Advanced use of HAMLab on Common Exercise 1 A.W.M. (Jos) van Schijndel Eindhoven University of Technology, Homepage HamLab: http://bf1.fago.bwk.tue.nl/jos/MatLab/MatLab.htm

Summary In this paper, the advanced use of HAMLab (Heat, Air & Moisture simulation Laboratory) on

Common Exercise 1 (CE1) is given. The aim to show more capabilities of HAMLab

compared with paper [TUE Oct 2004 Paper A41-T1-Nl-04-4]. The first Section presents a

comparison between the post processing approach and a full coupling between HAMBase and

FemLab. It seems that the post processing approach can be applied in this case. Section 2

shows how the 1D FemLab model can be extended to 2D and 3D. Section 3 shows the results

of a parameter study. A preliminary conclusion is that non-material based parameters as

mentioned in Section 3.1, whose values are uncertain in reality, have a great impact on the Rh

of the indoor air. Appendix A contains the complete mfiles for used S-Function of the full

coupling model of Section 1. Appendix B contains the complete mfile for 2D extension of the

roof. Appendix C contains the complete mfile for 3D extension of the roof

1 Post processing versus full coupled In figure 1.1 the HAMBase model used for the post processing approach is shown. This is the

same model that has been used at Section 2 and 5 of [1]:

Figure 1.1 The model used for the post processing approach

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This model will be compared to a full coupled approach, where a FemLab model of the roof

will be coupled to the HAMBase model of Figure 1. This full coupled model is shown in

figure 1.2:

Figure 1.2 The full coupling between HAMBase and the FemLab model of the roof

1.1 Input

1.1.1 HAMBase The HAMBase input file is identical to Appendix A of [1], except for one change. The

surface area of the roof is minimised by:

BASE.wallex{5} = [1, 0.01 , 3, 5, 0];

1.1.2 FemLab The FemLab mfile of Appendix C of [1] is transformed into 2 files, a starting mfile and a S-

Function mfile. The starting mfile is used as initialization of the S-Function mfile. The S-

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Function is used as a coupling block between FemLab and SimuLink. Both files are shown in

Appendix A.

1.2 Output Figures 1.3 – 1.6 show a comparison (simulation period 10 days) between the two modeling

approaches:

Figure 1.3 Indoor air temperature

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Figure 1.4 Indoor Rh

Figure 1.5 Roof surface temperature

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Figure 1.6 Roof surface vapor pressure

The comparison shows relative small differences between the post processing approach and

the full coupled model. It seems that the post processing approach can be applied in this case.

2. Roof model extensions to 2D and 3D

2.1 2D Model of the roof The FemLab mfile of Appendix C of [1] is extended to a 2D Heat and Moisture transfer

model. In Appendix B the complete FemLab file is given.

Figures 2.1 and 2.2 show some typical results:

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Figure 2.1 The geometry

Figure 2.2 The 2D temperature distribution at t=48 hr

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Figure 2.3 The 2D vapor pressure distribution at t=48 hr

2.2 3D Model of the roof and walls The FemLab mfile of Appendix C of [1] is extended to a 3D Heat and Moisture transfer

model. In Appendix C the complete FemLab file is given.

Figures 2.4 and 2.7 show some typical results:

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Figure 2.4 The geometry

Figure 2.5 The mesh

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Figure 2.6 The temperature distribution at t = 10 hrs

Figure 2.7 The vapor pressure distribution at t = 10 hrs

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3 Parameter study In this Section the influence of important uncertainties on the indoor Rh, heating and cooling

load is investigated. The studied uncertainties are divided into to groups a) non material based

uncertainties: ventilation, internal surface coefficients and furniture and b) material based

uncertainties: heat conduction, diffusion resistance and vapor capacity.

3.1 Influence of ventilation, heat transfer coefficients and furniture The next parameters are varied; each parameter has 3 possible values

1) The internal surface heat resistance coefficient of all constructions [0.08 , 0.121, 0.25]

2) The ventilation of the room: [0.2, 0.41, 0.6]

3) The moisture capacity of the furniture [0, 0.5, 1] (unit: times capacity of air in room)

This gives a total of 3x3x3=27 possible values for each time step. The maximum, minimum

and band-with is plotted for the Rh, heating and cooling loads in figures 3.1 – 3.3:

Figure 3.1 The Rh dispersion

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Figure 3.2 The heating load dispersion

Figure 3.3 The cooling load dispersion

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3.2 Influence of material properties The next parameters are varied; each parameter has 3 possible values

1) The heat conduction of the second layers (insulation) of all constructions [0.03, 0.04, 0.06]

2) The moisture capacity of each first internal layer is multiplied by [0.5, 1, 1.5]

3) All diffusion resistances are multiplied by [0.5, 1, 1.5]

Again this gives a total of 3x3x3=27 possible values for each time step. The maximum,

minimum and band-with is plotted for the Rh, heating and cooling loads in figures 3.4 –3.6

Figure 3.4 The Rh dispersion

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Figure 3.5 The heating load dispersion

Figure 3.6 The cooling load dispersion

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4. Discussion and preliminary conclusions

Full coupling versus post processing

The comparison shows relative small differences between the post processing approach and

the full coupled model. It seems that the post processing approach can be applied in this case.

Roof model extensions to 2D and 3D

It is shown that the 1D roof model in FemLab, is relative easy extended to 2D and 3D

Parameter study

One conclusion is that non-material based parameters as mentioned in Section 3.1, whose

values are very uncertain in reality, have a great impact on the Rh of the indoor air. Perhaps

more than the material based parameters uncertainties.

References [1] TUE Oct 2004 Paper A41-T1-Nl-04-4.pdf

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Appendix A, Starting Mfile of the S-Function of figure 1.2

%ROOF600SIMUST ROOF Case 600 Open Thermal and Hygric, Climate boundary % clear all s=solid1([0 0.010 (0.010+0.1118) (0.010+0.1118+0.019)]); figure(1) geomplot(s,'sublabels','on' ,'pointlabels','on'); % 1-2-3 appla.mode.class='HeatTransfer'; appla.assignsuffix='_ht'; appla.equ.init=20; appla.equ.k= {'0.16' '0.04' '0.14' }; appla.equ.rho= {'395' '55' '530' }; appla.equ.C= {'1880' '1880' '1880' }; appla.equ.ind=[1 2 3]; appla.bnd.h= {[8.29] [0] [29.3]}; appla.bnd.Tinf= {[0] [0] [0]}; appla.bnd.type= {'q' 'cont' 'q'}; appla.bnd.ind= [1 2 2 3]; applb.mode.class='FlDiffusion'; applb.assignsuffix='_di'; applb.equ.init=1000; applb.equ.D= {'psatf(T)*1.8e-10/(101*2.1)' 'psatf(T)*1.8e-10/(14*1.4)' 'psatf(T)*1.8e-10/(120*95)' }; applb.equ.ind=[1 2 3]; applb.bnd.kc= {[2e-8] [0] [0]}; applb.bnd.cb= {[0] [0] [0]}; applb.bnd.type= {'N' 'cont' 'N'}; applb.bnd.ind= [1 2 2 3]; fem.geom=s; fem.appl={appla applb}; fem.mesh=meshinit(fem); %fem.mesh=meshrefine(fem); %? fem=multiphysics(fem); fem.xmesh=meshextend(fem); %fem.sol=femtime(fem,'tlist',[0:3600:1*24*3600]); xp=[0 0.010 (0.010+0.1118) (0.010+0.1118+0.019)];

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Appendix A, Mfile of the S-Function of figure 1.2

function [sys,x0,str,ts] = sfunheatandmoistureroof(t,x,u,flag,fem,tstap,xp) % Diskrete S-function voor FemLab % fem = fem variable alles tot behalve sol % tstap = discrete tijdstap % xp= positie % JvS sept, 2004 global Sfunfem switch flag, case 0, [sys,x0,str,ts] = mdlInitializeSizes(fem,tstap,xp); case 2, sys = mdlUpdate(t,x,u,fem,tstap,xp); case 3, sys = mdlOutputs(t,x,u,fem,tstap,xp); case 9, sys = []; % do nothing otherwise error(['unhandled flag = ',num2str(flag)]); end %end dsfunc %======================================================================= % function [sys,x0,str,ts] = mdlInitializeSizes(fem,tstap,xp) global Sfunfem %********* fem.sol=femtime(fem,'tlist',[0:1]); ntijd=length(fem.sol.u(1,:)); nStates=length(fem.sol.u(:,1)); ngrid=2*length(xp); sizes = simsizes; sizes.NumContStates = 0; sizes.NumDiscStates = nStates; sizes.NumOutputs = ngrid; sizes.NumInputs = 4; sizes.DirFeedthrough = 1; sizes.NumSampleTimes = 1; sys = simsizes(sizes); x0 = fem.sol.u(:,ntijd); str = []; ts = [tstap 0];

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Sfunfem=fem; % end mdlInitializeSizes % %======================================================================= % mdlUpdate % Handle discrete state updates, sample time hits, and major time step % requirements. %======================================================================= % function [sys,fem] = mdlUpdate(t,x,u,fem,tstap,xp) global Sfunfem % Bereken nieuwe outputstap fem.appl{1}.bnd.Tinf={ [u(1)] [0] [u(2)] }; fem.appl{2}.bnd.cb={ [u(3)] [0] [u(4)] }; tijd=[t; t+tstap/2; t+tstap]; disp(['calc ' num2str(t) ' to ' num2str(t+tstap) ]) fem=multiphysics(fem); fem.xmesh=meshextend(fem); fem.sol=femtime(fem,'tlist',tijd,'init',x); ntijd=length(fem.sol.u(1,:)); sys = fem.sol.u(:,ntijd); Sfunfem=fem; %end mdlUpdate % %======================================================================= % mdlOutputs % Return Return the output vector for the S-function %======================================================================= % function sys = mdlOutputs(t,x,u,fem,tstap,xp) global Sfunfem % bepaal output ntijd=length(Sfunfem.sol.u(1,:)); Txp=postinterp(Sfunfem,'T',xp,'Solnum',ntijd); Pxp=postinterp(Sfunfem,'c',xp,'Solnum',ntijd); sys=[Txp Pxp]; %end mdlUpdate

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Appendix B, 2D FemLab Model of the roof

%ROOF600_OPEN2DEX Case 600 Open Thermal and Hygric, Climate boundary, 2D %example % clear all global tout Rh Rhe Te Tair t_roof Tesl_roof load Case600_OpenData.mat load TslData.mat xp=[0 0.010 (0.010+0.1118) (0.010+0.1118+0.019)] yp=[0 0.012 (0.012+0.066) (0.012+0.066 + 0.009)]; roofwood=poly2([0 0 0.5 0.5],[0.5 (0.5+xp(2)) (0.5+xp(2)) 0.5]); roofcel =poly2([0 0 0.5 0.5],[(0.5+xp(2)) (0.5+xp(3)) (0.5+xp(3)) (0.5+xp(2)) ]); roofdeck=poly2([0 0 0.5 0.5],[(0.5+xp(3)) (0.5+xp(4)) (0.5+xp(4)) (0.5+xp(3)) ]); wallwood=poly2([0 0 yp(2) yp(2)] ,[0 0.5 0.5 0]); wallcel =poly2([yp(2) yp(2) yp(3) yp(3)] ,[0 0.5 0.5 0]); wallsid =poly2([yp(3) yp(3) yp(4) yp(4)] ,[0 0.5 0.5 0]); s=roofwood+roofcel+roofdeck+wallwood+wallcel+wallsid; fem.geom=s; fem.mesh=meshinit(fem); nsub=flgeomnmr(s) negd=flgeomnes(s) figure(1) geomplot(s,'sublabels','on' ); % 1-2-3 figure(2) geomplot(s,'edgelabels','on' ); axis([-0.1 0.7 -0.1 0.7]) indvar=2*ones(1,negd); indvar([16 17] )=1; indvar([1 3 5 7 9] )=3; indvar([2 11 14 18 19 20])=4; appla.mode.class='HeatTransfer'; appla.assignsuffix='_ht'; appla.equ.init=20; appla.equ.k= {'0.16' '0.04' '0.14' }; appla.equ.rho= {'395' '55' '530' }; appla.equ.C= {'1880' '1880' '1880' }; appla.equ.ind=[3 1 2 3 2 1];

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appla.bnd.h= {[8.29] [0] [29.3] [0]}; appla.bnd.Tinf= {'ti600fun(t)' [0] 'tesl_roof600fun(t)' [0]}; appla.bnd.type= {'q' 'cont' 'q' 'q0'}; appla.bnd.ind= indvar; applb.mode.class='FlDiffusion'; applb.assignsuffix='_di'; applb.equ.init=1000; applb.equ.D= {'psatf(T)*1.8e-10/(101*2.1)' 'psatf(T)*1.8e-10/(14*1.4)' 'psatf(T)*1.8e-10/(120*95)' }; applb.equ.ind=[3 1 2 3 2 1]; applb.bnd.kc= {[2e-8] [0] [0] [0]}; applb.bnd.cb= {'pi600fun(t)' [0] 'pe600fun(t)' [0]}; applb.bnd.type= {'N' 'cont' 'N' 'N0' }; applb.bnd.ind= indvar; fem.appl={appla applb}; fem=multiphysics(fem); fem.xmesh=meshextend(fem); fem.sol=femtime(fem,'tlist',[0:3600:48*3600]); %%%%OUTPUT%%%%% tu=fem.sol.tlist; ntu=length(tu); tdag=tu/(24*3600); figure(1) Mfilm=postmovie(fem,'tridata','T','Repeat',1); mapM=colormap; mpgwrite(Mfilm,mapM,'Case600_T_2D') clear mapM Mfilm figure(2) Mfilm=postmovie(fem,'tridata','c','Repeat',1); mapM=colormap; mpgwrite(Mfilm,mapM,'Case600_P_2D') figure(3) postplot(fem,'tridata','T','Solnum',49) figure(4) postplot(fem,'tridata','c','Solnum',49)

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Appendix C, 3D FemLab Model of the roof and walls

%ROOF600_OPEN3DEX2 Case 600 Open Thermal and Hygric, Climate boundary, 3D %example % clear all global tout Rh Rhe Te Tair t_roof Tesl_roof load Case600_OpenData.mat load TslData.mat %xp=[0 0.010 (0.010+0.1118) (0.010+0.1118+0.019)]; %yp=[0 0.012 (0.012+0.066) (0.012+0.066 + 0.009)]; xp=[0 0.02 (0.02+0.08) (0.02+0.08+0.02) ]; yp=[0 0.02 (0.02+0.08) (0.02+0.08+0.02) ]; roofwood=poly2([0 0 0.25 0.25],[0.25 (0.25+xp(2)) (0.25+xp(2)) 0.25]); roofcel =poly2([0 0 0.25 0.25],[(0.25+xp(2)) (0.25+xp(3)) (0.25+xp(3)) (0.25+xp(2)) ]); roofdeck=poly2([0 0 0.25 0.25],[(0.25+xp(3)) (0.25+xp(4)) (0.25+xp(4)) (0.25+xp(3)) ]); wallwood=poly2([0 0 yp(2) yp(2)] ,[0 0.25 0.25 0]); wallcel =poly2([yp(2) yp(2) yp(3) yp(3)] ,[0 0.25 0.25 0]); wallsid =poly2([yp(3) yp(3) yp(4) yp(4)] ,[0 0.25 0.25 0]); s=roofwood+roofcel+roofdeck+wallwood+wallcel+wallsid; blk1=extrude(s,'distance',0.25); blk2=block3(0.25-yp(4),0.25,0.1,'pos',[yp(4),0,0.15]); blk=blk1+blk2; fem.geom=blk; nsub=flgeomnmr(blk) nbnd=flgeomnbs(blk) figure(1) geomplot(blk,'sublabels','on','transparency',0 ); % 1-2-3 figure(2) geomplot(blk,'facelabels','on','transparency',0); fem.mesh=meshinit(fem); figure(3) meshplot(fem)

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q1=min(meshqual(fem.mesh)) %fem.mesh=meshsmooth(fem) %q2=min(meshqual(fem.mesh)) indvar=zeros(1,nbnd); indvar([28 31 33] )=1; indvar([1 4 5 8 9 12 13 16 17 21 26 32 ] )=3; indvar([2 3 7 11 15 18 19 20 24 25 30 35 36 37 38])=4; indvar([6 10 14 18 22 23 27 29 34 ])=2; indvar appla.mode.class='HeatTransfer'; appla.assignsuffix='_ht'; appla.equ.init=20; appla.equ.k= {'0.16' '0.04' '0.14' }; appla.equ.rho= {'395' '55' '530' }; appla.equ.C= {'1880' '1880' '1880' }; % 1 2 3 4 5 6 7 appla.equ.ind=[ 3 1 2 3 2 1 2]; appla.bnd.h= {[8.29] [0] [29.3] [0]}; appla.bnd.Tinf= {'ti600fun(t)' [0] 'tesl_roof600fun(t)' [0]}; appla.bnd.type= {'q' 'cont' 'q' 'q0'}; appla.bnd.ind= indvar; applb.mode.class='FlDiffusion'; applb.assignsuffix='_di'; applb.equ.init=1000; applb.equ.D= {'psatf(T)*1.8e-10/(101*2.1)' 'psatf(T)*1.8e-10/(14*1.4)' 'psatf(T)*1.8e-10/(120*95)' }; % 1 2 3 4 5 6 7 applb.equ.ind=[ 3 1 2 3 2 1 2]; applb.bnd.kc= {[2e-8] [0] [0] [0]}; applb.bnd.cb= {'pi600fun(t)' [0] 'pe600fun(t)' [0]}; applb.bnd.type= {'N' 'cont' 'N' 'N0' }; applb.bnd.ind= indvar; fem.appl={appla applb}; fem=multiphysics(fem); fem.xmesh=meshextend(fem); flsave Roof3D2withoutSol fem disp('OK') fem.sol=femtime(fem,'tlist',[0:3600:48*3600]); flsave Roof6003D2 fem %%%%OUTPUT%%%%%

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tu=fem.sol.tlist; ntu=length(tu); tdag=tu/(24*3600); figure(1) Mfilm=postmovie(fem,'tridata','T','Repeat',1); mapM=colormap; mpgwrite(Mfilm,mapM,'Case600_T_3D') clear mapM Mfilm figure(2) Mfilm=postmovie(fem,'tridata','c','Repeat',1); mapM=colormap; mpgwrite(Mfilm,mapM,'Case600_P_3D') figure(3) postplot(fem,'tridata','T','Solnum',10) figure(4) postplot(fem,'tridata','c','Solnum',10)

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