scholarly journals Multivariate statistical optimization of the ethanol fuel dehydration process using ionic liquids

2020 ◽  
pp. 35-35
Author(s):  
Cláudia Cavalcanti ◽  
João Queiroz ◽  
Luiz Stragevitch ◽  
de Rodrigues ◽  
Maria Pimentel
Keyword(s):  
Ionic Liquids ◽  
Energy Consumption ◽  
Ethylene Glycol ◽  
Energy Use ◽  
Desirability Function ◽  
Extractive Distillation ◽  
Statistical Technique ◽  
Dehydration Process ◽  
Ethanol Fuel ◽  
Multivariate Statistical

In this work, the ethanol fuel dehydration process was optimized using the Aspen Plus? simulator and a multivariate statistical technique based on the desirability function. The suitability of the ionic liquids 1-methylimidazolium chloride ([Mim][Cl]), 1-ethyl-3-methylimidazolium chloride ([Emim][Cl]), 1-butyl-3-methylimidazolium chloride ([Bmim][Cl]) and 1-hexyl-3-methylimidazolium chloride ([Hmim][Cl]), as extractive distillation entrainers, was also evaluated and compared to the conventional solvents, ethylene glycol and cyclohexane. Among the solvents studied, [Mim][Cl] required the lowest energy consumption, about 8% less energy use when compared to the optimized process using ethylene glycol. The multivariate statistical techniques employed were effective in the optimization of the extractive distillation processes as the process energy consumption could be minimized while achieving ethanol purity in agreement with the current specifications as well as obtaining a high solvent recovery. With the desirability approach it was possible to improve the process performance with little or no modification of existing processing plants.

scholarly journals Effect of ionic liquids as entrainers on the dynamic behavior of ethanol-water extractive columns

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Nelly Ramírez-Corona ◽  
Andrés Schramm-Flores ◽  
Sofía Reyes-Lombardo ◽  
Arturo Jiménez-Gutiérrez
Keyword(s):  
Ionic Liquids ◽  
Extractive Distillation ◽  
Dynamic Responses ◽  
Dehydration Process ◽  
Ethanol Dehydration ◽  
Feed Mixture ◽  
Industrial Implementation ◽  
Lack Of Information ◽  
Azeotropic Mixtures ◽  
Product Stream

AbstractIonic liquids (ILs) have been recently considered as potential entrainers for extractive distillation. The use of ILs may affect the vapor-liquid properties to aid the separation of azeotropic mixtures. In particular, their effectiveness has been observed for ethanol dehydration, showing promising perspectives for their industrial implementation. However, there is still a lack of information about the effect of ILs on the system controllability. The objective of this work is to explore the dynamic implications of the use of two types of ionic liquids on the ethanol dehydration process. An equimolar feed mixture of ethanol and water was considered, and different IL concentrations were tested. The results show that changing the IL concentration affect the degree of stabilization of the product stream, even when smooth dynamic responses were in many cases observed.

scholarly journals Evaluation of Ionic Liquids as In Situ Extraction Agents during the Alcoholic Fermentation of Carob Pod Extracts

Fermentation ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 90 ◽  
Author(s):  
Sergio Sanchez-Segado ◽  
María José Salar-García ◽  
Víctor Manuel Ortiz-Martínez ◽  
Antonia Pérez de los Ríos ◽  
Francisco José Hernández-Fernández ◽  
...  
Keyword(s):  
Ionic Liquids ◽  
Energy Consumption ◽  
Molecular Sieves ◽  
Alcoholic Fermentation ◽  
Current System ◽  
Extractive Distillation ◽  
High Energy ◽  
Anhydrous Ethanol ◽  
Carbohydrate Source ◽  
Promising Alternative

Anhydrous ethanol is a promising alternative to gasoline in fuel engines. However, since ethanol forms an azeotrope with water, high-energy-consumption separation techniques such as azeotropic distillation, extractive distillation, and molecular sieves are needed to produce anhydrous ethanol. This work discusses the potential development of an integrated process for bioethanol production using ionic liquids and Ceratonia siliqua as a carbohydrate source for further fermentation of the aqueous extracts. A four-stage counter-current system was designed to improve the sugar extraction yield to values close to 99%. The alcoholic fermentation of the extracts showed ethanol concentrations of 95 g/L using the microorganism Saccharomyces cerevisae. The production of anhydrous ethanol through extractive distillation with ethylene glycol was simulated using CHEMCAD software, with an energy consumption of 13.23 MJ/Kg of anhydrous ethanol. Finally, several ionic liquids were analyzed and are proposed as potential solvents for the recovery of bioethanol for the design of an integrated extraction–fermentation–separation process, according to their ability to extract ethanol from aqueous solutions and their biocompatibility with the microorganism used in this study.

scholarly journals High-Throughput Computational Screening of Ionic Liquids for Butadiene and Butene Separation

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 165
Author(s):  
Hao Qin ◽  
Zihao Wang ◽  
Zhen Song ◽  
Xiang Zhang ◽  
Teng Zhou
Keyword(s):  
Ionic Liquids ◽  
Energy Consumption ◽  
High Throughput ◽  
Physical Property ◽  
Extractive Distillation ◽  
High Energy ◽  
Molecular Structures ◽  
Boiling Points ◽  
Computational Screening ◽  
Potential Alternative

The separation of 1,3-butadiene (1,3-C4H6) and 1-butene (n-C4H8) is quite challenging due to their close boiling points and similar molecular structures. Extractive distillation (ED) is widely regarded as a promising approach for such a separation task. For ED processes, the selection of suitable entrainer is of central importance. Traditional ED processes using organic solvents suffer from high energy consumption. To tackle this issue, the utilization of ionic liquids (ILs) can serve as a potential alternative. In this work, a high-throughput computational screening of ILs is performed to find proper entrainers, where 36,260 IL candidates comprising of 370 cations and 98 anions are involved. COSMO-RS is employed to calculate the infinite dilution extractive capacity and selectivity of the 36,260 ILs. In doing so, the ILs that satisfy the prespecified thermodynamic criteria and physical property constraints are identified. After the screening, the resulting IL candidates are sent for rigorous process simulation and design. 1,2,3,4,5-pentamethylimidazolium methylcarbonate is found to be the optimal IL solvent. Compared with the benchmark ED process where the organic solvent N-methyl-2-pyrrolidone is adopted, the energy consumption is reduced by 26%. As a result, this work offers a new IL-based ED process for efficient 1,3-C4H6 production.

scholarly journals Controlling surface chemistry and mechanical properties of metal ionogels through Lewis acidity and basicity

2021 ◽  
Vol 9 (8) ◽  
pp. 4679-4686
Author(s):  
Coby J. Clarke ◽  
Richard P. Matthews ◽  
Alex P. S. Brogan ◽  
Jason P. Hallett
Keyword(s):  
Mechanical Properties ◽  
Ionic Liquids ◽  
Ethylene Glycol ◽  
Surface Chemistry ◽  
Lewis Acidity ◽  
Metal Species ◽  
Poly Ethylene Glycol ◽  
Acidity And Basicity ◽  
Poly Ethylene

Gels prepared from metal containing ionic liquids with cross-linked poly(ethylene glycol) have surface compositions and mechanical properties that can be controlled by Lewis basicity and acidity of the metal species.

scholarly journals Evaluation of CO2 emissions and energy use with different container terminal layouts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Muhammad Arif Budiyanto ◽  
Muhammad Hanzalah Huzaifi ◽  
Simon Juanda Sirait ◽  
Putu Hangga Nan Prayoga
Keyword(s):  
Energy Efficiency ◽  
Sustainable Development ◽  
Energy Consumption ◽  
Statistical Analysis ◽  
Energy Use ◽  
Container Terminal ◽  
Container Terminals ◽  
Future Planning ◽  
Container Handling

AbstractSustainable development of container terminals is based on energy efficiency and reduction in CO2 emissions. This study estimated the energy consumption and CO2 emissions in container terminals according to their layouts. Energy consumption was calculated based on utility data as well as fuel and electricity consumptions for each container-handling equipment in the container terminal. CO2 emissions were estimated using movement modality based on the number of movements of and distance travelled by each container-handling equipment. A case study involving two types of container terminal layouts i.e. parallel and perpendicular layouts, was conducted. The contributions of each container-handling equipment to the energy consumption and CO2 emissions were estimated and evaluated using statistical analysis. The results of the case study indicated that on the CO2 emissions in parallel and perpendicular layouts were relatively similar (within the range of 16–19 kg/TEUs). These results indicate that both parallel and perpendicular layouts are suitable for future ports based on sustainable development. The results can also be used for future planning of operating patterns and layout selection in container terminals.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

scholarly journals A Decomposition Analysis of the Korean Manufacturing Sector: Monetary vs. Physical Outputs

2021 ◽  
Vol 13 (11) ◽  
pp. 6192
Author(s):  
Junghwan Lee ◽  
Jinsoo Kim
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Driving Forces ◽  
Manufacturing Sector ◽  
Decomposition Analysis ◽  
Primary Energy ◽  
Intensity Effect ◽  
Activity Effect ◽  
Index Decomposition ◽  
Output Indicator

This study analyzes the changes in energy consumption of the Korean manufacturing sector using the index decomposition analysis (IDA) method. To capture the production effect based on actual physical activities, we applied the activity revaluation (AR) approach in the analysis. We also developed energy consumption data in terms of primary energy supply to consider conversion loss in the energy sector to avoid any distortions in the intensity effect. The analysis covers every manufacturing subsector in Korea over the period between 2006 and 2018. Combining two distinctive approaches from the previous literature, the AR approach and primary energy-based analysis gives us helpful findings for a climate policy. First, the overall activity effect estimated from the physical output indicator is lower than that from the monetary output indicator. The monetary indicator shows that the share of energy-intensive industries decreases, whereas the physical indicator shows the opposite. Second, in terms of energy efficiency, the intensity effect is estimated as an increasing factor of energy use, whereas inversed results are shown when we use the monetary indicator. Lastly, unlike the previous studies, the AR approach results indicate that Korean manufacturing sectors have been shifting toward an energy-intensive, so it is hard to anticipate positive intensity effects, which means decreasing energy consumption factor, for a while. These results support why analyzing the driving forces of energy consumption through the AR approach and primary energy base is highly recommended.

scholarly journals Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3864
Author(s):  
Qiucheng Li ◽  
Jiang Hu ◽  
Bolin Yu
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Decomposition Analysis ◽  
Theil Index ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Index Method ◽  
Inequality Measures ◽  
Influencing Mechanism ◽  
Per Capita

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces’ URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China’s policymakers.

scholarly journals Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4046 ◽  
Author(s):  
Sooyoun Cho ◽  
Jeehang Lee ◽  
Jumi Baek ◽  
Gi-Seok Kim ◽  
Seung-Bok Leigh
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Simulation Analysis ◽  
Residential Buildings ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Building Energy ◽  
Major Effect ◽  
Measuring Instruments ◽  
Building Energy Consumption

Although the latest energy-efficient buildings use a large number of sensors and measuring instruments to predict consumption more accurately, it is generally not possible to identify which data are the most valuable or key for analysis among the tens of thousands of data points. This study selected the electric energy as a subset of total building energy consumption because it accounts for more than 65% of the total building energy consumption, and identified the variables that contribute to electric energy use. However, this study aimed to confirm data from a building using clustering in machine learning, instead of a calculation method from engineering simulation, to examine the variables that were identified and determine whether these variables had a strong correlation with energy consumption. Three different methods confirmed that the major variables related to electric energy consumption were significant. This research has significance because it was able to identify the factors in electric energy, accounting for more than half of the total building energy consumption, that had a major effect on energy consumption and revealed that these key variables alone, not the default values of many different items in simulation analysis, can ensure the reliable prediction of energy consumption.

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