Efficient peak-shaving technology is critical to couple with the ever-increasing natural gas demand, especially in the regions lack of natural gas resources. The aim of this paper is to present a novel natural gas peak-shaving process with gas hydrates as the medium to address the issue of natural gas supply and demand imbalance, especially for the LNG-sourced natural gas, in which the cold energy from LGN gasification can be efficiently utilized. Firstly, the whole process, including the production, storage, and dissociation of NGH is designed; afterwards, energy consumption analysis and economic accounting are conducted; finally, a case study is carried out to show the efficiency of the technology. The results show that the economic effectiveness can be improved maximumly by 9.42% compared to the traditional operation model of LNG receiving terminal, indicating the feasibility of providing a flexible natural gas peak-shaving process with the gas hydrate as medium.

Word embedding and deep learning methods have shown to be very effective in automated text information mining. In this work, a chemical accident case analysis method is proposed and tested based on the methods. Firstly, word vectors for the text corpus of chemical accident cases were produced based on word2vec. And then Bidirectional LSTM model with attention mechanism for text classification was constructed. Finally, case studies on the correlation analysis of the common trends of chemical accidents and automated text classification of chemical accident cases documents were performed respectively. The results revealed that the proposed method can identify common principles of chemical accidents and classify chemical accident cases. These findings highlight the feasibility of chemical accident case information mining based on word embedding through case studies. Compared with rule-based information mining, our method improves the efficiency, automation, and intelligence of information mining from chemical accident cases documents.

Toluene diisocyanate (TDI) is an important chemical intermediate prepared by phosgenation reaction between toluene diamine and phosgene with two steps name cold and thermal phosgenation respectively. In this paper, the reactive distillation model for the thermal phosgenation reaction based the kinetics equations was established for an industrial installation, and the effects of the different parameters on the process performance were studied firstly; then based on the analysis results, a thermal coupling process between the towers of reactive distillation and phosgene purification was presented and investigated; finally, the optimal operation scheme was simulated and the results showed that the proposed process can save the heat and cold energy with 7.29% and 32.78%, respectively, and reduce the total annual cost about 17.11%. The result of the paper can be used to guide the operation configuration or the revampment of the TDI production equipment.