Description Of Surface Research Articles

An isogeometric one-dimensional Kirchhoff–Love type model for developable elastic ribbons

This paper proposes a kinematical reduction for Kirchhoff–Love shells in the special case of developable base surfaces. The resulting model considers a curve and a director field along it, reducing the shell to one-dimensional items and thereby decreasing the number of degrees of freedom involved. The presented overview of the geometry of developable surfaces covers dissolution of two types of singularities: a relatively parallel frame allows for points or segments of zero curvature along the curve and an explicit condition accounts for local self-intersections of the ruled surface description. We generalise earlier results after which the geometric constraints proposed are equivalent to isometric shell deformation. We also give a more general update of the elastic bending energy of the ribbon, which yields equilibrium states as minimisers. Subsequently, we discuss the numerical details of the approach and illustrate the feasibility at hand of several examples, among them the famous Möbius ribbon.

Experimental study of the shear strength criterion of rock structural plane based on three-dimensional surface description

Abstract The failure of rock mass is mainly due to the failure of the structural plane, which is an important factor to reduce the mechanical properties and stability of rock mass. The shear strength of rock mass is one of the parameters for the stability calculation of large-scale rock mass engineering. The shear strength of a rock structural plane is strongly influenced by surface morphology. Considerable research has been conducted regarding the correlation between two-dimensional structural plane morphology and shear strength. However, quantitative research on three-dimensional (3D) morphology is relatively limited. In this study, 3D printing technology was used to create molds. Using cement and sand as the main materials, additives such as early strength and water-reducing agents were added, and test samples of irregular surface topography were created. The 3D roughness was quantified by formula calculation. Using a ZScanner® 800 hand-held 3D laser scanner to perform scanning on the structural surface, the parameter curve was analysed by generating 3D coordinate information and a 3D image of the fracture surface, and the quantitative parameter M p 3 D {M}_{\text{p}}^{3\text{D}} describing the 3D morphology of the structural surface was constructed. The change rule of R p 3 D {R}_{\text{p}}^{3\text{D}} and joint roughness coefficient (JRC) were analysed under different scanning resolutions, Δ(r), the scanning precision was suggested, and the functional relationship between JRC and M p 3 D {M}_{\text{p}}^{3\text{D}} was established. Finally, a formula for shear strength parameters considering the 3D characteristics of a structural plane surface was established. The model validation results show that the experimental data were within the 95% confidence band of the model curve, the average error of the shear strength was 10.4%, the errors of friction angle and cohesion, C, were 3.4 and 9.4%, and the reliability was fine.

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis

Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of atomic configurations. To address this challenge, we present Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that accounts for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt3Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combined with low symmetry of the alloy substrate produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to the Oxygen Reduction Reaction, where configurational complexity results from the presence of irregular crystal surfaces, high adsorbate coverages, and directionally-dependent adsorbate-adsorbate interactions. In both cases, the ACE-GCN model, trained on a fraction (~10%) of the total DFT-relaxed configurations, successfully describes trends in the relative stabilities of unrelaxed atomic configurations sampled from a large configurational space. This approach is expected to accelerate development of rigorous descriptions of catalyst surfaces under in-situ conditions.

Learning to Feel Textures: Predicting Perceptual Similarities From Unconstrained Finger-Surface Interactions.

Whenever we touch a surface with our fingers, we perceive distinct tactile properties that are based on the underlying dynamics of the interaction. However, little is known about how the brain aggregates the sensory information from these dynamics to form abstract representations of textures. Earlier studies in surface perception all used general surface descriptors measured in controlled conditions instead of considering the unique dynamics of specific interactions, reducing the comprehensiveness and interpretability of the results. Here, we present an interpretable modeling method that predicts the perceptual similarity of surfaces by comparing probability distributions of features calculated from short time windows of specific physical signals (finger motion, contact force, fingernail acceleration) elicited during unconstrained finger-surface interactions. The results show that our method can predict the similarity judgments of individual participants with a maximum Spearman's correlation of 0.7. Furthermore, we found evidence that different participants weight interaction features differently when judging surface similarity. Our findings provide new perspectives on human texture perception during active touch, and our approach could benefit haptic surface assessment, robotic tactile perception, and haptic rendering.

DETERMINATION OF THE FEATURES OF THE SHAPE AND VIBRATION FREQUENCY OF TURBINE BLADES ON DIGITAL MODELS

A digital solid model of a turbine blade with a mounting shelf has been developed in SolidWorks. The description of complex surfaces is made using spline functions. The method of computer simulation using SolidWorks Simulation was used to study the distribution of natural oscillations of the blade depending on the method of its fixing during machining. The spectra of natural oscillations of the blade in the sound range have been obtained and analyzed. The form of natural vibrations of complex surfaces is also analyzed. For the correct choice of processing parameters during machining, it is necessary to take into account both the conditions for fixing the part in the fixture and the natural frequency of the part. It is noted that an equally important parameter is the form of oscillations of a thin surface at the studied frequencies. It is noted that in the future it is possible to solve these problems through computer simulation.

Topography stitching in the spatial frequency domain for the representation of mid-spatial frequency errors.

Sub-aperture fabrication techniques such as diamond turning, ion beam figuring, and bonnet polishing are indispensable tools in today's optical fabrication chain. Each of these tools addresses different figure and roughness imperfections corresponding to a broad spatial frequency range. Their individual effects, however, cannot be regarded as completely independent from each other due to the concurrent formation of form and finish errors, particularly in the mid-spatial frequency (MSF) region. Deterministic Zernike polynomials and statistical power spectral density (PSD) functions are often used to represent form and finish errors, respectively. Typically, both types of surface errors are treated separately when their impact on optical performance is considered: (i) wave aberrations caused by figure errors and (ii) stray light resulting from surface roughness. To fill the gap between deterministic and statistical descriptions, a generalized surface description is of great importance for bringing versatility to the entire optical fabrication chain by enabling easy and quick exchange of surface topography data between three disciplines: optical design, manufacturing, and characterization. In this work, we present a surface description by stitching the amplitude and unwrapped phase spectra of several surface topography measurements at different magnifications. An alternative representation of surface errors at different regimes is proposed, allowing us to bridge the gap between figure and finish as well as to describe the well-known MSF errors.

Modeling stress anisotropy, strength differential, and anisotropic hardening by coupling quadratic and stress-invariant-based yield functions under non-associated flow rule

An accurate description of yield surface is essential for the high-fidelity numerical analyses of sheet metal forming processes. In this work, a simple coupling of anisotropic quadratic and isotropic stress-invariant-based yield functions is proposed under the non-associated flow rule. The quadratic part is the asymmetric Hill48 function, which describes the anisotropic hardening with explicitly calibrated parameters from stress-strain curves. A new stress-invariant-based yield function, as a second component, is developed to capture the shapes of yield surface for diverse metallic materials with enhanced flexibility. Finally, a yield function is established by multiplying the anisotropic quadratic and the isotropic stress-invariant-based parts, which satisfies the convexity requirement in terms of stress state. The proposed asymmetric anisotropic yield function is validated with automotive sheet metals including dual-phase steels, aluminum alloys and magnesium alloys. Results show that the new yield criterion can accurately predict the anisotropy in stress, strength differential effect and yield surface evolution (or anisotropic hardening) of the investigated sheet metals.

Change of the Structural Properties of High-Performance Concretes Subjected to Thermal Effects.

The paper refers to studies of the structure of high-performance concrete with polypropylene fibre at different dosages. The authors see a research gap in the study of the effect of adding polypropylene fibre on the parameters of concrete exposed to high temperatures. The study takes into account the thermal effect—groups of samples were heated to 200 °C, 400 °C and 600 °C. The authors carried out basic tests to describe the changes in density, ultrasonic tests, uniaxial compression strength tests and tensile tests by splitting. The positive effect of polypropylene fibres is mainly observed between 20 °C and 200 °C. The melting of polypropylene fibres causes a delay in the development of micro-cracks in the structure of these concretes compared to HPC. Adding polypropylene fibres to the mixtures also increased the speed of ultrasonic wave propagation in the medium. The research was deepened with tomographic imaging. A description of the splitting surface was carried out. The results of tensile by splitting tests clearly show an increase in the relative failure area for unheated concretes in proportion to the number of fibres used. Changes in splitting surfaces under the influence of temperature are graphically illustrated. Furthermore, differences in the samples under the influence of heating at high temperatures are presented. Finally, the porosity development of all sample groups before and after heating at all temperatures is described.

Surface Inspection and Description in Metrology and Tribology—Vol.1

The primary goal of this Special Issue was to present recent trends in surface inspection and description, from both metrological and tribological points of view [...]

Event stream learning using spatio-temporal event surface

Event cameras sense changes in light intensity and record them as an asynchronous event stream. Efficiently encoding and learning spatiotemporal information of the event streams remain challenging. In this paper, we propose a novel event descriptor to encode the spatio-temporal features for event streams and a local-search based multi-spike learning algorithm for spiking neural networks to classify encoded features. The spatio-temporal event surface (STES) descriptor explicitly captures both spatial and temporal correlations among events, and thus can characterize spatiotemporal features more accurately than existing feature descriptors that focus only on temporal or spatial information. In classification with multi-spike learning, we introduce a local search and gradient clipping mechanism to ensure the efficiency and stability of learning, which avoids other multi-spike learning rules’ time-consuming global search and the gradient explosion problem. Experimental results demonstrate the superior classification performance of our proposed model, especially for event streams with rich spatiotemporal dynamics.

Can the Applied Optics Employ Modern Approaches Developed in Seismic Prospecting? A Review

The concept of infinitesimal elastic deformation and the theory of elastic seismic waves was formed in the first part of the 19th century and was based mainly on the Fermat, Huygens and Snell developments in the theory of optics. At the same time, seismic wave propagation (utilized in geophysical prospecting) and optic wave propagation through defined media are based on the same physical-mathematical principles, making it possible to transfer nonconventional procedures developed in the first domain to the second one and back. In this investigation, we propose transferring advanced methodologies established in seismic prospecting to practical optics. We selected two advanced approaches with the following aims: (a) homeomorphic imaging; (b) novel description of boundary conditions. The first approach is established with the utilization of the revealed local theoretical relationship between the geometrical features of two fundamental beams and the geometrical properties of hidden geological targets of the media under study. The employed geometrical characteristics of the fundamental beams are spreading functions and curvatures of the singular wavefronts. The second approach is based on a novel description of the boundary conditions. It enables the determination of a faultless seismic (optical) system with the preassigned focusing and imaging assets when any aberrations are absent. An optimal optical system is usually determined as some arrangement agreeing to some perfect system with acceptable correctness. Employment of the developed procedures in the optical design will permit the application of a description of the optical surface using: (1) parametric functions, (2) differential equations, and (3) mixed (parametric-differential). On this basis, optical systems with a minimal number of optical features with complicated shapes can be promptly computed. Another important application field of the suggested methods is the design of optical systems with diffractive elements.

Frustration-induced complexity in order-disorder transitions of the J_{1}-J_{2}-J_{3} Ising model on the square lattice.

We revisit the field-free Ising model on a square lattice with up to third-neighbor (NNNN) interactions, also known as the J_{1}-J_{2}-J_{3} model, in the mean-field approximation. Using a systematic enumeration procedure, we show that the region of phase space in which the high-temperature disordered phase is stable against all modes representing periodic magnetization patterns up to a given size is a convex polytope that can be obtained by solving a standard vertex enumeration problem. Each face of this polytope corresponds to a set of coupling constants for which a single set of modes, equivalent up to a symmetry of the lattice, bifurcates from the disordered solution. While the structure of this polytope is simple in the half-space J_{3}>0, where the NNNN interaction is ferromagnetic, it becomes increasingly complex in the half-space J_{3}<0, where the antiferromagnetic NNNN interaction induces strong frustration. We then pass to the limit N→∞ giving a closed-form description of the order-disorder surface in the thermodynamic limit, which shows that for J_{3}<0, the emergent ordered phases will have a "devil's surface"-like mode structure. Finally, using Monte Carlo simulations, we show that for small periodic systems, the mean-field analysis correctly predicts the dominant modes of the ordered phases that develop for coupling constants associated with the centroid of the faces of the disorder polytope.

Accurate 3D hand mesh recovery from a single RGB image

This work addresses hand mesh recovery from a single RGB image. In contrast to most of the existing approaches where parametric hand models are employed as the prior, we show that the hand mesh can be learned directly from the input image. We propose a new type of GAN called Im2Mesh GAN to learn the mesh through end-to-end adversarial training. By interpreting the mesh as a graph, our model is able to capture the topological relationship among the mesh vertices. We also introduce a 3D surface descriptor into the GAN architecture to further capture the associated 3D features. We conduct experiments with the proposed Im2Mesh GAN architecture in two settings: one where we can reap the benefits of coupled groundtruth data availability of the images and the corresponding meshes; and the other which combats the more challenging problem of mesh estimation without the corresponding groundtruth. Through extensive evaluations we demonstrate that even without using any hand priors the proposed method performs on par or better than the state-of-the-art.

Analysis of Cracked Rail of the Crane of Type A120

The aim of the work was to find out the causes of cracking of the A120 crane track rail. Although the track was regularly inspected by defectoscopic techniques, after five years of operation, the rail was broken at the weldment. The elemental composition of the welded joint materials was verified and the mechanical properties were determined. A fractographic description of the fracture surface was performed and the structure of the material was evaluated. Several factors contributed to the formation of crack, the combination of which led to a rail failure. Defects of the welded joint, acting as notches, from which they initiated fatigue cracks, unfavourable microstructure of the weld metal, low toughness of the base material and operating environment and conditions were dominant.

Local Surface Descriptor for Geometry and Feature Preserved Mesh Denoising

3D meshes are widely employed to represent geometry structure of 3D shapes. Due to limitation of scanning sensor precision and other issues, meshes are inevitably affected by noise, which hampers the subsequent applications. Convolultional neural networks (CNNs) achieve great success in image processing tasks, including 2D image denoising, and have been proven to own the capacity of modeling complex features at different scales, which is also particularly useful for mesh denoising. However, due to the nature of irregular structure, CNNs-based denosing strategies cannot be trivially applied for meshes. To circumvent this limitation, in the paper, we propose the local surface descriptor (LSD), which is able to transform the local deformable surface around a face into 2D grid representation and thus facilitates the deployment of CNNs to generate denoised face normals. To verify the superiority of LSD, we directly feed LSD into the classical Resnet without any complicated network design. The extensive experimental results show that, compared to the state-of-the-arts, our method achieves encouraging performance with respect to both objective and subjective evaluations.

Simulation Based Poynting Vector Description of the Field Regions for Simple Radiating Structures

Estimating the coupling properties between a radiating structure and other conductive elements, the field behavior of the radiating source is essential to know. One well-known classification of the field behavior are the field-regions around antennas, namely, the far-field, the radiating near-field, and the reactive near-field. The different kinds of near-fields are distinguished by the reactive and radiating parts of the electromagnetic field, whereas in the far-field region the field behaves as a plane wave in the direction of propagation. One way to describe these field characteristics is to use the complex Poynting vector, which defines the electromagnetic power flow. This work presents a Poynting-vector-based approach to classify and visualize the field behavior around simple radiators using numerical simulations. First, the approach is applied to simple antenna structures such as dipoles and loop antennas. Later, the introduced field regions are utilized to predict the coupling behavior of practical applications, the coupling between single elements of a linear antenna array, and the coupling behavior of an electrically large loop antenna. It could be shown that the introduced approach, defining a surface description of the boundary between the near-field regions, enables the possibility of predicting the coupling behavior between radiating structures. The introduced error estimator for the far-field also delivers knowledge about the far-field quality in different angular directions and distances. All simulations have been executed applying a one-dimensional partial element equivalent circuit method.

Calculation of absolute Raman scattering cross-sections using vibrational self-consistent field/vibrational configuration interaction wave functions.

In the present study, the differential scattering cross-sections, depolarization ratios and Raman shifts of small molecular systems are obtained from configuration iteration wave functions of vibrational self-consistent field (VSCF) states. The transition polarizabilities were modeled using the Placzek approximation, neglecting those contributions not arising from the electric dipole mechanism. This theoretical approach is considered a good approximation for samples that absorb in the UV range if the excitation radiation falls in the visible region, as is the case of the molecules selected for the present study, namely: water, methane, and acetylene. Potential energy and electronic polarizability surfaces are calculated by the CCSD(T) and CC3 methods with aug-cc-p(C)V(T,Q,5)Z basis sets. The vibrational Hamiltonian includes the vibrational angular momentum contribution of the Watson kinetic energy operator. As expected, due to the variational nature of the VSCF and vibrational configuration interaction (VCI) methods, the Raman transition wavenumbers are substantially improved over the harmonic predictions. Surprisingly, the scattering cross-sections obtained using the harmonic approximation or the VSCF method better agrees with the experimental values than those cross-sections predicted using VCI wave functions. The more significant deviations of the VCI results from the experimental reference may be related to the significant uncertainties of the measured cross-sections. Still, it may also indicate that the VCI Raman transition moments may require a more accurate description of the electronic polarizability surface. Finally, the depolarization ratios calculated for H2 O and C2 D2 using harmonic and VCI wave functions have similar accuracy, whereas, for C2 H2 and C2 HD, the VCI results are more accurate.

Adaptive area-preserving parameterization of open and closed anatomical surfaces

The parameterization of open and closed anatomical surfaces is of fundamental importance in many biomedical applications. Spherical harmonics, a set of basis functions defined on the unit sphere, are widely used for anatomical shape description. However, establishing a one-to-one correspondence between the object surface and the entire unit sphere may induce a large geometric distortion in case the shape of the surface is too different from a perfect sphere. In this work, we propose adaptive area-preserving parameterization methods for simply-connected open and closed surfaces with the target of the parameterization being a spherical cap. Our methods optimize the shape of the parameter domain along with the mapping from the object surface to the parameter domain. The object surface will be globally mapped to an optimal spherical cap region of the unit sphere in an area-preserving manner while also exhibiting low conformal distortion. We further develop a set of spherical harmonics-like basis functions defined over the adaptive spherical cap domain, which we call the adaptive harmonics. Experimental results show that the proposed parameterization methods outperform the existing methods for both open and closed anatomical surfaces in terms of area and angle distortion. Surface description of the object surfaces can be effectively achieved using a novel combination of the adaptive parameterization and the adaptive harmonics. Our work provides a novel way of mapping anatomical surfaces with improved accuracy and greater flexibility. More broadly, the idea of using an adaptive parameter domain allows easy handling of a wide range of biomedical shapes.

An Anisotropic Continuum Damage Mechanics Model for the Simulation of Yield Surface Evolution and Ratcheting

A new anisotropic continuum damage model was presented on the basis of irreversible thermodynamics. Second rank symmetric damage tensor, kinematic hardening tensor, and damage potential surface were introduced. The yield surface in this study has been modeled to distort in the stress space by the evolution of the damage tensor. The new model was applied in yield surface characterization and led to a well description of the subsequent yield surfaces. This model is then applied to predict experimental results of the cyclic nonproportional loading paths obtained by Kang et al. [2004], Hassan et al. [2002] and Taleb and Cailletaud [2011]. It is demonstrated that the new model can predict the yield surface distortion and the ratcheting strains of multiaxial nonproportional cyclic loading with acceptable accuracy and by using less material constants with respect to the previous models.

General design method for dynamic freeform optics with variable functionality.

We propose and demonstrate a general design method for refractive two-element systems enabling variable optical performance between two specified boundary conditions. Similar to the Alvarez lens, small, relative lateral shifts in opposite directions are applied to a pair of plano-freeform elements. The surface prescriptions of the boundary lenses and a maximum desired shift between freeform plates are the main design inputs. In contrast to previous approaches, this method is not limited to boundaries with similar optical functions and can enable a wide range of challenging, dynamic functions for both imaging and non-imaging applications. Background theory and design processes are presented both for cases that are conducive to analytical surface descriptions, as well as for non-analytic surfaces that must be described numerically. Multiple examples are presented to demonstrate the flexibility of the proposed method.