Integrated Asset Management Framework and Model for Water Distribution Networks
Bibliographic record
Abstract
The Canadian Infrastructure Report Card (2012) estimates the replacement value of water assets to be $362 billion. Water distribution and wastewater collection networks have been in service for more than a century in the majority of the cities in Canada. Although “out of sight” infrastructure might often be “out of mind”, the functionality of these city arteries greatly influences public health. Lack of effective maintenance and proactive renewal plans increase the incurred costs of water infrastructure systems drastically until affordable water fees cannot cover them. The Sustainable Water and Sewage System Act (MEO, 2002) followed by the Water Opportunities and Water Conservation Act (MEO, 2010), both encourage public utilities to develop financially sustainable plans for water and wastewater systems. In addition, both Ontario Regulation 453/07 (MEO, 2007) and Public Sector Accounting Board (PSAB) Statement 3150 (CICA, 2007) require all public water utilities to prepare annual reports on the current and the future condition of their in-service assets. Managing aging water infrastructure systems with limited financial resources requires comprehensive asset management plans that help decision-makers minimize the total life-cycle cost of their assets while enhancing levels of service. A viable asset management plan should incorporate a Strategic plan (10+year), to set the policies and strategies; Tactical plan (2-10 years), to develop capital programs; and Operational plan (1-2 years), to establish capital projects. Effective dynamic communication among planning levels is critical to share and exchange information and, thus, promote alignment of their respective objectives. \nThis research develops an Integrated Water Infrastructure Asset Management (IWIAM) model comprised of strategic, tactical and operational plans to (1) align corresponding objectives; (2) share and exchange their information; and (3) optimize the allocation of financial resources. \nA novel hybrid Agent-Based and System Dynamics (AB-SD) modelling approach is employed to develop an IWIAM for water distribution networks. The SD and AB models are used to understand the complex dynamic behaviour of water infrastructure systems for network-level (i.e., strategic) and component-level (i.e., tactical-operational), respectively. A four-step Plan-Do-Check-Adjust (PDCA) iterative management process, along with an integrated Water Infrastructure Database (WIDB) is utilized to provide effective interaction and communication among all three planning levels. The research applies a bi-level heuristic optimization algorithm to find optimal solutions to group renewal activities in the development of capital programs. \nThe proposed research makes several noteworthy contributions to the body of knowledge for water distribution networks: \n(1) The development of an integrated decision-support system using Agent-Based and System Dynamics methods to aid water decision-makers in asset management planning; \n(2) The development of a platform for interactions between the network- and component-levels to align network-centric with component-centric decisions; \n(3) The development of an optimization model to select, group, and schedule optimal R&R activities; \n(4) the development of a bi-level heuristic optimization algorithm to find optimal solutions for group scheduling of capital works.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".