senvar 6 proposal - Institut Teknologi Sepuluh Nopember

The 6th International Seminar on Sustainable Environment and Architecture 19 – 20 September 2005 Department of Architecture, Institut Teknologi Bandung, Indonesia

THERMAL PERFORMANCE OPTIMIZATION FOR JAVANESE VILLAGE HOUSES FX Teddy Badai Samodra Environmetal Architecture Sepuluh Nopember Institute of Technology Kampus ITS-Sukolilo, Surabaya 60111 E-mail: [email protected]

Abstract The climate in humid tropic area is the most difficult aspect which can be solved by architectural method. In fact, thermal contribution would not happen if building and environmental design met human being’s need or is very subjective. This research studied Javanese village houses because this type of house has typical characteristics which can be recognized from the materials used, dimension and building shape. This research aims at finding out the influence of architectural design and building construction system on thermal performance optimization, recognizing characteristics of village houses which indicate thermal performance optimization as well as recognizing components of village houses which influence thermal performance most. To gain comfortable duration and Khours value in the coldest month (August) and the hottest (November), computer simulation using Aiolos and Archipak software was used from this simulation, the best thermal performance can be determined. The result shows that architectural design and building construction can optimize thermal performance. And with combination of kloneng wall and genteng roof with south orientation, the thermal performance will be the best, with roof variable as the most influential factor. Keywords:

humid tropical climate, material simulation, thermal performance, village houses, village image

INTRODUCTION Thermal performance for Javanese village house has not been optimal as colonial typology but it can be designed in this context by using air change (Santosa, 2003). In the other research (Nirwansjah dan Hariadi, 1988), there is contradiction on observation result; Thermal performance for Javanese village house has been more effective than colonial ones because it has lightweight material. In the range of village image that are roof style and dimension, material at the time variable, and also characteristic of Javanese village house plan, it has potential to have material simulation, by optimizing the roof, building skin construction system and orientation from the point of view of thermal performance. BUILDING THERMAL BEHAVIOUR In the area that has small variations in dry air temperature and relative humidity, daily or annually, some factors determine building thermal behaviour. They are capability for thermal resistance from building skin construction, solar radiation (direct or indirect), number of air change, and internal heat gain (Santosa,1993). This Environmental problems will take a lot of variables. Sub variables or components of variable have complex relation. In this case, designer as decision maker must take a decision for specific condition. This condition needs optimization process that can support all of aims. Optimization process will be efficient if it is supported by computer simulation system

Labtek IXB, 4th floor Department of Architecture ITB , Ganesha 10, Bandung 40132, Indonesia Tel.Fax : +62 22 2504962/ +62 22 2530705 Email : [email protected], URL : www.ar.itb.ac.id/senvar6

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because it needs iterations that have unpredictable number of simulation. Thus, it must use optimization software appropriates with the problems. VILLAGE ARCHITECTURAL IMAGE Javanese village house has specific charateristics as indentity (Gunadi and Prijotomo, 1979). That images can be used as range of simulation for obtaining thermal performance optimization. It must be done on that range, so the simulation can not neglect village image (Table 1). Table 1: Village Architectural Image No. 1.

Spesific aspects Roof Style

Notes Roof has kampung pokok style like brunjung on Joglo and there are emper on it. 2. Dimension The dimension of building ussualy appropriates with nuclear family. 3. Material Material would be taken from surroundings environment. Source: Gunadi and Prijotomo, 1979

Base on the village image study, elements of the village house whose potential for optimization are roof, building skin construction system, and orientation. Roof; in the thermal performance, optimization for the roof is the material, but in limited alternative. It is only taken from surroundings area. Building skin construction system; it consist on wall and openings (window, door, ect). Its material is also taken from surroundings area. Orientation; Javanese village house orientation has not specific regulation, so that all of orientation can be taken on the simulation. RESEARCH METHOD This research involves three main phases for environment temperature prediction to the Javanese village houses, that are: Indentification and specification phase; evaluation for characteristic of village houses and fixation for simulation object. Simulation phase; realization for simulation model and optimization system on the building design with Aiolos v1.0 (ventilation simulation) and Archipak v4.0 (thermal simulation) software. Optimization phase; evaluation for obtaining the optimization model in the thermal performance. The object in this research is Javanese village house with original condition, it means that object simulation must be occupied by ≤ 5 persons (it is decribed as nuclear family and consist on father, mother, and 3 children). Research location for Javanese house would be taken on the area whose village characteristic (rural). This study was conducted by doing direct observation about the available building materials, occupant characters and environmental condition in Kedawung, Blitar, East Java, which is determined on the basis of comparable data obtained from Meteorology and Geophysics Centre of Karangploso, Malang. Based on field study, the number of material simulation, which can be done to optimize thermal performance, reaches 24 (Table 2). To gain comfortable duration and Khours value in the coldest month (August) and the hottest (November), based on data obtained in the year 2000-2004, computer simulation using Aiolos and Archipak software was used from this simulation, the best thermal performance can be determined.


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Table 2: Village Houses Simulation Description Simulations

Variables

Notes

Wall

Wood Wood shingles (without plafond) a. Simulation 1 (North = 00)

a). PART 1 (Simulation 1- 4)

Roof

Existing Wall and Material, Different Orientation

Orientation

Roof

Wall b). PART 2 (Simulation 5- 8)

Roof

Different Wall material, Existing Roof Material, Different Orientation

Orientation Wall

c). PART 3 (Simulation 9- 12)

Roof

Different Wall material Existing Roof Material Different Orientation

Orientation

d). PART 4 (Simulation 13- 16)

Wall Roof

Existing Wall material, Different Roof Material, Different Orientation e). PART 5 (Simulation 17- 20)

Different Wall material, Different Roof Material, Different Orientation f). PART 6 (Simulation 21- 24)

Different Wall material, Different Roof Material, Different Orientation

Orientation Wall Roof Orientation Wall Roof Orientation

b. Simulation 2 (East = 900) c. Simulation 3 (South = 1800) d. Simulation 4 (West = 2700)

Bamboo Wood shingles (without plafond) a. Simulation 5 (North = 00) b. Simulation 6 (East = 900) c. Simulation 7 (South = 1800) d. Simulation 8 (West = 2700)

Kloneng Wood shingles (without plafond) a. Simulation 9 (North = 00) b. Simulation 10 (East = 900) c. Simulation 11 (South = 1800) d. Simulation 12 (West = 2700)

Wood Genteng a. Simulation 13 (North = 00) b. Simulation 14 (East = 900) c. Simulation 15 (South = 1800) d. Simulation 16 (West = 2700)

Bamboo Genteng a. Simulation 17 (North = 00) b. Simulation 18 (East = 900) c. Simulation 19 (South = 1800) d. Simulation 20 (West = 2700)

Kloneng Genteng a. Simulation 21 (North = 00) b. Simulation 22 (East = 900) c. Simulation 23 (South = 1800) d. Simulation 24 (West = 2700)

DISCUSSION AND RESULT In the coldest month, comfort duration of existing building (with wood wall and wood shingles roof) in active periode time on all of orientations (simulation 1-4) has the same value, that is 11 hours (Figure 1). Substitution the wood wall in to bamboo and kloneng (simulation 5-12) can not improve the existing; in fact, it is decrease become 8 hours. In the K-hours analysis also can be seen the same condition. Simulations involve wood shingles roof indicate that similar thermal performance from simulations have been


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obtained by Javanese village house models with the same wall material, like simulation 1-4 (wood), simulation 5-8 (bamboo), and simulation 9-12 (kloneng). Simulation phenomena show that underheating problem has been dominant, with bamboo and kloneng wall, the value is -15.7. Exactly, in the wood wall simulation, the underheating value is only -9.1. However, all of simulations that involve wood shingles roof, the overheating values are not different so much (maximum value is 0.7). Like coldest month, in the hottest month simulation 13-24 with genteng roof have thermal performance are better than wood shingles roof. However, in this month comfort duration (total or active periode) has resemble values. The difference value among simulation 1-24 is only 1 hours in the total calculation (20 of 21 hours) or active periode (15 of 16 hours). In details, only on simulation 14, 17-24 optimal performance have been showed. Comparable data in Khours analysis indicate that simulations involve genteng roof (simulation 13-24) have value are lower than wood shingle roof (simulation 1-12). In the genteng roof, underheating = 2.5 and overheating = 0.7, but in the wood shingles roof, underheating = -3.7 and overheating = 2.8. This Capability of the genteng roof is suitable in the hot humid tropical climate, its material has U-value = 0,84 W/mK, it is lower than wood shingles (U-value = 5,77 W/mK). In the other things, Tlag of genteng roof is 1 hours, higher than wood shingles (0 hours). It is sure that genteng has capability in the thermal resistance. 24 24

22

22

20

20

18

18

16

16

14

14

Total Comfort Duration Active Periode Comfort Duration

12

12

10

10

8

8

6

6

4

4

2

2

0

2 r oo

td

24

23

22

21

20

19

18

17

16

15

14

13

u O

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U n d e r h e a t in g

2 1

O v e r h e a t in g 23

2 td 4 o or O

u

22

21

20

19

18

17

16

15

14

13

12

9

11

8

10

7

6

5

4

1

-1

-1 0

3

0

-8

2

11

10

12

9

8

7

6

5

4

3

2

1

-4

-1 2

-2

-1 4 K-HOURS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 O 2 ut 4 do or 3

0 -2

Sim ulasi

O

Sim ulas i

2 ut 4 do or

22 23

20 21

18 19

16 17

14 15

12 13

8

9 10 11

7

6

5

4

3

2

1

0

-3

-1 6 -1 8

-4

-2 0

-5

-2 2

-6

-2 4 -2 6

-7

-2 8

-8

-3 0

-9

-3 2

-1 0

-3 4 -3 6

S IM U L A S I

S IM U L A S I

Figure 1: Thermal Performance Optimization


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Figure 2: Thermal Performance Optimization Base on comparable data of comfort duration and K-hours (Figure 1), the best performance simulation can be taken as optimization (Figure 2). According to the optimization criteria on Table 3, simulation 22 and 23 put on 3 cells, then simulation 14 for 2 cells. For selecting between simulation 22 and 23, there is one optimization criteria, that is K-hours on hottest month. In this month, overheating value of simulation 22 is 0.6, higher 0.2 than simulation 23 (0.4), but underheating value of simulation 22 is lower 0.1 than simulation 23 (-2 : -2.1). It can be determined by calculation for the total value, simulation 22 is 0.6 + 2 = 2.6 and simulation 23 has 0.4 + 2.1 = 2.5. So that, the best simulation of thermal performance can be determined with total value of K-hours is lowest, simulation 23, and it is the optimal village house (with kloneng wall, genteng roof, and south orientation). Table 3: Optimization Criteria No 1. 2.

Optimization Criteria Active periode duration K-hours

comfort

Month Coldest Simulations Simulation 17-24 Simulation 22 and 23

Value 15 hours UH = -4,2 OH = 0

Hottest Simulations Simulation 14, 17-24 Simulation 14 Simulation 15


Value 15 hours UH = -1,4 OH = 0,4 UH = -1,3 OH = 0,6

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30 29

To

28 27

degC

26 25 24

Ti

23 22

Low er C o m fo r t L im it

21 20 19 18 17

U pper C o m fo r t L im it

16 15 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

T im e

30 29

To

degC

28 27 26 25

Ti

24 23 22 21

Lower C o m fo rt L im it

20 19 18 17

Upper C o m fo rt L im it

16 15 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

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20

21

22

23

24

T im e

Figure 3: Temperature Fluctuations of Optimal Village House In the coldest and hottest month, the optimal village house (from simulation 23) has capability for reducing the thermal condition of environment and existing village house. In the hottest month, this optimal village house is in warm condition, but it still can reduce the overheating value or its condition. At 06.00 a.m. (coldest and hottest month) is in underheating (Figure 3), it has been indicated by any factors, such as: Opening schedule shows 1 (opened) at 05.00 a.m. and influence dynamically the condition at 06.00, it has also been determined by underheating condition of the environment. Solar radiation has not influence to the building. Material characteristic is heat loss, so that building in underheating condition. CONCLUSION Architecture design in the Javanese village house simulations has fixed value for optimization. That design elements are shape and dimension, building construction indicates about the material. From the discussion, combination for material (roof and wall) can improve the environment and existing building. This optimization shows that simulation 23 has the best performance. It has characteristic, such as: It uses genteng roof (traditional tile, slope ± 40 deg). It uses kloneng wall (combination of brick plestered and bamboo). It has south orientation (main opening on southern). By substitution wood shingles roof with genteng, the optimization can be obtained. The tabulation and graph illustration indicate that it has significant difference on this substitution. Substitution to the wall and combination with orientation have influence also,


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but their contribution are lower than in roof. From the elemental breakdown analysis, roof element is good element of building for losing the heat gain, so roof variable as the most influential factor. REFERENCES Allard, F. (1998) Natural Ventilation in Buildings. James & James LTD, London Aynsley, R.M. (1977) Architectural Aerodynamics. Applied Science publishers LTD, London Frick, H. (1997) Pola Struktural dan Teknik Bangunan di Indonesia. Kanisius, Yogyakarta Gunadi S., dan Prijotomo, J. (1979) Perkembangan Arsitektur Pedesaan. FTA – ITS, Surabaya Ismunandar, R. (1997) Arsitektur Rumah Tradisional Jawa. Daahra Prize, Semarang Nirvansjah, R. dan Hariadi, D. (1988) Study Faktor Kenyamaman dan Kenikmatan Bangunan Kolonial di Surabaya. Pusat Penelitian ITS, Surabaya Santosa, M. (1993). Sistem Informasi Aspek Panas dalam Rancang Arsitektur. Lemlit ITS, Surabaya Santosa, M. (2000) Specific Responses of Traditional Houses to Hot Tropic, Proceedings SENVAR2000, October 23-24. pp 13-17. Santosa, M. (2003) Totalitas Arsitektur Tropis. Orasi Pengukuhan Guru Besar ITS. Surabaya Swami dan Chandra (1988) Correlation for Pressure Distribution on Buildings and calculation of Natural-Ventilation Airflow. ASHRAE Transactions, vol. 94. no.1 Szokolay, S.V. (1987) Thermal Design of Buildings. RAIA Education Division, Canberra


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