Search

This study investigates the factors influencing the adoption of m-tourism apps in Bangladesh and their impact on being free from environmental challenges. Utilizing Structural Equation Modeling (SEM) and Necessity Condition Analysis (NCA), the research explores how various predictors affect the Intention to Adopt Tourism Apps (IATA) and, subsequently, the outcome of being free from environmental challenges (FEC). SEM results reveal that Perceived Usefulness (PU), Cultural Exchange of Technology (CET), Social Amusement and Entertainment (SAE), and Tourists' Lifestyles (TL) significantly enhance IATA, with IATA having a strong positive impact on FEC. Conversely, Attitudes Towards Technology (ATT) and Government Supportive Roles (GSR) show limited influence on adoption. NCA identifies CET, IATA, SAE, and TL as critical predictors with medium to large effect sizes, particularly at higher thresholds, indicating their role as major bottlenecks. Government Supportive Roles and Tourist Technology Readiness are less influential. These findings offer valuable insights for developers and policymakers to focus on enhancing the perceived value, cultural exchange, and lifestyle compatibility of m-tourism apps to improve adoption rates and effectively address environmental challenges.

Purpose – Drawing on the transformational leadership (TL) and knowledge-based view (KBV) theory, the present study investigates the impact of TL on radical innovation (RI) through the mediation of knowledge management capabilities (KMCs) and moderation of competitive intensity (CI) of textile and apparel industries with an Asian context. Design/methodology/approach – Data were collected from the relevant stakeholders of the industry-university collaboration teams with a structured survey questionnaire. Working with 304 textile and apparel industry respondents, structural equation modeling based partial least square (PLS-SEM) is used to test the conceptual framework. PLS-SEM technique was applied to test the hypothesis using Smart-PLS 3.8 packages program. Findings – The results proposed TL has a positive impact on KMC and RI. Furthermore, the study reveals KMC positively mediated the relationship between TL and RI. This mediation is conditional on the moderating role of CI for the KMC (knowledge acquisition capability + knowledge-sharing capability) path to RI. Conversely, moderation of CI is insignificant and does not influence on fostering RI. Practical implications – Leaders and managers have realized creative and innovative culture is built within the organizations by leader-follower collaboration through actual knowledge acquisition and knowledge sharing. Moreover, industry policymakers and practitioners establish the knowledge management department to enhance the innovation culture among the firms' stakeholders to encourage RI to sustain the global business market. Originality/value – The study has introduced KMC as a mediator and CI as a moderator in the proposed model between TL-RI and KMC-RI. Further, it explores the linkages between TL, KMC, CI and RI.

A thermodynamic model was developed for combustion, performance, and emissions with a reference diesel fuel, a 10 vol% methanol blend with 90 vol% diesel, a 10 vol% ethanol with 90 vol% diesel and a 4% hydrogen fumigating in the inlet port along with diesel direct injection. The diesel and two alcohol blends (10% methanol–90% diesel, and 10% ethanol–90% diesel) was directly injected into the cylinder, while hydrogen was fumigated at the inlet port. The model was developed by commercial GT-Suite software. Besides engine performance, exergy and energy rates were estimated for the four fuels. Among the four fuels/fuel blends, hydrogen fuel (4% fumigated hydrogen) shows the best performance in terms of exergy, energy rates, specific fuel consumption, power, and greenhouse gas emissions. Regarding greenhouse gases, carbon dioxide was only considered in this investigation as it contributes to a significant detrimental effect on environmental pollution.

A comprehensive fuel property using neat diesel, neat tire (100% tire oil after distillation of crude tire oil from pyrolysis process) oil, diesel–tire oil blend and diesel–tire oil–biodiesel blends were investigated in this study. The tire oil was derived from waste tire by pyrolysis process at a temperature of 450 °C. The tire oil was upgraded by the fractional distillation process. Different proportions (10 vol% and 20 vol%) of waste tire oil were mixed with a reference diesel fuel. Various ratios, including 10 vol% and 20 vol% biodiesel was blended with waste tire oil and waste tire oil–diesel blends to examine the fuel properties with a target to use the different fuel blends as compression ignition (CI) engine’s fuel. A novel pumpkin seed oil (Cucurbita pepo) biodiesel was chosen due to its abundant availability and renewable nature. The reason for blending pumpkin seed oil–biodiesel is to improve the waste tire oil fuel properties and investigate the influence of fuel oxygen on different fuel properties. Binary blends, including tire oil–diesel, tire oil–biodiesel, and ternary blends, including diesel–tire oil–biodiesel, were prepared for the tests. The properties tested in this investigation were density, viscosity, higher and lower heating value, smoke limit, flash point, fire point, aniline point, pour point, cloud point, cetane number, sulphur and carbon residue, proton nuclear magnetic resonance (1H NMR), Fourier transform infra-red (FTIR) spectroscopy and elemental analysis (CHONS). The comprehensive fuel property results showed that all binary and ternary blends show similar properties compared to reference diesel. Although the binary blends of tire oil and biodiesel indicate a little inferior property than reference diesel fuel, they can be used as fuels for compression ignition engines.

This study aims to develop a one-dimensional model to investigate the effect of hydrogen share in gasoline fuel on the performance, combustion, and exhaust emissions of a gasoline direct-injection engine. Iso-octane was used as a reference fuel to compare performance, combustion, and emission parameters. The model was developed using commercial GT-Suite and ANSYS software. The simulation results using GT-Suite were validated with the published data and ANSYS results. The hydrogen fractions were varied from 0% to 11.09% to validate the simulation results with the published results. The investigation continued with three higher hydrogen fractions (15%, 20% and 25%) to study the performance, combustion, emissions, and sustainability parameters. Compared to neat gasoline, hydrogen-shared fuels show a maximum 2% higher exergy efficiency, 51% higher exergy and 42% energy rates while reducing carbon dioxide (CO2) emissions by 51% with a penalty of nitrogen oxide emissions (NOx) by 62% at an excess ratio of 1.3. Other novel findings, including higher sustainability indices, lower depletion potentials, and lower unitary cost indices with higher-fraction hydrogen fuels, suggest that they are environmentally and economically sustainable. In the second part of this study, the NOx formation mechanism and its associated factors, including in-cylinder temperature, heat transfer rate, cumulative heat release, and burned rate, were confirmed and compared with gasoline and neat ethylene.

This work investigated engine performance and emissions using waste tire oil-diesel-biodiesel blends. A sustainable fuel glycine max biodiesel was blended with the tire oil-diesel blends to improve performance, combustion, and exhaust emissions. The seven fuels including a 100% diesel 10–30% waste tire oil to 90-70% diesel, 10% tire oil +10% biodiesel +80% diesel, 30% tire oil+10% biodiesel+60% diesel and 10% biodiesel+90% diesel was used as fuels in a direct injection diesel engine. Up to 30% (vol) waste tire pyrolysis oil was blended with diesel. More than 30% of waste tire pyrolysis oil shows inferior solubility issues and inferior engine performance and emissions. Thus, this investigation was limited to 30% waste tire pyrolysis oil. All fuel blends showed similar properties to diesel. With similar engine performance, like torque, power, efficiency, energy, and exergy metrics, the blends showed insignificant variations in emissions (carbon dioxide, nitrogen oxide) compared to a reference diesel fuel. Interestingly, the experimental results were compared with the modelling results, and the maximum variations between them were 10%. The outcome of this research can promote waste tire pyrolysis oil as an alternative fuel for diesel engines and accords with alternative energy development initiatives all over the world.

This paper reviews and discusses the potential of papaya seed and stone fruit kernel biodiesels — the two sources of 2nd generation transport biodiesels in Australia. The challenges associated with biodiesel production and their possible solutions, particularly on feedstock selection, oil extraction, conversion of oil into biodiesel, biodiesel storage and transport, costs of production and the information needs for commercialising these sources of biodiesels are discussed, along with the eco-friendly attributes of these biodiesels to Australian transport sector. Some researchers report that the use of papaya seed and stone fruit kernel biodiesels reduce engine power only 2 to 5%), however significantly reduce harmful engine emission such as HC reductions of 9 to 19%, PM reductions of 19.5 to 35% and CO reductions of 11 to 29%. Keywords: Papaya seed, Stone fruit kernel, Apricot, RSM, Biodiesel, Renewable energy, Australia, Optimisation, Challenges, Engine performance, Emission, Second generation

Physico-chemical properties of microalgae biodiesel depend on the microalgae species and oil extraction method. Dioctyl phthalate (DOP) is a clear, colourless and viscous liquid as a plasticizer. It is used in the processing of polyvinyl chloride (PVC) resin and polymers. A new potential biofuel, hydrothermally liquefied microalgae bio-oil can contain nearly 11% (by mass) of DOP. This study investigated the feasibility of using up to 20% DOP blended in 80% diesel fuel (v/v) in an existing diesel engine, and assessed the performance and exhaust emissions. Despite reasonable differences in density, viscosity, surface tension, and boiling point, blends of DOP and diesel fuel were found to be entirely miscible and no separation was observed at any stage during prolonged miscibility tests. The engine test study found a slight decrease in peak cylinder pressure, brake, and indicated mean effective pressure, indicated power, brake power, and indicated and brake thermal efficiency with DOP blended fuels, where the specific fuel consumption increased. This is due to the presence of 16.4% oxygen in neat DOP, responsible for the relatively lower heating value, compared to that of diesel. The emission tests revealed a slight increase in nitrogen oxides (NOx) and carbon monoxide (CO) emissions from DOP blended fuels. However, particulate matter (PM) emissions were lower from DOP blended fuels, although some inconsistency in particle number (PN) was present among different engine loads.

Physical and chemical properties of biodiesel are influenced by structural features of the fatty acids, such as chain length, degree of unsaturation and branching of the carbon chain. This study investigated if microalgal fatty acid profiles are suitable for biodiesel characterization and species selection through Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis. Fatty acid methyl ester (FAME) profiles were used to calculate the likely key chemical and physical properties of the biodiesel [cetane number (CN), iodine value (IV), cold filter plugging point, density, kinematic viscosity, higher heating value] of nine microalgal species (this study) and twelve species from the literature, selected for their suitability for cultivation in subtropical climates. An equal-parameter weighted (PROMETHEE-GAIA) ranked Nannochloropsis oculata, Extubocellulus sp. and Biddulphia sp. highest; the only species meeting the EN14214 and ASTM D6751-02 biodiesel standards, except for the double bond limit in the EN14214. Chlorella vulgaris outranked N. oculata when the twelve microalgae were included. Culture growth phase (stationary) and, to a lesser extent, nutrient provision affected CN and IV values of N. oculata due to lower eicosapentaenoic acid (EPA) contents. Application of a polyunsaturated fatty acid (PUFA) weighting to saturation led to a lower ranking of species exceeding the double bond EN14214 thresholds. In summary, CN, IV, C18:3 and double bond limits were the strongest drivers in equal biodiesel parameter-weighted PROMETHEE analysis.

Essential oils are derived from not-fatty parts of plants and are mostly used in aromatherapy, as well as cosmetics and perfume production. The essential oils market is growing rapidly due to their claimed health benefits. However, because only therapeutic grade oil is required in the medicinal sector, there is a substantial low-value waste stream of essential oils that can be used in the transportation and agricultural sectors. This study investigated the influence of orange, eucalyptus, and tea tree oil on engine performance and combustion characteristics of a multi-cylinder compression ignition engine. Orange, eucalyptus, and tea tree oil were blended with diesel at 10% by volume. For benchmarking, neat diesel and 10% waste cooking biodiesel-diesel blend were also tested. The selected fuels were used to conduct engine test runs with a constant engine speed (1500 RPM (revolutions per minute)) at four loads. As the load increased, frictional power losses decreased for all of the fuel samples and thus mechanical efficiency increased. At higher loads (75% and 100%), only orange oil-diesel blends produced comparable power to diesel and waste cooking biodiesel-diesel blends. Fuel consumption (brake and indicated) for the essential oil-diesel blends was higher when compared to base diesel and waste cooking biodiesel-diesel blends. Thermal efficiency for the essential oil-diesel blends was comparable to base diesel and waste cooking biodiesel-diesel blends. At higher loads, blow-by was lower for essential oil blends as compared to base diesel and waste cooking biodiesel-diesel blends. At 50% and 100% load, peak pressure was lower for all of the essential oil-diesel blends when compared to base diesel and waste cooking biodiesel-diesel blends. From the heat release rate curve, the essential oil-diesel blends ignition delay times were longer because the oils have lower cetane values. Overall, the low-value streams of these essential oils were found to be suitable for use in diesel engines at 10% blends by agricultural producers of these oils.

Due to the variability of Photovoltaic (PV) output, a forecasting framework is essential for grid connected PV plants to ensure a stable and uninterrupted power supply. Among existing prediction and forecasting algorithms, only some have attempted to provide a holistic framework for short and long-term forecasting of PV yield together using automated input feature selections and data cleaning features. Furthermore, it has been identified that many existing algorithms only predicted PV output instead of forecasting in future times; therefore, their reported accuracy needs to be upheld in forecasting scenarios. This paper has proposed a framework to streamline solar yield forecasting for both the short and long term to ensure effective integration of PV plant output with the main grid. The proposed framework has used a novel combination of XGBoost (eXtreme Gradient Boosting), time series seasonal decomposition and rolling LSTM (Long- and Short-Term Memory) model to address the need for a comprehensive forecasting framework in hourly, daily and yearly periods. Based on our experiment result, the developed framework has performed in 98% − 95% prediction accuracy with less than 0.15% normalized Root Mean Squire error (nRMSE). The framework has performed in 89%- 87% forecasting accuracy with less than 0.45% nRMSE. Both the prediction and forecasting performance of the proposed model have outperformed many benchmarks forecasting frameworks, including Long short-term memory (LSTM) based recurrent neural network (RNN), Full RNN (FRNN), Neural Network Ensemble (NNE), Neural Network with AdaBoost, and many more as detailed in our comparative study section.

This work revealed the investigation of the Casson nanofluid flow's MHD (magneto-hydrodynamic) unstable boundary layer characteristics in the simultaneous transmission of thermoelectric and radiation on a stretched sheet. On MHD Newtonian and non-Newtonian (Casson) nanofluid flows, the cumulative impact of radiation and thermoelectricity has been addressed. Thermal radiation, Casson nanofluids, and MHD are pivotal in engineering and industry, transforming applications like heat exchangers, nuclear power plants, thermal energy storage, and advanced drug delivery systems. The problem-related partial differential equations have been formulated with boundary layer approximation. The boundary layer equations have been changed into dimensionless form with the help of appropriate dimensionless variables and parameters. Finite difference techniques have been employed to get the numerical solution via the FORTRAN 6.6a programming algorithm, and the numerical solutions have been illustrated graphically with the support of Tecplot-360 software. The consequences of the numerous parameters have been investigated using a variety of figures, with the amounts of the various parameters being revised. The simultaneous effects of thermoelectric and radiation on primary velocity, secondary velocity, and temperature profiles have been presented and discussed with critical physical properties such as skin friction in addition to Nusselt number. The combined effects of thermoelectric and radiation on streamlines and isotherms have been illustrated with line and contour flood views. The most significant finding is that the collective influence of thermoelectric and thermal radiation impacts promotes the physical phenomena of non-Newtonian (Casson) fluid flow comparatively more than Newtonian fluid flow. For the purpose of creating effective procedures, forecasting flow patterns, and guaranteeing product performance in a variety of industries, it is crucial to explain the Casson fluids. This model can also aid in blood flow simulation and risk assessment for thrombosis and other cardiovascular diseases.

Climate change and severe emission regulations in many countries demand fuel and engine researchers to explore sustainable fuels for internal combustion engines. Natural gas could be a source of sustainable fuels, which can be produced from renewable sources. This article presents a complete overview of the liquefied natural gas (LNG) as a potential fuel for diesel engines. An interesting finding from this review is that engine modification and proper utilization of LNG significantly improve system efficiency and reduce greenhouse gas (GHG) emissions, which is extremely helpful to sustainable development. Moreover, some major recent researches are also analyzed to find out drawbacks, advancement and future research potential of the technology. One of the major challenges of LNG is its higher flammability that causes different fatal hazards and when using in dual-fuel engine causes knock. Though researchers have been successful to find out some ways to overcome some challenges, further research is necessary to reduce the hazards and make the fuel more effective and environment-friendly when using as a fuel for a diesel engine.

This investigation explores the influence of oxygenated fuels on different energy and exergy parameters first and the second law of thermodynamics. The parameters were estimated based on the experimental data using thermodynamic Equations. Due to similar fuel properties to diesel, a Fischer–Tropsch fuel (FT100) was used as a base fuel (reference fuel) in the current investigation. Three biodiesel blends were prepared with Fischer–Tropsch fuel. Non-edible Jatropha biodiesel (Jatropha curcas) was selected to avoid food versus fuel conflict. All blends were prepared on a volumetric basis. The first blend was prepared using 25% of biodiesel and 75% of Fischer–Tropsch fuel and termed as B25. The second blend was made with 50% biodiesel and 50% Fischer–Tropsch fuel and designated as B50. The third and the final blend was formulated with 75% biodiesel and 25% Fischer–Tropsch fuel and abbreviated as B75. The three blends were also termed as oxygenated blends as they contain 3 wt%, 5.9 wt% and 8.7 wt%, respectively oxygen content in their molecule. Neat biodiesel (B100) was not targeted in this investigation. A new parameter “oxygen ratio” was used to make a correlation between different energy and exergy parameters with oxygen ratio. Instead of showing different energy and exergy parameters against equivalence ratio or excess air ratio, for better understanding, it is worth showing those parameters with oxygen ratio as all blends are inherently oxygenated. The results show almost insignificant variations in different parameters with the three oxygenated blends when compared to those of the FT100.