Visualizing Search and Solution Spaces in the Optimum Design of Biaxial Columns

Abstract

Optimum detailing of reinforcement bars for biaxial columns is a non-trivial task and there is no guidance in the codes of practice on this issue. Conventional methods of producing a single design solution and the use of optimization methods to find a single global optimum solution is not what practicing engineers require. This paper introduces an innovative approach to design, which emphasizes the interactive use of evolutionary computing in design and a new approach to visualization of search and solution spaces. This replaces the 'black box' nature of the optimization techniques with an interactive approach in which the designer is in full control of the process. Instead of locating a single solution, clusters of good designs are identified in color which allows the designer to conduct a more focused search in the areas of high performance design solutions. This method enables the designer to view individual solutions in the vicinity of the local peaks in order to learn more about the interrelationship between design parameters. Interactive visualization tools enable designers to develop a deeper understanding of the search and solution spaces and assist them in evaluating the merits of alternative designs and in their decision making. A by-product of visualization is knowledge discovery which allows the designer to discover novel solutions which would not have been possible by conventional means. This approach could be easily extended to any stage of multidisciplinary design, especially to the conceptual stage of the design process. For example the position of bars within a column is similar to the position of columns in a floor layout optimization problem.

Automatic code compliance with multi-dimensional data fitting in a BIM context

“…: simple logical approach [54][55][56], predicate [57,58], deontology [59], ontological [60,61], Object-based approach [54,[62][63][64][65][66][67][68][69], programmatic aspects [70] or machine learning [71]. It appears that the current literature on structural design ACC within BIM is of a design concept nature rather than industry application of [48,69,[72][73][74][75][76][77][78][79][80][81][82]. Aimi Sara Ismail used a quote from the book 'Object-Oriented Methods: A foundation' [83], to justify the statement that 'The variety of different techniques will always continue to develop in this field, the challenge is how to select and integrate these approaches' [84].…”

Determining the structural layout of orthogonal framed buildings

“…As discussed above, the work required is so complex that inevitably it has to be tackled in a piecemeal fashion with various research teams working on different aspects. So for example Parmee and Abraham [10], Rafiq et al [12] and Grierson [2] are looking at how to communicate the search results to the user: Rivard [14] looks at some aspects of information capture relating to architects' sketches. Zhang et al [20] are investigating topological reasoning.…”

Heuristic optimization of RC bridge piers with rectangular hollow sections

“…And more recently, research by Rafiq et al examined the design of biaxial columns [16]. Since 2005, our research group has also studied the application of mainly simulated annealing and threshold acceptance to the optimization of RC walls, bridge frames, building frames, bridge piers and vault underpasses [17][18][19][20][21][22].…”