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The purpose of this study is to assess the performance of fuel blends containing ethanol and gasoline in spark ignition engines. The aim is to explore alternative fuels that can enhance performance while minimizing or eliminating adverse environmental impacts, particularly in the context of limited fossil fuel availability and the need for sustainable alternatives.

The authors used the Ricardo Wave software to evaluate the performance of fuel blends with varying ethanol content (represented as E0, E10, E25, E40, E55, E70, E85 and E100) in comparison to gasoline. The assessment involved different composition percentages and was conducted at various engine speeds (1,500, 3,000, 4,500 and 6,000 rpm). This methodology aims to provide a comprehensive understanding of how different ethanol-gasoline blends perform under different conditions.

The study found that, across all fuel blends, the highest brake power (BP) and the highest brake-specific fuel consumption (BSFC) were observed at 6,000 rpm. Additionally, it was noted that the presence of ethanol in gasoline fuel blends has the potential to increase both the BP and BSFC. These findings suggest that ethanol can positively impact the performance of spark-ignition engines, highlighting its potential as an alternative fuel.

This research contributes to the ongoing efforts in the automotive industry to find sustainable alternative fuels. The use of Ricardo Wave software for performance assessment and the comprehensive exploration of various ethanol-gasoline blends at different engine speeds add to the originality of the study. The emphasis on the potential of ethanol to enhance engine performance provides valuable insights for motor vehicle manufacturers and researchers working on alternative fuel solutions.

Combustion of fuel with oxidizer inside a combustion chamber of an internal combustion engine forms inevitable oxides of nitrogen (NOx) due to high temperature at different locations of the combustion chamber. This study aims to quantify NOx formed inside the combustion chamber using two fuels, a conventional diesel (n-heptane) and a biodiesel (methyl oleate).

This research uses a computational fluid dynamics simulation of chemically reacting fluid flow to quantify and compare oxides of nitrogen (NOx) in a compression ignition (CI) engine. The study expends species transport model of ANSYS FLUENT. The simulation model has provided the temperature profile inside the combustion chamber, which is subsequently used to calculate NOx using the NOx model. The simulation uses a single component hydrocarbon and oxygenated hydrocarbon to represent fuels; for instance, it uses n-heptane (C₇H₁₆) for diesel and methyl-oleate (C₁₉H₃₆O₂) for biodiesel. A stoichiometric air–fuel mixture is used for both fuels. The simulation runs a single cylinder CI engine of 650 cm³ swept volume with inlet and exhaust valves closed.

The pattern for variation of velocity, an important flow parameter, which affects combustion and subsequently oxides of nitrogen (NOx) formation at different piston locations, is similar for the two fuels. The variations of in-cylinder temperature and NOx formation with crank angles have similar patterns for the fuels, diesel and biodiesel. However, the numerical values of in-cylinder temperature and mass fraction of NOx are different. The volume averaged static peak temperatures are 1,013 K in case of diesel and 1,121 K in case of biodiesel, while the mass averaged mass fractions of NOx are 15 ppm for diesel and 141 ppm for biodiesel. The temperature rise after combustion is more in case of biodiesel, which augments the oxides of nitrogen formation. A new parameter, relative mass fraction of NOx, yields 28% lower value for biodiesel than for diesel.

This work uses a new concept of simulating simple chemical reacting system model to quantify oxides of NOx using single component fuels. Simplification has captured required fluid flow data to analyse NOx emission from CI engine while reducing computational time and expensive experimental tests.

The study aims to determine the the optimal value of output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The performance parameters like brake thermal efficiency (BTE) and brake specific energy consumption (BSEC), whereas CO emission, HC emission, CO₂ emission, NO_x emission, exhaust gas temperature (EGT) and opacity are the emission parameters measured during the test. Tests are conducted for 2, 6 and 10 kg of load, 16.5 and 17.5 of CR.

In this investigation, the first engine was fueled with 100% diesel and 100% Calophyllum inophyllum oil in single-fuel mode. Then Calophyllum inophyllum oil with producer gas was fed to the engine. Calophyllum inophyllum oil offers lower BTE, CO and HC emissions, opacity and higher EGT, BSEC, CO₂ emission and NO_x emissions compared to diesel fuel in both fuel modes of operation observed. The performance optimization using the Taguchi approach is carried out to determine the optimal input parameters for maximum performance and minimum emissions for the test engine. The optimized value of the input parameters is then fed into the prediction techniques, such as the artificial neural network (ANN).

From multiple response optimization, the minimum emissions of 0.58% of CO, 42% of HC, 191 ppm NO_x and maximum BTE of 21.56% for 16.5 CR, 10 kg load and dual fuel mode of operation are determined. Based on generated errors, the ANN is also ranked for precision. The proposed ANN model provides better prediction with minimum experimental data sets. The values of the R² correlation coefficient are 1, 0.95552, 0.94367 and 0.97789 for training, validation, testing and all, respectively. The said biodiesel may be used as a substitute for conventional diesel fuel.

The blend of Calophyllum inophyllum oil-producer gas is used to run the diesel engine. Performance and emission analysis has been carried out, compared, optimized and validated.

The study aims to verify and establish the result of the most suitable optimization approach for higher performance and lower emission of a variable compression ratio (VCR) diesel engine. In this study, three types of test fuels are taken and tested in a variable compression ratio diesel engine (compression ignition). The fuels used are conventional diesel fuel, e-diesel (85% diesel-15% bioethanol) and nano-fuel (85% diesel-15% bioethanol-25 ppm Al₂O₃). The effect of bioethanol and nano-particles on performance, emission and cost-effectiveness is investigated at different load and compression ratios (CRs). The optimum performance and lower emission of the engine are evaluated and compared with other optimization methods.

The test engine is run by diesel, e-diesel (85% diesel-15% bioethanol) and nano-fuel (85% diesel-15% bioethanol-25 ppm Al₂O₃) in three different loadings (4 kg, 8 kg and 12 kg) and CR of 14, 16 and 18, respectively. The optimum value of energy efficiency, exergy efficiency, NO_X emission and relative cost variation are determined against the input parameters using Taguchi-Grey method and confirmed by response surface methodology (RSM) technique.

Using Taguchi-Grey method, the maximum energy and exergy efficiency, minimum % relative cost variation and NO_X emission are 24.64%, 59.52%, 0 and 184 ppm, respectively, at 4 kg load, 18 CR and fuel type of nano-fuel. Using RSM technique, maximum energy and exergy efficiency are 24.8% and 62.9%, and minimum NO_X emission and % cost variation are 208.4 ppm and –6.5, respectively, at 5.2 kg load, 18 CR and nano-fuel. The RSM is suggested as the most appropriate technique for obtaining maximum energy and exergy efficiency, and minimum % relative cost; however, for lowest possible NO_X emission, the Taguchi-Grey method is the most appropriate.

Waste rice straw is used to produce bioethanol. 4-E analysis, i.e. energy, exergy, emission and economic analysis, has been carried out, optimized and compared.

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.

A combustor design is a particularly important and difficult task in the development of gas turbine engines. During studies for accurate and easy combustor design, reasonable design methodologies have been established and used in engine development. The purpose of this paper is to review the design methodology for combustor in development of advanced gas turbine engines. The advanced combustor development task can be successfully achieved in less time and at lower cost by adopting new and superior design methodologies.

The review considers the main technical problems (combustion, cooling, fuel injection and ignition technology) in the development of modern combustor design and deals with combustor design methods by dividing it into preliminary design, performance evaluation, optimization and experiment. The advanced combustion and cooling technologies mainly used in combustor design are mentioned in detail. In accordance with the modern combustor design method, the design mechanisms are considered and the methods used in every stage of the design are reviewed technically.

The improved performances and strict emission limits of gas turbine engines require the application of advanced technologies when designing combustors. The optimized design mechanism and reasonable performance evaluation methods are very important in reducing experiments and increasing the effectiveness of the design.

This paper provides a comprehensive review of the design methodology for the advanced gas turbine engine combustor.

Mahindra Trucks and Buses forayed into India's commercial vehicles sector in 2005. However, they had to battle numerous supply chain challenges associated with introducing a new product (a new truck brand) in the market and to gain a noticeable foothold in the market. In this case, we attempt to align customer brand stickiness with the supply chain expectations from a new product. In particular, we deliberate how the needs of all actors in the supply chain must be met and their interactions must be accounted in developing a robust supply chain. Finally, a supply chain is successful when demand can be matched with supply and the customer's service level can be achieved.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

The widespread family businesses play an important role in the national economy of developed countries in Europe and North America, or of developing countries in East Asia. However, family business succession is a worldwide difficult problem. The innovative family business succession practices of Robert Bosch GmbH, the German family company which has a history of 130 years (1886-2016), basically follow the trend of evolving from family businesses to social enterprises after further socialization. However, it has its own innovation and uniqueness which is worthy of reference by Chinese family businesses.

This study aims to understand the current production scenario emphasizing the significance of green manufacturing in achieving economic and environmental sustainability goals to fulfil future needs; to determine the viability of particular strategies and actions performed to increase the process efficiency of electrical discharge machining; and to uphold the values of sustainability in the nonconventional manufacturing sector and to identify future works in this regard.

A thorough analysis of numerous experimental studies and findings is conducted. This prominent nontraditional machining process’s potential machinability and sustainability challenges are discussed, along with the current research to alleviate them. The focus is placed on modifications to the dielectric fluid, choosing affordable substitutes and treating consumable tool electrodes.

Trans-esterified vegetable oils, which are biodegradable and can be used as a substitute for conventional dielectric fluids, provide pollution-free machining with enhanced surface finish and material removal rates. Modifying the dielectric fluid with specific nanomaterials could increase the machining rate and demonstrate a decrease in machining flaws such as micropores, globules and microcracks. Tool electrodes subjected to cryogenic treatment have shown reduced tool metal consumption and downtime for the setup.

The findings suggested eco-friendly machining techniques and optimized control settings that reduce energy consumption, lowering operating expenses and carbon footprints. Using eco-friendly dielectrics, including vegetable oils or biodegradable dielectric fluids, might lessen the adverse effects of the electrical discharge machine operations on the environment. Adopting sustainable practices might enhance a business’s reputation with the public, shareholders and clients because sustainability is becoming increasingly significant across various industries.

A detailed general review of green nontraditional electrical discharge machining process is provided, from high-quality indexed journals. The findings and results contemplated in this review paper can lead the research community to collectively apply it in sustainable techniques to enhance machinability and reduce environmental effects.