Process Simulation Software Research Articles

Performance assessment of drop tube reactor for biomass fast pyrolysis using process simulator

AbstractBiomass pyrolysis process from a drop tube reactor was modelled in a plug flow reactor using Aspen Plus process simulation software. A kinetic mechanism for pyrolysis was developed considering the recent improvements and updated kinetic schemes to account for different content of cellulose, hemicellulose, and lignin. In this regard, oak, beechwood, rice straw, and cassava stalk biomasses were analyzed. The main phenomena governing the pyrolysis process are identified in terms of the characteristic times. Pyrolysis process was found to be reaction rate controlled. Effects of pyrolysis temperature on bio‐oil, gases, and char yields were evaluated. At optimum pyrolysis conditions (i.e., 500°C), a bio‐oil yield of 67.3, 64, 43, and 52 wt.% were obtained from oak, beechwood, rice straw, and cassava stalk, respectively. Oak and beechwood were found to give high yields of bio‐oil, while rice straw produced high gas and char yields compared to other biomasses. Although temperature is the main factor that plays a key role in the distribution of pyrolysis products, the composition of cellulose, hemicellulose, and lignin in the feedstock also determines the yield behaviour and composition of products. With the rise in pyrolysis temperature, further decomposition of intermediate components was initiated favouring the formation of lighter fractions. Comparably, species belonging to the aldehyde chemical family had the highest share of bio‐oil components in all the investigated feedstocks. Overall, the present study shows a good agreement with the experimental study reported in the literature, confirming its validity as a predictive tool for the biomass pyrolysis process.

Nonlinear operational optimization of an industrial power-to-heat system with a high temperature heat pump, a thermal energy storage and wind energy

The heat demand for industrial processes is often provided in the form of steam generated by various fossil fueled equipment. In order to reduce CO2 emissions, the heat demand has to be covered by renewable energy sources. Electrified steam generation relies on complex energy systems, that can be operated according to energy availability and cost developments. However, such a multi component industrial energy system poses a challenge in modeling and determining the cost- or emission-optimal operation of the system. This study develops a methodology to model a multi component industrial energy system on the basis of a case study. By optimal system operation, either costs or emissions are minimized in response to fluctuating renewable wind energy and electricity prices.A high temperature heat pump (HTHP), a sensible thermal energy storage (TES) and a wind turbine are combined to create an electrified energy system to supply super-heated steam. During periods of low wind speed, additional grid electricity is purchased to ensure a steady heat supply. The HTHP offers a high operational flexibility and thus, enables the charging and discharging of the TES. A model of the closed reverse Brayton cycle HTHP, which is able to simulate part load behavior, is created in a process simulation software and consolidated in nonlinear surrogate models. The component behavior of a TES is represented by a combination of equations based on heat exchanger relations. Finally, the resulting algebraic nonconvex, nonlinear optimization problem based on the proposed system is solved using the local interior point optimizer (IPOPT) solver equipped with a multi-start approach to determine an optimal operation over a reference week with respect to the current wind power generation, grid emissions and electricity prices.The results of the optimization show, that optimal operating strategies enable a high potential to decarbonize future industries at minimum operational costs or emissions.

Progress Toward a Comprehensive Model for Mass Transfer in Structured Packings

Significant effort has been devoted to the study of mass transfer in sheet metal structured packings over the past half century. A number of mass transfer correlations have appeared in the literature as a result of those efforts. Unfortunately, none of these correlations has shown itself to be reliable over the full range of chemical systems, column operating conditions, and packing topologies encountered today. In an attempt to rectify some of the shortcomings of earlier correlations for sheet metal structured packings, we have employed a new data analysis methodology which simultaneously fits ⟨HETP⟩ data and mass transfer area data. The correlation we report upon here includes 444 ⟨HETP⟩ values from a variety of systems, operating pressures, and packing designs, along with 409 mass transfer area measurements. We demonstrate that this correlation outperforms all others while remaining simple enough to implement in process simulation software.

Application of Multi-Software Engineering: A Review and a Kinetic Parameter Identification Case Study

Limitations regarding process design, optimization, and control often occur when using particular process simulators. With the implementation of connection methodologies, integrated tools could be made by coupling popular process simulation software with each other or with programming environments. In the current paper, we summarized and categorized the existing research regarding the application of multi-software engineering in the chemical industry, with an emphasis on software connections. CAPE-OPEN, COM, OPC, and native integration were discussed in detail, with the intention to serve as a guide for choosing the most suitable software combination and connection. These hybrid systems can handle complex user-defined problems and can be used for decision support, performing custom unit operations, operator training, process optimization, building control systems, and developing digital twins. In this work, we proposed the use of process simulator Aspen HYSYS linked together with the numeric computing platform MATLAB to solve a reaction kinetic parameter identification problem regarding the production of γ-valerolactone.

Parallel column model for reactive dividing wall column simulation

Reactive Dividing Wall Column (RDWC) modelling has attracted significant attention in recent years because simulations of processes containing such columns have demonstrated the potential for significant savings in energy and capital cost. Most modelling of these columns involves decomposing RDWCs into a thermodynamically equivalent flowsheet of reactive and non-reactive column sections in a sequential modular process simulation package. Such simulations of (R)DWCs can be time consuming to create and difficult to converge. It has been suggested that equation-oriented solvers can have superior numerical performance. Here, we use a CAPE-OPEN compliant equation-based parallel column model (PCM) that enables the rapid modelling of an RDWC as a single self-contained unit. Some conventionally modelled RDWCs from the literature are reproduced with the PCM to demonstrate its validity and excellent numerical performance. The ease and rapidity with which different RDWC configurations can be created is a significant advantage of our PCM.

System design and analysis of refrigerated containers utilizing LNG cold energy

In order to solve the problems of excess cold energy of the fuel and large power load required for refrigeration of refrigerated containers on LNG powered container ships, this study proposes a scheme to use the fuel cold energy of LNG powered container ships for refrigerated containers, the process simulation software Aspen HYSYS is used to simulate the cold energy utilization scheme, with the help of MATLAB, the multivariable optimization research on the cold energy utilization scheme of LNG powered container ship is carried out, taking the cold energy utilization rate of LNG cold energy scheme as the objective function, the LNG cold energy utilization scheme is optimized.

Techno-economic analysis of hydrothermal carbonization of pulp mill biosludge

For many mills, the biosludge from wastewater treatment is difficult to recycle or dispose of. This makes it a challenging side stream and an important issue for chemical pulping. It often ends up being burned in the recovery or biomass boiler, although the moisture and non-process element (NPE) contents make it a problematic fuel. Biosludge has proven resistant to attempts to reduce its moisture. When incinerated in the biomass boiler, the heat from dry matter combustion is often insufficient to yield positive net heat. Mixing the sludge with black liquor in the evaporator plant for incineration in the recovery boiler is more energy efficient, but is still an additional load on the evaporator plant, as well as introducing NPEs to the liquor. In this study, treating the biosludge by hydrothermal carbonization (HTC), a mild thermochemical conversion technology, is investigated. The HTC process has some notable advantages for biosludge treatment; taking place in water, it is well suited for sludge, and the hydrochar product is much easier to dewater than untreated sludge. In this study, two HTC plant designs are simulated using IPSEpro process simulation software, followed by economic analysis. Low temperature levels are used to minimize investment costs and steam consumption. The results show that if the sludge is incinerated in a biomass boiler, payback periods could be short at likely electricity prices. The HTC treatment before mixing the sludge with black liquor in the evaporator plant is profitable only if the freed evaporator capacity can be used to increase the firing liquor dry solids content.

Recovery boiler back-end heat recovery

Sustainability and efficient use of resources are becoming increasingly important aspects in the operation of all industries. Recently, some biomass-fired boilers have been equipped with increasingly complex condensing back-end heat recovery solutions, sometimes also using heat pumps to upgrade the low-grade heat. In kraft recovery boilers, however, scrubbers are still mainly for gas cleaning, with only simple heat recovery solutions. In this paper, we use process simulation software to study the potential to improve the power generation and energy efficiency by applying condensing back-end heat recovery on a recovery boiler. Different configurations are considered, including heat pumps. Potential streams to serve as heat sinks are considered and evaluated. Lowering the recovery boiler flue gas temperature to approximately 65°C significantly decreases the flue gas losses. The heat can be recovered as hot water, which is used to partially replace low-pressure (LP) steam, making more steam available for the condensing steam turbine portion for increased power generation. The results indicate that in a simple condensing plant, some 1%–4% additional electricity could be generated. In a Nordic mill that provides district heating, even more additional electricity generation, up to 6%, could be achieved. Provided the availability of sufficient low-temperature heat sinks to use the recovered heat, as well as sufficient condensing turbine swallowing capacity to utilize the LP steam, the use of scrubbing and possibly upgrading the heat using heat pumps appears potentially useful.

Novel BECCS implementation integrating chemical looping combustion with oxygen uncoupling and a kraft pulp mill cogeneration plant

Bioenergy with CO2 capture and storage (BECCS) is a promising negative emission technology (NET). When using sustainably produced biomass as fuel, BECCS allows the production of power and heat with negative CO2 emissions. The main technical challenges hindering the deployment of BECCS technologies include energy penalties associated with the capture process. This work evaluates the performance of an advanced CO2 capture technology, chemical looping with oxygen uncoupling (CLOU), replacing a conventional fluidized bed boiler in the power boiler role in a large, modern integrated pulp and paper mill. Results from a MATLAB/Simulink reactor model were incorporated in a plant and integration model developed in a commercial process simulation software to quantify the performance of the CLOU-integrated cogeneration plant. The results show that in this specific application, the typically already low efficiency penalty of CLOU-based carbon capture and storage (CCS) systems could be eliminated entirely, and actually even a very small efficiency gain could be obtained. The highly efficient operation is possible due to the high moisture and hydrogen contents of the biomass and the separation of combustion products and excess air streams in the CLOU process; this provides an opportunity to recover a significant amount of heat by flue gas condensation at a higher temperature level than what is possible in a conventional boiler. Together with abundant low-temperature heat sinks available at the pulp and paper application allows freeing a considerable amount of low-pressure steam for expansion in the condensing turbine. The resulting increase in gross generator output proved enough to not only match, but very slightly exceed the approximately 18 MW parasitic load introduced by the CLOU system in comparison to the conventional boiler.

Rate-based column simulation in the complex domain

Several organizations provide both equilibrium stage and rate-based column models in commercially available process simulation software. Many years of troubleshooting rate-based simulations tells us that they are more likely to suffer convergence issues than is an equivalent equilibrium stage model. The increased difficulty of converging rate-based simulations has to do with ties to actual equipment size that does not exist in the classic equilibrium stage model. Some years ago, Lucia and coworkers proposed solving chemical process models using computations in the complex-domain. They found that some hard-to-converge equilibrium stage column simulations were much easier to solve when carried out in the complex domain. We wondered if Lucia’s approach could help converge very challenging rate-based simulations. To answer that question, we have built a rate-based complex-domain code. Our most important result is that the complex-domain code can easily solve-rate based column simulations that are too difficult for the real-domain code.

A reduced order model for triethylene glycol natural gas dehydration system

In natural gas processing plants, glycol dehydration is commonly used to remove water from the gas streams, to avoid pipeline blockage and equipment breakdown due to hydrates formation. This paper proposed a reduced order model developed based on integrated simulation-optimization approach for the glycol dehydration system, with the aim to minimize its operating cost while satisfying pipeline quality specifications. Steady-state process simulation software was used to identify important operating parameters for the glycol dehydration process; these include reboiler temperature and flow ratio of the regeneration column, and solvent flowrate. The identified parameters are built into a non-linear programming model, which was developed as a reduced order model for ease of implementation in the plant. The studied parameters are reboiler duties, hot oil, condenser, and pump, as well as TEG make-up flow rate and CO2 equivalent (CO2-eq) emissions. The Pareto Front is developed to identify the minimum operating cost at different levels of water dew point specification. The work has resulted in the annual savings of more than 34.6%.

Management of a simulation project in a manufacturing company

Purpose: The main goal of managing a simulation project in a manufacturing company regarding the optimization of warehouse preparation and placement of galvanized steel profiles using FlexSim software is to improve logistics processes in the warehouse and increase production efficiency. The aim of the research is to develop an effective package addressing scheme and to introduce a special code that will enable precise management of profile storage and will improve the process of completing customer orders. Design/methodology/approach: The simulation project management methodology is based on several key steps: defining goals and requirements, collecting data and modeling, designing scenarios, performing simulations, and designing an individual addressing scheme for parcels in the warehouse. Findings: Simulations allow you to find the optimal warehouse layout that ensures effective use of the available space. This, in turn, allows you to increase the storage capacity and better organize the storage of profiles, which translates into minimizing losses and costs. Simulations allow you to test different strategies for placing profiles in a warehouse to minimize the time and effort needed to find them. Optimizing the placement process allows parcels to be located faster and more precisely, which speeds up order picking. Research limitations/implications: Simulation-based process optimization requires model accuracy and reliability. Imprecise or inaccurate data can affect simulation results and lead to inappropriate decisions. This requires careful data collection and model validation before implementation. Further research may focus on optimizing routes inside the warehouse and optimizing internal logistics. Investigating the best routes and methods of transport will minimize the time your products pass through your warehouse. Research can introduce an element of random events, such as machine breakdowns or fluctuating demand, into the simulation model to better reflect real conditions and increase the reliability of the results. Practical implications: Improvement of warehouse processes and the introduction of a special code addressing the shipment can significantly reduce the risk of errors and material losses, which contributes to greater accuracy and efficiency of operation and improvement of customer relations. Social implications: Effective optimization of warehouse and production processes contributes to increased work efficiency. Reduction of redundant activities, more precise management of resources, and more efficient order picking can affect employee satisfaction as well as positively affect working conditions and security. Originality/value: The key element of originality is using advanced FlexSim software for modeling and simulation of storage processes and producing galvanized steel profiles. Simulations of this type integrated with real data and the implementation of a special package addressing code constitute a comprehensive approach to optimizing the entire process. The results of such a study can have a significant impact on the practice in manufacturing companies, enabling more effective warehouse management, shortening the time of picking orders, reducing costs, optimal use of resources, and improving the quality of customer service. It is an interdisciplinary approach that combines aspects of production management, logistics, process optimization, and the use of advanced IT tools. Keywords: Simulation project management, process simulation, FlexSim software. Category of the paper: research paper.

Simulation Model of the Effect of the COVID-19 Biosecurity Protocol in the Queues for the Return to Face-to-Face Classes

This article presents a simulation model of the effect of the COVID-19 Biosafety protocol in the Queues for the return to face-to-face classes as a basis for the return of educational activities. The restrictive measures to face the COVID-19 pandemic, greatly affected the normality of the development of activities carried out in higher education, constituting a great challenge since the measures and conditions of return and access to institutions are different from what was previously carried out before the pandemic. The objective of this article is to carry out a simulation of queues through SIMIO (Logistics process simulation software), where the number of students expected per day and the average entry times are taken into account to adjust them to an exponential distribution, from this information loaded into the simulation it is They will determine if the times increase or decrease taking into account the theory of queues and conditions presented in the study such as the probability distribution of the times of each of the processes involved in the process of accessing the University facilities.

PROCESS DESIGN AND ECONOMIC ANALYSIS OF TRADITIONAL SHEA BUTTER PRODUCTION IN NIGERIA

The promotion of agricultural diversification emerges as a critical component of broader strategies aimed at mitigating greenhouse gas emissions and fostering the development of sustainable production systems. Nigeria stands out as a significant exporter of shea butter, which play a vital contribution to poverty alleviation, particularly in rural areas through creation of opportunities for participation of local women in the shea butter industry using local technologies in sheanuts pre-processing, roasting, grinding, oil extraction and refining. However, this production route is said to be severely affecting the final product yield and quality in addition to possible significant impacts on the environment. Evaluation of this production pathway is necessary for identification of areas of resource inefficiency, such as excessive utility (water, energy) consumption, implementation of more efficient and eco-friendly production processes. This study presents a process design and economic analysis of the local technology for shea butter production using advanced process simulation software (Aspen Plus ® V11) and Aspen economic analyser following 1 st quarter 2018 price basis. The simulation result showed that nearly 230 kg/day shea butter could be produced from 1 tonne shea fruit, which translate to only about 23 wt%. Pulp, shell and cake representing waste streams account for approximately 70 wt%. Utility analysis revealed daily water footprint of 585kg and 500 kJ heating requirement/day with carbon emission of 63 kgCO 2. The economic evaluations of the entire process plant showed that the traditional technology requires approximately $1.70M capital cost and $0.066M operating cost/year for 25-year economic life of the project with net present value of $158M. This study suggests that the local shea butter production technology is profitable with a payback period of 7years. However, the technology generates huge amount of waste streams and have negative impact on the environment. Consequently, there is need to adopt best practices in the shea butter processing that will generate more income and promote environmental sustainability.

Software for computer simulation of multiphysics processes in electromagnets and actuators of vacuum switching devices taking into account contact interaction of structural elements. Part 1: general overview; features of in-house codes

For computer modeling of multiphysics processes in complex modern technical objects, for example, in actuators and electromagnets of vacuum switching devices, it is necessary to use modern application software aimed at solving the entire spectrum of the specified problems or one or another "subset" of them. Complexes of applied programs must implement modern mathematical models and corresponding effective numerical algorithms, as well as have convenient interfaces both for the preparation and input of initial information (preprocessor), and for the output and analysis of the obtained results (postprocessor). The presence of the most "user-friendly" preprocessor and postprocessor is extremely important, considering the significant complexity of the processes being modeled, as well as the structures considered by the researcher and/or design engineer. It is of interest to carry out a comparative analysis of specific software products, with the aim of choosing a "tool" for the implementation of a complex of computational studies (computer modeling of multiphysics processes in the structural elements of medium and high voltage vacuum switching devices, taking into account contact phenomena), specified above. The article considers the criteria by which a reasonable choice of software can be made, which will be directly used for mathematical modeling of technical objects and processes under consideration.

Стохастичний і динамічний підходи при моделюванні процесів поширення шкідливого програмного забезпечення автоматизованих енергетичних об'єктів та їх систем

The rapid development of information technologies in today's conditions makes it possible to control and automate processes and enterprises, institutions to ensure the correct and efficient operation of various energy systems. The mathematical apparatus used in the software for such objects and systems makes it possible to manage their states in various regular conditions. Sometimes unpredictable factors arise in the operation of energy facilities, which can lead to global catastrophes not only for a particular region, but also for all of humanity is the deliberate damage to the logic of the software that controls all the processes of the power system is one of these factors, for the purpose of terror or other malicious purposes. Such factors require the construction of models with which it is possible to predict the scale of risk and extent of damage, as well as to obtain a general estimate of the costs of protecting power system software against such malicious actions. An optimization mathematical model and a corresponding description of the implementation of a complex software tool for modeling the spread of malicious software (malware) in modern energy facilities and systems is the result of the work. The developed optimization mathematical model is based on the use of methods of optimization of functions and functionals with restrictions in the form of systems of ordinary differential equations with given corresponding initial conditions. To develop process simulation software modules based on the PSIDR mathematical model, stochastic population methods, models and algorithms were used to determine the control parameter at each time step. The use of such optimization methods and algorithms makes it possible to solve more complex tasks. It requires a procedure for predicting the spread of processes of various origins in general. The developed mathematical model consists in the minimization of costs for the purchase of antiviruses for the protection of relevant systems in energy facilities and systems. Keywords: malware, prediction, optimization, stochastic model, deterministic model, cellular automaton, energy objects

Pengaruh Variasi Kondisi Operasi pada Kolom Distilasi Ekstraktif terhadap Sifat Fisis Pelarut Hidrokarbon Terdearomatisasi

Solvent is one of the important components in chemical processes. The type of solvent that is often used in the paint and coating industry is a hydrocarbon-based solvent which consists of a diverse complex mixture of liquids and contains aliphatic, alicyclic and aromatic (C5-C8) elements. Aromatic hydrocarbons are environmental pollutants that are known to be toxic, carcinogenic and mutagenic, so a hydrocarbon-based solvent with an aromatic content of less than 1% is needed. An appropriate separation method for separating aromatic and nonaromatic components having close boiling points is extractive distillation with a sulfolane entrainer. In this study, a distillation system with a sulfolane entrainer was run using the process simulation software Aspen Plus with the aim of understanding the effect of the amount of sulfolane, feed stage and number of stages on the physical properties of hydrocarbon-based solvents. This simulation is focused on the variation of the ratio of sulfolane: crude feed (7:1, 7.5:1, 8:1, 8.5:1), the variation of the feed stage (10th stage to the 35th stage) and the variation of the number of stages (70, 75, 80). It was found that the number of stages did not affect the density and flash point of the solvent. An increase of number of stage will decrease the solvent flash point and density. Significant decreament also can be found when the sulfolane to crude feed ratio is increased. However, the physical properties of the current dearomatized solvent is close to the properties of commercial product namely SBP 65/70 from one of oil and gas companies.

Exploring design options for pressurized chemical looping combustion of natural gas

Chemical Looping Combustion (CLC) is a low-cost CO2 capture technology highly competitive for industrial and energy applications. Up to date, CLC has been mostly developed at atmospheric pressure. Pressurized CLC may bring additional advantages due to the intensification of the process. The main objective of this work was to determine whether an increase in the operating pressure could improve the fuel conversion in CLC systems of gaseous fuels when ilmenite was used as oxygen carrier. Fluid dynamics considerations were evaluated to determine a window of suitable design parameters at pressurized conditions. A theoretical model previously validated at atmospheric pressure was modified to consider fluid dynamics and reaction kinetics at pressurized conditions, both in the bubbling and turbulent regimes, using ilmenite as oxygen carrier. The conversion of natural gas was estimated as a function of several design and operating parameters, such as the gas velocity, particle size and reacting temperature. Uncompleted combustion of natural gas was predicted at atmospheric conditions, and a limited improvement was estimated at pressurized conditions. A discussion about the required reactivity of the oxygen carrier to achieve complete combustion was performed. Furthermore, an energy analysis of a CLC system operating at atmospheric or pressurized (0.5 MPa) conditions with fuel reactor designed under the bubbling or turbulent regimes was carried out using the Aspen HYSYS process simulation software for two different applications of heat generation: production of domestic hot water and process steam. From this energy balance, it could be concluded that the energy efficiency achieved at pressurized conditions was slightly higher than that obtained at atmospheric pressure, essentially because at pressurized conditions it was possible to use the latent heat of condensation of the water generated in the fuel reactor. In addition to the results obtained in this work, a thorough assessment of technical risks and a techno-economic analysis would be required in order to make a final decision about the feasibility of operating at pressurized conditions in CLC systems.

Digitalize Learning via Process Simulation to Understand Process Control

Process simulation has become an important tool in training chemical engineers, operators in the chemical and industry sectors. Although various process simulation tools are available, in this study the software from Simulation Solutions. Inc. was used. This dual screen approach for student training consists of outside field operation view with interacting digital equipment and with the 2nd screen, the students can be in the control room environment changing input values. This provides the students with training in both control room adjustments of the plant and field operations adjustments. Students are supplied with a student manual that consist of Pipe and Instrument Diagrams (P&ID), standard operating procedures and troubleshooting exercises which they can follow. This article will discuss how these students benefit from process simulation training and how “What- ifs” can be used to pinpoint a potential problem. Once a problem has been identified then through simulation, the students will implement a corrective plan to successfully mitigate the risk. The feedbacks from the students suggest they have thoroughly enjoyed the interaction with the process simulation software and the “What-if” scenarios to identify the problem and use various resources to mitigate the problem. They learn how to implement strategies, solve the problem successfully and continue with the production process.

Separation and purification of syngas-derived hydrogen: A comparative evaluation of membrane- and cryogenic-assisted approaches

Hydrogen (H2) separation and purification is challenging because of the high purity and recovery requirements in particular applications, as well as the critical properties of H2 and its associated components. Unlike pressure swing adsorption, cryogenic- and membrane-based technologies are currently employed for H2 separation. Membrane-assisted (case-I) and cryogenic-assisted (case-II) separation and purification of H2 were evaluated in this study in terms of the energy, exergy, and economic aspects of the processes. In case-I and case-II, H2 was first produced from synthesis gas via the water-gas shift reaction and was then separated from other components using membrane and cryogenic systems, respectively. Additionally, an organic Rankine cycle was integrated with the water-gas shift reactors to recover the waste heat. A well-known commercial process simulation software, Aspen Hysys® v11, was employed to simulate both processes. Energy analysis revealed that case-I has a lower energy consumption (0.50 kWh/kg) than case-II (2.01 kWh/kg). However, low H2 purity and recovery rates are the main limitations of case-I. In terms of exergy, the H2 separation section in case-I exhibited a higher efficiency (28.4%) than case-II (14.7%). Furthermore, the economic evaluation showed that case-I was more expensive ($17.7 M) than case-II ($10.2 M) because of the high cost of the compressors required. In conclusion, this study could assist industry practitioners and academic researchers in selecting optimal H2 separation and purification technologies for improving the overall H2 economy.