THEORETICAL BASIS AND GENERAL OPTIMAL FORMULATIONS OF ISOPARAMETRIC GENERALIZED HYBRID/MIXED ELEMENT MODEL FOR IMPROVED STRESS ANALYSIS

By the modified three-field Hu-Washizu principle, this paper establishes a theoretical founda- tion and general convenient formulations to generate convergent stable generalized hybrid/mixed cle- ment (GH/ME) model which is invariant with respect to coordinate, insensitive to geometric distortion and suitable for improved stress computation. In the two proposed formulations, the stress equilibrium and orthogonality constraints are imposed through incompatible displacement and internal strain modes respectively. The proposed model by the general formulations in this paper is characterized by including as- sumed stress/strain, assumed stress, variable-node, singular, compatible and incompatible GH/ME models. When using regular meshes or the constant values of the isoparametric Jacobian Det in the assumed strain in- terpolation, the incompatible GH/ME model degenerates to the hybrid/mixed element model. Both general and concrete guidelines for the optimal selection of element shape functions are suggested. By means of the GH/ME theory in this paper, a family of new GH/ME can be and have been easily constructed. The software can also be developed conveniently because all the standard subroutines for the corresponding isoparametric displacement elements can be utilized directly.

A criterion for high-cycle fatigue life and fatigue limit prediction in biaxial loading conditions

This paper presents a criterion for high-cycle fatigue life and fatigue strength estimation under periodic proportional and non-proportional cyclic loading. The criterion is based on the mean and maximum values of the second invariant of the stress deviator. Important elements of the criterion are： function of the non-proportionality of fatigue loading and the materials parameter that expresses the materials sensitivity to non-proportional loading. The methods for the materials parameters determination uses three S–N curves： tension–compression, torsion, and any non-proportional loading proposed. The criterion has been verified using experimental data, and the results are included in the paper. These results should be considered as promising. The paper also includes a proposal for multiaxial fatigue models classification due to the approach for the nonproportionality of loading.

Simulations of fast component and slow component of SMBI on HL-2A tokamak

It is very important to improve the penetration depth and fueling efficiency of supersonic molecular beam injection（SMBI） especially for the next generation fusion devices such as ITER. Two components, a fast component（FC） and a slow component（SC）, have been observed in the HL-2A SMBI experiments for several years, and the FC can penetrate much more deeply than the common SMBIs which draws a great deal of attention for a better fueling method. It is the first time to the FC and SC of SMBI have been simulated and interpreted in theory and simulation in this paper with the trans-neut module of the BOUT＋＋ code. The simulation results of the FC and SC are clear and distinguishable in the same way as the observation in experiment. For the major mechanism of the FC and SC, it is found that although the difference in the injection velocity has some effect on the penetration depth difference between the FC and SC, it is mainly caused by the self-blocking effect of the first ionized SMB. We also discuss the influence of the initial plasma density on the FC and SC,and the variation of the SC penetration depth with its injection velocity.

Method to generate training samples for neural network used in target recognition

Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps：use computer and simulation software to build target object＇s virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors＇ sequence.The vectors＇ sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.

Finite-time Stabilization of a General Class of Nonholonomic Dynamic Systems via Terminal Sliding Mode

This paper presents control strategies for finite-time stabilization of a class of nonholonomic dynamic systems with unknown virtual control coefficients and system parameters. The minimal dilation degree technique and the terminal sliding mode control scheme with finite-time convergence are used to design the controllers. The systematic control strategy development involves the introduction of state transformations and the application of recursive terminal sliding mode structure. Depending on whether the system in question can be converted into a time-invariant linear system or not, two control schemes are proposed respectively guaranteeing that system states converge to zero in finite time. The effectiveness and the robust feature of the developed control approaches are testified by two practical examples： the simplified underactuated hovercraft system and the parking problem for a mobile robot of the unicycle type.