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AI in Structural & Thermal Building Analysis

This document discusses novel approaches to structural and thermal analysis of buildings using artificial intelligence methods. It describes using image analysis techniques and mechanical tests to evaluate concrete properties, and implementing artificial intelligence tools like neural networks to reveal unknown features of building materials and predict properties from multidimensional data. Specific analysis techniques discussed include using backpropagation networks, conducting uniaxial tensile tests, and measuring the thermal resistance of various wall systems through guarded hot box tests and long-term monitoring of test modules.

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Eliana Ríos Bustos
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143 views10 pages

AI in Structural & Thermal Building Analysis

This document discusses novel approaches to structural and thermal analysis of buildings using artificial intelligence methods. It describes using image analysis techniques and mechanical tests to evaluate concrete properties, and implementing artificial intelligence tools like neural networks to reveal unknown features of building materials and predict properties from multidimensional data. Specific analysis techniques discussed include using backpropagation networks, conducting uniaxial tensile tests, and measuring the thermal resistance of various wall systems through guarded hot box tests and long-term monitoring of test modules.

Uploaded by

Eliana Ríos Bustos
Copyright
© Attribution Non-Commercial (BY-NC)
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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NOVEL APPROACHES IN STRUCTURAL AND THERMAL ANALYSIS OF BUILDINGS

Dariusz ALTERMAN
The University of Newcastle Australia

OVERVIEW

Artificial Intelligence methods Uniaxial tensile tests Image Analyse techniques Energy efficiency of buildings

www.newcastle.edu.au

Image Analysis

AE

Mechanical tests
3

- air content (A) - micropores content (A300) - specific surface (alfa) - spacing factor (L) - cracks

- AE signal - Vickers test - CoV of diagonals

DATABASE
Information from the object

www.newcastle.edu.au

- modulus of elasticity

ARTIFICIAL INTELLIGENCE TOOLS


Numerous multi-dimensional data comes from multithe real world and are often not exactly accurate, complete but fuzzy or scattered

Artificial Intelligence procedures can reveal unknown features of reality to an Engineer

www.newcastle.edu.au

OBSERVED FEATURES

AI

EVALUATED PROPERTIES OF CONCRETE


(frost resistance, compressive and tensile strength, ...)

www.newcastle.edu.au

TYPE OF ANALYSIS
approximation classification ???

www.newcastle.edu.au

BACKPROPAGATION NETWORK
hidden neuron
7

hidden neuron etc.

www.newcastle.edu.au

PREDICTION
F u n c t io n A p p ro x im a t io n 140 120

100 Output: -, Target: +

80

fc

60

40

20

0 0 0 .5 1 In p u t 1.5 2 2.5

w/c
www.newcastle.edu.au

HIGH PERFORMANCE CONCRETE

www.newcastle.edu.au

10

UNIAXIAL TENSILE TESTS EFFECTS OF SECONDARY FLEXURE

www.newcastle.edu.au

LOADING

11

www.newcastle.edu.au

THE EFFECTS OF SECONDARY FLEXURE

12

Without elimination

With elimination

www.newcastle.edu.au

IMPREGNATION TECHNIQUE

13

www.newcastle.edu.au

AUSTRALIAN HOUSING
Typically brick veneer, cavity brick or lightweight construction (some single skin) Developers in the past have paid little attention to climate design or energy consumption and often poor use of materials Widespread use of air conditioning Modelling using appropriate software (AccuRate, EnergyPlus, NatHERS, FirstRate, BERS Pro, NUMBERS) One of the dominant parameters is the thermal resistance (R-value) of the external walls
www.newcastle.edu.au

14

Sarking

OTHER MODULES INSTRUMENTATION

Exterior Wall

Roof Cavity Insulation R3.5

15
Cement Render (Average Thickness 10mm) T-type Thermocouple Locations Heat Flux Sensor Locations
600mm

R1 Polystyrene Insulation Interior Wall

600mm

Floor Slab

Reflective Foil Insulation Exterior Wall

Sarking Roof Cavity Insulation R3.5

Insulated Cavity Brick


Sarking Roof Cavity Insulation R3.5 Fibro-Cement Timber Framing with R1.5 Batts Interior Wall Cement Render (Average Thickness 10mm)

Timber Framing with R1.5 Batts Plasterboard


600mm

T-type Thermocouple Locations


600mm

600mm

Heat Flux Sensor Locations


600mm

T-type Thermocouple Locations Heat Flux Sensor Locations

600mm

Floor Slab

600mm

Floor Slab

Insulated Brick Veneer


www.newcastle.edu.au

Insulated Reverse Brick Veneer

INSTRUMENTATION

16

Temperature Heat flux profiles Solar radiation Weather conditions Heating/cooling energy

www.newcastle.edu.au

17

Thermal resistance of each walling system determined from guarded hot box tests

Guarded hot box (2.4m x 2.4 m walls)

Representative housing test modules for each walling system observed over several years in Newcastle (Interior temperature free floating or controlled by heating/cooling)
www.newcastle.edu.au

THERMAL MASS

18

http://www.monier.co.nz/AboutUs/Environmental/Default.aspx
www.newcastle.edu.au 18

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Artificial Intelligence methods can help you better understand different phenomena in your research field

www.newcastle.edu.au

10

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