effects of methanol/oil molar ratio, catalyst concentration (%), temperature (°C) and time (mins), on the yield of methyl ester for both cottonseed and moringa oleifera oils were determined. The design consisted of 25 experimental runs (5 lack of fit points, five replicate points, 0 additional center points and I optimality) and provided sufficient information to fit a second-degree polynomial model. The experimental results suggested that optimum conditions were as follows; cottonseed yield (96.231%), catalyst concentration (0.972%), temperature (55oC), time (60mins) and methanol/oil molar ratios (8/1) respectively while moringa oleifera optimum values were yield (80.811%), catalyst concentration (1.0%), temperature (54.7oC), time (30mins ) and methanol/oil molar ratios (8/1) respectively. This optimized conditions were validated with the actual biodiesel yield in experimental trials and literature.Keywords: optimization, Gossypium herbaceum, Moringa oleifera, biodiesel
Procedia PDF Downloads 1563365 A Review of Transformer Modeling for Power Line Communication Applications
Authors: Balarabe Nkom, Adam P. R. Taylor, Craig Baguley
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Power Line Communications (PLC) is being employed in existing power systems, despite the infrastructure not being designed with PLC considerations in mind. Given that power transformers can last for decades, the distribution transformer in particular exists as a relic of un-optimized technology. To determine issues that may need to be addressed in subsequent designs of such transformers, it is essential to have a highly accurate transformer model for simulations and subsequent optimization for the PLC environment, with a view to increase data speed, throughput, and efficiency, while improving overall system stability and reliability. This paper reviews various methods currently available for creating transformer models and provides insights into the requirements of each for obtaining high accuracy. The review indicates that a combination of traditional analytical methods using a hybrid approach gives good accuracy at reasonable costs.Keywords: distribution transformer, modelling, optimization, power line communications
Procedia PDF Downloads 5123364 3D Numerical Studies on Jets Acoustic Characteristics of Chevron Nozzles for Aerospace Applications
Authors: R. Kanmaniraja, R. Freshipali, J. Abdullah, K. Niranjan, K. Balasubramani, V. R. Sanal Kumar
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The present environmental issues have made aircraft jet noise reduction a crucial problem in aero-acoustics research. Acoustic studies reveal that addition of chevrons to the nozzle reduces the sound pressure level reasonably with acceptable reduction in performance. In this paper comprehensive numerical studies on acoustic characteristics of different types of chevron nozzles have been carried out with non-reacting flows for the shape optimization of chevrons in supersonic nozzles for aerospace applications. The numerical studies have been carried out using a validated steady 3D density based, k-ε turbulence model. In this paper chevron with sharp edge, flat edge, round edge and U-type edge are selected for the jet acoustic characterization of supersonic nozzles. We observed that compared to the base model a case with round-shaped chevron nozzle could reduce 4.13% acoustic level with 0.6% thrust loss. We concluded that the prudent selection of the chevron shape will enable an appreciable reduction of the aircraft jet noise without compromising its overall performance. It is evident from the present numerical simulations that k-ε model can predict reasonably well the acoustic level of chevron supersonic nozzles for its shape optimization.Keywords: supersonic nozzle, Chevron, acoustic level, shape optimization of Chevron nozzles, jet noise suppression
Procedia PDF Downloads 5213363 Fuzzy Time Series Forecasting Based on Fuzzy Logical Relationships, PSO Technique, and Automatic Clustering Algorithm
Authors: A. K. M. Kamrul Islam, Abdelhamid Bouchachia, Suang Cang, Hongnian Yu
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Forecasting model has a great impact in terms of prediction and continues to do so into the future. Although many forecasting models have been studied in recent years, most researchers focus on different forecasting methods based on fuzzy time series to solve forecasting problems. The forecasted models accuracy fully depends on the two terms that are the length of the interval in the universe of discourse and the content of the forecast rules. Moreover, a hybrid forecasting method can be an effective and efficient way to improve forecasts rather than an individual forecasting model. There are different hybrids forecasting models which combined fuzzy time series with evolutionary algorithms, but the performances are not quite satisfactory. In this paper, we proposed a hybrid forecasting model which deals with the first order as well as high order fuzzy time series and particle swarm optimization to improve the forecasted accuracy. The proposed method used the historical enrollments of the University of Alabama as dataset in the forecasting process. Firstly, we considered an automatic clustering algorithm to calculate the appropriate interval for the historical enrollments. Then particle swarm optimization and fuzzy time series are combined that shows better forecasting accuracy than other existing forecasting models.Keywords: fuzzy time series (fts), particle swarm optimization, clustering algorithm, hybrid forecasting model
Procedia PDF Downloads 2553362 An Effective Decision-Making Strategy Based on Multi-Objective Optimization for Commercial Vehicles in Highway Scenarios
Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong
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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle
Procedia PDF Downloads 1393361 Optimal Injected Current Control for Shunt Active Power Filter Using Artificial Intelligence
Authors: Brahim Berbaoui
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In this paper, a new particle swarm optimization (PSO) based method is proposed for the implantation of optimal harmonic power flow in power systems. In this algorithm approach, proportional integral controller for reference compensating currents of active power filter is performed in order to minimize the total harmonic distortion (THD). The simulation results show that the new control method using PSO approach is not only easy to be implanted, but also very effective in reducing the unwanted harmonics and compensating reactive power. The studies carried out have been accomplished using the MATLAB Simulink Power System Toolbox.Keywords: shunt active power filter, power quality, current control, proportional integral controller, particle swarm optimization
Procedia PDF Downloads 6203360 Time-Domain Simulations of the Coupled Dynamics of Surface Riding Wave Energy Converter
Authors: Chungkuk Jin, Moo-Hyun Kim, HeonYong Kang
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A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.Keywords: computer simulation, electromagnetics fully-coupled dynamics, floater-mooring-magnet, optimization, performance evaluation, surface riding, WEC
Procedia PDF Downloads 1503359 Optimization of Spatial Light Modulator to Generate Aberration Free Optical Traps
Authors: Deepak K. Gupta, T. R. Ravindran
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Holographic Optical Tweezers (HOTs) in general use iterative algorithms such as weighted Gerchberg-Saxton (WGS) to generate multiple traps, which produce traps with 99% uniformity theoretically. But in experiments, it is the phase response of the spatial light modulator (SLM) which ultimately determines the efficiency, uniformity, and quality of the trap spots. In general, SLMs show a nonlinear phase response behavior, and they may even have asymmetric phase modulation depth before and after π. This affects the resolution with which the gray levels are addressed before and after π, leading to a degraded trap performance. We present a method to optimize the SLM for a linear phase response behavior along with a symmetric phase modulation depth around π. Further, we optimize the SLM for its varying phase response over different spatial regions by optimizing the brightness/contrast and gamma of the hologram in different subsections. We show the effect of the optimization on an array of trap spots resulting in improved efficiency and uniformity. We also calculate the spot sharpness metric and trap performance metric and show a tightly focused spot with reduced aberration. The trap performance is compared by calculating the trap stiffness of a trapped particle in a given trap spot before and after aberration correction. The trap stiffness is found to improve by 200% after the optimization.Keywords: spatial light modulator, optical trapping, aberration, phase modulation
Procedia PDF Downloads 1953358 Optimization of a Flux Switching Permanent Magnet Machine Using Laminated Segmented Rotor
Authors: Seyedmilad Kazemisangdehi, Seyedmehdi Kazemisangdehi
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Flux switching permanent magnet machines are considered for wide range of applications because of their outstanding merits including high torque/power densities, high efficiency, simple and robust rotor structure. Therefore, several topologies have been proposed like the PM exited flux switching machine, hybrid excited flux switching type, and so on. Recently, a novel laminated segmented rotor flux switching permanent magnet machine was introduced. It features flux barriers on rotor structure to enhance the performances of machine including torque ripple reduction and also torque and efficiency improvements at the same time. This is while, the design of barriers was not optimized by the authors. Therefore, in this paper three coefficients regarding the position of the barriers are considered for optimization. The effect of each coefficient on the performance of this machine is investigated by finite element method and finally an optimized design of flux barriers based on these three coefficients is proposed from different points of view including electromagnetic torque maximization and cogging torque/torque ripple minimization. At optimum design from maximum developed torque aspect, this machine generates 0.65 Nm torque higher than that of the not-optimized design with an almost 0.4 % improvement in efficiency.Keywords: finite element analysis, FSPM, laminated segmented rotor flux switching permanent magnet machine, optimization
Procedia PDF Downloads 2363357 A Firefly Based Optimization Technique for Optimal Planning of Voltage Controlled Distributed Generators
Authors: M. M. Othman, Walid El-Khattam, Y. G. Hegazy, A. Y. Abdelaziz
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This paper presents a method for finding the optimal location and capacity of dispatchable DGs connected to the distribution feeders for optimal planning for a specified power loss without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37-nodes feeder. The results that are validated by comparing it with results obtained from other competing methods show the effectiveness, accuracy and speed of the proposed method.Keywords: distributed generators, firefly technique, optimization, power loss
Procedia PDF Downloads 5403356 Wind Speed Prediction Using Passive Aggregation Artificial Intelligence Model
Authors: Tarek Aboueldahab, Amin Mohamed Nassar
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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction
Procedia PDF Downloads 4563355 Effect of Nanoparticles Concentration, pH and Agitation on Bioethanol Production by Saccharomyces cerevisiae BY4743: An Optimization Study
Authors: Adeyemi Isaac Sanusi, Gueguim E. B. Kana
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Nanoparticles have received attention of the scientific community due to their biotechnological potentials. They exhibit advantageous size, shape and concentration-dependent catalytic, stabilizing, immunoassays and immobilization properties. This study investigates the impact of metallic oxide nanoparticles (NPs) on ethanol production by Saccharomyces cerevisiae BY4743. Nine different nanoparticles were synthesized using precipitation method and microwave treatment. The nanoparticles synthesized were characterized by Fourier Transform Infra-Red spectroscopy (FTIR), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Fermentation processes were carried out at varied NPs concentrations (0 – 0.08 wt%). Highest ethanol concentrations were achieved after 24 h using Cobalt NPs (5.07 g/l), Copper NPs (4.86 g/l) and Manganese NPs (4.74 g/l) at 0.01 wt% NPs concentrations, which represent 13%, 8.7% and 5.4% increase respectively over the control (4.47 g/l). The lowest ethanol concentration (0.17 g/l) was obtained when 0.08 wt% of Silver NPs was used. And lower ethanol concentrations were observed at higher NPs concentration. Ethanol concentration decrease after 24 h for all the processes. In all set up with NPs, the pH was observed to be stable and the stability was directly proportional to nanoparticles concentrations. These findings suggest that the presence of some of the NPs in the bioprocesses has catalytic and pH stabilizing potential. Ethanol production by Saccharomyces cerevisiae BY4743 was enhanced in the presence of Cobalt NPs, Copper NPs and Manganese NPs. Optimization study using response surface methodology (RSM) will further elucidate the impact of these nanoparticles on bioethanol production.Keywords: agitation, bioethanol, nanoparticles concentration, optimization, pH value
Procedia PDF Downloads 1903354 Finding Optimal Solutions to Management Problems with the use of Econometric and Multiobjective Programming
Authors: M. Moradi Dalini, M. R. Talebi
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This research revolves around a technical method according to combines econometric and multiobjective programming to select and obtain optimal solutions to management problems. It is taken for a generation that; it is important to analyze which combination of values of the explanatory variables -in an econometric method- would point to the simultaneous achievement of the best values of the response variables. In this case, if a certain degree of conflict is viewed among the response variables, we suggest a multiobjective method in order to the results obtained from a regression analysis. In fact, with the use of a multiobjective method, we will have the best decision about the conflicting relationship between the response variables and the optimal solution. The combined multiobjective programming and econometrics benefit is an assessment of a balanced “optimal” situation among them because a find of information can hardly be extracted just by econometric techniques.Keywords: econometrics, multiobjective optimization, management problem, optimization
Procedia PDF Downloads 873353 Changes in Textural Properties of Zucchini Slices Under Effects of Partial Predrying and Deep-Fat-Frying
Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner
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Changes in textural properties of any food material during processing is significant for further consumer’s evaluation and directly affects their decisions. Thus any food material should be considered in terms of textural properties after any process. In the present study zucchini slices were partially predried to control and reduce the product’s final oil content. A conventional oven was used for partially dehydration of zucchini slices. Following frying was carried in an industrial fryer having temperature controller. This study was based on the effect of this predrying process on textural properties of fried zucchini slices. Texture profile analysis was performed. Hardness, elasticity, chewiness, cohesiveness were studied texture parameters of fried zucchini slices. Temperature and weight loss were monitored parameters of predrying process, whereas, in frying, oil temperature and process time were controlled. Optimization of two successive processes was done by response surface methodology being one of the common used statistical process optimization tools. Models developed for each texture parameters displayed high success to predict their values as a function of studied processes’ conditions. Process optimization was performed according to target values for each property determined for directly fried zucchini slices taking the highest score from sensory evaluation. Results indicated that textural properties of predried and then fried zucchini slices could be controlled by well-established equations. This is thought to be significant for fried stuff related food industry, where controlling of sensorial properties are crucial to lead consumer’s perception and texture related ones are leaders. This project (113R015) has been supported by TUBITAK.Keywords: optimization, response surface methodology, texture profile analysis, conventional oven, modelling
Procedia PDF Downloads 4383352 Updating Stochastic Hosting Capacity Algorithm for Voltage Optimization Programs and Interconnect Standards
Authors: Nicholas Burica, Nina Selak
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The ADHCAT (Automated Distribution Hosting Capacity Assessment Tool) was designed to run Hosting Capacity Analysis on the ComEd system via a stochastic DER (Distributed Energy Resource) placement on multiple power flow simulations against a set of violation criteria. The violation criteria in the initial version of the tool captured a limited amount of issues that individual departments design against for DER interconnections. Enhancements were made to the tool to further align with individual department violation and operation criteria, as well as the addition of new modules for use for future load profile analysis. A reporting engine was created for future analytical use based on the simulations and observations in the tool.Keywords: distributed energy resources, hosting capacity, interconnect, voltage optimization
Procedia PDF Downloads 2003351 Design Optimization and Thermoacoustic Analysis of Pulse Tube Cryocooler Components
Authors: K. Aravinth, C. T. Vignesh
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The usage of pulse tube cryocoolers is significantly increased mainly due to the advantage of the absence of moving parts. The underlying idea of this project is to optimize the design of pulse tube, regenerator, a resonator in cryocooler and analyzing the thermo-acoustic oscillations with respect to the design parameters. Computational Fluid Dynamic (CFD) model with time-dependent validation is done to predict its performance. The continuity, momentum, and energy equations are solved for various porous media regions. The effect of changing the geometries and orientation will be validated and investigated in performance. The pressure, temperature and velocity fields in the regenerator and pulse tube are evaluated. This optimized design performance results will be compared with the existing pulse tube cryocooler design. The sinusoidal behavior of cryocooler in acoustic streaming patterns in pulse tube cryocooler will also be evaluated.Keywords: acoustics, cryogenics, design, optimization
Procedia PDF Downloads 1813350 Optimization of Flexible Job Shop Scheduling Problem with Sequence-Dependent Setup Times Using Genetic Algorithm Approach
Authors: Sanjay Kumar Parjapati, Ajai Jain
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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times
Procedia PDF Downloads 337