Ethylene Plant Research Articles

BASF and Sinopec may double China ethylene plant

BASF and Sinopec may double China ethylene plant

Chloroplast proteome analysis of Nicotiana tabacum overexpressing TERF1 under drought stress condition

BackgroundChloroplast is indispensable for plant response to environmental stresses, growth and development, whose function is regulated by different plant hormones. The chloroplast proteome is encoded by chloroplast genome and nuclear genome, which play essential roles in plant photosynthesis, metabolism and other biological processes. Ethylene response factors (ERFs) are key transcription factors in activating the ethylene signaling pathway and plant response to abiotic stress. But we know little about how ethylene regulates plastid function under drought stress condition. In this study we utilized tobacco overexpressing tomato ethylene responsive factor 1 (TERF1), an ERF transcription factor isolated from tomato, to investigate its effects on the plastid proteome under drought stress condition by method of iTRAQ technology.ResultsResults show that TERF1 represses the genes encoding the photosynthetic apparatus at both transcriptional and translational level, but the genes involved in carbon fixation are significantly induced by TERF1. TERF1 regulates multiple retrograde signaling pathways, providing a new mechanism for regulating nuclear gene expression. TERF1 also regulates plant utilization of phosphorus (Pi) and nitrogen (N). We find that several metabolic and signaling pathways related with Pi are significantly repressed and gene expression analysis shows that TERF1 significantly represses the Pi transport from root to shoot. However, the N metabolism is upregulated by TERF1 as shown by the activation of different amino acids biosynthesis pathways due to the induction of glutamine synthetase and stabilization of nitrate reductase although the root-to-shoot N transport is also reduced. TERF1 also regulates other core metabolic pathways and secondary metabolic pathways that are important for plant growth, development and response to environmental stresses. Gene set linkage analysis was applied for the upregulated proteins by TERF1, showing some new potential for regulating plant response to drought stress by TERF1.ConclusionsOur research reveals effects of ethylene signaling on plastid proteome related with two key biological processes, including photosynthesis and nutrition utilization. We also provide a new mechanism to regulate nuclear gene expression by ERF1 transcription factor through retrograde signals in chloroplast. These results can enrich our knowledge about ERF1 transcription factor and function of ethylene signaling pathway.

Troubleshooting a Thermosiphon Reboiler – Why New Is Not Always Better than Old

During an ethylene plant turn-around, a 38-year-old tube bundle of a vertical thermosiphon reboiler was replaced with a new, seemingly identical one. However, when the plant returned to full operation after the turn-around, the reboiler was not able to reach the same duty as the old tube bundle.Systematic troubleshooting using detailed column and thermosiphon simulation, neutron backscatter, plant data reconciliation and flow regime analysis ruled out possible reasons such as thermosiphon inlet line plugging, or lowered heat transfer due to steam superheat, or the presence of non-condensables in the steam, leaving reduced heat transfer on the tube side as the strongest suspect.To avoid plant shut-down, the issue was temporarily solved by switching from low pressure (1.6 barg) to medium pressure (7.2 barg) steam as heating medium. With the higher steam pressure and increased ?T across the exchanger the original duty was successfully recovered.To investigate the reduced heat transfer, light, laser and electron microscopy studies revealed that the surfaces of old and new reboiler tubes were very different in roughness and cleanliness, causing differing heat transfer characteristics. The gradual degradation of the tube surface, which occurred over the years, is believed to have increased the maximum heat transfer duty of the old reboiler. This theory is supported by a report from the old tube bundle’s first year of operation when similar capacity problems occurred.

Comparison between differential evolution algorithms and response surface methodology in ethylene plant optimization based on an extended combined energy - exergy analysis

This paper applies an extend energy - exergy analysis as a strategy for evaluating the performance of different types of distillation columns in ethylene production process by using industrial data. Regarding to the limitation and deficiency of energy – exergy combination, a new method named exergy destruction level (EDL) and conceptual diagram based on equipment target value is proposed for process equipment with pressure and chemical composition changes. The effects of different operational parameters on the component separation are evaluated by sensitivity analysis. Eventually response surface methodology (RSM) and artificial intelligence (DE) method are developed for optimization of the chemical plant. Comparing obtained results from ethylene plant optimization by using RSM and DE, it was found that annual profit percentage with DE method is 61.6% more than RSM method. Also, results of optimization showed that the most effective operating parameters consist of feed stream temperature, boil-up ratio, reflux ratio, column pressure and feed stage. It was observed that utilities and refrigeration cycle consumption work have been declined significantly by using DE optimizer and EDL analysis (12.6% and 11.6%) compared to RSM optimizer and exergy analysis (11.9% and 4.8%). It is obvious that, EDL analysis and DE method expedite process optimization and provide more precise analysis than conventional energy-exergy analysis.

Reprint of: Data-driven robust optimization under correlated uncertainty: A case study of production scheduling in ethylene plant

To hedge against the fluctuations generated from continuous production processes, practical solutions can be obtained through robust optimization induced by the classical uncertainty sets. However, uncertainties are sometimes correlated in industrial scheduling problems because of the connected process and various random factors. To capture and enrich the valid information of uncertainties, copulas are introduced to estimate the joint probability distribution and simulate mutual scenarios for uncertainties. Cutting planes are generated to remove unnecessary uncertain scenarios in the uncertainty sets, and then robust formulations induced by the cut set are proposed to reduce conservatism and improve the robustness of scheduling solutions. A real-world process of ethylene plant is introduced as the numerical case, and high-dimensional data-driven uncertainty sets are illustrated in detail. The proposed models are proved to control the fluctuation of consumed fuel gas below a lower level of conservatism.

Model-Based Optimization of an Acetylene Hydrogenation Reactor To Improve Overall Ethylene Plant Economics

The steam cracking process is a common technology for producing ethylene from naphtha. However, one of the major contaminants in the ethylene product stream is acetylene, which poisons catalysts used in downstream polymerization processes and must be converted to ethylene by selective catalytic hydrogenation in order to upgrade product quality and increase overall ethylene yield. The selective hydrogenation process is usually carried out in a multistage fixed-bed catalytic reactor with internal cooling between stages to ensure that the outlet concentration of acetylene does not exceed 1 ppm. Nevertheless, side reactions also occur, including total hydrogenation to ethane, which increases energy consumption at the recycle furnace and decreases overall plant productivity. Moreover, in a tail-end hydrogenation process, the catalyst surface often becomes covered by so-called green oil generated from acetylene oligomerization, which causes catalyst deactivation and lowers the selectivity to ethylene. A key cha...

A process design approach to manage the uncertainty of industrial flaring during abnormal operations

Flare management challenges are related to the flaring uncertainty during abnormal situations. In this work, a multi-objective optimization framework is upgraded with multi-period optimization and Monte Carlo simulation to incorporate the risk associated with uncertain flare events. An ethylene plant is used to present the developed framework. Using the ethylene process historical flaring data, Monte Carlo simulation generates probabilistic values for flaring events and event duration. Here, cogeneration unit (COGEN) is considered as the flare reduction alternative. The results of the formulations are presented as a set of Pareto fronts providing insights into the competing techno-economic and environmental objectives. Sensitivity analysis on the factors for the case suggests that some factors such as CO2 tax savings are severely affected by minor variations in flaring profiles, whereas others such as the fixed and operating costs are less sensitive. Hence, using this approach, the decision maker gains techno-economic-environmental insights regarding the flare reduction alternative (COGEN).

Overexpression of an EIN3-binding F-box protein2-like gene caused elongated fruit shape and delayed fruit development and ripening in tomato

Ethylene signaling converges on the ETHYLENE-INSENSITIVE3 (EIN3)/EIN3-like (EIL) transcription factors to regulate a wide range of developmental processes in plants. EBF1/2 (EIN3-binding F-box protein 1 and 2) negatively regulate the ethylene signaling pathway by mediating the degradation of EIN3/EIL proteins. We uncovered previously that SlEBF1 and SlEBF2 are involved in ethylene response, plant senescence, and fruit ripening in tomato. The present study reports on the identification of a novel tomato F-box gene, designated as SlEBF2-like due that its encoded protein is greater similarity to SlEBF2. The SlEBF2-like promoter region contains three ethylene-response elements (EREs). SlEBF2-like is upregulated by ethylene and downregulated by ethylene inhibitors in tomato seedlings. It is dynamically expressed in flowers during bud-to-anthesis and anthesis-to-post-anthesis transitions, and at the onset of fruit ripening, suggesting its role in these situations where ethylene is required for flower opening and fruit ripening. SlEBF2-like overexpression leaded to fruit elongation, caused ripening and color change to start from fruit bottom and expand gradually to the pedicel, and strongly delayed fruit development and ripening in tomato. Our study indicates that the novel EBF gene, SlEBF2-like, is involved in fruit development and ripening via regulating the ethylene response in tomato.

Research on Reliability Modeling, Allocation and Prediction of Chemical Production System

Reliability allocation and prediction play an important role in the chemical production system, controlling the significance of each production allocation and predicting system reliability to analyze the designs in each system or integrated system if meeting requirements or not. This paper takes an ethylene plant as an example to study reliability modeling, allocation and prediction of related system. It is aimed to allocate and predict each production system or unit. In terms of system reliability allocation, it finds out the reliability allocation R in integrated system is 0.76460 with improved fuzzy analytic hierarchy process (AHP). Due to the number higher than initial reliability value of 0.73886, it illustrates the integrated reliability allocation meets the design requirements. In terms of reliability prediction, the result is more accurate when using Bayes fuzzy reliability prediction to calculate system reliability level and it can reflect this kind of indeterminate small sample data better.

Optimal synthesis of compression refrigeration system using a novel MINLP approach

Abstract The optimal design of a compression refrigeration system (CRS) with multiple temperature levels is very important to chemical process industries and also represents considerable challenges in process systems engineering. In this paper, a general methodology for the optimal synthesis of the CRS, which simultaneously integrates CRS and Heat Exchanger Networks (HEN) to minimize the total compressor shaft work consumption based on an MINLP model, has been proposed. The major contribution of this method is in addressing the optimal design of refrigeration cycle with variable refrigeration temperature levels. The method can be used to make major decisions in the CRS design, such as the number of levels, temperature levels, and heat transfer duties. The performance of the developed methodology has been illustrated with a case study of an ethylene CRS in an industrial ethylene plant, and the optimal solution has been examined by rigorous simulations in Aspen Plus to verify its feasibility and consistency.

A stylized trend analysis approach for process monitoring and fault diagnosis

A stylized trend analysis was developed to identify recurring or standard operating procedures (SOP) such as equipment switching or maintenance from plant process history data to detect faults and near misses due to operator errors or equipment failures. Trend based fault detection and diagnosis systems have not been implemented widely in the chemical process industries because known fault scenarios are typically required. Known fault scenarios were not required for the stylized trend analysis because faults and near misses were identified by comparing trends with normal SOP transition responses. Large volumes of historical data were processed automatically allowing corrective action to be taken prior to an incident. The stylized trend analysis was demonstrated to detect unsteady‐state transition faults on historical distributed control system data simulated for a continuous process ethylene plant dryer switching operation. © 2017 American Institute of Chemical Engineers Process Process Saf Prog 37:411–418, 2018

Investigation of propane addition to the feed stream of a commercial ethane thermal cracker as supplementary feedstock

Abstract With the aim of investigating the solutions of ethane shortage in a commercial ethylene plant, addition of propane as supplementary feedstock and increasing steam to hydrocarbon ratio were proposed as possible strategies. These strategies were proposed to compensate for the ethane shortage in the thermal cracking unit of the commercial plant. Run length, ethylene yield, and propylene yield were considered as the determining factors to appraise the strategies. The major contribution of present work would be the investigation of effect of feed shift on the run length of the steam cracker. Regarding this, five different cases were investigated in real plant condition. To include all the aspects of process, a mathematical model with reasonable assumptions was developed and then validated against the real plant data. Based on the obtained results, increasing propane concentration leads to increase in propylene yield and decrease in ethylene yield. Besides, run length of process was obtained to be longer in the cases with higher propane content in the feed stream.

Enterprise-wide optimization in a petrochemical plant: a MILP approach to energy efficiency improvement

Public policy, dollar rate, market prices, contracts values and equipment efficiency influence the costs of the energy sources at an ethylene plant. The aim of this research is to identify energy efficiency opportunities at the energy management resources in a petrochemical industry. It was proved that using MILP makes it possible to achieve energy efficiency gains. MILP proved to be effective, accurate and robust. It confirmed the importance of modeling and simulation with quick response and its implementation in a higher possible rate, since the potential gains running the model once per day were 81% higher than performing it once a month. The optimal resources choice had an average annual potential saving of US$ 556.000/year.

Data-driven robust optimization under correlated uncertainty: A case study of production scheduling in ethylene plant

To hedge against the fluctuations generated from continuous production processes, practical solutions can be obtained through robust optimization induced by the classical uncertainty sets. However, uncertainties are sometimes correlated in industrial scheduling problems because of the connected process and various random factors. To capture and enrich the valid information of uncertainties, copulas are introduced to estimate the joint probability distribution and simulate mutual scenarios for uncertainties. Cutting planes are generated to remove unnecessary uncertain scenarios in the uncertainty sets, and then robust formulations induced by the cut set are proposed to reduce conservatism and improve the robustness of scheduling solutions. A real-world process of ethylene plant is introduced as the numerical case, and high-dimensional data-driven uncertainty sets are illustrated in detail. The proposed models are proved to control the fluctuation of consumed fuel gas below a lower level of conservatism.

Carbon dioxide and ethanol from sugarcane biorefinery as renewable feedstocks to environment-oriented integrated chemical plants.

The chemical industry share of environmental impacts derives predominantly from the use of non-renewable feedstocks and inefficient use of mass and energy, resulting in atmospheric emissions, especially carbon dioxide, which is the main cause of global warming and climate change and expressive generation of wastes. Rather than treating carbon dioxide as waste, it can be regarded as an alternative chemical feedstock for synthesis of fuels and chemicals. Using carbon dioxide as a renewable and environment-friendly source of carbon is one of the most attractive solutions to reduce our dependence on petrochemicals. This work evaluates the utilization of carbon dioxide as feedstock to the production of chemicals arranged in an industrial eco-pole to reduce environmental impacts of a sugarcane biorefinery. This environment-oriented chemical complex, the Eco-Pole, aims to increase the sustainability of the sugarcane bioethanol industry located nearby the complex using carbon dioxide produced in the sugarcane fermentation and bioethanol itself as feedstocks. The Eco-Pole benefits from the nearly pure carbon dioxide to produce chemicals traditionally derived from fossil raw materials, namely methanol, propylene, ethylene, ethylene oxide, propylene oxide, ethylene carbonate, propylene carbonate and dimethyl carbonate. Process simulation using Aspen HYSYS® is used to compute mass and energy balances to support the calculation of quantitative performance indexes (e.g., net carbon dioxide emissions, energy intensity and water intensity) to compare efficiency of individual process and arranged in the Eco-Pole. The propylene oxide plant shows best individual performance, while the worst performance occurs for the ethylene plant. A multi-criteria analysis ranking sustainability performance points to the dimethyl carbonate plant as the most sustainable and the propylene plant as the poorest performer. The Eco-Pole cash flow presents a deficient economic performance, but with a tendency to profitability. Nevertheless, Eco-Pole shows satisfactory performance regarding the raw material and energy consumption indexes. Moreover, the carbon dioxide emission per Eco-Pole products is relatively low.

Economic Evaluation of Mixed C4’sUpgrading Processes. (Raslanuf Ethylene Plant as a Case Study)

Reducing the operating cost (opex) is a method implemented by Ethylene producers to keep ethylene prices from expensive feedstock more competitive in comparison with cheaper feed stocks like ethane. Alternatively economics maybe improved by upgrading the mixed C4 stream which is produced from ethylene plant and contains valuable unsaturated C4s such as butadiene, isobutylene, butene-1, and butene-2. There are different processing options available to recover these components or turn them into final products. These processing options or routes are combination of different chemical processes such as Total hydrogenation, Butadiene extraction, MTBE production form butylenes, Butane-1 recovery and other processes. Several upgrading options have been proposed and evaluated for Raslanuf ethylene plant c4 feed of about 130000 tonne/y. Internal rate of return IRR , payback time or period PBP, and the net present value NPV, all have been estimated for options which can be implemented at the site; butadiene extraction and metathesis. Because base case results were not definitive, sensitivity analysis was performed. The parameters investigated are sales prices; feed cost, construction time and total investment. .The results suggest butadiene extraction is the best processing option for processing Raslanuf mixed C4 stream.

Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes

The complex chemical process is a high pollution and high energy consumption industrial process. Therefore, it is very important to analyze and evaluate the energy and environment efficiency of the complex chemical process. Data Envelopment Analysis (DEA) is used to evaluate the relative effectiveness of decision-making units (DMUs). However, the traditional DEA method usually cannot genuinely distinguish the effective and inefficient DMU due to its extreme or unreasonable weight distribution of input and output variables. Therefore, this paper proposes an energy and environment efficiency analysis method based on an improved environment DEA cross-model (DEACM) method. The inputs of the complex chemical process are divided into energy and non-energy inputs. Meanwhile, the outputs are divided into desirable and undesirable outputs. And then the energy and environment performance index (EEPI) based on the cross evaluation is used to represent the overall performance of each DMU. Moreover, the improvement direction of energy-saving and carbon emission reduction of each inefficiency DMU is quantitatively obtained based on the self-evaluation model of the improved environment DEACM. The results show that the improved environment DEACM method has a better effective discrimination than the original DEA method by analyzing the energy and environment efficiency of the ethylene production process in complex chemical processes, and it can obtain the potential of energy-saving and carbon emission reduction of ethylene plants, especially the improvement direction of inefficient DMUs to improve energy efficiency and reduce carbon emission.

Energy Efficiency Prediction Based on PCA-FRBF Model: A Case Study of Ethylene Industries

Energy conservation and emission reduction in the ethylene industry is the main way to attain sustainable development, which can be achieved if the energy efficiency of petrochemical industries can be accurately analyzed and predicted. This paper proposes an improved radial basis function neural network based on fuzzy ${C}$ -means (FCM) algorithm integrated with principal component analysis (PCA) technology (PCA-FRBF). The PCA is used to denoise and reduce dimensions of data to decrease the training time and errors of the modeling process. The FCM is used to separate every fuzzy class in input space and decide the number of neurons in hidden layer to overcome the shortcoming of setting them by experience subjectively. Meanwhile, the robustness and effectiveness of the PCA-FRBF model are validated through the standard data set from the University of California Irvine repository. Moreover, to predict the energy efficiency of ethylene plants, a multi-inputs and single-output model of energy efficiency is established based on the PCA-FRBF for monthly data of ethylene production process. We obtain a rational allocation of crude oil, fuel, steam, water, and electricity, and the greatest benefit of ethylene plants under different technologies. Finally, the empirical results show the effectiveness and practicability of the PCA-FRBF model applied to predict and guide the ethylene production in the petrochemical industry.

Energy efficiency improvement in an ethylene plant propylene refrigeration cycle (C3R)

A typical refrigeration cycle in an ethylene plant utilizes propene as fluid. When C3R is still in the warm zone, there is some process heat exchangers that leave it sub-cooled. This creates the opportunity for operational improvement in these systems which will result in less parasite steam formation on cycle expansion zone. The objective is analyze this energy efficiency improvement opportunity, showing the financial and energy earnings. The methodology applied to achieve this improvement in the energy efficiency of this cycle is based on: mass and energy balance calculation, design data comparison, and analysis of differences between the actual values and the design reference. An action plan was developed with necessary implementation steps and earnings calculations. The annual amount realized was around one million dollars in 2015. In terms of natural resources, this work is bringing an average reduction of 1.07 kg/s of steam, representing an amount of approximately 2.12 MW. This gain is about 2% of the turbine consumption. This framework can be applied at any Ethylene plant that has the similar equipments.

Optimal design of inter-plant hydrogen network with purification reuse/recycle

Hydrogen-rich gas from fertilizer plant and ethylene plant can be sent to refinery in a petrochemical complex, which can alleviate the deficit of hydrogen in refinery. Thus the optimization of inter-plant hydrogen network in a petrochemical complex is attractive. A novel superstructure for the optimal design of inter-plant hydrogen network with purification process is proposed and the corresponding mathematical programming models are presented for different scenarios. Two cases are utilized to illustrate the proposed approach. The flowrates of hydrogen utilities in refinery can be reduced via the inter-plant optimization. The number of inter-plant connections is optimized to simplify the network configuration. The shortcut model for pressure swing adsorption (PSA) considering the design conditions (pressure ratio and adsorbent selectivity) is also embedded into the mathematical programming model. The impacts of those design conditions of PSA on the performance of inter-plant hydrogen network are investigated. With the reduction of adsorbent selectivity and the increment of pressure ratio, the hydrogen recovery ratio will increase and the total annual cost will be reduced.