Modes Of Shape Variation Research Articles

Numerical Simulation of Added Mass Effects on a Hydrofoil in Cavitating Flow Using Acoustic Fluid–Structure Interaction

A fluid-structure interaction system has been solved using the coupled acoustic structural finite element method to simplify the cavitating flow conditions around a hydrofoil. The modes of vibration and the added mass effects have been numerically simulated for various flow conditions including leading edge attached partial cavitation on a 2D NACA0009 hydrofoil. The hydrofoil has been first simulated surrounded by only air and by only water. Then, partial cavities with different lengths have been modeled as pure vapor fluid domains surrounded by the corresponding water and solid domains. The obtained numerical added mass coefficients and mode shapes are in good agreement with the experimental data available for the same conditions. The study confirms that the fluid added mass effect decreases with the cavitation surface ratio and with the thickness of the cavitation sheet. Moreover, the simulations also predict slight mode shape variations due to cavitation that have also been detected in the experiments. Finally, the effects of changes in cavity location have been evaluated with the previously validated model.

Damage detection in railway bridges using Machine Learning: application to a historic structure

This paper presents a method that uses machine learning to detect and localize damage in railway bridges. Results of the method application to a historical bridge are presented and used to validate the proposed algorithm.For the application of this technique, both air temperature and deck accelerations data, measured under railway traffic at several locations on the bridge, are needed. The method consists of four stages: (1) collection of such data in both reference condition (i.e. when the state of preservation of the structure is known) and current one; (2) pre-processing of acceleration time histories aimed at extracting characteristics of the crossing train (i.e. running direction, speed and number of axles); (3) training of Artificial Neural Networks and Gaussian Processes using data collected in reference condition and (4) health classification of the bridge in current condition through the comparison between predicted and measured responses. During stage 3, a set of neural networks is trained to predict deck accelerations under every environmental and operational condition (i.e. air temperature and crossing vehicle characteristics, respectively) assuming the reference state of preservation. Then, in stage 4, the current response is compared with accelerations predicted under current environmental and operational conditions. Changes in the behavior of the structure due to damage are thus detected as a discrepancy between predicted and measured responses.The application of the proposed technique to data collected on San Michele Bridge (1889), in Northern Italy, has shown good agreement with results from previous studies based on mode shape variation. This shows the potential and confirms the possibility of applying the proposed technique to real bridges. This method can thus be used to detect anomalous responses that can be flagged as possible damage as well as give an indication of the location of the decayed structural region.

Modal Response‐Based Visual System Identification and Model Updating Methods for Building Structures

AbstractThis article proposes a new system identification (SI) method using the modal responses obtained from the dynamic responses of a structure for estimating modal parameters. Since the proposed SI method visually extracts the mode shape of a structure through the plotting of modal responses based on measured data points, the complex calculation process for the correlation and the decomposition for vibration measurements required in SI methods can be avoided. Also, without dependence on configurations of SI methods inducing variations of modal parameters, mode shapes and modal damping ratios can be stably extracted through direct implementation of modal response. To verify the feasibility of the proposed method, the modal parameters of a shear frame were extracted from modal displacement data obtained from a vibration test, and the results were compared with those obtained from the existing frequency domain SI method. The proposed method introduces the maximum modal response ratio of each mode computed by modal displacement data, and from this, the contribution of each mode and each measured location to the overall structural response is indirectly evaluated. Moreover, this article proposes a model updating method establishing the error functions based on the differences between the analytical model and measurement for the natural frequencies and the modal responses reflecting both mode shape and modal contribution. The validity of the proposed method is verified through the response prediction and modal contributions of the models obtained from model updating based on dynamic displacement from a shaking table test for a shear‐type test frame.

Bone shape difference between control and osteochondral defect groups of the ankle joint

The etiology of osteochondral defects (OCDs), for which the ankle (talocrural) joint is one of the common sites, is not yet fully understood. In this study, we hypothesized that bone shape plays a role in development of OCDs. Therefore, we quantitatively compared the morphology of the talus and the distal tibia between an OCD group and a control group. The shape variations of the talus and distal tibia were described separately by constructing two statistical shape models (SSMs) based on the segmentation of the bones from ankle computed tomography (CT) scans obtained from control (i.e., 35 CT scans) and OCD (i.e., 37 CT scans) groups. The first five modes of shape variation for the SSM corresponding to each bone were statistically compared between control and OCD groups using an analysis of variance (ANOVA) corrected with the Bonferroni for multiple comparisons. The first five modes of variation in the SSMs respectively represented 49% and 40% of the total variance of talus and tibia. Less than 5% of the variance per mode was described by the higher modes. Mode 5 of the talus (P=0.004) primarily describing changes in the vertical neck angle and Mode 1 of the tibia (P<0.0001) representing variations at the medial malleolus, showed statistically significant difference between the control and OCD groups. Shape differences exist between control and OCD groups. This indicates that a geometry modulated biomechanical behavior of the talocrural joint may be a risk factor for OCD.

Learning Category-Specific Deformable 3D Models for Object Reconstruction.

We address the problem of fully automatic object localization and reconstruction from a single image. This is both a very challenging and very important problem which has, until recently, received limited attention due to difficulties in segmenting objects and predicting their poses. Here we leverage recent advances in learning convolutional networks for object detection and segmentation and introduce a complementary network for the task of camera viewpoint prediction. These predictors are very powerful, but still not perfect given the stringent requirements of shape reconstruction. Our main contribution is a new class of deformable 3D models that can be robustly fitted to images based on noisy pose and silhouette estimates computed upstream and that can be learned directly from 2D annotations available in object detection datasets. Our models capture top-down information about the main global modes of shape variation within a class providing a "low-frequency" shape. In order to capture fine instance-specific shape details, we fuse it with a high-frequency component recovered from shading cues. A comprehensive quantitative analysis and ablation study on the PASCAL 3D+ dataset validates the approach as we show fully automatic reconstructions on PASCAL VOC as well as large improvements on the task of viewpoint prediction.

Automatic Segmentation of Wrist Bones in CT Using a Statistical Wrist Shape + Pose Model.

Segmentation of the wrist bones in CT images has been frequently used in different clinical applications including arthritis evaluation, bone age assessment and image-guided interventions. The major challenges include non-uniformity and spongy textures of the bone tissue as well as narrow inter-bone spaces. In this work, we propose an automatic wrist bone segmentation technique for CT images based on a statistical model that captures the shape and pose variations of the wrist joint across 60 example wrists at nine different wrist positions. To establish the correspondences across the training shapes at neutral positions, the wrist bone surfaces are jointly aligned using a group-wise registration framework based on a Gaussian Mixture Model. Principal component analysis is then used to determine the major modes of shape variations. The variations in poses not only across the population but also across different wrist positions are incorporated in two pose models. An intra-subject pose model is developed by utilizing the similarity transforms at all wrist positions across the population. Further, an inter-subject pose model is used to model the pose variations across different wrist positions. For segmentation of the wrist bones in CT images, the developed model is registered to the edge point cloud extracted from the CT volume through an expectation maximization based probabilistic approach. Residual registration errors are corrected by application of a non-rigid registration technique. We validate the proposed segmentation method by registering the wrist model to a total of 66 unseen CT volumes of average voxel size of 0.38 mm. We report a mean surface distance error of 0.33 mm and a mean Jaccard index of 0.86.

Vibration Response Analysis of Last Stage LP Turbine Blades for Variable Size of Crack in Root

This paper is intended to find the variation in vibration response of blades with the crack size of fir tree root free standing blades. Generation of crack in blade root causes the loss of stiffness in the vicinity of blade root. It results in shifting of natural frequencies and redistribution of dynamic and static stress in the blade root which may cause failure of the blade. A 3D finite element model of a blade and its fir-tree roots has been analyzed. Results of FEM study are validated by experimental results of cracked blades. Finally the variation in natural frequency and mode shapes for different sizes cracked blades are studied.

Analysis of pediatric airway morphology using statistical shape modeling.

Traditional studies of airway morphology typically focus on individual measurements or relatively simple lumped summary statistics. The purpose of this work was to use statistical shape modeling (SSM) to synthesize a skeleton model of the large bronchi of the pediatric airway tree and to test for overall airway shape differences between two populations. Airway tree anatomy was segmented from volumetric chest computed tomography of 20 control subjects and 20 subjects with cystic fibrosis (CF). Airway centerlines, particularly bifurcation points, provide landmarks for SSM. Multivariate linear and logistic regression was used to examine the relationships between airway shape variation, subject size, and disease state. Leave-one-out cross-validation was performed to test the ability to detect shape differences between control and CF groups. Simulation experiments, using tree shapes with known size and shape variations, were performed as a technical validation. Models were successfully created using SSM methods. Simulations demonstrated that the analysis process can detect shape differences between groups. In clinical data, CF status was discriminated with good accuracy (precision=0.7, recall=0.7) in leave-one-out cross-validation. Logistic regression modeling using all subjects showed a good fit (ROC AUC=0.85) and revealed significant differences in SSM parameters between control and CF groups. The largest mode of shape variation was highly correlated with subject size (R=0.95, p<0.001). SSM methodology can be applied to identify shape differences in the airway between two populations. This method suggests that subtle shape differences exist between the CF airway and disease control.

Identification of dominant modes in random dynamical and aeroelastic systems

Identification of dominant modes is an important step in studying linearly vibrating systems, including flow-induced vibrations. In the presence of uncertainty, when some of the system parameters and the external excitation are modeled as random quantities, this step becomes more difficult. This work is aimed at giving a systematic treatment to this end. The ability to capture the time-averaged kinetic energy is chosen as the primary criterion for selection of modes. Accordingly, a methodology is proposed based on the overlap of probability density functions (pdf) of the natural and excitation frequencies, proximity of the natural frequencies of the mean or baseline system, modal participation factor, and stochastic variation of mode shapes in terms of the modes of the baseline system — termed here as statistical modal overlapping. The probabilistic descriptors of the natural frequencies and mode shapes are found by solving a random eigenvalue problem. Three distinct vibration scenarios are considered: (i) undamped and damped free vibrations of a bladed disk assembly, (ii) forced vibration of a building, and (iii) flutter of a bridge model. Through numerical studies, it is observed that the proposed methodology gives an accurate selection of modes.

Analysis of the human osseous nasal shape--population differences and sexual dimorphism.

In this study, the shape of the outer osseous nose in a German and a Chinese sample is analyzed using a dense set of semi-landmarks. Shape differences related to population and sex as well as directional and fluctuating asymmetry were statistically evaluated and also visualized. Shape differences in the bony nose were investigated between a large sample of CT scans of German (140 ♀, 127 ♂) and Chinese (135 ♀, 132 ♂) crania. We used semi-automatic methods to represent the shape of this region as a dense point-cloud, consisting of 370 three-dimensional bilateral coordinates. Both the symmetric and asymmetric modes of shape variation were addressed. Strong differences in nasal shape were found between the two populations, while sex was found to play a minor role in explaining the observed shape variation. The expression of sexual dimorphism was similar in both populations. Differences attributed to population affinity and to sexual dimorphism were both found to affect the shape of the ossa nasalia and the projection of the spina nasalis. The correlation with population/sex was weak for directional asymmetry, but strong for fluctuating asymmetry. The nasal region is more asymmetric in Germans than in Chinese, with males displaying more asymmetry than females in both populations. While the bony nose is well suited for predicting population affinity, regarding the populations under investigation, its value for sexing unknown individuals is rather moderate. The similar expression of sexual dimorphism in those otherwise very dissimilar populations indicates common factors responsible for these differences.

Modal response of a computational vocal fold model with a substrate layer of adipose tissue.

This study demonstrates the effect of a substrate layer of adipose tissue on the modal response of the vocal folds, and hence, on the mechanics of voice production. Modal analysis is performed on the vocal fold structure with a lateral layer of adipose tissue. A finite element model is employed, and the first six mode shapes and modal frequencies are studied. The results show significant changes in modal frequencies and substantial variation in mode shapes depending on the strain rate of the adipose tissue. These findings highlight the importance of considering adipose tissue in computational vocal fold modeling.

An Experimental and FEM Modal Analysis of Cracked and Normal Steam Turbine Blade

This work concerns with comparative study of the model analysis of steam turbine blade with the analytical method and Experimental Method. In any steam turbine the last stage blades are most prone for the failure due to severe dynamic conditions of loading. NFT of these blades in lab conditions is mandatory to detune these blades. First the modal analysis of last stage blade is carried out with the help of FEM techniques then the blade is tested in NFT lab and the natural frequency calculated by both the methods is compared. After the validation of model through experimental results the similar study is also carried out for a cracked blade. Finally the variation in natural frequency and mode shapes for cracked and un-cracked blade is studied.

Structural-change localization and monitoring through a perturbation-based inverse problem.

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

Atlas-based quantification of cardiac remodeling due to myocardial infarction.

Myocardial infarction leads to changes in the geometry (remodeling) of the left ventricle (LV) of the heart. The degree and type of remodeling provides important diagnostic information for the therapeutic management of ischemic heart disease. In this paper, we present a novel analysis framework for characterizing remodeling after myocardial infarction, using LV shape descriptors derived from atlas-based shape models. Cardiac magnetic resonance images from 300 patients with myocardial infarction and 1991 asymptomatic volunteers were obtained from the Cardiac Atlas Project. Finite element models were customized to the spatio-temporal shape and function of each case using guide-point modeling. Principal component analysis was applied to the shape models to derive modes of shape variation across all cases. A logistic regression analysis was performed to determine the modes of shape variation most associated with myocardial infarction. Goodness of fit results obtained from end-diastolic and end-systolic shapes were compared against the traditional clinical indices of remodeling: end-diastolic volume, end-systolic volume and LV mass. The combination of end-diastolic and end-systolic shape parameter analysis achieved the lowest deviance, Akaike information criterion and Bayesian information criterion, and the highest area under the receiver operating characteristic curve. Therefore, our framework quantitatively characterized remodeling features associated with myocardial infarction, better than current measures. These features enable quantification of the amount of remodeling, the progression of disease over time, and the effect of treatments designed to reverse remodeling effects.

Application of Elliptic Fourier analysis to describe the lamina cribrosa shape with age and intraocular pressure

The lamina cribrosa (LC) plays an important biomechanical role in the optic nerve head (ONH). We developed a statistical shape model of the LC and tested if the shape varies with age or IOP. The ONHs of 18 donor eyes (47–91 years, mean 76 years) fixed at either 5 or 50 mmHg of IOP were sectioned, stained, and imaged under a microscope. A 3D model of each ONH was reconstructed and the outline of the vertical sagittal section closest to the geometric center of the LC extracted. The outline shape was described using Elliptic Fourier analysis, and principal components analysis (PCA) employed to identify the primary modes of LC shape variation. Linear mixed effect models were used to determine if the shape measurements were associated with age or IOP. The analysis revealed several modes of shape variation: thickness and depth directly (PC 1), or inversely (PC 2) related, and superior–inferior asymmetry (PC 3). Only PC 3 was associated with IOP, with higher IOP correlating with greater curvature of the LC superiorly compared to inferiorly. Our analysis enabled a concise and complete characterization of LC shape, revealing variations without defining them a priori. No association between LC shape and age was found for the relatively old population studied. Superior–inferior asymmetry of LC shape was associated with IOP, with more asymmetry at higher IOP. Increased IOP was not associated with LC thickness or depth.

Human L3L4 intervertebral disc mean 3D shape, modes of variation, and their relationship to degeneration

Intervertebral disc mechanics are affected by both disc shape and disc degeneration, which in turn each affect the other; disc mechanics additionally have a role in the etiology of disc degeneration. Finite element analysis (FEA) is a favored tool to investigate these relationships, but limited data for intervertebral disc 3D shape has forced the use of simplified or single-subject geometries, with the effect of inter-individual shape variation investigated only in specialized studies. Similarly, most data on disc shape variation with degeneration is based on 2D mid-sagittal images, which incompletely define 3D shape changes. Therefore, the objective of this study was to quantify inter-individual disc shape variation in 3D, classify this variation into independently-occurring modes using a statistical shape model, and identify correlations between disc shape and degeneration. Three-dimensional disc shapes were obtained from MRI of 13 human male cadaver L3L4 discs. An average disc shape and four major modes of shape variation (representing 90% of the variance) were identified. The first mode represented disc axial area and was significantly correlated to degeneration (R2=0.44), indicating larger axial area in degenerate discs. Disc height variation occurred in three distinct modes, each also involving non-height variation. The statistical shape model provides an average L3L4 disc shape for FEA that is fully defined in 3D, and makes it convenient to generate a set of shapes with which to represent aggregate inter-individual variation. Degeneration grade-specific shapes can also be generated. To facilitate application, the model is included in this paper׳s supplemental content.

Small signal stability analysis of power systems with DFIG based wind power penetration

With the increasing penetration of wind power generation into the power system, it is required to comprehensively analyze its impact on power system stability. The present paper analyzes the impact of wind power penetration by doubly fed induction generator (DFIG) on power system oscillations for two-area interconnected power system. The aspects of inter-area oscillations which may affect the operation and behaviour of the power systems are analyzed with and without the wind power penetration. Eigenvalue analysis is carried out to investigate the small signal behaviour of the test system and the participation factors have been determined to identify the participation of the states in the variation of different mode shapes. The penetration of DFIG in a test system results in an oscillatory instability, which can be stabilized with the coordinated operation of automatic voltage regulator (AVR) and power system stabilizer (PSS) equipped on synchronous generators. Also, the variations in oscillatory modes are presented to observe the damping performance of the test system at different wind power penetration level.

Free Vibration and Material Mechanical Properties Influence Based Frequency and Mode Shape Analysis of Transmission Gearbox Casing

The main objective of this research work is to study the effect of mechanical properties of materials on natural frequency and mode shapes of heavy vehicle gearbox transmission casing. Material mechanical properties play an important role for evaluation of frequency, deformation, stress and strain. Four materials have different density and the origin of material is also different. Grey cast iron has damping property, structural steel has high density and rigidity, Al and Mg alloys have low density. Free vibration study was performed for the vibration response study of casing. Grey cast iron grade FG 260, Structural Steel, Al alloy and Mg Alloy materials were analyzed on the design and vibration index. The free vibration study of casing was performed using finite element simulation. The vibration response for all materials shows the variation of natural frequency (1002-3879) Hz and various vibrations mode shapes. The vibration responses for first twenty modes were studied. Solid Edge and Pro-E was used for CAD designing of transmission gearbox casing. FEA based ANSYS 14.5 is used for modal analysis. Fixed- fixed constraint based boundary condition was used by constraining the connecting bolts hole. The transmission casing is tightly mounted on vehicle frame using connecting bolts. Loose transmission casing causes heavy noise and vibration problem. The simulation results were compared with experiment results available in literature.

Association of Incident Symptomatic Hip Osteoarthritis With Differences in Hip Shape by Active Shape Modeling: The Johnston County Osteoarthritis Project

To investigate hip shape by active shape modeling (ASM) as a potential predictor of incident radiographic hip osteoarthritis (RHOA) and symptomatic hip osteoarthritis (SRHOA). All hips developing RHOA from baseline (Kellgren/Lawrence [K/L] grade 0/1) to mean 6-year followup (K/L grade ≥2, 190 hips) and 1:1 control hips (K/L grade 0/1 at both times, 192 hips) were included. Proximal femur shape was defined on baseline anteroposterior pelvis radiographs and submitted to ASM, producing a mean shape and continuous variables representing independent modes of shape variation. Mode scores (n = 14, explaining 95% of shape variance) were simultaneously included in logistic regression models with incident RHOA and SRHOA as dependent variables, adjusted for intraperson correlations, sex, race, body mass index (BMI), baseline K/L grade, and/or symptoms. We evaluated 382 hips from 342 individuals: 61% women and 83% white, with mean age 62 years and mean BMI 29 kg/m(2) . Several modes differed by sex and race, but no modes were associated with incident RHOA overall. Among men only, modes 1 and 2 were significantly associated (for a 1-SD decrease in mode 1 score: odds ratio [OR] 1.7 [95% confidence interval (95% CI) 1.1-2.5] and for a 1-SD increase in mode 2 score: OR 1.5 [95% CI 1.0-2.2]) with incident RHOA. A 1-SD decrease in mode 2 or 3 score increased the odds of SRHOA by 50%. This study confirms other reports that variations in proximal femur shape have a modest association with incident hip OA. The observation of proximal femur shape associations with hip symptoms requires further investigation.

Operational mode-shape normalisation with a structural modification for small and light structures

When dealing with small and light structures, difficulties occur when measuring the modal parameters. The resonant frequencies are usually relatively high and therefore a wide frequency range is needed for the measurement. Furthermore, the mass that is added to the structure by the sensors causes structural modifications. To overcome these difficulties, an improved method using an operational modal analysis instead of an experimental modal analysis is proposed in this study. It is derived from the sensitivity-based operational mode-shape normalisation with a consideration of the mode-shape variation. The measurement of the excitation force is not needed, because the operational modal analysis is used and only two simultaneous response measurements at an unknown excitation are required. The proposed method includes the cancellation of the added mass, resulting in mode shapes and resonant frequencies of the unmodified structure. The numerical and experimental results on small and light structures are compared with the results of the experimental modal analysis. The comparison shows that the proposed approach allows measurements over a wide frequency range and increases the accuracy of the results compared to the sensitivity-based operational mode-shape normalisation and also compared to the particular experimental modal analysis method that was used in this study. The advantages of the proposed method can be seen whenever the mass that is added to the structure by the accelerometer is not negligible and therefore a variation of the mode shapes occurs.