Research On Thermal Insulation Properties Of Reflective Bubble Foil Insulation Material

Reflective bubble foil insulation material is a kind of material comprised of polyethylene bubbles combined up and down with two layers of aluminum foil reflective film,showing a "sandwich" structure.It is widely used as pipeline insulation material in many fields such as construction,thermoelectric petrochemical industry because of its light weight,waterproof and moisture proof ability,corrosion resistance and good heat insulation performance.This paper mainly studies the heat insulation performance of the reflective bubble foil insulation material.Reflective foil bubble series parallel composite heat transfer model was developed and the thermal conductivity coefficient of the composite material was calculated.The facts which influence thermal insulation property of reflective foil bubble composite materials(such as the number of bubble layers,bubble diameter,number of bubbles,temperature and aging treatment)were analyzed.The BP neural network method in Matlab was used to train the number of bubbles,the diameter of the bubbles and temperature,and the thermal conductivity of the materials was predicted and simulated.Finally,the best structure parameters were obtained.Results showed that firstly,according to the structure characteristics of the material,series-parallel heat transfer model was established.When the temperature was lower than 50 ?,the error between the calculation result and test value was less than 8%,which gave a good agreement and had practical guidance to heat insulation performance;Secondly,the thermal conductivity of composite materials decreased first and then increased as the bubble layer numbers increased.With the increase of the diameter of the bubbles and the decrease of the number of bubbles and temperature,the thermal conductivity of the materials decreased and the thermal insulation performance was improved respectively;Thirdly,when the material was treated in an aging environment(the relative temperature was 80 ?,humidity was 70%),the thermal conductivity coefficient of materials increased and the growth rate of thermal conductivity coefficient of double layers bubbles was obviously higher than the single layer;Fourthly,by rubbing the PET/Al/CPE and Al/PET/CPE the same number of times,the growth rate of thermal conductivity coefficient of PET/Al/CPE reflector sample was lower than Al/PET/CPE reflector sample.The former had better resistance to rubbing and aging;The bubble parameters were optimized based on the Matlab neural network method,and the lowest thermal conductivity of reflective foil bubble composite 0.032(W/m·K)could be obtained,when the bubble layer number was 2,air bubble diameter was 12 mm,and the temperature was 25 ?.Through the structure heat transfer model,the thermal conductivity of the material can be calculated,which has great guiding significance to the practical production and application of the material.The key parameters which affects the thermal conductivity of materials was trained and optimized using Matlab neural network tools.At the same time,with the help of memory and inductive ability of network after training,the thermal conductivity of the reflective bubble foil insulation material with different parameter structures is predicted and analyzed.The method reduces the experimental workload and has great potential application for the design and optimization of the performance of insulation materials in practical industry.