Mechanism Modeling Method Research Articles

Enhancing the precision of continuum robots in orthopedic surgery based on mechanical principles.

In the field of orthopedic surgery, the notched continuum robot has garnered significant attention due to its passive compliance, making it particularly suitable for procedures in complex and delicate bone and joint regions. However, accurately modeling the notched continuum robot remains a significant challenge. This paper proposes a high-precision mechanical modeling method for the notched continuum robot to address this issue. The flexible beam deflection prediction model based on the beam constraint model is established. The force balance friction model considering internal friction is established. An accurate static model is obtained, which can accurately estimate the deformation and deflection behavior of the robot according to the input driving force. The kinematic model of the notched continuum robot based on the static model is established. This method achieves high accuracywhile ensuring computational efficiency. Experimental results demonstrate that the static model's error is only 0.1629mm, which corresponds to 0.25% of the total length of the continuum robot, which is 66mm. This research provides valuable insights into the modeling and control of continuum robots and holds significant implications for advancing precision in orthopedic surgery.

Mechanism and Data-Driven Fusion SOC Estimation

An accurate assessment of the state of charge (SOC) of electric vehicle batteries is critical for implementing frequency regulation and peak shaving. This study proposes mechanism- and data-driven SOC fusion calculation methods. First, a second-order Thevenin battery model is developed to obtain the physical parameters of the battery. Second, data from the Thevenin battery model and data from four standard cycling conditions in the electric vehicle industry are added to the dataset of the feed-forward neural network data-driven model to construct the test and training sets of the data-driven model. Finally, the error of the mechanism and data-driven fusion modeling method is quantitatively analyzed by comparing the estimation error of the method for the battery SOC at different temperatures with the accuracy of the data-driven SOC estimation method. The simulation results show that the root mean square error, the mean age absolute error, and the maximum error of mechanism and data-driven method for the estimation error of battery SOC are lower than those of the data-driven method by 0.9%, 0.65%, and 1.3%, respectively. The results show that the mechanism and data-driven fusion SOC estimation method has better generalization performance and higher SOC estimation accuracy.

Machine learning assisted mechanism modeling for gas phase electrohydrodynamic system

In this paper, a hybrid physics-data driven model for electrohydrodynamic gas system (EHDGS) was developed by combining artificial neural network (ANN) with mechanism modeling method. ANN was used to correlate the relationship between the variables (electrode distance, diameter of grounding cylinder, applied voltage, electric field gradient, etc.) in a needle-cylinder EHDGS and the initial space charge density. The results showed that the ANN model of nine neurons can well predict the initial space charge density. The coefficient of determination (R2) reaches 0.9874, and the mean absolute error is as low as 0.0067. Subsequently, a hybrid mechanism model where the initial space charge density was predicted from the ANN model was constructed to simulate the needle-cylinder EHDGS. The experiment with the needle-cylinder EHDGS was carried out. The simulation results were in good agreement with the experimental data, demonstrating the reliability of the proposed hybrid model. The electric field distribution, space charge distribution, and flow field distribution behavior of the EHDGS were then analyzed in detail. The effects of key parameters on the flow characteristics of EHDGS were systematically studied, showing that higher voltage and shorter distance give higher flow rate up to 2.5 m/s. The diameter of the cylinder also significantly influences the breakdown voltage. Three dimensionless groups were defined and their effects on spatial charge density distribution were investigated. This study provides both insights and an efficient tool for the design and optimization of EHDGS.

Mechanical modeling and parameter analysis of the docking process for probe-drogue docking mechanisms

The on-orbit probe-drogue berthing docking of two spacecraft can effectively reduce impact force and adjust for initial deviations. However, its dynamic response and influence behaviors of design parameters are extremely concerning but difficult to obtain because of its complicated structure. In this paper, a fast mechanical modeling (FMM) method is proposed to obtain the dynamic response of probe-drogue docking mechanisms during spacecraft berthing missions. Regarding the quasi-static docking process, complex dynamic docking behaviors are simplified and decoupled. The FMM method divides docking into three contact processes based on the scene of contact; it analyzes the deviation adaptive docking principle of this type of docking mechanism by establishing the kinematics and mechanics models of active and passive parts. The finite element simulations and experiments of probe-drogue berthing docking were used to compare with the proposed FMM. The comparison results of different initial deviation conditions indicate that the FMM method guarantees computation accuracy and increases computation speed by two orders of magnitude, which greatly reduces computation costs. Then this efficient FMM method was utilized to analyze the influence of key parameters, such as friction coefficient and cone angle, on the contact force and driving force of the docking mechanism. The conclusions of the parameter analysis of probe-drogue berthing docking can be used to reduce contact force and accelerate iterative design as a reference for the design of this kind of docking mechanisms, making the docking process optimized and reliable.

Simultaneous analysis of continuously embedded Reissner–Mindlin shells in 3D bulk domains

AbstractA mechanical model and numerical method for the simultaneous analysis of Reissner–Mindlin shells with geometries implied by a continuous set of level sets (isosurfaces) over some three‐dimensional bulk domain is presented. A three‐dimensional mesh in the bulk domain is used in a tailored FEM formulation where the elements are by no means conforming to the level sets representing the shape of the individual shells. However, the shell geometries are bounded by the intersection curves of the level sets with the boundary of the bulk domain so that the boundaries are meshed conformingly. This results in a method which was coined Bulk Trace FEM before. The simultaneously considered, continuously embedded shells may be useful in the structural design process or for the continuous reinforcement of bulk domains. Numerical results confirm higher‐order convergence rates.

Bonding of ceramics to silver-coated titanium-A combined theoretical and experimental study.

It would be very beneficial to have a method for joining of ceramics to titanium reliably. Although several techniques have been developed and tested to prevent extensive interfacial chemical reactions in titanium-ceramic systems, the main problem of the inherent brittleness of interfaces was still unsolved. To overcome this problem also in dental applications, we decided to make use of an interlayer material that needs to meet the following requirements: First, it has to be biocompatible, second, it should not melt below the bonding temperatures, and third, it should not react too strongly with titanium, so that its plasticity will be maintained. Considering possible material options only the metals: gold, platinum, palladium, and silver, fulfill the first and second requirements. To find out-without an extensive experimental testing program-which of the four metals fulfills the third requirement best, the combined thermodynamic and reaction kinetic modeling was employed to evaluate how many and how thick reaction layers are formed between the interlayer metals and titanium. With the help of theoretical modeling, it was shown that silver fulfills the last requirement best. However, before starting to test experimentally the effect of the silver layer on the mechanical integrity of dental ceramic/Ag/Ti joints it was decided to make use of mechanical analysis of the three-point bending test, the result of which indicated that the silver layer increases significantly the bond strength of the joints. This result encouraged us to develop a new technique for plating silver on titanium. Subsequently, we executed numerous three-point bending tests, which demonstrated that silver-plated titanium-ceramic joints are much stronger than conventional titanium-ceramic joints. Hence, it can be concluded that the combined thermodynamic, reaction kinetic, and mechanical modeling method can also be a very valuable tool in medical research and development work.

Mechanical simulation and debonding risk analysis of OLED panels with optically clear adhesives

This paper presents a mechanical simulation model and analysis method for OLED panels. The functional layers within the panel are bonded using optically clear adhesives (OCAs), which are pressure-sensitive adhesives (PSAs), resulting in a soft interface bonding problem. It was discovered that the normal tensile debonding strength of OCAs was significantly lower than the shear debonding strength. To address this issue, a three-layer structure simulation model of “hard + soft + hard” is established, which allows for analyzing the screen folding problem of any radius. Additionally, a suitable element mesh generation strategy for multi-layer structure screens is proposed. A debonding risk index based on pressure is introduced by comparing the interlaminar normal and maximum principal stress. The influence of thickness, bending radius, and Young’s modulus on longitudinal stress and debonding risk index is examined. It is observed that the influence of thickness and Young’s modulus on debonding risk is non-monotonic, indicating the presence of an optimal solution. The high debonding risk area is located at the beginning of the folding mechanism and screen bonding. The proposed debonding risk index is not only applicable to OCAs but also to all PSA with similar structures.

Dynamic modeling and optimization of mechanical drift for compliant parallel micromanipulation driven by V-shape linear ultrasonic motors

Designing micro-mechanisms that satisfy large strokes, high precision, and multiple degrees of freedom has consistently been a research focus and challenge in the field of micromanipulation systems. Linear ultrasonic motors (LUMs), with advantages such as millimeter-level travel, nanometer-level motion resolution, and power-off self-locking, significantly contribute to the advancement in the mechanism design of micromanipulation systems. However, the challenge of mechanical drift lacks a comprehensive theoretical analysis to explain its cause and limits its application. This paper presents a mechanical drift modeling method for a compliant parallel micromanipulation (CPM) driven by a LUM. The model primarily focuses on the creep characteristics of the flexure clamp element in the LUM. Based on the stiffness matrix analysis method of the compliant parallel mechanism kinematics, the mechanical drift dynamics model of the CPM is established. The influence of the main structural parameters on the CPM mechanical drift is investigated. The research indicates that the creep of flexure clamps in the CPM is the main factor leading to the mechanical drift. Optimization of mechanical drift is achieved by choosing flexure clamps with higher tangential stiffness for LUM and flexure hinge joints with greater flexibility for CPM. Finally, experimental studies reveal that under equivalent conditions, the mechanical drift of the optimized CPM was significantly reduced than before, proving the rationality of the theoretical model and optimization method.

Evaluation and mitigation of deformable image registration uncertainties for MRI-guided adaptive radiotherapy.

We evaluate the performance of a deformable image registration (DIR) software package in registering abdominal magnetic resonance images (MRIs) and then develop a mechanical modeling method to mitigate detected DIR uncertainties. Three evaluation metrics, namely mean displacement to agreement (MDA), DICE similarity coefficient (DSC), and standard deviation of Jacobian determinants (STD-JD), are used to assess the multi-modality (MM), contour-consistency (CC), and image-intensity (II)-based DIR algorithms in the MIM software package, as well as an in-house developed, contour matching-based finite element method (CM-FEM). Furthermore, we develop a hybrid FEM registration technique to modify the displacement vector field of each MIM registration. The MIM and FEM registrations were evaluated on MRIs obtained from 10 abdominal cancer patients. One-tailed Wilcoxon-Mann-Whitney (WMW) tests were conducted to compare the MIM registrations with their FEM modifications. For the registrations performed with the MIM-CC, MIM-MM, MIM-II, and CM-FEM algorithms, their average MDAs are 0.62±0.27, 2.39±1.30, 3.07±2.42, 1.04±0.72mm, and average DSCs are 0.94±0.03, 0.80±0.12, 0.77±0.15, 0.90±0.11, respectively. The p-values of the WMW tests between the MIM registrations and their FEM modifications are less than 0.0084 for STD-JDs and greater than 0.87 for MDA and DSC. Among the three MIM DIR algorithms, MIM-CC shows the smallest errors in terms of MDA and DSC but exhibits significant Jacobian uncertainties in the interior regions of abdominal organs. The hybrid FEM technique effectively mitigates the Jacobian uncertainties in these regions.

Water Droplet Reflection Approximation using the Linear Least Square Method from Experimental Data

The impact of water droplets on droplet time is a phenomenon in nature that is implemented in the industrial world, where the contact time between droplets and surfaces affects the transfer of mass, momentum and energy. To manipulate and reduce the contact time of influencing droplets, previous publications reported surface microadjustments influencing droplet surface interfaces. In this final project simulation, water droplets will be discussed using a mechanical energy model and linear least squares method. In the first part the author will show that surface elasticity also influences the impact of droplets, where droplets on the surface of taro leaves can cause reflections again. In the second part the author will explain mechanical energy modeling to create a simulation of the model that influences water droplets. In the third part the author gets the results of the linear least square method modeling. The discussion of the linear least square method model will be related to problems in the industrial world.

The Nonlinear Mechanical Constitutive Model and Deep Learning Method to Inverse Design Dual‐Feature‐Integrated Lattice Metamaterial

The bio‐inspired lattice structure of a regularly fibrous organization is a kind of structural material with practical value in flexible bio‐integrated electronics. The recently proposed dual‐feature‐integrated lattice structure can accurately customize the nonlinear mechanical curve of biological issues. However, it is still lacking the constitutive models to inverse design the desirable mechanical properties. Herein, a nonlinear mechanical constitutive model for the dual‐feature‐integrated metamaterial is established by introducing the equilibrium equation and deformation coordination conditions. The experimental and numerical results show that the proposed constitutive model can predict accurately the stress–strain curves of dual‐feature‐integrated lattice structure. In addition, the machine learning‐whale optimization algorithm method is used to inverse design the dual‐feature‐integrated lattice structure, which can quickly find the target mechanical responses (chicken skin and human skin) in a board design space. The dual‐feature‐integrated mechanical metamaterial has a higher structural design option in comparison to the pure horseshoe and chiral metamaterial. The finding of this work contributes to the designs of lattice structures with flexibility and stretchable electronics.

A computational mechanical constitutive modeling method based on thermally-activated microstructural evolution and strengthening mechanisms

A mechanical constitutive relationship is the basis for the design and application of structural materials, and the establishment of a mechanical constitutive relationship generally relies on experimental data. Herein a computational mechanical constitutive modeling method is proposed, in which all required parameters possess unambiguous physical interpretations and/or can be obtained from accurate numerical simulations. With the inclusion of interaction between dislocations and crystal defects, the dislocation density and grain size evolution with strain for polycrystalline metallic materials are mathematically modeled, and the corresponding contribution to strength is analyzed, further a computational mechanical constitutive relationship can be obtained. Its effectiveness is verified by comparing it with experimental stress-strain relationships for Cu, Al-Mg, and Cu-W alloys. This method might be a powerful tool for the design of structural materials with desirable mechanical properties.

Research on intelligent analysis device for dynamic error of electric energy

With the development of smart grids, the introduction of intermittent energy and the increase in dynamic loads have led to more and more dynamic characteristics of electricity loads in the grid. Intelligent energy meters that passed calibration under steady-state load may not necessarily meet the measurement error requirements under the excitation of dynamic load test signals, and some may even produce significant errors. At present, research on dynamic error testing of intelligent energy meters mainly focuses on establishing models of dynamic error testing signals, and the reasons for the generation of dynamic errors are still unclear. In order to analyze the sources of dynamic errors in intelligent energy meters, this article adopts a mechanism modeling method to establish a full system model of intelligent energy meters, in order to analyze the influence of model parameters of each unit on the dynamic errors of active energy, and provide important theoretical reference for further improving the dynamic error characteristics of energy meters. In addition, identifying the sources of errors has important application value for improving the algorithm of energy metering chips, optimizing the overall design of energy meters, and selecting energy meters in dynamic load scenarios for the power sector.

Hybrid Data-Mechanism Modeling for Power Loss of a Boost Converter

Parameter design is the premise to ensure the optimal performance of power electronic converters, which depends on the accuracy of the established model. However, there is still many issues for improvements in modeling methods for the parameters design of power electronic converters. Due to the lack of key mechanism and the uncertainty of parameters, the existing modeling method shows poor accuracy or efficiency. In order to simplify the process and improve the accuracy of the existing modeling method, this paper proposes a hybrid data-mechanism modeling (HDMM) method for power loss of a typical power electronic converter, Boost converter, which is with UC3842 control chip. Based on the main loss from inductor, switch tube, diode and sampling resistance, the mechanism power loss modeling of Boost converter is built. Besides, the artificial neural network (ANN) is used to learn from the sampled data and train the data-driven model. To improve the accuracy of the mechanism model, the HDMM for power loss of Boost converter is established by modification of data-driven model with limited data. Through the proposed HDMM method, the mechanism modeling method and data-driven method are well combined and the HDMM has the advantage of high accuracy and strong generalization. In the end of this paper, feasibility and accuracy of the proposed HDMM method have been verified by hardware experiments.

Investigation of hydro-thermal variations and mechanical properties in cold region tunnels under long-term freeze–thaw cycles

Long-term freeze–thaw cycles have a significant impact on the safety and durability of tunnels located in cold regions. In this study, a hydro-thermal–mechanical coupling model and calculation method were developed based on the Guanjiaoshan Tunnel. The model's precision and rationality underwent comprehensive validation. The study aimed to discuss the temporal and spatial distributions of temperature, water, and mechanical fields under long-term freeze–thaw cycles. The findings revealed that the water migration influence zones can be classified into three distinct zones. The ice-water phase change and stress exhibit periodic fluctuations following an annual cycle. Significantly, the lining's stress, or danger level, exhibited two peaks during the autumn and spring seasons. The magnitude of the autumn peak exceeded that of the spring peak. Throughout the initial 12-year period, the tunnel's danger level consistently remained below the threshold value of 1.0, affirming its adherence to safety standards during its early service period. Furthermore, the construction of tunnels has the potential to contribute to frozen soils expansion in specific zones due to prolonged freeze–thaw cycles. These study results not only enhance our understanding of hydro-thermal variations but also provide valuable insights for predicting the long-term security performance of tunnels in cold regions.

An assembled beam-to-double skin composite wall joint with insert diaphragm: Configuration, experiment, mechanical model and design method

This paper proposes an assembled beam-to-double skin composite wall (DSCW) joint embedded with insert diaphragms. The insert diaphragms are designed to be welded to the slotted boundary column and bolted on-site to the steel beam, functioning as a corbel beam. This joint presents a suite of advantages such as eliminating on-site welding, easy decoration, and non-protruding from the column profile. To evaluate the hysteretic performance and failure model of the proposed joint, a full-scale quasi-static low-cycle hysteresis test on an individual specimen was conducted. The experimental results demonstrate that the insert-diaphragm joint has good performance in high ductility, favorable plastic rotation capacity, and energy dissipating capacity. A refined finite element model (FEM) was established and verified through the test results. The parametric analysis was conducted to analyze the influences of axial compression ratio, geometrical dimensions of the insert diaphragm, and column thickness on the stiffness and yield strength of the joint. Based on the experimental results and FEM analyses, an alternative mechanical model with two potential failure mechanisms was proposed, in which the connection strength was contributed by the insert diaphragm, the faceplate and the side plate of the column. An optimized plastic hinge relocation configuration was also investigated by FEM to further improve the seismic performance of the joint. Finally, the design method and configurational suggestions were proposed based on the Chinese specifications to facilitate practical applications/design of the proposed insert-diaphragm connection.

On the simultaneous solution of structural membranes on all level sets within a bulk domain

A mechanical model and numerical method for structural membranes implied by all isosurfaces of a level-set function in a three-dimensional bulk domain are proposed. The mechanical model covers large displacements in the context of the finite strain theory and is formulated based on the tangential differential calculus. Alongside curved two-dimensional membranes embedded in three dimensions, also the simpler case of curved ropes (cables) in two-dimensional bulk domains is covered. The implicit geometries (shapes) are implied by the level sets and the boundaries of the structures are given by the intersection of the level sets with the boundary of the bulk domain. For the numerical analysis, the bulk domain is discretized using a background mesh composed by (higher-order) elements with the dimensionality of the embedding space. The elements are by no means aligned to the level sets, i.e., the geometries of the structures, which resembles a fictitious domain method, most importantly the Trace FEM. The proposed numerical method is a hybrid of the classical FEM and fictitious domain methods which may be labelled as “Bulk Trace FEM”. Numerical studies confirm higher-order convergence rates and the potential for new material models with continuously embedded sub-structures in bulk domains.

Modeling and Control Design for Distillation Columns Based on the Equilibrium Theory

Distillation columns represent the most widely used separation equipment in the petrochemical industry. It is usually difficult to apply the traditional mechanism modeling method to online optimization and control because of its complex structure, and common simplified models produce obvious errors. Therefore, we analyze the mass transfer process of gas-liquid fluid on each column tray based on the theory of gas-liquid equilibrium and establish a nonlinear dynamic model of the distillation process. The proposed model can accurately characterize the nonlinear characteristics of the distillation process, and the model structure is largely simplified compared with the traditional mechanism model. Therefore, the model provides a new approach for model-based methods in distillation columns, especially for cases that require efficient online models. Two case studies of benzene-toluene distillation systems show that the nonlinear model has high concentration observation accuracy. Finally, a generic model control scheme is designed based on this model. Simulation results show that this control strategy performs better than a traditional PID control scheme.

Nanoporous Alumina Support Covered by Imidazole Moiety-Based Ionic Liquids: Optical Characterization and Application.

This work analyzes chemical surface and optical characteristics of a commercial nanoporous alumina structure (NPAS) as a result of surface coverage by different imidazolium-based ionic liquids (1-butyl-3-metylimidazolium hexafluorophosphate, 3-methyl-1-octylimidazolium hexafluorophosphate, or 1-ethyl-3-methylimidazolium tetrafluoroborate). Optical characteristics of the IL/NPAS samples were determined by photoluminescence (at different excitation wavelengths (from 300 nm to 400 nm), ellipsometry spectroscopy, and light transmittance/reflectance measurements for a range of wavelengths that provide information on modifications related to both visible and near-infrared regions. Chemical surface characterization of the three IL/NPAS samples was performed by X-ray photoelectron spectroscopy (XPS), which indicates almost total support coverage by the ILs. The IL/NPAS analyzed samples exhibit different photoluminescence behavior, high transparency (<85%), and a reflection maximum at wavelength ~380 nm, with slight differences depending on the IL, while the refractive index values are rather similar to those shown by the ILs. Moreover, the illuminated I−V curves (under standard conditions) of the IL/NPAS samples were also measured for determining the efficiency energy conversion to estimate their possible application as solar cells. On the other hand, a computational quantum mechanical modeling method (DFT) was used to establish the most stable bond between the ILs and the NPAS support.

Incipient fault detection of rotary steerable drilling tool equipment

Rotary steering drilling system is a high-end piece of equipment in oil and gas development. The reliable operation of its core equipment, the dynamic point-the-bit rotary steerable drilling tool (DPRSDT), is an important prerequisite for the normal operation of the drilling system. In this paper, the problem of incipient fault detection is investigated for the DPRSDT equipment based on the model method, which is expected to provide an important guarantee for the operation, maintenance, and health management of the system. First, the mathematical model of the DPRSDT is derived using the mechanism modeling method. Then, the moving weighted average approach is employed to improve the sensitivity of residuals to incipient faults. Based on the characteristics of the noncentral $\chi^2$ distribution, the detectability of incipient faults is analyzed in a statistical sense, and the window length and weight are derived, which ensures that the false alarm rate and missed detection rate can be reduced below the tolerance level. Finally, an experiment is performed in the rotary steerable drilling tool prototype to verify the effectiveness of the proposed method.