A model-based framework to prevent excavator induced damage in operations on natural gas pipelines
Source abstract
Abstract
Despite the presence of numerous safety precautions, the primary cause of damage to underground pipes is often attributed to external interference from excavators during their operations. To address this issue, this paper introduces a model-based approach that incorporates both static and dynamic contact in assessing the damage caused by excavators on pipes. The objective of this method is to offer a practical tool that can assist in determining the appropriate excavator size for buried gas pipes. By identifying the maximum safe excavator size, the aim is to minimize the potential risks of mechanical damage to the pipe, to prevent hazards for operators and to protect the integrity of the pipeline. For this purpose, a comprehensive excavator model is constructed. Following this, a suitable damage model for the pipe is selected and the interaction between the bucket tooth and the pipe is modelled. To enhance accuracy, the excavator and pipe are interconnected through the solution of damped contact equations, which take into account the stiffnesses of both the pipe and excavator, as well as the damping effect resulting from pipe deformation. Results provide valuable insight into the potential damage caused to the pipe, which can be attributed to either static or dynamic contacts, depending on which excavator is being used. Failure is addressed by plastic dent, that can be avoided by selecting the most suitable excavator size. Moreover, the analysis of dent depth caused by various excavators on different pipes for gas transmission, opens to the possibility of mitigating the risk of failures by limiting the excavator workspace.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Engineering Diagnostics and Reliability · Material Properties and Failure Mechanisms · Structural Integrity and Reliability Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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