34 research outputs found

    Experimental and numerical VOC concentration field analysis from flooring material in a ventilated room

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    International audienceThe aim of this study is to analyse the impact of volatile organic compounds emissions from a solid flooring material on the concentration field in a ventilated room. A field study has been conducted in the CSTB experimental house MARIA. Measurements were performed in a test room recently equipped with a flooring material made of pine wood and under controlled ventilation conditions. α-Pinene was selected as tracer from flooring VOC emissions. Velocity and temperature fields are measured in different points of the room. As the experiment is conducted in a room of a real house, thermal conditions cannot be imposed. However, indoor wall surface temperatures are measured in order to control the stability of boundary conditions during the experiment. α-Pinene concentrations were measured in the test room and in the extract flow. The emissions of the solid flooring material can be calculated from those measurements considering α-pinene as a non reactive compound and steady state conditions. Experiments were conducted for different air flow rates controlled with a mechanical extraction placed on the door of the room. Measured α-pinene concentrations and air velocities have been compared with steady state computional fluid dynamic (CFD) calculation fields. They show a good agreement. We observed a relatively homogeneous VOC concentration field in the room except in the air flow supply and near the flooring surface where stratification of the tracer occurs

    A framework for multi-objective optimization of small-scale food processes

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    International audienceFood process design is a challenging task, as several potentially conflicting objectives are targeted (product quality, cost reduction, environmental impact reduction...) under a number of constraints (e.g safety). Multi-objective optimization (MOO) is a powerful tool to solve this kind of problem but is still only partially used within design methods for food processes. By contrast, in other sectors such as mechanical engineering, Multi-criteria Decision Making (MCDM) methods are at the core of design optimization procedures.To help design food processes in a more holistic way, we propose a framework to develop MOO methods, consisting of five “building blocks”:i. a predictive process model;ii. performance indicators;iii. decision-maker and/or expert preferences;iv. a selection method to select one or several “best” trade-offs;v. an optimization algorithm to find the best design solutions among the feasible ones.This framework was used to solve a number of design problems at the QualiSud Joint Research Unit, including a fish hot-smoking process, a cassava starch dryer, and a supply of bioenergy for a cereal based dryer. The authors used these examples to illustrate the design framework and highlight the interest and the potential of coupling design theory principles to MOO and MCDM methods.The results first demonstrate the ability to find satisfying solutions despite multiple constraints and conflicting objectives. They also show the opportunity to provide guidelines for equipment design among numerous possible solutions. They finally show that decision-maker preferences and expert knowledge can be integrated in the design procedure thanks to MCDM methods

    Modelling the transfer and degradation kinetics of aroma compounds from liquid media into coffee beans during simulated wet processing conditions

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    International audienceModels of increasing complexity were developed to identify and represent mechanisms affecting the evolution of the concentration of 3 aroma compounds (2-phenylethanol, isoamyl acetate and butanal) usually produced by yeasts and transferred to coffee beans during the fermentation. Model parameters were identified from simulated wet treatment performed with four media (M1: dehulled beans, M2: demucilaginated beans, M3: depulped beans, M4: depulped beans with yeast), at 25 ◦C using labeled aroma compounds. The transfer of 2-phenylethanol was well described by a model including evolving resistance over time (R2 = 0.98) while the accumulation of isoamyl acetate and butanal was better described by a model including two first order reactions in parallel (r2 = 0.87–0.66 and r2 = 0.80–0.67, respectively). The model development contributed to understand several mechanisms involved during fermentation such as the evolutive parchment resistance and the complex degradation reactions that take place simultaneously and have a significant impact on the compounds transfer

    Optimal operating conditions calculation for a pork meat dehydration–impregnation–soaking process

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    Mass yield and operating time for a pork meat dehydration-impregnation-soaking (DIS) process were optimized using a coupled genetic algorithm/sequential quadratic programming method in order to obtain the optimal operating conditions: temperature and soaking solution concentrations. The DIS process was simulated by a neural network model. The non-linear optimization problem was constrained to ensure the main product characteristics: stability indicated by the water activity target and flavour characterized by the phenol gain target. The climatic conditions, the model validity region, the raw material costs and the operator working schedule were taken into account. Optimal solutions are discussed for three different batch configurations: single-stage processing under constant conditions, single-stage processing under varying temperature and two-stage processing under constant conditions. The most convenient operation resulted in a two-stage soaking process because of time, energy and cost savings, control convenience, product cooling anticipation and a reasonably high mass yield
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