ABSTRACT
In this study, extreme vertex design (EVD) was adapted for the mixture experiment involving the clayey soils’ mechanical strength properties modification for civil engineering construction purposes through utilization of geotextile materials for soil reinforcement. EVD method provides an efficient approach to mixture experiment design whereby the factor level possesses multiple dependencies expressed through components constraints formulation. Using design experts and Minitab 18 software, the design of experiments, statistical diagnostics and influences, graphical and numerical optimization were carried out. I-optimal design with Quadratic model design was utilized to explore the constrained experimental region so as to formulate mixture ingredients proportions at 10 experimental runs. I-optimality and D-optimality of 0.39093 and 1747.474 respectively was obtained with G-efficiency of 64.8%. The test soil’s general engineering properties and classification were carried out before the mechanical properties tests with respect to varying ratios of mixture components. Experimental responses were obtained through laboratory process and the generated data utilized for model development and statistical analysis. The fits-summary computation showed preferences for Quadratic and linear model source respectively for CBR and UCS respectively. The statistical influence and diagnostic test results showed that there is no significant difference between the experimental constant results and the model results. Furthermore, desirability function was utilized to achieve numerical and statistical optimization in order to arrive at the optimal solution for the mixture components combination at 0.002:0.098:0.9 for geogrid, water and soil respectively. A desirability score of 1.0 was obtained with optimal response of 19.546% and 41.270kN/m2 for CBR and UCS respectively. The results indicated improvement in the problematic soil’s mechanical properties due to the incorporation of geogrid material for pavement construction. Model simulation was further carried out to test the model’s applicability with the results compared with the actual results using ANOVA and student’s t-test. The statistical analysis results indicated a p-value>0.05 which indicates there is no significant difference between the compared datasets.
TABLE OF CONTENT
Cover page i
Title page ii
Declaration iii
Dedication iv
Certification v
Acknowledgement vi
Table of Contents vii
List of Tables xi
List of Figures xiii
Abstract xv
CHAPTER 1: INTRODUCTION 1
1.1 Background of the Study 1
1.2 Problem Statement 3
1.3 Aim and Objectives of Study 4
1.4 Significance of the Study 5
1.5 Scope of the Study 5
1.6 Location of the Study 6
1.7 Limitation of the Study 7
CHAPTER 2: LITERATURE REVIEW 8
2.1 General overview of the Design Application 8
2.2 Geotextile 9
2.2.1 Structure and Types of Geotextile 9
2.2.2 Geotextile Properties 11
2.2.3 Geotextiles Mechanical Properties 11
2.2.4 Geotextile Hydraulic Properties 11
2.2.5 Geotextile Durability 12
2.2.6 Geotextile Functions 12
2.2.7 Geotextile as Soil-reinforcement 15
2.3 Pavement Application 15
2.4 Extreme Vertices Design Optimization 16
2.4.1 Optimization through Desirability Function 17
2.4.2 Graphical Plots with Trace Plot 19
CHAPTER 3: MATERIALS AND METHODS 21
3.1 Test Materials 21
3.2 Methods 22
3.3 Formulation of Geotextile Soil Specimen Mix Proportions 23
3.3.1 Mixture Component Constraints Formulations 24
3.3.2 Design of Simplex and Factor Space 24
3.3.3 Design of Experimental Mix Proportions 31
3.4 Experimental Procedures 32
3.4.1 Moisture Content Test 32
3.4.2 Specific Gravity Test 33
3.4.3 Atterberg Limit Test 34
3.4.4 Sieve Analysis Test 35
3.4.5 Compaction Test 36
3.4.6 California Bearing Ratio (CBR) Test 37
3.4.7 Unconfined Compressive Strength Test 38
CHAPTER 4: RESULTS AND DISCUSSION 40
4.1 Characterization of Test Materials 40
4.2 Natural Moisture Content of the Sample 41
4.3 Specific Gravity (G) Test 41
4.4 Sieve Analysis Test 42
4.5 Atterberg Limit Tests 43
4.6 Mechanical Strength Evaluation Test Results 45
4.6.1 Mix Ratio Mass Conversion 45
4.6.2 Compaction Test 46
4.6.3 California Bearing Ratio (CBR) Test 48
4.6.4 Unconfined Compressive Strength (UCS) Test 51
4.7 Model Development and Analysis 53
4.7.1 Fit Summary 54
4.7.2 Fit Summary for CBR Response 55
4.7.3 Fit Summary for UCS Response 56
4.7.4 Analysis of Variance (ANOVA) 57
4.7.5 Coefficient Estimates and Model Equations 61
4.7.6 Diagnostics Plots 64
4.7.7 Normal Probability Plot 64
4.7.8 Residuals vs. Predicted 66
4.7.9 Residuals vs. Run 67
4.7.10 Predicted vs. Actual 69
4.7.11 Box-Cox Plot for Power Transforms 70
4.7.12 Influence Plots 72
4.7.13 Cook’s Distance 72
4.7.14 Leverage vs Run 74
4.7.15 DFFITS vs Runs 75
4.7.16 Diagnostic Plots and Influence Statistics Summary Report 77
4.8 Optimization Overview 79
4.8.1 Numerical Optimization Bar Graph and Ramps 80
4.8.2 Optimization Trace Plot 82
4.8.3 Optimization Contour Plot 83
4.8.4 3D Surface Plots 85
4.9 Post Analysis 87
4.9.1 Point Prediction 87
4.9.2 Confirmation 87
4.9.3 Coefficient Table 88
4.10 EVD Model Simulation 89
4.10.1 Statistical Analysis of Model Simulated CBR Results 90
4.10.2 Statistical Analysis of Model Simulated UCS Results 91
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS 93
4.1 Conclusions 93
4.1.1 Contribution(s) to Knowledge 94
4.2 Recommendations 95
REFERENCES 96
APPENDICES 102
LIST OF TABLES
1.1 Road Ownership in Nigeria 2
3.1 Test Geogrid Properties 21
3.2 Design Constraints 24
3.3 Design Matrix Evaluation for Mixture Quadratic Model 3 Factors: A, B, C With U_Pseudo Mixture 25
3.4 Power at 5 % alpha level to detect signal/noise ratio 25
3.5 Measures derived from the information matrix 27
3.6 Design Summary 31
3.7 Component experimental mix proportions for soil treatment with geogrids 32
4.1 Basic properties of the test soil 40
4.2 Natural moisture content 41
4.3 Specific gravity result 42
4.4 Sieve Analysis Test Results 42
4.5 Result of liquid and plastic limits 44
4.6 Values of Liquid and Plastic limits with Plasticity Index 44
4.7 Plasticity Chart 44
4.8 Design Mix Ratio Mass Conversion 46
4.9 Optimum Moisture Content and Dry Density Results 47
4.10 Summary of Corrected Force results and average CBR values 51
4.11 UCS results summary 52
4.12a Model Summary Statistics for CBR response 55
4.12b Lack of Fit Tests for CBR response 55
4.12c Sequential Model Sum of Squares [Type I] for CBR response 56
4.13a Model Summary Statistics for UCS response 56
4.13b Lack of Fit Tests for UCS response 57
4.13c Sequential Model Sum of Squares [Type I] for UCS response 57
4.14a ANOVA Results for CBR response 58
4.14b R-squared Calculations for CBR response 59
4.15a ANOVA Results for UCS response 60
4.15b R-squared Calculations for UCS response 61
4.16a Model Coefficients Calculation Results for CBR response 62
4.16b Final Equation in Terms of U Pseudo Components 62
4.16c Final Equation in Terms of Real Components 62
4.16d Model Coefficients Calculation Results for UCS response 63
4.16e Final Equation in Terms of U_Pseudo Components 63
4.16f Final Equation in Terms of U_Pseudo Components 63
4.17a Summary Report for the Influence and Diagnostic Plots for CBR response 78
4.17b Summary Report for the Influence and Diagnostic Plots for UCS response 78
4.18a Optimization Criteria Definition 80
4.18b Optimization Solutions 80
4.19a Point Prediction 87
4.19b Confirmation Report 88
4.19c Coefficient Table for CBR Response 89
4.19d Coefficient Table for UCS Response 89
4.20 ANOVA Test Results 91
4.21 t-Test: Paired Two Sample for Means 91
4.22 T-Test: Paired Two Sample for Means 92
4.23 ANOVA Test Results 92
LIST OF FIGURES
1.1 Satellite pictorial view of the Location 6
2.1 Filtration function 13
2.2 Separation function of geotextiles 14
2.3 Geotextile as barrier 14
3.1 Geogrid Material 22
3.2 Program Flowchart 23
3.3 Factor space simplex of a 3- component mixture experiment of
Geogrids, water and soil. 28
3.4 Experimental factor space of the components in a 3- component
Mixture space 29
4.1 Particle Size Distribution Graph 43
4.2 Graph of moisture content against no of blows 45
4.3 Moisture Content vs. Dry Density Results 47
4.4 CBR Plots of Corrected Force vs. Penetration 50
4.5 CBR Plots of Corrected Force vs. Penetration 50
4.6 UCS Stress vs. strain Plot 53
4.7a Normal Plot of Residuals for CBR response 65
4.7b Normal Plot of Residuals for UCS response 65
4.8a Residuals vs. Predicted for CBR response 66
4.8b Residuals vs. Predicted for UCS response 67
4.9a Residuals vs. Run-CBR 68
4.9b Residuals vs. Run-UCS 68
4.10a Predicted vs. Actual for CBR response 69
4.10b Predicted vs. Actual for UCS response 70
4.11a Box-Cox Plot for Power Transforms-CBR 71
4.11b Box-Cox Plot for Power Transforms-UCS 71
4.12a Cook’s distance for CBR response 73
4.12b Cook’s distance for UCS response 73
4.13a Leverage vs. Run 74
4.13b Leverage vs. Run 75
4.13c DFFITS vs. Run-CBR 76 4.13d DFFITS vs. Run-UCS 77
4.14a Optimization Ramps 81
4.14b Desirability Bar Graph 81
4.14c Trace Cox Plot 83
4.14d Contour Plots for the Optimal Solution 85
4.14e 3D Plot for the Optimal Solution-CBR 86
4.15 Computed simulated EVD model results and the actual laboratory results 90
CHAPTER 1
INTRODUCTION
1.1 BACKGROUND OF THE STUDY
Pavement is an essential infrastructure in a nation or community of people as it has great effects on the economy of any nation. Pavement ought to be designed properly and constructed to achieve an effective and efficient performance and service life. After construction, they ought to be maintained to meet the objective of strength and durability. Afolayan and Abidoye (2017) emphasized that pavement are constructed to avail safe and efficient transportation using vehicles and as a result require proper design and construction approach. From the various transportation means existing as of now, road transport seems to be the most common. Likewise in other means of transportation such as air transport, quality pavement at the runway is as equally important as the lives of individuals for whom the runway is made. This shows that transportation infrastructures are critical elements that indirectly affect the overall growth of the nation. Oni and Okanlawon (2008) opined that transportation infrastructures are the major economic tools which enhances development.
The most striking features of our modern Nigeria economy and way of life are our dependence upon road transportation. Good road network provide for a smooth ride and they play an important role in every phase of our daily activities that it is impossible to imagine what life would be like without them. Movement of goods and services required for social and recreational purposes as well as many other functions necessary to the functioning of our complex society all depend on accessible roads quality or standard (Enwerem and Ali, 2016).
According to Ndefo (2012), Nigeria road are categorized into three main classes which are the Federal roads, the State road and the local-government road which is divided into the urban and rural road. Nigeria has about two-hundred thousand km of roads which spread throughout the country. The Nigerian road includes over thirty-two thousand kilometers of federal-roads spread across the 36-states and the federal capital, over thirty thousand kilometers of state roads and also over one-hundred and thirty thousand kilometers of local government roads as seen in Table 1.1.
Table 1.1: Road ownership in Nigeria
A pavement structure according to Adams et al., (2015); is defined generally as the structural-material placed above the layer of the sub-grade. In asphalt-concrete pavement which is typically a multi layered engineered system consisting of the subgrade, sub base, base-course and wearing course. Its principal function is to receive load from the traffic and transmit it through the layer to the subgrade. When the asphalt-pavement can no longer deliver this function during its design life, such pavement is then taken to be defective which would impact the economy of the state. However, routine maintenance approach is also a remedy option.
Most roads in major cities in Nigerian today are easily known with varying degrees of failure of all kind like depression, pot-holes, ruts, cracks etc. And there is not just one reason for each type of failure. A survey of some roads under study by various researchers has however showed that these roads suffer several degrees of failures. Our roads’ physical conditions stands out like a sore thumb and their national picture is simply scandalous. This makes it difficult because they lead to problems of traffic delays or congestion and accidents. Therefore, a good stabilization design is required to produce a material that will provide the required stiffness over the road design-life (Phil, 2016).
According to Adams et al., (2015), it was observed that the pavements failed due to the following reasons:
i. Pavement failure by poor soil characteristics
ii. Poor design and construction
iii. Poor laboratory tests on soil
iv. Soil’s Geotechnical characteristics
v. Poor supervision
vi. Use of sub-standard materials
Geotextiles materials have shown that they are amongst the versatile, robust and cheaper soil additive components. Their utilization has rapidly grown into nearly all areas of geotechnical and civil engineering materials development. Geotextiles are defined by ASTM (1994) as permeable textile materials which are incorporated with soil and rock as an integral part of civil-engineering structure, project or system.
The geotextile usually costs no more than 2 inches to 3 inches (50 mm to 75 mm) of compacted, in-place aggregate, but can save several inches (millimeters) of aggregate. The separate function is more dramatic over weak sub grade soils, but is economically practical in the long run to use even on more competent sub grade. (Sayali and Priyanka, 2017).
Geotextile as reinforcement reduces the pavement thickness thereby reducing the construction cost. However, the benefit significantly outweighs the cost of using separation geotextile to reinforce soil for pavement. Geotextile as inert separators between the subgrade and the base-course in the layered cross-section has improved the durability performance of the road. Studies have shown the positive impact of incorporating geotextile in terms of extended life of pavement sections. These studies have reduced both long term pavement rehabilitation and maintenance costs for road using geotextile (Arora, 2008).
Furthermore, to examine the viability, durability and the bearing-capacity of these geotextiles, there is need to carry out comparative studies on them, which gives this study its utmost significance.
1.2 PROBLEM STATEMENT
The pavement in Nigeria today are faced with several challenges, discomfort and distress such as potholes, ruts, depression, cracks etc. These according to Afolayan and Abidoye (2017) are caused due to several reasons ranging from the quality of geotechnical materials utilized for the construction to inappropriate designs. Pavements across Nigeria are designed and built over a broad variety of water sensitive sub-grade soils including loess, clay and silt. These condition of soil, in combination with moisture, result pavement deterioration with time.
Potholes, ruts, and uneven-pavements are not just safety concern but affect goods movement and services that depend on a reliable surface transportation system. All these accounts for why in recent time, most of the highways do not stand the test of time. The adverse effect of this occurrence usually results in road accidents which causes destruction to lives and properties (Guyer, 2009).
Most causes of pavement failure can be attributed to the weak nature of the subsurface formation which are in most cases not treated or properly investigated before the actual construction process. An attempt to close the above gap will depend largely on soil reinforcements for pavement using geotextile materials beneath the bituminous-surface, support-layer or an engineered aggregate-base and then the natural soil sub-grade. Geotextile prevent the mixing of the fine subgrade soils with the aggregate support-layer thereby preventing early roadways deterioration. This research intends to examine pavement parameters and geotextile reinforce soils’ suitability which enhances the properties of pavement constructed using extreme vertex mixture design.
1.3 AIM AND OBJECTIVES OF STUDY
The aim of this research work is to investigate samples of the geotextile reinforced soil to determine its California-Bearing-Ratio (CBR), to ascertain its suitability for flexible-pavement construction and to formulate an optimization model for its use in the metropolitan area of Calabar South.
The specific objectives of this research include to:
i. Determine through laboratory test analysis, geotextile-reinforcement effects on the California-bearing-ratio and compressive-strength of weak lateritic soil.
ii. Examine the percentage level of geotextile-reinforcement optimum for pavement performance.
iii. Examine if the geotextile reinforced soil can be used for pavement construction.
iv. Provide baseline data for further research work on geotextile utilization as an additive to improve mechanical-properties of durable pavement.
v. To optimize through modelling and simulation the California-bearing-ratio (CBR) and unconfined-compressive-strength (UCS) characteristics of the reinforced soil blend.
1.4 SIGNIFICANCE OF THE STUDY
The research-significance can be summarized as follow:
i. Improvement of soil properties by reducing their compressibility and increasing their strength.
ii. Reduction in general, pavement maintenance cost.
iii. Improving the country’s economy by the optimal utilization of geotextile in construction.
iv. Improving on the soil’s bearing-capacity and mechanical-strength.
v. The important, properties and geotextile uses will be highlighted to the general public
vi. Employment and commerce activity will be created by the useful application of these.
1.5 SCOPE OF THE STUDY
This research-study is directed towards geotextile application in reinforcing soil by improving its bearing capacity, mechanical strength and durability behavior. In this study, geotextile as a tensile material was used as reinforcement for a soil of low bearing capacity. Laboratory tests were performed to evaluate the geotextile reinforced soils’ load bearing characteristics. Extreme-vertex-design mixture optimization technique was adapted for this research study; the steps involved in the model development consist of the following; components constraints formulation, simplex and factor space design, mixture components proportions formulation. Details generated from this process which produced the ingredients, mixture were taken meticulously to derive the experimental responses in the Laboratory. The test soil preliminary investigation were first carried out to derive its general engineering behavior, California-bearing-ratio (CBR) test and unconfined-compressive-strength (UCS) test were then carried out on the soil-geogrid mixture. The responses were be utilized to model the mechanical strength behavior of the soil-geogrid blend. Statistical fit tests, diagnostics and influences, trace plot and analysis of variances were carried out to validate the regression model assumptions while numerical optimization were further incorporated through the use of desirability-function to derive the optimal-solution for the mixture combination.
1.6 LOCATION OF THE STUDY
The soil used for this research work was sampled by method of disturbed sampling from Calabar South Council Headquarters. Calabar South is located at (longitude 8°19'37.992"E, latitude 4°54'54.685"N. Fig. 1.1 shows the satellite pictorial view of the location used for the study.
Fig. 1.1: Satellite pictorial view of the Location
1.7 LIMITATION OF THE STUDY
The challenges encountered in the course of the study include;
i. The soil used for this investigation was from a borrow site in Calabar-south, Calabar, Cross-River State. The compositions of other soils with similar mechanical and physical characteristics across the country may give different results.
ii. Due to variability in the properties of geotextile materials, results obtained from other brand of geotextiles materials may be different.
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