Development and Performance Evaluation of Catalyst for Productive Ethylene Cracking Feedstock in Selective Hydrocracking of Straight Run Diesel Oil

The upgrading of diesel oil to produce ethylene rich cracking feedstock is an important and promising technical route to reduce the ratio of diesel to gasoline. In the present work, a hydrocracking catalyst suitable for selective hydrocracking of straight run diesel oil to produce high-quality ethylene cracking feedstock at low cost was developed, by optimizing the composition of catalyst support materials, using amorphous silicon aluminum and aluminum oxide with high mesopore content as the main support, and modified Y zeolite with excellent aromatic ring opening selectivity as the acidic component. The catalyst has in-depth characterized by X-ray diffraction, transmission electron microscopy, scanning electron microscopy, N2-low temperature adsorption-desorption, NH3-temperature-programmed desorption, and IR techniques. And its catalytic cracking straight run diesel oil performance was evaluated. The results show that the prepared catalyst has high polycyclic aromatic hydrocarbon ring opening cracking selectivity. However, alkanes retained in diesel distillates can achieve the goal of producing more ethylene cracking feedstocks with low BMCI value under low and moderate pressure conditions. This work may shed significant technical insight for oil refining transformation.

Outlet Temperature Correlation and Prediction of Transfer Line Exchanger in an Industrial Steam Ethylene Cracking Process

Predicting the best shutdown time of a steam ethylene cracking furnace in industrial practice remains a challenge due to the complex coking process. As well known, the shutdown time of a furnace is mainly determined by coking condition of the transfer line exchangers （TLE） when naphtha or other heavy hydrocarbon feedstocks are cracked. In practice, it is difficult to measure the coke thickness in TLE through experimental method in the complex industrial situation. However, the outlet temperature of TLE （TLEOT） can indirectly characterize the coking situation in TLE since the coke accumulation in TLE has great influence on TLEOT. Thus, the TLEOT could be a critical factor in deciding when to shut down the furnace to decoke. To predict the TLEOT, a paramewic model was proposed in this work, based on theoretical analysis, mathematic reduction, and parameters estimation. The feasibility of the proposed model was further checked through industrial data and good agreements between model prediction and industrial data with maximum deviation 2% were observed.

Coupled simulation of recirculation zonal firebox model and detailed kinetic reactor model in an industrial ethylene cracking furnace

A coupled system simulating both firebox and reactor is established to study the naphtha pyrolysis in an industrial tubular furnace.The firebox model is based on zone method including combustion,radiation,and convection to simulate heat transfer in the furnace.A two-dimensional recirculation model is proposed to estimate the flow field in furnace.The reactor model integrates the feedstock reconstruction model,an auto-generator of detail kinetic schemes,and the reactor simulation model to simulate the reaction process in the tubular coil.The coupled simulation result is compared with industrial process and shows agreement within short computation time.

Dual-radiation-chamber coordinated overall energy efficiency scheduling solution for ethylene cracking process regarding multi-parameter setting and multi-flow allocation

Ethylene cracking process is the core production process in ethylene industry,and is paid more attention to reduce high energy consumption.Because of the interdependent relationships between multi-flow allocation and multi-parameter setting in cracking process,it is difficult to find the overall energy efficiency scheduling for the purpose of saving energy.The traditional scheduling solutions with optimal economic benefit are not applicable for energy efficiency scheduling issue due to the neglecting of recycle and lost energy,as well as critical operation parameters as coil outlet pressure(COP)and dilution ratio.In addition,the scheduling solutions mostly regard each cracking furnace as an elementary unit,regardless of the coordinated operation of internal dual radiation chambers(DRC).Therefore,to improve energy utilization and production operation,a novel energy efficiency scheduling solution for ethylene cracking process is proposed in this paper.Specifically,steam heat recycle and exhaust heat loss are considered in cracking process based on 6 types of extreme learning machine(ELM)based cracking models incorporating DRC operation and three operation parameters as coil outlet temperature(COT),COP,and dilution ratio according to semi-mechanism analysis.Then to provide long-term decision-making basis for energy efficiency scheduling,overall energy efficiency indexes,including overall output per unit net energy input(OONE),output-input ratio per unit net energy input(ORNE),exhaust gas heat loss ratio(EGHL),are designed based on input-output analysis in terms of material and energy flows.Finally,a multiobjective evolutionary algorithm based on decomposition(MOEA/D)is employed to solve the formulated multi-objective mixed-integer nonlinear programming(MOMINLP)model.The validities of the proposed scheduling solution are illustrated through a case study.The scheduling results demonstrate that an optimal balance between multi-flow allocation,multi-parameter setting,and DRC coordinated operation is reached,which achieves 3.37%and 2.63%decreases in net energy input for same product output and conversion ratio,as well as the 1.56%decrease in energy loss ratio.

Knowledge expression,numerical modeling and optimization application of ethylene thermal cracking:From the perspective of intelligent manufacturing

Applications of process systems engineering(PSE)in plants and enterprises are boosting industrial reform from automation to digitization and intelligence.For ethylene thermal cracking,knowledge expression,numerical modeling and intelligent optimization are key steps for intelligent manufacturing.This paper provides an overview of progress and contributions to the PSE-aided production of thermal cracking;introduces the frameworks,methods and algorithms that have been proposed over the past10 years and discusses the advantages,limitations and applications in industrial practice.An entire set of molecular-level modeling approaches from feedstocks to products,including feedstock molecular reconstruction,reaction-network auto-generation and cracking unit simulation are described.Multilevel control and optimization methods are exhibited,including at the operational,cycle,plant and enterprise level.Relevant software packages are introduced.Finally,an outlook in terms of future directions is presented.

Oxidation of Fe-Cr-Ni Alloys in a Low Oxygen Partial Pressure Atmosphere to Mitigate Coke Formation

Anti-coking oxide films were prepared on a 25Cr35Ni and 35Cr45Ni alloy surface under the low oxygen partialpressure atmosphere of a H2-H2O mixture. The composition and phase structure of the oxide films were analyzed by energydispersive spectroscopy (EDS), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The anti-cokingperformance of a mini tube made of a HP40 (25Cr35Ni) alloy was evaluated on a bench scale pyrolysis and coking test unit.The results showed that the surface Fe and Ni content decreased after the oxidation of the two alloys in a low oxygen partialpressure atmosphere. The oxide films were mainly composed of MnCr_(2)O_(4) and Cr_(2)O_(3). The average mass of coke in the minitube with oxide film decreased by 87% relative to that of a tube without an oxide film when the cracking temperature was 900℃. The ethylene, propylene, and butadiene yields in the pyrolysis tests were almost the same for the mini tubes withand without an oxide film. The oxide film on the alloy surface effectively inhibited catalytic filamentous coke formation.An industrial test showed that the run length of the cracking furnace with the in-situ coating technology was significantlyextended.

A New Fuzzy Clustering-Ranking Algorithm and Its Application in Process Alarm Management

Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information are challenge work that must be confronted. A new process alarm management method based on fuzzy clustering- ranking algorithm is proposed. The fuzzy clustering algorithm is used to cluster rationally the process variables, and difference driving decision algorithm ranks different clusters and process parameters in every cluster. The alarm signal of higher rank is handled preferentially to manage effectively alarms and avoid blind operation. The validity of proposed algorithm and solution is verified by the practical application of ethylene cracking furnace system. It is an effective and dependable alarm management method to improve operating safety in industrial process.