Stress intensity factor evaluations for a curved crack in orthotropic particulate composites using an interaction integral method

This paper develops a domain-independent interaction integral (DII-integral) for extracting mixed-mode stress intensity factors (SIFs) for orthotropic materials with complex interfaces. The DII-integral does not require material property gradients, and moreover its validity is not affected by material interfaces. Combined with the extended finite element method (XFEM), the DII-integral is employed to investigate a straight crack in an orthotropic functionally graded plate and a curved crack in orthotropic particulate composites.     

Research on Chromium Retrieval of Black Soil with Hyperspectral Imagery in Northeast of China#br#

According to the definition of spectral integral，a new spectral characteristic parameter，with the name Reversed Spectral Absorption Integral(RSAI)，is proposed and used to retrieve the chromium content based on the Partial Least Squares Regression(PLSR) model.The contrastive study with other traditional spectral characteristic parameters，including differential transformation，inverse transformation，absorption area，etc.indicates that(1) the first derivation of square root transformed model can predict the chromium content quantitatively in terms of spectral transformations.(2) the stability of the absorption area model is slightly poor，and the chromium content of samples can only be estimated roughly.(3) However，as to the inversed spectral absorption integral model，the adjustment determination coefficient(Ad-R²) of the modeling and verification is 0.73 and 0.77，while the Root Mean Squared Error(RMSE) is 2.63 mg/kg and 2.36 mg/kg respectively with Relative Percent Deviation(RPD) being 3.21，which shows that the RSAI model has excellent prediction ability.So，the inversed spectral absorption integral new model can improve the accuracy and stability used to retrieve the chromium content，which provides a new idea for monitoring the chromium contamination in soil.     

注塑机料筒温度调控和计算机仿真研究

利用模糊控制和比例积分微分(PID)控制相结合的手段对注塑机料筒温度进行了控制,同时以Matlab 6.0软件为仿真平台,对料筒温度控制进行了模拟仿真研究。实验发现,在注塑机料筒升温过程中利用CHR整定的PID控制手段和模糊控制手段,恒温过程中利用人工整定的PID控制手段,可保证快速的料筒升温响应速率和稳定的保温过程。通过实际注塑实验对该仿真结果进行了验证,在十组实验中,料筒温度误差不超过2%,产品翘曲变形量不超过0.059 mm。     

Measurements of thermal-neutron capture cross-section of Cesium-135 by applying mass spectrometry

ABSTRACT

The thermal-neutron capture cross-section (σ₀) and resonance integral (I₀) were measured for the ¹³⁵Cs(n,γ)¹³⁶Cs reaction by an activation method and mass spectrometry. Because of difficulty in the preparation of pure ¹³⁵Cs samples, we used ¹³⁵Cs contained as an impurity in a normally available ¹³⁷Cs standard solution. An isotope ratio of ¹³⁵Cs and ¹³⁷Cs in a standard ¹³⁷Cs solution was measured by mass spectrometry to quantify ¹³⁵Cs. Cesium-135 impurity along with the ¹³⁷Cs standard solution was irradiated at the hydraulic conveyer of the research reactor in the Institute for Integral Radiation and Nuclear Science, Kyoto University. Wires of Co/Al and Au/Al alloys were used as neutron monitors to measure thermal-neutron fluxes and epi-thermal Westcott’s indices at an irradiation position. A gadolinium filter was used to measure the σ₀, and a value of 0.133 eV was taken as the cut-off energy. Gamma-ray spectroscopy was used to measure induced activities of ¹³⁷Cs, ¹³⁶Cs and monitor wires. On the basis of Westcott’s convention, the σ₀ and I₀ values were derived as 8.57 ± 0.25 barn, and 45.3 ± 3.2 barn, respectively. The value of σ₀ obtained in the present study agreed within the limits of uncertainties with the past-reported value of 8.3 ± 0.3 barn.     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

A novel quasi-oppositional harmony search algorithm and fuzzy logic controller for frequency stabilization of an isolated hybrid power system

The intermittent wind power in isolated hybrid distributed generation (IHDG) may cause serious problems associated with frequency (f) and power (P) fluctuation. Energy storage devices such as battery, super capacitor, and superconducting magnetic energy storage (SMES) may be used to reduce these fluctuations associated with f and P. This paper presents a study of IHDG power system for improving both f and P deviation profiles with the help of SMES. The studied IHDG power system is consisted of wind turbine generator and diesel engine generator. Both f and P control problems of the studied power system model are addressed in presence or absence of SMES. Fuzzy logic based proportional–integral–derivative (PID) controller with SMES is used for the purpose of minimization of f and P deviations. The different tunable parameters of the PID controller and those of the SMES are tuned by a novel quasi-oppositional harmony search algorithm. Performance study of the IHDG power system model is carried out under different perturbation conditions. The results demonstrate minimum f and P deviations may be achieved by using the proposed fuzzy logic based PID controller along with SMES.     

Design of disturbance observer based on adaptive-neural control for large-scale time-delay systems in the presence of actuator fault and unknown dead zone

This article presents an adaptive neural compensation scheme for a class of large-scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.     

Controller design for distributed parameter systems with time delays in the boundary feedbacks via the backstepping method

For a distributed parameter system with an input delay in the boundary, a feedback control law is presented by means of the backstepping method. The square integrability of input signal is verified based on the target system. Then, the boundedness and invertibility of the corresponding backstepping transformation are proved under the regularity of system and the admissibility of feedback operator. Thus, the resulting closed-loop system is shown to be exponentially stable. Finally, as an application, a numerical simulation of a one-dimensional Schrödinger equation with a delay input is carried out, and the simulation results demonstrate the effectiveness of the suggested control law.     

Robustness analysis and distributed control of a networked system with time-varying delays

This paper is concerned with the robustness analysis and distributed output feedback control of a networked system with uncertain time-varying communication delays. This system consists of a collection of linear time-invariant subsystems that are spatially interconnected via an arbitrary directed network. Using a dissipation inequality that incorporates dynamic hard IQCs (integral quadratic constraints) for the delay uncertainties, we derive some sufficient robustness conditions in the form of coupled linear matrix inequalities, in which the coupled parts reflect the interconnection structure of the system. We then provide a procedure to construct a distributed controller to ensure the robust stability of the closed-loop system and to achieve a prescribed $\ell_2$-gain performance. The effectiveness of the proposed approach is demonstrated by some numerical examples.     

Solution for the general integral‐type nonlocal plasticity model with Tikhonov regularization

A new solution approach, based on Tikhonov regularization on the Fredholm integral equations of the first kind, is proposed to find the approximate solutions of the strain softening problems. In this approach, the consistency condition is regularized with the Tikhonov stabilizers along with a regularization parameter, and the internal variable increments are solved from the resulting Euler's equations. It is shown that, as the regularization parameter is increased, the solutions converge to a unique one. A nonlocal yield condition and a nonlocal return mapping algorithm are proposed to carry out the integration of constitutive equations in the time and spatial domains. A global plastic dissipation principle is proposed to relax the classical local plastic dissipation postulate. Numerical examples show that the proposed approach leads to objective, mesh‐independent solutions of the softening‐induced localization problems. A comparison of the results from the proposed approach with those from the gradient‐dependent plasticity model shows that the two models give close solutions.