An Experimental Study For Emission Of Four Stroke Carbureted And Fuel Injection Motorcycle Engine

Each manuscript should contain an abstract of about 200 words and should be typed using Palatino Linotype, Font size 10. The manuscript has to be camera ready. Antipollution laws in many countries impose a limit on the volume of poisonous gases which may be emitted from a vehicle’s exhaust. The aim of this study is to compare the emission characteristic of a carbureted and fuel injection system of a four-stroke motorcycle engine. For this objective, a carbureted engine of Honda Wave 125 cc was converted into a fuel injection system. Emissions of CO, CO2 and hydrocarbon (HC) were measured in the lab. The test was conducted at three different speeds: 2000, 4000 and 6000 RPM; and at two loads: 5Nm and 10Nm. Upon conversion of the motorcycle engine, the results show improvement in term of reduction of emissions of all three gasses. Emission at a 5 Nm load improved by 62.6%, 29.75% and 11.33% for CO, HC and CO2 respectively. The results also showed a similar trend at a 10 Nm load, where the emissions improved to 75.86%, 30.1% and 47.71% for CO, CO2 and HC respectively. The results show that fuel injection is evidently a better system as it delivers lower emission

Virtual Laboratory for Engineering Education: Review of Virtual Laboratory for Students Learning

E-learning is currently a rapidly growing trend which attempts to provide an infrastructural configuration that integrates and encompass learning content, services and tools as a single solution which can generate and deliver educational contents and training effectively, efficiently and cost-effectively. In advanced technical education, laboratories are essential learning spaces. Providing laboratory facilities at universities with limited funds and technical know-how is difficult due to the high expenses of installation and upkeep. In order to tackle these obstacles, "virtual laboratories" have been established. Through remote access, virtual laboratories make it possible for users to conduct experiments similar to genuine systems. Consequently, resources of laboratories can be shared across a wide community of geographically dispersed customers while restricting operational expenses and initial set-up to one single institution. This article reviews the virtual laboratory for engineering education. Three distinct e-learning resource methods are discussed. The intrinsic objectives of animation are also explained. Lastly, the conclusion is provided along with recommendation for future studies

Insight into Green Extraction for Roselle as a Source of Natural Red Pigments: A Review

Roselle (Hibiscus sabdariffa L.) is a source of anthocyanins as red pigments that is extensively farmed in tropical and subtropical regions, including Indonesia, Malaysia, China, Thailand, Egypt, Mexico, and West India. The roselle plant contains a variety of nutrients, including anthocyanins, organic acids, pectin, etc. Due to the toxicity and combustibility of the solvents, traditional extraction methods for these compounds are restricted. Obtaining pure extracts is typically a lengthy procedure requiring many processes. Supercritical carbon dioxide (ScCO2 ) extraction as a green technology is rapidly improving and extending its application domains. The advantages of this method are zero waste production, quicker extraction times, and reduced solvent consumption. The ScCO2 extraction of natural pigments has great promise in food, pharmaceuticals, cosmetics, and textiles, among other uses. The ScCO2 technique for natural pigments may also be advantageous in a variety of other contexts. Due to their minimal environmental risk, the high-quality red pigments of roselle rich in anthocyanins extracted using ScCO2 extraction have a high sustainability potential. Therefore, the objective of this review is to increase knowledge related to the natural colorant of roselle as a substitute for chemically manufactured colorants using ScCO2 as a green method. This article covers ScCO2 extraction, particularly as it relates to the optimization of pigments that promote health. This article focuses on the high extraction efficiency of ScCO2 extraction. Natural colorants extracted via ScCO2 are regarded as safe compounds, especially for human consumption, such as novel functional food additives and textile and pharmaceutical color

Recovery of Anthocyanins from Hibiscus sabdariffa L. Using a Combination of Supercritical Carbon Dioxide Extraction and Subcritical Water Extraction

Anthocyanins are one of the bioactive compounds in roselle that has many medicinal proposes. Anthocyanins are placed in the inner part of the roselle; therefore, combinations of two methods were applied to extract the anthocyanins. The first stage is employing supercritical carbon dioxide (ScCO2 ) to break the particle surface or outer layer of the roselle based on the total phenolic compounds (TPC) recovery, and the second step was to apply subcritical water extraction (SWE) for the extraction of anthocyanins. The objective is to determine the best conditions to obtain high yields of total anthocyanins compounds (TAC) from the roselle (Hibiscus sabdariffa) by employing a combination of ScCO2 and SWE. The optimal conditions of ScCO2 (first stage) were 19.13 MPa, 60 ◦C, and 4.31 mL/min, yielding 18.20%, and 80.34 mg/100 g TPC, respectively. The optimum conditions of SWE (second stage) were 9.48 MPa, 137 ◦C, and 6.14 mL/min, yielding 86.11% and 1224.61 mg/100 g TAC, respectively. The application of integrated ScCO2 and SWE proved successful in achieving high anthocyanins production and yield as compared to previous extraction methods. This approach may be used to extract the roselle with a greater anthocyanin’s concentration than the prior method

Developments in nanoparticles enhanced biofuels and solar energy in Malaysian perspective: a review of state of the art

The rapid rise in global oil prices, the scarcity of petroleum sources, and environmental concerns have all created severe issues. As a result of the country’s rapid expansion and financial affluence, Malaysia’s energy consumption has skyrocketed. Biodiesel and solar power are currently two of the most popular alternatives to fossil fuels in Malaysia. These two types of renewable energy sources appear to be viable options because of their abundant availability together with environmental and performance competence to highly polluting and fast depleting fossil fuels. The purpose of adopting renewable technology is to expand the nation’s accessibility to a reliable and secure power supply. The current review article investigates nonconventional energy sources added with nanosized metal particles called nanomaterials including biodiesel and solar, as well as readily available renewable energy options. Concerning the nation’s energy policy agenda, the sources of energy demand are also investigated. The article evaluates Malaysia’s existing position in renewable energy industries, such as biodiesel and solar, as well as the impact of nanomaterials. This review article discusses biodiesel production, applications, and government policies in Malaysia, as well as biodiesel consumption and recent developments in the bioenergy sector, such as biodiesel property modifications utilizing nanoparticle additions. In addition, the current review study examines the scope of solar energy, different photovoltaic concentrators, types of solar energy harvesting systems, photovoltaic electricity potential in Malaysia, and the experimental setup of solar flat plate collectors (FPC) with nanotechnology

Effects of Pre-Turbocharger Turbine Water Injection on the Sustainable Performance of Spark Ignition Engine

Water injection strategy is considered a promising technique to improve the performance of boosted engine and reduce the NOx emission via the latent heat of water vaporization. Numerous research on water injection has been conducted on in-cylinder and intake port water injection. However, the water injection focusing on the spark ignition (SI) engine exhaust system is still lacking. This study proposed a pre-turbocharger turbine water injection (PTWI) concept to reduce the turbine inlet temperature. This was done so that the stoichiometric engine operation could be achieved at a medium–high load and engine speed without resorting to a fuel enrichment strategy to reduce the exhaust gas temperature. This study aims to investigate the effect of injecting water into the exhaust gas at the pre-turbine of a turbocharged spark ignition engine. This study experimented on a 1.3-L 4-cylinder turbocharged engine to collect engine data for computational fluid dynamics (CFD) baseline model validation. A one-dimensional engine model was then developed based on the 1.6-L 4-cylinder turbocharged engine experiment using AVL BOOST software. The CFD model was used to investigate the effects of water injection pressure, pipe diameter, and water injector location. The CFD results showed that a 50 mm connecting pipe with 4 bar of injection pressure gives the largest reduction in exhaust temperature. The CFD results were then applied to the one-dimensional engine model. The engine model simulation results showed that the fuel consumption could be reduced up to 13% at 4000 rpm during wide-open throttle and 75% engine load. The PTWI is a new approach, but this study has proved the potential of using water injection at the pre-turbine turbocharger to reduce the fuel consumption of a turbocharged SI engine

Recent advances in butanol production by acetone-butanol-ethanol (ABE) fermentation

Butanol can be produced from renewable sources via the acetone-butanol-ethanol (ABE) fermentation route to create biobutanol or from fossil fuel to create petrobutanol. Despite the similar chemical properties of these two forms of butanol, the market penetration of biobutanol is still hindered due to its higher production costs compared to those for petrobutanol. This review article traces the history of the butanol industry and discusses recent advances in butanol production by ABE fermentation, with several novel approaches being highlighted. These approaches include searching for abundant and inexpensive substrates and optimising upstream and downstream processes. As butanol production by ABE fermentation consists of several critical stages, this review article divides the whole process into five significant steps: (1) feedstock selection, (2) upstream, (3) midstream, (4) downstream and (5) final products. Recent progress involving all stages along with their challenges and potential research routes are summarised. Recent progresses in the direct use of ABE as a biofuel are also reviewed in brief. Low butanol yield and end-product toxicity remain the major drawbacks of a typical butanol production by ABE fermentation. For successful biobutanol production, a number of critical issues should be considered. These include the development of clostridial and non-clostridial strains as well as innovative in-situ recovery methods integrated with the ABE fermentation process. Finally, future research direction of butanol production by ABE fermentation is presented in the last section of this article

Response surface methodology (RSM) for optimizing engine performance and emissions fueled with biofuel: Review of RSM for sustainability energy transition

Response Surface Methodology (RSM) is a statistical method to design experiments and optimize the effect of process variables. RSM is based on the principles of design of experiments or DOE. Design of experiments or DOE is a field of applied statistics that plans, conducts, analyses, and interprets controlled tests to assess factors that affect parameter values. Response surface methodology or RSM uses a statistical method for designing experiments and optimization. Despite the potential of response surface methodology to predict and optimize engine performance and emissions characteristics, a comprehensive review on RSM for biofuels, particularly for internal combustion engines (ICEs), is difficult to find. The review of response surface methodology is sometimes included together with other machine learning approaches such as ANN. Therefore, a review article that is exclusively written to address the specific of RSM for biofuel and ICE is required. This review article offers a fresh perspective on the application of RSM for biofuel in ICE. This article aims to critically review the RSM to optimize engine performance and emissions using biofuel. The study concludes with several possible research gaps for future works of RSM biofuel application. Although response surface methodology or RSM has drawbacks such as extrapolation inaccuracy outside the investigational ranges and discrete variables error, RSM has numerous advantages to design, model, estimate, and optimize biofuel for ICE with satisfactory accuracy. With its prediction and optimization capability, response surface methodology has the potential to assist the development of ICE optimization powered by biofuel for sustainability energy transition

Application of Elman and Cascade neural network (ENN and CNN) in comparison with adaptive neuro fuzzy inference system (ANFIS) to predict key fuel properties of ABE-diesel blends

Today, a growing interest to use Acetone-Butanol-Ethanol (ABE) as a biofuel has emerged. Fuel properties play important roles to determine engine’s performance, combustion, and emission behaviors. Yet, the determination of fuel properties is expensive and time-consuming. Previous studies on ABE did not provide information on how to predict its fuel properties. This study developed an Elman and Cascade neural networks (ENN and CNN) and compared their results with adaptive neuro inference system (ANFIS) to predict ABE’s key fuel properties. Three properties, i.e., calorific value, density, and kinematic viscosity were used as the target outputs, while ABE, acetone, butanol, and ethanol ratio were selected as the input parameters. The ENN and CNN models were trained using 10 different training algorithms, while the ANFIS model was examined using eight unique membership functions. To evaluate the prediction accuracy of each model, six different parameters were employed. Results showed that, compared to ENN and CNN, the ANFIS model gave the best performance accuracy with the least errors to predict the key fuel properties of ABE-diesel blends. For calorific value, density, and kinematic viscosity prediction, the best results of the ANFIS model were given by triangular, Pi curve, and trapezoidal membership functions, respectively. Therefore, ANFIS gave the best model of all the investigated models in this study