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Grid shells are efficient structural systems covering large open spaces with relatively small amount of materials. Also, post forming techniques allow realization of geometrically complex (free-form) shapes by means of standard connection systems.However, due to complexity of the analysis-design process, they are rarely utilized in construction design. In this paper, a 'facilitating' numerical framework is introduced in which, for a given continuous reference shape, a geometrically similar discrete model is found by implementation of a six degree of freedom formulation of the Dynamic Relaxation method, to handle members bending and torsional stiffness. A grid cutting pattern algorithm is introduced, as well as methods to numerically simulate the double-layer construction technique and a novel (singlenode) cylindrical joint model. The methods are extensively tested and validated on a range of structures, from 'simple' single-rod cases to more complex, actively bent, grid shell frameworks.

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Life cycle assessment (LCA) is increasingly becoming a common technique to assess the embodied energy and carbon of buildings and their components over their life cycle. However, the vast majority of existing LCAs result in very definite, deterministic values which carry a false sense of certainty and can mislead decisions and judgments. This article tackles the lack of uncertainty analysis in LCAs of buildings by addressing the main causes for not undertaking this important activity. The research uses primary data for embodied energy collected from European manufacturers as a starting point. Such robust datasets are used as inputs for the stochastic modelling of uncertainty through Monte Carlo algorithms. Several groups of random samplings between 10 1 and 10 7 are tested under two scenarios: data are normally distributed (empirically verified) and data are uniformly distributed. Results show that the hypothesis on the data no longer influences the results after a high enough number of random samplings (10 4). This finding holds true both in terms of mean values and standard deviations and is also independent of the size of the life cycle inventory (LCI): it occurs in both large and small datasets. Findings from this research facilitate uncertainty analysis in LCA. By reducing significantly the amount of data necessary to infer information about uncertainty, a more widespread inclusion of uncertainty analysis in LCA can be encouraged in assessments from practitioners and academics alike.

The built environment is hard to decarbonize but has a pivotal role in climate-change mitigation amid rapid urbanization. Substituting conventional building materials with bio-based materials that store carbon offers one possible solution. Here, we reflect on the capacity of global forests to deliver the floor area required by mid-century.