University essay from Lunds universitet/Byggnadsmekanik

Abstract: The deregulation of timber for use in large scale constructions has seen the addition of new innovative timber-based products to a category of products referred to as engineered wood products. A now well established addition to these products is cross laminated timber, or CLT for short. CLT products use a form of orthogonal layering, where several parallel wooden boards are arranged in a number of layers, each layer being orthogonal to the previous. The use of orthogonal layering allows for increased stiffness in the two plane directions, resulting in a lightweight construction product with high load bearing capacity and stiffness. To evaluate the dynamic behaviour of structures, engineers commonly apply the finite element method, where a system of equations are solved numerically. Given a sufficient amount of computational power and time, the finite element method can help to solve most dynamical problems. For sufficiently large or complex structures the amount of resources needed may be outside the scope of possibility or feasibility for many. Therefore, evaluating the usage of certain design simplifications, such as omitting to models aspects of the geometry, or alternative forms of analysis for CLT panels may help to reduce the time and resources required for an analysis. In this Master's dissertation, a seven-layer CLT-panel has been created. In the model, each individual board and the gaps between the boards are modelled. The seven-layer model is used as a reference to evaluate the possibility of using less detailed alternative models. The alternative models are created as a layered 3D model and a composite 2D model, both models omit the modelling of the individual laminations, resulting in the layers being solid. The results show small errors for the alternative models when using modal analysis. Concluding that the modal behaviour and dynamic response of a CLT panel can be evaluated using a composite 2D model or a less-detailed layered 3D model. This significantly reduces the amount of time and computational power needed for an analysis, and clearly indicates the benefit of using alternative less detailed models.

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