A CAST-based causal analysis of the catastrophic underground pipeline gas explosion in Taiwan

https://doi.org/10.1016/j.engfailanal.2019.104343Get rights and content

Highlights

  • The study originally adopts the CAST model to pipeline gas transportation industry.

  • The causes of the pipeline gas explosion in Taiwan are analyzed based on CAST.

  • The safety control structure to enforce the safety constraints is developed.

  • The safety control structure is analyzed hierarchically.

  • The CAST model is feasible for continuous improvements in safety management.

Abstract

A deep and thorough analysis of typical accidents beyond immediate failures from a systematic perspective is necessary for safety decision-making in an area. The Systems-Theoretic Accident Model and Processes (STAMP) is one of the most widely used accident models based on systems and control theory, which derives a powerful accident analysis tool defined as Causal Analysis based on Systems Theory (CAST). This study adopts a CAST analysis of the catastrophic underground pipeline gas explosion in Taiwan, which is one of the largest petroleum catastrophes in Chinese history. The safety control structure to enforce the safety constraints required by the system hazards is developed and analyzed hierarchically. The analysis has systematically demonstrated the inadequate control and violated safety constraints and uncovered the in-depth rationale behind the decisions that were made leading up to this tragedy. The necessary changes in the overall system safety structure are also recommended based on control flaws identified for each hierarchical level, accordingly. The CAST model is demonstrated to be feasible for continuous improvements in accident analysis and in turn establishing a robust safety system of pipeline gas transportation in Taiwan.

Introduction

With the growing demand for fuel gas in urban living and industry, urban gas pipelines develop rapidly in recent years [1], [2], which may lead to potential safety hazards and risks [3], [4]. In the urban context with dense population, buildings and wealth, a minor disruption of gas pipeline may escalate to catastrophic events, such as fire and explosion, and result in numerous fatalities, casualties and property losses [5], [6]. Pipeline gas transportation, especially in urban areas, has been referred as a high-risk process industry, where various failures could bring out unexpected interactions which would cause the collapse of a safety system [7]. According to our statistics, in China, a total of 195 underground pipeline gas accidents were reported online from 1/01/2014 to 31/12/2018, of which some typical ones are shown in Table 1. Although most of them are minor accidents, the tremendous loss of life and property caused by any of the catastrophic ones are unacceptable for our country. For example, on 31 July 2014, a rupture caused by constant corrosion of a gas pipeline triggered a series of explosions in a busy road of Kaohsiung, Taiwan, which resulted in 32 deaths and 321 injuries, making this disaster one of the most tragic petroleum catastrophes in Chinese history [8], [9]. It is imperative to prevent potential pipeline gas accidents by conducting reliable accident analysis and taking effective accident prevention measures [10].

In recent years, underground pipeline gas accidents keep occurring that seem preventable and have similar systemic causes, and we do not seem to make much progress in reducing accidents lately (see Fig. 1), which sound alarm bells for us to think deeply on why traditional approaches to learn from events do not work well [11]. In the pipeline gas transportation industry, the accident prevention strategies mainly rely on risk assessment using traditional event-based accident models [10], [12], which are not sufficient for explaining accidents related to the complex socio-technical system [13]. An argument has been made that sophisticated accident models based on systems theory provide us an opportunity to conduct more powerful accident causation analysis and help engineers to learn about the factors involved [11]. Several accident causation models on basis of systems theory have been developed, including System hazard identification, prediction and prevention (SHIPP) methodology [14], Functional Resonance Analysis Method (FRAM) [15], and AcciMap [16], among which the Systems-Theoretic Accident Model and Processes (STAMP) [17] is one of the most widely used models based on systems and control theory.

There are several studies have compared several other systems-based approaches with STAMP. For example, Salmon et al. [18] pointed out that STAMP is with high comprehensiveness and has distinctive features for identifying the context of decision-making and mental model flaws. Underwood and Waterson [19] reported that STAMP incorporates explicit description of system structure, behavior and components relationships. However, these studies also pointed out that the implementation of STAMP is challenging. Therefore, more applications of STAMP in various area are needed for practitioners adopt it easily.

The STAMP derives a powerful accident analysis tool defined as Causal Analysis based on Systems Theory (CAST), which provides a new model of causality for analyzing and designing against accidents, especially in those complex socio-technical systems [17]. This model has shown great superiority on accident analysis in various fields including aerospace engineering [20], crude oil processing [21], maritime transportation [22], coal mining [23], and so on. These studies show that CAST prevails traditional accident models by accounting for human error, organizational factors, and adaptation to change over time, which enables CAST to reveal more potential hazards and failures [11].

However, to the authors’ knowledge, systematic analysis of pipeline gas accidents using CAST has not been reported. To meet this need, this paper conducted a CAST-based accident analysis to illustrate the applicability of CAST approach to analyze pipeline gas accidents by taking the pipeline gas explosions occurred in Taiwan on 31 July 2014 as an example. The safety control structure to enforce the safety constraints required by the system hazards is developed and analyzed hierarchically, to dig up systematic causes contributed to the tragedy and take precautions against similar accidents in the future. Besides, learning from the accident with this insight can be in turn applied to safety design during the system development.

Section snippets

STAMP/CAST methodology

Tradition view of safety have treated operator error as activities of critical importance for investigation of accidents, which confuses safety with reliability and has been criticized by many researchers [14], [22]. For safety analysis of complex socio-technical systems, it is necessary to consider how components interact with each other on basis of system theory [24]. To meet this challenge, a new accident causation model based on systems and control theory referred to as STAMP [17] was

Proximate events in the accident

On 31 July 2014, constant corrosion result in leakage of a 4″ propylene pipe, belonging to LCY Chemical Corp. (LCY), and the gas spread through the sewer system, which ultimately led to a series of large underground explosions along Kaisyuan Road in a busy district of Kaohsiung. As shown in Fig. 3, the blasts split the roads in two and overturned cars and trucks. The fireballs soared into the sky, and flames reached 15 stories high. Unfortunately, this catastrophic accident caused 32 deaths and

Conclusions

With the rapid development of gas pipeline network, the resulting potential safety hazards to the public are receiving more and more attention, especially after the Taiwan tragedy. This accident provides an important lesson for the gas transportation industry. It highlights the need for taking a systems approach to the identification of inadequate control and violated safety constraints and calls for effective actions to prevent similar accidents in the future.

In this study, the adopted CAST

Declaration of Competing Interest

All authors declare that no commercial or associative interest from any organization that may represent a conflict of interest in connection with the work submitted. And there are no other relationships or activities that could appear to have influenced the submitted work.

Acknowledgement

This work was sponsored by National Natural Science Foundation of China (NSFC 51874063, 51304259 and 51254001), China Scholarship Council, and Chongqing Science and Technology Commission (CSTC2017jcyjBX0011). The authors appreciate for editors’ and reviewers’ valuable comments and hard work concerning our manuscript. Also, the authors are grateful for the support from Ba-yu Program for the Talents from Overseas by Chongqing Municipal Education Committee, the Canada Research Chairs (Tier I)

References (25)

Cited by (0)

View full text