Recirculation Ratio Research Articles

Comparison and analysis of heat exchange and off-gas recycle strategies in tri-reforming-SOFC system

Integrating tri-reforming into SOFC system can convert fuels flexibly and reduce carbon emissions. The tri-reformer-SOFC system requires heat management to reduce energy consumption and to average temperature profiles. In this paper, four system configurations were built with two gas recirculation strategies (anode off gas recycling and burner off-gas recycling) and two reformer types (with heat exchange and oxygen injections). 1-D spatial distributions in the reformer/SOFC and the effect of recirculation ratio (RR) are explored. It is found that the two recirculation strategies can enhance the system electric efficiency due to the recycled fuel and heat, and the two reformers can both average the temperature profiles. Among the four configurations, configuration A exhibits the best performance, and higher RR increases the system electric efficiency, decreases the max temperature gradient in the SOFC and decreases the system global efficiency slightly. This work proposes novel strategies for SOFC system and provides important data for practice.

Numerical Study of Critical Recirculation Ratio for Achieving Unconditional MILD Combustion

Moderate or Intense Low Oxygen Dilution (MILD) combustion is a regime in which fuels burn in a distributed reaction zone generating ultra-low emissions and no visible flame front. Also known as flameless combustion, it can be achieved by recirculating flue gases into the reaction zone. A recirculation factor based on the mass recirculated is used to characterize a flameless regime. However, the original definition of MILD is based on the temperature levels of a reactor. This work connects both criteria by introducing a parameter called recirculation ratio derived theoretically from a mass balance. The ratio was numerically calculated by simulating a network of perfectly stirred reactors and performing an energy balance using open-source software. This methodology was validated against experimental and simulated data from the literature. Simulations were carried out for methane, ethane, propane, and hydrogen under adiabatic conditions and equivalence ratios from 0.6 to 1. Results indicate that a critical recirculation ratio is required for establishing unconditional MILD combustion, which changes with fuel type and equivalence ratio. In all cases studied, the critical ratio diminishes as the equivalence ratio is reduced. Hydrogen and methane require the highest and lowest critical ratio, respectively. Results suggest that externally diluting hydrogen with carbon dioxide could potentially reduce recirculation requirements for MILD combustion.

Multivariate optimization of characteristic parameters of continuous-flow system with a front buffer tank for industrial reverse osmosis concentrate treatment

Industrial reverse osmosis concentrate (ROC) was electrochemically oxidized using a continuous-flow system (CFS) with a front buffer tank. Multivariate optimization including Plackett-Burman (PBD) and central composite design based on response surface method (CCD-RSM) was implemented to investigate the effects of characteristic (e.g., recirculation ratio (R value), ratio of buffer tank and electrolytic zone (RV value)) and routine (e.g., current density (i), inflow linear velocity (v) and electrode spacing (d)) parameters. R, v values and current density significantly influenced chemical oxygen demand (COD) and NH4+−N removal and effluent active chlorine species (ACS) level, while electrode spacing and RV value had negligible effects. High chloride content of industrial ROC facilitated the generation of ACS and subsequent mass transfer, low hydraulic retention time (HRT) of electrolytic cell improved the mass transfer efficiency, and high HRT of buffer tank prolonged the reaction between the pollutants and oxidants. The significance levels of COD removal, energy efficiency, effluent ACS level and toxic byproduct level CCD-RSM models were validated by statistical test results, including higher F value than critical effect value, lower P value than 0.05, low deviation between predicted and observed values, and normal distribution of calculated residuals. The highest pollutant removal was achieved at a high R value, a high current density and a low v value; the highest energy efficiency was achieved at a high R, a low current density and a high v value; the lowest effluent ACS and toxic byproduct levels were achieved at a low R value, a low current density and a high v value. Following the multivariate optimization, the optimum parameters were decided to be v = 1.2 cm h−1, i ≥ 8 mA cm−2, d ≥ 4, RV = 10−20 and R = 1 to achieve better effluent quality (i.e., lower effluent pollutant, ACS and toxic byproduct levels).

Improvement of the SOFC System by Anode Recirculation

Solid Oxide Fuel Cells (SOFCs) provides an efficient and clean pathway to generate electricity. In this study, two system configurations with anode off-gas recirculation are introduced, and corresponding process models are developed using MATLAB. The study examines the effects of two key parameters, namely system methane utilization and recirculation ratio, on system characteristics, based on the typical performance of a 30-cell stack. Suitable operating parameter ranges are selected for both system configurations, and their respective characteristics are compared. The results demonstrate that D#1 system configuration improves system fuel utilization from 76.6% to 83.0% without altering the operating conditions of the stack. D#2 system configuration achieves a fuel utilization of 88.6%. The results indicate the potential for further enhancing the electrical efficiency while maintaining the output power and operation stability. This study provides valuable insights for the design and parameter selection of practical systems in future research.

Comparison of combustion characteristics of MILD model combustor and multi-nozzle array model combustor fueled hydrogen-methane mixtures

Key issues facing the development of hydrogen gas turbines include achieving low NOx emissions on hydrogen-enriched fuels, prevention of flashback and thermoacoustic instability. The present experimental investigation shows the fuel feasibility of MILD combustion and multi-nozzle array combustion with hydrogen-enriched fuels. The combustion characteristics, such as the range of combustion stability, NOx/CO emissions, and reaction zone distribution, have been determined for hydrogen contents ranging from 0% to 50% by volume. Compared to the MILD model combustor, the multi-nozzle array model combustor can achieve a broader range of stable combustion up to 40% by volume. As the hydrogen content increases from 0% to 40% by volume, the lean blowout (LBO) temperature of the multi-nozzle array model combustor decreases from 1600 K to 1400 K. When the hydrogen content reaches 50% of the volume, both the MILD model combustor and the multi-nozzle array model combustor exhibit thermoacoustic instability at high equivalence ratios. For the multi-nozzle array model combustor, NOx emissions are less than 20 ppm@15% O2 and CO emissions are less than 30 ppm@15% O2 in the adiabatic temperature range of 1400 K–2100 K. NOx emissions of the multi-nozzle array combustor are higher than that of the MILD combustor, but remain ultra-low due to the flue gas recirculation ratio. With increasing hydrogen content, the reaction zone becomes more concentrated along the axial and radial directions. The lift-off height of the reaction zone is 1.6 nozzle diameters at 40% by volume hydrogen content, which ensures the safety of the nozzles and prevent flashback.

Development of in-vitro pulsatile flow generator for evaluating the performance of hemodialysis catheters

Hemodialysis (HD) using an HD catheter is performed widely on renal failure patients. The catheter was evaluated using the recirculation ratio in pre-clinical status, which is a crucial index indicating its performance. However, pre-clinical in-vivo experiments have limitations: high cost, and ethical issues. Hence, computational and in-vitro methods have been developed as alternatives. However, computational methods require fluid dynamic knowledge, whereas in-vitro experiments are complicated and expensive. In this study, we developed a pulsatile flow generator to mimic blood flow achieving cost effectiveness and user convenience. The device used iterative learning control, achieving blood flow in the superior and inferior vena cava within a 3.3% error. Furthermore, the recirculation ratios were measured based on two insertion directions and two different external pipe materials to evaluate the catheter regarding patients’ posture and blood vessel stiffness. The results provide a better understanding of cardiovascular device performance without complicated and costly pre-clinical tests.

A Review on Recent Developments of RCCI Engines Operated with Alternative Fuels

Environmental concerns over automotive exhaust emissions and consumer demand for higher fuel efficiency have led to the development of low-temperature combustion concepts. The reactivity-controlled compression ignition (RCCI) engine is one among them and has the potential to reduce NOx and smoke emissions simultaneously. In this concept, a low-reactivity fuel is injected into the intake port and another high-reactivity fuel is injected into the cylinder directly. This results in reactivity stratification and provides more control over the rate of heat release. However, operating parameters such as reactivity of fuels, premixing ratio, injection strategies, exhaust gas recirculation ratio, piston bowl geometry, and compression ratio influence emissions formation. The article reviews recent developments on the effect of the above operating parameters on the performance and emission characteristics of RCCI engines operated with alternative fuels. The combustion strategies used to extend the RCCI mode to higher loads are also reviewed. Applications of computational fluid dynamics (CFDs) to design the combustion chamber for RCCI engines are discussed. The need for further improvements in the CFD models for RCCI engines is explained. After presenting a thorough review of recent literature, directions for future research on RCCI engines are proposed.

Structural optimization of hydrogen recirculation ejector for proton exchange membrane fuel cells considering the boundary layer separation effect

Ejectors can greatly improve the efficiency of proton exchange membrane fuel cells (PEMFCs) by pumping unreacted hydrogen, and boundary layer separation (BLS) significantly impacts the recirculation performance of an ejector. However, current studies usually focus on improving ejector performance without considering the effect of the BLS. Therefore, this paper focuses on the influence of the key structural parameters of the ejector on the BLS and the recirculation performance of the ejector. A mathematical model of the hydrogen recirculation ejector is established. Considering the BLS effect, the influence of the ejector structure parameters on the BLS and the performance of the ejector are studied under the design condition. To ensure the high performance of the ejector in a wide working range, the structure of the ejector is optimized in the full working range. The results show that when the backpressure is less than the reflux point (3.47 bar), the ejector works in the subcritical mode, and the hydrogen recirculation ratio decreases rapidly with increasing backpressure. When the backpressure is 3.35 bar, the BLS appears, and the separation area increases with increasing backpressure. The optimized ejector has good hydrogen recirculation performance in a specific range of throat diameters (6.2–7.2 mm), constant-area mixing chamber lengths (26.8–33.5 mm), and nozzle exit positions (−8–2 mm). When the throat diameter is less than 13.4 mm or greater than 33.5 mm, the degree of BLS is intensified, and the recirculation performance of the ejector decreases sharply. When the primary flow pressure is 6 bar, the efficiency of the optimized hydrogen recirculation ejector is significantly improved by 33.2%.

Numerical simulation of the effects of the EGR ratio and ignition timing on a supercharged and high compression ratio hybrid gasoline engine

This paper explores the potential effects of the exhaust gas recirculation (EGR) ratio and ignition timing on knock suppression in a supercharged and high compression ratio (CR) hybrid gasoline engine, whereas previous knock studies have focused on conventional CRs and equivalence ratios. According to the simulation results, EGR can significantly reduce the knock intensity (KI). The high CR and EGR enable the realization of an indicated thermal efficiency of 47.46 %. Chemical modeling and solvers make free radical detection convenient. Therefore, this paper investigates the relationships between chemical kinetics and low-temperature reactions, preignition (PI) and spontaneous combustion of end mixtures (SCEM). The numerical results demonstrate that IC4H7 is an important indicator of low-temperature reactions. In the cases where SCEM and PI occur, H2O2 and CH2O substantially decompose and the masses of CH3, HCO, and CO start to decrease before the peak heat release rate (HRR) is attained. High CH2O concentration is an important indicator for high-temperature reactions, while high concentrations of CH3 and HCO can characterize the onset of SCEM or PI. The peak masses of IC4H7, HCO, and CH3 positively correlate with the KI value.

A novel autotrophic denitrification and nitrification integrated constructed wetland process for marine aquaculture wastewater treatment

We undertook a lab-scale evaluation of a novel autotrophic denitrification and nitrification integrated constructed wetland (ADNI-CW) for improved carbon (C), nitrogen (N), and sulfur (S) cycling to treat mariculture wastewater. The process involved an up-flow autotrophic denitrification constructed wetland unit (AD-CW) for sulfate reduction and autotrophic denitrification, and an autotrophic nitrification constructed wetland unit (AN-CW) for nitrification. The 400-day experiment investigated the performance of the AD-CW, AN-CW, and entire ADNI-CW processes under various hydraulic retention times (HRTs), nitrate concentrations, dissolved oxygen levels, and recirculation ratios. Under various HRTs, the AN-CW achieved a nitrification performance exceeding 92%. Correlation analysis of the chemical oxygen demand (COD) revealed that, on average, approximately 96% of COD was removed by sulfate reduction. Under different HRTs, increases in influent NO3−–N concentrations caused the amount of sulfide to gradually decrease from sufficient to deficient, and the autotrophic denitrification rate also decreased from 62.18 to 40.93%. In addition, when the NO3−–N load rate was above 21.53 g N/m2·d, the transformation of organic N by mangrove roots may have increased NO3−–N in the top effluent of the AD-CW. The coupling of N and S metabolic processes mediated by various functional microorganisms (Proteobacteria, Chloroflexi, Actinobacteria, Bacteroidetes, and unclassified_d__Bacteria) enhanced N removal. We intensively explored the effects of changing inputs as culture species developed on the physical, chemical, and microbial changes of CW to ensure a consistent and effective management of C, N, and S. This study lays the foundation for green and sustainable mariculture development.

Energy and economic performance assessment of a solar-assisted regenerative vacuum membrane desalination system

Vacuum membrane water desalination is a promising technology for freshwater production with the advantages of low conduction heat loss and mass transfer resistance, compared to other membrane technologies. Such systems can be driven by solar thermal collectors for green water production, yet there is a lack of dynamic system simulations in the literature to comprehensively assess the energy and economic system performance and evaluate the impact of brine recirculation as a method of regeneration, especially under hot desert climates where solar resources are abundant, but freshwater resources are scarce (e.g., the northern coast of Egypt, considered as the case study here). In this study, a dynamic system simulation model is developed in TRNSYS, where a new “Type” is introduced for the vacuum membrane module. Initial sizing of the system with ∼20 % solar fraction resulted in annual average gained output ratio and specific thermal energy consumption of 2.51 and 133.5 kWh/m3, respectively, with levelized cost of water and payback period of 14.7 USD/m3 and 1.53 years, respectively. By increasing the solar collectors’ area from 8 to 16 m2, the levelized cost of water increased by 14.54 %. The storage volume was highly influential on the solar fraction, which increased by 101.39 % as the volume increased from 0.3 to 0.7 m3. Increasing the membrane area from 0.3 to 0.5 m2 increased the gained output ratio by 76.75 % while decreasing the levelized cost of water by 14.79 %. Internal heat regeneration through brine recirculation enhanced the system performance at lower recirculation ratios. Without recirculation, the levelized cost of water increased by 117.41 % and the system met the daily distillate water demand for only 90 days of the year.

Simulation and experimental measurements of 10-kW PEMFC passive hydrogen recovery system

Simulations are performed to examine the performance of a vacuum ejector in the hydrogen recovery loop of a 10-kW PEMFC system. The simulations commence by examining the effects of the primary flow fluid pressure and secondary flow temperature on the recirculation ratio and hydrogen stoichiometric ratio. Further simulations are then performed to investigate the temperature, pressure, velocity and Mach number distributions within the ejector for various values of the primary flow inlet pressure and temperature. A prototype ejector is fabricated using a 3D printing technique. Experiments are performed to evaluate the gas tightness and gas recovery performance of the ejector under realistic operating conditions. The simulation results show that the recirculation ratio and hydrogen stoichiometric ratio increase with a decreasing primary flow inlet pressure and secondary flow inlet temperature. As the primary flow inlet pressure increases, the pressure, velocity, and Mach number in the mixing chamber increase, and the hydrogen recovery performance decreases. Furthermore, as the temperature of the primary fluid flow increases, the stability of the isentropic flow condition within the ejector is enhanced. The experimental results show that the prototype vacuum ejector has a maximum gas leakage of just 0.7 psi and a minimum hydrogen recirculation rate of 59.3%. Consequently, it has significant potential for passive hydrogen recovery in large-scale fuel cell systems.

Thermodynamic sensitivity analysis of SOFC integrated with blade cooled gas turbine hybrid cycle

In the area of clean energy production along with higher efficiency, integrated combine power system, specifically gas turbine (GT) cycle with solid oxide fuel (SOFC) system, is gaining the attention of researchers. Thermodynamic modeling for the SOFC-GT hybrid cycle has been presented in this paper. For the proposed hybrid cycle, a high-temperature SOFC has successfully integrated with the recuperated-blade cooled gas turbine cycle. The gas turbine outlet waste heat has perfectly utilized the recuperator to power the fuel cell system. However, to maintain the temperature of the gas turbine blade within the permissible limit, air–film blade cooling scheme has been used. The SOFC-GT hybrid cycle has been operated under steady-state conditions, and a developed MATLAB program has been used to solve the governing equations for the components of the hybrid cycle. The impact of main operating parameters such as the temperature intake turbine (TIT), compression ratio (rpc), fuel utilization ratio (UF), and recirculation ratio are examined. From the obtained result, it can be revealed that the integration of the SOFC has seen significant improves overall hybrid cycle efficiency. The performance of fuel cell (SOFC) increases notably as the level of recuperation increases. To check the influence of main operating parameters, a sensitivity analysis has been performed for the hybrid cycle, and the maximum efficiency of 73% has been achieved. Moreover, to extend this research, an exclusive performance map has been plotted for power plant designers.

Process modelling and optimisation of methane yield from palm oil mill effluent using response surface methodology and artificial neural network

Methane yield plays an important role in evaluating the performance of anaerobic digestion (AD) process due to fluctuating characteristics of palm oil mill effluent (POME). In this study, two years of industrial-scale plant data collected from biogas plant in Pahang, Malaysia consisting of methane yield and H2S concentration were modelled using supervised Machine Learning (ML) algorithms, i.e. artificial neural network (ANN) and response surface methodology (RSM). Input parameters appraised were pH, temperature, and recirculation ratio (RR) of total treated effluent and bottom sludge to raw POME. Fitness of all models was evaluated based on performance metrics, namely determination coefficient (R2) and root mean square error (RMSE). Results demonstrated that ANN was superior to RSM model with R2 of 0.9762 and 0.8500, respectively. Besides, three-dimensional (3-D) response surface plot was utilised to study interactive effects between AD parameters on methane yield. Temperature and recirculation ratio (RR) was found to be main interactive factor of methane yield which was corroborated using Pareto chart. Process optimisation using RSM revealed that the highest methane yield was 0.2733 N m3 CH4/kg CODremoved (i.e. improvement percentage of 9.3%) with the least H2S concentration of 1086.4 mg/L under optimum operating conditions, i.e. temperature, pH and RR of 42 °C, 7.36 and 2.5, respectively. Sensitivity analysis revealed that RR plays substantial roles in yielding more methane in AD process. Maintaining RR ratio at optimum level (1.05 to 2.60) is key to achieve high methane yield with good stability by considering the trade-off between operating cost and revenue of biogas plant.

Elucidating the performance of integrated anoxic/oxic moving bed biofilm reactor: Assessment of organics and nutrients removal and optimization using feed forward back propagation neural network

A lab-scale integrated anoxic and oxic (A/O) moving bed biofilm reactor (MBBR) was investigated for the removal of organics and nutrients by varying chemical oxygen demand (COD) to NH4-N ratio (C/N ratio: 3.5, 6.75, and 10), hydraulic retention time (HRT: 6 h, 15 h, and 24 h), and recirculation ratio (R: 1, 2, and 3). The use of activated carbon coated carriers prepared from waste polyethylene material and polyurethane sponges attached to a cylindrical frame in the integrated A/O MBBR increased the attached growth biomass significantly. >95 % of COD removal was observed under the C/N ratio of 10 at an HRT of 24 h. While the low C/N ratio favored the removal of NH4-N (∼98 %) and PO43--P (∼90 %) with an optimal R of 1.75. Using the experimental dataset, to predict and forecast the performance of integrated A/O MBBR, a feed-forward-backpropagation-neural-network model was developed.

Assessment of CO2 enrichment mechanism in integrated coal gasification fuel cell combined cycle system with carbon capture

The present research proposes an innovative multi-physics coupled model of different configurations of an integrated coal gasification fuel cell combined cycle (IGFC) system employing Solid Oxide Electrolytic Cell (SOEC) for CO2 capture. Full-system simulation is carried out to examine efficiency. The model incorporates a Solid Oxide Fuel Cell (SOFC), a SOEC, a gas turbine (GT), and multiple recirculation loops operated by two ejectors. The results reveal that compared with traditional power plants, the proposed IGFC system equipped with SOEC can reduce CO2 emission by almost 80%, and operates environmentally beneficial. The efficiency of the system varies greatly depending on the design parameters implemented. The CO2 enrichment phenomenon by SOFC and capture measures of CO2 by SOEC are simultaneously analyzed. In addition, parametric analysis is performed to evaluate the coupling influence of multiple operating parameters on the IGFC system. Recirculation ratios of 0.75 with four times recirculations are found to be the optimal conditions for both SOFC fuel electrode and SOEC air electrode aimed at getting to the highest power generation efficiency and total CO2 capture rate of the system. After systematic optimization of the design parameters, the electrical efficiency and CO2 capture rate of the proposed system could achieve 68.47% and 87.88%, respectively, which are about 20% and 60% greater than those of traditional power plants. Furthermore, after optimizing the control strategy, the fuel utilization rate of the system increases from 63.09% to 83.40%.

Optimisation and performance evaluation of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the prediction of biogas production from palm oil mill effluent (POME)

In recent years, machine learning (ML) techniques have been developed to predict the performance of anaerobic digestion (AD) processes including methane potential and reactor stability. However, their practical applications to industrial-scale palm oil mill effluent (POME) treatment plant are limited. In this study, ML algorithms such as response surface methodology (RSM), adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) are employed to model the biogas production and methane yield from the AD of POME in a local industry-scale anaerobic covered lagoon. Results demonstrated that these models were well aligned with two years of operational data with high coefficient of determination (R2) of up to 0.98. ANFIS yields the highest prediction accuracy, with R2 of 0.9791 along with the lowest mean absolute error (MAE) of 0.0730 and root mean squared error (RMSE) of 0.1438. Subsequently, ANFIS is used in the multi-objective optimisation to maximise the biogas production and methane yield. Optimal conditions for the temperature of the anaerobic digester, pH and recirculation ratio are 38.9 °C, 7.03 and 1.89 respectively which could enhance the biogas production and methane yield by 19.4% and 12.2% respectively. Confirmatory experiments were carried out in the biogas plant under this set of optimised variables for a period of two months. The predicted biogas production and methane yield are highly correlated to the actual data with small percentage difference of 1.25% and 5.09% respectively, indicating that ANFIS model was accurate and reliable. Sensitivity analysis shows that pH has the most dominant effect on the methane yield.

Simultaneous sludge minimization and membrane fouling mitigation in membrane bioreactors by using a microaerobic - Settling pretreatment module

Membrane fouling is the major obstacle for membrane bioreactors operated at a long sludge retention time to reduce sludge production. In this study, a sludge process reduction (SPR) module, consisting of a microaerobic tank and a settler, was inserted before an anoxic/oxic MBR (AO-MBR) to achieve dual objectives of fouling alleviation and sludge reduction. Three SPR-MBRs were operated to investigate influences of sludge recirculation ratios from the SPR settler to the microaerobic tank on process performance. Compared to AO-MBR, the SPR-MBRs reduced sludge production by 43.1–56.4% by maintaining sludge retention times above 175 d, and decreased foulant layer resistance and pore clogging resistance. Inserting SPR reduced the accumulation of dissolved organic matters and extracellular polymeric substances, enlarged sludge flocs, and decreased sludge viscoelasticity. However, increasing RSPR stimulated outward diffusion of extracellular polymeric substances and increased sludge viscosity. SPR-MBRs achieved effective sludge reduction by enriching hydrolytic (Trichococcus and Aeromonas) and fermentative genera (Lactococcus, Paludibacter, Macellibacteroides, and Acinetobacter) in the SPR, and alleviated membrane fouling by prohibiting the growth of extracellular polymeric substance-secreting bacteria and enriching filamentous bacteria to enlarge particle size. The results revealed that the SPR-MBR maximized sludge reduction with a very long sludge retention time, and alleviated membrane fouling synchronously.

Optimization on structure and operation parameters of biofilter for decentralized sewage treatment

Aiming for treating decentralized domestic wastewater in rural China, this study evaluates the effects of ceramsite size and structure, and water recirculation parameters, upon the performance of recirculating biofilter (RBF). RBF shows stable capability of chemical oxygen demand (COD) remediation and ammonia nitrification. In addition, the microbial flora and structures of the various layers in the system are analyzed via high-throughput sequencing in order to study the microbial diversity. The results indicate that while the ceramic particle size has no significant influence on the COD remediation capacity, the ceramics with smaller particle sizes exhibit better ammonia nitrogen (NH4+-N) removal ability, with a first-order linear relationship between the influent ammonia nitrogen load and the effluent NH4+-N concentration in RBF (R2 > 0.64). An increased hydraulic load and intermittent operation are shown to deteriorate the water quality with respect to NH4+-N, while an increased recirculation ratio increases the removal rate of NH4+-N from the effluent. Further, the water distribution time has a stronger effect upon the NH4+-N concentration in the effluent than does the recirculation ratio. Moreover, the microbial structure of the multi-layer recirculating trickle biofilter varies significantly during the process. The results indicate that a high recirculation ratio, long water distribution time, and multi-layer structure will be beneficial for improving the pollutant treatment capacity of RBF.

The multi-parameter optimization of injections on double-layer diesel engines based on genetic algorithm

In this paper, a coupling model of the NSGA-II genetic algorithm and KIVA-3 V program is developed to perform a multi-objective intelligent optimization study of the injection parameters in a diesel engine with double-layer diverging combustion (DLDC) chamber. Four optimization parameters, involving the first injection timing, the first fuel split ratio, the injection timing interval, and the exhaust gas recirculation (EGR) ratio, are optimized after comparing the pollutant emissions and fuel consumption characteristics. The computation results reveal that both soot and fuel consumption function as the optimization objectives, proving a trade-off relationship with the NOx emission. The analysis of the response surface demonstrates that the application of the multiple-injection strategies is beneficial for enhancing the performance of diesel engines. A large first fuel split ratio and a low EGR rate can minimize both ISFC (indicated specific fuel consumption) and soot emission concurrently. A high EGR rate can significantly reduce NOx emission. In addition, the distribution of the final Pareto font shows that 66.7 % percent of the first fuel split ratio is above 0.56, and only two solutions (8.3 %) have values below 0.35. Furthermore, three representative points of the first fuel split ratio are selected for combustion analysis, which are 0.05, 0.35, and 0.88. As the first fuel split ratio rises, the high-temperature areas in the cylinder are gradually enlarged, and the NOx emission is increased while the soot emission and ISFC are further reduced.