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Presence of risks and uncertainties inherent in project development and implementation plays

significant role in poor project performance. Thus, there is a considerable need to have an effective risk

analysis approach in order to assess the impact of different risks on the project objectives. A powerful risk

analysis approach may consider dynamic nature of risks throughout the life cycle of the project, as well as

accounting for feedback loops affecting the overall risk impacts. This paper presents a new approach to

construction risk analysis in which these major influences are considered and quantified explicitly. The

proposed methodology is a system dynamics based approach in which different risks may efficiently be

modeled, simulated and quantified in terms of time, cost and quality by the use of the implemented object

oriented simulation methodology. To evaluate the performance of the proposed methodology it has been

employed in a bridge construction project. Due to the space limitations, the modeling and quantification

process for one of the identified risks namely “pressure to crash project duration” is explained in detail.

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Geographic information systems (GIS) are one of the fastest growing computer-based technologies of past two decades, yet, full potential of this technology in construction has not been realized. Based upon GIS capabilities, construction site layout is one of the areas that GIS could be applied. The layout of temporary facilities (TFs) such as warehouses, fabrication shops, maintenance shops, concrete batch plants, construction equipments, and residence facilities has an important impact on the cost savings and efficiency of construction operations, especially for large projects. The primary objectives of this paper are to describe GIS technology and to present application of GIS technology to construction site layout. The study also delineated the methods of location TFs in construction site. An example application of GIS to location optimization of tower crane and concrete batch plant is provided to demonstrate GIS capabilities as compared with previous models. The spatial and nonspatial data which used in construction site layout process are analyzed and arranged on GIS environment and results showed the GIS can solve site layout problem. Finally, areas of additional research are noted.

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It has been shown that geopolymerization can transform a wide range of waste aluminosilicate materials into building materials with excellent chemical and physical properties such as fire and acid resistance. In this research work, geopolymerization of construction waste materials with different alkali-activators based on combinations of Na2SiO3 and NaOH has been investigated. A number of systems were designed and prepared with water-to-dry binder ratio, silica modulus, and sodium oxide concentration were adjusted at different levels and setting time and 28-day compressive strength were studied. The results obtained reveal that construction wastes can be activated using a proportioned mixture of Na2SiO3 and NaOH resulting in the formation of a geopolymer cement system exhibiting suitable workability and acceptable setting time and compressive strength. Laboratory techniques of Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM) were utilized for studying molecular and microstructure of the materials.

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Cash flow forecasting is an indispensable tool for construction companies, and is essential for the survival

of any contractor at all stages of the work. The time available for a detailed pre-tender cash flow forecast is often

limited. Therefore, contractors require simpler and quicker techniques which would enable them to forecast cash flow

with reasonable accuracy. Forecasting S-curves in construction in developing countries like Iran in compare with

developed countries has many difficulties. It is because of uncertainty and unknown situation in nature of construction

industry of these countries. Based on knowledge of authors there is a little attempt for cash flow forecasting in

construction industry of Iran. As a result authors produced An S-curve equation for construction project from historical

data which has reasonable accuracy. A sample of 20 completed projects was collected and classified in to the three

different groups. In order to model S-curves for each group, a simple and reliable method of S curve fitting has been

used. S-curves were fitted into each group by using different techniques. Errors incurred when fitting these curves were

measured and compared with those associates in fitting individual projects. At the end, accuracy of each model has

been calculated and an equation has been proposed to forecast S-curves.

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Java is an object-oriented program that has abundant open-source libraries for application development and 3D model rendering. Spatial database is the database that can efficiently store and manage geographic information data though various spatial data management techniques. This paper explores the rationale of coupling java with spatial database to develop an effective platform for future Building Information Modeling (BIM) application. The paper methodically presents the prototype system integration design to demonstrate how the system can be developed. The paper also meticulously presents the logical and physical data models in designing optimum BIM database for a reinforced concrete building. An 8-storey reinforced concrete building was used as an implementation case study to validate the proposed prototype system design and investigates the implementation issues. The outcome shows that not only the proposed prototype system offers technological advantages over the traditional BIM applications, its open-source solution can also overcome the financial constraint that currently inhibits the implementation of BIM especially for medium and small enterprises.

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In this paper, a location allocation (LA) problem in construction and demolition (C&D) waste management (WM) is studied. A bi-level model for this problem under a fuzzy random environment is presented where the upper level is the governments who sets up the processing centers, and the lower level are the administrators of different construction projects who control C&D waste and the after treatment materials supply. This model using an improved particle swarm optimization program based on a fuzzy random simulation (IPSO-based FRS) is able to handle practical issues. A case study is presented to illustrate the effectiveness of the proposed approach. Conclusions and future research directions are discussed.

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Learning rapidly and competently has become a pre-eminent strategy for improving organizational performance in the

new knowledge era. Improving dynamic learning capability is an exclusive strategy for corporate success in construction

industry. Thus engineering design firms should implement OL to accomplish a state of readiness for change and develop a

competence to respond and identify future business potentials. This study aims to analyze the relationship between

organizational learning (OL) and performance improvement (PI) in civil engineering design firms of Turkish construction

industry. OL structure in engineering design firms incorporates five constructs: organizational environment, strategy

development and implementation, supportive leadership, leveraging knowledge, and learning capability. The empirical data

was collected through a questionnaire survey conducted to engineering design firms registered to the Turkish Chamber of Civil

Engineers. The hypothesized model relationships were tested using Structural Equation Modeling (SEM). The results show that

each of the variables has a different role and significant positive impact on the OL process and organizational PI. The variables

“Supportive leadership” and “Learning capability” proved to be strongly significant and positively related to organizational

performance in engineering design firms. In engineering design firms, supportive leadership is needed in order to establish a

participative cultural environment that helps design a new form of organization which emphasizes learning, flexibility, and

rapid response. Learning capability is the potential to explore and exploit knowledge through learning flows that make possible

the development, evolution and use of knowledge stocks enacting engineering design firms and their members to add value to

the design business.

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Owing to the proximity of certain locations to the thermal power stations, it has always been efforts of Engineers to enhance

the flyash utilization rate in various Civil Engineering Constructions adopting suitable strategies. In the present study, a soilflyash

interface mechanism has been evolved using different soil-flyash ratios to upgrade significantly stabilization of supporting

medium based on CBR tests. The study confirms soundness of approach when a particular interface arrangement gives high

flyash utilization rate along with many fold increase CBR values. A study was carried out to investigate the interface effect of

soil-flyash layered system in terms of CBR values so that an optimum arrangement can be achieved by using flyash in

combination with soil. In this study, 18 samples of different ratios of soil and flyash (1:0.5, 1:1, 1:1.5, 1:2, 1:2.5, 1:3) with three

sets of interfaces N = 2, 4 and 6 were tested to arrive at the most optimized combination of soil and flyash. The results indicate

that the CBR value optimized at soil-flyash ratio 1:2.5 and number of interface N = 4. The present study reveals that soil with

flyash when used in layered system with various numbers of interfaces gives considerable improvement in CBR values. In the

above arrangement about 71 % of flyash and 29 % of soil thus contributing significantly in utilization of flyash in subgrade of

flexible pavements. In the overall study, three equations for number of interfaces N = 2, 4 and 6 have also been developed in

terms of soil-flyash ratio and CBR value, so that CBR value can directly be obtained by substituting the value of soil-flyash ratio

at a particular number of interfaces.

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This paper describes a methodology in designing high-performance concrete for simply supported beams, using a hybrid optimization strategy based on a variable neighborhood search threshold acceptance algorithm. Three strategies have been applied to discrete optimization of reinforced concrete beams: Variable Neighborhood Descent (VND), Reduced Neighborhood Search (RNS) and Basic Variable Neighborhood Search (BVNS). The problem includes 14 variables: two geometrical one material type one mix design and 10 variables for the reinforcement setups. The algorithms are applied to two objective functions: the economic cost and the embedded CO2 emissions. Firstly, this paper presents the application of these three different optimization strategies, which are evaluated by fitting the set of solutions obtained to a three-parameter Weibull distribution function. The Variable Neighborhood Descent with Threshold Accepting acceptance strategy algorithm (VND-TA) results as the most reliable method. Finally, the study presents a parametric study of the span length from 10 to 20 m in which it can be concluded that economic and ecological beams show a good parabolic correlation with the span length.

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In this paper, a bi-level decision making model is proposed for a vehicle routing problem with multiple decision-makers (VRPMD) in a fuzzy random environment. In our model, the objective of the leader is to minimize total costs by deciding the customer sets, while the follower is trying to minimize routing costs by choosing routes for each vehicle. Demand for each item has considerable uncertainty, so customer demand is considered a fuzzy random factor in this paper. After setting up the bi-level programming model for VRPMD, a bi-level global-local-neighbor particle swarm optimization with fuzzy random simulation (bglnPSO-frs) is developed to solve the bi-level fuzzy random model. Finally, the proposed model and method are applied to construction material transportation in the Yalong River Hydropower Base in China to illustrate its effectiveness.

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This paper aims to develop a quantitative game model for preventing construction project managers from moral hazard problem from the standpoint of construction enterprises in China. The authors analyze the sources of construction managers’ moral hazard behaviors under China’s specific situation on the basis of the principal-agent theory, establish a game theoretic model to analyze the moral hazard problem between construction enterprises and construction project managers, and calculate the equilibrium solution through building up the payoff matrix. Our crucial contribution is a quantitative characterization of risk deposit system and performance appraisal system which help to resolve the moral hazard problem of construction project managers. The solution results show that the probability of moral hazard problem of construction project managers can be reduced after implementing risk deposit system and performance appraisal system. Thus the two systems we proposed can be taken by China’s construction enterprises as the effective measures to resolve moral hazard problem of construction project managers.

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Project Management knowledge has been used in many project oriented organizations in last two decades across the world. Despite, rate of project success did not change during these years. We believe there is a basic challenge in projects environment for managing them based on its inherent characteristics. In fact, project management knowledge use theories and concepts that are belong to process management world, as a different world. There is no enough attention to project characteristics as a fundamental differentiation for coping projects. Identification of construction projects nature in order to discern variables that create the project behaviors is main concern of the paper.Considering project characteristics in this research revealed construction project nature creates from combination two aspects. First, detecting environmental changes to develop a need and second prepare resources structure to respond the need. Important management challenge in this model is environmental continuous changes that alter the need and exchange resources structure. So, the paper considers how these aspects can be operationalized for developing a dynamic project management model. It gives some ideas about why project complexity might be considered to be increasing, and how construction projects move towards shorter timescales. The effectiveness of the model is verified by applying it for predicting some construction projects behavior. The results of the paper may capable future project managers to test any decision before its applying and lead to a new project management tool for construction projects management.

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In order to improve the utilization of high liquid limit soil, the fundamental properties of high liquid limit soil and its direct utilization method are studied in this paper. This work involves both laboratory and fieldwork experiments. The results show that clay and sandy clay both with high liquid limit can be directly used for the road embankment, and the degree of compaction can be controlled at 88 %. The pack-and-cover method in accordance with Chinese technical specifications is recommended to be operated in the engineering practice. The packed height should be less than 8 meters and the total height of embankment no more than 12 meters in the interests of settlement. From the view of stability, the optimal thickness value of top sealing soil layer and edge sealing soil layer is about 1.5 meter respectively, and the geogrid reinforcement spacing should be about 2.0 meters. In addition, based on Yun-Luo expressway in China filled with high liquid limit soil, the construction techniques and key points of quality control in subgrade with pack-and-cover method are compared and discussed in detail, and the feasibility of these schemes are verified by the experimental results.

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The management philosophy, namely, Customer relationship management (CRM) has been widely accepted and successfully applied across a range of sectors. However, there has been very little research efforts in the field of CRM in the construction industry. This paper provides a review of the CRM philosophy and technology, and considers the implications benefits and challenges to construction organizations at a strategic business and operational level. Given the generally unstable economic and highly competitive marketplace, implementation of CRM throughout the lifecycle of assets may provide for more effective management of existing and prospective clients. The CRM approach would seem to be compatible with general trends in the construction industry towards more collaborative working and the paper provides that both the philosophy and technologies can be integrated with current initiatives such as building information modeling (BIM). Construction clients in the public and private sector are diverse in nature, complex in their buying processes and at varying levels of knowledge of the Industry. In addition to seeking value for money from their projects and assets, they have become more concerned about sustainability and environmental impact. It has been recognized that management of a broader range of business and project level stakeholders is necessary.

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Various methods have been applied to construction crew productivity problem. This paper additionally introduces the use of two novel artificial intelligent methods which are Self Organizing Maps and Artificial Bee Colony. It first presents the results of the prediction performances of these two methods and then focuses on the visualisation ability of SOM through the presentation of two dimensional maps produced for the current problem. The prediction performances are compared by comparing MAPE, MAE and MSE values obtained during seven fold cross validation. Two dimensional maps produced by SOM based model are additionally presented in order to analyse the relationship between labour related factors of crew size, age and payment method with productivity rates of ceramic tiling crews.

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Soils with poor engineering properties have been a concern to construction engineers because of the need to strike a balance between safety and economy during earthworks construction. This research work investigates the effects of treating a soil having poor geotechnical properties with a bio-enzyme to determine its suitability for use as road pavement layer material. The elemental composition and microstructure of the soil was determined using energy dispersive X-ray spectroscopy and scanning electron microscopy, respectively. The specific gravity, Atterberg limits, compaction, strength and permeability characteristics of the soil was determined for various dosages of the bio-enzyme. The mountain soil is classified as clayey sand and A-2–4, according to unified soil classification and AASHTO classification systems, respectively. With increasing dosage of the bio-enzyme, the plasticity index, maximum dry unit weight and permeability of the soil decreased, while its 28-day California bearing ratio value, unconfined compressive strength and shear strength increased. Consequently, the application of bio-enzyme to the soil improved its plasticity and strength, and reduced its permeability. It, therefore, became more workable and its subgrade quality was improved for use as a road pavement layer material. The stabilized soil can be suitably used for constructing pavement layers of light-trafficked rural (earth) roads, pedestrian walkways and bicycle tracks.

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The study presents a model for the evaluation of construction projects from the point of view of the investor. The problem lies in choosing the best solution from the point of view of many criteria. The proposed model is based on a multi-criteria comparative analysis using fuzzy logic. The first part of the paper presents a selection of criteria describing the construction project along with their description. The set of attributes describing the analyzed object was determined on the basis of the synthesis of specific proposals for the parameters of construction projects. The set of criteria has been divided into two groups: technical, technological and organizational criteria and separately the economic criteria. Then, the number of variables describing the observations was checked using principal component analysis (PCA). Course of action was presented in the event of multiple criteria analysis using the fuzzy set theory. Both the weights and the evaluations of individual criteria were modelled using membership functions due to the fact that when describing a construction project, or the validity of the criteria of describing variables, they are approximate. An analysis of the correlation of selected project criteria was presented. The proposed decision support model of assessing a construction project makes possible to compare various variants based on 11 factors identified. The use of fuzzy logic has enabled more accurate description of the phenomenon analysed when the exact parameters of the project in the planning and preparation stage of the project are not known.

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Construction industries are the most dangerous worksites with high risk of occupational accident and bodily injuries, which ranges from mild to very severe cases. The aim of this study was to explore the causal factors of accident severity rate (ASR), in 13 of the biggest Iranian construction industries. In this analytical cross-sectional study, the data of registered accidents from 2009 until 2013 were obtained from an official database. Data of HSE risk management systems and HSE training were also gathered from comprehensive accident investigation reports. Data analysis and regression modeling were done using SPSS statistical software (version 22). The mean and SD of ASR of studied construction worksites was 257.52±1098.95. The results show that the system associated with HSE and HSE risk management established only 41.8 and 18.4%, respectively. The results of multiple linear regression indicated that some individual and organizational factors (IOFs), HSE training factors (HTFs), and Risk Management System factors (RMSFs) were significantly associated with ASR (p<0.05). The study revealed the causal factors of ASR. Hence, these findings can be applied in the design and implementation of a comprehensive HSE risk management system to reduce ASR.

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The study has been developed a qualitative System Dynamics model to measure sustainability performance of construction project, considering contractors’ tendency to productivity. Construction contractors do not have a clear understanding of sustainability especially in developing countries. However, they welcome higher productivity as a determinant parameter in scheduling and financial success of construction project. Therefore, construction productivity improvement can be employed as an incentive to persuade contractors for implementing sustainability mechanisms in construction project. Sustainability performance has been examined in three aspects of economic, social and environmental by introducing different subsystems and feedback loops. These loops are based on the causal links among the factors affecting construction sustainability and productivity. The findings provide a proper basis for both practitioners and researchers through illustrating the cohesion between productivity and sustainability.