Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control

Introducing Dynamic Nonlinear Soil-Foundation-Structure Interaction Effects in Displacement-Based Seismic Design

An iterative linear-equivalent procedure to take into account nonlinear soilstructure interaction effects in the displacement-based seismic design is presented for the case of shallow foundations. The procedure is based on the use of empirical curves to evaluate the stiffness degradation and the increase of damping ratio as a function of foundation rotation. Iterations are performed to ensure that admissible values of foundation rotations are complied with, in addition to the standard checks on structural displacements and drifts. Some examples of application of the approach to the design of bridge piers are provided. Design results are checked by means of nonlinear dynamic time-history analyses performed by a macro-element-based numerical tool, assuming nonlinear behavior of both structure and soil-foundation system

Biomolecules extraction from coffee and cocoa by‐ and co‐products using deep eutectic solvents

BACKGROUND : Coffee pulp (CP), cocoa husk (CH), and pod husk (CPH) are the main agro‐residues from coffee and cocoa industries. They are sources of useful biomolecules, such as phenolic compounds, fibers, and alkaloids, among others. In this study, different compositions of deep eutectic solvents (DES) were investigated as a green and sustainable extraction media, with respect to their extraction capacity. The extraction yields were evaluated using heat stirring‐assisted extraction (HSE) or ultrasound‐probe assisted extraction (UPAE).RESULTS : The results showed an important effect of the DES composition. Choline chloride (ChCl) based‐DES were the most effective, specifically lactic acid:ChCl (2:1 mol ratio), and the extraction capacity of DES was higher with UPAE (3 min/constant duty cycle (200 W)), in comparison with HSE (1 h/30 min). Chlorogenic acid, caffeine, and theobromine were identified as the main bioactive compounds. Interestingly, under specific conditions, DES allowed the formation of a molecule, identified as furfural by ultrahigh‐performance liquid chromatography mass spectrometry (UPLC‐MS), which could not be obtained using conventional extraction solvent (ethanol 70% v/v).CONCLUSION : DES showed a sustainability and high extraction capacity of biomolecules. In addition, their use as extraction solvents could lead to the formation and production of valuable building block molecules from plant biomas