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Tokyo, ICCS 2013. Hygrothermal behavior modeling of different Lime-Hemp concrete mixes. Samuel Dubois. PhD Student , Gembloux ABT, Belgium. Lime-Hemp Concretes. A sustainable construction material (Low carbon) Made of hemp shivs + Lime-based binder Cast, sprayed or prefabricated
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Tokyo, ICCS 2013 Hygrothermal behavior modeling of different Lime-Hemp concrete mixes Samuel Dubois PhDStudent, Gembloux ABT, Belgium
Lime-Hemp Concretes • A sustainable construction material (Low carbon) • Made of hemp shivs + Lime-based binder • Cast, sprayed or prefabricated • Different proportions depending on final usage
Lime-Hemp Concretes Roof, wall, slab or plaster mixes
Lime-Hemp Concretes • Stated to offer a comfortable indoor climate • High porosity and hygroscopicity • Moisture storage and vapor permeability both high Surrounding Air High moisture exchange capacitywithenvironment +Q • Potentially good in regulating variations of indoor relative humidity • Linked latent heateffects
How to characterize this behavior? • Experimentally : • Numerically : • Moisture Buffer Value (MBV) protocol • Sampleundercyclic relative humidity sollicitations • Weight variation monitoring • Heat Air and Moisture (HAM) Models • PDE Equations • Lots of availablemodels • Differenthygrothermalparameters
Objectives • Characterize the behavior of differentsamplesduring a MBV test (cyclic RH) • Confront the experimentalresults to a HAM model • Gethygrictransfersparametersthrough inverse modeling
Experimental set-up • 3 different samples • Variation of portland cement dosage Quantify a possible effect of hydraulic binder on moisture exchange capacity • Sample conditionment • Initially in equilibrium with 50%RH • One unique exchange face 25% PC 75% PC 100% QSC
Experimental set-up • Climate chamber + sensors • 8 hours @ 75%RH followed by 16 hours @ 33%RH • Constant temperature • Continuous weight monitoring • Surface temperature monitoring (Latent heat!) • Indoor air temperature/relative humidity monitoring
Hygrothermal model • Developed in COMSOL Multiphysics • Advantages concerning interoperability • Coded in MatLab for communication with the inverse modeling tool • Mathematical representation • Two balance equations + Boundary conditions • Two variables (temperature and relative humidity) / 1D / Simplification assumptions Moisture Heat
Inverse Modeling? • The opposite of direct modeling • Find the best estimates of hygrothermal transfer parameters • We would normally measure first the parameters and then predict the behavior • Here an algorithm compares experimental and numerical results in an optimization process • Benefit? • Multiple parameters obtained within one experiment Findparameterswhichminimize the differencebetween model output and experimentalresults Twodatasets for the estimation : surface T and weight variation
Hygrothermal model • What are the parameters to be estimated? • Moisture capacity (storage), vapor permeability and surface resistance • Impossible to estimate heat transfer parameters! • Optimization on 2 datasets with fixed heat parameters Exchange properties of the boundary layer Moisture balance Boundary conditions
Results (Experimental) • The 3 samples behave similarly
Results (Inverse modeling) • LH sample • Resistance factor and initial conditions well optimized • Vapor permeability and moisture capacity highly correlated Inverse modeling
Results (Inverse modeling) • Model and experimental data comparison
Conclusions • The hydraulic binder dosage (Portland cement) have little influence on isothermal hygric properties of LHC (in the range 33-75%RH) • The proportion hemp/binder is more crucial • The MBV protocol is unable to give information about thermal transfer properties but shows latent heat effects • Interesting to explore other RH range other phenomena • Inverse modeling is a powerful tool