Name: Chirag Agrawal (Visiting Scholar IITK-VT 2015) Supervisor: Dr. Sunil Sinha (Virginia Tech)

Transcription

1 Name: Chirag Agrawal (Visiting Scholar IITK-VT 2015) Supervisor: Dr. Sunil Sinha (Virginia Tech)

2 Infrastructure Asset Management: Meeting a required level of service in the most cost-effective way through the creation, acquisition, operation, maintenance, rehabilitation, and disposal of assets to provide for present and future customers. Risk Assessment: Risk assessment forms an integral part of Asset Management and is defined as process to identify potential hazards and analyze what could happen if hazard occurs. It is calculated as: Risk = Likelihood of Failure (LOF) x Consequences of Failure (COF) (Likelihood of Failure Probability of occurrence of any event/failure) (Consequences of Failure s/effects of that event/failure) Infrastructure Asset Management Risk Assessment Likelihood of Failure (LOF) Consequences of Failure (COF)

3 A community, water or wastewater utility should care about managing its assets in a cost effective manner for several reason: These type of assets represent major public investment Well-run infrastructure in necessary for economic development Proper operation & maintenance is essential for public health & safety Utility assets provide an essential customer service Asset Mng. promotes efficiency and innovation in operating system

4 Very rudimentary research has been done on this topic. Most of them revolve around the Likelihood of Failure part of Risk Assessment. Some parameters have been developed previously but none of them incorporates all the dimensions of consequences. Only a list of parameters has been mentioned without giving detailed explanation.

5 Objective: To develop a weighted COF index Goals: To develop as comprehensive and exhaustive list of parameters as possible on basis of which COF can be assessed & to give legitimate reasoning for their inclusion in the list. To give proper units to each parameter. To categorize them into different ranges (qualitatively or quantitatively). To give weightages as per their relative importance in assessing COF, based on which, weighted average will be calculated to arrive at the final value of COF. Based on this COF, utilities can prioritize their action/management plan to avoid the catastrophic effects of failure of these pipes

6 1. Develop a list of parameters along with units and ranges. 2. Categories of each parameter will be given a score from 1-5 (least-to-most on basis of their intensity) and each parameter will be given weight. 3. This list will be mailed to various water utilities to know their perspective on developed parameters, ranges and their units along with scores & weights. 4. Data will be collected from these utilities. 5. Based on this data, final COF score will be calculated using Indexing Model (weighted average).

7 Extensive literature review, practice review and various failure reports were studied and understood. Engineering judgement/knowledge was also used in developing these parameters Inputs from various water utilities will also be taken before finalizing the list of parameters.

8 Economic Environmental Cost of Renewal on Protection / Conservation Zones Cost to Property Damage on Surface Water and/or surroundings Social on Customers Length of Time Out of Service Legal Issues Potential Landslides Traffics Flow Cost of Lost Water Pipe Characteristics Function of Pipe Depth of Pipe Size of Pipe Renewal Complexity Access to Pipe Ground Cover Utility Density Others Infiltration Age of Pipe Utility Pattern Others Fire Flow Pipe Material Types of Utility Others Pipe Class Average Daily Traffic Proximity to Assets/Property Flow Rate Others Quality of Utility Records Availability of Repair Materials Others Highlighted parameters are exclusive to Water

9 Economic Environmental Cost of Renewal on Protection / Conservation Zones Cost to Property Damage on Surface Water and/or surroundings Social on Customers Length of Time Out of Service Legal Issues Toxicity in Wastewaster Traffics Flow Pipe Characteristics Function of Pipe Depth of Pipe Size of Pipe Renewal Complexity Access to Pipe Ground Cover Utility Density Others Others Others Age of Pipe Utility Pattern Pipe Material Pipe Class Proximity to Assets/Property Flow Rate Others Types of Utility Average Daily Traffics Quality of Utility Records Availability of Repair Materials Contaminated Soil Others Highlighted parameters are exclusive to Wastewater

10 All the parameters listed are categorized into different ranges and also each parameter are given a unit along with a score. For example, Scores Cost of Repair ($) Time (hours) Size of Pipe (inches) 1 Very Low (< 5,000) Very Short Term (< 1 hours) < 6 inches 2 Low (5,000-50,000) Short Term (1-6 hours) 6-18 inches 3 Medium (50, ,000) Medium (6-24 hours) inches 4 High (500,000-1,000,000) Long Term (24-48 hours) inches 5 Very High (> 1,000,000) Very Long Term (> 48 hours) > 48 inches

11 Work Accomplished: 1. Most of the time was used in developing the parameters. 2. The logic/explanation behind inclusion of every parameter in the list is well understood. 3. Ranges to each parameter are also given mainly based on previous failure data and engineering knowledge. Work Remaining: 1. Develop similar kind of list for Stormwater Pipes also so as to complete the holistic study of all kind water pipe infrastructure. 2. Reaching out to water utilities (both US and Indian) and data collection has to be started as soon as possible as it is the most time consuming task. 3. After data has been collected, it has to be analyzed, calculations need to be carried out and based on the results, conclusion are to be drawn.

12 Asset Management Guide, A Guide for Water and Wastewater Systems, (2006 Edition). Boston Water and Sewer Commission (BWSC) Report, Risk Assessment Methodology, (2015): Section 9. Hicks J, Roche D, Lynch D, Bendeli M., Collaboratively Aligning the Risk-Based Asset Management of Pressure Water Pipelines in the Australian Urban Water Sector. Sekar V.R., Web-Based and Geospatially Enabled Tool for Water and Wastewater Pipeline Infrastructure Risk Management, (2011). Sinha S.K., Angkasuwansiri T., Thomasson R., Development of Standard Data Structure to Support Wastewater Pipe Condition & Performance Prediction (Phase 1), (2008)

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