As fossil fuel reserves continue to diminish and environmental concerns intensify, the search for renewable, sustainable, and cleaner alternatives has gained momentum. Biodiesel derived from tobacco seed oil offers an eco-friendly and non-edible option for compression ignition (CI) engines. In this study, tobacco seed oil methyl ester (TSOME) was blended with diesel at B10, B20, B30, and B40 ratios, each supplemented with 0.5 wt% cerium oxide (CeO2) nanoparticles to enhance combustion efficiency and emission behavior. A combined framework of experimental evaluation, machine learning (ML) prediction, and response surface methodology (RSM) optimization was employed. Performance and emission characteristics were assessed using a single-cylinder, four-stroke, water-cooled Kirloskar CI engine under varying loads (25–100%). Standard instrumentation measured brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), oxides of nitrogen (NOx), carbon monoxide (CO), hydrocarbons (HC), smoke opacity, and exhaust gas temperature (EGT). Results showed that B10 and B20 blends achieved efficiencies comparable to diesel at higher loads, with <1% deviation in BTE and BSFC. All biodiesel blends exhibited substantial reductions in CO, HC, and smoke emissions, although NOx emissions increased due to higher in-cylinder temperatures. Among the ML models, artificial neural networks (ANN) outperformed random forest (RF) and support vector regression (SVR), achieving R2 values above 0.99 in the experimentally studied operational field. RSM optimization identified B20–B30 blends at 75–100% engine load as the optimum operating range, balancing efficiency and emissions. The findings indicate that biodiesel mixtures in which the CeO2 nano-additive TSOME is used are a feasible and compatible partial diesel replacement in compression-ignition engines that are run under controlled conditions, and hence investments into the real-time combustion diagnostics, adaptive injection sets, and tailored fuel-nanoparticle complexes are justified.

Solar desalination is a technology that demonstrates an environmental innocuous method of freshwater generation in water-stressed areas; however, the application of the technology is limited by low thermal efficiency and unpredictable performance in different climatic conditions. This paper presents an experimental study of a inclined solar still, which has been complemented with a phase-change material (PCM) and optimized using a hybrid Genetic Algorithms (GA) and Machine Learning (ML) algorithm. Design and operating variables, such as the angle of the glass cover, the depth of the water in the basin, and the temperature of the glass surface were all optimized to achieve maximum thermal efficiency as well as to achieve maximum distillate yield. It was experimentally shown that the optimized configuration achieved a peak thermal efficiency of about 44%, and the highest freshwater yield of 4.9 L m-2 day-1. The combined GA-ML approach, in turn, will optimize the usage of energy and predictability of its operations, which in turn facilitates the evolution of smart and low-emission solar desalination systems allowing it to be used in decentralized and off-grid water-supply systems.

Biodiesel is a good renewable source as a substitute of the traditional diesel, but the oxidative stability is low limiting its extensive use in storage. This analysis compares oxidative stability and storage of soybean biodiesel (BS100) and macauba biodiesel (BM100) and blends (BSM10-BSM50) at ambient temperatures during 90 days. Gas chromatography mass spectrometry (GC-MS) and Fourier-transform infrared spectroscopy (FTIR) were used to analyze the chemical composition and functional group characteristics of the newly developed products, whereas physicochemical properties such as water content, acid value, cold filter plugging point, and oxidation stability were periodically measured. The results of GC-MS showed that macauba bio-diesel is rich in saturated fatty acids (65.01%), where lauric acid (36.37%) and thus provides good oxidation resistance. Addition of macauba biodiesel to soybean biodiesel greatly enhanced the oxidative stability with 4.5 h (BS100) and 9.2 h (BM100) corresponding to induction phases. The amount of water BS100 contained increased by about 325%-363% and the acid value increased between 0.50 and 0.86 mg KOH/g during the storage period of 90 days, a fact that revealed a gradual degradation of the material. Blended fuels on the other hand did not experience the same steep rise in water content and acidity. In spite of the changes, the level of kinematic viscosity (3.0-6.0 mm(2)/s) and density (850-900 kg/m(3)) stayed at an acceptable level. The results show that, macauba biodiesel enhances the oxidative stability of soybean biodiesel within the first storage period; notwithstanding, severe deterioration causes it to be ineffective in long-term storage stability at ambient conditions. Nevertheless, the fact that the degradation becomes important after 60 days is an indication that more stabilization measures should be employed in case of long-term storage.

Abstract This paper is an experimental study of the heat transfer of silicon carbide (SiC) and boron nitride (BN) nanoparticles in a tube-in-tube (TIT) heat exchanger setup. SiC nanoparticles (40–60 nm) and BN nanoparticles (30–50 nm) were dispersed in water with a maximum volume concentration of 2.0 vol%. Thermal conductivity improvement was 7.30% at 0.2 vol% concentration of BN nanofluid and 4.20% of SiC nanofluid. Relative to this, the convective heat transfer performance of SiC nanofluids was better as a 24.6% enhancements in the heat transfer coefficient was attained compared to the base fluid. Of all the concentrations tested, the best concentration of the two types of nanoparticles was found to be 0.2 vol% concentration. The increase in flow rate (0.3 to 0.7 m3/h) led to an increase in the heat transfer efficiency by 92%. Nevertheless, the rate of erosion was the highest at flow rates exceeding 0.084 m3/h, which explains the importance of a close control of operations. Altogether, SiC nanofluids with the concentration of 0.2 vol% can manifest a high potential of enhancing industrial cooling systems and considerations of erosion to facilitate sustainable thermal management.

This study investigates a dual-fuel enhancement strategy that integrates Fe2O3-SiO2 hybrid nano-additives with staged hydrogen enrichment to overcome the combustion inefficiencies and emission drawbacks commonly observed in Jatropha Methyl Ester (JME) biodiesel. While previous studies have generally examined either hydrogen enrichment or nanoparticle additiona isolated interventions, this research uniquely evaluates their combined effects under systematically controlled engine operating conditions. Experiments were conducted on a single-cylinder, direct-injection (DI) diesel engine using six fuel configurations, ranging from neat diesel to B20 blends containing 50 ppm Fe2O3-SiO2 and hydrogen injection rates of 2-6 L/min, tested across five discrete load levels. The results demonstrate that the combined nano-additive and hydrogen-enriched fuel promoted enhanced premixed combustion, accelerated flame propagation, and shortened ignition delay, resulting in a peak brake thermal efficiency (BTE) 32.5%, a 15.2% increase over diesel. The optimized blend (B20N50H4) had a 24.7% thru cut in brake-specific fuel consumption (BSFC) and comparable NOx emissions as diesel, with the success of an approximate 24% reduction in smoke amplification. There were also better emission profiles, as the emissions were 24% lighter than that of conventional diesel, which highlights the catalytic quality of the hybrid nanoparticles and the clean-burning nature of hydrogen. These indicate that the combined approach of hydrogenenrichment and nanoadditive allows clean and more efficient combustion of bio-diesel without the engine architecture requirements. In line with this, this solution is an acceptable avenue to development and implementation of low-carbon dual-fuel technologies.

The increasing need for sustainable, lightweight and multifunctional materials has boosted the creation of natural fiber-reinforced polymer composites (NRF) with increased mechanical and vibroacoustic functions. Sisal–maize hybrid polymer composites that are reinforced with natural seaweed bio-fillers were compression-molded in this study, and their mechanical, vibrational, and acoustical characteristics were systematically studied. The content of seaweed filler (0–8 wt

Polymer composites have replaced traditional materials in offshore and onshore applications due to their outstanding mechanical qualities and corrosion resistance. This study examined woven and random mat glass fiber polyester matrix composites’ tensile, flexural, impact, and vibrational properties. Mechanical properties and free vibration were affected by woven and random fiber mat, fiber ratio, and coupling agent. Fiber breakage on ruptured samples during tensile testing was also examined. Mechanical characteristics peaked at 40

The growing global demand for sustainable materials has driven the shift toward bio-based fiber composites to replace synthetic polymers. However, limited studies have addressed the poor thermal stability and interfacial adhesion of natural fibers, particularly the unexplored Acacia leucophloea bark fiber and Lotus Seed Shell Powder combination. This study develops Acacia leucophloea bark fiber (ALF) reinforced epoxy composites with Lotus Seed Shell Powder (LSSP) as a bio-filler, constant fiber content at 30 wt% and LSSP from 1 to 3 wt% at an interval of 0.5wt%. The fibers were alkali-treated (5 % NaOH, 45 min, room temperature), cut to 20 mm, and dried, while LSSP was mechanically and ultrasonically dispersed in the epoxy prior to hand layup casting. Seven composite specimens were fabricated without and with fiber and differing weight ratios of LSSP filler to evaluate their effects on the mechanical and thermal properties of the composite materials. The integration of LSSP fillers markedly enhanced the mechanical and thermal performance. Compared to the control sample (pure epoxy), the optimized composite (A30L3) exhibited significant improvements with increases of 47.29 % in tensile strength (TS), 33.66 % in flexural strength (FS), 39.71 % in impact strength (IS) and 28.28 % in Shore D hardness. Thermal conductivity increased by 30.28 %, while the coefficient of linear thermal expansion (CLTE) decreased by 35.49, indicating enhanced thermal stability. The thermal stability of the composites, as determined by thermogravimetric analysis (TGA), varied from 235 to 445 degrees C, indicating a notable enhancement compared to unaltered natural fiber composites. Dynamic mechanical analysis demonstrated the improved viscoelastic properties, signifying superior thermal durability and dimensional stability under dynamic heating conditions. One-way ANOVA and Tukey's HSD test revealed statistically significant differences (p < 0.0001) across all composite groups. Fourier-transform infrared (FTIR)spectroscopy verified the existence of C-H bond vibrations associated with cellulose in AL fiber reinforcement, and XRD shows the crystallinity index of 30.44 %. These composites demonstrated robust antibacterial characteristics, thereby improving functional value. Surface morphological and elemental analysis demonstrated the strong bonding at the interface between AL fibers and the matrix reinforced with LSSP filler, hence reinforcing the structural integrity of the materials. The A30L3 composites consistently exhibited superior mechanical and thermal properties. This work is novel in demonstrating that the combination of ALF and LSSP produces sustainable, multifunctional composites with enhanced mechanical and thermal properties, highlighting their potential for lightweight structural applications.

Refrigeration methods in secluded regions are a major issue for sustaining the quality of perishables like vaccines and food. Traditional refrigeration systems, including kerosene and gas-powered units, often suffer from interruptions in the supply of fuel. Additionally, they do not satisfy the stringent criteria set by the World Health Organization (WHO) Performance, Quality and Safety (PQS) system requirements. While solar-powered refrigeration is an alternative, existing systems heavily rely on battery storage, which increases maintenance, costs, and limits system lifespan. This study analyses the operational efficiency of a solar-powered VISI cooler with a DC compressor-based refrigeration system, adding and omitting phase change materials (PCM). The experimental findings demonstrate that incorporating PCM significantly enhances energy efficiency by reducing average power consumption from 48 to 40 W. This decreased power consumption increases suction pressure by 0.13 bar and decreases compressor output pressure by 0.76 bar. These improvements aid in optimised thermal regulation which lowers dependency on conventional energy storage methods. The research indicates the role of collaborative partnerships between governments, research bodies, and technology developers aimed at fostering sustainable and innovative peak-shaving refrigeration solutions geared towards off-grid systems.

The research was investigated Turkey Berries drying capability using Active Mode Indirect Solar Dryers at Kovaipudur in Coimbatore, India. The conic-shaped Thermal Energy Storage (TES) covered the solar collector selectively and photovoltaic (PV) panels used to power divergent ducts equipped with DC blowers to enhance the AMISD. An energy analysis revealed meaningful distinctions between the AMISD systems equipped with TES and those operated without TES. The implementation of Thermal Energy Storage brought about a 89.6% collector efficiency rate that exceeded the results commonly reported in related PCM-based solar drying platforms. The proposed combination of a conic-shaped PCM module and a PV-powered diverging duct serves as the main cause behind this performance gain by supporting heat retention and enhancing airflow distribution. The solar dryers achieved better overall efficiency when using TES because they reached 15.23% efficiency compared to 14.8% without TES. The TES system increased the Energy Utilization Ratio up to 29.31 from its initial value of 28. Without TES AMISD used 1384 W of energy but with the implementation of TES it only needed 1268 W to function properly. The information about energy output demonstrates TES produces maximum energy consumption efficiency both with and without Phase Change Material (PCM). The PCM integration in the Specific Collector Area (SAC) improved its energy efficiency from 6.84 to 7.1%. The Sustainability Index scores achieved 8.1 when PCM was included in the experiments while the baseline scores remained at 8.01 without PCM application. Regardless of positive findings the actual experimental data fell short of projecting greenhouse dryer service expectancy to last for 35 years. The study demonstrates that using AMISD with PCM works effectively with improved energy performance while diminishing environmental influence and decreasing operational costs. Based on present circumstances in the region Turkey Berries drying with these specifications appears feasible and sustainable.

Background: A comparative regression modelling of fluidization bed data parameters is performed in this work using different algorithms. Computational fluid dynamics (CFD) modelling of particle and fluid flow characters using two-fluid Eulerian-Eulerian model. RNG k-epsilon turbulence coupled with kinetic theory of granular flow was also combined. The developed numerical model is used for generating the fluidization related data of parameters like turbulent viscosity, turbulent dissipation rate, solid velocity, solid volume fraction, granular temperature, and turbulent kinetic energy. Methods: Comparative modelling and performance analysis between ensemble learning, supervised learning, and neural networks is performed for the mentioned fluidized bed parameters. Ensemble Regression algorithms: Gradient boosting regressor (GBR), Voting regressor (VR), and Random-forest regressor (RFR), supervised learning algorithm - Decision tree (DT), and Deep Artificial neural network (ANN) models are used for the data mapping of fluidization parameters. Performance metrices are accessed in details to compare the modelling results or the algorithms in details for each fluidization parameter. Findings: From the modelling of this data it is found that numerical data is highly non-linear. DT and RFR algorithms are the most accurate algorithms that predicted with >90 % of accuracy in each case. VT and GBR trained and tested with around 85 % accuracy in most cases but failed in prediction of granular temperature. ANN also sufficiently provided good accuracy while it also failed to predict granular temperature. Solid volume fraction, turbulent kinetic energy, turbulent viscosity, and turbulent dissipation rate were modelled perfectly with all the algorithms. Among all the parameters, turbulent viscosity during training and testing from each model is highly accurately modelled from each of the algorithm with prediction accuracy >90 %.

The increasing world need to cleaner and renewable fuel has fast tracked the development of alternative biodiesel especially non-edible sources. When the 'Tobacco seed oil biodiesel (TSOB) is augmented with nanocatalysts, there is a potential route towards bending fossil diesel and better performance and clean air. The paper discusses the performance, combustion and emission characteristics of a compression ignition (CI) engine, which is running on TSOB blends both in presence and absence of 0.5 % by weight cerium oxide (CeO2) nano particles. The proportions of three blends B20, B40, and B60 were tested during variable loads condition. Data indicate that 0.5-wt percent addition of nanoparticle CeO2 got the best results in the B40 mixture. The thermal performance of the brake improved to 29.2 % and specific fuel consumption was reduced to 0.21kg/kWh, which exceeds those of neat diesel and untreated blend of biodiesel. The maximum value of the cylinder pressure attained 77 bar, the highest heat release rate equal to 36 J/degrees CA indicated a high combustion kinetics of CeO2 assisted oxidation and catalytic surface action. Analyzing the emissions allowed the demonstration of a large decrease in both carbon monoxide and unburned hydrocarbons (by 20 % and 25 %, respectively) as well as in particulate matter (blended down by about 15 %), relative to baseline blends. Even though with the utilization of biodiesel there was usually an increase in the NOx emissions, the CeO 2 addition was the effective remedy to this increase. In the research, it is established that in addition to presenting better thermal and combustion efficiency, nanoparticles-aided biodiesel present significant reductions in harmful emissions. This makes B40 + 0.5 % CeO2 a plausible and techno-environmentally friendly alternative to diesel use in CI engines, and to the adoption of more sustainable transport and decentralized energy systems.

The usage of magnesium alloys is limited because of their deprived tribological performance. Hence, the extant effort is to develop the AZ91 matrix composites augmented with 12wt.% zirconium diboride (ZrB2) through the stir casting route. Metallurgical examinations depicted the presence and scattering of the ZrB2 in the matrix with no defects and pores. A pin-on-disc device was used in the dry sliding wear tests, which were conducted on hardened counter discs. The experiment was performed according to Taguchi's L9 array by utilizing three factors, such as load (L), sliding velocity (V), and sliding distance (D). The gray relational analysis has been employed to predict the wear rate (Wr) and coefficient of friction (CF) for the synthesized composite. Analysis of variance (ANOVA) was used to find out the consequences of the involved variables on the outputs. The experimental finding shows that the lower Wr and CF were produced at 10N of L, 2m/s of V, and 1500m of D. ANOVA results indicate that L has the most consequence that affects the Wr and CF, followed by D and V, respectively.

This study investigates the production of biodiesel from pyrolytic oil obtained from Delonix regia pods (DRP), a novel biomass feedstock underutilized in renewable energy research. The research employs a dual-pathway esterification approach, utilizing methanol (methanolysis) and ethanol (ethanolysis) to optimize biodiesel production. Pyrolysis of 100 g DRP at 450 degrees C yielded 41 g bio-oil. From this, 250 mL of oil was processed into 200 mL methyl ester (MB20) and 190 mL ethyl ester (EB20), corresponding to biodiesel yields of 17.4 % and 16.6 % (g/g DRP), respectively. Comparative analysis revealed that MB20 outperformed EB20 in critical fuel properties and engine performance. MB20 exhibited a viscosity of 2.8 cSt and a heating value of 40.25 MJ/kg, surpassing EB20's viscosity of 3.2 cSt and heating value of 39.65 MJ/kg. Engine tests demonstrated a 2 % higher brake thermal efficiency for MB20 compared to EB20, along with a significant reduction in emissions-NOx (654 ppm), CO (0.17 %), and HC (34 ppm)-making MB20 a more sustainable and efficient alternative and also shows that MB20 blends has closer fuel properties of diesel and thus MB20 blends has closer BTE and lower emission than diesel. The study further demonstrated the superior oxidative and thermal stability of MB20, evidenced by an 11 % lower viscosity increase during storage compared to EB20, highlighting its potential as a viable alternative to conventional diesel without requiring engine modifications. This study addresses the scientific niche of utilizing underexplored biomass feedstocks like DRP for sustainable biodiesel production, contributing to the optimization of renewable energy technologies. Future research should focus on scaling up production, optimizing reactor designs, and enhancing economic feasibility to support global energy sustainability goals.

Flat plate solar thermal collectors (FPCs) are widely used in energy engineering to capture solar energy through flat plates and feature with hybrid nanofluid that improves the heat transfer rate, ensures a uniform temperature distribution, and demonstrates good thermal efficiency. However, several challenges persist, including low absorption, variations in thermal conductivity caused by heat loss/ agglomeration of nanoparticles, and moderate thermal efficiency. This research aims to address these challenges and enhance the thermal performance of FPCs by applying different thicknesses of graphene nano-coatings and utilizing a 2.45 GHz microwave heating process, which has a penetration depth of 1 cm. This process is supported by silver-coated fabric to serve as a microwave shield. A hybrid nanofluid consisting of copper oxide (CuO) and zinc oxide (ZnO) in a 50:50 ratio at a concentration of 3 vol% is employed to improve the heat transfer rate by increasing surface contact with the absorber tube. The study investigates the effects of graphene nano-coating, combined with the microwave heating process, on the functional behaviour and absorptivity properties of the FPCs. The results are compared to those of FPCs operated without the graphene nano-coating and the hybrid nanofluid. The findings reveal that applying a 75 nm graphene nano-coating, along with the 2.45 GHz microwave heating process and a 3 vol% concentration of hybrid nanofluid, resulted in the following maximum values: absorption of 1700.3 nm, thermal conductivity of 0.84 W/mK, fluid temperature of 83.2 degrees C, energy storage of 742.5 kJ, thermal cyclic resistance of 1.63, and efficiency of 62.5 %.

Solar water heaters as a renewable energy solutions technology are being increasingly requested globally and are a critical technology route towards achieving Sustainable Development Goal 7 (SDG 7) of ensuring access to affordable, reliable, sustainable, and modern energy for all. This research investigates the enhancement of solar water heater performance through the integration of phase change materials (PCMs) with three distinct nanoparticles: copper powder (Cu), silicon carbide (SiC), and boron nitride (BN). Results of statistical analysis showed that heat transfer rates enhanced by up to 71.9 %, relative to conventional PCM, were achieved with Cu nanoparticles as a result of varying thermal conductivity enhancement compared to the rest of the nanoparticles. Thermal conductivities of silicon carbide (SiC) nanoparticles in the 82-100 W/m & sdot;K range led to a 25 % composite material thermal conductivity increase. The system's heat retention performance was improved by up to 60 percent, largely due to the thermal stability of boron nitride (BN) nanoparticles. The incorporation of these nanoparticle enhanced PCMs yielded large gains in system efficiency. With optimized configurations, the solar fraction was increased to 75 %, from 35 %, and the heat loss coefficient was reduced to 14.3 W/m2 & sdot;K from 22.5 W/m2 & sdot;K. These improvements are in line with targets under SDG 7, by increasing energy efficiency and growing the share of renewable energy in the global energy mix. The system validated the Energy Efficiency by SDG 7 initiative to double the rate of energy efficiency improvements by 2030 with overall efficiency improvement 47.6 % without PCM, to 52.0 % with nanoparticle-enhanced PCM.

Conventional solar driven desalination systems have suffers from low thermal efficiency and salt accumulation. This paper examines the use of black silicon and carbon nanotube based surface coatings to increase photo-thermal performance of solar desalination systems. The absorber plates were spray coated with these coatings using a low cost spray coating technique and tested in outdoors weather conditions. The maximum evaporation rate reached 2.65 kg/m2 center dot h under solar irradiance of 870 W/m2 for the coated system, compared to 1.12 kg/m2 center dot h for the uncoated control. Consequently, more than 99 % of the total dissolved solids (TDS) concentration was removed from the collected water, as confirmed by spot water tests that fell within WHO's potable water limits. First, the coatings showed sufficient thermal stability after 1000 hat 900 degrees C and a preliminary economic analysis indicated a projected coating cost ranging from USD 8-12/m2 with a return on investment favorable for offgrid deployment. This work distinguishes itself from the previous studies by simply combining spectrally optimized nanomaterial with scalable fabrication with the evaluation of environmental impact, anti-fouling behavior and ion rejection mechanisms. These results indicate that black silicon-carbon nanotube composites are a durable, efficient and scalable approach toward sustainable solar based desalination technologies.

Solar desalination performance enhancement through the use of copper and silicon carbide nanoparticles in solar still systems is discussed in this research. The objective of the work is to improve thermal conductivity, heat absorption, and general efficiency of the solar desalination processes. For the sake of comparison, two similar solar stills were prepared in order to investigate influence of these nanoparticles under standard conditions. The experimental setup incorporated specified amounts of Cu and SiC nanoparticles into the working fluid of the solar stills, productivity, and efficiency being evaluated under different operational conditions. The outcome shows enhanced day-to-day desalination capability through the addition of nanoparticles. High thermal conductivity of copper nanoparticles enhanced the efficiency of the solar still by 9.62

The global production of biodiesel in 2023 amounted to 34 billion liters because compression ignition engines need environmentally friendly fuel alternatives. The research investigates Annona biodiesel in combination with machine learning (ML) and STATCOM (Static Synchronous Compensator) technology to enhance power quality along with noise and vibration control in CI engines. Engine performance testing of diesel and B20-20% Annona biodiesel occurs under controlled conditions at rpm from 1200 to 2400 at which point STATCOM implemented both power factor improvement and current harmonic reduction for enhanced power quality. The B20 blend delivered 1.2400 kW output power while operating at 2400 RPM but generated a lower delivery than diesel engines produced at 4.8 kW. At a torque peak zone between 2100 and 2400 rpm diesel fuel exhibited enhanced performance because it had a better calorific value and reduced viscosity. Tests demonstrated B20 decreased engine vibrations to 16.8 m/s2 in contrast to diesel's 21.1 m/s2 level thus indicating enhanced operation smoothness. Engine speed was varied from 40 Hz/1200 rpm to 80 Hz/2400 rpm during vertical testing. The improved combustion process in B20 resulted in reduced noise emissions that followed engine speed and vibration pattern variations. The results of Multiple Linear Regression analysis displayed robust capability through its R2 scores of 0.883 and 0.947 but Support Vector Machine produced average accuracy with R2 scores of 0.722 for both parameters1.STATCOM and ML optimization of Annona biodiesel demonstrates evidence that this biodiesel can be used as an acceptable alternative fuel. Engine operation using power quality upgrades from these technologies produces better power quality at reduced vibration and noise levels than standard diesel fuel.