Towards a Free-form Transformable Structure: A critical review for the attempts of developing reconfigurable structures that can deliver variable free-form geometries

In continuation of our previous research (Hussein, et al., 2017), this paper examines the kinetic transformable spatial-bar structures that can alter their forms from any free-form geometry to another, which can be named as Free-form transformable structures (FFTS). Since 1994, some precedents have been proposed FFTS for many applications such as controlling solar gain, providing interactive kinetic forms, and control the users' movement within architectural/urban spaces. This research includes a comparative analysis and a critical review of eight FFTS precedents, which revealed some design and technical considerations, issues, and design and evaluation challenges due to the FFTS ability to deliver infinite unpredictable form variations. Additionally, this research presents our novel algorithmic framework to design and evaluate the infinite form variations of FFTS and an actuated prototype that achieved the required movement. The findings of this study revealed some significant design and technical challenges and limitations that require further research work

A stochastic multiple mapping conditioning computational model in OpenFOAM for turbulent combustion

Computational models for combustion must account for complex and inherently interconnected physical processes including dispersion, mixing, chemical reactions, particulate nucleation and growth and, critically, the interactions of these with turbulence. The development of affordable and accurate models that are widely applicable is a work in progress. Stochastic multiple mapping conditioning (MMC) is a fast-emerging approach that has been successfully applied to non-premixed, premixed and partially premixed flames as well to the modelling of liquid and solid particulate synthesis. The method solves the conventional PDF transport equation but incorporates an additional constraint in that the mixing is localised in a reference space. This paper describes the numerical implementation of stochastic MMC in an OpenFOAM compatible code called mmcFoam. The model concepts and equations along with alternative submodels, code structure and numerical schemes are explained. A focus is placed on validation of the computational methods in particular demonstrating numerical convergence and mass consistency of the hybrid Eulerian/Lagrangian schemes. Four validation cases are selected including a combustion direct numerical simulation (DNS) case, two combustion experimental jet flame cases and a non-combusting particulate synthesis case. The results show that the total mass and mass distribution of Eulerian and Lagrangian schemes are consistent and confirm that the solutions numerically converge with increasing number of stochastic computational particles and sections for describing particulate size distribution