Structural design using matrix-based performance indicators

Abstract

The development and realization of civil engineering structures involves a wide range of disciplines, amongst which architectural design and structural engineering are key to transform early drafts into viable buildings. This thesis is concerned with the matrix-based assessment of structures to enrich the existing performance evaluation at the verge of design and engineering. Special emphasis on the use of these structural assessment strategies lies in early planning stages and design exploration stages. The degree of static indeterminacy is probably the most widely known and a load-independent measure for evaluating structural performance. The question which element is redundant with which other element can be answered using the so-called redundancy matrix. The application of the redundancy matrix is showcased in the field of robust structural design as well as in the assessment of structural assembly, which is tightly connected to the imperfection sensitivity of structures. Similar to the quantification of static indeterminacy, an in-depth study of distributed kinematic indeterminacy is presented. Another way to assess structures comes with graph theory, a branch of mathematics, which is also independent of explicit load cases and stiffness distributions. Combining graph-theoretical structural assessment and redundancy analysis offers yet another way to thoroughly analyze structures. Supported by a literature review of the above-mentioned structural assessment strategies, involving state of the art specifications in standards, the central aspect of this thesis is the application to structural design. A systematic study reveals the advantages and applicability of new performance indicators within structural optimization schemes.