PRACTICUM WORKSHEET
SATUAN OPERASI TEKNIK LINGKUNGAN
Analysis of Gravel Size Effect on Velocity Gradient in Hydraulic Mixing
Arranged by :
NAME : SHINTA NUR IHSANI STUDENT’S ID : 225100907111039 GROUP : ME 5
ASSISTANT :
Muhammad Zidan Ghifari Kana Nawafila Eiski Ishma Yusrina Nur Hanifah Michael Teudas Tertius Tsania Naila Firdausi Shafa Ariza Agmi Putri Raullyno Ghozali Ilham Mellysa Machfiro Zhafran Kamal Sultani Tjokorda Istri Mahagita Aura Dinar Ramadhani Ariya Ratana Teja Windy Trisnawati Dewi Sabina Fitri Enggal Alhamdra Andika S
WATER QUALITY AND WASTE MANAGEMENT LABORATORY DEPARTMENT OF BIOSYSTEM ENGINEERING
FACULTY OF AGRICULTURAL TECHNOLOGY BRAWIJAYA UNIVERSITY
MALANG
2024
CHAPTER I INTRODUCTION
1.1 Background
The wastewater treatment process is composed of several critical steps, with the mixing process being particularly important in ensuring the coagulation-flocculation process is effective. It's vital to align the effluent standard with the available wastewater plant features and specifications to achieve optimal efficiency. The mixing process varies depending on the wastewater treatment and desired outcome. Rapid mixing is necessary for the coagulation process to promote an evenly effective reaction between coagulation agents and dirt. In contrast, slow mixing is required for the flocculation process to ensure numerous flocs form and settle.
Apart from process effectiveness, energy efficiency, and economic aspects are also crucial considerations. Gravel bed flocculators, in combination with hydraulic mixing, are often used as a cost-effective flocculator unit. Therefore, it's essential to ensure the specifications of the hydraulic mixing in wastewater plants and gravel bed flocculators, as both can impact each other's performance. The choice of gravel size can affect the turbulence flow provided by hydraulic mixing, which can promote a mixing effect in the flocculator. However, certain turbulent flows of wastewater can affect the effectiveness of the gravel bed flocculator in building flocs and settling them. Addressing this issue requires comprehensive calculation and analysis, which this practicum provides.
1.2 Objectives
a. Students can understand the working principle of a gravel bed flocculator as a form of hydraulic mixing.
b. Students can analyze the correlation between gravel size variables, head loss, and velocity gradient across various gravel sizes.
CHAPTER II LITERATURE REVIEW
2.1 Mixing in Wastewater Treatment
Mixing in wastewater treatment generally refers to the process of combining treatment agents with wastewater to facilitate effective contaminants removal. The mixing process has been crucial in water treatment to ensure the treatment agents are worked entirely along the process by creating a movement in the water and therefore promoting the optimum physicochemical reaction between reactants and contaminants. Additionally, mixing also has a significant role in initiating the dirt settlement process in the coagulation-flocculation process (Meiramkulova et al., 2020).
There are two types of mixing involved in wastewater treatment: rapid mixing and slow mixing. Each type of mixing serves a different purpose in the treatment process. Rapid mixing occurs during coagulation, where chemical substances are added to initiate colloid and particle destabilization. The rapid movement of water is critical during this process to ensure the even distribution of the chemical substances in the wastewater. Rapid mixing typically takes around 5-10 minutes and requires a velocity gradient of 750/s or more (Abdullah, 2018).
Following the coagulation process, the wastewater proceeds to a fluctuation stage, where the impurities are separated. To facilitate the formation of flocs—denser particles that settle more efficiently due to their gravitational weight—a slow mixing approach is crucial.
According to Prakoso (2018), this mixing type is usually implemented for a duration of approximately 10 to 60 minutes, using a velocity gradient of less than 100/s. Additionally, Mechanical, hydraulic, or pneumatic techniques can all be employed to achieve slow mixing.
2.2 Hydraulic Mixing
According to Prakoso (2018), hydraulic mixing refers to a method in a slow mixing process of wastewater treatment, where hydraulic energy is utilized to bring up a slow water movement in a settlement pool. It has a similar function as another slow mixing type method, promoting more attachment of colloids to form a floc and giving it more chance to settle by gravitational force as the water flow is slow. Hydraulic mixing also differentiates into horizontal baffled channel, vertical baffled channel, gravel bed, and perforated.
This method has a prominent advantage in energy saving by utilizing hydraulic energy from wastewater flow. Instead of using a rotating paddle, a certain wastewater treatment plant construction is utilized to create a particular hydraulic movement. The construction has a winding piping system that includes junctions, elevation differences, and several mixing chambers. This customization will increase the potential energy and further increase of Reynold number that implicates turbulence movement in the wastewater flow (Minakov et al., 2020).
2.3 Gravel Bed Flocculator
A gravel bed flocculator is a reactor utilized in the flocculation process that utilizes a hydraulic mixing unit to move water. The term "gravel bed" refers to the reactor's ability to agglomerate flocs and store them within the interstices or settle them on top or below the gravel bed due to the sudden drop in water velocity as it exits the bed. Furthermore, gravel-bed flocculators are highly effective in storing sludge, making them a preferred choice for pretreatment in small plants before filtration, frequently eliminating the need for a separate sedimentation step. It’s also known for its effectiveness with a processing duration of around 3- 5 minutes, which is equal to the 25-minute process of a conventional flocculation unit or the 15-minute process of a jar test process (Sarwono et al., 2017).
According to a study by Putri and Hadi in 2014, a specific type of reactor can lower the concentration of organic matter in water by 3.02 mg/L and decrease water turbidity by 0.5 NTU.
The reactor has demonstrated an impressive efficiency rate with 73.17% and 96%
effectiveness in reducing organic matter and turbidity, respectively. When paired with Al2(SO4)3, the gravel bed flocculator proves to be the most cost-effective flocculator with a removal efficiency rate of 65,9%, surpassing FeCl3. Consequently, the research findings indicate that the gravel bed flocculator is a highly effective flocculator that consumes minimal energy as hydraulic mixing is also utilized to minimize energy used in the system.
2.4 Head Loss Calculation
According to Rahayu et al. (2021), frictional flow is a crucial concept that impacts fluid flow in channels. This phenomenon occurs due to the frictional force between moving fluids and the channel's surface, resulting in a frictional effect that affects the fluid's kinetic stress sigma. This action causes energy loss in the fluid flow, commonly referred to as head loss.
Additionally, head losses are not always caused by frictional forces along the pipe’s surface, apparently sudden geometric changes in the piping system also create a sudden kinematic stress sigma, known as minor head loss. Minor losses in the pipe are caused by the cross- sectional area of the flow that can be found in piping junction, piping contraction, or piping expansion. However, the head loss value in minor loss is usually very small compared to head losses along the piping length (major head loss).
The calculation of head losses is measured in a unit of length that represents the amount of energy needed to move one unit of fluid mass up one unit of height. This calculation is determined using the Darcy-Weisbach formula, which factors in the fluid's viscosity and pipe characteristics. To calculate major and minor head losses, it is necessary to determine the friction factor (f) and loss coefficient (k) through mathematical calculations. Moreover, the calculation of the friction factor can only be done once the stream types in the pipe have been identified using the Reynolds number (Re) with the following mathematical formula:
𝑅𝑒 =𝜌 × 𝑑 × 𝑣 𝜇 Where:
ρ : density (Kg/m3) d : pipe diameter (m) v : flow velocity (m/s) μ : viscosity (N.s/m2)
According to the calculation, flow in a pipe can be determined in three terms, laminar flow (Re<2300), transitional (2300≤Re<4000), and turbulent flow (Re≥4000). The friction factor can be determined as 𝑓 =64
𝑅𝑒 if the flow is laminar. However, transitional and turbulent flow has many factors to consider that make the calculation complicated. Therefore, a moody diagram—
an interpolation of the Re number and relative roughness coefficient—is usually used to determine the friction factor. The relative roughness coefficient is determined by dividing the roughness coefficient of a certain pipe material by its diameter. Hence, a major head loss can be determined by the mathematic formulation below:
𝐻𝑓 = 𝑓 (𝐿𝑣2 2𝐷𝑔) Where:
f : friction factor L : pipe length (m) v : flow velocity (m/s) D : pipe diameter (m) g : gravitational force (m/s2)
On the other hand, minor loss can be determined using a formulation as follows:
𝐻𝑙 =𝑘𝑣2 2𝑔 Where:
k : pipe loss coefficient v : flow velocity (m/s)
g : gravitational forces (m/s2)
The minor losses calculation involves the use of the pipe loss coefficient which is also utilized in Moody's diagram to determine the relative roughness coefficient. This coefficient is typically determined based on the material and shape of the piping accessories and is an absolute statute. It should be noted that different types of piping accessories can produce varying loss coefficients, depending on the amount of energy losses they generate due to sudden geometrical changes (Sudirman, 2021).
2.5 Velocity Gradient Calculation
Fully turbulent has a very unstable tendency of flow which is characterized by intermittent formation of very localized and intense velocity gradients. Therefore, predicting turbulent flow phenomena by using velocity gradient has been crucial to determining fundamental quantities that happen in turbulent flows such as dissipation, enstrophy, and small-scale topology turbulence. Velocity gradient has a dynamic equation to comprehensively describe the nonlinear physics of turbulence flow, offering an intuitive description of turbulence phenomena in dynamics, statistics, and flow structure (Johnson and Wilczek, 2024).
According to Anggrani et al. (2014), the calculation of the velocity gradients is closely associated with fine-scale motion in turbulent flows. Viscosity can be utilized as an approaching method to analyze velocity gradient concerning that fluids particles flow in a pipe is different due to friction. Shear stress happens between fluid and the surface which is caused by fluid viscosities and is positively correlated. However, in the mixing process of wastewater treatment, the flow forces come from water turbulence in the flocculator. Therefore, according to that relationship, the velocity gradient (G) in wastewater treatment can be determined as follows:
𝐺 = (𝑃 𝜇𝑉)
1 2
𝑃 = 𝐾𝑇× 𝑛3× 𝐷𝑖 × 𝜌 Where:
P : power goes to the wastewater (N.m/s) μ : wastewater viscosity (N.s/m2)
V : volume of wastewater mixed (m3) ρ : wastewater density (kg/m3) n : rotary speed (rpm)
KT : coefficient of the impeller types
CHAPTER III METHODOLOGY
3.1 Tools, Materials, and Functions Table 3.1 Tools, Materials, and Functions
No. Tools and Materials Functions
1. Gravels 0,008 m Materials to initiate hydraulic mixing in flocculation were used as an independent variable in this practicum 2. Thermometer Used for measuring the wastewater temperature 3. Ruller Used to measure the height of gravel and wastewater
in the container
4. Stopwatch Used to determine the required time for the wastewater outflow to reach 1 L
5. 1 L Beaker Glass Used to measure the outflow volume of wastewater 6. Wastewater Used for wastewater flocculation process materials 7. Wastewater
Treatment Container
A container to place wastewater and gravel in the gravel bed flocculation process
3.2 Tools and Materials Figures Table 3.2 Tools and Materials Figures
No. Tools and Materials Pictures
1. Gravels 0,008 m
Picture 3.1 Gravels Source: Personal documentation 2. Thermometer
Picture 3.2 Thermometer Source: Personal documentation
3. Ruller
Picture 3.3 Ruller
Source: Personal documentation
4. Stopwatch
Picture 3.4 Stopwatch Source: Personal documentation 5. 1 Liter Beaker Glass
Picture 3.5 1 L Beaker Glass Source: Personal documentation 6. Wastewater
Picture 3.6 Wastewater Source: Personal documentation 7. Wastewater
Treatment Container
Picture 3.1 Wastewater Treatment Container
Source: Personal documentation
3.3 Flowchart
Tools and materials are prepared
The wastewater treatment container dimension is measured
Gravel is inserted into the container (30 cm under and above the outflow faucet)
Wastewater is inserted into the container at a height of 100 cm
Wastewater temperature is measured using a thermometer
The output faucet is opened and the outflow is stable
Used 1 L beaker glass to accommodate the outflow and start the stopwatch once the water filled in the glass
Stop the volume and time measurement once the water has reached 1 L
Calculation analysis
Result
CHAPTER IV RESULT AND DISCUSSION
4.1 Practicum Result Data Table 4.1 Primary Result
Long (m) Length (m)
Gravel Height
(m) Gravel Size (cm) T (°C)
Time (s)
0.18 0.18 0.3 0.005 29.7 24.9
0.18 0.18 0.3 0.008 29.7 24.2
Table 4.2 Final Result
Gravel Size (m) Head Loss (m) Velocity Gradient (/s)
0.005 0.001572 42.35
0.008 0.001178 39.64
4.2 Practicum Result Data Analysis
This practicum aims to calculate the head loss (Hl) and velocity gradient (G) from two different sizes of gravel in a gravel bed flocculator unit. The primary data obtained during the practicum are the container's dimensions, gravel size, temperature, and time required for the outflow to reach a certain volume. The container has a square area with a length of 0.18 m, and it is filled with gravel of 0.3 m height above and below the outflow faucet. Additionally, the flow rate was measured by determining the time required for the outflow to fill a one-liter glass, where 0.005 m gravel size required more time than 0,008 gravel size on 24.9 s and 24.2 s respectively. These data are crucial in determining the flow velocity in the outflow and are used to calculate the head loss and velocity gradient.
Besides, there are several provisions of data such as wastewater viscosity, density, rounded rate, and percolation rate. These provisions are elaborated in the calculation along with the primary data to determine the head loss and velocity gradient difference between 0.005 m gravel size and 0.008 m gravel size. The final calculation result shows that gravel with an average size of 0.005 m has a higher head loss and velocity gradient of 0.001672 m and 42.35 /s compared to 0.008 m gravel size with a final result of 0.001178 m and 39.64/s, respectively.
The hypothesis of this practicum states that the gravel size has a negative correlation with both velocity gradient and head loss, which has been proven by the calculation result.
Smaller gravel size promotes stronger higher flow velocity, resulting in a significant velocity difference and stronger head loss. Based on the calculation result gravel with an average size of 0,005 m shows higher head loss and velocity gradient of 0,001672 m and 42,35/s compared with 0,008 m gravel size with a final result of 0,001178 m and 39,64/s respectively.
4.3 Gravel Size and Head Loss Relation
4.3.1 Gravel Size and Head Loss Correlation Graph
Picture 4.1 Gravel Size and Head Loss Correlation Graph Source: Personal documentation
The displayed graph in Picture 4.1 highlights a clear correlation between gravel size and head loss, with a negative gradient indicating a relationship between the two variables. Within the range of 0.005 m to 0.008 m, an increase in gravel size results in a decreasing trend in head loss value. The head loss value decreased from 0.001572 m to 0.001178 m. While the difference in head loss values may be minimal due to the slight variation in gravel size, the gap is still perceivable.
4.3.2 Gravel Size Factor Effect on Head Loss
According to Lopik et al. (2021), a bigger size of gravel results in a greater volume of pores, which in turn provides more pathways for water to penetrate through the layer of gravel. This characteristic is referred to as porosity, which indicates the rate at which a material can allow liquid to pass through its pores. When the porosity level is high, the flow rate increases, resulting in a decrease in head due to the reduction of friction between wastewater and gravel. However, smaller gravel clogs the liquid path, which increases the friction between wastewater and gravel. This results in a slower flow rate and higher head loss.
In this practicum case, greater gravel size and porosity result in smaller head loss and vice versa which correspond with the literature reference. The increase in head loss was primarily caused by the increase in friction factor due to clogs by smaller gravel size rather than the flow velocity. The calculation shows that 0.005 m and 0.008 m gravel sizes have friction factors of 14.2953 and 10.0036, respectively. Moreover, the velocity of both gravel sizes does not show a significant difference at 0.000036.
4.4 Gravel Size and Velocity Gradient Relation
4.4.1 Gravel Size and Velocity Gradient Correlation Graphs
Picture 4.2 Gravel Size and Velocity Gradient Correlation Graph Source: Personal documentation
Picture 4.2 revealing the correlation between gravel size and velocity gradient indicates a negative trend, suggesting a correlation between the two. The graphic shows that gravel size has a significant impact on velocity gradient, as demonstrated by a steep gradient. In the range of 0.005m to 0.008m, an increase in gravel size leads to a decrease in velocity gradient from 42.35/s to 39.64/s.
4.4.2 Gravel Size Factor Effect on Velocity Gradient
Gravel size has a negative correlation with velocity gradient due to the effect of the kinetic energy of water flow through the gravel layer. The flow of water through the layer of gravel affects its kinetic energy, meaning that smaller or denser gravel with fewer pores for water to pass through will increase the friction between wastewater and the gravel. This leads to an increase in head loss and a decrease in kinetic energy due to friction, resulting in a high-velocity gradient that is significant only in the short term. On the other hand, using sparser gravel with higher porosity provides more room for water to move through the layers with less friction and kinetic energy loss, resulting in a lower velocity gradient. A practical demonstration found that the velocity gradient of 0.005 m gravel size was greater than that of 0.008 m gravel size, with values of 42.35/s and 39.64/s, respectively (Liu et al., 2019).
4.5 Head Loss and Velocity Gradient Relation
4.5.1 Head Loss and Velocity Gradient Correlation Graphs
Picture 4.3 Head Loss and Velocity Gradient Correlation Graph Source: Personal documentation
The Picture 4.3 reveals a direct relationship between head loss and velocity gradient, as indicated by a linear graph with an upward trend. As head loss increases, so does the velocity gradient, as demonstrated by the steep slope of the graph. This suggests a strong correlation between the two variables, implying a substantial increase in velocity gradient.
4.5.2 Head Loss Factor Effect on Velocity Gradient
The relationship between velocity and head losses is close. Head loss is a phenomenon where fluid flow loses its kinetic energy due to additional forces that work against it. The primary cause of head loss is friction or shear stress between fluid particles and the surface layer. In this practicum case, the flow's friction caused by gravels, especially smaller or denser gravel, which creates fewer pores for water, can increase the friction and kinetic energy of the flow, resulting in a bigger head loss. As the kinetic energy loss is significant, the flow velocity decreases significantly in the short term. Thus, an increasing number of head loss indicates a bigger velocity gradient in the flow (Liu et al., 2019).
The practicum result shows a positive correlation between head loss and velocity gradient, which is consistent with the literature reference. A small difference in head loss leads to a significant difference in velocity gradient. For instance, within a head loss of 0.001178 m to 0.001572 m, the velocity gradient ranges from 39.64/s to 42.35/s.
CHAPTER V CLOSING
5.1 Conclusion
A gravel bed flocculator is a widely used unit in the flocculation process of wastewater treatment. It employs hydraulic movement to create a mixing effect that enhances the efficiency of the process. The gravels in this unit create a turbulence effect in the flow that promotes the aggregation of suspended particles in the wastewater. The effectiveness of the flocculation process is affected by the gravel specification, which in turn influences the hydraulic movement in the flocculator unit. Therefore, this study aims to investigate the effect of gravel size utilization on velocity gradient and head loss, in addition to the gravel bed flocculator's working principle.
The experiment involves flow analysis using different gravel sizes (0.005 m and 0.008 m) in the same wastewater temperature and volume. The experimental and calculation analyses indicate that the gravel size of 0.005 m has a lower flow rate on the outflow due to its smaller porosity, referring to less pore volume for water to flow through the gravel's layer. This condition increases the friction between water and gravel, leading to a higher head loss and velocity gradient. Moreover, the head loss and velocity gradient have a positive correlation.
The head loss and velocity gradient for 0.005 m and 0.008 m gravel sizes are 0.001572 m and 0.001178 respectively, with flow rates of 42.35/s and 39.64/s.
5.2 Suggestion
The learning objectives of this practicum have been effectively conveyed. No significant improvements are required for this practicum. However, to gain a more thorough understanding, it would be beneficial to conduct observations using a variety of gravel materials to examine the impact of porosity on head loss and velocity gradient beyond just considering gravel size.
BIBLIOGRAPHY
Abdullah T. 2018. Studi Penurunan Kekeruhan Air Permukaan Dengan Proses Flokulasi Hydrocyclone Terbuka. Tesis. Departemen Teknik Lingkungan, Fakultas Teknik Sipil, Lingkungan, dan Kembumian, Institut Teknologi Sepuluh Nopember.
Anggarani BO, Karnaningroem N, Moesriati A. 2014. Peningkatan efektifitas proses koagulasi- flokulasi dengan menggunakan Aluminium sulfat dan Polydadmac. Prosiding Seminar Nasional Manajemen Teknologi XXII. Surabaya, 24 Januari 2014.
Johnson PL, Wilczek M. 2024. Multiscale velocity gradients in turbulence. Annual Review of Fluid Mechanics 56: 463–490. https://doi.org/10.1146/annurev-fluid-121021-031431.
Meiramkulova K, Orynbekov D, Saspugayeva G, Aubakirova K, Arystanova S, Kydyrbekova A, Tashenov E, Nurlan K, Mkilima T. 2020. The effect of mixing ratios on the performance of an integrated poultry slaughterhouse wastewater treatment plant for a recyclable high-quality effluent. Sustainability 12(15): 6097.
https://doi.org/10.3390/su12156097.
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https://doi.org/10.3390/fluids5040211.
Prakoso H. 2018. Uji Kinerja Unit Pengaduk Lambat Tipe Hidraulis. Tugas Akhir. Departemen Teknik Lingkungan, Fakultas Teknik Sipil, Lingkungan, dan Kebumian, Institut Teknologi Sepuluh Nopember.
Putri HY, Hadi W. 2014. Efektifitas Al2(SO4)3 dan FeCl3 dalam pengolahan air menggunakan gravel bed flocculator ditinjau dari parameter warna dan zat organik. Jurnal Teknik Pomits 3(2): 167–171.
Sarwono E, Aprillia KR, Setiawan Y. 2017. Penurunan parameter kekeruhan, TSS dan TDS dengan variasi unit flokulasi. Jurnal Teknologi Lingkungan 1(2): 8–14.
Sudirman. 2021. Major and minor head losses analysis on the piping system in Pondok Pesantren Tahfizhul Qur'an Ibnu Abbas Tarakan. Journal of Applied Electrical and Science Technology 3(1): 11–16.
ADDITIONAL BIBLIOGRAPHY
Liu X, Fan D, Yu X, Liu Z, Sun J. 2019. Effects of simulated gravel on hydraulic characteristics of overland flow under varying flow discharges, slope gradients, and gravel coverage degrees. Scientific Report 9(1): 19781. https://doi.org/10.1038/s41598-019-56223-2.
Lopik JH, Swijen T, Hartog N, Schotting RJ. 2021. Contribution to head loss by partial penetration and well completion: implications for dewatering and artificial recharge wells. Hydrogeology Journal 29(1): 875–893. https://doi.org/10.1007/s10040-020- 02228-5.
APPENDIX
ADDITIONAL APPENDIX
PRACTICUM RESULT DATA (ACC)
