Dr. Khalid Ghuzlan graduated from University of Illinois at Urbana-Champaign in 2001. He worked as Research Scientist in California Department of Transportation (Caltrans) at the Division of Research and Innovation between years 2001 and 2008. Dr. Ghuzlan served as Associate Professor of Civil Engineering at Jordan University of Science and Technology since 2008. In 2018, he joined Ajman University, and founded the Civil Engineering Department. Research area of Dr. Ghuzlan is transportation engineering, pavement engineering, and materials behavior. He published many research papers in international Journals. Furthermore, he supervised many graduate students in their thesis work.
Every driver, irrespective of factors such as age, gender, driving experience and type of vehicle being used, faces a risk of being involved in traffic accidents. These accidents consist of incidents encompassing all types of vehicles such as cars, buses, motorcycles, bicycles, and trucks. and many times even pedestrians, resulting in about 1.35 million fatalities annually. Such accidents carry a noteworthy economic and social burden for the families of the victims. The accident severity factor plays a major role in incidents where deaths occur on the spot. Improvising the ability of predicting accident severity can benefit victims in getting a faster emergency response, thereby increasing their probability of surviving post impact. This paper analyzes the prediction methods of traffic accident severity using the Support Vector Machine (SVM) model using the classification learner application on MATLAB R2022b. Multiple factors were used in this analysis, namely age and gender of driver, types and numbers of vehicles involved in the accident, weather and street lighting conditions, day and time details. This model achieved an accuracy of 83.7%.
This study focuses on assessing the high-temperature performance of warm mix asphalt binder (WMB) modified with various quantities of date seeds oil (DSO). The penetration, softening point, rotating viscosity tests, and Dynamic Shear Rheometer (DSR) test at the high-temperature range were used for this assessment. The results showed that adding higher percentages of DSO to WMB is not advised; however, the results reveal an improvement in the performance at high temperatures compared to the control asphalt binder when (1.5% DSO) was used.
All vehicle drivers are prone to traffic accidents no matter their age, years of experience, type of vehicle driven, etc. It is estimated that 1.35 million people are killed yearly in crashes involving vehicles such as cars, buses, motorcycles, bicycles, trucks, etc. or even while being bare pedestrians. Such accidents often have a critical economic and social impact on the lives of the deceased's family. Whilst some may die at the instant moment of the accident and some may survive the impact to further meet death later, the severity of the accident itself plays a huge role in the prior. Hence, prediction of accident severity using various features such as time of day, weather conditions, ages of drivers, etc. may aid in the readiness of the dedicated emergency response and may further then increase the chances of surviving the after-impact. This paper discusses the prediction of traffic accident severity using Artificial Neural Networks (ANNs) whilst having a total of 10 input features such as the number of vehicles involved in the accident, day of the week, time of day, road surface condition, street lighting condition, weather condition, type of vehicles involved in the accident, type of causal vehicle, gender of causal driver and their age. The prediction model was implemented using the deep learning toolbox on MATLAB. The model was able to achieve an accuracy of 80% approximately.
Rutting is one of the most important distresses in asphalt concrete pavements. It is typically caused by consolidation or lateral movement of the materials (reorientation of aggregate particles) due to traffic loading in a hot climate. The ability to predict rutting depth in asphalt concrete pavements is an important aspect of pavement design. In this study, two different finite element models were created using ABAQUS software to predict the mechanical rutting behavior and performance of asphalt concrete pavements. In the first model, a linear elastic behavior was assumed for all layers in all pavement sections. In the second model, a viscoelastic behavior was assumed for the asphalt layer and a linear elastic behavior for all other layers. The finite element models (FEM) were calibrated and verified by comparing the proposed models’ predictions with the multilayered theory results, and the available field measurement of pavement response obtained from the Heavy Vehicle Simulator (HVS) at Richmond Field Station. A significant level of accuracy was found in the viscoelastic model compared to the available field measurement of pavement response obtained from the Heavy Vehicle Simulator (HVS) at Richmond Field Station while the linear elastic model represents an accurate simulation of the multilayer elastic theory.
Asphalt pavements are subjected to major distresses like fatigue, rutting, and low temperature cracking due to repeated traffic loading and climatic conditions. The modification of the asphalt binder (a major component of an asphalt paving mixture) using additives helps in minimizing the possibility of pavement distresses. The cement additive was used in this study at cement-to-asphalt (C/A) percentages of 0, 10, and 20% by volume. The main objective of the study was to investigate the impact of C/A percentage, temperature, and loading frequency on the rutting resistance of asphalt binders using statistical analysis. Two aging conditions were also used: unaged condition and short-term aging condition in the rolling thin-film oven (RTFO). The dynamic shear rheometer (DSR) test was used to characterize the asphalt binders at ten loading frequencies (0.1, 0.3, 0.6, 1, 1.59, 3, 5, 7, 8, and 10 Hz) and four temperatures (58, 64, 70, and 76°C). These combinations were used to cover a wide range of combined conditions and to follow the high-temperature range for the Superpave performance grade (PG) system. Multiple statistical analyses [the one-way analysis of variance (ANOVA) and correlation tests] were performed to identify the relation between the tested variables and the rutting parameter (G*/sinδ). Findings of the study have shown that the loading frequency has a significant effect on the rutting parameter for unaged and RTFO-aged asphalt binders under different temperatures and using different C/A percentages. Regression analysis was conducted to depict an accurate model that can predict the rutting parameter (G*/sinδ) for each aging condition. Based on the regression analysis, nonlinear power models were developed for the rutting parameter of four groups: unaged unmodified, unaged cement-modified, RTFO-aged unmodified, and RTFO-aged cementmodified asphalt binders with the coefficient of determination (R2) values of 0.986, 0.986, 0.996, and 0.992, respectively. The ANOVA test results showed that the cement addition (represented by the C/A percentage) had a significant impact on the rutting parameter of cement-modified asphalt binders for both aging groups. Furthermore, the correlation tests conducted in this study showed that the temperature and loading frequency had significant effects in the predictive models of the rutting parameter of unmodified asphalt binders and that the temperature, loading frequency, and C/A percentage had significant effects in the predictive models of the cement-modified asphalt binders.
Rutting, fatigue cracking and low temperature cracking are the most important distresses in asphalt pavements as a result of changes in rheological properties of asphalt binder. Many types of modifiers were used to enhance asphalt behavior at both low and high temperatures. In this study, carbon nanotubes (CNT) were used as one of many nanomaterials that take a large attention in the latest research related to asphalt modification against different types of distresses. Effect of CNT on rheological properties of asphalt binder was investigated by testing unmodified and CNT modified asphalt binders using two of Superpave devices: Dynamic Shear Rheometer (DSR) and Bending Beam Rheometer (BBR). Penetration, softening point, flash point and rotational viscosity (RV) tests were carried out as well. CNT was added in 0.1%, 0.5% and 1% by weight of asphalt binder. It was found that adding CNT in 0.5% and 1% increase stiffness of asphalt and consequently asphalt pavement rutting resistance. On the other hand, this increase in stiffness affected pavement behavior adversely which is not desirable for fatigue and low temperature cracking. However, Superpave specifications were still satisfied and asphalt binder’s relaxation properties were improved upon CNT modification. It was eventually found that 0.5% of CNT is the optimum percentage for the best performance.
Fatigue cracking is considered one of the major distresses that occur in asphalt pavements, which can decrease the expected service life of this type of pavements. This study aimed at investigating the effect of aging, strain level, modification, and temperature on the fatigue behavior of asphalt binders. To achieve the objectives of this study, a 60/70-penetration grade asphalt binder having a Superpave performance grade of PG 6416 and 4% Styrene-Butadiene-Styrene (SBS) modification were used in this study. Unmodified and modified asphalt binders were aged using the rolling thin-film oven (RTFO) test and pressure aging vessel (PAV). The PAV aging was conducted for four periods: 0, 20, 40, and 60 hr providing four PAV-aged asphalt binders named as: PAV0, PAV20, PAV40 and PAV60, respectively. Asphalt binders were tested using the dynamic shear rheometer (DSR) at a single loading frequency (10 Hz), four different temperatures (22, 25, 28 and 31C), and four strain levels (5, 10, 15, and 20%). Findings of the study showed that increasing the aging period generally decreased the fatigue life of unmodified asphalt binders particularly at lower temperatures (22 and 25C). However, at higher temperatures (28 and 31C), the fatigue life for 60-hr aging period was higher than that for 40-hr aging. The SBS modification increased the fatigue life of asphalt binders and showed opposite trend to that of the unmodified asphalt binders at low temperatures. The strain level increase decreased the fatigue life for both unmodified and SBS-modified asphalt binders. However, the fatigue life reduction was higher at low strain levels. The effect of temperature on the fatigue life agreed with literature; the increase in the temperature resulted in a decrease in the fatigue life of asphalt binders for all aging periods and strain levels.