Marshall Mix design was developed for the hottest pavement surface temperature of the USA, which is 60-degree Celsius. This design mechanism is very dominant in our country. It was directly adopted without any modification. The research aims to develop a prediction model that will be employed to modify the Marshall Mix design method for the Ethiopian climate and incorporate maximum pavement surface temperature.
In order to do so, ten years historical air temperature of Ethiopia, taken from the National Metrology Agency which was used to determine the hottest month for onsite measurement of 24 towns. For each town, actual maximum pavement surface temperature was measured from August 2016- February 2018, using Nanosensor/ radiator thermometer. The countries climate was classified into four climatic regions for the purpose of this research. For each region, a representative town is incorporated on the study.
Based on site measurement and maximum air temperature with the associated latitude, Multivariate Regression Model was selected. To select the model R-squared value method, an excel analysis of scatter plots and collinearity of the explanatory variables was checked. All the inputs were provided to STATA SE-13 statistical software and model developed. After the model was developed by all the 24 towns' data, it was validated and cross-validated by dividing the data into 5 folds in order to make it applicable for all scenarios. The model was further elaborated in a laboratory case study, for the hottest town of Samara, Afar region capital. Mix design was prepared at 60°C, which is the standard specimen heating temperature and at 75°C, which is the actual maximum pavement surface
temperature of Samara town. The mix that was prepared at 60° C, found to fulfill all the criteria's of Marshall Mix design outlined by Asphalt Institute for heavy Traffics. Whereas, at 75°C, it fails to do so. Therefore, mix design should be conducted at the place maximum pavement surface Temperature rather than conducting at the standard 60degree Celsius.
Table of Contents
1. INTRODUCTION
1.1 Statement of the problem
1.2 Objective
1.2.1 General Objective
1.2.2 Specific Objectives
1.3 Significance of the study
1.4 Research questions
1.5 Scope of the study
1.6 Research Design
2. LITERATURE REVIEW
2.1 Previously Developed Temperature Prediction Algorithms & Models
2.2 Effect of Environmental Factors on Flexible Pavement Performance
2.3 Relationship between Maximum Air Temperature & Pavement Surface Temperature
2.4 Marshall Mix Design
2.4.1 Procedures
2.4.2 Preparation of test specimens
2.4.3 Density & Void analysis
2.5 Statistical Modeling
2.5.1 Regression analysis
2.5.1.1 Multivariate regression
2.5.1.2 Testing the Significance of R
2.5.1.3 Adjusted R²
2.5.1.4 Cross validation
3. RESEARCH METHODOLOGY
3.1 Study Area and Study Period
3.2 Historical Air Temperature and Latitude of the Study Areas
3.2.1 Berha/ Desert places of Ethiopia
3.2.2 Kola (tropical) places of Ethiopia
3.2.3 Sub-tropical (Weina-dega) places of Ethiopia
3.2.4 Temperate & alpine (Dega& Kur) Places of Ethiopia
3.3 Research Materials
3.4 Data Collection and Sampling Techniques
3.4.1 Determining Normality
3.4.1.1 Pearson`s Index of Skewness
3.4.1.2 Frequency distribution
3.4.2 Sample Size Determination
3.5 Model Development
3.5.1 Model Selection
3.5.2 Collinearity
3.5.3 Model Development
3.5.4 Model Validation
3.5.5 Cross validation
3.6 Laboratory Experiment (case study for Samara town)
3.6.1 Marshall Mixture Design Procedures
3.6.1.1 Aggregate Evaluation
3.6.1.2 Asphalt Cement Evaluation
3.6.1.3 Preparation of Marshall Specimens
3.6.1.4 Marshall Stability & flow test
4. Result Analysis and Discussion
4.1 Result Analysis
4.1.1 Analysis to develop the Model
4.1.1.1 Normality test and Confidence interval determination
4.1.1.2 Model selection
4.1.2 Analyzing Laboratory Test Results
4.1.2.1 Aggregate Evaluation Results
4.1.2.2 Asphalt cement evaluation results
4.1.2.3 Marshall Specimen heating at 75°C
4.2 Result Discussion
4.2.1 Result discussion related to the model
4.2.2 Implication of laboratory Test results
4.2.2.1 Implication of Aggregate test results
4.2.2.3 Comparison between the two Marshall Specimen heating temperatures (60°C and 75°C)
4.2.3 Options to determine maximum pavement surface temperature
5. Conclusion and Recommendation
5.1 Conclusion
5.2 Recommendation
Research Goals and Themes
The main objective of this study is to develop a predictive model that estimates maximum pavement surface temperature in Ethiopia by utilizing historical maximum air temperature and latitude data. This model aims to improve the standard Marshall Mix design process, which is currently limited by testing at a fixed temperature of 60°C, a value that does not always align with the actual thermal conditions of the Ethiopian climate.
- Development of a multivariate regression model for pavement surface temperature prediction.
- Calibration of the Marshall Mix design method based on local climatic variations.
- Comparative analysis of Marshall test results at standard (60°C) versus actual maximum pavement temperatures.
- Geographic classification of Ethiopia into four distinct climatic zones for pavement design.
- Validation of the predictive model through laboratory case studies and cross-validation techniques.
Extract from the book
1. INTRODUCTION
Temperature variations have an important influence on the pavement thermal state. Depending on the temperature variation, stresses are induced in the overlay in two different ways, which need to be distinguished: through restrained shrinkage of the overlay and through the existing movements of slabs, due to the thermal shrinking phenomenon.
The time variation of pavement thermal state is controlled by climatic conditions, thermal diffusivity of the materials, thermal conductivity, specific heat, density and the depth below the surface (Sousa et al., 2002).
The temperature distribution in a pavement structure can be obtained through field measurements, using temperature-recording equipment (Data logger associated with thermocouples) or estimated by using mathematical models. The option of using the field measurement is desirable because actual temperature can be reliably measured and used in stress calculation models. However, this method is relatively slow and only provides information about temperatures in the observed period. On the other hand, a temperature theoretical model will give a temperature distribution quickly and can be used to predict temperature distributions under a wide range of conditions, including any unusual or extreme conditions.
The angular distance on a plane perpendicular to the plane of the equator is known as the latitude. This is used as one of the two coordinates for a location on earth. In the physical sense, it gives the north-south position of the location considered. The line at which the latitude is constant runs parallel to the equator around the globe.
Taken together with longitude, latitude can be used to specifically locate a position on earth. The equator is considered as the zero latitude (i.e. 0°). The North Pole has the latitude +90° and the South Pole has -90°. There are specially defined latitudes, such as Arctic circle and Tropic of Cancer in the northern hemisphere and Antarctic circle and Tropic of Capricorn in the southern hemisphere.
Summary of Chapters
1. INTRODUCTION: Outlines the significance of pavement temperature variations, the limitations of current measurement methods, and establishes the research objective to create a predictive model for Ethiopia.
2. LITERATURE REVIEW: Examines existing temperature prediction algorithms, the impact of environmental factors on pavement performance, and theoretical foundations of Marshall Mix design and statistical modeling.
3. RESEARCH METHODOLOGY: Details the study area, data collection from 24 Ethiopian towns, material properties, sampling techniques, and the development and validation of the regression model and laboratory experimental procedure.
4. Result Analysis and Discussion: Presents the statistical model development, laboratory findings for aggregate and bitumen, and a critical comparison of mix design performance at 60°C and 75°C.
5. Conclusion and Recommendation: Summarizes key research findings, confirms the significance of the developed model, and provides recommendations for future research and improved mix design practices in Ethiopia.
Keywords
Pavement Surface Temperature, Marshall Mix Design, Maximum Air Temperature, Latitude, Multivariate Regression Model, Climatic Zones, Asphalt Concrete, Ethiopia, Temperature Prediction, Laboratory Testing, Statistical Modeling, Cross Validation, Pavement Performance, Bitumen, Aggregate
Frequently Asked Questions
What is the primary focus of this research?
The research focuses on predicting maximum pavement surface temperatures in Ethiopia by correlating them with maximum air temperature and geographic latitude to enhance pavement design accuracy.
What are the central themes of the work?
The study centers on the interaction between climate and asphalt pavement performance, the limitations of standard 60°C testing, and the development of a predictive mathematical model for local conditions.
What is the core research objective?
The primary goal is to develop a predictive model that relates maximum pavement surface temperature to air temperature and latitude to better tailor asphalt mix designs for Ethiopian climates.
Which scientific methodology is utilized?
The research employs a multivariate regression model developed using STATA-SE/13 software, supported by field measurements and laboratory Marshall Mix experiments.
What topics are covered in the main body?
The main body covers literature on temperature prediction, the research methodology including data collection from 24 towns, statistical model construction, and extensive laboratory testing of aggregate and bitumen mixtures.
Which keywords characterize this thesis?
Key terms include Pavement Surface Temperature, Marshall Mix Design, Multivariate Regression, Climate Classification, and Asphalt Concrete Performance.
Why is the 60°C standard considered a limitation in this study?
The standard 60°C testing temperature is a legacy parameter that often fails to represent the actual, higher maximum pavement surface temperatures experienced in various tropical and desert regions of Ethiopia.
How does this study validate its findings?
The model is validated using a five-fold cross-validation technique to ensure it is applicable across different scenarios, and supplemented by laboratory case studies comparing 60°C and 75°C heating protocols.
- Arbeit zitieren
- Debela Daba (Autor:in), 2019, Prediction of Maximum Pavement Surface Temperature Using Maximum Air Temperature and Latitude, München, GRIN Verlag, https://www.grin.com/document/489870
