We have studied the effect of the series resistance on the heating of the cathode, which is based on carbon nanotubes and serves to realize the field emission of electrons into the vacuum. The experiment was performed with the single multi-walled carbon nanotube (MCNT) that was separated from the array grown by CVD method with thin-film Ni-Ti catalyst (nickel 4 nm/Ti 10 nm). The heating of the cathode leads to the appearance of a current of the thermionic emission. The experimental voltage current characteristic exhibited the negative resistance region caused by thermal field emission. This current increases strongly with increasing voltage and contributes to the degradation of the cold emitter. The calculation of the temperature of the end of the cathode is made taking into account the effect of the phenomenon that warms up and cools the cathode. We have developed a method for processing of the emission volt-ampere characteristics of a cathode, which relies on a numerical calculation of the field emission current and the comparison of these calculations with experiments. The model of the volt-ampere characteristic takes into account the CNT’s geometry, properties, its contact with the catalyst, heating and simultaneous implementation of the thermionic and field emission. The calculation made it possible to determine a number of important parameters, including the voltage and current of the beginning of thermionic emission, the temperature distribution along the cathode and the resistance of the nanotube. The phenomenon of thermionic emission from CNTs was investigated experimentally and theoretically. The conditions of this type emission occurrence were defined. The results of the study could form the basis of theory of CNT emitter’s degradation.

Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.

Accurate temperature control during the induction heating process of carbon fiber reinforced polymer (CFRP) is crucial for the curing effect of the material. This paper first builds a finite element model of induction heating, which combines the actual fiber structure and resin matrix, and systematically analyzes the heating mechanism and temperature field distribution of CFRP during the heating process. Based on the temperature distribution and variation observed in the material heating process, a PID control method optimized by the sparrow search algorithm is proposed, which effectively reduces the temperature overshoot and improves the response speed. The experiment verifies the effectiveness of the algorithm in controlling the temperature of the CFRP plate during the induction heating process. This study provides an effective control strategy and research method to improve the accuracy of temperature control in the induction heating process of CFRP, which helps to improve the results in this field.

Four alloys based on niobium and containing about 33wt.%Cr, 0.4wt.C and, in atomic content equivalent to the carbon one, Ta, Ti, Hf or Zr, were elaborated by classical foundry under inert atmosphere. Their as-cast microstructures were characterized by X-ray diffraction, electron microscopy, energy dispersion spectrometry and while their room temperature hardness was specified by Vickers indentation. The microstructures are in the four cases composed of a dendritic Nb-based solid solution and of an interdendritic NbCr₂ Laves phase. Despite the MC-former behavior of Ta, Ti, Hf and Zr usually observed in nickel or cobalt-based alloys, none of the four alloys contain MC carbides. Carbon is essentially visible as graphite flakes. These alloys are brittle at room temperature and hard to machine. Indentation shows that the Vickers hardness is very high, close to 1000HV_10kg. Indentation lead to crack propagation through the niobium phase and the Laves areas. Obviously no niobium-based alloys microstructurally similar to high performance MC-strengthened nickel-based and cobalt-based can be expected. However the high temperature mechanical and chemical properties of these alloys remain to be investigated.

Quartz sand was used as bed material in a small fluidized bed reactor with 1 kg/h feed. Corn straw powder with particle size of 20–40 mesh, 40–60 mesh, 60–80 mesh and 80–120 mesh was used as raw material for rapid pyrolysis at reaction temperatures of 400 °C, 450 °C, 500 °C and 550 °C. The bio-oil obtained after liquefaction of pyrolysis gas was analyzed. The variation trend of bio-oil composition in pyrolysis of corn straw powder with different reaction temperatures and raw material sizes was compared. The results show that: (1) the content of 3-hydroxyl-2-phenyl-2-acrylic acid in bio-oil increases with the decrease of raw material particle size, but it is less at 450 °C; (2) with the increase of reaction temperature, the content of hydroxyacetaldehyde in bio-oil increases at first and then decreases: the content of hydroxyacetaldehyde in bio-oil is the highest at 500 °C when the particle size is 20–40 mesh, and the highest at 450 °C with the other three particle sizes. Compared with other particle sizes, raw material with the particle size of 60–80 mesh is not conducive to the formation of aldehyde compounds; (3) the reaction temperature of 500 °C and the particle size of 60–80 mesh of raw materials are more conducive to the formation of phenolic compounds in bio-oil; (4) the ester compounds with particle size of 20–40 mesh in bio-oil is 20% higher than that of other particle sizes; (5) the reaction temperature and the particle size of raw materials had no significant effect on the formation of ketones, alcohols and alkane compounds in bio-oils.