Outlet Stream Research Articles

Integrating Discharge‐Concentration Dynamics Across Carbon Forms in a Boreal Landscape

AbstractThe flux of terrestrial carbon across land‐water boundaries influences the overall carbon balance of landscapes and the ecology and biogeochemistry of aquatic ecosystems. The local consequences and broader fate of carbon delivered to streams is determined by the overall composition of carbon inputs, including the balance of organic and inorganic forms. Yet, our understanding of how hydrologic fluxes across different land‐water interfaces regulate carbon supply remains poor. We used 7 years of data from three boreal catchments to test how different land‐water interfaces (i.e., forest, wetland, and lake) modulate concentration‐discharge (C‐Q) relationships for dissolved organic carbon (DOC), carbon dioxide (CO2), and methane, as well as the balance among forms (e.g., DOC:CO2). Seasonal patterns in concentrations and C‐Q relationships for individual carbon forms differed across catchments. DOC varied between chemostasis and transport limitation in the forest catchment, between supply limitation and chemostasis in the wetland catchment, and was persistently chemostatic in the lake outlet stream. Carbon gases were supply limited overall, but exhibited chemostasis or transport limitation in the forest and wetland catchments linked to elevated flow in summer and autumn. Unique C‐Q relationships for individual forms reflected the properties of different interfaces and underpinned changes in the composition of lateral carbon supply. Accordingly, DOC dominated the carbon flux during snowmelt, whereas gas evasion increased in relative importance during other times of the year. Integrating the C‐Q dynamics of individual carbon forms provides insight into the shifting composition of lateral export, and thus helps to predict how hydrologic changes may alter the fate of carbon supplied to streams.

Coastal Remote Sensing: Merging Physical, Chemical, and Biological Data as Tailings Drift onto Buffalo Reef, Lake Superior

On the Keweenaw Peninsula of Lake Superior, two stamp mills (Mohawk and Wolverine) discharged 22.7 million metric tonnes (MMT) of tailings (1901–1932) into the coastal zone off the town of Gay. Migrating along the shoreline, ca. 10 MMT of the tailings dammed stream and river outlets, encroached upon wetlands, and contaminated recreational beaches. A nearly equal amount of tailings moved across bay benthic environments into critical commercial fish spawning and rearing grounds. In the middle of the bay, Buffalo Reef is important for commercial and recreational lake trout and lake whitefish production (ca. 32% of the commercial catch in Keweenaw Bay, 22% along southern Lake Superior). Aerial photographs (1938–2016) and five LiDAR and multispectral over-flights (2008–2016) emphasize: (1) the enormous amounts of tailings moving along the beach; and (2) the bathymetric complexities of an equal amount migrating underwater across the shelf. However, remote sensing studies encounter numerous specific challenges in coastal environments. Here, we utilize a combination of elevation data (LiDAR digital elevation/bathymetry models) and in situ studies to generate a series of physical, chemical, and biological geospatial maps. The maps are designed to help assess the impacts of historical mining on Buffalo Reef. Underwater, sand mixtures have complicated multispectral bottom reflectance substrate classifications. An alternative approach, in situ simple particle classification, keying off distinct sand end members: (1) allows calculation of tailings (stamp sand) percentages; (2) aids indirect and direct assays of copper concentrations; and (3) permits determinations of density effects on benthic macro-invertebrates. The geospatial mapping shows how tailings are moving onto Buffalo Reef, the copper concentrations associated with the tailings, and how both strongly influence the density of benthic communities, providing an excellent example for the International Maritime Organization on how mining may influence coastal reefs. We demonstrate that when large amounts of mine tailings are discharged into coastal environments, temporal and spatial impacts are progressive, and strongly influence resident organisms. Next steps are to utilize a combination of hi-resolution LiDAR and sonar surveys, a fish-monitoring array, and neural network analysis to characterize the geometry of cobble fields where fish are successful or unsuccessful at producing young.

Double-Layer Simulated Moving Bed Chromatography for Ternary Separations: Serialized Layer Configurations

Double-layer simulated moving bed chromatography introduced for the complete ternary separation problems utilizes parallel column configurations. The inlet and outlet streams of paired columns need to be properly split and merged to realize parallel operations with the packed bed columns. To make a pair of split streams, at least one flow control unit is additionally required. Therefore, the double-layer simulated moving bed chromatography that consists of six zones with parallelized two columns required at least 10 pumps to control five internal flow splits and five external inlet and outlet flows. In this work, two alternative layer configurations of the double-layer simulated moving bed were introduced to simplify the internal flow patterns. Applying an orthogonal parameter screening method, the design parameters of the double-layer simulated moving bed processes were optimized. The simplified layer configurations were compared with the standard parallel double-layer configuration in terms of process performances and system pressure decrease.

Modelling of a continuous distillation process with finite reflux ratio using the hydrodynamic analogy approach

The hydrodynamic analogy (HA) approach offers an alternative to stage models describing packed distillation columns. So far, HA models have been successfully applied to separation processes, in which the properties of fluid streams entering the packing bed are pre-set as input parameters. However, in a continuous distillation process, the internal fluid streams are coupled via a reboiler and a condenser, thus making the inlet compositions a part of the solution.In the present work, an extension of the HA approach for the description of a continuous distillation process with finite reflux ratio is presented. Equations describing the relationships between the inlet and outlet streams at the column top and bottom are incorporated in the model. Furthermore, changes in compositions and flow rates induced by the feed stream are considered. The model is verified by comparison with experimental data on distillation of a methanol/ethanol/water mixture in a column of 2.3m height and 210mm diameter. The simulated composition profiles are in good agreement with the experiments.

Rigorous NLP distillation models for simultaneous optimization to reduce utility and capital costs

Two non-linear programming (NLP) models with rigorous stage-by-stage MESH calculations are proposed based on the concept of bypass efficiency. The models can be used to simultaneously optimize the number of stages, feed stage location and operating parameters such as the reflux ratio and column pressure. They can also be used for simultaneous flowsheet optimization with distillation columns and heat integration, as demonstrated in a case study. The first model removes an over-specification where the enthalpy of the outlet stream is calculated using an equation-of-state. A degrees of freedom (DOF) analysis shows that the calculation is not required since the enthalpy of the outlet stream is computed from the inlet stream and equilibrium stream and the outlet temperature does not need to be known for subsequent stage calculations. The second model reduces the number of free variables by grouping the bypass efficiencies in a systematic manner. This modification reduces the model size and solution time without sacrificing accuracy or the number of unique solutions. Other than that, the pressure drop equations were improved. The improvement proved to be significant as the original equations caused all stages to be active in a case study, while the same problem was not observed with the new set of pressure drop constraints. Both proposed models had shorter solution times, smaller model size and they yielded minimized objective values 1.5–5.4% lower compared to the original bypass efficiency model. • A modified bypass efficiency model with the removal of enthalpy equations is proposed in this work. • An NLP distillation model with grouped bypass efficiencies to reduce the free variables is presented in this paper. • A new set of pressure drop equations was developed to improve the original set of pressure drop constraints. • The proposed models performed better in terms of convergence, objective values and solution speed in the case studies.

Phase distribution of two-phase refrigerant flow over an impacting horizontal T-junction

Two-phase flows of refrigerants commonly occur in a multitude of systems in the power and process industries, including heat pumps, organic flash cycle,... These flows often have to pass through T-junctions to divide the inlet stream into two outlet streams. Herein, phase maldistribution can occur, meaning that the vapour qualities in the outlet are not equal to the inlet vapour quality. Undesired splitting could lead to unwanted effects, such as to much superheat after evaporation if less liquid phase entered the corresponding exit branch than was expected. Or liquid impact in turbines when to much liquid was allowed to flow to the turbine. Therefore, gaining insight into phase maldisdribution for refrigerants is important to be able to predict the amount of each phase in each exit branch.In literature, data is mostly available for air-water flows and models are built and validated solely on these datasets. The present work extends the air-water data of phase distribution over a horizontal impacting T-junction with data on different refrigerants. For this purpose an experimental setup was developed which can test refrigerant flows with mass flux G up to 700 kg.m−2.s−1 at a saturation temperature between 10 ∘C and 20 ∘C and with a vapour quality x between 0 and 1. In total 551 experiments were performed with four different refrigerants: R32, R134a, R125 and R1234ze.For inlet superficial liquid velocities equal or higher than 0.2m/s it was found that with increasing inlet superficial vapour velocities, the amount of liquid phase flowing to the branch with the lowest mass flow rate decreased. This trend is consistent with literature.A discontinuity in this trend was observed when a flow regime transition occured. For the refrigerant R32 and an inlet superficial liquid velocity equal or lower than 0.1 m/s, the liquid phase followed an opposite trend by preferring the branch with the highest mass flow rate.The models from literature do not predict the refrigerant data with the necessary accuracy. They only work for specific refrigerants and for inlet flow regimes similar to the flow regimes of the air-water data used to construct the model. For this reason, the provided work also presents a new phase distribution model created upon the data gathered.

High-temperature sorption of sodium vapors in typical outlet streams from biomass gasifiers

High-temperature sorption of sodium vapors in typical outlet streams from biomass gasifiers

Effects of source digital elevation models in assessment of gross runoff-river hydropower potential: A case study of West Rapti Basin, Nepal

Advancements in Geographical Information System (GIS), Remote Sensing (RS) technology, hydrologic modeling and availability of wider coverage hydrometeorological data have facilitated the use of GIS and hydrological modelling tools in studies related to hydropower potential. Digital Elevation Model (DEM) is the primary data required for these tools. They have become more accessible and many are freely available. These DEMs have different resolution and their errors vary due to their primary data acquisition techniques and processing methods. However, their effects on the hydropower potential assessment are less investigated. This study evaluates the effects of 6 freely available DEMs: ALOS 12.5 m, SRTM 90 m, SRTM 30 m, ASTER G-DEM version-3 30 m, AW3D 30 m and Cartosat-1 version-3 30 m on the Gross Run-off-River Hydropower Potential (GRHP) assessment, using GIS and hydrological modelling tools. West Rapti River (WRR) basin in Nepal was chosen for the case study.
 Soil and Water Tool (SWAT) hydrological model, coupled with GIS was used to discretize the WRR basin into several sub-basins/streams. Flow at the inlet and outlet of streams were estimated from the SWAT model whereas the topographic head was extracted from the DEMs. The GRHP of the streams were computed using the estimated stream flow and the topographic head for flows at 40% to 60% Probability of Exceedance (PoE). The total potential of the basin was computed by summing up the potential of all streams. The GRHP of WRR basin for flows at 40% PoE was estimated as 512 MW for ALOS 12.5 m resolution DEM, referred as a base case in this study. The GRHP estimated from the remaining DEMs showed the variation of less than 6% compared to the base case. The topographic head was found to be sensitive with respect to the DEM resolution and the highest variations were observed in the main river channels.

Investigation of flux stability and fouling mechanism during simultaneous treatment of different produced water streams using forward osmosis and membrane distillation

Forward osmosis-membrane distillation (FO-MD) hybrids were recently found suitable for produced water treatment. Exclusion of synthetic chemical draw solutions, typically used for FO, can reduce FO-MD operational costs and ease its onsite application. This study experimentally validates a novel concept for the simultaneous treatment of different produced water streams available at the same industrial site using an FO-MD hybrid system. The water oil separator outlet (WO) stream was selected as FO draw solution and it generated average fluxes ranging between 8.30 LMH and 26.78 LMH with four different feed streams. FO fluxes were found to be governed by the complex composition of the feed streams. On the other hand, with WO stream as MD feed, an average flux of 14.41 LMH was achieved. Calcium ions were found as a main reason for MD flux decline in the form of CaSO4 scaling and stimulating the interaction between the membrane and humic acid molecules to form scale layer causing reduction in heat transfer and decline in MD flux (6%). Emulsified oil solution was responsible for partial pore clogging resulting in further 2% flux decline. Ethylenediaminetetraaceticacid (EDTA) was able to mask a portion of calcium ions and resulted in a complete recovery of the original MD flux. Under hybrid FO-MD experiments MD fluxes between 5.62 LMH and 11.12 LMH were achieved. Therefore, the novel concept is validated to produce fairly stable FO and MD fluxes, with few streams, without severe fouling and producing excellent product water quality.

An improved vacuum pressure swing adsorption process with the simulated moving bed operation mode for CH4/N2 separation to produce high-purity methane

Methane is a clean fossil fuel and an important greenhouse gas, so it is more significant to recover methane from massive resources of unconventional gas. Because of the similar physicochemical properties of methane and nitrogen, it is difficult to obtain the high-purity methane from the low-grade methane gas with nitrogen mixture by the conventional vacuum pressure swing adsorption (VPSA) process. In this work, this process was improved, where multicolumn in series operation was adopted at both adsorption and displacement steps to enhance the CH4/N2 separation, and one column went on blowdown, purge, and pressurization steps for the effective regeneration of the adsorbent. In order to run the improved VPSA process automaticly, the SMB operation mode was introduced, synchronously shifting the inlet and outlet stream ports from one column to other column along the gas flow direction, and a countercurrent contact between the gas phase and adsorbent phase in the multicolumn system was formed to enhance the CH4/N2 separation. To verify the feasibility of the improved VPSA process, the experimental device with eight-column unit had been set up in laboratory, and 30% ~ 50% CH4 gases were denitrified by the improved VPSA process using activated carbon beads. The experimental results demonstrated that the improved VPSA process was capable of producing a high-purity CH4 product gas (99.99% CH4) meeting pipeline grid specification and a high-concentration N2 by-product gas meeting emission standards from 30% ~ 50% CH4 feed gases. In the end, we compared the CH4/N2 separation performance among the conventional VPSA process, dual reflux-pressure swing adsorption process, improved VPSA process with SMB operation mode, CO2 displacement VPSA process and concentration temperature swing adsorption process.

Forecasting Abrupt Depletion of Dissolved Oxygen in Urban Streams Using Discontinuously Measured Hourly Time‐Series Data

AbstractDepletion of dissolved oxygen (DO) is a major cause of fish kills in urban streams. Although forecasting short‐term DO concentrations in streams prior to hypoxic events is necessary, such efforts have been rarely made. In this study, 24‐h forecasting models were developed for DO concentrations in three urban streams of South Korea. To forecast the DO concentrations at the outlet sites, which coincide with fish kill hot spot areas, water quality parameters at the lower reaches and hydrometeorological parameters were used as input variables. The monitoring data were measured hourly between 2017 and 2018 and divided into training and test sets at a ratio of 8:2. Tenfold cross validation was performed for hyperparameter optimization. Due to the dynamic characteristics of DO concentrations and the discontinuity in time‐series data, a long short‐term memory (LSTM) neural network modeling approach was selected. Overall, a high degree of accuracy was recorded for all study streams. Although hypoxic events were forecast with lower accuracy, the timing and magnitude of abrupt DO depletion were well captured. Water temperature and DO concentrations at the lower reaches and 24‐h cumulative precipitation were important variables for forecasting DO concentrations at all stream outlets. In particular, the importance of cumulative precipitation across all streams indicated that the effects of nonpoint sources were critical in depleting DO in urban streams. Monitoring of both lower reaches and outlets in conjunction with a variable importance analysis enhanced interpretability of the LSTM model outputs. This study improves our understanding of precursors of hypoxic events in urban streams.

Analysis of water quality indices and machine learning techniques for rating water pollution: a case study of Rawal Dam, Pakistan

Abstract Water Quality Index (WQI) is a unique and effective rating technique for assessing the quality of water. Nevertheless, most of the indices are not applicable to all water types as these are dependent on core physico-chemical water parameters that can make them biased and sensitive towards specific attributes including: (i) time, location and frequency for data sampling; (ii) number, variety and weights allocation of parameters. Therefore, there is a need to evaluate these indices to eliminate uncertainties that make them unpredictable and which may lead to manipulation of the water quality classes. The present study calculated five WQIs for two temporal periods: (i) June to December 2019 obtained in real time (using the Internet of Things (IoT) nodes) at inlet and outlet streams of Rawal Dam; (ii) 2012–2019 obtained from the Rawal Dam Water Filtration Plant, collected through GIS-based grab sampling. The computed WQIs categorized the collected datasets as ‘Very Poor’, primarily owing to the uneven distribution of the water samples that has led to class imbalance in the data. Additionally, this study investigates the classification of water quality using machine learning algorithms namely: Decision Tree (DT), k-Nearest Neighbor (KNN), Logistic Regression (LogR), Multilayer Perceptron (MLP) and Naive Bayes (NB); based on the parameters including: pH, dissolved oxygen, conductivity, turbidity, fecal coliform and temperature. The classification results showed that the DT algorithm outperformed other models with a classification accuracy of 99%. Although WQI is a popular method used to assess the water quality, there is a need to address the uncertainties and biases introduced by the limitations of data acquisition (such as specific location/area, type and number of parameters or water type) leading to class imbalance. This can be achieved by developing a more refined index that considers various other factors such as topographical and hydrological parameters with spatial temporal variations combined machine learning techniques to effectively contribute in estimation of water quality for all regions.

Optimizing the energy recovery section in thermal desalination systems for improved thermodynamic, economic, and environmental performance

Integration of energy recovery section with thermal desalination systems improves their performance from thermodynamics, economics, and environmental viewpoints. This is because it significantly reduces input energy, heat transfer area, and capital cost requirements. Above all, the system outlet streams can achieve thermal equilibrium with the environment by supplying heat for useful preheating purposes thus reducing the environmental impacts. The plate heat exchangers are generally employed for this purpose as preheaters. The current paper presents a comprehensive investigation and optimization of these heat exchangers for thermal desalination systems applications. An experimentally validated numerical model employing Normalized Sensitivity Analysis and Genetic Algorithm based cost optimization is developed to investigate their performance at assorted operating conditions. The analysis showed that the heat transfer coefficient, pressure drop, and outlet water cost were improved by an increase in feed flow rate. However, with an increased flow rate, the comprehensive output parameter (h/ΔP) decreased due to the high degree increase in pressure drop. Moreover, an increase in the chevron angle reduced the heat transfer coefficient, pressure drop, and water cost. Finally, the optimization lowered the heat transfer area by ~79.5%, capital investment by ~62%, and the outlet cost of the cold stream by ~15.7%. The operational cost is increased due to the increased pressure drop but the overall impact is beneficial as Ctotal of equipment is reduced by ~52.7%.

Investigating the Performance of CO Boiler Burners in the RFCC Unit with CFD Simulation

The combustion chamber's internal refractory in Imam Khomeini Oil Refinery Company (IKORC) was damaged in several parts, requiring operating conditions and re-inspecting the design of the combustion chamber using CFD. Simplify the combustion chamber 3D simulation, decrease in the number of calculations, the symmetry principle was applied in the simulation. The results, independent of the mesh network, were investigated via increasing the mesh nodes. The one-stage, two-stage, multi-stage and overall mechanisms, which were designated, were examined and compared to actual measured data and a calculation error of less than 8% was obtained. Ultimately, selecting overall mechanisms, the simulation results, streams mixing and length of the chamber were scrutinized, and as a result, the current design was approved. The temperature and velocity of the flows in the combustion chamber were investigated. In the combustion chamber, the farther we are from the burners, the more uniform the velocity and temperature profiles also become as the wall temperature increases. The rate of combustion reaction was evaluated with the temperature of different points in the combustion chamber. The results showed that the combustion chamber wall's temperature is in the appropriate range and has not suffered any thermal damage. Unlike the combustion chamber wall, the burner wall (at the mixing point) has an unauthorized temperature; there is the possibility of thermal damage that can be eliminated by changing the number of currents. Unsuitable thermal profiles also showed large amounts of oxygen in the exhaust gas indicated that the steam boiler performance is far from the optimal condition and specific changes would be required in the air streams. Streamline demonstrated that the primary air stream was more effective for decreasing CO and NOX amounts in the outlet stream. The secondary air stream was also significant to prevent thermal damage to the internal coating and reduce safety hazards.

Modelling of desiccant wheels using radial basis neural networks

The desiccant wheel based air conditioning systems are superior over conventional vapour compression systems in terms of the efficiency and power consumption. Researchers are consistently focusing on the various aspects of the desiccant wheel such as the architecture of the wheel, effect of operating parameters on the performance of the wheel and the overall configuration of air-conditioning systems. For the simulations of the air-conditioning systems it is essential to have an accurately performing model of the desiccant wheel. Thus, for solving this purpose, the radial basis neural network is applied to forecast the performance of a desiccant wheel data. The input parameters are the inlet process air humidity, temperature, regeneration temperature, number of rotations per hour of the desiccant wheel and the ratio of the volume flow rates of the process air and the regeneration air. The output parameters are the temperature and humidity of the process air outlet stream. The model is able to predict the original data within ± 5% accuracy and the r-square value is obtained to be 0.9963. A parametric study presenting the variations of the process air outlet temperature and humidity with respect to the various input parameters is also included in the article.

Investigating tertiary amine alkylation/benzylation kinetics with ramp-flow in a plug-flow reactor using in-line [formula omitted]H NMR spectroscopy

Quaternary ammonium salts are readily utilised within the chemical industry as, e.g., phase-transfer catalysts and anti-microbials, and their annual production capacity exceeds 1 million tonnes. These surfactants are conventionally produced in batch Menshutkin reactions from tertiary amines and an alkyl halide. With an incentive to move towards a more efficient continuous process, a better understanding of its kinetics is paramount. This paper explores a novel method to determine kinetic parameters, by introducing a linear flow ramp, combined with in-line Proton Nuclear Magnetic Resonance (1H NMR) analytics.Batch reactions between N,N-dimethyldecylamine (DMDA) and benzyl chloride (BnCl) have been performed in various solvents to examine solvent effects, and to validate the ramp-flow method. 1H NMR spectrometry showed that acetonitrile had the highest reaction rate, while methanol (MeOH) was deemed to have the best overall potential with regards to process intensification and product separation.Kinetic data was also obtained in a Plug-Flow Reactor (PFR) subjected to ramp-flow, under continuous measurement of the outlet stream composition. Between 20 and 70 °C, DMDA quaternisation rates were determined in MeOH, using both BnCl and methyl iodide reactants. This resulted in the successful elucidation of the respective Arrhenius parameters.Furthermore, the data from the ramp-flow method has been compared with the data obtained in batch, and in the PFR under conventional steady-state conditions. In general, all three methods were in good agreement, and it was concluded that the proposed method is valid. This method can thus provide a more efficient way to determine highly accurate kinetic parameters.

Continuous Mixing Technology: Characterization of a Vertical Mixer Using Residence Time Distribution.

Continuous powder mixing technology (CMT) application during continuous direct compression has emerged as a leading technology used in the development and manufacture of solid oral dosage forms. The critical quality attributes of the final product are heavily dependent on the performance of the mixing step as the quality of mixing directly influences the drug product quality attributes. This study investigates the impact of blend material properties (bulk density, API particle size distribution) and process parameters (process throughput, hold up mass and impeller speed) on the mixing performance. Mixing of the blend was characterized using the Residence Time Distribution (RTD) of the process by trending the outlet stream of the mixer using a near-infrared (NIR) probe after the injection of a small mass of tracer at the inlet stream. The outcomes of this study show that the RTDs of the mixer with throughput ranging between 15 and 30kg/h; impeller speed ranging between 400 and 600rpm and hold up mass (HUM) ranging between 500 and 850g can be described by a series of two ideal Continuous Stirred Tank Reactors (CSTRs) with different volumes, and correspondingly, different mean residence times. It is also observed that the mixing is mainly occurring in the lower chamber of the CMT and the normalized RTDs of the mixer are similar across the range of process conditions and material attributes studied. The results also showed that the formulation blend with different API particle sizes and bulk properties, like bulk density and flowability, provide insignificant impact on the mixing performance. The CMT allows independent selection of target set points for HUM, impeller rotational speed and line throughput and it shows great robustness and flexibility for continuous blending in solid oral dose manufacturing.

Validation of the Molar Flow Rates of Oil and Gas in Three-Phase Separators Using Aspen Hysys

A three-phase separator is the first vessel encountered by well fluids. The application of separators has been of great value to the oil and gas industry. In order to generate the gas phase envelope that is applicable to the study of reservoir fluid and the selection of optimum operating conditions of separators, this research utilizes a specified reservoir fluid stream to simulate a three-phase separator executed in Aspen HYSYS. Subsequently, a comparative study of the effects of specified inlet operating conditions on the output of gas and oil streams was carried out. The results show that changing the inlet pressure of the separator from 1000 to 8000 kPa reduces the gas outlet flow from 1213 to 908.6 kg mol/h, while it increases the liquid flow rate from 374 to 838.0 kg mole/h. By changing the temperature of the separator feed stream from 13 to 83 °C, the gas outlet stream was raised from 707.4 to 1111 kg mol/h, while the liquid flow rate dropped from 1037.0 to 646.1 kg mol/h. It was observed that the concentration of the outlet methane product is not affected by changing the flow rate of the feed stream at a specific pressure and temperature. Therefore, the thermodynamic property method is appropriate to simulate the separation of reservoir fluids which was achieved by selecting the Peng–Robinson (PR) model. The operating conditions of the separator were at 8000 kPa and 43 °C, which lies right on the dew point line. This is comparable to similar work on CHEMCAD which was in turn validated by plant data. Thus, the gas flow rate and the oil flow rate were dependent on pressure and temperature conditions of the plant.

Environmental and Exergetic Analysis of Large-Scale Production of Citric Acid-Coated Magnetite Nanoparticles via Computer-Aided Process Engineering Tools.

Considering that functional magnetite (Fe3O4) nanoparticles with exceptional physicochemical properties can be highly applicable in different fields, scaling-up strategies are becoming important for their large-scale production. This study reports simulations of scaled-up production of citric acid-coated magnetite nanoparticles (Fe3O4-cit), aiming to evaluate the potential environmental impacts (PEIs) and the exergetic efficiency. The simulations were performed using the waste reduction algorithm and the Aspen Plus software. PEI and energy/exergy performance are calculated and quantified. The inlet and outlet streams are estimated by expanding the mass and energy flow, setting operating parameters of processing units, and defining a thermodynamic model for properties estimation. The high environmental performance of the production process is attributed to the low outlet rate of PEI compared to the inlet rate. The product streams generate low PEI contribution (−3.2 × 103 PEI/y) because of the generation of environmentally friendlier substances. The highest results in human toxicity potential (3.2 × 103 PEI/y), terrestrial toxicity potential (3.2 × 103 PEI/y), and photochemical oxidation potential (2.6 × 104 PEI/y) are attributed to the ethanol within the waste streams. The energy source contribution is considerably low with 27 PEI/y in the acidification potential ascribed to the elevated levels of hydrogen ions into the atmosphere. The global exergy of 1.38% is attributed to the high irreversibilities (1.7 × 105 MJ/h) in the separation stage, especially, to the centrifuge CF-2 (5.07%). The sensitivity analysis establishes that the global exergy efficiency increases when the performance of the centrifuge CF-2 is improved, suggesting to address enhancements toward low disposal of ethanol in the wastewater.

Catalytic performance of Na-Mn2O3-based catalysts towards oxidative coupling of methane

Various active materials (NaCl and Na2WO4 doped on Mn2O3) and supports (SiC, SiO2, WO4, CoO, La2O3, Ce2O3, ZnO, Al2O3, Cr2O3, La0.3Sr0.7Cr0.7Fe0.3O3-δ (LSCF), and clinker) were prepared and tested for use in the OCM reaction in a packed-bed reactor. NaCl-Mn2O3/SiO2 showed the best performance among the catalysts, with 37.5 % methane conversion, 60.5 % C2 selectivity, and 22.7 C2 yield at an optimum temperature of 750 °C under atmospheric pressure. The ethylene-to-ethane ratio of NaCl-Mn2O3/SiO2 (7.5) was found to be the highest, and higher than that of Na2WO4-Mn2O3/SiO2 (1.4), possibly due to its high basicity. Na2WO4-Mn2O3/SiO2 showed good catalytic stability during 12 h time-on-stream experiment whereas slight deactivation was observed in NaCl-Mn2O3/SiO2 due to the decomposition of NaCl, evidenced from traces of gaseous chloride compounds such as CH3CH2Cl, CH3Cl, and Cl2 in the outlet stream. However, the degree of deactivation was found to be more severe when (1) level of NaCl was lower (from 60 % to 10 %) and (2) time-on-stream experiment was tested for the longer period of time (12 h–62 h). The loss of chloride was estimated at 57 and 69 % (by weight) after 12 and 62 h TOS, respectively. The results were in good agreement with information received from XRD where Na2SiO3 was observed due to the loss of chloride, when the deactivation was extreme. From O2-TPSR result, Na2WO4-Mn2O3/SiO2 showed no coke deposition, which could be the result of the high surface oxygen (Os) contained in Na2WO4. Carbon formation at 56.36 μmol/g.hr was detected when using NaCl-Mn2O3/SiO2 as catalyst. The solid-gas mechanism of the catalytic OCM reaction was predicted using the CH4-TPSR technique.