Simulation Of Process Research Articles

Simulation of intra-chamber processes in a low-thrust rocket engine with a hydrogen-air mixture and counterflow cooling

The principles and methods of improvement of thrust, efficiency and cooling of rocket engines for space flight safety are of great interest for aerospace industry. The development of reliable and durable low-thrust rocket engines for space missions seems to be one of the important areas of development of the rocket and space industry. Issues related to the implementation of a new direction related to the design of propulsion systems for orientation systems of upper stages of launch vehicles using environmentally friendly fuel components are considered. A mathematical model is developed and numerical modelling of processes in the combustion chamber of a low-thrust rocket engine with gaseous fuel components (hydrogen and oxygen) is carried out. The model takes into account the presence of a cooling jacket. The mathematical model includes the effects of turbulence, combustion of a gaseous fuel mixture, kinetics of hydrogen combustion, and radiation. As a result of calculations, distributions of flow quantities in the combustion chamber and thermal loads on its walls are obtained. The influence of hydrogen mass flow rate on the efficiency of the working process and the dependence of thrust on hydrogen mass flow rate are discussed. The results of numerical modelling are compared with the data of a physical experiment obtained through fire tests of an engine model made of stainless steel on a three-dimensional printer.

A nested non-intrusive stochastic isogeometric method for nonlinear thermal vibration of FGM plates under random loading

This paper introduces an adaptive nested non-invasive dynamic SIGA method based on RBFNN for the nonlinear thermal vibration analysis of FGM plates under random loading. This method is robust and accurate in high-dimensional input spaces regardless of the sample sequence, addresses the low convergence rate of QMCS, and solves the stochastic dynamic response probability density function under random loading. Firstly, the multidimensional input space for random loading is constructed based on several mutually independent random variables via the stationary Gaussian stochastic process simulation technique. The nonlinear FGM plate model subjected to random loading in the thermal environment is modeled using HSDT with von Kármán strain-displacement relation within the IGA framework. Subsequently, a nested non-invasive dynamic response surface analysis method, SIGA-RBFNN, is proposed based on the RBFNN technique. Analysis of the FGM plate response under random loading demonstrates that SIGA-RBFNN, compared to tensor-product-based SIGA methods, is less affected by sample sequence types. It effectively addresses high-dimensional stochasticity and offers significant advantages in robustness, accuracy, and efficiency. Finally, SIGA-RBFNN compensates for the low convergence speed of QMCS and successfully solves the FGM plate displacement response statistics and probability density function under random loading.

Analysis of Electromagnetic Buffer Characteristics of DC Fast Vacuum Switch

In order to solve the contradiction between the rapid isolation of low voltage DC faults and the low bounce of small stroke vacuum switches, taking the fast vacuum switch for 400 V DC power distribution system as the research object, the electromagnetic buffer simulation and experimental research in the opening process are carried out. The influencing factors of the dynamic and reaction mechanism and buffer output characteristics are analyzed, and the electromagnetic buffering effect under typical working conditions is simulated, which proves that electromagnetic buffer is a necessary part of 400 V fast vacuum switch and the motion characteristics of fast switching are optimal when applying 220 V electromagnetic buffer. According to the simulation calculation results, the engineering prototype was made, the experimental research on the electromagnetic buffer under typical working conditions was carried out, and the design criteria of the small stroke electromagnetic buffer were proposed, which solved the problem of fast switching of small stroke and reliable control and low bounce. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Simulation and optimization of separation processes for the downstream of the catalytic oxidation of HCl as byproduct from the fluorochemical industry

The catalytic oxidation of gaseous HCl with a small amount of HF to Cl2 is of utmost importance and desire for chlorine recycling in the fluorochemical industry. Herein, based on the results from the catalytic oxidation of HCl as byproduct contaminated with HF and fluorocarbons from the production of 1,1,1,2-tetrafluoroethane (HFC-134a) over a recently developed RuO2/MgF2 catalyst, the separation and purification processes of the downstream from the catalytic oxidation unit were simulated and optimized using the Aspen Plus software. In the simulation and optimization, a separation flow for Cl2 purification was built up and the corresponding mass and energy balances were made as well. The results show that both produced H2O vapor and unconverted HCl from the catalytic reactor can be effectively removed by a two-stage cooling dehydration unit coupled with a three-stage drying tower to obtain 29.90 wt% hydrochloric acid. In addition, the relationship between the dehydration amount and the heat load of the drying tower was optimized, showing a H2SO4 (98.00 wt%) consumption of 11.8 kg per ton of Cl2 produced, i.e., 11.8 kg/t, in the drying tower. Furthermore, the gaseous mixture of Cl2 and O2 can be separated by a pressurized distillation unit, in which the operating pressure and temperature as well as the heat load of the condenser were optimized, showing that a liquified Cl2 concentration of 99.93 wt% with a recovery efficiency of 97.0 % can be achieved. The current research, therefore, provides some fundamental base for the industrialization of the recovery of Cl2 from the byproduct HCl in the fluorochemical industry.

Design and three-dimensional simulation of flat-knitted sports uppers based on loop structure

PurposeThe purpose of this paper is to solve the diverse and complex problems of flat-knitting sports upper process design, improve the design ability of upper organization, and realize three-dimensional simulation function.Design/methodology/approachFirstly, the matrix is used to establish the corresponding pattern diagram and organizational diagram model, and the relationship between the two is established by color coding as a bridge to completed the transformation of the flat-knitted sports upper process design model. Secondly, the spatial coordinates of the loop type value points are obtained through the establishment of loop mesh model, the index of two-dimensional and three-dimensional models of uppers and the establishment of spatial transformation relationship. Finally, using Visual Studio as a development tool, use the C# language to implement this series of processes.FindingsDigitizing the fabric into a matrix model, combined with matrix transformation, can quickly realize the design of the flat-knitting process. Taking the knitting diagram of the upper process as the starting point, the loop geometry model corresponding to the element information is established, and the three-dimensional simulation effect of the flat-knitted upper based on the loop structure is realized under the premise of ensuring that it can be knitted.Originality/valueThis paper proposes a design and modeling method for flat-knitted uppers. Taking the upper design process and 3D simulation effect as an example, the feasibility of the method is verified, which improves the efficiency of the development of the flat-knitted upper product and lays the foundation for the high-end customization of the flat-knitted upper.

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces.

Performing reliable computer simulations of elementary processes occurring at metal-water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Due to the large system sizes needed for studying processes at liquid water-metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate-metal interactions. Next, for the water-water and water-adsorbate interactions, we used established classical force fields. Finally, for the water-Ru surface interaction, for which no reliable force fields have been published, we used Behler-Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Parametric modeling and engineering application of the high-speed continuous beam bridge based on Building Information Modeling.

To improve the informatization and intelligence level of high-speed railway (HSR) bridge construction, a parametric modeling method for continuous beam bridges based on Building Information Modeling (BIM) is proposed in this study. By this method, the parametric families of continuous beam components and key construction machinery are established, and the rapid modeling of overall continuous beam bridge and the simulation of critical construction process are realized as well. Taking the Caoxian-Shangqiu bridge of Xiong'an-Shangqiu HSR as a case study, the parametric modeling method is applied to conduct the engineering application on the prestressed duct layout and rebar clash detection. The results indicate that the modeling efficiencies of HSR continuous beam bridge and construction machinery are significantly increased by the established parametric modeling method. Based on the BIM model of continuous beam bridge, the improvement in the precision of prestressed duct layout and the elimination of rebar clash points can be achieved. The research achievement can guide the visualization of construction disclosure, enhance construction efficiency, and provide reference and technical support for the construction management and control of HSR continuous beam bridges.

Physical Mechanisms of Improved Performance of Scaffolded Zinc-Silver Battery Cathodes.

Nanostructuring can greatly improve the electrode stability of rechargeable battery systems, such as Zn-Ag. In this report, we investigate the physical mechanisms by which nanostructuring alters structural properties of nanomaterials and thereby influences the structural stability of electrodes. We specifically consider the effects of Au-based nanoscaffolds on Ag. Through density functional theory calculations, we propose that the charge transfer at the Au-Ag interface can facilitate the formation of Ag2O from Ag centers. Structural analysis of samples prepared in this work shows that Ag2O is extruded from Au-Ag material in the form of sheets. Interestingly, the length scale of such protrusions depends on the Au mole fraction that significantly alters the system's overall structural morphology. We rationalize these findings via kinetic Monte Carlo simulations of the Ag2O growth process and highlight the role of Au as a heterogeneous nucleation center.

Equilibrium modelling of steam gasification of PKS system and CO2 sorption using CaO: A digitalized parametric and techno-economic analysis

The conversion of palm oil waste into energy can complement the energy mix with renewable energy and bring economic benefits to the palm oil industry. A process simulation model for palm kernel shell (PKS) steam gasification for H2-enriched syngas with the integration of CO2 capturing using CaO has been investigated using Aspen Plus V10®. Techno-economic and energy analyses have also been conducted to identify energy-saving opportunities for commercialization. The effect of process variables, including reactor temperature (600–800 °C), Steam/PKS ratio (0.5–2 wt/wt), and CaO/PKS ratio (0–1.5 wt/wt), have been determined, with the predicted results compared to the reported experimental data. H2 concentration has been increased with 76–78 vol% with the temperature elevation from 650 to 750 °C. Additionally, a substantial increase in H2 content from 68 to 72vol% was observed when the steam flow rate was increased from 0.5 to 1.5. Conversely, the CO2 concentration decreased from 25 to 8vol% as the adsorbent ratio was raised from 0.5 to 1.5. The techno-economic analysis showed that the capital investment is $4.11 million, and the operating cost is $3.89 million per year, which is also very high due to the high raw material costs. In the case of energy, saving that 3.03 and 1.513 Gcal/hr can be saved in terms of utilities and gas cooling that economized the process which shows that utilization of these in heat exchange networks can significantly reduce costs, with up to 78 % savings in heat exchanger capital and 35 % in total energy consumption. The energy potential could be harnessed through the digitalization of the process.

Structural models of the keratin derivatives. An approach to its solubility and processability

Small-size models of keratin constituent units and products of its decomposition are proposed and computed to i) reproduce the interaction patterns that hold the macromolecule structure and its behavior under different reaction media and physico-chemical conditions; ii) estimate the energy of interactions that support the tridimensional structure of the protein, and consequently, the energy requirements to break it. To create these models and evaluate their performance, quantum-chemical, COSMO, and COSMO-RS calculations were performed. They seem to be capable to support process simulations during the conceptual design and optimization of operations and processes to transform the raw keratin into products of higher added value. Besides, proper analyses using these models demonstrated that the cleavage of the disulfide bonds is the primary condition to break the macromolecule but additionally, the intramolecular H-bond network should be dissociated enabling the intramolecular interaction with the chemicals used to dissolve and regenerate the keratin.

Simulation, technical-economic evaluation and risk analysis of the purification of different bio-oils obtained by the fast pyrolysis process

Biomass is a natural compound that originates from various forms of organic matter. One way to transform biomass into value-added products is through the fast pyrolysis process, which is a thermochemical process that produces solid, liquid and gaseous compounds. The main product of this process is the bio-oil, found in the liquid phase and containing a wide range of value-added compounds that can be obtained through extraction and distillation. Simulation is an important tool for predicting, modeling and understanding the feasibility of the desired process, along with economic analysis of risks and uncertainties, which are useful techniques for studying the feasibility of projects. In this context, this work aimed to carry out the simulation using the Aspen Plus ® process simulator, the analysis of economic viability and the analysis of risks and uncertainties of the process of separation and purification of bio-oil compounds, derivatives of wood from eucalyptus, eucalyptus residues and sugarcane bagasse. After completing these steps, the project achieved a good result, with desired products being obtained with a considerable degree of purity for commercialization. Economically, all processes were viable, obtaining a good return on investment and a short payback period, despite the high costs involved. Even considering risks and uncertainties, including the variation in the cost of raw materials and production capacity, the investment still returned good results, demonstrating that the project is economically viable even under these circumstances.

Solving crystallization/precipitation population balance models in CADET, Part II: Size-based Smoluchowski coagulation and fragmentation equations in batch and continuous modes

A particle size-based Smoluchowski coagulation and fragmentation equation was solved in the free and open source process modeling package CADET. The WFV and MCNP schemes were selected to discretize the internal particle size coordinate. Weights in these schemes were modified to preserve and conserve the zeroth and third moments for size-based equations. Modified propositions and proofs for the scheme are provided. Analytical Jacobians were derived and implemented to reduce the solver’s runtime. A two-dimensional Smoluchowski coagulation and fragmentation equation with axial position as external coordinate was formulated and discretized to support simulations of continuous particulate processes in dispersive plug flow reactors. Five 1D and four 2D test cases were used to validate the implementation and benchmark the solver’s performance. The runtime, L1 error norm, L1 error rate, particle size distribution moments up to sixth order and several scalar metrics were analyzed in detail.

Process-induced stress tuning to improve linearity performance in AlGaN/GaN HEMTs with SiNx passivation

Strain engineering has proven to be a useful technique for enhancing the performance of many modern-day transistors. Stress engineering can also have a non-trivial effect on the performance of GaN HEMTs, which are devices of choice for high-power, high-frequency microwave applications. Process-induced stress can have a significant effect on AlGaN/GaN HEMT electrical characteristics in addition to the growth-induced strain present due to lattice constant mismatch between device layers. Understanding the true impact of process-induced strain on AlGaN/GaN HEMT microwave performance is highly necessary. This is especially the case for nonlinearity effects which affect the high-frequency performance of the device. To the best of our knowledge, there is no systematic report on the effect of nitride passivation-induced stress on AlGaN/GaN HEMT device linearity. This work uses a systematic combination of TCAD process simulation and device simulation to quantify the effect of process-induced stress on the device’s linearity. This work demonstrates that nonlinearity effects can be minimized through proper tuning of stress by varying design-dependent parameters such as the nitride layer thickness. The effect of stress on highly important linearity parameters of the device like gm, gm2, gm3, VIP2, VIP3, IIP3 and IMD3 is investigated in detail. Comparing the compressive-stress device to the no-stress and tensile-stress devices, we conclude that the compressive stress device has a max gm2 value that is 61% and 71% higher respectively. The max gm3 for compressive stress is 0.13 A V−3 whereas those for no-stress and tensile stress are 0.067 A V−3 and 0.045 A V−3 respectively. However, the voltage-variations of VIP2, and the VIP3 parameters which are derived from these gm values shows that the compressive stress case can help achieve overall better device linearity by stress tuning. This work also studies how the effect of process-induced stress on device linearity varies with the crucial gate length parameter.

Identifying Impacts of Contact Tracing on Epidemiological Inference from Phylogenetic Data.

Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007-2008 Swedish HIV-1 outbreak and the broader 1998-2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at github.com/MolEvolEpid/SEEPS.

Molecular Mechanism of Ciprofloxacin Translocation Through the Major Diffusion Channels of the ESKAPE Pathogens Klebsiella pneumoniae and Enterobacter cloacae.

Experimental studies on the translocation and accumulation of antibiotics in Gram-negative bacteria have revealed details of the properties that allow efficient permeation through bacterial outer membrane porins. Among the major outer membrane diffusion channels, OmpF has been extensively studied to understand the antibiotic translocation process. In a few cases, this knowledge has also helped to improve the efficacy of existing antibacterial molecules. However, the extension of these strategies to enhance the efficacy of other existing and novel drugs require comprehensive molecular insight into the permeation process and an understanding of how antibiotic and channel properties influence the effective permeation rates. Previous studies have investigated how differences in antibiotic charge distribution can influence the observed permeation pathways through the OmpF channel, and have shown that the dynamics of the L3 loop can play a dominant role in the permeation process. Here, we perform all-atom simulations of the OmpF orthologs, OmpE35 from Enterobacter cloacae and OmpK35 from Klebsiella pneumoniae. Unbiased simulations of the porins and biased simulations of the ciprofloxacin permeation processes through these channels provide insight into the differences in the permeation pathway and energetics. In addition, we show that similar to the OmpF channel, antibiotic-induced dynamics of the L3 loop are also operative in the orthologs. However, the sequence and structural differences, influence the extent of the L3 loop fluctuations with OmpK35 showing greater stability in unbiased runs and subdued fluctuations in simulations with ciprofloxacin.

Experimental Analysis and Optimization of Clearance between Punch and Die in Sheet Metal Blanking Process for Soft Steel

Blanking process is commonly used process in production of sheet metal industries to fabricate components. The Global market of sheet metal production is facing highly competition. Due to unavailability of skilled operators and shortage of affordable CAD/CAM systems, it is difficult to predict optimum clearance between punch and die to obtain high quality in small scale industries. Blanking is metal fabricating process and it is characterized by complete material separation. The simulation of the shearing process is complicated as the shear band formed is narrow and fracture criterion is inappropriate. The effect of potential parameters like thickness of sheet, punch-die clearance, tool wear, and punch geometry are studied to investigate their interactions on blanking process. It is important to select process leading parameters which can lead the process such that two similar products from two separate materials can be manufactured on same mold with high quality. This study will help to investigate the effect of thickness of sheet, clearance between punch and die and type of material on blanking process and will help to predict optimal set of parameters to obtain reasonable quality. A mathematical model of blanking process is developed and design of experiments method is used to predict optimum punch-die clearance for soft steel which will result into high quality of component.

An energetic approach to the statistical analysis and optimization of friction welding processes applied to an aluminum-steel-joint

The present publication deals with an energy-oriented approach to the statistical analysis of rotational friction welding processes. To illustrate the methodological approach, it is applied to investigate the effects of energy flow on material flow behavior and joint quality during friction welding of an AA6060 alloy with a low-alloy 16MnCr5 filler steel. The influences of the setting parameters on the energetic states are first analyzed by means of an initial screening. The evaluation using process simulation and statistical methods enables the generation of regressive response surfaces for the friction power, the friction time and the resulting induced friction energy. Based on these findings, a second experimental field is formed and evaluated, which considers the interaction between the energy input of the frictioning stage and the workpiece forging. This new approach results in the functional separation of the frictioning and forging stage, which eliminates the usual statistical interaction effects and thus facilitates analysis and optimization. The qualitative result variable required for the purpose of interpreting the results is the ultimate tensile strength of the friction-welded joint. Additionally determined hardness curves provide information about the properties of the thermally influenced zone and strength-relevant process sequences. The result is that, in addition to the amount of energy induced, the frictional power with which the former is induced also has a considerable influence on the joint strength, as it influences the material flow and the properties of the joining zone.

Effects of soy protein isolate interaction with brown rice starch on the multiscale structure of brown rice bread.

Gluten-free bread (GFB) has technical bottlenecks such as hard texture, rough taste and low nutrition in practical production. In order to solve these problems, this study used germinated brown rice starch as the main raw material, and investigated the effects of soybean isolate protein (SPI) on the multiscale structure of germinated brown rice starch and bread quality. A gluten-free rice bread process simulation system was established, and the interaction between SPI and starch in the simulation system was characterized. The result shows that the interaction forces between SPI and germinated brown rice starch were mainly represented by hydrogen bonds, and with the addition of SPI, the crystallinity of starch showed a downward trend. At the same time, when the amount of SPI was 3%, the appearance quality was the best and the specific volume of bread was 1.08 mL g-1. When the amount of SPI was 6%, the texture quality was the best. Compared with the bread without SPI, the hardness of the bread with 6% SPI was reduced by 0.13 times, the springiness was increased by 0.03 times, the color was the most vibrant, the L* value being 1.02 times the original, and the baking loss was reduced to 0.98 times the original. The interaction force between SPI and germinated brown rice starch and its effect on bread quality were clarified, and these results inform choices about providing a theoretical basis for the subsequent development of higher-quality GFB. © 2024 Society of Chemical Industry.

Experimental and process simulation on solid fuel chemical looping cascade utilization conversion technology aiming hydrogen generation

In this work, a novel chemical looping process towards hydrogen generation based on the cascade utilization of components in solid fuels (like biomass and coal) with different reactivity (pyrolysis gas and char) was proposed, aiming for energy conversion from carbon-intensive fuels to carbon-free renewable hydrogen via the material migration of iron oxides. Biomass, represented by sawdust, is an important part among various renewable energy sources and a typical solid fuel with great potential. Therefore, in the most concerned reduction stage, experiments were conducted mainly using sawdust to investigate the effects of various parameters (temperature, oxygen/fuel ratio, residence time) on the carbon conversion involved in char in the primary reduction stage, gas/solid spatiotemporal distribution in the deep reduction stage and subsequent H2 generation performance, and kinetic parameters were fitted for different reduction stages. Process simulation was further conducted based on the actual experimental results. The proposed process demonstrated satisfactory applicability to solid fuels with different characteristics, and biomass was more suitable for hydrogen production. Compared with chemical looping combustion process, a significant improvement of sawdust-fueled energy conversion efficiency from 33.26 % to 51.76 % and a decrease of OCs theoretical circulation rate (27.77 %) were achieved under the chemical looping process aiming hydrogen generation.

Simulation and Economic Analysis of Helium Extraction Process from Natural Gas

The investment estimation of the helium extraction project from natural gas is a crucial step in economically obtaining helium from both domestic and international projects. This article employs Aspen HYSYS to simulate the process and estimate the investment levels of Linde and Exxon Mobil integrated helium extraction processes. We investigate the influence of feed composition and processing capacity on investment costs and product returns. The results indicate that higher helium content of feed correlates with increased equipment investment costs and total capital cost (CAPEX), and that the Linde integrated process is significantly more sensitive to changes in helium content of feed than the Exxon Mobil integrated process. As the helium content of feed rises, the product returns of the two processes are evidently improved, leading to reduced investment payback periods. Both techniques exhibit favorable payback periods when the feed helium content exceeds 0.5 vol%. Nevertheless, elevated nitrogen content in the feed notably escalates the equipment investment costs and total capital costs. Furthermore, an increase in the processing capacity of feed gas leads to a nonlinear increase in total capital costs and annual operating costs. However, the cost per unit of helium extraction diminishes with increasing capacity. In general, the Linde integrated process requires higher separation energy consumption in comparison with the Exxon Mobil integrated process at similar processing capacities. Moreover, the sensitivity analysis shows that helium breakeven price is strongly affected by the price of both LNG and feed gas.