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Available construction time-cost trade-off analysis models can be used to generate trade-offs between these two important objectives, however, their application is limited in large-scale construction projects due to their impractical computational requirements. This paper presents the development of a scalable and multi-objective genetic algorithm that provides the capability of simultaneously optimizing construction time and cost large-scale construction projects. The genetic algorithm was implemented in a distributed computing environment that utilizes a recent standard for parallel and distributed programming called the message passing interface (MPI). The performance of the model is evaluated using a set of measures of performance and the results demonstrate the capability of the present model in significantly reducing the computational time required to optimize large-scale construction projects.
The scientific transfer of key technology features to developing countries, together with adequate competence, localisation and adaptation, is the primary purpose of the proposed investigation. It is evident that introducing high-level CAD design and detailing will improve the planning process in developing countries. Successful utilization of applied information technology for the planning process, however, depends on the user-interface of individual software. Therefore, to open the great opportunity embedded in CAD software for clients globally, the language and character-set barrier of traditional user-interfaces must be overcome. A proposal for a research program is given here to address such issue in favour of global civil engineering.
We present a software prototype for fluid flow problems in civil engineering, which combines essential features of Computational Steering approaches with efficient methods for model transfer and high performance computing. The main components of the system are described: - The modeler with a focus on the data management of the product model - The pre-processing and the post-processing toolkit - The simulation kernel based on the Lattice Boltzmann method - The required hardware for real-time computing
This paper reports on the latest results in the development of a new approach for simulating the thermal behavior of buildings that overcomes the limitations of conventional heat-transfer simulation methods such as FDM and FEM. The proposed technique uses a coarse-grain approach to model development whereby each element represents a complete building component such as a wall, internal space, or floor. The thermal behavior of each coarse-grain element is captured using empirical modeling techniques such as artificial neural networks (ANNs). The main advantages of the approach compared to conventional simulation methods are: (a) simplified model construction for the end-user; (b) simplified model reconfiguration; (c) significantly faster simulation runs (orders of magnitude faster for two and three-dimensional models); and (d) potentially more accurate results. The paper demonstrates the viability of the approach through a number of experiments with a model of a composite wall. The approach is shown to be able to sustain highly accurate longterm simulation runs, if the coarse-grain modeling elements are implemented as ANNs. In contrast, an implementation of the coarse-grain elements using a linear model is shown to function inaccurately and erratically. The paper concludes with an identification of on-going work and future areas for development of the technique.
The methods currently used for scheduling building processes have some major advantages as well as disadvantages. The main advantages are the arrangement of the tasks of a project in a clear, easily readable form and the calculation of valuable information like critical paths. The main disadvantage on the other hand is the inflexibility of the model caused by the modeling paradigms. Small changes of the modeled information strongly influence the whole model and lead to the need to change many more details in the plan. In this article an approach is introduced allowing the creation of more flexible schedules. It aims towards a more robust model that lowers the need to change more than a few information while being able to calculate the important propositions of the known models and leading to further valuable conclusions.
This ethnographic study reports on emerging work processes and practices observed in the AEC (Architecture/Engineering/Construction) Global Teamwork program, i.e., what people experience when interacting with and through collaboration technologies, why people practice in the way they do, how the practice fits into the environment and changes the work patterns. It presents the experience of two high-performance typical but extreme AEC teamwork cases adopting and adapting to collaboration technologies and how these technologies in practice impact their work processes. The findings illustrate the importance of collaboration technologies in cross-disciplinary, global teamwork. Observations indicate that high performance teams that use the collaboration technologies effectively exhibit collaboration readiness at an early stage and manage to define a “third way” to meet the demands of the cross-disciplinary, multi cultural and geographically distributed AEC workspace. The observations and implications represent the blueprint for yearly innovations and improvements to the design of the AEC Global Teamwork program.
Re-using knowledge in architecture, engineering and construction (AEC) firms can lead to greater competitive advantage, improved designs, and more effective management of constructed facilities. This paper discusses the importance of exploration and discovery of reusable knowledge from a corporate archive as opposed to simple search and retrieval. We describe and illustrate through a scenario of use an exploration framework and prototype, CoMemTM that formalizes the added value of exploration in the process of knowledge reuse. We discuss two exploration activities: (i) Breadth- Only overview exploration that assist a user to rapidly localize pockets of re-usable knowledge from the large corporate archive and (ii) Iterative breadth-depth exploration that enables a user to identify those re-usable components of the Corporate Memory that may yield design issues that were not originally considered.
A/E/C Team members, while collaborating on building projects, rely on past experiences and content through the use of project design archives (whether in paper or digital format). This leads to underutilization of potential knowledge, as decision-making of data, information, and knowledge reuse is limited by access to these archives, due to sheer size and inconvenient presentation. This paper presents an integrated solution that leverages two technologies CoMem (Corporate Memory) and iRoom (interactive Room) developed at Stanford. This addresses critical limitations, i.e., content, context, visualization and interactivity, constraining the process of collaborative exploration towards knowledge reuse and decision-making.
The process of matching data represented in two different data models is a longstanding issue in the exchange of data between different software systems. While the traditional manual matching approach cannot meet today’s demands on data exchange, research shows that a fully automated generic approach for model matching is not likely, and generic semi-automated approaches are not easy to implement. In this paper, we present an approach that focuses on matching data models in a specific domain. The approach combines a basic model matching approach and a version matching approach to deduce new matching rules to enable data transfer between two evolving data models.
Re-examination of the behaviour of structures can be necessary due to deterioration or changes in the traffic situation during their lifetime. The Finite Element Method (FEM) is widely used in order to accomplish numerical analysis. Considering the development of computer performance, more detailed FEM models can be analyzed, even on site, with mobile computers. To compensate the increasing amount of data needed for the model input, measures need to be taken to save time, by distributing the work. In order to provide consistency to the model, fedback data must be checked upon reception. A local wireless computer network of ultra-portable devices linked together with a computer can provide the coordination necessary for efficient parallel working. Based on a digital model consisting of all data gathered, structural modelling and numerical analysis are performed automatically. Thus, the user is released from the work that can be automatized and the time needed for the overall analysis of a structure is decreased.