Structural optimization has matured from a narrow academic discipline, where researchers focused on the optimum design of small-idealized structural components and systems, to become the basis in modern design of complex structural systems.

Some software applications in recent years have made these tools accessible to professional engineers, decision-makers and students outside the structural optimization research community.

These software applications, mainly focused on aerospace, aeronautical, mechanical and naval structural systems, have incorporated the optimization component primarily as an additional feature of the finite element software package.

However, these tools fall short of meeting the needs of the professional engineer. ACE OCP has been created to fill this gap by offering a holistic optimization approach in terms of final design stage for real-world civil engineering structures such as buildings, bridges or more complex civil engineering structures.

Optimization is the act of obtaining the best result under given circumstances. In design, construction, and maintenance of any engineering system, engineers have to take many technological and managerial decisions at several stages.

The ultimate goal of all such decisions is either to minimize the effort required or to maximize the desired benefit. Among others construction and material cost reduction can be achieved.

Design optimization refers to the process of generating improved designs in terms of cost, manufacturability or performance without compromising safety. Structural optimization problems are characterized by various objective and constraint functions that are generally non-linear functions of the design variables. ACE OCP supports various objective functions.

The implementation of optimum design formulations to real-world problems requires significant computational effort which can only be addressed with a synergy of cutting edge technologies in the field. Therefore, the tools required for dealing with structural optimization problems basically must serve four purposes: (i) accurate numerical modelling of the structural system, (ii) structural analysis for calculating response quantities such as displacements and stresses under various loading conditions, (iii) design procedure for performing the constraints checks imposed by the design codes and/or the design engineers and (iv) efficient optimization algorithm for achieving optimized designs that satisfy both design requirements and economic, manufacturability or performance criteria. ACE OCP harnesses technology to drive efficiency, increase performance and reduce cost while preserving safety excellence.

ACE OCP is the result of over 20-years of Research and Development including practical experience in developing a general-purpose code for structural analysis and design optimization in the form of a modular standalone code co-developed by ACE-Hellas and the Institute of Structural Analysis and Antiseismic Research of NTUA. Methodology integrated into ACE OCP add-on has been approved with the publication of the theoretical framework and indicative results in the official Journal (http://goo.gl/cZIbgB) of the International Society for Structural and Multidisciplinary Optimization (ISSMO, http://www.issmo.net).

ACE OCP is based on the next generation computational procedures and the implementation of such computing tools is expected to have a profound impact in optimized design of structural systems, leading to revolutionary changes in civil engineering design practice. Effectively, it makes value engineering available to every professional engineer.

ACE OCP add-on has been successfully implemented in a variety of real-world structural systems, leading to cost reduction of up to 30%. Among others it has been used for optimizing the Beijing National Stadium (Bird’s Nest) and the Beijing National Aquatics Centre (Water Cube) where ACE OCP produced design improvements leading to a cost reduction of 10%. In other projects ACE OCP delivered improved designs to drive better structural performance while maintaining the same financial allocation.