Hesham Osman

A hybrid CAD-based construction site layout planning system using genetic algorithms

The efficient layout planning of a construction site is a fundamental task to any project undertaking. In an attempt to enhance the general practice of layout planning of construction sites, the paper introduces a novel approach for producing the sought layouts. This approach integrates the highly sophisticated graphical capabilities of computer-aided design (CAD) platforms with the robust search and optimization capabilities of genetic algorithms (GAs). In this context, GAs are utilized from within the CAD environment to optimize the location of temporary facilities on site. The functional interaction between GAs and CAD and the details of the GA-based layout optimization procedure are presented. A fully automated computer system is further developed to demonstrate the practicality of the chosen approach. In order to evaluate the systems performance, a local construction project with a 24,000m2 site is used. The automated system produced highly satisfactory results and showed notable flexibility through its CAD-based input/output media.

Comparison of Statistical Deterioration Models for Water Distribution Networks

The use of water main break history as a proxy for condition has become common practice because of the high costs associated with direct assessments. Statistical deterioration models predict future water main breaks on the basis of historical patterns. Many municipalities are beginning to understand the value of utilizing water pipe break histories to manage their noncritical distribution networks via deterioration models. This paper presents a generic IDEF0 process model for developing water main deterioration models. Two common statistical deterioration models for water pipes are compared: rate-of-failure models (ROF) and transition-state (TS) models. ROF models extrapolate the breakage rate for a particular cohort of pipes and do not differentiate between the times between successive failures. On the other hand, transition-state models attempt to model the time between successive failures for pipes. This paper presents a comparison and analysis of ROF models and transition-state models by using a singl...

Risk-Based Life-Cycle Cost Analysis of Privatized Infrastructure

One main shortcoming in the use of life-cycle cost analysis (LCCA) for analyzing long-term infrastructure projects is the uncertainty in the value of the LCCA parameters. Probabilistic LCCA incorporates these elements of uncertainty by assigning probabilistic values to cost and performance parameters. Studies that have performed probabilistic LCCA in the infrastructure domain propose a probability-based framework for alternative comparison. Although such frameworks convey a wealth of probabilistic information, they are not well suited to decision making. This study proposes a risk-based framework that is similar to techniques used in portfolio risk management. To illustrate the use of such a framework, a Monte Carlo simulation is used to perform probabilistic LCCA for a highway project. Two highway investment opportunities with varying risks and returns are analyzed. The decision framework is used to compare the simulation results with some common investment opportunities in the market. This framework ena...

Ontological Modeling of Infrastructure Products and Related Concepts

The large number of infrastructure renewal projects taking place along congested urban transportation corridors poses several challenges for all project proponents. As such, closer integration of processes between all stakeholders is required throughout a project life cycle. This integration can be accomplished through enhancing interorganizational information interoperability. This paper presents ontologies, an emerging tool that is gaining momentum in the computer science field and has great potential to facilitate knowledge sharing and interoperability. A four-layer distributed ontology for representing infrastructure products and related concepts is presented. The root level is a representation of the abstract superclasses (entities and supporting concepts) on which the next levels construct their semantics. The next two levels are considered ontologies specific to the domain of infrastructure products but are created at different levels of detail to maintain consistency with other ontology development efforts. The final level is the application ontology that uses the core knowledge defined at the domain level to create sets of task-specific ontologies. In this paper, an urban infrastructure design coordination ontology is presented. The ontology was then used to build a collaborative system based on the geographic information system to support design coordination of utilities along urban transportation corridors. The system demonstrates how ontologies can be used to streamline the utility design coordination process among utility companies and municipalities.

Coordination of urban infrastructure reconstruction projects

The large number of urban infrastructure renewal activities occurring in cities throughout the world leads to social, economic and environmental impacts on the communities in its vicinity. As such, a coordinated effort is required to streamline these activities. This paper presents a framework to enable temporal (time-based) coordination of water, sewer and road intervention activities. Intervention activities include routine maintenance, renewal and replacement of physical assets. The coordination framework considers (1) life-cycle costs, (2) infrastructure level-of-service and (3) risk exposure to system operators. The model enables infrastructure asset managers to trade-off options of delaying versus bringing forward intervention activities of one system in order to be executed in conjunction with another co-located system in the right-of-way. The framework relies on a combination of meta-heuristics and goal-based optimisation. In order to demonstrate the applicability of the framework, a case study for a major infrastructure corridor in Cairo, Egypt, is taken as an example. Results show that the framework can be scaled up to include other infrastructure systems located in the right-of-way like electricity, gas and telecom, provided that information can be shared among these entities

Optimizing Inspection Policies for Buried Municipal Pipe Infrastructure

Condition assessment is an integral component in any infrastructure asset management system. Without condition information, asset managers lack the ability to make appropriate decisions regarding needed maintenance, rehabilitation, and replacement of infrastructure. Existing and emerging technologies for assessing the condition of water and sewer pipes provide a better picture of the state of these buried assets. Unfortunately, many of these technologies are costly and provide results that are not always highly reliable. This paper presents a methodology to assist asset managers in balancing the value of information revealed by a condition assessment technology with the cost of obtaining this information. The paper describes the computational platform of the developed methodology and focuses primarily on the optimization process that utilizes the partially observable Markov decision process (POMDP) and genetic algorithms. This policy determines the most appropriate condition assessment technology and interval between inspections. The developed methodology takes into consideration direct and indirect costs of infrastructure failure. Optimization models are developed at both the asset and network levels. A case study of the water distribution network for the city of Hamilton, Canada, is presented to demonstrate the use and capabilities of the developed methodology. At the asset level, results allow the asset manager to select the most suitable condition assessment technology and inspection interval for a particular pipe. At the network level, results enable the proper allocation of a condition assessment budget across all pipes in the system.

Integrating Value Engineering and Context-Sensitive Solutions: The St. Clair Avenue West Transit Improvements Project

The designers of transportation infrastructures are increasingly using the term “context-sensitive design” (CSD) or the broader term “context-sensitive solutions” (CSSs) to refer to a design process that strives to be more cognizant of its surrounding environment. Transportation infrastructures, especially in urban environments, are part of a much larger urban ecology that consists of a complex set of natural and human-made systems. As such, design guidelines that solely address engineering and safety considerations have proved themselves incapable of delivering street designs that respond to the functional requirements of the multitude of stakeholders within urban environments. Analysis of these requirements is a necessary first step for any successful CSD-CSS. In this regard, value engineering has been identified as a successful tool for product functional analysis. Several phases of value engineering overlap with the guiding principles of CSD-CSS. As such, this paper presents a value engineering framework that can be used for the analysis of the functional requirements of urban streets within a CSD-CSS approach. To place the proposed framework into context, a major transit improvement project in the city of Toronto, Ontario, Canada, was studied. Seven of the main design elements were analyzed against the primary and secondary objectives identified by the value engineering process. Almost all objectives were attained by the design elements selected. The proposed framework and analysis of the case study show that the value engineering methodology can be efficiently used to address the needs of CSD design of urban streets.

A simulation-based planning system for wind turbine construction

Wind turbine construction is a challenging undertaking due to the need to lift heavy loads to high locations in conditions of high and variable wind speeds. These conditions create great risks to contractors during the turbine assembly process. This paper presents a simulation-based system to aid in the construction planning of wind turbines. The system is composed of three main components; 1) A wind speed forecasting module based on artificial neural networks, 2) A series of discrete event simulation models that act as a test bed for different turbine construction methods and resource utilizations, and 3) A rule-based system that relates prevalent wind speed to the impact on lifting activity durations. Actual wind speed data from the Zafarana wind farm in Egypt is used and turbine construction productivity and resource utilization is compared for two common turbine construction methods.

LAYOUT PLANNING OF CONSTRUCTION SITES CONSIDERING MULTIPLE OBJECTIVES: A GOAL- PROGRAMMING APPROACH

The construction site layout planning problem has been studied by several researchers for the last 15 years; each presenting it from his/her own perspective. Yet, one fundamental aspect of site layout planning was not as well investigated and documented in the literature, that is, considering several planning objectives simultaneously. In principle, objectives nee d to be achieved by a site layout are many and could include transportation costs, labor movement, material handling, safety consideration, etc. These objectives are rather heterogeneous and in some cases conflicting. The paper attempts to handle this real ity by using the optimization capabilities of goal programming (GP). While traditional optimization tools aim at finding the optimum solution for an objective function, GP seeks a solution that satisfies as many goals as possible rather than optimizing a s ingle goal, which fully suits the case in hand. Formulation and specifics of the GP model are elaborated on in the paper, including use of the analytical hierarchy process (AHP) to identify the priorities among the various objectives. Following the computerization of the model, a case study of a university campus extension project in Toronto, Canada, was utilized to demonstrate the workings of this model.

A systems engineering approach for realizing sustainability in infrastructure projects

Abstract Sustainability is very quickly becoming a fundamental requirement of the construction industry as it delivers its projects; whether buildings or infrastructures. Throughout more than two decades, a plethora of modeling schemes, evaluation tools and rating systems have been introduced en route to realizing sustainable construction. Many of these, however, lack consensus on evaluation criteria, a robust scientific model that captures the logic behind their sustainability performance evaluation, and therefore experience discrepancies between rated results and actual performance. Moreover, very few of the evaluation tools available satisfactorily address infrastructure projects. This paper introduces a systems model that abstracts the environment, the construction product, and its production system as three interacting systems that basically exchange materials, energy and information. The model utilizes this setup to capture and quantify essential flows exchanged between such three systems, with the objective of evaluating sustainability. The paper walks through the development of a generic case of the model, and then demonstrates its utility in evaluating the sustainability performance of civil infrastructure projects using a typical water pipeline installation project that uses horizontal directional drilling (HDD) technology as a trenchless installation method. The developed model addresses an identified gap within the current body of knowledge by considering infrastructure projects. Through the ability to simulate different scenarios, the model enables identifying which activities, products, and processes impact the environment more, and hence potential areas for optimization and improvement.