Search results for: data center optimization

Authors: Ikram Slamani, Hicheme Ferdjani

Abstract:

This study focuses on analyzing a Griffith crack situated at the center of an infinite strip. The problem is reformulated as a hyper-singular integral equation and solved numerically using second-order Chebyshev polynomials. The primary objective is to calculate the stress intensity factor in mode 1, denoted as K1. The obtained results reveal the influence of the strip width and crack length on the stress intensity factor, assuming stress-free edges. Additionally, a comparison is made with relevant literature to validate the findings.

Keywords: center crack, Chebyshev polynomial, hyper singular integral equation, Griffith, infinite strip, stress intensity factor

Procedia PDF Downloads 142

Authors: Yasin Ibrahim, Hisham Almohandes, Chia Hsu, Regina Baronia, Jesse Worsham, Sara Abdelgawad, Mansour Shawky, Mohammed Abdelfattah, Nesif Alhemiary

Abstract:

Background: The matrix model (MM) is an evidence-based program for treating substance use disorders. Since first translated into Arabic in 2010, the MM has been gaining popularity in Arabic countries. However, there is no published data as pertains to its efficacy and feasibility in Arabic communities. Here we aimed at exploring providers’ perspectives on its feasibility and efficacy. Methods: Eight addiction treatment centers from four Arabic countries, namely Egypt, Kingdom of Saudi Arabia, the United Arab Emirates, and Iraq, were contacted via email. They were asked to fill in a 21-item questionnaire. Results: Matrix model continues to be utilized in 6 out of the 8 contacted programs. One center in Egypt has discontinued the MM as the providers felt it was not suitable for substance disorders other than stimulants, which are not common in Egypt. Baghdad University Medical Center has substituted MM with Colombo Program as there have been more training opportunities available for it. Data showed wide variability in regards to number of clients treated with the MM (from 300 to 2500). The Arabic version was utilized for training providers in 5 out of the 8 centers while the providers of the other 3 have been trained in the United States. All providers reported that MM made their job significantly easier, and seven providers believed that MM has favorably affected the relapse rate. In all of the six centers, MM is being utilized for many substance use disorders in addition to stimulant use disorders. Reported challenges included the acceptability of patients and their families, difficulty understanding some concepts, and high drop rates in some centers. Conclusion: Matrix model seems to be a valuable modality for the treatment of substance use disorders in Arabic countries. It has its own challenges and limitations that call for more culturally adapted versions.

Keywords: addiction, Arabic countries, developing countries, matrix model

Procedia PDF Downloads 154

Authors: D. Tohlob, E. Abo Hashem, N. Ghareeb, M. Ghanem, R. Elfarahaty, S. A. Roberts, P. Pemberton, L. Mohiyiddeen, W. G. Newman

Abstract:

Gonadotropin stimulation is used in females undergoing assisted reproductive treatment for ovulation induction, but ovarian response is variable and unpredictable in these women. More effective protocols and individualization of treatment are needed to increase the success rate of IVF/ICSI cycles. We genotyped seven variants reported in previous studies to be associated with ovarian response (number of ova retrieved and total gonadotropin dose) in women undergoing IVF treatment including FSHR variants Asn 680 Ser (c.2039 A > G), Thr 307 Ala (c. 919 > A), -29 G > A, HRG c.610 C > T gene, BMP15 -9 C > G, AMH Ile 49 Ser (c.146 G > T), and AMHR -489A˃G in 118 Egyptian females attending Mansoura Integrated Fertility Center in Egypt, these females were undergoing their first cycle of controlled ovarian hyper stimulation for IVF/ICSI treatment. They were analyzed by TaqMan allelic discrimination assay in Manchester Center of Genomic Medicine. We found no evidence of any significant difference (p value < 0.05) in the number of eggs retrieved or the gonadotropin dose used between individuals in all genotypes except for HRG c.610 C > T gene polymorphism where regression analysis gives a p value of 0.04 with a fewer eggs number in TT genotyped females. These results indicate that these variants do not provide sufficient clinically relevant data to individualize the treatment protocols.

Keywords: controlled ovarian hyperstimulation, gene variants, ovarian response, assisted reproduction

Procedia PDF Downloads 316

Authors: Chao-Ton Su, Li-Fei Chen

Abstract:

The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

Procedia PDF Downloads 145

Authors: Touil Djamal, Fergani Zineb

Abstract:

In this study, an Organic Rankine Cycle (ORC) with Cyclohexane working fluid is proposed for cogeneration in the cement industry. In this regard: first, a parametric study is conducted to evaluate the effects of some key parameters on the system performances. Next, single and multi-objective optimizations are performed to achieve the system optimal design. The optimization considers the exergy efficiency, the cost per exergy unit and the environmental impact of the net produced power as objective functions. Finally, exergy, exergoeconomic and exergoenvironmental analysis of the cycle is carried out at the optimum operating conditions. The results show that the turbine inlet pressure, the pinch point temperature difference and the heat transfer fluid temperature have significant effects on the performances of the ORC system.

Keywords: organic rankine cycle, multi-objective optimization, exergy, exergoeconomic, exergoenvironmental, multi-objective optimisation, organic rankine cycle, cement plant

Procedia PDF Downloads 278

Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

Abstract:

This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

Procedia PDF Downloads 574

Authors: Hakim T. Kadhim, Faris A. Jabbar, Aldo Rona, Audrius Bagdanaviciu

Abstract:

Computer-based optimization techniques can be employed to improve the efficiency of energy conversions processes, including reducing the aerodynamic loss in a thermal power plant turbomachine. In this paper, towards mitigating secondary flow losses, a design optimization workflow is implemented for the casing geometry of a 1.5 stage axial flow turbine that improves the turbine isentropic efficiency. The improved turbine is used in an open thermodynamic gas cycle with regeneration and cogeneration. Performance estimates are obtained by the commercial software Cycle – Tempo. Design and off design conditions are considered as well as variations in inlet air temperature. Reductions in both the natural gas specific fuel consumption and in CO₂ emissions are predicted by using the gas turbine cycle fitted with the new casing design. These gains are attractive towards enhancing the competitiveness and reducing the environmental impact of thermal power plant.

Keywords: axial flow turbine, computational fluid dynamics, gas turbine power plant, optimization

Procedia PDF Downloads 159

Authors: Young Min Kim, Jeong Lak Sohn, Eui Soo Yoon

Abstract:

This study describes the optimization of supercritical carbon dioxide (S-CO2) power cycle for recovering waste heat from a gas turbine. An S-CO2 cycle that recovers heat from small industrial and aeroderivative gas turbines can outperform a steam-bottoming cycle despite its simplicity and compactness. In using S-CO2 power cycles for waste heat recovery, a split cycle was studied to maximize the net output power by incorporating the utilization efficiency of the waste heat (lowering the temperature of the exhaust gas through the heater) along with the thermal efficiency of the cycle (minimizing the temperature difference for the heat transfer, exergy loss). The cooling condition of the S-CO2 WHR system has a great impact on the performance and the optimum low pressure of the system. Furthermore, the optimum high pressure of the S-CO2 WHR systems for the maximum power from the given heat sources is dependent on the temperature of the waste heat source.

Keywords: exergy loss, gas turbine, optimization, supercritical CO2 power cycle, split cycle, waste heat recovery

Procedia PDF Downloads 348

Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

Abstract:

The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

Procedia PDF Downloads 409

Authors: Maria L. McLeod

Abstract:

This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers –The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, ten from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting repeated use of specific metaphors and tropes while charting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals with university affiliations, that emphasizes an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. Thus, the use of anecdotal evidence presented in patient narratives could be perceived as being in conflict with this evidence-based model, as the patient stories are not an accurate representation of scientific outcomes related to developing cancer, cancer reoccurrence, or cancer outcomes. The representative patient narratives tend to exclude or downplay adverse responses to treatment, survival rates, integrative and/or complementary cancer treatments, cancer prevention and causes, and barriers to treatment, such as the limitation of insurance plans, costs of treatment, and/or other issues related to access, potentially contributing to false narratives and inaccurate notions of cancer prevention, cancer care treatment and the potential for a cure. Both quantitative and qualitative findings demonstrate that cancer patient stories featured on the blogsites of the nation’s top cancer care centers deemphasize patient agency and, instead, emphasize deference and gratitude toward the institutions where the featured patients received treatment. Along these lines, language choices reflect positive framing of the cancer experience. Accompanying portrait photos of healthy appearing subjects as well as positive-framed headlines, subheads, and pull quotes function similarly, reflecting hopeful, transformative experiences and outcomes over hardship and suffering. Although patient narratives include real, factual scientific details and descriptions of actual events, the stories lack references to more negative realities of cancer diagnosis and treatment. Instead, they emphasize the triumph of survival by which the cancer care center, in the savior/hero role, enables the patient’s success, represented as a cathartic medical journey.

Keywords: cancer framing, cancer stories, medical gaze, patient narratives

Procedia PDF Downloads 160

Authors: Faruk Aras, Melih Inal, Tansel Cinar

Abstract:

The coordination of airport staff especially in the operations and maintenance departments is important for the airport operation. As a result, this coordination will increase the efficiency in all operation. Therefore, a Collaborative Decision-Making (CDM) system targets on improving the overall productivity of all operations by optimizing the use of resources and improving the predictability of actions. Enlarged productivity can be of major benefit for all airport operations. It also increases cost-efficiency. This study explains how predictive maintenance using IoT (Internet of Things), predictive operations and the statistical data such as Mean Time To Failure (MTTF) improves airport terminal operations and utilize airport terminal equipment in collaboration with collaborative decision making system/Airport Operation Control Center (AOCC). Data generated by the predictive maintenance methods is retrieved and analyzed by maintenance managers to predict when a problem is about to occur. With that information, maintenance can be scheduled when needed. As an example, AOCC operator would have chance to assign a new gate that towards to this gate all the equipment such as travellator, elevator, escalator etc. are operational if the maintenance team is in collaboration with AOCC since maintenance team is aware of the health of the equipment because of predictive maintenance methods. Applying predictive maintenance methods based on analyzing the health of airport terminal equipment dramatically reduces the risk of downtime by on time repairs. We can classify the categories as high priority calls for urgent repair action, as medium priority requires repair at the earliest opportunity, and low priority allows maintenance to be scheduled when convenient. In all cases, identifying potential problems early resulted in better allocation airport terminal resources by AOCC.

Keywords: airport, predictive maintenance, collaborative decision-making system, Airport Operation Control Center (AOCC)

Procedia PDF Downloads 364

Authors: Ritesh Joshi, Kishan Fuse, Gopal Zinzala, Nishit Nirmal

Abstract:

Ti-6Al-4V is a titanium alloy having high strength, low weight and corrosion resistant which is a required characteristic for a material to be used in aerospace industry. Titanium, being a hard alloy is difficult to the machine via conventional methods, so it is a call to use non-conventional processes. In present work, the effects on Ti-6Al-4V by drilling a hole of Ø 6 mm using copper (99%) electrode in Electric Discharge Machining (EDM) process is analyzed. Effect of various input parameters like peak current, pulse-on time and pulse-off time on output parameters viz material removal rate (MRR) and electrode wear rate (EWR) is studied. Multi-objective optimization technique Grey relational analysis is used for process optimization. Experiments are designed using an L9 orthogonal array. ANOVA is used for finding most contributing parameter followed by confirmation tests for validating the results. Improvement of 7.45% in gray relational grade is observed.

Keywords: ANOVA, electric discharge machining, grey relational analysis, Ti-6Al-4V

Procedia PDF Downloads 362

Authors: Desalegn Feyissa Desu

Abstract:

Drug therapy problem is a significant challenge to provide high quality health care service for the patients. It is associated with morbidity, mortality, increased hospital stay, and reduced quality of life. Moreover, pediatric patients are quite susceptible to drug therapy problems. Thus this study aimed to assess drug therapy problem and its contributing factors among pediatric patients diagnosed with infectious disease admitted to pediatric ward of Jimma university medical center, from April 1 to June 30, 2018. Prospective observational study was conducted among pediatric patients with infectious disease admitted from April 01 to June 30, 2018. Drug therapy problems were identified by using Cipolle’s and strand’s drug related problem classification method. Patient’s written informed consent was obtained after explaining the purpose of the study. Patient’s specific data were collected using structured questionnaire. Data were entered into Epi data version 4.0.2 and then exported to statistical software package version 21.0 for analysis. To identify predictors of drug therapy problems occurrence, multiple stepwise backward logistic regression analysis was done. The 95% CI was used to show the accuracy of data analysis and statistical significance was considered at p-value < 0.05. A total of 304 pediatric patients were included in the study. Of these, 226(74.3%) patients had at least one drug therapy problem during their hospital stay. A total of 356 drug therapy problems were identified among two hundred twenty six patients. Non-compliance (28.65%) and dose too low (27.53%) were the most common type of drug related problems while disease comorbidity [AOR=3.39, 95% CI= (1.89-6.08)], Polypharmacy [AOR=3.16, 95% CI= (1.61-6.20)] and more than six days stay in hospital [AOR=3.37, 95% CI= (1.71-6.64) were independent predictors of drug therapy problem occurrence. Drug therapy problems were common in pediatric patients with infectious disease in the study area. Presence of comorbidity, polypharmacy and prolonged hospital stay were the predictors of drug therapy problem in study area. Therefore, to overcome the significant gaps in pediatric pharmaceutical care, clinical pharmacists, Pediatricians, and other health care professionals have to work in collaboration.

Keywords: drug therapy problem, pediatric, infectious disease, Ethiopia

Procedia PDF Downloads 152

Authors: Zhoucheng Bao, Haiyan Zhu, Tingting Pang, Zuling Wang

Abstract:

This paper proposes a multi-population DE with adaptive mutation and local search for global optimization, named AMMADE. In order to better coordinate the cooperation between the populations and the rational use of resources. In AMMADE, the population is divided based on the Euclidean distance sorting method at each generation to appropriately coordinate the cooperation between subpopulations and the usage of resources, such that the best-performed subpopulation will get more computing resources in the next generation. Further, an adaptive local search strategy is employed on the best-performed subpopulation to achieve a balanced search. The proposed algorithm has been tested by solving optimization problems taken from CEC2014 benchmark problems. Experimental results show that our algorithm can achieve a competitive or better than related methods. The results also confirm the significance of devised strategies in the proposed algorithm.

Keywords: differential evolution, multi-mutation strategies, memetic algorithm, adaptive local search

Procedia PDF Downloads 155

Authors: Sara A. Pakvis, Giulia Scalet, Stefania Marconi, Ferdinando Auricchio, Matthijs Langelaar

Abstract:

In recent developments in the field of multi-material additive manufacturing, differences in material properties are exploited to create printed shape-memory structures, which are referred to as 4D-printed structures. New printing techniques allow for the deliberate introduction of prestresses in the specimen during manufacturing, and, in combination with the right design, this enables new functionalities. This research focuses on bi-polymer 4D-printed structures, where the transformation process is based on a heat-induced glass transition in one material lowering its Young’s modulus, combined with an initial prestress in the other material. Upon the decrease in stiffness, the prestress is released, which results in the realization of an essentially pre-programmed deformation. As the design of such functional multi-material structures is crucial but far from trivial, a systematic methodology to find the design of 4D-printed structures is developed, where a finite element model is combined with a density-based topology optimization method to describe the material layout. This modeling approach is verified by a convergence analysis and validated by comparing its numerical results to analytical and published data. Specific aspects that are addressed include the interplay between the definition of the prestress and the material interpolation function used in the density-based topology description, the inclusion of a temperature-dependent stiffness relationship to simulate the glass transition effect, and the importance of the consideration of geometric nonlinearity in the finite element modeling. The efficacy of topology optimization to design 4D-printed structures is explored by applying the methodology to a variety of design problems, both in 2D and 3D settings. Bi-layer designs composed of thermoplastic polymers are printed by means of the fused deposition modeling (FDM) technology. Acrylonitrile butadiene styrene (ABS) polymer undergoes the glass transition transformation, while polyurethane (TPU) polymer is prestressed by means of the 3D-printing process itself. Tests inducing shape transformation in the printed samples through heating are performed to calibrate the prestress and validate the modeling approach by comparing the numerical results to the experimental findings. Using the experimentally obtained prestress values, more complex designs have been generated through topology optimization, and samples have been printed and tested to evaluate their performance. This study demonstrates that by combining topology optimization and 4D-printing concepts, stimuli-responsive structures with specific properties can be designed and realized.

Keywords: 4D-printing, glass transition, shape memory polymer, topology optimization

Procedia PDF Downloads 207

Authors: Fatma Kürüm Varolgüneş, Fatih Canan

Abstract:

Mardin is one of the unique cities in Turkey with its rich cultural and historical heritage. Mardin’s traditional dwellings have been affected both by natural data such as climate and topography and by cultural data like lifestyle and belief. However, in the new settlements, housing is formed with modern approaches and unsuitable forms clashing with Mardin’s culture and environment. While the city is expanding, traditional textures are ignored. Thus, traditional settlements are losing their identity and are vanishing because of the rapid change and transformation. The main aim of this paper is to determine the physical and social data needed to define the characteristic features of Mardin’s old and new settlements. In this context, based on social and cultural data, old and new settlement formations of Mardin have been investigated from various aspects. During this research, the following methods have been utilized: observations, interviews, public surveys, literature review, as well as site examination via maps, photographs and questionnaire methodology. In conclusion, this paper focuses on how changes in the physical forms of cities affect the typology and the identity of cities, as in the case of Mardin.

Keywords: urban and local identity, historical city center, traditional settlements, Mardin

Procedia PDF Downloads 327

Authors: Konstantinos Tolidis

Abstract:

The mountains are amongst the most fragile environments in the world. The world’s mountain areas cover 24% of the Earth’s land surface and are home to 12% of the global population. A further 14% of the global population is estimated to live in the vicinity of their surrounding areas. As urbanization continues to increase in the world, the mountains are also key centers for recreation and tourism; their attraction is often heightened by their remarkably high levels of biodiversity. Due to the fact that the features in mountain areas vary spatially (development degree, human geography, socio-economic reality, relations of dependency and interaction with other areas-regions), the spatial planning on these areas consists of a crucial process for preserving the natural, cultural and human environment and consists of one of the major processes of an integrated spatial policy. This research has been focused on the spatial decision problem of land use allocation optimization which is an ordinary planning problem on the mountain areas. It is a matter of fact that such decisions must be made not only on what to do, how much to do, but also on where to do, adding a whole extra class of decision variables to the problem when combined with the consideration of spatial optimization. The utility of optimization as a normative tool for spatial problem is widely recognized. However, it is very difficult for planners to quantify the weights of the objectives especially when these are related to mountain areas. Furthermore, the land use allocation optimization problems at mountain areas must be addressed not only by taking into account the general development objectives but also the spatial objectives (e.g. compactness, compatibility and accessibility, etc). Therefore, the main research’s objective was to approach the land use allocation problem by utilizing a hybrid meta-heuristic optimization technique tailored to the mountain areas’ spatial characteristics. The results indicates that the proposed methodological approach is very promising and useful for both generating land use alternatives for further consideration in land use allocation decision-making and supporting spatial management plans at mountain areas.

Keywords: multiobjective land use allocation, mountain areas, spatial planning, spatial decision making, meta-heuristic methods

Procedia PDF Downloads 345

Authors: Efrain Rodriguez, Sergio Pertuz, Cristhian Riano

Abstract:

Tool-path generation is an essential step in the FFF (Fused Filament Fabrication)-based Additive Manufacturing (AM) process planning. In the manufacture of a mechanical part by using additive processes, high resource consumption and prolonged production times are inherent drawbacks of these processes mainly due to non-optimized tool-path generation. In this work, we propose a heuristic-search intelligent algorithm-based approach for optimized tool-path generation for FFF-based AM. The main benefit of this approach is a significant reduction of travels without material deposition when the AM machine performs moves without any extrusion. The optimization method used reduces the number of travels without extrusion in comparison with commercial software as Slic3r or Cura Engine, which means a reduction of production time.

Keywords: additive manufacturing, tool-path optimization, fused filament fabrication, process planning

Procedia PDF Downloads 441

Authors: Lahoucine Zaama, Sanae Douama

Abstract:

In this work, we present the results of a dosimetry study in a Moroccan radiology department . The results are compared with those of a similar study in France. Furthermore, it determines the coefficient of transmission of the lead sheets of different thicknesses depending on the voltage (KV) in a direct exposure. The objective of this study is to choose the thickness of the radiation means to determine the leaf sample sealed with the smallest percentage value radiation transmission, and that in the context of optimization. Thus the comparison among the studies is essential to consider conduct studies and research in this framework to achieve the goal of optimization.

Keywords: radiology, dosimetry, radiation, dose, transmission

Procedia PDF Downloads 493

Authors: Mustahsan Mir, Ahmed Hassanin, Mohammed A. Al-Saleh

Abstract:

The layout optimization of building blocks of unequal areas has applications in many disciplines including VLSI floorplanning, macrocell placement, unequal-area facilities layout optimization, and plant or machine layout design. A number of heuristics and some analytical and hybrid techniques have been published to solve this problem. This paper presents an efficient high-quality building-block layout design technique especially suited for solving large-size problems. The higher efficiency and improved quality of optimized solutions are made possible by introducing the concept of Promising Infant Clusters in a constructive placement procedure. The results presented in the paper demonstrate the improved performance of the presented technique for benchmark problems in comparison with published heuristic, analytic, and hybrid techniques.

Keywords: block layout problem, building-block layout design, CAD, optimization, search techniques

Procedia PDF Downloads 384

Authors: Ibrahim Cicek, Melike Nikbay

Abstract:

Electrically propelled vehicles, either road or aerial vehicles are studied on contemporarily for their robust maneuvers and cost-efficient transport operations. The main power generating systems of such vehicles electrified by selecting proper components and assembled as e-powertrain. Generally, e-powertrain components selected considering the target performance requirements. Since the main component of propulsion is the drive unit, e-motor control system is subjected to achieve the performance targets. In this paper, the optimization of e-motor control parameters studied by Integral Squared Method (ISE). The overall aim is to minimize power consumption of such vehicles depending on mission profile and maintaining smooth maneuvers for passenger comfort. The sought-after values of control parameters are computed using the Optimal Control Theory. The system is modeled as a closed-loop linear control system with calibratable parameters.

Keywords: optimization, e-powertrain, optimal control, electric vehicles

Procedia PDF Downloads 129

Authors: Arkadiusz Mezyk, Wojciech Klein, Mariusz Pawlak, Jacek Gnilka

Abstract:

The aortic heart valve stents should fulfill many criterions. These criteria have a strong impact on the geometrical shape of the stent. Usually, the final construction of stent is a result of many year experience and knowledge. Depending on patents claims, different stent shapes are produced by different companies. This causes difficulties for biomechanics engineers narrowing the domain of feasible solutions. The paper present optimization method for stent geometry defining by a specific analytical equation based on various mathematical functions. This formula was implemented as APDL script language in ANSYS finite element environment. For the purpose of simulation tests, a few parameters were separated from developed equation. The application of the genetic algorithms allows finding the best solution due to selected objective function. Obtained solution takes into account parameters such as radial force, compression ratio and coefficient of expansion on the transverse axial.

Keywords: aortic stent, optimization process, geometry, finite element method

Procedia PDF Downloads 278

Authors: Zhongjie Yu, Hancheng Yu

Abstract:

In this paper, we propose an effective method to detect concentric circles with imperfect edges. First, the gradient of edge pixel is coded and a 2-D lookup table is built to speed up normal generation. Then we take an accumulator to estimate the rough center and collect plausible edges of concentric circles through gradient and distance. Later, we take the contour-based method, which takes the contour and edge intersection, to pre-classify the edges. Finally, we use the extended RANSAC method to find all the candidate circles. The center of concentric circles is determined by the two circles with the highest concentricity. Experimental results demonstrate that the proposed method has both good performance and accuracy for the detection of concentric circles.

Keywords: concentric circle detection, gradient, contour, edge pre-classification, RANSAC

Procedia PDF Downloads 129

Authors: Mrinmoy Majumder, Apu Kumar Saha

Abstract:

The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers.

Keywords: power allocation, optimization problem, neural networks, environmental and ecological engineering

Procedia PDF Downloads 478

Authors: Hamid R. Lashgarian Azad, Seyed N. Shetab Boushehri

Abstract:

Wireless sensor networks (WSN) have become progressively popular due to their wide range of applications. Wireless Sensor Network is made of numerous tiny sensor nodes that are battery-powered. It is a very significant problem to maximize the lifetime of wireless sensor networks. In this paper, we propose a two-stage protocol based on an imperialist competitive algorithm (2S-ICA) to solve a sensor network optimization problem. The energy of the sensors can be greatly reduced and the lifetime of the network reduced by long communication distances between the sensors and the sink. We can minimize the overall communication distance considerably, thereby extending the lifetime of the network lifetime through connecting sensors into a series of independent clusters using 2SICA. Comparison results of the proposed protocol and LEACH protocol, which is common to solving WSN problems, show that our protocol has a better performance in terms of improving network life and increasing the number of transmitted data.

Keywords: wireless sensor network, imperialist competitive algorithm, LEACH protocol, k-means clustering

Procedia PDF Downloads 102

Authors: Shraddha Digole, Swarali Hingse, Uday Annapure

Abstract:

Mycophenolic acid (MPA) is an immunosuppressant; produced by Penicillium Sp. Box-Behnken statistical experimental design was employed to optimize the condition of Penicillium brevicompactum NRRL 2011 for mycophenolic acid (MPA) production. Initially optimization of various physicochemical parameters and media components was carried out using one factor at a time approach and significant factors were screened by Taguchi L-16 orthogonal array design. Taguchi design indicated that glucose, KH2PO4 and MgSO4 had significant effect on MPA production. These variables were selected for further optimization studies using Box-Behnken design. Optimised fermentation condition, glucose (60 g/L), glycine (28 g/L), L-leucine (1.5g/L), KH2PO4 (3g/L), MgSO4.7H2O (1.5g/L), increased the production of MPA from 170 mg/L to 1032.54 mg/L. Analysis of variance (ANOVA) showed a high value of coefficient of determination R2 (0.9965), indicating a good agreement between experimental and predicted values and proves validity of the statistical model.

Keywords: Box-Behnken design, fermentation, mycophenolic acid, Penicillium brevicompactum

Procedia PDF Downloads 449

Authors: Maximilian Winkens, Peter Nyhuis

Abstract:

Components with sensory properties such as gentelligent components developed at the Collaborative Research Center 653 offer a new angle on the full utilization of the remaining service life in case of a preventive maintenance. The developed methodology of component status driven maintenance analyses the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance called for in this case. The procedure is derived from the case-based reasoning method and will be elucidated in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.

Keywords: gentelligent component, preventive maintenance, case-based reasoning, sensory

Procedia PDF Downloads 361

Authors: Mamidi Ramakrishna Rao

Abstract:

Doubly-fed induction generators (DFIG) due to their advantages like speed variation and four-quadrant operation, find its application in wind turbines. DFIG besides supplying power to the grid has to support reactive power (kvar) under grid voltage variations, should contribute minimum fault current during faults, have high efficiency, minimum weight, adequate rotor protection during crow-bar-operation from +20% to -20% of rated speed.  To achieve the optimum performance, a good electromagnetic design of DFIG is required. In this paper, a simple and heuristic global optimization – Differential Evolution has been used. Variables considered are lamination details such as slot dimensions, stack diameters, air gap length, and generator stator and rotor stack length. Two operating conditions have been considered - voltage and speed variations. Constraints included were reactive power supplied to the grid and limiting fault current and torque. The optimization has been executed separately for three objective functions - maximum efficiency, weight reduction, and grid fault stator currents. Subsequent calculations led to the conclusion that designs determined through differential evolution help in determining an optimum electrical design for each objective function.

Keywords: design optimization, performance, DFIG, differential evolution

Procedia PDF Downloads 148

Authors: Shashikant Kumar, Chandraraj K.

Abstract:

Perennial grasses have presented interesting choices in the current demand for renewable and sustainable energy sources to alleviate the load of the global energy problem. The perennial grass Napier grass (Pennisetum purpureum Schumach) is a promising feedstock for the production of cellulosic ethanol. The conversion of biomass into glucose and xylose is a crucial stage in the production of bioethanol, and it necessitates optimal pretreatment. Alkali treatment, among the several pretreatments available, effectively reduces lignin concentration and crystallinity of cellulose. Response surface methodology was used to optimize the alkali pretreatment of Napier grass for maximal reducing sugar production. The combined effects of three independent variables, viz. sodium hydroxide concentration, temperature, and reaction time, were studied. A second-order polynomial equation was used to fit the observed data. Maximum reducing sugar (590.54 mg/g) was obtained under the following conditions: 1.6 % sodium hydroxide, a reaction period of 30 min., and 120˚C. The results showed that Napier grass is a desirable feedstock for bioethanol production.

Keywords: Napier grass, optimization, pretreatment, sodium hydroxide

Procedia PDF Downloads 504

Authors: Vignesh Ratnaraj, Daniel Marascia, Kelly Ruecker

Abstract:

Purpose: Pulmonary embolism (PE) is a major cause of morbidity and mortality in trauma patients. Data suggests PE is occurring earlier in trauma patients, with attention being turned to possible de novo events. Here, we examine the incidence of early PE at a level 1 trauma center and examine the relationship with a chest injury. Method: A retrospective analysis was performed from a prospective trauma registry at a level 1 trauma center. All patients admitted from 1 January 2010 to 30 June 2019 diagnosed with PE following trauma were included. Early PE was considered a diagnosis within 72 hours of admission. The severity of the chest injury was determined by the Abbreviated Injury Score (AIS). Analysis of severe chest injury and incidence of early PE was performed using chi-square analysis. Sub-analysis on the timing of PE and PE location was also performed using chi-square analysis. Results: Chest injury was present in 125 of 184 patients diagnosed with PE. Early PE occurred in 28% (n=35) of patients with a chest injury, including 24.39% (n=10) with a severe chest injury. Neither chest injury nor severe chest injury determined the presence of early PE (p= > 0.05). Sub-analysis showed a trend toward central clots in early PE (37.14%, n=13) compared to late (27.78%, n=25); however, this was not found to be significant (p= > 0.05). Conclusion: PE occurs early in trauma patients, with almost one-third being diagnosed before 72 hours. This analysis does not support the paradigm that chest injury, nor severe chest injury, results in statistically significant higher rates of early PE. Interestingly, a trend toward early central PE was noted in those suffering chest trauma.

Keywords: trauma, PE, chest injury, anticoagulation

Procedia PDF Downloads 99