Feasibility Analysis of IMA Configuration Design Tool

With the widespread application of integrated modular aviation(IMA)electronic systems,the requirements of IMA characteristic analysis and configuration generation have also improved significantly."Configuration and design system based on AADL models(real-time,reliability,interactive complexity,and schedulability)analysis of the AADL model"mainly get through key characteristic analysis for optimization,combined with input of component parameter information and constraint information,assist designers in generating system configuration information,and form a comprehensive modular avionics system resource configuration strategy generation platform.Also,the tool can generate configuration plans for avionics system software and hardware physical architecture configuration.The analysis of the avionics system model mainly involves designers inputting the existing system model architecture for multi characteristic analysis,it can realize the multi-character analysis based on software intensive system architecture models for software dense systems.Inter-complexity and schedulability analysis,and according to characteristic constraint analysis、system model assessment parameters and system architecture constraint parameters to generate configuration scheme information that meets the requirements.The system can meet domestic and foreign software-intensive systems and meet its quality requirements.

Multi-Parameter Analysis of Optimal Transitions from Chaotic to Stable Regions for Two Classes of Systems

The study of the parameter space of chaotic systems is complicated by its high dimensionality (multi-parametricability). Two approaches to the study of chaotic systems are presented: multi-parameter analysis and optimal suppression of chaotic dynamics. For non-autonomous chaotic systems, this is the way to compare the effectiveness of various correction parameters that provide optimal removal of irregular dynamics. For the class of autonomous chaotic systems, this is the way to investigate the optimal conditions of super-stable behavior for the chaotic system.

Constraint and Mobility Change Analysis of Rubik’s Cube-inspired Reconfigurable Joints and Corresponding Parallel Mechanisms

The current research of reconfigurable parallel mechanism mainly focuses on the construction of reconfigurable joints.Compared with the method of changing the mobility by physical locking joints,the geometric constraint has good controllability,and the constructed parallel mechanism has more configurations and wider application range.This paper presents a reconfigurable axis(rA)joint inspired and evolved from Rubik’s Cubes,which have a unique feature of geometric and physical constraint of axes of joint.The effectiveness of the rA joint in the construction of the limb is analyzed,resulting in a change in mobility and topology of the parallel mechanism.The rA joint makes the angle among the three axes inside the groove changed arbitrarily.This change in mobility is completed by the case illustrated by a 3(rA)P(rA)reconfigurable parallel mechanism having variable mobility from 1 to 6 and having various special configurations including pure translations,pure rotations.The underlying principle of the metamorphosis of this rA joint is shown by investigating the dependence of the corresponding screw system comprising of line vectors,leading to evolution of the rA joint from two types of spherical joints to three types of variable Hooke joints and one revolute joint.The reconfigurable parallel mechanism alters its topology by rotating or locking the axis of rA joint to turn all limbs into different phases.The prototype of reconfigurable parallel mechanism is manufactured and all configurations are enumerated to verify the validity of the theoretical method by physical experiments.

Simulation analysis of regional surface mass anomalies inversion based on different types of constraints

Surface mass anomalies estimated by mass concentration(mascon)approach using Gravity Recovery and Climate Experiment(GRACE)observations with regularization constraints generally present higher spatial resolution than the spheric harmonic(SH)solutions.To analyze the influence of different types of constraints on the estimation of mascon solutions,we carried out a closed-loop simulation experiment to estimate surface mass anomalies over South America based on simulated GRACE intersatellite geopotential differences.Tikhonov regularization with spatial constraint(SC),uniform weighting constraint(UWC),and a prior information constraint(APC)were employed to stabilize the mascon solutions,and the corresponding optimal regularization parameters were determined based on the minimum residual root-mean-square(RMS)criterion.The results show that mascon solutions estimated under different types of constraints are consistent and equivalent when the optimal regularization parameters are selected.The spatial distributions and main characteristics of regional surface mass anomalies estimated by the three types of constraints agree well,and the values of residual RMS with different constraints are very close.But due to the smoothing effect of regularization,the signal strength of mascon solutions is a bit weaker than that of original true signal,especially in the regions with strong signals.In addition,due to the ill-conditioned problem is more serious for higher grid resolution,the relative contribution of the three types of constraints to the final mascon solutions would be stronger.The results show that the averages of relative contribution percentages of these constraints for 2°×2° mascon grids are 80%-90%,while the corresponding values for 4°×4° mascon grids are 30%-60%.However,based on the minimum residual RMS criterion,the accuracy of estimation results is not affected by the type of constraints and their relative contribution to the final mascon solutions.

Probabilistic-Ellipsoid Hybrid Reliability Multi-Material Topology Optimization Method Based on Stress Constraint

This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization design.The probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical loads.The topology optimization formula is combined with the ordered solid isotropic material with penalization(ordered-SIMP)multi-material interpolation model.The stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm function.Furthermore,the sequential optimization and reliability assessment(SORA)is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization(DTO)problem.Stochastic response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point(MPP).In each cycle,the equivalent topology optimization formula is updated according to the MPP information obtained in the previous cycle.The adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method(MMA)is used to update design variables.Finally,the validity and feasibility of the method are verified by the numerical example of L-shape beam design,T-shape structure design,steering knuckle,and 3D T-shaped beam.

Constraint-induced movement therapy in treatment of acute and sub-acute stroke: a meta-analysis of 16 randomized controlled trials

OBJECTIVE： The aim of this meta-analysis was to evaluate the clinical efficacy of constraint-induced movement therapy in acute and sub-acute stroke. DATA SOURCES： The key words were stroke, cerebrovascular accident, constraint-induced therapy, forced use, and randomized controlled trial. The databases, including China National Knowledge Infrastructure, WanFang, Weipu Information Resources System, Chinese Biomedical Literature Database, PubMed, Med- line, Embase, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews, were searched for studies on randomized controlled trials for treating acute or sub-acute stroke published before March 2016. DATA SELECTION： We retrieved relevant randomized controlled trials that compared constraint-induced movement therapy in treatment of acute or sub-acute stroke with traditional rehabilitation therapy （tradi- tional occupational therapy）. Patients were older than 18 years, had disease courses less than 6 months, and were evaluated with at least one upper extremity function scale. Study quality was evaluated, and data that met the criteria were extracted. Stata 11.0 software was used for the meta-analysis. OUTCOME MEASURES： Fugl-Meyer motor assessment of the arm, the action research-arm test, a motor activity log for amount of use and quality of movement, the Wolf motor function test, and a modified Bar- thel index. RESULTS： A total of 16 prospective randomized controlled trials （379 patients in the constraint-induced movement-therapy group and 359 in the control group） met inclusion criteria. Analysis showed significant mean differences in favor of constraint-induced movement therapy for the Fugl-Meyer motor assessment of the arm （weighted mean difference （WMD） = 10.822; 95% confidence intervals （95% CI）： 7.419-14.226）, the action research-arm test （WMD = 10.718; 95% CI： 5.704-15.733）, the motor activity log for amount of use and quality of movement （WMD = 0.812; 95% CI： 0.331-1.293） and the modified Barthel index （WMD = 10.706; 95% CI： 4.417-16.966）. CONCLUSION： Constraint-induced movement therapy may be more beneficial than traditional rehabili- tation therapy for improving upper limb function after acute or sub-acute stroke.

Feasibility analysis and online adjustment of constraints in model predictive control integrated with soft sensor

Feasibility analysis of soft constraints for input and output variables is critical for model predictive control(MPC).When encountering the infeasible situation, some way should be found to adjust the constraints to guarantee that the optimal control law exists. For MPC integrated with soft sensor, considering the soft constraints for critical variables additionally makes it more complicated and difficult for feasibility analysis and constraint adjustment. Therefore, the main contributions are that a linear programming approach is proposed for feasibility analysis, and the corresponding constraint adjustment method and procedure are given as well. The feasibility analysis gives considerations to the manipulated, secondary and critical variables, and the increment of manipulated variables as well. The feasibility analysis and the constraint adjustment are conducted in the entire control process and guarantee the existence of optimal control. In final, a simulation case confirms the contributions in this paper.

An Unique Glomerophyric Diorite Porphyry from the Southern Margin of North China Craton:Geochronology,Geochemical and Quantitative Textural Analysis Constraints

1 Introduction The Wulong glomerophyric diorite porphyry has an extremely peculiar texture with plagioclase phenocrysts clustered as flower-like glomerocrysts(Figs.1a&b),which is never discovered elsewhere of the world.The

A Dimensional Reduction Approach Based on Essential Constraints in Linear Programming

This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two algorithms: the weighted average and the cosine simplex algorithm. The first approach identifies binding constraints by using the weighted average of each constraint, whereas the second algorithm is based on the cosine similarity between the vector of the objective function and the constraints. These two approaches are complementary, and when used together, they locate the essential subset of initial constraints required for solving medium and large-scale linear programming problems. After reducing the dimension of the linear programming problem using the subset of the essential constraints, the solution method can be chosen from any suitable method for linear programming. The proposed approach was applied to a set of well-known benchmarks as well as more than 2000 random medium and large-scale linear programming problems. The results are promising, indicating that the new approach contributes to the reduction of both the size of the problems and the total number of iterations required. A tree-based classification model also confirmed the need for combining the two approaches. A detailed numerical example, the general numerical results, and the statistical analysis for the decision tree procedure are presented.

Defeating constraint based program analysis with temporal correlation function

Constraint based program analysis is widely used in program validation,program vulnerability analysis,etc.This paper proposes a temporal correlation function to protect programs from analysis.The temporal correlation function can be applied to resist against both static and dynamic function summary and concolic testing.What's more,the temporal correlation function can produce different outputs even with same input.This feature can be used to damage the premise of function summary as well as prevent concolic testing process to run the new branch with new input.Experiment results show that this method can reduce efficiency and path coverage of concolic testing,while greatly increasing the difficulty of constraint based program analysis.

Kinematics Analysis of Mechanisms Based on Virtual Assembly

Currently, virtual assembly technology has attracted increasing attention due to considerations of solving assembly problems in virtual environment before actual assembly in manufactory. Previous studies on kinematic analysis of mechanism only aim at analyzing motion law of single mechanism, but can not simulate the multi-mechanisms motion process at the same time, let alone simulating the automatic assembly process of products in a whole assembly workshop. In order to simulate the assembly process of products in an assembly workshop and provide effective data for analyzing mechanical performance after finishing assembly simulation in virtual environment, this study investigates the kinematics analysis of mechanisms based on virtual assembly. Firstly, in view of the same function of the kinematic pairs and the assembly constraints on restricting the motion of components （subassembly or part）, the method of identifying kinematic pairs automatically based on assembly constraints is presented. The information of kinematic pairs can be obtained through calculating the constraint degree of the assembly constraints. Secondly, the incidence matrix eliminating element method is proposed in order to search the information and establish the models of mechanisms automatically after finishing assembly simulation in virtual environment. Both methods have important significance for reducing the workload of pretreatment and promoting the level of automation of kinematics analysis. Finally, the method of kinematics analysis of mechanisms is presented. Based on Descartes coordinates, three types of kinematics equations are formed. The parameters, like displacement, velocity, and acceleration, can be obtained by solving these equations. All these data are important to analyze mechanical performance. All the methods are implemented and validated in the prototype system virtual assembly process planning（VAPP）. The mechanism models are established and simulated in the VAPP system, and the result curves are shown accurately. The proposed kinematics analysis of mechanisms based on virtual assembly provides an effective method for simulating product assembly process automatically and analyzing mechanical performance after finishing assembly simulation.

Kinematic Analysis of Mobile Manipulator for Measurement and Maintenance in Dangerous Environment

This paper studies the kinematic modeling of a mobile manipulator that consists of 5-DOF manipulator and an autonomous wheeled mobile platform.Then an artificial neural network to realize the coordination motion between manipulator and mobile platform is developed.On the basis of the task specifications,the algorithm determines the appropriate control variables to respond to the well tracking trajectory.The control strategy employed for either subsystem is achieved by using a robust supervised controller.A learning paradigm is used to produce the required reference variables for an overall cooperative behavior of the sys- tem.Simulation results are presented to show the effectiveness of this approach.

Culm form analysis for bamboo, Phyllostachys pubescens

We investigated the culm form for one of the largest bamboo species, Phyllostachys pubescens Mazel ex Houz. in relation to the me- chanical constraint principles, i.e., elastic, stress and geometric similarity. The fine-resolution analysis of the culm taper indicated that the culm for P. pubescens consisted of three or four segments with various forms, except for the butt swell. This implied that the taper of the whole culm for P. pubescens could be expressed by neither of these principles. The regression slope between culm height and diameter at breast height on the double logarithmic coordinates was 0.629, which was significantly different from the values predicted from these principles. In conclusion, none of these mechanical constraint principles can express the culm taper and height-diameter relationship, and there may be a need for a more complicated model to express the culm form for P. pubescens.

Effects of Joint Controller on Analytical Modal Analysis of Rotational Flexible Manipulator

Modal analysis is a fundamental and important task for modeling and control of the flexible manipulator. However, almost all of the traditional modal analysis methods view the flexible manipulator as a pure mechanical structure and neglect feedback action of joint controller. In order to study the effects of joint controller on the modal analysis of rotational flexible manipulator, a closed-loop analytical modal analysis method is proposed. Firstly, two exact boundary constraints, namely servo feedback constraint and bending moment constraint, are derived to solve the vibration partial differential equation. It is found that the stiffness and damping gains of joint controller are both included in the boundary conditions, which lead to an unconventional secular term. Secondly, analytical algorithm based on Ritz approach is developed by using Laplace transform and complex modal approach to obtain the natural frequencies and mode shapes. And then, the numerical simulations are performed and the computational results show that joint controller has pronounced influence on the modal parameters： joint controller stiffness reduces the natural frequency, while joint controller damping makes the shape phase non-zero. Furthermore, the validity of the presented conclusion is confirmed through experimental studies. These findings are expected to improve the performance of dynamics simulation systems and model-based controllers.

NOVEL METHOD FOR ERROR ANALYSIS AND SELF-CALIBRATION OF LASER TRACKING MIRROR MECHANISM

Laser tracking system （LTS） is an advanced device for large size 3D coordinates measuring with the advantages of broad range, high speed and high accuracy. However, its measuring accuracy is highly dominated by the geometric errors of the tracking mirror mechanism. Proper calibration of LTS is essential prior to the use of it for metrology. A kinematics model that describes not only the motion but also the geometric variations of LTS is developed. Through error analysis of the proposed model, it is claimed that gimbals axis misalignments and tracking mirror center off-set are the key contributors to measuring errors of LTS. A self-calibration method is presented of calibrating LTS with planar constraints. Various calibration strategies utilizing single-plane and multiple-plane constraints are proposed for different situations. For each calibration strategy, issues about the error parameter estimation of LTS are exploded to find out in which conditions these parameters can be uniquely estimated. Moreover, these conditions reveal the applicability of the planar constraints to LTS self-calibration. Intensive studies have been made to check validity of the theoretical results. The results show that the measuring accuracy of LTS has increased by 5 times since this technique for calibration is used.

An Extended Algorithm of Flexibility Analysis in Chemical Engineering Processes

An extended algorithm of flexibility analysis with a local adjusting method for flexibility region of chemical processes, which is based on the active constraint strategy, is proposed, which fully exploits the flexibility region of the process system operation. The hyperrectangular flexibility region determined by the extended algorithm is larger than that calculated by the previous algorithms. The limitation of the proposed algorithm due to imperfect convexity and its corresponding verification measure are also discussed. Both numerical and actual chemical process examples are presented to demonstrate the effectiveness of the new algorithm.

Application of 1D/3D finite elements coupling for structural nonlinear analysis

An element coupling model (ECM) method was proposed to simulate the global behavior and local damage of a structure.In order to reflect the local damage and improve the computational efficiency,three-dimensional (3D) solid elements and one-dimensional (1D) beam element were coupled by the multi-point constraint equations.A reduced scale 1?8 model test was simulated by the ECM and a full three dimensional model (3DM) contrastively.The results show that the global behavior and local damages of ECM agree well with the test and 3DM.It is indicated that the proposed method can be used in the structural nonlinear analysis accurately and efficiently.

Design and Structural Analysis of Flexible Wearable Chair Using Finite Element Method

The flexible wearable chair is like a light weight mobile exoskeleton that allows people to sit any-where in any working position. The traditional chair is difficult to move to different working locations due to its large size, heavy weight (~5 - 7 kg) and rigid structure and thus, they are inappropriate for workplaces where enough space is not available. Flexible wearable chair has a gross weight of 3 kg as it utilizes light-weight aluminium alloy members. Unlike the traditional chair, it consists of kinematic pairs which enable taking halts between continuous movements at any working position and thus, it is capable of reducing the risk of the physical musculoskeletal disorder substantially among workers. The objective of this paper is to focus on the mechanical design and finite element analysis (FEA) of the mechanism using ANSYS® software. In the present work, all the parts of the mechanism are designed under static load condition. The results of the analysis indicate that flexible wearable chair satisfies equilibrium and stability criterion and is capable of reducing fatigue during working in an assembly line/factory.

LOGICAL ANALYSIS FOR NEURAL NETWORKS

By comparison with constraint satisfaction networks, this paper presents an essential frame of the logical theory for continuous-state neural networks, and gives the quantitative analyzing method for contradiction. The analysis indicates that the basic reason for the alternation of the logical states of the neurons is the existence of superior contradiction inside the networks. The dynamic process for a neural network to find a solution corresponds to eliminating the superior contradiction.

Effect of Multi-parameter Environmental Factors on Cucumber Leaf Surface Wetness

In this study, artificial leaf resistance was used to simulate leaf wetness. Specific to the solar greenhouse environment in Tianjin, microclimate monitoring equipment was installed for the collection of temperature group and humidity group data, as well as solar radiation and leaf wetness in the greenhouse. In order to reduce the complexity of multivariate factor prediction and ensure the richness of selected data types, correlation analysis was made to the 2 groups of data, screening 5 000 groups of data, including the humidity group data RH, RH_(20), RH_(40), temperature group data T, T_(20), T_(40), and solar radiation W. The data were then analyzed by principal component analysis, screening out 4 groups of principal components to show the leaf wetness index.