The purpose of this study was to perform an analysis of accidents with new risk analysis methods to determine if they might be of value to the Office of Hazardous Materials Transportation in the management of hazardous materials transportation risks.
The first specific objective of the study was to develop one or more models displaying interacting events in accidents and near misses involving Class A explosives in highway truckload and rail carload transportation, to assess the type and degree of risks that might be encountered in such transportation.
Using the models, the next objective was to identify problem areas that exist, evaluate the adequacy of DOT's hazardous materials regulations governing Class A explosives, and propose countermeasures for potential rule making activities.
The final task was to report the findings.
Findings and conclusions
Events reported in 10 accident cases were modeled using multilinear events sequencing-based analytic methods. The modeling suggested several candidate areas for action that would result in reduced risks. One clear candidate is a redefinition of tasks that surviving truck drivers might be asked to do between the time a collision occurs or a fire begins, and the time when the fire results in explosion of the driver's cargo. Another is to try to better understand why explosives burned rather than detonated in some of the accidents. In both examples, the models showed clearly the accident process might be controlled with new options.
Two fire and explosions risks were assigned RAC 1 (highest) values, using a widely recognized risk assessment coding protocol. A third risk was assigned a RAC 3 (moderate) value. Using the models, the effectiveness of regulations and guidance with respect to the RAC 1 and RAC 3 risk models was analyzed and judged adequate or not adequate, resulting in identification of several areas where change might be introduced to reduce risks.
The demonstration analysis also showed that currently available accident data do not focus on higher risks, or provide sufficient information for comprehensive evaluation of the effectiveness of hazardous materials safety regulations and guidance materials.
Recommendations.
Recommendations are made to
1. adopt a risk assessment coding method to help establish priorities for allocation of limited resources to reduce the most significant Class A explosives transportation risks,
2. develop the best possible understanding of the highest level risks in Class A explosives transportation from past accidents by additional inquiries and analyses,
3. develop specific regulatory or guidance action in two promising areas identified by the analysis, and
4. take a lead role in efforts to capture needed new data about Class A explosives transportation risks from incidents or accidents that occur in the future,
CHAPTER 1. BACKGROUND
1.1. Purpose and objectives.
The purpose of this study was to perform an analysis of accidents with new risk analysis methods to determine if they might be of value to the Office of Hazardous Materials Transportation in the management of hazardous materials transportation risks.
The first specific objective of the study was to develop one or more models displaying interacting events in accidents and near misses involving Class A explosives in highway truckload and rail carload transportation, to assess the type and degree of risks that might be encountered in such transportation.
Using the models, the next objective was to identify problem areas that exist, evaluate the adequacy of DOT's hazardous materials regulations governing Class A explosives, and propose countermeasures for potential rule making activities.
The final task was to report the findings.
1.2. Introduction
The transportation of Class A explosives by motor carrier and railroad has been accompanied by a small number of accidents. Class A explosives are hazardous materials. When accidents involving Class A explosives occur, they have the potential to produce substantial losses. Thus, this type of hazardous materials transportation falls into the low-frequency, large consequences category of risk. By several popular risk assessment models, such as the Risk Assessment Coding (RAC) scheme of the Department of Defense (DOD), the risks would be rated "high" because of these characteristics. For example, a risk with a low probability but with the potentially lethal consequences of a truckload of carload or explosives would be rated a RAC 1 risk, and be treated accordingly for control purposes.
In non-transportation environments, Class A explosives risks are controlled by established requirements, of which quantity/distance (QD) tables are considered among the most important. QD tables specify the nearest distance where exposures may be located relative to specified quantities of stored explosives. These QD tables are based on the estimated probabilities of harm that would be produced by explosion of specified quantities. These estimates are based on the specific explosive's explosive equivalency compared to trinitrotoluene (TNT).
In transportation, other controls are relied on to achieve acceptable risk levels for Class A explosives. These controls presently include a wide range of regulated actions, such as assuring their proper condition and preparation for transportation; their proper classification, packaging, marking and labeling or placarding; transport vehicle specifications; operator requirements and emergency notification requirements, among others.
Since accidents involving Class A explosives involving fires occur infrequently and differ in many details, they do not provide a basis for traditional statistical analyses for that reason. Experimentation on the scale required to produce persuasive results appears infeasible. This research was undertaken to determine whether a new analysis methodology might prove helpful for determining the risks involved, for assessing the effectiveness of present controls in those accidents, and for identifying possible regulatory options that might be proposed. One such recent development is a method based on arraying specially structured event data into simultaneous timed event plots (STEP) showing the interactions among events constituting the accident process. (See Reference 1) The displayed events are then tested by pairing events into sets, and testing the logic flow and relationships with sequential logic testing techniques to establish relevance and completeness. The events sets can then be analyzed to define problem relationships and possible corrective actions.
1.3. Accidents analyzed
Eight highway and two railroad accidents during Class A explosives transportation, about which accident data could be acquired, with the assistance of the OHMR, were selected and analyzed in this way. The accidents selected occurred between 1971 and 1987. A few other lesser mishaps were known to have occurred, but few involved fire, and none of the others involved explosion of the Class A being transported. A few other explosions involved other classes of hazardous materials, some of which involved detonations, but these were excluded from the study. Accidents occurring before about 1970 were considered to involve obsolete transportation and explosives technology and were excluded for that reason. The highway loads involved various size vehicles, so truckload was construed liberally to include dedicated movements in a truck, and mixed loads including Class A explosives.
1.4. Investigation process.
The first step in the investigation process was to transform the surviving information about past accidents into a format suitable for use by the STEP process, called "event building blocks". Several qualifying criteria for data used for this task were used. To qualify for use data had to:
o have occurred during the time the accident process was occurring, rather than during previous operations or activities.
o be convertible into a specific action by a specific "actor" (person or thing)
o the action, when finally documented, had to have initiated a change in state that led to one or more subsequent events (specific actors doing some specific action)
o be visualizable, as in a "mental movie" of the actors and their actions during the accident process
As the data were acquired from the narrative and summary data reports, the event building blocks were arrayed on a worksheet, using a list of "actors" whose actions determined the subsequent events that followed during the accident process. One worksheet was prepared from the data available to us for each accident.
The arrayed events were then tested using an event linking technique by which events pairs meeting sequential logic test criteria were linked with precede/follow arrows. Additionally a necessary and sufficient logic test was applied to each event pair on the worksheet to ensure that all necessary events for the process to flow to a conclusions were present, and that no more than sufficient for that to occur were used. Gaps where insufficiencies existed after these tests were noted with a "?".
A technique applied for the first time in this work was a STEP worksheet overlay technique, to ascertain whether known events during one accident might be used to indicate events during another accident, or to build a general model of the accident that might prove useful for predictive purposes.
After the worksheets were completed, a second analysis of the events pairs was undertaken to identify and define the problems indicated by the model. The general approach was to take each event pair, ask why one led to or followed from another, hypothesize possible changes that might be introduced into those relationships, and - using the model - predict what effects these changes might make in the final risk levels.
After the events set analyses were completed, risk assessment codes (RACs) selected from a possible range of 1 (high) to 5 (low) were assigned to the accident risks, and judgments of need prepared from the analyses. Based on observations during the analyses, conclusions and recommended actions were reported.
1.5. Findings
The main findings, in addition to specific points indicated in the analysis sections, include:
Two types of Class A transportation accident risks pose RAC 1 (high) risks
Judgments of needs for regulatory attention are summarized from the analyses
The present 5800 reporting system does not provide the incident information needed to evaluate the full range of Class A explosives transportation safety regulations.
The work produced in this study can be used to guide the development of information for future assessments of the regulations.
Recommendations are made to
1. adopt a risk assessment coding method to help establish priorities for allocation of limited resources to reduce the most significant Class A explosives transportation risks,
2. develop the best possible understanding of the highest level risks in Class A explosives transportation from past accidents by additional inquiries and analyses,
3. develop specific regulatory or guidance action in two promising areas identified by the analysis, and
4. take a lead role in efforts to capture needed new data about Class A explosives transportation risks from incidents or accidents that occur in the future,
Go to Section B: Data and Analysis, Truck Accident Analyses
- - - - - -Last updated on Sun, Jul 29, 2012