Crack Length Prediction Research Articles

Comparative analysis of unloading compliance and normalization methods for fracture toughness assessment in 316L stainless steel at cryogenic temperatures

In the present study, the impact of test temperature, specimen geometry, and evaluation methodologies on the fracture toughness of 316L stainless steel was evaluated. Tensile and fracture mechanics tests were conducted utilizing a cryostat across a range of temperatures from ambient conditions to liquid hydrogen environments. The analysis of crack length prediction and resistance curve was performed using two fracture toughness evaluation methods: the unloading compliance method and the normalization method. The difference in fracture toughness by specimen thickness using the normalization method was within acceptable tolerances for all temperatures. However, fracture toughness evaluation using the unloading compliance method showed apparent negative crack growth at all temperatures, causing differences in J-integrals between specimen thicknesses and discrepancies between physical and estimated crack extensions. The application of the offset technique to the unloading compliance method significantly reduced these differences and made the J-integral of the normalization method and the unloading compliance method agree well. The substantial underestimation in the correction of the rotation angle at ambient temperatures was confirmed through real-time imaging of the crack tip with the unloading compliance method, which contributed to the large deviations between estimated and measured crack extensions.

A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF

A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF

Surface roughness and surface crack length prediction using supervised machine learning–based approach of electrical discharge machining of deep cryogenically treated NiTi, NiCu, and BeCu alloys

Surface roughness and surface crack length prediction using supervised machine learning–based approach of electrical discharge machining of deep cryogenically treated NiTi, NiCu, and BeCu alloys

Fatigue Crack Length Estimation and Prediction using Trans-fitting with Support Vector Regression

A method is described in this paper for crack propagation prediction using only the initial crack length of the target specimen. The proposed method consists of two parts, (1) crack length estimation using support vector regression (SVR) and (2) crack length prediction using a new trans-fitting method. Features based on the filtered wave signals were defined and a model was constructed using the SVR method to estimate the crack length. The hyper-parameters of the SVR model were selected based on a grid search algorithm. Prediction of the crack length was based on the previous crack length, which was estimated based on the wave signals. In this step, a newly proposed trans-fitting method was applied. The proposed trans-fitting method updated the selected candidate function to translocate the trend of crack propagation based on the training dataset. By translocating the trends to the estimated crack length of the target specimen, the crack propagation could be predicted. The proposed method was validated by comparison with given specimens. The results show that the proposed method can estimate and predict the crack length accurately.

Compliance Methods For Bonded Joints: Part II - Investigation Of The Equivalent Crack Methodology To Obtain The Strain Energy Release Rate For Mode I

ABSTRACT The present work investigates the equivalent crack methodology by considering the Double Cantilever Beam (DCB) test to obtain the strain energy release rate of adhesive joints, using different compliance methods rather than the Compliance Based Beam Model (CBBM). This procedure allows the determination of the crack length based on the compliance of the specimen, which avoids crack growth monitoring during tests. The compliance values predicted by the analytical methods were studied and compared with a computational model, considering different crack lengths. Results showed that the preciseness of the crack length obtained by the equivalent crack method relies on the accuracy of the respective compliance method in predicting the load-displacement curve of a bonded double cantilever beam. The Euler–Bernoulli and Timoshenko beam models are not recommended to obtain an equivalent crack length based on the specimen’s compliance since they overestimate the actual crack length. Best crack length predictions were obtained using compliance methods based on the beam-on-elastic foundation models, including an elastic interface to model the adhesive layer joint. Similar strain energy release rate results were found for different compliance methods when using the equivalent crack methodology.

Star Crack Formation via Low-Velocity Impact on Glass Windows

The resistance to crack formation induced by gravel impacts on laminated glass windshields is a crucial issue for windshield manufacturers. It is proposed to study the star crack formation on polyvinyl butyral (PVB) laminated glass by designing a new highly-instrumented device that can break the glass under dynamic loading. The set-up is composed of a spring-loaded projectile that mimics a gravel momentum and an input bar equipped with strain gauges, whose end is an indenter initially in contact with the laminated glass sample. A synchronized high-speed camera allows for the observation of the crack growth. A unidimensional model introduces the local non-linear behavior of the indented zone. Crack monitoring synchronized with the Force and Velocity measurements are presented. Live-indentation depth measurements are performed. Experimental results are used in a dynamic simulation to analyze the non-linear damage behavior under the indenter tip. Dynamic and well-instrumented indentation experiments on the laminated glass are performed to investigate the star-shaped crack formation and describe the indented zone. This work is a prelude to the crack length prediction on windshields submitted to gravel pitting.

Evaluation of prediction models for crack length of duplex 2205 stainless steel based on acoustic emission technology

Fatigue fracture is a common failure mode of steel structure, and it usually leads to steel structure failure. In this study, the fatigue damage of duplex 2205 stainless steel with different stress ratios was monitored based on acoustic emission (AE) technology. The fatigue crack growth length, stress intensity factor, fatigue crack growth rate, and the various characteristics of the count, amplitude, and average signal level (ASL) of AE parameters during the whole process were recorded. The results show that AE parameters count and amplitude can well characterize the three stages of fatigue crack initiation, steady-state growth and failure fracture. In the steady-state growth stage, the crack length prediction models based on single-factor and multi-factor of AE parameters suitable for different stress ratios were established and compared for the first time. The multi-factor model has the highest prediction accuracy and it can provide an effective basis for monitoring methods.

Deviation-based calibration for progressive damage analysis in pultruded glass fiber reinforced composites

This paper presents a systemic calibration methodology to efficiently simulate progressive damage evolution in four different pultruded glass fiber reinforced polymer (GFRP) composites using the strain-based COMposite DAMage Model (CODAM2) in the commercial finite element software LS-DYNA. In particular, Compact Tension (CT), scaled-up CT, and wide CT tests are simulated to find the best set of input parameters by considering four distinct indicators obtained from experimental and numerical load vs displacement data. By combining these indicators into a physically meaningful equivalent deviation value via a linear weighted-sum method, the results show that the most suited input damage variables yield physically accurate crack length predictions which underlines the robustness and accuracy of the proposed method. Furthermore, it is shown that the incorporation of bi-linear softening laws improves CODAM2 simulation results by up to 90%, however it also increases the number of parameters to be calibrated.

A hybrid PSO and Grey Wolf Optimization algorithm for static and dynamic crack identification

This paper introduces an inverse problem for crack identification in two-dimensional structures using eXtend Finite Element Method (XFEM) associated with original Grey Wolf Optimization (GWO) and improved GWO using Particle Swarm Optimization (PSO) (IGWO). Static analysis with different boundary conditions and experimental modal analysis of cracked plates with varying crack length, positions, and orientation are used to test the accuracy of IGWO compared with the original GWO. The objective function is based on vertical measured strain and is computed at each iteration. The obtained results indicate that IGWO provides more accurate results than GWO based on convergence study and the error between exact and estimated results. Next, another application based on dynamic experimental cracked plates is used to improve Artificial Neural Network (ANN) parameters using GWO and IGWO. The frequencies and crack lengths are used as input and output for vertical and horizontal cracks in the plates. Thus, the model can be used for the prediction of crack length. IGWO can select the best parameters for better prediction compared with GWO.

Evaluation of time series forecasting approaches for the reliable crack length prediction of riveted aluminium plates given insufficient data

In all fields, the significance of a reliable and accurate predictive model is almost unquantifiable. With deep domain knowledge, models derived from first principles typically outperforms other models in terms of reliability and accuracy. When it may become a cumbersome or an unachievable task to build or validate such models of complex (non-linear) systems, machine learning techniques are employed to build predictive models. However, the accuracy of such techniques is not only dependent on the hyper-parameters of the chosen algorithm, but also on the amount and quality of data. This paper investigates the application of classical time series forecasting approaches for the reliable prognostics of technical systems, where black box machine learning techniques might not successfully be employed given insufficient amount of data and where first principles models are infeasible due to lack of domain specific data. Forecasting by analogy, forecasting by analytical function fitting, an exponential smoothing forecasting method and the long short-term memory (LSTM) are evaluated and compared against the ground truth data. As a case study, the methods are applied to predict future crack lengths of riveted aluminium plates under cyclic loading. The performance of the predictive models is evaluated based on error metrics leading to a proposal of when to apply which forecasting approach.

Digital twin for the structural health management of reusable spacecraft: A case study

Reusable spacecraft can significantly reduce the cost of space travel, while evaluation of the structural health of the craft between flights becomes one of the key issues. A digital twin framework is proposed in this paper to track the life of spacecraft structures. A digital twin is a digital representation of an engineering system. It can simulate, monitor, diagnose, predict states and optimize operations of the real engineering system in real time. The proposed framework can be divided into offline and online stages. It has the functions of diagnosis, model updating, performance evaluation and data storage. To demonstrate the prognosis and decision support capabilities of the framework, a numerical example considering fatigue crack growth in a load-bearing frame is carried out. The method of manufactured solutions is employed for validation. Information entropy and relative entropy are used for measuring the uncertainties in crack length prediction. The results show that through the framework, crack growth model can be updated to have a lower uncertainty. Future crack growth and reusable life can be predicted more accurately using the improved model. With the structural life of the spacecraft quantified by the framework, mission success rates for repeated flights can be maximized at a lower cost.

Mode I interlaminar crack length prediction by the resistance signal of the integrated MWCNT sensor in WGF/epoxy composites during DCB test

The interlaminar peformance of composites palys an important role in the damage process of fiber reinforced composites. In-situ monitoring by an embedded sensor could avoid the sudden failure. This paper investigates the in-situ monitoring of mode I interlaminar crack propagationg behavior in woven glass fiber reinforced epoxy (WGF/epoxy) composite laminates. The resistance signal of multi-walled carbon nanotube (MWCNT) located in the mid-thickness of WGF/epoxy during the double cantilever beam (DCB) test is recorded. Relationship between the relative resistance and the interlaminar crack length is theoretically built and experimentally verified. Results show that the mode I crack propagating length can be successfully predicted by the relative resistance. A linear relationship between the interlaminar crack propagating length and the total relative resistance is found by the experimental and theoretical results.

LCD 패널의 응력 해석을 통한 단순화 칩핑 허용균열 길이 예측

LCD 패널 제작과정에서 다양한 칩핑이 발생한다. 이는 초기 균열의 형태로 패널의 내구성에 영향을 미칠 수 있다. 본 연구에서는 칩핑이 LCD 패널의 내구성에 미치는 영향을 확인하고 칩핑 제거를 위해 수행되는 연마가공의 효과를 확인하였다. 이를 위해 외부 하중에 대한 9인치와 4인치 LCD 패널의 응력 변화를 연마 가공된 LCD 패널과 가공되지 않은 패널에서 비교하였다. 결과적으로 LCD 패널에 발생한 칩핑은 국부 응력집중 현상으로 인해 내구성이 약화되는 것을 확인하였다. 칩핑 제거를 위한 연마작업은 손상이 없는 패널과 같이 응력집중 현상이 완화되는 것을 확인하였다.

Establishment of a new hybrid fracture criterion for cross wedge rolling

This paper relates to the problem of fracture in cross wedge rolling (CWR). A FEM analysis is performed of the stresses in the axial zone of the workpiece formed by this method. Thirteen CWR cases are analyzed for different values of the forming angle, α=<15°; 35°>, spreading angle, β=<4°; 12°>, and reduction ratio, δ=<1.1; 1.9>. Numerical results demonstrate that the stresses in the CWR process are characterized by the mean stress triaxiality ηav=<0.075; 0.334> and the mean Lode angle parameter Θav<−0.905; −0.415>. Under this stress state, fracture may occur as a result of both void formation and shear fracture. A new hybrid criterion of fracture is proposed, which combines 2 well-known fracture criteria, i.e. the maximum shear stress criterion and the Oh criterion (normalized Cockcroft-Latham criterion). It should, however, be mentioned that the effect of the above criteria on the final value of the proposed hybrid criterion depends on the stress triaxiality. The critical value of the proposed fracture criterion is determined by a new calibration test based on rotary compression, in which the stress state is similar to that in parts produced by the CWR method. The critical value of the new fracture criterion is determined for the C45 grade steel in the temperature range of 950–1150 °C. Results demonstrate that increasing the forming temperature leads to an increase in the critical damage function. To verify the proposed fracture criterion, CWR tests are performed under conditions leading to fracture of the material (C45 steel). Experimental findings and numerical results obtained by the new hybrid fracture criterion show a very high agreement in terms of both quality (crack occurrence prediction) and quantity (crack length prediction).

Fatigue Crack Length Estimation and Prediction using Trans-fitting with Support Vector Regression

This paper explains the proposed method of Team SeouLG in detail for crack length estimation and prediction based on wave signals. The proposed method consists of two parts; (1) crack length estimation using support vector regression (SVR), (2) crack length prediction using new trans-fitting method. For the estimation of the crack length, we define the features based on the filtered wave signals and construct the model using SVR method. The hyper-parameters of the SVR model are selected based on grid search algorithm. The prediction of the crack length is based on the previous crack length, which is estimated based on the wave signals. In this part, we apply a new proposed trans-fitting method. The trans-fitting method updates the selected candidate function to fit the trend of the crack propagation from the training dataset. By translocating the selected candidate functions to the estimated crack length, we can predict the crack length of the target cycles. The proposed method is validated with the new given specimens. The results show that the proposed method can estimate and predict the crack length to lead Team SeouLG to the first place in 2019 PHM Conference Data Challenge.

Ensemble Linear Regression and Paris’ Law Based Methods for Structure Fatigue Crack Length Estimation and Prediction Using Ultrasonic Wave Data

This paper presents the methods developed for the 2019 PHM Conference Data Challenge. The PHM Data Challenge aims to estimate the fatigue crack length of a type of aluminum structure using ultrasonic signals at the current loading cycle, and to predict the crack length at multiple future loading cycles (multiple-step ahead prediction) as accurate as possible. For the crack length estimation, four crack sensitive features are extracted from ultrasonic signals, namely, the first peak value, root mean squared value, log of kurtosis and correlation coefficient. These features and their 2nd order interactions are used as inputs for an ensemble linear regression model which is built to map the features to crack length. The Best Subset Selection method is employed to select optimal features. For the crack length prediction, variations of the Paris’ law are derived to describe the mutual relationships between crack length and the number of loading cycles. The specimen material parameters and stress range of the Paris’ law are learned using the Genetic Algorithm, and updated with the next-step predicted crack length. The crack length corresponding to a future loading cycle number under constant amplitude cyclic loading and under variable amplitude cyclic loading is predicted respectively. The presented overall methodology achieves a score of 16.14 with the score calculation rule provided by the Data Challenge organization team, and ranks 3rd among all teams.

Quantitative prediction of crack length where fatigue crack propagation life has no scatter

Quantitative prediction of crack length where fatigue crack propagation life has no scatter

Characterization of J-R curves of a HSLA-steel and an Alloy 52 DMW with SE(T) specimens

The J-R curves determined with high constraint specimens can be overly conservative for structural integrity analyses of cracks in pipes and pressure vessels. In this investigation, J-R curves are determined experimentally with low-constraint single edge tension (SE(T)) specimens of a HSLA-steel and an Alloy 52 dissimilar metal weld (DMW) and the quality of the data is analysed. The results show that the CANMET crack length prediction gives a good fit to the measured data within the validity limits of the prediction, the stress in the remaining ligament does not exceed the true tensile strength, and the increase in the J-R curve due to loss of constraint was predicted analytically.

Spacecraft Module Hole Size and Crack Length Prediction Following a Penetrating Debris Particle Impact

The process used to calculate and reduce the consequences of meteoroid and orbital debris (MOD) penetrations and their link to catastrophic failure has evolved over time. As the threat of the orbital debris population increased in the 1980s and early 1990s, NASA developed a tool to determine the probability of no catastrophic failure, or PNCF, for the space station and to assess possible changes in station design and/or operations to improve that survivability percentage. PNCF is directly related to the PNP, or probability of no penetration, as calculated by Bumper, the code used by NASA to perform MOD risk assessments. Part of the process in determining PNCF involves calculating the size of the holes and cracks caused by any penetrations. In this paper, the features of new generic hole- and crack-size prediction equations, as well as the phenomenology involved in the formation of holes and cracks in habitable space station modules are presented and discussed. When these new hole and crack size equations are used in survivability assessments, the fidelity of the PNCF calculations and predictions are expected to increase dramatically.

Acoustic emission source mechanism analysis and crack length prediction during fatigue crack propagation in 16Mn steel and welds

The acoustic emission (AE) signals during four-point bending fatigue crack propagation in the base metal and weld of 16Mn steel were monitored and analyzed. The fatigue properties and acoustic emission characteristics were analyzed based on the micro-structural and fractographic observations. The results show that: AE signal was divided into three stages, correspond with the three stages of fatigue damage process, which were crack initiation, stable crack extension and unstable crack extension. The corresponding dominated AE source were micro-crack initiation in the first stage, stacking and slipping of dislocations ahead of the crack tip in the intermediate stage, shearing of ligaments and connectivity between dimples in the final stage. Fatigue crack growth rate and AE count rate is greater in weld specimen than in the base material, mainly due to the coarse ferritic grain in widmanstatten structure and a large number of oxide inclusions.The fatigue crack length was predicted by BP neural network method and AE parameter fitting method respectively. The relative error of each specimen was less than 15%. The results showed that acoustic emission technology could be used for fatigue life prediction and safety assessment in 16Mn steel and welds.