White, Chris, White

White, Chris

Chris White is the VP of Data Services with RedZone Robotics with over 13 years in the wastewater industry. With Mr. Whites support, RedZone has successfully aided engineers and municipalities in better understanding sensor technologies and data for managing their collection systems. He oversees the transition of software and data to the end-client and provides a hands-on approach to continuing education. His technical knowledge of RedZones technology and interpretation of deliverables is recognized as an asset to RedZones clients. Mr. White maintains a current NASSCO certification.

Titles from this speaker

Description: Identifying Tomorrow's Problem Today: Predictive Analytics in Wastewater...

Identifying Tomorrow's Problem Today: Predictive Analytics in Wastewater Collections

Abstract

1. Introduction
The cost of pipeline failure in sanitary sewer systems serving cities and municipalities is increasingly high. A failure where a collapse occurs typically causes a sanitary sewer overflow (SSO) and requires bypass pumping, public notification, and costly construction under emergency conditions. Soil saturation from failing sewer pipelines can lead to collapses and result in imminent danger to surrounding infrastructure and the public. The liability associated with collapse increases in high density areas, high-density traffic regions, and nearby other critical above ground infrastructure. Additionally, the age of the sewer can have a vital impact on the longevity of the infrastructure asset. Most pipe structures often have lifespans of 80-100 years. As the length of use increases past this timeframe, the need for condition assessment becomes increasingly critical. This assessment provides information on the current conditions, but also informs capital planning decisions: pipes may have outrun their useful life due to increased population and demand on services. The pipes within a wastewater collection system have a finite service life due to a multitude of variables, including material, usage, operations and maintenance schedules, and external environmental conditions. In order to identify and better understand the conditions within these main lines, utility and system owners have recognized the importance of regular inspection and assessment of these structures. This inspection data can prevent sewer system overflows (SSO), service disruptions, and most importantly, pipe collapses. However, due to field conditions, it can be incredibly difficult to inspect all structures. Infrastructure assets that are inaccessible or in hard-to-reach locations can pose problems with inspection and often extend the amount of time and money required on a project. Further, the need for inspection does not go away and is only emphasized. It poses a unique conundrum: How does a utility owner assess and prioritize their entire system, if a portion of the system cannot be addressed? How does a utility owner budget their maintenance schedules if their financial budget cannot support a baseline of inspecting their entire system fast enough to prevent failures?
2. Predictive Analytics
Predictive analytics is the use of data mining, predictive modelling, and machine learning to analyze current and historical characteristics to predict future events. It has been used from advertisements, shopping, healthcare diagnoses, and virtual assistants to identify what someone or something is likely to do.
Predictive Analytics has also been utilized in the water industry. Drinking water infrastructure is mostly pressurized pipe (i.e. Force main), which is often difficult to assess without redundancy, costly bypassing, or taking the pipe out of service. This makes it even more difficult for system owners to determine current condition, remaining useful life, or even rehabilitation decisions. Through the use of artificial intelligence and machine learning, pipeline attributes are fed through proprietary analytical models to look at commonalities of pipes that have failures to determine patterns and trends. These patterns and trends lead to predictability.
These attribute datasets are enormous and include: - historical failures and when those failures occurred - types of failures - pipe size and material - pipe age and repair history - current conditions - maintenance schedules - geospatial data (GIS) - weather patterns - foliage environment - soil conditions
The output that is produced is a ranking list of pipes based on their likelihood of failure (LoF). LoF indicates the probability of failure based on the attributes above. The weight and severity of these attributes can vary from system to system, but some generalities can be assigned: A pipe that is larger in diameter or conveys more flow has a higher consequence of failure (CoF) than a smaller diameter line. Additionally, a pipe that is below a populated area or nearby critical piece of infrastructure such as a hospital or government building, could have devastating consequences if it were to fail, compared to those in more rural or less-populous areas.
3. Wastewater
Asset Management is not just for the drinking water side of our industry! There are plenty of utility owners responsible for the oversight, budgets, and maintenance of wastewater collections systems. Further, these systems are often gravity-fed, providing access to the pipe for condition assessment compared to pressurized lines. These conditions assessments typically involve CCTV to identify defects and deficiencies. Fortunately, NASSCO has set the standard for how these defects should be coded and classified, making it easier to compare datasets. The approach to maintenance and rehabilitation decisions are commonly based on 2 main facets of a pipe: whether the pipe had failed before and the age of the pipe. It is assumed that as the pipes get older or has an issue that requires maintenance, that pipe is likely to fail again or require continued maintenance in the future.
4. Approach and Case Study
With over one hundred (100) million linear feet of inspections completed to date, RedZone Robotics sought to see how this NASSCO-coded defect data could be used to better predict failures within a wastewater system. Four (4) million linear feet of CCTV data was provided to Voda.ai's machine learning algorithm. All data is PACP v6 compliant and is comprised of inspections ranging from 6-inch to 36-inch pipe of various materials.
This case study and presentation covers the methodology of cleansing the data, building the model, and the results for predicting structural and operations and maintenance failures within wastewater assets. In summary, the predictive model was able to identify 3x as many failures on pipes compared to prior failure history and 65x as many failures compared to the age of the pipe and. Additionally, the model could also identify the types of failures, providing utility owners with more knowledge about potential failures and how to address them.

Within wastewater systems, the approach to maintenance decisions is often based on the age of the pipe or prior failures. These static, one-variable approaches often miss the mark and have dire economic and environmental impacts due to unexpected pipe failures. One method system owners use to identify potential issues is regular visual assessments of these pipelines. How do we use the CCTV inspections with an AI model to develop better maintenance programs and prevent failures?

SpeakerWhite, Chris

Presentation time

13:45:00

14:05:00

Session time

13:30:00

15:00:00

TopicIntermediate Level, Collection Systems, Intelligent Water, Wet Weather

Author(s)

White, Chris

Author(s)Chris White1; Jeff Griffiths2; George Demosthenous3

Author affiliation(s)RedZone Robotics, Inc, Warrendale, PA1;RedZone Robotics, Inc, Newport News, VA 2; Voda.ai, Boston, MA3

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2022

DOI10.2175/193864718825158613

Volume / Issue

Content sourceWEFTEC

Word count10

The Calm Before the Storm: Proactive I/I Remediation in Brevard County, FL

Abstract

Brevard County, situated on the East Central coast, is home to over 600k individuals. It encompasses sixteen municipalities including Cocoa Beach and Cape Canaveral. The latter serves both cruise ships as well as the Space Force Station and Kennedy Space Center. Brevard is also home to over 250sq miles of wildlife refuges which sit alongside the Indian River Lagoon. It is considered one of the most bio-diverse estuaries in the Northern Hemisphere. With such important national treasures and delicate environments, Brevard was aware for the need to be prepared for major weather events. Unfortunately, the below ground infrastructure was not as ready. Brevard County Utilities operates and maintains over 500 miles of gravity wastewater mainline, across 291 lift stations, ranging from 6'-30' inch. Over 95% of these pipelines are 12-inch and below and consist of PVC and VCP materials. There are also 6 WWTPs in various unincorporated locations of the County, the largest which operates at 6mgd. In 2017, with storm surges and rainfall from Hurricane Irma, the WWTPs were unable to handle the increased flow, resulting in a discharge of 100mil. gallons of untreated water to the Indian River Lagoon. The water was clear, which was evidence of extreme I/I from Irma's weather. Rainfall was getting into the system through structural deficiencies and overwhelming an already fragile network — resulting in significant costs via pump station run times, treating water, and environmental consequences. These effects did not go unnoticed by Commissioners and the public. For weeks after Irma, reports of sewage and wastewater debris were noted in the Lagoon and along the Anchor Drive Canal. For the Utility, it was either discharge or have this backup into people's homes. The County was in the midst of an extensive Capital Improvement Program (CIP) for fixing these pipes and manholes but had not made enough of an impact to mitigate Irma's torrent. The program involved CIPP lining of entire areas of the system. Due to public outcry, lining became the go-to project resulting in entire basins being lined without prior investigation. It seemed like a perfect 'quick fix'. However, it was costly. Over the span of 2017-2019, not enough pipes were completed using the County's annual budget. At the rate they were going, it would take decades to line everything. The need for prioritization was apparent. In 2019, Brevard utilized a contract from nearby Palm Bay for sewer inspection services. While the concept of inspection was not new, the technology was new to Brevard. Robotic crawlers capable of inspecting 3-4x the footage of a conventional camera was exactly the solution they needed. The company, RedZone Robotics, manufacture an autonomous CCTV camera called Soloïƒ¢ designed for 8-12' pipelines — over 95% of Brevard's collections system. It is equipped with 2 cameras, one on the front and rear, creating a 360-degree video of inside the mainline. It did not require a box truck and could be easily transported into easements, rear lots, or other harder to access areas. Traffic control was also reduced significantly. Where the value peaked for the Utilities department, was in the speed and spend. The services provided by RedZone would allow for larger portions of the system to be inspected using NASSCO's PACP standard. While the budget did not allow for the entire system to be inspected in one year, it did allow enough to create a prioritization program. The Solo units could confirm which pipes were in need of repair, and after analysis of risk and criticality scoring, rank those pipes for CIPP-lining need. The Solo units were operated on an 'Inspect-to-Clean' approach. On average, 70%-80% of a system does not need to be cleaned in order to inspect. The defects that cause blockages are also not likely to be resolved by jetting: roots and intruding taps are some of the biggest inhibitors. By placing a camera into the pipe and determining condition, the right tool can then be used, saving on cleaning costs in the process. In 2019, Brevard halted their lining efforts and converted to inspections. Starting in May, through June 2021, over 1.6mil LF of pipe was assessed using the Solo. By applying the PACP ratings, any pipes identified as having a grade level 4 or 5 structural issue were placed onto the priority list for criticality assessment. Using Esri's ArcGIS platform, the Utility could denote key environmentally sensitive areas within the County, to place pipe assets nearby higher in rank for rehabilitation and lining projects. Any grade level 4 or 5 O&M issues were then handled internally by the Operations to perform cleaning and mitigate any potential overflow. The initial results confirmed two things: 1) The system was not in bad shape. Basins that were set to be entirely lined showed that many of the pipes were still in good structural condition, free of defects. 2) By lining the most troubled spots after assessments, pump station run times were reduced by 50% - going from an average of 200gpm to 100gpm. Switching to a baseline assessment was proving to be a great strategy. Despite there still being evidence of I/I, the reduction in the power consumption and use of those lift stations was monumental. On future wet weather events, there was little worry about the ability to convey and treat that water. In October 2020, the County began incorporating manhole inspections into the program alongside the pipe. As another vital component of the collections system, the need for assessment and rehabilitation of failing access points could not be ignored. By May 2021, nearly 5000 manholes had been assessed using NASSCO's MACP. As of today, over 2mil. LF of pipe (66%) and 8,000+ manholes (60%) have been inspected. Using the 'Inspect-to-Clean' approach, approximately 275,000 LF of pipe was identified as needing to be cleaned. This amounted to only 9% of the system! As for structural issues and the lining program, approximately 134,000 LF of pipe contained a grade level 4 or 5 defect (4%) and ~250 manholes that would require rehab. While these lining programs would be expensive, these results further confirmed Brevard's approach to inspecting first. Without a baseline assessment, Brevard would have spent their resources 'fixing' problems that were not likely to exist in the system. The issues identified from Irma were not insurmountable. The key to tackling the problem was investigation: using CCTV collection and NASSCO scoring, delivered via robotic technology, to create an effective condition assessment program. The data is actionable and defensible. By tying it back to their GIS and using risk scoring, it enables the Utility to be in sync for improving the system before the next hurricane arrives.

This paper was presented at the WEF Collection Systems and Stormwater Conference, April 9-12, 2024.

SpeakerWhite, Chris

Presentation time

09:00:00

09:30:00

Session time

08:30:00

11:45:00

SessionCollection System Inspection

Session number28

Session locationConnecticut Convention Center, Hartford, Connecticut