Railway reinforced concrete infrastructure life management and sustainability index

Infrastructure healthy enhancement for saving resources in operation procedures is one of the most important objectives for owners on their decision support system based on cost management. In this manner, finding the intervention action priority, as well as the inspection method and maintenance system for each component, with regard to a limited resources amount is investigated in this paper. Defects on infrastructure components create data and these data are undoubtedly useful to increase the knowledge in decision making in practice. In that sense, risk analysis and value of information can be applied using decision trees together with Bayesian networks. For data filtering and noise reduction, a principal component analysis may also be applied to manage a database and prepare useful input variables for the decision tree system. This paper presented an approach for the maintenance managers to prepare their infrastructure available with a sustainable index with minimum cost. This index would be a tool for decision-makers with regard to the cost management and sustainability aspects

Operation reliability index for maintenance decision making in bridges

Maintenance management developed by several approach to optimize cost recently. Meanwhile decision making during operation is difficult task for mangers to keep them safe as well as stakeholder demands satisfaction and costs with regard to resources limitation. This paper presents an approach for decision making process to select alternatives based on their costs. For this manner, the uncertainty of defect probability combine with other availability and performance features to find priority of maintenance equipment and their reliability. This multi-dimensional decision making do not deal with the essential imprecision of subjective judgment based on quantitative evaluation. To demonstrate the use and capability of the model, a case study is presented. In this case, results shows the quality value combined by delay as an effectiveness parameters (91.08) and then decision tree will complete it by risk and reliability factors

Pesticide Consumption in Greenhouses; a Case Study of Kashan Region

Aims: In regard to increasing greenhouse area in Iran followed by increased use of pesticides and contaminated crops, this study aimed to determine the frequency and types of consumed pesticides in Kashan region, Iran, greenhouses. Instrument & Methods: In this descriptive study in 2011-2012, samples was entered by census method. At the first step, a list of greenhouses was obtained from agricultural organization, 39 active greenhouses were detected, thereafter the questionnaires have been completed in detail by direct interview; obtained data were analyzed in SPSS 23 by descriptive statistics. Findings: 87.1 of greenhouses used chemical methods for controlling pest and diseases of products and 43.5 used non-chemical methods. The most frequent used chemical pesticides were Deltamethrin (37.9) and Permethrin (28.3) as pyrethroid insecticides, Diazinon (23.1) as an organophosphate insecticide and Carbendazim (23.2) as a fungicides. Conclusion: 87.1 of the greenhouses’ owners of Kashan region, Iran, use chemical pesticide for pest control

Quality control index survey for railway bridge health monitoring

Inspection and rehabilitation are the most important activities during any maintenance procedure. A maintenance project demands to manage resources with regard to data related to components’ condition, defined by a given index. In this manner, data sets obtained for each index, and for each case study, are used for finding the new quality control index with maximum value of data. In this approach, risk analysis is used for prioritization and reducing costs with increasing data value with focusing on important elements as well as maximizing value of information (VoI) in measurements and inspections. Risk analysis is the most common tool for data mining and intelligent judgment obtained from observations. Risk analysis results are usually calculated to find the weight for each data set index in terms of their scores, which are called factor scores and finding the new quality control indexed for each case. Finally, the major and important index according to their weight and risk scores, is obtained and used for decision making in maintenance projects. An application is shown consisting of 29 Railway Bridges in suburban area with data obtained from periodic inspections. All of these bridges are constructed in reinforced concrete. Finally, it is desirable to produce new check list with regard to important data and quality control indexes. The priority of each bridge in the railway network as well as the priority for each component in their structure could be obtained by the new quality control indexes. Resource planning usage for the network component could be determined by this approach after computation of the new quality control index. Resources planning consists of inspection intervals and their materials usage for maintenance activities.- (undefined

Decision-Making Based on Multi-Dimensional Quality Control for Bridges

Quality control (QC) may be applied as a framework for maintenance planning when assigning different intervention measures to single structural elements or systems. This work proposes a reliability-based maintenance decision-making process for planning visual inspections on bridges based on the value of information and prior inspection data, and also promotes updating and improvement cycles for subsequent planning. To that aim, an integration between SHM (Structural Health Monitoring) data with a multidisciplinary approach is proposed to obtain a reliability index attending to QC. The data analysis was mainly carried out with respect to an existing measurement database and structural assessments, which were combined to obtain weighted importance coefficients for each component according to their significance in the structure. The Iranian railway network has a built stock of nearly 28,200 bridges from which a database obtained from 104 bridges was studied in this work, considering the data obtained from technical identification checklists. The results were then calibrated and validated with a dataset of seven bridges, which were inspected onsite. The inspection comprised the identification and grading of damages and defects on each element. Observed defects were considered as input for the risk analysis of each component of the network by considering the probability of detection, occurrence and its likely consequences. Decision making with inspection and intervention costs optimization was then performed, for a specific case study, using Principal Component Analysis (PCA) together with the value of information (VOI) for data filtering. With this approach, several parameters with lower values reduced from inspection and other valuable data remain for bridge quality assessment with optimum maintenance cost

Railway reinforced concrete infrastructure life management and sustainability index

Infrastructure healthy enhancement for saving resources in operation procedures is one of the most important objectives for owners on their decision support system based on cost management. In this manner, finding the intervention action priority, as well as the inspection method and maintenance system for each component, with regard to a limited resources amount is investigated in this paper. Defects on infrastructure components create data and these data are undoubtedly useful to increase the knowledge in decision making in practice. In that sense, risk analysis and value of information can be applied using decision trees together with Bayesian networks. For data filtering and noise reduction, a principal component analysis may also be applied to manage a database and prepare useful input variables for the decision tree system. This paper presented an approach for the maintenance managers to prepare their infrastructure available with a sustainable index with minimum cost. This index would be a tool for decision-makers with regard to the cost management and sustainability aspects.This work was partly financed by FCT / MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB / 04029/2020. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No769255

Pesticide Consumption in Greenhouses; a Case Study of Kashan Region

Abstract Aims: In regard to increasing greenhouse area in Iran followed by increased use of pesticides and contaminated crops, this study aimed to determine the frequency and types of consumed pesticides in Kashan region, Iran, greenhouses. Instrument & Methods: In this descriptive study in 2011-2012, samples was entered by census method. At the first step, a list of greenhouses was obtained from agricultural organization, 39 active greenhouses were detected, thereafter the questionnaires have been completed in detail by direct interview; obtained data were analyzed in SPSS 23 by descriptive statistics. Findings: 87.1% of greenhouses used chemical methods for controlling pest and diseases of products and 43.5% used non-chemical methods. The most frequent used chemical pesticides were Deltamethrin (37.9%) and Permethrin (28.3%) as pyrethroid insecticides, Diazinon (23.1%) as an organophosphate insecticide and Carbendazim (23.2%) as a fungicides. Conclusion: 87.1% of the greenhouses’ owners of Kashan region, Iran, use chemical pesticide for pest control