Designing price-contingent vegetable rotation schedules using agent-based simulation

Chinese vegetable production cooperatives supply their members, mostly smallholder farmers, with a rotation schedule for the year. Since vegetable prices are not stable throughout the year, designing a rotation schedule that maximizes expected profits, distributes farmers＇ profits more equitably, maintains the diversity of produce in the market, and reduces the risk of pests and diseases, requires adaptive, price-contingent rotation schedules（here, called ＂self-adaptive adjustment＂）. This study uses an agent-based simulation（ABS） to design self-adaptive rotation schedules that deliver these aims. The selfadaptive adjustment strategy was more profitable for farmers when faced with price volatility, and more equitable as well. This work provides a decision-support tool for managers of Chinese vegetable production cooperatives to provide farmers with more profitable and equitable rotation schedules.

Dynamic analysis on pressure fluctuation in vaneless region of a pump turbine

As the pump turbine tends to be operated with high head and high rotational speed, the study of stability problems becomes more important. The pump turbine usually works at operating conditions where the guide vanes experience strong vibrations. However, most traditional studies were carried out based on constant GVO(guide vane opening) simulations. In this work, dynamic analysis on pressure fluctuation in the vaneless region of a pump turbine model was conducted using a dynamic mesh method in turbine mode. 3D unsteady simulations were conducted where GVO was closed and opened by 1° from the initial 18°. Detailed time domain and frequency domain characteristics on pressure fluctuation in the vaneless region under different guide vane rotational states compared with constant GVO simulations were investigated. Results show that, during the guide vanes oscillating process, the low and intermediate frequency components in the vaneless region are significantly different. The amplitudes of pressure fluctuation are higher than those with constant GVO simulations, which agree better with the experimental data. In addition, the pressure fluctuation increases when GVO is opened, and vice versa. It can be concluded that pressure fluctuation in the vaneless region is strongly influenced by the oscillating of the guide vanes.

Application research of multivariate linkage fluctuation analysis on condition evaluation in process industry

Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.

Development of a portable mid-infrared methane detection device

Based on direct absorption spectroscopy(DAS), a portable methane(CH_4) detection device was implemented. The device mainly includes a dual-channel non-dispersive infrared sensor(integrated with an infrared light source, light path and pyroelectric detector), a driving circuit of the sensor, an ARM11 embedded Win CE system, and a Lab VIEW-based data-processing platform. Experiments were carried out with prepared CH_4 samples to investigate the sensing performance. The relative detection error is less than 9.14% within the measuring range of 0—7×10^(-2). For a CH_4 sample with concentration of 0(i.e., pure nitrogen), the measured concentration fluctuation range is-1.2×10^(-5)—+2×10^(-5). An Allan deviation analysis on the gas sample with concentration of 0 indicates that the 1σ limit of detection(LoD) of the device is 4.8×10^(-6) with an average time of 1 s. Experiments were performed on three CH_4 samples with different concentrations to test the response time, which is validated to be less than 20 s. Due to the small size of the ARM11 embedded system and the powerful data processing capability of the Lab VIEW platform, the proposed portable and miniaturized CH_4 sensor shows a good application prospect in mining operations and some other industrial fields.