Impact of sampling technique on the performance of surrogate models generated with artificial neural network (ANN): A case study for a natural gas stabilization unit

Data-driven models are essential tools for the development of surrogate models that can be used for the design, operation, and optimization of industrial processes. One approach of developing surrogate models is through the use of input-output data obtained from a process simulator. To enhance the model robustness, proper sampling techniques are required to cover the entire domain of the process variables uniformly. In the present work, Monte Carlo with pseudo-random samples as well as Latin hypercube samples and quasi-Monte Carlo samples with Hammersley Sequence Sampling (HSS) are generated. The sampled data obtained from the process simulator are fitted to neural networks for generating a surrogate model. An illustrative case study is solved to predict the gas stabilization unit performance. From the developed surrogate models to predict process data, it can be concluded that of the different sampling methods, Latin hypercube sampling and HSS have better performance than the pseudo-random sampling method for designing the surrogate model. This argument is based on the maximum absolute value, standard deviation, and the confidence interval for the relative average error as obtained from different sampling techniques.Qatar UniversityScopu

Natural Gas Sweetening Using an Energy-Efficient, State-of-the-Art, Solid-Vapor Separation Process

With the anticipated rise in global demand for natural gas (NG) and liquefied natural gas (LNG), sour gas reserves are attracting the attention of the gas industry as a potential resource. However, to monetize these reserves, sour natural gas has to be sweetened by removing acid gases (carbon dioxide and/or hydrogen sulfide) before liquefaction. The solidification of these acid gases could be the basis for their separation from natural gas. In this study, a state-of-the art solid-vapor (SV) separation unit is developed for removal of acid gases from methane and simulated using a customized Aspen Plus operation unit. The operating principles and conditions, mathematical model, and performance results are presented for the SV unit. Further performance analyses, means of optimization and comparisons to conventional methods used by the industry were studied. Results showed that for similar sweet gas purity, the developed SV unit consumes only 27% of the energy required by the amine sweetening unit. Furthermore, it saves on capital costs, as it requires less equipment and does not suffer from high levels of corrosion.Scopus2-s2.0-8513643009

How sustainable is liquefied natural gas supply chain? An integrated life cycle sustainability assessment model

Integrating sustainability into the distribution network process is a significant problem for any industry hoping to prosper or survive in today's fast-paced environment. Since gas is one of the world's most important fuel sources, sustainability is more important for the gas industry. While such environmental and economic effects have been extensively researched in the literature, there is little emphasis on the full social sustainability of natural gas production and supply chains in terms of the triple bottom line. This research aims to perform the first hybrid life cycle sustainability assessment (LCSA) of liquefied natural gas and evaluate its performance from the natural gas extraction stage to LNG regasification after delivery through maritime transport carriers. LCSA is used for estimating the social, economic, and environmental impacts of processes, and our life cycle model included the multi-region input–output analysis, Aspen HYSYS, and LNG maritime transport operations sustainability assessment tools. The results spot the light on the most contributors of CO2-eq emission. It is found that LNG loading (export terminal) is the source that generated the highest carbon footprint, followed by the MDEA sweetening unit with the contribution of 40% and 24%, respectively. Socially, around 73% of human health impact comes from SRU and TGTU units which are the most contributors to the particulate matter emission. Based on the interpretation of life cycle results, the environmental indicators show better performance in the pre-separation unit and LNG receiving terminal representing a sustainability factor equal to 1. In terms of social and economic impacts, the natural gas extraction stage presents the best performance among all other stages, with a sustainability factor equal to 1. Based on this study's findings, an integrated framework model is proposed. Various suggestions for sustainability strategies and policies that consider business sustainability and geopolitics risk are presented

Reactive Absorption of CO2 Using Ethylaminoethanol Promoted Aqueous Potassium Carbonate Solvent

Atmospheric concentration of CO2, which is considered as one of the major greenhouse gases (GHGs), has increased up to 398 ppmv as of 2015. CO2 concentration in atmosphere was 280 ppmv in pre-industrial era, and due to the continuous discharge, it is expected to increase up to 550 ppmv by 2050. Many of the major industrial sources of CO2 emissions are natural gas fired power plants, synthesis gas used in integrated gasification combined cycle (IGCC) and power generation, gas streams produced after combustion of fossil fuels or other carbonaceous materials, and oxyfuels. Reactive absorption of CO2 from the industrial off gases by using chemical solvents is considered as one of the most common, efficient, and cost effective technologies utilized by the industry for CO2 capture. The captured CO2 can be stored by using the geological or oceanic sequestration approaches. As an alternative to geological or oceanic sequestration, the captured CO2 can be re-energized into CO by using solar energy and combined with H2, which can be generated from different methods, to produce syngas. The syngas produced can be further processed to liquid fuels such as methanol, gasoline, jet fuel, etc. via the catalytic Fischer-Tropsch process. In past, a variety of chemical solvents (mostly aqueous amines and there derivatives) have been used for CO2 capture from different gaseous streams via reactive absorption. Though the amines are attractive for the CO2 capture application, there are several disadvantages such as very strong corrosion to equipment and piping, high energy requirement during the stripping of CO2 and they are prone to oxidative and thermal degradation. Recently, use of aqueous potassium carbonate (K2CO3) as a solvent for the absorption of CO2 has gained widespread attention. The usage of K2CO3 has been employed in a number on industries for the removal of CO2 and H2S. Due to its high chemical solubility of CO2, low toxicity and solvent loss, no thermal and oxidative degradation, low heat of absorption, and absence of formation of heat stable salts, K2CO3 seems to be more attractive compared to the conventional amines towards CO2 capture. However, K2CO3 solvent shows slow rate of reaction with CO2 and, consequently, low mass transfer in the liquid phase as compared to the amine solvents. Hence, several investigators are focused towards improving the rate of reaction of CO2 in K2CO3 solvent with the help of different types of promoters. In this paper, the kinetics of absorption of CO2 into an aqueous K2CO3 (20 wt %) promoted by ethylaminoethanol (EAE) solution (hereafter termed as APCE solvent) was studied in a glass stirred cell reactor using a fall in pressure method. Reactive absorption of CO2 in EAE promoted aqueous K2CO3 solution (APCE solvent) was studied at different initial EAE concentrations (0.6 to 2 kmol/m3) and reaction temperatures (303 to 318 K). The reaction between the CO2 and APCE solvent was very well represented by the zwitterion mechanism. The N2O analogy was employed for the determination of H_(CO2) in the APCE solvent. The H_(CO2) was observed to be decreased by 5 and 31% due to the increase in the EAE concentration from 0.6 to 2 kmol/m3 and reaction temperature from 303 to 318 K, respectively. The D_(CO2) in the APCE solvent was also decreased by 21% due to the similar increase in the initial EAE concentration. In contrast, the D_(CO2) increased with the rise in the reaction temperature from 303 to 318 K by a factor of 1.678. The rate of absorption of CO2 in the APCE solvent was observed to increase by 35.10% and 47.59% due to the increase in EAE concentration (0.6 to 2 kmol/m3) and reaction temperature (303 to 318 K). The absorption kinetics was observed to be of overall second order i.e. first order with respect to both CO2 and EAE concentrations, respectively. The rate constant (k_2) for the absorption of CO2 in the APCE solvent was observed to be equal to 45540 m3/kmol√s at 318 K. The temperature dependency of k_2 for the CO2 – APCE solvent system was experimentally determined as: k_2 = (1.214 × [10]^18)√exp(( − 9822.7)/T). Findings of this study indicate EAE as a promising promoter for the aqueous K2CO3 solution.qscienc

Sythhesis and Optimization of Hybrid Membrane Desalination Networks with Value Extraction

Membrane desalination technology has become a valuable advanced water treatment process to purify difficult water sources for potable use. Reverse Osmosis (RO) and Nanofiltration (NF) processes are commonly used desalination technologies. Studies of hybrid RO-NF membrane desalination systems have shown promising benefits of lower power usage, higher overall obtainability, and better water quality. Under the proposed title, a systematic network synthesis approach is to be developed to evaluate the performance of a hybrid membrane desalination plant consisting of NF and RO processes in order to achieve an optimal design network for a given water capacity with ideal operating conditions. This work is done using a superstructure optimization, while taking into account desired process conditions and constraints that are associated with the hybrid RO-NF system. The superstructure captures all the structural and operational options that enable the extraction of a global optimal design, giving a better visualization of the hybrid design network. The optimization problem is formulated while accounting for all the design decisions that are supported by superstructure representation, based on numbers and types of units, flow rates, and pressures.An economic objective function is utilized so as to provide an efficient and desirable configuration capturing all the significant capital and operating costs, such as intake, pre and post treatment, along with the revenue from the value extraction. Optimized designs for hybrid RO-NF desalination plant were illustrated using a case study of sea water desalination with around 35 parts per thousand (ppt) of salinity. The solutions show increased the overall recovery with the addition of an NF membrane into the design

Application of a property-based inherently safety quantification framework for integrating risk assessment into process safety life cycle

Process plant involves different types of risks which need to be managed appropriately to avoid dangerous incidents. Some risks are associated with design decisions such as choice of unit, chemicals or design layout etc. Some are related to the management of proper operating conditions within safely operational limits. It is advantageous to consider the safety aspects and to assess the risks associated with potential hazardous sources from the early stage of process safety life cycle to avoid unfavorable conditions and complexity on the later phase. Process safety metrics provide a good balance between sophisticated quantitative evaluation and simple application. The metrics can be easily adopted, enable comparison between different alternatives and be integrated in optimization for the supply chain. There have been multiple efforts to develop process safety metrics, which are made by both industrial and academic agencies. The concept of inherent safer design is very helpful to reduce the hazardous conditions by safer design principles instead of controlling them by add-on protective systems and procedures. Degree of freedom for the decision for inherently safer process design continuously decreases as life cycle proceeds. Therefore, changing plant design in a later stage will cost more than in the early stage. But the implementing of inherent safer design principles from early stage of design remains challenging due to the lack of proper tool/methodology which can assess the safety performance continuously with the change of mixture properties, operating conditions and even for the unit types. The significant challenges of the problem related to the safety parameters are the possible means to represent the associated results for different scenarios and processes. One safety parameter which is very important to a process may not be the critical issue for others. The scope to identify the key root safety parameters from the historical accidental data base can overcome this limitation. Again, most of the time it is very hard to do the techno-economic analysis simultaneously due to the lack of continuous equations to comply with the whole system's model. In this work, an Inherently Safer Design Tool (i-SDT) is presented for early stage process synthesis to characterize and track the risk associated with different life-cycle phases of industrial processes and products. It also helps to develop characteristic equations for different safety parameters (i.e., flammability, explosiveness, toxicity, etc.) and provides cluster safety parameter score for doing inherent safer design during early stage of design using very limited amount of process information. This property-based inherent safety quantification framework is a tailor made semi-quantitative safety analysis tool which will provide safety assessment in continuous manner to overcome the subjective nature of the existing available safety metric. The proposed safety metric has the flexibility to operate by identifying the major accident-prone units of a process, as well as the major safety and operating parameters. Therefore, in the future it can be embedded to any techno-economic framework to do the cost and safety analysis simultaneously using available materials, design and accidents information. The developed i-SDT tool was used to compare different technologies and variable capacity of ammonia processes to identify the safer alternative in terms of risks associated with the accident-prone unit/section and to highlight the areas of improvement in any existing process using the inherent safer design principles.Scopu

Carbon Capture from Post-Combustion Flue Gas Using a State-Of-The-Art, Anti-Sublimation, Solid–Vapor Separation Unit

This work attempts to address the quest of removing carbon dioxide from flue gas streams to help preserve the environment. It is based on a model that is able to describe the solid-liquid-vapour and solid-vapour phase equilibria for the ternary system of N2-O2-CO2 at pressures from 5 to 130 bar and over a wide range of temperature (140 to 220 K). Furthermore, a corresponding state-of-the art solid-vapor (SV) CO2 capture/separation unit is developed and introduced in this work. The SV unit was modeled using the Aspen Custom Modeler software by implementing the thermodynamic model developed before. It was then simulated using the Aspen Plus simulator; its performance was studied and analyzed. Moreover, the performance of the unit was optimized and compared to the most conventional corresponding technology used by the industry (i.e., amine-scrubbing). Results proved that for the same output clean gas composition, which contains only 0.3% CO2, the developed state-of-the-art SV unit consumes almost half of the energy required by the conventional process. Other advantages of the novel SV separation unit include the lower requirement of capital equipment, no need of additional agents (such as solvents) and the avoidance of product contamination with such additional agents

Bio-methanol production from palm wastes steam gasification with application of CaO for CO2 capture: techno-economic-environmental analysis

The gasification of biomass as a source of energy has gained much attention due to their potential in generating valuable downstream products. In this study, the production of downstream methanol using sorption enhanced steam gasification of palm oil wastes is configured through the Aspen Plus® simulator. The CO2 capture is accomplished by deploying CaO, which is an economically viable technique. For this purpose, the flowsheet configuration for methanol production is evaluated from techno-economic and environmental feasibility perspectives using built-in Aspen Plus techniques considering the impact of three key operating parameters; temperature, steam flowrate and CaO flowrate on methanol production. The results of the economic and environmental assessments demonstrate a reduction in CO2 emissions with respect to the optimum CaO case at 52.7 tonnes CO2-e/h, and in comparison with the base case (90.7 tonnes) and the case without adsorbent regeneration (53.3 tonne) for the Palm kernel shell (PKS) biomass feedstock. Whereas, the reduction in CO2 emissions for empty fruit bunches (EFB) biomass feedstock with respect to optimum CaO case is approximated at 61.8 tonne CO2-e/h, and in comparison with the base case (86.6 tonne CO2-e/h) and the case without adsorbent regeneration (62.6 tonne CO2-e/h). This reduction is also associated with an increase in the capital cost at $120.2 and$119.7 million, and the total annualised cost at $155.4 and$153.1 million of the optimum CaO case for PKS and EFB, respectively. Whereas, $119.1 and$107 million in capital costs with $146 and$139 million in annualised costs are reported for the base case and $118.9 and$117.3 capital costs with $146.7 and$142.3 million annualised costs reported for the case without adsorbent regeneration with respect to PKS and EFB feedstocks, respectively. However, it is also associated with a comparable net profit per methanol production at $201,$132 and $208 million, respectively for the three cases of PKS feedstock, and$170, $130 and$179 million respectively for the three cases of EFB feedstock. The use of CaO and regeneration slightly increases the cost, however, it significantly reduces the CO2 emissions