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Plate fin-tube heat exchangers are widely used in air conditioning and refrigeration systems and other industry fields. Various errors made in the manufacturing process can result in the formation of an air gap between the tube and fin. Several numerical simulations were carried out for a symmetric section of plate fin-tube heat exchanger to study the influence of air gap on heat transfer under periodic flow conditions. Different locations and sizes of an air gap spanning 1/2 circumference of the tube were considered for the range of airflow velocities. Velocity and temperature fields for cases with air gap were compared with ideal thermal contact cases. Blocking of heat flow by the gap leads to the reduction of heat transfer rate. Fin discontinuity in the front of the tube causes the smallest reduction of the heat transfer rate in comparison to the ideal tube-fin contact, especially for thin slits. The rear gap position is the worst in the smallest gap range. Therefore, reversing the flow direction can lead to up to a 15% heat transfer increase, if mainly the rear gaps are present. The introduction of a thin slit in the front of the tube leads to convective heat transfer enhancement, which should be further investigated.

The conversion of chemical energy contained in organic matter into electricity has become an object of interest for many scientists worldwide. This technology is used in microbial fuel cells (MFC). Apart from generating electrical energy, these cells can be used simultaneously for wastewater treatment. Although the technology is constantly being improved, currently functioning microbial fuel cells cannot provide appropriate output parameters to use on an industrial scale. One of the barriers is so-called extracellular electron transfer, which in turn depends on the electrode type used, its material, shape, and size. According to current literature, carbon, graphite, stainless steel, and ceramics are the most frequently used electrode materials. However, more and more often, scientists are turning to other, unusual materials, the production of which uses the newest technologies, and one of them is graphene. This material is modified in different ways and connected with other materials, and the results of this seem to be very promising. Scientists manage to get a higher level of extracellular electron transfer and, hence, higher output parameters of the whole system. This article describes chosen technologies and attempts made by scientists worldwide to use graphene in MFC and their results.

The 2030 zero-net emission target in the E.U. demands a significant improvement in the energy performance of the building stock. This study analyses the adoption of connected thermostats and Home energy-management system solutions (HEMS) as an effective means to tackle the residential energy footprint. It reviews the main features of HEMS systems in terms of technology, cross-study performances, and the obstacles to widespread adoption; the study adopts the case-study methodology to examine the impact on the Italian real estate stock at a regional level. A matrix of adoption scenarios assesses the potential benefits of global residential energy savings, weighted by local climatic variations, dimension, number of single dwellings, and average primary energy reduction per household. Results demonstrate that all adoption scenarios dramatically reduce residential energy consumption, outperforming the E.U. targets for Italy by 2030.

The built environment remains a strategic research and innovation domain in view of the goal of full decarbonization. The priority is the retrofitting of existing buildings as zero-emission to improve their energy efficiency with renewable energy technologies pulling the market with cost-effective strategies. From the first age of photovoltaics (PV) mainly integrated in solar roofs, we rapidly moved towards complete active building skins where all the architectural surfaces are photoactive (Building Integrated Photovoltaics - BIPV). This change of paradigm, where PV replaces a conventional building material, shifted the attention to relate construction choices with energy and cost effectiveness. However, systematic investigations which put into action a cross-disciplinary approach between construction, economic and energy related domains is still missing. This paper provides the detailed assessment of a real multifamily building, taking into account retrofit scenarios for making active the building skin, with the goal to identify the sensitive aspects of the energetic and economic effectiveness of BIPV design options. By assuming a real case study with monitored data, the analysis will consider a breakdown of the main individual parts composing the building envelope, by then combining alternative re-configurations in merged clusters with different energy and construction goals. Results will highlight the correlation between building skin construction strategies and the energy and cost parameters by identifying the cornerstones for enhancing efficiency. The outcomes, related to the total life cost, self-consumption/sufficiency, in combination with different building design options (façade, roof, balconies, surface orientations, etc.), provide a practical insight for researchers and professionals to identify renovation strategies by synergistically exploiting the solar active parts towards lower global costs and higher energy efficiency of the whole building system.

Wind energy represents one of the leading renewable energy sectors and is considered instrumental in the ongoing decarbonization process. Accurate forecasts are essential for a reliable large-scale wind power integration, allowing efficient operation and maintenance, planning of unit commitment, and scheduling by system operators. However, due to non-stationarity, randomness, and intermittency, forecasting wind power is challenging. This work investigates a multi-modal approach for wind power forecasting by considering turbine-level time series collected from SCADA systems and high-resolution Numerical Weather Prediction maps. A neural architecture based on stacked Recurrent Neural Networks is proposed to process and combine different data sources containing spatio-temporal patterns. This architecture allows combining the local information from the turbine’s internal operating conditions with future meteorological data from the surrounding area. Specifically, this work focuses on multi-horizon turbine-level hourly forecasts for an entire wind farm with a lead time of 90 h. This work explores the impact of meteorological variables on different spatial scales, from full grids to cardinal point features, on wind power forecasts. Results show that a subset of features associated with all wind directions, even when spatially distant, can produce more accurate forecasts with respect to full grids and reduce computation times. The proposed model outperforms the linear regression baseline and the XGBoost regressor achieving an average skill score of 25%. Finally, the integration of SCADA data in the training process improved the predictions allowing the multi-modal neural network to model not only the meteorological patterns but also the turbine’s internal behavior.

The united nations educational, scientific and cultural organization (UNESCO) considers the historic urban landscapes as the world heritages. Managing historic city centers and maintaining historic cores are the emerging challenges for sustainable urban planning. Today, the historic cores form an important part of the economic, social, environmental, and physical assets and capacities of contemporary cities, and play a strategic role in their development. One of the most important approaches to the development of central textures, especially in historical and cultural cities, is the sustainable urban regeneration approach, which encompasses all aspects of sustainability, such as the economic, social, cultural and environmental aspects. To maintain sustainability and regeneration of historic cores of cities, it is necessary to provide insight into the underlying characteristics of the local urbanization. Furthermore, the fundamental assets are to be investigated as indicators of sustainable regeneration and drivers of urban development. In the meantime, a variety of research and experience has taken place around the world, all of which has provided different criteria and indicators for the development of strategies for the historic cores of cities. The present study, through a meta-analytic and survey method, analyzing the experience and research reported in 139 theoretical and empirical papers in the last twenty years, seeks to provide a comprehensive conceptual model taking into account the criteria and indices of sustainable regeneration in historic cores of cities. The quality of the survey has been ensured using the preferred reporting items for systematic reviews and meta-analysis (PRISMA).

The main aim of this work is to propose a new algorithm of reliability assessment for steel civil engineering structures subjected to fire temperatures. This new algorithm is based upon the relative probabilistic entropy concept elaborated by Bhattacharyya, and this probabilistic distance is sought in-between extreme and admissible deformations of some structural beam subjected to higher temperatures. Similar to the First Order Reliability Method, this approach uses the first two probabilistic characteristics of the structural response, when structural output may be modelled with the use of Gaussian distribution. The probabilistic structural response is found here using hybrid computational technique–the Finite Element Method system ABAQUS with its fully coupled thermo-elastic analysis with 3D solid elements and probabilistic modules implemented in the computer algebra system MAPLE. The probabilistic response is determined via a triple stochastic analysis, which is based on the classical Monte-Carlo simulation, iterative generalized stochastic perturbation technique, and also using semi-analytical probabilistic calculus. Final determination of the relative entropy in the Serviceability Limit State of the given structure and its comparison with the results obtained using the FORM analysis enables to calibrate this new technique to numerical values proposed in the engineering designing codes. Hence, a more accurate probabilistic method may use some experimental-based admissible values included in the existing design of legal provisions.