Suchergebnisse

Introduction. The museum provides society with the opportunity for special interaction with space and time for the purposes of acquiring knowledge and the most complete assimilation of codes existing in culture and society. Theoretical analysis. Society's perception of space and time in the museum will be examined and analyzed from the perspective of myth, which makes it possible to identify archetypal ideas of humanity that developed in ancient times and have largely not lost their influence on modern culture and society. The methods of institutionalizing the activities of society, which originated in the past, passed from one era to another in a transformed form, while retaining some characteristic features and at the same time acquiring new ones that became necessary for existence in a different sociocultural context. One of these characteristic features is the idea that space and time in a museum have profane and sacred dimensions. Conclusion. Space and time in the museum are a mirror not only of mythical motifs, but also of the dominant developments of the modern world. These fundamental principles concentrate all the most significant features inherent in human communities for the purpose of their further transmission to society.

Multi-objective optimization (MOO) is increasingly being used in a wide variety of applications to identify alternatives that balance several criteria. The energy sector is not an exception to this trend. Unfortunately, the complexity of MOO grows with the number of environmental objectives. This limitation is critical in energy systems, in which several environmental criteria are typically used to assess the merits of a given technology. In this paper, we investigate the use of a rigorous dimensionality reduction method for reducing the complexity of MOO as applied to an energy system (i.e., a solar Rankine cycle coupled with reverse osmosis and thermal storage). Instead of using an aggregated environmental metric, a common approach for reducing the number of environmental objectives in MOO, we propose to optimize the system in a reduced search space of objectives that fully describe its performance and which results from eliminating redundant criteria from the analysis. Numerical results show that it is possible to reduce the problem complexity by omitting redundant environmental indicators from the optimization. ; The authors would like to acknowledge financial support from the Spanish GovernmentENE2011-28269-C03-03, ENE2011-22722, DPI2012-37154-C02-02, CTQ2012-37039-C02) and to thank the Catalan Government for the quality accreditation given to their research groups SUSCAPE and GREA (2009 SGR 545, 2009 SGR 534).

This paper addresses the optimal design of desalination plants that integrate reverse osmosis, a Rankine cycle, parabolic trough solar collectors and thermal energy storage (TES). A multi-objective mixed-integer nonlinear programming model (MINLP) is developed to model such an integrated system and optimize its design and operating conditions according to economic and environmental metrics. The model considers the simultaneous minimization of cost and environmental impact given a specific water demand to be fulfilled. The environmental performance is quantified via life cycle assessment (LCA) principles. Particularly, the CML 2001 methodology, a widely used LCA-based framework, is used to assess the impact, enabling the identification of the main sources of damage across the entire life cycle of the plant. The capabilities of our method are illustrated through its application to a case study considering weather data in Tarragona (Spain). We show that coupling seawater desalination with solar collectors and thermal energy storage leads to significant environmental savings at a marginal increase in cost. ; The authors would like to acknowledge financial support from the Spanish Government (DPI2008-04099, ENE2011-28269-C03-03, ENE2011-22722, CTQ2009-14420-C02) and to thank the Catalan Government for the quality accreditation given to their research groups SUSCAPE and GREA (2009 SGR 545, 2009 SGR 534).

Multi-objective optimization (MOO) has emerged recently as a useful technique in the design andplanning of engineering systems because it allows identifying alternatives leading to significant envi-ronmental savings. MOO models typically contain an infinite number of Pareto solutions, from whichdecision-makers should choose the best one according to their preferences. An approach is here pre-sented that identifies and retains for further inspection a reduced set of Pareto solutions showing betteroverall performance. The capabilities of our approach are illustrated through its application to the designof reverse osmosis desalination plants considering simultaneously the unitary production cost and a setof environmental impacts in several damage categories. Our method reduces significantly the number ofPareto points, thereby facilitating the decision-making process in MOO. ; The authors would like to acknowledge financial support from the Spanish Government(ENE2011-28269-C03-03, ENE2011-22722, DPI2012-37154-C02-02, CTQ2012-37039-C02) and the Catalan Government for the quality accreditation given to their research groups SUSCAPE and GREA (2009 SGR 545, 2009 SGR 534)