Search Results (14)

To address greenhouse gas (GHG) emissions from the maritime sector, the European Union (EU) has introduced the FuelEU Maritime regulation to incentivize ships to adopt diversified compliance pathways and energy solutions. This study aims to determine the optimal alternative fuel configurations for dual-fuel ships of different types under environmental, economic, and regulatory constraints. An integrated environmental and cost assessment model from a well-to-wake (WtW) perspective to systematically evaluate the environmental benefits and economic feasibility of fossil-based, bio-based, and renewable electricity-based alternative fuels applied in dual-fuel ships. By incorporating the PROMETHEE II method within a multi-criteria decision analysis (MCDA) framework, together with the CRITIC objective weighting method, the study enables a robust ranking of alternative fuel configurations across three key dimensions: environmental performance, cost feasibility, and regulatory compliance. The results indicate that, regardless of ship type, the very low sulfur fuel oil (VLSFO) + marine gas oil (MGO) and VLSFO + methanol (MEOH) combinations fail to meet the GHG intensity targets for 2025–2050. Only the VLSFO + electrolytic liquid hydrogen (E-LH₂) and VLSFO + electrolytic ammonia (E-NH₃) configurations are compliant. Although e-fuels incur the highest annual costs, the EU compliance penalty associated with fossil fuels increases exponentially. In contrast, e-fuels retain long-term cost advantages, ultimately driving a sector-wide transition toward e-fuel-dominated energy structures by 2050. Their superior environmental performance and regulatory compatibility emerge as the core drivers of the maritime energy transition. Full article

The current commitment towards aviation climate neutrality and decarbonisation is boosting research programmes on disruptive aircraft configurations featuring sustainable powertrains and fuel-efficient airframes. This trend is pushing the design towards high-aspect-ratio wings made of lightweight structures housing distributed propulsion systems. Airframe preliminary sizing and mass estimation of non-conventional configurations, if performed using legacy methodologies based on experience, gathered with traditional configurations may result in non-optimised and non-viable designs. Therefore, a physics-based optimisation approach may allow more accurate sizing and airframe mass estimation. The methodology suggested in this paper is based on the automatic generation of a global finite element model to estimate the weight and determine a feasible material distribution for the wing box structure of a strut-braced wing configuration by means of size optimisation. Composite materials with defined stacking sequences were assigned to the wing components and structural weight minimised with the aim of offsetting the weight penalties associated with this non-conventional aircraft configuration. Preliminary results suggest that the composite strut-braced wing could achieve a weight reduction of up to 44% compared to a composite cantilever wing with equal aspect ratio of 20. The actual weight reduction is thought to be lower due to potential overestimation of the cantilever configuration. Full article

This paper proposes a Q-learning-driven butterfly optimization algorithm (QLBOA) by integrating the Q-learning mechanism of reinforcement learning into the butterfly optimization algorithm (BOA). In order to improve the overall optimization ability of the algorithm, enhance the optimization accuracy, and prevent the algorithm from falling into a local optimum, the Gaussian mutation mechanism with dynamic variance was introduced, and the migration mutation mechanism was also used to enhance the population diversity of the algorithm. Eighteen benchmark functions were used to compare the proposed method with five classical metaheuristic algorithms and three BOA variable optimization methods. The QLBOA was used to solve the green vehicle routing problem with time windows considering customer preferences. The influence of decision makers’ subjective preferences and weight factors on fuel consumption, carbon emissions, penalty cost, and total cost are analyzed. Compared with three classical optimization algorithms, the experimental results show that the proposed QLBOA has a generally superior performance. Full article

The fuel system serves as the core component of marine diesel engines, and timely and effective fault diagnosis is the prerequisite for the safe navigation of ships. To address the challenge of current data-driven fault-diagnosis-based methods, which have difficulty in feature extraction and low accuracy under small samples, this paper proposes a fault diagnosis method based on digital twin (DT), Siamese Vision Transformer (SViT), and K-Nearest Neighbor (KNN). Firstly, a diesel engine DT model is constructed by integrating the mathematical, mechanism, and three-dimensional physical models of the Medium-speed diesel engines of 6L21/31 Marine, completing the mapping from physical entity to virtual entity. Fault simulation calculations are performed using the DT model to obtain different types of fault data. Then, a feature extraction network combining Siamese networks with Vision Transformer (ViT) is proposed for the simulated samples. An improved KNN classifier based on the attention mechanism is added to the network to enhance the classification efficiency of the model. Meanwhile, a Weighted-Similarity loss function is designed using similarity labels and penalty coefficients, enhancing the model’s ability to discriminate between similar sample pairs. Finally, the proposed method is validated using a simulation dataset. Experimental results indicate that the proposed method achieves average accuracies of 97.22%, 98.21%, and 99.13% for training sets with 10, 20, and 30 samples per class, respectively, which can accurately classify the fault of marine fuel systems under small samples and has promising potential for applications. Full article

In order to improve the efficiency of agricultural machinery operations and reduce production costs, this article proposes a path planning algorithm based on the improved A* algorithm (IA*) and a tracking controller based on fuzzy sliding mode variable structure control (F-SMC) to meet the operation requirements of tracked agricultural machinery. Firstly, we introduce a heuristic function with variable weights, a penalty, and a fifth-order Bezier curve to make the generated path smoother. On this basis, the ant colony algorithm is introduced to further optimize the obtained path. Subsequently, based on fuzzy control theory and sliding mode variable structure control theory, we established a kinematic model for tracked agricultural machinery as the control object, designed a fuzzy sliding mode approaching law, and preprocessed it to reduce the time required for sliding mode control to reach the chosen stage. The simulation experiment of path planning shows that compared with A*, the average reduction rate of the path length for IA* is 5.51%, and the average reduction rate of the number of turning points is 39.01%. The path tracking simulation experiment shows that when the driving speed is set to 0.2 m/s, the adjustment time of the F-SMC controller is reduced by 0.99 s and 1.42 s compared to the FUZZY controller and PID controller, respectively. The variance analysis of the adjustment angle shows that the minimum variance of the F-SMC controller is 0.086, and the error converges to 0, proving that the vehicle trajectory is smoother and ultimately achieves path tracking. The field test results indicate that the path generated by the IA* algorithm can be tracked by the F-SMC controller in the actual environment. Compared to the A* algorithm and FUZZY controller, the path tracking time reduction rate of IA* and F-SMC is 29.34%, and the fuel consumption rate is reduced by 2.75%. This study is aimed at providing a feasible approach for improving the efficiency of tracked agricultural machinery operations, reducing emissions and operating costs. Full article

Contrails are responsible for a significant proportion of aviation’s climate impact. This paper uses data from the European Centre for Medium-Range Weather Forecasts to identify the altitudes and latitudes where formed contrails will not persist. This reveals that long-lived contrails may be prevented by flying lower in equatorial regions and higher in non-equatorial regions. Subsequently, it is found that the lighter fuel and reduced seating capacity of hydrogen-powered aircraft lead to a reduced aircraft weight, which increases the optimal operating altitude by about 2 km. In non-equatorial regions, this would lift the aircraft’s cruise point into the region where long-lived contrails do not persist, unlocking hydrogen-powered, low-contrails operation. The baseline aircraft considered is an A320 retrofitted with in-fuselage hydrogen tanks. The impacts of the higher-altitude cruise on fuel burn and the benefits unlocked by optimizing the wing geometry for this altitude are estimated using a drag model based on theory proposed by Cavcar, Lock, and Mason, and verified against existing aircraft. The weight penalty associated with optimizing wing geometry for this altitude is estimated using Torenbeek’s correlation. It is found that thinner wings with higher aspect ratios are particularly suited to this high-altitude operation and are enabled by the relaxation of the requirement to store fuel in the wings. An example aircraft design for the non-equatorial region is provided, which cruises at a 14 km altitude at Mach 0.75 with a less than 1% average probability of generating long-lived contrails when operating at latitudes more than 35° from the equator. Compared to the A320, this concept design is estimated to have a 20% greater cruise lift–drag ratio, due to the 33% thinner wings with a 50% larger aspect ratio, enabling just 5% more energy use per passenger-km, despite fitting 40% fewer seats. Full article

Air cycle systems (ACSs) are primarily used in aircraft environmental control systems (ECSs) to provide a suitable cabin temperature and pressure environment for passengers and avionics. It comprises heat exchangers, compressors, turbines, water separators, and various other components that are interconnected to form an information-transmission network. Traditional research on ACSs has focused primarily on their thermal performance. This study abstracted ACSs into network graphs based on their information-transmission characteristics, determined the weight of each information-transmission route using the fuel weight penalty method, calculated and compared the order degree of different ACSs using the structure entropy method, and measured the importance of each component using centrality for the first time. The results showed that the order degree of the ACSs gradually increased with an increase in the number of wheels in the air cycle machine (ACM), and ACSs with high-pressure water separation had a higher order degree under wet conditions than under dry conditions. Moreover, based on the centrality of each vertex in the graphs, the ACM and secondary heat exchanger in the ACS were fundamentally important and should be focused on during the system design. The methodology proposed in this study provides a theoretical basis for the evaluation of the ACS organizational structure and the design performance of components. Full article

Past studies of microgrids have been based on measurements of fuel consumption by generators under static loads. There is little information on the fuel efficiency of generators under time-varying loads. To help analyze the impact of time-varying loads on optimal generator operation and fuel consumption, we formulate a mixed-integer linear optimization model to plan generator and energy storage system (ESS) operation to satisfy known demands. Our model includes fuel consumption penalty terms on time-varying loads. We exercise the model on various scenarios and compare the resulting optimal fuel consumption and generator operation profiles. Our results show that the change in fuel efficiency between scenarios with the integration of ESS is minimal regardless of the imposed penalty placed on the generator. However, without the assistance of the ESS, the fuel consumption increases dramatically with the penalty imposed on the generator. The integration of an ESS improves fuel consumption because the ESS allows the generator to minimize power output fluctuation. While the presence of a penalty term has a clear impact on generator operation and fuel consumption, the exact type and weight of the penalty appears insignificant; this may provide useful insight for future studies in developing a real-time controller. Full article

Smooth power injection is one of the possible services that modern wind farms could provide in the not-so-far future, for which energy storage is required. Indeed, this is one among the three possible operations identified by the International Energy Agency (IEA)-Hydrogen Implementing Agreement (HIA) within the Task 24 final report, that may promote their integration into the main grid, in particular when paired to hydrogen-based energy storages. In general, energy storage can mitigate the inherent unpredictability of wind generation, providing that they are deployed with appropriate control algorithms. On the contrary, in the case of no storage, wind farm operations would be strongly affected, as well as their economic performances since the penalty fees wind farm owners/operators incur in case of mismatches between the contracted power and that actually delivered. This paper proposes a Model Predictive Control (MPC) algorithm that operates a Hydrogen-based Energy Storage System (HESS), consisting of one electrolyzer, one fuel cell and one tank, paired to a wind farm committed to smooth power injection into the grid. The MPC relies on Mixed-Logic Dynamic (MLD) models of the electrolyzer and the fuel cell in order to leverage their advanced features and handles appropriate cost functions in order to account for the operating costs, the potential value of hydrogen as a fuel and the penalty fee mechanism that may negatively affect the expected profits generated by the injection of smooth power. Numerical simulations are conducted by considering wind generation profiles from a real wind farm in the center-south of Italy and spot prices according to the corresponding market zone. The results show the impact of each cost term on the performances of the controller and how they can be effectively combined in order to achieve some reasonable trade-off. In particular, it is highlighted that a static choice of the corresponding weights can lead to not very effective handling of the effects given by the combination of the system conditions with the various exogenous’, while a dynamic choice may suit the purpose instead. Moreover, the simulations show that the developed models and the set-up mathematical program can be fruitfully leveraged for inferring indications on the devices’ sizing. Full article

The scramjet of hypersonic vehicles faces severe high-temperature challenges, but the heat sink available for scramjet cooling is extremely finite. It is necessary to optimize its power and thermal management system (PTMS) with a finite heat sink of hydrocarbon fuel. This paper proposes a two-level optimization method for the PTMS of hypersonic vehicles at Mach 6. The PTMS is based on a supercritical carbon dioxide (SCO₂) closed Brayton cycle, and its heat sink is airborne hydrocarbon fuel. System-level optimization aims to obtain the optimal system parameters for the PTMS. The minimum fuel weight penalty and the minimum heat sink consumption of fuel are the optimization objectives. The segmental (SEG) method is used to analyze the internal temperature distribution of fuel–SCO₂ heat exchangers in the system-level optimal solution set. This ensures the selected optimal solutions meet the requirement of a pinch temperature difference greater than or equal to 10 °C. Further, the component-level optimization for the fuel–SCO₂ heat exchanger is carried out based on the selected optimal solutions. The lightest weight of the heat exchanger and the minimum entropy production are the optimization objectives in this step. Finally, the optimal system parameters and the optimal key component parameters can be searched using this presented two-level optimization method. Full article

By considering the weight penalty of batteries on payload and total vehicle weight, this paper shows that almost all forms of land-based transport may be served by battery electric vehicles (BEV) with acceptable cost and driving range. Only long-distance road freight is unsuitable for battery electrification. The paper models the future Indian electricity grid supplied entirely by low-carbon forms of generation to quantify the additional solar PV power required to supply energy for transport. Hydrogen produced by water electrolysis for use as a fuel for road freight provides an inter-seasonal energy store that accommodates variations in renewable energy supply. The advantages and disadvantages are considered of midday electric vehicle charging vs. overnight charging considering the temporal variations in supply of renewable energy and demand for transport services. There appears to be little to choose between these two options in terms of total system costs. The result is an energy scenario for decarbonized surface transport in India, based on renewable energy, that is possible, realistically achievable, and affordable in a time frame of year 2050. Full article

Aircraft and engine technology have continuously evolved since their introduction and significant improvement has been made in fuel efficiency, emissions, and noise reduction. One of the major issues that the aviation industry is facing today is pollution around the airports, which has an effect both on human health and on the climate. Although noise emissions do not have a direct impact on climate, variations in departure and arrival procedures influence both CO₂ and non-CO₂ emissions. In addition, design choices made to curb noise might increase CO₂ and vice versa. Thus, multidisciplinary modeling is required for the assessment of these interdependencies for new aircraft and flight procedures. A particular aspect that has received little attention is the quantification of the extent to which early design choices influence the trades of CO₂, NOx, and noise. In this study, a single aisle thrust class turbofan engine is optimized for minimum installed SFC (Specific Fuel Consumption). The installed SFC metric includes the effect of engine nacelle drag and engine weight. Close to optimal cycles are then studied to establish how variation in engine cycle parameters trade with noise certification and LTO (Landing and Take-Off) emissions. It is demonstrated that around the optimum a relatively large variation in cycle parameters is allowed with only a modest effect on the installed SFC metric. This freedom in choosing cycle parameters allows the designer to trade noise and emissions. Around the optimal point of a state-of-the-art single aisle thrust class propulsion system, a 1.7 dB reduction in cumulative noise and a 12% reduction in EINOx could be accomplished with a 0.5% penalty in installed SFC. Full article

In this paper, an improved fuel consumption and emissions control strategy based on a mathematical and heuristic approach is presented to optimize Parallel Hybrid Electric Vehicles (HEVs). The well-known Sequential Quadratic Programming mathematical method (SQP-Hessian approach) presents some limitations to achieve fuel consumption and emissions control optimization, as it is not able to find the global minimum, and it generally shows efficient results in local exploitation searches. The usage of a combined Modified Artificial Bee Colony algorithm (MABC) with the SQP approach is proposed in this work to obtain better optimal solutions and overcome these limitations. The optimization is performed with boundary conditions, considering that the optimized vehicle performance has to satisfy Partnership for a New Generation of Vehicles (PNGV) constraints. The weighting factor of the vehicle’s performance parameters in the objective function is varied, and optimization is carried out for two different driving cycles, namely Federal Test Procedure (FTP) and Economic commission Europe—Extra Urban Driving Cycle (ECE-EUDC), using the MABC and MABC with SQP approaches. The MABC with SQP approach shows better performance in terms of fuel consumption and emissions than the pure heuristic approach for the considered vehicle with similar boundary conditions. Moreover, it does not present significant penalties for final battery charging and it offers an optimized size of the key vehicle’s components for different driving cycles. Full article

The aerospace-based heat sink is defined as a substance used for dissipating heat generated by onboard heat loads. They are becoming increasingly scarce in the thermal management system (TMS) of advanced aircraft, especially for supersonic aircraft. In the modern aircraft there are many types of heat sinks whose cooling abilities and performance penalties are usually obviously different from each other. Besides, the cooling ability and performance penalty of a single heat sink is even different under different flight conditions—flight altitude, Mach number, etc. In this study, the typical heat sinks which are the fuel mass, ram air, engine fan air, skin heat exchanger, and expendable heat sink will be studied. Their cooling abilities/capacities, and exergy penalties under different flight conditions have been systematically estimated and compared with each other. The exergy penalty presented in this paper refers to the exergy loss of aircraft caused by the extra weight, drag and energy extraction of various heat sinks. The estimation models, as well as the results and discussion have been elaborated in this paper, which can be can be used to further optimize the TMS of modern advanced aircraft, for example, the layout design of various heat sinks and the improvement the control algorithm. Full article