Implementation of the DER rating system within a power generation environment
Bibliographic record
Abstract
The main purpose of this research study is to test the applicability of the DER (Degree of defect, Extent and Relevancy of defect) rating system, used for road network infrastructures, to the support structures of a dry cooling tower in a power generation environment. The DER is a defect-based rating system developed locally by the Built Environment Division of the Council for Scientific and Industrial Research (CSIR) in Pretoria, South Africa. This study involved a visual inspection and the rating and analysis of defects of reinforced concrete (RC) structures in an Eskom power generation plant located in Grootvlei in Mpumalanga Province. Visual inspection and condition rating systems form part of an Asset Management System (AMS) that is used to ensure a safe operation and the economic benefit of the structure throughout its life cycle. For that reason, various organisations and roads authorities have developed condition-rating systems similar to the DER for visual assessment of their road network structures using a Bridge Management System (BMS) as a vehicle to achieve their operation and maintenance objectives. Other condition-rating systems have been identified and their applicability to structures in a power generation environment as compared to that of the DER was also tested. These condition-rating systems are: 1) The Overall Structural Condition Index (OSCI) - proposed by the Australasian Transport Research Forum (ATRF) for bridge condition assessment and prioritisation of maintenance activities and budget allocation. 2) The National Bridge Inspection Standard (NBIS) which establishes a uniform program for all state departments of transportation in the USA to regulate the minimum requirements for inspection types and procedures, inspection intervals, inspector qualifications, and inventory reporting, and 3) The Ontario Structure Inspection Manual (OSIM) which sets standards and provides uniform approaches for visual and detailed inspections and condition evaluation for all types of bridge structures in Ontario, Canada. Comparative rating analyses of the defects of the same RC structure in a power generation environment was conducted in order to establish the applicability of the DER in comparison with the other rating systems. The use of the DER, amongst other selected condition rating systems, was recommended with the suggestion that further improvement be undertaken so as to extend its usage within a power generation environment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".