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Individual views on a building product of people involved in the design process imply different models for planning and calculation. In order to interpret these geometrical, topological and semantical data of a building model we identify a structural component graph, a graph of room faces, a room graph and a relational object graph as aids and we explain algorithms to derive these relations. The application of the technique presented is demonstrated by the analysis and discretization of a sample model in the scope of building energy simulation.
The presented work focuses on the presentation of a discrete event simulator which can be used for automated sequencing and optimization of building processes. The sequencing is based on the commonly used component–activity–resource relations taking structural and process constraints into account. For the optimization a genetic algorithm approach was developed, implemented and successfully applied to several real life steel constructions. In this contribution we discuss the application of the discrete event simulator including its optimization capabilities on a 4D process model of a steel structure of an automobile recycling facility.
Many problems related to data integration in AEC can be better tackled by an approach that takes into account the heterogeneity of tasks, models and applications but does not require continuous consistency of the evolving design data, at each data management operation. Such an approach must incorporate adequate services that can facilitate reintegration of concurrently modified data at reasonably selected coordination points. In this paper we present a set of methods which, used in combination, can achieve that goal. After a description of the principal envisaged cooperative work scenario each of these methods is discussed in detail and current observations drawn from their software realisation are given. Whilst the suggested approach is valid for any EXPRESS-based data model, the practical focus of work has been on facilitating IFC-driven integration.
Civil engineering decision support systems (construction, building life cycle, refurbishment, total quality management, innovation, etc.) created in Lithuania are described in this paper. The above decision support systems comprise of the following constituent parts: data (database and its management system), models (model base and its management system) and a user interface. Presentation of information in databases may be in conceptual (digital, textual, graphical, photographic, video) and quantitative forms. Quantitative information presented involves criteria systems and subsystems, units of measurement, values and initial weight fully defining the variants provided. The databases were developed providing a multiple criteria analysis of alternatives from economical, infrastructure, technical, technological, qualitative, legislative, social and other perspectives. This information is provided in a user-oriented way. Since the analysis of alternatives is usually performed by taking into account economical, infrastructure, technical, technological, qualitative and other factors, a model-base include models which enable a decision maker to carry out a comprehensive analysis of the variants available and make a proper choice. These systems, related questions and practical case study were analysed the paper.