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the sample on both sides of the thin‐layer heater were used to determine the heat partition generated by the heater and the temperature responses at some locations of the outer faces of the sample were input data for an inverse procedure of the parameter estimation. 244 Power supply PPS 2017 U [V], I [A] GPiB Personal Comp. H Insulation (Foamed polystyrene ) Sample (Foamglas) Sample (Foamglas) Kapton thin – layer heater KHR Sample Th3 (Foamglas) Th4 Sample (Foamglas) Bench vice Th2 Th1 Insulation (Foamed polystyrene ) Bench vice GPiB Th5 NiCr-NiAl Thermostat (Water+ice) Meas. Data Multimeter Keithley 2001 Figure 4: Sketch of measurement setup (scale not preserved) The thin‐layer Kapton heater of thickness 0.15 mm and of effective diameter (2Rg = 29.09 mm) was program driven due to stabilized power supply PPS 2017 made by AMREL firm (USA). To obtain temperature characteristics of the estimated thermal conductivity λz (T), and the specific heat cp(T) of the investigated material the specimen was kept in the oven with a set and controlled temperature. The view of some parts of the experimental setup is shown in Figure 5.
Figure 5: View of experimental setup The accepted data for inverse calculations are given in Table 1. 245
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Thermophysics 2009 29 th and 30 th
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Content Ivan Baník, Jozefa Lukovi
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Measurement of the thermo‐physica
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As the right side of the previous r
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The initial vector k r in the k1, k
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2.4 The computer programs testing T
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Investigation of moisture influence
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⎛ t t ⎞ −1 ⋅ ln⎜ ⎝ tm t
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Density [kg.m -3 ] 620 600 580 560
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for a new building have to be great
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Fig.1. Photo of the hot ball sensor
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Fig.6.Left: formation of blocks. Ri
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4. Conclusions With this experiment
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1a. Three‐dimensional temperature
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n+ ∞ ( ) 4 ( ) ∑ π n= 1 ( 2 1)
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a 2 2 ( Fo) ⎛ l ⎞ r = ⎜ ⎟
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Substitution of ordinates of the in
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Moisture transport through porous m
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Data acquired through the hot ball
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In this way, the water spreading wa
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Thermal conductivity [W m -1 K -1 ]
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Relationship between relative permi
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( ) i n Φ − Φ K i = ki i i, cri
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Figure 4: Comparison of measured an
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Computational modelling of coupled
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a ξ = d 2 ( lnκ − lnκ ) lnξ +
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on the results of experiments and c
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Figures 8a, b: Moisture content (a)
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Conclusions The computer simulation
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properties as are the bulk density,
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elation determined from the measure
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In the evaluation of the difference
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Heat source I RT-Lab II Specimen Ch
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Thermal conductivity [W m -1 K -1 ]
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silicon glue epoxy probe hole Figur
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Computational modelling of temperat
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1 2 3 EXT. INT. 5-15 50-60 375 5 Nu
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Fig. 4 shows a comparison of the re
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Envelope D Figs. 14, 15 present the
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Application of computational modell
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Table 2: Basic material characteris
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Temperature [K] 320 300 280 260 240
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Mineral wool has the same effect as
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Nowadays, most of concrete building
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Figure 2: Ceramic dessicator plate
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dessicators are decreased by the pe
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The surface water vapour diffusion
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where h is the Planck constant and
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(a) (b) Figure 2: Schematic picture
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[7] BLUM, V.; HART, G. L. W.; WALOR
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Analysis of moisture hysteresis of
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The water content during scanning b
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All analysed cellulose based materi
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Thermodilatometry of ceramics using
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of the dilatometric cell with the s
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thermal expansion / % 2 1,5 1 0,5 0
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[8] KAMSEU, E. ; LEONELLI, C. ; BOC
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heating, the temperatures were meas
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temperature difference [°C] 140 12
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temperature difference [°C] 180 16
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[4] ČÍČEL, B. - NOVÁK, I. - HOR
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space and the crystallization press
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20 mm face to the penetrating KNO3
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Cb [kg/m 3 (sample)] 1800 1600 1400
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D [m 2 /s] 1.0E-03 1.0E-04 1.0E-05
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Thermomechanical modelling of matur
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ε ε (velocity rates) a x , t . By
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ε ε w v The process of redistribu
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Conclusion In this paper we have br
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most popular among direct technique
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• Closed pores (not available for
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espective volume of inclusions frac
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Summary Among the indirect methods
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Thermal, hygric and salt‐related
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The water vapor diffusion coefficie
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Thermal properties Thermal conducti
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On the other hand, apparent moistur
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Thermal conductivity.. [Wm -1 K -1
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Properties of innovative materials
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or hygrothermal analysis of buildin
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where Da is the diffusion coefficie
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The bending and compressive strengt
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moisture diffusivity which was caus
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Abstract: Thermal conductivity in d
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, (5) where λ is thermal conductiv
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4.Measured values and calculation I
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Acknowledgements This research has
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3 Results During heating, the struc
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Acknowledgment This work was suppor
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mixture by short mixing, the mixtur
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detected by MIP and thus the intrus
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diffusion. The general Arrhenius eq
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Thermal conductivity measurement of
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S s o 2 4 4 λ ∇ T = wεσ ( T
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steel (20 W m ‐1 K ‐1 ) is arou
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significant larger cross‐section.
Page 193 and 194: Water and heat transport properties
Page 195 and 196: The open porosity ψ0 [%], bulk den
Page 197 and 198: Table 3: Basic material parameters
Page 199 and 200: Acknowledgements This research has
Page 201 and 202: comparison of results we can determ
Page 203 and 204: specimen and heat source R at infin
Page 205 and 206: 6.E-04 4.E-04 ΔU (V) 2.E-04 0.E+00
Page 207 and 208: [3] KUBIČÁR Ľ. Pulse method of m
Page 209 and 210: silicate binders as partial replace
Page 211 and 212: Table 2. Mechanical properties HPC
Page 213 and 214: HPC Table 5. Water transport proper
Page 215 and 216: The results obtained for using high
Page 217 and 218: aerospace engineering, cryogenic en
Page 219 and 220: 4 ⎡ ′ ⎤ Δθ( t) = ⎢ l ∫
Page 221 and 222: Alloy Components Weight Percent, [%
Page 223 and 224: Figure 8: Final results of the ther
Page 225 and 226: Figure 11: Preliminary results of t
Page 227 and 228: In case of the FeNi35, FeNi39 and F
Page 229 and 230: Experimental Methods Compressive st
Page 231 and 232: Type of mixture Water transport pro
Page 233 and 234: Thermal properties The thermal para
Page 235 and 236: Identification of Some Thermophysic
Page 237 and 238: Physical model of the direct proble
Page 239 and 240: 2 ( λ − Bi) sin( λ) − 2λ Bic
Page 241 and 242: To calculate the sensitivity coeffi
Page 243: symmetry of the specimen when the t
Page 247 and 248: During the inverse calculations the
Page 249 and 250: temperature dependence for the blac
Page 251 and 252: 4. Conclusions The results of the t
Page 253 and 254: cross‐planar direction applying s
Page 255 and 256: 3. Thermal diffusivity identificati
Page 257 and 258: Table 2: Effect of the convective h
Page 259 and 260: [2] BODZENTA, J.; BURAKA, B.; NOWAK
Page 261 and 262: doc. Ing. Jiří Vala, CSc. Brno Un
Page 263 and 264: 263
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