Ebrahim Karan

Roller-compacted concrete (RCC) offers a cost-effectiveness and ease of construction concrete pavement alternative. The use of waste materials into RCC pavement contributes to sustainable development with economic and environmental benefits. Traditional RCC mixture proportioning method does not objectively consider waste materials such as reclaimed asphalt pavement (RAP) or crumb rubber and thus may not meet performance criteria. Numerous statistical and robust design methods have been used for optimising the design of concrete mixture. However, the available methods cannot satisfy practical requirements for concrete mixtures incorporated waste materials. This methodology is unique in that it is specifically designed to focus on mixtures containing RAP and crumb rubber. In this paper, a statistical method called Taguchi is applied to optimise the mix design of RCC mixtures incorporated RAP and rubber materials. Parameters such as compressive and flexural strengths, density and toughness index are selected to study RCC performance characteristics. The best possible levels of mix proportions are determined for maximising compressive and flexural strength with considering the toughness property. These optimal values in the preparation of RCC specimens are determined experimentally. In addition, an analysis of variance (ANOVA) is performed on RCC parameters such as flexural and compressive strengths and toughness index. ARTICLE HISTORY

The process of building design is a means of meeting client expectations for a building, followed by a set of comprehensive standards and codes relating to the design, construction, and maintenance of buildings. The rapidly rising volume of data along with increasing client expectations inspired many researchers to develop new computerized techniques to automate building design process. These techniques can be broken down into two broad categories: automated computer-aided design tools (e.g., development of building information modeling or BIM) and measuring or modeling client expectations (e.g., use of facial expressions to find psychological expectations of the client). Advances in artificial intelligence (AI) and machine learning have made possible new approaches to the automation of design. This represents a shift from a focus on client-designer or designer-technology relationships to a more intelligent and independent client-technology communication. In this paper, a novel AI system called intelligent designer is proposed to understand (or learn) the client's need and expectations and generate valid designs. The design environment (i.e., the interaction between the client and the design) is formulated as a Markov decision process (MDP) and a mathematical framework is provided for making design decisions in situations where new designs are partly random (as they are influenced by the client's feedback) and partly under the control of the computer (as they are influenced by the regulations, standards, and guidelines). The approach is demonstrated using a window design experiment.

The increasing costs of energy and water, fossil fuel depletion, and food shortages caused by climate change challenge long-term sustainability of food, energy, and water (FEW) systems. In working toward sustainable development, a fundamental question for deciding on whether and how to invest in FEW systems is " how sustainable FEW systems are? ". In order to measure sustainability across the FEW systems, an integrated sustainability index (SI) is developed. The SI is comprised of three components; food, energy, and water. These components each consist of different sub-components (e.g. transportation fuel for energy component) that make up integrated FEW systems. The sustainability of an FEW system can be calculated using the integrated FEW SI, but a more thought provoking question is to understand how each sub-component affects overall sustainability of the system. This cannot be achieved without formulating the interconnections associated with FEW components. This study formulates in-terconnections associated with FEW components. In an effort to increase the degree to which the results would generalize to FEW systems with different scales, the calculations of the study are performed for a sustainable FEW system that can consistently yield food for a family of four (two adults and two children) and supply its own water and energy needs from sustainable sources. Also, the sustainability is measured for two systems located in two different climates; one is relatively cloudy and humid and the other is sunny and arid. The results show that the highest sustainability improvement in both climates is associated with irrigation sub-component. Not only a sustainable water supply for irrigation sub-component improves the sustainability of water component, it also improves food sustainability and consequently energy sustainability. This finding can be explained by the fact that the irrigation sub-component is a resource supplier for grain sub-component, and that is a resource supplier for transportation fuel sub-component.

Labeling and mapping existing infrastructure is one of the grand challenges for civil engineers in the 21st century. The challenge remains in finding an appropriate data collection method that rapidly collects structural and geometrical information of bridges and automatically converts it into three-dimensional (3D) models. Over the last decade, there has been a tremendous effort to develop prototypes for capturing the as-is condition of a bridge and converting it into 3D bridge-information models (BrIMs). Bridge-information models are 3D-information-rich data models that can be used in various phases of bridge design, construction, operations, and maintenance. As an alternative solution, researchers are now studying the processing of videos to capture the required 3D information (videogrammetry) and using algorithms to automatically extract 3D objects and convert the results into a BrIM. This study evaluates the applicability of a novel videogrammetric pipeline for automatically documenting the physical condition of bridges. It also describes the results of three case studies of highway bridge assessment and modeling in which 3D information is extracted from two-dimensional video frames and point cloud data (PCD) are generated. As the next step, the PCD can be converted into a data-rich BrIM object for further processing.

The magnitude of building-and transportation-related GHG (greenhouse gas) emissions makes the adoption of all-EVs (electric vehicles) powered with renewable power as one of the most effective strategies to reduce emission of GHGs. This paper formulates the problem of GHG mitigation strategy under uncertain conditions and optimizes the strategies in which EVs are powered by solar energy. Under a pre-specified budget, the objective is to determine the type of EV and power generation capacity of the solar system in such a way as to maximize GHG emissions reductions. The model supports the three primary solar systems: off-grid, grid-tied, and hybrid. First, a stochastic optimization model using probability distributions of stochastic variables and EV and solar system specifications is developed. The model is then validated by comparing the estimated values of the optimal strategies and actual values. It is found that the mitigation strategies in which EVs are powered by a hybrid solar system lead to the best cost-expected reduction of CO 2 emissions ratio. The results show an accuracy of about 4% for mitigation strategies in which EVs are powered by a grid-tied or hybrid solar system and 11% when applied to estimate the CO 2 emissions reductions of an off-grid system. Published by Elsevier Ltd.

Since the early 2000s, building information modeling (BIM) has been used through the entire project life cycle to facilitate effective project collaboration and integration of data to support project activities. Despite the successful applications of BIM in the design and construction stages, the use of BIM for preconstruction planning has not gained wide acceptance as in other project phases. The integration of BIM and geospatial analyses can offer substantial benefits to manage the planning process during the design and preconstruction stages. However, this integration suffers from a lack of interoperability across the geospatial and BIM domains. Semantic web technology is used in this study to convey meaning, which is interpretable by both construction project participants as well as BIM and geographic information systems (GIS) applications processing the transferred data. To achieve this, we first translate building's elements and GIS data into a semantic web data format. Then we use a set of standardized ontologies for construction operations to integrate and query the heterogeneous spatial and temporal data. Finally, we use a query language to access and acquire the data in semantic web format. Through two scenario examples, the potential usefulness of the proposed methodology is validated.

When making design and construction decisions, planners must consider information from different scales and domains. Currently, building and geospatial data are shared and exchanged through a common data format, such as industry foundation classes (IFC). Because of the diversity and complexity of domain knowledge across building information modeling (BIM) and geographic information system (GIS) systems, however, these syntactic approaches are not capable of completely sharing semantic information that is unique in each system. This study uses semantic web technology to ensure semantic interoperability between existing BIM and GIS tools. The proposed approach is composed of three main steps: ontology construction, semantic integration through interoperable data formats and standards, and query of heterogeneous information sources. The completeness of the methodology is validated through a case study.

Purpose – This paper aims to develop a framework to represent semantic web query results as Industry Foundation Class (IFC) building models. The subject of interoperability has received
considerable attention in the construction literature in recent years. Given the distributed, semantically heterogeneous data sources, the problem is to retrieve information accurately and with minimal human intervention by considering their semantic descriptions.
Design/methodology/approach – This paper provides a framework to translate semantic web
query results into the XML representations of IFC schema and data. Using the concepts and relationships in an IFC schema, the authors first develop an ontology to specify an equivalent IFC entity in the query results. Then, a mapping structure is defined and used to translate and fill all query results
into an ifcXML document. For query processing, the proposed framework implements a set of predefined query mappings between the source schema and a corresponding IFC output schema. The resulting ifcXML document is validated with an XML schema validating parser and then loaded into a
building information modeling (BIM) authoring tool.
Findings – The research findings indicate that semantic web technology can be used, accurately and with minimal human intervention, to maintain semantic-level information when transforming information between web-based and BIM formats. The developed framework for representing
IFC-compatible outputs allows BIM users to query and access building data at any time over the web from data providers.
Originality/value – Currently, the results of semantic web queries are not supported by BIM authoring tools. Thus, the proposed framework utilizes the capabilities of semantic web and query technologies to transform the query results to an XML representation of IFC data.

In recent years, with the increasing level of competition in the global construction market, several research efforts
have focused on the application of information technology (IT) as a way to improve the integration process of construction
supply chain management (CSCM). Visual representation of the process can provide an effective tool for
monitoring resources in the CSCM. In order to support this objective, this paper integrates building information
modeling (BIM) and geographic information systems (GIS) into a unique system, which enables keeping track
of the supply chain status and provides warning signals to ensure the delivery of materials. First, the proposed
methodology is implemented by using BIM due to its capability to accurately provide a detailed takeoff in an
early phase of the procurement process. Furthermore, in order to support the wide range of spatial analysis
used in the logistics perspective (warehousing and transportation) of the CSCM, GIS is used in the present
model. Thus, this paper represents the integrated GIS-BIM model manifesting the flow of materials, availability
of resources, and “map” of the respective supply chains visually. A case example is presented to demonstrate the
applicability of the developed system.

Tower cranes, on today’s typical building construction sites, are the centerpiece of production,
hoisting and transporting of a variety of loads. Occasionally tower cranes operate with overlapping work zones
and often under time, cost and labor constraints. Identifying optimal number and location of tower cranes is an
important issue that can reduce conflicts between groups of tower cranes. Geographic information systems (GIS)
facilitate the analysis of large amounts of spatial data used in the process of location optimization for tower cranes.
In addition, integrating analysis results from GIS with 3D visual models enables managers to visualize the potential
conflicts with tower cranes in great detail. Building Information Modeling (BIM) helps managers to visualize
buildings before implementation takes place through a digitally constructed virtual model. Hence, in this
paper, the integrated GIS-BIM model starts with the identification of feasible locations for defined tower cranes.
The method presented is based on previous works using “geometric closeness” and coverage of all demand and
supply points as key criteria for locating a group of tower cranes*). Once the geometry of the construction site is
generated by the BIM tool, the model determines the proper combination of tower cranes in order to optimize
location. The output of the GIS model includes one or more feasible areas that cover all demand and supply
points, which is then linked to the BIM tool and generates 3D models to visualize the optimum location of tower
cranes. As a result, potential conflicts are detected in different 3D views in order to identify optimal location of
tower cranes. To address the feasibility of a GIS-BIM integrated model for layout of tower cranes, an actual
case example is introduced.