Reestructuración Económica Y Ventaja Comparativa Dinámica

Mercantilistas y liberales reconocen un papel importante al comercio internacional en el proceso de desarrollo económico nacional. Según la concepción mercantilista, sin embargo, la contribución del comercio internacional a la acumulación de capitales, al incremento de la actividad económica y al empleo nacionales, depende del superávit de la balanza de pagos. Situando el origen de la riqueza a nivel de circulación y midiendo los beneficios comerciales en términos de superávit de la balanza de pagos, los mercantilistas se enfrentan a la dificultad de reconciliar los intereses de todos los países comerciantes. El intercambio internacional podría transformarse así en fuente de conflicto, más que de beneficio mutuo entre países comerciantes. Además, la política mercantilista de "precios altos'' y "salarios bajos" conduciría necesariamente a la parálisis tanto del mercado interno como del intercambio internacional. La solución del dilema mercantilista exige una nueva visión del origen de la riqueza y del papel del comercio internacional en la creación de riqueza

Multiple Bi-phase Interfaces in a PCM Layer Subject to Periodic Boundary Conditions Characteristic of Building External Walls

Abstract The thermal fields, which form in a PCM layer subject to external and internal loadings that operate on the external wall of buildings, are determined by a physical model that describes conduction in the solid phase and the liquid phase and the phase change of the melting temperature with a thermal balance equation at the bi-phase interface. The system of equations is resolved with a finite difference numerical model that uses a resolution algorithm that provides for the contemporaneous presence of one or more bi-phase interfaces in the layer. The thermal analysis in steady periodic regime conditions by a layer situated in Turin has highlighted that layer behaviour varies monthly in relation to the number and position of the bi-phase interfaces that form in the layer

Experimental validation of the exact analytical solution to the steady periodic heat transfer problem in a PCM layer

Phase change materials (PCM) are used in many industrial and residential applications for their advantageous characteristic of high capacity of latent thermal storage by means of an isothermal process. In this context, it is very useful to have predictive mathematical models for the analysis of the thermal performance and for the thermal design of these layers. In this work, an experimental validation of an analytical model that resolves the steady periodic heat transfer problem in a finite layer of PCM is presented. The experimental investigation was conducted employing a PCM with thermophysical and thermochemical behavior very close to those hypothesized in the formulation of the analytical model. For the evaluation of the thermophysical properties of the PCM sample used, an experimental procedure created by the authors was employed. In all tests realized in a sinusoidal and non-sinusoidal periodic regime, the comparison between the measured and calculated trends of the temperature at different sample heights and of the surface heat fluxes show an excellent agreement. Moreover, also having verified the analytical total stored energy, the analytical model constitutes a valid instrument for the evaluation of the latent and sensible contribution and the trend in time of the position of the bi-phase interface.The work was partially funded by the Spanish government (ENE2015-64117-C5-1-R (MINECO/FEDER), ENE2015-64117-C5-3-R (MINECO/FEDER), and ULLE10-4E-1305). GREA is certified agent TECNIO in the category of technology developers from the Government of Catalonia. The authors would like to thank the Catalan Government for the quality accreditation given to their research group (2014 SGR 123). This project has received funding from the European Commission Seventh Framework Programme (FP/2007-2013) under Grant agreement Nº PIRSES-GA-2013-610692 (INNOSTORAGE) and from European Union's Horizon 2020 research and innovation programme under grant agreement Nº 657466 (INPATH-TES). Alvaro de Gracia would like to thank Ministerio de Economia y Competitividad de España for Grant Juan de la Cierva, FJCI-2014-19940. Julià Coma would like to thank the Departament d'Universitats, Recerca i Societat de la Informació de la Generalitat de Catalunya for his research fellowship (2016FI_B2 00147). Aran Solé would like to thank Ministerio de Economía y Competitividad de España for Grant Juan de la Cierva, FJCI-2015-25741

Forecasting green roofs’ potential in improving building thermal performance and mitigating urban heat island in the Mediterranean area: An artificial intelligence-based approach

Green roofs are widely used in hot or cold climates mainly because they are capable to improve the energy efficiency of buildings and, when implemented at a large scale, reducing air pollution and the urban heat island effect (UHI) in urban contexts. Artificial Neural Network (ANN) black-box algorithms are a valid alternative to studying complex systems. However, the literature highlights - quite surprisingly – none of the available research refers to coupling ANNs and green roofs in the Mediterranean area, where green roofs are instead considered one of the most suitable technologies to reduce the high cooling demand. Therefore, the objective of this research work is to create and validate an ANN for the prediction of the monthly green roof’s internal and external surface temperatures and the monthly internal air temperature, starting from different green roof parameters and climatic variables. Specifically, the ANN was created with reference to a Mediterranean climate considering an existing green roof on a building of the University of Palermo characterized by a cooling demand predominance; 180 green roof configurations, obtained by varying the characteristic parameters of vegetation (plant height, leaf area index and leaf reflectivity) and the substrate thickness and thermophysical properties (lightweight and heavyweight), were dynamically simulated on an hourly basis to build the training dataset. In addition, other 72 green roof configurations were simulated to generate the dataset for the validation purpose of the ANN accuracy. The optimal ANN-related architecture consists of 90 neurons with one hidden layer and guarantees very high accuracy predictions. The outcomes of this research represent a useful tool to determine the thermal response of green roofs and their impact on the building energy demand and indoor thermal comfort and UHI mitigation

Air-source heat pump (ASHP) under very climate change scenarios: a numerical analysis

Air-source heat pumps are strongly influenced by outdoor conditions, it is expected that ongoing climate changes may impact their operation. This paper presents a predictive analysis of the behaviour of air-source heat pumps in two cities with extremely cold and warm climates in the short, medium, and long term. The seasonal coefficient of performance and heat pump seasonal energy efficiency index are evaluated over the years, considering climate change for both locations. Climate change will shorten the winter period and prolong the summer. In winter, this results in a slight softening of the seasonal coefficient of performance and a reduction in operating hours. In summer, there is a slight increase in seasonal energy efficiency ratio values and hours of operation. The work highlights how the performance of the air-source heat pump, on average, will improve in winter due to an average increase in temperature. Heat pumps are expected to be used in the future and in geographical areas where they are not currently used due to the extreme winter temperatures

Energy Independence of a Small Office Community Powered by Photovoltaic-Wind Hybrid Systems in Widely Different Climates

Hybrid renewable energy systems are an optimal solution for small energy communities’ energy supply. One of the critical issues is the strong correlation of these systems with outdoor climatic conditions. The goal is to make local communities increasingly energy independent. To this end, an in-depth analysis of the behaviour of hybrid photovoltaic (PV)–wind systems powering small office communities in 48 locations around the world characterized by widely varying climates was conducted. System sizes, assumed to be stand-alone or grid-connected, were varied, for a total of 343 system power configurations. Highest satisfied load fraction (SLF) values are obtained with a significant predominance of PV over wind; the trend is more pronounced in dry and continental climates (zones B and D according to the Köppen climate classification). The utilization factor (UF) values of 1 are rarely reached and never in the wind-only or PV-only configurations. In all climates, the grid energy interaction factor (GEIF) values of zero are never reached but come very close. The benefit-cost ratio (BCR) of grid-connected systems is significantly higher than stand-alone systems

Automatic modal identification of bridges based on free vibrations and advanced signal decomposition techniques

Free vibration tests are attractive because they can be performed by means of a network consisting of few sensors temporarily installed on the structure in such a way to limit duration and cost of the experimental campaign. Additionally, free vibration tests are usually performed by introducing an initial perturbation that can induce a structural response significantly higher than the ambient excitation. This, in turn, allows to reduce the noise-to-signal ratio in the final measurements and/or to consider less stringent requirements about the technical specifications of the sensors. Since free vibration tests can provide accurate estimates of the modal parameters while being rather cheap and easy to implement, they have been performed in many applications, such as the experimental dynamic characterization of base-isolated buildings, masonry towers, ancient tie-rods, and bridges. An efficient and automatic computational framework is thus presented for the modal identification of bridges based on their free vibrations. The novel procedure proposed in the current work combines advanced signal decomposition techniques and a robust approach for damping identification. Two advanced signal decomposition techniques are considered, namely the Variational Mode Decomposition and the Empirical Fourier Decomposition. Experimental applications are then illustrated for roadway and railway bridges

Data from a dynamic simulation in a free-floating and continuous regime of a solar greenhouse modelled in TRNSYS 17 considering simultaneously different thermal phenomena

This dataset supports the research article “Complete green- house dynamic simulation tool to assess the crop thermal well-being and energy needs”[1] . In the agricultural sector, the use of energy can be very intensive [2] and the sim- ulation of solar greenhouses is a very complex work [3] . This dataset provides the results of thermal modeling and dynamic simulation of a solar greenhouse considering si- multaneously several thermal phenomena. The analysis was performed by TRNSYS 17 software (TRaNsient SYstem Sim- ulation)