Dynamic Coefficient Research Articles

Analytical Solution of Horizontal Dynamic Response of a Floating Pile Embedded in an Elastic–Poroelasitc-Layered Soil

The horizontal dynamic interaction problems of a floating pile with soil have received little attention from scholars in recent years. This paper first proposed an analytical solution for the dynamic characteristics of the floating pile subjected to horizontal steady-state excitation embedded in soil containing the groundwater table level. Based on Biot’s elastodynamic theory, the governing equations of the soil around the pile are obtained. By virtue of the Hankel transform technique and variable separation method, the shaft reactions and base resistances transferred from the soil are calculated and substituted into the dynamic equation of the floating pile derived by the Euler beam model. The dynamic impedance coefficient of the pile head in the frequency domain is obtained by using the transfer matrix method. Comparisons with the previous studies are performed to validate the accuracy of the presented approach. The effects of the thickness of the pile end soil, the slenderness ratio of the pile, the groundwater table level and the relative modulus of pile material on the pile dynamic response are investigated through several numerical analyses. The results show that there is an “active soil thickness” for the horizontal dynamic forced floating piles due to the reflection and refraction of the stand waves. Meanwhile, the effect of the groundwater table level should not be neglected to ensure the safety of pile foundation under service life.

Friction between human skin and incontinence pads in the presence of barrier protection products.

This novel experimental work aims to bring further knowledge of frictional performance of common barrier products used in the treatment of incontinence-associated dermatitis and determine how the skin-pad interface changes when a treatment is applied to the skin. Key data is reported and there is an in-depth analysis into friction profiles which reveals great differences between how different skin-pad tribosystems operate when exposed to commercially available barrier treatments. In a wet-pad state Barrier cream A (3M™ Cavilon™ Barrier cream) reduced friction and had much lower dynamic and static coefficients of friction than the other barrier treatments (Barrier cream B (Sorbaderm Barrier cream) and the Barrier spray C (Sorbaderm Barrier spray)). Barrier cream A provided stable friction coefficients in reciprocating sliding, whereas the other treatments, and untreated skin, did not display this unique characteristic. The barrier spray gave rise to high static friction coefficients and exhibited the most stick-slip. All three candidate barrier protection products were found to reduce directional differences in the static coefficient of friction: indicative of reduced shear loading. Knowledge of the desirable frictional properties would drive innovation in product development, and benefit companies, clinicians and users.

Transfer matrix Method-based dynamic model to compensate the pulsating pressure in Strain-based nonintrusive pressure measurement for the L-shaped pipe

Currently, the strain-based nonintrusive pressure measurement does not consider the dynamic case, errors could be introduced. However, the calibration of the dynamic strain-pressure sensitivity coefficient (DSSC) is complicated due to the need to design a special standard dynamic pressure source for different pipes. To address this issue, the present study introduces a model-based and easy-to-implement approach to calibrate it indirectly. Firstly, the baseline dynamic model developed by transfer matrix method is calibrated with the tested static strain-pressure sensitivity coefficient and natural frequencies utilizing model updating. Secondly, the DSSC is generated by the calibrated dynamic model to compensate the dynamic pressure. The closed-form sensitivities of the DSSC and natural frequency are derived to conduct the parametric sensitivity analysis to select the reasonable parameters to calibrate the analytical model. The uniqueness of the field transfer matrix is also proven strictly to make sure the output from the model is unique. The case studies showed that the maximum relative errors of the natural frequencies and closed-form sensitivities predicted by the presented method to the tested results in the existing literature and those predicted by finite difference method are −10% and 1.20% respectively. The experimental results indicated that the proposed method can reduce the maximum relative error of the dynamic pressure to the one measured by commercial pressure sensor from 13.04% to 4.35%.

SH Wave Scattering and Dynamic Stress Concentration in Piezomagnetic Materials with Non-Circular Openings

The study uses complex variable functions and conformal mapping to investigate the scattering and dynamic stress concentration phenomena of SH waves in non-circular opening magnetic–elastic materials. Elastic dynamics and piezomagnetic equations are employed to derive expressions for the scattered wave intensity and dynamic stress concentration coefficient around non-circular openings. Special attention is devoted to elliptical openings, where different incident angles and dimensionless wave numbers exhibit varying effects on the dynamic stress concentration coefficients. The numerical results indicate a positive correlation between the dynamic stress concentration coefficient and the illumination region of elliptical openings, with low wave numbers exerting a more significant influence. These findings provide a valuable theoretical foundation for studying fatigue mechanics in piezomagnetic materials. Therefore, to enhance the performance and reliability of piezomagnetic materials, it is imperative to conduct elastic dynamic analysis of non-circular defects in low-frequency environments.

Optimization of Energy Allocation Strategies in Spanish Collective Self-Consumption Photovoltaic Systems

Collective self-consumption (CSC) systems offer a great opportunity to increase the viability of photovoltaic installations by reducing costs and increasing profitability for consumers. In addition, CSC systems increase self-sufficiency (SS) and self-consumption (SC). These systems require a proper energy allocation strategy (EAS) to define the energy distribution within the CSC. However, most EASs do not analyze the individual impact of the rules and mechanisms adopted. Therefore, six different EASs are proposed and evaluated in terms of both collective and individual cost, SC, and SS. The results show that the EASs based on minimizing collective costs are the most beneficial for the community, although they imply an unfair distribution of energy among users. On the other hand, the other EASs proposed stand out for reaching an equilibrium in terms of cost, SS, and SC, although the collective profitability is lower. The best results are achieved considering dynamic coefficients, which are preferred over static ones.

Spatial Separation of Enantiomers by Field-Modulated Surface Scattering

A new optomechanical chiral resolution scheme for molecules possessing a permanent dipole moment is proposed. The approach involves the following molecular manipulation sequence: (i) a molecular alignment electromagnetic pulse, (ii) a time-delayed dipole orienting static electric field, and (iii) scattering from a frictional surface. The method offers various control parameters including pulse duration and intensity, static field strength, delay time, surface dynamic friction coefficient, and incident molecular velocity that can be tuned to optimize spatial enantioseparation. The scheme is demonstrated for the prototypical HSOH chiral molecule, predicting an enantiomeric excess as high as 50%.

Active learning in multi-label image classification with graph convolutional network embedding

Active learning has achieved considerable success in sample selection for deep learning models and has been widely used to address the issue of high-cost sample annotation. However, most of the existing active learning methods focus on single-label image classification and have limited use in multi-label scenarios. To address this issue and take advantage of label associations, we propose an active learning model based on the graph convolutional network (GCN) embedding and loss prediction network. Specifically, we construct a heterogeneous information network (HIN) that uses GCN embeddings to learn multiple label associations, as well as associations between images and labels. We also use a loss prediction network to predict target losses of unlabeled inputs. In addition, we propose a dynamic active coefficient to adjust the proportion of active learning gradually in the training process. Comprehensive multi-label image classification experiments with limited training labels are conducted on the MS-COCO, VOC 2007, and NUS-WIDE datasets. The comparison results demonstrate the superiority of our method compared with conventional methods in terms of both classification accuracy and convergence speed.

Estimation of Dynamic Wind Shear Coefficient to Characterize Best Fit of Wind Speed Profiles under Different Conditions of Atmospheric Stability and Terrains for the Assessment of Height-Dependent Wind Energy in Libya

Estimation of Dynamic Wind Shear Coefficient to Characterize Best Fit of Wind Speed Profiles under Different Conditions of Atmospheric Stability and Terrains for the Assessment of Height-Dependent Wind Energy in Libya

Household Electricity Scheduling Strategy Solution Based on SA-α-QLearning

<p>Traditional household power dispatching methods are difficult to deal with the complexity of dispatching environment and the randomness of power consumption behavior, and the QLearning algorithm is prone to fall into local optimal solutions and slow convergence when solving problems, this paper proposes a new method based on SA-α-QLearning’s home electricity scheduling strategy solution method. Firstly, a multi-intelligent Markov decision process model is established based on household electrical equipment; then the learning rate of a single value in the QLearning algorithm is replaced by a linear iterative learning rate; finally, a simulated annealing (SA) is used to optimize the QLearning algorithm to solve the model, by taking the Q value change difference as the new solution acceptance probability of Metropoils criterion and the dynamic adjustment temperature reduction coefficient, it alleviates the problem that the QLearing algorithm is easy to fall into the local optimal solution and the convergence speed is slow. Through a large number of comparative experiments, it is proved that the proposed method has a significant improvement in the solution of household electricity dispatching strategy.</p> <p> </p>

Numerical calculation of barrel chamber mechanical wear based on the principle of dynamic pressure lubrication

Thermal-chemical erosion and mechanical wear are the main factors restricting the service life of barrel weapons. Considering the lack of systematic research on the mechanical wear of the barrel weapons, this paper gives the display expression of the dynamic pressure lubrication friction coefficient in projectile-barrel clearance based on the principle of dynamic pressure lubrication. The trend of friction coefficient is basically consistent with the friction experiment data. In the framework of dynamic pressure lubrication friction, the mechanical wear model of artillery barrel is derived, and the mechanical wear model in the whole life cycle is calculated by using the ALE mesh adaptive technology. The results show that the derived mechanical wear model can accurately describe the material degradation of the barrel chamber. The mechanical wear is mainly concentrated at the beginning of the rifling and the muzzle. After 500 shots, the mechanical wear of the beginning of the rifling and the muzzle are generally 0.3mm and 0.4mm.

Kinematic bending of piles in made ground

This work explores earthquake-induced kinematic bending in the so far unresolved case of a pile embedded in a two-layer soil with a thin surface layer. The problem is treated analytically by means of a generalised Winkler model, which in addition considers the effect of boundary conditions at the pile head over earlier contributions on the subject. Novel analytical closed-form expressions of the kinematic bending moment at the pile head and at the interface between the two soil layers are provided for both fixed- and free-head piles. The analytical solutions are validated through a rigorous finite-element model, which proves a remarkable accuracy in the static regime. While for interface bending the past literature indications for the dynamic coefficient make the proposed formula accurate for both shallow and deep interface, a novel dynamic interaction factor, describing dynamic effects for pile-head bending, is introduced. A numerical example provides guidance on application of the formulae in real design scenarios.

Bending mechanics test and parameters calibration of ramie stalks

Research and development of ramie harvesting equipment is a key link to revitalize ramie industry, problems such as the tendency of stalks to tangle and clog the machine are very problematic, seriously affect the quality and fluency of the harvester. The structure of ramie stalk is complex, and the mechanical properties of each component vary greatly, collision between stalk and machine creates complex stress relationship. By building a finite element model, it is possible to analyze the stress state of the stalk during bending from a microscopic perspective, and to analyze the complex stress–strain situation within the stalk. The purpose of this paper is to establish a standard ramie stalk bending finite element model to provide a theoretical basis for the subsequent kinematics and dynamics. Firstly, material experiments were carried out on ramie straw. The structural and mechanical parameters of the straw components were obtained through measurement and calculation tests, and the force–deformation curves for straw bending were obtained. Bending finite element simulations were carried out on the basis of mechanical tests, and the parameters such as dynamic friction coefficient, wood Poisson's ratio and bast Poisson's ratio were determined by the central combination design. Then established an accurate bending finite element simulation model of ramie stalk, the accuracy of the model was verified at the end. In this paper, the key parameters of the ramie stalk model were calibrated through a combination of material tests and simulations. All parameters of the ramie stalk model were finally obtained, and the bending mechanical properties of the ramie stalk were analysed by applying finite element analysis. This bending mechanics simulation model can be used for kinematic and dynamics simulation analysis of conveying and baling to provide a theoretical basis for the structural design of the harvester. The methods explored here can be applied to other slender straw crops.

Highly Durable Bidirectional Rotary Triboelectric Nanogenerator with a Self-Lubricating Texture and Self-Adapting Contact Synergy for Wearable Applications.

Sliding-freestanding triboelectric nanogenerators (SF-TENGs) are desirable for application in wearable power sources; however, improving their durability is the primary challenge. Meanwhile, few studies focus on enhancing the service life of tribo-materials, especially from an anti-friction perspective during dry operation. Herein, for the first time, a surface-textured film with self-lubricating property is introduced into the SF-TENG as a tribo-material, which is obtained by the self-assembly of hollow SiO2 microspheres (HSMs) close to a polydimethylsiloxane (PDMS) surface under vacuum conditions. The PDMS/HSMs film with micro-bump topography simultaneously reduces the dynamic coefficient of friction from 1.403 to 0.195 and increases the electrical output of SF-TENG by an order of magnitude. Subsequently, a textured film and self-adapting contact synergized bidirectional rotary TENG (TAB-TENG) is developed, and the superiorities of the soft flat rotator with bidirectional reciprocating rotation are systematically investigated. The obtained TAB-TENG exhibits a remarkable output stability and an outstanding mechanical durability over 350 000 cycles. Furthermore, a smart foot system for stepping energy harvesting and wireless walking states monitoring is realized. This study proposes a pioneering strategy for extending the lifetime of SF-TENGs and advances it toward practical wearable applications.

Numerical Evaluation of Dynamic Earth Lateral Pressure on Basement Walls in Cohesionless Soils (A Case Study of Iranian Earthquakes)

Various earth-retaining structures are extensively used in different civil engineering projects. Using the results of experimental and numerical modeling, the effect of the earthquake loading on the distribution of the earth lateral pressures on basement walls was investigated. The UBCHYST constitutive model was used in the performed numerical simulations, and using the results of 12 centrifuge dynamic model tests, a calibration process was conducted to obtain the proper input parameters for numerical models. Based on the results, some correlations between the dynamic increment coefficient of earth lateral pressure (ΔKae) and the free-field peak ground acceleration (PGAff) were established. The correlations are different for stiff and flexible basement walls. In the end, the results of the model calibration process were verified by the examination of 12 major earthquakes that occurred in the Iran plateau. The results showed that the proposed ΔKae-PGAff correlations are precise enough for the applied design projects.

A hierarchical tensor error correction GRU model

Massive and complex longitudinal data processing of extended target-effective observations highlights a major challenge: existing methods are concerned with the difficulty of improving prediction robustness and ensuring relatively low computing costs. This paper proposes a novel hierarchical tensor processing error correction gated recurrent unit-effective observation prediction lower- and upper-bound estimation ensemble model. First, we introduce a continuous-time tensor value function to integrate time and context information and create a dynamic variable coefficient embedding layer of continuous-time tensor decomposition, including time granularity, observation, Gaussian component, and context information through a B-spline function approximation. The main advantages of this method include accurate normalized distance squared, effective threshold delimitation, and effective prediction boundary estimation. Second, to solve the error interference caused by the physical factors of multivariate observations, the lower and upper interval boundaries of prediction interval (PI) are deeply integrated into the proposed tensor model through the error factor correction method. The experimental results for aviation datasets from Central and Southern China demonstrate that the proposed model is better than other benchmark models in terms of PI output quality, prediction performance, and computing resource consumption.

Theoretical study of effect of the geometrical parameters on the dynamic properties of the elastic rings of an air journal bearing

The paper investigates theoretically the effect of the geometry of the elastic rings of an air journal bearing on the elastic rings dynamic coefficients. The physical finite element method (FEM) model used to obtain the dynamic coefficients of the rings is discussed. A theoretical model is implemented to predict the effect of the geometrical parameters on the dynamic coefficients of the elastic rings. The effect of the geometrical parameters on the dynamic coefficients at different frequencies is studied using FEM. The elastic geometry that result in desired dynamic coefficients is demonstrated. Since predicting the dynamic coefficients for all possible ring geometries using FEM would be computationally expensive. A neural network (NN) is trained to predict the dynamic coefficients for all possible ring geometries generated by the different ring geometrical parameters within a given input domain. The NN results are compared to the experimentally verified FEM results and the results are in good agreement.

Impact of dynamic loading on pavement deflection measurements from traffic speed deflectometer

Traffic speed deflectometer (TSD) provides an efficient way for evaluating pavement condition. The current principle is to convert measured deflection slopes into the deflection basin using the Area Under The Curve (AUTC) method based on the time-space transform and elastic material theory. This study aims to investigate impact of dynamic loading due to pavement roughness on TSD measurements. Semi-analytical finite element (SAFEM) method was developed to simulate dynamic moving loads on flexible pavements with viscoelastic asphalt layer. The variations of pavement deflection and deflection velocity were found increasing linearly with dynamic loading coefficient (DLC), especially for deflection velocity. The average relative error between the actual deflection basin and the one from the AUTC method could be 15% at DLC of 0.1 with the highest error for the maximum deflection. This indicates the necessity of developing correction method of TSD deflection measurements on rough pavements.

Method of Lines for flexible coupling of the Single Particle Model for Lithium-Ion Batteries demonstrated by thermal modelling

Electrochemical models like the Pseudo-two-dimensional (P2D) model and the Single Particle Model (SPM) are widely used in the field of battery simulation. The SPM provides accurate results for small currents with low computational costs. However, commonly used solving strategies limit the applicability of the SPM to certain physical effects. This work introduces a universal solving strategy using Method of Lines (MOL) that allows the integration of several electrochemical and thermal effects without changing the basic mathematical model structure. The model can be easily extended, which was demonstrated by including thermal effects and dynamic diffusion coefficients. The MOL-SPM is compared to a P2D model and experimental data of galvanostatic discharges and a dynamic current profile. The MOL-SPM calculates up to 400 times faster than the P2D model for the dynamic current profile while producing a similar small model error with an RMSE difference of only 0.9 mV compared to the P2D model.

ОЦЕНКА ВИБРАЦИОННЫХ ВОЗДЕЙСТВИЙ МАССИВНЫХ ДЕТАЛЕЙ НА ЦИЛИНДРИЧЕСКУЮ ЧАСТЬ КОТЛОВ ВАГОНОВ-ЦИСТЕРН НА ОСНОВЕ ТЕОРИИ ОБОЛОЧЕК

The problems related to the vibration effects of bulky elements on the cylindrical shell of tank car boilers are considered. To do this, an approach based on the shell theory is proposed. Donnell equations are used to define the loading during vibrations.
 Equations based on the theories of depressed cylindrical shells and on the polytechnic theory of shells are used. In order to confirm the reliability of the results obtained according to the proposed approach comparative analysis is performed. The rigidity of the attached cylindrical shell is estimated, for which experimental values of deformation under the local load are obtained.
 The results of calculations for the local single load of a closed cylindrical shell by means of finite element method (FEM) are given. These results show a satisfactory conformity with the data obtained experimentally (based on calculations). Using the proposed technique, the authors evaluated rigidity of the boiler cylindrical part where bulky elements are installed and this makes it possible to define the values of natural frequencies and the level of dynamic addition for various design parameters. Geometrics for tetra axial and eight axial tank cars are used as examples. Additionally, gain-frequency characteristics of deformations, accelerations and dynamic coefficients in the places of bulky elements are presented. Study results can be used to improve the design and the conditions for using tank car boilers.

Comparative Study of Hedging Models in US

This study focuses on the use of three dynamic hedging models in the American stock market, and it computes the dynamic correlation coefficient, dynamic hedging ratio, and hedging effectiveness of three common models (DCC, BEKK, CCC). This paper fills in the gaps in the application and comparison of three hedging models commonly used in the US stock market during the pandemic. The results showed that NASDAQ index and futures were highly correlated and had significant volatility spillover effect before and during the epidemic. The hedging efficiency of the three models before the epidemic was higher than 0.931, and the hedging efficiency of the three models during the epidemic was higher than 0.936. It is proved that futures hedging is a good way to avoid risk no matter before or during the epidemic, and the highest hedging efficiency is dcc-garch.