Search Results (90)

This paper proposes a data-driven framework for simulating turbocharger (TC) failure scenarios and modelling specific fuel oil consumption (SFOC) degradation in two-stroke low-speed marine diesel engines. A GaussianCopula model was fitted to the joint distribution of fifteen variables, using approximately eleven months of operational sensor data (n = 480 clean records, 4 h interval, January–December 2014) taken from a container ship. Three physically motivated failure scenarios were produced: turbine blade fouling, bearing wear and compressor surge. Predictive models trained on the real dataset achieved R² = 0.9998 for TC RPM and R² = 0.984 for fuel flow when using Gradient Boosting with 5-fold cross-validation. Feature importance analysis showed that the dominant determinants of TC speed were scavenging air intake pressure (35.3%) and engine power (MCR, 31.3%). Shaft power (45.5%) and TC RPM (19.3%) together explained most of the fuel consumption variance. Simulated failure scenarios produced SFOC increases of +6.6% (fouling), +9.6% (surge), and +13.3% (bearing wear) when compared to a normal operating baseline of 202 g/kWh, which is in line with published empirical data from MAN B&W engine performance curves. An IsolationForest anomaly detector trained only on normal operating samples flagged failure scenario records at a rate of 17.5–23.7%, which demonstrates that moderate-sensitivity early warning detection is feasible from routine sensor streams. The results show that TC condition monitoring could serve as a leading indicator of fuel-efficiency degradation. This has significant implications for condition-based maintenance planning and CII (Carbon Intensity Indicator) compliance. Full article

Anaerobic digestion is a viable pathway to mitigate environmental impacts from swine manure in tropical regions while contributing to circular economy strategies. However, no standardized or integrated framework currently exists that simultaneously quantifies the closure of energy, material, carbon, nutrient, and water loops at the farm scale. This research presents the techno-economic design and environmental assessment of a covered, mechanically agitated lagoon biodigester for a 10,000-head swine fattening module located in Matanzas, Cuba. The system is sized by integrating hydraulic, thermal, and structural parameters, and its economic viability is assessed through Net Present Value (NPV = $1.09 million), Internal Rate of Return (IRR = 32%), and a payback period of approximately three years. A comparative screening-level life cycle assessment shows that biogas-based electricity generation substantially reduces impacts on climate change, air quality, and fossil fuel scarcity compared with conventional diesel-based generation, with trade-offs in eutrophication and ecotoxicity. As a key methodological contribution, five quantitative circular economy indicators are proposed and calculated: the Energy Self-Sufficiency Ratio (ESSR = 1.71), the Waste Valorization Index (WVI = 0.91), the Decarbonization Index (DCI = 6.7), the Fertilizer Substitution Rate (FSR = 16.3 t N year⁻¹), and the Water Closure Factor (WCF = 1.30). These indicators show that the system achieves a 71% net energy surplus, valorizes over 90% of the input mass, avoids 6.7 times more emissions than it generates, replaces synthetic fertilizers, and returns more water than it consumes. The findings provide quantitative evidence that the convergence of mesophilic operation without auxiliary heating, high carbon intensity of the power grid, and availability of agricultural land enhances circularity performance in tropical covered lagoon bioreactors, and the proposed integrated indicator framework, aligned with ISO 59020:2024, provides a reproducible and transferable methodological basis for the comparative assessment of anaerobic digestion systems for livestock waste. Full article

This review analyzes the advances over a five-year period in the development of polymeric sorbents for the purification of aqueous media from key classes of pollutants: hydrocarbons (crude oil, diesel fuel), organic dyes, pharmaceuticals (antibiotics), pesticides, herbicides, volatile organic compounds, and polycyclic aromatic hydrocarbons. Attention is paid to the analysis of structure-property-performance relationships, with an emphasis on comparing materials derived from renewable natural feedstocks (such as cellulose, chitosan, terpenes, vegetable oils, and aloe vera) with synthetic polymers. The analysis reveals that biopolymer-based sorbents exhibit comparable or superior sorption capacities combined with environmental safety, biodegradability, and low cost. The key sorption mechanisms include physical adsorption, hydrophobic interactions, and electrostatic interactions. Despite persisting challenges related to scalability, stability in real-world environments, and the need for efficient regeneration protocols, a convergent approach that combines the advantages of modified natural polymers and functional synthetic components appears to be the most promising strategy for developing cost-effective and sustainable technologies for the restoration of water quality. Full article

The global transition toward carbon-neutral energy solutions has established Solid Oxide Fuel Cells (SOFCs) as a key technology for next-generation power generation. This work presents a comprehensive numerical study and multi-factor statistical analysis of an anode-supported SOFC fueled by synthetic diesel. A three-dimensional computational fluid dynamics model, validated against experimental data, was integrated with a Taguchi L₂₇ orthogonal array to systematically evaluate the influence of six key parameters: temperature, fuel mass flow rate, operating pressure, current load, flow channel configuration, and methane molar fraction. Statistical analysis through the signal-to-noise ratio and analysis of variance identified the operating current as the most significant factor affecting cell voltage, followed by the fuel mass flow rate and temperature. The experiments showed that the highest levels of all factors (except for the current, which had the lowest level) maximize electrochemical performance while maintaining a steam-to-carbon ratio (S/C) within a range of 0.83 to 0.92, calculated based on total carbon content, ensuring sufficient humidification for internal reforming across all tested fuel compositions. Furthermore, a multiple linear regression model was developed as a computationally efficient surrogate, demonstrating exceptional predictive accuracy with an R² of 0.9954 and a mean relative error of 1.76% across independent validation cases. These results provide a robust methodology for rapid design and sensitivity analysis of internal-reforming SOFCs, offering a precise tool for optimizing fuel utilization in high-temperature electrochemical systems. Full article

Aviation heavy-fuel piston engines are widely used in UAVs, general aviation, and military platforms due to their fuel efficiency and adaptability. However, emissions of NO_x, PM, and other pollutants pose significant environmental challenges. This paper reviews emission-reduction strategies, including combustion-chamber optimization, fuel-injection control, alternative fuels, and exhaust after-treatment technologies. Research indicates that optimizing combustion-chamber geometry, high-pressure common-rail injection, and turbulence enhancement improve combustion efficiency and reduce emissions. Biofuels, synthetic aviation fuels (SAF), and hydrogen-based fuels demonstrate strong potential for low-carbon emissions, while after-treatment technologies such as SCR, DPF, and EGR effectively mitigate NO_x and PM emissions. Despite technological advancements, challenges remain in balancing combustion efficiency with NO_x control and ensuring compatibility between EGR and combustion stability. Future advancements in intelligent combustion control, novel catalytic materials, low-temperature combustion, and high-efficiency after-treatment systems will drive aviation diesel engines toward lower emissions, higher efficiency, and greater intelligence, contributing to the green and sustainable transformation of aviation propulsion systems. Full article

Heavy-duty vehicles dominate global freight movement and primarily rely on fossil-derived diesel fuel. However, fluctuations in crude oil prices and evolving emissions regulations have prompted interest in alternative powertrains to enhance fleet energy resiliency. This study paired real-world operational data from a large commercial fleet with high-fidelity vehicle models to evaluate the potential for replacing diesel internal combustion engine (ICE) trucks with alternative powertrain architectures. The baseline vehicle for this analysis is a diesel-powered ICE truck. Alternatives include ICE trucks fueled by bio- and renewable diesel, compressed natural gas (CNG) or hydrogen (H₂), as well as plug-in hybrid (PHEV), fuel cell electric (FCEV), and battery electric vehicles (BEV). While most alternative powertrains resulted in some payload capacity loss, the overall fleetwide impact was negligible due to underutilized payload capacity for the specific fleet considered in this study. For sleeper cab trucks, CNG-powered trucks achieved the highest replacement potential, covering 85% of the fleet. In contrast, H₂ and BEV architectures could replace fewer than 10% and 1% of trucks, respectively. Day cab trucks, with shorter daily routes, showed higher replacement potential: 98% for CNG, 78% for H₂, and 34% for BEVs. However, achieving full fleet replacement would still require significant operational changes such as route reassignment and enroute refueling, along with considerable improvements to onboard energy storage capacity. Additionally, the higher total cost of ownership (TCO) for alternative powertrains remains a key challenge. This study also evaluated lifecycle impacts across various fuel sources, both fossil and bio-derived. Bio-derived synthetic diesel fuels emerged as a practical option for diesel displacement without disrupting operations. Conversely, H₂ and electrified powertrains provide limited lifecycle impacts under the current energy scenario. This analysis highlights the complexity of replacing diesel ICE trucks with admissible alternatives while balancing fleet resiliency, operational demands, and emissions goals. These results reflect a US-based fleet’s duty cycles, payloads, GVWR allowances, and an assumption of depot-only refueling/recharging. Applicability to other fleets and regions may differ based on differing routing practices or technical features such as battery swapping. Full article

Background: Prostate cancer in the Middle East and North Africa (MENA) region is shaped by a complex interplay of behavioral and environmental risk factors, yet comprehensive estimates of preventable cases remain scarce. To address this gap, we estimated population-attributable fractions (PAFs) for a range of modifiable exposures among men aged 50 years and older and assessed potential reductions in incidence under feasible intervention scenarios. Methods: Regional prevalence data were combined with relative risks from meta-analyses to compute closed-form PAFs for tobacco smoking, obesity, physical inactivity, high dairy and calcium intake, heavy alcohol use, drinking water nitrates, trihalomethanes, arsenic, lead, selenium status, ambient PM_2.5 and NO₂, and occupational diesel exhaust, covering an estimated 47 million men. Estimates were validated using a synthetic cohort simulation of 100,000 individuals, with uncertainty quantified through Monte Carlo sampling. Results: Results showed that drinking water nitrate exposure accounted for the largest single fraction (17.4%), followed by tobacco smoking (9.5%), physical inactivity (6.7%), and trihalomethane exposure (5.0%), while other exposures contributed smaller but meaningful shares. Joint elimination of all exposures projected a 45.5% reduction in incidence, and simultaneous feasible reductions in four targeted exposures yielded a combined potential impact fraction of 12.1%. Conclusions: These findings suggest that integrated water quality management, tobacco control, lifestyle interventions, and targeted environmental surveillance should be prioritized to reduce prostate cancer burden in the MENA region. However, estimates of drinking-water nitrate exposure rely on limited evidence from a single case–control study with a relatively small sample size, and should therefore be considered exploratory and primarily hypothesis-generating. Full article

This study analyzes the injection behavior of fossil and sustainable aviation fuel blends, in comparison with conventional diesel fuel, using a common-rail injection system applied to reciprocating engines. Neat commercial diesel and Jet A1 were tested as fossil fuels. A neat Fischer–Tropsch Synthetic Paraffinic Kerosene was tested and blended with Jet A1. Another alternative fuel, Hydrotreated Vegetable Oil, was also blended with Jet A1. The blending proportion was established to meet 51 as the derived cetane number, as required for fuels used in diesel reciprocating engines. Experimental tests were carried out under an energizing time of 2 ms at injection pressures between 50 and 110 MPa, with a fuel temperature ranging from 293 to 313 K, and a constant back pressure of 5 MPa, using a 130 µm single-hole injector. The results show that kerosene fuel exhibits slightly lower injection rates and total injected mass than diesel fuel, mainly due to their lower density. Under low-pressure conditions, an increase in hydraulic injection delay with diesel fuel is observed, mainly at the highest tested temperature. Mass flow rate, hydraulic injection delay, injection duration, total mass injected, and nozzle discharge coefficient do not show significant variations within the tested temperatures. Fossil kerosene fuel and its blend with Synthetic Paraffinic Kerosene show slightly higher injection rates. Overall, the results indicate that both neat kerosene and the studied blends may achieve injection characteristics comparable to diesel fuel, supporting their technical feasibility in reciprocating engines within the framework of the Single Fuel Concept. Full article

This study presents a scenario-based modeling framework to evaluate potential decarbonization pathways for Portugal’s road transport sector. The model simulates the evolution of a light-duty vehicle (LDV) fleet under varying degrees of electrification and biofuel integration, accounting for energy consumption, CO₂ emissions and market shares of alternative propulsion technologies. Coupled with projected energy mix trajectories, the framework estimates final energy demand and well-to-wheel (WTW) emissions for each scenario, benchmarking outcomes against national and European climate targets. A key structural limitation identified is the long vehicle survival rate—averaging 14 years—which constrains fleet renewal and delays the transition to full electrification. Diesel-powered light commercial vehicles exhibit even slower replacement dynamics, rendering the Portuguese targets of full electrification by 2030 highly improbable without targeted scrappage and incentive programs. Scenario analysis indicates that even with accelerated electric vehicle (EV) uptake, battery electric vehicles (BEVs) would comprise only 12% of the fleet by 2030 and 77% by 2050. Electrification scenario raises electricity demand fortyfold by 2050, stressing generation and infrastructure. Scenarios that consider diversification of energy sources reduce this strain but require triple electricity for large-scale green hydrogen and synthetic fuel production. Full article

The research problem concerning oils used for lubricating piston combustion engines is still very current and important. The proper selection of oil and its properties have a significant impact on engine reliability and durability, their efficiency, effective operating parameters, fuel consumption, environmental impact, and the proper operation of the turbocharger and exhaust system. The work concerned determining the effect of temperature and operating time on the dynamic viscosity of oils: mineral, semi-synthetic, and synthetic, used in compression-ignition engines (diesel engines). Dynamic viscosity tests were conducted for new oils, after a mileage of seven thousand kilometers, and after a mileage of fifteen thousand kilometers. The range of temperature measurement conditions used was from 0 to 50 °C and the shear transmission rate was 1000 s⁻¹. This range allows the oil to be preserved at low and medium temperatures, which are crucial for engine operation during start-up and short operating cycles. As the conducted studies showed, both temperature and operating time have a very large influence on the dynamic viscosity of oils. It was demonstrated that as the operating time of the oils in the engine increased, their dynamic viscosity decreased, and increasing the viscosity measurement temperature results in smaller absolute changes in it. Full article

This study presents a systematic comparison of five crossover operators used in genetic algorithms (GA) for the Traveling Salesman Problem (TSP). Partially Mapped Crossover (PMX), Order Crossover (OX), Cycle Crossover (CX), Edge Recombination (ERX), and Alternating Edges (AEX) are evaluated within an identical GA framework using tournament selection, inversion mutation, generational replacement, and elitism. Experiments were conducted on seven datasets, including three TSPLIB benchmarks, a clustered synthetic instance, a uniformly random instance, and two real-world Croatian city sets of 50 and 100 cities. Thirty independent GA runs per operator were analyzed using the Friedman test followed by Holm-corrected Wilcoxon pairwise comparisons. The Friedman test shows highly significant global performance differences. After applying Holm correction, the top four operators (PMX, OX, CX, and ERX) are statistically comparable on most datasets, as the correction eliminates most pairwise differences among them. All pairwise comparisons involving AEX remain significant across every dataset, confirming its consistently inferior performance. OX achieves the best average ranks across all datasets consistently, while PMX, CX, and ERX exhibit comparable mid-range performance. To illustrate practical relevance, optimized routes for Croatian instances were used to estimate fuel consumption and CO₂ emissions for petrol, diesel, and electric vehicles. The results demonstrate meaningful sustainability benefits achievable through optimized routing. Full article

The use of non-renewable energy resources is one of the main drivers of climate change. In response, the United Nations established the seventh Sustainable Development Goal, “Affordable and clean energy”, which promotes the transition toward renewable and environmentally friendly sources such as wind and solar energy. However, the intermittent nature of these resources poses challenges for maintaining a stable, continuous power supply, highlighting the need for hybrid technology approaches, such as Hybrid Renewable Energy Systems (HRES), which integrate complementary renewable sources with energy storage. In this context, this study applies a Particle Swarm Optimisation (PSO)-based approach to determine the optimal sizing and operating strategy for a hybrid system comprising photovoltaic, wind, battery storage, and diesel backup units under various synthetic load profiles. The results indicate that diesel-assisted configurations achieve lower levelized costs of energy (0.23–0.35 USD/kWh) and maintain high reliability (LPSP < 0.25%), although at the expense of higher fuel consumption and CO₂ emissions. Conversely, fully renewable configurations present higher energy costs (0.29–0.44 USD/kWh), but reduce annual CO₂ emissions by up to 50% and create more employment opportunities, particularly in regions with abundant wind resources such as La Guajira, Colombia. Full article

Oil and its derivatives affect marine ecosystems due to pollution. Analytical methods for detecting oils and greases in saline water can identify oil-derived pollutants in seas and oceans, supporting the preservation and recovery of water quality. This study describes a methodology based on Raman spectroscopy to quantify oil in saline water. Specific seriate volumes of synthetic lubricating oil (SLO) and diesel fuel oil (DFO) were added to a beaker containing 1000 mL of saline water. A magnetic stirrer was used to create vortex, where the added oil dispersed uniformly over the surface and created a thin film. Raman spectra of the surface’s film were obtained by a spectrometer (830 nm, 350 mW) at a fixed position with reference to the beaker border, in triplicate. Two spectral models were developed; one based on the intensity of the peak at ~1400–1500 cm⁻¹ and another based on partial least squares regression (PLSR). Both spectral models enabled the quantification of SLO and DFO at concentrations ranging from 25.6 to 307 mg/L, and from 16.8 to 205 mg/L, respectively, with correlation coefficients as high as r = 0.99. The results highlight the potential of using Raman spectroscopy for analyzing oil in environmental water samples. Full article

This work presents the development of an intelligent system designed to support the predictive maintenance of the Colombian Navy’s maritime vessels through the estimation of remaining useful life and unsupervised anomaly detection, within the framework of the project called “Colombian Integrated Platform Supervision and Control System” (SISCP-C). This project seeks to guarantee the sustainability of the vessels over time, increase their operational availability, and optimize their life cycle cost, in accordance with the institution’s strategic direction established in the Naval Development Plan 2042. The system provides useful information to the crew, enabling informed decision-making for intelligent and efficient maintenance strategies. To address the limited availability of normal operating data, synthetic data generation techniques with seeding are implemented, including tabular variational autoencoders, conditional tabular generative adversarial networks, and Gaussian copulas. Among these, tabular variational autoencoders achieved the best performance and are used to generate synthetic datasets under normal conditions for the Wärtsilä 6L26 diesel engine (manufactured by Wärtsilä Italia S.p.A., Trieste, Italy). These datasets are used to train several unsupervised anomaly detection models, including one-class support vector machines, classical autoencoders, and long short-term memory-based autoencoders. The long short-term memory autoencoders outperformed the others in terms of detection metrics. Dedicated multivariate long short-term memory autoencoders are subsequently trained for each engine subsystem. By calculating the mean absolute error of the reconstructions, a subsystem-specific health index is computed, which is used to estimate the remaining useful life. Full article

This work focuses on the fabrication, characterization, and performance of a structured iron catalyst to produce hydrocarbons by the Fischer–Tropsch synthesis (FTS). The structured catalyst enhances the heat and mass transfer and provides a larger surface area and lower pressure drop. Iron-based structured catalysts indicate more activity in lower H₂/CO ratios and improve carbon conversion as compared to other metals. These catalysts were manufactured using the sponge replication method (powder metallurgy). The performance of the structured iron catalyst was assessed in a fixed-bed reactor under industrially relevant conditions (250 °C and 20 bar). The feed gas was a synthetic syngas with a H₂/CO ratio of 1.2, simulating a bio-syngas derived from lignocellulosic biomass gasification. Notably, the best result was reached under these conditions, obtaining a CO conversion of 84.8% and a CH₄ selectivity of 10.4%, where the catalyst exhibited a superior catalytic activity and selectivity toward desired hydrocarbon products, including light olefins and long-chain paraffins. The resulting structured catalyst reached a one-pass CO conversion of 84.8% with a 10.4% selectivity to CH₄ compared to a traditionally produced catalyst, for which the conversion was 18% and the selectivity was 19%, respectively. The results indicate that the developed structured iron catalyst holds considerable potential for efficient and sustainable hydrocarbon production, mainly C10–C20 (diesel-range hydrocarbons), via Fischer–Tropsch synthesis. The catalyst’s excellent performance and improved stability and selectivity offer promising prospects for its application in commercial-scale hydrocarbon synthesis processes. Full article