The Gasoil options market is illiquid, making it difficult to construct its implied volatility surface directly. However, it is closely linked to the highly liquid Brent options market. In this paper, we jointly model Brent and Gasoil futures prices through a correlated Bachelier local volatility model: the Brent factor is described by a normal mixture diffusion model, while the Gasoil-Brent spot volatility spread is estimated using a data-driven procedure that identifies clusters of historical crack-spread levels and Gasoil-Brent volatility spreads. The resulting bivariate model allows us to compute an implied volatility correction that maps Brent implied volatilities to Gasoil implied volatilities without using illiquid Gasoil option prices as inputs. Monte Carlo simulations demonstrate that the resulting implied volatilities closely match observed Gasoil implied volatilities when benchmarked against more direct approaches. These results suggest that the proposed framework is well suited for modeling refined products and pricing the corresponding financial derivatives.
The knowledge of the brake linings coefficient of friction (BLCF) is crucial for the control of the braking moment in modern vehicles equipped with electric powertrains. In the case of race vehicles equipped with carbon–carbon brakes, the coefficient of friction exhibits great variations as a function of the main influencing factors, namely the pressure, the temperature, and the sliding speed at the pad–disc interface. In this work, a Le Mans Hypercar instrumented with more than 150 sensors was adopted to perform the characterization of the BLCF from racetrack acquisitions. The front and rear left suspensions of the vehicle were instrumented with strain gauge channels and position transducers to acquire the reaction loads at the upright and the orientation of the arms. Then, the geometric matrix method was implemented for calculating the moments at the upright from which the braking torque was derived without the need to know any of the wheel inertia, nor the driveshaft torque. Data from multiple acquisitions across different racetracks, operating temperatures, and ambient conditions were used to characterize the BLCF of the front and rear carbon brakes equipped on the vehicle. After implementing pre-processing steps aimed at improving data homogeneity, two friction maps were characterized for the front and rear systems, respectively. The friction maps were validated against new experimental data showing an average 3% error reduction over assuming a constant BLCF. Accordingly, the characterized friction maps can be integrated in the brake-by-wire system of the vehicle for accurate caliper pressure control through real-time estimation of the BLCF from commonly available sensor signals, such as caliper pressure, wheel speed, and disc temperature. In this context, the effectiveness of the friction maps was demonstrated by comparing the predicted brake moments with the torques measured by the instrumented suspensions, highlighting the advantages over assuming a constant BLCF.
The energy transition in the European Union is shaped by complex technological, economic, and geopolitical interdependencies. A coherent policy approach must account for the interaction between efforts to decarbonize the energy mix and measures that support the adoption of end-use clean technologies, in particular in the industrial sector. Photovoltaic and battery storage systems face structural challenges in Europe, including elevated production costs and limited upstream integration. Heat pumps, while more mature, would require demand stimulation and workforce skill development to fully realize their potential. Concurrently, industrial electrification presents considerable technical potential, especially for low- and medium-temperature heat processes, but progress remains constrained by infrastructure gaps, regulatory barriers, and cost competitiveness. Moreover, manufacturing industries are highly exposed to international competition, making them particularly sensitive to trade policies. A comprehensive policy framework should prioritize effective use of EU funds and ensure stable regulatory conditions. Key actions involve developing clean technology gigafactories, securing critical raw materials, supporting circular economy practices, expanding recycling capabilities, and fostering R&D collaboration. Complementary fiscal incentives, green finance mechanisms, and workforce upskilling are essential to reduce external dependencies, advancing Net-Zero Industry Act (NZIA) targets, and generating socioeconomic and environmental benefits. To bolster EU industrial competitiveness, accelerating the deployment of renewables, facilitating access to long-term instruments such as power purchase agreements, and establishing a coherent EU-wide framework to support industrial electrification are imperative. In particular, hard-to-abate manufacturing sectors will require targeted incentives—whether in terms of capital expenditures (CAPEX) or operational ones (OPEX)—to bridge the cost gap with fossil fuel-based reference technologies.
Several recently published studies regarding flow problems propose schemes of high order of accuracy designed as evolution of traditional methods. A drawback common to these new schemes is the necessity to adopt uniform mesh refinement for solving sharp problems, by increasing the computational cost. Even the so called essentially non-oscillatory and weight essentially non-oscillatory methods suffer of the same drawback and are not suitable to cope with h-adaptive methods due to their definition on finite volumes necessarily of equal diameter. Therefore, in order to overcome the above drawback, the formulation of dynamically locally self h-adaptive processes is designed to achieve the dual purpose to increase the accuracy and to keep as small as possible the number of finite volumes. To define a locally h-adaptive finite volume (FV) scheme need two simple but important tools, namely a particular FV named Bridge FV positioned between two adjacent subdomains and the definition of suitable profiles approximating the fluxes on the FV faces. In this article a new FV method for the numerical solution of convective-diffusive 1D problems is developed. It is conservative, second order in time and space for equal FV, and allows the partitioning of the domain by equal or unequal finite volumes, thus dynamically locally self h-adaptive. The definition of the monotonic profiles is accomplished by means of cubic weighted ν-splines and Taylor expansions. The profile analysis respect to the numerical properties is conducted in the normalized plane with the velocity varying in time and space and gives the flux value on the FV faces. Moreover the flux is assigned by Upwind or by second order back-ward Characteristics if the estimated flux is outside of the unit square or the transformation into the normalized plane is not possible, respectively. The initial-boundary stability and convergence properties of the new method are examined in detail, also in presence of h-adaptivity. In addition, a generalization of the new scheme to 2D and 3D problems is presented. Finally, some numerical test are carried out to verify the properties of the new method, including two CFD problems.
The Brazilian energy spot price is obtained through a chain of dynamic stochastic optimization models that works with the uncertainties related to its continental hydrogeneration-based power system. In that sense, this paper presents an information theoretic learning neural forecasting model for daily streamflow prediction of Brazilian hydroelectric power plants. More precisely, the maximum correntropy criterion was used as the error function of a multilayer perceptron. After the prediction stage, the generated outputs were used as one of the inputs of the model chain that is used to compute the hourly energy spot price in Brazil. To the best of the authors’ knowledge, it is the first paper that aims to analyze the impact of the streamflow prediction on the Brazilian hourly energy spot price formation. In terms of streamflow forecast, results indicated that the predictions originated from the proposed forecasting model were equivalent to the ones from the official models, especially in the first predicted day. In the spot price graph analysis, the main result pointed that the curves provided from the modeled structure were closer to the values obtained using the actual flows than the official prices, which shows that the proposed work could produce prices more aligned to the real hydrological system conditions. From that, the study’s relevance is due to the conclusion that the official process of streamflow forecasting can be improved to generated outputs more consistent with the actual system conditions, to avoid further expenses in the system operation due to potential unscheduled hydrothermal dispatches.
