Translation of pipe inspection results into condition ratings using the fuzzy synthetic evaluation technique
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Bibliographic record
Abstract
Research Article| February 01 2006 Translation of pipe inspection results into condition ratings using the fuzzy synthetic evaluation technique Balvant Rajani; Balvant Rajani 1Institute for Research in Construction, National Research Council Canada (NRC), 1200 Montreal Road, Building, M-20Ottawa, ON Canada K1A 0R6, e-mail: yehuda.kleiner@nrc-cnrc.gc.ca; rehan.sadiq@nrc-cnrc.gc.ca Phone: 1-613-993-3810 Fax: 1-613-954-5984 E-mail: balvant.rajani@nrc-cnrc.gc.ca Search for other works by this author on: This Site PubMed Google Scholar Yehuda Kleiner; Yehuda Kleiner 1Institute for Research in Construction, National Research Council Canada (NRC), 1200 Montreal Road, Building, M-20Ottawa, ON Canada K1A 0R6, e-mail: yehuda.kleiner@nrc-cnrc.gc.ca; rehan.sadiq@nrc-cnrc.gc.ca Search for other works by this author on: This Site PubMed Google Scholar Rehan Sadiq Rehan Sadiq 1Institute for Research in Construction, National Research Council Canada (NRC), 1200 Montreal Road, Building, M-20Ottawa, ON Canada K1A 0R6, e-mail: yehuda.kleiner@nrc-cnrc.gc.ca; rehan.sadiq@nrc-cnrc.gc.ca Search for other works by this author on: This Site PubMed Google Scholar Journal of Water Supply: Research and Technology-Aqua (2006) 55 (1): 11–24. https://doi.org/10.2166/aqua.2005.069 Article history Received: August 23 2005 Accepted: November 03 2005 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Cite Icon Cite Permissions Search Site Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThis Journal Search Advanced Search Citation Balvant Rajani, Yehuda Kleiner, Rehan Sadiq; Translation of pipe inspection results into condition ratings using the fuzzy synthetic evaluation technique. Journal of Water Supply: Research and Technology-Aqua 1 February 2006; 55 (1): 11–24. doi: https://doi.org/10.2166/aqua.2005.069 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex An important step towards the assessment and management of failure risk in large-diameter (transmission) water mains is to observe distress indicators through scheduled inspections (using non-destructive or visual techniques) and translate these into condition ratings. Condition rating reflects an aggregate state of the pipe's health.Distress indicators are physical manifestations of the ageing process. The type (or form) and location of observed distress indicators in large-diameter mains are dependent on the pipe material and its surrounding environment. The physicochemical processes that promote ageing are often not understood well enough to merit an adequate physicochemical (based on mechanics or electrochemistry or microbiology) model. Further, the encoding of distress indicators into condition rating is inherently imprecise and involves subjective judgement. Fuzzy logic-based tools enable the use of engineering judgement, experience and scarce field data to translate the level of distress to condition ratings.This paper describes the translation of distress indicators detected by non-destructive or visual techniques into fuzzy condition ratings. Examples of distresses observed in prestressed cylinder concrete pipes (PCCP) and cast iron pipes are used to illustrate the proposed method. distress indicator, fuzzy condition ratings, large-diameter transmission mains This content is only available as a PDF. © National Research Council of Canada 2006 You do not currently have access to this content.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it