Article
Mechanics
Nan Zhang, Mengsheng Zhai, Liang Zeng, Liping Huang, Jing Lin
Summary: This paper presents a damage assessment approach for composites by using the Lamb wave factorization method. The method utilizes both forward and back-scattering waves to visualize 2D defects through solving the inverse scattering problem. The detection area is sampled into numerous points and the pixel values are determined through calculating the corresponding indicator function. By visualizing the area using all the pixel values, the defect image can be obtained. Experimental results on different 2D defects validate the effectiveness and accuracy of the proposed method for damage assessment in composite laminates.
COMPOSITE STRUCTURES
(2023)
Review
Engineering, Aerospace
Leandro Maio, Paul Fromme
Summary: The increasing use of composite materials in aerospace applications has led to the need for quantitative analysis methods. Ultrasonic guided waves are a physical approach for nondestructive evaluation and structural health monitoring, but their behavior can be complicated by material anisotropy, complex geometries, and defects. Computational models of ultrasonic wave propagation in composites can aid in designing practical hardware, software, and methodologies for accurate and reliable inspection methods.
PROGRESS IN AEROSPACE SCIENCES
(2022)
Article
Mechanics
Rosalin Sahoo, N. Grover, B. N. Singh
Summary: This study investigates the random free vibration response of laminated composite and sandwich plates using inverse hyperbolic zigzag theory, considering uncertainties in system parameters and obtaining second-order statistics of natural frequency. The results include mean and standard deviations of natural frequency for different variations in span-to-thickness ratios, geometric parameters, stacking sequence, and boundary conditions, ensuring the evaluated results by comparing with existing literature and Monte Carlo simulation results.
ARCHIVE OF APPLIED MECHANICS
(2021)
Article
Materials Science, Multidisciplinary
Da Cui, Daokui Li, Shiming Zhou, Anfeng Zhou, Xuan Zhou
Summary: This paper establishes a trapezoidal laminate model of composite materials and solves the bending problem of trapezoidal laminates using the Kantorovich method and the principle of minimum potential energy. The accuracy of the analytical solution is verified by the finite element method, and a multi-objective optimal design of bending-twisting coupled trapezoidal laminates is realized using the Differential Evolution algorithm. The hygrothermal stability of laminates is also verified by the finite element method, and the robustness analysis of the bending-twisting coupling effect of laminate is conducted based on the Monte Carlo method to verify the feasibility and reliability of the design scheme.
MATHEMATICS AND MECHANICS OF SOLIDS
(2021)
Article
Mechanics
Sergio Cantero-Chinchilla, Muhammad Khalid Malik, Dimitrios Chronopoulos, Juan Chiachio
Summary: This paper proposes a physics-based Bayesian framework for localizing and identifying damage in composite beam structures using ultrasonic guided-waves. The methodology efficiently enables the localization and identification of damage without the need for baseline comparison or further transformation, hence reducing additional sources of uncertainty. Experimental results demonstrate the effectiveness and efficiency of the proposed approach in reconstructing and identifying different types of damage at a relatively low computational cost.
COMPOSITE STRUCTURES
(2021)
Article
Computer Science, Artificial Intelligence
Wei Li, John C. Schotland, Yang Yang, Yimin Zhong
Summary: The study presents a method to reconstruct the electrical current density inside a conducting medium from acoustically modulated boundary measurements of the electric potential with Lipschitz stability. Numerical simulations were performed to illustrate the analytical results, including exploring the partial data setting when measurements are taken only on part of the boundary.
SIAM JOURNAL ON IMAGING SCIENCES
(2021)
Article
Engineering, Multidisciplinary
J. M. Winter, R. Abaidi, J. W. J. Kaiser, S. Adami, N. A. Adams
Summary: In this work, the authors propose an efficient solution to the inverse Stefan problem using multi-fidelity Bayesian optimization. They construct a multi-fidelity Gaussian process surrogate model by combining low-fidelity estimates with high-fidelity measurements. The proposed method improves the stability of the optimization procedure by reformulating the target function as a composite function. It demonstrates superior convergence properties compared to an approach based solely on high-fidelity measurements.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Mathematics, Applied
Jan Bohr
Summary: This note discusses a finite dimensional statistical model for the Calderon problem with piecewise constant conductivities. It demonstrates that the injectivity of the forward map and its linearization are sufficient to establish the invertibility of the information operator, leading to a Bernstein-von-Mises theorem and optimality guarantees for Bayesian posterior means estimation.
Article
Computer Science, Artificial Intelligence
Teemu Sahlstrom, Tanja Tarvainen
Summary: There is a growing interest in using machine learning methods for inverse problems and imaging. However, most of the research has focused on image reconstruction problems, and there are limited studies on the complete solution of the inverse problem. In this study, we explore a machine learning-based approach for the Bayesian inverse problem of photoacoustic tomography. We propose a method for estimating the posterior distribution in photoacoustic tomography using a variational autoencoder, and evaluate it through numerical simulations and comparison with a Bayesian approach for solving the inverse problem.
SIAM JOURNAL ON IMAGING SCIENCES
(2023)
Review
Engineering, Aerospace
V Lopresto, A. Langella, V Pagliarulo, I Papa
Summary: This manuscript provides an overview of low-velocity impact behavior of composite materials under different temperature conditions by comparing results of various fiber-matrix combinations and reviewing the impact behavior and damage evolution of marine and aerospace composites. Experimental impact tests were conducted using a modular falling weight tower, testing complete penetration at different impact energy levels. Different Non Destructive Techniques (NDT) were tested for detecting and evaluating barely-visible and invisible impact damage on composite laminates.
PROGRESS IN AEROSPACE SCIENCES
(2022)
Article
Thermodynamics
Nan Cao, Xiang Luo, Hui Tang
Summary: This paper presents a Bayesian method for calculating heat transfer in gas turbine engines based on simulated temperature measurements, reducing the uncertainties in the inverse problem. The results show that the Bayesian method offers better accuracy, stability, and robustness compared to traditional curve-fitting methods.
APPLIED THERMAL ENGINEERING
(2022)
Article
Mathematics, Applied
Dijana Mosic, Predrag S. Stanimirovic, Vasilios N. Katsikis
Summary: This paper introduces the definition of weighted composite outer inverses and related concepts, explores their basic properties and characteristics, and provides general solutions and numerical examples.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Xin Wang, Yang Zeng, Hu Wang, Yong Cai, Enying Li, Guangyao Li
Summary: This paper proposes a data-driven approximate Bayesian computation (ABC) inverse method for quantifying the uncertainties of fiber path parameters in variable stiffness composite laminates (VSCL). The novelty lies in using an auto-encoder to extract feature vectors of the high-dimensional physical field and constructing the mapping between fiber path parameters and feature vectors using back-propagation neural network. Additionally, a hybrid adaptive nested sampling strategy is introduced by introducing differential operation to accelerate the sampling process of posterior distribution. Two engineering examples are used to verify the feasibility of the proposed method.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Manufacturing
T. Khan, M. S. Irfan, W. J. Cantwell, R. Umer
Summary: Pre-cracked carbon fiber reinforced composite laminates were manufactured and repaired using the vacuum assisted resin transfer molding process. The effects of healing parameters on fracture toughness were investigated using a factorial design of experiments. The results showed that joining temperature had the most significant influence on fracture toughness, followed by contact time. Optimizing the processing parameters can enhance fracture toughness.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2022)
Article
Mathematics, Applied
Barbara Kaltenbacher, William Rundell
Summary: This paper considers the attenuated Westervelt equation in pressure formulation and proposes various models with non-local operators to achieve attenuation, which provides power law damping instead of exponential damping in classical models. The goal is to recover the spatially dependent coefficient, the nonlinearity parameter kappa(x), in a nonlinear hyperbolic equation by using measured data on a subset of the domain or its boundary. The paper shows the injectivity of the linearized map from kappa to the measured data and develops Newton-type schemes for its recovery.
MATHEMATICS OF COMPUTATION
(2022)
Article
Automation & Control Systems
Juan Fernandez, Manuel Chiachio, Juan Chiachio, Rafael Munoz, Francisco Herrera
Summary: Modern machine learning algorithms perform well in various tasks but need to deal with uncertainty from different sources. A new gradient-free training algorithm based on Approximate Bayesian Computation is proposed, providing a flexible and fair representation of uncertainty.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Materials Science, Characterization & Testing
Mohammad Ali Fakih, Manuel Chiachio, Juan Chiachio, Samir Mustapha
Summary: This study proposes a novel structural health monitoring approach using a minimal LW sensor-actuator set-up for damage detection, localization, and assessment. The results show that damage of different sizes and locations can be successfully identified with a high level of resolution and with quantified uncertainty.
NDT & E INTERNATIONAL
(2022)
Article
Acoustics
Ali Aghaei, Nicolas Bochud, Giuseppe Rosi, Quentin Grossman, Davide Ruffoni, Salah Naili
Summary: This paper presents a model-based approach to study the interaction of ultrasound waves with homogeneous and heterogeneous additively manufactured samples, paving the way for characterizing and optimizing multi-material systems that display complex bioinspired features.
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
(2022)
Article
Acoustics
Max Gattin, Nicolas Bochud, Giuseppe Rosi, Quentin Grossman, Davide Ruffoni, Salah Naili
Summary: Photopolymer-based additive manufacturing has gained attention in acoustics for designing tissue-mimicking phantoms and ultrasound components. This study investigated the longitudinal and transverse bulk properties of photopolymer materials using a double through-transmission method. The results showed that these properties are sensitive to slight variations in the manufacturing process.
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
(2022)
Article
Automation & Control Systems
Morteza Moradi, Agnes Broer, Juan Chiachio, Rinze Benedictus, Theodoros H. Loutas, Dimitrios Zarouchas
Summary: In this study, a semi-supervised deep neural network is proposed to construct a health indicator (HI) by SHM data fusion. The acoustic emission method was used to monitor composite panels during fatigue loading, and extracted features were used to construct an intelligent HI. The results demonstrate that this method can improve the quality of HI.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Physics, Applied
J. Torres, G. Laloy-Borgna, G. Rus, S. Catheline
Summary: In the field of acoustics, the definition of a liquid medium becomes unclear when it contains polymer chains or surfactant aggregates. This study used dynamic elastography to investigate the liquid-solid phase transitions in such viscoelastic liquid media. By comparing the dominant shear modulus, the medium can be classified as solid or liquid. The studied medium, an aqueous solution of xanthan gum, demonstrated liquid-solid-liquid behavior with transition bands. Various rheological models were tested to predict the phase transition frequencies, and the Jeffreys model provided the best fit.
APPLIED PHYSICS LETTERS
(2023)
Article
Automation & Control Systems
Juan Fernandez, Juan Chiachio, Manuel Chiachio, Jose Barros, Matteo Corbetta
Summary: This manuscript proposes a physics-guided Bayesian neural network that combines Approximate Bayesian Computation training with physics-based models. The hybrid algorithm uses the laws of physics to overcome the lack of data and neural networks' flexibility to model the complexities of nature. By using approximate Bayesian computation as the learning engine, the algorithm achieves higher prediction accuracy and flexibility in quantifying uncertainty due to its gradient-free nature, lack of loss/likelihood function, and non-parametric weight formulation.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Civil
Enrique Hernandez-Montes, Maria L. Jalon, Ruben Rodriguez-Romero, Juan Chiachio, Victor Compan-Cardiel, Luisa Maria Gil-Martin
Summary: This paper proposes a reliable model based on Bayesian learning approach to identify the main parameters of a Finite Element (FE) model with quantified uncertainty using ambient vibration data. The approach integrates a parameterised computational model to automate the simulation process, and a real case study demonstrates its suitability and effectiveness.
ENGINEERING STRUCTURES
(2023)
Article
Chemistry, Analytical
Wen Wu, Sergio Cantero-Chinchilla, Wang-ji Yan, Manuel Chiachio Ruano, Rasa Remenyte-Prescott, Dimitrios Chronopoulos
Summary: This paper investigates defect detection and identification in aluminium joints using guided wave monitoring. It first performs guided wave testing on the scattering coefficient as a selected damage feature to prove its feasibility. A Bayesian framework is then presented for damage identification in three-dimensional joints with arbitrary shape and finite size, taking into account modelling and experimental uncertainties. The proposed approach adopts a hybrid wave and finite element approach (WFE) to predict scattering coefficients of different size defects in joints. It also leverages a kriging surrogate model and replaces WFE with a prediction equation in probabilistic inference to enhance computational efficiency. Numerical and experimental case studies are conducted to validate the damage identification scheme and investigate the impact of sensor location on the results.
Article
Engineering, Multidisciplinary
Yi-Chen Zhu, Sergio Cantero Chinchilla, Han Meng, Wang-Ji Yan, Dimitrios Chronopoulos
Summary: Resonant metamaterials have been widely studied in mechanical and acoustic engineering for their applications in sound and vibration control. However, the issue of local damage in resonating parts hinders their industrial application. This work presents a study on quantifying and identifying damaged oscillators in a resonant metamaterial using measured frequency response function (FRF) data. Both data-driven and physics-based methods are implemented and the impact of manufacturing-induced structural uncertainty is considered. The proposed methodologies provide probabilistic estimation indices for damage level and location.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Materials Science, Characterization & Testing
Sergio Cantero-Chinchilla, Anthony J. Croxford, Paul D. Wilcox
Summary: This paper proposes a data-driven framework for artefact suppression in non-destructive testing data. The framework involves two stages of dimensionality reduction using principal component analysis and an autoencoder. The proposed method effectively suppresses artefacts leading to good defect detection and characterisation performance in an ultrasonic phased-array imaging application.
NDT & E INTERNATIONAL
(2023)
Article
Acoustics
Jorge Torres, Antonio Callejas, Antonio Gomez, Guillermo Rus
Summary: This study proposed an optical micro-elastography technique using magnetic excitation to generate and track high frequency shear waves. The cutoff frequency of shear wave propagation was found to vary depending on the mechanical properties of the samples. By comparing the low frequency range with the high frequency range, it was observed that the relative errors for the viscosity parameter could reach 60% and could be higher with higher dispersive behavior. The proposed technique has important implications for the mechanical characterization of cell culture media.
Article
Engineering, Industrial
Juan Fernandez, Juan Chiachio, Jose Barros, Manuel Chiachio, Chetan S. Kulkarni
Summary: This manuscript proposes a new physics-guided Bayesian recurrent neural network, which combines the advantages of physics-based models, recurrent neural networks, and Bayesian methods. The algorithm significantly improves the accuracy in multistep-ahead forecasting, provides stability during multiple runs, and accurately quantifies uncertainty. The algorithm has been applied to fatigue in composites and accelerations in concrete buildings, with comparable accuracy to state-of-the-art recurrent neural networks.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Chemistry, Multidisciplinary
Majdi Al Shdifat, Maria L. Jalon, Esther Puertas, Juan Chiachio
Summary: This paper proposes a large-scale group decision-making methodology for selecting structural eco-materials based on sustainability criteria. The approach considers both the technical aspects of the materials and their impact on the United Nations' Sustainable Development Goals, using survey data for probabilistic assessment and ranking.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Mechanical
Xuanen Kan, Yanjun Lu, Fan Zhang, Weipeng Hu
Summary: A blade disk system is crucial for the energy conversion efficiency of turbomachinery, but differences between blades can result in localized vibration. This study develops an approximate symplectic method to simulate vibration localization in a mistuned bladed disk system and reveals the influences of initial positive pressure, contact angle, and surface roughness on the strength of vibration localization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zimeng Liu, Cheng Chang, Haodong Hu, Hui Ma, Kaigang Yuan, Xin Li, Xiaojian Zhao, Zhike Peng
Summary: Considering the calculation efficiency and accuracy of meshing characteristics of gear pair with tooth root crack fault, a parametric model of cracked spur gear is established by simplifying the crack propagation path. The LTCA method is used to calculate the time-varying meshing stiffness and transmission error, and the results are verified by finite element method. The study also proposes a crack area share index to measure the degree of crack fault and determines the application range of simplified crack propagation path.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Rongjian Sun, Conggan Ma, Nic Zhang, Chuyo Kaku, Yu Zhang, Qirui Hou
Summary: This paper proposes a novel forward calculation method (FCM) for calculating anisotropic material parameters (AMPs) of the motor stator assembly, considering structural discontinuities and composite material properties. The method is based on multi-scale theory and decouples the multi-scale equations to describe the equivalence and equivalence preconditions of AMPs of two scale models. The effectiveness of this method is verified by modal experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Zhang, Jiangcen Ke
Summary: This research introduces an intelligent scheduling system framework to optimize the ship lock schedule of the Three Gorges Hub. By analyzing navigational rules, operational characteristics, and existing problems, a mixed-integer nonlinear programming model is formulated with multiple objectives and constraints, and a hybrid intelligent algorithm is constructed for optimization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Jingjing He, Xizhong Wu, Xuefei Guan
Summary: A sensitivity and reliability enhanced ultrasonic method has been developed in this study to monitor and predict stress loss in pre-stressed multi-layer structures. The method leverages the potential breathing effect of porous cushion materials in the structures to increase the sensitivity of the signal feature to stress loss. Experimental investigations show that the proposed method offers improved accuracy, reliability, and sensitivity to stress change.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Benyamin Hosseiny, Jalal Amini, Hossein Aghababaei
Summary: This paper presents a method for monitoring sub-second or sub-minute displacements using GBSAR signals, which employs spectral estimation to achieve multi-dimensional target detection. It improves the processing of MIMO radar data and enables high-resolution fast displacement monitoring from GBSAR signals.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xianze Li, Hao Su, Ling Xiang, Qingtao Yao, Aijun Hu
Summary: This paper proposes a novel method for bearing fault identification, which can accurately identify faults with few samples under complex working conditions. The method is based on a Transformer meta-learning model, and the final result is determined by the weighted voting of multiple models.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaomeng Li, Yi Wang, Guangyao Zhang, Baoping Tang, Yi Qin
Summary: Inspired by chaos fractal theory and slowly varying damage dynamics theory, this paper proposes a new health monitoring indicator for vibration signals of rotating machinery, which can effectively monitor the mechanical condition under both cyclo-stationary and variable operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Wang, Songye Zhu
Summary: This paper extends the latching mechanism to vibration control to improve energy dissipation efficiency. An innovative semi-active latched mass damper (LMD) is proposed, and different latching control strategies are tested and evaluated. The latching control can optimize the phase lag between control force and structural response, and provide an innovative solution to improve damper effectiveness and develop adaptive semi-active dampers.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Menghao Ping, Xinyu Jia, Costas Papadimitriou, Xu Han, Chao Jiang, Wang-Ji Yan
Summary: Identification of non-Gaussian processes is a challenging task in engineering problems. This article presents an improved orthogonal series expansion method to convert the identification of non-Gaussian processes into a finite number of non-Gaussian coefficients. The uncertainty of these coefficients is quantified using polynomial chaos expansion. The proposed method is applicable to both stationary and nonstationary non-Gaussian processes and has been validated through simulated data and real-world applications.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Lei Li, Wei Yang, Dongfa Li, Jianxin Han, Wenming Zhang
Summary: The frequency locking phenomenon induced by modal coupling can effectively overcome the dependence of peak frequency on driving strength in nonlinear resonant systems and improve the stability of peak frequency. This study proposes the double frequencies locking phenomenon in a three degrees of freedom (3-DOF) magnetic coupled resonant system driven by piezoelectricity. Experimental and theoretical investigations confirm the occurrence of first frequency locking and the subsequent switching to second frequency locking with the increase of driving force. Furthermore, a mass sensing scheme for double analytes is proposed based on the double frequencies locking phenomenon.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Kai Ma, Jingtao Du, Yang Liu, Ximing Chen
Summary: This study explores the feasibility of using nonlinear energy sinks (NES) as replacements for traditional linear tuned mass dampers (TMD) in practical engineering applications, specifically in diesel engine crankshafts. The results show that NES provides better vibration attenuation for the crankshaft compared to TMD under different operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Wentao Xu, Li Cheng, Shuaihao Lei, Lei Yu, Weixuan Jiao
Summary: In this study, a high-precision hydraulic mechanical stand and a vertical mixed-flow pumping station device were used to conduct research on cavitation signals of mixed-flow pumps. By analyzing the water pressure pulsation signal, it was found that the power spectrum density method is more sensitive and capable of extracting characteristics compared to traditional time-frequency domain analysis. This has significant implications for the identification and prevention of cavitation in mixed-flow pump machinery.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaodong Chen, Kang Tai, Huifeng Tan, Zhimin Xie
Summary: This paper addresses the issue of parasitic motion in microgripper jaws and its impact on clamping accuracy, and proposes a symmetrically stressed parallelogram mechanism as a solution. Through mechanical modeling and experimental validation, the effectiveness of this method is demonstrated.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zhifeng Shi, Gang Zhang, Jing Liu, Xinbin Li, Yajun Xu, Changfeng Yan
Summary: This study provides useful guidance for early bearing fault detection and diagnosis by investigating the effects of crack inclination and propagation direction on the vibration characteristics of bearings.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
