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The critical state of granular soils needs to make proper reference to the fabric that develops at critical state. This study substantialises the concept of critical fabric surface (CFS), which attracts the fabric state of granular soils upon continuous shearing. Numerical experiments using discrete-element method (DEM) modelling are conducted under drained and undrained conditions with varying Lode angles. Fabric tensors are defined based on the normals of all contacts and of the strong force contacts only. Both tensors have their spherical component preserved such that the information of coordination number can be carried. A separate series of low-confining-pressure undrained tests is conducted to probe the fabric states of soils in the post-liquefaction regime. Finally, a single CFS spanning across a wide range of coordination numbers is established based on the DEM results. The CFS concept provides an important reference state for soils sheared to large strains, complementary to the traditionally defined critical state. This provides a new perspective to interpret and model the mechanics of granular soils in both pre- and post-liquefied regimes. The evolution of fabric shows that the normalised strong-contact fabric evolves linearly with the stress ratio even for liquefied or anisotropically consolidated soils.

A counter-current jet (CCJ) is significantly different from a classical jump – it is like a classical jump with a reverse surface jet layer above it. A series of experiments, with the jet's Froude number in the range 4–10, was conducted to investigate the velocity distribution characteristics of CCJs. It was found, compared with a classical jump, the CCJ velocity distribution was more even and the decay of the maximum velocity was more efficient. It was beneficial to the energy dissipation and the deceleration of a high-speed flow. The variations of velocity with depth were opposite in the upper and lower parts of the zero-velocity line, resulting in relatively large fluid internal friction near the zero-velocity line. The internal friction between the surface jet layer and the lower fluid also increased the energy dissipation rate. A counter-current energy dissipator was found to achieve a good energy dissipation effect without auxiliary energy dissipators, which could be beneficial to engineering applications.

Photovoltaics convert solar radiation into electrical current. For the present study, blends containing electron donor and acceptor are used instead of materials made with silicon. Carbon-based organic semiconductors are easy to process and have low fabrication costs. There are several fabrication steps playing important role in the photovoltaic device performance such as, substrate preparation, polymer-acceptor ratios in the blend, thermal annealing of the active layer and top electrode deposition. It has been shown that nanoscale morphology of the blend can be altered via thermal annealing treatment. As a result, efficiency is affected by surface roughness. The blend of P3HT: PCBM as donor: acceptor was used to fabricate thin films and photovoltaic cells. The power conversion efficiencies and surface morphologies of the devices annealed at various times were measured. Atomic force microscopy (AFM) images revealed that the surface roughness of the active layer is mainly affected by the annealing time, and the film with the roughest surface results in the most efficient solar cell.

Bearings are used to reduce friction between two rolling /sliding members of the machines. Under normal operating conditions, an increase in the fatigue load cycles on the bearing contact surfaces results in surface defects viz. micro pitting, macro pitting, spalling and scuffing, thereby causing lubricant degradation. Hence, to maintain a better operating performance of rotating machines, it is essential to keep track of operating parameters. This paper describes the results of experimental investigations carried out to assess wear propagation on bearing contact surfaces using tribological and vibration parameters. Results obtained from experimental investigations provide a good correlation between the increase in surface fatigue wear and corresponding effects on transition in lubrication regimes, increased vibration levels, variations in rheological properties of lubricant and wear mechanisms developed on the contact surfaces of the roller bearing. The proposed approach can be used as a promising tool to assess incipient faults developed in roller bearing.

s Recently, super gas wet and gas wet surfaces have been extensively attended in petroleum industry, as supported by the increasing number of publications in the last decade related to wettability alteration in gas condensate reservoirs. In many cases, contact angle measurement has been employed to assess the wettability alteration. Even though contact angle measurement seems to be a straightforward approach, there exist many misuses of this technique and consequently misinterpretation of the corresponding results. In this regard, a critical inspection of the most recent updated concepts and the intervening parameters in the contact angle based wettability evaluation of liquid-solid-gas systems could aid to provide some remediation to alleviate this problem. To this end, this work presents a survey on the accurate terms and rigorous protocols based on the community of surface science and chemistry. As a preliminary step, advancing, receding, static, and the most stable contact angle terminology are defined. The study is followed by the definition of the contact angle hysteresis effect. The application of surface free energy in the selection of the best gas wet agent is then analyzed. Afterward, the impact of the size-dependent behavior of drop on contact angle is discussed. Finally, a sessile drop experiment is explained to achieve the defined parameters. For future contributions to petroleum industry journals, like this journal, this work could offer an easy use of the conceptual framework for analyzing the results and comparative evaluations in chemical wettability modifier agents.

The paper studies strike-slip fault rupture propagation through dense sand and its interaction with surface foundations, combining physical and numerical modelling. A series of centrifuge tests is conducted using a three-section split-box, which allows the modelling of two strike-slip faults per test. A free-field test is initially conducted, followed by four interaction tests. Eight different foundation configurations are studied, varying the foundation location, surcharge load, aspect ratio and rigidity. The experiments are numerically simulated employing three-dimensional finite-element modelling, combining periodic boundaries and a relatively simple yet efficient constitutive model, developed as part of this study. Based on a Mohr–Coulomb yield criterion, the model incorporates post-yield isotropic frictional hardening and softening (MC–HS). Carefully calibrated on the basis of triaxial tests, the model is validated against the centrifuge model tests, and exploited to derive further insights. The MC–HS model covers the entire range from elastic to fully softened response, capturing the deviatoric and volumetric behaviour of dense sand, and especially its pre-softening volumetric response, which is proven to be crucial for the simulation of the complex mechanisms of strike-slip faulting. Both physical and numerical modelling reveal the formation of diagonal shear ruptures at the ground surface (Riedel shears). These are complex helicoidal structures, formed due to the spatial variation of shear stresses. Foundation response is mainly governed by the kinematic constraint offered by its presence. Fault rupture locations close to its sides typically lead to a translational mechanism, whereas locations close to its centreline lead to a rotational one. Foundation rigidity is proven to be a prerequisite for the development of both mechanisms, which rely on the ability of the foundation to resist the developing normal and shear stresses.

Among a variety of additive manufacturing technologies, constrained-surface image-projection-based stereolithography (SLA) technology has unique advantages in printing precision and commercial matu...

While the dimensional accuracy of the intaglio surface of a removable complete denture is key to its adaptation, comfort, and clinical performance, information on the ability of milling and 3D-printing workflows to accurately reproduce this surface is lacking.The purpose of this clinical study was to compare the trueness of the intaglio surface of milled and 3D-printed removable complete digital dentures.Intraoral scans were obtained from 14 participants for a total of 20 edentulous arches. Ten maxillary and 10 mandibular denture bases were then designed and fabricated with a completely digital workflow, both with milling and 3D-printing. Fabricated dentures were digitized with the same intraoral scanner used to obtain intraoral digital scans of the edentulous arches. Standard tessellation language (STL) files of the printed and milled denture bases were used for 3D analysis and comparisons with the STL file of the corresponding designed denture base. Specifically, a reverse engineering software program was used to trim and extract intaglio surfaces, align them, and measure their global mean 3D distance. In order to evaluate the homogeneity of production accuracy of each manufacturing process, the intaglio surfaces were also divided into several regions of interest and the corresponding 3D distances measured. Within- and between-group differences and maxillary and mandibular dentures differences were assessed with parametric and nonparametric tests (α=.05).Milling showed a global better trueness of the entire intaglio surface (-0.002 mm) than 3D-printing (0.018 mm), both for the whole data set (P.001) and for maxillary (P=.032) or mandibular (P=.049) denture base subgroups. Within each fabrication technology, maxillary (P.11) and mandibular dentures (P=.2) showed no significant difference in trueness. Measured deviations were significantly different from zero for the 3D-printed dentures (P.001), but not for the milled dentures (P=.487). Additionally, for milled dentures, no significant difference in trueness was found among the 11 regions of interest identified for the maxillary dentures (P=.085) and the 13 regions of interest for the mandibular dentures (P=.211). Conversely, 3D-printing showed significant variations in trueness among the same zones of interest, both in maxillary (P.001) and mandibular (P=.004) dentures.Within the limits of the manufacturing methodologies used for complete dentures, milling can provide a slightly better trueness of the intaglio surface than 3D-printing, with less variation across several zones of interest. However, given the magnitude of such differences, they may be reasonably considered to be of limited, if any, clinical significance.

Humans routinely sit or lean against supporting surfaces and it is important to shape these surfaces to be comfortable and ergonomic. We give a method to design the geometric shape of rigid supporting surfaces to maximize the ergonomics of physically based contact between the surface and a deformable human. We model the soft deformable human using a layer of FEM deformable tissue surrounding a rigid core, with measured realistic elastic material properties, and large-deformation nonlinear analysis. We define a novel cost function to measure the ergonomics of contact between the human and the supporting surface. We give a stable and computationally efficient contact model that is differentiable with respect to the supporting surface shape. This makes it possible to optimize our ergonomic cost function using gradient-based optimizers. Our optimizer produces supporting surfaces superior to prior work on ergonomic shape design. Our examples include furniture, apparel and tools. We also validate our results by scanning a real human subject's foot and optimizing a shoe sole shape to maximize foot contact ergonomics. We 3D-print the optimized shoe sole, measure contact pressure using pressure sensors, and demonstrate that the real unoptimized and optimized pressure distributions qualitatively match those predicted by our simulation.

In mechanised tunnelling, the filling of the annular gap behind the precast concrete segments is one of the essential operations. The main goal of filling this space is to reduce surface settlements and limit movements due to tunnel excavation in the soil mass. To achieve this aim, a two-component grout is often used to fill the annular gap. Determination of the amounts of ingredients in the two-component grout should be carried out in such a way that the injection materials will be able to fulfil the required performance and technical properties. In this study, laboratory tests were carried out to investigate two-component grout properties, such as flowability, bleeding, gelling time and uniaxial compressive strength. The effect of lateral pressure on grout resistance was studied according to real excavation situations. The influences of the grout ingredients and effective parameters such as bentonite and cement contents, water–cement ratio and the dosage of accelerator (sodium silicate) and accelerator ratio were also investigated.

We introduce the problem of clustering the set of vertices in a given 3D mesh. The problem is motivated by the need for value engineering in architectural projects. We first derive a max-norm based metric to estimate the geometric disparity between a given pair of vertices, and characterize the problem in terms of this measure. We show that this distance can be computed by using Sequential Quadratic Programming (SQP). Next we introduce two different algorithms for clustering the set of vertices on a given mesh, respectively based on two disparity measurements: max-norm and L2-norm based metric. An equivalence is established between mesh vertices and physical joints in an architectural mesh. By replacing individual joints by their equivalent cluster representative, the number of unique joints in the facade mesh, and therefore the fabrication cost, is dramatically reduced. Finally, we present an algorithm for remeshing a given surface in order to further reduce the number of joint clusters. The framework is tested for a set of real-world architectural surfaces to illustrate the effectiveness and utility of our approach. Overall, this approach tackles the important problem reducing fabrication cost of joints without modifying the underlying connectivity that was specified by the architect.

In this paper, we develop a novel method for fast geodesic distance queries. The key idea is to embed the mesh into a high-dimensional space, such that the Euclidean distance in the high-dimensional space can induce the geodesic distance in the original manifold surface. However, directly solving the high-dimensional embedding problem is not feasible due to the large number of variables and the fact that the embedding problem is highly nonlinear. We overcome the challenges with two novel ideas. First, instead of taking all vertices as variables, we embed only the saddle vertices, which greatly reduces the problem complexity. We then compute a local embedding for each non-saddle vertex. Second, to reduce the large approximation error resulting from the purely Euclidean embedding, we propose a cascaded optimization approach that repeatedly introduces additional embedding coordinates with a non-Euclidean function to reduce the approximation residual. Using the precomputation data, our approach can determine the geodesic distance between any two vertices in near-constant time. Computational testing results show that our method is more desirable than previous geodesic distance queries methods., Comment: Presented at Computational Visual Media 2021; to be published in IEEE Transactions on Visualization and Computer Graphics

The Appalachians, and Central Appalachia in particular, have a long history of resource extraction including coal mining. In the past half century, the region experienced a shift from underground to surface mining, which leaves highly visible changes on the landscape. This study presents an analysis of changes in surface mining extents between 1984 and 2015 using remote sensing techniques, and tests the methods of previous research over a broader study area. The authors found that 3070 km2 (7.1%) of land within the central Appalachian coalfield was classified as mined land through the study period, and that the rate of newly mined land, as well as total mined land has decreased in recent years. The overall classification accuracy was 0.888 and the kappa coefficient was 0.880. Study results indicate that previously developed methods for identifying surface mines in a sub-region of Central Appalachia can successfully be applied over the broader region. The resulting surface mining datasets will be applied to a future study examining the potential human health impacts of surface mining. Published version

The recent success in supervised multi-view stereopsis (MVS) relies on the onerously collected real-world 3D data. While the latest differentiable rendering techniques enable unsupervised MVS, they are restricted to discretized (e.g., point cloud) or implicit geometric representation, suffering from either low integrity for a textureless region or less geometric details for complex scenes. In this paper, we propose SurRF, an unsupervised MVS pipeline by learning Surface Radiance Field, i.e., a radiance field defined on a continuous and explicit 2D surface. Our key insight is that, in a local region, the explicit surface can be gradually deformed from a continuous initialization along view-dependent camera rays by differentiable rendering. That enables us to define the radiance field only on a 2D deformable surface rather than in a dense volume of 3D space, leading to compact representation while maintaining complete shape and realistic texture for large-scale complex scenes. We experimentally demonstrate that the proposed SurRF produces competitive results over the-state-of-the-art on various real-world challenging scenes, without any 3D supervision. Moreover, SurRF shows great potential in owning the joint advantages of mesh (scene manipulation), continuous surface (high geometric resolution), and radiance field (realistic rendering).

Tactile devices provide an intuitive way for texture display, which allows users to perceive the detailed surface properties of virtual or remote objects. For existing tactile devices that create actual topographical transformations, it remains challenging to render surface textures with high spatial resolution due to the limitation of the size of actuators. To address this challenge, a magnetically responsive soft actuator with a diameter of 1 mm is proposed. Integrating the high-density soft actuator array and a soft membrane bracket, we develop a magnetically responsive soft tactile device (named MRS-Tex) for texture display. When a magnetic field is applied, the magnetic units will sink to form pits, and the soft membrane bracket resists the finger pressure so that users can perceive the rendered surface texture. Thanks to the proposed sunken solution, MRS-Tex is capable of rendering surface textures with millimeter-level resolution while providing the sufficient upward holding force. Moreover, we conduct quantitative experiments and two user studies to evaluate the performance of MRS-Tex. Experimental results show that MRS-Tex can generate pits with a depth of more than 0.20 mm, which is sufficient for rendering perceivable surface textures.

We prove the first polynomial bound on the number of monotonic homotopy moves required to tighten a collection of closed curves on any compact orientable surface, where the number of crossings in the curve is not allowed to increase at any time during the process. The best known upper bound before was exponential, which can be obtained by combining the algorithm of De Graaf and Schrijver [ J. Comb. Theory Ser. B , 1997] together with an exponential upper bound on the number of possible surface maps. To obtain the new upper bound, we apply tools from hyperbolic geometry, as well as operations in graph drawing algorithms—the cluster and pipe expansions—to the study of curves on surfaces. As corollaries, we present two efficient algorithms for curves and graphs on surfaces. First, we provide a polynomial-time algorithm to convert any given multicurve on a surface into minimal position. Such an algorithm only existed for single closed curves, and it is known that previous techniques do not generalize to the multicurve case. Second, we provide a polynomial-time algorithm to reduce any k -terminal plane graph (and more generally, surface graph) using degree-1 reductions, series-parallel reductions, and Δ Y -transformations for arbitrary integer k . Previous algorithms only existed in the planar setting when k ≤ 4, and all of them rely on extensive case-by-case analysis based on different values of k . Our algorithm makes use of the connection between electrical transformations and homotopy moves and thus solves the problem in a unified fashion.

This article solves the problem of proximate fixed-time prescribed performance trajectory tracking for robot manipulators in the presence of bounded external disturbances and parametric uncertainties. A novel prescribed performance function (PPF) is first presented. A sliding surface with the prescribed performance tracking errors is constructed and a nonsingular proximate fixed-time terminal sliding mode prescribed performance control (FTSMPPC) is developed. It is proved that the position tracking error satisfies the prescribed performance boundaries all the time and globally converges to a preset small region centered on the origin within fixed time and then converges to the origin asymptotically. The proposed FTSMPPC provides faster transient performance quantified and higher steady-state accuracy by the proposed PPF. The effectiveness and improved performances of the presented approach are validated by simulations and experiments.

Motivated by the problem of optimization of force-field systems in physics using large-scale computer simulations, we consider exploration of a deterministic complex multivariate response surface. The objective is to find input combinations that generate output close to some desired or "target" vector. In spite of reducing the problem to exploration of the input space with respect to a one-dimensional loss function, the search is nontrivial and challenging due to infeasible input combinations, high dimensionalities of the input and output space and multiple "desirable" regions in the input space and the difficulty of emulating the objective function well with a surrogate model. We propose an approach that is based on combining machine learning techniques with smart experimental design ideas to locate multiple good regions in the input space.

In this paper, a new data augmentation algorithm, named Mask2Defect is proposed. Via prior knowledge based data infusing, this method is able to generate defects with varied features. Large volume of defects with different shapes, severities, scales, rotation angles, spatial locations, and part numbers can be generated in a controllable manner. These generated defects will work as teacher samples to fine-tune the inspection model, and automatically adapt it to a wider range of defects. To be specific, we first encode the prior knowledge into the teacher mask via the Industrial Prior Knowledge Encoder, and render the defect details according to the mask with the Mask-to-Defect Construction Network. Then, the Fake-to-Real Domain Transformation GAN is used to transform the rendered samples from the fake domain into the real defect domain. Experiments reveal that the synthesized image quality of our method outperforms the state-of-the-art generative methods, and the performance of the inspection model in defect classification and localization has also been improved by fine-tuned with the generated samples.

We consider codimension 2 sphere congruences in pseudo-conformal geometry that are harmonic with respect to the conformal structure of an orthogonal surface. We characterise the orthogonal surfaces of such congruences as either $S$-Willmore surfaces, quasi-umbilical surfaces, constant mean curvature surfaces in 3-dimensional space forms or surfaces of constant lightlike mean curvature in 3-dimensional lightcones. We then investigate Bryant's quartic differential in this context and show that generically this is divergence free if and only if the surface under consideration is either superconformal or orthogonal to a harmonic congruence of codimension 2 spheres. We may then apply the previous result to characterise surfaces with such a property., 15 pages

Knitting can efficiently fabricate stretchable and durable soft surfaces. These surfaces are often designed to be worn on solid objects as covers, garments, and accessories. Given a 3D model, we consider a knit for it wearable if the knit not only reproduces the shape of the 3D model but also can be put on and taken off from the model without deforming the model. This "wearability" places additional constraints on surface design and fabrication, which existing machine knitting approaches do not take into account. We introduce the first practical automatic pipeline to generate knit designs that are both wearable and machine knittable. Our pipeline handles knittability and wearability with two separate modules that run in parallel. Specifically, given a 3D object and its corresponding 3D garment surface, our approach first converts the garment surface into a topological disc by introducing a set of cuts. The resulting cut surface is then fed into a physically-based unclothing simulation module to ensure the garment's wearability over the object. The unclothing simulation determines which of the previously introduced cuts could be sewn permanently without impacting wearability. Concurrently, the cut surface is converted into an anisotropic stitch mesh. Then, our novel, stochastic, any-time flat-knitting scheduler generates fabrication instructions for an industrial knitting machine. Finally, we fabricate the garment and manually assemble it into one complete covering worn by the target object. We demonstrate our method's robustness and knitting efficiency by fabricating models with various topological and geometric complexities. Further, we show that our method can be incorporated into a knitting design tool for creating knitted garments with customized patterns.

This article studies a novel fixed-time track- ing controller for a class of degree-of-freedom (DoF) nonlinear systems with mismatched and matched perturbations. A modified fixed-time stable system (FTSS) is first proposed, which has an advantage in convergence rate over the existing results. Moreover, an adaptive version of fixed-time disturbance observer (DO) is established to eliminate the requirement for prior knowledge of the perturbation bounds. Based on the aforementioned FTSS and DO, a new fixed-time terminal sliding mode surface (FTTSMS) with singularity circumvention is constructed. Then a novel composite tracking controller is designed, which can guarantee the tracking errors to converge to zero within fixed time. The stabilities of both of the DO and the resulting closed-loop systems are rigorously proved by the Lyapunov theorem. Simulation results of two representative examples demonstrate the efficiency of the proposed approach.

In simulating viscous incompressible SPH fluids, incompressibility and viscosity are typically solved in two separate stages. However, the interference between pressure and shear forces could cause the missing of behaviors that include preservation of sharp surface details and remarkable viscous behaviors such as buckling and rope coiling. To alleviate this problem, we introduce for the first time the semi-implicit method for pressure linked equations (SIMPLE) into SPH to solve incompressible fluids with a broad range viscosity. We propose to link incompressibility and viscosity solvers, and impose incompressibility and viscosity constraints iteratively to gradually remove the interference between pressure and shear forces. We will also discuss how to solve the particle deficiency problem for both incompressibility and viscosity solvers. Our method is stable at simulating incompressible fluids whose viscosity can range from zero to an extremely high value. Compared to state-of-the-art methods, our method not only produces realistic viscous behaviors, but is also better at preserving sharp surface details.

A novel adaptive sliding mode observer-based control strategy is put forward for a type of uncertain singular systems subject to unknown state delay, input nonlinearity and uncertain perturbation in this article. Firstly, the unmeasured state is reconstructed by a particular observer without any inputs, from which a novel linear switching surface is provided. Subsequently, performance analysis of the resultant system on the switching surface is ensured under a new admissibility criterion. An associated adaptive control signal is synthesized to ensure that the established switching surface can be attained in finite moment. Finally, three numerical simulations are conducted to confirm the validity and superiority of the specified method.

Laser powder bed fusion (LPBF) is a promising technology that requires further work to improve productivity to be adopted more widely. One possible approach is to increase the laser power and scan ...

Defects on rail surfaces, which have become critical problems, need to be detected and removed as quickly as possible to ensure the fast, safe, and stable operation of trains. At present, although many solutions have been proposed to address these problems, the comprehensiveness, rapidity, and accuracy of defect detection remain unsatisfactory. This study aims to resolve these existing problems and accordingly proposes a multi-model rail surface defect detection system based on convolutional neural networks (MRSDI-CNN) from the standpoint of studying the squat on the rail surface. The convolutional neural networks utilized include the improved Single Shot MultiBox Detector (SSD) and You Only Look Once version 3(YOLOv3)--two types of one-stage networks. We expounded and analyzed the performance of the convolutional neural networks as well as their applicability to rail surface defect detection. We used a diverse range of rail defect sizes to improve the detection performance of the two deep learning networks, following which they could identify three types of squats in parallel with improved accuracy and without reduction of the detection speed. The experimental results confirm the effectiveness and superiority of the proposed method over those of previous studies.

The oscillatory motion on the ocean surface is a combination of a variety of different types of waves. The regularized waves are among them. Here, it is shown that they arise as solutions of the (1+2)-dimensional Benjamin-Bona-Mahony equation (BBME). Numerous works on (1+1)-dimensional BBME were carried in the literature. In this paper, we consider the (1+2)-dimensional non-autonomous BBME, with time-dependent coefficients. The model equation is completely new. Our objective is to find the exact solutions and investigate the relevant phenomena. To solve this issue, the extended unified method is used to find the exact solutions in the form of semi-self similar and self similar solutions. To solve this issue, similarity transformations are introduced. Here, the generalized unified methods (GUM) are also used in the symbolic computations. The numerical results of these solutions are evaluated and are shown graphically. Different wave patterns of regularized waves in shallow water, near ocean shores, are observed. Oscillatory waves and vector of lumps with troughs are shown. The time-dependent coefficients are used, here, to control the different wave patterns that take the forms of the multi-U shaped wave with basins with a trough. Further pattern formation occurs, which is in the form of two layers of lumps with troughs. Wave tunneling is also observed. These waves patterns are novel. The stability of the steady state solutions is analyzed. It is found that the stability depends significantly on the dispersion coefficient.

The (2+1)-dimensional interaction of a Riemann wave propagating along the y-axis with a long wave along the x-axis is described by the space-time fractional Calogero-Degasperis (CD) and fractional potential Kadomstev-Petviashvili (PKP) equation. It can be modeled according to the Hamiltonian structure, the lax pair with the non-isospectral problem, and the pain level property. The proposed equations are widely used in beachfront ocean and coastal engineering to describe the propagation of shallow-water waves, demonstrate the propagation of waves in dissipative and nonlinear media, and reveal the propagation of waves in dissipative and nonlinear media. In this paper, we have established further exact solutions to the nonlinear fractional partial differential equation (NLFPDEs), namely the space-time fractional CD and fractional PKP equations using the modified Rieman-Liouville fractional derivative of Jumarie through the two variable ( G ′ / G , 1 / G )-expansion method. As far as trigonometric, hyperbolic, and rational function solutions containing parameters are concerned, solutions are acquired when unique characteristics are assigned to the parameters. Subsequently, the solitary wave solutions are generated from the solutions of the traveling wave. It is important to observe that this method is a realistic, convenient, well-organized, and ground-breaking strategy for solving various types of NLFPDEs.

This paper proposes a new reconfigurable intelligent surface based three-dimensional beam tracking method to solve the beam tracking problems for the unmanned aerial vehicle with obstacles in communication channels. The proposed beam tracking method can not only regulate the reconfigurable intelligent surfaces to achieve the beam tracking of the obstructed communications, but also optimize the transmission efficiency of the communication. Firstly, a reconfigurable intelligent surface is proposed, which can correlate the transmission signals by adjusting the phase-shift matrix. Meanwhile, a new communication channel is constructed according to the reconfigurable intelligent surface, which consists of two parts. The first one is the channel between the unmanned aerial vehicle and the reconfigurable intelligent surface, the other is the channel between the reconfigurable intelligent surface and the ground base station. Note that the transmission performance of the communications can be optimized by adjusting the phase shift of each uniform linear array on the reconfigurable intelligent surface. Then, a new beam tracking method for the unmanned aerial vehicle with obstructed communications is proposed on the basis of the reconfigurable intelligent surface. By proposing the mixed genetic algorithm, the estimation accuracy of the azimuth and elevation angles is improved to enhance the performance of the beam tracking. Finally, the simulations are provided to verify the effectiveness of the proposed three-dimensional beam tracking method with reconfigurable intelligent surface.

Designing and the construction of a tunnel in urban areas has their own specific considerations. Usually, excessive settlement caused by tunneling during construction damages the adjacent infrastructures and utilities, especially if the tunnel is excavated by the new Austrian tunneling method (NATM). Thus, it’s important to make accurate predictions and effective control on tunneling-induced settlement. In this study, the soil’s Young’s modulus was modeled using a three-dimensional random field and coupled with a finite difference method (FDM) analysis to reveal the influence of scale of fluctuation (SOF) on the maximum surface settlement (Smax). To generate the field of soil’s Young’s modulus, the Fourier series method is employed and sensitivity studies are further performed via Monte-Carlo simulations (MCS). The results demonstrate both the mean value of Smax and its coefficient of variation (COV) increase from 28 mm to 31 mm and from 0.02 to 0.35 respectively, with an increasing horizontal SOF but they stabilize at higher values of SOF. Furthermore, the probability of failure increases as COV increases for each allowable limit greater than the verification FDM of Smax. It is observed that ignoring the spatial variability of soil’s properties leads to an underestimate of the risk of excessive surface settlement.

Ultrasonic surface rolling process (USRP) is one of the effective mechanical surface enhancement techniques. During the USRP, unstable static force will easily do harm to the surface quality. In order to achieve a higher surface quality on the part with a curved surface, an active and passive compliant USRP system has been developed. The compliant USRP tool can produce the natural obedience deformation along the part surface. Force control based on the fuzzy Proportional-integral-derivative (PID) method is then designed to maintain the static force during the USRP. Experiments have been performed on a real aero-engine blade with curved surface. It is proved that the deigned active and passive compliant USRP system can significantly reduce the force variation from 42.2 N to 4.2 N, and achieve a uniform surface quality after processing.

We demonstrate detection of ice formations on a road surface using a polarimetric radar operating at 87.5-92.5 GHz. The radar measures the scattering parameters of the surface at horizontal and vertical polarizations and their cross-polarization components. We demonstrate detection of ice for radar beam directed at up to 45⁰ angle of incidence with respect to the surface which allows for road surface characterization in front of a vehicle. The method used is based on a statistical approach where the 2-port scattering parameters are measured multiple times and used to calculate an average scatter coherence matrix representing the surface. The coherence matrix is then decomposed to eigenvalues/vectors, which are used to estimate polarimetric attributes such as target entropy(degree of randomness) and polarimetric pedestal (degree of depolarization). Through measurements of dry, ice-covered and wet road surfaces, we show that both entropy and depolarization are increased with respect to dry surface when a thin ice layer is formed, while their value decrease for the case of wet surface. It is also shown that these polarimetric attributes are not sensitive to surface roughness in dry conditions, minimizing the probability of false alarm due to road surface wear.

Unknown surface material classification can inform a robot about material properties, enabling it to interact with environments appropriately. Recent research has leveraged multimodal data using deep learning to improve the performance of surface material classification. In this paper, we present a deep learning model, multimodal temporal convolutional neural network (MTCNN), which integrates energy spectrum, dilated convolutions, and sequence poolings into a unified network architecture. The proposed model can learn material representations from auditory and multi-tactile (i.e., acceleration, normal force, and friction force) data generated by dragging a tool along surfaces, and distinguish unknown object surface materials into categories. For surface material data collection, a tool is also designed to detect different object surfaces. The performance of MTCNN is evaluated on a public dataset and the highest classification accuracy is 87.55%. A robotic curling example is provided to illustrate how the presented model helps the robot in manipulation.

The Gardner’s equation is the generalization of Kortweg-de Vries equation and modified Kortweg-de Vries equation having real life applications in different fields of science, such as, hydrodynamics, quantum field theory, etc. Moreover, it has applications in fluid mechanics where it explains surface and internal waves. This manuscript addresses application of the new ϕ 6 -model expansion method to Gardner’s equation for getting its solitary wave solutions. Such new results aid in getting noteworthy advances in various disciplines of science and technology. Periodic, kink, anti-kink, bright, dark, w-shaped and singular soliton solutions of the governing equation have been constructed. The proposed method takes into account a variety of closed form solutions using the Jacobi elliptic functions. The graphical illustration of some of the obtained solutions has been presented for a suitable choice of free parameters to depict the dynamic nature of the obtained wave solutions.

Based on the theory of elastic fracture and using direct modeling method, a numerical model was developed for solving the composite stress intensity factor of semi-elliptical cracks on exchanger outer walls with inclined angles. The model exchanger had an outer diameter of φ50 mm, inner diameter of φ44 mm and length of 300 mm. The values of crack plane inclination β (0°, 10°, 20°, 30°, 40° and 45°), crack depth a (0.5 mm, 0.75 mm, 1 mm and 1.25 mm), and crack shape ratio a/b (0.4, 0.5, 0.55, 0.6, 0.7, 0.8, 0.9 and 1.0) were obtained and 3D surface crack model was established. The results were significance for the evaluation of the remaining life of exchanger components.

Although surface with multiple holes (SMHs) is widely used in industrial components, the precise inspection of SMH is a knotty task due to the inefficiency of traditional surface inspection technology. Recently, a five-axis surface sweep scanning approach is emerging and shows great potential to boost the surface inspection efficiency by sensing surface in a continuous sweep scanning way. However, an efficient sweep scanning path should cater to the unique kinematic characteristics of the five-axis inspection system. In this article, we present an approach to automatically generate efficient five-axis sweep scanning paths for inspecting SMH. First, the skeleton of SMH is extracted along with the surface partitioned into several patches, based on which a guiding curve-based sweep scanning path can be defined for each surface patch. By modeling the skeleton of SMH as a directed Euler graph and finding a proper sequence to traverse the graph, a continuous five-axis sweep scanning path is then generated to sweep all patches without any transition among them. The nonsweeping time could be eliminated so that the sweep scanning efficiency is drastically improved in this way. Simulation and physical inspection experiments are conducted on two SMHs, showing that our method significantly outperforms existing approaches, such as the popular zigzag method and the method from the leading commercial software of RENISHAW.

The successful use of a microband electrode printed on a silicon internal reflection element to perform time resolved infrared spectroscopy is described. Decreasing the critical dimension of the microband electrode to several hundred micrometers provides a sub-microsecond time constant in a Kretschmann configured spectroelectrochemical cell. The high brilliance of synchrotron sourced infrared radiation has been combined with a specially designed horizontal attenuated total reflectance (ATR) microscope to focus the infrared beam on the microband electrode. The first use of a sub-microsecond time constant working electrode for ATR surface enhanced infrared absorption spectroscopy (ATR-SEIRAS) is reported. Measurements show that the advantage afforded by the high brilliance of the synchrotron source is at least partially offset by increased noise from the experimental floor. The test system was the potential induced desorption of an adsorbed monolayer of 4-methoxypyridine (MOP) as measured using step-scan interferometry. Based on diffusion considerations alone, the expected time scale of the process was less than 10 microseconds but was experimentally measured to be three orders of magnitude slower. A defect-mediated dissolution of the condensed film is speculated to be the underlying cause of the unexpected slow kinetics.

This study solves the attitude stabilization problem of 2-degree-of-freedom (2-DOF) helicopters by robustly assigning the variable-performance to the closed-loop system in the presence of the model-plant mismatches and load variations. The proposed approach re-formulates the original problem to a surface stabilization one which yields three contributions: a) the proposed attitude velocity observer forms a conventional Luenberger-type observer incorporating the parameter-independence and estimation gains specifically designed for causing the pole-zero cancellation, b) the pole-zero cancellation velocity control loop makes it possible to accomplish the surface stabilization task with the first-order closed-loop order, and c) the closed-loop analysis results demonstrate the attractive properties of the exponential performance recovery and convergence. The effectiveness of the proposed technique is verified using the experimental platform provided by the Quanser AERO.

One of the bottlenecks in flexible flank polishing is the non-uniform over-cuts problem caused by the difficulties of the polishing tool to conform to variable curvatures of the freeform surface along the polishing path. Consequently, it will significantly reduce the quality of finished surfaces and the service life of polishing tools. To solve the problem, a novel path generation method is proposed in this article, which not only gets the uniform over-cut at a single cutter location, but also keeps its uniformity over an entire polishing path. First, a tool orientation model is built on the freeform surface by analyzing the process of flexible flank polishing. Then, a novel indicator of over-cut uniformity is proposed with the developed Dupin indicatrix, and the tool orientation is determined by maximizing the indicator. Next, based on Taylor expansion, a polishing path generation method is presented with the consideration of over-cut uniformity. Finally, the proposed method is verified and analyzed relative to a comparison method by both virtual simulations and physical experiments. These results present a good consistency with each other and together provide strong support for the correctness, feasibility, and efficiency of the proposed method, which further contributes to surface quality and polishing tools service life.

The purpose of this paper is to present a shape preserving topology optimization method to prevent the adverse effects of the mechanical deformation on the Radar Cross Section (RCS). The optimization will suppress the variation of RCS on the perfect conductor surface by structural design. On the one hand, the physical optics method is utilized to calculate the structural RCS, which is based on the surface displacement field obtained from the finite element analysis of the structure. The corresponding design sensitivities of topology optimization are derived analytically and solved by the adjoint method. On the other hand, the RCS variation and mechanical performance are taken into account simultaneously by extending a standard compliance-based topology optimization model. Two optimization formulations are discussed in an illustrative example, where the influences of upper limits of the compliance and the RCS variation are considered. Two more examples are further tested to show the ability and validity of the proposed optimization method.

In leader-following formation, the leader plays a central role and is more vulnerable to malicious attacks. To effectively protect the leader, this paper investigates an event-based formation control problem of autonomous surface vehicles (ASVs) with multiple attackers and actuator failure. A novel adaptive formation keeping and interception scheme is developed for ASVs. In this scheme, a formation keeping controller and an interception controller are designed under a unified framework by sharing same event-triggered mechanism and fault-tolerant structure. To bridge these two controllers, a degree and distance driven formation interception (D3FI) strategy is designed by generating defenders. It is shown that with the proposed scheme, all attackers are intercepted without affecting formation keeping of remaining ASVs if the original topology is connected. Advantages of our scheme are: 1) stable controller switching is ensured during the formation cooperation; 2) the fault-tolerance is obtained with lower actuator updating frequencies and least number of adaptive parameters for each ASV.

A novel analytical propagation model for diffusive molecular communication systems in a three-dimensional fluid environment is derived. The model takes into account the geometry of a spherical receiver, the inclination angle, and the reaction rate of the receiver to accurately model the time-varying distribution and the number of absorbed information molecules at the receiver over a period of time. Accordingly, we derive an expression for the net number of accumulatively-absorbed information molecules at the surface of the receiver. We also study the bit error rate (BER) performance of diffusion-based molecular communications in the presence of the inter-symbol interference. Simulations based on the developed model show the impact of the transmitter-receiver distance, the reaction rate at the surface of the receiver and the diffusion constant of the environment on the fraction of absorbed molecules and the BER performance. A particle-based simulator is implemented to verify the accuracy of the proposed model. Moreover, our results are compared with that of a conventional model, where the geometry of the receiver and the inclination angle are ignored. It is shown that, especially at small transmitter-receiver separation distances, the proposed model predicts a significantly smaller number of absorbed molecules compared to the conventional models.

Visual inspection techniques for rail surface defects have become prevalent approaches to obtain information on rail surface damage. However, uneven illumination leads to illegibility of local information, and the change of the wheel-rail area results in the changeful background of the rail surface, both of which pose challenges to the visual inspection. This paper proposes a novel algorithm that detects rail surface defects via partitioned edge features (PEF). PEF eliminates the effect of uneven illumination by effectively extracting edge features and building homogeneous background on the rail surface. In the process of edge feature extraction, the thresholding based on adaptive partition of rail surface (APRS) plays an indispensable role. In APRS, the rail surface is adaptively partitioned into three types of regions according to the wheel-rail contact degree. After that, the dynamic threshold is set adaptively for each region type on the basis of the prior information of defect proportion. Subsequently, based on neighborhood information and fuzzy decision, the spatial information of adjacent pixels and the direction information of fracture edges are utilized to realize the effective recovery of incomplete defect contours. In addition, defect contours are precisely filled via a flexible combination of morphological hole filling operation and defect region extraction based on improved background difference. The accuracy of this PEF algorithm was confirmed by experiments and comparisons with related algorithms. The experiment results show that PEF detects defects with 92.03% recall and 88.49% precision, which achieves higher accuracy than the established detection algorithms for rail surface defects.