Measuring domestic implications of tariff cuts under EU entry price regime

The entry price regime in the European Union (EU) applies to several products, mainly fresh fruits and vegetables. The complexity of the system with endogenous applied tariffs makes the evaluation of different alternatives of tariff cuts more challenging than for other regimes. The challenge applies to academics with interest on estimating market impacts, to WTO negotiators that need to evaluate proposals and to policy-makers that may need to take decisions on options such as the declaration of a sensitive product. This paper develops a methodology to compare different tariff cuts alternatives, including the URAA method that implies reductions in the level of the entry price, constant entry price, and Tariff Rate Quotas expansion. Uncertainty about international prices plays a central role on the estimated impacts on market access of different options. Reducing the level of entry prices can have relatively large impacts on market access for some products. The sensitive product treatment with TRQs may generate larger market access than the normal treatment. The proposed methodology proofs to be able to quantify the economic impacts of tariff cuts under EU entry price regime.International Relations/Trade,

Identification of Public Objectives Related to Agricultural Sector Support

The Common Agricultural Policy (CAP) is a widely debated policy in terms of both its budget and its instruments. In order to serve the citizens of Europe properly, CAP requires optimal identification of the public objectives desired. This paper aims to analyse the relative weights that citizens assign to the various potential objectives of the CAP and to show how these can be used to improve the selection of policy instruments. As a means of identifying social preferences we used the Analytical Hierarchy Process (AHP) technique on a population sample in Castilla y León (Spain). Results show how the current policy decision process lacks mechanisms capable of identifying social preferences and thus leading to the choice of sub-optimal policies.Common Agricultural Policy, Objectives, Social preferences, AHP, Castilla y León.

Optimal management of smart grids using machine learning techniques

Fossil fuels -including coal, oil, and natural gas- have been powering economies for over 150 years, and currently supply about 80% of the world's energy. But this number is meant to decrease drastically before the end of the century to prevent global warming. Russia’s invasion of Ukraine has created shock waves in global energy markets, leading to price volatility, supply shortages, security issues and economic uncertainty, leading us to the biggest energy crisis of the history. To deal with these problems, our society has to take serious actions to optimize the electric supply in the world while taking into account intermittent energy sources such as solar, wind or hydraulic power. As a consequence, the target of climate neutrality by 2050 has encouraged the growth of renewable energy in Europe: in 2020, around one-fifth of the European electricity was generated from wind and solar electricity, surpassing fossil-based electricity generation. This same year, electricity generation from coal decreased by almost 50% since 2015, which is equivalent to avoiding around 320 Mt CO2 per year1. Smart grids have the potential to optimize the efficiency, reliability, economics, and sustainability of the production, distribution, and consumption of electrical energy. In 2021, the Smart Grid Index benchmarked a total of 86 Smart Grid utilities across 37 countries2, with Enedis achieving the number one position. Indeed, a classical electrical grid is defined as a reliable integrated power delivery system consisting of interconnected Distributed Energy Resources (DERs), which has the purpose of satisfying load demands without any interruption. However, introducing renewable energies in the grid requires some predictive measures in order to guarantee the reliability and stability of the energy supply as they are highly influenced by weather conditions, economic situations, and environmental issues. As a solution, Smart Grids can handle the presence of uncertainties as well as ensuring a high level of security and quality of electricity supply, minimizing the energy production and distribution costs. In this research assignment, we will try to implement a Smart Grid model using Machine Learning methods and a Model Predictive Control (MPC) as a baseline for optimal control solution to compare with Deep Learning. We will start understanding some already existent well-known cases from Matlab and try to adapt them to our Smart Grid proble

New dimensionless number to predict cavitation in accelerated fluid

Cavitation is the formation of vapour cavities in a liquid due to a local low pressure. The traditional cavitation number is used to predict the occurrence of cavitation in liquid flows through devices such as pumps, propellers or dam spillways. However this number can only be applied when cavitation is produced by changes of dynamic and static pressure in a liquid flow. There are other means to produce cavitation where the traditional cavitation number cannot be applied. The purpose of this research is to formulate a new dimensionless number valid to predict cavitation in some scenarios where the traditional cavitation number fails. The “tube-arrest” method produces cavitation by subjecting a column of liquid to a high acceleration without the need of any velocity between the liquid and the tube. In this scenario the traditional number is not useful due to the low values of relative velocity between liquid and walls. However the dimensionless number reported here predicts accurately the occurrence of cavitation in the “tube-arrest” method, as it is shown by Finite Element Method analysis. There is another scenario where the dimensionless number is tested successfully that is the bulk of a liquid downstream of a closing valve. A systematic comparison between the values of the dimensionless number and the occurrence of cavitation predicted by the FEM analysis is given. On the other hand the values of the traditional cavitation number are calculated and it is shown that these values are meaningless in these scenarios. In contrast, the agreement between the prediction of the dimensionless number and the simulations is excellent. It is concluded that the new dimensionless number predicts cavitation in scenarios where the traditional number is meaningless. It can also be used for a better design of experiments with the “tube-arrest” method as a practical application

De la erección, unión y división de obispados

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 201

Prediction of ultrasonic cavitation with a dimensionless number, towards higher reproducibility

Ultrasonic cavitation is the formation of vapour cavities within a liquid due to the action of an ultrasound source. It is widely used for homogenization, dispersion, deagglomeration, erosion, cleaning, milling, emulsification, extraction, disintegration and sonochemistry. On the other hand, the so-called cavitation number is used to assess the likelihood of cavitation in fluid flows within a conduit or around a hydrofoil but it is not valid in ultrasonic cavitation since there is no fluid flow. A recently formulated number predicts the cavitation in case of sudden accelerations. The tip surface of an ultrasonic probe is subjected to a continuous repetition of alternating accelerations at high frequency. Therefore, the use of the recently formulated number in ultrasonic cavitation is explored here. Simulations of the ultrasonic probe in water just at the condition of cavitation onset have been performed for a combination of probe diameters from 0.2 to 100 mm and frequencies 20, 30, 40, 100 and 1000 KHz. The recently formulated number is applied to these combinations and it is found that can be used to predict ultrasonic cavitation. Consequently, the dimensionless number can be used to decide the conditions to avoid or generate cavitation when a fluid is sonicated and to increase reproducibility in such conditions.Comment: 11 pages, 3538 words, 8 figure