Refine
Has Fulltext
- yes (27) (remove)
Document Type
- Conference Proceeding (23)
- Article (4)
Keywords
- Bauwerk (27) (remove)
Year of publication
- 2004 (27) (remove)
The problem of data interoperability is now very important. The formal description of construction systems and objects must base upon the modeling for the description of construction data domain. The XML-language was selected as a basis of a universal data format, ensuring natural hierarchy of objects, flexibility, good layout and expandability. The language, developed by the author, is called Building Object Description Extensible Markup Language (bodXML). The types of all objects used by data transfer should be definite beforehand with existing methods of programming. It limits the possibilities of IT in application of new types. But the recipient software must recognize the building objects even if the kind of object is unknown at the outset. The author offers a set of main topological and geometric properties being sufficient for recognition of main three-dimensional building constructions with flat edges. The tests of artificial neuron network have shown that the recognition of a kind of the constructions represented as a set of indicated parameters happens enough confidently.
The paper describes further developments of the interactive evolutionary design concept relating to the emergence of mutually inclusive regions of high performance design solutions. These solutions are generated from cluster-oriented genetic algorithm (COGAs) output and relate to a number of objectives introduced during the preliminary design of military airframes. The data-mining of multi-objective COGA (moCOGA) output further defines these regions through the application of clustering algorithms, data reduction and variable attribute relevance analyses. A number of visual representations of the COGA output projected onto both variable and objective space are presented. The multi-objective output of the COGA is compared to output from a Strength Pareto Evolutionary Algorithm (SPEA-II) to illustrate the manner in which moCOGAs can generate good approximations to Pareto frontiers.
The evolution of data exchange and integration standards within the Architectural, Engineering and Construction industry is gradually making the long-held vision of computer-integratedconstruction a reality. The Industry Foundations Classes and CIMSteel Integration Standards are two such standards that have seen remarkable successes over the past few years. Despite successes, these standards support the exchange of product data more than they do process data, especially those processes that are loosely coupled with product models. This paper reports on on-going research to evaluate the adequacy of the IFC and CIS/2 standards to support process modeling in the steel supply chain. Some initial recommendations are made regarding enhancements to the data standards to better support processes.
At the start of the conceptual design process, designers start to give tangible form to their thoughts by sketching. This helps with reasoning and communicates ideas to other members of the team. Sketches are gradually worked up into more formal drawings which are then passed to the other stages of the design process. There are however some problems with basing early ideas on sketching. For example, due to their ad-hoc nature, sketches tend only to be diagrammatic representations and so designers cannot be sure that their ideas are feasible and what is being proposed meets the constraints described in the client brief. This can result in designers wasting time working up ideas which prove to be unsuitable. Also the process of constraint checking is complex and time consuming and so designers tend limit their search of possible options and instead choose satisfying rather than good solutions. This paper describes the INTEGRA project which examines the role of sketching in early conceptual design and how this can be linked to other aspects of the process and particularly automated constraint checking using an IT based approach. The focus for the work is the design of framed buildings. A multi-disciplinary approach has been adopted and the work has been undertaken in close collaboration with practising designers and clients.
There are many construction projects in China and mass documents are exchanged among the multi-party, including the owner, the contractor and the engineer in the projects. Based on previous studies, an approach to the utilization of the exchanged documents is established by using data warehouse technology and a prototype system called EXPLYZER is developed. The approach and the prototype system are verified through their application in a construction project. It is concluded that the approach can support the decision-making in project management.
Advances in construction data analysis techniques have provided useful tools to discover explicit knowledge on historical databases supporting project managers’ decision making. However, in many situations, historical data are extracted and preprocessed for knowledge discovery based on time-consuming and problem-specific data preparation solutions, which often results in inefficiencies and inconsistencies. To overcome the problem, we are working on the development of a new data fusion methodology, which is designed to provide timely and consistent access to historical data for efficient and effective management knowledge discovery. The methodology is intended to be a new bridge between historical databases and data analysis techniques, which shields project managers from complex data preparation solutions, and enables them to use discovered knowledge for decision making more conveniently. This paper briefly describes the motivation, the background and the initial results of the ongoing research.
In current AEC practice client requirements are typically recorded in a building program, which, depending on the building type, covers various aspects from the overall goals, activities and spatial needs to very detailed material and condition requirements. This documentation is used as the starting point of the design process, but as the design progresses, it is usually left aside and changes are made incrementally based on the previous design solution. These incremental small changes can lead to a solution that may no longer meet the original requirements. In addition, design is by nature an iterative process and the proposed solutions often also cause evolution in the client requirements. However, the requirements documentation is usually not updated accordingly. Finding the latest updates and evolution of the requirements from the documentation is very difficult, if not impossible. This process can lead to an end result, which is significantly different from the documented requirements. Some important requirements may not be satisfied, and even if the design process was based on agreed-upon changes in the scope and requirements, differences in the requirements documents and in the completed building can lead to well-justified doubts about the quality of the design and construction process...
All construction project are constrained by their schedules, budgets and specifications, and safety and environmental regulations. These constraints made construction management more complex and difficult. At the same time, many historical data that can support the decisions in the future are kept in construction enterprises,. To use the historical data effectively and efficiently, it is essential to apply the data warehouse and data mining technologies. This paper introduces a research which aims to develop a data warehouse system according to the requirements of construction enterprises and use data mining technology to learn useful information and knowledge from the data warehouse system. The design, the development and the application of this system are detailedly introduced in this paper.
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.