Prediction of Repair and Maintenance Costs of Two-wheel Drive Tractors in Iran

Predicting of repair and maintenance （R＆M） costs of tractors in any mechanized farm is necessary for owners and managers to obtain information on overall costs and to control financial balance and production economy. In this context a study was conducted to predict accumulated R＆M costs （Y） of two-wheel drive （2WD） tractors based on accumulated usage hours （X） in Misagh-e-Sabz Agribusiness Company in Iran. Recorded data of the company were used to determine regression models for predicting accumulated R＆M costs （as percentage of initial purchase price） based on accumulated usage hours. The statistical results of the study indicated that in order to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or less the power regression model Y=0.013 （X/100）1.677 with R2=0.976, and to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or more the polynomial regression model Y=0.004 （X/100）2-0.181 （X/1 00）＋4.373 with R2=0.998 can be strongly suggested.

Performance-based system seismic assessment for long-span suspension bridges under two-level seismic hazard

Since there are few studies on the performance-based seismic evaluation of the long-span suspension bridge system under two-level earthquake hazard in Chinese code,the developed procedure of this study can be regarded as a general program to assess the seismic performance of the overall system for long-span suspension bridges.In the procedure,the probabilistic seismic demand models of multiple bridge components were developed by nonlinear time-history analyses incorporating the related uncertainties,and the component-level fragility curves were calculated by the reasonable definition of limit states of the corresponding components in combination with seismic hazard analysis.The bridge repair cost ratios used to evaluate the system seismic performance were derived through the performance-based methodology and the damage probability of critical components.Furthermore,the repair cost ratios of the overall bridge system that was retrofitted with fluid viscous dampers for the main bridge and changed restraint systems for the approach bridges were compared.The results show that peak ground velocity and peak ground acceleration can be selected as the optimal intensity measurements of long-span suspension bridges using the TOPSIS(technique for order preference by similarity to an ideal solution).The bridge repair cost ratios can serve as accurate evaluation indicators to provide an efficient evaluation of retrofit measures.The seismic evaluation of long-span bridges is misled when ignoring the interaction of adjacent structures.However,the repair cost ratios of a bridge system that has optimum seismic performance are less sensitive to the relative importance of adjacent structures.

DESIGN OF EXACT REGENERATING HIERARCHICAL CODE FOR DISTRIBUTED STORAGE SYSTEM

Erasure code is widely used as the redundancy scheme in distributed storage system. When a storage node fails, the repair process often requires to transfer a large amount of data. Regenerating code and hierarchical code are two classes of codes proposed to reduce the repair bandwidth cost. Regenerating codes reduce the amount of data transferred by each helping node, while hierarchical codes reduce the number of nodes participating in the repair process. In this paper, we propose a "sub-code nesting framework" to combine them together. The resulting regenerating hierarchical code has low repair degree as hierarchical code and lower repair cost than hierarchical code. Our code can achieve exact regeneration of the failed node, and has the additional property of low updating complexity.

Artificial neural network-based repair and maintenance cost estimation model for rice combine harvesters

This research proposes an artificial neural network(ANN)-based repair and maintenance(R&M)cost estimation model for agricultural machinery.The proposed ANN model can achieve high estimation accuracy with small data requirement.In the study,the proposed ANN model is implemented to estimate the R&M costs using a sample of locally-made rice combine harvesters.The model inputs are geographical regions,harvest area,and curve fitting coefficients related to historical cost data;and the ANN output is the estimated R&M cost.Multilayer feed-forward is adopted as the processing algorithm and Levenberg-Marquardt backpropagation learning as the training algorithm.The R&M costs are estimated using the ANN-based model,and results are compared with those of conventional mathematical estimation model.The results reveal that the percentage error between the conventional and ANN-based estimation models is below 1%,indicating the proposed ANN model’s high predictive accuracy.The proposed ANN-based model is useful for setting the service rates of agricultural machinery,given the significance of R&M cost in profitability.The novelty of this research lies in the use of curve-fitting coefficients in the ANN-based estimation model to improve estimation accuracy.Besides,the proposed ANN model could be further developed into web-based applications using a programming language to enable ease of use and greater user accessibility.Moreover,with minor modifications,the ANN estimation model is also applicable to other geographical areas and tractors or combine harvesters of different countries of origin.

Estimation of Load-Induced Damage and Repair Cost in Post-Tensioned Concrete Rocking Walls

Post-tensioned concrete rocking walls might be used to avoid severe seismic damage at the base of structural walls, decrease residual drift, and lessen post-earthquake repair costs. The prediction of load-induced damage to the rocking wall resulting from seismic loading can provide an extremely valuable tool to evaluate the status and safety of structural concrete walls following earthquakes. In this study, the behavior and the damage state of monolithic, self-centering, rocking walls, as a new type of concrete rocking wall, are investigated. The nonlinear mechanical behavior of the wall is first modeled numerically, and subsequently the mechanical parameters from the numerical simulation are used to generate the local damage index. The results from the damage index model are compared with the full-scale test results, confirming the viability of the numerically based damage index method for estimating the seismically induced damage in concrete walls. Moreover, the estimated damage can be utilized as a qualitative and quantitative scale to assess the status of the wall following seismic loading events.Finally, an equation is proposed to estimate the repair cost based on the predicted damage state for the studied structural system.

Seismic Resilience Analysis of a Concrete-Framed Hospital Building with Viscous Dampers

To study the seismic resilience of a concrete-framed hospital building with viscous dampers,the elastoplastic time history analysis of a three-story concrete-framed hospital building under moderate and rare earthquakes was carried out by finite element analysis software.The structure’s overall response was studied,meanwhile,the seismic resilience of the building was evaluated from three aspects:repair cost,repair time,and casualties.The results show that viscous dampers can effectively reduce the repair cost,repair time,and casualties under earthquakes.Compared with the structure without dampers,the repair cost and repair time of the structure with dampers have been reduced by 67%and 69%respectively under moderate earthquakes,42%and 39%respectively under rare earthquakes,and the seismic resilience grade has been increased from zero to one star.