Search results for: multi criteria evaluation

Authors: Uroš Durlević, Ivan Novković, Nina Čegar, Stefanija Stojković

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Snow avalanches represent one of the most dangerous natural phenomena in mountain regions worldwide. Material and human casualties caused by snow avalanches can be very significant. In this study, using geographic information systems and remote sensing, the natural conditions of the Šar Mountains were analyzed for geospatial modeling of dry slab avalanches. For this purpose, the Fuzzy Analytic Hierarchy Process (FAHP) multi-criteria analysis method was used, within which fifteen environmental criteria were analyzed and evaluated. Based on the existing analyzes and results, it was determined that a significant area of the Šar Mountains is very highly susceptible to the occurrence of dry slab avalanches. The obtained data can be of significant use to local governments, emergency services, and other institutions that deal with natural disasters at the local level. To our best knowledge, this is one of the first research in the Republic of Serbia that uses the FAHP method for geospatial modeling of dry slab avalanches.

Keywords: GIS, FAHP, Šar Mountains, snow avalanches, environmental protection

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Authors: Mohammad Reza Ostad Ali Naghi Kashani, Esfanji Elia

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Nowadays, the amounts of companies which tend to have an Enterprise Resource Planning (ERP) application are increasing particularly in developing countries like Iran. ERP projects are expensive, time consuming, and complex, in addition the failure rate is high among these projects. It is important to know whether these projects could meet their goals or not. Furthermore, the area which should be improved should be identified. In this paper we made a framework to evaluate ERP projects success implementation. First, based on literature review we made a framework based on BSC model, financial, customer, processes, learning and knowledge, because of the importance of change management it was added to model. Then an organization was divided in three layers. We choose corporate, managerial, and operational levels. Then to find criteria to assess each aspect, we use Delphi method in two rounds. And for the second round we made a questionnaire and did some statistical tasks on them. Based on the statistical results some of them are accepted and others are rejected.

Keywords: ERP, BSC, ERP project evaluation, IT projects

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Authors: Rong Guo, Mengshi Huang, Yujing Bai

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With the rapid development of urbanization, the urban population increases and urban sprawl appeared. And these issues led to a sharp deterioration of the ecological environment. So, the urban ecological security evaluation was imminent. The weights identify of index was a key step of the research of ecological security evaluation. The AHP was widely used in the extensive research of weights identify of ecological security index. The characteristics of authority and quantitative can fully reflect the views of relevant experts. On the basis of building the ecological security evaluation index of Harbin, the paper combed and used the basic principle of the AHP, and calculated the weights of Harbin ecological security evaluation index through the process of the expert opinions “summary-feedback-summary”. And lay a foundation of future study of Harbin ecological security index, and guide the quantitative evaluation of Harbin ecological security.

Keywords: AHP, ecological security, evaluation Index, weights identify, harbin

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Authors: Kasirga Yildirak, Ismail Gur

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We propose a model to measure hail risk of an Agricultural Insurance portfolio. Hail is one of the major catastrophic event that causes big amount of loss to an insurer. Moreover, it is very hard to predict due to its strange atmospheric characteristics. We make use of parcel based claims data on apricot damage collected by the Turkish Agricultural Insurance Pool (TARSIM). As our ultimate aim is to compute the loadings assigned to specific parcels, we build a portfolio risk model that makes use of PD and the severity of the exposures. PD is computed by Spherical-Linear and Circular –Linear regression models as the data carries coordinate information and seasonality. Severity is mapped into integer brackets so that Probability Generation Function could be employed. Individual regressions are run on each clusters estimated on different criteria. Loss distribution is constructed by Panjer Recursion technique. We also show that one risk-one crop model can easily be extended to the multi risk–multi crop model by assuming conditional independency.

Keywords: hail insurance, spherical regression, circular regression, spherical clustering

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Authors: Ivanka Valova

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This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

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Authors: Vahidreza Mahmoudabadi, Omid Bahar, Mohammad Kazem Jafari

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In many applied engineering problems, structural analysis is usually conducted by assuming a rigid bed, while imposing the effect of structure bed flexibility can affect significantly on the structure response. This article focuses on investigation and evaluation of the effects arising from considering a soil-structure system in evaluation of dynamic characteristics of a steel structure with respect to elastic and inelastic behaviors. The recorded structure acceleration during Taiwan’s strong Chi-Chi earthquake on different floors of the structure was our evaluation criteria. The respective structure is an eight-story steel bending frame structure designed using a displacement-based direct method assuring weak beam - strong column function. The results indicated that different identification methods i.e. reverse Fourier transform or transfer functions, is capable to determine some of the dynamic parameters of the structure precisely, rather than evaluating all of them at once (mode frequencies, mode shapes, structure damping, structure rigidity, etc.). Response evaluation based on the input and output data elucidated that the structure first mode is not significantly affected, even considering the soil-structure interaction effect, but the upper modes have been changed. Also, it was found that the response transfer function of the different stories, in which plastic hinges have occurred in the structure components, provides similar results.

Keywords: bending steel frame structure, dynamic characteristics, displacement-based design, soil-structure system, system identification

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Authors: M. R. Vaezi, R. Ghasemi, A. Akramizadeh

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Frequency stability of microgrids under islanded operation attracts particular attention recently. A new cooperative frequency control strategy based on centralized multi-agent system (CMAS) is proposed in this study. On this strategy, agents sent data and furthermore each component has its own to center operating decisions (MGCC). After deciding on the information, they are returned. Frequency control strategies include primary and secondary frequency control and disposal of multi-stage load in which this study will also provide a method and algorithm for load shedding. This could also be a big problem for the performance of micro-grid in times of disaster. The simulation results show the promising performance of the proposed structure of the controller based on multi agent systems.

Keywords: frequency control, islanded microgrid, multi-agent system, load shedding

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Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

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Authors: Bryan M. Baltazar, Marjorie V. Remolador, Klathea H. Sevilla, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Biomass energy is a traditional source of sustainable energy, which has been widely used in developing countries. The Philippines, specifically Central Luzon, has an abundant source of biomass. Hence, it could supply abundant agricultural residues (rice husks), as feedstock in a biomass power plant. However, locating a potential site for biomass development is a complex process which involves different factors, such as physical, environmental, socio-economic, and risks that are usually diverse and conflicting. Moreover, biomass distribution is highly dispersed geographically. Thus, this study develops an integrated method combining Geographical Information Systems (GIS) and methods for energy planning; Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP), for locating suitable site for biomass power plant development in Central Luzon, Philippines by considering different constraints and factors. Using MCDA, a three level hierarchy of factors and constraints was produced, with corresponding weights determined by experts by using AHP. Applying the results, a suitability map for Biomass power plant development in Central Luzon was generated. It showed that the central part of the region has the highest potential for biomass power plant development. It is because of the characteristics of the area such as the abundance of rice fields, with generally flat land surfaces, accessible roads and grid networks, and low risks to flooding and landslide. This study recommends the use of higher accuracy resource maps, and further analysis in selecting the optimum site for biomass power plant development that would account for the cost and transportation of biomass residues.

Keywords: analytic hierarchy process, biomass energy, GIS, multi-criteria decision analysis, site suitability analysis

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Authors: Muqaddas Javed, Muhammad Hanif

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The generalized multivariate ratio and regression type estimators for population mean are suggested under multi-phase stratified systematic sampling (MPSSS) using multi auxiliary information. Estimators are developed under the two different situations of availability of auxiliary information. The expressions of bias and mean square error (MSE) are developed. Special cases of suggested estimators are also discussed and simulation study is conducted to observe the performance of estimators.

Keywords: generalized estimators, multi-phase sampling, stratified random sampling, systematic sampling

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Nida Iftikhar, Jamaluddin Thaheem, Bilal Iftikhar

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In the construction industry, adequate and effective decision-making can mean the difference between success and failure. Bidding is the most important element of the construction business since it is a mean by which contractors obtain work. This is probably the only option for any contractor firm to sustain in the market and achieve its objective of earning the profits by winning tenders. The capability to select most appropriate ventures not only defines the success and wellbeing of contractor firms but also their survival and sustainability in the industry. The construction practitioners are usually on their own when it comes to deciding on bidding for a project or not. Usually, experience-based solutions are offered where a lot of subjectivity is involved. This research has been opted considering the local construction industry of Pakistan in order to examine the critical success factors from contractors’ perspective while making bidding decisions, listing and evaluating critical factors in order of their importance, categorization of these factors into decision support & decision oppose groups and to develop a framework to help contractors in the decision-making process. Literature review, questionnaires, and structured interviews are used for identification and quantification of factors affecting bid/no bid decision-making. Statistical methods of ranking analysis and analytical hierarchy process of multi-criteria decision-making method are used for analysis. It is found that profitability, need for work and financial health of client are the most decisive factors in bid/no bid decision-making while project size, project type, fulfilling the tender conditions imposed by the client and relationship, identity & reputation of the client are least impact factors in bid/no bid decision-making. Further, to verify the developed framework, case studies have been conducted to evaluate the bid/no bid decision-making in building procurement. This is the first of its nature study in the context of the local construction industry and recommends using a holistic decision-making framework for such business-critical deliberations.

Keywords: bidding, bid decision-making, construction procurement, contractor

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Authors: Shubham Banerjee

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The paper focuses on, how the business model of the Indian multi brand ecommerce industry is unstable and is headed towards an e-commerce bubble burst. Due to multiple players in the industry and little or no product differentiation, the Indian multi brand ecommerce industry has turned into an oligopoly market where there is hardly any brand loyalty of the customers. Companies have been rapidly increasing their selling cost in the forms of discounts and advertisements to retain and grow its customer base. This is resulting into higher revenues, but is driving the companies further away from their break-even point. With close to half a decade into the industry, none of the companies have been able to generate profits. With private investors losing patience and devaluing companies, the paper will throw light on how the multi brand e-commerce industry will change in the coming years.

Keywords: bubble burst, finance, multi brand ecommerce, product differentiation, private investor

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Authors: Helia Moayedi, Mahdi Moaidi

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Nowadays, the managing and planning of hospitals is facing many problems. Failure to recognize the main criteria for strategic management to ensure long-term hospital performance can lead to many health problems. To achieve this goal, a qualitative-quantitate method titled Delphi-Fuzzy has been applied. This strategy makes it possible for experts to screen among the most important criteria in strategic management. To conduct this operation, a statistical society consisting of 20 experts in Ahwaz hospitals has been questioned. The final model confirms the key criterions after three stages of Delphi. This model provides the possibility to focus on the basic criteria and can determine the organization’s main orientation.

Keywords: Delphi-fuzzy method, hospital management, long-term planning, qualitative-quantitate method, screening of strategic criteria, strategic planning

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Authors: Mehdi Seifbarghy, Zahra Mansouri

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In this paper a few location-allocation models are developed in a multi-echelon supply chain including suppliers, manufacturers, distributors and retailers. The objectives are maximizing demand coverage, minimizing the total distance of distributors from suppliers, minimizing some facility establishment costs and minimizing the environmental effects. Since nature of the given models is multi-objective, we suggest a number of goal-based solution techniques such L-P metric, goal programming, multi-choice goal programming and goal attainment in order to solve the problems.

Keywords: location, multi-echelon supply chain, covering, goal programming

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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Authors: Shreya Thusoo, Karan Modi, Rajesh Kumar, Hitesh Madahar

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Over the years, it has been extensively established that the practice of assuming a structure being fixed at base, leads to gross errors in evaluation of its overall response due to dynamic loadings and overestimations in design. The extent of these errors depends on a number of variables; soil type being one of the major factor. This paper studies the effect of Soil Structure Interaction (SSI) on multi-storey buildings with varying under-laying soil types after proper validation of the effect of SSI. Analysis for soft, stiff and very stiff base soils has been carried out, using a powerful Finite Element Method (FEM) software package ANSYS v14.5. Results lead to some very important conclusions regarding time period, deflection and acceleration responses.

Keywords: dynamic response, multi-storey building, soil-structure interaction, varying soil types

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Authors: Aleksandr A. Gajour, Vladimir G. Merzlikin, Vladimir I. Veselov

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This paper refers to the analysis of the characteristics of industrial and lifestyle facilities heat- energy objects as a part of the thermal envelope of Earth's surface for inclusion in any database of economic forecasting. The idealized model of the Earth's surface is discussed. This model gives the opportunity to obtain the energy equivalent for each element of terrain and world ocean. Energy efficiency criterion of comfortable human existence is introduced. Dynamics of changes of this criterion offers the possibility to simulate the possible technogenic catastrophes with the spontaneous industrial development of the certain Earth areas. Calculated model with the confirmed forecast of the Gulf Stream freezing in the polar regions in 2011 due to the heat-energy balance disturbance for the oceanic subsurface oil polluted layer is given. Two opposing trends of human development under limited and unlimited amount of heat-energy resources are analyzed.

Keywords: Earth's surface, heat-energy consumption, energy criteria, technogenic catastrophes

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Authors: Ahmad Kavousi, Ali Delaviz

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In this project, the landing process is simulated by using of multi-body dynamics commercial software. Various factors, including landing situations, aircraft structures and climate are used in this simulation. The purpose of this project is to determine the forces exerted on the aircraft landing gears in landing process in various landing conditions. For this purpose, the ADAMS multi-body dynamics software is used. Different scenarios based on FAR-25, including level landing, tail-down landing, crab landing are simulated. Results of dynamic simulation software with landing load factor obtained from the analytical solution are compared. The effect of fuselage elasticity on the landing load is studied. For this purpose, both of elastic and rigid body assumptions are used in the simulation process, and the results are compared and some conclusions are made.

Keywords: landing gear, landing process, aircraft, multi-body dynamics

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Authors: Tusar Kanti Dash, Ganapati Panda

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The evaluation of speech quality and intelligence is critical to the overall effectiveness of the Speech Enhancement Algorithms. Several intrusive and non-intrusive measures are employed to calculate these parameters. Non-Intrusive Evaluation is most challenging as, very often, the reference clean speech data is not available. In this paper, a novel non-intrusive speech evaluation measure is proposed using audio features derived from the Stockwell transform. These features are used with the Light Gradient Boosting Machine for the effective prediction of speech quality and intelligibility. The proposed model is analyzed using noisy and reverberant speech from four databases, and the results are compared with the standard Intrusive Evaluation Measures. It is observed from the comparative analysis that the proposed model is performing better than the standard Non-Intrusive models.

Keywords: non-Intrusive speech evaluation, S-transform, light GBM, speech quality, and intelligibility

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Authors: Aditi Viswanathan, Shree Ranjani, Aruna Govada

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With data sizes constantly expanding, and with classical machine learning algorithms that analyze such data requiring larger and larger amounts of computation time and storage space, the need to distribute computation and memory requirements among several computers has become apparent. Although substantial work has been done in developing distributed binary SVM algorithms and multi-class SVM algorithms individually, the field of multi-class distributed SVMs remains largely unexplored. This research seeks to develop an algorithm that implements the Support Vector Machine over a multi-class data set and is efficient in a distributed environment. For this, we recursively choose the best binary split of a set of classes using a greedy technique. Much like the divide and conquer approach. Our algorithm has shown better computation time during the testing phase than the traditional sequential SVM methods (One vs. One, One vs. Rest) and out-performs them as the size of the data set grows. This approach also classifies the data with higher accuracy than the traditional multi-class algorithms.

Keywords: distributed algorithm, MapReduce, multi-class, support vector machine

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: A. Fathianpour, M. B. Jelodar, S. Wilkinson

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This paper outlines the approaches taken to assess multi-hazard assessments. There is currently confusion in assessing multi-hazard impacts, and so this study aims to determine which of the available options are the most useful. The paper uses an international literature search, and analysis of current multi-hazard assessments and a case study to illustrate the effectiveness of the chosen method. Findings from this study will help those wanting to assess multi-hazards to undertake a straightforward approach. The paper is significant as it helps to interpret the various approaches and concludes with the preferred method. Many people in the world live in hazardous environments and are susceptible to disasters. Unfortunately, when a disaster strikes it is often compounded by additional cascading hazards, thus people would confront more than one hazard simultaneously. Hazards include natural hazards (earthquakes, floods, etc.) or cascading human-made hazards (for example, Natural Hazard Triggering Technological disasters (Natech) such as fire, explosion, toxic release). Multi-hazards have a more destructive impact on urban areas than one hazard alone. In addition, climate change is creating links between different disasters such as causing landslide dams and debris flows leading to more destructive incidents. Much of the prevailing literature deals with only one hazard at a time. However, recently sophisticated multi-hazard assessments have started to appear. Given that multi-hazards occur, it is essential to take multi-hazard risk assessment under consideration. This paper aims to review the multi-hazard assessment methods through articles published to date and categorize the strengths and disadvantages of using these methods in risk assessment. Napier City is selected as a case study to demonstrate the necessity of using multi-hazard risk assessments. In order to assess multi-hazard risk assessments, first, the current multi-hazard risk assessment methods were described. Next, the drawbacks of these multi-hazard risk assessments were outlined. Finally, the improvements to current multi-hazard risk assessments to date were summarised. Generally, the main problem of multi-hazard risk assessment is to make a valid assumption of risk from the interactions of different hazards. Currently, risk assessment studies have started to assess multi-hazard situations, but drawbacks such as uncertainty and lack of data show the necessity for more precise risk assessment. It should be noted that ignoring or partial considering multi-hazards in risk assessment will lead to an overestimate or overlook in resilient and recovery action managements.

Keywords: cascading hazards, disaster assessment, mullti-hazards, risk assessment

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Authors: Xavier Bertrand, Alexandre Cayrel

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The early phase of an aircraft development is instrumental as it really drives the potential of a new concept. Any weakness in the high-level design (wing planform, moveable surfaces layout etc.) will be extremely difficult and expensive to recover later in the aircraft development process. Aerodynamic evaluation in this very early development phase is driven by two main criteria: a short lead-time to allow quick iterations of the geometrical design, and a high quality of the calculations to get an accurate & reliable assessment of the current status. These two criteria are usually quite contradictory. Actually, short lead time of a couple of hours from end-to-end can be obtained with very simple tools (semi-empirical methods for instance) although their accuracy is limited, whereas higher quality calculations require heavier/more complex tools, which obviously need more complex inputs as well, and a significantly longer lead time. At this point, the choice has to be done between accuracy and lead-time. A brand new approach has been developed within Airbus, aiming at obtaining quickly high quality evaluations of the aerodynamic of an aircraft. This methodology is based on a joint use of Surrogate Modelling and a lifting line code. The Surrogate Modelling is used to get the wing sections characteristics (e.g. lift coefficient vs. angle of attack), whatever the airfoil geometry, the status of the moveable surfaces (aileron/spoilers) or the high-lift devices deployment. From these characteristics, the lifting line code is used to get the 3D effects on the wing whatever the flow conditions (low/high Mach numbers etc.). This methodology has been applied successfully to a concept of medium range aircraft.

Keywords: aerodynamics, lifting line, surrogate model, CFD

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Authors: G. Bhushan, S. Dhingra, K. K. Dubey

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This paper presents the evaluation of performance (BSFC and BTE), combustion (P_max) and emission (CO, NO_x, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: genetic algorithm, rsm, biodiesel, karanja

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Authors: Claudio L. M. Souza, Milton Erthal, Aldo Shimoya, Elias R. Goncalves, Igor C. Rangel, Allysson R. T. Tavares, Elias G. Figueira

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The process of choosing a region for the implementation of wind farms involves factors such as the wind regime, economic viability, land value, topography, and accessibility. This work presents results obtained by multi-criteria decision analysis, and it establishes a hierarchy, regarding the installation of wind farms, among geopolicy regions in the state of ‘Rio de Janeiro’, Brazil: ‘Regiao Norte-RN’, ‘Regiao dos Lagos-RL’ and ‘Regiao Serrana-RS’. The wind regime map indicates only these three possible regions with an average annual wind speed of above of 6.0 m/s. The method applied was the Analytical Hierarchy Process-AHP, designed to prioritize and rank the three regions based on four criteria as follows: 1) potential of the site and average wind speeds of above 6.0 ms-¹, 2) average land value, 3) distribution and interconnection to electric network with the highest number of electricity stations, and 4) accessibility with proximity and quality of highways and flat topography. The values of energy generation were calculated for wind turbines 50, 75, and 100 meters high, considering the production of site (GWh/Km²) and annual production (GWh). The weight of each criterion was attributed by six engineers and by analysis of Road Map, the Map of the Electric System, the Map of Wind Regime and the Annual Land Value Report. The results indicated that in 'RS', the demand was estimated at 2,000 GWh, so a wind farm can operate efficiently in 50 m turbines. This region is mainly mountainous with difficult access and lower land value. With respect to ‘RL’, the wind turbines have to be installed at a height of 75 m high to reach a demand of 6,300 GWh. This region is very flat, with easy access, and low land value. Finally, the ‘NR’ was evaluated as very flat and with expensive lands. In this case, wind turbines with 100 m can reach an annual production of 19,000 GWh. In this Region, the coast area was classified as of greater logistic, productivity and economic potential.

Keywords: AHP, renewable energy, wind energy

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Authors: Anicet Dansou

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Textile reinforced concrete (TRC)is increasingly used nowadays in various fields, in particular civil engineering, where it is mainly used for the reinforcement of damaged reinforced concrete structures. TRC is a composite material composed of multi- or uni-axial textile reinforcements coupled with a fine-grained cementitious matrix. The TRC composite is an alternative solution to the traditional Fiber Reinforcement Polymer (FRP) composite. It has good mechanical performance and better temperature stability but also, it makes it possible to meet the criteria of sustainable development better.TRCs are highly anisotropic composite materials with nonlinear hardening behavior; their macroscopic behavior depends on multi-scale mechanisms. The characterization of these materials through numerical simulation has been the subject of many studies. Since TRCs are multiscale material by definition, numerical multi-scale approaches have emerged as one of the most suitable methods for the simulation of TRCs. They aim to incorporate information pertaining to microscale constitute behavior, mesoscale behavior, and macro-scale structure response within a unified model that enables rapid simulation of structures. The computational costs are hence significantly reduced compared to standard simulation at a fine scale. The fine scale information can be implicitly introduced in the macro scale model: approaches of this type are called non-classical. A representative volume element is defined, and the fine scale information are homogenized over it. Analytical and computational homogenization and nested mesh methods belong to these approaches. On the other hand, in classical approaches, the fine scale information are explicitly introduced in the macro scale model. Such approaches pertain to adaptive mesh refinement strategies, sub-modelling, domain decomposition, and multigrid methods This research presents the main principles of numerical multiscale approaches. Advantages and limitations are identified according to several criteria: the assumptions made (fidelity), the number of input parameters required, the calculation costs (efficiency), etc. A bibliographic study of recent results and advances and of the scientific obstacles to be overcome in order to achieve an effective simulation of textile reinforced concrete in civil engineering is presented. A comparative study is further carried out between several methods for the simulation of TRCs used for the structural reinforcement of reinforced concrete structures.

Keywords: composites structures, multiscale methods, numerical modeling, textile reinforced concrete

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Authors: Darwin Castillo Huamaní, Francisco A. M. Gomes

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The aim of the multi-material topology optimization (MTO) is to obtain the optimal topology of structures composed by many materials, according to a given set of constraints and cost criteria. In this work, we seek the optimal distribution of materials in a domain, such that the flexibility of the structure is minimized, under certain boundary conditions and the intervention of external forces. In the case we have only one material, each point of the discretized domain is represented by two values from a function, where the value of the function is 1 if the element belongs to the structure or 0 if the element is empty. A common way to avoid the high computational cost of solving integer variable optimization problems is to adopt the Solid Isotropic Material with Penalization (SIMP) method. This method relies on the continuous interpolation function, power function, where the base variable represents a pseudo density at each point of domain. For proper exponent values, the SIMP method reduces intermediate densities, since values other than 0 or 1 usually does not have a physical meaning for the problem. Several extension of the SIMP method were proposed for the multi-material case. The one that we explore here is the ordered SIMP method, that has the advantage of not being based on the addition of variables to represent material selection, so the computational cost is independent of the number of materials considered. Although the number of variables is not increased by this algorithm, the optimization subproblems that are generated at each iteration cannot be solved by methods that rely on second derivatives, due to the cost of calculating the second derivatives. To overcome this, we apply a globally convergent version of the sequential linear programming method, which solves a linear approximation sequence of optimization problems.

Keywords: globally convergence, multi-material design ordered simp, sequential linear programming, topology optimization

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Authors: Richa Grover, Rahul Grover, V. Balaji Rao, Kavish Kejriwal

Abstract:

Selection of suppliers is a crucial problem in the supply chain management. On top of that, sustainable supplier selection is the biggest challenge for the organizations. Environment protection and social problems have been of concern to society in recent years, and the traditional supplier selection does not consider about this factor; therefore, this research work focuses on introducing sustainable criteria into the structure of supplier selection criteria. Sustainable Supply Chain Management (SSCM) is the management and administration of material, information, and money flows, as well as coordination among business along the supply chain. All three dimensions - economic, environmental, and social - of sustainable development needs to be taken care of. Purpose of this research is to maximize supply chain profitability, maximize social wellbeing of supply chain and minimize environmental impacts. Problem statement is selection of suppliers in a sustainable supply chain network by ranking the suppliers against sustainable criteria identified. The aim of this research is twofold: To find out what are the sustainable parameters that can be applied to the supply chain, and to determine how these parameters can effectively be used in supplier selection. Multicriteria decision making tools will be used to rank both criteria and suppliers. AHP Analysis will be used to find out ratings for the criteria identified. It is a technique used for efficient decision making. TOPSIS will be used to find out rating for suppliers and then ranking them. TOPSIS is a MCDM problem solving method which is based on the principle that the chosen option should have the maximum distance from the negative ideal solution (NIS) and the minimum distance from the ideal solution.

Keywords: sustainable supply chain management, sustainable criteria, MCDM tools, AHP analysis, TOPSIS method

Procedia PDF Downloads 299

Authors: Bayan Bevrani, Robert L. Burdett, Prasad K. D. V. Yarlagadda

Abstract:

This article focuses upon multi-modal transportation systems (MMTS) and the issues surrounding the determination of system capacity. For that purpose a multi-objective framework is advocated that integrates all the different modes and many different competing capacity objectives. This framework is analytical in nature and facilitates a variety of capacity querying and capacity expansion planning.

Keywords: analytical model, capacity analysis, capacity query, multi-modal transportation system (MMTS)

Procedia PDF Downloads 331