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Thermo-resistive mesh sensors (TMS) for temperature field measurements
Flow Measurement and Instrumentation 22 (2011) 343–349
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Flow Measurement and Instrumentation journal homepage: www.elsevier.com/locate/flowmeasinst
Thermo-resistive mesh sensors (TMS) for temperature field measurements Martin Ritterath ∗ , Onur Can Öztürk, Horst Michael Prasser ETHZ, IET – Laboratory of Nuclear Energy Systems Sonneggstr. 3, CH – 8092 Zürich, Switzerland
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Article history: Received 9 February 2011 Received in revised form 4 April 2011 Accepted 15 April 2011 Keywords: Temperature field Thermo-resistive mesh Containment safety Nuclear reactor safety Air ingress Mixing experiment
abstract Temperature is one of the – if not the – most frequently measured physical quantity. Most conventional temperature sensors provide only a point measurement of the temperature. In many fields of research and industry, knowledge of the temperature distribution is a great advantage. In the present contribution, a sensor for temperature field measurements is presented. The sensor is based on thermo-resistive elements (thermistors) arranged in a two- or three-dimensional matrix, where efforts for the signal acquisition do not grow proportionally to the number of channels, but only proportionally to its square root. The temperature measurement matrix has been successfully applied to a medium scale multi compartment test facility where buoyancy driven gas flows are studied in the context of nuclear reactor safety. Examples of test results are presented to demonstrate the potential of the sensor. © 2011 Elsevier Ltd. All rights reserved.
1. Introduction As temperature is one of the most frequently measured process quantities, a large variety of temperature sensors is available [1]. In industry, temperature is mostly measured with the help of single thermocouples or thermo resistive elements, such as Pt-100 thermometers. These gauges provide a temperature measurement only in the location of their installation. In order to measure a temperature distribution, a large number of gauges has to be installed in a distributed way. Commonly, temperature distributions can be measured optically using infrared imaging [2,3]. If optical access is available (i.e., if the walls are not too thick) images with high spatial resolution can be taken, depicting the incoming far-infrared radiation. The fact that the recorded images represent a superposition of the incoming radiation is disadvantageous. It is neither possible to ‘‘look behind’’ a hot body nor to extract data from a specific slice of depth-of-field. Using tomography, it is possible to reconstruct the cross-sectional distribution of a desired quantity based on the measurement of integral absorption, refraction, reflection or other. Tomographic temperature measurement on the basis of measuring the sound velocity in solids has been reported in [4]. This measurement technique seems to be inappropriate for the measurement of gases because sound irradiation into gases, and sound bending in the presence of sound velocity gradients, pose major challenges.
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Another technique, called holographic tomography, is based on the change of refractive index with temperature [5,6]. Here, the wave front shift of multiple beams from different directions around the control volume have been fed as interferometric line patterns into a computer algorithm to obtain the visualization of one threedimensional temperature field. A thermistor multiplex measurement technique was introduced [7]. They connected a set of thermistors, each in series with a diode to a TTL line decoder. Together with a voltage dividing resistor, a single thermistor temperature could be read out by pulling the according decoder line to low voltage. The voltage at the voltage divider corresponds to the temperature at the activated thermistor’s position. After all, 200 thermistors could be scanned in two seconds with a single ADC. In reactor safety research, large scale test facilities are employed to experimentally generate a database of the transient thermalhydraulic behavior of a nuclear power plant during normal operation or accident scenarios. In these experiments, aimed at CFD code validation, the desired density of the instrumentation is usually very high, which leads to high costs for a measuring system with a large number of channels. In the present work, the problem of organizing large measuring fields is solved by a comparatively low-cost adaptation of the wire-mesh sensor technology [8], where efforts for the signal acquisition do not grow proportionally to the number of channels, but only proportional to its square root. This is achieved by arranging the sensitive elements in a two-dimensional matrix that is scanned line by line. These thermo-resistive mesh sensors (TMS) were developed for generic turbulent mixing experiments of two gases with a large difference in density in presence of strong buoyancy effects. One of the gases is labeled with a higher temperature to visualize
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the mixing processes. The test facility where they are installed is called MiniPanda. The facility consists of two cylindrical volumes connected with a horizontal pipe. Both vessels, as well as the interconnecting pipe, are equipped with mesh sensors to obtain time-dependent cross-sectional temperature distributions during experiments where an exchange between cold helium from one vessel and heated air from the second vessel takes place. This experiment provides an ideal test case for CFD codes with regard to the modeling of real containment flows. 2. Thermo-resistive mesh sensors Wire-mesh sensors, as introduced [8], are based on the detection of the local electrical conductivity of a fluid using grids of crossing electrode wires. The information about the local conductivity is obtained by supplying the electrode wires of the first grid (transmitter wires) with voltage pulses in a successive order. The current arriving at the electrodes wires of the second grid (receiver wires), which are crossing the wires of the first grid in a small distance, are sampled (Fig. 1). Low impedance driving and sampling cascades of the signal acquisition unit allow focusing the measurement on each individual crossing point of a transmitter and a receiver wire. A full sampling cycle provides a two-dimensional matrix of the measuring results from all crossing points. Wire-mesh sensors are used to measure phase distributions in a gas–liquid flow with a high time resolution, which allows the detailed characterization of the dynamic gas–liquid interface [9]. A second field of application is mixing studies, where one of the fluids involved is labeled with a salt tracer affecting conductivity [10]. A third application is high-speed liquid film thickness measurement [11]. If the electrodes are arranged flush against the wall, the conductivity between the electrodes is defined by the thickness of the liquid film covering them. The wire-mesh electronics unit performs a measurement of the conductance matrix of the two-dimensional network of resistive elements, usually formed by the conducting fluid being in contact with the transmitter and the receiver wire at each crossing point of the sensor matrix. A gas temperature distribution measurement can be realized by connecting transmitter and receiver wires via thermoresistive elements arranged at the crossing points, which replace the conducting fluid of the classical application case. This simple solution allows using standard signal acquisition units for wire-mesh sensors, provided that thermoresistive elements of a convenient conductance range are available . Suitable thermo-resistive elements are negative or positive temperature coefficient semiconductors called thermistors, or any kind of metallic resistors [12]. Thermistors have a high resistance temperature coefficient, usually on the order of several percent per Kelvin, while the resistance temperature coefficient for e.g. platinum resistors is only around 3.9e−3 per Kelvin. The application of Pt1000 resistors with a wire-mesh electronics unit was described [13]. The low resistance change with varying temperature and consequently the low temperature resolution after sampling and discretization are disadvantageous in this case. Instead, the large resistance changes of a negative temperature coefficient thermistor provide good resolution with the present wire-mesh signal acquisition device WMS-200 [14]. Consequently, it is more convenient to use to semiconductor thermistors. For an application in MiniPanda, three thermo-resistive mesh sensors (TMS) were constructed. The two different designs were:
Fig. 1. Sketch of the operational principle of wire-mesh sensors [8].
• TMS-IP: A small sensor for a pipe with a diameter of 220 mm consisting of a matrix of 8×8 crossing points with a spatial pitch
wires were fixed to the back side. The axial distance of both wire planes was consequently equal to the thickness of the PCB, which is about 2 mm, a distance just suitable to accommodate the thermistors at the crossing points. The circular flow crosssection was cut out of the PCB, so that the wires were stretched over the opening. They were fixed at the border by soldering them to conducting pads on the PCB. The wires of both planes crossed at an angle of 90 deg. At the crossing points, SMD thermistors in a 0603 housing were laser soldered between a transmitter and a receiver wire (EPCOS, B57321V2473H060), see Fig. 2. • TMS-DW: Two large diameter temperature mesh sensors were constructed to be mounted in the circular cross-section of cylindrical vessels of MiniPanda. They consisted of a matrix of 16 × 16 sensing elements with a pitch of 57 mm. This time, the wires were directly attached to hooks that were fixed to the walls. Each sensor was mounted into a segment of a cylindrical PVC pipe of 968 mm inner diameter and 16 mm wall thickness. The vessels were finally composed of a number of such elements, including those with a mesh sensor. Small springs generated a nearly constant tension in the wires, which was needed to allow for thermal dilatation due to the different thermal expansion coefficients of the vessel (PVC) and the wire materials (stainless steel), as well as to reduce the impact of vibrations during the construction. The slightest stretching of the wires would otherwise have immediately lead to plastic deformation, or even destruction, and to the loss of the tension needed to keep them straight. The two wire planes were spanned with an axial distance of 40 mm. For these sensors, leaded glass encapsulated thermistors with a 0.8 mm tip size were used (EPCOS, B57540G0503H000) (Fig. 3).
of 24 mm. A double-sided printed circuit board (PCB) served as a frame for holding two grids of wires. The transmitting wires were fixed to the front side of the board, while the receiving
The sensor wires are contacted to the wire-mesh signal acquisition unit by flat ribbon cables at the outside of the vessel segments or, respectively, at the edge of the PCB of the small sensor.
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the thermistor resistance, R0 , low in order to have a high current that can be sampled with a low gain. A reference resistance of 50 k at 25 °C and 12.3 k at 60 °C was chosen as a tradeoff between low gain and sufficiently high maximum temperature. The nonlinear thermistor transfer function of the thermistor that connects resistance with temperature, as well as the lower initial precision, require an adequate calibration function. Eq. (1) approximates the transfer function of the thermistor around a reference temperature, θ0 .
R(θ ) = R0 · exp B Fig. 2. View on temperature mesh sensor, designed for the pipe.
The main differences between the two thermistor types are their housing, and consequently their mounting process, and their dynamic behavior. The glass encapsulated thermistors exhibit a response time of 0.8 s to a temperature jump induced by a hot jet. Their maximum operating temperature is 240 °C. They are ideal for wire wrapping and soldering to large meshes with a receiver–transmitter layer distance between 40 and 70 mm. The SMD thermistors exhibit a time constant of 1 s. They are designed for a maximum operation temperature of 125 °C. They are well suited for PCB-mounting or for being soldered into small gaps, such as described for the small pipe mesh sensor. Unfortunately, neither the glass case nor the SMD housing seal the thermistors hermetically. Consequently, they cannot be used in atmospheres with high humidity because water vapor destroys the sensing element. For the application presented, the thermoresistive mesh sensors were used exclusively for tests on the mixing of air and helium. The following opposing limitations restrict the choice of the resistance of the thermistors:
• A transmitter line of the WMS-200 device can drive a maximum current of 120 mA [14]. Exceeding this current leads to a loss of the low impedance of the voltage supply, which causes the excitation voltage to reduce. Consequently, the mesh sensor loses the ability to suppress cross-talk [8]. The load limit must not be exceeded. Maximum load is reached when the maximum number of (in this case 64 thermistors) acquire their minimal resistance at the upper design limit of the temperature measurement. This restriction requires a higher reference resistance R0 of the thermistors. • The received and sampled conductivity signals are amplified to meet the dynamic range of the analog-to-digital converter. The amplification can be controlled to meet the conductivity of the fluid in the case of a traditional mesh-sensor use. For higher gains the noise superimposed on the sampled signal becomes larger. Therefore, it would be advantageous to keep
1
θ
−
1
θ0
(1) [21]
where θ is temperature, R0 is the reference resistance at the reference temperature θ0 , and B is the steepness coefficient. 3. Measurement uncertainty After construction, the wire-mesh sensors were calibrated. For this purpose, both large wire-mesh sensor segments were stacked and closed with a lid. In this way, a small calibration vessel was formed. Inside a heater, a fan and the TMS-IP were placed as shown in Fig. 4. An in-situ calibration has been performed using a high precision PREMA 3040 PT100 temperature sensor as a reference instrument. Nine different temperatures were set up inside the calibration vessel and sampled for 1 s by operating the wiremesh sensor signal acquisition system at a sampling frequency of 100 Hz. The fan ensures isothermal conditions inside the calibration vessel. Afterwards, 100 samples of the AD conversion result were averaged individually for each thermistor and stored, along with the reference temperature. Parallel to the averaging, the standard deviation of the ADC results was calculated over the calibration period (i.e., from 100 samples). Due to heat loss through the vessel wall, it was difficult to set up a stationary temperature for the high temperatures, and thus no standard deviation can be given since the reference temperature is superimposed by a maximum temperature drop of 0.2 K during the sampling. For room temperature, a long time stationary reference temperature was achieved. There, the sampling period was set to 5 s. A standard deviation of 0.067 K at this constant (room) temperature was observed. The temperature resolution is not constant due to the nonlinear thermistor transfer function. It is 20 LSB (LSB = least significant bit) per Kelvin at 20 °C and 66 LSB per Kelvin at 60 °C. However, the standard deviation is larger than the discretization error. For each thermistor, a third order calibration function (Eq. (2)) was obtained by using the least-square method to fit a curve to the calibration points. The calibration function type is derived by inserting Eq. (1) into the conductance transfer function of the wire-mesh acquisition unit and solving for the temperature. The
Fig. 3. Construction principle of the temperature mesh sensor for the vessel cross sections [15].
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Fig. 5. Typical calibration function of the thermistors. The standard deviation is plotted as red error bars. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Fig. 4. Calibration setup for the temperature mesh sensors [16]. Table 1 Components of measurement uncertainty. Uncertainty of reference instrument (K) Standard deviation of measurement (K) Quality of calibration function fit, 3rd order (K) 5th order Estimated long term stability of thermistors (6 months of operation) (K)
0.01 0.067 0.3 0.1 1.5
higher-order terms compensate for the approximate character of Eq. (1), being valid only for a limited temperature range around the reference temperature, and thus allowing for application of the calibration function over a wide temperature range [16].
θ(ADC ) = a · log(ADC ) + b · log(ADC )2 +c · log(ADC )3 +d
(2)
where ADC is the conversion result from the wire-mesh electronics unit, and a, b, c and d are the polynomial coefficients (Fig. 5). It has been observed that the transfer function of the amplifier and analog-to-digital-converter-track varies slightly from day to day. If these variances of the electronics were not compensated for, an additional uncertainty of 0.24 K would be introduced to the measurement [16]. In order to compensate for these electronic variances, a self-calibration of the electronics is carried out before and after each experiment. To calibrate the electronics, a set of high precision resistors is switched between the transmitting and receiving electrodes that match the nominal thermistor resistances at 28, 45 and 88 °C. The analog-to-digital conversion results obtained from the measurement are then corrected for the electronics unit’s variance before the calibration function (Eq. (2)) is applied . The components of the measurement uncertainty are summarized in Table 1. During the experiments, the complete temperature sensor matrix was sampled at a rate of 100 Hz. 4. MiniPanda MiniPanda is a small scale test facility dedicated to the experimental investigation of phenomena that are relevant to the safety of nuclear reactor containments. MiniPanda got its name from the fact that it is a 1:4 scaled-down model of the large-scale, multi compartment nuclear reactor containment test facility PANDA at the Paul Scherrer Institute, Villigen, Switzerland. For the small test
facility, two out of four containment volumes were built at the Swiss Federal Institute of Technology (ETH) in Zurich. The two vessels (each 2 m high, 1 m diameter) are interconnected by a horizontal pipe. The vessels are referred to as ‘‘Vessel 1’’ and ‘‘Vessel 2’’. The facility enables the application of advanced instrumentation such as the in-house developed thermo-resistive mesh sensors, 520 temperature sensors in three planes. MiniPanda can be operated at ambient pressure and temperatures up to 100 °C. The advantage of having two geometrically similar facilities is that scaling studies can be performed by conducting the same experiment in both setups under similar boundary conditions. The tests presented here have so far been performed only in MiniPanda. It is planned to repeat them in the larger PANDA facility. The vessels and the interconnecting pipe (IP) are made from PVC(-U). The vessel shells have a wall thickness of 16 mm, the vessel lid and bottom are 10 mm thick, and the IP’s wall thickness is 2.5 mm. The vessel wall thickness requires no further heat insulation, but the IP is wrapped in rubber foam blankets. For accessibility and manageability, each vessel consists of six segments. The connecting gaps are sealed with duct tape. The IP consists of three flanged segments. Detailed geometric information is archived [16]. The initial conditions for the experiments described below required a separation of the two vessels during the preconditioning phase. For this separation, the interconnecting pipe was blocked by a metal sheet. On one side of the IP, a frame was installed, which served as a sliding guide for the metal sheet and held two electromagnets that pulled the metal sheet against the front side of the IP when activated. In order to start the experiment (i.e., in order to connect the two vessels) the electro-magnets were switched off. Consequently, the metal sheet slid down, unsealing the front side of the IP. For the generic air ingress experiment described below, the facility was equipped with the already-described three planes of temperature mesh sensors: TMS-DW1 (horizontal) in the lower part of Vessel 1, where the hot air falls to the bottom, TMS-DW2 (horizontal) in Vessel 2, above the pipe entrance, where the cold helium rises, and TMS-IP (vertical) in the pipe connecting both vessels (see Fig. 6). The facility is further equipped with commercial thermocouples to measure the axial temperature distribution and katharometers to measure the helium molar fraction, both located on the vessel axes (see Fig. 6). The helium molar fraction is also computed from an ultrasound time-of-flight measurement [17] along the diameter
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Fig. 6. Overview over the geometry of MiniPanda and its instrumentation: US=ultrasound transmitter, TC=thermocouple, KM=katharometer, TWMS=temperature mesh sensor.
on four levels of each vessel. Four velocity probes, based on a time-of-flight measurement of a hot air cloud created by a pulsed heater inside a measuring tube (pulsed-wire anemometers) [18] are placed above each other in the interconnecting pipe. Innerand outer- wall thermocouples mounted on both vessels allow monitoring well-controlled boundary conditions. 5. Results of generic air ingress tests Generic air ingress experiments were performed with the aim of providing data suitable for CFD code validation. A gravity-driven ingress of heavier air into the helium-filled vessel is a phenomenon found in so-called air ingress accidents at High Temperature Gas-cooled Reactors (HTGR) and Very High Temperature Reactors (VHTR) under development within the framework of the Generation IV research initiative [19,20]. In order to assess consequences of such an accident, the determination of the time-dependent air inflow into the core is essential. Important modeling issues include the molecular diffusion as well as the density gradient transient of the induced flow which is limited by countercurrent flow. These processes pose challenges to the simulation of fluid-dynamics using CFD, which creates a need for adequate experimental data suitable for model development and validation. In the preparation phase of the presented experiment, the interconnecting pipe was blocked at the side of Vessel 1. Vessel 2 was heated for approximately three hours until the air inside Vessel 2 and the IP, as well as the walls of Vessel 2 and the IP, reached the desired initial temperature of 60 °C. A homogeneous temperature distribution is achieved by stirring with the builtin fan. Vessel 1 is filled with pure helium and remains unheated at room temperature, 25 °C. Well-controlled initial and boundary conditions are guaranteed by the homogeneous filling and conditioning of both vessels during the preconditioning phase. The temperature difference between the two gases serves as labeling to visualize the mixing process and has no meaning with regard to the investigated scenario. A sudden initiation of the transient process is achieved by switching off the magnets that hold the blocking metal sheet in place. The metal sheet rapidly slides down due to gravity, thus unblocking the flow in the IP. The high density difference between the gases in the two vessels induced a gravity-driven exchange flow. A hot downward air plume penetrated the previously helium-filled Vessel 1 (see Fig. 7, upper graphs), the hot downward air plume is visualized by the warm area in yellow. The gas in the part of the vessel that
is affected by the aforementioned plume was subject to intensive mixing with increasing air fraction (Fig. 8, upper graphs). The air ingress was expressed by the temperature increase in the region around the plume as well as in the increase of the molar air fractions measured at the lower levels. In contrast to this, the upper part of Vessel 1 stayed practically filled with unmixed helium (see Fig. 8, upper graph, air fraction for the higher two sensors). Due to the air ingress in Vessel 1, helium is pushed through the IP towards Vessel 2. A counter-current flow was established with warm air at the bottom and cold helium at the top of the IP crosssection (see Fig. 7, middle graphs). Helium, after arriving in the previously air-filled Vessel 2, forms a rising plume (see Fig. 7, lower graphs, cold plume is characterized by the yellow area). In the part above the IP of Vessel 2, the helium fraction increased. Due to the vertical density gradient, helium cannot reach the part of Vessel 2 below the IP. The lower graph of Fig. 8 displays the evolution of the air inflow temperature, measured with the TMS-IP (position 4, 7). Furthermore, the lower graph of Fig. 8 depicts the evolution of the temperature at the intersection of the air plume and the measuring plane at the position of the plume center and the over the next neighbors. The temperature fluctuations in and around the air plume indicate an oscillatory movement of the plume. In order to validate the signals from the thermo-resistive mesh sensor against the molar gas fraction measured by the ultrasonic technique, the temperatures were converted into molar fractions. This transformation is possible for binary mixtures of gases. According to Richmann’s law, the temperature of two mixed fluids is given by the mass, temperature, and heat capacity of the fluid components. In case of the air ingress described, the mixing components are cold helium, initially present in Vessel 1, and hot ingressing air. The initial temperature of helium is set to 25 °C. The inflow temperature measured with the TMS-IP is applied (see Fig. 8, lower graph) as initial temperature for the ingressing air. The calculated air fraction is plotted in Fig. 8, upper graph as ‘‘calculated from Temp’’. Note that the molar air fraction calculated from the temperature is underestimated because there are heat losses from the air flow to the initially cold walls of Vessel 1. The phase of intense mass exchange finishes when the helium layer in the previously helium-filled Vessel 1 is eroded to the top of the cross-section area of the interconnecting pipe. The transient ends up in a scenario which is controlled by molecular diffusion alone. The mean temperature and the short-term standard deviation of the temperature signals obtained, both from 40 s < t < 75 s, with the TMS in Vessel 1 and 2 are plotted as a cross sectional
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Fig. 7. Cross sectional temperature distribution of TMS DW1 (Vessel 1, upper row), TMS IP (central row) and TMS DW2 (Vessel 2, lower row), blue=cold, red=hot. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 8. Upper graph: molar air fraction measured by the ultrasound gauges at different heights along the axis of Vessel 1. Lower graph: temperature evolution of the air inflow and at the plume center and surrounding.
distribution in Fig. 9. The maximum/minimum temperature is found at the plume position. The positions surrounding the plume exhibit the maximum of the temperature standard deviation. The main findings of this air ingress experiment can be summarized as follows: - Air ingresses into the lower part of Vessel 1 and helium ingresses into the upper part of Vessel 2. Intense turbulent mixing takes place. - A counter-current flow is set up in the IP with cold helium on top and hot air on the bottom. - The volumes not affected by the ingressing plumes remain unmixed in their initial state. - The downward air plume and the upward helium plume are detached from the wall. They are characterized by a local maximum/minimum in the cross-sectional temperature distribution and a local maximum in the short-term standard
deviation (i.e., temperature fluctuations are present). The temperature fluctuations measured at the plume-TMS intersections indicate an oscillatory movement of the plumes. In general, the air plume penetrates deeper into Vessel 1 than the helium plume penetrates into Vessel 2. This is an effect associated with the lower density and therefore lower inertia of helium. - The cold wall of Vessel 1 cools the gas mixture heated by the hot ingressing air. The hot walls of Vessel 2 heat the gas mixture that is cooled down slightly by the incoming cold helium. The interpretation of the experimental data allows the process to be qualitatively described as shown in Fig. 10. 6. Conclusion and outlook A small containment test facility equipped with novel instrumentation, namely MiniPanda with the temperature mesh sensors,
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References
Fig. 9. Cross-sectional distribution of the standard deviation distribution. The upper graphs depict the standard deviation in Vessel 1 and the lower graphs depict the standard deviation from Vessel 2.
Fig. 10. Sketch of the air ingress scenario transient (blue=helium, red=air). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
has been introduced. The temperature mesh sensor consists of a matrix of transmitting and receiving wires with a thermistor at each intersection. These temperature-sensing elements are sampled receiver-wise in parallel and transmitter-wise in serial, allowing for a high sampling frequency and low cabling and hardware effort compared to conventional intrusive techniques. Three temperature mesh sensors were installed at functional planes in order to investigate a density-driven air ingress scenario into a light gas environment. Temperature is used to label a gas for the temperature mesh sensors. The results prove the high quality of the data, allowing for a deep understanding of the processes. They are suitable for a detailed CFD code validation applied to mixing phenomena occurring in reactor containments, as well as during air ingress accidents in future helium-cooled reactors. In a further step, the number of temperature mesh sensors was increased to a total of 780 thermistors in 5 planes, including a vertical sensor in the symmetry plane of the right vessel. This new instrumentation setup is used to repeat tests that have been conducted at the large-scale containment test facility PANDA (Paul Scherrer Institute, Switzerland). The comparison between the large- and small-scale tests will be used for the investigation of scaling effects.
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Flow Measurement and Instrumentation journal homepage: www.elsevier.com/locate/flowmeasinst
Thermo-resistive mesh sensors (TMS) for temperature field measurements Martin Ritterath ∗ , Onur Can Öztürk, Horst Michael Prasser ETHZ, IET – Laboratory of Nuclear Energy Systems Sonneggstr. 3, CH – 8092 Zürich, Switzerland
article
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Article history: Received 9 February 2011 Received in revised form 4 April 2011 Accepted 15 April 2011 Keywords: Temperature field Thermo-resistive mesh Containment safety Nuclear reactor safety Air ingress Mixing experiment
abstract Temperature is one of the – if not the – most frequently measured physical quantity. Most conventional temperature sensors provide only a point measurement of the temperature. In many fields of research and industry, knowledge of the temperature distribution is a great advantage. In the present contribution, a sensor for temperature field measurements is presented. The sensor is based on thermo-resistive elements (thermistors) arranged in a two- or three-dimensional matrix, where efforts for the signal acquisition do not grow proportionally to the number of channels, but only proportionally to its square root. The temperature measurement matrix has been successfully applied to a medium scale multi compartment test facility where buoyancy driven gas flows are studied in the context of nuclear reactor safety. Examples of test results are presented to demonstrate the potential of the sensor. © 2011 Elsevier Ltd. All rights reserved.
1. Introduction As temperature is one of the most frequently measured process quantities, a large variety of temperature sensors is available [1]. In industry, temperature is mostly measured with the help of single thermocouples or thermo resistive elements, such as Pt-100 thermometers. These gauges provide a temperature measurement only in the location of their installation. In order to measure a temperature distribution, a large number of gauges has to be installed in a distributed way. Commonly, temperature distributions can be measured optically using infrared imaging [2,3]. If optical access is available (i.e., if the walls are not too thick) images with high spatial resolution can be taken, depicting the incoming far-infrared radiation. The fact that the recorded images represent a superposition of the incoming radiation is disadvantageous. It is neither possible to ‘‘look behind’’ a hot body nor to extract data from a specific slice of depth-of-field. Using tomography, it is possible to reconstruct the cross-sectional distribution of a desired quantity based on the measurement of integral absorption, refraction, reflection or other. Tomographic temperature measurement on the basis of measuring the sound velocity in solids has been reported in [4]. This measurement technique seems to be inappropriate for the measurement of gases because sound irradiation into gases, and sound bending in the presence of sound velocity gradients, pose major challenges.
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Another technique, called holographic tomography, is based on the change of refractive index with temperature [5,6]. Here, the wave front shift of multiple beams from different directions around the control volume have been fed as interferometric line patterns into a computer algorithm to obtain the visualization of one threedimensional temperature field. A thermistor multiplex measurement technique was introduced [7]. They connected a set of thermistors, each in series with a diode to a TTL line decoder. Together with a voltage dividing resistor, a single thermistor temperature could be read out by pulling the according decoder line to low voltage. The voltage at the voltage divider corresponds to the temperature at the activated thermistor’s position. After all, 200 thermistors could be scanned in two seconds with a single ADC. In reactor safety research, large scale test facilities are employed to experimentally generate a database of the transient thermalhydraulic behavior of a nuclear power plant during normal operation or accident scenarios. In these experiments, aimed at CFD code validation, the desired density of the instrumentation is usually very high, which leads to high costs for a measuring system with a large number of channels. In the present work, the problem of organizing large measuring fields is solved by a comparatively low-cost adaptation of the wire-mesh sensor technology [8], where efforts for the signal acquisition do not grow proportionally to the number of channels, but only proportional to its square root. This is achieved by arranging the sensitive elements in a two-dimensional matrix that is scanned line by line. These thermo-resistive mesh sensors (TMS) were developed for generic turbulent mixing experiments of two gases with a large difference in density in presence of strong buoyancy effects. One of the gases is labeled with a higher temperature to visualize
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the mixing processes. The test facility where they are installed is called MiniPanda. The facility consists of two cylindrical volumes connected with a horizontal pipe. Both vessels, as well as the interconnecting pipe, are equipped with mesh sensors to obtain time-dependent cross-sectional temperature distributions during experiments where an exchange between cold helium from one vessel and heated air from the second vessel takes place. This experiment provides an ideal test case for CFD codes with regard to the modeling of real containment flows. 2. Thermo-resistive mesh sensors Wire-mesh sensors, as introduced [8], are based on the detection of the local electrical conductivity of a fluid using grids of crossing electrode wires. The information about the local conductivity is obtained by supplying the electrode wires of the first grid (transmitter wires) with voltage pulses in a successive order. The current arriving at the electrodes wires of the second grid (receiver wires), which are crossing the wires of the first grid in a small distance, are sampled (Fig. 1). Low impedance driving and sampling cascades of the signal acquisition unit allow focusing the measurement on each individual crossing point of a transmitter and a receiver wire. A full sampling cycle provides a two-dimensional matrix of the measuring results from all crossing points. Wire-mesh sensors are used to measure phase distributions in a gas–liquid flow with a high time resolution, which allows the detailed characterization of the dynamic gas–liquid interface [9]. A second field of application is mixing studies, where one of the fluids involved is labeled with a salt tracer affecting conductivity [10]. A third application is high-speed liquid film thickness measurement [11]. If the electrodes are arranged flush against the wall, the conductivity between the electrodes is defined by the thickness of the liquid film covering them. The wire-mesh electronics unit performs a measurement of the conductance matrix of the two-dimensional network of resistive elements, usually formed by the conducting fluid being in contact with the transmitter and the receiver wire at each crossing point of the sensor matrix. A gas temperature distribution measurement can be realized by connecting transmitter and receiver wires via thermoresistive elements arranged at the crossing points, which replace the conducting fluid of the classical application case. This simple solution allows using standard signal acquisition units for wire-mesh sensors, provided that thermoresistive elements of a convenient conductance range are available . Suitable thermo-resistive elements are negative or positive temperature coefficient semiconductors called thermistors, or any kind of metallic resistors [12]. Thermistors have a high resistance temperature coefficient, usually on the order of several percent per Kelvin, while the resistance temperature coefficient for e.g. platinum resistors is only around 3.9e−3 per Kelvin. The application of Pt1000 resistors with a wire-mesh electronics unit was described [13]. The low resistance change with varying temperature and consequently the low temperature resolution after sampling and discretization are disadvantageous in this case. Instead, the large resistance changes of a negative temperature coefficient thermistor provide good resolution with the present wire-mesh signal acquisition device WMS-200 [14]. Consequently, it is more convenient to use to semiconductor thermistors. For an application in MiniPanda, three thermo-resistive mesh sensors (TMS) were constructed. The two different designs were:
Fig. 1. Sketch of the operational principle of wire-mesh sensors [8].
• TMS-IP: A small sensor for a pipe with a diameter of 220 mm consisting of a matrix of 8×8 crossing points with a spatial pitch
wires were fixed to the back side. The axial distance of both wire planes was consequently equal to the thickness of the PCB, which is about 2 mm, a distance just suitable to accommodate the thermistors at the crossing points. The circular flow crosssection was cut out of the PCB, so that the wires were stretched over the opening. They were fixed at the border by soldering them to conducting pads on the PCB. The wires of both planes crossed at an angle of 90 deg. At the crossing points, SMD thermistors in a 0603 housing were laser soldered between a transmitter and a receiver wire (EPCOS, B57321V2473H060), see Fig. 2. • TMS-DW: Two large diameter temperature mesh sensors were constructed to be mounted in the circular cross-section of cylindrical vessels of MiniPanda. They consisted of a matrix of 16 × 16 sensing elements with a pitch of 57 mm. This time, the wires were directly attached to hooks that were fixed to the walls. Each sensor was mounted into a segment of a cylindrical PVC pipe of 968 mm inner diameter and 16 mm wall thickness. The vessels were finally composed of a number of such elements, including those with a mesh sensor. Small springs generated a nearly constant tension in the wires, which was needed to allow for thermal dilatation due to the different thermal expansion coefficients of the vessel (PVC) and the wire materials (stainless steel), as well as to reduce the impact of vibrations during the construction. The slightest stretching of the wires would otherwise have immediately lead to plastic deformation, or even destruction, and to the loss of the tension needed to keep them straight. The two wire planes were spanned with an axial distance of 40 mm. For these sensors, leaded glass encapsulated thermistors with a 0.8 mm tip size were used (EPCOS, B57540G0503H000) (Fig. 3).
of 24 mm. A double-sided printed circuit board (PCB) served as a frame for holding two grids of wires. The transmitting wires were fixed to the front side of the board, while the receiving
The sensor wires are contacted to the wire-mesh signal acquisition unit by flat ribbon cables at the outside of the vessel segments or, respectively, at the edge of the PCB of the small sensor.
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the thermistor resistance, R0 , low in order to have a high current that can be sampled with a low gain. A reference resistance of 50 k at 25 °C and 12.3 k at 60 °C was chosen as a tradeoff between low gain and sufficiently high maximum temperature. The nonlinear thermistor transfer function of the thermistor that connects resistance with temperature, as well as the lower initial precision, require an adequate calibration function. Eq. (1) approximates the transfer function of the thermistor around a reference temperature, θ0 .
R(θ ) = R0 · exp B Fig. 2. View on temperature mesh sensor, designed for the pipe.
The main differences between the two thermistor types are their housing, and consequently their mounting process, and their dynamic behavior. The glass encapsulated thermistors exhibit a response time of 0.8 s to a temperature jump induced by a hot jet. Their maximum operating temperature is 240 °C. They are ideal for wire wrapping and soldering to large meshes with a receiver–transmitter layer distance between 40 and 70 mm. The SMD thermistors exhibit a time constant of 1 s. They are designed for a maximum operation temperature of 125 °C. They are well suited for PCB-mounting or for being soldered into small gaps, such as described for the small pipe mesh sensor. Unfortunately, neither the glass case nor the SMD housing seal the thermistors hermetically. Consequently, they cannot be used in atmospheres with high humidity because water vapor destroys the sensing element. For the application presented, the thermoresistive mesh sensors were used exclusively for tests on the mixing of air and helium. The following opposing limitations restrict the choice of the resistance of the thermistors:
• A transmitter line of the WMS-200 device can drive a maximum current of 120 mA [14]. Exceeding this current leads to a loss of the low impedance of the voltage supply, which causes the excitation voltage to reduce. Consequently, the mesh sensor loses the ability to suppress cross-talk [8]. The load limit must not be exceeded. Maximum load is reached when the maximum number of (in this case 64 thermistors) acquire their minimal resistance at the upper design limit of the temperature measurement. This restriction requires a higher reference resistance R0 of the thermistors. • The received and sampled conductivity signals are amplified to meet the dynamic range of the analog-to-digital converter. The amplification can be controlled to meet the conductivity of the fluid in the case of a traditional mesh-sensor use. For higher gains the noise superimposed on the sampled signal becomes larger. Therefore, it would be advantageous to keep
1
θ
−
1
θ0
(1) [21]
where θ is temperature, R0 is the reference resistance at the reference temperature θ0 , and B is the steepness coefficient. 3. Measurement uncertainty After construction, the wire-mesh sensors were calibrated. For this purpose, both large wire-mesh sensor segments were stacked and closed with a lid. In this way, a small calibration vessel was formed. Inside a heater, a fan and the TMS-IP were placed as shown in Fig. 4. An in-situ calibration has been performed using a high precision PREMA 3040 PT100 temperature sensor as a reference instrument. Nine different temperatures were set up inside the calibration vessel and sampled for 1 s by operating the wiremesh sensor signal acquisition system at a sampling frequency of 100 Hz. The fan ensures isothermal conditions inside the calibration vessel. Afterwards, 100 samples of the AD conversion result were averaged individually for each thermistor and stored, along with the reference temperature. Parallel to the averaging, the standard deviation of the ADC results was calculated over the calibration period (i.e., from 100 samples). Due to heat loss through the vessel wall, it was difficult to set up a stationary temperature for the high temperatures, and thus no standard deviation can be given since the reference temperature is superimposed by a maximum temperature drop of 0.2 K during the sampling. For room temperature, a long time stationary reference temperature was achieved. There, the sampling period was set to 5 s. A standard deviation of 0.067 K at this constant (room) temperature was observed. The temperature resolution is not constant due to the nonlinear thermistor transfer function. It is 20 LSB (LSB = least significant bit) per Kelvin at 20 °C and 66 LSB per Kelvin at 60 °C. However, the standard deviation is larger than the discretization error. For each thermistor, a third order calibration function (Eq. (2)) was obtained by using the least-square method to fit a curve to the calibration points. The calibration function type is derived by inserting Eq. (1) into the conductance transfer function of the wire-mesh acquisition unit and solving for the temperature. The
Fig. 3. Construction principle of the temperature mesh sensor for the vessel cross sections [15].
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Fig. 5. Typical calibration function of the thermistors. The standard deviation is plotted as red error bars. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Fig. 4. Calibration setup for the temperature mesh sensors [16]. Table 1 Components of measurement uncertainty. Uncertainty of reference instrument (K) Standard deviation of measurement (K) Quality of calibration function fit, 3rd order (K) 5th order Estimated long term stability of thermistors (6 months of operation) (K)
0.01 0.067 0.3 0.1 1.5
higher-order terms compensate for the approximate character of Eq. (1), being valid only for a limited temperature range around the reference temperature, and thus allowing for application of the calibration function over a wide temperature range [16].
θ(ADC ) = a · log(ADC ) + b · log(ADC )2 +c · log(ADC )3 +d
(2)
where ADC is the conversion result from the wire-mesh electronics unit, and a, b, c and d are the polynomial coefficients (Fig. 5). It has been observed that the transfer function of the amplifier and analog-to-digital-converter-track varies slightly from day to day. If these variances of the electronics were not compensated for, an additional uncertainty of 0.24 K would be introduced to the measurement [16]. In order to compensate for these electronic variances, a self-calibration of the electronics is carried out before and after each experiment. To calibrate the electronics, a set of high precision resistors is switched between the transmitting and receiving electrodes that match the nominal thermistor resistances at 28, 45 and 88 °C. The analog-to-digital conversion results obtained from the measurement are then corrected for the electronics unit’s variance before the calibration function (Eq. (2)) is applied . The components of the measurement uncertainty are summarized in Table 1. During the experiments, the complete temperature sensor matrix was sampled at a rate of 100 Hz. 4. MiniPanda MiniPanda is a small scale test facility dedicated to the experimental investigation of phenomena that are relevant to the safety of nuclear reactor containments. MiniPanda got its name from the fact that it is a 1:4 scaled-down model of the large-scale, multi compartment nuclear reactor containment test facility PANDA at the Paul Scherrer Institute, Villigen, Switzerland. For the small test
facility, two out of four containment volumes were built at the Swiss Federal Institute of Technology (ETH) in Zurich. The two vessels (each 2 m high, 1 m diameter) are interconnected by a horizontal pipe. The vessels are referred to as ‘‘Vessel 1’’ and ‘‘Vessel 2’’. The facility enables the application of advanced instrumentation such as the in-house developed thermo-resistive mesh sensors, 520 temperature sensors in three planes. MiniPanda can be operated at ambient pressure and temperatures up to 100 °C. The advantage of having two geometrically similar facilities is that scaling studies can be performed by conducting the same experiment in both setups under similar boundary conditions. The tests presented here have so far been performed only in MiniPanda. It is planned to repeat them in the larger PANDA facility. The vessels and the interconnecting pipe (IP) are made from PVC(-U). The vessel shells have a wall thickness of 16 mm, the vessel lid and bottom are 10 mm thick, and the IP’s wall thickness is 2.5 mm. The vessel wall thickness requires no further heat insulation, but the IP is wrapped in rubber foam blankets. For accessibility and manageability, each vessel consists of six segments. The connecting gaps are sealed with duct tape. The IP consists of three flanged segments. Detailed geometric information is archived [16]. The initial conditions for the experiments described below required a separation of the two vessels during the preconditioning phase. For this separation, the interconnecting pipe was blocked by a metal sheet. On one side of the IP, a frame was installed, which served as a sliding guide for the metal sheet and held two electromagnets that pulled the metal sheet against the front side of the IP when activated. In order to start the experiment (i.e., in order to connect the two vessels) the electro-magnets were switched off. Consequently, the metal sheet slid down, unsealing the front side of the IP. For the generic air ingress experiment described below, the facility was equipped with the already-described three planes of temperature mesh sensors: TMS-DW1 (horizontal) in the lower part of Vessel 1, where the hot air falls to the bottom, TMS-DW2 (horizontal) in Vessel 2, above the pipe entrance, where the cold helium rises, and TMS-IP (vertical) in the pipe connecting both vessels (see Fig. 6). The facility is further equipped with commercial thermocouples to measure the axial temperature distribution and katharometers to measure the helium molar fraction, both located on the vessel axes (see Fig. 6). The helium molar fraction is also computed from an ultrasound time-of-flight measurement [17] along the diameter
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Fig. 6. Overview over the geometry of MiniPanda and its instrumentation: US=ultrasound transmitter, TC=thermocouple, KM=katharometer, TWMS=temperature mesh sensor.
on four levels of each vessel. Four velocity probes, based on a time-of-flight measurement of a hot air cloud created by a pulsed heater inside a measuring tube (pulsed-wire anemometers) [18] are placed above each other in the interconnecting pipe. Innerand outer- wall thermocouples mounted on both vessels allow monitoring well-controlled boundary conditions. 5. Results of generic air ingress tests Generic air ingress experiments were performed with the aim of providing data suitable for CFD code validation. A gravity-driven ingress of heavier air into the helium-filled vessel is a phenomenon found in so-called air ingress accidents at High Temperature Gas-cooled Reactors (HTGR) and Very High Temperature Reactors (VHTR) under development within the framework of the Generation IV research initiative [19,20]. In order to assess consequences of such an accident, the determination of the time-dependent air inflow into the core is essential. Important modeling issues include the molecular diffusion as well as the density gradient transient of the induced flow which is limited by countercurrent flow. These processes pose challenges to the simulation of fluid-dynamics using CFD, which creates a need for adequate experimental data suitable for model development and validation. In the preparation phase of the presented experiment, the interconnecting pipe was blocked at the side of Vessel 1. Vessel 2 was heated for approximately three hours until the air inside Vessel 2 and the IP, as well as the walls of Vessel 2 and the IP, reached the desired initial temperature of 60 °C. A homogeneous temperature distribution is achieved by stirring with the builtin fan. Vessel 1 is filled with pure helium and remains unheated at room temperature, 25 °C. Well-controlled initial and boundary conditions are guaranteed by the homogeneous filling and conditioning of both vessels during the preconditioning phase. The temperature difference between the two gases serves as labeling to visualize the mixing process and has no meaning with regard to the investigated scenario. A sudden initiation of the transient process is achieved by switching off the magnets that hold the blocking metal sheet in place. The metal sheet rapidly slides down due to gravity, thus unblocking the flow in the IP. The high density difference between the gases in the two vessels induced a gravity-driven exchange flow. A hot downward air plume penetrated the previously helium-filled Vessel 1 (see Fig. 7, upper graphs), the hot downward air plume is visualized by the warm area in yellow. The gas in the part of the vessel that
is affected by the aforementioned plume was subject to intensive mixing with increasing air fraction (Fig. 8, upper graphs). The air ingress was expressed by the temperature increase in the region around the plume as well as in the increase of the molar air fractions measured at the lower levels. In contrast to this, the upper part of Vessel 1 stayed practically filled with unmixed helium (see Fig. 8, upper graph, air fraction for the higher two sensors). Due to the air ingress in Vessel 1, helium is pushed through the IP towards Vessel 2. A counter-current flow was established with warm air at the bottom and cold helium at the top of the IP crosssection (see Fig. 7, middle graphs). Helium, after arriving in the previously air-filled Vessel 2, forms a rising plume (see Fig. 7, lower graphs, cold plume is characterized by the yellow area). In the part above the IP of Vessel 2, the helium fraction increased. Due to the vertical density gradient, helium cannot reach the part of Vessel 2 below the IP. The lower graph of Fig. 8 displays the evolution of the air inflow temperature, measured with the TMS-IP (position 4, 7). Furthermore, the lower graph of Fig. 8 depicts the evolution of the temperature at the intersection of the air plume and the measuring plane at the position of the plume center and the over the next neighbors. The temperature fluctuations in and around the air plume indicate an oscillatory movement of the plume. In order to validate the signals from the thermo-resistive mesh sensor against the molar gas fraction measured by the ultrasonic technique, the temperatures were converted into molar fractions. This transformation is possible for binary mixtures of gases. According to Richmann’s law, the temperature of two mixed fluids is given by the mass, temperature, and heat capacity of the fluid components. In case of the air ingress described, the mixing components are cold helium, initially present in Vessel 1, and hot ingressing air. The initial temperature of helium is set to 25 °C. The inflow temperature measured with the TMS-IP is applied (see Fig. 8, lower graph) as initial temperature for the ingressing air. The calculated air fraction is plotted in Fig. 8, upper graph as ‘‘calculated from Temp’’. Note that the molar air fraction calculated from the temperature is underestimated because there are heat losses from the air flow to the initially cold walls of Vessel 1. The phase of intense mass exchange finishes when the helium layer in the previously helium-filled Vessel 1 is eroded to the top of the cross-section area of the interconnecting pipe. The transient ends up in a scenario which is controlled by molecular diffusion alone. The mean temperature and the short-term standard deviation of the temperature signals obtained, both from 40 s < t < 75 s, with the TMS in Vessel 1 and 2 are plotted as a cross sectional
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Fig. 7. Cross sectional temperature distribution of TMS DW1 (Vessel 1, upper row), TMS IP (central row) and TMS DW2 (Vessel 2, lower row), blue=cold, red=hot. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 8. Upper graph: molar air fraction measured by the ultrasound gauges at different heights along the axis of Vessel 1. Lower graph: temperature evolution of the air inflow and at the plume center and surrounding.
distribution in Fig. 9. The maximum/minimum temperature is found at the plume position. The positions surrounding the plume exhibit the maximum of the temperature standard deviation. The main findings of this air ingress experiment can be summarized as follows: - Air ingresses into the lower part of Vessel 1 and helium ingresses into the upper part of Vessel 2. Intense turbulent mixing takes place. - A counter-current flow is set up in the IP with cold helium on top and hot air on the bottom. - The volumes not affected by the ingressing plumes remain unmixed in their initial state. - The downward air plume and the upward helium plume are detached from the wall. They are characterized by a local maximum/minimum in the cross-sectional temperature distribution and a local maximum in the short-term standard
deviation (i.e., temperature fluctuations are present). The temperature fluctuations measured at the plume-TMS intersections indicate an oscillatory movement of the plumes. In general, the air plume penetrates deeper into Vessel 1 than the helium plume penetrates into Vessel 2. This is an effect associated with the lower density and therefore lower inertia of helium. - The cold wall of Vessel 1 cools the gas mixture heated by the hot ingressing air. The hot walls of Vessel 2 heat the gas mixture that is cooled down slightly by the incoming cold helium. The interpretation of the experimental data allows the process to be qualitatively described as shown in Fig. 10. 6. Conclusion and outlook A small containment test facility equipped with novel instrumentation, namely MiniPanda with the temperature mesh sensors,
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References
Fig. 9. Cross-sectional distribution of the standard deviation distribution. The upper graphs depict the standard deviation in Vessel 1 and the lower graphs depict the standard deviation from Vessel 2.
Fig. 10. Sketch of the air ingress scenario transient (blue=helium, red=air). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
has been introduced. The temperature mesh sensor consists of a matrix of transmitting and receiving wires with a thermistor at each intersection. These temperature-sensing elements are sampled receiver-wise in parallel and transmitter-wise in serial, allowing for a high sampling frequency and low cabling and hardware effort compared to conventional intrusive techniques. Three temperature mesh sensors were installed at functional planes in order to investigate a density-driven air ingress scenario into a light gas environment. Temperature is used to label a gas for the temperature mesh sensors. The results prove the high quality of the data, allowing for a deep understanding of the processes. They are suitable for a detailed CFD code validation applied to mixing phenomena occurring in reactor containments, as well as during air ingress accidents in future helium-cooled reactors. In a further step, the number of temperature mesh sensors was increased to a total of 780 thermistors in 5 planes, including a vertical sensor in the symmetry plane of the right vessel. This new instrumentation setup is used to repeat tests that have been conducted at the large-scale containment test facility PANDA (Paul Scherrer Institute, Switzerland). The comparison between the large- and small-scale tests will be used for the investigation of scaling effects.
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