Table of Contents
Anabatic Flow
Infrastructure | T-SAIL | ||
Project title (long) | Experimental study of thermally driven anabatic flows | ||
Participants | Roni Hilel Goldshmid, Dan Liberzon | ||
Date Campaign Start | 01.10.2016 | ||
Date Campaign End | 28.02.2020 |
0 Publications from this project
1 Background
1.1 Motivation
The motivation is
1.2 Up-to-date literature
The current state of knowledge is
1.3 Knowledge Gaps
Gaps in the field is
1.4 Expected Contributions
The significance of the proposed research lies in its expected contribution toward increasing the performance and accuracy of weather prediction models. Experimental investigation of the developing turbulent anabatic BL under various forcing and conditions in lab setup, accompanied by field experiments based on similar parameters, will result in obtaining extensive sets of comprehensive data on all important parameters of the flow. These data sets will be used to derive an empirical model for anabatic thermally driven flows, separation lengths, and apex plume formation. The products of the proposed research will therefore contribute to the ability of producing more accurate weather forecast models, investigation of climate processes, and understanding of the processes governing pollution transport in complex terrains.
2 Hypothesis and Objectives
The hypothesis of the proposed work is that thermally driven anabatic flow can be truthfully modeled in the lab using heated slopes inside water tank setups[11, 16–18]. The lab setup will allow investigation of various aspects of such flows, namely the turbulent nature of the BL, the BL thickness, separation lengths, flow entrainment, and formation of apex plumes. Eventually gaining a better understanding of the role played by thermally driven anabatic flows in setting meteo-conditions and pollutant transport. There are three main and three secondary objectives that will be striven for. They are motivated mainly by the desire to gain a better understanding of the physical processes governing mountainous terrain weather formation, providing parameterizations of important parameters, developing appropriate empirical and theoretical models, and hence contributing to the development of more accurate prediction models.
2.1 Major
- Development of qualitative and quantitative descriptions the upslope flow adjustment due to decreasing roughness of the slope corresponding to natural reduction in vegetation cover with height and due to geometrical break of the slope as is often present in natural mountainous terrains.
- Development of an empirical model for upslope flow separation location and separation critical velocity along the slope. Functional dependencies of the separation location and upslope separation velocity on the slope angle and roughness, developing inflow velocity, and slope heating rates (e.g. seasonal changes) will be developed.
- Development and testing in the wind tunnel of an improved combo probe design to be used to verify findings from lab experiments in field studies.
2.2 Secondary
- Quantitative characterization of apex plume developing due to upslope flow separation.
- Quantification of fluxes of heat and scalars in the plume, which are paramount in precipitation models.
- Producing new field data with the improved combo to support lab work.
3 Experimental Setup
3.1 General description
The Coriolis ta
3.2 Definition of the coordinate system
The coordinate system is aligned with the slope
4 Instrumentation and data acquisition
4.1 Instruments used
We use two PIV
Thermocouples: we have 32 channels.
Acquires with two NI ChassisModel: 'cDAQ-9171'
Each has its own 'NI 9214' 16 channels
Each of the channels has a WATLOW K type 30 Gauge thermocouple.
4.2 Definition of time origin and instrument synchronization
It is important
4.3 Requested final output and statistics
Separation Locations
5 Methods of calibration and data processing
Calibration done with laser sheet on slope
6 Data Files Organization
All data
7 Table of experiments
List of parameter, Param1… , denoted by names defined in section 4.2.
8 Diary:
2018 April:
Experiments
2018 May:
create profiles
2018 October 02:
Automatic detection of 1 second means of max location of velocity profiles
9 Data management
PIV of initial runs: parameters ParaPIV version 1.2
10 Data format
10.1 Images
.png images are recorded at 5 fps File Names as follows:
10.2 Text Files
text files with TC Add image of their location wrt the slope File Names as follows:
10.3Mat files
- .mat files include calibrated PIV vector maps
- .mat files include profiles in slope coordinate system
11 Next Steps
- step 1
- step 2
- etc