THERMO-MECHANICAL FATIGUE OF STEEL PILES IN INTEGRAL ABUTMENT BRIDGES

The issue of fatigue in steel piles of Integral Abutment Bridges (IABs) is investigated. A three-dimensional, non-liner finite element (FE) model is constructed for a bridge located in a harsh climate. Historic temperature data for the region is obtained and a sinusoidal model was developed to represent the daily and seasonal temperature changes. The FE is parametrically run for 5 cases with bridge lengths varying between 400 and 1800 feet under the cyclic load of daily and seasonal temperature variations. The pile behavior and stresses in the piles are evaluated and a fatigue model is used to determine the fatigue life of the piles. The Palmgren-Miner rule is used to evaluate the combined effects and contribution of both types of temperature cycles. The critical location of the pile is modeled locally utilizing a global-local modeling approach. "Successive initiation" in conjunction with a strain-based fatigue damage model is implemented in the local model to determine the thermo-mechanical fatigue crack initiation site, propagation path, and rate in the piles. The results show that maximum stress occurs in the pile furthest from the center of the bridge in its flange right below the concrete abutment. Plastic deformation is observed in all the piles and in all the cases studied indicating the possibility of low cycle fatigue. Lateral displacement and maximum plastic deformation in the piles increases as the length of the bridge increases. A linear relationship was found between the length of the bridge and the lateral displacement for both seasonal and daily temperature variations. The longer the bridge is the shorter the fatigue life. The crack modeling results indicate that the crack initiates in the tip of the flange. Multiple cracks form in the flange, which causes an increased propagation rate. The propagation rate decreases when the crack reaches the web. The crack could initiate in the pile in the first decade, but it will take several decades to reach the web. The final failure of the pile may not occur for several decades

Is determinism completely rejected in the standard Quantum Mechanics?

Determinism is related to other fundamental concepts such as causality. However, with the growth of quantum physics, determinism became a scientific "dilemma" and has created many challenges in various contemporary sciences. Most of modern physicists chose elimination of determinism. The basic question is: Is determinism completely removable? To answer this question, this paper is to investigate this concept analytically. At first we consider different aspects of the terminology and definition of determinism. Particularly, we pay attention to different kinds of determinism including global/local domain, complete/incomplete form, and the main factor in the formation of events. It is discussed that although determinism took a complete and universal form in classical physics, because of some philosophical ideas, determinism changed into a different concept, even as a problem and an undesirable element, in the standard (Copenhagen interpretation of) quantum mechanics. It is explained that determinism is a complex concept with a number of aspects and characteristics. Prediction, the world accessibility, and connection between the past and the future are the characteristics of the concept of determinism which cannot be set aside from the science. The final result is that, without any pre-assumption or alternative interpretation as what is done in already known realistic and deterministic theories as Bohmian quantum mechanics and/or many worlds interpretation of quantum mechanics, determinism cannot be completely denied in the standard (Copenhagen interpretation of) quantum mechanics

Multimodal Transportation p-hub Location Routing Problem with Simultaneous Pick-ups and Deliveries

Centralizing and using proper transportation facilities cut down costs and traffic. Hub facilities concentrate on flows to cause economic advantage of scale and multimodal transportation helps use the advantage of another transporter. A distinctive feature of this paper is proposing a new mathematical formulation for a three-stage p-hub location routing problem with simultaneous pick-ups and deliveries on time. A few studies have been devoted to this problem; however, many people are still suffering from the problems of commuting in crowded cities. The proposed formulation controlled the tumult of each node by indirect fixed cost. Node-to-node traveling cost was followed by a vehicle routing problem between nodes of each hub. A couple of datasets were solved for small and medium scales by GAMS software. But, for large-scale instances, a meta-heuristic algorithm was proposed. To validate the model, datasets were used and the results demonstrated the performance suitability of the proposed algorithm

A Threshold Based Dynamic Routing for Jobs with QoS Ranking

Abstract: We consider a set of n heterogeneous servers which differ in processing time and Quality of Service (QoS). Jobs are divided into m levels with regard to their service ranks. We present a Threshold Policy (TP) depending on number of different jobs in the queues as a practical and flexible dynamic routing policy to control the QoS. Two performance measures are discussed: the QoS and the Average Waiting Time (AWT) in the queues. The TP is compared with both a static routing policy which maximizes the QoS level and the Minimum Expected Delay (MED) policy which minimizes the AWT. Numerical example validate that the proposed TP is more effective when both measures are considered. The TP balances the trade-off between QoS and AWT and therefore it is superior to the MED policy and any static routing which keeps the QoS in a certain level

A Computational Method for Measuring Transport Related Carbon Emissions in a Healthcare Supply Network under Mixed Uncertainty: An Empirical Study

Measuring carbon emissions is an essential step in taking required action to fight global warming. This research presents a computational method for measuring transport related carbon emissions in a healthcare supply network. The network configuration significantly impacts carbon emissions. First, a multi-objective mathematical programing model is developed for designing a healthcare supply network in the form of a two-graph location routing problem under demand and fuel consumption uncertainty. Objective functions are minimizing total cost and minimizing total fuel consumption. In the presented model, the demand of each customer must be completely satisfied in each time period, and backlog is not permitted. The number and capacity of vehicles are determined, and vehicles are heterogeneous. Furthermore, fuel consumption depends on traveling distance, vehicle and road conditions, and the load of a vehicle. The centroid method is applied to face demand uncertainty. Next, a multi-objective non-dominated ranked genetic algorithm (M-NRGA) is proposed to solve the model. Then, a Monte Carlo based approach is presented for measuring  transport-related carbon emissions based on fuel consumption in supply network. Finally, the proposed approach is applied to the case of a healthcare supply network in the Fars province in Iran. The obtained results illustrate that the proposed approach is a practical tool in designing healthcare supply networks and measuring transport-related carbon emissions in the network

A Mathematical Model for a Flow Shop Scheduling Problem with Fuzzy Processing Times

This paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). However,, two significant criteria for each schedule in stochastic models are: expectable makespan and the probability of minimizing the makespan. These criteria can be considered for fuzzy problems as well. In this paper, we propose a solution for the fuzzy model by the use of fuzzy logic based on developing the model presented by MacCahon [18]

A Mathematical Model for a Flow Shop Scheduling Problem with Fuzzy Processing Times

Abstract This paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). However,, two significant criteria for each schedule in stochastic models are: expectable makespan and the probability of minimizing the makespan. These criteria can be considered for fuzzy problems as well. In this paper, we propose a solution for the fuzzy model by the use of fuzzy logic based on developing the model presented by MacCahon [18]

Cluster-based supplier segmentation: a sustainable data-driven approach

Purpose – Supplier segmentation provides companies with suitable policies to control each segment, thereby saving time and resources. Sustainability has become a mandatory requirement in competitive business environments. This study aims to develop a clustering-based approach to sustainable supplier segmentation. Design/methodology/approach – The characteristics of the suppliers and the aspects of the purchased items were considered simultaneously. The weights of the sub-criteria were determined using the best-worst method. Then, the K-means clustering algorithm was applied to all company suppliers based on four criteria. The proposed model is applied to a real case study to test the performance of the proposed approach. Findings – The results prove that supplier segmentation is more efficient when using clustering algorithms, and the best criteria are selected for sustainable supplier segmentation and managing supplier relationships. Originality/value – This study integrates sustainability considerations into the supplier segmentation problem using a hybrid approach. The proposed sustainable supplier segmentation is a practical tool that eliminates complexity and presents the possibility of convenient execution. The proposed method helps business owners to elevate their sustainable insights

Uncertain Supply Chain Management A location-routing model on relief distribution centers Sahar Padasht

There have been many unexpected natural disasters such as earthquake, flood, etc. in developing countries, which have created catastrophic incidents and we need to do appropriate planning for relief to reduce the possible casualties. Such actions normally face different challenges such as damages on transportation infrastructures including roads, bridges, etc. One of the primary actions for such crises management is associated with facility location for relief distribution centers. This paper presents a multi-objective mathematical problem and applies it for a real-world case study in northern region of Iran. The study uses Lp metric to handle different objectives and fuzzy programming is used to cope with uncertainty. The preliminary results indicate that the proposed study of this paper has been able to provide efficient results. Growing Science Ltd. All rights reserved.

Introducing a Novel Model to Determine CLV

Customer Relationship Management (CRM) is a productive tool for monitoring the customer and recognizing their characteristics, behaviors, and his/her requirements and anticipating his/her reactions in order to establish a long term and strong relation with customer. CRM is a business strategy selecting and managing the most valuable customer relationships. CRM includes different parts and dimensions that covers the whole stages of business from marketing to conclusion of contract, R&D, product/service design, sale and period after that. One of the important tools applied in CRM is Customer Lifetime Value (CLV). CLV allocates a quantitative value to each customer or a specific group and ranks them with this quantity. Different methods have been introduced to calculate this quantitative value. This paper tries to analyze all mentioned methods and presents the weakness and strength of each method. The most weakness of the typical method is not to concentrate on the future value of the customer. In order to rectify the weakness, in this paper an innovative model which combines two methods of RFM (which considers qualitative factors) and ROI (which considers financial factors) has been introduced. The validation of the model has been accomplished based upon real case study of one of the Iranian Insurance Companies