Current asphalt binder specifications lack the ability to characterize asphalt binder damage resistance to fatigue loading. Multiple accelerated testing procedures that attempt to efficiently and ...accurately characterize the contribution of asphalt binders to mixture fatigue are under investigation. One of these tests, which has received significant acceptance by experts and has been submitted as a draft AASHTO standard, is the linear amplitude sweep (LAS) test. This procedure uses viscoelastic continuum damage mechanics to predict binder fatigue life as a function of strain in the pavement. The LAS test uses cyclic loading with systematically increasing load amplitudes to accelerate damage and provides sufficient data for analysis in less than 30 min. Although results of the current LAS testing protocol are promising, the time and the complex numerical procedures required for the analysis have raised concern. In addition, insufficient damage accumulation was observed when the strain amplitudes proposed in the LAS test were used for a set of polymer-modified binders. This paper presents simplifications of the current analysis procedures and evaluates the ability of extended strain levels to cause sufficient damage for better calculation of the binder fatigue law parameters. The effectiveness of the modified procedure was validated by comparison of the results with the fatigue performance recorded by the Long-Term Pavement Performance program with consideration of the pavement structure. The fair correlations showed the potential for effective use of the modified method for binder specifications.
The fatigue assessment of structural components is a significant topic investigated both in the academia and industry. Despite the significant progress in comprehension over the past few decades, ...fatigue damage remains a significant challenge, often leading to unexpected component failures. One commonly used approach for fatigue assessment is the critical plane analysis, which aids in identifying the critical location and early crack propagation direction in a component. However, the conventional method for calculating critical plane factors is computationally demanding and is typically utilized only when the critical regions of the component are already known. In situations where the critical areas are difficult to be identified due to complex geometry, loads, or constraints, a more efficient method is required for evaluating critical plane factors. This research paper introduces an analytical algorithm to efficiently evaluates the widely used Findley critical plane factor. The algorithm operates within the framework of linear-elastic material behavior and proportional loading conditions, relying on tensor invariants and coordinate transformation laws. The algorithm has been tested on different component geometries, including a box-welded joint and a tubular specimen, subjected to proportional loading conditions such as tension, torsion, and a combination of them. The analytical method allowed a significant reduction in computation time while providing the exact solution of critical plane factor and critical plane orientations.
•This study introduces a solution in closed form for the Findley critical plane factor.•The approach applies effectively to proportional loading and linear elasticity scenarios.•Its precision and efficiency were demonstrated in comparison to the standard procedure.•A remarkable reduction of over 99.8% in computation time was attained.
Corrosion identification and repair is a vital task in aircraft maintenance to ensure continued structural integrity. Regarding fuselage lap joints, typically, visual inspections are followed by ...non-destructive methodologies, which are time-consuming. The visual inspection of large areas suffers not only from subjectivity but also from the variable probability of corrosion detection, which is aggravated by the multiple layers used in fuselage construction. In this paper, we propose a methodology for automatic image-based corrosion detection of aircraft structures using deep neural networks. For machine learning, we use a dataset that consists of D-Sight Aircraft Inspection System (DAIS) images from different lap joints of Boeing and Airbus aircrafts. We also employ transfer learning to overcome the shortage of aircraft corrosion images. With precision of over 93%, we demonstrate that our approach detects corrosion with a precision comparable to that of trained operators, aiding to reduce the uncertainties related to operator fatigue or inadequate training. Our results indicate that our methodology can support specialists and engineers in corrosion monitoring in the aerospace industry, potentially contributing to the automation of condition-based maintenance protocols.
Vehicle collisions with bridge piers result in a complex set of actions and reactions between the structural system and the vehicle. The design of these piers is very important as it can have an ...adverse effect on both the economy and the health and safety of users. Current design provisions, although simple to apply, do not account for the many variables that influence demand and capacity. The goal of this study was to analyze the behavior of bridge piers under vehicle collisions with respect to vehicle mass, velocity, pier diameter, and transverse reinforcement. The commercial finite element software LS-DYNA was used to simulate and analyze the vehicle collisions. The finite element models were first validated with available experimental data, then verified with the available finite element models to ensure accuracy and reliability of the results. Conservation of energy was continuously checked throughout the analyses to assure stability within each impact simulation. The results of the study show that the pier diameter governed the overall failure mode of the pier while the transverse reinforcement governed the degree of local failure. The results could be useful to bridge design engineers in ensuring that performance measures are acceptable.
The object of this research is to demonstrate that the composite materials can replace the classic ones (for example steel) used to produce the structural mechanical components. The focus of this ...study is a double effect hydraulic cylinder installed on the excavator. Its design has been addressed using three different materials: the composite one made of carbon fiber, the classic structural steel and the aluminium alloy. The analytical sizing was verified through the FEM analysis. The next phase considers the fatigue phenomena due to pressure variation in time in the hydraulic cylinder. The results show that the hydraulic cylinder made of composite material has a very similar performance, in terms of the safety factor, to the one made of structural steel and that the weight reduction is about 87% passing from 2286 N to 314 N.
Abstract Infolge dynamischer Belastung von Stahlbetontragwerken (Windenergieanlagen) kann es auch bei Lasten unterhalb der statischen Festigkeit zu Materialermüdung im Betonstahl kommen. ...Materialseitig wird die dynamische Festigkeit im Dauerschwingversuch geprüft. Neben der Oberflächengeometrie, der chemischen Zusammensetzung hängt das Dauerschwingverhalten auch vom Belastungsregime ab. Im vorliegenden Beitrag wurden theoretische Berechnungen zur verrichteten physikalischen Arbeit während den Dauerschwingversuchen durchgeführt und in einer Parameterstudie für unterschiedliche Lastregime ausgewertet. Vergleichende experimentelle Untersuchungen zeigten, dass die Ergebnisse des Lastregimes mit fixierter Oberspannung zur Prüfung von Betonstahl nicht den theoretischen Berechnungen gleichen. Vor diesem Hintergrund ist zu diskutieren, inwieweit die Rahmenbedingungen des Dauerschwingversuchs die Absicht der Quantifizierung einer realitätsnahen Wöhlerlinie für Betonstahl tatsächlich erlauben.
Abstract Investigations of the test methodology in fatigue tests of reinforcing steel – Considerations on physical work Cyclic loading of reinforced concrete structures (e. g. wind energy plants) can cause fatigue fractures in reinforcing steel even with loads far below its yield strength. The dynamic tensile strength of rebars is determined in the fatigue tests of which the results strongly depend on the geometry and chemical composition of the reinforcing steel. Furthermore, the influence of the load regime has to be taken into account. In this paper, theoretical calculations of the physical work borne during the fatigue tests were carried out on three different load regimes within a parameter study. Comparative experimental investigations showed that the results of the load regime with fixed upper stress level (for testing reinforcing steel according to DIN EN ISO 15630‐1) could not be explained by theoretical calculations. The results seem to depend more on process factors and surface conditions of the rebars than on the tests boundary conditions. Hence, it should be discussed to what extent the boundary conditions of the fatigue test allow for an actual quantification of a S‐N‐curve for reinforcing steel.
The simplified viscoelastic continuum damage model (S-VECD) has been widely accepted as a computationally efficient and a rigorous mechanistic model to predict the fatigue resistance of asphalt ...concrete. It operates in a deterministic framework, but in actual practice, there are multiple sources of uncertainty such as specimen preparation errors and measurement errors which need to be probabilistically characterized. In this study, a Bayesian inference-based Markov Chain Monte Carlo method is used to quantify the uncertainty in the S-VECD model. The dynamic modulus and cyclic fatigue test data from 32 specimens are used for parameter estimation and predictive envelope calculation of the dynamic modulus, damage characterization and failure criterion model. These parameter distributions are then propagated to quantify the uncertainty in fatigue prediction. The predictive envelope for each model is further used to analyze the decrease in variance with the increase in the number of replicates. Finally, the proposed methodology is implemented to compare three asphalt concrete mixtures from standard testing. The major findings of this study are: (1) the parameters in the dynamic modulus and damage characterization model have relatively strong correlation which indicates the necessity of Bayesian techniques; (2) the uncertainty of the damage characteristic curve for a single specimen propagated from parameter uncertainties of the dynamic modulus model is negligible compared to the difference in the replicates; (3) four replicates of the cyclic fatigue test are recommended considering the balance between the uncertainty of fatigue prediction and the testing efficiency; and (4) more replicates are needed to confidently detect the difference between different mixtures if their fatigue performance is close.
Fatigue cracking is a critical distress in asphalt pavements. The linear amplitude sweep (LAS) test has recently been proposed for accelerated fatigue characterization of asphalt binders (AASHTO TP ...101). The fatigue resistance of asphalt pavements depends on temperature because of the inherent viscoelastic nature of the asphalt binder contained in the pavement. This study sought to develop recommendations for the selection of LAS test temperature based on climatic performance grades (PGs). Developing recommendations for selecting the test temperature involved two components: investigation of climatic data for a wide range of PGs and investigation of the effect of linear viscoelastic dynamic shear modulus on the observed failure mechanism in the LAS test. Results demonstrate that test temperatures should be selected such that linear dynamic shear moduli fall within the range of 12 to 60 MPa to avoid the confounding effects of flow or adhesion loss. On the basis of the aforementioned moduli range—coupled with the analysis of pavement temperature data corresponding to a range of PGs and geographic regions—it is recommended that the LAS test temperature be selected as the average climatic PG minus 4°C. In addition, temperature effects are incorporated into simplified viscoelastic continuum damage modeling of LAS test results to enable the prediction of fatigue performance under any temperature and loading history of interest using LAS test results at a single temperature coupled with linear viscoelastic time–temperature shift factors.
Aging affects the properties of asphalt mixtures in different ways; increase of stiffness, decrease of relaxation capability, and the increase of brittleness, resulting in changes in cracking ...behavior of asphalt mixtures. In this study, ten plant-produced, lab-compacted mixtures with various compositions (recycled materials, binder grades, binder source, and nominal maximum aggregate size) are evaluated at different long-term aging levels (24 hours at 135°C, 5 days at 95°C, and 12 days at 95°C on loose mix and 5 days at 85°C on compacted specimens). The asphalt mixture linear viscoelastic properties (|E*| and δ) and master curve shape parameters measured from complex modulus testing and fracture properties (measured from disc-shaped compact tension and semi-circular bending fracture testing) are compared at different levels of aging. The results indicate that the mixture exposure time to aging is proportional to the dynamic modulus and phase angle changes. Generally, the fracture parameters of mixtures become worse when aging level changes from 5 to 12 days aging. In spite of the similar viscoelastic properties, the mixtures with 24 hours at 135°C and 12 days at 95°C aging do not show similar fracture parameters.
Top-down cracking (TDC) is recognized as one of the major distress modes in asphalt pavements. This study aimed to determine the fracture parameter J-integral of TDC, which is a critical input to ...predict the crack growth rate and fatigue life of pavements for this type of distress. Previous research studies demonstrated that TDC is affected by various factors, including the complex state of high tensile or shear stresses induced by the loading at the edge of or within the tire and material properties such as the modulus gradient in the asphalt layer, moduli of the base and subgrade layers, and pavement structures. In this study, the finite element model (FEM) was adopted to simulate the propagation of TDC by considering combinations of these essential factors and to calculate the J-integral for 194,400 cases. It was shown that the modulus gradient plays an important role in determining the J-integral, and the J-integral is not uniformly distributed within the pavement depth. On the basis of the database generated from the FEM, six backpropagation artificial neural network (ANN) models—including one input layer, two hidden layers, and one output layer—were developed by using the same input variables and output variable as those for the FEM. The R2 value for each ANN model was greater than .99, which indicates the goodness of fit. After the parameters of each ANN model have been determined, the J-integral can be predicted for any combination of the design parameters without reconstruction of the FEM.
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