Simulation Of Chemical Processes Research Articles

Introducing an integrated chemical looping hydrogen production, inherent carbon capture and solid oxide fuel cell biomass fueled power plant process configuration

A novel integrated system is proposed which combines biomass gasification, chemical looping combustion, solid oxide fuel cell system and a steam power cycle. Sensitivity analysis is done for effective parameters to analyze the performance of the integrated system and investigation of the optimal operating condition. Because of some restrictions in the integrated system experiments, a chemical process simulator is used for analysis of the hybrid system. Products of this process are high-purity hydrogen and electrical power which are produced by chemical looping and solid oxide fuel cell (and a power cycle) respectively. The net efficiency of the system reaches to 55.8% with 100% carbon dioxide capture. Solid oxide fuel cell operates at 850°C and 12bar. Chemical looping system uses Calcium oxide metal oxide as oxygen carrier. Also carbonator, calcinator and hydrator reactors operating temperature are 800°C 850°C and 650°C respectively.

A chemical EOR benchmark study of different reservoir simulators

Interest in chemical EOR processes has intensified in recent years due to the advancements in chemical formulations and injection techniques. Injecting Polymer (P), surfactant/polymer (SP), and alkaline/surfactant/polymer (ASP) are techniques for improving sweep and displacement efficiencies with the aim of improving oil production in both secondary and tertiary floods. There has been great interest in chemical flooding recently for different challenging situations. These include high temperature reservoirs, formations with extreme salinity and hardness, naturally fractured carbonates, and sandstone reservoirs with heavy and viscous crude oils.More oil reservoirs are reaching maturity where secondary polymer floods and tertiary surfactant methods have become increasingly important. This significance has added to the industry's interest in using reservoir simulators as tools for reservoir evaluation and management to minimize costs and increase the process efficiency. Reservoir simulators with special features are needed to represent coupled chemical and physical processes present in chemical EOR processes. The simulators need to be first validated against well controlled lab and pilot scale experiments to reliably predict the full field implementations.The available data from laboratory scale include 1) phase behavior and rheological data; and 2) results of secondary and tertiary coreflood experiments for P, SP, and ASP floods under reservoir conditions, i.e. chemical retentions, pressure drop, and oil recovery. Data collected from corefloods are used as benchmark tests comparing numerical reservoir simulators with chemical EOR modeling capabilities such as STARS of CMG, ECLIPSE-100 of Schlumberger, REVEAL of Petroleum Experts. The research UTCHEM simulator from The University of Texas at Austin is also included since it has been the benchmark for chemical flooding simulation for over 25 years.The results of this benchmark comparison will be utilized to improve chemical design for field-scale studies using commercial simulators. The benchmark tests illustrate the potential of commercial simulators for chemical flooding projects and provide a comprehensive table of strengths and limitations of each simulator for a given chemical EOR process. Mechanistic simulations of chemical EOR processes will provide predictive capability and can aid in optimization of the field injection projects. The objective of this paper is not to compare the computational efficiency and solution algorithms; it only focuses on the process modeling comparison.

Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.

A sensitivity analysis and a comparison of two simulators performance for the process of natural gas sweetening

Chemical processes simulation is an important instrument for the design, optimization and control of industrial plants. Simulation cases can be accomplished with relatively low costs and the absence of risks for the operators. However, the precision of the results depends on the similarity between the simulation performed and the process considered. In this article, two simulators, Aspen Hysys V8.6 and Aspen Plus V8.6, are employed to simulate the process of natural gas sweetening using diethanolamine (DEA). Additionally, a parametric sensitivity analysis is performed to define the optimal operative range for the process. The required data and the conditions of the operating units are taken from a gas conditioning plant in northern Argentina. Finally, a comparison between the block of obtained results from both simulations is also detailed.

Near-optimal single-photon sources in the solid state

Single-photons are key elements of many future quantum technologies, be it for the realisation of large-scale quantum communication networks for quantum simulation of chemical and physical processes or for connecting quantum memories in a quantum computer. Scaling quantum technologies will thus require efficient, on-demand, sources of highly indistinguishable single-photons. Semiconductor quantum dots inserted in photonic structures are ultrabright single photon sources, but the photon indistinguishability is limited by charge noise induced by nearby surfaces. The current state of the art for indistinguishability are parametric down conversion single-photon sources, but they intrinsically generate multiphoton events and hence must be operated at very low brightness to maintain high single photon purity. To date, no technology has proven to be capable of providing a source that simultaneously generates near-unity indistinguishability and pure single photons with high brightness. Here, we report on such devices made of quantum dots in electrically controlled cavity structures. We demonstrate on-demand, bright and ultra-pure single photon generation. Application of an electrical bias on deterministically fabricated devices is shown to fully cancel charge noise effects. Under resonant excitation, an indistinguishability of $0.9956\pm0.0045$ is evidenced with a $g^{2}(0)=0.0028\pm0.0012$. The photon extraction of $65%$ and measured brightness of $0.154\pm0.015$ make this source $20$ times brighter than any source of equal quality. This new generation of sources open the way to a new level of complexity and scalability in optical quantum manipulation.

Modelling of an alternative process technology for biofuel production and assessment of its environmental impacts

It is easy to predict that in the coming years in Europe biodiesel will play an increasingly important role in the transport sector. The European Commission has set at 10% by 2020 the proportion that biofuels should represent in total fuel used in transport and biodiesel is currently the most widely used biofuel in the European Union. The most common way to produce biodiesel is through transesterification of vegetable oils with methanol; glycerol is the main co-product. Although glycerol has many industrial applications, increased production of biodiesel could make complete market placement of this chemical difficult. In this context, increasing interest is paid towards different methods of biodiesel production that provide alternative co-products. This article offers a “cradle to gate” evaluation of potential environmental impacts caused by an innovative process for the production of DMC-BioD, an alternative biofuel to biodiesel which does not involve the production of glycerol. Transesterification of soybean oil with dimethyl carbonate to obtain DMC-BioD has been modelled with the aid of the Chemical Process Simulation software Aspen HYSYS® that produced the material and energy balances and the preliminary sizing of the process units. Results have been also compared with background information from database on the production of conventional biodiesel from soybean oil and of fossil diesel. The study suggests that DMC-BioD can be an interesting route for the production of biofuels from an environmental point of view. Compared to fossil diesel, GHG (Greenhouse gases) emissions can be decreased, although trade-offs are registered in other environmental categories. In any case, future investigation is needed in order to understand and optimize its environmental profile through the entire life cycle and possibly bring its production to a commercial scale. This preliminary analysis of potential environmental impacts provides useful information to continue the testing and scale-up phases and to improve the environmental performances of the process.

Novel mixed fluid cascade natural gas liquefaction process configuration using absorption refrigeration system

In this study, a novel process configuration for large scale natural gas liquefaction process is introduced and analyzed. This configuration is based on replacement of vapor compression refrigeration cycle by absorption refrigeration system. The required heat duty in the absorption refrigeration system is obtained by available waste heat in the plant. Process simulation is done by Aspen HYSYS software which is a conventional chemical process simulator. Coefficient of performance of the ammonia- water cycle is 0.48. Specific power consumption of the introduced process is 0.172 kWh/kgLNG which shows 30% reduction in the power consumption. The required heat transfer area of the modified process can be decreased up to 31%.

Evaluación del proceso de producción de detergente en polvo a partir de la simulación

In Cuba, powder detergent production is carried out by a single factory. This work research was intended to evaluate the powder detergent production process from a simulation process. For this purpose, the HYSYS v. 3.2 chemical process simulator was employed and definition of properties of hypothetical components that are nor part of the pure components database was required. Results of the basic case showed inefficiencies of the process operation, the most important being during the neutralization stage and the drying gas heating stage. Results of Study Case 2 show that it is possible to reduce pH of the neutral paste to 15.34% when compared to the basic case, for a production of 848 kg neutral paste per hour, without affecting the percentage of the active ingredient. Additionally, a decreased consumption of liquefied gas of 1,500 L/d implies increased profit in the amount of $ 227,301 per year, compared to the basic case.

Разработка системы глубокой сероочистки синтез-газов

Experiments with thermogravimetrical analyzer determined kinetic characteristics of clean zinc oxide (GOST 10262–73) and dynamic characteristics of Katalco 32-4 Johnson Matthey sorbent. Obtained data enable calculation of the sorbent volume required for a complete synthesis gas desulfurization, duration of sorbent working cycle, sorbent conversion rate and general kinetic characteristics of hydrogen sulfide absorption by zinc oxide. Chemical process simulation considering transient multiphase hydrodynamics resulted in the conversion rate of ZnO2SC oxide zinc with different isotherms and parameters of process involving pure zinc oxide and Katalco sorbent within 250 – 950 °C temperatures range.

A Test Environment to Evaluate the Integration of Operators in Nonlinear Model-Predictive Control of Chemical Processes

Abstract: In industrial process control, basic controllers such as linear PI(D) control and cascade controllers are widely accepted by the plant operators because they are easy to understand due to their clear cause-and-effect relation. When the control and performance objectives cannot be met by simple controllers and manual interventions, advanced process control (APC) solutions, usually MPC controllers are employed. The design of APC solutions requires a considerable understanding of the process and more mathematical background—but also during the operational phase (e.g. error diagnosis). Then the issue of the trust of the operators into such complex control solutions and in their ability to monitor their behavior during plant operation arises. It may happen that APC solutions are not accepted or are fully or partly switched off by the operators after a while, which means a wasted effort and lost opportunities for better plant performance. By providing carefully chosen information about the behavior of the controller and well-designed operator interfaces, the trust of the operators and their ability to monitor advanced controllers can be increased. In this contribution we present an environment to investigate trust in automation experimentally and to explore new opportunities for the user-interaction with APC methods. The test environment consists of a chemical process simulator which is controlled online by a NMPC scheme, an interface editor for the fast development of interface concepts as well as a control room simulation in order to evaluate the synergetic cooperation between the operator and the algorithmic control schemes.

CFD modeling of homogenizer valve: A comparative study

Designing an efficient homogenizer valve requires an in-depth understanding of the flow structure in the valve region. Therefore, the choice of an appropriate strategy in the numerical simulation of homogenization and chemical process plays a significant role and determines the accuracy of results which returns an improved design criterion. The performance of two computational fluid dynamics (CFD) strategies in the simulation of a homogenizer valve is assessed in this study; namely, the large eddy simulation (LES) and hybrid LES-RANS methods. For LES calculations, two sub-grid scale (SGS) models are considered: (a) RAST one-equation model (OEM) (b) dynamic Smagorinsky model (DSM) while the SST-SAS and delayed detached eddy simulation (DDES) methods are the variants of a hybrid-type RANS-LES approach. The predictions of these models are compared with the experimental data available in the literature. The comparisons show that an LES can reproduce accurate information in terms of main parameters such as the mean velocity and turbulent kinetic energy that are important in designing the homogenization process. However, the SST-SAS predictions are not as accurate as the DDES and LES ones, especially downstream of the gap in reproducing the mean velocity and turbulent fluctuations.

Design and Implementation of Optimized Fuzzy Logic Controller for a Nonlinear Dynamic Industrial Plant Using Hysys and Matlab Simulation Packages

A fuzzy logic controller (FLC) is appropriate for systems with high complexity and nonlinearity. FLC is implemented directly on a chemical process simulator in dynamic mode to handle some uncertainty of the system. Also because accurate tuning of the fuzzy membership functions (MFs) is difficult and has an important effect on FLC performance, particle swarm optimization (PSO) is utilized. To display capability of this method, FLC is optimized with PSO. Next PSO-FLC is used to control pressure of a distillation column in an ethane plus recovery process in dynamic mode. Results show that the proposed method can use PSO-FLC in the Hysys dynamic efficiently.

Dielectric Constants for Quantum Chemistry and Li-Ion Batteries: Solvent Blends of Ethylene Carbonate and Ethyl Methyl Carbonate

This work reports measurements of the dielectric constants of ethylene carbonate (EC)/ethyl methyl carbonate (EMC) blends between 25 and 60 °C. Dielectric constants were measured using a cylindrical capacitance cell and a frequency response analyzer. EC and EMC form nonideal mixtures that cannot be described by a simple linear mixing model. A quadratic mixing rule was instead adopted, and the mixing parameter is reported for 25–60 °C. The results of this research may be used to calculate the dielectric constant of any EC/EMC mixture over this temperature range with ≤4% estimated error. By modeling the ionic dissociation of lithium hexafluorophosphate (LiPF6) in various solvents, the significance of the dielectric constant on quantum chemistry simulations of chemical processes is explored. The effect of the dielectric constant accuracy on electrochemical processes was similarly evaluated by calculating the solvation energy of neutral and singly oxidized vinylene carbonate in various solvents. It is demonst...

Numerical Simulation of Physical and Chemical Processes in Fluidized Bed

The paper presents a numerical simulation of the furnace with a circulating fluidized bed. Numerical study carried out for the bottom of the combustion chamber with the varying heights of volume filling. The results contours of particulate matter concentration and of velocities, as well as a graphical representation of changes in the concentration of particles on the bed height are shown. Simulation performed in Eulerian - Eulerian representation on a 2D model.

Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods.

We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation double- and single-ended transition-state optimization algorithms--the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several single-molecule systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes.

Efficiency Analysis of Gas Turbine Combined-Cycle Fed with Synthetic Natural Gas (SNG) and Mixture of Syngas and SNG

The effect of synthetic natural gas (SNG) and mixture of syngas and SNG fed to Natural Gas Combined-Cycle (NGCC) plants is presented in this study via a system-level simulation model. The commercial chemical process simulator, Pro/II® V8.1.1, was used in the study to build the analysis model. The NGCC plant consists of gas turbine (GT), heat recovery steam generator (HRSG) and steam turbine (ST). The study envisages two analyses as the basic and feasibility cases. The former is the benchmark case which is verified by the reference data with the GE 7FB gas turbine. According to vendor’s specification, the typical net plant efficiency of GE 7FB NGCC with two gas turbines to one steam turbine is 57.5% (LHV), and the efficiency is the benchmark in the simulation model built in the study. The latter introduces a feasibility study with actual parameters in Taiwan. The SNG-fed GE 7FB based combined-cycle is evaluated, and the mixture of SNG and syngas is also evaluated to compare the difference of overall performance between the two cases. The maximum ratio of syngas to SNG is 0.14 due to the constraint for keeping the composition of methane at a value of 80 mol%, to meet the minimum requirement of NG in Taiwan. The results show that the efficiency in either case of SNG or mixture of SNG and syngas is slightly lower than the counterpart in the benchmark one. Because the price of natural gas is much higher than that of coal, it results in higher idle capacity of NGCC. The advantage of adopting SNG in Taiwan is that it could increase the capacity factor of combined-cycles in Taiwan. The study shows a possible way to use coal and reduce the CO2 emission, since coal provides nearly half of the electricity generation in Taiwan in recent years.

Potential assessment on gas turbine combined cycle with alternative gaseous fuel from coal gasification

In the 21st century, fossil fuels will remain the mainstay of energy production, while natural gas combined cycle (NGCC) features environmental benignity and high efficiency. Hence, it is desirable to assess the potential of NGCC for power generation, in which gas turbine (GT) is operated with alternative gaseous fuel from coal gasification, since coal is the most abundant fossil fuel. System-level analyses for NGCC plants, combining advanced GTs with various fuels, are performed in this study. The commercial chemical process simulator, Pro/II® V8.1.1, is implemented to build the simulation models. This work further performs various analyses as the basic and feasibility cases. The former is the benchmark case verified with the reference data of an operating NGCC power plant located in northern Taiwan. The latter introduces a feasibility study with advanced GTs and actual parameters in Taiwan. Alternative fuel, including synthetic natural gas (SNG) or a mixture of SNG and syngas, is fed to combined cycle for evaluating the overall performance. The results indicate that the system output or efficiency in either case is slightly (2–3 % points, LHV) lower than the counterpart in the benchmark one. In Taiwan, the natural gas price is much higher than that of coal, and results in higher idle capacity of NGCC. The advantage of adopting SNG to NGCC is that it could increase the capacity factor and subdue the environmental impact of the energy portfolio. The outcome of this study indicates a possible means to utilize coal more efficiently and reduce emissions.

Modelling the properties of liquid foods for use of process flowsheeting simulators: Application to milk concentration

In this paper, a modelling approach for liquid food products in a chemical process simulator is proposed from the flowsheeting methodology widely used for chemical processes. The focus is set on dairy concentration processes, in which milk is defined as a mixture of water and four dry matter components (fat, proteins, carbohydrates, minerals) modelled as “pseudo-components” in a conventional simulator which has been adapted to take into account the behaviour of the liquid food product considered. The significant properties of milk (heat capacity, boiling point elevation, thermal conductivity, density, viscosity, surface tension) are modelled with empirical models found in the literature and implemented in the simulator. In order to validate the approach, an industrial milk evaporation process and a pilot-scale evaporator are modelled and simulated. The results are compared with industrial and experimental results respectively, and show a good agreement with the industrial process. However improvements are needed in modelling the pilot scale evaporator. The proposed approach is generic enough to be extended to other liquid foods.

Numerical Simulation of Rheological, Chemical and Hydromechanical Processes of Thrombolysis

Mathematical model of clot lysis in blood vessels is developed on the basis of equations of convection-diffusion. Fibrin of the clot is considered stationary solid phase, and plasminogen, plasmin and plasminogen-activators – as dissolved fluid phases. As a result of numerical solution of the model predictions of lysis process are gained. Important influence of clot swelling on the process of lysis is revealed.

Gravitational Search, Monkey, and Krill Herd Swarm Algorithms for Phase Stability, Phase Equilibrium, and Chemical Equilibrium Problems

Phase equilibrium calculations (PECs) and phase stability (PS) analysis of reactive and nonreactive systems problems are important for the simulation and design of chemical engineering processes. These problems, which are challenging, multi-variable, and non-convex, require optimization techniques that are both efficient and effective in finding the solution. Stochastic global optimization algorithms, especially swarm algorithms, are promising tools for such problems. In this study, monkey algorithm (MA), gravitational search algorithm (GSA), and Krill Herd algorithm (KHA) were used to solve PS, phase equilibrium, and chemical equilibrium problems. We have also studied the effect of adding a local optimizer at the end of the stochastic optimizer run. The results were compared to determine the strengths and weaknesses of each algorithm. When a local optimizer was used, MA was found to be a reliable algorithm in solving the problems. GSA had relatively the least numerical effort for all problems among the three algorithms but with low reliability. KHA was more reliable than other two algorithms without the use of a local optimizer. The performance of GSA, MA, and KHA was compared with firefly algorithm and cuckoo search (CS). In summary, this study found that CS algorithm was more reliable than the newly tested algorithms. Nevertheless, MA and GSA algorithms, when combined with a local optimizer, solve the thermodynamic problems as reliably and efficiently as CS.