A new solution to the inverse position analysis of the redundant serial robot

A new solution to the inverse position analysis of the redundant serial robot is presented. The inverse position analysis problem of the redundant serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least square problem with the analytic form of a new Jacobi matrix. In this way, the inverse solution of the redundant serial robot can be searched out quickly under the desired precision when the positions of the three non-collinear end effector points are given. The inverse position analysis of the 7R redundant serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm.     

Iterative algorithm of steered minimum variance and its application in weak targets detection

The steered covariance matrix (STCM) and its inverse matrix should be calculated in each beam for steered minimum variance (STMV). The inverse matrix needs complex computation and restricts its application in engineering. Combining the integration character of one-phase regressive filter with the iterative formula of inverse matrix, an STMV iterative algorithm is proposed. The computational cost of the iterative algorithm is reduced approximately to be 2/M times of the original one when there are M sensors, and is more advantaged for the realization of the algorithm in real time. Simulation results show that the STMV iterative algorithm can preserve the characters of STMV on high azimuth resolution and weak target detection while the computational cost reduced sharply. The analysis on sea trial data proves that the proposed algorithm can estimate each target’s azimuth even when the source powers differ in large scales or their bearings are very approximate.     

Gas turbulence modulation model for gas-solid flows in two-fluid approach

Turbulence enhancement by particle wake effect is studied by numerical simulation of gas turbulent flows passing over particle under various particle sizes, inlet gas velocities, gas viscosity, gas density and the distance of particles. By performing dimension analysis and using the form of gas-particle interaction source term for reference, a new semi-empirical turbulence enhancement model by the particle-wake effect is proposed. The turbulence model is then incorporated into second-order moment model for simulating gas-particle flows in a horizontal channel with different wall roughness and a sudden-expansion chamber. The results show that this model is with higher calculating accuracy than another two turbulence models in comparison with the experimental results.     

Structural Optimization for Roof Crush Test Using an Enforced Displacement Method

A roof crush test has been utilized to reduce passengers’ injuries from a vehicle rollover. The Federal Motor Vehicle Safety Standards (FMVSS) 216 and the Insurance Institute for Highway Safety (IIHS) perform actual vehicle tests and evaluate the vehicle’s ratings. Nonlinear dynamic response structural optimization can be employed not only for achievement of a high rating but also minimization of the weight. However, the technique needs a huge computation time and cost because many nonlinear dynamic response analyses are required in the time domain. A novel method is proposed for nonlinear dynamic response structural optimization regarding the roof crush test. The process of the proposed method repeats the analysis domain and the design domain until the convergence criteria are satisfied. In the analysis domain, the roof crush test is simulated using a high fidelity model of nonlinear dynamic finite element analysis. In the design domain, a low fidelity model of linear static response structural optimization is utilized with enforced displacements that come from the analysis domain. Correction factors are employed to compensate the differences between a nonlinear dynamic analysis response and a linear static analysis response with enforced displacement. A full-scale vehicle problem is optimized with a constraint on the rigid wall force from the analysis in the design domain.     

Wind turbine gearbox reliability analysis based on the system level stress-strength model

In order to estimate the reliability of wind turbine gearbox based on the system level, a generalized stress-strength model is introduced. Considering that the system works properly under a variety of random stresses which affect every component, the total stress on the system is given by a known linear combination of the stresses of all components. Then the strength of the system can be viewed as a linear combination of the strengths of relative components. In this model, stress and strength are independent of each other. Reliability of the system is the probability that strength exceeds stress. Finally, the reliability of wind turbine gearbox is estimated by the multivariable reliability calculation method. The corresponding result is compared with the results of reliability in the extreme cases(completely dependent and completely independent) by the traditional evaluation method.     

Construction of rate-compatible (RC) low-density parity-check (LDPC) convolutional codes based on RC-LDPC block codes

In this paper, a family of rate-compatible (RC) low-density parity-check (LDPC) convolutional codes can be obtained from RC-LDPC block codes by graph extension method. The resulted RC-LDPC convolutional codes, which are derived by permuting the matrices of the corresponding RC-LDPC block codes, are systematic and have maximum encoding memory. Simulation results show that the proposed RC-LDPC convolutional codes with belief propagation (BP) decoding collectively offer a steady improvement on performance compared with the block counterparts over the binary-input additive white Gaussian noise channels (BI-AWGNCs).     

Evolutionary game on oil and gas companies’ pollution treatment

This paper presents a dynamic model of pollution treatment strategies, driven by the bargaining relationships between governments, oil and gas companies and local residents. The results show that government plays a dominating role and government environmental policies have significant impact on other two parties’ behavior. To achieve better pollution treatment in the future, we put forward the following suggestions. An improvement in the legal system is required, and the legal enforcement needs to be strengthened. In terms of pollution treatment, responsibilities and obligations of these three parties need to be clearly defined. A wellfunctioned reward and penalties system needs to be established for minimizing the environment damage in the future.     

Lubricating performance of carbon nanotubes in internal combustion engines – engine test results for CNT enriched oil

The main purpose of this research is to reduce friction losses by adding carbon nanotubes to engine oil. Extremely favorable tribological properties of carbon nanotubes have been extensively studied on the microscopic scale and using tribometers, have not yet been verified in the engine. Enriching oil with nanotubes can lead to significant, exceeding 7 %, reduction in the motoring torque of the engine at low crankshaft rotational speed. The phenomena associated with the dispersion of carbon nanotubes in the engine are stated and discussed. It has been shown that the oil shear during normal operation of the engine can effectively improve the dispersion of nanotubes. At the same time the oil filtration system removes agglomerates of nanotubes very quickly.