Imperfection Mode Research Articles

A Multi-Strategy Hybrid Sparse Reconstruction Method Based on Spatial-Temporal Sparse Wave Number Analysis for Enhancing Pipe Ultrasonic-Guided Wave Anomaly Imaging.

Ultrasonic-guided waves (UGWs) in defective pipes are subject to severe coherent noise caused by imperfect detection conditions, mode conversion, and intrinsic characteristics (dispersion and multiple modes), inducing the limited performance of anomaly imaging. To achieve the high resolution and accuracy of anomaly imaging, a multi-strategy hybrid sparse reconstruction (MHSR) method based on spatial-temporal sparse wavenumber analysis (ST-SWA) is proposed. MHSR leverages the capability of ST-SWA to extract the wavenumber dispersion curves, thereby providing a more refined and precise search space for MHSR. Furthermore, it mitigates the impact of coherent noise by conducting dispersion compensation on the reconstructed signal. The sparse compensated signals through MHSR are employed for sparse reconstruction imaging. To validate the efficacy of the proposed method, UGW testing is performed on the defective steel pipe, and the results demonstrate the significant enhancement of anomaly imaging in defect resolution and positioning accuracy. The lowest estimated errors for axial and circumferential defect positions are 10 mm and 4 mm, respectively.

Seismic analyses of single-layer dome structures with random geometrical imperfections under stochastic ground motions

In this paper, seismic analyses of single-layer dome structures are carried out, with a particular emphasis on the incorporation of randomness in both geometrical imperfections and ground motions. First, the paper introduces models for random geometrical imperfections and stochastic ground motions, employing the Stochastic Imperfection Mode Superposition Method (SIMSM) for imperfections and utilizing the Spectral Representation Method (SRM) for ground motions. These models are designed to comprehensively account for the inherent uncertainties in real-world structural behavior. Subsequently, the Probability Density Evolution Method (PDEM) is applied to investigate the probabilistic response and seismic reliability of dome structures, which allows for a detailed examination of key performance indicators, such as displacement, plastic ratio, and strength damage, under the influence of random factors. Both deterministic and stochastic analyses are conducted to gain insights into the impact of randomness in geometrical imperfections and ground motions. The computational results unveil a crucial finding: an unfavorable distribution of imperfections can significantly compromise the dynamic performance and safety of single-layer dome structures. Furthermore, the paper delves into parametric analyses, with a specific focus on imperfection amplitude, the rise-span ratio and roof load as pivotal parameters. These analyses provide valuable insights into the sensitivity of the structural response to variations in these critical design factors.

1/2 and 1/3 Subharmonic Resonance Behaviors of a Rotating FG-CNTRC Beam with Geometric Imperfections

This paper aims at investigating 1/2 and 1/3 subharmonic resonances of a rotating functionally graded carbon nanotube-reinforced composite (FG-CNTRC) beam in the presence of geometric imperfections. A general function is introduced to denote three types of imperfections containing sine, global, and local modes. At first, based on the von-Kármán geometric nonlinearity assumption, the forced vibration equation is set up. Then, the Galerkin method and multiple scale method are utilized to study subharmonic resonance behaviors. Finally, coupled effects of FG-CNTRCs, rotating motion, and geometric imperfections on subharmonic resonance responses are investigated. It is found that a specific range of the excitation amplitude and frequency motivates the subharmonic resonance behavior. The coupling of geometric imperfections and geometric nonlinearities generates the 1/2 resonance phenomena, and geometric nonlinearities result in the 1/3 resonance behavior. Both the imperfection mode and amplitude can affect the resonance response and resonance regions. Moreover, in contrast with the 1/3 subharmonic resonance, geometric imperfections produce greater influence on the 1/2 subharmonic resonance.

Knowledge-induced Multiple Kernel Fuzzy Clustering.

The introduction of domain knowledge opens new horizons to fuzzy clustering. Then knowledge-driven and data-driven fuzzy clustering methods come into being. To address the challenges of inadequate extraction mechanism and imperfect fusion mode in such class of methods, we propose the Knowledge-induced Multiple Kernel Fuzzy Clustering (KMKFC) algorithm. Firstly, to extract knowledge points better, the Relative Density-based Knowledge Extraction (RDKE) method is proposed to extract high-density knowledge points close to cluster centers of real data structure, and provide initialized cluster centers. Moreover, the multiple kernel mechanism is introduced to improve the adaptability of clustering algorithm and map data to high-dimensional space, so as to better discover the differences between the data and obtain superior clustering results. Secondly, knowledge points generated by RDKE are integrated into KMKFC through a knowledge-influence matrix to guide the iterative process of KMKFC. Thirdly, we also provide a strategy of automatically obtaining knowledge points, and thus propose the RDKE with Automatic knowledge acquisition (RDKE-A) method and the corresponding KMKFC-A algorithm. Then we prove the convergence of KMKFC and KMKFC-A. Finally, experimental studies demonstrate that the KMKFC and KMKFC-A algorithms perform better than thirteen comparison algorithms with regard to four evaluation indexes and the convergence speed.

Geometric Imperfection Simulations in Cee-Shape Cold-Formed Steel Members Based on Newly Developed Machine-Vision Inspection Techniques

This paper insightfully studies geometric imperfection simulations of cee-section CFS members from laser-based measurements. A machine-vision imperfection inspection technique is first developed where an algorithm is implemented to automate imperfection characterization from volumetric data. The measured imperfections are statistically analyzed and resemble past measurements from other researchers. Two imperfection simulation approaches are studied, i.e., the modal imperfection simulation method and the 1D spectral simulation method, where strength performance and deformation are predicted from finite element analysis. The analysis results are compared with those of testing. The 1D spectral simulation method is superior where stochasticity and regularity of real im-perfection can be properly addressed. The study provides feasible access to imperfection simulations of cee-section CFS members that other researchers can directly apply. The prediction results can aid the future direct analysis and design of CFS members.

Data-driven strategy for geometric imperfection analysis of assembled large-span ring truss components

Assembled large-span ring truss, constructed using circular steel tubes, is gaining popularity as a new structural form. However, the insufficient availability of design and modeling methods for geometric imperfection of components poses a challenge in studying the cumulative effects of these imperfections on the overall structural performance. Therefore, a data-driven strategy for analyzing geometric imperfections in assembled ring truss structural components (circular steel tubes) is presented in this study. The primary objective is to enable the design of geometric imperfections based on measured data and establish a corresponding equivalent calculation model to incorporate the measured imperfections into the structural analysis model. The core of this strategy lies in utilizing the high-precision point cloud data of components obtained through 3D laser scanning technology as the primary input. The geometric imperfection modes are extracted accurately and rapidly by employing a developed algorithm. Furthermore, a comprehensive framework is proposed for establishing the geometric imperfection calculation model based on the identified modes. A case study was conducted to validate the proposed strategy, revealing its high reliability. Moreover, it is recommended to extend this strategy for analyzing geometric imperfections in similar building structural members.

Digital Twin-Based Numerical Simulation Method for Cee-Shape Cold-Formed Steel Members

Cold-formed steel (CFS) structures are widely used in construction and infrastructure due to their lightweight and high-strength properties. However, their thin-walled nature makes them geometrically sensitive to compressive loading. The Digital Twin (DT)-based numerical simulation method is developed using the actual geometries of CFS shapes, which are acquired by a 3D laser scanner. The DT-based numerical simulation incorporates the reconstructed measurement point clouds into the finite element modeling, ensuring that actual geometric features are retained. A series of tests, including material and axial compression testing, are conducted to validate the modeling parameters, such as mesh sizes and boundary conditions. The advantages of the DT-based numerical simulation method are highlighted compared to the traditional CFS member numerical simulation, which incorporates only the first mode of geometric imperfection. Additionally, DT-based numerical simulations offer more accurate load capacities and deformation predictions. Moreover, the automated and validated DT-based numerical simulation demonstrates prevalence in modeling efficiency and computation effectiveness. The DT-based numerical simulation method holds potential for application in smart structural analysis, where accurate geometries derived from extensive measurement point clouds are integrated into numerical modeling.

Assessment of the ultimate strength of stiffened panels of ships considering uncertainties in geometrical aspects: Finite element approach and simplified formula

The development of reliability-based assessments has improved the safety design of ship structures by considering the stochastic behaviour of structural components such as stiffened panels. However, previous studies generally considered the variation in the initial geometric imperfection of a stiffened panel as a single deterministic value. To enhance the analysis, in this study, a series of ultimate strength analyses of stiffened panels were carried out by varying and combining the stiffened panel parameters, including variations in the initial geometric imperfection (2.5%, 25%, 50%, 75%, and 100% of the maximum value), modes of the imperfection (column, local, and torsional imperfection modes), slenderness ratios (plate and web slenderness), and span-to-bay ratios (3 and 6). A total of 750 stiffened panel configurations were investigated through a nonlinear finite element method (FEM) analysis using ANSYS APDL incorporated with a code in MATLAB to model the imperfections based on idealised models. The obtained ultimate strength values were then formulated using a nonlinear correlation between the variables in the regression method to yield a new formula for predicting the ultimate strength of the stiffened panel. The results showed that combining the varied parameter values significantly affected the ultimate strength of the stiffened panel and collapse modes. The newly derived formula provided good accuracy with a standard error of only 2.08% when compared with the FEM results of stiffened panels having a significant disparity with the configuration of the idealised models. This confirms the validity of the formula as a reference for evaluating the ultimate strength value with the influence of an initial geometric imperfection.

Numerical simulation of local-distortional buckling behavior of lipped C-section stainless steel columns

The stainless steel components with lipped C-section are prone to Local-Distortional Interaction Buckling (LDIB) failure when subjected to compressive load, whereas the design formula of LDIB capacity has not been well-established so far. As a follow-up work of previous experimental study, this paper aims to conduct a parametric study on the LDIB behavior of lipped C-section stainless steel columns through numerical simulation and propose the relevant calculation formulas of LDIB bearing capacity. The factors governing the buckling behavior include the initial geometric imperfection mode, the local-distortion buckling slenderness ratio, the corner region material strength improvement, and the nominal yield strength of the stainless steel materials. Based on the validated Finite Element (FE) model, the LDIB capacity of 169 lipped C-section stainless steel columns with strong-axis rotation and 201 lipped C-section stainless steel columns with weak-axis rotation were numerically computed, and the calculation formulas of LDIB capacity were then proposed using the direct strength method. Based on the comparative study, the proposed formulas deliver enhanced accuracy and robustness than the existing formulas and hence could be employed reliably for the design of lipped C-section stainless steel columns.

Nonlinear dynamic modeling of geometrically imperfect magneto-electro-elastic nanobeam made of functionally graded material

Smart magneto-electro-elastic (MEE) structures with high performance are highly valuable across a vast range of aerospace and industrial applications like smart sensing, space robotics, energy harvesting and biomedical research. This work focuses on the nonlinear dynamic response of a functionally graded MEE nanobeam. Initial geometric imperfection including global and localized imperfection modes is considered to reflect the effect of undesired error during nanofabrication process. Such geometric imperfection is involved by the product of hyperbolic and trigonometric functions. The nonlinear dynamic model for the FG-MEE nanobeam is established according to Hamilton’s principle and nonlocal constitutive relation to derive its governing equations of motion. The interaction between the imperfect FG nanobeam and its multi-physical stimulus is numerically solved via differential quadrature method. After validating the proposed model with existing works, the parametric study is conducted to fully reveal the coupling effect of geometric imperfection and numerous parameters including imperfection mode and amplitude, external electric and magnetic potentials, functionally graded index, boundary constraint and size-dependent parameter on nonlinear dynamic response of the FG-MEE nanobeam. Simulation results have demonstrated the significance of the MEE coupling effect, which can be used as a guide to design smart and advanced devices for aerospace and industrial applications.

Experiment study of dynamic buckling for stiffened panels under longitudinal impact

The stiffened panels of marine structures are usually suffered from various dynamic loads. However, there are very few reports about the dynamic buckling experiment for stiffened panels. In this paper, stiffened panels are designed to carry out a series of impact experiments on a falling hammer platform. The high-speed deflection fields during the extremely short impact time are recorded using 3D-DIC (Digital Image Correlation) system in these experiments. Thus, the dynamic deflections are acquired to analyze the dynamic buckling behavior for stiffened panels. Based on the experiment results, the application of dynamic buckling criteria is studied to determine the critical impact velocity for the experiment models. At last, the FE simulation is used to compare with the experiment results of dynamic response for stiffened panels, and the influence of initial imperfection modes are also discussed. The analysis results show that, the stiffened panels tend to have dynamic bucking modes with more half-waves of deformation in longitudinal direction, and the dynamic response can be significantly influenced by the initial imperfection modes.

Understanding the Paradox of (Im)Perfection: An Actor-Network Approach to Digitally Mediated Preaching

This paper adds to the growing body of literature on digitally mediated preaching by using actor–network theory (ANT) in conjunction with Amanda Lagerkvist’s work on digital media as theoretical lenses to describe and discuss what we term “the paradox of (im)perfection”. This paradox refers to the tension between an ideal of perfection and an ideal of imperfection (or vulnerability) as experienced by church practitioners who were “thrown” online abruptly and unexpectedly due to the pandemic. In our analysis we show how human and non-human actors interact (and act on each other) in ways that assemble their networks towards a mode of visibility and perfection, or towards a mode of authenticity, intimacy, and imperfection. In the former mode, preachers and church practitioners find themselves competing in “a mimetic visibility contest” that is characterized by an ontology of numbers (likes, follower counts, retweets, etc.) and a subsequent ethos of quantification. In the latter mode, an ethos of care affords the opportunity for spiritual intimacy, even among “anonymous” online individuals. Drawing on Deanna A. Thompson’s and Amanda Lagerkvist’s work, we argue that the latter mode enacts “a cruciform media ethics” in which the embodied worshiping community interacting online can be understood as “the virtual body of the suffering Christ”. Here, digital media is enacting as “caring media” rather than “metric media”. While the paper introduces message-oriented, media-oriented, and ontology-oriented approaches as helpful for the study of digitally mediated preaching, it ultimately argues for the superior virtues of ANT as a non-dichotomous approach—overcoming both the message/media and the virtual/real divides which are often inherent to other approaches.

Asynchronous event-triggered guaranteed cost control of two-dimensional Markov jump Roesser systems

This paper deals with the problem of asynchronous event-triggered guaranteed cost control for two-dimensional Markov jump systems in Roesser model. The hidden Markov model is introduced to characterize the asynchronous phenomenon induced by imperfect mode detection, and a hidden Markov model-based event-triggered mechanism is employed in controller design to reduce the communication burden of the network. By using the quadratic Lyapunov function technique, some sufficient criteria are developed to ensure the asymptotic stability of the addressed system with a guaranteed cost value under three different boundary conditions. Finally, an optimization algorithm with linear matrix inequality constraints is formulated to design the optimal asynchronous event-triggered guaranteed cost control law, and a simulation example is considered to illustrate its validity.

Decision tree for local + global imperfection combinations in double‐symmetric prismatic members – Practical recommendations in the framework of advanced analysis

AbstractBetter and simpler possibilities of structural optimization due to increasing computational power but also for reasons of environmental sustainability, the use of materials and their reusability lead to greater acceptance towards more advanced numerically intensive, so‐called ‘design by analysis' methods like geometrically and materially non‐linear analyses with imperfections (GMNIA). The general choice of imperfections and their combination in such models, especially for slender cross sections of intermediate length prone to an interaction between a global and local plate buckling, is crucial in terms of the reached load‐bearing capacity. Annex C of EN 1993‐1‐5:2010 makes use of the ‘70 %‐rule' for the combination of imperfection modes and amplitudes. This rule postulates that two GMNIA calculations should be conducted when local and global interactive buckling may be dominant; one with 100 % + 70 % of the maximum specified amplitude in either case. In addition, extended information is provided on the choice and combination of imperfections in the newly introduced and currently available draft of the prEN 1993‐1‐14:2020 (design assisted by finite element analysis). Although information is provided on how the local and global imperfections should be combined, it is not stated when it is relevant to consider those. Based on conducted GMNIA simulations on SHS/RHS (square and rectangular hollow sections) and I‐shaped sections, this article presents general decision support on the choice of equivalent imperfections. On the basis of numerical analysis, the developed flow chart and design routine allow for the decision whether the consideration of the interaction of local and global imperfections is required or not.

On the large amplitude vibration of shallow sandwich shells with FG-GNPRP core considering initial geometric imperfections

The present study investigates the influence of initial geometric imperfections on large amplitude vibration of shallow sandwich shells with functionally graded graphene nanoplatelets reinforced porous (FG-GNPRP) core embedded between two aluminium facets. The aluminium core is reinforced with graphene nano-platelets (GNP) and the effective properties such as elastic modulus, and mass density, etc. are estimated using Halpin-Tsai and Voigt models, respectively. The continuous functions are adopted to accomplish micro-structural gradation while creating pores which imparts the variation in material properties along thickness direction. The nonlinear governing equations based on higher order shear deformation theory and Sander’s approximation are derived using variational approach. The nonlinearity is introduced in von-Kármán sense and various imperfection modes such as sine, global and local types are considered in transverse direction. The nonlinear results are accessed using finite element method in conjunction with direct iterative technique. The influence of porosity, GNP weight fraction, imperfection amplitude, thickness, side, and radius ratios on the vibration response of the sandwich shells is explored in detail.

A novel evolution model to investigate the collaborative innovation mechanism of green intelligent building materials enterprises for construction 5.0

<abstract> <p>Green intelligent building materials is an effective way for building materials industry to reduce carbon. However, a small amount of research and development (R&D, unstable R&D investment and imperfect collaborative innovation mode hinder the development of green intelligent building materials industry. However, few scholars study the development mechanism of green intelligent building materials industry from the perspective of industrial chain considering the above obstacles. In this study, the game models under market mechanism and government regulation were constructed to analyze the income distribution mechanism for the development mechanism of green intelligent building materials industry. Finally, the questionnaire method was used to discuss the game strategy of collaborative innovation behavior among agents. The results are as follows. In the game strategy selection of collaborative innovation behavior among green intelligent building materials, factors such as database marketing maturity, information flow and technology volume generated by collaborative innovation, technical benefit coefficient, social benefit coefficient and profit and loss barrier factors are conducive to the collaborative innovation behavior of green intelligent building materials. When the market mechanism fails, the incentive effect of cost subsidy adopted by the government is more efficient and fast, and the driving force of achievement reward is more lasting. The combination of the two incentives is the best. Moderate supervision and punishment lower than the free rider income can not ensure fair competition among green intelligent building materials enterprises. The punishment above the threshold can effectively restrain the negative impact of free rider income and prospect profit and loss. This study not only theoretically expands the development theory of digital industry from the perspective of industrial chain by considering the maturity factor of database, but also provides policy guidance for the development of green intelligent building materials industry in practice.</p> </abstract>

Numerical prediction and experimental analysis of the buckling loads of SMPC cylindrical shells under axial compression

The axial compressive buckling loads of shape memory polymer composite (SMPC) cylindrical shells are very sensitive to geometric imperfections and temperatures, but few studies have been conducted on this phenomenon. In this study, the buckling loads and geometric imperfection sensitivities of SMPC cylindrical shells at different temperatures are determined by means of numerical simulations and experimental analyses. The single perturbation displacement imperfection (SPDI), multiple perturbation displacement imperfection (MPDI) and linear buckling mode imperfection (LBMI) techniques are used to simulate the initial geometric imperfections and calculate the corresponding buckling loads and knock-down factors (KDFs) of SMPC cylindrical shells at different temperatures. In the experimental part, the [0/90/±45]s SMPC cylindrical shells are manufactured through the autoclave molding process. The load-bearing capacities at different temperatures are tested and compared with the numerical results. The results demonstrate that the buckling loads of the SMPC cylindrical shell obtained by numerical techniques are sensitive to temperature, while the KDFs are insensitive to temperature. Meanwhile, results indicate that brittle fracture is the main failure mode instead of buckling at low temperature, so there is a risk when using any numerical technique to design SMPC cylindrical shells in low-temperature region. At high temperatures, the SPDI method overestimates the KDFs, while the KDFs calculated by the MPDI and LBMI techniques are in good agreement with the experimental results. However, only the LBMI method can distinguish the influence of temperature on the post-buckling patterns, and the corresponding post-buckling pattern is more consistent with the experiment. In addition, the shape-recovery properties and repeatability of the SMPC cylindrical shells are good.

Effect of support settlement on ultimate bearing capacity of Zhoukoudian steel structure

In order to study the effect of non-uniform support settlement on global stability ultimate bearing capacity of lattice shell structure, combining with the project of first site protective building in Zhoukoudian Ruins, the finite element software ANSYS is employed to conduct geometric nonlinear and double nonlinear global stability analysis of the single-layer lattice shell respectively based on consistent mode imperfection method and advanced consistent mode imperfection method, thus the global stability ultimate bearing capacity under different settlement cases is obtained and compared. Analysis results show that non-uniform support settlement is beneficial to increase the elastic global stability ultimate bearing capacity of the structure by a small margin, but excessive settlement may have adverse effects on the bearing capacity of the structures with initial imperfections. When considering material nonlinearity, small non-uniform support settlement is conducive to a slight increase in the elastoplastic global stability ultimate bearing capacity of the structure that decreases and is lower than that without settlement with the increase of non-uniform settlement. In addition, non-uniform support settlement will not affect the instability path of the lattice shell.

Thermo‐mechanical nonlinear stability analysis of geometrically imperfect functionally graded plates with microstructural defects using logarithmic structure kinematics: An unified expression

AbstractIn the present paper, thermo‐mechanical stability analysis of geometrically imperfect porous functionally graded plates (FGP) with geometric nonlinearity is presented. The equilibrium, stability, and compatibility equations are derived using Logarithmic structural kinematics in conjunction with the von‐Karman type of geometric nonlinearity. A logarithmic‐based shear‐strain function has been used for the first time for the buckling response of functionally graded material (FGM) plates. Generic imperfection function has been implemented to incorporate the various imperfection modes like sin‐type or global type in the formulation. The effective materials properties of the plates with porosity inclusion have been computed using modified power law. The plate is subjected to uniaxial and biaxial compression as well as combined compression and tension along with thermal loading. An exact expression for the critical buckling load and critical buckling thermal load of geometrically imperfect porous FGM plate for each loading case has been developed. After confirming the excellent accuracy of the current exact solutions, the effect of geometric imperfection, porosity inclusion, and geometric configurations on the nonlinear stability of the FGM plate have been discussed extensively. The results presented in this paper will be used as a benchmark for future research.

Anomaly detection in rolling bearings based on the Mel‐frequency cepstrum coefficient and masked autoencoder for distribution estimation

It is difficult to establish a classification and recognition model of machinery and equipment based on labeled samples in the actual industrial environment because of the imperfect fault modes and data missing. To solve this problem, a semisupervised anomaly detection method based on masked autoencoders of distribution estimation (MADE) is designed. First, the Mel-frequency cepstrum coefficient (MFCC) is employed to extract fault features from vibration signals of rolling bearings. Then, a group of mask matrices are set on each hidden layer to overcome the perfect reconstruction problem of the autoencoders' input, and the full-connection probability of reconstruction is used to replace the reconstruction error and adopted as the anomaly score. Finally, the diagnostic threshold is determined according to the Youden index. Experimental results show that the MADE method can extract fault-sensitive features from a noisy industrial environment and introduce mask matrices renders to make the network autoregressive, thus solving the problem of perfect reconstruction of autoencoders. It is verified based on three rolling bearing datasets that the accuracy, precision, recall, and F1-score of the proposed method are confirmed to be all 100%. Moreover, the accuracy of the proposed method is 17.19% higher than that of the memory-inhibition method on the rolling bearing dataset provided by the Center for Intelligent Maintenance Systems (IMS) in University of Cincinnati (USA). The accuracy of the proposed method is also improved compared with other state-of-the-art anomaly detection methods.