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EN
Combi-steamer condensation hoods are widely used in modern gastronomy. They condense steam produced by the combi-steamer and also filter solid particles, moisture, grease and smells. All these factors negatively affect the staff and dishes, so efficient work of the condensation hoods becomes important. A mathematical and experimental analysis of such a device is described in this paper. First a measurement methodology was designed and measurements of air humidity, temperature and mass flow rates were performed. The measurement procedure concerned dedicated a steam generator and combi-steamer. Next a mathematical model was developed. It was based on mass and energy balances of the condensation hood. The condensate flow rate turned out to be insufficient to fulfill the energy balance while measured directly. Hence, it was calculated from heater’s power of the steam generator and the balance model was validated. The combisteamer had an unknown output, so the condensate flow rate was provided by the balance model after its validation. A preliminary diagnosis of the device was carried out as well.
2
EN
In this work, a three-dimensional simplified computational model was built to simulate the passive thermo-physiological response of part of a newborn’s head for neonate’s selective brain cooling. Both metabolicheat generation and blood perfusion were considered. The set of model parameters was selected anda sensitivity study was carried out. Analysis of dimensionless sensitivity coefficients showed that the mostimportant are: the contact thermal resistance between the cool-cap and skin, the thermal resistance ofthe plastic wall material, and deep (arterial) blood temperature. The function specification method wasapplied to estimate the value of the contact resistance. Two, four and six computationally simulated mea-surements with different uncertainties were used to adjust random contact resistance value to the assumedone. Results showed that when using only two measurements having 2% of the uncertainty, the error ofestimation does not exceed 9.8%. However, when using six measurements having 1% of uncertainty, theresulting estimation is burdened with an error of 0.3% only.
3
Content available remote Estimation of the ischemic brain temperature with the particle filter method
EN
In this work, a two-dimensional model was developed to analyze the transient temperature distribution in the head of a newborn human, during local cooling promoted by the flow of cold water through a cap. The inverse problem dealt with the sequential estimation of the internal temperature of the head, by performing non-invasive transient temperature measurements. A state estimation problem was solved with the sampling importance resampling (SIR) algorithm of the particle filter method. Uncertainties in the evolution and observation models were assumed as additive, Gaussian, uncorrelated and with zero means. The uncertainties for the evolution model were obtained from the Monte Carlo simulations, based on the uncertainties of the model parameters. The head temperature was accurately predicted with the particle filter method. Such a technique might be applied in the future to monitor the brain temperature of newborns and control the local cooling treatment of neonatal hypoxic-ischemic encephalopathy.
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