Dynamics of inorganic nutrient species in the Bohai seawaters

Within the frame of a Sino-German Joint Research Program, two cruises of “R/V Dong Fang Hong 2” were carried out in September–October 1998 and April–May 1999, respectively, to understand the dynamics of nutrients in the Bohai. Nutrient species (NO₃⁻, NO₂⁻, NH₄⁺, PO₄³⁻ and SiO₃²⁻) are determined colorimetrically on board for five anchor and 30 grid stations. In situ incubation experiments are performed to determine planktonic nutrient uptake and benthic exchange flux. Nutrient concentrations display short-term variability and seasonal change in the Bohai, with higher levels in shallow coastal waters than in the Central Bohai. The influence of riverine discharge on nutrient levels can be seen from salinity isopleths, nutrient distribution and species ratios. Near-bottom (nb) waters have similar nutrient concentrations as to the surface waters in the Central Bohai, whereas stratification takes place in the Bohai Strait and North Yellow Sea. In situ incubation experiments provide evidence that the uptake ratio (i.e. N, P) by phytoplankton is proportional to the ratios among nutrient species in ambient waters. Based on the data of this study and previously publications, a preliminary estimate of nutrient budgets via riverine input and atmospheric deposition is established. The results indicate that atmospheric deposition gains importance over rivers in delivering nutrients into the Bohai and sustain the new production, following recent decrease in riverine inflow caused by drought periods in North China and damming practices. A historical review of nutrient data indicates that concentrations of nitrogen increase and phosphorus and silica decrease in the Central Bohai over last 40 years. This potentially has an important influence on the health of ecosystem in Bohai (e.g. food web and community structure), though further study is needed to examine the scenario in more detail.     

Geometric calibration algorithm of polarization camera using planar patterns

Polarization pattern provides additional information besides spectral signatures. It can be used in many applications, such as navigation, defect detection and object identification. A novel polarization camera composed of four synchronized cameras is proposed, and it can realize real-time polarization measurement. This study particularly concentrates on the geometric calibration of the system. The projection model is analyzed and the multi-camera calibration algorithm is proposed. Firstly, each camera is calibrated separately using planar patterns, and then the geometric calibration algorithms are performed. Due to the geometrical constraint, a global optimization method results in smaller estimation uncertainties. A mean rotation error of 0.025° and a mean translation error of 0.26mm are achieved after geometric calibration. The images are rectified to establish a correspondence among cameras and are combined to acquire the polarization measurement. The polarization pattern of the skylight is measured by the system and the results are consistent with the previous studies.     

Research of legal affair simulation based on Petri net

Legal affair simulation is on the basis of information technology, and can simulate legal scene. College students do legal experiments with virtual reality scene. This helps to train college students. Petri net has not only strict math definition to analyze the dynamic behavior of models, but also intuitive graphic expression. Petri net is used to model for legal process. Reduction rules of Petri net are used to analyze the correctness of the system. At last Java Business Process Management (JBPM) technology is used to realize legal affair simulation models, models are transformed into flow charts. Simulation software deduces processes of legal affair. Many college students have improved their ability with the software, the fact proves that the method is effective.     

Magnetic field tuning characteristics of bimodal ultrasonic motor stator

The magnetic field tuning characteristics of an ultrasonic motor (USM) stator are discussed. The stator consists of two piezoelectric ceramic transducer (PZT) plates and one sandwiched-in Terfenol-D plate. The dimensions of the stator are carefully adjusted to specifically discuss the influence of the magnetic field on the frequency difference between the longitudinal and bending modes of the stator. The frequency difference discussed in this paper is usually small and mainly caused by uneven materials, machining errors and changes in external conditions (temperature, pre-stress or load). The longitudinal and bending modes of the stator are simultaneously excited by an external electric field to generate the elliptic motion trajectories of the driving points. A direct current (DC) magnetic field is applied to decrease the difference between the two mode frequencies of the fabricated stator. In experiments, the dependences of the two mode frequencies and their difference on DC magnetic fields are all investigated. The experimental results indicate that the difference between the longitudinal and bending mode frequencies of the PZT/Terfenol-D/PZT composite stator can be tuned by changing the intensity of the external DC magnetic field.     

Sensorimotor self-learning model based on operant conditioning for two-wheeled robot

Traditional control methods of two-wheeled robot are usually model-based and require the robot’s precise mathematic model which is hard to get. A sensorimotor self-learning model named SMM TWR is presented in this paper to handle these problems. The model consists of seven elements: the discrete learning time set, the sensory state set, the motion set, the sensorimotor mapping, the state orientation unit, the learning mechanism and the model’s entropy. The learning mechanism for SMM TWR is designed based on the theory of operant conditioning (OC), and it adjusts the sensorimotor mapping at every learning step. This helps the robot to choose motions. The leaning direction of the mechanism is decided by the state orientation unit. Simulation results show that with the sensorimotor model designed, the robot is endowed the abilities of self-learning and self-organizing, and it can learn the skills to keep itself balance through interacting with the environment.     

Compensation of pressure enthalpy effects on temperature fields for throttling of high-pressure real gas

For the pressure enthalpy of high pressure pneumatics, the computational fluid dynamics (CFD) simulation based on ideal gas assumption fails to obtain the real temperature information. Therefore, we propose a method to compensate the pressure enthalpy of throttling for CFD simulation based on ideal gas assumption. Firstly, the pressure enthalpy is calculated for the pressure range of 0.101 to 30 MPa and the temperature range of 190 to 298 K based on Soave-Redlich-Kwong (S-R-K) equation. Then, a polynomial fitting equation is applied to practical application in the above mentioned range. The basic idea of the compensation method is to convert the pressure enthalpy difference between inlet air and nodes into the compensation temperature. In the above temperature and pressure range, the compensated temperature is close to the real one, and the relative temperature drop error is below 10%. This error is mainly caused by the velocity difference of the orifice between the real and ideal gas models. Finally, this compensation method performs an icing analysis for practical high pressure slide pilot valve.     

Approximate method for reliability assessment of complex phased mission systems

Phased-mission systems (PMSs) have wide applications in engineering practices, such as manmade satellites. Certain critical parts in the system, such as cold standby, hot standby and functional standby, are designed in redundancy architecture to achieve high reliability performance. State-space models such as Markov process have been used extensively in previous studies for reliability evaluation of PMSs with dynamic behaviors. The most popular way to deal with the dynamic behaviors is Markov process, but it is well known that Markov process is limited to exponential distribution. In practice, however, the lifetime of most machinery products can follow non-exponential distributions like the Weibull distribution which cannot be handled by the Markov process. In order to solve this kind of problem, we present a semi-Markov model combined with an approximation algorithm to analyze PMS reliability subjected to non-exponential failures. Furthermore, the accuracy of the approximation algorithm is investigated by comparing to an accurate solution, and a typical PMS (attitude and orbit control system) is analyzed to demonstrate the implementation of the method.     

Fault diagnosis for wind turbine based on improved extreme learning machine

A fault diagnosis method based on improved extreme learning machine (IELM) is proposed to solve the weakness (weak generalization ability, low diagnostic rate) of traditional fault diagnosis with feedforward neural network algorithm. This method fuses signal feature vectors, extracts six parameters as the principal component analysis (PCA) variables, and calculates correlation coefficient matrix among the variables. The weight values of control parameters in the extreme learning model are dynamically adjusted according to the test samples’ constantly changing. Consequently, the weight fixed drawback in the original model can be remedied. A fault simulation experiment platform for wind turbine drive system is built, eight kinds of fault modes are diagnosed by the improved extreme learning model, and the result is compared with that of other machine learning methods. The experiment indicates that the method can enhance the accuracy and generalization ability of diagnosis, and increase the computing speed. It is convenient for engineering application.     

Gain and noise figure analysis of Er<Superscript>3+</Superscript>-doped YAG transparent ceramic microchip amplifier

The rate equations and the power evolution equations based on excited state absorption (ESA) and cooperative upconversion (CUC) of high concentration erbium-doped yttrium aluminum garnet (YAG) transparent ceramic waveguide amplifier are set up to analyze the effects of the pump power, active ion concentration and waveguide length on the amplifier gain and noise figure (NF). The numerical analysis predicts that with a pump power of 100mW, an active ion concentration of 1.0×10²⁶ ion/m³ and a waveguide length of 3 cm, a small-signal gain of 30 dB and an NF of 5 dB can be achieved in the micro-chip amplifier.     

Effect of orthogonal stiffeners on the stability of axially compressed steel jacking pipe

Load conditions for steel pipe-jacking are complex during the construction stage. The stability of steel jacking pipe has been an increasingly important problem as jacking forces, pipe diameters and jacking distances increase. However, there are no standards for pipe reinforcement, for prevention of buckling, or for remedying pipe that buckles when being jacked axially. Past experience suggests that stiffeners can effectively reinforce the structure. This study analyzes the effect of different stiffeners on the stability of steel jacking pipe under axial compression using finite element analysis. The results suggest that the stability of steel jacking pipe can be significantly improved by using orthogonal stiffeners, in terms of engineering costs and construction space inside the pipe. Based on current engineering practice, the application of orthogonal stiffeners is discussed. This study provides a useful reference for the design and construction of steel jacking pipe.