3D structured TiO2-based aerogel photocatalyst for high-efficiency degradation of toluene gas

Photocatalytic technology is a “green”, environmentally friendly, energy-saving technology, which is considered to be an ideal method for removing volatile organic compounds (VOCs). At present, photocatalytic technology mostly uses powdered...

Energy-Saving Technology Opportunities and Investments of the Italian Foundry Industry

The foundry industry is regarded as one of the most energy-intensive industrial sector due to its energy consumption up to 9 MWh/ton of produced metal. As a result, many companies are trying to increase the energy efficiency of their foundry plants. Since many energy-saving technologies are proposed by manufacturers and the literature, choosing the most appropriate one is a difficult task. Moreover, being updated with the available energy-saving solutions is complicated because of the quick technology advances. Consequently, this paper aims at investigating the recent and future opportunities and investments for reducing the energy consumptions of the technologies of Italian foundry companies. Additionally, it aims at presenting a list of available technological solutions validated by Italian experts. To this end, the Energy Audits developed by 231 plants were analyzed to extract the implemented and planned interventions. Furthermore, the economic data available within the Energy Audits were studied to determine the advantages of a given technological solutions compared to the others. It emerged that the companies are strongly investing in increasing the efficiency of the auxiliary systems such as compressors and motors. The outcomes of this study can assist both researchers and energy managers in choosing the most appropriate energy-saving solutions.

Energy-saving technology of BIM green buildings using fractional differential equation

In order to solve the problem of the traditional gray prediction model (GM) during determination of the accuracy of buildings’ energy savings and its poor fitting of data, the idea of a fractional model based on the traditional first-order one-variable GM(1,1) model is applied. We use the GM–backpropagation (GM-BP) neural network to solve the optimal fractional order and establish a fractional GM(1,1) model based on the GM-BP neural network. Example calculation shows that the fractional GM(1,1) model can improve the prediction accuracy of buildings’ energy savings, and selecting the optimal order can further improve the prediction accuracy and decrease the error level when using the GM-BP neural network. This work shows that the fractional GM(1,1) model based on the GM-BP neural network has an important guiding role in the energy savings of buildings.

Formulation and development of energy-saving technology for drying seeds of desert fodder plants

The article discusses the possibility of increasing the efficiency of seed drying using energy storage. The recommended modes of the drying process and the selection of the most effective modes to use in drying units are presented. A method of additional thermal radiation for a vacuum chamber using a phase change of the heat carrier is presented. The diagram of the energy storage process and the diagram of the process of using the stored energy are shown.