Volume 11, Issue 1

The fluidity of a cement mortar is a key factor for 3-D printing technology and cement-based materials. This paper introduces the measurement of the fluidity according China’s national standard, and a mathematical model is established to reveal main factors affecting the measure accuracy. The result shows the fluidity reveals mainly the rheological property of the mortar, but it is also affected by other measuring conditions, e.g., the vibration properties of the measuring table.

Novel results on conformable Bessel functions are proposed in this study. We complete this study by proposing and proving certain properties of the Bessel functions of first order involving their conformable derivatives or their zeros. We also establish the orthogonality of such functions in the interval [0,1]. This study is essential due to the importance of these functions while modeling various physical and natural phenomena.

Delayed response (delay of the elasticity) and time needed for initial stress can lead to relaxation and retardation phenomenon; this is because of the consistent behavior of viscoelastic fluid on thermodynamic principles. In this context, the aim of this article is to investigate the unsteady, incompressible, and Oldroyd-B viscoelastic fluid under wall slip conditions to know the hidden aspects of relaxation and retardation. The motion of the liquid is assumed over a flat vertical plate which moves through an oscillating velocity. A fractional model is developed by using the modern definition of the non-singular kernel proposed by Caputo and Fabrizio. We have obtained a semi-analytical solution of the non-dimensional model by using the Laplace transformation that satisfies our imposed suitable boundary conditions. We have tackled the Laplace inverse by employing Stehfest’s and Tzou’s algorithms. The velocity is enhanced by decreasing the estimations of relaxation time λ as well as slip parameter, and the temperature is also increasing for a considerable measure of the fractional factor. The effects of different fractional and physical parameters are plotted using Mathcad software based on the relaxation and retardation phenomenon of Oldroyd-B viscoelastic fluid.

In this article, the Ansys Workbench was used to carry out the finite element analysis of 15 kW wind turbine blades with different damaged positions and different damaged degrees. The results show that the change rate of natural frequency, displacement modes, and strain modes of the blades increased with the increase in the damage degree; the change rate of the natural frequency and displacement modes of the blade decreased with the increase in the speed, while the change rate of the strain modes increased; the change allocation ratio of the displacement modes and strain modes after the damage was more obvious at the damage location than other positions, which can be used to locate the damage position of the blade; the change allocation ratio of strain modes is higher than the change allocation ratio of displacement modes when the damage degree is the same, which means that the recognition effect of the strain modes is more significant than that of the displacement modes.

Concrete is one of the most extensively utilized building materials that can be produced, and has the potential to release a significant quantity of CO 2 into the environment. In this research, through studying lightweight (LW) concrete, attempts are made to produce environmentally friendly LW concrete with high strength using nanosilica rather than part of the cement and waste glass powder instead of aggregates. Recycled polypropylene fibers are used to increase the concrete’s compressive strength and nonlinear behavior. The use of glass powder was 20, 25, and 30% of the weight of aggregates, the consumption of nanosilica was 1, 2, and 3% of the weight of cement, and the consumption of recycled fibers (FORTA Ferro-Green) was 0.5, 1, and 1.5% of the weight of cement. Leca is also utilized as a LW aggregate. According to 7- and 28-day experimentation results and field emission scanning electron microscope analysis, the best sample had 1.5% fiber, 3% nanosilica, and 25% waste glass powder, and had a compressive and tensile strengths of roughly 1.7 and 1.6 times, respectively, those of the control specimen after 28 days. Also, using 3% nanosilica instead of cement can reduce greenhouse gas emissions by about 3%.

This work presents the existential and unique results for the solution to a kind of high-order fractional nonlinear differential equations involving Caputo fractional derivative. The boundary condition is of the integral type, which entangles both starting and ending points of the domain. First, the unique exact solution is extracted in terms of Green’s function for the linear fractional differential equation, and then Banach contraction mapping theorem is applied to prove the main result in the case of the general nonlinear source term. Then, our main result is demonstrated by an illustrative example, which shows its legitimacy and applicability. Furthermore, numerical-based semi-analytical technique has been presented to approximate the unique solution to the desired order of precision.

In this article, we are attracted to discover the multiple-optical soiltons in birefringent fibers for Radhakrishnan–Kundu–Lakshmanan equation (RKLE) by applying the Sardar-subequation method (SSM) and the new extended hyperbolic function method (EHFM). We construct the solutions in the form of exponential, trigonometric, and hyperbolic functions solitons solutions like mixed complex solitons and multiple-optical solitons solutions. In addition, singular periodic wave solutions are constructed, and the restraint conditions for the presence of soliton solutions are also defined. Moreover, the physical interpretation of the obtained solutions is disclosed in forms of 3D and 2D plots for different suitable parameters. The attained results indicate that the implemented computational scheme is straight, proficient, and brief and can be applied in more complex phenomena with the associate of representative computations. We have obtained several sorts of new solutions.

In this article, a prey–predator system is considered in Caputo-conformable fractional-order derivatives. First, a discretization process, making use of the piecewise-constant approximation, is performed to secure discrete-time versions of the two fractional-order systems. Local dynamic behaviors of the two discretized fractional-order systems are investigated. Numerical simulations are executed to assert the outcome of the current work. Finally, a discussion is conducted to compare the impacts of the Caputo and conformable fractional derivatives on the discretized model.

This article puts forward a facial expression recognition (FER) algorithm based on multi-feature fusion and convolutional neural network (CNN) to solve the problem that FER is susceptible to interference factors such as non-uniform illumination, thereby reducing the recognition rate of facial expressions. It starts by extracting the multi-layer representation information (asymmetric region local binary pattern [AR-LBP]) of facial expression images and cascading them to minimize the loss of facial expression texture information. In addition, an improved algorithm called divided local directional pattern (DLDP) is used to extract the original facial expression image features, which not only retains the original texture information but also reduces the time consumption. With a weighted fusion of the features extracted from the above two facial expressions, new AR-LBP-DLDP facial local features are then obtained. Later, CNN is used to extract global features of facial expressions, and the local features of AR-LBP-DLDP obtained by weighted fusion are cascaded and fused with the global features extracted by the CNN, thereby producing the final facial expression features. Ultimately, the final facial expression features are input into Softmax for training and classification. The results show that the proposed algorithm, with good robustness and real-time performance, effectively improves the recognition rate of facial expressions.

In continuation to what we started from developing the B-spline functions and putting them in n -dimensional to solve mathematical models in n -dimensions, we present in this article a new structure for the quintic B-spline collocation algorithm in n -dimensional. The quintic B-spline collocation algorithm is shown in three different formats: one, two, and three dimensional. These constructs are critical for solving mathematical models in different fields. The proposed method’s efficiency and accuracy are illustrated by their application to a few two- and three-dimensional test problems. We use other numerical methods available in the literature to make comparisons.

This work is an experiment to solve the fractional diffusion equation in two dimensions with a novel hybrid method. The method involves an amalgamation of the well-known differential transform method and the differential quadrature method. This work is not about the superiority of one method over the other, instead this is an idea that can be worked upon for possible greatness. Numerical examples are discussed with tables and figures.

Hybrid nanofluids, which are formed by dispersing two solid materials in a conventional fluid, have recently attracted the attention of researchers as they are able to improve the thermal properties. The present article, therefore, conducts a numerical analysis to investigate the heat transfer in magnetohydrodynamic three-dimensional flow of magnetic nanofluid (ferrofluid) across a bidirectional exponentially stretching sheet of hybrid nanofluid. Suitable similarity transformations convert the conservative equations for mass, energy, and momentum into ordinary differential equations. To solve these equations, a fifth-order Runge–Kutta–Fehlberg method is used. The findings revealed that with the enhancement of shape factor and generation/absorption parameters, the temperature over the surface increased. But if this parameter is decreased, the temperature profiles move towards the surface. Also, when exponent parameter is decreased, the temperature profiles go near the surface and a larger temperature exponent parameter means decreased heat transfer rate closer to the surface. The findings prove that skin friction coefficient corresponds to magnetic and suction/injection parameters and local Nusselt number is decreased with larger exponent parameter and heat absorption/generation parameter.

In this article, we report for the first time the application of a novel and extremely valuable methodology called the Rach–Adomian–Meyers decomposition method (MDM) to obtain numerical solutions to the rotational pendulum equation. MDM is a tool for solving nonlinear differential equations that combines both series solution and the Adomian decomposition method efficiently. We present a simple and highly accurate MDM-based algorithm and its numerical implementation via a one-step recurrence approach for obtaining periodic solutions to the rotational pendulum equation. Finally, numerical simulations are performed to demonstrate the efficiency and accuracy of the proposed technique for both large and small amplitudes of oscillation.

A cone crusher is a machine that crushes rock materials with high efficiency and low power consumption; it is one of the typical road construction equipment. To improve the production efficiency, mechanical performance, and crushing performance of the cone crusher, thus increasing profit, this study used Discrete element method (DEM) particle analysis software to optimize the structure of the moving cone, studied the crushing effect of the crusher, and carried out kinetics analyses. Based on DEM, the structure of the cone crusher cavity was analyzed and optimized. A Y51 cone crusher was selected as a representative example to study its moving cone structure. By analyzing the factors that affect the performance and efficiency of the crusher, the precession angle, base angle, shape, and rotational speed of the moving cone were optimized. Using the Genetic Algorithm-Support Vector machine method (GA-SVW), the optimal combination of parameters was determined, and the key parts of the crusher were thus optimized.

This article discusses the stability results for solution of a fractional q -integro-differential problem via integral conditions. Utilizing the Krasnoselskii’s, Banach fixed point theorems, we demonstrate existence and uniqueness results. Based on the results obtained, conditions are provided to ensure the generalized Ulam and Ulam–Hyers–Rassias stabilities of the original system. The results are illustrated by two examples.

Since it is difficult for manual recording to track the rapid change of indication of the power meter, the power meter images are collected by the camera and automatically recognized and recorded to effectively overcome the disadvantages of manual recording. However, the complex scene lighting environment and smearing character shadows make it difficult to transfer captured images directly to convolutional neural networks for character recognition. A smear character recognition method of side-end power meter under complex lighting conditions is proposed in this article. First, the uneven illumination image enhancement algorithm is studied. Through the estimation of the illumination component of the image, the fusion weight is calculated by the principal component analysis for multiscale fusion, and the up-sampling and down-sampling are adopted to reduce the calculation of the algorithm and achieve the rapid image enhancement. A convolution neural network framework based on deep learning is proposed to realize the segmentation of smear characters, and the final segmented individual characters are fed into a network to identify the meter readings. The experimental results show that the proposed smear character recognition method has fast recognition speed, and the recognition rate of samples with the smear character and complex illumination reaches 99.8%, which meets the requirements of power meter character recognition and is better than other algorithms.

With the emphasis on the properties of titanium dioxide nanoparticles and numerous applications of chemical reactive distilled water due to bioconvection in the industries, nothing is known about the significance of adding titanium dioxide nanoparticles to an existing distilled water conveying aluminum oxide and zinc oxide nanoparticles when viscous dissipation, heat source, and higher buoyancy forces and thermal radiation are substantial. The governing partial differential equations that model the motion of both transport phenomena mentioned earlier were transformed into ordinary differential equations using appropriate similarity transmutations and solved with bvp4c (MATLAB built-in function). Multiple linear regression ( i.e. , a statistical tool used to explain outcomes related to engineering parameters of interest) was adopted for a deep scrutinization and exploration. The outcome of the analysis suggests that the thermal radiation parameter can be used to control the heat transferred via convection in the fluid flow. It is detected that the magnetic field parameter and volume fraction of nanoparticle parameters are useful to reduce the shear stress near the surface. The heat source ameliorates the fluid temperature, and the concentration of the fluid decreases with the rise in the chemical reaction parameter. Worthy to conclude that the Peclet and Schmidt number escalates the density number of motile microorganisms.

Obtaining the numerical approximation of fractional partial differential equations (PDEs) is a cumbersome task. Therefore, more researchers regarding approximated-analytical solutions of such complex-natured fractional PDEs (FPDEs) are required. In this article, analytical-approximated solutions of the fractional-order coupled Burgers’ equation are provided in one-, two-, and three-dimensions. The proposed technique is named as Iterative Shehu Transform Method (ISTM). The simplicity and accurateness of the method are affirmed through five examples. Graphical representation and tabular discussion are provided to compare the exact and approximated results. The robustness of the proposed regime is also validated by error analysis. In the present work, approximated and exact solutions are compared to verify the validity of the proposed scheme. Error analysis is also provided through which the efficiency of the proposed scheme can be assured. Obtained errors are lesser than the compared results. Graphical abstract

The present physical problem has a significant number of applications in intra-uterine fluid motion with tiny particles in a nonpregnant uterus, and this situation of fluid motion is very important in examining the embryo motion in a uterus. Due to these real-life applications, in the current investigation, a perturbation-oriented numerical investigation has been performed to describe the characteristics features of velocity, pressure rise, and trapping bolus through streamlines in a tapered channel under a porous medium. The present physical model results in the governing two-dimensional coupled nonlinear flow equations under low Reynolds number and long-wavelength approximations. A suitable equation for stream function is derived and a regular perturbation scheme is employed to produce the numerical solutions in terms of pressure rise, velocity, and streamlines for various values of physical parameters. The current investigation depicts that the enhancing Darcy parameter upsurged the pressure field, and the increasing power-law index suppressed the pressure field in the flow regime. The rincreasing channel width significantly diminished the velocity field at the central portion of the channel. The size of the trapping bolus suppressed for the enhancing values of Weissenberg number. In addition, the size of the trapping bolus increased for the magnifying values of wave amplitudes. Finally, current numerical solutions reasonably agree with the previously published results in the literature, and this fact confirms the accuracy of the present problem.

In this article, the bond performance of recycled coarse aggregate concrete with rebar after freeze–thaw cycles is analyzed by the ABAQUS finite element method. The result shows that the finite element simulation value of the ultimate bond strength of recycled aggregate concrete specimens is in good agreement with the experimental value, while the agreement between the finite element simulation value of the peak bond slip of recycled aggregate concrete specimens and the experimental value is low; the bond strength between rebar and recycled aggregate concrete increased with the increase of concrete strength and concrete cover depth; the calculation formula for the bond strength between recycled aggregate concrete specimens with different concrete strengths and different concrete cover depth after freeze and thaw cycles are obtained.

In order to improve the performance of edge detection for noisy images, a new edge detection method based on nonlinear structure tensor is proposed. First, the tensor product of noisy images is calculated. The tensor product is diffused according to the image gradient, which depends on the tensor product itself. Finally, the eigenvalues and eigenvectors of the diffusion tensor product are calculated, and the edges of the image are detected according to the eigenvalues. The method is compared with other methods. The experimental results show that the average number of edge points detected by method 1, method 2, method 3, and this method are 513.7, 530.0, 509.0, and 719.3, respectively. The average detection time of method 1, method 2, method 3, and this method were 65.3, 54.9, 57.3, and 33.6 s, respectively. When the number of edge detection is the largest, the average detection time of this method is significantly smaller than that of the three comparison methods. Therefore, this method is more suitable for edge detection of noisy images, and the performance of this method is better than that of the comparison method and can improve the performance of edge detection of noisy images.

The synchronverter is a device used in some microgrids to perform self-synchronization and represent the behavior of a synchronous machine. However, the original control has been proposed for balanced networks, which is not present in all distribution systems. In unbalanced networks, the negative sequence may appear and generate a double frequency oscillation when delivering power or a non-symmetrical current from the inverter; thus, it must compensate unbalanced load. Therefore, this article shows that a synchronverter can be synchronized using the positive sequence even when there are voltage unbalances. The proposed strategy was simulated in the Simulink-Matlab© software, considering an unbalanced power grid with a single inverter and a load. The results confirm the effectiveness of this strategy, as the synchronverter can follow the grid frequency and the wave shape amplitude after starting the frequency droop control.

We relate this article to the emerging idea of distinguishability of conformable linear hybrid time-invariant control systems. To obtain the necessary and sufficient conditions of α \alpha -distinguishability for fractional cases, we develop the Leibnitz rule for conformable derivatives. Furthermore, with the help of a study of Laplace techniques, a more simple criterion of α \alpha -distinguishability for the fractional linear system is developed.

Various new exact solutions to ( 3 + 1 ) \left(3+1) -dimensional Wazwaz–KdV equations are obtained in this work via two techniques: the modified Kudryashov procedure and modified simple equation method. The 3D plots, contour plots, and 2D plots of some obtained solutions are provided to describe the dynamic characteristics of the obtained solutions. Our employed techniques are very helpful in constructing new exact solutions to several nonlinear models encountered in ocean scientific phenomena arising in stratified flows, shallow water, plasma physics, and internal waves.

Smoking has become one of the major causes of health problems around the globe. It harms almost every organ of the body. It causes lung cancer and damage of different muscles. It also produces vascular deterioration, pulmonary disease, and ulcer. There is no advantage to smoking except the monetary one to the tobacco producers, manufacturers, and advertisers. Due to these facts, a passive verse active exposure of mathematical smoking model has been analyzed subject to the dynamical aspects for giving up smoking. In this context, mathematical modelling and qualitative analysis have been traced out for smoking model having five classes. Mathematical forms of smoke absent and smoke present points of equilibrium have been calculated for knowing optimal and dynamical control. By making use of the Lyapunov function theory, we have shown the global asymptotic behavior of smoke-free equilibrium for threshold parameter R 0 < 1 {R}_{0}\lt 1 . The ability to observe theoretically and through graphs is invoked to study the general behavior of single smoke present point. To make effective, vigorous, authentic, and stable strategies to control the disease, we have performed the sensitivity examination of threshold parameter and disease, present apartments.

In the present article, we geometrically and analytically examine the mutual impact of space-time Caputo derivatives embedded in (1 + 2)-physical models. This has been accomplished by integrating the residual power series method (RPSM) with a new trivariate fractional power series representation that encompasses spatial and temporal Caputo derivative parameters. Theoretically, some results regarding the convergence and the error for the proposed adaptation have been established by virtue of the Riemann–Liouville fractional integral. Practically, the embedding of Schrödinger, telegraph, and Burgers’ equations into higher fractional space has been considered, and their solutions furnished by means of a rapidly convergent series that has ultimately a closed-form fractional function. The graphical analysis of the obtained solutions has shown that the solutions possess a homotopy mapping characteristic, in a topological sense, to reach the integer case solution where the Caputo derivative parameters behave similarly to the homotopy parameters. Altogether, the proposed technique exhibits a high accuracy and high rate of convergence.

This article is aimed to investigate the peristaltic pumping of a two-layered model in a two-dimensional channel. The core region occupies Casson fluid, while the porous medium occupies the peripheral region. The fluid flow in a porous medium was described with a suitable model using the Brinkman-extended Darcy equation. In the interface between fluid and porous medium, a shear stress jump boundary condition was applied. Closed-form solutions were obtained in both regions (core and peripheral). The physical quantities of peristaltic flow, such as axial velocity, pumping and change in the interface, were derived and explained. The fluid flow was analyzed by different physical parameters such as viscosity, permeability, porosity, Casson parameter and Darcy number. It is observed that the peristalsis mechanism has greater pressure in a two-layered model containing a non-Newtonian fluid in contact with a porous medium compared to a viscous fluid in the peripheral layer. It was observed that pumping decreased with the increase in Darcy number and an increase in shear stress jump constant resulted in increasing the pumping. The outcomes of the pumping phenomenon may be helpful for understanding the fluid flow aspects of blood flow in capillaries.

In order to classify data and improve extreme learning machine (ELM), this study explains how a hybrid optimization-driven ELM technique was devised. Input data are pre-processed in order to compute missing values and convert data to numerical values using the exponential kernel transform. The Jaro–Winkler distance is used to identify the relevant features. The feed-forward neural network classifier is used to categorize the data, and it is trained using a hybrid optimization technique called the modified enhanced Invasive Weed, a meta heuristic algorithm, and Cuckoo Search, a non-linear optimization algorithm ELM. The enhanced Invasive Weed optimization (IWO) algorithm and the enhanced Cuckoo Search (CS) algorithm are combined to create the modified CSIWO. The experimental findings presented in this work demonstrate the viability and efficacy of the created ELM method based on CSIWO, with good experimental result as compared to other ELM techniques.

In this study, the nonlinear analytical analysis of a two-layer geometry made of functionally graded materials (FGMs) is examined. FGMs can be used in various engineering applications, such as building materials in civil engineering, due to the advantages of smoothly varying properties. The equations of stresses and displacements in the radial and circumferential directions ( r ,  θ ) have been found by extracting the governing equations and defining them in the form of power-exponential functions. In the present paper, modulus of elasticity and heat conductivity coefficient (except for Poisson’s coefficient) are assumed to be expressed by power-exponential functions in radial and circumferential coordinates. The temperature distribution is also considered as a function of radius ( r ) and angle ( θ ). The analysis is implemented based on the theory of small elastic deformations and with the assumption of a very large length in plane strain mode. To analyze the governing equations, first, the heat transfer equations are obtained, and then the Navier’s equations are derived by combining the stress–strain, strain–displacement, and stress equilibrium equations. Then, the displacement equations and stress equations are obtained by solving the Navier’s equations. A direct method is presented to solve these equations analytically.

Geometrically nonlinear analysis is required for resolving issues such as loading causes failure and structure buckling analysis. Although numerical methods are recommended for estimating the exact solution, they lack the necessary convergence in the presence of bifurcation points, making it challenging to find the equilibrium path using these methods. Thus, the modified energy method is employed instead of the numerical method, frequently used to solve quasi-static problems with nonlinear nature and bifurcation points. The ultimate goal of this study is to determine the critical load of structures through the modified energy method rather than other methods in which the relationship between force, displacement, and constraint is used to solve the problem. This study first describes the energy method for this type of problem and then details its computational steps progressively. This method yields numerical results when applied to numerical examples such as truss and frame structures and coded in MATLAB software. These findings are compared to the analytical results. The energy method is more precise than the alternative methods and superior to the Newton–Raphson method at crossing the load–displacement curve’s bifurcation points.

Fins are commonly utilized to enhance (dissipate) heat in various engineering systems that include heat exchangers. In the present investigation, the impact of multi-boiling and thermo-geometric factors on a convective–radiative rectangular porous fin subjected to the temperature-dependent thermal conductivity of linear and non-linear variations is discussed extensively. The governing equations describing the problem were formulated with the aid of Darcy law. Similarity variables were employed to reduce the models to non-dimensional form. The solution of the governing dimensionless equation is approximated using the RK4 and spectral local linearization methods. Before parametric analysis, the agreement between the two numerical methods was established. Findings reveal that the non-linear variation of thermal conductivity shows better thermal efficiency than the linear variation. An improvement in the multi-boiling heat transfer parameter retards the temperature distribution of the fin. Furthermore, increasing the thermo-geometric parameter will result in a progressive decrease in the temperature of the fin. The results obtained in this work will aid in the design of heat exchangers and other heat transfer equipments.

Designing a safe, collision-free navigation route is critical for unmanned ships. This article applies the path planning method to the generation of collision avoidance paths for unmanned ships. Since the path length function is obtained from the distribution points constructed in space, it is necessary to transfer the safe domain of the unmanned ship to the obstacle, treating the unmanned ship as a particle. Then, the constructed artificial neural network (ANN) is applied to compute the collision penalty function for distribution points and obstacles. Furthermore, an evaluation function including the path length function and collision penalty function is designed, and the optimal path is obtained by computing the minimum value of the evaluation function. Meanwhile, the simulated annealing method is introduced to optimize the activation function of the output layer of the ANN to improve its classification performance and suppress the local minima problem. Finally, the application of ANN in ship autonomous dynamic collision avoidance path planning is demonstrated in two types of experiments. Among them, when avoiding static obstacles, the minimum safe passing distance between the two ships reaches 30 m; when avoiding dynamic obstacles (navigating ships), the minimum safe passing distances between the two ships in the head-on situation and the overtaking situation are 378 and 430 m, respectively.

The strength of soil can significantly increase by stabilisation with binders. Adding binders in correct proportions to improve soil parameters is of paramount importance for earthworks. In this article, we presented a framework to explore strength characteristics of soil stabilised by several binders and evaluated using applied geophysical methods by estimated P-wave velocities. The core of our work is a systematic assessment of the effects on clay stabilisation from various binders on shear and compressive strength. The binders were combined from four stabilising agents: (i) CEM II/A, a Portland limestone cement; (ii) burnt lime; (iii) lime kiln dust (LKD) limited up to 50%; and (iv) cement kiln dust (CKD). Shear strength has shown a nonlinear dependence as an exponential curve with P-waves. Natural frequency analysis was modelled to simulate resonant frequencies as eigen values. Variations in strength proved that CEM II/A-M (Recipe A, 100% CEM II) has the best performance for weak soil stabilisation followed by the combinations: Recipe B (70% CEM II/A-M, 30% LKD), Recipe C with added 80% CEM II/A-M and 20% CKD, and Recipe D (70% CEM II/A-M 30% CKD). Recipe B has shown high values with maximum uniaxial compressive strength (UCS) at 13.8 MPa. The Recipe C was less effective with the highest value of UCS as 8.8 MPa. The least strength was shown in Recipe D, where UCS has maximal values of 3.7 MPa. The specimens stabilised by Recipe B demonstrated the highest P-wave velocity at 2,350 m/s, while Recipe C and Recipe D showed the highest P-wave velocity at 1,900 and 1,550 m/s. All specimens shown a gain of UCS with sharply increased P-wave speed during the 3 days of curing. The study contributes to the development of methods of soil testing in civil engineering.

In this article, thermal behavior analysis of nonlinear fin problem with power-law heat transfer coefficient is studied to determine temperature distribution. This new supposition for the thermal conductivity, exponential-law temperature dependent, makes it to be nonlinear that is a general case in some sense. It is shown that the governing fin equation, that is, a nonlinear second-order differential equation, is exactly solvable with proper boundary conditions. To this purpose, the order of differential equation is reduced and then is converted into a total differential equation by multiplying a proper integration operant. An exact analytical solution is given to advance physical meaning, and the existence of unique solution for some specific values of the parameters of the model is demonstrated. The results are shown graphically. It is observed that fin efficiency is decreasing with respect to the power-law mode for heat transfer.

In the present study, nonlinear dynamic process data are mapped into the kernel state space by kernel gauge variable analysis method to obtain decorrelated state data. The time-lapse covariance matrix of the state data is weighted and summed to obtain the time-lapse structure matrix of the state data, and then supervised kernel independent component analysis (SKICA) is established, the independent component feature data is extracted from the status data and the monitoring statistics are constructed to detect the process faults. The data show that kernel independent component analysis (ICA) method (KICA) method can detect slow fault faster than the ICA method, except that the statistical detection ability of F3 and FS is reduced, and the KICA method can significantly improve the detection performance of other faults and statistics. By analyzing the detection results of SKICA method, it is obvious that in the detection process of all five kinds of slow faults, the fault detection capability of SKICA is better than that of ICA and KICA. The results of continuous stirred reactor simulation system show that, compared with the basic linear process, the slow fault detection has a good monitoring performance, it can detect the small deviation in the process sensitively and give alarm information to the slow fault in time, to improve the fault detection rate.

In order to solve the problems of data acquisition, quantitative analysis and model solving in the field of construction schedule optimization, a construction schedule optimization system based on genetic algorithm was constructed. On this basis, the construction schedule two-stage multi-objective optimization models of “duration-cost” and “fixed duration-resource equilibrium” are established, which aim at the lowest cost and resource equilibrium. Through the investigation and analysis of the project contract documents, the energy consumption and cost of the normal construction and emergency construction state of the contract plan of the basic project part (from the beginning of precipitation activities to the end of +0) are obtained. This section was optimized for the analysis. The genetic algorithm is used to solve the model, and the optimal duration of each process and the optimal start time of non-critical process are determined. The feasibility and effectiveness of the system and model are verified by practical application in the actual project, which provides support for determining the construction schedule scientifically and reasonably and helps to improve the construction schedule technical application effect and construction schedule management level.

To study the nonlinear characteristics of the modal recognition of civil engineering parameters, a method of nonlinear recognition of the parameters of characteristics based on LMD is proposed. The LMD method is applied to decompose the acceleration response signals of the disturbing structure of the building, to obtain the PF components, the instantaneous frequency, and the instantaneous amplitude of each PF component, to determine the modal natural frequency and damping coefficient. To determine the modal parameter based on the LMD, the calculation and analysis results are presented as follows: the frequency of the components fluctuates between the fifth and sixth models, which shows that the components contain the reaction of the fifth and sixth design modes. This is because these two modes (3.101 Hz and 3.147 Hz) are very close to each other, which makes it difficult to distinguish between the responses of these two modes by the LMD method. The frequency of the components is always stable (the first 2.5 s), which indicates that during this period the responses of modes 5e and 6e do not dampen, and the ratio between them in the PF1 components does not differ much. The component frequency curve shows an interesting phenomenon. Starting from about 3.8 s, the frequency curve gradually approaches the first mode, and only the frequency of the first mode is about 6 s, which indicates that the response of the first mode still exists and makes up a significant proportion. Modular response, caused by the damping, is only detected in the first half of the 10 s response, after which it is verified from the nonlinear characteristics of the LMD parameter recognition method that half of the third-order modal response on the scale is very low and almost equal to zero, and despite problems with dense frequency separation mode in the LMD method, the frequency responses of its PF components may reflect the mode combination phenomenon and reflect the duration of each mode throughout the response.

In order to explore the influence of cold heading equipment based on polyvinylidene fluoride (PVDF) polymer sensing material on steel ball stamping, a new method was proposed to reflect the defects of cold heading forming of steel ball by load signal. PVDF piezoelectric film is used as the sensor design of force and support structure of steel ball cold heading electromechanical sensor model. PVDF piezoelectric thin film force sensor is used for the structural optimization and simulation. The structural parameters affecting the natural frequency are numerically analyzed by MATLAB software. The mapping relationship between the external load and the output load of the sensor is obtained by using ANSYS software, and the simulation curve of the natural frequency of the sensor is compared with the theoretical curve to verify the factors affecting the natural frequency. The results show that the nonlinear error of sensors refers to the measured curve and the maximum deviation between the fitting line and the percentage of full-scale output.

The author in order to solve the problem of optimizing the accuracy of mechanical equipment failure detection proposes a vibration signal collection and computer simulation detection for mechanical equipment failure. Using wavelet domain Wiener filtering-based mechanical equipment fault detection method, the author first combined Wiener filtering and wavelet threshold filtering, established a vibration signal collection model for mechanical equipment, obtained the true signal and the filtered signal error and fusion of the principle of wavelet threshold filtering to perform orthogonal wavelet transform on noisy signals, and through the principle of fast independent component analysis to separate the vibration signals of mechanical equipment, build the initial separation matrix of the signal with unit variance, and found the estimated value of the source signal; the collection of vibration signals of mechanical equipment is completed according to the estimated value, realizing the optimization of the detection of mechanical faults and equipment failures. The simulation results prove that the signal-to-noise ratio of the vibration signal of mechanical equipment collected by this method is higher than 15.7% of the signal-to-noise ratio based on the FastICA method; this is mainly because when this method is used for anti-interference collection of vibration signals of mechanical equipment, combining the principle of fast independent component analysis to separate the vibration signals of mechanical equipment, construct the initial separation matrix of the signal with unit variance. Using the proposed method for signal acquisition can greatly reduce the error, and it can provide effective support for fault detection of mechanical equipment.

In order to seek a refined model analysis software platform that can balance both the computational accuracy and computational efficiency, a CPU-GPU heterogeneous platform based on a nonlinear parallel algorithm is developed. The modular design method is adopted to complete the architecture construction of structural nonlinear analysis software, clarify the basic analysis steps of nonlinear finite element problems, so as to determine the structure of the software system, conduct module division, and clarify the function, interface, and call relationship of each module. The results show that when the number of model layers is 10, the GPU is 210.5/s and the CPU is 1073.2/s, and the computational time of the GPU is significantly better, with an acceleration ratio of 5.1. For all the models, the GPU calculation time is much less than that of the CPU, and when the number of model degrees of freedom increases, the acceleration effect of the GPU becomes more obvious. Therefore, the CPU-GPU heterogeneous platform can more accurately describe the nonlinear behavior in the complex stress states of the shear walls, and is computationally efficient.

Neural network modeling for nonlinear time series predicts modeling speed and computational complexity. An improved method for dynamic modeling and prediction of neural networks is proposed. Simulations of the nonlinear time series are performed, and the idea and theory of optimizing the initial weights and threshold of the GA algorithm are discussed in detail. It has been proved that the use of GA-BP neural network in cigarette sales forecast is 80% higher than before, and this method has higher accuracy and accuracy than the gray system method.

To study the radiation effect of Fermi–Dirac (F–D) semiconductor devices based on numerical simulation, two methods are used. One is based on the combination of F–D statistical method and computer simulation. The method discusses the influence of temperature and light energy on the carrier number by starting from an intrinsic silicon semiconductor and carries out computer simulation on the carrier number in intrinsic silicon semiconductor. TID Sim, a three-dimensional parallel solver for ionizing radiation effects of semiconductor devices, is developed. The ionization radiation damage of typical metal oxide semiconductor (MOS) FET NMOS and bipolar transistor GLPNP is simulated. It was proved that the variation trend was close to a straight line in the temperature range (278–358 K) studied in this article. The results are consistent with those of the statistical distribution of semiconductor carriers. This method is suitable for calculating the number of semiconductor carriers, and it is an effective method to study the problems related to carrier distribution.

In order to improve the level of intelligent rehabilitation training equipment and assist patients to effectively restore the walking function, a motion-assisted training control system based on nonlinear mechanics is proposed. According to the robot direction of lower limb rehabilitation equipment studied in this article, a stable, safe, and reliable mechanical structure system is designed to optimize the structure, and the anti-overturning stability of the robot static system and dynamic system is analyzed. Then, through the human-computer interaction system, the robot automatically realizes the automatic forward and backward, left and right turn, anti-overspeed, anti-fall, and other functions. A joint simulation platform of rehabilitation robot speed control was built using MATLAB and ADAMS to verify the effectiveness of the designed control algorithm. The results showed that users slowly increased their training speed from 1 to 5, walking at approximately 0.3 m/s. The user adapts slowly during the use process, and through training, and the walking speed is improved slowly. Therefore, the lower limb rehabilitation equipment training robot is highly applicable, convenient for operation, with good robot control performance, high stability, and good mobility ability.

In order to understand the real environment and specific needs of China’s current tobacco industry, master the signal information in the tobacco supply chain, and timely discover the source of the tobacco supply chain, this paper puts forward the detection method of anti-counterfeiting at the source of the tobacco supply chain. Based on this, this article constructs a nonlinear discrete system model, which mainly studies the logistics information existing in the tobacco supply chain, utilizes the noise existing in the tobacco supply chain information obtained by EKF filtering, and combines it with Support vector machine data analysis method. The results showed that out of 450 sample tests, 0 real sample errors and 1 misuse of 49 false samples, with a total detection rate of up to 100% was achieved. The results show that the nonlinear discrete system model is better, has higher detection effect of tobacco supply source, and improves the detection accuracy.

In order to realize the safety status monitoring and health management of aeroengine fuel system, a performance degradation detection method of aeroengine fuel metering device was proposed. Aiming at the internal leakage, external leakage, static friction increase, dynamic friction increase, differential pressure controller degradation, and other common performance degradation modes of fuel metering devices, a residual life estimation method based on random forest support vector regression (RF-SVR) was proposed. The SVR model optimized by RF feature selection is used to estimate the remaining life of components. The simulation results show that the mean square error of remaining useful life (RUL) estimation is less than 1.8, the average percentage error is less than 3%, and it has high prediction accuracy. Therefore, the evaluation and verification of the internal leakage health indicators proposed in this article screen out the health indicators that are sensitive to changes in performance degradation parameters but insensitive to changes in environmental and structural parameters and provide decision-making reference for onsite maintenance of engine fuel metering devices.

This article solves the issue of long extraction time and low extraction accuracy in traditional moving image contour feature extraction methods. Here authors have explored deformable active contour model to research the image processing technology in scientific research and the application of multiple sports and the method. A B-spline active contour model based on dynamic programming method is proposed in this article. This article proposes a method of using it to face image processing and extracting computed tomography (CT) image data to establish a three-dimensional model. The Lyapunov exponent, correlation dimension and approximate entropy of the nonlinear dynamics algorithm were used to extract the features of eight types of motor imagination electroencephalogram (EEG) signals. The results show that the success rate of pose reconstruction is more than 97% when the contour extraction quality is relatively ideal. The method is also robust to image noise, and the success rate of pose reconstruction can reach 94% when the video image has large noise. The execution efficiency is sub-linear, which can basically meet the requirements of real-time processing in video-based human posture reconstruction. The proposed method has a low error rate in the calculation of curvature features, effectively reduces the time for extracting contour features of moving images, and improves the accuracy of feature information extraction.

In order to realize and design a software monitoring and early warning system for the Internet of Things (IoT), this paper establishes a “trinity” control platform integrating PLC, WINCC, and MATLAB based on nonlinear technology and realizes the proportion integration differentiation (PID) control based on the RBF neural network tuning on this platform. Based on the framework of the trinity control platform, the PID control system set by the radial basis function (RBF) neural network and the STEP7 virtual object programming of the control platform are designed and realized. The experimental data update cycle is 0.5 s to record 1,000 data item objects, U is the control quantity, which is associated with the U communication driver variable in WINCC, and the corresponding storage address in the PLC is MD200; Yout is the controlled quantity, which is related to the Yout communication driver variable in WINCC, and the corresponding storage address in the PLC is MD100; start is the control switch, associated with the start communication driver variable in WINCC, corresponding to the storage address in the PLC of M0.1; reset is the reset control switch, It is associated with the reset communication driver variable in WINCC, and corresponds to the storage address in the PLC as M0.0. KP, KI, KD, and TIME correspond to three real-time PID parameters and are the cycle time in MATLAB (used for the X -axis of trend graphing), and are the variables of the communication driver. The addresses in the PLC are MD20, MD24, MD28, and MD32. It shows that for these three software programs, the update cycle of the data in the respective storage areas must be consistent, the program control cycles in MATLAB and PLC need to be consistent, and the transmission of parameters must be correctly implemented in a control cycle according to the programming logic sequence, in order to realize the design of an IoT software monitoring and early warning system.

This article addresses the challenges in the periodic law of high-frequency motion and effectively identifies the influence of high-frequency motion on ship dynamic positioning. The main aim of the article is to design a dynamic positioning filter by applying nonlinear adaptive technology to eliminate the disturbance to the ship’s dynamic propulsion system. This article proposes a method to control the ship’s dynamic positioning and apply nonlinear adaptive technology in the dynamic positioning control in order to obtain the ship’s state and reference coordinate system. Further, a mathematical model and a dynamic environmental model in ship dynamic positioning control are analyzed in this work. The control index model is located by the experimental data, and the control performance is improved within the allowable range. The experimental analysis revealed that if the initial position of the ship is (0, 0, 0), then the desired position is (100, 100, 0). The operating ranges of –0.6 × 10 7 to 0.6 × 10 7 , –0.4 × 10 7 to 0.4 × 10 7 , and –5.6 × 10 8 to 5.6 × 10 8 are used. The ranges of motion of –150 to 150, –130 to 130, and –5 to 5 are observed, respectively, along with a wind disturbance force of 8 m/s. The wave disturbance force of 1 m/s is observed along with 90° wind. It was observed from the experimentation that the ship could basically achieve a stable operation and control the environmental disturbance within the error range. The outcomes reveal that the proposed dynamic positioning model based on nonlinear adaptive technology has strong stability and accuracy.

In order to study the real-time control research of laboratory information system based on nonlinear programming, by analyzing the role played by the laboratory information management system (LIMS) in quality management, and the relationship with quality control, put forward the functions that LIMS should set up and possess in the management of controlled documents, processing of inspection data, etc. , an accurate and reliable method to ensure the test results. It has been verified that the system can meet the performance requirements of 350 virtual concurrent users, its memory usage and CPU usage are within acceptable limits, the response time of important operations of each module of the system is within 3 s. The average memory consumption obtained from the test is 2.02 GB, and the average utilization rate of CPU is 66%. The two indicators basically meet the performance requirements of the system. The system can meet the performance requirements of the number of virtual concurrent users 350, both its memory occupancy and CPU utilization rate are in the acceptable range. It not only improves the accuracy of the sample processing results, but also reduces the labor intensity of the technicians, so that the laboratory expands the analysis function from the simple reporting function.

With the increasing reliance on automatic software-based applications, it is important to automate the classification of software defects and ensure software reliability. An automatic software defect classification system based on an expert system is proposed in this article. In this method, DACS first determines the category of software defects through the selection of typical features, then reduces the spatial knowledge base searched by the inference engine and selects the characteristics of a certain type of defect. Make a selection, determine the name of the defect, and finally select different causes and prevention methods for the defect as needed. The DACS structure was built, and the experiment showed that the AI system took 15 s to complete, whereas the traditional mechanism took 48 s; the accuracy of the AI was 99%, whereas the accuracy of the traditional mechanism was only 68%. According to the aforementioned experimental results, the recognition accuracy of the proposed research scheme is higher than that of the traditional mechanism. Hence, the time required to solve the problem of software engineering defect detection and classification is less than that of the traditional mechanism.

This article addresses the challenge of large error rate and low accuracy of the vibration signal collection of mechanical equipment failure, and proposes a mechanical equipment failure vibration signal collection and analysis based on computer simulation detection. Then, it uses the Kalman filter algorithm for data filtering, according to the mathematical model established by the system, thus choosing a suitable noise covariance calculation method. In the integration process after filtering, using a piecewise integration method between acceleration peaks, the integration calculation is optimized to obtain the vibration displacement. The simulation results of this article show the vibration data collected by the main controller, after Kalman filtering and piecewise trapezoidal integration method optimization. The error of the proposed method is 0.5% when the frequency is 80 Hz, relative to the displacement measurement method of the three-axis acceleration sensor at 8.3%, and the error of data calculation results is greatly reduced. The greater the amplitude of vibration, the smaller the error. This method significantly improves the accuracy of vibration signal collection of mechanical equipment.

Diabetic retinopathy (DR) is caused by diabetes mellitus. Vision loss occurs as a result of DR. The goal of this study was to use the DIARETDB-1, DIARETDB-0, STARE, MESSIDOR, E-ophtha-EX, and E-ophtha-MA databases to do Fourier fractal analysis and see how it is related to retinal illnesses. Following the extraction and inversion of colour channels, blood vessel augmentation was conducted. For the blood vessel enhanced image, the fractal dimension was determined. For DR patients and normal patients, measures such as standard deviation, mean, and significance were calculated. In the E-ophtha-EX database, significance was realized. In the DIARETDB-1, STARE, and DIARETDB-0 databases, the mean fractal value for normal patients is higher than for DR patients. The STARE database’s forecast of the association between fractal dimensions and various retinal disorders and the E-ophtha-EX database’s accomplishment of significance are the study’s main highlights. This study also improved the robustness of the blood vessel extraction there and increased the accuracy of its diagnosis.

To explore the application of programmable logic control (PLC) in the automatic control of nonlinear machine tools, the application of PLC in the nonlinear electronic system control is studied. First, the author takes PLC technology in the numerical control machine tool electrical control application as the research equipment, PLC technology in the numerical control machine tool electrical control application is divided into four types. Then, according to the need of management number, the overall structure of PLC is designed and developed, and the concept of operation modularization is adopted to realize the decentralized development of PLC. There are three functional modules: repair, compile, and simulate. Finally, the machining performance of the nc system is evaluated experimentally. The processing time difference of two kinds of machine tools is compared. The average processing time of the original (Numerically controlled) NC system is 3.06 s, and the average processing time of the embedded soft PLC system is 2.01 s, with a gap of 1.04 s between the two systems. The Computer Numerical Control (CNC) machining improvement of 1 s is significant in the processing efficiency of CNC machine tools. The numerical control system embedded in the PLC system is more stable in the machining time, so it can be concluded that the numerical control-embedded soft PLC system has carried on some improvements and upgrades to the operation of machine tools. PLC has relatively strong reliability, stability, and flexibility and is widely used in industrial control systems. In the production process of CNC machine tools, the application of PLC can improve the automatic control level of machine tools. The application of PLC can improve the automatic control level of machine tools and realize the effective control of each link in the production process of CNC machine tools, such as the start-stop program, the automatic replacement of cutting tools in the production process, the automatic diagnosis, and treatment of various faults in the production process, which can be realized through the application of PLC technology.

In order to solve the problem of recursion equation in network security, the author proposes an application of network security risk detection. The search efficiency of the artificial intelligence planning algorithm is better than the traditional attack graph generation method, designed and implemented a planning engine for security risk assessment, according to the application problem definition, design data processing methods and grammar translation modules; efficient planning algorithms for penetration plan planning are selected and the analysis of the risk association process is completed. First, the development status and challenges of network security are summarized, and then, the research status of existing risk assessment methods is analyzed, the research ideas are introduced, and the main research results are given; the organizational structure is listed at the end. In the optimized parallel algorithm for recursive equations, when using P processors to solve a class of recursive equations of size N, the speedup of this algorithm is 0 ( p ), where 1 > p > 0.1 is an arbitrarily small positive number. Using the advantages of neural networks dealing with nonlinearity and complexity to predict the network security situation based on the improved recurrent neural network, the experimental results prove that the proposed method has high operation efficiency, low error and high accuracy compared with the actual value.

To study the electrical performance of high-speed railway ballasted work and the long running and rotating characteristics of the bed, different design methods are adopted. The longitudinal and transverse resistance of the bed increases with the increase in the ballast grading width. When ballast particle gradation is the lowest interpolation between envelope line and envelope line boundary, the longitudinal and transverse resistance of the bed work according to special requirements. With the increase in the shoulder width, the transverse resistance of running bed increases, while the longitudinal resistance remains constant. When the shoulder width is more than 400 mm, the longitudinal and transverse resistance of the bed works according to the required specifications. Maintenance costs for the various ballasts running on high-speed trains are not cheap. The test results show that the workability can be reduced, and improved by using complete asphalt or stone instead of tussah. Daily cleaning work only accounts for about 10% of the tussah, especially emergency work and special riders should not spend time working. The rubber cushion in sleeper and asphalt concrete cushion in ballast have their advantages and disadvantages in improving the strength of bed. In fact, it should be stipulated in the case file.

In order to study the influence of nonlinear numerical simulation on the optimal control of the tunnel rock deformation parameters, the author proposes a numerical simulation study of the deformation characteristics of the layered rock tunnel, and determines the calculation model according to the thickness of the rock mass. The estimated thicknesses of the dolomite limestone surrounding the tunnel are 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, and 0.9 m. Select the vertical displacement to analyze as a result of the calculation. In order to study the influence of the structural slope on the tunnel stability, the thickness of the rock layer was 0.6 m, and the structural slopes of 5°, 15°, 30°, 45°, 60°, 75°, and 85° were used for simulation calculations. During on-site construction, focus on monitoring the tunnel section deformation before the construction of the secondary lining. Every 10–20 m and at the change of the surrounding rock, the observation section of the surrounding convergence and vault settlement shall be arranged, according to the observed deformation, the peripheral displacement rate and the vault subsidence rate are calculated. The results show that the vertical displacement of the top of the tunnel is generally in a “V” shape, that is, the maximum settlement in the tunnel; when the layer thickness is 0.3 m, the maximum vertical displacement of the rock layer is 7.2 mm, and the total settlement in the lining support tunnel is 8.23 mm. When the layer thickness is 0.9 m, the vertical displacement of the rock layer is 5.14 mm, and the total settlement in the lining support tunnel is 5.22 mm. When the layer thickness is from 0.9 to 0.3 m, the maximum vertical displacement of the rock layer increases by 140%, and the settlement at the vault increases by 158%. The focus of tunnel support at this time is the two sides of the lining structure and the vault with large vertical settlement. For the YK51 + 032 section, the phenomenon of first decreasing and then increasing is due to the sudden mud on the surrounding YK51 + 040, which causes the short-term deformation to increase. Only the ZK49 + 356 sections at the entrance of the spider has very good deformation due to the thin overlying stratum, and other sections are similar, which shows the reliability of the calculation results.

Rail transit network is the backbone of the transport network. In this article, a topology nonlinear model based on L-space and P-space is proposed to understand the unreliability of urban rail transit network in computer-aided design. The proposed model requires different characteristics of rail transit according to L-space and P-space. The experiment result shows that the degree value of the network is relatively small in the L-space. In the L-space, more than 80% of the nodes have degree 2, and the degree distribution is very concentrated. In P-space, the overall degree value of the network is higher, and the distribution area is wider. Experiment results have proved that the aggregation coefficient of more than 85% of the nodes in the Shanghai rail transit network is 1, which provides a basis for the comparison of different trains and the research on the changes in future urban trains.

To optimize the mechanical arm target capture and classification of the open multiple-view (MV) visualization program, the open MV visualization programming and deep learning detection method combined with the different capture strategies of robotic arm, a method to extend the research is proposed. For the proposed sorting robot’s multi-cargo grasping, the analysis required to detect a wide variety of goods in a storage environment that lacks color or structural features uniformly. On the basis of SSD target detection method regression, the object’s 3D position information is reconstructed by default preselected cell selection. 3D coordinate accuracy of binocular navigation system was verified as 8% when the target cargo location distance is more than 5 cm, and binoculars matching success rate is 89.7%. The success rate of Sorting and hoarding is increased from 6% to 85% by adding a change to the scoring points of the target products of uneven quality, with this we have achieved efficient and accurate import.

To study the influence of the nonlinear connection of pile and soil on the dynamic response characteristics of the pile foundation, this article proposes to study the dynamic response of the bridge pile foundation to the slope by combining the centrifugal shaking table test and OPENSEES open source finite element program. This article introduces the pressure-dependent multiyield surface model based on confining pressure. Through the inverse calculation of the similarity ratio of the centrifuge model test, the OPENSEES two-dimensional nonlinear finite element model of the pile group in the slope section can be established. The centrifuge shaking table test is to input the preset seismic wave horizontally at the bottom of the model box. The form of seismic wave is El Centro wave verification of two-dimensional finite element model of the pile group in slope section under earthquake. The reliability of the model is verified by comparing the test and calculated values of dynamic response (residual horizontal displacement and final bending moment) of the pile body under five different peak acceleration seismic wave loading conditions. In the dynamic response experiment of slope pile foundation, in the embedded part below the bedrock surface, the residual horizontal displacement of each pile body is zero. Constrained by the cap beam and tie beam, the displacement of the free section of the pile group at these two positions is basically the same. Through comprehensive analysis, the displacement of P1 and P2 piles is basically the same. The calculated value of the final bending moment of P1 and P2 piles shows the same change trend as the test value, and the test value is slightly larger than the calculated value. The relative errors of the maximum final bending moment of P1 pile under each loading condition are 7.4, 7.8, 12.6, 3.9, and 9.6%, respectively, and the relative errors of P2 pile are 4.6, 3.6, 12.5, 13.6, and 11.5%, respectively. The analysis relative error is caused by the elastic element used in the calculation of the pile body, which is different from the mechanical behavior of the simulated pile body material in the test. Dynamic response of slope site according to the existing centrifuge test results can be seen that the deformation at the slope shoulder of slope site is the most obvious under the earthquake. The inclined interface of soft and hard rock and soil layer will aggravate the dynamic response of the overburden layer on the slope, weakening its ability of seismic energy consumption.

In order to avoid the interference of the excavator hydraulic control system by external factors, the output stability of the hydraulic control system has to be improved. The method introduces a nonlinear Proportional integral differentiation (PID) controller with deviation correction parameters through the simulation verification of the control effect and the creation of excavator hydraulic drive diagram. PID, whose full English name is proportional integral derivative, is a mathematical and physical term. The controller is modeled in Matlab/Simulink. Finally, the whole hydraulic system is co-simulated by the interface of AMESim and Matlab. The simulation results show that the system model realizes the co-simulation through the interface combination of the two software, which is more accurate than the traditional PID control, and the pressure and flow fluctuation are smaller, which can suppress the interference of external load mutation, and improve the stability of the hydraulic drive output of the excavator. The validity of the experiment is verified.

When a car is operating, the road roughness will cause it to vibrate. When this vibration reaches a particular threshold, the driver will get uncomfortable and fatigued, affecting the bearing system’s durability and longevity. The vehicle vibration virtual test system’s framework design and implementation approach is based on virtual reality (VR), and it is made up of a VR subsystem, a model subsystem, and a virtual instrument subsystem. A virtual car vibration test system based on VR is built, and the results of the virtual vehicle vibration test are reported. The findings indicate that the virtual test (VT) technology theoretical model pertains to the creation of VT systems for car vibration based on VR. Users may monitor the vehicle vibration as well as its time domain and frequency domain signals in three separate observation modes using the system.

In this article, marine environment detection has been studied for improving the high resolution of the environment. The problem of low resolution of marine environment detection is caused by data synthesis defects. The supply chain management (SCM) technology is used to optimize related data to improve the resolution. The main procedure is to first preprocess the obtained hydrological data and eliminate the unreasonable amount represented by extreme values, and then the SCM method was used to estimate the results. Finally, the accuracy of the estimation is evaluated by the cross-validation algorithm. In the example verification, the comparison between the SCM method and the traditional optimal interpolation (OI) method in data integration accuracy has been done. This article compares mean square error, mean absolute error (MAE), root-mean-square error (RMSE), and R 2 parameters. SCM provides better results than OI. Mean error (ME) = 0.6°C/month, MEA = 1.6°C/month, RMSE = 42.3°C/month, and ME and MAE values are lower in summer. It shows that it is sensitive to the lack of data and has a better ability to provide high-resolution and accurate marine environmental data in real time.

There are many factors that can lead to the transmission of coronavirus disease 2019 (COVID-19), one of which is the lack of knowledge on the virus and its prevention, notably in Indonesia. This study was focused to design and build an interactive learning app for COVID-19 education. The design of this study was research and development, and in terms of the app development, it utilized the analysis, design, development, implementation, and evaluation model. The project was carried out from July to December 2021, and it involved 25 study participants. The findings of this study confirmed that the educational app consisted of education, a symptom checker, a list of vaccine information links, the latest news, and COVID-19 statistics. The validity assessment showed that the educational app in this study was very appropriate to be utilized as a digital medium for patient education. In addition, it was also confirmed that all the functions of the app worked well, and participants strongly agreed that the educational materials and features of the app were interesting and helped them to learn COVID-19 prevention easily. It could be concluded that the app could be used as a learning medium for patient education. Further studies, however, were needed to prove its effectiveness in the real clinical world.

Artificial intelligence (AI) is a machine intelligence technology with vast potential for a smart industrial revolution. This study aims to create new electric-powered transportation such as bicycles, motorbikes, and other vehicles. The combination of high-speed, resiliency, and low-latency connection, as well as AI and Internet of Things (IoT) technologies, will enable the transformation to fully autonomous vehicles. This electric motorcycle tracks its speed, location, and other data using IoT logic. A smart charging system has also been developed to keep them ready to use effectively. The proposed research also reduces the damage to the environment efficiently.

In order to study the vibration engineering project construction risk assessment, algorithms based on nonlinear characteristics, a nonlinear feature extraction local linear embedding (LLE) combined with adaptive neuro-fuzzy inference system (ANFIS) assessment of risk assessment methods have been proposed. This method is first utilized by the LLE manifold method to extract a number of sample construction vibration risk assessment factors of high-dimensional data vector of the nonlinear components. The nonlinear component is then used as the input for ANFIS evaluation method to evaluate and classify construction vibration risk samples. An example shows that this method can effectively improve the accuracy of risk assessment and reduce the error rate to less than 10%. Applying it to practical projects can provide effective decision-making information for construction managers and improve the credibility of decision-making. The identification results prove that the method in this article improves the accuracy of feature extraction and vibration risk assessment, and can as a vibration risk assessment method, be applied to the actual engineering vibration risk assessment.

In order to explore the application of third-order nonlinear optical (NLO) materials in complex borate crystalline chemical reactions, the laser light source with limited wavelength range can be extended to ultraviolet (UV) and deep UV region by using NLO crystal materials and frequency conversion technology, which has become a hot research direction of deep UV light source. The experimental results show that the UV cutoff edge of the grown KLi(HC 3 N 3 O 3 )·2H 2 O crystal is 237 nm. The refractive index of the crystal was measured by prism coupling technique, and the Sellmeier equation of the refractive index of the crystal was fitted. The chemical bond of the crystal is a fundamental means to understand the relationship between structure and properties. With the emergence of a large number of hybrid functional crystals, the composition and structure of crystals become more complex, and the chemical bond theory has also been greatly developed, and then the chemical bond theory of meta crystals or complex crystals has emerged. Once proposed, the theory has been widely used, such as analyzing the eligibility of luminescent crystals, NLO crystals and high-temperature superconductor crystals. NLO materials are the dominant field of China in the world. Crystals with good nonlinear behavior have more complex crystal structures, due to the theory of amorphous structure, the exploration of this aspect is particularly difficult. For the first time, the influence of the composition of rare earth-doped bismuth borate glass on the crystal precipitation and glass microstructure of NLO materials was systematically studied, which laid a theoretical foundation for further development and understanding of new bismuth borate optical systems.

The Internet of Things concept can be implemented using Long-range wireless access network protocol. The work in this article is done to implement LoRa terrestrial network which will be connected to a satellite in future. The work mainly studies the number of collisions and the impact of it on the network. The work is simulated and is done to determine the number of LoRa nodes which can successfully transmit at a given time. Different combinations of spreading factor and bandwidth at different duty cycles are used to assess the performance of the network.

To solve the problem that most computer network security assessment systems cannot comprehensively analyze data, this article proposes a research method for computer network confidentiality information security system based on the Bayesian classification algorithm. This research takes the computer network security secret-related information security as the core, cleverly uses the EBCA back-propagation model, and comprehensively uses nonlinear functions to propose a computer network secret-related information security application system considering EBCA, which effectively solves the complex cross-linking relationship. The effectiveness of the method is verified by simulation experiments. Simulation experiments show that when the network performance is in the optimal state, the slope is 1, the intercept is 0, and the fitting degree is 1. The method proposed in this article is especially suitable for the nonlinear characteristics of computer network security and can accurately, comprehensively, and systematically reflect the security operation status of network security and confidential information. Then, through the simulation test, it is found that the method in this study can effectively meet the error requirements of equipment integrity and equipment normal rate.

Wearable and movable lodged health monitoring gadgets, micro-sensors, human system locating gadgets, and other gadgets started to appear as low-power communication mechanisms and microelectronics mechanisms grew in popularity. More people are interested in energy capture technology, which turns the energy created by motion technology into electric energy. To understand the difference in motor skill levels, a nonlinear feature-oriented method was proposed. A bi-stable magnetic-coupled piezoelectric cantilever was designed to detect the horizontal difference of motion technology. The horizontal difference was increased by the acceleration generated by the oscillation of the leg and the impression betwixt the leg and the ground during the movement. Based on the Hamiltonian principle and motion technique signal, a nonlinear dynamic model for energy capture in motion technique is established. According to the shaking features of human leg motion, a moveable nonlinear shaking energy-gaining system was the layout, which realized the dynamic characteristics of straight, nonlinear, mono-stable, and bi-stable. The experimental outcome shows that nonlinearity can effectively detect the difference of motion techniques. The experimental results of different human movement states confirm the benefits of the uncertain bi-stable human power capture mechanism and the effectiveness of the electromechanical combining design established. The nonlinear mono-stable beam moves in the same way as the straight mono-stable beam in the assessment, but owing to its higher stiffness, its frequency concentration range (13.85 Hz) is moved to the right compared to the linear mono-stable beam, and the displacement of the cantilever beam is reduced. If the velocity is 8 km/h, the mean energy of the bi-stable method extends to the utmost value of 23.2 μW. It is proved that the nonlinear method can understand the difference in the level of motion technique effectively.

This article uses the nonlinear digital chaos theory algorithm to generate the corresponding encryption system initial parameters, by analysing the correlation degree of image elements from the angles of horizontal, vertical, and diagonal direction, in order to study computer three-dimensional (3D) image encryption processing. The correlation degree of the cypher text obtained by the nonlinear algorithm is weak in the image's adjacent pixels, and the adjacent pixels are not related at all, horizontal angle: 0.915989, vertical angle: 0.968184, diagonal angle: 0.913533. The nonlinear algorithm distributes the image's statistical features into the random cypher text. By applying permutations and replacements in 3D space, the proposed approach improves performance parameters and widens key space in comparison to previous image cryptography investigations. The important qualities of such a secure system are its simplicity and efficacy. Simulations and analysis show that the proposed method can produce a large key space while also surviving standard cipher attacks. Because of its powerful cryptographic properties, it is suited for image applications. The nonlinear algorithm has very high sensitivity to the secret key and plaintext, as well as better statistical performance, higher security, and higher efficiency in the operation of the algorithm.

This article evaluates the energy-harvesting capabilities of a multiuser non-orthogonal multiple access-based system, where energy harvesting relays utilise the power splitting relaying protocol to harvest energy and amplify-and-forward protocol to forward the signals to the connected users. The expressions for each user’s energy harvesting outage probability are calculated and compared to the same system model without energy harvesting. Simulation results show the effectiveness of the energy-harvesting relay nodes and the improved outage probability of each user.