Advancing renewable fuel integration: A comprehensive response surface methodology approach for internal combustion engine performance and emissions optimization.

In the realm of internal combustion engines, there is a growing utilization of alternative renewable fuels as substitutes for traditional diesel and gasoline. This surge in demand is driven by the imperative to diminish fuel consumption and adhere to stringent regulations concerning engine emissions. Sole reliance on experimental analysis is inadequate to effectively address combustion, performance, and emission issues in engines. Consequently, the integration of engine modelling, grounded in machine learning methodologies and statistical data through the response surface method (RSM), has become increasingly significant for enhanced analytical outcomes. This study aims to explore the contemporary applications of RSM in assessing the feasibility of a wide range of renewable alternative fuels for internal combustion engines. Initially, the study outlines the fundamental principles and procedural steps of RSM, offering readers an introduction to this multifaceted statistical technique. Subsequently, the study delves into a comprehensive examination of the recent applications of alternative renewable fuels, focusing on their impact on combustion, performance, and emissions in the domain of internal combustion engines. Furthermore, the study sheds light on the advantages and limitations of employing RSM, and discusses the potential of combining RSM with other modelling techniques to optimise results. The overarching objective is to provide a thorough insight into the role and efficacy of RSM in the evaluation of renewable alternative fuels, thereby contributing to the ongoing discourse in the field of internal combustion engines.

Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods.

The damaging effects of corona faults have made them a major concern in metal-clad switchgear, requiring extreme caution during operation. Corona faults are also the primary cause of flashovers in medium-voltage metal-clad electrical equipment. The root cause of this issue is an electrical breakdown of the air due to electrical stress and poor air quality within the switchgear. Without proper preventative measures, a flashover can occur, resulting in serious harm to workers and equipment. As a result, detecting corona faults in switchgear and preventing electrical stress buildup in switches is critical. Recent years have seen the successful use of Deep Learning (DL) applications for corona and non-corona detection, owing to their autonomous feature learning capability. This paper systematically analyzes three deep learning techniques, namely 1D-CNN, LSTM, and 1D-CNN-LSTM hybrid models, to identify the most effective model for detecting corona faults. The hybrid 1D-CNN-LSTM model is deemed the best due to its high accuracy in both the time and frequency domains. This model analyzes the sound waves generated in switchgear to detect faults. The study examines model performance in both the time and frequency domains. In the time domain analysis (TDA), 1D-CNN achieved success rates of 98%, 98.4%, and 93.9%, while LSTM obtained success rates of 97.3%, 98.4%, and 92.4%. The most suitable model, the 1D-CNN-LSTM, achieved success rates of 99.3%, 98.4%, and 98.4% in differentiating corona and non-corona cases during training, validation, and testing. In the frequency domain analysis (FDA), 1D-CNN achieved success rates of 100%, 95.8%, and 95.8%, while LSTM obtained success rates of 100%, 100%, and 100%. The 1D-CNN-LSTM model achieved a 100%, 100%, and 100% success rate during training, validation, and testing. Hence, the developed algorithms achieved high performance in identifying corona faults in switchgear, particularly the 1D-CNN-LSTM model due to its accuracy in detecting corona faults in both the time and frequency domains.

Ultralow Sulfur Diesel and Rapeseed Methyl Ester Fuel Impact on Performance, Emitted Regulated, Unregulated, and Nanoparticle Pollutants.

The operation of engines using rapeseed methyl ester (RME) and ultralow sulfur diesel (ULSD) was tested for the combustion properties, emitted regulated, unregulated exhaust pollutants, and the size of nanoparticles. The combustion analysis showed higher apparent heat release rate and shorter ignition delay period during RME combustion than during ULSD combustion. The ULSD engine has a combustion chamber maximum pressure relatively higher than that of RME. This study showed that the heat release rate of ULSD is always higher than that of RME while more fuel consumption occurred from the combustion of biodiesel in comparison with diesel. When the engine is running on RME, HC and NOx formation increased at high loads up to 15% and 13%, respectively; meanwhile, CO concentrations reduced by 30.9% for the same conditions. Most of the particulate matter (PM) emitted from a diesel engine has a particle size from 5 to 100 nm, while the particle size from ULSD ranged from 5 to 40 nm. Overloading the engine caused a decrease in the sizes of emitted PM for both fuels. The smoke number for RME was less than that for ULSD by 33.9% at high loads. For high engine load, the cumulative concentration number for the nucleation mode decreased, while it increased for the accumulation mode. Furthermore, measurements of formaldehyde, ethane, methane, acetylene, ethylene, propylene, and isocyanic acid emissions showed the presence of these harmful substances at very low concentrations (8 ppm) for both fuels.

Assessing the application and downstream effects of pulsed mode ultrasound as a pre-treatment for alum coagulation.

The application of pulsed mode ultrasound (PMU) as a pre-treatment for alum coagulation was investigated at various alum dosages and pH levels. The effects of the treatments on turbidity and dissolved organic carbon (DOC) removal and residual Al were evaluated. Response surface methodology (RSM) was utilized to optimize the operating conditions of the applied treatments. The results showed that PMU pre-treatment increased turbidity and DOC removal percentages from maximum of 96.6% and 43% to 98.8% and 52%, respectively. It also helped decrease the minimum residual Al from 0.100 to 0.094 ppm. The multiple response optimization was carried out using the desirability function. A desirability value of >0.97 estimated respective turbidity removal, DOC removal and Al residual of 89.24%, 45.66% and ∼ 0.1 ppm for coagulation (control) and 90.61%, >55% and ∼ 0 for coagulation preceded by PMU. These figures were validated via confirmatory experiments. PMU pre-treatment increased total coliform removal from 80% to >98% and decreased trihalomethane formation potential (THMFP) from 250 to 200 ppb CH3Cl. Additionally, PMU application prior to coagulation improved the settleability of sludge due to the degassing effects. The results of this study confirms that PMU pre-treatment can significantly improve coagulation performance.

Investigating natural organic carbon removal and structural alteration induced by pulsed ultrasound.

The application of pulsed ultrasound for DOC removal from natural water samples has been thoroughly investigated in this work. Natural water samples were treated with ultrasound at power levels of 48 and 84 W with treatment times of 5 and 15 min. Chemical fractionation was conducted for both untreated and treated samples to clearly identify the change in DOC structure caused by ultrasonic treatments. Statistical analyses applying 2(3) factorial design were performed to study the behaviour of the response (i.e. DOC removal) under different operating conditions. Overall, ultrasonic treatments resulted in DOC removal of 7-15% depending on the applied operating conditions. The treated water had high microbial loading that interfered with DOC removal due primarily to the release of microbial products when exposed to ultrasound. Pulse ultrasound was found to be more effective than the continuous mode for DOC removal at the same effective power level. A regression model was developed and tested for DOC removal prediction. The model was adequate in predicting DOC removal with a maximum deviation from the experimental data of <11%. Pulsed ultrasound at low power levels and short treatment times was found to be the most energy efficient treatment for DOC removal.

Insights into the scalability of magnetostrictive ultrasound technology for water treatment applications.

To date, the successful application of large scale ultrasound in water treatment has been a challenge. Magnetostrictive ultrasound technologies for constructing a large-scale water treatment system are proposed in this study. Comprehensive energy evaluation of the proposed system was conducted. The effects of chosen waveform, scalability and reactor design on the performance of the system were explored using chemical dosimetry. Of the fundamental waveforms tested; sine, triangle and square, the highest chemical yield resulted from the square wave source. Scaling up from the 0.5L bench-scale system to the 15 L large-scale unit resulted in a gain of approximately 50% in sonochemical efficiency (SE) for the system. The use of a reactor tank with 45° inclined sides further increased SE of the system by 70%. The ability of the large scale system in removing contaminants from natural water samples was also investigated. The results revealed that the large-scale unit was capable of achieving a maximum removal of microbes and dissolved organic carbon (DOC) of 35% and 5.7% respectively at a power density approximately 3.9 W/L. The results of this study suggest that magnetostrictive ultrasound technology excited with square wave has the potential to be competitive in the water treatment industry.

Tracking ultrasonically structural changes of natural aquatic organic carbon: Chemical fractionation and spectroscopic approaches.

In this study, the structural alteration to DOC for a range of ultrasound treatments was investigated with chemical fractionation and UV-vis spectroscopic measurement. Ultrasound treatments were applied in continuous and pulsed modes at power levels of 48 and 84 W for effective treatment times of 5 and 15 min. Overall results show that the ultrasound treatments tended to degrade the hydrophobic aromatic fraction, while increasing the hydrophilic fraction to a lesser extent. The highest recorded reduction of hydrophobic DOC (17.8%) was achieved with pulse treatment of 84 W for15 min, while the highest increase in the hydrophilic DOC (10.5%) was obtained with continuous treatment at 84 W and 5 min. The optimal ultrasound treatment conditions were found to be pulse mode at high power and short treatment time, causing a minimal increase in the hydrophilic fraction of 1.3% with moderate removal of the hydrophobic fraction of 15.52%. The same treatment conditions, with longer treatment time, resulted in the highest removal of SUVA254 and SUVA280 of 17.09% and 16.93, respectively. These results indicate the potential for ultrasound treatments in DOC structural alteration. The hydrophobic fraction showed strong and significant correlations with UV absorbance at 254 and 280 nm. A254/A204 also exhibited strong and significant correlations with the hydrophobic/hydrophilic ratio. The other UV ratios (A250/A365 (E2/E3) and A254/A436) had weak and insignificant correlations with the hydrophobic/hydrophilic ratio. This confirms the applicability of UV indices as a suitable surrogate method for estimating the hydrophobic/hydrophilic structure.

Impact of pulsed ultrasound on bacteria reduction of natural waters.

There is a limited work on the use of pulsed ultrasound for water disinfection particularly the case of natural water. Hence, pulsed ultrasound disinfection of natural water was thoroughly investigated in this study along with continuous ultrasound as a standard for comparison. Total coliform measurements were applied to evaluate treatment efficiency. Factorial design of 2(3) for the tested experimental factors such as power, treatment time and operational mode was applied. Two levels of power with 40% and 70% amplitudes, treatment time of 5 and 15 min and operational modes of continuous and pulsed with On to Off ratio (R) of 0.1:0.6 s were investigated. Results showed that increasing power and treatment time or both increases total coliform reduction, whereas switching from continuous to pulsed mode in combination with power and treatment time has negative effect on total coliform reduction. A regression model for predicting total coliform reduction under different operating conditions was developed and validated. Energy and cost analyses applying electrical and calorimetric powers were conducted to serve as selection guidelines for the choosing optimum parameters of ultrasound disinfection. The outcome of these analyses indicated that low power level, short treatment time, and high R ratios are the most effective operating parameters.

Energy characterisation of ultrasonic systems for industrial processes.

Obtaining accurate power characteristics of ultrasonic treatment systems is an important step towards their industrial scalability. Calorimetric measurements are most commonly used for quantifying the dissipated ultrasonic power. However, accuracy of these measurements is affected by various heat losses, especially when working at high power densities. In this work, electrical power measurements were conducted at all locations in the piezoelectric ultrasonic system equipped with ½â€³ and ¾â€³ probes. A set of heat transfer calculations were developed to estimate the convection heat losses from the reaction solution. Chemical dosimeters represented by the oxidation of potassium iodide, Fricke solution and 4-nitrophenol were used to chemically correlate the effect of various electrical amplitudes and treatment regimes. This allowed estimation of sonochemical-efficiency (SE) and energy conversion (XUS) of the ultrasonic system. Results of this study showed overall conversion efficiencies of 60-70%. This correlated well with the chemical dosimeter yield curves of both organic and inorganic aqueous solutions. All dosimeters showed bubble shielding and coalescence effects at higher ultrasonic power levels, less pronounced for the ½â€³ probe case. SE and XUS values in the range of 10(-10) mol/J and 10(-3) J/J respectively confirmed that conversion of ultrasonic power to chemical yield declined with amplitude.

Characterisation of mixing rate due to high power ultrasound.

For meaningful assessment of results from laboratory and pilot plant trials, it is often necessary to know the mixing characteristics within the ultrasonic reactors. Previous workers have used conductivity measurements in an attempt to characterize the residence time distribution in ultrasonic reactors, but these results do not provide direct data on the mixing within the high power region adjacent to the ultrasonic probe tip. We overcome this difficulty through direct visualization of the mixing process within the high energy region close to the tip of the ultrasonic probe. Our analysis proceeds by determining an approximate turbulent diffusivity in a batch reactor arrangement for different values of ultrasonic energy input. For input electrical power levels between 70 and 120 W and a processing volume of 30 ml, the effective turbulent diffusivity varied from about 0.2 x 10(-3) to 0.7 x 10(-3)m(2)/s. We demonstrate that such results can be coupled to a suitable dispersion model to estimate the actual residence time distribution in flow-though arrangements when the through-put adds little additional mixing energy. Therefore, coupling the effective turbulent diffusivity identified in a batch reactor with a suitable dispersion model for the reactor offers an alternative approach to the deduction of RTD when determining the actual RTD in the high intensity zone of steady flow sonochemical reactors is problematic.