Application Layer Model

Introduction

Sewer systems are a critical part of urban infrastructure; however, they are also a hotbed for microbial growth and corrosion, particularly sulfate-reducing bacteria (SRB), which can lead to damage to pipes and increased maintenance costs. To address this issue, we conducted a macro-level simulation study of engineered bacteria placement decisions to explore the potential effects of introducing probiotic organisms (E.coli) into the sewer system to control SRBs.

Our simulation is based on a meta cellular automata model that takes into account the physical parameters of the sewer system, including pipe depth, pipe diameter, and water flow rate, as well as the diffusion of E.coli colonies in the water and their interaction with SRB. Our study aims to answer the following three key questions:

  1. The process follows the law of mass action
  2. Average cell volume is a constant
  3. Cell volume is much smaller than total volume

The goal of this research is to provide new, sustainable solutions for the maintenance of urban sewer systems that reduce maintenance costs and improve system reliability. Our simulation results will contribute to a better understanding of how the introduction of E.coli affects the microbial ecosystem in the sewer system and provides a strong reference for future engineering practices.

Fig.1 Application Layer Flowchart

Assumption

  1. Uniform Flow: We assume that the water flow in the sewer is uniform and has a constant flow rate.
  2. Probability of colony spreading: In our model, the probability of an E.coli colony spreading to neighboring metacells is a constant.
  3. Probability of bacteria being washed away by water flow: We assume that the probability of an E.coli colony being washed away by water flow is a constant.
  4. Maintenance Costs: We assume that maintenance costs are related to the distribution of SRBs on the sewer line. Actual repair costs may be affected by other factors, such as material costs and labor costs.
  5. Time Scale: Our simulations are based on a discrete time-stepping model with a uniform time scale.

Data Accession

Specific situation of Chengdu municipal pipe network

The length of Chengdu's municipal pipe network is about 7,400km, with sewage network accounting for 3,000km and rainwater 4,000+km.

the general types of pipeline diseases

They are generally categorized into two main types. Functional Diseases and Structural Diseases. Functional diseases generally include siltation, and structural are generally rupture, deformation, or collapse of the pipe network. The level of disease can be divided into 1-4 (see "Technical Regulations for Detection and Evaluation of Urban Drainage Pipes" p21-p26), three and above is a major disease that needs to be dealt with, and 1-2 is mainly focused on prevention. Diseases caused by corrosion are still the most numerous.

Means of treating the infestation

There are a variety of processes, with the main choice being non-excavation, which has less impact on municipal roads. There is a non-excavation guide. The most used in non-excavation is UV light, which is generally used to treat corrosion and costs about $2,000 for a single use.

standards for manhole cover installation

Outdoor drainage design code? There are clear requirements. According to the pipe diameter, the interval of 25, 30, and 40m are possible.

Main materials and anti-corrosion measures adopted for sewage pipes in Chengdu City

The most used are reinforced concrete pipe and some plastic pipe. Now, Chengdu City is mainly reinforced concrete, which can also be divided into plain concrete pipe and socketed concrete pipe. Socketed concrete pipe is more in line with the standard; the earlier plain concrete pipe is on the high side more prone to problems. Now, the new pipeline to take anti-corrosion measures is mainly epoxy asphalt coating. The technical department is also studying.

Total cost of pipeline operation and maintenance

The calculation of the cost of a single attendance is more complicated; the current charge for O&M is $45/m for one year, excluding disease management. The cost of disease management is about 15% of the O&M fee (45*7400*1000*15% = 49.95 million)

Pipeline water flow rate

The situation is different for different pipe diameters and different times of the day, and the flow rate of the water level at the peak of water consumption is even higher. The average 1.2-1.3m/s for the main pipe can reach 2m/s near the downstream treatment plant.

1 Sewer placement time for Modified E.coli

Based on a realistic physical model, we modeled the process of bacteriophage placement.

The time from the well cover to the water surface : \begin{equation} F_{\text{gravity}} \;=\; M \cdot g \label1 \end{equation} \begin{equation} F_{\text{drag}} \;=\; \frac{1}{2} \cdot c \cdot \rho_w \cdot A \cdot v^2 \label2 \end{equation} \begin{equation} F_{\text{net}} \;=\; F_{\text{gravity}} - F_{\text{drag}}\;\;=\;\;M \cdot a_1 \label3 \end{equation} \begin{equation} H \;=\; \frac{1}{2}\, a_1 \cdot t^2 \label4 \end{equation}

Time from surface to bottom of pipe : \begin{equation} F_{\text{water_drag}} \;=\; \frac{1}{2} \cdot \delta_1 \cdot \rho_w \cdot A \cdot v^2 \label5 \end{equation} \begin{equation} F_{\text{net_water}} \;=\; F_{\text{gravity}} - F_{\text{water_drag}}\;\;\;=\;\;M\cdot a_2 \label6 \end{equation} \begin{equation} h \;=\; a_1\cdot t_1 \;+\; \frac{1}{2}\, a_2 \cdot t_2^2\;\;=\;\;M \cdot a_1 \label7 \end{equation} \begin{equation} T \;=\; t_1 \;+\;t_2 \label8 \end{equation}

Based on aerodynamics and hydrodynamics, we simulated the physical process of dropping our colony from the air to falling to the bottom of the sewer, as shown in Figure :

Fig.1 E.coli placement simulates physical processes

From the figure, green indicates the trajectory of the colony in the air and red indicates the trajectory of the colony in the water, and we calculate that the time for the colony to drop from the mouth of the manhole cover to the bottom of the sewer pipe is 2.177 seconds.

2 Changes in the distribution of SRB and E.coli in sewers

After obtaining the time when the engineered bacterium ECO was dropped from the manhole cover to the bottom of the sewer pipe, we used a meta-cellular automaton model to simulate the changes in the distribution of E.coli colonies and SRBs in the sewer. The following are the basic rules of the model:

  1. Initialization : We divide the sewer pipes into a grid of tuples of equal size and initialize the distribution of SRBs and E.coli at random. Each tuple can have one of the following states: empty, containing E.coli, containing SRB.
  2. Time steps : At each time step, we apply the following rules :
    • E.coli-containing metazoans have a certain probability of diffusing into neighboring empty metazoans.
    • E.coli has a certain probability of being swept away by the current.
    • if a metameric contains both E.coli and SRB metameric, E.coli will kill SRB.
  3. Simulation results: The simulation will reach equilibrium after multiple time steps. At the end of each time step, we recorded the distributions of E.coli and SRB for visualization and analysis

These meta-cellular automata rules model the dynamic interactions and distributional changes of E.coli and SRBs in sewer pipes. With multiple time steps, we can observe how the introduction of E.coli affects the distribution of SRBs and the potential effects of maintaining the sewer system..

To further determine the colonization of the bottom of the sewer pipe by our engineered bacterium E.coli and the changes in the distribution of SRBs before and after placement, we visualized the distribution of E.coli and SRBs before and after placement, respectively, as shown in Fig:

Fig.2 Changes in the distribution of E.coli before and after placement

As can be seen from the figure, a significant increase in the distribution of E.coli at the bottom of the sewer pipe after placement can be clearly seen.

Fig.3 Changes in the distribution of SRB before and after placement

As can be seen from the figure, a significant reduction in the distribution of SRB at the bottom of the sewer pipe after placement can be clearly seen.

3 Changes in maintenance costs

According to the information provided by Chengdu Sewerage Municipal Corporation, the daily maintenance cost per 1m of pipeline in Chengdu is 45 RMB. Since SRBs form biofilm in sewers, which accelerates the corrosion of sewer pipelines, we use the projected engineering bacterium E.coli to inhibit the formation of SRBs biofilm and to kill SRBs so as to slow down the corrosion of the sewer pipelines and to reduce the maintenance cost.

Fig.4 Changes in maintenance costs of E.coli before and after placement

Combined with our previous model simulation, we calculated that the daily maintenance cost of this 30m long pipe will be reduced by 211.5 RMB.

Reference

[1] Jin P, Wang B, Jiao D, Sun G, Wang B, Wang XC. Characterization of microflora and transformation of organic matters in urban sewer system. Water Res. 2015 Nov 1;84:112-9.

[2] Li W, Zheng T, Ma Y, Liu J. Current status and future prospects of sewer biofilms: Their structure, influencing factors, and substance transformations. Sci Total Environ. 2019 Dec 10;695:133815.