Small Scale gamma-ray densitometer for in-situ measurements of two-phase void fraction in subsurface soils

1996 ◽  
Vol 63 (JG) ◽  
Author(s):  
Reinhard Scharf
2021 ◽  
Author(s):  
Karolin S. Ferner ◽  
K. Heinke Schlünzen ◽  
Marita Boettcher

<p>Urbanisation locally modifies the regional climate: an urban climate develops. For example, the average wind speed in cities is reduced, while the gustiness is increased. Buildings induce vertical winds, which influence the falling of rain. All these processes lead to heterogeneous patterns of rain at ground and on building surfaces. The small-scale spatial rain heterogeneities may cause discomfort for people. Moreover, non-uniform wetting of buildings affects their hydrothermal performance and durability of their facades.</p><p>Measuring rain heterogeneities between buildings is, however, nearly impossible. Building induced wind gusts negatively influence the representativeness of in-situ measurements, especially in densely urbanised areas. Weather radars are usually too coarse and, more importantly, require an unobstructed view over the domain and thus do not measure ground precipitation in urban areas. Consequently, researchers turn to numerical modelling in order to investigate small-scale precipitation heterogeneities between buildings.</p><p>In building science, numerical models are used to investigate rain heterogeneities typically focussing on single buildings and vertical facades. Only few studies were performed for more than a single building or with inclusion of atmospheric processes such as radiation or condensation. In meteorology, increasing computational power now allows the use of small-scale obstacle-resolving models resolving atmospheric processes while covering neighbourhoods.</p><p>In order to assess rain heterogeneities between buildings we extended the micro-scale and obstacle-resolving transport- and stream model MITRAS (Salim et al. 2019). The same cloud microphysics parameterisation as in its mesoscale sister model METRAS (Schlünzen et al., 2018) was applied and boundary conditions for cloud and rain water content at obstacle surfaces were introduced. MITRAS results are checked for plausibility using radar and in-situ measurements (Ferner et al., 2021). To our knowledge MITRAS is the first numerical urban climate model that includes rain and simulates corresponding processes.</p><p>Model simulations were initialised for various wind speeds and mesoscale rain rates to assess their influence on the heterogeneity of falling rain in a domain of 1.9 x 1.7 km² around Hamburg City Hall. We investigated how wind speed or mesoscale rain rate influence the precipitation patterns at ground and at roof level. Based on these results we assessed the height dependence of precipitation. First analyses show that higher buildings receive more rain on their roofs than lower buildings; the results will be presented in detail in our talk.</p><p>Ferner, K.S., Boettcher, M., Schlünzen, K.H. (2021): Modelling the heterogeneity of rain in an urban neighbourhood. Publication in preparation</p><p>Salim, M.H., Schlünzen, K.H., Grawe, D., Boettcher, M., Gierisch, A.M.U., Fock B.H. (2018): The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory. Geosci. Model Dev., 11, 3427–3445, https://doi.org/10.5194/gmd-11-3427-2018.</p><p>Schlünzen, K.H., Boettcher, M., Fock, B.H., Gierisch, A.M.U., Grawe, D., and Salim, M. (2018): Scientific Documentation of the Multiscale Model System M-SYS. Meteorological Institute, Universität Hamburg. MEMI Technical Report 4</p>


2013 ◽  
Vol 30 (11) ◽  
pp. 2689-2694 ◽  
Author(s):  
Nadya T. Vinogradova ◽  
Rui M. Ponte

Abstract Calibration and validation efforts of the Aquarius and Soil Moisture and Ocean Salinity (SMOS) satellite missions involve comparisons of satellite and in situ measurements of sea surface salinity (SSS). Such estimates of SSS can differ by the presence of small-scale variability, which can affect the in situ point measurement, but be averaged out in the satellite retrievals because of their large footprint. This study quantifies how much of a difference is expected between in situ and satellite SSS measurements on the basis of their different sampling of spatial variability. Maps of sampling error resulting from small-scale noise, defined here as the root-mean-square difference between “local” and footprint-averaged SSS estimates, are derived using a solution from a global high-resolution ocean data assimilation system. The errors are mostly <0.1 psu (global median is 0.05 psu), but they can be >0.2 psu in several regions, particularly near strong currents and outflows of major rivers. To examine small-scale noise in the context of other errors, its values are compared with the overall expected differences between monthly Aquarius SSS and Argo-based estimates. Results indicate that in several ocean regions, small-scale variability can be an important source of sampling error for the in situ measurements.


2020 ◽  
Author(s):  
Marc Buckley ◽  
Jochen Horstmann

<p>Small-scale turbulent dynamics within the coupled atmospheric and oceanic wave boundary layers control air-sea fluxes of momentum and scalars. However measuring and understanding small-scale dynamics very close to the rapidly moving ocean surface remains technically challenging.</p><p>We present novel in situ measurements of small-scale motions in the airflow above, and in the water below the wavy air-water interface. A high resolution, large field of view PIV system (Particle Image Velocimetry) was developed for in situ air-water measurements within the first millimeters to meters above and below the wavy surface. The system was recently deployed on a single pile platform in the Szczecin lagoon (Baltic Sea coast, Germany). We will show first results and we will discuss the influence of waves on the partitioning of momentum flux within the coupled air-water wave boundary layers.</p>


Author(s):  
M. H. Kebriaee ◽  
H. Karabi ◽  
S. Khorsandi ◽  
M. H. Saidi

Studies on two-phase flow in small scale pipes have become more important, because of the application of mini-scale devices in several engineering fields including, high heat-flux compact heat exchangers, and cooling systems of various types of equipment. In a mini pipe the behavior of two phase flow is not the same as flow in conventional pipes. The difference is caused by different effective forces; for e. g. inside a mini pipe capillary forces are more important in comparison with gravitational forces. This paper is devoted to numerical simulation of gas-liquid two phase flow in a vertical mini pipe. Prediction of bubble shape and the effects of gas and liquid velocities on flow characteristics are considered. Also simulation involves prediction of changes in average void fraction along pipe axis. Numerical simulations in this paper are performed by a designed and developed CFD package which is based on Eulerian-Eulerian approach. The governing equations which are solved in the CFD package are momentum, continuity and Fractional Volume of Fluid (VOF) function equations. The fluid is assumed to be viscous and incompressible. The pressure-velocity coupling is obtained using the SIMPLEC algorithm. The geometry, which have been studied in this paper, is a D = 1.02 mm pipe, with 500 mm height. Bubble shape and the distribution of void fraction in a mini pipe are related to many parameters such as: gas and liquid velocities, pressure losses and etc. Since these mechanisms vary over time, time-average value of void fraction is used. Comparisons between Numerical results and experimental work which performed by hibiki et al. [1] indicated good agreement. Also results have shown that the present model is capable to simulate the behavior of nitrogen-water two phase flow in a mini pipe with acceptable accuracy. Furthermore, the results indicates that average void fraction along the pipe axis is related to the height and nitrogen superficial velocity. Also it is observed that at constant nitrogen superficial velocities, average void fraction decreases with water superficial velocity increments.


2016 ◽  
Vol 48 (1) ◽  
pp. 64-71 ◽  
Author(s):  
E. Nazemi ◽  
S.A.H. Feghhi ◽  
G.H. Roshani ◽  
R. Gholipour Peyvandi ◽  
S. Setayeshi

2021 ◽  
Author(s):  
Clovis Thouvenin-Masson ◽  
Jacqueline Boutin ◽  
Jean-Luc Vergely ◽  
Dimitry Khvorostyanov ◽  
Xavier Perrot ◽  
...  

<p>Sea Surface Salinity (SSS) are retrieved from SMOS and SMAP L-band radiometers at a spatial resolution of about 50km.</p><p> </p><p>Traditionally, satellite SSS products validation is based on comparisons with in-situ near surface salinity measurements.</p><p> </p><p>In-situ measurements are performed on moorings, argo floats and along ship tracks[JB1] , which provide punctual or one-dimensional (along ship tracks) estimations of the SSS.</p><p> </p><p>The sampling difference between one-dimensional or punctual in-situ measurements and two-dimensional satellite products results in a sampling error that must be separated from measurement errors for the validation of satellite products.</p><p> </p><p>We use a small-scale resolution field (1/12° Mercator Global Ocean Physics Analysis and Forecast) to estimate the expected sampling error of each kind of in-situ measurements, by comparing punctual, [JB2] one-dimensional and two-dimensional SSS variability.</p><p> </p><p>The better understanding of sampling errors allows a more accurate validation of satellite SSS and of the errors estimated by satellite retrieval algorithms. The improvement is quantified by considering the standard deviation of satellite minus in-situ salinities differences normalized by the sampling and retrieval errors. This quantity should be equal to one if all the error contributions are correctly considered. This methodology will be applied to SMOS SSS and to merged SMOS and SMAP SSS products.</p>


2018 ◽  
Vol 180 ◽  
pp. 02124
Author(s):  
Marcin Zych ◽  
Robert Hanus ◽  
Marek Jaszczur ◽  
Volodymyr Mosorov ◽  
Dariusz Świsulski

To determine the parameters of two-phase flows using radioisotopes, usually two detectors are used. Knowing the distance between them, the velocity of the dispersed phase is calculated based on time delay estimation. Such a measurement system requires the use of two gamma-ray sealed sources. But in some situations it is also possible to determine velocity of dispersed phase using only one scintillation probe and one gamma-ray source. However, this requires proper signal analysis and prior calibration. This may also cause larger measurement errors. On the other hand, it allows measurements in hard to reach areas where there is often no place for the second detector. Additionally, by performing a previous calibration, it is possible to determine the void fraction or concentration of the selected phase. In this work an autocorrelation function was used to analyze the signal from the scintillation detector, which allowed for the determination of air velocities in slug and plug flows with an accuracy of 8.5%. Based on the analysis of the same signal, a void fraction with error of 15% was determined.


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