ANN Models to Correlate Structural and Functional Conditions in AC Pavements at Network Level

Artificial Neural Network (ANN) model was developed to estimate the correlation between structural capacity and functional conditions in Asphalt Cement (AC) pavements at the network level. To achieve this objective, the relevant data were obtained and integrated from the Iowa Pavement Management Program (IPMP) including construction parameters, traffic loading and subgrade stiffness, and Iowa Environmental Mesonet (IEM) for climate data. The ANN model proves its ability to learn and generalize from the input data. Overall, rutting data were found to be appropriate indicator of the structural capacity. Since the deflection tests are expensive and require experience and knowledge to deal with such data, this approach might be feasible for small transportation agencies (cities and counties) that do not have these capabilities

Prediction of geogrid-reinforced flexible pavement performance using artificial neural network approach

This study aimed to develop a methodology to incorporate geogrid material into the Pavement ME Design software for predicting the geogrid-reinforced flexible pavement performance. A large database of pavement responses and corresponding material and structure properties were generated based on numerous runs of the developed geogrid-reinforced and unreinforced pavement models. The artificial neural network (ANN) models were developed from the generated database to predict the geogrid-reinforced pavement responses. The developed ANN models were sensitive to the change of base and subgrade moduli, and the variation of geogrid sheet stiffness and geogrid location. The ANN model-predicted geogrid-reinforced pavement responses were then used to determine the modified material properties due to geogrid reinforcement. The modified material properties were finally input into the Pavement ME Design software to predict geogrid-reinforced pavement performance. The ANN approach was rapid and efficient to predict geogrid-reinforced pavement performance, which was compatible with the Pavement ME Design software

Damage identification in bridge structures : review of available methods and case studies

Bridges are integral parts of the infrastructure and play a major role in civil engineering. Bridge health monitoring is necessary to extend the life of a bridge and retain safety. Periodic monitoring contributes significantly in keeping these structures operational and extends structural integrity. Different researchers have proposed different methods for identifying bridge damages based on different theories and laboratory tests. Several review papers have been published in the literature on the identification of damage and crack in bridge structures in the last few decades. In this paper, a review of literature on damage identification in bridge structures based on different methods and theories is carried out. The aim of this paper is to critically evaluate different methods that have been proposed to detect damages in different bridges. Different papers have been carefully reviewed, and the gaps, limitations, and superiority of the methods used are identified. Furthermore, in most of the reviews, future applications and several sustainable methods which are necessary for bridge monitoring are covered. This study significantly contributes to the literature by critically examining different methods, giving guidelines on the methods that identify the damages in bridge structures more accurately, and serving as a good reference for other researchers and future works

EVALUATION ON MECHANICAL FRACTURE OF PWR PRESSURE VESSEL AND MODELING BASED ON NEURAL NETWORK

ABSTRACT EVALUATION ON MECHANICAL FRACTURE OF PWR PRESSURE VESSEL AND MODELING BASED ON NEURAL NETWORK. The important component of the PWR is a pressure vessel. The material resistance in the pressure vessel needs to be evaluated. One way of evaluation is by the mechanical fracture analysis. The modeling needs to know the phenomena of the analysis result in general. A number of researches have been completed on the calculation of mechanical fracture in the pressure vessel with an internal load. The mechanical fracture was modeled using a neural network approach. In relation to the material resistance of the pressure vessel, which is used in PWR AP1000, the material must be evaluated because of the effect of the load. The modeling is needed to predict the effect of the load. The aim of this study is to evaluate the material resistance through mechanical fracture analysis because of the influence load on the pressure vessel on PWR AP1000. The material, which was observed, is SA 508. This analysis consists of the calculation of stress intensity factor and J-integral with some load at the crack propagation position. The fracture mechanic was analyzed by finite element simulation. The result of Stress Intensity factor and J-Integral was compared with fracture toughness to know the durability of the material. The modeling of  J-Integral and Stress Intensity Factor were obtained for some load based on neural network approach. Keywords: Material resistance, mechanical fracture, neural network, PWR, pressure vessel, crack propagation.   ABSTRAK EVALUASI FRAKTUR MEKANIK PADA BEJANA TEKAN PWR DAN PEMODELAN BERBASIS NEURAL NETWORK. Komponen penting dari PWR adalah  bejana tekan. Ketahanan bahan di bejana tekan perlu dievaluasi. Salah satu cara adalah dengan analisis fraktur mekanik. Pemodelan diperlukan untuk mengetahui fenomena hasil analisis pada umumnya. Terdapat penelitian untuk perhitungan fraktur mekanik dalam bejana tekan dengan beban internal. Penelitian lain adalah hasil dari fraktur mekanik dimodelkan menggunakan pendekatan jaringan syaraf. Sehubungan dengan ketahanan material dari bejana tekan yang digunakan dalam PWR AP1000, bahan harus dievaluasi karena efek dari beban. Pemodelan diperlukan untuk memprediksi pengaruh beban pada bahan dalam bejana tekan. Tujuan dari penelitian ini adalah untuk mengevaluasi ketahanan material melalui analisis fraktur mekanik karena pengaruh beban pada bejana tekan. Bahan yang diamati, adalah SA 508. Analisis ini terdiri dari perhitungan faktor intensitas tegangan dan J-integral dengan beberapa beban pada posisi perambatan retak. Fraktur mekanik dianalisis dengan metode elemen hingga. Hasil faktor intensitas tegangan dan J-Integral dibandingkan dengan ketangguhan patah untuk mengetahui daya tahan material. Pemodelan J-Integral dan faktor intensitas stres diperoleh untuk beberapa beban berdasarkan  jaringan saraf. Kata kunci: Ketahanan bahan, teknik patahan,  jaringan syaraf,  PWR,  bejana tekan, perambatan retak.

Recent Advances and Future Trends in Pavement Engineering

This Special Issue “Recent Advances and Future Trends in Pavement Engineering” was proposed and organized to present recent developments in the field of innovative pavement materials and engineering. The 12 articles and state-of-the-art reviews highlighted in this editorial are related to different aspects of pavement engineering, from recycled asphalt pavements to alkali-activated materials, from hot mix asphalt concrete to porous asphalt concrete, from interface bonding to modal analysis, and from destructive testing to non-destructive pavement monitoring by using fiber optics sensors. This Special Issue partly provides an overview of current innovative pavement engineering ideas that have the potential to be implemented in industry in the future, covering some recent developments

Eleventh International Conference on the Bearing Capacity of Roads, Railways and Airfields

Innovations in Road, Railway and Airfield Bearing Capacity – Volume 3 comprises the third part of contributions to the 11th International Conference on Bearing Capacity of Roads, Railways and Airfields (2022). In anticipation of the event, it unveils state-of-the-art information and research on the latest policies, traffic loading measurements, in-situ measurements and condition surveys, functional testing, deflection measurement evaluation, structural performance prediction for pavements and tracks, new construction and rehabilitation design systems, frost affected areas, drainage and environmental effects, reinforcement, traditional and recycled materials, full scale testing and on case histories of road, railways and airfields. This edited work is intended for a global audience of road, railway and airfield engineers, researchers and consultants, as well as building and maintenance companies looking to further upgrade their practices in the field

Stress Intensity Failure Rate Propagators Of Flexible Pavement

ThesisA responsive pavement management infrastructure is essential for providing durable pavement infrastructure. This need has been accentuated by the quest for sustainability through the adoption of Road Traffic Management System (RTMS) patterns as employed by the various Departments of Transportation (DOT) in South Africa. It can be summarised that increasing humidity/moisture content resulting in percentage increase in saturation content of the underlying base, subbase or subgrade layers will significantly result to a reduction of the Resilient Modulus (MR) of the entire pavement structure weather flexible or rigid. However, this scenario poses a great threat to the structural carrying capacity of the pavement structure. Therefore, it is imperative to provide a solution to such critical problems as they occur and when there is no control to avert them. This can, only be made possible by identifying the exact cause of the problem and providing a feasibly efficient and achievable solution. In the design of roads, flexible pavement has overtime experienced associated distress failure modes resulting in potholes, loss of skid resistance, and reduction in riding quality, noise and road surface ponding. Many of these have being tackled by research, both in the past and currently. The structural collapse of pavement is as a result of distress modes caused by human factors, construction error, excessive traffic loading, environmental factors, cumulative design and geometric errors results to unnecessary loss of strength and stability during the estimated design pavement service life. The objective of this current study is to develop stress intensity failure rate propagators induced by the factors of distress earlier mentioned in order to develop performance functions of asphaltic pavement model using the finite element method followed by a semantic stream-web data analysis (JAVA Expert System Shell analysis JESS). Multivariable transfer functions are generated in order to assess the different modes of failure for Mode I where the onset of crack begins to develop. Moisture sensors are embedded into the pavement in other to determine the real time failure modes populated under service loading and environmental conditions. Damage models are obtained to evaluate the evolution of crack growth and the strain energy release rate for failure mode I (crack initiation). The analysis of this study is further modelled in Abaqus CAE 6.13 as well as a proposed web-based computation analysis of pavement failure (JESS). The FE model indicates that at 20% moisture ingress, the vertical deformation of the subgrade is stable with a value 6.65 E-05. With further increase in moisture, the pavement stiffness reduces and the deformation increases with a failure rate value of 9.68 E-05. The difference indicates that there is a high percentage correlation between moisture content or saturation content increase in pavement and the resilient modulus of the pavement (Stiffness coefficient). Further subjecting the pavement to the same load or increasing load cycles will result in gradual delamination and further yield to total deformation. The results are as presented and discussed as the data obtained from the sensor probes are discretised for analysis in the workbench. A network level pavement management system to contribute to the development of a framework for evaluating pavements’ quality index (PQI) and service life capacity with varying environmental and climatic conditions is presented. The results indicate variation of stiffness with increasing moisture content. Increase in moisture propagation increased saturation of the unbound granular base which reduced the elastic modulus of the subbase layer and reduced the strength of the pavement leading to formation of bottom-up cracks and cracking failure. The horizontal tensile strain (E11) at the asphalt layer at 20% was 69.57x10-4, which increased to 140.8x10-4 at 60% moisture content. The horizontal deformation (E22) reduced, assuming that the material is experiencing work-hardening and no further stress can result to any significant damage. The damage remained at a constant value of 96.8 x 10-4 at 60% saturation. Consequently, the performance of the pavement is affected by temperature gradient. This implies that increasing temperature gradient results in reduction in stiffness of the asphalt layer. In tropical regions, this can result to immediate rutting failure of the asphalt layer, which overtime leads to formation of top-down cracks and potholes with increasing moisture content, even if it is a newly constructed road less than two years old. The web data architecture analysis provides deflection values for failure occurring within the pavement underlying layers. The findings indicate that there is a high correlation between Environmental Condition and road pavement (Asphalt Concrete). The result indicates that increasing temperature gradient of the pavement reduces the fracture energy of the pavement, which results in delamination and collapse over a longer period of time. On the contrary, reduced temperature gradient increases the fracture Energy, making the pavement stiffness high and resistant to failure, but at very low temperatures a compromise is reached and the strength is breached resulting in a brittle material (glass). Although the failure is not visible at the onset of crack propagation, but continual exposure to increasing temperatures as well as increasing moisture content will lead to failure of the pavement before the design life is reached. There is also a surge in the relationship between Pavement Fracture Energy and the Pavement Resilient Modulus. Further, it is found that, the higher the temperature, the higher the rate of deflection and the lower the temperature, the lower the deflection