scale model study for a ventilation system …4th international conference on building energy,...

4th International Conference On Building Energy, Environment

Scale Model Study for a Ventilation System Optimization inside a Sludge Dewatering Area

C Croitoru1, M. Sandu1, I. Nastase1, F. Bode1,2 and L Tacutu1

1CAMBI, Technical University of Civil Engineering of Bucharest, Building Services Department, 66 Pache Protopopescu Avenue, 020396, Bucharest, Romania

2 Department of Mechanical Engineering, Technical University of Cluj Napoca, Romania

SUMMARY The paper focus on the air quality inside the final sludge dewatering area where the working environment is very unsuitable for human exploitation mainly due to ammonia. The existing ventilation system is not facing this situation and a new ventilation system is required. The solution obtained by means of numerical simulation need to be validated by experimental approach. We have built a reduced scaled physical model in order to simulate the flow pattern inside the sludge dewatering area and the main equipment inside the building has been reproduced using a geometrical scale ratio. The flow pattern was considered isothermal and incompressible. The similarity criteria used was the Reynolds number to characterize the flow pattern inside the enclosure. From here there were many imposed constraints related to the velocity scale in order to avoid high velocities which could lead to a compressible flow pattern which is no more characterized by Re. The opportunity to use a different fluid for the reduced scaled model because of the different viscosities values which could help to obtain more convenient values for the geometrical and velocity scales from the Re similarity criteria but finally the same fluid – air on the model and nature was used.

INTRODUCTION The wastewater issued from the municipal drainage systems has to be treated in wastewater plants in order to be released back into nature without polluting the environment. Basically a common wastewater plant has two main lines, the water line and the sludge/biogas line. The water line includes mainly the processes like mechanical treatment with coarse and fine filters, grit removal channels, primary settlers and biological treatment, while the sludge/biogas line includes sludge thickening, digestion and dewatering stabilization, transformation of biogas into electricity and heat.

Our goal here is to study how to improve the air quality inside the sludge dehydratation building where the ammonia emissions from waste sludge are at very high level. The advanced dehydration hall has a metallic structure and is made of sandwich panels with polyurethane foam core, with dimensions of the building of 37.60m x 18.10m x 13.50m located adjacent to sludge thickening and dewatering hall. Inside the building there is a technical room with dimensions of 2.60m x 2.30m x 10.00m, for electric supply and control of technological equipment and also used as a workstation for operating personnel. The three lines of dehydration are identical, consisting of a decanter centrifuge, a unit for the preparation of the polymer, a storage tower for lime, a fixed inclined screw to transport and mix the sludge with lime and a horizontal swivel screw to discharge treated sludge in

containers used for evacuation, two for each line of dehydration. The ventilation system installed is not working properly, for ensuring the optimal parameters that are required, and a new system must be configured for an enhancement of indoor environmental conditions.

Figure 1. Technological lines of the advanced dehydration hall and the pollutants emission zones

METHODS The authors have to perform four tasks in order to do the study and to obtain results:

- The first task was to perform measurementsregarding the quantity of the pollutants releasedinside the hall in order to be able to have theboundary conditions. Ammonia concentrationsdetermined for this case are the averageconcentrations measured over a period of 15minutes by aqueous ammonia absorption methodand then determining the ammonia concentrationusing the spectrophotometric method by the HachMethod 8038 with a range of 0.02-2.50 mg/L NH3-N.

- The second task was to find the best solution forventilating the area. Several cases have beenenvisaged and we have considered generalventilation strategies and local ventilation strategies.At the end we have decided to use a generalventilation strategy and depending on the results to

ISBN: 978-0-646-98213-7 COBEE2018-Paper199 page 575


add a local ventilation system if needed. Numerical simulations have been performed in order to find the best solution using a commercial CFD code by Croitoru C et al (2016).

- The third task was to validate the numerical resultson a reduced scale experimental model.

- The fourth task was to use the validated numericalmodel in order to find the final solution.

Figure 2. Flow chart showing the research methodology

The choice of the four steps described above is very simple, it is much more convenient to use numerical tools to find the best solution and to validate it on an experimental setup instead of building and modifying experimental devices.

NUMERICAL SIMULATIONS The Computational Fluid Dynamics is a powerful tool for indoor air quality evaluation, especially when it is difficult to evaluate it for different scenarios, like different airflow rates of ventilation strategies. Since the indoor heat release and ammonia release will impose the largest airflow rate, the simulations were performed mainly to evaluate the efficiency of the air distribution when using different strategies. The numerical simulations were carried out in Ansys Fluent Software. The turbulence model used was k-ω SST chosen for better results when predicting airflows in large areas (Yu H., Thé J. 2016), (Hussain S. et al 2012), (Bode F., Unguresan P 2014). It is more accurate for estimating the details of the boundary layer characteristics and it was developed by Menter (1994) to obtain both the accuracy of the standard k-w model in the areas near the wall and the accuracy of the k-ε model in the field areas. The k-ω SST model is like the standard model but it has also the following important modifications:

The model particularity is that it has one form at theboundary layer near the wall (k-ω model) andanother form in the free form area (k-ε model);;

The SST model incorporates a derivative diffusionterm in the ω equation;

The definition of the turbulent viscosity is modified totake account of the transport of tangential forces.

The k-ω SST model is similar to the standard model with respect to transport equations, except for the presence of the additional diffusion term in the ω equation.

𝜌 𝜕𝑘

𝜕𝑡+ 𝜌

𝜕𝑘𝑢𝑖

𝜕𝑥𝑖=

𝜕

𝜕𝑥𝑗(𝛤𝑘

𝜕𝑘

𝜕𝑥𝑗) + 𝐺𝑘 − 𝑌𝑘 + 𝑆𝑘 (1)

𝜌𝜕𝜔

𝜕𝑡+ 𝜌

𝜕𝜔𝑢𝑖

𝜕𝑥𝑖=

𝜕

𝜕𝑥𝑗(𝛤𝜔

𝜕𝜔

𝜕𝑥𝑗) + 𝐺𝜔 − 𝑌𝜔 + 𝐷𝜔 + 𝑆𝜔 (2)

With the following signification of parameters: 𝐺𝑘 - the generation of turbulent kinetic energy due to average

speed gradients; 𝐺𝜔 - generation for ω

Γk and Γω - diffusivity for k and ω;

𝑌𝑘 and 𝑌𝜔 - dissipation of k and ω due to turbulence;

𝐷𝜔 - cross-diffusion;

𝑆𝑘 and 𝑆𝜔 - terms defined by the user.

The mesh of the model has 4.3 million tetrahedral elements and 5 layers elements in the boundary layer. For pressure velocity coupling we have used the coupled scheme, second order discretization. All these simulations are detailed in previous papers by Croitoru C et al (2016) so here we will focus only on the chosen solution. The air have been introduced on the lateral walls of the hall using five grilles on each side. The grilles were set to have an angle of 30º facing down and they were positioned at 2.5 m height. The evacuation of air is done at the ceiling using 2 rows with 5 grilles each one. The parameters used for the boundary conditions corresponding to the final ventilating solution are presented in table 1 below:

Table 1. Boundary Conditions

These values have been obtained from the condition that the average ammonia concentration should be less than 14 mg/m3 during 8 hours and less than 36 mg/m3 during 15 minutes according to Directive 2000/39/EC. The results detailed by Croitoru C et al (2016) regarding the ammonia concentrations above the containers are shown in figure 3 at 1.8 m height.

Figure 3. Ammonia concentrations at 1.8 m height Here the main issue is to validate the numerical model on a reduced scale model. There are three parameters of interest for the air flow inside the hall, the velocity, the ammonia concentration and the temperature. Our goal here is to validate from the velocity point of view so we have extracted from the numerical results those which are related to the velocity profiles. Numerical results for the flow pattern are partially shown in figure 4.

Figure 4. Streamlines and velocity magnitude inside the enclosure

Heat

load

Humidity

load

Ammonia

Emissions

Inlet air

temperature

Ground

temperature

Inlet Air

Flow

Rate

Exhaust Air

Flow Rate

kW kg/h g/h grd C grd C mc/h mc/h

70 74 361 30 24 50000 60000



SIMILITUDE CRITERIA Complete similitude between two physical phenomena means that they have to be of the same nature and both geometric, dynamic, kinematic similitude and boundary conditions should be accomplished. The geometric similitude requires the proportionality of the corresponding lengths and the equality of angles. The result of the geometric similitude is the length scale. The kinematic similitude requires that if the flow is made of particles, the corresponding particles take the same place inside the flow pattern at same moments in time. As a result if the kinematic similitude is accomplished between the two phenomena there are a constant length scale and a constant velocity scale. The dynamic similitude implies also the proportionality of the corresponding forces between the phenomena in addition to the geometric and kinematic similitude. The result is obviously a constant force scale. For this study the dynamic similitude has been found as appropriate. However the complete similitude between two phenomena of the same nature is impossible to achieve so one have to consider only the main forces that govern the flow. It results a restraint dynamic similitude criteria as follow:

- The Froude similitude: the leading forces are theinertia and the gravity forces.

𝐹𝑟 =𝑢

√𝑔𝐿 (3)

Froude similitude implies the condition FrN=FrM. The relation

between the scales in case of the Froude similitude is:

𝑆𝑢2

𝑆𝑔𝑆𝑙= 1 (4)

- The Euler similitude: the leading forces are the inertiaand the pressure forces.

𝐸𝑢 =𝑝

𝜌𝑢2 (5)

Euler similitude implies the condition EuN=EuM. The relation between the scales in case of the Euler similitude is:

𝑆𝑝

𝑆𝜌𝑆𝑢2 = 1 (6)

- The Reynolds similitude: the leading forces are theinertia and the viscosity forces.

𝑅𝑒 =𝑢𝑙

𝜗 (7)

Reynolds similitude implies the condition ReN=ReM. The relation between the scales in case of the Reynolds similitude is:

𝑆𝑢𝑆𝑙

𝑆𝜗= 1 (8)

The next step was to choose the similarity criteria to use. The airflow pattern has been considered under isothermal conditions. Considering that Fr is normally used to the free surface flow and Eu is not indicated to the airflow patterns under isothermal conditions the Reynolds similitude is used here. If the same fluid (air) is used on site and on the reduced model it means that the viscosity scale is the same and the relation (8) becomes:

𝑆𝑢𝑆𝑙 = 1 (9)

Considering the imposed constraints related to the velocity scale in order to avoid high velocities which could lead to a compressible flow pattern which is no more characterized by Re the maximum length scale that could be applied on the model is 1/10. It means that the dimensions of the model could not be reduced more than 10 times the actual size. In this case the overall dimensions of the model will be 3.76 m x 1,81 m x 1.35 m. The model should be used at a later stage to measure velocity profiles using PIV techniques but these model dimensions are too large for the equipment that we own. So we thought of diminishing the model dimensions by using different viscosity scales which means different fluids, air on site and other fluid on the model. The possibility of using water on the model has been analysed. The viscosity scale in this case is Sν=1/15 and the model dimensions could be reduced

up to a 1/90 ratio. In this case the model dimensions will be 0.41 m x 0.20m x 0.15m which is suitable for the PIV system to be used but the problem here is that the flow rate on the model is calculated to be at 172.8 l/s. Technically it is very difficult to have such a water flow rate on the model because we should have in this case a very big pumping booster set and the energy consumption would be also at very high level. We have decided to use air as fluid on the model but to reduce the experimental setup with a 1/45 ratio (length scale). It is obvious that we will not be able to reproduce on the model the onsite conditions for the ventilating system at parameters specified before in the paper. A numerical simulation has been then performed keeping the same geometry but with a different inlet air flow rate at 74 m3/h. To this flow rate value it correspond a velocity value of 2 m/s for every inlet. The results are shown in figure 5 below:

Figure 5. Streamlines and velocity magnitude inside the enclosure at an inlet air flow rate of 74m3/h

EXPERIMENTAL SETUP AND RESULTS The experimental setup was finally built using the length scale 1/45. The enclosure was made of transparent plexy in order to have the possibility to measure velocity profiles using non-intrusive techniques like PIV or LDV. The air pressure is ensured by an air compressor capable of delivering 120liter/min at max. 8 bar which feeds the main distributor. There are 5 inlets on each side of the enclosure and each inlet is provided with its own air circuit from the main air distributor. The air hoses which feed the inlets are provided with flow rate regulators in order to set the pressure and with rotameters to measure the air flow rate corresponding to every inlet. There is also a general pressure regulator on the compressor discharge. The air exhaust from the enclosure is made using 10 outlets provided in the ceiling of the enclosure. All these outlets are collected into a plenum and from here the air is extracting with an air fan. The schema of the experimental setup is shown in figure 6 below:



Figure 6. Schema of experimental setup

The front of the control panel containing the rotameters displays, the pressure displays and the flow regulator devices is shown in figure 7

Figure 7. Control panel of experimental setup

The back of the control panel with all the connections to the air inlets in the enclosure is shown in figure 8

Figure 8. Back of control panel of experimental setup

The first step after the construction of the experimental setup was to make tests on it to see if it works properly. The main goal of the test was to obtain for every inlet the corresponding similar velocity that we have imposed for the numerical simulations described in figure 4. The difficulty here was to manage to have the same values for the air flow rate for all the ten inlets of the enclosure. The value of the total flowrate was

1.66 m3/h corresponding to an onsite flowrate of 74 m3/h reduced by the similitude flowrate scale which is 1/45. The measured velocity values at inlets were between 85 m/s and 91 m/s. If we adjust these values by the velocity scale which is a factor of 45 we find that they match very well with the imposed velocity value of 2 m/s for the numerical simulations.

CONCLUSIONS AND PERSPECTIVES This study shows partially how to improve the working conditions inside an atypical enclosure like the sludge dehydration area in a waste water plant. Starting from the ammonia quantity released in the air which we have used as boundary conditions we have performed numerical simulations in order to find the best ventilating solution. This numerical model have to be validated by experimental measurements so we have conceive an experimental setup using Re similitude criteria and we have proved its feasibility. Starting from here the next step will be to perform velocity profile measurements inside the experimental setup and to compare them with the numerical simulations in order to validate completely the numerical model.

ACKNOWLEDGEMENT This work was supported by a Grant of the Romanian National Authority for Scientific Research, CNCS, UEFISCDI, Project code: PN-III-P2-2.1-BG-2016-0158.

REFERENCES Bode F., Unguresan P. 2014. “Combustie si instalatii de

ardere”, U.T.Press 2014, ISBN 978-973-662-998-3, 446

Croitoru C. et al 2016. “General ventilation system optimization study for environment improvement of sludge dewatering area from a wastewater treatment plant” Energy Procedia, Volume 112, March 2017, Pages 640-649

Degeratu M. 2015 “Analiza dimensionala, similitudine si modelare, Bucharest 2015

E. Comission, Directive 2000/39/EC - indicative occupationalexposure limit values, in,2000

HACH, Nitrogen Ammonia Nessler Method 8038 - Hach, in: Standard Methods for the Examination of Water and Wastewater.

Hussain S. et al 2012 “Evaluation of various turbulence models for the prediction of the airflow and temperature distributions in atria”, Energy and Buildings, 48 (2012) 18-28.

Menter F.R. 1994 “Two-Equation Eddy-Viscosity Turbulence Models for Engineering Applications”, AIAA Journal, 32(8):1598-1605

Yu H., Thé J. 2016 “Validation and optimization of SST k-ω turbulence model for pollutant dispersion within a building array”, Atmospheric Environment, 145 (2016) 225-238.


scale model study for a ventilation system …4th international conference on building energy,...

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