Prediction the individual component distillation curves of the blended feed using a hybrid GDM-PcLE method

A comprehensive knowledge of the properties and characterisations of the individual component in the blended feed is primary importance because different feedstock blending yields different products palate. Crude oil / condensate distillation unit optimization is an uphill task because unavailability of cheaper and reliable on line feed and product analyzers. Furthermore, laboratory analysis for feedstock characterization is very costly and time consuming. Alternatively, feed synthesis technique is used to reconcile the entire range of feed distillation curves by back blending the product streams from the actual column operation. The TBP and SG correlation are widely been used to estimate other bulk properties because they give the most accurate results. Due to highly nonlinear behaviour, methods like linear regression, non linear regression and rigorous models are adopted to predict TBP and SG distillation curves. The latter could give better accuracy results, but it is more complex, lengthy and costly to be implemented. In addition, the rigorous model commercially available such as PetrosimTM and Hysis 3.1TM are only being used to predict blended feed distillation curves, not for the individual component. Thus, a hybrid approach is proposed to overcome the deficiency of current methods and practices. The proposed method integrates the most versatile General Distribution Model (GDM) with a Pseudo-component Linear Equation (PcLE) method to predict the entire range individual component TBP and SG distillation curves of the blended feed from the readily available plant data, which are routinely taken by refiners. The predicted results given by hybrid GDM-PcLE model are almost agreeable with the lab results. A case study using the proposed short cut feed synthesis procedure and hybrid GDM-PcLE model showed additional 5% Naphtha yield can be achieved by changing the current feed blending ratio and product cut points. The accuracy of the predicting results can be improved if the distillates samples are to be carried out simultaneously and the flow meters are calibrated and corrected the measurements to density and temperature of the measuring devices. Since PcLE method is simple and open application, it can be easily integrated with iCONTM to enhance its application predicting the pure component TBP and other distillation curves from blended feed

PSecurity Specification Language for Distributed Health Information System (DiHIS)

The introduction of policy based management which to manage distributed, complex and numerous systems is widely accepted and used in various sectors. The policy creators create policies that suit best for their operations and management. Since there are numerous of policies, this research focuses on the security policies only which are appointed to the distributed system of health information system. In order to implement the security policies, we need a language that can represent the security policies for distributed health information system completely. From the literature review conducted, there are numerous of security languages have been introduced since two decades ago. Those languages carry their own approaches representing the security policy and some of them do not support the characteristics of distributed system. There is no security language to implement the security policy for distributed health information system. This thesis introduces and initiates a security language to implement security policies in distributed health information system called DiHIS. Adding to that, there are three existing security languages used for discussion and comparison with the proposed DiHIS security language. They are ASL, LaSCO and Ponder. DiHIS security language has shown that it is able to represent the Security Policy Model for Clinical Information System completely compares to those three security languages. This language also has an added value when it covers the Need To Know Policy which other security languages do not. Need To Know Policy is one of the crucial issues in the health sector. DiHIS security language has also been tested with the application domain in health information system. The strength of the language can be seen with the ability of DiHIS to represent the security policies in various connections between various organizations involved in distributed health information system

Computer model for refinery operations with emphasis on jet fuel production. Volume 2: Data and technical bases

The FORTRAN computing program predicts the flow streams and material, energy, and economic balances of a typical petroleum refinery, with particular emphasis on production of aviation turbine fuel of varying end point and hydrogen content specifications. The program has provision for shale oil and coal oil in addition to petroleum crudes. A case study feature permits dependent cases to be run for parametric or optimization studies by input of only the variables which are changed from the base case. The report has sufficient detail for the information of most readers

Process design Optimisation, heat integration, and techno-economic analysis of oil refinery: A case study

This paper outlines a comprehensive analysis of the optimal design and simulation of a crude oil distillation system within a refinery process, including pre-treatment and blending of two crude oils to increase the refinery’s annual profit. This distillation process is currently in operation, and the desired amount of feedstock is obtained from Iraqi Basra light-2015 and Kirkuk-2011 crude oil. To improve the energy efficiency of the utilization rate of crude oil, an atmospheric distillation process unit in this refinery with a capacity of 150,000 barrels per day (bpd) is considered. Aspen HYSYS simulation is used to optimize the distillation unit configuration and its operating performance. This paper also deals with three scenarios by comparing the feedstock compositions to the distillation process and the produced product compositions to minimize utility consumption. A heat integration approach was applied to the 3rd scenario by recycling hot outlet streams to the heat exchangers to increase the temperature of the inlet stream of the distillation column. Results indicated that about £2.29 million per year (Mpy) could be saved from the heat integration systems. Economic analysis and cut yields were carried out for each scenario to investigate the cost-effective and economically viable. Based on the economic analysis, scenario three showed better performance with a comparatively high cumulative cash flow of £31,886 M

Petroleum refinery scheduling with consideration for uncertainty

Scheduling refinery operation promises a big cut in logistics cost, maximizes efficiency, organizes allocation of material and resources, and ensures that production meets targets set by planning team. Obtaining accurate and reliable schedules for execution in refinery plants under different scenarios has been a serious challenge. This research was undertaken with the aim to develop robust methodologies and solution procedures to address refinery scheduling problems with uncertainties in process parameters. The research goal was achieved by first developing a methodology for short-term crude oil unloading and transfer, as an extension to a scheduling model reported by Lee et al. (1996). The extended model considers real life technical issues not captured in the original model and has shown to be more reliable through case studies. Uncertainties due to disruptive events and low inventory at the end of scheduling horizon were addressed. With the extended model, crude oil scheduling problem was formulated under receding horizon control framework to address demand uncertainty. This work proposed a strategy called fixed end horizon whose efficiency in terms of performance was investigated and found out to be better in comparison with an existing approach. In the main refinery production area, a novel scheduling model was developed. A large scale refinery problem was used as a case study to test the model with scheduling horizon discretized into a number of time periods of variable length. An equivalent formulation with equal interval lengths was also presented and compared with the variable length formulation. The results obtained clearly show the advantage of using variable timing. A methodology under self-optimizing control (SOC) framework was then developed to address uncertainty in problems involving mixed integer formulation. Through case study and scenarios, the approach has proven to be efficient in dealing with uncertainty in crude oil composition

Advanced and novel modeling techniques for simulation, optimization and monitoring chemical engineering tasks with refinery and petrochemical unit applications

Engineers predict, optimize, and monitor processes to improve safety and profitability. Models automate these tasks and determine precise solutions. This research studies and applies advanced and novel modeling techniques to automate and aid engineering decision-making. Advancements in computational ability have improved modeling software’s ability to mimic industrial problems. Simulations are increasingly used to explore new operating regimes and design new processes. In this work, we present a methodology for creating structured mathematical models, useful tips to simplify models, and a novel repair method to improve convergence by populating quality initial conditions for the simulation’s solver. A crude oil refinery application is presented including simulation, simplification tips, and the repair strategy implementation. A crude oil scheduling problem is also presented which can be integrated with production unit models. Recently, stochastic global optimization (SGO) has shown to have success of finding global optima to complex nonlinear processes. When performing SGO on simulations, model convergence can become an issue. The computational load can be decreased by 1) simplifying the model and 2) finding a synergy between the model solver repair strategy and optimization routine by using the initial conditions formulated as points to perturb the neighborhood being searched. Here, a simplifying technique to merging the crude oil scheduling problem and the vertically integrated online refinery production optimization is demonstrated. To optimize the refinery production a stochastic global optimization technique is employed. Process monitoring has been vastly enhanced through a data-driven modeling technique Principle Component Analysis. As opposed to first-principle models, which make assumptions about the structure of the model describing the process, data-driven techniques make no assumptions about the underlying relationships. Data-driven techniques search for a projection that displays data into a space easier to analyze. Feature extraction techniques, commonly dimensionality reduction techniques, have been explored fervidly to better capture nonlinear relationships. These techniques can extend data-driven modeling’s process-monitoring use to nonlinear processes. Here, we employ a novel nonlinear process-monitoring scheme, which utilizes Self-Organizing Maps. The novel techniques and implementation methodology are applied and implemented to a publically studied Tennessee Eastman Process and an industrial polymerization unit

Computer model for refinery operations with emphasis on jet fuel production. Volume 3: Detailed systems and programming documentation

The FORTRAN computing program predicts flow streams and material, energy, and economic balances of a typical petroleum refinery, with particular emphasis on production of aviation turbine fuels of varying end point and hydrogen content specifications. The program has a provision for shale oil and coal oil in addition to petroleum crudes. A case study feature permits dependent cases to be run for parametric or optimization studies by input of only the variables which are changed from the base case

Use of refinery computer model to predict fuel production

Several factors (crudes, refinery operation and specifications) that affect yields and properties of broad specification jet fuel were parameterized using the refinery simulation model which can simulate different types of refineries were used to make the calculations. Results obtained from the program are used to correlate yield as a function of final boiling point, hydrogen content and freezing point for jet fuels produced in two refinery configurations, each one processing a different crude mix. Refinery performances are also compared in terms of energy consumption

Optimization in Eugenol Production from Clove Oil with Saponification – Neutralization Process by using Response Surface Methods

The objective of this research was to obtain optimum condition in eugenol production from clove oil with response surface methods. Clove oil was founded from essential oil cluster in Batang district Central Java. The eugenol was produced with saponification and neutralization process. Eugenol was obtained with vacuum distillation. Eugenol concentration was analyzed with gas chromatography. In this research, the variable was studied are temperature and ratio of sodium hydroxide to clove oil and yield of eugenol as response variable. So the results was obtain in minimum condition with yield of eugenol 39.17% at X 1 = -0,0109 and X 2 = 0.3095 with determinant coefficient 0.764

Improving refinery productivity through better utilization of crude oil blending using linear programming.

Refinery Linear Programming (LP) Models and other mathematical techniques for optimization have evolved over many years to create solutions for complex crude oil blending problems. The objective of this case study was to develop a mathematical single period programming model to simulate blending problems to ensure the greatest possible revenue is generated. The yield of products at a refinery, given stringent environmental regulations on product qualities, the reducing availability of quality light, sweet, feedstock make refinery optimization a significant exercise to perform in order to stay in business. In this work a representation of a case study refinery model was presented, in which the overall gross profit margin, density, and sulphur content of the products were calculated, and evaluated to ensure they fall within the market specification and demand. The model is also able to predict operating variables like the cut-point temperatures in the Crude Distillation Unit which will result in the best outcome for the given scenario. The model formulation is illustrated, scenario based evaluations performed, and results discussed