Fuzzy AHP Method for Selection of a Suitable Seismic Retrofitting Alternative in Low-Rise Buildings

Decision making for selecting an appropriate alternative among nominated alternatives is still a problem among retrofit designers. It is clear that selected alternative should comply the current codes in terms of structural criteria, but the other criteria may not be considered. The main goal of this study is to introduce a suitable method for making a decision in order to find the best alternative considering the effective criteria in retrofitting of low-rise buildings. Analytic Hierarchy Process (AHP), as a technique of Multi-Criteria Decision Making (MCDM), is compatible to solve the problem. Effective criteria have been categorized to structural, operational, economic and functional criteria and sixteen sub-criteria considered as a pattern that satisfies the entire involved group including structural and architectural engineers, contractor, client, and authorities in retrofitting of low-rise buildings. Since most of the involved criteria such as aesthetic, durability, and compatibility have fuzzy nature and cannot be compared numerically, fuzzy AHP can be a compatible method for comparison different retrofitting alternatives among both fuzzy and non-fuzzy criteria. A matrix of pair-wise comparison (MPC) is used for determining the weight of criteria and also for scoring the alternatives respect to each criterion. A Fuzzy Importance scale with Triangular Fuzzy Numbers (TFN) is applied for comparing the criteria. The method is examined by a case study and the results show the used method can help designers for selecting the appropriate alternative

OpenSRANE, a Flexible and Extensible Platform for Quantitative Risk Assessment of NaTech Events

The effects of natural hazards triggering technological disaster (NaTech) on a society, economy and the environment is a multi-disciplinary research topic. The novelty of the issue and the lack of a standard procedure for risk assessment of this category of incidents show the need for more research in this area. This article introduces OpenSRANE as an open-source, extensible, flexible and object-oriented software for calculating the quantitative risk of NaTech events in process plants. Implementing the software in the Python programming environment provides high flexibility for the modeling and evaluations desired by users. The possibility of implementing the modifications and developments to the existing software as needed by users allows them to add their desired algorithms, elements and models to it, if needed. The software is based on the Monte Carlo method, but it is possible to implement other algorithms and approaches to it. Object-oriented programming and separation of the different parts of the software can increase the readability of the program, allowing researchers in different disciplines to focus easily on studying or developing the desired part with minimal interference from other parts. The applicability of the software has been demonstrated in a case study as well as the ability of the software to calculate results such as the individual risk, scenarios that consider domino effects and physical effects

A Survey on Weapon Target Allocation Models and Applications

In Command and Control (C2), Threat Evaluation (TE) and Weapon Target Allocation (WTA) are two key components. To build an automated system in this area after modeling Threat Evaluation and Weapon Target Allocation processes, solving these models and finding the optimal solution are further important issues. This setting demands instantaneous operational planning and decision making under inherent severe stress conditions. The associated responsibilities are usually divided among a number of operators and also computerized decision support systems that aid these operators during the decision making process. In this Chapter, the literature in the area of WTA system with the emphasis on the modeling and solving methods are surveyed

A new hybrid model for evaluating the working strategies: case study of construction company

Selection of the working strategy is a critical problem and it plays a significant role in the success of organization development. On the other hand, selecting the most appropriate working strategy among a pool of alternatives is a multi-criteria decision making (MCDM) problem. Since every working strategy has its benefits and costs and may bring a company different opportunities and risks, which kind of working strategy is the most appropriate for a company to accomplish is a sophisticated and complex decision with a high degree of uncertainty. Therefore, the current paper proposed an integrated evaluation model based on the analytic network process (ANP) and the complex proportional assessment (COPRAS), to help the decision makers or managers with the selection of proper working strategy in a fuzzy environment where the fuzziness and uncertainties are handled with linguistic terms parameterized by triangular fuzzy numbers (TFNs). In this paper fuzzy ANP (FANP) is utilized to take into account interdependence and dependencies and determine the importance weights of benefit, opportunities, cost and risk (BOCR) factors, and fuzzy COPRAS is applied to rank the alternatives. To show the potential application of the proposed model, a real world application is conducted to illustrate the use of the proposed model for the working strategy selection problem. The results show the capability and effectiveness of the proposed model

An Engineering Comment for Simply Accelerating Seismic Response History Analysis of Mid-Rise Steel-Structure Buildings

Response history analysis using a time integration method is a powerful versatile tool in accessing structures seismic behaviours. To reduce the analysis run-time, a technique was proposed in 2008 for time integration with steps larger than the steps of ground motions. The technique has been implemented in seismic assessment of frames, buildings, bridges, silos, etc., leading to considerable reductions in the analysis run-time, without notable effect on the response accuracy. The technique has recently been named as the SEB THAAT (Step- Enlargement-Based Time-History-Analysis-Acceleration-Technique). To use the SEB THAAT, the smallest dominant period of the response needs to be available prior to the analysis. In this paper, concentrating on 5-20-floor steel-structure buildings, a simple engineering comment is proposed that eliminates this need. As a result, in response history analysis of mid-rise steel-structure buildings subjected to ground motion, by using the proposed comment, we may reduce the analysis run-time, significantly, without any initial information about the response. The reduction is 50% for the linear analyses

Selecting the optimal renewable energy using multi criteria decision making

Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives. First published online: 23 Sep 201

Landslide Risk Assessment by Using a New Combination Model Based on a Fuzzy Inference System Method

Landslides are one of the most dangerous phenomena that pose widespread damage to property and human lives. Over the recent decades, a large number of models have been developed for landslide risk assessment to prevent the natural hazards. These models provide a systematic approach to assess the risk value of a typical landslide. However, often models only utilize the numerical data to formulate a problem of landslide risk assessment and neglect the valuable information provided by experts’ opinion. This leads to an inherent uncertainty in the process of modelling. On the other hand, fuzzy inference systems are among the most powerful techniques in handling the inherent uncertainty. This paper develops a powerful model based on fuzzy inference system that uses both numerical data and subjective information to formulate the landslide risk more reliable and accurate. The results show that the proposed model is capable of assessing the landslide risk index. Likewise, the performance of the proposed model is better in comparison with that of the conventional techniques

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2