journal - road construction material

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THE DEVELOPMENT OF ROAD CONSTRUCTION MATERIAL SELECTION SYSTEM (RC-MSS) Kian Teck TEH Research Assistant Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected] Ratnasamy MUNIANDY Lecturer Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected] Azmi HASSAN Director Kelantan Public Work Department 15990 Kota Bharu, Kelantan. Malaysia E-mail: [email protected] Salihuddin HASSIM Lecturer Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected] Husaini OMAR Lecturer Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected] Abstract: This paper looks into the development of a prototype Road Construction Material Selection System (RC-MSS) which based on the outcome through interviewed to the pavement experts to obtain the appropriate material for each pavement layer under particular design conditions. Data collected from the experts would be analysis using nonparametric statistical method to determine the ranking of each pavement material alternative prior to the development of RC-MSS. RC-MSS is developed with a prototype of an expert system using written using programming tool Microsoft Visual Basic 6.0 according the framework from the system. With this tool, better road design can also be achieved and save more time in the initial stage of on material selection, before scrutiny to laboratory test. This software would be the pioneer and provide guidance to engineers and consultants. Key Words: Material Selection, Expert System, Pavement, Road Construction 1. INTRODUCTION Pavement design is aimed to achieving a pavement structure which is economical, comfortable and yet safe to travel by motorist; and which minimizes development of pavement distress features during the design life of the pavement. However, inappropriate selection of road materials for construction may have caused premature pavement failure. In view of these problems, a study was undertaken with the aid of Intensification of Research in Priority Areas (IRPA) funding to develop a prototype expert system of pavement material selection in order to assist the pavement designer in selecting pavement material alternative. The system incorporates the properties of soil along the selected road alignments where Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, pp. 1313 - 1328, 2005 1313

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Page 1: Journal - Road Construction Material

THE DEVELOPMENT OF ROAD CONSTRUCTION MATERIAL SELECTION SYSTEM (RC-MSS)

Kian Teck TEH

Research Assistant Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected]

Ratnasamy MUNIANDY Lecturer Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected] Azmi HASSAN Director Kelantan Public Work Department 15990 Kota Bharu, Kelantan. Malaysia E-mail: [email protected]

Salihuddin HASSIM Lecturer Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected] Husaini OMAR Lecturer Civil Engineering Department Universiti Putra Malaysia 43400 Serdang, Selangor D.E., Malaysia. E-mail: [email protected]

Abstract: This paper looks into the development of a prototype Road Construction Material Selection System (RC-MSS) which based on the outcome through interviewed to the pavement experts to obtain the appropriate material for each pavement layer under particular design conditions. Data collected from the experts would be analysis using nonparametric statistical method to determine the ranking of each pavement material alternative prior to the development of RC-MSS. RC-MSS is developed with a prototype of an expert system using written using programming tool Microsoft Visual Basic 6.0 according the framework from the system. With this tool, better road design can also be achieved and save more time in the initial stage of on material selection, before scrutiny to laboratory test. This software would be the pioneer and provide guidance to engineers and consultants. Key Words: Material Selection, Expert System, Pavement, Road Construction 1. INTRODUCTION Pavement design is aimed to achieving a pavement structure which is economical, comfortable and yet safe to travel by motorist; and which minimizes development of pavement distress features during the design life of the pavement. However, inappropriate selection of road materials for construction may have caused premature pavement failure. In view of these problems, a study was undertaken with the aid of Intensification of Research in Priority Areas (IRPA) funding to develop a prototype expert system of pavement material selection in order to assist the pavement designer in selecting pavement material alternative. The system incorporates the properties of soil along the selected road alignments where

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pavement materials are severely over stressed. The type and soil conditions, and expected load repetitions are other parameters found to be indispensable in the formulation of material selection system for road construction. The material performance and the selection of the appropriate construction materials for the various layers under certain traffic-loading under the type of terrains such as flat, rolling and mountainous was incorporated as important parameters. Such conditions govern the duration of axle loading on the pavement. Pavement material selection should be based on road user-oriented, not only based on industry-oriented process. There is a drive towards the development of more appropriate material selection approaches as these will allow alternative solutions to be readily compared and, thus, evaluated. A prerequisite for any successful analytical design methodology is the reliable measurement of representative material properties. The objective of this study is to develop a first expert system that could be used as a tool in pavement material selection to help engineers in better decision making.

2. FACTORS THAT CONSIDERED IN RC-MSS The system has look into the anticipated traffic loading, soil condition, type of terrain and geometric features as aspects which should not be neglected in pavement material selection. 2.1 Anticipated Traffic Loading Condition Commercial traffic loading is the main factor to any pavement design problem. It heavy axle loads which cause pavement to damage and fail if poor pavement material is chosen. Typically, the traffic magnitudes and configurations are expressed in terms of the number of equivalent standard axles load (ESAL) (Lay 1990; JKR 1985) and equal to the number of passes of the local standard axle load carried on a pair of dual tires which would cause the same pavement damage as a single pass of axle load equivalent to 8.16 Tonne (Harold, 2003; JKR, 1985). The system will incorporated the anticipated ESAL as another input factor which classified it into three categories (high, moderate and low anticipated ESAL) as illustrated in Table 1.

Table 1. Classification of Anticipated ESAL for 10 years Design Life

Traffic Loading Low Moderate High Anticipated ESAL < 300,000 300,000 – 10,000,000 > 10,000,000 Denoted Symbol E1 E2 E3

2.2 Soil Condition Soil condition is also another main factor to be considered in pavement design and material selection. The properties of the soil are important not only as the foundation of pavement structure but also crucial factor of cost in construction project. Poor material such as peat, clay soil, highly organic soils and soils contaminated with hazardous chemicals would caused serious damage to the pavement in the initial stage and extremely costly to reconstruction (Harold, 2000). The strength of road subgrade is commonly assessed in terms of the

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California Bearing Ratio (CBR) and this is dependent on the type of soil, its density, and its moisture content (Huang 1993; Lay 1990). Higher value of CBR would be suitable to use as subgrade, CBR value which is less than 5 should considered as poor subgrade soil, due to poor sustainable to heavy load. The system will use the CBR value input data to the system. The CBR value is classified into three categories (good, moderate and poor) and each category range is shows in Table 2.

Table 2. Soil CBR value Divided into Three Categories

Soil Condition Good Fair Poor CBR, % > 10 5 – 10 ≤ 5 Denoted Symbol S1 S2 S3

2.3 Geometric Feature Climbing lane and sharp horizontal curve where multiple heavily loaded vehicles firmly brake, travel at slow speeds or remain standing for periods of time have caused the pavement to deteriorate due to highly stresses on the pavement. Consequently, pavement exhibited rutting and premature distresses due to the combination of truck traffic patterns, counts and weights before the reaching the predicted design period (Harun, 1992). However, these factors are only considered in safety purpose on geometric design and less concern in pavement material by road designer. Hence, geometric feature on vertical gradient and degree of horizontal curvature the system had been considered in the system and classified into two categories of critical area and non-critical area as presented in Table 3.

Table 3. Geometric Features Classification

Geometric Feature Non-Critical Critical

Vertical Gradient < 5 % ≥ 5 % Denoted Symbol (Vertical Gradient) V1 V2 Degree of Horizontal Curve ≤ 7º > 7º Denoted Symbol (Horizontal Curve) H1 H2

Topography profile of road such as type of terrain is crucial in pavement design and it is generally divided into three group, that are flat, rolling and mountainous which determine by the percentage of cross slope as shown in Table 4 (JKR, 1986). The terrain types incorporated in the system as determine type of material selection.

Table 4. Terrain Type

Type of Terrain

Flat Rolling Mountainous Cross Slope ≤ 3 % 3 – 25 % ≥ 25 % Denoted Symbol T1 T2 T3

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3. MATERIALS AND METHODS Two stages of questionnaires had been carried out to obtain the opinions from the pavement experts who specialize in road design or evaluation and familiar in pavement materials’ characteristics. Material suitable to use for nine site conditions (presented in Table 5) which were the combination of anticipated traffic loading, soil, geometric feature and terrain type were obtained. These factors were verified again from the experts. While, for poor soil CBR value (2.5 – 5%) and very poor soil CBR (less than 2.5%), adopted measure to the condition were selected and suggested by the experts. The suggested materials by the experts were then rearranged and gather together prior to the second interview conducted. Second stage of questionnaire, experts were required to rate the materials suggested for each site conditions based on the material durability, performance and ease of construction using Likert scale (very suitable=10 to less suitable=1). Adopted measure to poor soil condition was designated as site condition 10th. The non-numeric data were ranked as in ordinal type data using Friedman statistical test due to several related materials were suitable to use (Conover 1999; Daniel 1978). This method was used to determine the hypothesis test of identical performance of the materials under particular design condition. was used as the hypothesis analysis tool in second stage. The knowledge derived from outcome of the statistical method was then stored in the system database. The material selected and ranking will be used as “knowledge base” and particular design site condition will be use as the “inference engine” in the system. If-then will incorporated in the rule-bases of the expert system, the materials and ranking database could be determine from the design conditions matrix. The results generated by these rule-bases are used to assist in decision making.

Table 5. Designed Site Condition and Assigned Symbol

Soil Anticipated ESAL Geometric Site Condition Condition Symbol Condition Symbol Condition Symbol

1 Good S1 High E3 Non-critical area C1 2 Fair S2 Moderate E2 Non-critical area C1 3 Fair S2 High E3 Non-critical area C1 4 Good S1 Low E1 Critical area C2 5 Good S1 Moderate E2 Critical area C2 6 Good S1 High E3 Critical area C2 7 Fair S2 Low E1 Critical area C2 8 Fair S2 Moderate E2 Critical area C2 9 Fair S2 High E3 Critical area C2

4. RESULTS AND DISCUSSION Results from the first questionnaire is illustrated in Table 6.

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Table 6. Domain Experts Results from First Stage of Questionnaire

No. Statement A B C D E

1 Pavement material selection should considered geometric factor of vertical gradient.

√ √ √ √ √

2 Pavement material selection should considered geometric factor of horizontal curvature.

√ √ √ √ √

3 Pavement material selection should considered soil condition of CBR. √ √ √ √ √

4 Pavement material selection should considered traffic loading of designed ESAL.

√ √ √ √ √

5 Pavement material selection should considered type of terrain. √ √ √ √ √

6 Vertical gradient considered as critical area when ≥ 5 %. √ √ √ √ √

7 Horizontal curvature considered as critical area when > 7°. √ √ √ √ √

8 Low if designed ESAL when < 300,000. √ √ √ √ √

9 Moderate if designed ESAL when 300,000 – 10,000,000. √ √ √ √ √

10 High if designed ESAL when > 10,000,000. √ √ √ √ √

11 Good if soil CBR when > 10 %. √ √ √ √ √ 12 Fair if soil CBR when 5 % – 10 %. √ √ √ √ √ 13 Poor if soil CBR when 2 % – 5 %. X X X X √ 14 Very poor if soil CBR when < 2 %. X X X X √

Note: √ : Pavement experts agree with the statement. X: Pavement experts disagree with the statement. From Table 6, all the five domain experts agree the statements 1 to 12. Only one expert agree to the statements 13 and 14, however, four experts who did not agree with the statement mentioned that the soil is considered poor whenever CBR value is less than 5 %, and treatment must be done to that particular soil, no compromise to let the soil untreated. The treatment selected and suggested by the experts were as followed.

• Chemically stabilized; • Geosynthetics stabilized; • Excavated and replaced stronger soil material; • Dynamic compaction; • Preloading or vertical drain cohesive.

The second stage of questionnaire results adopted Friedman statistical test method was tabulated as shows in Table 7. The Table shows that null hypothesis at 95% significant level for site condition 1st (rolling and mountainous terrain), 2nd (mountainous terrain), 6th (rolling and mountainous terrain), 8th (mountainous terrain), 9th (rolling and mountainous terrain) and 10th (any terrain) were rejected. It may be concluded that there were a tendency for some

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types of pavement materials to be provide better durability, performance and ease of construction over the others. For the rejected null hypothesis site conditions, sum of the ranks of each pavement material were ranked within each block. The results illustrated that the some pavement material at critical condition such as high anticipated ESAL, highly stress area from rolling to mountainous terrain might not durable and caused premature distresses to the road such as rutting and cracking ultimately elongated to structural failure.

Table 7. Friedman’s Test Result for Site Conditions

Site Condition Terrain Type K k1 k2

Referred to F-distribution Table at 0.95

Quantiles

Friedman Test Result

Flat 14 13 52 1.92 1.72 Accept Ho Rolling 14 13 52 1.92 2.20 Reject Ho 1

Mountainous 14 13 52 1.92 2.20 Reject Ho Flat 7 6 24 2.51 0.73 Accept Ho

Rolling 8 7 28 2.36 1.32 Accept Ho 2 Mountainous 8 7 28 2.36 3.02 Reject Ho

Flat 14 13 52 1.92 1.91 Accept Ho Rolling 14 13 52 1.92 1.85 Accept Ho 3

Mountainous 14 13 52 1.92 1.06 Accept Ho Flat 6 5 20 2.71 1.89 Accept Ho

Rolling 6 5 20 2.71 1.08 Accept Ho 4 Mountainous 7 6 24 2.51 0.73 Accept Ho

Flat 6 5 20 2.71 2.04 Accept Ho Rolling 7 6 24 2.51 1.22 Accept Ho 5

Mountainous 7 6 24 2.51 0.73 Accept Ho Flat 7 6 24 2.51 1.65 Accept Ho

Rolling 7 6 24 2.51 6.02 Reject Ho 6 Mountainous 7 6 24 2.51 4.51 Reject Ho

Flat 8 7 28 2.36 0.89 Accept Ho Rolling 7 6 24 2.51 1.11 Accept Ho 7

Mountainous 7 6 24 2.51 0.86 Accept Ho Flat 7 6 24 2.51 1.08 Accept Ho

Rolling 7 6 24 2.51 1.30 Accept Ho 8 Mountainous 7 6 24 2.51 8.67 Reject Ho

Flat 7 6 24 2.51 1.14 Accept Ho Rolling 7 6 24 2.51 8.62 Reject Ho 9

Mountainous 7 6 24 2.51 0.82 Reject Ho Flat 5 4 16 3.01 8.02 Reject Ho

Rolling 5 4 16 3.01 4.82 Reject Ho 10 Mountainous 5 4 16 3.01 5.54 Reject Ho

Tables 8 and 9 represented the ranking for each material at each pavement layer under site condition 1st to 9th and site condition 10 respectively.

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Table 8. Materials Ranked at Each Site Condition and Type of Terrain

Pavement Layer Ranked

Site Condition / Denoted Symbol (vertical texts)

Ter

rain

No SG SB BC SC

1 M4 2 M5 3 M6 4 M7 5 M8 6 M9 7 M

10

8 M11

9 M12

1 SG1 SB1 BC1 SC1 S S S S S S S S S 2 SG1 SB1 BC1 SC2 S S S S S S S S 3 SG1 SB1 BC1 SC3 S S S S S S S S S 4 SG1 SB1 BC1 SC4 S S S 5 SG1 SB1 BC2 SC1 S S S S S S S S S 6 SG1 SB1 BC2 SC2 S S S S S S S S 7 SG1 SB1 BC2 SC3 S S S S S S S S S 8 SG1 SB1 BC2 SC4 S S S 9 SG1 SB1 BC3 SC1 S S

10 SG1 SB1 BC3 SC2 S S 11 SG1 SB1 BC3 SC3 S S 12 SG1 SB1 BC3 SC4 S S 13 SG1 SB1 BC4 SC2 S 14 SG1 SB1 BC5 SC3 S 15 SG2 SB1 BC1 SC1 S 16 SG1 SB1 BC4 SC1 S 17 SG1 SB1 BC5 SC2 S 18 SG1 SB1 BC4 SC3 S 19 SG3 SB1 BC2 SC1 S 20 SG3 SB1 BC2 SC2 S 21 SG1 SB2 BC4 SC3 S 22 SG3 SB1 BC1 SC1 S 23 SG1 SB1 BC5 SC1 S

Flat

24 SG3 SB1 BC1 SC2 S 1 SG1 SB1 BC1 SC1 12 S S S S 7 S S 7 2 SG1 SB1 BC1 SC2 9 S S S 6 S S 6 3 SG1 SB1 BC1 SC3 10 S S S S 5 S S 5 4 SG1 SB1 BC1 SC4 14 S S 5 SG1 SB1 BC2 SC1 11 S S S S 4 S S 3 6 SG1 SB1 BC2 SC2 4 S S S 1 S S 2 7 SG1 SB1 BC2 SC3 5 S S S S 3 S S 3 8 SG1 SB1 BC2 SC4 12 S S 9 SG1 SB1 BC3 SC1 7 S S

10 SG1 SB1 BC3 SC2 1 S S 11 SG1 SB1 BC3 SC3 1 S S 12 SG1 SB1 BC3 SC4 6 S 13 SG1 SB1 BC4 SC2 3 14 SG1 SB1 BC5 SC3 7 15 SG2 SB1 BC2 SC1 S 16 SG2 SB1 BC1 SC1 S

Rol

ling

17 SG1 SB1 BC4 SC1 S

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18 SG3 SB1 BC5 SC2 S 19 SG1 SB1 BC1 SC2 S 20 SG1 SB1 BC4 SC3 2 21 SG1 SB2 BC4 SC3 S 1 22 SG3 SB1 BC5 SC1 S

23 SG3 SB1 BC2 SC1 S 1 SG1 SB1 BC1 SC1 12 6 S S S 7 S 7 7 2 SG1 SB1 BC1 SC2 5 5 S S S 5 S 6 6 3 SG1 SB1 BC1 SC3 8 8 S S S 6 S 4 5 4 SG1 SB1 BC1 SC4 14 S 4 5 SG1 SB1 BC2 SC1 11 7 S S S 4 S 2 3 6 SG1 SB1 BC2 SC2 3 4 S S S 1 S 1 1 7 SG1 SB1 BC2 SC3 3 1 S S S 2 S 2 8 SG1 SB1 BC2 SC4 13 S 9 SG1 SB1 BC3 SC1 8 S

10 SG1 SB1 BC3 SC2 1 S 11 SG1 SB1 BC3 SC3 2 S 12 SG1 SB1 BC3 SC4 5 S 13 SG1 SB1 BC4 SC2 5 14 SG1 SB1 BC5 SC3 8 15 SG2 SB1 BC1 SC1 2 16 SG3 SB1 BC1 SC2 2 S 17 SG1 SB1 BC4 SC1 S 18 SG2 SB1 BC5 SC2 S 19 SG1 SB1 BC5 SC2 S 20 SG1 SB1 BC4 SC3 3 21 SG3 SB1 BC5 SC1 S 22 SG3 SB1 BC2 SC2 5

Mou

ntai

nous

23 SG1 SB2 BC4 SC3 1 Note: 1. Referred to appendix to obtain the symbol descriptions for pavement material. 2. Symbol ‘S’ represent the materials in the particular site condition is equally likely in

performance, durability and ease of construction. 3. Shaded cell indicated the particular material not used at the particular site condition.

Table 9. Material Ranked for Site Condition 10th (denoted symbol for ‘TSG’)

Terrain Type/

Denoted Symbol No Adopted measured to the existing soil Ranked

1 Chemically stabilized 3 2 Geosynthetics stabilized 4 3 Excavated and replaced stronger soil material 1 4 Dynamic compaction 5

Flat, T1

5 Preloading/ vertical drain 2 1 Chemically stabilized 5 2 Geosynthetics stabilized 3 3 Excavated and replaced stronger soil material 1 4 Dynamic compaction 4

Rolling, T2

5 Preloading/ vertical drain 2

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1 Chemically stabilized 5 2 Geosynthetics stabilized 3 3 Excavated and replaced stronger soil material 1 4 Dynamic compaction 4

Mountainous, T3

5 Preloading/ vertical drain 2

5. RC-MSS FRAMEWORK In the pavement material selection system (RC-MSS) the factors that considered in developing RC-MSS is shown previous from Tables 1 to 4. In order to adopt RC-MSS, user should provide the information of existing soil CBR value done by surveyor, anticipated ESAL, geometric design feature for vertical gradient, degree of curvature and type of terrain. Geometric features of horizontal curvature group and vertical gradient group were regrouped to divide to non-critical area (assigned symbol as C1) and critical area (assigned symbol as C2) as presented in Figure 1.

Note: Symbol ‘C’ Denoted as Critical Condition

Figure 1. Regrouping of Horizontal Curvature and Vertical Gradient Groups to Critical and Non-Critical Group

Design conditions consisted of anticipated ESAL group (denoted as ‘E’), soil CBR group (denoted as ‘S’) and critical area group (denoted as ‘C’) as shows in Figure 2. These design conditions would then followed the path sorted from denoted symbol ‘E’, ‘S’, ‘C’ to ‘M’. However, if design condition consisted of symbol ‘S3’ that is poor soil group. Then, the block ‘TSG’ that is adopted measure to poor soil would be the next station. The ‘modify’ design condition after ‘TSG’ would considered equivalent to good soil group as denoted by symbol ‘S1’ before proceed to the ‘C’ group to reach Materials Suggested Database denoted as ‘M’, if the previous design condition of symbol enter block ‘TSG’, the database to reach is Material Suggested Database with asterisk (denoted symbol ‘M*’). Block symbol ‘TSG’ was extracted from the result from Table 9. Since it was not significant to conclude that the adopted measured for poor soil are more likely to perform better than others, hence the adopted measured were not ranked. The database of ‘M*’ have the same suggested pavement material

Horizontal curvature

H2 H1

Vertical gradient

V2 V1

C1 C2

C

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for subbase, base course and surface course as database of ‘M’ except the subgrade where ‘M*’ adopted the subgrade from block symbol ‘TSG’.

Note: Symbol ‘M’ Denoted as Materials Suggested Database, and * Represented Material

Suggested Database Directed from the Path from Denoted Symbol ‘TSG’.

Figure 2. Direction Path from Design Condition to Materials Suggested Database 6. PROBLEM EXAMPLE A simple example has been run to illustrate the framework of RC-MSS. The design conditions are as followed. Example problem:

• Anticipated ESAL = 500,000 • Soil CBR value, % = 3 • Vertical gradient, % = 3 • Horizontal curvature, ° = 8 • Type of terrain = Flat

Every particular from the design condition has been classified to each group as shows in Table 10. The geometric feature of vertical gradient was non-critical but horizontal curvature was critical. As mentioned earlier in Figure 1, once either one of the geometric features of vertical gradient or horizontal curvature is in critical that is ‘V2’ or ‘C2’, it would be considered as critical region. So, the example has been classified as symbol ‘C2’ of critical area. However, the soil condition was classification as poor which denoted as symbol ‘S3’. As

RC-MSS Framework

E1 E2 E3

TSG

M1,

M1*

M8,

M8*

M5

M11

M4,

M4*

M9,

M9*

M6

M12

M7,

M7*

M1

M10

M1,

M1*

S1 S2S1S3 S2 S3 S1 S2

C1C1

C1 C1

C1

C1

C2

C2 C2 C2

C2

S3

C2

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discussed in the previous section RC-MSS framework, the design would enter the station denoted symbol ‘TSG’ then exit to station ‘S1’ before reaching the 8th Asterisk Material Suggested Database denoted as symbol ‘M8*’. The whole flow diagram is illustrated in Figure 2 which given the ticker plotted line. In the Asterisk Material Suggestion Database, database of pavement materials suggested for each layer would then referred to the flat terrain section denoted as symbol ‘T1’ except subgrade material would referred to station denoted from symbol ‘TSG’. The flow path can be illustrated in Figure 3 and materials suggested is summarizes as presented in Table 11. No ranked is assigned to the database ‘M8*’ at ‘T1’ as discussed in the previous section 4 referred to Table 8 except adopted measured to subgrade. Referred to Table 11 of denoted symbol ‘TSG’ at ‘T1’ shown method of adopted measured were ranked.

Table 10. Classification of Design Condition in Example Problem

Design Condition Classification Denoted Symbol Anticipated ESAL Moderate E2 Soil condition Poor S3 Vertical gradient Non-critical V1 Horizontal curvature Non-critical H1 Type of Terrain Flat T1

Figure 3. Whole Flow Path Diagram in Example Problem

Table 11. Problem Example Summary using Database ‘M8*’ and ‘TSG’ at ‘T1’

Subgrade, SG Subbase, SB Base, BC Surface, SC Adopted Measured

Denoted Symbol (ranked)

Type of Material Denoted Symbol

Type of MaterialDenoted Symbol

Type of MaterialDenoted Symbol

SB1 BC1 SC1 SB1 BC1 SC2 SB1 BC1 SC3 SB1 BC2 SC1 SB1 BC2 SC2 SB1 BC2 SC3

TSG3 (1); TSG5 (2); TSG1 (3);

TSG2 (4), and TSG4 (5)

SB1 BC1 SC2

Note: Referred to appendix for description of denoted symbol.

E2 S3 TSG C2S1

M8*

M8* referred to T1 with sugrade referred to TSG.

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7. PROTOTYPE EXPERRT SYSTEM FOR RC-MSS RC-MSS is developed with Microsoft Visual Basic 6.0 (VB6) as the expert system tool due to the simplicity of this program and save time by providing an easy developing of interface with capabilities of toolbox facilities (Deitel, et al, 1999). While conventional programming language may need to type pages of instruction to create the similar visual elements. The first component is the knowledge base, which contains all relevant, domain-specific, problem-solving knowledge. It contains rules and facts and it represents this knowledge in a very simple form that could be understood by human beings. The second component is the inference engine, which drives the knowledge stored in the knowledge base through reasoning processes, which are similar to those of a human expert. The third component is user interface which serves as screen with a friendly means and the keyboard to communicating with the system (Gonzalez, et al 1993; Omar 2001). It allows the expert system to answer the questions from user. The flow diagram RC-MSS’ expert system is shown in Figure 4 and the main diagrams of expert system applied for RC-MSS are presented from Figures 5 to 8.

Figure 4. Hierarchy of Expert System in Pavement Material Selection System

Suggested materials and ranked

Print

Selected material output

Soil Input

ESAL Input

Terrain Input

Horizontal and Vertical Input

Input Data

Select Pavement Material

Material cost calculation

Ultimate output

Implement Inference Engine Rule to determine the matching matrix from the Knowledge Base

Knowledge Base Where Material Database and Rule Facts

Section (i+1)

Project Name

Company Name

Number of Section

Load existing project

Project Input

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Figure 5. RC-MSS Data Input Diagram (Geometric Design and Traffic Estimation)

Figure 6. RC-MSS Data Input Diagram (Soil Classification and CBR)

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Figure 7. RC-MSS Suggested Pavement Materials

Figure 8. RC-MSS Selected Pavement Material

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8. CONCLUSION With this prototype development of pavement material selection system, the road designer is more likely to view more proper pavement materials alternatives in the initial stage of material selection prior to the scrutiny laboratory work is carry out. Better road design can also be achieved and save more time on material selection process by engineer, before they carry out the laboratory test on the selected material. The system will also be an excellent device for novice engineers to make better pavement design decisions. However, further investigation such as weather influential, material property in the future to make the database of the system more effective, valid, precise and reliable database are needed to be more comprehensive and suitable to our climate. Since this is a prototype material selection system, the materials suggested are more general. Hence, to make the system more efficient, further development of mechanistic analysis should be incorporate to the system. Furthermore, thickness design, specific material performance and life cycle cost analysis should integrate to make a comprehensive pavement material selection system.

ACKNOWLEDGEMENT We would like to acknowledge the Ministry of Science, Technology and Environment, Malaysia in funding the project. We would also like to show appreciation to those road design engineers and pavement’s experts who helped in data collection sessions.

REFERENCE Gonzalez, A.J. and Dankel, D.D. (1993) The Engineering of Knowledge-Based Systems: Theory and Practice. Prentice Hall, New Jersey. Deitel, H. M., Deitel, P.J. and Nieto, T.R. (1999) Visual Basic 6: How to Program. Prentice Hall, New Jersey. Atkins, H.N. (2003) Highway Materials, Soils, and Concrete, 4th Edition. Prentice-Hall, New Jersey. Omar, H (2001) Development of Expert Systems, Qualifying Exam. Universiti Putra Malaysia. JKR (1985) Manual on Pavement Design. Arahan Teknik (Jalan) 5/85. Public Work Department, Kuala Lumpur. JKR (1986) A Guide On Geometric Design of Roads. Arahan Teknik (Jalan) 8/86. Public Work Department, Kuala Lumpur. Lay, M.G. (1990) Transportation Studies Volume 8, Handbook of Road Technology, 2nd Edition, Vol. 1, Planning and Pavements. Harun, M. H. (1992) The Performance of Various Bitumen Modifiers On Climbing Lanes. JKR, Mesyuarat Penolong Pengarah Jalan 3/92. Public Work Department, Kuala Lumpur.

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Conover. W.J. (1999) Practical Nonparametric Statistics: Third Edition, Wiley Series in Probability and Statistics: Applied Probability and Statistics Section, John Wiley & Sons, Inc, New York, Chichester, Weinheim, Brisbane. Daniel, W.W. (1978) Applied Nonparametric Statistics, Houghton Mifflin Company. Boston. Huang, Y.H. (1993) Pavement Analysis and Design. Prentice-Hall, New Jersey.

APPENDIX

Notations

SG1 Compacted existing soil: Compaction of the natural soil to strengthen the soil

property by increasing dry density without remove or replaced the existing soil. SG2, TSG2 Geosynthetic stabilize: Prevent migration of weak soil and provide a working

platform. It can be goetextiles, geogrids, geonets or geomembranes. SG3 Remove and replace existing soil: Substitute with stronger soil and compact. TSG1 Chemically stabilized: To strengthen the soil, remove soil sensitivity to water.

Stabilizer can be lime, cement or asphalt depend on each criteria and suitability of particular soil.

TSG Excavated and replaced stronger soil material. TSG4 Dynamic compaction: Free fall up to 20m of heavy weight in a pattern

designed to remedy poor soil conditions. TSG5 Preloading/ vertical drain: Suitable applied to areas with compressible water

satured soil such as clay and silty clays. SB1 Untreated subbase material: Generally consists of lower quality materials than

the base course. Act as filter and drainage system. SB2 Treated subbase material: Strengthen subbase using lime, cement or aspalt. BC1 Untreated base course material: Consists of quarried rock crushed or natural

gravel. Provide the structural functions. BC2 Treated base course material: Strengthen base course using lime, cement or

asphalt. BC3 Dense bitumen macadam base course: Suitable to use in heavily trafficked road

and less susceptible to environmental moisture effect. BC4 Dense bitumen macadam base with crusher run underneath: Same as function

BC3 but provide better working platform. BC5 Untreated but thicker base course: Same as function BC1 but provide more

strength and hence reduce the thickness of surface layer. SC1 Dense graded asphalt mixture: Asphalt Concrete is of this type. Able to

provides resilient, waterproof, resistance to deformation. But susceptible to heat and to fuel spillage.

SC2 Dense graded asphalt mixture with modified binder: Same as SC1, but provide extra durability to asphalt.

SC3 Gap graded asphalt mixture: Stone Mastic/ Matrix Asphalt is of this type. Suitable to use in highly stress areas, increase skid resistance, lower noise level.

SC4 Open graded asphalt mixture: Porous Asphalt is of this type. Able to drain water, reduce splash, prevent skidding, lower noise level, but low structural strength, not suitable to build in steep terrain and shorter life span.

Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, pp. 1313 - 1328, 2005

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