Systematic Elastostatic Stiffness Model of Over-Constrained Parallel Manipulators Without Additional Constraint Equations

The establishment of an elastostatic stiffness model for over constrained parallel manipulators(PMs),particularly those with over constrained subclosed loops,poses a challenge while ensuring numerical stability.This study addresses this issue by proposing a systematic elastostatic stiffness model based on matrix structural analysis(MSA)and independent displacement coordinates(IDCs)extraction techniques.To begin,the closed-loop PM is transformed into an open-loop PM by eliminating constraints.A subassembly element is then introduced,which considers the flexibility of both rods and joints.This approach helps circumvent the numerical instability typically encountered with traditional constraint equations.The IDCs and analytical constraint equations of nodes constrained by various joints are summarized in the appendix,utilizing multipoint constraint theory and singularity analysis,all unified within a single coordinate frame.Subsequently,the open-loop mechanism is efficiently closed by referencing the constraint equations presented in the appendix,alongside its elastostatic model.The proposed method proves to be both modeling and computationally efficient due to the comprehensive summary of the constraint equations in the Appendix,eliminating the need for additional equations.An example utilizing an over constrained subclosed loops demonstrate the application of the proposed method.In conclusion,the model proposed in this study enriches the theory of elastostatic stiffness modeling of PMs and provides an effective solution for stiffness modeling challenges they present.

Optimization Techniques for GPU-Based Parallel Programming Models in High-Performance

This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.

Gravity-Based Kinetostatic Modeling of Parallel Manipulators Using Screw Theory

The pose accuracy of parallel manipulators(PMs)is a key index to measure their performance.Establishing the grav-ity-based kinetostatic model of a parallel robot provides an important basis for its error composition and accuracy improvement.In this paper,a kinetostatic modeling approach that takes real gravity distribution into consideration is proposed to analyze the influence of gravity on the infinitesimal twist and actuator forces of PMs.First,the duality of the twist screw and constraint wrenches are used to derive the gravity-attached constraint wrenches independent of the external load and the limb stiffness matrix corresponding to the kinematics-based constraint wrenches.Sec-ond,the gravity model of the mechanism is established based on the screw theory and the principle of virtual work.Finally,the analytical formulas of the infinitesimal twist and the actuator force of PMs are obtained,and the influences of the external load,platform gravity,and rod gravity on the stiffness of the mechanism are decoupled.The non-overconstrained 3RPS and overconstrained 2PRU-UPR PMs are taken as examples to verify the proposed method.This research proposes a methodology to analyze the infinitesimal deformation of the mechanism under the influence of gravity.

A Novel Parallel Computing Confidentiality Scheme Based on Hindmarsh-Rose Model

Due to the inherent insecure nature of the Internet,it is crucial to ensure the secure transmission of image data over this network.Additionally,given the limitations of computers,it becomes evenmore important to employ efficient and fast image encryption techniques.While 1D chaotic maps offer a practical approach to real-time image encryption,their limited flexibility and increased vulnerability restrict their practical application.In this research,we have utilized a 3DHindmarsh-Rosemodel to construct a secure cryptosystem.The randomness of the chaotic map is assessed through standard analysis.The proposed system enhances security by incorporating an increased number of system parameters and a wide range of chaotic parameters,as well as ensuring a uniformdistribution of chaotic signals across the entire value space.Additionally,a fast image encryption technique utilizing the new chaotic system is proposed.The novelty of the approach is confirmed through time complexity analysis.To further strengthen the resistance against cryptanalysis attacks and differential attacks,the SHA-256 algorithm is employed for secure key generation.Experimental results through a number of parameters demonstrate the strong cryptographic performance of the proposed image encryption approach,highlighting its exceptional suitability for secure communication.Moreover,the security of the proposed scheme has been compared with stateof-the-art image encryption schemes,and all comparison metrics indicate the superior performance of the proposed scheme.

A Comparative Study on Kinematic Calibration for a 3-DOF Parallel Manipulator Using the Complete-Minimal,Inverse-Kinematic and Geometric-Constraint Error Models

Kinematic calibration is a reliable way to improve the accuracy of parallel manipulators, while the error model dramatically afects the accuracy, reliability, and stability of identifcation results. In this paper, a comparison study on kinematic calibration for a 3-DOF parallel manipulator with three error models is presented to investigate the relative merits of diferent error modeling methods. The study takes into consideration the inverse-kinematic error model, which ignores all passive joint errors, the geometric-constraint error model, which is derived by special geometric constraints of the studied RPR-equivalent parallel manipulator, and the complete-minimal error model, which meets the complete, minimal, and continuous criteria. This comparison focuses on aspects such as modeling complexity, identifcation accuracy, the impact of noise uncertainty, and parameter identifability. To facilitate a more intuitive comparison, simulations are conducted to draw conclusions in certain aspects, including accuracy, the infuence of the S joint, identifcation with noises, and sensitivity indices. The simulations indicate that the complete-minimal error model exhibits the lowest residual values, and all error models demonstrate stability considering noises. Hereafter, an experiment is conducted on a prototype using a laser tracker, providing further insights into the diferences among the three error models. The results show that the residual errors of this machine tool are signifcantly improved according to the identifed parameters, and the complete-minimal error model can approach the measurements by nearly 90% compared to the inverse-kinematic error model. The fndings pertaining to the model process, complexity, and limitations are also instructive for other parallel manipulators.

Attenuate Class Imbalance Problem for Pneumonia Diagnosis Using Ensemble Parallel Stacked Pre-Trained Models

Pneumonia is an acute lung infection that has caused many fatalitiesglobally. Radiologists often employ chest X-rays to identify pneumoniasince they are presently the most effective imaging method for this purpose.Computer-aided diagnosis of pneumonia using deep learning techniques iswidely used due to its effectiveness and performance. In the proposed method,the Synthetic Minority Oversampling Technique (SMOTE) approach is usedto eliminate the class imbalance in the X-ray dataset. To compensate forthe paucity of accessible data, pre-trained transfer learning is used, and anensemble Convolutional Neural Network (CNN) model is developed. Theensemble model consists of all possible combinations of the MobileNetv2,Visual Geometry Group (VGG16), and DenseNet169 models. MobileNetV2and DenseNet169 performed well in the Single classifier model, with anaccuracy of 94%, while the ensemble model (MobileNetV2+DenseNet169)achieved an accuracy of 96.9%. Using the data synchronous parallel modelin Distributed Tensorflow, the training process accelerated performance by98.6% and outperformed other conventional approaches.

Research on Mixed Logic Dynamic Modeling and Finite Control Set Model Predictive Control of Multi-Inverter Parallel System

Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems.

Dynamic Modeling and Experimental Verification of an RPR Type Compliant Paralle Mechanism with Low Orders

Efficiency of calculating a dynamic response is an important point of the compliant mechanism for posture adjustment.Dynamic modeling with low orders of a 2R1T compliant parallel mechanism is studied in the paper.The mechanism with two out-of-plane rotational and one lifting degrees of freedom(DoFs)plays an important role in posture adjustment.Based on elastic beam theory,the stiffness matrix and mass matrix of the beam element are established where the moment of inertia is considered.To improve solving efficiency,a dynamic model with low orders of the mechanism is established based on a modified modal synthesis method.Firstly,each branch of the RPR type mechanism is divided into a substructure.Subsequently,a set of hypothetical modes of each substructure is obtained based on the C-B method.Finally,dynamic equation of the whole mechanism is established by the substructure assembly.A dynamic experiment is conducted to verify the dynamic characteristics of the compliant mechanism.

A possible probe to neutron-skin thickness by fragment parallel momentum distribution in projectile fragmentation reactions

Neutron-skin thickness is a key parameter for a neutron-rich nucleus;however,it is difficult to determine.In the framework of the Lanzhou Quantum Molecular Dynamics(LQMD)model,a possible probe for the neutron-skin thickness(δ_(np))of neutron-rich ^(48)Ca was studied in the 140A MeV ^(48)Ca+^(9)Be projectile fragmentation reaction based on the parallel momentum distribution(p∥)of the residual fragments.A Fermi-type density distribution was employed to initiate the neutron density distributions in the LQMD simulations.A combined Gaussian function with different width parameters for the left side(Γ_(L))and the right side(Γ_(R))in the distribution was used to describe the p∥of the residual fragments.Taking neutron-rich sulfur isotopes as examples,Γ_(L) shows a sensitive correlation withδ_(np) of ^(48)Ca,and is proposed as a probe for determining the neutron skin thickness of the projectile nucleus.

LARGE SIGNAL DISCRETE-TIME MODEL FOR PARALLELED BUCK CONVERTERS

As a number of switch combinations are involved in operation of multi converter system, conventional methods for obtaining discrete time large signal model of these converter systems result in a very complex solution. A simple sampled data technique for modeling distributed dc dc PWM converters system (DCS) was proposed. The resulting model is nonlinear and can be linearized for analysis and design of DCS. These models are also suitable for fast simulation of these networks. As the input and output of dc dc converters are slow varying, suitable model for DCS was obtained in terms of the finite order input/output approximation.

Parallel Inference for Real-Time Machine Learning Applications

Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.

Error modeling of 3-RSR parallel robot based on D-H transformation matrix

By selecting any one limb of 3-RSR parallel robot as a research object, the paper establishes a position and orienta- tion relationship matrix between the moving platform and the base by means of Denavit-Hartenberg （D-H） transformation matrix. The error mapping model is derived from original error to the error of the platform by using matrix differential method. This model contains all geometric original errors of the robot. The nonlinear implicit function relation between po- sition and orientation error of the platform and the original geometric errors is simplified as a linear explicit function rela- tion. The results provide a basis for further studying error analysis and error compensation.

A Novel Interconnect Crosstalk Parallel RLC Analyzable Model Based on the 65nm CMOS Process

Based on the 65nm CMOS process,a novel parallel RLC coupling interconnect analytical model is presented synthetically considering parasitical capacitive and parasitical inductive effects. Applying function approximation and model order-reduction to the model, we derive a closed-form and time-domain waveform for the far-end crosstalk of a victim line under ramp input transition. For various interconnect coupling sizes, the proposed RLC coupling analytical model enables the estimation of the crosstalk voltage within 2.50% error compared with Hspice simulation in a 65nm CMOS process. This model can be used in computer-aided-design of nanometer SOCs.

Compliance Modeling and Analysis of a 3-RPS Parallel Kinematic Machine Module

The compliance modeling and rigidity performance evaluation for the lower mobility parallel manipulators are still to be remained as two overwhelming challenges in the stage of conceptual design due to their geometric complexities. By using the screw theory, this paper explores the compliance modeling and eigencompliance evaluation of a newly patented 1T2R spindle head whose topological architecture is a 3-RPS parallel mechanism. The kinematic definitions and inverse position analysis are briefly addressed in the first place to provide necessary information for compliance modeling. By considering the 3-RPS parallel kinematic machine（PKM） as a typical compliant parallel device, whose three limb assemblages have bending, extending and torsional deflections, an analytical compliance model for the spindle head is established with screw theory and the analytical stiffness matrix of the platform is formulated. Based on the eigenscrew decomposition, the eigencompliance and corresponding eigenscrews are analyzed and the platform＇s compliance properties are physically interpreted as the suspension of six screw springs. The distributions of stiffness constants of the six screw springs throughout the workspace are predicted in a quick manner with a piece-by-piece calculation algorithm. The numerical simulation reveals a strong dependency of platform＇s compliance on its configuration in that they are axially symmetric due to structural features. At the last stage, the effects of some design variables such as structural, configurational and dimensional parameters on system rigidity characteristics are investigated with the purpose of providing useful information for the structural design and performance improvement of the PKM. Compared with previous efforts in compliance analysis of PKMs, the present methodology is more intuitive and universal thus can be easily applied to evaluate the overall rigidity performance of other PKMs with high efficiency.

Error Modeling and Sensitivity Analysis of a Parallel Robot with SCARA(Selective Compliance Assembly Robot Arm) Motions

Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.

The parallel 3D magnetotelluric forward modeling algorithm

The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.

Influence of heterogeneity on rock strength and stiffness using discrete element method and parallel bond model

The particulate discrete element method(DEM) can be employed to capture the response of rock,provided that appropriate bonding models are used to cement the particles to each other.Simulations of laboratory tests are important to establish the extent to which those models can capture realistic rock behaviors.Hitherto the focus in such comparison studies has either been on homogeneous specimens or use of two-dimensional(2D) models.In situ rock formations are often heterogeneous,thus exploring the ability of this type of models to capture heterogeneous material behavior is important to facilitate their use in design analysis.In situ stress states are basically three-dimensional(3D),and therefore it is important to develop 3D models for this purpose.This paper revisits an earlier experimental study on heterogeneous specimens,of which the relative proportions of weaker material(siltstone) and stronger,harder material(sandstone) were varied in a controlled manner.Using a 3D DEM model with the parallel bond model,virtual heterogeneous specimens were created.The overall responses in terms of variations in strength and stiffness with different percentages of weaker material(siltstone) were shown to agree with the experimental observations.There was also a good qualitative agreement in the failure patterns observed in the experiments and the simulations,suggesting that the DEM data enabled analysis of the initiation of localizations and micro fractures in the specimens.

Dynamic Modeling and Experiment of a New Type of Parallel Servo Press Considering Gravity Counterbalance

The large capacity servo press is traditionally realized by means of redundant actuation, however there exist the over-constraint problem and interference among actuators, which increases the control difficulty and the product cost. A new type of press mechanism with parallel topology is presented to develop the mechanical servo press with high stamping capacity. The dynamic model considering gravity counterbalance is proposed based on the virtual work principle, and then the effect of counterbalance cylinder on the dynamic performance of the servo press is studied. It is found that the motor torque required to operate the press is a lot less than the others when the ratio of the counterbalance force to the gravity of ram is in the vicinity of 1.0. The stamping force of the real press prototype can reach up to 25 MN on the position of 13 mm away from the bottom dead center. The typical deep-drawing process with 1 200 mm stroke at 8 strokes per minute is proposed by means of five order polynomial. On this process condition, the driving torques are calculated based on the above dynamic model and the torque measuring test is also carried out on the prototype. It is shown that the curve trend of calculation torque is consistent to the measured result and that the average error is less than 15%. The parallel mechanism is introduced into the development of large capacity servo press to avoid the over-constraint and interference of traditional redundant actuation, and its dynamic characteristics with gravity counterbalance are presented.

ON THE DYNAMIC MODELING AND CONTROL OF 2-DOF PLANAR PARALLEL MECHANISM WITH FLEXIBLE LINKS

The object of study is about dynamic modeling and control for a 2degree-of-freedom (DOF) planar parallel mechanism (PM) with flexible links. The kinematic anddynamic equations are established according to the characteristics of mixed rigid and flexiblestructure. By using the singular perturbation approach (SPA), the model of the mechanism can beseparated into slow and fast subsystems. Based on the feedback linearization theory and inputshaping technique, the large scale rigid motion controller and the flexible link vibrationcontroller can be designed separately to achieve fast and accurate positioning of the PM.

Forward and backward models for fault diagnosis based on parallel genetic algorithms

In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.