Search Results (19)

The structural modal parameter identification method can be classified into time-domain and frequency-domain methods. Practically, two types of methods are characterized by different advantages, and the estimated modal parameters are always subjected to statistical uncertainties due to measurement noise. In this work, an uncertainty-based fusion method for structural mode identification is proposed to merge the advantages of different methods. The extensively applied time-domain AutoRegressive (AR) and frequency-domain Left-Matrix Fraction (LMF) models are expressed in a unified parametric model. With this unified model, a generalized framework is developed to identify the modal parameters of structures and compute variances associated with modal parameter estimates. The final modal parameter estimates are computed as the inverse-variance weighted sum of the results identified from different methods. A numerical and an experimental example demonstrate that the proposed method can obtain reliable modal parameter estimates, substantially mitigating the occurrence of extremely large estimation errors. Furthermore, the fusion method demonstrates enhanced identification capabilities, effectively reducing the likelihood of missing structural modes. Full article

The dynamic mode decomposition serves as a useful tool for the coherent structure extraction of the complex flow fields with characteristic frequency identification, but the phase information of the flow modes is paid less attention to. In this study, phase information around the locally flexible membrane airfoil is quantitatively studied using dynamic mode decomposition (DMD) to unveil the physical mechanism of the lift improvement of the membrane airfoil. The flow over the airfoil at a low Reynolds number (Re = 5500) is computed parametrically across a range of angles of attack (AOA = 4°–14°) and membrane lengths (LM = 0.55c–0.70c) using a verified fluid–structure coupling framework. The lift enhancement is analyzed by the dynamic coherent patterns of the membrane airfoil flow fields, which are quantified by the DMD modal phase propagation. A downstream propagation pressure speed (DPP) on the upper surface is defined to quantify the propagation speed of the lagged maximal pressure in the flow separation zone. It is found that a faster DPP speed can induce more vortices. The correlation coefficient between the DPP speed and lift enhancement is above 0.85 at most cases, indicating the significant contribution of vortex evolution to aerodynamic performance. The DPP speed greatly impacts the retention time of dominant vortices on the upper surface, resulting in the lift enhancement. Full article

Strategically important objects, such as dams, tunnels, bridges, and others, require long-term structural health monitoring programs in order to preserve their structural integrity with minimal downtime, financial expenses, and increased safety for civilians. The current study focuses on developing a damage detection methodology that is applicable to the long-term monitoring of such structures. It is based on the identification of resonant frequencies from operational modal analysis, removing the effect of environmental factors on the resonant frequencies through support vector regression with optimized hyperparameters and, finally, classifying the global structural state as either healthy or damaged, utilizing the Mahalanobis distance. The novelty lies in two additional steps that supplement this procedure, namely, the nonlinear estimation of the relative effects of various environmental factors, such as temperature, humidity, and ambient loads on the resonant frequencies, and the selection of the most informative resonant frequency features using a non-parametric neighborhood component analysis algorithm. This methodology is validated on a wooden two-story truss structure with different artificial structural modifications that simulate damage in a non-destructive manner. It is found that, firstly, out of all environmental factors, temperature has a dominating decreasing effect on resonance frequencies, followed by humidity, wind speed, and precipitation. Secondly, the selection of only a handful of the most informative resonance frequency features not only reduces the feature space, but also increases the classification performance, albeit with a trade-off between false alarms and missed damage detection. The proposed approach effectively minimizes false alarms and ensures consistent damage detection under varying environmental conditions, offering tangible benefits for long-term SHM applications. Full article

In oncology, longitudinal biomarkers reflecting the patient’s status and disease evolution can offer reliable predictions of the patient’s response to treatment and prognosis. By leveraging clinical data in patients with advanced non-small-cell lung cancer receiving first-line chemotherapy, we aimed to develop a framework combining anticancer drug exposure, tumor dynamics (RECIST criteria), and C-reactive protein (CRP) concentrations, using nonlinear mixed-effects models, to evaluate and quantify by means of parametric time-to-event models the significance of early longitudinal predictors of progression-free survival (PFS) and overall survival (OS). Tumor dynamics was characterized by a tumor size (TS) model accounting for anticancer drug exposure and development of drug resistance. CRP concentrations over time were characterized by a turnover model. An x-fold change in TS from baseline linearly affected CRP production. CRP concentration at treatment cycle 3 (day 42) and the difference between CRP concentration at treatment cycles 3 and 2 were the strongest predictors of PFS and OS. Measuring longitudinal CRP allows for the monitoring of inflammatory levels and, along with its reduction across treatment cycles, presents a promising prognostic marker. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies allowing the timely identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and provide alternative treatment decisions. Full article

The seismic vulnerability assessment of existing structures is a well-known challenging task, due to a combination of several aspects. The use of analytical or finite element (FE) numerical models can offer robust support in this analysis but necessitates the accurate calibration of geometrical and mechanical input, with related uncertainties. In this paper, attention is focused on the identification of dynamic parameters, based on modal numerical analysis, of a 50-year-old, reinforced concrete, elevated water tank (EWT) characterised by a reservoir with a truncated cone shape. The structure is located in a high seismic region of northern Italy and presently necessitates retrofit plans to preserve its functionality. Based on the limited available experimental evidence and technical drawings, major efforts are spent for the numerical prediction of fundamental vibration modes and frequencies of the structure, which represent a first key step for seismic analyses, under various water-filling levels. To this aim, four different FE numerical strategies able to include both structural features and possible fluid–structure interaction (FSI) effects are developed. By progressively increasing the computational cost (and expected the accuracy of the solutions), FE models based on added-mass (M0 model), spring-mass (M1-DM or M1-DS models), or acoustic (M2 model) strategies are taken into account and combined with increasing detailing in geometrical description of the structure. Results from parametric modal analyses are discussed for the case-study EWT, in terms of computational cost, possible numerical limitations, accuracy of predicted frequencies/modal shapes, sensitivity to water-filling levels and operational configurations, with the support of several pieces of experimental evidence and consolidated analytical formulations for fundamental frequency estimations. Full article

The drive-by method has become a popular indirect approach for bridge damage inspection (BDI) because of its simplicity in deployment by evaluating the bridge health status solely via the vehicle dynamic response. Derived from the vehicle dynamic response, the recent proposed contact-point response involves no vibration signal with the vehicle frequency, bearing great potential for drive-by BDI. However, an appropriate methodology for the application of contact-point response in drive-by BDI remains lacking. The present study proposes a novel drive-by method, in which a new damage factor index, i.e., the characteristic wavelet coefficient (CWC), is established for bridge damage identification in an efficient and accurate manner. The CWC is obtained by analyzing the contact-point response via the continuous wavelet transform (CWT) and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) techniques. CEEMDAN is introduced to overcome the issue of modal aliasing and pseudo-frequency. First, the general framework of the proposed drive-by BDI method is introduced. Then, a demonstration case study is carried out to examine the effectiveness of the proposed method. Subsequently, a parametric study is carried out to explore the effects of several parameters on the performance of BDI including the scale factor, vehicle speed, environmental noise, and boundary effect. The results indicate that the proposed drive-by BDI method can better eliminate the mode mixing and pseudo-frequency problems during the extraction of the CWC, compared with the traditional ensemble empirical mode decomposition method. The extracted CWC curve is smooth, convenient for damage inspection, and has strong anti-noise performance. After adding white noise with a signal-to-noise ratio of 20, a bridge girder with a damage severity of 20% can be identified successfully. In addition, the selection of the scale factor is critical for bridge damage inspection based on the extracted CWC. The effective scale factor of the CWC extracted using the proposed method has a wide range, which improves the inspection efficiency. Finally, a low vehicle speed is beneficial to alleviate the adverse effect of the boundary effect on the damage inspection of bridge girder ends. Full article

As a critical component of rotating machinery, rolling bearings are essential for the safe and efficient operation of machinery. Sudden faults of rolling bearings can lead to unscheduled downtime and substantial economic costs. Therefore, diagnosing and identifying the equipment status is essential for ensuring the operation and decreasing the additional maintenance costs of the machines. However, extracting the features from the early bearing fault signals is challenging under background noise interference. With the purpose of solving the above problem, we propose an integrated rolling bearing fault diagnosis model based on the improved grey wolf optimized variational modal decomposition (IGVMD) and an improved 1DCNN with a parametric rectified linear unit (PReLU). Firstly, an improved grey wolf optimizer (IGWO) with the fitness function, the minimum envelope entropy, is designed for adaptively searching the optimal parameter values of the VMD model. The performance of the basic grey wolf optimizer (GWO) algorithm by introducing three improvement strategies, the non-linear convergence factor adjustment strategy, the grey wolf adaptive position update strategy, and the Levy flight strategy in the IGWO algorithm, is improved. Then, an improved 1DCNN model with the PReLU activation function is proposed, which extracts the bearing fault features, and a grid search to optimize the model parameters of the 1DCNN is introduced. Finally, the effectiveness of the proposed model is demonstrated well by employing two experimental datasets. The preliminary comparative results of the average identification accuracy in the proposed method in two datasets are 99.98% and 99.50%, respectively, suggesting that this proposed method has a relatively higher recognition accuracy and application values. Full article

The mine hoisting headframe is a typical towering truss structure, and its damage is complicated after long-term service, which affects the safety of the structure. To achieve rapid identification of corrosion damage on a towering steel headframe, the degradation law of headframe under different damage was analyzed via parametric modeling method and verified via field measurement. The results show that the influence range of element corrosion damage is localized, and a 50% corrosion rate of the bottom column will lead to a collapse risk of the headframe. After that, the single index method, of superimposed curvature mode difference and modal flexibility difference curvature, is used to identify corrosion damage of headframe column. The results indicate that the single index method is susceptible to interference in the undamaged position and leads to error identification. The improved multi-index data fusion damage identification method based on D-S evidence matrix is proposed, through which the multi-position damages in headframe structure can be identified accurately. Compared to the one-stage fusion method, the improved two-stage fusion method is more robust, with an increase of 42.9% in identification accuracy, and a reduction of 75% in misjudgment. Full article

System identification proves in general to be very efficient in the extraction of modal parameters of a structure under ambient vibrations. However, great difficulties can arise in the case of structures composed of many connected bodies, whose mutual interaction may lead to a multitude of coupled modes. In the present work, a methodology to approach the identification of interconnected diaphragmatic structures, exploiting a simplified analytical model, is proposed. Specifically, a parametric analysis has been carried out on a numerical basis on the simplified model, i.e., a multiple spring–mass model. The results were then exploited to aid the identification of a significant case study, represented by the Pavilion V, designed by Riccardo Morandi as a hypogeum hall of the Turin Exhibition Center. The structure is indeed composed of three blocks separated by expansion joints, whose characteristics are unknown. As the main result, light was shed on the contribution of the stiffness of the joints to the global dynamic behavior of structures composed of interacting diaphragms, and, in particular, on the effectiveness of the joints of Pavilion V. Full article

Vented brake rotors used in an automobile behave similarly to centrifugal fans, drawing cool air from the inboard side, passing it through the disc vents, and exhausting it from the periphery. A vented brake rotor with a better heat dispersing ability is often superior to a solid rotor, in both thermal performance and brake efficiency. In this research, a fully parameterized model for a ventilated brake rotor is created using the ANSYS Parametric Design Language, to uniquely define the rotor’s geometry. With this parameterized model, two structural optimization cases are studied in this paper. The first one investigated is a modal frequency separation problem: The frequency differences in a tangential mode sandwiched between two nodal diameter modes of the brake rotor model are maximized. An automatic identification scheme for extracting correct mode orders is implemented in the program to track the correct modes during optimization. The second case is a thermal deformation problem: The distortion on the frictional surfaces of the rotor loaded with heat flux generated during the braking process is minimized. The optimization results show that a brake rotor design with a thinner outboard disc and a thicker inboard disc provides a great choice for rotor coning reduction. Full article

The present paper is a study of output-only modal estimation based on the stochastic subspace identification technique (SSI) to avoid the restrictions of well-controlled laboratory conditions when performing experimental modal analysis and aims to develop the appropriate algorithms for ambient modal estimation. The conventional SSI technique, including two types of covariance-driven and data-driven algorithms, is employed for parametric identification of a system subjected to stationary white excitation. By introducing the procedure of solving the system matrix in SSI-COV in conjunction with SSI-DATA, the SSI technique can be efficiently performed without using the original large-dimension data matrix, through the singular value decomposition of the improved projection matrix. In addition, the computational efficiency of the SSI technique is also improved by extracting two predictive-state matrixes with recursive relationship from the same original predictive-state matrix, and then omitting the step of reevaluating the predictive-state matrix at the next-time moment. Numerical simulations and experimental verification illustrate and confirm that the present method can accurately implement modal estimation from stationary response data only. Full article

Steel storage racks are widely used in logistics for storing materials and goods. Rack design is carried out by adopting the so-called design-assisted-by-testing procedure. In particular, experimental analyses must be carried out by rack producers on the key structural components in order to adopt the design approach proposed for the more traditional carpentry frames. For existing racks, i.e., those in-service for decades, it is required to evaluate the load carrying capacity in accordance with the design provisions currently in use. The main problem in several cases should be the appraisal of the key component performance, owing to the impossibility to obtain specimens from in-service racks without reduction or interruption of the logistic flows. To overcome this problem, a quite innovative procedure for the identification of the structural unknowns of existing racks has been proposed in the paper. The method is based on in-situ modal identification tests combined with extensive numerical analyses. To develop the procedure, cheap measurement systems are required, and they could be immediately applied to existing racks. A real case study is discussed, showing the efficiency of the procedure in the evaluation of the effective elastic stiffness of beam-to-column joints and base plate connections, that are parameters which remarkably affect the rack performance. The structural unknowns have been determined based on four sets of modal tests (two configurations on the longitudinal direction and two in the transversal direction) plus 9079 iterative structural analyses. The results obtained were then directly compared with experimental component tests, showing differences lower than 9%. Full article

Scientifically sound methods are essential to estimate the survival of trees, as they can substantially support sustainable management of natural forest resources. Tree mortality assessments have mainly been based on forest inventories and are mostly limited to planted forests; few studies have conducted age-based survival analyses in natural forests. We performed survival analyses of individual tree populations in natural forest stands to evaluate differences in the survival of two coniferous species (Abies sachalinensis (F. Schmidt) Mast. and Picea jezoensis var. microsperma) and all broad-leaved species. We used tree rings and census data from four preserved permanent plots in pan-mixed and sub-boreal natural forests obtained over 30 years (1989–2019). All living trees (diameter at breast height ≥ 5 cm in 1989) were targeted to identify tree ages using a Resistograph. Periodical tree age data, for a 10-year age class, were obtained during three consecutive observation periods. Mortality and recruitment changes were recorded to analyze multi-temporal age distributions and mean lifetimes. Non-parametric survival analyses revealed a multi-modal age distribution and exponential shapes. There were no significant differences among survival probabilities of species in different periods, except for broad-leaved species, which had longer mean lifetimes in each period than coniferous species. The estimated practical mean lifetime and diameter at breast height values of each coniferous and broad-leaved tree can be applied as an early identification system for trees likely to die to facilitate the Stand-based Silvicultural Management System of the University of Tokyo Hokkaido Forest. However, the survival probabilities estimated in this study should be used carefully in long-term forest dynamic predictions because the analysis did not include the effects of catastrophic disturbances, which might significantly influence forests. The mortality patterns and survival probabilities reported in this study are valuable for understanding the stand dynamics of natural forests associated with the mortality of individual tree populations. Full article

This paper describes the evaluation of a single output, online, and time domain modal parameters identification technique based on differential algebra and operational calculus. In addition, an analysis of the frequency response function (FRF) of the system is conducted in a specific set up, emulating its nominal or operational conditions to determine the influence of the non-linearities over the dynamic behavior of the system in those particular magnitudes of deformations; thus, this influence is quantified by a numerical index. This methodology is applied to a wind turbine blade submitted to wind tunnel experiments. The natural frequencies and modal damping ratios of six bending modes associated with the blade are estimated using real-time velocity measurements from one single point of the blade. A comparison with the usual impact hammer modal testing is performed to evaluate and establish the proposed approach’s main contributions. The developed modal parameter identification algorithms are implemented to run into a standard personal computer (PC) where the data acquisition system’s measurements are conditioned and processed. The results show the performance and the fast parametric estimation of the proposed algebraic identification approach. Full article

The paper presents the novel method of damage identification and quantification in beams using the Wigner-Ville distribution (WVD). The presented non-parametric method is characterized by high sensitivity to a local stiffness decrease due to the presence of damage, comparable with the sensitivity of the wavelet-based approaches, however the lack of selection of the parameters of the algorithm, like wavelet type and its order, and the possibility of reduction of the boundary effect make this method advantageous with respect to the mentioned wavelet-based approaches. Moreover, the direct relation between the energy density resulting from the application of WVD to modal rotations make it possible to quantify damage in terms of its width and depth. The results obtained for the numerical modal rotations of a beam presented in this paper, simulating the results of non-destructive testing achievable with the shearography non-destructive testing method, confirm high accuracy in localization of a damage as well as quantification of its dimensions. It was shown that the WVD-based method is suitable for detection of damage represented by the stiffness decrease of 1% and can be identified and quantified with a high precision. The presented results of quantification allowed extracting information on damage width and depth. Full article