Real-Time Data in Architectural Practice; Embracing A.I. in the design for energy efficiency

该项目旨在解决创建一个计算系统的方法，以提高西北部高等教育（HE）校园的设计效率。随着技术的新发展，如生成式设计流程，自主系统和自我意识机器人，AEC行业必将在全球范围内受到影响。但人工智能（AI）将如何增强建筑设计？建筑师利用这些技术进步有哪些可能性？该案例研究将与一家经验丰富的工业合作伙伴合作，该合作伙伴曾参与英国校园的设计和建设。更具体地说，该项目的主要重点是确定大学校园建筑物能源消耗的改善战略。大学校园通常在城市结构中占据很大的面积。据建筑分析师Barcelona ABI称，由于计划在2017年至2020年期间签订20亿英镑的合同，因此建造更多校园或进一步开发现有校园的冲动仍在继续。同样，英国《金融时报》报道称，2016年，英国大学在6个月内将新建筑的预算增加了43%。然而，校园是一个复杂的结构，举办各种活动。这些活动随着时间的推移不断变化。因此，校园的发展或扩张具有复杂性的特点。这种复杂性需要一种不同于英国快速城市化期间所采用的梯田房屋建筑风格的方法。单纯的重复建设方法不会有效地响应，因为校园的整体行为发生变化，它发生在程序层面。因此，该方法应在设计的早期阶段考虑自适应系统的灵活性。在这个项目中，将探索人类和人工智能相结合的好处。通过使用来自校园的数据，目标是了解哪个因素是能源消耗的最大贡献者。这些数据将涉及校园的设计，以及其能源性能，以及入住后的信息和见解。通过在设计过程的早期阶段将这种类型的数据与计算相结合，该项目将研究高等教育校园建筑实践的工作流程和输出的改进。根据《清洁增长战略》文件，包括校园在内的大多数建筑物的供暖排放量约占英国总排放量的32%。然而，在能源消耗方面设计一个高效的高等教育校园不仅可以减少排放，而且有助于推动增长。爱丁堡大学金融系主任特伦斯·福克斯（Terence Fox）表示，新建筑可以证明是决定性的。“如果一个学生来自美国，澳大利亚或中国，他们需要来这里，因为我们不仅有最好的学生，而且有最好的设施。如果选择是曼彻斯特或爱丁堡，而曼彻斯特有新的建筑，他们可能会去曼彻斯特。“从研究的角度来看，各自方法的应用可以扩展到高等教育校园的能源规划之外。虽然能量因素在AEC实践中变得越来越重要，但可以重新审视和探索其他同样重要的设计变量。建筑物内的人流或外部视野最大化就是这些变量的例子。这样，建筑师的专业界限就可以被超越。然而，即使对于大型国际公司来说，人工智能在设计决策中的应用也处于起步阶段。随着越来越多的实践创建专家组来拥抱这种技术发展，好处将变得更加明显。AEC行业将通过嵌入解决设计挑战的新方法来增强;如果没有计算建模系统的实施，这些方法将是不可能的。

The project aims to address methods for creating a computational system for design efficiency of the Higher Education (HE) campuses in the North-West. With new developments in technology, like generative design processes, autonomous systems and self-aware bots, the AEC industry is bound to be affected at a global scale. But how would Artificial Intelligence (AI) augment the architectural design and what are the possibilities for architects working with these technological advancements?The case study will run as a collaboration with an experienced industrial partner that has been involved in designing and building school campuses in the UK. More specifically, the project's main focus is to identify improvement strategies for energy consumption in university campus buildings. A university campus usually occupies large areas in a city's fabric. The urge to create additional campuses or to further develop the existing ones continues as contracts that reach £2 billion are planned between 2017 and 2020, according to Barbour ABI, the construction analysts. Similarly, the Financial Times report that, in 2016, British universities have increased their budget on new buildings by 43 per cent in six months. However a campus is a complex structure that hosts various activities. These activities change continuously over time. Thus, the development or expansion of a campus is characterized by complexity. This complexity requires an approach different from the terraced houses construction style that was applied during the UK's rapid urbanization. The mere repetitive construction approach wouldn't respond efficiently since the overall behavior of a campus changes and it happens on a procedural level. Therefore, the approach should consider the flexibility of an adaptive system in the early stages of their design. During this project, the benefits of combining Human and Artificial Intelligence will be explored. Through the use of data from the campus, the goal is to realize which factor is the biggest contributor for the energy consumption. The data will relate to the design of the campus, as well as its' energy performance, and post-occupancy information & insights. By embracing this type of data with computation in the early stages of the design process, the project will investigate improvements in the workflow and output of the architectural practice for HE campuses. Based on The Clean Growth Strategy paper, the majority of buildings including campuses, heating creates around 32 per cent of total UK emissions. However the design of an efficient HE campus in energy consumption may not only reduce the emissions but help to drive growth. According to Terence Fox, a director in the finance department at Edinburgh University, new buildings can prove decisive. "If a student [comes] from the US, Australia or China, they need to come here because we've got not just the best students, but the best facilities. If the choice is Manchester or Edinburgh, and Manchester has new buildings, they'll probably go to Manchester."From a research aspect, the applications of the respective methodology could extend beyond the energy planning of higher education campuses. While the energy factor is becoming ever more critical within the AEC practice, further equally important design variables could be revisited and explored. People's flow in a building or the exterior view maximization are examples of such variables. In this manner, the architect's professional boundaries could be transcended. This application of Artificial Intelligence for design decision-making however is its' infancy even for large international firms. As more and more practices create specialist groups to embrace this technological development the benefits will become more tangible. And the AEC industry will be enhanced by embedding new ways of tackling design challenges; ways that would be impossible without the implementation of computational modelling systems.