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The importance of a backcalculation method in the analysis of elastic modulus in pavement engineering has been known for decades. Despite many backcalculation programs employing different backcalculation procedures and algorithms, accurate inverse of the pavement layer moduli is still very challenging. In this work, a detailed study on the backcalculation of pavement layer elastic modulus and thickness using genetic algorithm is presented. Falling weight deflectometer (FWD) data is generated by applying a load to the pavement and measuring pavement deflection at various fixed distances from the load center. The measurement errors in FWD data are simulated by perturbing the theoretical deflections. Based on these data, backcalculation technique is performed using an improved genetic algorithm (GA). Besides root mean square (RMS), another objective function called area value with correction factor (AVCF) is proposed for accurate backcalculation of pavement modulus and thickness. The proposed backcalculation method utilizes the efficient and accurate program MultiSmart3D for the forward calculation and it can backcalculate the modulus and thickness simultaneously for any number of pavement layers. A simple, user-friendly, and comprehensive program called BackGenetic3D is developed using this new backcalculation method which can be utilized for any layered structures in science and engineering.
"The static elastic moduli of pavement layers can be considered to be among the most controversial physical properties in pavement engineering. In addition, pavement analysis using the static elastic moduli of the constituting layers is widely known and accepted by engineers and practitioners due to its simplicity. Nondestructive tests are commonly performed on existing pavements to measure the surface deflections, which in turn are used to backcalculate the elastic moduli of the pavement layers. However, the accuracy of the backcalculated moduli is dependent on the backcalculation procedure and the associated seed moduli. None of the existing classical backcalculation methods can find the 'actual' pavement moduli due to the theoretical limitations of the existing methods. These limitations include the convergence to local optima due to the use of seed moduli, which in turn lead to erroneous pavement moduli. The genetic algorithms can be used to optimize the search domain of the backcalculated moduli to avoid the premature convergence to local optima. The use of genetic algorithms in pavement engineering is new and no guidelines or thorough investigations have been carried out to address all the aspects and challenges associated with the backcalculation procedure using the genetic algorithms. This study can be considered as the first comprehensive work that deals with all aspects of both pavement and genetic algorithms and how to merge them. In addition, this work can be considered as the first state of the art work on the backcalculation of pavement moduli using genetic algorithms. In this study, the use of genetic algorithms has been studied thoroughly to address all the important parameters and operators that affect the backcalculation process. In addition, recommendations and findings regarding all the details needed to carry out the backcalculation process were identified and discussed thoroughly. New novel methods to study the interaction between the genetic operators and parameters and their effect on the backcalculation process were developed. Recommendations regarding the genetic operators as well as the genetic parameters were presented throughout the work. In addition, the AASHTO recommended ranges of pavement moduli were modified based on the study results to suit the GAs backcalculation process. On the other hand, a new novel method was developed to automate the backcalculation process. The automation of the backcalculation process was aimed at reducing the number of inputs needed to carry out the backcalculation process and to make it more appealing to be used in practice. A new Dynamic Parameterless Genetic Algorithm (DPGA) was developed as part of this work. The new DPGA can be extended to many other applications of genetic algorithms including robotics and optimizations. A new program (BackGenetic3d) was developed based on the novel MultiSmart3D program developed by the Computation and Simulation Group at the University of Akron. The new program is the first in the world that can backcalculate the pavement moduli of pavement systems with any arbitrary number of layers, loading conditions, and loading configurations. Existing classical programs use backcalculation procedures that lead to local optima and limited to a maximum of 5 pavement layers and one loading circle with uniform pressure."--Abstract.
The analysis of pavement responses is important for better understanding of pavement performance and accurate estimation of pavement service life. This dissertation aims to study flexible pavement responses using forward and inverse analysis. The first objective is development of axisymmetric finite element (FE) models that can simulate FWD loading on the pavement system. After that, the backcalculation of pavement layer moduli from FWD testing was studied by means of soft computing techniques such as Artificial Neural Networks (ANNs) and Genetic Algorithms (GA). The axisymmetric FE models were used to generate a synthetic database. The ANN-GA backcalculating program is developed to assess existing pavement condition after the training and verification using the synthetic database. The second objective of this dissertation is to investigate airfield flexible pavement responses under aircraft loading in consideration of the realistic aircraft tire-pavement interaction. An advanced three-dimensional (3-D) finite element (FE) model was developed to simulate heavy aircraft loading with high tire pressure. The aircraft loading was simulated as moving wheels having non-uniform contact stress distributions. Different tire rolling conditions caused by aircraft ground maneuvering were simulated, including free rolling, full-braking, and turning. The multi-wheel aircraft loading was modeled in two-wheel, four-wheel and six-wheel assembly. The analysis concludes that FWD deflections were affected by dynamic analysis, temperature gradient, bedrock depth, asphalt layer delamination, viscoelasticity, and unbound material nonlinearity. After validated with the field measurements in the long-term pavement performance program (LTPP) database, the developed ANN-GA program can be used to obtain damaged dynamic moduli of asphalt concrete and evaluate in-situ pavement conditions from structural point of view, which facilitates pavement overlay design procedure using Mechanistic-Empirical Pavement Design Guideline (MEPDG). The investigation on airfield flexible pavement emphasized the importance of considering non-uniform tire contact stresses and temperature profiles in airfield pavement analysis. For the aircraft ground maneuvering, aircraft braking or turning significantly increases shear failure potential in asphalt layer. The analysis of stress states would facilitate evaluation of the shear failure potential at airfield asphalt pavements. Finally, the investigation on multi-wheel aircraft loading indicates that the six-wheel gear configuration would cause more fatigue cracking and near-surface cracking potential than dual-wheel and four-wheel gears.
Bituminous Mixtures and Pavements contains 113 accepted papers from the 6th International ConferenceBituminous Mixtures and Pavements (6th ICONFBMP, Thessaloniki, Greece, 10-12 June 2015). The 6th ICONFBMP is organized every four years by the Highway Engineering Laboratory of the Aristotle University of Thessaloniki, Greece, in conjunction with
The book presents a compilation of studies regarding applied geomechanics, mining, and excavation analysis and simulation. The material is suitable for presentation to senior undergraduate and post-graduate students in both mining and geological engineering. It should also be of interest to students of other aspects of Geomechanics and, notably, engineering geologists interested in mining and underground excavation design. Practising mining engineers and rock mechanics engineers involved in mine design may use the book profitably to obtain an appreciation of the current state of engineering knowledge in their area of specialisation. Papers were selected from the 5th GeoChina International Conference on Civil Infrastructures Confronting Severe Weathers and Climate Changes: From Failure to Sustainability, held in July 23-25, 2018 in Hang Zhou, China.