The document describes a numerical study analyzing the thermal resistance of different wood coating enclosure designs. Four common wood strip join systems were simulated using thermal modeling software to analyze variables like material properties, geometry, and boundary conditions. The goal was to develop a simplified numerical model to estimate thermal conductivity based on geometry. Results found the most efficient design had more material and less discontinuity, while the least efficient had the smallest cross-sectional area. The numerical model closely matched software simulations with errors below 3%, providing an easier way to estimate thermal resistance without complex modeling.
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
CMN2015_2
1. Numerical model development for the
optimization of wood coating enclosures
Numerical Methods for Building Energy Simulation
Jesús Mª Blanco Ilzarbe
Associate Professor
University of the Basque Country (UPV/EHU)
Authors: Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco, Eduardo Rojí
2. Numerical model development for the optimization of
wood coating enclosures
Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco and Eduardo Rojí
The most common wood coatings
applied to exterior cladding are based
on joined wood strips solutions.
In this case, the main requirements
are:
• Water-proof (humidity)
• Mechanical resistance
• Durability
- Biotic agents
- Abiotic agents
• Thermal resistance
In this study, the thermal resistance of
wood coating enclosures is analysed.
Introduction
4. Numerical model development for the optimization of
wood coating enclosures
Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco and Eduardo Rojí
3 6 9 12 Quad Tree Mesh
Parameter
between 3 - 12
W1
Aim & Method
W2
3 6 9 12
W3
W4
3 6 9 12
3 6 9 12
1440 1393 3204 NODES
10639 3899 4895 NODES
1020 365 3523 NODES
52543 45986 29861 NODES
5. Numerical model development for the optimization of
wood coating enclosures
Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco and Eduardo Rojí
Material
properties
*Código Técnico de la Edificación (Spanish regulation)
Table 1. Wood characterization
Catalog of building elements of CTE*
Material: Wood ρ λ Cp µ
kg/m
3
W/(m∙K) J/(kg∙K)
Softwood - Very heavy ρ > 610 0,23 1600 20
- Heavy 520 < ρ ≤ 610 0,18 1600 20
- Medium weight 435 < ρ ≤ 520 0,15 1600 20
- Light ρ ≤ 435 0,13 1600 20
- Balsa wood ρ ≤ 200 0,057 1600 20
Hardwood - Very heavy ρ > 870 0,29 1600 50
- Heavy 750 < ρ ≤ 870 0,23 1600 50
- Medium weight 565 < ρ ≤ 750 0,18 1600 50
- Light 435 < ρ ≤ 565 0,15 1600 50
- Very light 200 < ρ ≤ 435 0,13 1600 50
Pine Insigne
Aim & Method
6. Numerical model development for the optimization of
wood coating enclosures
Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco and Eduardo Rojí
h: Height
e: Thickness
a: angle
W: wood
Geometry
Material
properties
Aim & Method
W1 W3
W2 W4
8. Numerical model development for the optimization of
wood coating enclosures
Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco and Eduardo Rojí
Numerical
approach I
W1 Value
λ 0.1500
h1 0.0930
h2 0.0270
e1 0.0200
e2 0.0100
Ac 0.0019
At 0.0001
Xc 0.0050
Xt 0.0133
Yc 0.0135
Yt 0.0090
Xg 0.0056
Yg 0.0132
er 0.0151
R1 0.1333
R2 0.1007
Rw 0.1261
Rsi 0.1300
Rse 0.0400
R 0.2961
U 3.3777
-2.73%
P1 0.2476
P2 0.2620
C 0.9450
R 0.2798
U 3.5742
THERM
R 0.2882
U 3.4698
EEN 0.73%
2.92%
Geometry
Characterization
Material
properties
Aim & Method
h: height
e: Thickness
er: Relative thickness
Te, Ti: Exterior and interior temperature
hce, hci: Convection coeficient, exterior
and interior
R1 = Rv: Thermal resistance variable
R2 = Rc: Thermal resistance constant
9. Numerical model development for the optimization of
wood coating enclosures
Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco and Eduardo Rojí
W2 Value W3 Value W4 Value
λ 0.1500 λ 0.1500 λ 0.1500
h 0.1200 h1 0.0100 h 0.1200
e1 0.0200 h2 0.0300 e1 0.0200
e2 0.0100 h3 0.0040 e2 0.0100
Seg/2 0.0611 e1 0.0200 Ac 0.0012
Ac 0.0012 e2 0.0100 At 0.0006
As 0.0008 Ac 0.0002 Xc 0.0050
Xc 0.0050 At 0.0000 Xt 0.0133
Xs 0.0160 Xc 0.0050 Yc 0.0600
Yc 0.0600 Xt 0.0133 Yt 0.0400
Ys 0.0450 Yc 0.0150 Xg 0.0078
Xg 0.0094 Yt 0.0013 Yg 0.0533
Yg 0.0540 Xg 0.0058
Yg 0.0138
er 0.0155 er 0.0154 er 0.0156
R1 0.1333 R1 0.1333 R1 0.1037
R2 0.1033 R2 0.1028 Rsi 0.1300
Rw 0.1183 R3 0.0667 Rse 0.0400
Rsi 0.1300 Rw 0.1064
Rse 0.0400 Rsi 0.1300
Rse 0.0400
R 0.2883 R 0.2764 R 0.2737
U 3.4682 U 3.6176 U 3.6536
-4.02% -7.43% -3.60%
P1 0.1311 P1 0.0908 P1 0.2457
P2 0.1400 P2 0.1 P2 0.2600
C 0.9365 C 0.9083 C 0.9449
R 0.2700 R 0.2511 R 0.2586
U 3.7035 U 3.9829 U 3.8665
THERM THERM THERM
R 0.2772 R 0.2573 R 0.2642
U 3.6075 U 3.8865 U 3.7850
EEN 0.81% EEN 0.82% EEN 0.78%
2.59% 2.42% 2.11%
Material
properties
Aim & Method
Geometry
Characterization
Numerical
approach II
10. Numerical model development for the optimization of
wood coating enclosures
Belinda Pelaz, Jesús Cuadrado, Jesús M. Blanco and Eduardo Rojí
Numerical
approach II
Material
properties
• The most efficient shape is the first one
(W1), which has more material and less
discontinuousness on average than the
rest.
• The third solution (W3) is the least
efficient one, taking into account the
same total thickness.
Aim & Method
Geometry
Characterization
W1 W2 W3 W4
Conclusions
• The second and the third solutions (W2, W3) present the least area in
section. When comparing section vs. thermal resistance for both cases, the
difference is proportional, around 5%.
• Solution (W4) has less material than (W3) although is more efficient because
its thermal resistance is slightly higher. That demonstrates that the design
has a strong influence on efficiency, even considering the same total
thickness.
The simplified numerical model is close to the real scenario as has been
shown here, being the error values lower than 3 %. This method allows a
relatively easy estimation of the thermal resistance of particular solutions
without the higher requirements of finite elements software.
11. THANKS FOR YOUR ATTENTION!
Jesús Mª Blanco Ilzarbe
Doctor in Industrial Engineering (UPV/EHU)
Editor's Notes
Nombrar los requerimientos
Aquí decimos que el pino radiata es una de las especies más abundantes en nuestro territorio y que su conductividad térmica para una densidad media, según el CTE (Código Técnico de la Edificación), es de 0,15 W/mk (que es el dato que hemos tomado para realizar los siguientes cálculos)
Estas son las geometrías machihembradas escogidas para el estudio por ser las más comunes en paramentos verticales
Hemos evaluado la resistencia térmica de las diferentes opciones con el software de cálculo THERM It is a 2D finite-element heat-transfer analysis tool
Para definir la metodología primero se ha realizado un primer cálculo de resistencia térmica basado en el área y espesor de la pieza, para el cual se ha considerado un espesor equivalente. A posteriori se le aplica un coeficiente de corrección basado el la relación entre el perímetro que inscribe la pieza y el perímetro equivalente, obtenido a partir del espesor equivalente.
Realizamos el mismo proceso para las otras tres muestras. Como se puede apreciar en los resultados, el error de cálculo entre la opción simplificado que hemos realizado y los resultados del THERM, éste en todos los casos resulta un valor positivo y menor que 4. El valor positivo de indica que dicho error se inclina del lado de la seguridad, siendo la resistencia térmica real de la pieza ligeramente mayor que la obtenida.
