Mechanics of Micro- and Nano-Size Materials and Structures

For this reprint, we intend to cover theoretical as well as experimental works performed on small scale to predict the material properties and characteristics of any advanced and metamaterials. New studies on mechanics of small-scale structures such as MEMS/NEMS, carbon and non-carbon nanotubes (e.g., CNTs, Carbon nitride, and Boron nitride nanotubes), micro/nano-sensors, nanocomposites, macrocomposites reinforced by micro-/nano-fillers (e.g., graphene platelets), etc., are included in this reprint

Corrosion and Degradation of Materials

Studies on the corrosion and degradation of materials play a decisive role in the novel design and development of corrosion-resistant materials, the selection of materials used in harsh environments in designed lifespans, the invention of corrosion control methods and procedures (e.g., coatings, inhibitors), and the safety assessment and prediction of materials (i.e., modelling). These studies cover a wide range of research fields, including the calculation of thermodynamics, the characterization of microstructures, the investigation of mechanical and corrosion properties, the creation of corrosion coatings or inhibitors, and the establishment of corrosion modelling. This Special Issue is devoted to these types of studies, which facilitate the understanding of the corrosion fundamentals of materials in service, the development of corrosion coatings or methods, improving their durability, and eventually decreasing corrosion loss

Advances in Laser Materials Processing

Laser processing has become more relevant today due to its fast adaptation to the most critical technological tasks, its ability to provide processing in the most rarefied and aggressive mediums (vacuum conditions), its wide field of potential applications, and the green aspects related to the absence of industrial cutting chips and dust. With the development of 3D production, laser processing has received renewed interest associated with its ability to achieve pointed to high-precision powder melting or sintering. New technologies and equipment, which improve and modify optical laser parameters, contribute to better absorption of laser energy by metals or powder surfaces and allow for multiplying laser power that can positively influence the industrial spread of the laser in mass production and advance the existing manufacturing methods. The latest achievements in laser processing have become a relevant topic in the most authoritative scientific journals and conferences in the last half-century. Advances in laser processing have received multiple awards in the most prestigious competitions and exhibitions worldwide and at international scientific events. The Special Issue is devoted to the most recent achievements in the laser processing of various materials, such as cast irons, tool steels, high entropy alloys, hard-to-remelt materials, cement mortars, and post-processing and innovative manufacturing based on a laser

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.project LifeSaver - Context sensitive monitoring of energy consumption to support energy savings and emissions trading in industry (G.A. FP7-ICT-287652