ABSTRACT
Process economy and dynamic controllability are critical for DMC/MeOH separation via the PSD process. In this paper, rigorous steady-state and dynamic simulations of atmospheric-pressurized process for DMC/MeOH separation with no, partial, and full heat integration have been carried out with Aspen Plus and Aspen Dynamics. Further investigations have been conducted into the economic design and dynamic controllability of the three neat systems. Simulation results indicated that: the separation process via full and partial heat integration provided TAC savings of 39.2 and 36.2%, respectively, compared to that of no heat integration; the non-heat-integrated system displays good dynamic performance, critical dynamic penalties were demonstrated for both partial and full heat integration processes, while the partial one exhibited a more robust control except for precisely maintaining XB2(DMC); a PCTC scheme with a CC/TC cascade control was proposed to precisely maintain the product concentration for the fully heat-integrated PSD process. A comparison of the economy between atmospheric-pressurized and pressurized-atmospheric sequences indicated that the former is more energy efficient. Further, a comparison of the economy between atmospheric-pressurized and pressurized-atmospheric sequences indicated that the former is more energy efficient. This study will provide new insights into the energy efficiency and has some implications for design and control of DMC/MeOH separation in the industrialization process.
ABSTRACT
The calorific value of coal ash is an important indicator to evaluate the coal quality. In the experiment, the effect of spectrum and processing methods such as smoothing, differential processing, multiplicative scatter correction (MSC) and standard normal variate (SNV) in improving the near-infrared diffuse reflection spectrum signal-noise ratio was analyzed first, then partial least squares (PLS) and principal component analysis (PCR) were used to establish the calorific value model of coal ash for the spectrums processed with each preprocessing method respectively. It was found that the model performance can be obviously improved with 5-point smoothing processing, MSC and SNV, in which 5-point smoothing processing has the best effect, the coefficient of association, correction standard deviation and forecast standard deviation are respectively 0.9899, 0.00049 and 0.00052, and when 25-point smoothing processing is adopted, over-smoothing occurs, which worsens the model performance, while the model established with the spectrum after differential preprocessing has no obvious change and the influence on the model is not large.
ABSTRACT
Rottenness is most prevalent and devastating disease that threats citrus fruit. Automatic detection of early rottenness can enhance the competitiveness and profitability of the citrus industry. However, there is no efficient automatic detection technology at this time that could detect this disease. The navel orange was selected as research objective. Hyperspectral fluorescence imaging was used to detect early rottenness in orange. Optimum index factor (OIF) method was applied to identify the optimal band combination. 100% detection rate was achieved based on the optimal bands ratio image and two threshold values. The research showed that the proposed method can effectively overcome the affect from florescence effect because stem damage area and stem also can produce florescence under ultraviolet light. This study will lay a foundation for developing multispectral detection system used in on-line detection of early rottenness fruit.
