Pyrolysis and combustion characteristics of typical waste thermal insulation materials

Experimental Study on the Effects of Washing Time, Washing Temperature, and Particle Size on the Combustion and Ash Formation Characteristics of Rice Husk

There are many problems in the direct combustion of biomass, such as low combustion efficiency and easy slagging. In this paper, rice husk (RH) was taken as the research object, and the effects of different washing pretreatment conditions (washing time (WTI), washing temperature (WTE), and particle size) on the combustion characteristics and ash formation characteristics were discussed. The results show that the combustion characteristics of RH were significantly coupling-affected by the WTE and WTI, and the comprehensive characteristics of volatile release were significantly coupling-affected by the particle size and WTI. Specifically, under the condition of high-temperature washing, prolonging the WTI will increase the ignition temperature of washed RH powder. The particle size could affect the temperature of the maximum rate of decomposition. Under the same conditions, the temperature difference of maximum rate of decomposition between washed RH powder and RH was 5-10 °C. For the original RH, the longer the WTI, the more unfavorable it was to increase the maximum weight loss rate, and the opposite was true for RH powder. With the increase in WTE, the flammability index, burnout temperature, and volatile devolatilization initial temperature increased obviously. In addition, washing pretreatment could reduce the ashing quality of RH and RH powder to varying degrees, and the ash quality was decreased by about 15% compared with that of unwashed RH. The alkali metal removal effect of washed RH powder was better than that of washed RH. The proportion of alkali metal K was decreased from 1 to 4% (washed RH) to 0.2-1% (washed RH powder). The ash deposit and slagging phenomenon were obviously improved. Under the same WTI, the higher the WTE was, the better the removal effect of alkali metals was. Correspondingly, the proportion of the eutectic composite salt of Mg-Fe-Al with a high melting point increased in the high-temperature sintering stage, which effectively improved the ash melting point and reduced the probability of ash deposit and slagging.

Mechanisms of the Action of Fire-Retardants on Reducing the Flammability of Certain Classes of Polymers and Glass-Reinforced Plastics Based on the Study of Their Combustion

In the present review, using an integrated approach based on the experimental and theoretical study of the processes of thermal decomposition and combustion of practically important polymers, such as polymethyl methacrylate, polyethylene, and glass-fiber-reinforced epoxy resin, the features of the mechanism for reducing the combustibility of these materials with phosphorus-containing flame-retardants (FR), as well as graphene, are identified. A set of original experimental methods was developed and applied that make it possible to study the kinetics of thermal decomposition and the thermal and chemical structure of the flames of the studied materials, including those with FR additives, as well as to measure the flame propagation velocity, the mass burning rate, and the heat fluxes from the flame on the surface of a material. Numerical models were developed and tested to describe the key parameters of the flames of the studied polymeric materials. An analysis of the experimental and numerical simulation data presented showed that the main effect of phosphorus-containing fire-retardants on reducing the combustibility of these materials is associated with the inhibition of combustion processes in the gas phase, and the effect of adding graphene manifests itself in both gas and condensed phases.

Multi-Scale Tumor Localization Based on Priori Guidance-Based Segmentation Method for Osteosarcoma MRI Images

Osteosarcoma is a malignant osteosarcoma that is extremely harmful to human health. Magnetic resonance imaging (MRI) technology is one of the commonly used methods for the imaging examination of osteosarcoma. Due to the large amount of osteosarcoma MRI image data and the complexity of detection, manual identification of osteosarcoma in MRI images is a time-consuming and labor-intensive task for doctors, and it is highly subjective, which can easily lead to missed and misdiagnosed problems. AI medical image-assisted diagnosis alleviates this problem. However, the brightness of MRI images and the multi-scale of osteosarcoma make existing studies still face great challenges in the identification of tumor boundaries. Based on this, this study proposed a prior guidance-based assisted segmentation method for MRI images of osteosarcoma, which is based on the few-shot technique for tumor segmentation and fine fitting. It not only solves the problem of multi-scale tumor localization, but also greatly improves the recognition accuracy of tumor boundaries. First, we preprocessed the MRI images using prior generation and normalization algorithms to reduce model performance degradation caused by irrelevant regions and high-level features. Then, we used a prior-guided feature abdominal muscle network to perform small-sample segmentation of tumors of different sizes based on features in the processed MRI images. Finally, using more than 80,000 MRI images from the Second Xiangya Hospital for experiments, the DOU value of the method proposed in this paper reached 0.945, which is at least 4.3% higher than other models in the experiment. We showed that our method specifically has higher prediction accuracy and lower resource consumption.