当前位置: 毕业论文 > 外文文献翻译 >


时间:2018-12-05 19:33来源:毕业论文
ABSTRACT: An essential role of architecture is to provide built environments that sustain occupants safety, health, physiological comfort, and productivity. Because of complexity of modelling for environmental quality design, its importance

ABSTRACT:  An essential role of architecture is to provide built environments that sustain occupants’ safety, health, physiological comfort, and productivity. Because of complexity of modelling for environmental quality design, its importance has often been overlooked in the quest for energy  and environmental conservation.  About the air quality issue, the benefits of suitable natural ventilation go beyond the need for oxygen and the energy saving in cooling phases. Continuous recirculation of interior air exposes people to concentrated levels  of bacteria and chemicals within the building and forced ventilation may often produce incompatible noise level with activity and well-being of occupants. 31244
Green building practices offer an opportunity to create environmentally sound and resource efficient b uildings by using an integrated approach to design. Integration means to face architectural and environmental aspects of design contemporarily, without disjoining them in a hierarchical sequence of resolving. This requires designer ability of understanding and handling complex physical knowledge in order to correctly address preliminary design decisions rather than commissioning the performance assessment when the design features are truly defined.  This paper describes VENTPad, a design environment we are  developing  to help students and architects in understanding and therefore planning suitable internal fluid-dynamic behaviour of buildings (especially focused on wide internal spaces, like concert halls and theatres, which behaviour is more manifold, thus pedagogically more interesting, than residential buildings).  A novel contribution of the system approach, compared with conventional numerical simulation techniques, is the ability to generate explanations about the building physical behaviour, diagnosing  contributes of each relevant design decision to the system performance.  KEYWORDS: Preliminary Sustainable Design, Qualitative Modelling,
Education   1.  INTRODUCTION  Buildings have perse effects on the environment during their entire life cycles. Although  the tangible impacts are visible only after construction begins, decisions made on the drawing board have long-term environmental consequences. To achieve environmental sustainability in the building sector, architects must be educated about environmental  issues during their professional training. Faculties have to foster environmental awareness, introduce students to environmental ethics, and developing their skills and knowledge base in sustainable design. In spite of the urgent need, teaching materials specifically designed for sustainable architecture have been virtually non-existent.  While there is a universal consensus on the importance of environmental education in architecture, the questions of what, when, and how to teach specific subjects related to environmental sustainability cannot be easily answered. One reason for this is that architecture covers a vast number of disciplines ranging from art to science; determining the level and extent of environmental education within design, technology, history, theory, practice, and environmental behaviour is a formidable task. At present, in the absence of a clear pedagogical framework, sustainable design is being presented as an ethical issue rather than science. While a change of lifestyles and attitudes toward the local and global environments is important, the development of scientific approach that addresses the implementation of environmental design goals is urgent.  源自/六^维:论"文;网(加7位QQ3249~114 www.lwfree.cn
The unique way to this aim, is that of giving students the scientific skills and modelling bases to seek and find sustainable design solutions rather than giving them a set of typological solutions. About this issue, while many energy conservation materials and quantitative analysis methods have been developed since the 1970s’, resources for  addressing larger environmental design techniques are greatly lacking. To date, advances made in methods to predict and measure building airflows have truly revolutionised the fields of building ventilation and air quality research in the past two decades,  so that many simulation techniques for  natural ventilation and  indoor air quality prediction are well established. Anyway  a variety of problems arise in synthesising and applying design principles in the context of ‘green buildings’ design in view of the total environmental performance. This difficulty  stems largely from the complexity of the fluid-dynamic behaviour, because of its evident non-linearity and instability. This often forces to place one’s trust in computational or experimental numerical results, without a chance of explaining the causal framework of calculated performance or forecasting the stability of observed physical behaviour. Consequently, we presently find ourselves armed with a veritable arsenal of tools to evaluate the thermal comfort,  air quality and energy conservation efficacy of existing and proposed building ventilation systems. Yet, ironically, we have yet to develop tools to directly answer simple design questions relating to building ventilation: How wide should windows be opened in a given building for wind-driven cross ventilation on a moderate summer day? How should I configure the roof to mitigate air recirculation which obstacles the dilution of internally generated pollutants and exposes people to concentrated levels of bacteria and chemicals within the building? Incidentally, the role that spaces shape and openings geometry play in setting a local as well as global sound fluid-dynamic behaviour is quite central, so that architectural and environmental design decisions can  be never disjoined to study them in a strictly hierarchical sequence. Then the challenging opportunity facing researchers today is that of synthesising design techniques to handle and explain the complexity concealed in numerical simulation results and expe rimental data. A method is needed, to examine building environmental response from an engineering point of view rather than a physicist one that is allowing the arrangement of design features by assuming sustainability criteria as the basis for comprehensive evaluation of the environmental building performance. Such a tool could support the development of students’ and architects’ abilities to explore, assess, and pursue various alternatives for sustainable design with special attention to  the close integration between architectural and scientific-technical issues. The aim we propose requires a qualitative understanding and representation of how the studied system behaves, by deriving from raw and unstructured numerical data and from a ground knowledge of general physical laws, a framework of explicit relationships among a selected set of relevant design variables.   2.  THE QUALITATIVE PHYSICAL MODELLING APPROACH  About this aim, computer applications in design have pursued two main development directions: analytical modelling and information technology. The former line has produced a large number of tools for reality simulation (i.e. finite element models), the latter is producing an equally large amount of advances in conceptual design support (i.e. artificial intelligence tools). Nevertheless we can trace rare interactions between computation models related to those different approaches. This lack of integration is the main reason of the difficulty of analytical methods application to the preliminary stage of  design, where logical and quantitative reasoning are closely related in a process that we often call ‘qualitative evaluation’. In this paper, after a brief survey about the current state of qualitative physical modelling applied to design, we propose a general approach of building natural ventilation modelling by means of Bayesian networks. We are employing this technique to develop VENTPad, a tutoring and coaching system to support natural ventilation modelling of buildings in the preliminary stage of design. This tool explores the possibility of modelling the causal mechanism that operate in real systems in order to allow a number of integrated logical and quantitative inference about the fluid-dynamic behaviour of buildings. It represents an innovative connection tool between logical and analytical modelling in preliminary design aiding, able to help students or unskilled architects, both to guide them through the analysis process of numerical data (i.e. obtained with sophisticate Computational Fluid Dynamics software) or experimental data (i.e. obtained with laboratory test models) and to suggest improvements to the design. VENTPad relies on a probabilistic causal representation, to qualitatively express the knowledge of fluid-dynamics needed to explain the ventilation behaviour of a space. We view VENTPad as part of a virtual laboratory, a conceptual CAD environment consisting of facilities for assembling, analysing and testing design ideas. By working in this software environment, students can ‘build’ their designs and try out improving them without expense or danger. In simpler domains some commercial software exists that can be viewed as virtual laboratories (e.g. Electronics Workbench) but a novel contribution of VENTPad, compared with these tools, is the ability to generate explanations about the system response, diagnosing contribute of each relevant design parameter or boundary condition to the system behaviour. For educational applications, explanation generation is vital, to help students see what aspects of a situation are important and to tie what they are observing back to fundamental principles. This aim requires a qualitative understanding and representation of how the studied system behaves, by deriving from raw and unstructured numerical data  and from ground knowledge of general physical laws, a framework of explicit relationships among a selected set of variables, which describes the specific system behaviour. This idea constitutes the  original motivations of the research area called ‘qualitative physics’ whose main aim is the development of intelligent tutoring systems and learning environments for physical domains and complex systems. This paper demonstrates how a synergistic combination of qualitative physics and other AI techniques can be used to create an intelligent learning environment for students learning to analyse and design natural ventilation in buildings. Pedagogically this problem is important because natural ventilation involves the integration of complex physical, thermodynamic and fluid-dynamic knowledge, an area normally closed to architects. The methodological approach of qualitative physics is based on capturing the tacit knowledge engineers use to organise and control knowledge gained through formal training. The initial motivation for qualitative physics was to set up and guide the solution of textbook motion problems (de Kleer 1975). Since then, research has mainly focused on purely qualitative reasoning (Bobrow 1984), and significant progress has been made. I believe the time is right to begin exploring the integration of qualitative and quantitative reasoning again. In particular, the long-range goal of my research is to develop a system which can automatically perform engineering analyses of design problems in a human-like way. This paper describes a first step towards that goal. Studies of natural ventilation problem solving have tended to focus on quantitative reasoning. We begin instead with the view that qualitative models are the starting point for the accumulation and use of more sophisticated, quantitative models. This view is widely held in the mental models literature (Gentner and Stevens 1983), and widely but less formally in the engineering community.  In problem solving, the analysis begins by constructing a qualitative understanding of the situation. This initial understanding provides the framework for further analyses, such as deriving and solving sets of equations. Developing a correct qualitative understanding of the problem is essential to solving complex problems. Qualitative simulation is used to verify that questions make sense by ensuring that the behaviour mentioned could actually occur. We have tested these ideas through implementation in a program called VENTPad, which solves simple natural ventilation design problems typically addressed at the preliminary design stage. Section 3 of this document, describes the pedagogical problems that motivated the design of VENTPad, including a brief overview of nature of fluid-dynamic issues in design. Section 4 outl ines the causal modelling approach of building behaviour that we use to integrate predictive with diagnostic support in guiding the preliminary design and its successive improvement or correction. How VENTPad represents the causal framework, which operates in the airflow behaviour of a simple application, is the subject of Section 5, with Section 6 outlining our plans for future work.   可持续绿色建筑英文文献和中文翻译:http://www.lwfree.cn/fanyi/20181205/27331.html