Chemical Process Industries Research Articles

Seismic risk in the chemical process industry: A semi-quantitative methodology for critical equipment identification

Natural events, such as earthquakes, floods, etc., can play a significant role in triggering industrial accidents of various intensities (the so-called Na-Tech risk), so that their inclusion in a comprehensive risk assessment is very important. However, a detailed and comprehensive quantitative approach is often unrealistic, because of the extremely large number of calculations to be carried out and of scenarios to be analysed. A preliminary semi-quantitative methodology is here presented for the characterization of the safety level of the different equipment items located in an industrial site, with respect to seismic hazard. Still based on objective evaluations, the presented approach allows to reduce the calculation burden, rank the equipment items in terms of relative seismic risk, and to identify the most critical items which more urgently need further attention. Along with the proposed methodology, an example of its application to a real industrial case is presented.

Dynamic Characteristics of Continuous Stirred Tank Reactor (CSTR) Part I: Adiabatic Reactor

CSTR is a very common reactor type which is widely used in the chemical process industries. It is well-known that its dynamics are nonlinear with a multi-mode behavior. This aspect was and still is an active subject of research with the investigative approach being either mathematical or experimental involving specific reaction systems. In this work a different approach is adopted in which the variation of the damping coefficient value of the linearized reactor’s transfer function is investigated over chosen values/ranges of relevant parameters. Our results indicate that an adiabatic type of such a reactor in which a liquid-phase, 1st-order, irreversible, exothermic chemical reaction takes place can be unstable or stable. If stable, it is either critically damped or overdamped with the latter mode being overwhelming; however, it is never underdamped. Furthermore, even when stable its dynamic behavior can be peculiar depending on certain values of some parameters.

Orthogonal projection based statistical feature extraction for continuous process monitoring

Multivariate statistical techniques have been widely applied in industrial processes to detect abnormal behaviors, while their performance could be unsatisfactory due to insufficient extraction of complex data characteristics. A method named Orthogonal transformed statistics Mahalanobis distance (OTSMD) is developed to handle this issue. As a feature-based method, OTSMD simultaneously considers various data characteristics through monitoring statistical features of process variables. Orthogonal transformed components (OTCs) are first calculated to capture variable correlation, and a set of statistical features is determined to extract other crucial characteristics, especially for the process non-stationarity. Statistical features of OTCs, which reveals implied process information, are continuously obtained using a sliding window, and a Mahalanobis distance index is utilized for fault detection. Compared with existing methods, OTSMD extracts data characteristics more comprehensively with a lower dimension, making it more effective in monitoring various faults. The results are illustrated through a numerical example, and two chemical industrial processes.

Hazardous wastes in Campania (Italy) and health impact

During the 1980s, the region of Campania (particularly Naples and Caserta) underwent illegal dumping of toxic waste. In this regard, adverse health outcomes of this population could increase and contribute to risk of diseases. The highly toxic waste (HTW) dumping along the coast and the hinterland has led to high rates of congenital disabilities and cancers. In this context, the waste derived from hospitals, mining, agriculture, petroleum refining, textile, chemical, construction, and food processing industries has contaminated the land. It has caused the local population to have high exposure to toxic waste. In addition, the scientific community tried to show a relationship between exposure to pollutants and health issues. Here, we point out the importance of epidemiological and biomonitoring data from an environmental perspective to address the correlation between long-term exposure to different pollutants and consequences on human health.

Nanoparticles: Role in the Chemical Industry, Potential Sources and Application in Chemical Catalysis

Chemical industries produce polymers, and with the help of nanotechnology, their structure can be modified to be used for other chemical applications and industrial processes. The chemical industry synthesized useful products and chemical compounds at great cost and with large amounts of energy required to produce them. In the article, the authors consider various approaches in the study of nanotechnology to improve chemical methods in order to increase their strength and performance. The role of nanoparticles and nanotechnologies in the processing of magnetic substances, the role in cleaning coatings and surfaces, and the role in the detoxification and filtration system of water are analyzed.

Inherent Process Risk Index (IPRI) – A tool for analyzing inherently safer design using Aspen Plus simulation

The rapid expansion of the chemical process industry necessitates an increased emphasis on process safety. Inherently safer design strategies are one of the most reliable and robust methods for process safety and are generally considered cost-optimal for loss prevention. In this manuscript, a semi-quantitative risk-based index, named the Inherent Process Risk Index (IPRI), is proposed to evaluate a process’s inherent safety from first-principle chemical engineering calculations. The strategy proposed relies on simulation data from Aspen Plus and helps quantify the risk associated with both individual unit operation and the process. Input to the risk calculations include process parameters, such as temperatures, pressure, and flow rates. More specifically, in this manuscript, the risk estimated is presented using two case studies to elaborate the functioning of IPRI, namely the production of formic acid using Kemira-Leonard process and methyl methacrylate production. In addition to benchmarking the process risk with IPRI, the results obtained were compared to those obtained using existing indexing methods to highlight the novelty of IPRI and also explain the differences between IPRI and other indexing methods. It is believed that integrating risk indexing with Aspen plus simulation will aid in teaching process safety to undergraduate engineering students.

CFD Analysis of the Effect of Mass Flow Rate in a Shell and Tube Heat Exchanger Design

Heat exchangers are often found in the chemical process industry, but of all types of heat exchangers, the Shell and Tube Heat Exchanger (STHE) are the most used. The design of shell and tube heat exchangers are continually evolving because of it reduce production costs. A computational fluid dynamics (CFD) simulation was employed using SOLIDWORKS Flow Simulation version 2022 to model the effect of operating parameter such as the mass flow rate on the pressure drop, heat transfer coefficient and the turbulence intensity. The turbulence model adopted for the simulation was the k–ɛ turbulence model incorporating the boundary conditions. Three conditions were studied increasing both shell and tube side mass flow rate, maintaining either the shell or tube constant and then varying the other. The results obtained showed that an increase in mass flow rate have tremendous effect on the pressure drop, heat transfer and turbulence intensity.

A hybrid model for dynamic analysis of domino effects in chemical process industries

A hybrid model for dynamic analysis of domino effects in chemical process industries

Kinetics of Electron Transfer Reaction Between Co(II) and Chlorate Ions: Isothermal Reactor Design and Experimental Validation

The Batch Stirred Tank Reactor (BSTR) has been commonly used for decades in the chemical process industries and even on a pilot plant or laboratory scale whenever expensive and delicate raw materials and products such as pharmaceuticals or fragile transition metal complexes are involved. This research article describes the details of isothermal BSTR and subsequent experimental validation of the rate law discovered in the previous paper of this series on the electron transfer reaction between Co(II) and chlorate ions in acetic acid solution. A Series of tests were performed to evaluate the efficiency of the BSTR at multiple temperatures and illustrate the differences between the theoretical and experimental conversion of potassium chlorate through relative error. The experimental conversions are calculated with the design equation. Theoretical and experimental conversions are correlated and proportional to the initial concentrations of the reactant and electron transfer reaction among the reactants. Based on the parameters of the design equation, a set with average parameters was chosen and tested over BSTR. The model was then validated for different temperatures and conversions. A design equation for the BSTR has been written and applied for the conversions of 25%, 50%, 75%, and 95%. The time interval is going to be predicted by the model to achieve the desired conversions. The percent relative error between predicted and experimental conversions clearly shows the modeland#39;s predictability, power, and reliability. The precision of the observed rate constant for the electron transfer reaction is found to be 2.2023and#215;〖10〗^(-2 )%

Identification of Process Networks with Recycle Streams

Processes with material and energy recycle are frequently encountered in chemical process industries. Most of the existing data-driven model identification techniques assume that the underlying process units are without any recycle. While the ideas of traditional closed-loop system identification are useful in dealing with recycle streams, identifying each of the subsystem models embedded in the process network in the presence of unmeasured disturbances and measurement noise requires careful consideration of the underlying process topology and a systematic step-wise procedure. In this work, we utilize the existing ideas of two-stage (SISO) identification of dynamical networks in combination with process topology to efficiently identify process networks with recycle streams. We demonstrate the efficacy of the approach through simulation case studies comprising different levels of process network complexity.

Predictive Modeling of Surface Tension in Chemical Compounds: Uncovering Crucial Features with Machine Learning

Surface tension (SFT) can shape the behavior of liquids in industrial chemical processes, influencing variables such as flow rate and separation efficiency. This property is commonly measured with experimental approaches such as Du Noüy ring and Wilhelmy plate methods. Here, we present machine learning (ML) methodologies that can predict the SFT of hydrocarbons. A comparative analysis encompassing k-nearest neighbors, random forest, and XGBoost (extreme gradient boosting) methods was done. Results from our study reveal that XGBoost is the most accurate in predicting hydrocarbon SFT, with a mean squared error (MSE) of 4.65 mN2 m-2 and a coefficient of determination (R2 ) score of 0.89. The feature importance was evaluated with the permutation feature importance method and Shapley analysis. Enthalpy of vaporization, density, molecular weight and hydrogen content are key factors in accurately predicting SFT. The successful integration of these methodologies holds the potential to impact efficiency in different industry processes.

Laser doppler device for simultaneous measurement of the velocity and size of aerosols in the nozzle flame

Liquid aerosol is used in technological processes in mechanical engineering, instrument building, chemical industry, medicine and agriculture and other areas. Nozzles are used to spray liquids, which allow to obtain their uniform distribution on the surface or in the volume. In aviation jet engines, fuel is sprayed using nozzles. The thrust of an aircraft engine depends on the quality of fuel atomization. Information on the distribution of droplet sizes and their movement velocity is required to assess the properties of the entire droplet-air system of the nozzle torch. To determine the main characteristics of the nozzle, you need to have a device that measures the velocity of aerosols and the size of aerosols in the nozzle flame. In order to solve this problem, the possibility of using a laser Doppler velocitymeter is investigated. Analysis of the radiation scattered by aerosols by intensity and state of polarization was carried out. It is proposed to increase the signal/interference ratio of the device by ensuring the matching of scattered radiation by intensity and polarization state. For this purpose, it is proposed to install a spatial filter of scattered laser radiation in the device. Such a filter should have the form of a diaphragm with two holes in the form of a narrow slit. Within the limits of one hole, the condition of complete matching of radiation in terms of intensity will be fulfilled, and within the limits of the other hole, the condition of matching according to the state of polarization will be fulfilled. It is shown that if such a receiving diaphragm is inserted into a differential-type laser velocity meter, it can be used to simultaneously measure the velocity and size of aerosols in the nozzle plume. The laser velocity meter photo detector must contain a built-in amplifier with a wide bandwidth. Doppler signals must then be sent simultaneously to an amplitude detector and a digital device. Using a digital device, the frequency of the variable component of the signal will be measured, which is proportional to the velocity of the aerosol and the amplitude of the signal is measured which is proportional to the size of the aerosol.

Reinforcement Aided Latent Temporal Feature Transfer Learning: Time Series Prediction With Insufficient Labeled Data for Industrial Chemical Process

Reinforcement Aided Latent Temporal Feature Transfer Learning: Time Series Prediction With Insufficient Labeled Data for Industrial Chemical Process

Modelling of consumer dynamics to improve fuel gas blending control

Although fuel gas systems represent a large part of industrial chemical processes, there has been limited literature on their modelling and control. The available literature typically neglects the effects of fuel gas consumer dynamics, leaving much of the system's important dynamic behaviour omitted. This paper aims to contribute to the existing literature on fuel gas control and improve an existing fuel gas control benchmark problem by including the effects of fuel gas consumer dynamics on the system. Two model predictive controllers (MPC) were designed, where the first MPC uses a model that neglects the consumer dynamics and the second MPC uses a model that includes the consumer dynamics. It was found that the MPC neglecting consumer dynamics has a pressure variability 5.8 times higher than the MPC that includes the dynamics. It also has a relative sensitivity index (RSI) of 7.2, indicating the presence of model-plant mismatches (MPM) affecting controller performance.

A theoretical study of the oxidation of benzene by manganese oxide clusters: formation of quinone intermediates.

Manganese oxides (MnxOy) have been widely applied in various chemical industrial processes owing to their long lifetime, low cost and high abundance. They have been used as co-reactants for the elimination of volatile organic compounds (VOCs); however, their oxidation mechanism is not clearly established. In this theoretical study, interaction capacities between benzene (C6H6) and MnxOy clusters, which were modeled with MnO2 and Mn2O3 molecules, were investigated by quantum chemical computations using density functional theory (DFT) with the PBE-D3 functional. The interaction capacity between C6H6 and MnxOy was evaluated, and the probing of the initial stage of the C6H6 oxidation at a molecular level offers an in-depth oxidation reaction path. Interaction energies computed in several spin states, along with the analysis of the electron distribution using the quantum theory of atoms in molecules, natural bond orbital and Wiberg bond index techniques as well as local softness values and MO energies of fragments, point out that the interaction between C6H6 and Mn2O3 is stronger than that with MnO2, amounting to -43 and -35 kcal mol-1, respectively, and the metal atom is identified as the primary active site. During the oxide cluster-assisted oxidation, benzene firstly undergoes an oxidation reaction by active oxygen to generate intermediates such as hydroquinone and benzoquinone. The pathway involving p-benzoquinone as the product (noted as PR1) is the most energetically favored one through a transition structure lying at 19 kcal mol-1, below the energy reference of the reactants, leading to an energy barrier significantly lower than that of 36 kcal mol-1 found for the gas phase oxidation reaction with molecular oxygen without the assistance of the oxide clusters. Potential energy profiles illustrating the reaction paths and molecular mechanisms were described in detail.

Performance assessment of a system to provide steady high temperature air via solar thermal suspension flow technology with storage and combustion back-up

The imperative for economically viable sources of high-temperature heat without contributing to net carbon emissions has become a pressing global concern, particularly in the context of industrial chemical processes. Solar thermal heat generation emerges as a pivotal solution in addressing this formidable challenge. By concentrating sunlight to achieve high temperatures, solar thermal technology can provide the intense heat required for various industrial applications, including chemical processes, without relying on fossil fuels. This not only helps reduce greenhouse gas emissions but also enhances energy efficiency and sustainability in energy-intensive industries. However, the full integration of solar thermal systems into energy-intensive industrial processes necessitates continued advancements of new technologies to achieve temperatures in the order of 1000 °C. In this paper, the performance of a high temperature concentrating solar thermal plant based on a 50MWth suspension flow solar particle receiver sub-system integrated with sensible thermal storage and combustion backup is analyzed, to supply steady output of reheated air to a downstream thermochemical process. The analysis is performed with transient mathematical models of the receiver and packed bed thermal storage sub-systems considering solar resource variability, written in a Simulink environment, to estimate useful annual thermal gain, thermal efficiency, solar share and levelized cost of solar heat, for a range of parameters including particle mass loading, air mass flow rate, thermal storage capacity and solar multiple. The time-dependent temperature fields of the receiver and thermal losses, together with their influence on the performance of the combined system are reported for each condition with a transient input solar resource spanning over a whole year. New insights are provided of the relative tradeoffs between these parameters on the overall system performance, solar share and levelized cost of solar energy. Also reported is the sensitivity of the levelized cost to different system combinations sized to provide a solar share of up to 75 % of the yearly process thermal demand, along with the influence of the specific costs of the system components varied in the range of ± 60 %.

Metal Recovery from Wastewater Using Electrodialysis Separation

Electrodialysis is classified as a membrane separation process in which ions are transferred through selective ion-exchange membranes from one solution to another using an electric field as the driving force. Electrodialysis is a mature technology in the field of brackish water desalination, but in recent decades the development of new membranes has made it possible to extend their application in the food, drug, and chemical process industries, including wastewater treatment. This work describes the state of the art in the use of electrodialysis (ED) for metal removal from water and wastewater. The fundamentals of the technique are introduced based on the working principle, operational features, and transport mechanisms of the membranes. An overview of the key factors (i.e., the membrane properties, the cell configuration, and the operational conditions) in the ED performance is presented. This review highlights the importance of studying the inter-relation of parameters affecting the transport mechanism to design and optimize metal recovery through ED. The conventional applications of ED for the desalination of brackish water and demineralization of industrial process water and wastewater are discussed to better understand the key role of this technology in the separation, concentration, and purification of aqueous effluents. The recovery and concentration of metals from industrial effluents are evaluated based on a review of the literature dealing with effluents from different sources. The most relevant results of these experimental studies highlight the key role of ED in the challenge of selective recovery of metals from aqueous effluents. This review addresses the potential application of ED not only for polluted water treatment but also as a promising tool for the recovery of critical metals to avoid natural resource depletion, promoting a circular economy.

A highly water-soluble hydrogen-bond-induced emission carbon dots for ratiometric fluorescent detection of water content in organic solvents

Water in organic solvents is a prevalent impurity that significantly influences chemical reactions and industrial processes. Carbon dots (CDs) gained attention as promising tools for chemosensing due to their advantageous characteristics, including easy synthesis, cost-effectiveness, and excellent adjustability and stability. However, limited solubility in water and turn off fluorescence response mode hinder the practical utilization of CDs for water sensing. To tackle such dilemma, a highly water-soluble CDs with distinctive hydrogen-bond-induced emission (HBIE) was rationally designed through introducing sulfone group into the widely employed p-phenylenediamine precursor. The inclusion of sulfone group imparts the CDs with notable water solubility, as well as distinctive ratiometric fluorescent response towards water content, exhibiting high sensitivity and selectivity. Upon exposure to water, the emission color of CDs undergoes a real-time transition from blue to yellow-green, which can be readily discerned by naked eyes. The CDs have been successfully applied in detecting water in commercially available alcohol. This study presents a straightforward yet efficacious approach for rationally design of CDs with unique HBIE characteristics and ratiometric fluorescent response, offering great potential for practical chemosensing applications.

(Invited) A Sustainable Future Fueled By Science: Recent Advances in Power-to-X Activities at Topsoe

Topsoe aims at being recognized as the global leader in carbon emission reduction technologies by 2024, by developing a wide range of energy-efficient solutions to produce sustainable transportation fuels, such as ammonia, methanol, and hydrogen. With over 80 years of expertise in heterogeneous catalysis and its application to industrial chemical processes, Topsoe is now striving to develop strong Power-to-X solutions to fuel the transition towards a sustainable chemical industry and energy infrastructure. One of the key-technology that Topsoe has envisioned for such transition is the solid oxide electrolysis cell (SOEC) technology, well-recognized as the most energy-efficient amongst the electrolysis solutions. Here, Topsoe’s expertise in heterogeneous catalysis also plays a role in ensuring an effective downstream catalytic conversion of SOEC products (H2, CO, or syngas) into green fuels and chemicals. To tackle climate change at the pace that our times impose, Topsoe is committing to a goal of net-zero greenhouse gas emissions by 2040. To reach such an ambitious goal, a large industrial scale application of the SOEC technology is necessary. Accordingly, Topsoe has announced the construction of a SOEC manufacturing facility in Denmark to produce electrolysis stacks and modules with a capacity of 500 MW per year, planned to be operational in 20251.In this presentation, Topsoe will provide an overview of its initiatives, lines of work and results in the field of SOECs, spanning from the thorough investigation of materials properties and electrode microstructure to the design and realization of a MW-sized electrolyzer plant. An extensive R&D effort is also directed towards increasing the lifetime of Topsoe’s fuel electrode-supported Ni/YSZ based cells, aiming at the development of robust and durable electrodes. The presentation will give examples of the analysis of electrode nano- and micro-structures by advanced characterization techniques, while illustrating the valuable role of impedance spectroscopy for the electrochemical characterization of the state-of-the-art cell performance. Finally, the presentation will also showcase results of stack testing applying Topsoe's stack technology for H2 production, as well as an update and outlook of Topsoe's efforts in upscaling its SOEC capacity. P. Blennow, T. Heiredal-Clausen, J. Rass-Hansen, J. B. Hansen; M. Hultqvist, and P.-G. Moses, in Proceedings - 14th Europrean Solid Oxide Fuel and SOE Cell Forum, p. A0304 (2022)

Integrated Mass and Energy Balance Course Project using Spreadsheet for a Chemical Engineering Degree Program

In this innovation, team projects from two courses offered in different semesters are integrated. On top of that, students are trained to use a spreadsheet-based tool to solve the problem in the project. Those two courses are Mass Balance (SETK 1123) and Energy Balance (SETK 2133) offered to Chemical Engineering students in Universiti Teknologi Malaysia at their second and third semester. The main objective of the innovation is to scaffold the students’ understanding of the problems given to them in the projects. At the end of the project, they should be able to clearly see the overall processes in a typical chemical industry, starting from raw materials to the targeted products, by-products, and wastes produced. In addition to that, the projects also foster digital skills by enhancing the students’ skills to use the spreadsheet tools to solve Chemical Engineering problems. This is inline with their study as the students learnt about computer programming and spreadsheet tools in their first semester. From the students’ reflections, it can be concluded that this innovation are able to increase the comprehension of the students on the two courses, increase the skills in using spreadsheet tools for solving problems and also inculcate critical thinking and problem solving skills.