Garcia, David

David has 16 years of experience as a collection systems infrastructure planning engineer. David began his career in wastewater collection systems by performing condition assessment, smoke testing, and flow monitoring. He brings the unique perspective of his field experience to strategic planning and alternatives development. With WCS, he develops innovative, holistic, and robust solutions to provide clean, safe water for communities. In his free time away from the office, David enjoys mountain biking, hiking, and camping with his family.

Titles from this speaker

Description: Best Practice of Intelligent Algorithms to Optimize and Prioritize Capital...

Best Practice of Intelligent Algorithms to Optimize and Prioritize Capital Investments and Asset Rehabilitation

Abstract

Purpose The purpose of the presentation is to illustrate that for digital-water solutions to be successful we need to shift the focus from 'digital' and 'smart,' data and tools to the people and value added. It is easier and cheaper than ever to collect data, numerous tools are available for data processing/visualization, vendors offer different digital twin platforms to integrate and deliver this new information. The key component in the future success of digital-water implementations is not in the digital domain, but instead it is in a clear definition of value added / return on investment and close collaboration with the utility staff on the implementation of the solution. The Jefferson County, AL, application of intelligent algorithms to optimize and prioritize capital investments and asset rehabilitation demonstrates a collaborative approach through every stage of the project and delivers simple to understand optimal solutions based on cutting-edge technology.

Benefits This presentation will provide the following benefits to the audience and industry:

-- demonstrate how formal optimization software can be applied using best practice techniques to evaluate alternatives.

-- provide an apples-to-apples comparison of the SSO Remedial Measures Plan (RMP) developed using traditional trial-and-error modelling techniques and the optimized RMP developed using optimization software

-- illustrate how performing sensitivity analyses on the effectiveness of I/I reduction identifies basins that are cost-effective and ensures conservative conveyance capacity upgrades.

-- demonstrate how asset condition and sediment data can be incorporated into an optimization to determine whether it is more cost-effective to clean the sediment or replace and upsize based on a holistic consideration of conveyance, storage, and I/I reduction alternatives.

-- demonstrate how the optimization approach can incorporate multiple design storms in a single analysis to determine the cost-effective strategy that eliminates SSOs in both events.

-- illustrate how Optimizer can be applied to prioritize the schedule of implementation of a capital program to maximize return on investment.

Background Jefferson County owns and operates wastewater collection systems across nine treatment plant basins serving approximately 600,000 people. A total of approximately 200 reported SSOs are currently recorded by Jefferson County. In 2019, Jefferson County engaged WCS and Hazen to undertake an optimization demonstration project to evaluate conveyance, storage and I/I reduction alternatives for the Valley Creek basin which had the highest density of reported SSOs. This project successfully demonstrated life-cycle cost savings on the order of $54 M (30%) when compared to the Baseline RMP (developed using traditional trial-and-error modelling). It also demonstrated that a prioritized capital improvement schedule could achieve 40% SSO volume reduction within the first 10% of capital expenditure and 98% reduction within 70% of the total capital expenditure required to eliminate all SSOs and achieve surcharge objectives. The Jefferson County, System-Wide RMP Optimization project was undertaken and completed in 2020 based on the success of the Valley Creek demonstration project. The system-wide optimization incorporated five treatment plant basins that are all interconnected either by existing or potential future flow diversion structures.

Details The primary objective of this study was to apply intelligent algorithm optimization technology, 'Optimizer', to evaluate and prioritize remedial measure alternatives including conveyance, storage, inter-basin transfer, treatment, and inflow and infiltration (I&I) reduction alternatives to eliminate SSOs in the 2-year design storm (6-hour and 24-hour events). Secondary objectives include performing sensitivity analyses for key assumptions and to identify aspects of the planning strategy that may require further investigation. The 'Optimizer' software integrates improvement alternatives, comprehensive life-cycle costs, design criteria, and the calibrated hydraulic model of the collection system. In a single analysis, the software applies intelligent algorithms and cloud computing to evaluate tens of thousands of possible solution configurations with respect to life-cycle cost and hydraulic performance. Scenarios and sensitivity analyses are easily completed by adjusting relevant assumptions or inputs and rerunning the cloud-based optimization.

-- Improvement alternatives evaluated in the optimization include:

-- Parallel relief sewers and upsized gravity sewers
-- Sediment removal.
-- Pump station upgrades. Force mains.
-- New storage facilities.
-- Inter-basin diversion controls
-- High rate treatment facilities.

I&I reduction. Unit cost rates adopted for the optimization analysis are planning level estimates developed by Hazen based on the County's bid tab records. The unit costs include capital, O&M, and replacement estimates of all alternatives.

System-wide optimization runs were completed for the following scenarios:

Conveyance-Only
-- Optimization without storage or I&I reduction alternatives
-- Conveyance + Storage - Optimization without I&I reduction alternatives
-- All Alternatives (Ultra-Conservative I&I)
-- All Alternatives (Conservative I&I)
-- All Alternatives (Aggressive I&I)

The optimized solution costs for each scenario are compared in Figure 1. The preferred RMP strategy was the All Alternatives (Aggressive I&I) scenario illustrated in Figure 2. The optimization model used for the prioritization task was formulated to select projects from the Optimized RMP (aggressive I&I reduction scenario). The prioritization analysis used the optimization model to determine the sequence of implementation that provides the maximum return on investment with respect to reducing total overflow volume in the 2-year design storms. The preliminary prioritization results are shown in Figure 3.

Conclusion The Jefferson County, Valley Creek Optimization demonstration project and the System-Wide Optimization project demonstrate both significant savings when compared with an apples-to-apples Baseline RMP developed using traditional trial-and-error modelling and highlighted opportunities for incorporating flexibility to allow the RMP to be adapted over time. The prioritization analysis completed for each project consistently demonstrated a high return on investment whereby the vast majority of SSOs could be eliminated at a fraction of the total program cost. This outcome allows Jefferson County to provide customers with immediate and noticeable improvements in system performance during the early stages of the program while also providing an opportunity for the final stages of the program to be adapted and potentially eliminated if a diminishing return on investment can be illustrated as more data is collected. The County considered the optimization projects successful in minimizing capital expenditure required to meet consent requirements and informing decision making when selecting where to focus short-term investments to maximize value provided to customers.

The following conference paper was presented at Collection Systems 2021: A Virtual Event, March 23-25, 2021.

SpeakerGarcia, David

Presentation time

13:40:00

14:00:00

Session time

13:00:00

14:00:00

SessionData & Analytics

Session number8

Session locationLive

Topicartificial intelligence, Combined Sewer Overflow, Innovative Technology, Optimization, Predictive Analytics, Prioritization, Remote Monitoring, Smart Water Infrastructure, Wet Weather

Author(s)

J. WilsonD. GarciaS. TomicS. KingD. White

Author(s)J. Wilson1; D. Garcia2; S. Tomic3; S. King4; D. White5

Author affiliation(s)WCS Engineering1; WCS Engineering2

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Mar 2021

DOI10.2175/193864718825157697

Volume / Issue

Content sourceCollection Systems Conference

Word count15

Description: Strategic CIP Prioritization Utilizing Optimization Algorithms to Maximize Return on...

Strategic CIP Prioritization Utilizing Optimization Algorithms to Maximize Return on Investment

Abstract

SUMMARY OF ABSTRACT
Engineers have long been concerned about the risk of corrosion in force mains, and with recent improvements in pressure measurement engineers have become more aware of the risks posed by hydraulic transients. Traditionally, these risks have been considered independently. Recent research indicates that hydraulic transients and corrosion are more interrelated than previously realizeda,b. Western Lake Superior Sanitary Sewer District (WLSSD) and HR Green, Inc. collaborated on this project where the two risks were considered jointly. We will present the results of high-speed hydraulic transient pressure measurement at the headers of three of WLSSD's most critical force mains. We will show how we used calibrated hydraulic transient models to recommend alternatives that considered both of the aforementioned risks. By considering both risks in our recommendations, we have improved the chances that the upgrades will bolster the resiliency of the overall hydraulic system, and not simply trade one risk for another.
BACKGROUND
WLSSD owns and maintains a total of 34 miles of force mains, the majority of which is ductile iron pipe. The utility is concerned about the future longevity of the pipe given that the majority is more than 20 years old, with much of it more than 30 and 40 years old. Due to serving the paper milling industry two of the force mains we will be discussing have relatively high temperature, and high H2S concentrations, putting those mains at greater risk of failure due to corrosion. The hilly nature of the terrain that the force mains traverse creates many opportunities for gas pockets to form at high points, which can exacerbate corrosion risks. In addition to the traditional understanding of the causes of corrosion, recent research indicates that corrosion can also be caused by hydraulic transient pressure cyclesa,b. The high flow, high head, high pump horsepower, and long pipe length also make these lines susceptible to hydraulic transients. The force mains studied in this project are single force mains, without a redundant line, and as a result minimizing the risks to them from corrosion and hydraulic transients is of critical importance to WLSSD.
SCOPE OF PROJECT
In this presentation, we will discuss our findings assessing and addressing the interrelated risks of corrosion and hydraulic transients in three of the larger ductile iron force mains in the state of Minnesota. We will present the results of high-speed transient pressure monitoring, hydraulic transient modeling, as well as the results of our corrosion risk assessment. The three lines studied are the Scanlon Force Main (4.6 miles of 30' and 42' DIP and FRP), the Knowlton Creek Force Main (4.9 miles of 48' and 54' DIP), and the Carlton Force Main (2.2 miles of 14' DIP).
GENERAL PROCEDURES
Hydraulic transients were measured close to the header of each of the three pump stations at a scan rate of 100 samples per second via an Omega Transient Pressure Data Logger (OM-CP-PRTRANSIS-1-500G). An example of the pressure monitoring set up is shown in the attached photo, the data logger is located in the white box on the photo. We measured the force main pressures under typical operating conditions. Understandably, the project team did not want to trigger a high-risk scenario just for the sake of measurement. We built hydraulic models for each pump station and force main that after calibration generally mimicked the results measured in the field. The hydraulic transient models were then used to extrapolate the results across the entire system and to evaluate more extreme events than we were comfortable triggering. The high-risk scenario evaluated for each station was a multi-pump trip (i.e., power failure simulation) of the highest number of pumps that are run simultaneously at each station. The highest number of pumps tripped (in the model) were three, two, and two for Carlton, Scanlon, and Knowlton Creek pump stations, respectively. We performed modeling using KY Pipe Surge Software, which uses the Wave Characteristic Method, and Hazen Williams Equation to calculate the transient pressures.
RESULTS
An example of the measured data overlaid upon the post-calibration model results is shown in the attached Pressure vs. Time plot. An example of a high-risk scenario extrapolation (a 3-pump trip of the Carlton Pump Station) is shown in the attached Pressure vs. Distance plot. From this particular plot we observe that the pressure envelope (in grey), which represents the high and low pressures seen in the pipeline with the recommended number of combination air valves (2) added along the line. As can be seen from the graph, the system with the new valves is exposed to minimum pressures above the level of vapor cavity formation (horizontal pink line) and above -6 psi (horizontal orange line), which provides a sufficient margin of safety against vapor cavity formation. We concluded that to provide a similar level of protection from hydraulic transients seven new combination valves are needed on the Scanlon line, and a single new combination valve is needed on the Knowlton Creek line. The Scanlon line required special consideration because, if all seven combination valves are installed, oxygen (via the air) will be introduced into the force main under normal operating conditions. This will increase the risk of microbiologically influenced corrosion. As a result, we are also considering evaluating other alternatives that do not add oxygen to the line, and therefore do not increase the risk of corrosion. Lastly, a corrosion risk assessment was performed for each force main and we recommend three locations for further pipe integrity testing on each pipe system. We have attached an example of the testing location recommendations for the Carlton force main on Carlton pipe profile.
CONCLUSIONS
- All three pipelines could benefit from improvements to their surge protection systems. - In some cases, existing combination air valves were ineffective due to the existing venting arrangement (or lack thereof). Modeling showed that improving the venting will reduce the observed transients (provided valve slam is not an issue). - In some cases, existing combination air valves did not open under typical or high-risk scenarios, and those valves could be eliminated. - Measurement and modeling of hydraulic transients complement each other, and iterating between the two can provide the most accurate representation of the system in question. - Because surge protection equipment can introduce oxygen, as was seen on the Scanlon force main, it can create an added risk of microbiologically influenced corrosion in wastewater force mains. - Methods of surge protection that do not rely on the addition of air to the system are available and should be considered for problematic pipe profiles in order to address the risks from hydraulic transients without increasing corrosion risks.

SpeakerGarcia, David

Presentation time

14:00:00

14:15:00

Session time

13:30:00

15:00:00

TopicIntermediate Level, Asset Management, Collection Systems, Intelligent Water

Author(s)

Garcia, David

Author(s)Joel Wilson1; Andrew Faulkner1; David F. Garcia, Jr.,1; James M. Brescol2

Author affiliation(s)WCS Engineering1; TetraTech2

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2022

DOI10.2175/193864718825158625

Volume / Issue

Content sourceWEFTEC

Word count12

Strategic CIP Prioritization Utilizing Optimization Algorithms to Maximize Return on Investment

Abstract

INTRODUCTION The City of Tulsa, OK engaged Tetra Tech and WCS Engineering to evaluate, optimize and prioritize sanitary sewer overflow remedial alternatives for the Northslope collection system. The Northslope sanitary sewer collection system and treatment facility provide service to the northern portion of Tulsa. This current system has over 950 miles of pipe, 18 lift stations, 4 storage facilities, and an 85 MGD treatment facility. OBJECTIVE This presentation will provide municipalities with an example framework to prioritize capital investments using a best in practice approach to apply intelligent algorithm optimization. The case study maximizes return on investment with respect to scheduling capital improvements to reduce the frequency and severity of sanitary sewer overflows as early as possible. There are many factors to consider when prioritizing collection system capital improvement projects. Selecting the implementation sequence that maximizes overflow volume reduction is one factor to consider; however, there may be value delivered to a greater number of customers if an investment is made that reduces several overflows in close proximity to houses rather than reducing a large, centralized overflow away from direct customer exposure. In this case study, these factors are considered when prioritizing capital projects to maximize return on investment. SIGNIFICANCE This presentation will provide the following benefits to the audience and industry: - Demonstrate how formal optimization software can be applied to prioritize large and complex capital programs including conveyance projects, storage facilities, inflow and infiltration remediation, and treatment plant upgrades. - Illustrate how approximately 82% of SSOs can be eliminated within the first 27% of capital expenditure in the case study example. - Provide a framework for other cities to optimize and prioritize SSO remedial measure plans. METHODOLOGY Optimization The Tulsa Optimization evaluated conveyance, storage, I/I remediation, and treatment alternatives to abate SSOs for different levels of service. To enable an exhaustive and objective evaluation of all feasible improvement alternatives, the optimization analysis was undertaken using Optimizer (product of Optimatics). The raw output from Optimizer was linked to customized post-processing tools to automatically generate ArcGIS maps and detailed solution summaries. Optimization runs were completed for a wide range of scenarios to demonstrate key trends and differences between strategies for different levels of service and with different combinations of alternatives. Additionally, a broad range of sensitivity analyses were completed to provide confidence in the recommended strategy. The variety of scenarios optimized provides valuable insights into potential treatment and collection system improvement strategies to mitigate system capacity deficiencies. The results from each scenario help to identify key trends and illustrate solution components that are consistent in each scenario and other solution components that are sensitive to key assumptions. The City can thereby make a more informed decision in determining a preferred solution based on the robust set of scenarios, anticipated costs and levels of service presented. Prioritization The objective of the prioritization was to determine the sequence of project implementation that would maximize return on investment with respect to scheduling capital improvements to reduce the frequency and severity of sanitary sewer overflows (SSOs) as early as possible. Multi-objective optimization analysis was applied using Optimizer WCS to evaluate thousands of implementation schedule alternatives to determine the Pareto front of capital projects that maximize return on investment. Return on investment was quantified based on reduction in the number and volume of modelled overflows. The following weightings were included in the prioritization: - Modelled overflows that were correlated with observed SSOs were defined as 'confirmed' and were weighted by a factor of five in the prioritization relative to unconfirmed modelled overflows. If an SSO was reported on more than one occasion, then any modelled overflows corelated to that location were weighted by a factor of ten. This had the effect of the prioritization targeting investment into projects that address confirmed SSOs earlier in the program than unconfirmed modelled overflows. - A non-worsening penalty was applied to avoid the prioritization shifting overflow issues downstream. Any instance where the overflow/freeboard violation becomes worse than the current value a weighting factor of ten was applied. This had the effect of the prioritization ensuring either the downstream system has sufficient capacity prior to an upstream conveyance improvement being implemented, or that conveyance upgrades were balanced with rehabilitation projects to avoid impacting the downstream system. RESULTS Optimization Optimization runs were completed for multiple scenarios to determine the cost savings as each improvement type was implemented. Sensitivity analysis was performed on certain scenarios to assess the impact of new storage facilities and potential investment by the City into a private I/I program. Improved utilization of existing storage facilities requires significant increases to the influent lift stations. Expensive lift station upgrades can be avoided by including new below-grade storage facilities that have gravity inflow and pumped dewatering to avoid large influent lift station sizes. The cost savings that may be achieved by including strategically located new storage facilities is on the order of $175 M (16%). I/I reduction presents a significant opportunity to reduce the overall cost of the master plan by eliminating or reducing the size of projects that are otherwise required. The cost savings associated with the selected public sector I/I rehabilitation program are on the order of $454 M (29%). Prioritization The prioritization results show the sequence of CIP project implementation based on highest return on investment with respect to modeled hydraulic performance. There may be other considerations outside the scope of the cost/hydraulic-based prioritization that influence the sequence of implementation; thus, the results from this analysis are intended to be used as a guide only. Consideration of road surfacing programs, combining relief sewer projects that are in proximity of each other, and allowing for detailed planning and design are factors that should be considered when refining the schedule of improvements. The prioritization results show projects that achieve a relatively high return on investment in Priority 1, 2, and 3 with an 82% improvement in weighted SSO reduction within the first 27% of the total capital expenditure. A 95% improvement in weighted SSO reduction is achieved within 43% of the total capital expenditure by Priority 4 projects. CONCLUSIONS The Tulsa optimization and subsequent prioritization analysis delivered the following outcomes for the City: - Supports the City's Planning efforts to identify the immediate CIP for the next five years due to budgetary constraints. - Minimizes capital and life-cycle costs required to achieve SSO compliance. - Prioritizes the investment schedule to maximize the reduction in overflows at each stage of capital investment. - Enables the City to tackle manageable pieces of the overall solution. - Provides a framework and strategy to assess improvement efforts on a continuous basis.

This paper was presented at the WEF Collection Systems Conference in Detroit, Michigan, April 19-22.

SpeakerGarcia, David

Presentation time

9:00:00

9:30:00

Session time

8:30:00

10:00:00

Session number5

Session locationHuntington Place, Detroit, Michigan

Topicartificial intelligence, Capital Expenditures, Prioritization

Author(s)