Search results for: optimization tool

Authors: Lana Dalawr Jalal

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This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: obstacle avoidance, particle swarm optimization, three-dimensional path planning unmanned aerial vehicles

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Authors: Zhang Jianrun, He Tangling

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Superposition wave form automotive exhaust bellows is a new type of bellows, which has the characteristics of large compensation, good vibration isolation performance and long life. It has been paid more and more attention and applications in automotive exhaust pipe system. Aiming at the lack of current design methods of superposition wave form automotive exhaust bellows, this paper proposes a response surface parameter optimization method where the fatigue life and vibration transmissibility of the bellows are set as objectives. The parametric modeling of bellow structure is also adopted to achieve the high efficiency in the design. The approach proposed in this paper provides a new way for the design of superposition wave form automotive exhaust bellows. It embodies good engineering application value.

Keywords: superposition wave form, exhaust bellows, optimization, vibration, fatigue life

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Danah Al-Selahi, Sulaiman Al-Ghunaim, Bashayer Sadiq, Fatma Al-Otaibi, Ali Ameen

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In light of recent changes affecting the Oil & Gas Industry, optimization measures have become imperative for all companies globally, including Kuwait Oil Company (KOC). To keep abreast of the dynamic market, a detailed Integrated Asset Plan (IAP) was developed to drive optimization across the organization, which was facilitated through the in-house developed software “Well Inventory Data Entry” (WIDE). This comprehensive and integrated approach enabled centralization of all planned asset components for better well planning, enhancement of performance, and to facilitate continuous improvement through performance tracking and midterm forecasting. Traditionally, this was hard to achieve as, in the past, various legacy methods were used. This paper briefly describes the methods successfully adopted to meet the company’s objective. IAPs were initially designed using computerized spreadsheets. However, as data captured became more complex and the number of stakeholders requiring and updating this information grew, the need to automate the conventional spreadsheets became apparent. WIDE, existing in other aspects of the company (namely, the Workover Optimization project), was utilized to meet the dynamic requirements of the IAP cycle. With the growth of extensive features to enhance the planning process, the tool evolved into a centralized data-hub for all asset-groups and technical support functions to analyze and infer from, leading WIDE to become the reference two-year operational plan for the entire company. To achieve WIDE’s goal of operational efficiency, asset-groups continuously add their parameters in a series of predefined workflows that enable the creation of a structured process which allows risk factors to be flagged and helps mitigation of the same. This tool dictates assigned responsibilities for all stakeholders in a method that enables continuous updates for daily performance measures and operational use. The reliable availability of WIDE, combined with its user-friendliness and easy accessibility, created a platform of cross-functionality amongst all asset-groups and technical support groups to update contents of their respective planning parameters. The home-grown entity was implemented across the entire company and tailored to feed in internal processes of several stakeholders across the company. Furthermore, the implementation of change management and root cause analysis techniques captured the dysfunctionality of previous plans, which in turn resulted in the improvement of already existing mechanisms of planning within the IAP. The detailed elucidation of the 2 year plan flagged any upcoming risks and shortfalls foreseen in the plan. All results were translated into a series of developments that propelled the tool’s capabilities beyond planning and into operations (such as Asset Production Forecasts, setting KPIs, and estimating operational needs). This process exemplifies the ability and reach of applying advanced development techniques to seamlessly integrated the planning parameters of various assets and technical support groups. These techniques enables the enhancement of integrating planning data workflows that ultimately lay the founding plans towards an epoch of accuracy and reliability. As such, benchmarks of establishing a set of standard goals are created to ensure the constant improvement of the efficiency of the entire planning and operational structure.

Keywords: automation, integration, value, communication

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Authors: Pablo Ignacio Hernández Arango, Niels Lindemeyer

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Chlorine, as Sodium Hypochlorite (NaClO) solution in water, is an effective, worldwide spread, and economical substance to eliminate germs in the water. The disinfection potential of chlorine lies in its ability to degrade the outer surfaces of bacterial cells and viruses. This contribution reports the main parameters of the brine electrolysis for the production of NaClO, which is afterward used for the disinfection of water either for drinking or recreative uses. Herein, the system design was simulated, optimized, build, and tested based on titanium electrodes. The process optimization considers the whole process, from the salt (NaCl) dilution tank in order to maximize its operation time util the electrolysis itself in order to maximize the chlorine production reducing the energy and raw material (salt and water) consumption. One novel idea behind this optimization process is the modification of the flow pattern inside the electrochemical reactors. The increasing turbulence and residence time impact positively the operations figures. The operational parameters, which are defined in this study were compared and benchmarked with the parameters of actual commercial systems in order to validate the pertinency of those results.

Keywords: electrolysis, water disinfection, sodium hypochlorite, process optimization

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Authors: Haider M. Alsaeq

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The present research is an attempt to figure out the best configuration of composite cylindrical shells of the sandwich type, i.e. the lightest design of such shells required to sustain a certain load over a certain area. The optimization is based on elastic-plastic geometrically nonlinear incremental-iterative finite element analysis. The nine-node degenerated curved shell element is used in which five degrees of freedom are specified at each nodal point, with a layered model. The formulation of the geometrical nonlinearity problem is carried out using the well-known total Lagrangian principle. For the structural optimization problem, which is dealt with as a constrained nonlinear optimization, the so-called Modified Hooke and Jeeves method is employed by considering the weight of the shell as the objective function with stress and geometrical constraints. It was concluded that the optimum design of composite sandwich cylindrical shell that have a rigid polyurethane foam core and steel facing occurs when the area covered by the shell becomes almost square with a ratio of core thickness to facing thickness lies between 45 and 49, while the optimum height to length ration varies from 0.03 to 0.08 depending on the aspect ratio of the shell and its boundary conditions.

Keywords: composite structure, cylindrical shell, optimization, non-linear analysis, finite element

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Authors: Richardson Ciguene, Bertrand Marron, Nicolas Habert

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Today, more and more consumers are purchasing their products and services online. At the same time, the penetration rate of very small and medium-sized businesses on marketplaces continues to increase, which has the direct impact of intensifying competition between sellers. Thus, only the best-optimized deals are ranked well by algorithms and are visible to consumers. However, it is almost impossible to know all the Brand Content rules and criteria established by marketplaces, which is essential to optimizing their product sheets, especially since these rules change constantly. In this paper, we propose to detail this question of Brand Content optimization by taking into account the case of Amazon in order to capture the scientific dimension behind such a subject. In a second step, we will present the genesis of our research project, DEEPERFECT, which aims to set up original methods and effective tools in order to help sellers present on marketplaces in the optimization of their branded content.

Keywords: e-commerce, scoring, marketplace, Amazon, brand content, product sheets

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Authors: Sebastian Kehne, Alexander Epple, Werner Herfs

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A new method for optimal selection of components for multi-axes forward-feed drive systems is proposed in which the choice of motors, gear boxes and ball screw drives is optimized. Essential is here the synchronization of electrical and mechanical frequency behavior of all axes because even advanced controls (like H∞-controls) can only control a small part of the mechanical modes – namely only those of observable and controllable states whose value can be derived from the positions of extern linear length measurement systems and/or rotary encoders on the motor or gear box shafts. Further problems are the unknown processing forces like cutting forces in machine tools during normal operation which make the estimation and control via an observer even more difficult. To start with, the open source Modelica Feed Drive Library which was developed at the Laboratory for Machine Tools, and Production Engineering (WZL) is extended from one axis design to the multi axes design. It is capable to simulate the mechanical, electrical and thermal behavior of permanent magnet synchronous machines with inverters, different gear boxes and ball screw drives in a mechanical system. To keep the calculation time down analytical equations are used for field and torque producing equivalent circuit, heat dissipation and mechanical torque at the shaft. As a first step, a small machine tool with a working area of 635 x 315 x 420 mm is taken apart, and the mechanical transfer behavior is measured with an impulse hammer and acceleration sensors. With the frequency transfer functions, a mechanical finite element model is built up which is reduced with substructure coupling to a mass-damper system which models the most important modes of the axes. The model is modelled with Modelica Feed Drive Library and validated by further relative measurements between machine table and spindle holder with a piezo actor and acceleration sensors. In a next step, the choice of possible components in motor catalogues is limited by derived analytical formulas which are based on well-known metrics to gain effective power and torque of the components. The simulation in Modelica is run with different permanent magnet synchronous motors, gear boxes and ball screw drives from different suppliers. To speed up the optimization different black-box optimization methods (Surrogate-based, gradient-based and evolutionary) are tested on the case. The objective that was chosen is to minimize the integral of the deviations if a step is given on the position controls of the different axes. Small values are good measures for a high dynamic axes. In each iteration (evaluation of one set of components) the control variables are adjusted automatically to have an overshoot less than 1%. It is obtained that the order of the components in optimization problem has a deep impact on the speed of the black-box optimization. An approach to do efficient black-box optimization for multi-axes design is presented in the last part. The authors would like to thank the German Research Foundation DFG for financial support of the project “Optimierung des mechatronischen Entwurfs von mehrachsigen Antriebssystemen (HE 5386/14-1 | 6954/4-1)” (English: Optimization of the Mechatronic Design of Multi-Axes Drive Systems).

Keywords: ball screw drive design, discrete optimization, forward feed drives, gear box design, linear drives, machine tools, motor design, multi-axes design

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Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

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Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Waseem Shahzad, Ayesha Tahir Khan, Hamid Hussain Awan

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Ant-Miner algorithm that lies under ACO algorithms is used to extract knowledge from data in the form of rules. A variant of Ant-Miner algorithm named as cAnt-MinerPB is used to generate list of rules using pittsburgh approach in order to maintain the rule interaction among the rules that are generated. In this paper, we propose a parallel Ant MinerPB in which Ant colony optimization algorithm runs parallel. In this technique, a data set is divided vertically (i-e attributes) into different subsets. These subsets are created based on the correlation among attributes using Mutual Information (MI). It generates rules in a parallel manner and then merged to form a final list of rules. The results have shown that the proposed technique achieved higher accuracy when compared with original cAnt-MinerPB and also the execution time has also reduced.

Keywords: ant colony optimization, parallel Ant-MinerPB, vertical partitioning, classification rule discovery

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Authors: M. C. Lin, C. W. Su

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The paper investigates the optimization analysis to the heat exchanger design, mainly with response surface method and genetic algorithm to explore the relationship between optimal fluid flow velocity and temperature of the heat exchanger using field synergy principle. First, finite volume method is proposed to calculate the flow temperature and flow rate distribution for numerical analysis. We identify the most suitable simulation equations by response surface methodology. Furthermore, a genetic algorithm approach is applied to optimize the relationship between fluid flow velocity and flow temperature of the heat exchanger. The results show that the field synergy angle plays vital role in the performance of a true heat exchanger.

Keywords: optimization analysis, field synergy, heat exchanger, genetic algorithm

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Authors: Mukesh A. Modi

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High-nitrate concentration in groundwater of unconfined aquifers has been a serious issue for public health risk at a global scale. Various anthropogenic activities in agricultural land and urban land of alluvial soil have been observed to be responsible for the increment of nitrate in groundwater. The present study was designed to identify suitable denitrification strategies to minimize the effects of high nitrate in groundwater near the Mahi River of Vadodara block, Gujarat. There were 11 wells of Jal Jeevan Mission, Ministry of Jal Shakti, along with 3 observation wells of Gujarat Water Resources Development Corporation have been used for the duration of 21 years. MODFLOW and MT3DMS codes have been used to simulate solute transport phenomena along with attempted effectively for optimization. Current research is one step ahead by optimizing various denitrification strategies with the simulation of the model. The in-situ and ex-situ denitrification strategies viz. NAS (No Action Scenario), CAS (Crop Alternation Scenario), PS (Phytoremediation Scenario), and CAS + PS (Crop Alternation Scenario + Phytoremediation Scenario) have been selected for the optimization. The groundwater model simulates the most suitable denitrification strategy considering the hydrogeological characteristics at the targeted well.

Keywords: groundwater, high nitrate, MODFLOW, MT3DMS, optimization, denitrification strategy

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Authors: Linh Nguyen Tung, Anh Truong Viet, Nghien Nguyen Ba, Chuong Trinh Trong

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This paper proposes a reconfiguration methodology based on a continuous genetic algorithm (CGA) and particle swarm optimization (PSO) for minimizing active power loss and minimizing voltage deviation. Both algorithms are adapted using graph theory to generate feasible individuals, and the modified crossover is used for continuous variable of CGA. To demonstrate the performance and effectiveness of the proposed methods, a comparative analysis of CGA with PSO for network reconfiguration, on 33-node and 119-bus radial distribution system is presented. The simulation results have shown that both CGA and PSO can be used in the distribution network reconfiguration and CGA outperformed PSO with significant success rate in finding optimal distribution network configuration.

Keywords: distribution network reconfiguration, particle swarm optimization, continuous genetic algorithm, power loss reduction, voltage deviation

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Authors: Kazi Hossain

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The National Australian Built Environment Rating System (NABERS) is the key industry standard for measuring and benchmarking environmental performance of existing buildings in Australia. Developed and run by the New South Wales government, NABERS measures the operational efficiency of different types of buildings by using a set of tools that provide an easy to understand graphical rating outcome ranged from 0 to 6 stars. This set of tools also include a tool called NABERS IE which enables tenants or building managers to benchmark their buildings indoor environment quality against the national market. Launched in 2009, the number NABERS IE ratings have steadily increased from 10 certified ratings in 2011 to 43 in 2013. However there is a massive uptake of over 50 ratings alone in 2014 making the number of ratings to reach over 100. This paper outlines the methodology used to create this tool, a statistical overview of the tool, and the driving factor that motivates the building owners and managers to use this tool every year to rate their buildings.

Keywords: Acoustic comfort, Indoor air quality, Indoor Environment, NABERS, National Australian Built Environment Rating System, Performance rating, Rating System, Thermal comfort, Ventilation effectiveness, Visual comfort.

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Authors: Xiaoping Qiu, Binci You, Yue Hu

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The executive time of the workflow network has an important effect on the efficiency of the business process. In this paper, the activity executive time is divided into the service time and the waiting time, then the lead time can be extracted from the waiting time. The executive time formulas of the three basic structures in the workflow network are deduced based on the activity lead time. Taken the process of e-commerce logistics as an example, insert appropriate lead time for key activities by using Petri net, and the executive time optimization model is built to minimize the waiting time with the time-cost constraints. Then the solution program-using VC++6.0 is compiled to get the optimal solution, which reduces the waiting time of key activities in the workflow, and verifies the role of lead time in the timeliness of e-commerce logistics.

Keywords: electronic business, execution time, lead time, optimization model, petri net, time workflow network

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Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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Authors: Luis Guilherme Resende Santos, Ido Nevat, Leslie Norford

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The Urban Heat Island (UHI) is characterized by increased air temperatures in urban areas compared to undeveloped rural surrounding environments. With urbanization and densification, the intensity of UHI increases, bringing negative impacts on livability, health and economy. In order to reduce those effects, it is required to take into consideration design factors when planning future developments. Given design constraints such as population size and availability of area for development, non-trivial decisions regarding the buildings’ dimensions and their spatial distribution are required. We develop a framework for optimization of urban design in order to jointly minimize UHI intensity and buildings’ energy consumption. First, the design constraints are defined according to spatial and population limits in order to establish realistic boundaries that would be applicable in real life decisions. Second, the tools Urban Weather Generator (UWG) and EnergyPlus are used to generate outputs of UHI intensity and total buildings’ energy consumption, respectively. Those outputs are changed based on a set of variable inputs related to urban morphology aspects, such as building height, urban canyon width and population density. Lastly, an optimization problem is cast where the utility function quantifies the performance of each design candidate (e.g. minimizing a linear combination of UHI and energy consumption), and a set of constraints to be met is set. Solving this optimization problem is difficult, since there is no simple analytic form which represents the UWG and EnergyPlus models. We therefore cannot use any direct optimization techniques, but instead, develop an indirect “black box” optimization algorithm. To this end we develop a solution that is based on stochastic optimization method, known as the Cross Entropy method (CEM). The CEM translates the deterministic optimization problem into an associated stochastic optimization problem which is simple to solve analytically. We illustrate our model on a typical residential area in Singapore. Due to fast growth in population and built area and land availability generated by land reclamation, urban planning decisions are of the most importance for the country. Furthermore, the hot and humid climate in the country raises the concern for the impact of UHI. The problem presented is highly relevant to early urban design stages and the objective of such framework is to guide decision makers and assist them to include and evaluate urban microclimate and energy aspects in the process of urban planning.

Keywords: building energy consumption, stochastic optimization, urban design, urban heat island, urban weather generator

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Authors: Prabha Rohatgi

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To obtain an efficient control over a huge amount of inventory of drugs in pharmacy department of any hospital, generally, the medicines are categorized on the basis of their cost ‘ABC’ (Always Better Control), first and then categorize on the basis of their criticality ‘VED’ (Vital, Essential, desirable) for prioritization. About one-third of the annual expenditure of a hospital is spent on medicines. To minimize the inventory investment, the hospital management may like to keep the medicines inventory low, as medicines are perishable items. The main aim of each and every hospital is to provide better services to the patients under certain limited resources. To achieve the satisfactory level of health care services to outdoor patients, a hospital has to keep eye on the wastage of medicines because expiry date of medicines causes a great loss of money though it was limited and allocated for a particular period of time. The objectives of this study are to identify the categories of medicines requiring incentive managerial control. In this paper, to minimize the total inventory cost and the cost associated with the wastage of money due to expiry of medicines, an inventory control model is used as an estimation tool and then nonlinear programming technique is used under limited budget and fixed number of orders to be placed in a limited time period. Numerical computations have been given and shown that by using scientific methods in hospital services, we can give more effective way of inventory management under limited resources and can provide better health care services. The secondary data has been collected from a hospital to give empirical evidence.

Keywords: ABC-VED inventory classification, multi item inventory problem, nonlinear programming technique, optimization of EOQ

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, lévy flight distribution, optimization, improved multi–objective firefly algorithms, Pareto optimal

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Authors: Wu Xiaojun, Liu Ruiping, Yu Xingzhan, Wu Qian

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In precision grinding, utilizing the elastic matrix ball has higher processing efficiency and better superficial quality than traditional grinding. The diversity of characteristics which elastic abrasive tool contact with bend surface results in irregular wear abrasion，and abrasive tool machining status get complicated. There is no theoretical interpretation that parameters affect the grinding accuracy.Aiming at corrosion resistance, wear resistance and other characteristics of M 300 material, it is often used as a material on aerospace precision components. The paper carried out grinding and polishing experiments by using material of M 300,to theoretically show the relationship between stress magnitude and grinding efficiency，and predict the optimal combination of grinding parameter for effective grinding, just for the high abrasion resistance features of M 300, analyzing the micro-contact of elastic ball abrasive tool (Whetstone), using mathematical methods deduce the functional relationship between residual peak removal rate and the main parameters which impact the grinding accuracy on the plane case.Thus laying the foundation for the study of elastic abrasive prediction and compensation.

Keywords: flexible abrasive tool, polishing parameters, Hertz theory, removal rate

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Authors: Ahmed Ishtiaq, Maeeda Khalid, Umair Sajjad

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In the fast-moving world, information is the key to success. If information is easily available, then it makes work easy. The Internet is the biggest collection and source of information nowadays, and with every single day, the data on internet increases, and it becomes difficult to find required data. Everyone wants to make his/her website at the top of search results. This can be possible when you have applied some techniques of SEO inside your application or outside your application, which are two types of SEO, onsite and offsite SEO. SEO is an abbreviation of Search Engine Optimization, and it is a set of techniques, methods to increase users of a website on World Wide Web or to rank up your website in search engine indexing. In this paper, we have compared different techniques of Onpage and Offpage SEO, and we have suggested many things that should be changed inside webpage, outside web page and mentioned some most powerful and search engine considerable elements and techniques in both types of SEO in order to gain high ranking on Search Engine.

Keywords: auto-suggestion, search engine optimization, SEO, query, web mining, web crawler

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Authors: Jung-Ho Moon, Tae Kwon Ha

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In the present study, the effect of Si, Al, Ti, Zr, and Nb addition on the microstructure and hot workability of cast M42 tool steels, basically consisting of 1.0C, 0.2Mn, 3.8Cr, 1.5W, 8.5Co, 9.2Mo, and 1.0V in weight percent has been investigated. Tool steels containing Si of 0.25 and 0.5 wt.%, Al of 0.06 and 0.12 wt.%, Ti of 0.3 wt.%, Zr of 0.3 wt.%, and Nb of 0.3 wt.% were cast into ingots of 140 mm´ 140 mm´ 330 mm by vacuum induction melting. After solution treatment at 1150°C for 1.5 hrs. followed by furnace cooling, hot rolling at 1180 °C was conducted on the ingots. Addition of titanium, zirconium and niobium was found to retard the decomposition of the eutectic carbides and result in the deterioration of hot workability of the tool steels, while addition of aluminium and silicon showed relatively well decomposed carbide structure and resulted in sound hot rolled plates.

Keywords: high speed steels, alloying elements, eutectic carbides, microstructure, hot workability

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Authors: Mansour H. Alkmim, Adriano T. Fabro, Marcus V. G. De Morais

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In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of an undamped primary system under white noise excitation. Finally, a numerical example considering a simplified wind turbine model is given to illustrate the efficacy of the TLCD. Results from the random vibration analysis are shown for four types of random excitation wind model where the response PSDs obtained showed good vibration attenuation.

Keywords: generalized pattern search, parameter optimization, random vibration analysis, vibration suppression

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Authors: Yoshio Kurosawa, Takao Yamaguchi

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High frequency automotive interior noise above 500 Hz considerably affects automotive passenger comfort. To reduce this noise, sound insulation material is often laminated on body panels or interior trim panels. For a more effective noise reduction, the sound reduction properties of this laminated structure need to be estimated. We have developed a new calculate tool that can roughly calculate the sound absorption and insulation properties of laminate structure and handy for designers. In this report, the outline of this tool and an analysis example applied to floor mat are introduced.

Keywords: automobile, acoustics, porous material, transfer matrix method

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Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

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Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

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Authors: Michael R. Phangtriastu, Herriyandi Herriyandi, Diaz D. Santika

Abstract:

This paper presents a comparison of the implementation of metaheuristic algorithms to train the antecedent parameters and consequence parameters in the adaptive network-based fuzzy inference system (ANFIS). The algorithms compared are genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC). The objective of this paper is to benchmark well-known metaheuristic algorithms. The algorithms are applied to several data set with different nature. The combinations of the algorithms' parameters are tested. In all algorithms, a different number of populations are tested. In PSO, combinations of velocity are tested. In ABC, a different number of limit abandonment are tested. Experiments find out that ABC is more reliable than other algorithms, ABC manages to get better mean square error (MSE) than other algorithms in all data set.

Keywords: ANFIS, artificial bee colony, genetic algorithm, metaheuristic algorithm, particle swarm optimization

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

Abstract:

A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Karim Akkouche, Amine Nekmouche, Leyla Bouzid

Abstract:

This study focuses on the development of a multifunctional Expert System (ES) called post-seismic damage inspection tool (PSDIT), a powerful tool which allows the evaluation, the processing, and the archiving of the collected data stock after earthquakes. PSDIT can be operated by two user types; an ordinary user (ingineer, expert, or architect) for the damage visual inspection and an administrative user for updating the knowledge and / or for adding or removing the ordinary user. The knowledge acquisition is driven by a hierarchical knowledge model, the Information from investigation reports and those acquired through feedback from expert / engineer questionnaires are part.

Keywords: .disaster, damaged structures, damage assessment, expert system

Procedia PDF Downloads 82