Impacts of transportation projects on urban trends in İzmir

The effects of major transportation projects on urban trends in Izmir were analyzed using the Delphi method. Once convergence was maintained in expert opinions, the Delphi results were re-evaluated according to the suggested method of total evaluation for obtaining much concise and general results. Accordingly, Absolute Total Impacts (ATI), Net Total Impacts (NTI) and the impact levels in broader terms were defined. The most effective projects were found to be: Integrated Rail Transportation System, Enhancement of Existing İzmir Port. The most impacted trends were: Development in Tourism Sector, Economic Development, Air Pollution and the Ratio of Private Car Ownership

İzmir municipality housing and zoning code analysis and representation for compliance checking

20th International Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2013; Vienna; Austria; 1 July 2013 through 3 July 2013Systems for code compliance checking of building projects require representation of building codes. Building codes are complex, and the development of computer implementable representations is challenging. As a case in point, this paper reports on experiences gained while modeling ̄zmir Municipality Housing and Zoning Code (IMHZcode). First, IMHZcode was analysed to understand the various types of information contained in it in order to develop a comprehensive building code model. The rules were classified according to their formalizability and self-containedness. Then, existing modeling approaches were evaluated to find the most convenient method that meets the needs for modeling IMHZcode. A key criterion used in this evaluation was ease of maintenance by non-programmers. The paper concludes with an illustrative example of the selected methodology's application within the context of IMHZcode

BIM execution process of construction companies for building projects

Building Information Modeling (BIM) has been an emerging concept in architecture, engineering and construction (AEC) industry with a vast amount of promising benefits to construction projects. Implementation of BIM, however, requires comprehensive research and strategic planning. Industry-wide and organizational implementation guidelines and standards have been published around the world either to encourage organizations to adopt BIM or to present the minimum requirements to be followed where BIM implementation is a statutory obligation. In contrast, governments or organizations in several countries such as Turkey have not mandated BIM implementation and provide no guidance. Organizations in these countries which plan to adopt BIM processes are forced to develop their own implementation plans. The purpose of this study is to provide guidance in BIM implementation for construction companies in countries where BIM implementation has not been mandated particularly during the construction phase of the building projects. 23 BIM standards and guidelines covering the BIM execution process have been reviewed. Topics that need to be addressed by BIM implementation plans have been identified and categorized under four headings. A case study of BIM implementation at a large construction company that focuses on conducting quantity takeoff and cost estimation is presented, and unique challenges of BIM implementation in Turkish AEC industry are discussed

The effects of transportation projects on urban trends in İzmir

İzmir’deki önemli ulaştırma projelerinin kentsel eğilimlere olan etkileri Delphi yöntemi sonuçları temel alınarak analiz edilmiştir. Delphi yöntemine göre yakınsama sağlanmış etkiler, sonrasında daha anlamlı ve özet sonuçlar elde etmek amacıyla toplamdaki etkiler yöntemiyle yeniden değerlendirilmiştir. Yönteme göre, mutlak toplam etkilere (MED), net toplam etkilere (NED) ve en genel anlamda etki yeterlik düzeylerine bakılarak genel sonuçlara ulaşılmıştır. En etkili (olumlu/olumsuz yönde) projeler, bütünleştirilmiş raylı toplu taşıma sistemi, mevcut İzmir limanının geliştirilmesi; en fazla etkilenen sosyoekonomik eğilimler ise turizm sektöründeki gelişim, ekonomik gelişme, hava kirliliği ve özel araç kullanım oranı olarak çıkmıştır.The effects of major transportation projects on the urban trends in İzmir were analyzed using the Delphi method. Once the convergence was maintained in the expert opinions, the Delphi results were re-evaluated according to suggested method of total evaluation for obtaining much concise and general results. Accordingly, Absolute Total Impacts (MED), Net Total Impacts (NED) and the impact levels in broader terms were defined. The most effective projects were found to be: Integrated Rail Transportation System, Enhancement of Existing İzmir’s Port. The most impacted trends were: Development in Tourism Sector, Economic Development, Air Pollution and the Rate of Private Car Ownership

Optimization of an envelope retrofit strategy for an existing office building

Energy-efficient retrofits include improvement of building envelope via insulation, employment of building integrated renewable energy technologies, and climate control strategies. Building envelope improvements with insulation is a common approach, yet decision-making plays an important role in determining the most appropriate envelope retrofit strategy. In this study, main objective is to evaluate and optimize envelope retrofit strategies through a calibrated simulation approach. Based on an energy performance audit and monitoring, an existing building is evaluated on performance levels and improvement potentials with basic energy conservation measures (ECMs). The existing building is monitored for a full year and monitoring data is used in calibrating the simulation model. In order to obtain a better-performing building envelope three retrofit strategies including several ECMs are proposed. Retrofit strategies are simulated through calibrated base-case model, and results are evaluated according to changes in indoor environmental parameters and annual energy consumption measures. The analysis of results indicated that pre-assessed strategies yield close results. Therefore, a more comprehensive evaluation based on different decisive criteria is used in optimization of the final retrofit strategy, with the intention to evaluate the effect of individual ECMs on annual end-use energy consumption and investment

Perceptions of process quality in building projects

A Delphi process and a questionnaire survey are conducted to investigate the differences in the perceptions of entry-level professionals and long-time practitioners with regard to process quality in building projects. The factors that affect process quality in the three phases (design, construction, and operation) of a building project's life cycle are identified and ranked by the respondents' perceived degree of importance. The findings indicate that the perceptions of entry-level professionals and long-time practitioners are in agreement for most (74%) of the factors. Given the differences in the respondents' background, expectations, and experience, differences in perceptions are to be expected in the remaining 26% of the factors. Analyzing these differences helps in revising and improving existing training courses and academic programs. It is recommended that college programs include courses that treat the administrative aspects involved in the building project in great detail and that continuing education programs cover quality training and life cycle cost analysis

A neural network approach for early cost estimation of structural systems of buildings

The importance of decision making in cost estimation for building design processes points to a need for an estimation tool for both designers and project managers. This paper investigates the utility of neural network methodology to overcome cost estimation problems in early phases of building design processes. Cost and design data from thirty projects were used for training and testing our neural network methodology with eight design parameters utilized in estimating the square meter cost of reinforced concrete structural systems of 4-8 storey residential buildings in Turkey, an average cost estimation accuracy of 93% was achieved

Artificial neural networks to predict daylight illuminance in office buildings

A prediction model was developed to determine daylight illuminance for the office buildings by using artificial neural networks (ANNs). Illuminance data were collected for 3 months by applying a field measuring method. Utilizing weather data from the local weather station and building parameters from the architectural drawings, a three-layer ANN model of feed-forward type (with one output node) was constructed. Two variables for time (date, hour), 5 weather determinants (outdoor temperature, solar radiation, humidity, UV index and UV dose) and 6 building parameters (distance to windows, number of windows, orientation of rooms, floor identification, room dimensions and point identification) were considered as input variables. Illuminance was used as the output variable. In ANN modeling, the data were divided into two groups; the first 80 of these data sets were used for training and the remaining 20 for testing. Microsoft Excel Solver used simplex optimization method for the optimal weights. The model's performance was then measured by using the illuminance percentage error. As the prediction power of the model was almost 98%, predicted data had close matches with the measured data. The prediction results were successful within the sample measurements. The model was then subjected to sensitivity analysis to determine the relationship between the input and output variables. NeuroSolutions Software by NeuroDimensions Inc., was adopted for this application. Researchers and designers will benefit from this model in daylighting performance assessment of buildings by making predictions and comparisons and in the daylighting design process by determining illuminance

Determining attribute weights in a CBR model for early cost prediction of structural systems

This paper compares the performance of three optimization techniques, namely feature counting, gradient descent, and genetic algorithms (GA) in generating attribute weights that were used in a spreadsheet-based case based reasoning (CBR) prediction model. The generation of the attribute weights by using the three optimization techniques and the development of the procedure used in the CBR model are described in this paper in detail. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of 29 residential building projects. The results indicated that GA-augmented CBR performed better than CBR used in association with the other two optimization techniques. The study is of benefit primarily to researchers as it compares the impact attribute weights generated by three different optimization techniques on the performance of a CBR prediction tool

Using decision trees for determining attribute weights in a case-based model of early cost prediction

This paper compares the performance of three different decision-tree-based methods of assigning attribute weights to be used in a case-based reasoning (CBR) prediction model. The generation of the attribute weights is performed by considering the presence, absence, and the positions of the attributes in the decision tree. This process and the development of the CBR simulation model are described in the paper. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of residential building projects. The CBR results indicate that the attribute weights generated by taking into account the information gain of all the attributes performed better than the attribute weights generated by considering only the appearance of attributes in the tree. The study is of benefit primarily to researchers, as it compares the impact of attribute weights generated by three different methods and, hence, highlights the fact that the prediction rate of models such as CBR largely depends on the data associated with the parameters used in the model