Advanced Building Simulation

267 Pages·2004·2.41 MB·english

by  Ali M Malkawi

Advanced Building Simulation

Advanced Building Simulation
Edited by
Ali M. Malkawi and Godfried Augenbroe
First published 2003
by Spon Press
29 West 35th Street, New York, NY 10001
Simultaneously published in the UK
by Spon Press
2 Park Square, Milton Park, Abingdon, Oxfordshire OX14 4RN
This edition published in the Taylor & Francis e-Library, 2004.
Spon Press is an imprint of the Taylor & Francis Group
© 2004 Spon Press
All rights reserved. No part of this book may be reprinted or reproduced
or utilised in any form or by any electronic, mechanical, or other means,
now known or hereafter invented, including photocopying and recording,
or in any information storage or retrieval system, without permission in
writing from the publishers.
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Cataloging in Publication Data
Advanced building simulation / edited by Ali M. Malkawi and Godfried
Augenbroe.
p. cm.
Includes bibliographical references and index.
I. Buildings—Performance—Computer simulation. 2. Buildings—
Environmental engineering—Data processing. 3. Intelligent buildings.
4. Architectural design—Data processing. 5. Virtual reality. I. Malkawi, Ali M.
II. Augenbroe, Godfried, 1948–
TH453.A33 2004
690(cid:1).01(cid:1)13–dc22 2003027472
ISBN 0-203-07367-3 Master e-book ISBN
ISBN 0-203-67045-0 (Adobe eReader Format)
ISBN 0–415–32122–0 (Hbk)
ISBN 0–415–32123–9 (Pbk)
Contents
List of figures vii
List of tables xi
List of contributors xii
Acknowledgement xiii
Prologue: introduction and overview of field 1
ALI M. MALKAWI AND GODFRIED AUGENBROE
1 Trends in building simulation 4
GODFRIED AUGENBROE
2 Uncertainty in building simulation 25
STEN DE WIT
3 Simulation and uncertainty: weather predictions 60
LARRY DEGELMAN
4 Integrated building airflow simulation 87
JAN HENSEN
5 The use of Computational Fluid Dynamics tools
for indoor environmental design 119
QINGYAN (YAN) CHEN AND ZHIQIANG (JOHN) ZHAI
6 New perspectives on Computational Fluid
Dynamics simulation 141
D. MICHELLE ADDINGTON
7 Self-organizing models for sentient buildings 159
ARDESHIR MAHDAVI
vi Contents
8 Developments in interoperability 189
GODFRIED AUGENBROE
9 Immersive building simulation 217
ALI M. MALKAWI
Epilogue 247
GODFRIED AUGENBROE AND ALI M. MALKAWI
Index 249
Figures
1.1 Simulation viewed as a (virtual) experiment 6
1.2 Standard approach to simulation 7
1.3 Trends in technical building performance simulation tools 9
1.4 Reduction of domain knowledge in the migration of expert
tools to designer-friendly tools 13
1.5 Variants of delegation of expert analysis to domain experts
and their tools 14
2.1 Schematic view of the office building with its main dimensions 27
2.2 Schematic layout of the building and its environment 27
2.3 Process scheme of building performance assessment as input
to decision-making 30
2.4 An illustration of the procedure to assess two samples of the
elementary effect of each parameter 34
2.5 Wind pressure difference coefficients from three different
models as a function of wind angle 37
2.6 Histogram of the performance indicator TO 40
2.7 Sample mean m and standard deviation S of the elementary
d d
effects on the performance indicator TO obtained in the
parameter screening 41
2.8 Quantile values of the combined expert 46
2.9 Frequency distribution of the comfort performance indicator
TO on the basis of 500 samples 49
2.10 Marginal utility function of the two decision-makers over the
level of attribute 52
3.1 Characteristic shape of the daily temperature profile 64
3.2 The probability density function for the Normal Distribution 66
3.3 Cumulative distribution plots for two separate months 67
3.4 Actual record of daily maximum and average temperatures 69
3.5 Monte Carlo generated daily maximum and average temperatures 70
3.6 Sun position angles 72
3.7 Relationship between air mass and altitude angle 73
–
3.8 The generalized K curves 75
T
3.9 Daily horizontal direct fraction versus daily clearness index 76
3.10 Comparison of solar radiation curves 78
3.11 Relation between generalized K curves, local weather data,
T
and Monte Carlo results for a selected January 79
viii Figures
3.12 Relation between generalized K curves, local weather data,
T
and Monte Carlo results for a selected July 80
3.13 Hourly temperatures and wind speeds 81
3.14 Hourly insolation values 81
3.15 Comparison of heating degree-days from simulated
versus real weather data 82
3.16 Comparison of cooling degree-days from simulated
versus real weather data 82
3.17 Comparison of horizontal daily solar radiation from
simulated versus real data 83
3.18 Comparison of results from the simulation model to
historical weather data 83
4.1 Summary overview of typical building airflow applications and
modeling techniques 88
4.2 Glasgow’s Peoples Palace museum with corresponding
simplified airflow model 89
4.3 Model of a double-skin façade 90
4.4 Model of a historical building and CFD predictions of
air velocity distribution 91
4.5 Example building and plant schematic 93
4.6 An example two zone connected system 95
4.7 Example of successive computed values of the pressure and
oscillating pressure corrections at a single node 98
4.8 Schematic representations of decoupled noniterative (“ping-pong”)
and coupled iterative (“onion”) approach 100
4.9 Schematic flow diagram showing the implementation of
a coupled (“onion”) and decoupled (“ping-pong”) solution
method for heat and airflow 101
4.10 Cross-section and plan of atrium with airflow network 103
4.11 Simulation results for vertical airflow through atrium 104
4.12 Simulation results for top floor air temperatures 105
4.13 Early assessment design strategies 110
4.14 Prototype performance-based airflow modeling selection strategy 111
4.15 Different scenarios resulting from sensitivity analysis in AMS 114
4.16 A future integrated building simulation environment 115
5.1 The schematic of a room with mixed convection flow 124
5.2 Geometry and boundary conditions for two-dimensional
natural convection in a cavity 127
5.3 The vertical velocity profile at mid-height and temperature profile
in the mid-height for two-dimensional natural convection case 128
5.4 Schematic of experimental facility 129
5.5 Air speed contour in the room 129
5.6 Development of the wall jet in front of the displacement diffuser 130
5.7 Predicted temperature gradient along the vertical central line of
the room 131
5.8 Comparison of convective heat fluxes from enclosures with
various grid resolutions 132
Figures ix
5.9 Velocity and temperature distributions for the displacement
ventilation case 133
5.10 The comparison of the velocity profiles at five positions in
the room between the calculated and measured data for the
displacement ventilation case 134
5.11 The comparison of the temperature profiles at five positions in
the room between the calculated and measured data for the
displacement ventilation case 135
5.12 The comparison of the tracer-gas concentration profiles at five
positions in the room between the calculated and measured data
for the displacement ventilation case 136
6.1 Schematic representation of typical buoyant boundary conditions 148
6.2 Vertical transition from laminar to turbulent regimes in no-slip
buoyant flow 149
6.3 Temperature profile comparisons 155
6.4 Velocity profiles comparing micro-source placement 156
7.1 Scheme of the constitutive ingredients of a sentient building 161
7.2 SEMPER’s shared object model 163
7.3 A general control scheme 164
7.4 A high-level building product and control process scheme 165
7.5 Meta-controller for individually controllable identical devices for
different devices addressing the same control parameter 166
7.6 Schematic floor plan of the test spaces 168
7.7 Association between sensors and devices 168
7.8 An automatically generated control model 169
7.9 Application of rules 4 and 5 170
7.10 Illustrative preference functions for selected performance variables 180
7.11 Measurements for interior illuminance rule 184
7.12 Heat output of DC-Va as a function of supply temperature 185
7.13 The relation between measured and simulated illuminance levels 185
7.14 Simulated valve positions and space temperatures 186
7.15 Simulated illuminance levels 186
8.1 From non-scalable to scalable interoperability solutions 190
8.2 Data exchange through a central Building Model 192
8.3 File based exchange 196
8.4 Definition of Building Model subschemas 197
8.5 Process-driven interoperability 198
8.6 Data exchange with off-line applications 199
8.7 Sample ExEx startup screen 200
8.8 The Project Window concept 201
8.9 Design analysis interaction defined at specific interaction
moments 203
8.10 Analysis tasks with multiple interaction links with design
activities 204
8.11 Different types of interaction and information exchange 204
8.12 Four-layered workbench 206
8.13 Start of the analysis process 207