Material Alignments

IF 0.5 0 ARCHITECTURE
M. Gutierrez
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Abstract

Introduction Advances in computation have fomented a new era of material and building technology invention in architecture. Architects are reclaiming the territory of material invention through processes and methodologies forged through new computational protocols. New approaches to Pareto optimization, artificial intelligence (AI) integration, and non-invasive testing protocols pave the way to transformative material experimentation. However, how do we guide experiments designed around accomplishing specific material properties in architecture vis-a-vis engineering and sciences? Materials science addresses optimal experimental design by advancing computational analysis and tools to accelerate the materials discovery process. The capacity to discover or shape materials with augmented complexity increases as a function of time despite its disciplinary approach. In materials science, this trajectory revolves around trial-and-error and intuition, where often rapid progress is made if the synergy between theorists—who can often generate and suggest a list of compounds for possible synthesis—and experimentalists is utilized (Lookman et al. 2019). How and what is its equivalence in architecture and construction? The process of material innovation in design can stem from two varying routes: a design-led approach or a science-led approach (Ashby 2019, 33). The first approach starts with the performance requirements in a design usually geared towards applications. While architecture and engineering stem from varying perspectives and overall aims, both fields share the commonality of application. However, testing protocols and development differ significantly (Gutierrez 2014). The materialsscience-driven process originates in a deep understanding and manipulation of material properties. Material invention involves two fundamental steps: the material itself and the process by which it is turned into a new entity with computational, conceptual, and numerical differences essential in each field’s corresponding operations.
材料比对
计算机技术的进步推动了建筑材料和建筑技术发明的新时代。建筑师们正在通过新的计算协议锻造的过程和方法来重新夺回材料发明的领域。帕累托优化、人工智能(AI)集成和非侵入性测试协议的新方法为变革材料实验铺平了道路。然而,相对于工程和科学,我们如何指导围绕实现建筑中特定材料特性而设计的实验?材料科学通过推进计算分析和工具来加速材料发现过程,解决了最佳实验设计。发现或塑造具有增强复杂性的材料的能力随着时间的推移而增加,尽管它的学科方法。在材料科学中,这一轨迹围绕着试错和直觉,如果理论家(他们经常可以生成并提出可能合成的化合物列表)和实验家之间的协同作用得到利用,通常会取得快速进展(Lookman et al. 2019)。它在建筑和建造中是如何等价的?设计中的材料创新过程可以源于两种不同的途径:以设计为主导的方法或以科学为主导的方法(Ashby 2019, 33)。第一种方法从通常面向应用程序的设计中的性能需求开始。虽然建筑和工程源于不同的视角和总体目标,但这两个领域都有共同的应用。然而,测试协议和开发差异很大(Gutierrez 2014)。材料科学驱动的过程源于对材料特性的深刻理解和操纵。材料发明包括两个基本步骤:材料本身和将其转化为具有计算、概念和数值差异的新实体的过程,这些差异在每个领域的相应操作中都是必不可少的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Technology Architecture and Design
Technology Architecture and Design Arts and Humanities-Visual Arts and Performing Arts
CiteScore
1.30
自引率
0.00%
发文量
18
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