Experimental and numerical analysis of the influence of cable tray arrangements on the resulting mass loss rate and fire spreading

In the context of industrial buildings and power plants, electrical installations and cable trays represent a main fuel load and a potential initial fire source due to possible short circuits or comparable malfunction. Furthermore, a fire can spread from one tray to additional trays mounted above and/or horizontally on one tray. Because of the high significance of cable fires, several research projects have been carried out, investigating the fire behaviour of cables from small‐scale tests, eg, the cone calorimeter, up to large‐scale tests, analysing complete cable tray constructions. The goal of the work presented in this paper is the extension of the knowledge regarding the influence of geometrical parameters like the packing density and tray distance on the burning behaviour and fire spread of cable tray installations. The results are considered, together with test results from the literature, to quantify the main physical parameters describing the burning behaviour. In a next step, the general applicability of these parameters as input data for the parametrization of the source term of numerical simulations is shown. The test results show that the burning behaviour and the fire spreading highly depend on the cable arrangement of the cables on the cable tray, in combination with other boundary conditions. By applying the results as input for a fire simulation, the mass loss rate is considered appropriately.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Fabrication and optimization of polypyrrole/cerium oxide/glassy carbon sensing platform for the electrochemical detection of flupirtine

Journal of Applied Electrochemistry - In spite of single nanomaterials, nanocomposites have come to be the superior modifying materials for electrochemical sensing. Herein, the highly...     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

A facile method for preparation of PGS@ZB‐N and gas‐sol alternating synergistic effect for fire resistance of EVA

Through the simple precipitation of palygorskite (PGS) by zinc borate (ZB) (to make PGS@ZB) and the decoration of PGS@ZB by dodecylamine (N), a novel organic‐inorganic@inorganic hybrid flame retardant of PGS@ZB‐N was prepared and was incorporated with ethylene vinyl acetate copolymer (EVA) to improve its flame retardance. The structure and morphology of PGS@ZB‐N were characterized by Fourier transform infrared (FTIR) spectroscopy, X‐ray diffraction (XRD), and scanning electron microscopy (SEM), and it was confirmed that the PGS@ZB‐N hybrid had been successfully prepared. The flame retardancy and burning behavior of EVA/PGS@ZB‐N/EG (EG = expandable graphite) composite were studied through thermogravimetric analysis (TGA), limiting oxygen index (LOI), UL‐94 (by the vertical burning test), and cone calorimeter test (CCT) characterizations. The prepared EVA/PGS@ZB‐N/EG composite obtained an LOI value of 41.2% with the addition of 30 wt% PGS@ZB‐N/EG. It was found that EVA/PGS@ZB‐N/EG was protected through a gas phase and condensed phase alternating synergistic effect mechanism.     

Effect of fortification with asparagus powder on the qualitative properties of processed cheese

The qualitative properties of processed cheese (PC) fortified with different levels of asparagus powder (AP) (0.5%, 1% and 1.5% wt/wt) were evaluated during storage. AP decreased the pH and lipolysis indexes and increased the phenolic content, antioxidant activity and proteolysis of the processed cheeses. AP made the structure of the cheese more elastic, increased the rigidity and decreased the spreadability compared with the control sample, which corresponded to the results obtained using dynamic oscillatory rheometry. The results showed that AP as a rich source of bioactive components could be used for the fortification of processed cheeses.     

Random poly(ε‐caprolactone‐L‐alanine) by direct melt copolymerization

A series of random polyesteramides (PEAs) with a range of molar composition from 90/10 to 50/50 were synthesized by direct melt polycondensation of ε‐caprolactone and l ‐alanine. Their structure was fully characterized by Fourier transform IR and NMR spectroscopy. The resulting copolymers are completely amorphous with the exception of PEA‐90/10 which possesses a semicrystalline structure. These PEAs present increasing glass transition temperatures at increasing l ‐alanine contents and exhibit fairly good thermal stability with 10% mass loss temperatures reaching 315 °C. © 2020 Society of Industrial Chemistry