Analytical Prediction of Steel Grid-Shell Stability and Dynamic Behaviors Using Neural Networks – Part 1

<p>Artificial Intelligence is a cutting-edge technology expanding very quickly into every industry. It has made its way into structural engineering and it has shown its benefits in predicting structural performance as well as saving modelling and experimenting time. This paper is the first one (out of three) of a broader research where artificial intelligence was applied to the stability and dynamic analyzes of steel grid-shells. In that study, three Artificial Neural Networks (ANN) with 8 inputs were independently designed for the prediction of a single target variable, namely: (i) the critical buckling factor for uniform loading (i.e. over the entire roof), (ii) the critical buckling factor for uniform loading over half of the roof, and (iii) the fundamental frequency of the structure. This paper addresses target variable (i). The ANN simulations were based on 1098-point datasets obtained via thorough finite element analyzes.</p> <p>The proposed ANN for the prediction of the critical buckling factor in steel grid-shells under uniform loading yields mean and maximum errors of 1.1% and 16.3%, respectively, for all 1098 data points. Only in 10.6% of those examples (points), the prediction error exceeds 3%. </p>

A Form-Finding Method for Branching Structures Based on Dynamic Relaxation

Branching structure is often used as a supporting structure of the grid shell due to its geometrical and force-transferring features, and the rationality of its shape is very important. The “physical” and “numerical” hanging models can be used for the joint form-finding of the branching structure and free-form grid shell. However, slack elements may exist in the equilibrium model which corresponds to the inefficient members in the form-found branching structure. To solve this problem, a form-finding method of branching structure based on dynamic relaxation is proposed in this study. The proposed method clusters the elements of the branching model and equalizes the axial forces of the elements in the same cluster, in other words, there are no slack elements in the equilibrium branching model. This method overcomes the defect that the equilibrium branching model may have slack elements and needs many manual adjustments during the procedure of determining the rational shape of a branching structure, and effectively prevents the inefficient members existing in the form-found structure. Numerical examples are provided to demonstrate the characteristics of the proposed method and its effectiveness is verified as well.

Sustainable Architecture Creating Arches Using a Bamboo Grid Shell Structure: Numerical Analysis and Design

Bamboo is known as a sustainable alternative for green building design, and it has been tied culturally to some regions around the world. However, bamboo’s structural strength for different design scenarios needs more investigation before it is widely adopted. Timber and bamboo have similar mechanical properties, but the latter is a repaid, renewable, sustainable, disaster-resilient system and is versatile, which has more advantages for construction purposes. Natural bamboo and its derivatives have been considered as a high-demand green and environmentally responsible alternative construction material, and this interest is increasing globally. Because of the rapid growth rate and large developing area, it is more useable than the limited timber resource. However, natural bamboo has an anisotropic and nonhomogeneous material property, which varies in multiple directions. There is limited engineering data and investigation of bamboo material and its use in and impact on construction. In this study, three different bamboo models were analyzed by Strand7; each of them had different features in structure and in the major construction material. A new model was proposed by improving the three given structures and was maximized in the mechanical capacity. Some design guidelines were proposed based on the analysis and comparison of different bamboo structures. The model will replace natural bamboo with bamboo scrimber, which is an engineered bamboo derivative that has more uniform material properties.

Optimizing maсhining parameters for milling pockets in waffle-grid shell structures

The paper aims to develop a procedure for calculating parameters characterizing the process of milling box-shaped parts with waffle-grid shell design made of high-strength aluminum alloys. The calculated parameters are approximated by power equations and are provided for various ranges of the technological coefficient for the bottom of the waffle-grid structure. During final machining and penetration, when setting up the advance, one should take into account the inertial properties of the linear drives of the machines, in addition to this the advance of the tool and the angle of penetration should be constrained to prevent deformation of the bottom of the pocket. Based on the results of the math simulations, the ranges of acceptable values for advance per a tooth and the penetration angle were defined. The optimal ranges for milling parameters were established, which are recommended for implementation in the manufacturing processes of machining box-shaped parts with waffle-grid shell design made of high-strength aluminum alloys. Key words: milling, shell, pocket, aluminum alloys, optimization, waffle-grid structure.

ARCHITECTURAL POTENTIALITY OF FREE-FORM STRUCTURES

Contemporary architecture has witnessed a new innovative trend in design characterized by the creation of interesting free-flowing structures that reflect expressiveness of form and design, as well as the uniqueness of structure and approaches of construction. These fascinating structures are often perceived as landmarks that blend harmoniously into their surroundings. In the last two decades, parametric design and advanced computational tools, with prefabrication and construction techniques, enabled architects and engineers to explore new materials and methods to create such impressive structures, breaking the obsolete ways of thinking. Several examples of free-form structures lack obviously to explore architectural potentialities, that enrich the intention of architect, are still unformulated. The main objective of the present paper includes a conceptual proposal exploring the architectural potentiality of the free-form structures, focusing on form-finding possibilities through optimizing both the geometry and the mass of the structure, to generate configurations that ensure self-supported forms with stable force equilibrium. The paper introduces two simplified analytical methods to achieve the efficiency of the free-form architectural structures: the first depends on using extra materials to strengthen surfaces (such as grid shell system), and the second includes changing the geometry to achieve high “strength-to-weight” ratio (such as folding or conical self supports). By applying these methods, it is possible to explore various form-finding possibilities that contribute to the generation of characteristic landmarks with impressive structures.

Analytical Prediction of Steel Grid-Shell Stability and Dynamic Behaviors Using Neural Networks – Part 1

<p>Artificial Intelligence is a cutting-edge technology expanding very quickly into every industry. It has made its way into structural engineering and it has shown its benefits in predicting structural performance as well as saving modelling and experimenting time. This paper is the first one (out of three) of a broader research where artificial intelligence was applied to the stability and dynamic analyzes of steel grid-shells. In that study, three Artificial Neural Networks (ANN) with 8 inputs were independently designed for the prediction of a single target variable, namely: (i) the critical buckling factor for uniform loading (i.e. over the entire roof), (ii) the critical buckling factor for uniform loading over half of the roof, and (iii) the fundamental frequency of the structure. This paper addresses target variable (i). The ANN simulations were based on 1098-point datasets obtained via thorough finite element analyzes.</p> <p>The proposed ANN for the prediction of the critical buckling factor in steel grid-shells under uniform loading yields mean and maximum errors of 1.1% and 16.3%, respectively, for all 1098 data points. Only in 10.6% of those examples (points), the prediction error exceeds 3%. </p>

Analytical Prediction of Steel Grid-Shell Stability and Dynamic Behaviors Using Neural Networks – Part 1

<p>Artificial Intelligence is a cutting-edge technology expanding very quickly into every industry. It has made its way into structural engineering and it has shown its benefits in predicting structural performance as well as saving modelling and experimenting time. This paper is the first one (out of three) of a broader research where artificial intelligence was applied to the stability and dynamic analyzes of steel grid-shells. In that study, three Artificial Neural Networks (ANN) with 8 inputs were independently designed for the prediction of a single target variable, namely: (i) the critical buckling factor for uniform loading (i.e. over the entire roof), (ii) the critical buckling factor for uniform loading over half of the roof, and (iii) the fundamental frequency of the structure. This paper addresses target variable (i). The ANN simulations were based on 1098-point datasets obtained via thorough finite element analyzes.</p> <p>The proposed ANN for the prediction of the critical buckling factor in steel grid-shells under uniform loading yields mean and maximum errors of 1.1% and 16.3%, respectively, for all 1098 data points. Only in 10.6% of those examples (points), the prediction error exceeds 3%. </p>