Advanced Building Simulation

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Chapter 9 Immersive building simulation Ali M. Malkawi 9.1 Introduction Advancements in visualization led to new developments in simulation. Different technologies made it possible to create environments that are virtual or augmented. Immersive simulation is the representation of the behavior or characteristics of the physical environment through the use of computer-generated environment with and within which people can interact. These environments support variety of applications including building simulation. The advantage of this simulation is that it can immerse people in an environment that would normally be unavailable due to cost, safety, or perception restrictions. It offers users immersion, navigation, and manipulation. Sensors attached to the participant (e.g. gloves, bodysuit, footwear) pass on his or her movements to the computer, which changes the graphics accordingly to give the participant the feeling of movement through the scene. This chapter introduces a newly defined area of research we termed “immersive building simulation” and discusses the different techniques available and their applications. It illustrates how this emerging area is benefiting from the more established immersive simulation field. It begins by describing its background, which is rooted in virtual and augmented reality, and describes the application of these techniques used in different fields. It defines the essential components of immersive building simulation with a focus on data representation and interaction regarding building performance. Two example cases and recent work in this area will be discussed. In this chapter, the term immersive building simulation is used to illustrate a specific type of simulation that uses immersive virtual or augmented reality environments. Although the term virtual reality (VR) was originally coined by Jaron Lanier, the founder of VPL Research in 1985, the concept of virtual reality can be linked to the development of calculating machines and mechanical devices (Schroeder 1993). Its modern roots can be associated with Edwin Link who developed the flight simulator in order to reduce pilot training time and cost in the early 1940s. The early 1960s show milestone developments in the field of virtual and augmented environments. In 1965, Ivan Sutherland published a paper “The Ultimate Display” (Sutherland 1965) in which he provided an argument to utilize the computer screen as a window through which one beholds a virtual world. The same year, Sutherland built the first seethrough head mounted display and used it to show a wire frame cube overlaid on the real world, thereby creating the first Augmented Reality Interface. In addition, video mapping was introduced around the same time in a publication written by Myron Krueger in the early 1960s (Krueger 1985).
218 Malkawi Table 9.1 Development of virtual environments 1940 Link Aviation developed the first flight simulator. 1957 M.L.Heilig patented a pair of head-mounted goggles fitted with two color TV units. 1965 Ivan Sutherland published “The Ultimate Display”. 1971 Redifon Ltd (UK) began manufacturing flight simulators with computer graphics display. 1977 Dan Sandin and Richard Sayre invented a bend-sensing glove. 1982 Thomas Zimmerman patented a data input glove based upon optical sensors, such that internal refraction could be correlated with finger flexion and extension. 1983 Mark Callahan built a see-through HMD at MIT. Myron Krueger published “Artificial Reality”. 1985 VPL Research, Inc. was founded. Mike McGreevy and Jim Humphries built a HMD from monochrome LCD pocket TV displays. Jaron Lanier, CEO of VPL, coined the term “virtual reality”. 1989 VPL Research and Autodesk introduced commercial HMDs. 1992 CAVE built by University of Illinois, Chicago. 1994 Milgram introduced the term—“Mixed Reality”. 2000� New human–computer interface mechanisms, sensors and displays for virtual environments. It took an additional 20 years before VR hardware became relatively affordable. This is due to the introduction of PCs and the increased speed and quality of the graphics and rendering technology (Krueger 1991). In the 1980s, many commercial companies emerged to support the hardware and software of VR. These include Virtual Research, Ascension, Fakespace, etc. In addition, large industrial entities made substantial investment in the technology (Boeing, General Motors, Chrysler, etc.) and academic institutions become a driving force in this development. Table 9.1 provides a summary historical view. Virtual and augmented systems today embody a growing area of research and applications related to Human–Computer Interface (HCI). It has demonstrated tremendous benefits in many areas including commerce and entertainment. Immersive virtual reality (IVR) has only recently started to mature. Its techniques are used in the industry for product development, data exploration, mission planning, and training. Augmented Reality (AR) is still in the prototype stage, however research systems for medical, engineering, and mobile applications are now being tested. Stable hardware and graphics application programming interfaces, such as OpenGL and Performer, and reasonably priced software resulted in emerging successes for VR and AR research and applications. The <strong>Building</strong> <strong>Simulation</strong> field has been slow in taking advantage of these recent developments. Challenges related to utilizing the technology in this field will be illustrated later in this chapter. In order to discuss immersive building simulation, the concepts of immersive environments, which form the base for such simulation, will be discussed. 9.1.1 Immersive environments Virtual, immersive, or synthetic environments (VEs) are computer-generated threedimensional environments that can be interactively experienced and manipulated by the user in real-time. One way to classify immersive environments is by their end use.
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Advanced Building Simulation
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First published 2003 by Spon Press
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vi Contents 8 Developments in inter
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viii Figures 3.12 Relation between
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x Figures 8.14 Workflow Modeling Wi
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Contributors D. Michelle Addington,
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Prologue Introduction and overview
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Prologue 3 two topics that represen
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Trends in building simulation 5 com
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Reality Space averaged treatment of
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Pervasive/invisible Web-enabled Des
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Trends in building simulation 11 in
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Trends in building simulation 13 ea
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Trends in building simulation 15 ba
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Trends in building simulation 17 1.
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Trends in building simulation 19 th
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and predictive simulation-based con
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Trends in building simulation 23 Fu
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Chapter 2 Uncertainty in building s
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Uncertainty in building simulation
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This completes the outline of the c
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and inputs may be a formidable task
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Kleijnen (1997), Reedijk (2000), an
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Table 2.1 Categories of uncertain m
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∆C p (-) 1.6 1.2 0.8 0.4 0.0 -0.4
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S d (h) 80 60 40 20 0 -80 2 Uncerta
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2.4.2 Uncertainty in wind pressure
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an experiment involving structured
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with their uncertainties, in terms
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Table 2.5 Expected utilities for de
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y a performance gain on another asp
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Simulation and uncertainty: weather
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makes every month normalized to a z
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Dry-bulb temperature (°F) 60 50 40
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(b) Compute today’s average tempe
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ackward. First, the average daily h
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a��sin(�)* ln[I SC * � D] (
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H = Total daily horizontal insolati
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Temperature (°C) or wind speed (m/
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Horizontal insolation (MJ/m 2 /day)
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References Simulation and uncertain
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Chapter 4 Integrated building airfl
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(a) (b) zone 6 5 4 3 2 1 3 1 Pre-he
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a different physical state variable
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West Zone n Zone m Figure 4.5 Examp
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Node n Figure 4.6 An example two zo
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The nodal pressures are then iterat
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when employing Newton-Raphson solut
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Integrated building airflow simulat
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25.9 15.9 13.7 10.2 7.2 4.2 0.0 10.
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Air temperature (°C) 40.0 35.0 30.
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It was found that the differences a
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of the problem. In any event, calib
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Resolution CFD Decision Reduced Dec
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Although most of the basic physical
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Chapter 5 The use of Computational
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CFD tools for indoor environmental
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the Reynolds average rules can be s
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3m Control room Enclosure 5.5 m Out
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y the room conditions. In fact, the
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Y/H Y/H 1 0.8 0.6 0.4 0.2 Plot-1 Pl
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magnitude computing time than the R
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Chapter 6 New perspectives on Compu
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New perspectives on CFD simulation
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law must be invariant to a transfor
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References New perspectives on CFD
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Chapter 7 Self-organizing models fo
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Self-organizing models for sentient
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SOM topo- SOM site 1 graphy 1 1 1 1
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Self-organizing models for sentient
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