To reveal quality change rules and establish the predicting model of konjac vacuum drying, a response surface methodology was adopted to optimize and analyze the vacuum drying process, while an artificial neural network (ANN) was applied to model the drying process and compare with the response surface methodology (RSM) model. The different material thickness (MT) of konjac samples (2, 4 and 6mm) were dehydrated at temperatures (DT) of 50, 60 and 70 °C with vacuum degrees (DV) of 0.04, 0.05 and 0.06 MPa, followed by Box–Behnken design. Dehydrated samples were analyzed for drying time (t), konjac glucomannan content (KGM) and whiteness index (WI). The results showed that the DT and MT should be, respectively, under 60 °C and 4 mm for quality and efficiency purposes. Optimal conditions were found to be: DT of 60.34 °C; DV of 0.06 MPa and MT of 2 mm, and the corresponding responses t, KGM and WI were 5 h, 61.96% and 82, respectively. Moreover, a 3-10-3 ANN model was established to compare with three second order polynomial models established by the RSM, the result showed that the RSM models were superior in predicting capacity (R² > 0.928; MSE < 1.46; MAE < 1.04; RMSE < 1.21) than the ANN model. The main results may provide some theoretical and technical basis for the konjac vacuum drying and the designing of related equipment.

To realize energy-saving and efficient industrial grain drying, the present work studied the variable-temperature drying process of corn drying in a novel industrial corn-drying system with a heat recycling and self-adaptive control function. The drying kinetics, thermal performance, heat-loss characteristics and the heat-recycling performance of the drying system under different allocations between flue gas and hot air were investigated, and the optimized drying process was proposed and compared with two constant drying processes. The results showed that the optimized drying process exhibited better drying kinetic and thermal performance than the two constant drying processes. More specifically, the total heat loss, total energy consumption and specific energy consumption of the optimized drying process were ascertained to be 36,132.85 MJ, 48,803.99 MJ and 7290.27 kJ/kg, respectively, which were lower than those of the other two processes. On the other hand, the thermal efficiency of the drying chamber for the optimized drying process was ascertained to be varied within the range of 6.81–41.71%. Overall, the validation results showed that the optimized drying process can significantly improve the drying performance of the drying system.

Laser-induced graphene (LIG) has been widely used in flexible sensors due to its excellent mechanical properties and high conductivity. In this paper, a flexible pressure sensor prepared by bionic micro/nanostructure design and LIG mass fraction regulation is reported. First, prepared LIG and conductive carbon paste (CCP) solutions were mixed to obtain a conductive polymer. After the taro leaf structure was etched on the surface of the aluminum alloy plate by Nd:YAG laser processing, the conductive polymer was evenly coated on the template. Pressure sensors were packaged with a stencil transfer printing combined with an Ecoflex flexible substrate. Finally, the effects of different laser flux and the proportion of LIG in the composite on the sensitivity of the sensor are discussed. The results show that when the laser flux is 71.66 J·cm⁻² and the mass fraction of LIG is 5%, the sensor has the best response characteristics, with a response time and a recovery time of 86 ms and 101 ms, respectively, with a sensitivity of 1.2 kPa⁻¹ over a pressure range of 0–6 kPa, and stability of 650 cycle tests. The LIG/CCP sensor with a bionic structure demonstrates its potential in wearable devices.

The purpose of this research work is to perform detailed exergetic, energetic and techno-economic analysis of the black tea drying process in the gas-type industrial dryer. Exergy–energy and techno-economic methodology was applied to investigate the heat loss, exergetic and energetic performance, exergy efficiency, improvement potential rate, sustainability index and techno-economic performance of a drying system. The results showed that the heat loss of exhaust air in the late drying process played a main contributing role in the heat loss and exergy loss of the whole drying system. Therefore, the exergy efficiency of the initial drying period and the redrying period varied from 38.08% to 65.09% and 24.76% to 26.97%, respectively. In addition, the improvement potential rate and sustainability index of the whole system varied from 6.93 kW to 12.94 kW and 1.33 to 2.86, respectively. The improvement potential obtained in the present work indicated that the drying operation is greatly in need of exergy performance improvement. Finally, the net present value and payback period obtained from techno-economic analysis were 179,442.03 USD and 5.3 years, the result is useful for investors or contractors to refer to and make investment decisions.

In order to precisely reproduce the precise seeding process of the population in the air-suction seed-metering device, it is necessary to execute accurate modeling of seed particles using the bonded-particle model, in combination with the discrete element method (DEM) and computational fluid dynamics (CFD). Through the repose angle, slope screening, rotating container, and particle sedimentation experiments, in this paper, the influence of the filling accuracy of the bonded-particle model on the flow behavior and mixing characteristics of the seed population was first explored based on EDEM software. The viability of the suggested modeling approach for pelleted vegetable seeds, as described in this study, was confirmed by comparing experimental and simulation outcomes. The surface roughness values obtained from the studies above were utilized to assess the accuracy of the bonded-particle model in filling. Additionally, a mathematical technique for determining the surface roughness was provided. Furthermore, an analysis of the multiple contacts in the bonded-particle model was also performed. The results indicated that the simulation results closely matched the experimental data when the number of sub-spheres in the bonded-particle model was equal to or more than 70, as measured by the standard deviation. In addition, the most optimal modeling scheme for the pelletized vegetable seed bonded-particles, based on the cost of coupling simulation, was found to be the bonded-particle surface roughness (BS) with a value of 0.1. Ultimately, a practical example was utilized to demonstrate the utilization of the pelleted vegetable seed bonded-particle model and the DEM-CFD coupling approach in analyzing the accuracy of the seeding process in the air-suction seed-metering device. This example will serve as a valuable reference point for future field studies.

The performance evaluation and optimization of an energy conversion system design of an energy intensive drying system applied the method of combining exergy and economy is a theme of global concern. In this study, a gas-type industrial drying system of black tea with a capacity of 100 kg/h is used to investigate the exergetic and economic performance through the exergy and exergoeconomic methodology. The result shows that the drying rate of tea varies from the maximum value of 3.48 g_water/g_{dry matter} h to the minimum 0.18 g_water/g_{dry matter} h. The highest exergy destruction rate is found for the drying chamber (74.92 kW), followed by the combustion chamber (20.42 kW) in the initial drying system, and 51.83 kW and 21.15 kW in the redrying system. Similarly, the highest cost of the exergy destruction rate is found for the drying chamber (18.497 USD/h), followed by the combustion chamber (5.041 USD/h) in the initial drying system, and 12.796 USD/h and 5.222 USD/h in the redrying system. Furthermore, we analyzed the unit exergy rate consumed and the unit exergy cost of water removal in different drying sections of the drying system, and determined the optimal ordering of each component. These results mentioned above indicate that, whether from an energy or economic perspective, the component improvements should prioritize the drying chamber. Accordingly, minimizing exergy destruction and the cost of the exergy destruction rate can be considered as a strategy for improving the performance of energy and economy. Overall, the main results provide a more intuitive judgment for system improvement and optimization, and the exergy and exergoeconomic methodology can be commended as a method for agricultural product industrial drying from the perspective of exergoeconomics.