Search results for: space optimization advice

Authors: Mandeep Kaur, Fatehgarh Sahib

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The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system.

Keywords: economic load dispatch, genetic algorithm, generating units, multiobjective optimization, weighting method

Procedia PDF Downloads 122

Authors: Wan-I Chen, Tsung-I Pai

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Future the society aging of population will create the social problem has not had the good mechanism solution in the Asian country, especially in Taiwan. In the future ten year the people in Taiwan must facing the condition which is localization aging social problem. In this situation, how to use the spatial in eco way to development space use to solve the old age spatial demand is the way which might develop in the future Taiwan society. Over the next 10 years, taking care of the aging people will become part of the social problem of aging phenomenon. The research concentrate in the feasibility of spatial substitution, secondary use of spatial might solve out of spatial problem for aging people. In order to prove the space usable, the research required to review the project with the support system and infill system for space experiment, by using network grid way. That defined community level of space elements location relationship, make new definitions of space and return to cooperation. Research to innovation in the the appraisal space causes the possibility, by spatial replacement way solution on spatial insufficient suitable condition. To evaluation community spatial by using the support system and infill system in order to see possibilities of use in replacement inner space and modular architecture into housing. The study is discovering the solution on the Eco way to develop space use to figure out the old age spatial demand.

Keywords: sustainable use, space conversion, integration, replacement


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Authors: Daham Owaid Matrood, Naqaa Hussein Raheem

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Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.

Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization

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Authors: Mohammad Mohammadi, Mohammad Pashmchi

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Background: Malnutrition commonly develops and worsens following gastric cancer surgery, particularly after discharge, which is associated with adverse outcomes. Former studies have primarily focused on patients during their hospital stay period, and there is limited evidence regarding the recommendation of nutritional interventions for patients after discharge from the hospital following gastric cancer surgery. This review is aimed to evaluate the efficiency of post-discharge dietary counseling with oral nutritional supplements (ONS), and dietary counseling alone on post-surgical nutritional outcomes in patients undergoing gastric cancer surgery. Methods: The four databases of Embase, PubMed, web of science, and google scholar were searched up to November 2022 for relevant randomized controlled trials. The Cochrane Collaboration’s assessment tool for randomized trials was used to evaluate the quality of studies. Results: Compared to patients who only received dietary counseling, patients who received both dietary counseling and ONS had considerably higher SMI, BMI, and less weight loss and sarcopenia occurrence rate. The patients who had received dietary counseling and ONS had significantly lower risk of chemotherapy intolerance. No differences in the readmission rate between the two groups was found. In terms of the quality of life, concomitant dietary advice and ONS significantly was associated with lower appetite loss and fatigue rate, but there was no difference in the other outcomes between the two groups. Conclusions: Post-discharge dietary advice with ONS following gastric cancer surgery may improve skeletal muscle maintenance, nutritional outcomes, quality of life variables, and chemotherapy tolerance. This evidence supports the recommendation of post-discharge dietary advice with ONS for patients who underwent gastric cancer surgery.

Keywords: gastric cancer surgery, oral nutritional supplements, malnutrition, gastric cancer

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Authors: Francisco Borja de Lara, Ali Ravanbakhsh, Robert F. Wimmer-Schweingruber, Lars Seimetz, Fermín Navarro

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The intense structural loads during the launch of a spacecraft represent a challenge for the space structure designers because enough resistance has to be achieved while maintaining at the same time the mass and volume within the allowable margins of the mission requirements and inside the limits of the budget project. In this conference, we present the structural analysis of the Lunar Lander Neutron Dosimetry (LND) experiment on the Chang'E4 mission, the first probe to land on the moon’s far side included in the Chinese’ Moon Exploration Program by the Chinese National Space Administration. To this target, the software Nastran/Patran has been used: a structural model in Patran and a structural analysis through Nastran have been realized. Next, the results obtained are used both for the optimization process of the spacecraft structure, and as input parameters for the model structural test campaign. In this way, the feasibility of the lunar instrument structure is demonstrated in terms of the modal modes, stresses, and random vibration and a better understanding of the structural tests design is provided by our results.

Keywords: Chang’E4, Chinese national space administration, lunar lander neutron dosimetry, nastran-patran, structural analysis

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Authors: Bushra Alghamdi, Alla Alsharif, Hamzah Aljohani, Saba Kassim

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Introduction: Collaborative work has always been acknowledged as a fundamental concept in delivering oral health care. Aim: This study aimed to assess the perception and attitude of pharmacists in oral health promotion and to determine the confident levels of pharmacists in delivering advice on oral health problems. Methods: An observational cross-sectional survey, using self-administered anonymous questionnaires, was conducted between March and April 2017. The study recruited a convenience sample of registered community pharmacists who were working in local private pharmaceutical stores in the urban area of Madinah, Kingdom of Saudi Arabia (KSA). A preliminary descriptive analysis was performed. Results: Thirty-five pharmacists have completed the surveys. All participants were males, with a mean age of 35.5 ( ± 6.92) years. Eighty-six percent of the participants reported that pharmacists should have a role in oral health promotion. Eighty percent have reported adequate level of confident when giving advice on most of the common oral health problems that include; oral health related risk behaviors such as tobacco cessation (46%), bleeding gums (63%) and sensitive teeth (60%). However, higher percentages of pharmacists have reported low confident levels when giving advice in relation to specific domain of dentistry, such as lost dental fillings (57%), loose crowns (60%), trauma to teeth (40%), denture-related problems (51%) and oral cancer (6.9%). Conclusion: Community pharmacists recognized their potential role in promoting oral health in KSA. Community pharmacists had varying levels of ability and confidence to offer support for oral health. The study highlighted that inner professional collaboration between pharmacists and dental care healthcare should be enhanced.

Keywords: community, oral health, promotion, pharmacist

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Authors: Rimmy Yadav, Avtar Singh

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—Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: ant colony optimization, link failure, prim’s algorithm, shortest path

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Arthur Baraov

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Nearly all rocket and spacecraft propulsion concepts in existence today can be linked one way or the other to one of the two ancient warfare devices: the gun and the sling. Chemical, thermoelectric, ion, nuclear thermal and electromagnetic rocket engines – all fall into the first group which, for obvious reasons, can be categorized as “hot” space propulsion concepts. Space elevator, orbital tower, rolling satellite, orbital skyhook, tether propulsion and gravitational assist – are examples of the second category which lends itself for the title “cold” space propulsion concepts. The “hot” space propulsion concepts skyrocketed – literally and figuratively – from the naïve ideas of Jules Verne to the manned missions to the Moon. On the other hand, with the notable exception of gravitational assist, hardly any of the “cold” space propulsion concepts made any progress in terms of practical application. Why is that? This article aims to show that the right answer to this question has the potential comparable by its implications and practical consequences to that of transition from Jules Verne’s stillborn and impractical conceptions of space flight to cogent and highly fertile ideas of Konstantin Tsiolkovsky and Yuri Kondratyuk.

Keywords: propulsion, rocket, rollet, spacecraft

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Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Shabadini Sampath, Jinglang Feng

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With huge kinetic energy, space debris poses a major threat to astronauts’ space activities and spacecraft in orbit if a collision happens. The active removal of space debris is required in order to avoid frequent collisions that would occur. In addition, the amount of space debris will increase uncontrollably, posing a threat to the safety of the entire space system. But the safe and reliable removal of large-scale space debris has been a huge challenge to date. While capturing and deorbiting space debris, the space manipulator has to achieve high control precision. However, due to uncertainties and unknown disturbances, there is difficulty in coordinating the control of the space manipulator. To address this challenge, this paper focuses on developing a robust and intelligent control algorithm that controls joint movement and restricts it on the sliding manifold by reducing uncertainties. A neural network adaptive sliding mode controller (NNASMC) is applied with the objective of finding the control law such that the joint motions of the space manipulator follow the given trajectory. A computed torque control (CTC) is an effective motion control strategy that is used in this paper for computing space manipulator arm torque to generate the required motion. Based on the Lyapunov stability theorem, the proposed intelligent controller NNASMC and CTC guarantees the robustness and global asymptotic stability of the closed-loop control system. Finally, the controllers used in the paper are modeled and simulated using MATLAB Simulink. The results are presented to prove the effectiveness of the proposed controller approach.

Keywords: GNC, active removal of space debris, AI controllers, MatLabSimulink

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Authors: Xiyue Wen

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With the rapid development of the city, old communities in the city are facing a series of problems. On one hand, aging facilities, obsolete spatial patterns, aging populations arouse in the aging of the community. On the other hand, public space is reduced and is taking up by cars parking or facilities setting, which lead to the collapse of traditional life in the old communities. That is to say, modern amenities haven’t helped to reform the old community, but have leading to tedious and inefficient, when it is not accommodated in the traditional space. Exploring a way is imminent to the east the contradiction between modern living facilities and spatial patterns of traditional. We select a typical site-GeDa Community in Xi’an, built in 70-80s，and carry out a concept calling 'Raising Landscape', which enables a convenient and efficient space for parking, as well as a high-quality yard for activities. In addition, the design implements low cost, simple construction, resident participation, so that it can be spread in the same texture of urban space.

Keywords: old communities, renewal strategy, raising landscape, public space, parking space

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Authors: A. Samer Ezeldin, Sarah A. Fotouh

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Optimization of resources is very important in all fields, as in construction management. Project managers have to face problems regarding management of cost, time and available resources of single projects and more problems arise when managing multiple projects. Most of the studies focused on optimization of resources for a single project, but, this paper will discuss the design and modeling of multiple resources optimization for multiple projects using Genetic Algorithm. Most of the companies in construction industry optimize the resources for single projects only, but with the presence of several mega projects in several developing countries running at the same time, there is a need for a model to enhance the efficiency of available resources and decreases the fluctuation as much as possible. The proposed model calculates the cost of each resource, tries to minimize the cost of extra resources as much as possible and generates the schedule of each project within a selected program.

Keywords: construction management, genetic algorithm, multiple projects, multiple resources, optimization

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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: L. Abdou, O. Taibaoui, A. Moumen, A. Talib Ahmed

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This paper proposes an application of the simulated annealing to optimize the detection threshold in an ordered statistics constant false alarm rate (OS-CFAR) system. Using conventional optimization methods, such as the conjugate gradient, can lead to a local optimum and lose the global optimum. Also for a system with a number of sensors that is greater than or equal to three, it is difficult or impossible to find this optimum; Hence, the need to use other methods, such as meta-heuristics. From a variety of meta-heuristic techniques, we can find the simulated annealing (SA) method, inspired from a process used in metallurgy. This technique is based on the selection of an initial solution and the generation of a near solution randomly, in order to improve the criterion to optimize. In this work, two parameters will be subject to such optimisation and which are the statistical order (k) and the scaling factor (T). Two fusion rules; “AND” and “OR” were considered in the case where the signals are independent from sensor to sensor. The results showed that the application of the proposed method to the problem of optimisation in a distributed system is efficiency to resolve such problems. The advantage of this method is that it allows to browse the entire solutions space and to avoid theoretically the stagnation of the optimization process in an area of local minimum.

Keywords: distributed system, OS-CFAR system, independent sensors, simulating annealing

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Authors: Olusola Bamisile, Oluwaseun Ayodele, Mustafa Dagbasi

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The main objective of this research is to optimize the power produced by a solar chimney wind turbine. The cut out speed and the maximum possible production are considered while performing the optimization. Solar chimney is one of the solar technologies that can be used in rural areas at cheap cost. With over 50% of rural areas still yet to have access to electricity. The OptimTool in MATLAB is used to maximize power produced by the turbine subject to certain constraints. The results show that an optimized turbine produces about ten times the power of the normal turbine which is 111 W/h. The rest of the research discuss in detail solar chimney power plant and the optimization simulation used in this study.

Keywords: solar chimney, optimization, wind turbine, renewable energy systems

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Authors: M. Saeed, A. Shahidzadeh

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Interaction between teachers and learners requires applying a set of samples (examples) which helps to create coordination between the goals and methods. The main result and achievement and application of samples (examples) are that they can bring the teacher and learner to a shared understanding of the concept. mathematical concepts, and also one of the challenging issues in the discussion of the function is to find the collision points of functions of and, regarding that the example space of teachers is different in this issue, this paper aims to present an example space including several problems of the secondary school with the help of intuition and drawing various graphs of functions of and for more familiarity of teachers.

Keywords: inverse function, educational example, Mathematic example, example space

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Authors: Seyed Abbas Tabatabaei, Marjan Naderan Tahan, Arman Kadkhodai

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An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model’s computation time and solution quality. On the other, highway alignment optimization through Feasible Gates, eventuates only economic model by considering minimum design constrains includes minimum reduce of circular curves, minimum length of vertical curves and road maximum gradient. This modelling can reduce passenger comfort and road safety. In most of highway optimization models, by adding penalty function for each constraint, final result handles to satisfy minimum constraint. In this paper, we want to propose a safety-function solution by introducing gift function.

Keywords: safety, highway geometry, optimization, alignment

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Authors: U. Yerlikaya, R. T. Balkan

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In this research, a method is developed to obtain high-dimensional configuration space for path planning problems. In typical cases, the path planning problems are solved directly in the 3-dimensional (D) workspace. However, this method is inefficient in handling the robots with various geometrical and mechanical restrictions. To overcome these difficulties, path planning may be formalized and solved in a new space which is called configuration space. The number of dimensions of the configuration space comes from the degree of freedoms of the system of interest. The method can be applied in two ways. In the first way, the point clouds of all the bodies of the system and interaction of them are used. The second way is performed via using the clearance function of simulation software where the minimum distances between surfaces of bodies are simultaneously measured. A double-turret system is held in the scope of this study. The 4-D configuration space of a double-turret system is obtained in these two ways. As a result, the difference between these two methods is around 1%, depending on the density of the point cloud. The disparity between the two forms steadily decreases as the point cloud density increases. At the end of the study, in order to verify 4-D configuration space obtained, 4-D path planning problem was realized as 2-D + 2-D and a sample path planning is carried out with using A* algorithm. Then, the accuracy of the configuration space is proved using the obtained paths on the simulation model of the double-turret system.

Keywords: A* algorithm, autonomous turrets, high-dimensional C-space, manifold C-space, point clouds

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Badr M. Alshammari, T. Guesmi

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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations

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Authors: Parastoo Kazemiyan

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Over the past 80 years, in compliance with the advent of modernity in Iran and Turkey, the presence of women in economic and social arenas has creates serious challenges in the capacity of urban spaces to respond to their presence and transport because urban spaces up until then were based on masculine criteria and therefore, women could use such spaces in the company of their fathers or husbands. However, as modernity expanded by Reza Shah and Ataturk, women found the opportunity to work and be present in urban spaces alongside men and their presence in economic and social domains resulted in their presence in these spaces in the early and late hours of the day. Therefore, the city had to be transformed in structural, social, and environmental terms to accommodate women's activities and presence in various urban arenas, which was a huge step in transition from a masculine man-based culture to an all-inclusive human-based culture in these two countries. However, the optimization of urban space was subject to political changes in the two countries, leading to significant differences in designing urban spaces in Tehran and Istanbul. What shows the importance and novelty of the present study lie in the differences in urban planning and optimization in the two capital cities, which gave rise to different outcomes in desirability and quality of living in these two capital cities. Due to the importance of the topic, one of the most significant factors in desirability and acceptability of urban space for women was examined using a descriptive-analytic method based on qualitative methodology in Tehran and Istanbul. The results showed that the infrastructural factors in Istanbul, including safety of access, variety, and number of public transport modes, transparency, and supervision over public spaces have provided women with a safer and more constant presence compared to Tehran. It seems that challenges involved in providing access to urban spaces in Tehran in terms of infrastructure and function have made Tehran unable to respond to the most basic needs of its female citizens.

Keywords: gender differences, urban space security, access to transportation systems, women's challenges

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Authors: H. Ghodbane, A. A. Taleb, O. Kraa

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This paper presents geometric design of induction heating system. The objective of this design is to improve the temperature distribution in the load. The study of such a device requires the use of models or modeling representation, physical, mathematical, and numerical. This modeling is the basis of the understanding, the design, and optimization of these systems. The optimization technique is to find values of variables that maximize or minimize the objective function.

Keywords: optimization, modeling, geometric design system, temperature increase

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Muhammad Feteha

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The socio-political Middle East scene has radically changed over the last decade, and one major contributor to this change was the Egyptian revolution of 2011. The massive impact of this revolution that originally started as a small protest in the Tahrir square has attracted more scholars to study the public space in Egypt, where it has become a necessity in order to understand and improve the socio-political conditions. The status of public space in Egypt has been deteriorating due to many reasons, including privatization and neglect. This paper studies one of the major problems of the contemporary public space in Cairo, which is the lack of identity. This takes place through a comparative analysis between selected case studies from both medieval and contemporary Cairo. The theoretical framework upon which the analysis is based views public space as a ‘container of social action’ and a ‘product of spatial practice’. Through the ‘deciphering of space’, differences in the socio-political role, symbolism, and identity of public spaces between both eras are shown. The paper aims to extract some lessons from public space in medieval Cairo, which was truly the ‘centerpiece of the public realm’ and a ‘fundamental expressions’ of the unique trans-dynastic architectural identity of Cairo. In addition, it suggests some strategies to revive the Cairene identity of public space instead of constructing new ones to be only ‘utilitarian spaces used for circulation’ and lack any identity.

Keywords: architectural identity, Cairene public space, Islamic architectural history, production of space

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Authors: U. M. Swamy

Abstract:

A compact Hausdorff and totally disconnected topological space are known as Boolean space in view of the stone duality between Boolean algebras and such topological spaces. A sheaf over X is a triple (S, p, X) where S and X are topological spaces and p is a local homeomorphism of S onto X (that is, for each element s in S, there exist open sets U and G containing s and p(s) in S and X respectively such that the restriction of p to U is a homeomorphism of U onto G). Here we mainly concern on sheaves over Boolean spaces. From a given sheaf over a Boolean space, we obtain an algebraic structure in such a way that there is a one-to-one correspondence between these algebraic structures and sheaves over Boolean spaces.

Keywords: Boolean algebra, Boolean space, sheaf, stone duality

Procedia PDF Downloads 325

Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

Abstract:

Lunar exploration is a necessary foundation for deep-space exploration. For the functional limitations of the fixed landers which are widely used currently and are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability, a movable lunar soft-landing device based on cantilever type buffer mechanism and leg-foot type walking mechanism is presented. Firstly, a 20 DoFs quadruped configuration based on pushrod is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and can make the kinematics of the whole mechanism unchanged before and after buffering. Secondly, the multi-function main/auxiliary buffers based on crumple-energy absorption and screw-nut mechanism, as well as the telescopic device which could be used to protect the plantar force sensors during the buffer process are designed. Finally, the kinematic model of the whole mechanism is established, and the configuration optimization of the whole mechanism is completed based on the performance requirements of slope adaptation and obstacle crossing. This research can provide a technical solution integrating soft-landing, large-scale inspection and material-transfer for future lunar exploration and even mars exploration, and can also serve as the technical basis for developing the reusable landers.

Keywords: configuration design, lunar soft-landing device, movable, optimization

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Authors: Pulak Swain, A. K. Ojha

Abstract:

Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of  E- constraint method.

Keywords: portfolio optimization, multi-objective optimization, ϵ - constraint method, box uncertainty, robust optimization

Procedia PDF Downloads 119