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170 required temperature the first door will be replaced for another one in which scale sample is located. [3] Measuring recording central control panel (exchange) – see picture 2 – is connected with cable departures from all measuring places (thermo‐couples). This control panel records data from each thermo‐couples in dependence on time during all measuring time until we reach steady state. After that we subtract needed temperatures to define temperature gradient and through measured out points we interlay curve. Notice: Temperature record during heating can be used for calculation of thermal conductivity coefficient in dependence on temperature by our develop non‐stationary method. [4] Ventilator which is fan exterior surface of scale sample so that the constant temperature in room was guaranteed. Figure 1: Thermo‐couple “tree” Figure 2: Recording central control panel
4.Measured values and calculation In order to check measuring we used samples made of cement mortar which had been used for finding temperature dependence on thermal conductivity coefficient by non‐ stationary method. Measured values of temperature gradient were downloaded in electrical protocol from measuring panel to computer. To particular calculation was created computer programme. Input data are measured values of temperature gradient and one value of thermal conductivity coefficient by one specific temperature which was define by another method. In the picture 3 there is output from computer program. In right top part there is figure of temperature gradient after stabilization and in right down part there is temperature dependence on thermal conductivity coefficient calculated according measured values inserted on left side. In order to compare picture 4 there is plot dependence of thermal conductivity coefficient realized by non‐stationary method. Figure 3: Output from computer program 171
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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
Page 119 and 120: temperature difference [°C] 180 16
Page 121 and 122: [4] ČÍČEL, B. - NOVÁK, I. - HOR
Page 123 and 124: space and the crystallization press
Page 125 and 126: 20 mm face to the penetrating KNO3
Page 127 and 128: Cb [kg/m 3 (sample)] 1800 1600 1400
Page 129 and 130: D [m 2 /s] 1.0E-03 1.0E-04 1.0E-05
Page 131 and 132: Thermomechanical modelling of matur
Page 133 and 134: ε ε (velocity rates) a x , t . By
Page 135 and 136: ε ε w v The process of redistribu
Page 137 and 138: Conclusion In this paper we have br
Page 139 and 140: most popular among direct technique
Page 141 and 142: • Closed pores (not available for
Page 143 and 144: espective volume of inclusions frac
Page 145 and 146: Summary Among the indirect methods
Page 147 and 148: Thermal, hygric and salt‐related
Page 149 and 150: The water vapor diffusion coefficie
Page 151 and 152: Thermal properties Thermal conducti
Page 153 and 154: On the other hand, apparent moistur
Page 155 and 156: Thermal conductivity.. [Wm -1 K -1
Page 157 and 158: Properties of innovative materials
Page 159 and 160: or hygrothermal analysis of buildin
Page 161 and 162: where Da is the diffusion coefficie
Page 163 and 164: The bending and compressive strengt
Page 165 and 166: moisture diffusivity which was caus
Page 167 and 168: Abstract: Thermal conductivity in d
Page 169: , (5) where λ is thermal conductiv
Page 173 and 174: Acknowledgements This research has
Page 175 and 176: 3 Results During heating, the struc
Page 177 and 178: Acknowledgment This work was suppor
Page 179 and 180: mixture by short mixing, the mixtur
Page 181 and 182: detected by MIP and thus the intrus
Page 183 and 184: diffusion. The general Arrhenius eq
Page 185 and 186: Thermal conductivity measurement of
Page 187 and 188: S s o 2 4 4 λ ∇ T = wεσ ( T
Page 189 and 190: steel (20 W m ‐1 K ‐1 ) is arou
Page 191 and 192: 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 ∫
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Alloy Components Weight Percent, [%
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Figure 8: Final results of the ther
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Figure 11: Preliminary results of t
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In case of the FeNi35, FeNi39 and F
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Experimental Methods Compressive st
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Type of mixture Water transport pro
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Thermal properties The thermal para
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Identification of Some Thermophysic
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Physical model of the direct proble
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2 ( λ − Bi) sin( λ) − 2λ Bic
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To calculate the sensitivity coeffi
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symmetry of the specimen when the t
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Figure 5: View of experimental setu
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During the inverse calculations the
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temperature dependence for the blac
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4. Conclusions The results of the t
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cross‐planar direction applying s
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3. Thermal diffusivity identificati
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Table 2: Effect of the convective h
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[2] BODZENTA, J.; BURAKA, B.; NOWAK
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doc. Ing. Jiří Vala, CSc. Brno Un
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