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Wissenschaftliches Kolloquium vom 27. bis 30. Juni 1989 in Weimar an der Hochschule für Architektur und Bauwesen zum Thema: ‚Produktivkraftentwicklung und Umweltgestaltung. Sozialer und wissenschaftlich-technischer Fortschritt in ihren Auswirkungen auf Architektur und industrielle Formgestaltung in unserer Zeit. Zum 100. Geburtstag von Hannes Meyer'
Due to the importance of identifying crop cultivars, the advancement of accurate assessment of cultivars is considered essential. The existing methods for identifying rice cultivars are mainly time-consuming, costly, and destructive. Therefore, the development of novel methods is highly beneficial. The aim of the present research is to classify common rice cultivars in Iran based on color, morphologic, and texture properties using artificial intelligence (AI) methods. In doing so, digital images of 13 rice cultivars in Iran in three forms of paddy, brown, and white are analyzed through pre-processing and segmentation of using MATLAB. Ninety-two specificities, including 60 color, 14 morphologic, and 18 texture properties, were identified for each rice cultivar. In the next step, the normal distribution of data was evaluated, and the possibility of observing a significant difference between all specificities of cultivars was studied using variance analysis. In addition, the least significant difference (LSD) test was performed to obtain a more accurate comparison between cultivars. To reduce data dimensions and focus on the most effective components, principal component analysis (PCA) was employed. Accordingly, the accuracy of rice cultivar separations was calculated for paddy, brown rice, and white rice using discriminant analysis (DA), which was 89.2%, 87.7%, and 83.1%, respectively. To identify and classify the desired cultivars, a multilayered perceptron neural network was implemented based on the most effective components. The results showed 100% accuracy of the network in identifying and classifying all mentioned rice cultivars. Hence, it is concluded that the integrated method of image processing and pattern recognition methods, such as statistical classification and artificial neural networks, can be used for identifying and classification of rice cultivars.
Integrated structural engineering system usually consists of large number of design objects that may be distributed across different platforms. These design objects need to communicate data and information among each other. For efficient communication among design objects a common communication protocol need to be defined. This paper presents the elements of a communication protocol that uses a mediator agent to facilitate communication among design objects. This protocol is termed the Mediative Communication Protocol (MCP). The protocol uses certain design communication performatives and the semantics of an Agent Communication language (ACL) mainly the Knowledge and Query Manipulation Language (KQML) to implement its steps. Details of a Mediator Agent, that will facilitate the communication among design objects, is presented. The Unified Modeling Language (UML) is used to present the Meditative protocol and show how the mediator agent can be use to execute the steps of the meditative communication protocol. An example from structural engineering application is presented to demonstrate and validate the protocol. It is concluded that the meditative protocol is a viable protocol to facilitate object-to-object communication and also has potential to facilitate communication among the different project participants at the higher level of integrated structural engineering systems.
Identification of modal parameters of a space frame structure is a complex assignment due to a large number of degrees of freedom, close natural frequencies, and different vibrating mechanisms. Research has been carried out on the modal identification of rather simple truss structures. So far, less attention has been given to complex three-dimensional truss structures. This work develops a vibration-based methodology for determining modal information of three-dimensional space truss structures. The method uses a relatively complex space truss structure for its verification. Numerical modelling of the system gives modal information about the expected vibration behaviour. The identification process involves closely spaced modes that are characterised by local and global vibration mechanisms. To distinguish between local and global vibrations of the system, modal strain energies are used as an indicator. The experimental validation, which incorporated a modal analysis employing the stochastic subspace identification method, has confirmed that considering relatively high model orders is required to identify specific mode shapes. Especially in the case of the determination of local deformation modes of space truss members, higher model orders have to be taken into account than in the modal identification of most other types of structures.
The characteristic values of climatic actions in current structural design codes are based on a specified probability of exceedance during the design working life of a structure. These values are traditionally determined from the past observation data under a stationary climate assumption. However, this assumption becomes invalid in the context of climate change, where the frequency and intensity of climatic extremes varies with respect to time. This paper presents a methodology to calculate the non-stationary characteristic values using state of the art climate model projections. The non-stationary characteristic values are calculated in compliance with the requirements of structural design codes by forming quasi-stationary windows of the entire bias-corrected climate model data. Three approaches for the calculation of non-stationary characteristic values considering the design working life of a structure are compared and their consequences on exceedance probability are discussed.
The fire resistance of concrete members is controlled by the temperature distribution of the considered cross section. The thermal analysis can be performed with the advanced temperature dependent physical properties provided by 5EN6 1992-1-2. But the recalculation of laboratory tests on columns from 5TU6 Braunschweig shows, that there are deviations between the calculated and measured temperatures. Therefore it can be assumed, that the mathematical formulation of these thermal properties could be improved. A sensitivity analysis is performed to identify the governing parameters of the temperature calculation and a nonlinear optimization method is used to enhance the formulation of the thermal properties. The proposed simplified properties are partly validated by the recalculation of measured temperatures of concrete columns. These first results show, that the scatter of the differences from the calculated to the measured temperatures can be reduced by the proposed simple model for the thermal analysis of concrete.