Crack Location Research Articles

Nonlinear vibrations of cracked microbeams based on modified couple stress theory

In this study, nonlinear vibrations of cracked microbeams have been investigated. The micro size characteristics of the beam have been involved in the model by utilizing the modified couple stress theory. Longitudinal elongation of the microbeam during transverse vibrations have been considered to capture the nonlinear behavior. To model the crack, a torsional spring has been introduced at the crack location and the spring constant corresponds to the severity of the crack. Approximate solutions have been obtained by using the method of multiple scales, a perturbation technique. The results have been validated by comparing them with existing literature and have been presented in terms of both crack severity and micro scale properties. The effects of the crack have been examined on various aspects, including natural frequency, nonlinear frequency-response curves and nonlinear frequency responses. These effects have been investigated with respect to parameters such as crack severity, crack location, amplitude of excitation, slenderness of the beam, all under differing boundary conditions. The predicted results reveal that as the crack severity increases, both natural frequency and nonlinear frequency decrease. Furthermore, the modified couple stress theory predicts an increase in natural frequencies as the size scale of the microbeams reduces. The frequency-response curves with varying crack severity and crack locations have indicated the significant effects of the presence of the crack in microbeams.

Multilevel thresholding with divergence measure and improved particle swarm optimization algorithm for crack image segmentation

Crack formation is a common phenomenon in engineering structures, which can cause serious damage to the safety and health of these structures. An important method of ensuring the safety and health of engineered structures is the prompt detection of cracks. Image threshold segmentation based on machine vision is a crucial technology for crack detection. Threshold segmentation can separate the crack area from the background, providing convenience for more accurate measurement and evaluation of the crack condition and location. The segmentation of cracks in complex scenes is a challenging task, and this goal can be achieved by means of multilevel thresholding. The arithmetic-geometric divergence combines the advantages of the arithmetic mean and the geometric mean in probability measures, enabling a more precise capture of the local features of an image in image processing. In this paper, a multilevel thresholding method for crack image segmentation based on the minimum arithmetic-geometric divergence is proposed. To address the issue of time complexity in multilevel thresholding, an enhanced particle swarm optimization algorithm with local stochastic perturbation is proposed. In crack detection, the thresholding criterion function based on the minimum arithmetic-geometric divergence can adaptively determine the thresholds according to the distribution characteristics of pixel values in the image. The proposed enhanced particle swarm optimization algorithm can increase the diversity of candidate solutions and enhance the global convergence performance of the algorithm. The proposed method for crack image segmentation is compared with seven state-of-the-art multilevel thresholding methods based on several metrics, including RMSE, PSNR, SSIM, FSIM, and computation time. The experimental results show that the proposed method outperforms several competing methods in terms of these metrics.

Optimized analytical approach for the detection of process-induced defects using acoustic emission during directed energy deposition process

Directed energy deposition (DED), an advanced additive manufacturing (AM) technique, facilitates the production of complex metallic and metal matrix composite structures. The DED process has continuously improved and offers numerous advantages for depositing high-quality coatings with excellent wear and corrosion resistance onto metallic surfaces. The dynamic nature of the process, however, introduces a significant risk of process-induced defects in manufactured parts. This study presents an optimized analytical approach using acoustic emission (AE) based defect detection technique to identify and quantify process-induced cracks during the DED process. The developed signal processing technique enabled the identification of actual AE events associated with cracking, distinguishing them from other disturbances. Experimental validation was conducted using manufactured parts that were longitudinally sectioned to determine the relationship of the crack location with the recorded acoustic signal. The demonstrated correlation of acoustic signatures with cracking illustrates the robustness of the AE technique to identify the process-induced cracking for quality assurance during the DED process.

Acoustic emission onset time detection for structural monitoring with U-Net neural network architecture

Acoustic Emission (AE) is a non-destructive structural health monitoring technique, which studies elastic waves emitted during crack formation. Utilizing piezoelectric sensors, these waves are converted into electrical signals for subsequent analysis, offering insights into crack propagation and structural durability. This study focuses on the identification of AE signal onset times, crucial for determining crack locations. Conventional methods often encounter challenges with background noise, prompting the need for innovative approaches. Leveraging a U-Net neural network, specialized in segmentation tasks, onset time identification is approached as a one-dimensional segmentation challenge. Through training and testing on Pencil Lead Break (PLB) test data, commonly used in AE evaluations, the effectiveness of the method is demonstrated even with continuous signals, suggesting potential applicability in real-time monitoring.

Damage localization on reinforced concrete slab structure using electromechanical impedance technique and probability-weighted imaging algorithm

Damage localization plays a key role in structural damage identification and health monitoring. This paper proposed a new damage localization approach using electromechanical impedance/admittance (EMI/EMA) technique integrated with probability-weighted imaging algorithm based on Gaussian distribution. The proposed approach comprises five steps namely measurement of the EMA signature from an array of piezoelectric ceramic lead zirconate titanate (PZT) transducers, computation of statistic damage indicator, establishment of regression model for the indicator, damage visualization via Gaussian distribution and final damage localization. Experimental validation of the approach was conducted on a reinforced concrete (RC) slab with artificial crack damages detected by using an array of surface-bonded PZT patches. Comparative studies on localization accuracy were performed by utilizing root mean square deviation (RMSD), baseline-changeable RMSD namely RMSDk, mean absolute percentage deviation (MAPD) and correlation coefficient (CC). Experimental results demonstrated that the proposed approach could achieve precise localization of concrete crack with error as small as 0 mm, and that using RMSDk index exhibited the highest localization accuracy in average. The proposed approach promoted the capability of the EMI technique in characterization of concrete structural damages.

Quantifying tidal versus non-tidal stresses in driving time-varying fluxes of Enceladus' plume eruptions

In this study we investigate the relative importance of endogenic vs. exogenic stresses in controlling the location and timing of active ice-shell deformation on Enceladus, which is expressed by cyclic plume eruptive flux along active fault zones (i.e., the tiger stripes). Although the variation of the eruption flux on Enceladus follows the periodicity of the diurnal tide, it remains unclear why there is a consistent phase delay of the observed peak eruption when compared to the predicted peak tidal stress. Here, we explore whether endogenic stresses in the ice shell are capable of explaining this observed phase delay. To achieve this goal, we performed geologic mapping along the tiger-stripe faults that host the erupting plumes. Using the fault kinematics established from our mapping, we determine the general stress state (i.e., the principal-stress directions) along the tiger-stripe faults. This knowledge in turn forms the basis for inferring the most likely plume-eruption mechanism. Our mapping shows that the tiger-stripe fractures are not tensile cracks but are instead left-slip fault zones locally displaying extensional fissures. This insight leads to a hypothesis that strike-slip faults and their local tensile cracks experience simultaneous shear and tensile failure, and that the tensional opening reaches maximum at the time of the peak plume flux. We quantified this hypothesis using a stress decomposition model that assesses (1) the relative importance in magnitude between the tectonic stress and tidal stress exerted on the tiger-stripe faults and (2) the role of ice shell properties such as the shear strengths, tensile strengths, and ice shell thickness in controlling the eruption phase delay. Using laboratory-determined ice strengths and the best estimate of the ice shell thickness at the South Polar Terrain of Enceladus, which hosts the tiger-stripe faults, our model results indicate that the endogenic tectonic stress is comparable in magnitude to the tidal stress. Although we cannot rule out warm-ice convection, true polar wander, and non-synchronous rotation as causes of endogenic stresses, the large variation in ice shell thickness makes the lateral gravitational-potential gradient the most plausible source of the endogenic stress required by our model results.

Study on failure mechanism of suspension lug elbow in an ethylene cracking pyrolyzer

The cracking of a suspension lug elbow caused a shutdown in a certain petrochemical enterprise. In this study, the authors conducted physical and chemical analysis to investigate the cracking mechanism. Macroscopic observations indicated no signs of corrosion or thinning on the inner and outer surfaces of the head, and the cracks were distributed in the body of the head and the ear. Chemical composition analysis revealed that the main chemical components of the failed elbow met the standard requirements. Metallographic observations showed significant creep damage in the substrate material, and after long-term high-temperature service, both the room temperature and high-temperature mechanical properties of the failed elbow significantly deteriorated. The failure sample exhibit a fracture elongation of 0 %, and the high-temperature creep performance of the head material was only 6.868 h, both lower than the standard requirement of a fracture elongation of 4 % and 120 h of high-temperature creep performance. Fracture surface observation revealed obvious creep voids and fatigue striations, indicating severe creep damage and the influence of alternating loads on the head. Field observations indicated that the head experienced significant shaking inside the furnace. Therefore, simulation analysis suggested that the maximum stress coincided with the crack location, ranging from 121 MPa to 131 MPa, far exceeding the tensile strength at the operating temperature when the elbow was subjected to alternating loads generated by left–right and back-forth swinging. In conclusion, the failure of the suspension lug elbow was caused by creep-fatigue cracking. This study reveals that, even when the internal medium is in single gaseous phase, elbows are still susceptible to cracking under the combined effects of high temperature vibration and creep interaction. To avoid future failures, strengthening the monitoring of the cracking furnace operation, controlling the load appropriately, and preventing severe vibration and shaking of the furnace tube are recommended.

Analysis of crack-tip stress field in unidirectional fiber-reinforced composites based on 3D micromechanical model

Accurately clarifying the influence of cracks on the mechanical behaviors of unidirectional fiber-reinforced composites (UD FRCs) is of great significance for the structural integrity evaluation of UD FRCs with defects. Although several experiments and numerical analyses have explored the impact of cracks on stress field, satisfactory quantitative characterizations of crack size, a/W and location, Δ, fiber content, Vf have not yet been obtained. In this paper, the accurate and detailed microscopic models containing crack were first established and thoroughly validated. Then, a parametric study was conducted using three-dimensional micromechanical analysis to investigate how the crack size and location, fiber content affect the von Mises, stress triaxiality, Lode angle and J-integral of UD FRCs. Results showed that homogeneous models, whether isotropic or anisotropic, cannot accurately describe the mechanical behavior of cracked UD FRCs. The von Mises stress and J-integral are greatly influenced by the crack and fiber content, while stress triaxiality and Lode angle are not sensitive to changes in these factors. Further, the von Mises and J-integral increase with the decrease of Vf and the increase of a/W, but show a more complex trend in the variation of Δ. These findings will help clarify the failure mechanism of cracked UD FRCs and can be used for reliability evaluation.

Enhanced high-resolution structural crack detection using hybrid interacting Particle-Kalman filter

Monitoring the health of large-scale infrastructure with the required precision necessitates high-dimensional support models and extensive instrumentation. However, in a model-based structural health monitoring (SHM) framework, the ability to localize damage is constrained by the discretization of the model. To enhance the resolution of discretization, dense instrumentation is essential to address the inherent challenges in solving the inverse problem. Yet, increasing dimensionality can introduce detection delays, a critical concern in SHM. Additionally, addressing uncertainties stemming from the model, measurements, or external factors is crucial for reliable real-world SHM. This study focuses on localized damages, such as cracks, where detection precision is paramount. To tackle these challenges, this study proposes an innovative hybrid interacting Particle-Kalman filter (h-IPKF)-based SHM approach that surpasses model discretization limitations for detection resolution. This approach employs two distinct indices for crack localization: global (GDI) and local (LDI) damage indices. GDI identifies the affected element using a coarsely discretized predictor model, while LDI precisely pinpoints the crack location within the element. This paper represents the crack as a massless rotational spring with deteriorated stiffness (γ) and parameterizes it using GDI, LDI, and γ. Subsequently, the h-IPKF framework is employed to estimate the crack parameters, capable of handling both continuous and discrete random variables, which is advantageous for addressing discrete variables like GDI. Extensive numerical and real validation tests on beam structures were conducted to assess the algorithm’s sensitivity to noise and damage severity, demonstrating its efficiency, promptness, and precision in detecting cracks within structures.

A novel sequentially linear approach based on exponential saw-tooth softening in fracture analysis of quasi-brittle material

The Newton-Raphson iterative scheme is a widely used technique for modeling the non-linear problems, but it is well known that the scheme is unstable and the convergence may be difficult to obtain in case of snap-back or bifurcation. The sequentially linear approach, which sets a critical integration point and uses a saw-tooth softening approximation, is an alternative approach to address these issues. However, the sequentially linear approach cannot fully solve some drawbacks such as mesh dependency of crack patterns, which is main shortcomings of smeared crack approach. In this paper, the saw-tooth curve based on exponential softening is newly developed and an approach combined it with local crack tracking algorithm is proposed. The crack tip point is chosen by crack tracking algorithm and the fracture behavior is analyzed by sequentially reducing the stiffness and strength in elements within crack path. Several benchmark examples are numerically solved to check the accuracy of crack path, ultimate load and capture of snap-back predicted by the proposed approach and the results are compared with those by traditional sequentially linear approach and experiments.

Numerical estimation of the equivalent hydraulic conductivity for canal concrete lining with cracks

The equivalent saturated hydraulic conductivity of concrete lining (Ksce) is a key parameter to estimate seepage loss, while few studies have quantified the effect of cracks on Ksce, potentially leading to significant errors in canal seepage estimation. A three-dimensional numerical model is employed to simulate seepage loss from canals lined with concrete, and then to obtain the value of Ksce by an equivalent method. A total of 58,400 scenarios are simulated for different concrete lining and crack conditions (e.g., crack length, crack width, crack location, hydraulic conductivity of concrete (Ksc), and underlying soil (Ksoil)), and the corresponding Ksce values are estimated. Results show that the Ksce value determined by the equivalent method is reliable in calculating seepage loss from concrete lined canals. Ksce increases linearly with crack length with a slope Ck, and Ck exhibits a power function relationship with crack width, reaching a maximum value when the crack width surpasses the critical threshold, which ranges from 0.424 to 0.435 mm. When the crack width follows a log-normal distribution, the logarithmic value of Ck increases linearly with the mean value of the logarithmic crack width. The influence of crack location and Ksc on Ksce can be negligible. The maximum increment of Ksce of a crack is proportional to Ksoil. Considering the variation of Ksce with crack parameters and Ksoil, equations to determine the value of Ksce are established by adding the increment of Ksce caused by cracks to Ksc. This study establishes a quantitative relationship between Ksce and crack parameters, thereby enhancing the accuracy of seepage loss calculations in lined canal under different damage status.

Application of Machine Learning (ML)-based multi-classifications to identify corrosion fatigue cracking phenomena in Naval steel weldments

Corrosion fatigue (CF) crack detection in welded ship hull structures is quite crucial as well as challenging for ensuring their structural integrity. This is conventionally done by offline ship hull survey and inspection methods, which have large time and cost implications. Data-driven approaches of ship hull crack detection are promising in this regard. Corrosion fatigue crack growth rate (CFCGR) behaviour of shipbuilding steel was studied for its base metal (BM), fatigue-prone heat affected zones (HAZs) of Submerged Arc Welding (SAW), and shielded metal arc welding (SMAW) joints of Naval-grade steel. The results indicated the highest CFCGR for BM, intermediate for SAW, and smallest for SMAW welds. This was attributed to 44% lath martensite observed in the SMAW HAZ microstructure as compared to 33% in SAW HAZ. A novel ML-based method has been proposed for CF crack location identification by a multi-classification approach using CFCGR data for structural health monitoring (SHM) applications. Prediction of crack location (either BM, SMAW HAZ, or SAW HAZ) was investigated using K-nearest neighbour (KNN), linear support vector machine classifier (LSVC), Naïve Bayes (NB), decision tree (DT), random forest (RF), and artificial neural network (ANN) models. DT and RF models were found to perform very well even without scaling and hyper-parameter tuning operations and exhibited 98–99% classification accuracy. Scaling and tuning operations resulted in significant improvements in accuracy of KNN models from 43% to 84% (minmax scaling) and 98% (standard scaling). Significant improvement in the accuracy from 37% to 98% ANN model was achieved by standard scaling. The proposed method shall be useful in data-driven real-time crack location identification in ship hull structures.

Free vibration of cracked FGM Mindlin plate in fluid

The free vibration of cracked functionally graded material (FGM) plate in fluid is investigated in this paper. The material components are supposed following the power law and formulated by the Voigt model. The Mindlin plate theory (MPT) including the shear deformation effect is established and the physical neutral plane is adopted to simplify the derivation due to the in-plane displacements of this plane assumed as zero. A massless linear rotational spring model (LRSM) is established to simulate the through-width surface crack. The hydrodynamic pressure at the fluid-plate interface is derived by the potential flow theory, and is regarded as the added mass of cracked FGM plate during the analyses of fluid-plate coupled vibration. The derivation and discretization of vibrational equations for cracked FGM plates in fluid are respectively achieved though the Hamilton’s principle and differential quadrature (DQ) method. The frequencies and mode shapes are iteratively calculated with these values of the vacuum case. The influences of immersed depth, fluid density, gradient index, crack depth, crack location, length-to-width ratio, length-to-thickness ratio, and boundaries on vibration characteristics are conducted in the section of numerical results. The present vibration analyses of cracked structures can be applicable to avoid structural resonance and failure.

An analysis of fatigue crack features at various crack lengths through mating fracture surface pairs

AbstractThis paper presents a novel high‐resolution direct analysis of mating AA7050‐T7451 fracture surfaces at crack lengths from 0.1 to 1.3 mm (Kmax of 4.51 to 16.39 MPa√m) for the purpose of analyzing the fatigue growth mechanisms. The various fractographic features observed at these crack lengths were then compared to the known accelerative effects of an applied loading sequence that contained underloads at regular intervals. A correlation was found between some of the observed features and the local fatigue crack growth rate. This study provides new insight into the prominent mechanisms that dictate crack growth rate and ultimately should assist with developing crack growth prediction methods that more accurately represent the physics of the fatigue crack growth mechanisms.

Flexural Behavior of Alkali-Activated Ultra-High-Performance Geopolymer Concrete Beams

Ultra-high-performance geopolymer concrete (UHPGC) emerges as a sustainable and cost-effective alternative to Portland cement-based UHPC, offering similar mechanical properties while significantly reducing carbon footprint and energy consumption. Research on UHPGC components is extremely scarce. This study focuses on the flexural and crack behavior of UHPGC beams with different steel fiber contents and longitudinal reinforcement ratios. Five UHPGC beams were tested under four-point bending. The test results were evaluated in terms of the failure mode, load–deflection relationship, flexural capacity, ductility, average crack spacing, and short-term flexural stiffness. The results show that all the UHPGC beams failed due to crack localization. Increases in the reinforcement ratio and steel fiber content had favorable effects on the flexural capacity and flexural stiffness. When the reinforcement ratio increased from 1.18% to 2.32%, the flexural capacity and flexural stiffness increased by 60.5% and 12.3%, respectively. As the steel fiber content increased from 1.5% to 2.5%, the flexural capacity and flexural stiffness increased by 4.7% and 4.4%, respectively. Furthermore, the flexural capacity, flexural stiffness, and crack spacing of the UHPGC beams were evaluated using existing methods. The results indicate that the existing methods can effectively predict flexural capacity and flexural stiffness in UHPGC beams but overestimate crack spacing. This study will provide a reference for the structural design of UHPGC.

Bending resistance mechanism of prestressed ultra-high performance concrete - reinforced concrete beam based on a full-scale experiment

Ultra-High Performance Concrete (UHPC) is a new type of engineering material with high compressive strength, high tensile strength, and high fracture toughness. Its bending failure mechanism is different from that of traditional concrete beams, which requires a new computational model to describe the bending failure phenomena of the prestressed ultra-high performance concrete - reinforced concrete (UHPC-RC) beam without web reinforcement. Therefore, this paper, through full-scale tests on a 30m prestressed UHPC-RC beam without web reinforcement, captures unique bending failure phenomena, including initial cracking, development of local cracks, and rupture of prestressed steel strands. Considering the tension-compression constitutive relationship of UHPC material, an innovative computational model for bending bearing capacity is proposed. Based on this model, a study on the minimum reinforcement ratio of full prestressed-ordinary steel bars is conducted. The results show that in the bending failure of the prestressed UHPC-RC beam without web reinforcement, excessive tensile strain of steel strands will occur at the local crack location. At this time, the structure does not satisfy the assumption of plane sections, and the introduction of the calculation model of the limit state of external prestressed tendons can effectively match this model, which is highly consistent with the experimental results. The minimum reinforcement ratio of full prestressed-ordinary steel bars is revised to the auxiliary reinforcement ratio of full prestressed-ordinary steel bars, quantifying the minimum reinforcement requirements of ordinary steel bars. The research results of this paper can provide reference for the next step of theoretical research.

Effect of pH on primary and secondary crack propagation in sandstone under constant stress (creep) loading

Time-dependent, chemically assisted crack propagation behavior in rocks is fundamental to understanding the long-term stability of civil engineering structures. In this study, we investigated the propagation of primary and secondary cracks in macrofractured sandstone in distilled water (pH = 5.6) and in an aqueous solution of hydrochloric acid (HClaq, pH = 1.82) using digital image correlation (DIC), comparing the results to those from experiments performed in air. Results show that for the macrofracture angles γ = 0 and 90°, the nucleation position r of the primary crack is not affected by pH, and always occurs at the fracture tip (r = 0) and fracture center (r = 1), respectively. For γ = 30, 45, and 60°, r increases quasi-linearly with the increase of γ in semi-log plots, and an increase in pH moves the primary crack away from the fracture tip. For a given γ, an increase in pH produces an increase in the kink angle k1 of the secondary crack. The influence of pH on secondary crack propagation is most pronounced at high γ values. As the pH increases, the location of the secondary cracks gradually turns counterclockwise with a decreasing swing range, from 37° at pH 1.82–35° at pH 5.6. The secondary crack is inclined at a maximum of 30° and 32° to the maximum principal stress direction at pH 1.82 and pH 5.6, respectively. Right-lateral shear secondary cracks with well-developed tensile tail fractures are more prevalent in higher pH environments. The comparison with dry experiments indicates that distilled water is more aggressive than HClaq. The significant loss of calcium ions in distilled water and the reduction of large pore volume fraction in HClaq are considered the main reasons for the deterioration of the pH effect.

Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs, this study presents an intelligent strategy for extracting road cracks. This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images. The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously. A convolutional neural network is utilized to extract cracks from the panoramic sequence image. The extracted sequence image is then aligned with the laser point cloud, enabling the assignment of RGB information to the vehicle-mounted three dimensional (3D) point cloud and location information to the two dimensional (2D) panoramic image. Additionally, a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud. The three-dimensional data pertaining to the cracks can be acquired. The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks. The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks. This approach exhibits superior accuracy when compared to conventional methods. Moreover, it facilitates rapid and accurate identification and localization of road cracks, thereby playing a crucial role in ensuring road maintenance and traffic safety. Consequently, this technique finds extensive application in the domains of intelligent transportation and urbanization development. The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

An Analysis of Two Case Studies on the Construction of Underground Caverns-A Focus on the Tiantai Pumped Storage Station

This paper presents a numerical analysis of two case studies on the construction of underground caverns by FLAC3D, with a specific focus on the Tiantai Pumped Storage Power Station. During the construction period, two main problems, which are crane beam stability and rock support, have been numerically analysed and addressed. The first case study examines the influence of rock wall crane beam support on excavation stability. It has been proven that The reinforcement of connected concrete enhances integrity but may lead to localized cracking. Moreover, over-excavation reinforcement marginally improves anchor safety. The second case study investigates abnormal anchor stress in a powerhouse resulting from excavation. Recommended measures include conducting timely stability evaluations, identifying weakened zones to control rock stress relaxation effects, and establishing effective feedback mechanisms. By enhancing the safety of pumped storage power stations, promoting sustainable energy infrastructure, and improving the design and construction processes of such stations, this research paper aims to contribute to the overall development and success of these projects. In conclusion, the paper has discussed the rock wall crane beam stability and rock support effect, which implement the lack of this type of numerical analysis in underground cavern group construction. Also, it is recommended to accurately determine the rock mass mechanics parameters and timely support the excavated spaces to prevent abnormal increases in anchor stress.

Assessment of process-induced cracks in hot-working operations using crack susceptibility index based on plastic instability criteria

A processing map representing the efficiency of power dissipation as a function of the temperature and strain rate has been used as a guide to depict the hot workability of metallic alloys. However, it has limitations in indicating the local positions where process-induced cracks may occur during hot-working operations. A process-induced crack is formed during hot deformation because the plastic instability associated with crack formation is more favorable than normal flow under a given set of process conditions. This paper proposes a novel approach to assess local cracks using the crack susceptibility index (CSI), which is based on Ziegler's plastic instability criteria. This solution provides useful information regarding the effect of each process parameter on the workability required for high-temperature processes. Lowering the CSI value by controlling process variables, such as the temperature and strain rate, is recommended for a design free from process-induced cracks. More importantly, a coded finite element subroutine coupled with the CSI can help visualize local positions where cracks may be produced during a hot-working operation. For experimental validation, a Gleeble test was performed on Ti6Al4V specimens containing four notches with different depths. The successful application of the CSI to the process design of shop-floor unmanned aircraft components helped confirm the applicability and validity of this study.