Shape Deformation Research Articles

A Non-Rigid Three-Dimensional Image Reconstruction Algorithm Based on Deformable Shape Reliability

A Non-Rigid Three-Dimensional Image Reconstruction Algorithm Based on Deformable Shape Reliability

Shear force distribution mechanism of perfobond leiste connectors in joint between corrugated steel web and concrete top slab

Compared to composite bridges with flat steel webs (FSWs), the corrugation shape and significant shear deformation of the steel web in composite bridges with corrugated steel webs (CSWs) will influence the distribution and magnitude of the shear force of connectors in the joint between the steel web and concrete slab. However, these effects have not been considered in current design specifications, which may lead to unsafe designs. This paper investigates the shear force distribution mechanism of perfobond leiste (PBL) connectors in the joint between the CSW and concrete top slab in composite bridges with CSWs. The theoretical solution for the shear force of the joint per unit length is firstly derived based on the elastic bending theory considering the shear deformation of the CSW. Then, finite element simulations using hybrid models of solid and spring elements are conducted to further investigate the shear force distribution of PBL connectors and influencing parameters. The results show that the shear deformation of the CSW has a negligible effect on the shear force of the joint per unit length. In contrast to composite bridges with FSWs, the CSW induces sinusoidal variations in the shear force of PBL connectors, which leads to an increase in the shear force of partial PBL connectors. The amplification factor for the shear force increases with the wavelength of the CSW and the shear stiffness of the PBL connector, while it decreases with the increasing dimensions of the steel upper flange, perforated ribs, and hole spacing. Finally, a calculation formula and corresponding procedure are proposed for predicting the shear force of PBL connectors in the joint between the CSW and concrete top slab for composite bridges with CSWs.

Multi-stimuli responsive, shape deformation, and synergetic biomimetic actuator

Hydrogel actuators with controllable deformation and excellent biocompatibility are widely used in soft robot, valve, drug delivery and lenses. However, the stimulation response performance of existing hydrogel actuators mostly focuses on a single active layer, which greatly affects its driving performance and service life. In this work, we integrate temperature-responsive hydrogel (Poly (N-isopropyl acrylamide), PNIPAM) and pH-responsive hydrogel (polyacrylic acid, PAAc) into one system to fabricate a dual active layer composite hydrogel actuator with high performance. Based on the PAAc hydrogels achieving contract or expand at different pH values, the obtained actuator exhibits admirable bidirectional bending characteristics. In addition, the anisotropic bamboo sheet endows the hydrogel actuator with programmable 3 D complex deformation. Benefitting from the synergy and different responsiveness between the two active layers, the hydrogel actuator not only has multiple response performance, but also greatly improves its deformation degree and response speed. More importantly, these promising properties of the actuator have broad application prospects in the development of pattern design and intelligent switch. This work proposes a promising strategy for the structural design of hydrogel actuators with excellent performance, and encourages more exploration of the application range of the actuator.

Shape recovery behavior of polylactic acid/thermoplastic polyurethane polymer blends

Polylactic acid (PLA) and thermoplastic polyurethane (TPU)-based blends were prepared by twin-screw extruder and conventional injection molding (CIM) machine at various weight ratios of PLA/TPU, that is, 90/10, 80/20, and 70/30. The prepared blends were investigated for their shape memory properties by performing shape deformation and recovery experiments at various temperatures and bending angles. During the deformation process, TPU acted as a toughening agent that prevented the PLA/TPU blends from distortion. Hence, the temporary shape can be kept as the internal stress was stored in the blends. On heating above the glass transition (Tg) temperature of PLA, the deformed parts recovered their original shapes quickly along with the release of the stress. The prepared blends were found to exhibit significant shape memory properties at the TPU content of 10 wt%. The recovery rate was found to reach up to approximately 95%. Such shape memory polymers found fascinating applications in aerospace engineering, engineering plastics, biomedical implant materials, and textiles.

An AFM-based approach for quantification of guest particle deformation during mechano-fusion

During the mechano-fusion process for dry particle coating, (hetero)-aggregates are formed consisting of host particles coated by smaller guest particles. During this process, the latter are exposed to intense particle–particle interactions and particle–wall impacts, which lead to deformation of their original shape. These deformations on the nano- and microscale can heavily influence the effective macroscopic properties of the resulting coated particles. We present a method for quantification of shape deformation based on measurements acquired by atomic force microscopy and apply it to guest particles during mechano-fusion. The 3D shape of guest particles is reconstructed by means of an ellipsoidal fit. Using these reconstructed shapes, we quantify the degree of deformation by comparing the aspect ratios of the ellipsoidal fits before and after mechano-fusion. Such a quantification enhances the understanding of how process-related parameters influence geometric descriptors of involved particles, which in turn impacts overall macroscopic properties of the material.

Comparison and development of scanning electron microscope techniques for delicate plant tissues

Cell deformation often occurs during sample preparation and imaging with scanning electron microscope (SEM), especially with delicate samples, which influences the accuracy of the results. Here we investigate the influence of several preparation methods on cell deformation, using water content and tissue hardness as indicators to classify “delicate” samples of plant species. The degree of deformation in samples resulting from five preparation methods was measured at the tissue and single-cell levels, revealing that a cryo- and methanol-fixation produced lower degrees of tissue dimension deformation and better preservation of cell shape for delicate samples, while for harder tissues, other preparation methods for a dehydrated specimen are also suitable. Stability and image quality of delicate samples could be improved with the application of a cryo-protectant combined with a lower cryo-stage temperature, e.g. − 30 °C. We show that the sample stability under the beam was improved by combining larger sample size and cryo-stage application. Furthermore, the influence of adaxial and abaxial tissue surfaces, the accelerating voltage, and sputter coating time on sample stability and image quality was evaluated. Our study is valuable for artifact reduction and easy application of SEM.

An adaptive machine learning-based optimization method in the aerodynamic analysis of a finite wing under various cruise conditions

Conventional wing aerodynamic optimization processes can be time-consuming and imprecise due to the complexity of versatile flight missions. Plenty of existing literature has considered two-dimensional infinite airfoil optimization, while three-dimensional finite wing optimizations are subject to limited study because of high computational costs. Here we create an adaptive optimization methodology built upon digitized wing shape deformation and deep learning algorithms, which enable the rapid formulation of finite wing designs for specific aerodynamic performance demands under different cruise conditions. This methodology unfolds in three stages: radial basis function interpolated wing generation, collection of inputs from computational fluid dynamics simulations, and deep neural network that constructs the surrogate model for the optimal wing configuration. It has been demonstrated that the proposed methodology can significantly reduce the computational cost of numerical simulations. It also has the potential to optimize various aerial vehicles undergoing different mission environments, loading conditions, and safety requirements.

Investigation of the ultrasound-induced collapse of air bubbles near soft materials

A numerical investigation into the ultrasound-induced collapse of air bubbles near soft materials, utilizing a novel multi-material diffuse interface method (DIM) model with block-structured adaptive mesh refinement is presented. The present work expands from a previous five-equation DIM by incorporating Eulerian hyperelasticity. The model is applicable to any arbitrary number of interacting fluid and solid material. A single conservation law for the elastic stretch tensor enables tracking the deformations for all the solid materials. A series of benchmark cases are conducted, and the solution is found to be in excellent agreement against theoretical data. Subsequently, the ultrasound-induced bubble-tissue flow interactions are examined. The bubble radius was found to play a crucial role in dictating the stresses experienced by the tissue, underscoring its significance in medical applications. The results reveal that soft tissues primarily experience tensile forces during these interactions, suggesting potential tensile-driven injuries that may occur in relevant treatments. Moreover, regions of maximal tensile forces align with tissue elongation areas. It is documented that while early bubble dynamics remain relatively unaffected by changes in shear modulus, at later stages of the penetration processes and the deformation shapes, exhibit notable variations. Lastly, it is demonstrated that decreasing standoff distances enhances the interaction between bubbles and tissue, thereby increasing the stress levels in the tissue, although the behavior of the bubble dynamics remains largely unchanged.

Creeping thermocapillary motion of a Newtonian droplet suspended in a viscoelastic fluid

In this work we consider theoretically the problem of a Newtonian droplet moving in an otherwise quiescent infinite viscoelastic fluid under the influence of an externally applied temperature gradient. The outer fluid is modelled by the Oldroyd-B equation, and the problem is solved for small Weissenberg and Capillary numbers in terms of a double perturbation expansion. We assume microgravity conditions and neglect the convective transport of energy and momentum. We derive expressions for the droplet migration speed and its shape in terms of the properties of both fluids. In the absence of shape deformation, the droplet speed decreases monotonically for sufficiently viscous inner fluids, while for fluids with a smaller inner-to-outer viscosity ratio, the droplet speed first increases and then decreases as a function of the Weissenberg number. For small but finite values of the Capillary number, the droplet speed behaves monotonically as a function of the applied temperature gradient for a fixed ratio of the Capillary and Weissenberg numbers. We demonstrate that this behaviour is related to the polymeric stresses deforming the droplet in the direction of its migration, while the associated changes in its speed are Newtonian in nature, being related to a change in the droplet’s hydrodynamic resistance and its internal temperature distribution. When compared to the results of numerical simulations, our theory exhibits a good predictive power for sufficiently small values of the Capillary and Weissenberg numbers.

Direct-writing assembly of high-strength hierarchical porous mullite-based lattices with a multiscale reinforcing strategy

High-strength mullite-based lattices with a hierarchical porous structure were assembled using waste fly ash hollow microspheres (FAHMs) as the main raw material by a direct ink writing (DIW) technique. The hollow microspheres were uniformly distributed in the strut matrix, creating a pore structure with a size ranging from 54 μm to 97 μm. Wet printed lattices were solidified by a protein gelling technique to further inhibit the shape deformation. Hollow microspheres, together with the dense matrix formed by aluminum silicate powder, formed the three-dimensional skeleton of struts in the mullite-based lattices. The lattice with a porosity of 84.3 % exhibited a high compressive strength of 2.74 MPa, along with a low thermal conductivity of 0.191 W m−1 K−1. Compared to most reported lattices with the same density, such as conventional mullite lattices, the stretching-bending dominated hierarchical porous mullite-based lattice exhibited superior mechanical properties. These lattices with both high porosity and high strength are cost-effective, flexible, scalable, and can facilitate the application of porous ceramics in emerging fields.

GeoLatent: A Geometric Approach to Latent Space Design for Deformable Shape Generators

We study how to optimize the latent space of neural shape generators that map latent codes to 3D deformable shapes. The key focus is to look at a deformable shape generator from a differential geometry perspective. We define a Riemannian metric based on as-rigid-as-possible and as-conformal-as-possible deformation energies. Under this metric, we study two desired properties of the latent space: 1) straight-line interpolations in latent codes follow geodesic curves; 2) latent codes disentangle pose and shape variations at different scales. Strictly enforcing the geometric interpolation property, however, only applies if the metric matrix is a constant. We show how to achieve this property approximately by enforcing that geodesic interpolations are axis-aligned, i.e., interpolations along coordinate axis follow geodesic curves. In addition, we introduce a novel approach that decouples pose and shape variations via generalized eigendecomposition. We also study efficient regularization terms for learning deformable shape generators, e.g., that promote smooth interpolations. Experimental results on benchmark datasets show that our approach leads to interpretable latent codes, improves the generalizability of synthetic shapes, and enhances performance in geodesic interpolation and geodesic shooting.

Aeroelastic response of a thin panel excited by a separated shock–boundary layer interaction

Wind-tunnel experiments were conducted to investigate the effects of a separated shock–boundary layer interaction on the aeroelastic behavior of a thin panel in turbulent flow. A suite of traditional sensors and non-contact measurement techniques, including stereo digital image correlation (DIC), were used to characterize the operating conditions and structural response. The impact of the temperature differential between the panel and frame as well as cavity pressure on the panel response were explored. For a majority of the operating conditions, measured time histories of the panel dynamics revealed small-amplitude, forced oscillations about a stationary deformation. These deformations were due to the pressure fluctuations from the turbulent boundary layer and separated shock/boundary layer interaction. However, for a cavity pressure of 83 kPa and temperature differentials of [15, 17.2] K, the response transitioned to bi-stable, cross-well oscillations that were captured for the first time using DIC. The dynamic response was centered about the panel midpoint, coincident with the location of the shock-induced separation on the panel. Using several indirect tests, the intermittent, cross-well oscillations were characterized as potentially chaotic. As the temperature differential continued to decrease, the snap-through motions subsided and the panel response resumed a stationary behavior, albeit at a different deformation shape.

Interactive NeRF Geometry Editing With Shape Priors.

Neural Radiance Fields (NeRFs) have shown great potential for tasks like novel view synthesis of static 3D scenes. Since NeRFs are trained on a large number of input images, it is not trivial to change their content afterwards. Previous methods to modify NeRFs provide some control but they do not support direct shape deformation which is common for geometry representations like triangle meshes. In this paper, we present a NeRF geometry editing method that first extracts a triangle mesh representation of the geometry inside a NeRF. This mesh can be modified by any 3D modeling tool (we use ARAP mesh deformation). The mesh deformation is then extended into a volume deformation around the shape which establishes a mapping between ray queries to the deformed NeRF and the corresponding queries to the original NeRF. The basic shape editing mechanism is extended towards more powerful and more meaningful editing handles by generating box abstractions of the NeRF shapes which provide an intuitive interface to the user. By additionally assigning semantic labels, we can even identify and combine parts from different objects. We demonstrate the performance and quality of our method in a number of experiments on synthetic data as well as real captured scenes.

Abnormalities of hippocampal shape in idiopathic normal‐pressure hydrocephalus patients

AbstractBackgroundWe utilized 3‐dimensional, surface‐based, morphometric analysis to investigate hippocampus shape between 2 groups: (1) idiopathic normal‐pressure hydrocephalus (INPH) patients who had a positive response to the cerebrospinal fluid tap test and (2) healthy controls. The aims were (1) to evaluate INPH‐related structural abnormalities of the hippocampi and (2) to investigate relationships between hippocampal shape changes and gait disturbance in INPH patients.MethodForty‐eight INPH patients and 25 healthy controls were imaged with MRI, including 3‐dimensional volumetric images, for vertex‐based 3‐dimensional hippocampal shape analysis.ResultVertex‐wise shape analysis revealed significant bilateral deformation in patients with INPH compared with healthy controls after FDR correction. Both the left and right hippocampi were more elongated and narrowed in INPH patients than in the healthy controls. In both hemispheres, INPH patients demonstrated an upward bending of the middle and posterior hippocampus reflecting a bilateral vertical displacement from body to tail. Significant correlations were found between local shape deformity and the timed up and go and 10 meter walking tests (to a greater degree on the right than on the left). Bilateral inward deformations at the superomedial hippocampal tail and inferior hippocampal body were consistently associated with inferior performance across tests. Inward deformations at the right medial and lateral hippocampal head and right superior hippocampal body were also consistently associated with worse performance across tests.ConclusionThese results suggest that patients with INPH have unique patterns of hippocampal shape changes. Our findings encourage future studies to elucidate the underlying mechanism of hippocampal morphometric abnormalities in INPH patients. Changes in overall shape may contribute to the distinctive gait abnormalities associated with INPH.

Damping effect of surfactants on induced bubble shape deformations

The addition of surfactants suppresses interfacial deformations, and surface elasticity is expected to play a critical role. High-speed imaging is used to study the influence of surfactants on the shape oscillations of air bubbles attached to a capillary and on the rebound of bubbles from a horizontal glass plate. The experiments are conducted in pure water and in aqueous solutions containing five different surfactants: terpineol, sodium dodecyl sulfate, hexadecyltrimethylammonium bromide, Triton X-100, and Triton X-45. The frequencies and damping times of the decaying oscillations and the restitution coefficients of the decaying rebounds are evaluated. The damping time and the restitution coefficient both decrease sharply with an increasing surfactant concentration and then reach a minimum before finally stabilizing. The oscillation frequency initially increases due to enhanced surface elasticity but then drops suddenly when the surfactant concentration corresponding to the maximum damping is reached. The suppression of bubble rebounds by surfactants bears a strong resemblance to the damping of quadrupole bubble oscillations. In both cases studied, a surface elasticity of about 4 mN/m is required to achieve the maximum damping of interfacial deformations, regardless of the surfactant used. Moreover, the bubble rebounds are found to be more susceptible to the presence of trace concentrations of surfactants.

Red Blood Cells’ Area Deformation as the Origin of the Photoplethysmography Signal

The origin of the photoplethysmography (PPG) signal is a debatable topic, despite plausible models being addressed. One concern revolves around the correlation between the mechanical waveform’s pulsatile nature and the associated biomechanism. The interface between these domains requires a clear mathematical or physical model that can explain physiological behavior. Describing the correct origin of the recorded optical waveform not only benefits the development of the next generation of biosensors but also defines novel health markers. In this study, the assumption of a pulsatile nature is based on the mechanism of blood microcirculation. At this level, two interconnected phenomena occur: variation in blood flow velocity through the capillary network and red blood cell (RBC) shape deformation. The latter effect was qualitatively investigated in synthetic capillaries to assess the experimental data needed for PPG model development. Erythrocytes passed through 10 µm and 6 µm microchannel widths with imposed velocities between 50 µm/s and 2000 µm/s, according to real scenarios. As a result, the length and area deformation of RBCs followed a logarithmic law function of the achieved traveling speeds. Applying radiometric expertise on top, mechanical-optical insights are obtained regarding PPG’s pulsatile nature. The mathematical equations derived from experimental data correlate microcirculation physiologic with waveform behavior at a high confidence level. The transfer function between the biomechanics and the optical signal is primarily influenced by the vasomotor state, capillary network orientation, concentration, and deformation performance of erythrocytes.

Intelligent image-based deformability assessment of red blood cells via dynamic shape classification

Red blood cells (RBC), the primary component of whole blood, play an essential role in maintaining blood fluidity and mass transport throughout the human body. RBC deformability is an important property that indicates RBC quality and diseases. Among the techniques for RBC deformability measurements, the hydrodynamic image-based approach represents the most advanced method. However, RBC have a complex shape and high deformability, they display a wide range of shapes during the transition in microvessels, making it a challenge for deformation measurement. Therefore, we propose an image-based RBC deformability assessment via a shape-classification approach (IRIS) to solve this issue, where six shapes are identified by deep learning technique. Then, the deformations of RBC stiffened by different glutaraldehyde (GA) concentrations are measured and compared. The results elucidate that IRIS is able to sensitively distinguish 0.001% GA treated RBC from the control. Moreover, it is superior to two-shape classification or zero-shape classification in terms of sensitivity for deformability quantification. IRIS demonstrates an improved sensitivity for deformability analysis, high automaticity and unprecedented large data volume by applying deep learning method, it has a vast potential to benefit the hemorheology field as a powerful tool for early detection and diagnosis of RBC related diseases.

Bioinspired Multistimuli-Induced Synergistic Changes in Color and Shape of Hydrogel and Actuator Based on Fluorescent Microgels.

Fluorescent hydrogels have emerged as one of the most promising candidates for developing biomimetic materials and artificial intelligence owing to their unique fluorescence and responsive properties. However, it is still challenging to fabricate hydrogel that exhibits synergistic changes in fluorescence color and shape in response to multistimulus via a simple method. Herein, blue- and orange-emitting fluorescent microgels (MGs) both are designed and synthesized with pH-, thermal-, and cationic-sensitivity via one-step polymerization, respectively. The two fluorescent MGs are incorporated into transparent doubly crosslinked microgel (DX MG) hydrogels with a preset ratio. The DX MG hydrogels can tune the fluorescent color accompanied by size variation via subjecting to external multistimulus. Thus, DX MG hydrogels can be exploited for multiresponsive fluorescent bilayer actuators. The actuators can undergo complex shape deformation and color changes. Inspired by natural organisms, an artificial morning glory with color and size changes are showcased in response to buffer solutions of different pH values. Besides, an intelligent skin hydrogel, imitating natural calotes versicolor, by assembling four layers of DX MG with different ratios of MGs, is tailored. This work serves as an inspiration for the design and fabrication of novel biomimetic smart materials with synergistic functions.

In-situ scrutiny of the transition melting of pristine (Au) and metal oxide (Au-gallia)-supported plasmonic nanostructures

Morphological and compositional stabilities of pristine and metal-oxide-supported gold/gold-gallia nanostructures were determined at elevated temperatures (800 °C) for the first time. Emphasis was on the size and shape dependence of the transitional melting temperatures, from which conclusions were drawn predominantly from monitoring in-situ changes to plasmonic properties of the nanostructures. The morphological, crystalline, optical and elemental analyses supported and revealed new insights into temperature-driven morphological transformations. The experimentally-derived melting temperature of pristine nanostructures was corroborated using theoretical melting models, with the best results for the liquid skin melting model. The shape deformations and thermal expansion of pristine nanostructures were precluded by reinforcement of the plasmonic Au nanostructures with a matrix material of gallium oxide, which gave markedly different results in terms of enhancing thermal stability at temperatures where the pristine nanostructures were completely vaporized. The interfacial energies were likely the reason for the enhanced stability against shape transitions and/or melting, wherein it was found that the formative steps of gallia were insufficient to achieve these effects and that complete phase formation was necessary for stabilization. The insights concerning the reasons for the enhancements, the supportive role of the metal oxide matrix, the plasmonic stabilities of the Au nanoparticles, the shape dependence of the melting transitions and the crystalline stabilities of the composites in this report will help in predictive composite design for high-temperature applications such as sensing, catalysis, energy storage and design of compatible optical communication devices.

Dynamic Oscillation and Motion of Oil-in-Water Emulsion Droplets.

The interplay of interfacial tensions on droplets results in a range of self-powered motions that mimic those of living systems and serve as a tunable model to understand their complex non-equilibrium behavior. Spontaneous shape deformations and oscillations are crucial features observed in nature but difficult to incorporate in synthetic artificial systems. Here, we report sessile oil-in-water emulsions that exhibit rapid oscillating behavior. The oscillations depend on the nature and concentration of the surfactant, the chemical composition of the oil, and the wettability of the solid substrate. The rapid changes in the contact angle per oscillation are observed using side-view optical microscopy. We propose that the changes in the interfacial tension of the oil droplets is due to the partitioning of the surfactant into the oil phase and the movement of self-emulsified oil out of the parent droplets giving rise to the rhythmic variation in droplet contact-line. The ability to control and understand droplet oscillation can help model similar oscillations in out-of-equilibrium systems in nature and reproduce biomimetic behavior in artificial systems for various applications, such as microfluidic lab-on-a-chip and adaptive materials.