A SYSTEMS RELIABILITY APPROACH TO MODELING OPERATIONAL RISKS IN COMPLEX ENGINEERED SYSTEMS
Bibliographic record
Abstract
Since the beginning of the industrial revolution in the late 18th century, the cause of many serious accidents in hydrosystems engineering has shifted from natural causes to human and technology related causes as these systems get more complex. While natural disasters still account for a significant amount of human and material losses, man-made disasters are responsible for an increasingly large portion of the toll, especially in the safety critical domain such as Dam and Levee systems. The reliable performance of hydraulic flow-control systems such as dams, reservoirs, levees etc. depends on the time-varying demands placed upon it by hydrology, operating rules, the interactions among subsystem components, the vagaries of operator interventions and natural disturbances. In the past, engineers have concerned themselves with understanding how the component parts of dam systems operate individually and not how the components interact with one another. Contemporary engineering practices do not address many common causes of accidents and failures, which are unforeseen combinations of usual conditions. In recent decades, the most likely causes of failures associated with dams have more often had to do with sensor and control systems, human agency, and inadequate maintenance than with extreme loads such as floods and earthquakes. This thesis presents a new approach, which combines simulation, engineering reliability modeling, and systems engineering. The new approach seeks to explore the possibilities inherent in taking a systems perspective to modeling the reliability of flow-control functions in hydrosystems engineering. Thus, taking into account the interconnections and dependencies between different components of the system, changes over time in their state as well as the influence upon the system of organizational limitations, human errors and external disturbances. The proposed framework attempts to consider all the physical and functional interrelationships between the parts of the dam and reservoir, and to combine the analysis of the parts in their functional and spatial interrelationships in a unified structure. The method attempts to bring together the systems aspects of engineering and operational concerns in a way that emphasizes their interactions. The argument made in this thesis is that systems reliability approach to analyzing operational risks—precisely because it treats systems interactions—cannot be based on the decomposition, linear methods of contemporary practice. These methods cannot logically capture the interactions and feedback of complex systems. The proposed systems approach relies on understanding and accurately characterizing the complex interrelationships among different elements within an engineered system. The modeling framework allows for analysis of how structural changes in one part of a system might affect the behavior of the system as a whole, or how the system responds to emergent geophysical processes. The implementation of the proposed approach is presented in the context of two case studies of US and Canadian water projects: Wolf Creek Dam in Kentucky and the Lower Mattagami River Project in Northern Ontario.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".