Design Of Chemical Plants Research Articles

Thermodynamic properties of binary, ternary and quaternary mixtures: N‑butyl acetate- n-hexanol - n,n-dimethylacetamide-water. Modeling using regression algorithms and optimization using socially-inspired evolutionary algorithms

BackgroundThe design of chemical plants requires knowledge of the thermodynamic properties of the fluids involved. MethodsIn our research, we performed experimental measurements of the refractive index and density of binary, ternary and quaternary systems containing n‑butyl acetate, n-hexanol, n,n-dimethylacetamide and water, at atmospheric pressure and the following temperatures: 293.15 K, 303.15 K, 313.15 K and 323.15 K. They were used to determine the excess molar volume, which was correlated with mole fractions, normalized temperature and refractive index, using artificial neural networks and other models obtained with regression algorithms, optimized with different socially-inspired evolutionary algorithms. Significant FindingsThe best results were achieved with decision tree regression and the queuing search optimization algorithm. The present approach is based on the fact that there are few similar studies in the literature; in addition, the models obtained can complement/supplement the experimental data through predictions.

Optimisation of Irrigation and Fertigation Processes through Automated Control Systems: A Case of Maziwa Farm’s Low-yielding Boreholes in Murewa, Zimbabwe

The aim of this research was to design an automated irrigation and fertigation system in low yielding boreholes at Maziwa farm, Murewa, Mashonaland East Province of Zimbabwe. The study focused on designing an automated controlsystem of irrigation and fertigation using the PIC18F4550 microcontroller. The work entailed the designing of a fertilizer and herbicide chemical plant and the simulation of the developed control system. An irrigation and fertigation control system program was developed using Mikro C Pro software and simulated using Proteus software. Key considerations in the fertiliser and herbicide chemical plant design included a drip irrigation system for optimised water, fertiliser, and herbicide distribution, featuring chemical tanks and solenoid valves for controlled injection. Emitters, laterals and the mainline pipes, a medium for the irrigation water and fertilizer or herbicides to the plants were also selected. The automated irrigation system employs a microcontroller that utilizes Global System for Mobile Communication (GSM) technology in facilitating operator communication. The system status updates were sent to the user via SMS (Short Message Service) with connection between the user and the system being possible also through text messages for action confirmation. The results of the research were validated using simulation with proteus software.

Process & occupational safety integrated inherently safer chemical plant design: Framework development and validation

Chemical plants encompass diverse chemical and non-chemical hazards that can potentially lead to accidents. Consequently, it is imperative to implement appropriate risk management strategies to effectively reduce these hazards. Inherent safety, with its emphasis on eliminating hazards at source, has resulted in notable success in generating safer process routes. Conventional inherent safety methodologies are limited to optimizing process designs by reducing chemical and process hazards; however, occupational safety hazards (e.g., burns, electrocutions, drowning, and vehicle incidents) associated with ancillary services and working environments are not commonly scrutinized in the inherent safety framework. To this end, this work developed a dedicated tool called Safety Metric for Plant Design (SMPD), integrating occupational safety and process safety aspects, to generate a holistic safer chemical plant via inherent safety oriented modifications. Firstly, the index framework was constructed based on the safety consideration of chemical and process, ancillary services, and working environments. Then, the index framework was integrated with the Fuzzy Risk Rating (FRR), Precedence Chart (PC), and Bayesian Network (BN) to develop SMPD, and the Systematic Risk Reduction Framework (SRRF) was proposed to implement the inherent safety oriented design. Lastly, the SMPD was demonstrated using the case study of a methanol plant. The results revealed that the overall safety level increased from 2.7 to 3.39 after SRRF-based design modifications, implying that the revised chemical plant design is inherently safer than the base design. The proposed SMPD addresses both process hazards and occupational hazards by inherently safer approaches. This work provides a new perspective for designers to shift from inherently safer process design to plant design, aiming to establish a safety design framework for chemical plants oriented towards inherent safety.

Editorial Overview of the Special Issue “Innovation in Chemical Plant Design”

Innovation in chemical plant design stands at the forefront of transformative advancements in the dynamic field of chemical engineering [...]

Multi-objective optimization of chemical process plant layout considering economy and inherent safety

Economy and safety are important factors for the layout design of chemical process plants. However, safety factors are often translated into economic indicators as a part of the objective function for layout optimization in previous studies. This may result in safety performance of chemical process plants does not meet the actual production requirements. In this paper, a multi-objective optimization method for chemical process plant layout is proposed to obtain series of solutions that can achieve the trade-off between economy and safety. The economic objective function is characterized by the total capital cost, including land cost, pipe cost, protection device cost and expected property loss from accidents. The safety objective function involves inherent safety which is evaluated by the Comprehensive Inherent Safety Index (CISI). The proposed multi-objective optimization model solved by non-dominated sorting genetic algorithm II (NSGA-II) is applied for layout optimization of an acrylic acid production plant. The results show a strong trade-off between competing economic and safety objectives according to the Pareto curve. The optimal solution ranges from 236,099 $ to 379,622 $ for total cost, corresponding to 87.7–132 for CISI. Safety will be improved significantly in the low-safety layout scheme when the capital investment increases slightly.

Design and Development of an Open-Source Virtual Reality Chemical Processing Plant

It is challenging to provide students studying in chemical engineering, biotechnology and other related fields with an opportunity to tour and interact with a full-scale chemical processing plant. To address this challenge, an open-sourced virtual reality (VR) chemical processing plant was designed and built to provide students with an experiential learning opportunity. The VR plant is modelled after an ampicillin processing facility complete with a piping and instrumentation diagram (P&ID). The initial student experience inside the VR plant is a tour of the plant, various plant features and unit operations. The tour enables students to freely tour the plant but also engages them in a “Quest” style experience where they need to search for specific areas and components within the plant. An EngPad was designed to provide learners with a help tool to assist their navigation and strengthen their understanding during the VR experience. Experiential learning theory was used to guide the design of the VR application and take students through the four learning modes of concrete experience, reflective observation, abstract conceptualization, and active experimentation. A focus group provided feedback on the design and user interaction of the VR experience. This paper will outline how design features and enhancements were selected based on their connection to experiential learning theory.

Adaptive Control for Narrow Bandwidth Input and Output Disturbance Rejection for a Non-Isothermal CSTR System

This paper presents an adaptive control scheme to face the challenge of rejecting input and output disturbances. The research is put on a layer of the design and start-up of chemical plants. The emphasis is on handling disturbances appearing in a narrow band of frequencies, which illustrates standard forms of disturbances in the alluded kind of systems. The controller is made up of a central RS structure that stabilizes the closed-loop plant. A second layer boosts the control law performance by adding the Youla–Kucera (YK) filter or Q parametrization and taking advantage of the internal model principle (IMP). This practice aids in modeling unknown disturbances with online control adjustment. We probe the resultant compensator for three non-isothermal continuous stirred tank reactors connected in series. The plant should conduct a first-order exothermic reaction consuming reactant A, while an isothermal operation stays and the outlet concentration is close to its nominal value. The primary concerns are open-loop instability and steady-state multiplicity in the plant’s first unit. The control objective is to reject input and output disturbances in a band of frequencies of 0.0002Hz to 0.007Hz, whether there are variants or not in time. We test the controller with input signals depicting both variations in the auxiliary services and abrupt changes. We then compare the executions of the resultant control law with a model-based predictive control (MPC). We find comparable responses to multiple disturbances. However, the adaptive control offers an effortless control input. We also conclude that the adaptive controller responds well to reference changes, while the MPC fails due to input constraints.

Surrogate-assisted evolutionary multi-objective optimisation applied to a pressure swing adsorption system

The complexity of chemical plant systems (CPS) makes optimising their design and operation challenging tasks. This complexity also results in analytical and numerical simulation models of these systems having high computational costs. Research demonstrates the benefits of using machine learning models as surrogates or substitutes for these computationally expensive simulation models during CPS optimisation. This paper presents the results of our study, extending recent research into optimising chemical plant design and operation. The study explored the original surrogate-assisted genetic algorithms (SA-GA) in more complex variants of the plant design and operation optimisation problem. The more complex plant design variants include additional parallel and feedback components. The study also proposes a novel multivariate extension, surrogate-assisted NSGA (SA-NSGA), to the original univariate SA-GA algorithm. The study evaluated the SA-NSGA extension on the popular pressure swing adsorption (PSA) system. This paper outlines our extensive experimentation, comparing various meta-heuristic optimisation techniques and numerous machine learning models as surrogates. The results in both more complex plant design variants and the PSA case show the suitability of genetic algorithms combined with surrogate models as an optimisation framework for CPS design and operation in single and multi-objective scenarios. The analysis further confirms that combining a genetic algorithm framework with machine learning surrogate models as a substitute for long-running simulation models yields significant computational efficiency improvements, 1.7–1.84 times speedup for the increased complexity examples and a 2.7 times speedup for the pressure swing adsorption system. The discussion successfully concludes that surrogate-assisted evolutionary algorithms can be scaled to increasingly complex CPS with parallel and feedback components.

Multi-objective optimisation for safe multi-floor process plant layout using the Dow’s Fire & Explosion Index

In this work, we propose a multi-objective mixed-integer linear programming (MILP) model for evaluation of safe multi-floor process plant layout using the Dow’s Fire & Explosion Index (F&EI). Two objectives are considered, namely the total monetary cost and the financial risk, and solved via the ε-constraint method. The total monetary cost consisted of the piping costs, horizontal and vertical pumping costs, land purchase cost, fixed and area-dependent floor construction cost, and the cost of protection devices. The financial risk was evaluated as the maximum probable property damage cost obtained using the F&EI evaluation procedure. The proposed model was applied to an ethylene oxide plant consisting of 7 equipment items with Pareto-optimal solutions showing that the financial risk can be greatly reduced by layout reconfiguration without the need for protection devices and their associated monetary costs. Further increase in the safety levels of the plant can then be achieved through protection device installation at a cost. These, and more information obtained, which are non-existent in previous single objective considerations, are helpful for a more informed decision making process in the planning stages of the design of chemical process plants.

Single‐phase fluid mass transfer in petroleum processing and petrochemical technology: Theory and application

AbstractThe application of single‐phase fluid mass transfer theory in petrochemical industry, particularly in chemical plants and operating processes, has attracted wide attention for decades. In this review, the single‐phase fluid mass transfer theory, including molecular diffusion and convective diffusion, and its application in petroleum refining and chemical industry are systematically summarized. Both experimental studies and theoretical calculations, based on numerical and analytical methods, are exactly introduced. Their applications in porous media of fixed bed, fluidized bed and pebble bed, structured packed tower, rotary disc contactor, chemical reactors, and corrosion are discussed in detail. The existing technology and knowledge can provide potential approaches to optimize design and modification of chemical plants and further study on related theories of fluid mass transfer.

Pre-design of Biphenyl Chemical Factory from Benzene with Capacity of 10.000 Ton Per Year

The design of a biphenyl chemical plant from benzene with a capacity of 10,000 tons/year will be built in Tuban, East Java with a land area of ​​10,010 m2. The raw material in the form of Benzene is obtained from Trans-Pacific Petrochemical Indotama (TPPI), Tuban. The factory is designed to operate continuously for 330 days, 24 hours per day, and requires 214 employees. Biphenyl preparation begins with reacting benzene (2,807.74 kg/hour) in a Pipe Flow Reactor (R-01) at a reactor temperature of 377 oC and a pressure of 2 atm. This reaction takes place with a conversion of 90% and is endothermic so that a Hitech heater is used to maintain the operating temperature. The products that come out of the reactor are biphenyl and hydrogen. It is then cooled and condensed in a Partial Condenser (CD-01) to a temperature of 151 oC. Then enter into Separator-02 (SP-02) to separate hydrogen from a mixture of benzene, toluene and biphenyl. Hydrogen in the gas phase as a result of the separtor. The bottom product in the form of benzene, toluene and biphenyl in the liquid phase is pumped and put into a distillation tower (MD-01) to purify the product with the bottom product in the form of biphenyl with a purity of 99.3%. The result of the distillation tower is benzene and its impurities are recycled as feed into the reactor with a temperature of 83 oC and a pressure of 1 atm. This factory requires Fixed Capital (FC) Rp. 34,341,856,338,- + US$ 4,195,836, Working Capital (WC) (Rp. 127,536,505,173,- + US$ 170,019), Manufacturing Cost (MC) (Rp. 254,092,040,390,- + US$ 816,090), and General Expenses (GE) (Rp. 33,990,417,539,- + US$ 81,609). Economic analysis shows the value of ROI before tax is 50.38 % and the value of ROI after tax is 32.75%. POT before tax is 1.65 years and POT after tax is 2.34 years. The BEP value is 43.11% and the SDP value is 23.75%. The interest rate in DCF for 10 years is 19% on average. Thus, from a technical and economic point of view, a biphenyl plant from benzene with a capacity of 10,000 tons/year is worthy of consideration.

Specialty chemicals production case study: Economic analysis of modular chemical process intensification versus conventional stick‐built approaches

AbstractThe beneficial synergies of chemical process intensification and plant modularization present a unique step‐wise advancement opportunity for many chemical manufacturers, but economic case studies are needed to raise awareness of such opportunities. The primary objective of this case study is to better understand the business case economics of a specialty chemical plant using modular chemical process intensification (MCPI), by comparing it with that of a conventional stick‐built (CSB) plant that produces the same product at the same production capacity. When comparing MCPI against CSB approaches for a plant project strategy decision, analysts should thoroughly understand and model the differences and similarities in scope bases. The MCPI approach for this case study benefitted from dramatic reductions in capital expenditures (CAPEX). A sizeable reduction in plant spatial volume likely explains some of these reductions. Sizeable operational expenditure (OPEX) reductions with the MCPI plant appear to be associated with the reduced operator staffing required from converting a labor‐intensive batch process into an automated, continuous flow process. Traditional project investment economic measures strongly favored the MCPI case for the design, construction, and operation of the specialty chemical plant. The net present value for the MCPI case was nearly twice that for the CSB case over a ten‐year period, and the payback period for the CSB case was nearly five times longer than that of the MCPI case. The opinion‐based perspective of the study participant identified significant contributors to superior MCPI economic performance for this case study. With the two conditions of low MCPI CAPEX and high product profit margin, economic analysis indicates that incorporation of a backup MCPI train, for operational redundancy when downtime occurs, is a very beneficial strategy.

A Comparative Assessment Framework for Sustainable Production of Fuels and Chemicals Explicitly Accounting for Intermittency

The ubiquity of fossil fuels in the provision of mobility services and in the production of platform chemicals constitutes a substantial fraction of total anthropogenic CO2 emissions and resulting climate change. There is therefore substantial interest in the production of sustainable alternatives. Whilst much attention is directed to the individual elements in the value chain, there is a paucity of work focusing on the performance of the integrated system. To address this gap, we present a novel modelling framework for the design and scheduling of the production of platform chemicals and fuels from just air, water, and renewable energy throughout the year. Optimal routes are determined for solar ammonia and methanol. A combination of hydrogen storage for balancing seasonal intermittency and battery storage for balancing daily intermittency is determined as optimal. It is found that nitrogen-based fuels may offer advantages over carbon-based fuels. The cost of intermittency of renewable energy inputs is found to be as much as two thirds of total cost, again varying by location. This reinforces that future design of chemical plants needs to include a treatment of intermittency and opens questions on how to operate sustainable plants - for instance, operating seasonally, or more flexibly.

Using techno-economic modelling to determine the minimum cost possible for a microbial palm oil substitute

BackgroundHeterotrophic single-cell oils (SCOs) are one potential replacement to lipid-derived biofuels sourced from first-generation crops such as palm oil. However, despite a large experimental research effort in this area, there are only a handful of techno-economic modelling publications. As such, there is little understanding of whether SCOs are, or could ever be, a potential competitive replacement. To help address this question, we designed a detailed model that coupled a hypothetical heterotroph (using the very best possible biological lipid production) with the largest and most efficient chemical plant design possible.ResultsOur base case gave a lipid selling price of $1.81/kg for ~ 8,000 tonnes/year production, that could be reduced to $1.20/kg on increasing production to ~ 48,000 tonnes of lipid a year. A range of scenarios to further reduce this cost were then assessed, including using a thermotolerant strain (reducing the cost from $1.20 to $1.15/kg), zero-cost electricity ($ 1.12/kg), using non-sterile conditions ($1.19/kg), wet extraction of lipids ($1.16/kg), continuous production of extracellular lipid ($0.99/kg) and selling the whole yeast cell, including recovering value for the protein and carbohydrate ($0.81/kg). If co-products were produced alongside the lipid then the price could be effectively reduced to $0, depending on the amount of carbon funnelled away from lipid production, as long as the co-product could be sold in excess of $1/kg.ConclusionsThe model presented here represents an ideal case that which while not achievable in reality, importantly would not be able to be improved on, irrespective of the scientific advances in this area. From the scenarios explored, it is possible to produce lower cost SCOs, but research must start to be applied in three key areas, firstly designing products where the whole cell is used. Secondly, further work on the product systems that produce lipids extracellularly in a continuous processing methodology or finally that create an effective biorefinery designed to produce a low molecular weight, bulk chemical, alongside the lipid. All other research areas will only ever give incremental gains rather than leading towards an economically competitive, sustainable, microbial oil.

Chemical Plant Design for the Conversion of Plastic Waste to Liquid Fuel

This paper presents the plant design for fuel production from plastic waste. The types of plastics to be used for the fuel production include polyethylene, polypropylene and polystyrene. All these materials are to be sourced from Kpone landfill site in Accra, Ghana, where the plant is to be situated. The major fuels produced are gasoline, diesel and kerosene with a plant capacity of approximately 1000 tons of plastic waste per day and its attainment is 95%. The production process involves sorting the municipal solid waste to obtain suitable plastics. The plastics are extruded and cracked thermally in a Pyrolyzer and the gases from it are reformed over Zeolite-ZSM 5 as the catalyst in a reactor. Resulting vapours are fractionated in a column to obtain the various fuel components. The plant operates 24 hours/day and 347 days/year with 3 shifts per day of 8 hours per shift. Total capital required to build and start up the plant amounts to approximately 17 Million US Dollars. The plant life is 25 years with an annual rate of return of 34% and a payback period of 2.9 years for this project, after setting up. Annually, the plant would generate gross and net profits of approximately 9 Million US Dollars and 6.7 Million US Dollars respectively.

Application of BIM in Pipeline and Equipment Project of an Energy Centre

This paper is based on BIM chemical plant upgrade project energy centre plant design, BIM Technology is applied to the project pipeline comprehensive design, using the Revit to complete the professional system modelling, using Naviswork to analyse the collision conflict between various disciplines and generate collision conflict report, through the pipeline comprehensive adjustment optimization model, improve the design quality.

Thermophysical Properties of Amorphous‐Paracrystalline Celluloses by Molecular Dynamics

AbstractFor the engineering and process design of chemical and pharmaceutical plants, the knowledge of thermophysical properties is essential. Here, glass transition temperature (Tg), curves of heat capacity (Cp), isotropic thermal expansion (∝p), and isothermal compressibility (βT) are computed for amorphous/paracrystalline (Am‐Par) structures of cellulose over a wide range of temperature (380–680 K) using molecular dynamics with the CHARMM36 (C36) force field (FF). The fluctuation method under the NPT ensemble is used to calculate Cp, ∝p, and βT, whereas Tg is computed by monitoring specific volume versus temperature. Here, the fluctuation method is used with a quantum mechanical correction term for the calculation of Cp. Results of Cp, ∝p, and βT values at 298 K using extrapolation from these curves are also obtained. The thermophysical properties values from the simulations are compared with experimental data for cellulose with different degree of crystallinity and with those obtained by prominent FFs suggested for cellulose, such as GLYCAM06 and COMPASS. The findings reveal that ∝p, βT, and Tg are somewhat better reproduced than Cp with C36 over the studied temperature range. From this study, it is inferred that, for accurate modeling of heat capacity of pure Am‐Par celluloses with large fragments of glucose, the C36 FF needs re‐parameterization.

Simulation of Ammonia Production using HYSYS Software

Now-a-days, Because of cost and time consuming in the design of plants chemical engineer used simulators to simulate design and operation of chemical equipment and plant, which spares a great deal of time and cash.Today, there are many number of the simulators are refreshed and utilized in the simulation of chemical equipment and plant such as ChemCad, ProII, UniSim……..etc. Among of these simulators, Aspen Hysys is the most utilized programming in all ventures because of aiding in two noteworthy fields (design & operation). Simulation of ammonia synthesis process is done on Aspen Hysys V8.8 with steady state mode making some assumptions and using hypothetical reactors ammonia. By fluctuating the distinctive parameters in this simulation environment, the impact of these parameters in the generation rate of the procedure are watched. Keywords: Ammonia, Simulation, Aspen Hysys DOI : 10.7176/CPER/62-03 Publication date: January 31 st 2020

Comparison of chemical routes based on inherent safety, health and environmental impacts of accidental and daily operational releases

One of the key decisions made during initial stages of chemical plant design and development is the chemical route selection. A chemical route is considered as the raw material(s) and the sequence of reaction steps that convert them to the desired chemical product. The selection of a chemical route focused on environmental, health and safety (EHS) issues has been given increased attention recently as avoiding hazards related to EHS can be largely achieved during initial stages of plant development. In order to select a route, alternate potential chemical routes need to be assessed and compared. In this work a fuzzy based inherent environmental, health and safety hazard index called EHS-Fuzzy Index is presented to compare chemical routes based on integrated EHS hazards due to accidental releases as well as releases from daily operational activities of the plant. Thirteen parameters representing EHS related hazards are included in the EHS-Fuzzy Index. The lower the EHS-Fuzzy Index the more environmentally friendly, occupationally healthy and safer the chemical route. The EHS-Fuzzy Index was applied in a case of six routes to manufacture methyl methacrylate (MMA). The least hazard was shown in tertiary butyl alcohol (TBA) route.

Representation of the process of oxidative regeneration of coked catalysts in a fixed layer based on graph theory

Representation of processes by means of graphs allows increasing their visibility in comparison with the technological scheme. This makes it possible to facilitate the design of chemical plants, especially in the case when going from the principal graph to more complex graphs of the same production. The presented representation of chemical technology processes based on graph theory is of a purely qualitative nature. The article shows the technological scheme and the resulting graph of the process of oxidative regeneration. Quantitative regularities derived from this theory can form the basis of optimization of the oxidative regeneration.