Validation of the recommended distances and assessment of emergency response guidance for boiling liquid expanding vapour explosion (BLEVE) behaviour in the Emergency Response Guidebook (ERG) using updated modelling techniques

Department of Transport (TC)
canadabuys Posted: July 17, 2026

WHAT: Contractor to conduct a comprehensive search and technical review of existing BLEVE hazard modelling approaches, propose a data-driven modelling approach, develop an open-source predictive model in Python, and compare predicted hazard distances against current ERG BLEVE guidance. BUYER: Depart...

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Due Date
August 17, 2026
(6 days left)
Solicitation #
T8080-260061

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Documents

rfp-t8080-260061.pdf
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amendment-1_t8080-260061.pdf
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Description

Transport Canada’s Transportation of Dangerous Goods (TDG) Program is undertaking a project to validate the current distances in the BLEVE table found in the Emergency Response Guidebook (ERG) for BLEVEs involving propane, or more generally liquefied petroleum gases (LPG), to support the work of the Canadian Transport Emergency Centre (CANUTEC), part of Transport Canada’s (TC) Multimodal Security and Emergency Management Directorate. CANUTEC is a national advisory service that assists emergency response personnel in handling dangerous goods emergencies, 24 hours per day, 7 days a week. The ERG is produced by TC, the US Department of Transportation (DOT), and the Secretariat of Infrastructure, Communications and Transport of Mexico (SICT),[Z(1.1][JP1.2] with help from the Centro de Informaciòn Quìmica para Emergencias (CIQUIME) of Argentina. The ERG is available in English, French, and Spanish, in various formats, on the CANUTEC website. (Information about the ERG, including the most up-to-date PDF versions for download, can be found here: https://tc.canada.ca/en/dangerous-goods/canutec/emergency-response-guidebook). The ERG, published every four years, is primarily a guide to aid first responders in quickly identifying the specific or generic hazards of the product(s) involved in a dangerous goods transportation incident, and in protecting themselves and the public during the initial phase of the response. The guidebook contains emergency guides (orange section) with emergency recommendations addressing products that share certain physical and chemical properties. Each UN number included in the Transportation of Dangerous Goods Regulations (TDGR) at the time of publication of the ERG is accounted for. The emergency actions in the ERG are updated periodically to account for changes in the TDG landscape, such as changes to means of containment that may change the likelihood of a release or failure, or new scientific knowledge that may change the assessment that applies for a particular substance. One important feature of the ERG is the BLEVE table, which details recommended distances for various sizes of means of containment with potential for a BLEVE event involving propane and, more generally, liquefied petroleum gases (LPG). A BLEVE is defined as an event where a container holding a pressure-liquefied gas fails catastrophically followed by the explosive release of boiling liquid and expanding vapour. The BLEVE is a physical explosion where the hazards include blast and projectiles. If the commodity is flammable, then a fireball and thermal radiation may also result, if the released cloud is immediately ignited. This is usually the case if the container failure is caused by fire impingement. The current distances in the ERG BLEVE table are based on the projectile distance and the fireball radius for a given amount of propane and have been generalized more broadly for LPG. The distances prescribed in the ERG for large means of containment were determined by extrapolation using models validated by physical testing on small means of containment, in research conducted by Birk et al. in 1995 for TC [AP2.1]. [AC3.1][Z(3.2][JP3.3]Reports from previous BLEVEs, however, demonstrate that the current distances prescribed in the ERG are not always adequate to protect from the hazards of a BLEVE. Given that the original research behind these recommended safety distances was completed several decades ago, there is interest in exploring whether updates can be made to the guidance using newer technologies that may not have been as developed at the time of the original experiments on which the BLEVE-related distances were established, to generate improved models. To validate the distances in the BLEVE table in the ERG, the TDG Program requires the services of a contractor to perform a search and review of previous work related to BLEVE modelling of related hazards (e.g., fireball, thermal radiation, blast overpressure, projectiles) and propose an optimized data-driven modelling approach based on state of the art technologies to more accurately predict BLEVE hazard ranges and protective action distances. To achieve this objective, the contractor must: 5. Conduct a comprehensive search and technical review of existing BLEVE hazard modelling approaches, from physics-based and empirical methods to modern data-driven and machine learning techniques. The review must evaluate the underlying assumptions, required inputs, computational feasibility, and validation status for propane and other liquefied petroleum gases (LPG) for each modelling approach identified. 6. Identify, define, and document all variables and datasets necessary to model BLEVE hazards (e.g., fireball, thermal radiation, blast overpressure, and projectiles, at a minimum), and develop a detailed data dictionary and data management and quality assurance strategy to ensure traceability, consistency, and defensibility of results. 7. Propose and justify a modelling architecture that optimizes predictive capability for BLEVE hazard distances using state-of-the-art technologies, and that includes a structured methodology for model refinement, including, at a minimum, training, validation, and uncertainty-quantification. 8. Develop an open-source predictive model in Python that: • Incorporates elements from identified modelling techniques, as appropriate, for improved performance and is validated against available historical BLEVE testing and incident data, and • outputs protective action distance predictions in a form suitable for ERG-related decision-making. 6. Compare the model’s predicted hazard distances against the current ERG BLEVE guidance and provide an assessment of performance improvements, limitations, and readiness for potential operational consideration.

Additional Information

Amendment Number

001

Contact Info Address Line

330 Sparks Street

Contact Info City

Ottawa

Contact Country

Canada

Contact Info Email

Contact Info Name

Natasha Blackstein

Contact Info Postal Code

K1A 0N5

Contact Info Province

Ontario

Contracting Entity Name

Department of Transport (TC)

Created

August 11, 2026

Is Public

true

Organization Address City

Ottawa

Organization Country

Canada

Organization Address Line

300 Sparks Street

Organization Address Postal Code

K1A ON5

Organization Address Province

Ontario

Procurement Category

*SRV

Procurement Method

Competitive - Open bidding

Reference Number

cb-70-85451497

Regions Of Delivery

*Canada

Regions Of Opportunity

*Canada

Selection Criteria

Highest Combined Rating of Technical Merit and Price

Source

canadabuys

Source Record ID

cb-70-85451497_001

Source System

canadabuys

Status

open

Status En

Open

Summary Updated At

August 11, 2026

Tender Closing Date

August 17, 2026

Last Updated

August 11, 2026

Frequently Asked Questions

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The proposal submission deadline is August 17, 2026 (6 days left).

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AI Summary

WHAT: Contractor to conduct a comprehensive search and technical review of existing BLEVE hazard modelling approaches, propose a data-driven modelling approach, develop an open-source predictive model in Python, and compare predicted hazard distances against current ERG BLEVE guidance.

BUYER: Department of Transport (TC), Ottawa, Ontario, Canada. Contact: Natasha Blackstein ([email protected]).

GEOGRAPHY: Canada.

DATES: Posted: 2026-07-17; Due: 2026-08-17.

INDUSTRY/DOMAIN: Risk or hazard assessment related to transportation of dangerous goods.

MANDATORY QUALS: Expertise in BLEVE modelling, data-driven and machine learning techniques, and experience in developing predictive models.

SPECS & CAPABILITIES: Must evaluate existing modelling approaches, document necessary variables and datasets, propose a modelling architecture, and ensure traceability and quality assurance of results.

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