Performance enhancement of active structures during service lives

This thesis describes a successful application of advanced computational methods to tasks in the field of active structural control. The control-task involves finding good control movements for a highly coupled, non-linear structure. It is demonstrated how these methods improve the accuracy of the analytical model. Also, stochastic search techniques are compared for the same task. Furthermore, the performance of the system can be enhanced during service life by storing, retrieving and adapting good solutions. The structure studied, a Tensegrity, is a special type of cable structure. Tensegrities stimulate the imagination of artists, researchers and engineers. Varying the amount of selftress changes structural shape as well as the load-bearing capacity. They offer unique applications, as deployable structures in the context of aerospace applications and more generally, as actively controlled structures. However, the non-linear behavior of tensegrities is difficult to model. Aspects of this work involve subjects such as tensegrity structures, active structural control, search algorithms and artificial intelligence. The focus of this thesis is on the last two subjects. This work demonstrates how advanced computing techniques can be used in order to increase solution quality. A hybrid approach, employing neural networks, increases the accuracy of the analytical model that is employed for simulating tensegrity structures. A comparison of three stochastic search techniques shows that computational time, first estimated to take centuries when adapting a "brute-force" approach, can be reduced to hours. Case-based reasoning (CBR) is used for a further tenfold decrease in computation time. The time needed to find good control solutions decreased from hours, when stochastic search is used, to minutes with CBR. CBR also provides possibilities for improving performance over service life. Successfully solved situations are stored as cases in a case-base. In new situations, a case close to the new situation is retrieved and then adapted. By storing additional cases, the system is able to retrieve better cases for adaptation. With increasing case-base size, adaptation time decreases. The combination of these techniques has much potential for improving the performance of complex structures during service lives. Results should contribute to the development of innovative structural solutions. Finally, it is expected that the findings in this thesis will become points of departure for subsequent studies

Combining dynamic relaxation method with artificial neural networks to enhance simulation of tensegrity structures

Abstract: Structural analyses of tensegrity structures must account for geometrical nonlinearity. The dynamic relaxation method correctly models static behavior in most situations. However, the requirements for precision increase when these structures are actively controlled. This paper describes the use of neural networks to improve the accuracy of the dynamic relaxation method in order to correspond more closely to data measured from a full-scale laboratory structure. An additional investigation evaluates training the network during the service life for further increases in accuracy. Tests showed that artificial neural networks increased model accuracy when used with the dynamic relaxation method. Replacing the dynamic relaxation method completely by a neural network did not provide satisfactory results. First tests involving training the neural network online showed potential to adapt the model to changes during the service life of the structure. DOI: 10.1061/�ASCE�0733-9445�2003�129:5�672

A study of two stochastic search methods for structural control

Abstract: Many engineering tasks involve the search for good solutions among many possibilities. In most cases, tasks are too complex to be modeled completely and their solution spaces often contain local minima. Therefore, classical optimization techniques cannot, in general, be applied effectively. This paper studies two stochastic search methods, one well-established �simulated annealing � and one recently developed �probabilistic global search Lausanne�, applied to structural shape control. Search results are applied to control the quasistatic displacement of a tensegrity structure with multiple objectives and interdependent actuator effects. The best method depends on the accuracy related to requirements defined by the objective function and the maximum number of evaluations that are allowed

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Engineering architectural creativity

Technical mastery is only one condition for successful construction projects. Management skills should be considered as equally important. Architects and engineers are the backbone of project teams. When this team fails to work effectively together, project success is put at risk. Teaching and training of team and management skills in engineering and architectural education contributes to minimize this risk. It creates dynamics which will facilitate the application of innovative construction materials and methods for the benefit of the project. Introduction of those "soft skills" through an integrated teaching approach will foster joined up thinking and prepare students to deliver high quality projects during their professional career

Du BIM pour le sous-sol?

La modélisation numérique de l’environnement urbain est au cœur de l’attention depuis quelque temps, du fait notamment de la propagation de la méthode BIM. Le BIM, technologie disruptive1, bouleverse notre façon de travailler à toutes les échelles: si les systèmes d’information géographique (SIG) gèrent aujourd’hui des territoires étendus, les systèmes de BIM aident d’ores et déjà à planifier les ouvrages au millimètre près. La Haute école du paysage, d’ingénierie et d’architecture de Genève (HEPIA) a été mandatée par l’Office fédéral de topographie swisstopo et le canton de Genève pour répondre à la question suivante: jusqu’à quel point ces deux technologies peuvent-elles être utilisées pour une modélisation structurée des objets situés en sous-sol