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Raw data measured from the images from A circuit analogy based girth growth model for living architecture design

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The Royal Society Figshare2023-05-11 更新2026-04-17 收录
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https://rs.figshare.com/articles/dataset/Raw_data_measured_from_the_images_from_A_circuit_analogy_based_girth_growth_model_for_living_architecture_design/22800284/1
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资源简介:
Architecture with and from living trees (Baubotanik) is a promising approach to sustainable, climate-adapted construction. Shaping and grafting allows to create resilient structures that combine the ecological performance and aesthetics of trees with the functions of buildings. In order to design and engineer such living structures, it is necessary to predict the growth of different tree segments, especially when trunks, branches or roots are bent and jointed into a complex inosculated network. To address this, we have developed a tool to forecast the relative girth growth of different segments in such structures based on topological skeletons, the pipe model theory and circuit analogy. We have validated our results with a set of (scaled) photographs of inosculated tree structures of the so-called ‘Tree Circus’, covering over 80 years of their growth. Our model has proven to predict the relative girth growth with sufficient accuracy for conceptual design purposes. So far, it does not allow the simulation of absolute growth in circumference over the course of time that is necessary to predict quantitative technical aspects, such as mechanical performance at a given time. We conclude by briefly lining out how this could be addressed in future research.

基于活树的建筑(Baubotanik)是一种极具前景的可持续、气候适应性建造路径。通过塑形与嫁接技术,可构建兼具树木生态性能与美学价值、同时具备建筑功能的高韧性结构体系。为了设计并工程实现此类活体结构,需对不同树木构件的生长情况进行预测——尤其当树干、枝条或根系被弯折并接合形成复杂的交织网络时。针对这一需求,本研究基于拓扑骨架、管道模型理论与电路类比法,开发了一款可预测此类结构中不同构件相对围度生长的工具。我们通过一套针对所谓“树木马戏团(Tree Circus)”接合树木结构的(缩放版)照片对模型结果进行了验证,该数据集涵盖了该结构超过80年的生长历程。实验结果表明,本模型可足够精准地预测相对围度生长,满足概念设计阶段的需求。但截至目前,该模型尚无法模拟随时间变化的绝对围度生长,而这一数据是预测特定时间点下结构力学性能等定量技术指标的必要前提。最后,本文简要梳理了未来研究可针对该局限展开的优化方向。
提供机构:
Shu, Qiguan; Ludwig, Ferdinand
创建时间:
2023-05-11
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