Hazardous Materials Transportation Research Articles

Incorporating Fairness Into the Gateway‐Based Risk Mitigation Policy for Hazmat Transport

ABSTRACTIn hazardous material transport on road networks, two conflicting objectives must be addressed simultaneously: minimizing risk and minimizing cost. Risk mitigation policies may yield as a secondary outcome uneven flow distribution on the network. This study empowers an existing risk mitigation policy based on gateways (GBP) to improve fairness. According to GBP, each vehicle is obliged to traverse a compulsory node (a gateway) on its minimum cost itinerary from origin to destination. Gateways must be located on a few network nodes and assigned to vehicles to minimize total risk, yielding a bi‐level optimization problem. GBP already proved able to reduce total risk by opening just a few gateways and to a limited detriment of total cost. However, gateways may end up acting as flow concentrators, thus hampering equity. This study aims to bridge the gap between risk mitigation and fairness. To this aim, we generalize the multi‐commodity flow formulation of the problem by imposing a capacity constraint on the nodes, discuss its impact on the model structure, and experimentally investigate whether it is possible to achieve a more equitable risk distribution and how total risk and total cost are affected.

The territory faced with technological risks in Algeria: case of the BLEVE phenomenon’s effects related to the transport of hazardous materials

The territory faced with technological risks in Algeria: case of the BLEVE phenomenon’s effects related to the transport of hazardous materials

Optimizing hazardous materials transportation network: A bi-level programming approach considering road blocking

Road transportation serves as the primary mode for hazardous materials (hazmat) transportation in China. However, the current academic literature lacks sufficient exploration of optimizing transportation networks through road-blocking strategies. This research proposed a bi-level programming model, where the government acts as the decision-maker in the upper-level programming, and the transportation enterprise operates at the lower level. Road-blocking strategies are employed by the government to mitigate transportation risks. We developed exact solution algorithms for the upper programming and employed genetic algorithms for the lower model separately. Finally, using a real road network in Beijing as a case study, we showcased the effectiveness of our approach. We computed government decision schemes and enterprise transportation routes for 13 scenarios, and conducted a further discussion and analysis on scenarios with road service levels of 83% and 80.9%. The method and results presented in our study can adeptly dissect the transportation of hazmat in city areas, offering insightful perspectives and robust support for devising more streamlined management strategies.

Selection and planning of hazardous materials transportation routes based on explosion accident risks

The explosiveness of hazardous materials determines that once an accident occurs during transportation, severe damage will be imposed on surrounding targets. However, the increasing complexity of the road network significantly augments the risk of damage occurrence. To maintain low accident risks in transporting hazardous materials, this study proposes a method for selection and planning of transportation routes based on explosion accident risks. Firstly, the road network topology is associated with vehicle status to establish a relationship between the accident probability and speed gradient. Meanwhile, an independent grid-based approach is used to perform multi-level damage quantification on various objects. Secondly, route risks are quantitatively characterized, and a comparison system for multiple risk metrics is established. Based on search algorithms, route planning and risk ranking are achieved. Finally, the method is validated. It has been confirmed that this method can quickly and accurately obtain route ranking and risk distribution. The results offer practical guidance for relevant organizations to improve risk management and strategy development, and provide reference for future research.

Quantitative risk analysis of road transportation of hazardous materials in coastal areas

Given the complex climate conditions in coastal areas and their role as key transportation hubs for hazardous chemicals, this study proposes a method to quantitatively and comprehensively evaluate transportation risks. Initially, accident data were analyzed to identify risk factors from five aspects: human, vehicle, materials, environment, and management, based on system safety theory. Subsequently, a risk analysis model was developed using Decision-making Trial and Evaluation Laboratory, interpretive structural model theory, and Bayesian theory to quantitatively assess accident risk levels. The model was applied to a case involving a hazardous chemical accident on a cross-sea bridge, where Bayesian backward reasoning was used to analyze the sensitivity and importance of risk factors. This approach facilitated the key risk factors affecting the safety of hazardous chemical transportation systems. Notably, the study incorporated scenarios involving hazardous material transport vehicles crossing sea bridges into the risk assessment framework, offering valuable insights for management authorities. It also considered the impact of strong side winds-a factor often overlooked-in hazardous material transport. The validation process demonstrated that the method accurately quantifies the risk of hazardous chemical transportation and identifies the key factors influencing accident occurrence. The research highlights that strong gusts of wind significantly impact safety, and human factors are crucial in the overall risk system.

Robustness of higher‐order network pertinent to first‐ and higher‐order dependency

AbstractRobustness of higher‐order network (HON) with dependency is different from first‐order network (FON), as the attack orders and the number of iterations are totally different. To measure the robustness of HON with dependency, this study proposed new attack strategies on node and edge failure through measuring the size of the giant component and global efficiency. And two real‐world systems of hazardous materials transportation accident causation system and Chinese high‐speed railway system with different network size were empirically studied. Results show that HON is more fragile to robustness attacks than FON. The number of attack iterations is uncertain in HON, which depends on the attack strategies and the network structure. Meanwhile, nodes and edges with high dependency have greater impacts on network robustness, providing valuable insights into capturing critical information. This study may be helpful to design the robust system, improve the system's reliability and serve as a valuable reference for future exploration of HONs robustness.

A learning optimization for resilience enhancement of risk-informed traffic control system with hazardous materials transportation under uncertainty

A learning optimization is proposed to enhance overall resilience of interdependent traffic systems with hazardous materials (hazmat) transportation under uncertainty. To this end, three interconnected systems are proposed against traffic dynamics and congestion in a complex environment of regular traffic and hazmat carriers incurred with time-varying travel cost. In order to increase control resilience against traffic instability, a reinforcement learning hazmat network is proposed. In order to efficiently improve computation resilience against disruption of risk uncertainty, a resilience-aware learning optimization is proposed to obtain optimal solutions. In order to demonstrate computational performance of proposed approach, numerical experiments are performed at a real-world city under various kinds of traffic conditions. Computational comparisons are numerically made with stochastic and robust optimization at large-scale traffic control systems. As it reported, the proposed learning-based optimization can better greatly enhance overall traffic system resilience, control resilience and computation resilience compared to other models under mixed risk of hazmat transportation and uncertain demand.

Risk assessment of hazmat road transportation accidents before, during, and after the accident using Bayesian network

Risk exists in the whole process of before, during and after the accident of hazardous materials (hazmat) transportation, which usually lead to serious consequences. Risk assessment is a significant way to identify hidden dangers and their interactions, which can curb accidents happen. The purpose of this study is to analyze the risk factors of hazmat road transportation accidents through entire process risk assessment and propose management strategies. Considering nodes dependency, i.e. accident type and rescue time, this study applies the concept of Tree Augmented Naive Bayes (TAN) and built a hazmat road transportation Bayesian network (HRT-BN). Mutual information and model validation are carried on to better facilitate convenient inference and diagnosis of risk nodes and their interactions. Results show that in causal inference with single factors, human risk factors are more significant, which are likely to lead to leakage accident with slight consequences and short rescue time (s2). Meanwhile, with coupling effect of multiple factors, accident types become more diverse with serious consequence. In diagnostic inference, the rescue time is linked to seasonal and regional factors, e.g., the rescue time in summer is longer. Based on these analysis, targeted recommendations have been proposed at the end. This study provides a whole angle of view to assess risks in hazmat transportation, which has significant practical feasibility for risk management and planning of hazmat road transportation.

Analysis of Spill Accident Damage Scale and Explosion Accident Impact Distance of Hazardous Material Transportation Vehicles

Analysis of Spill Accident Damage Scale and Explosion Accident Impact Distance of Hazardous Material Transportation Vehicles

Route optimization for hazardous materials transportation vehicles based on BFA-ACO under carbon tax policy

Excessive emission of greenhouse gases leads to the increasing greenhouse effect, adversely affecting the global climate. Carbon dioxide is the dominant part of greenhouse gases; reducing its emission is the most important way to solve the climate problem. Aiming at the characteristics of the dangerous goods transportation market and the development of the carbon tax policy, the carbon tax cost and the cost of dangerous goods transportation are introduced, and the characteristics of the dangerous goods transportation and the road traffic network and the road traffic in each period are fully analyzed. The optimization model of the path of the hazardous goods vehicles is established with the optimization objective of the lowest total cost. Then, by analyzing the advantages and disadvantages of bacterial foraging algorithm (BFA) and ant colony algorithm (ACO), the hybrid BFA-ACO algorithm is established by combining the two, and the replication and convergence operations of bacterial foraging algorithm are introduced into the ACO algorithm to improve the convergence speed and global convergence ability of the algorithm. The hybrid algorithm is then used to optimize and solve the path optimization model of hazardous materials vehicles and compared with the classical algorithms Genetic Algorithm (GA) and ACO for solving the path of dangerous materials vehicles. A comparison of the optimization results reveals that optimizing the model by bacterial foraging-ACO algorithm is better than optimizing the model by a single algorithm.

Transportation of hazardous material via railroad: Incident investigation and a case study of derailment in 2023

AbstractRailway transportation of hazardous materials (HAZMAT) is common and is generally considered safe. However, transporting toxic, flammable, and explosive substances via railways carries significant risk due to their high volume, proximity to populated areas, low public awareness, and potential domino effect. Particularly, the practice has come into question after a Norfolk Southern train derailed in Ohio in February of 2023. This derailment continuously reminds the public and the industry that such incidents can profoundly affect a community, critical infrastructure, and the environment. To identify the root cause of the Ohio train derailment and discover the deficiency of the safety system applied, combining the cause mapping approach with the safety triad concept was employed in this study. Based on this approach and the preliminary incident investigation released by the National Transportation Safety Board, the incident sequence is established, and the causal events leading to this incident are identified in the three essential pillars of its safety system: prevention, mitigation, and response, respectively. The study subsequently develops recommendations to improve the safety system of HAZMAT freight trains. This is expected to lower further the probability and consequence of HAZMAT freight train incidents and ultimately result in long‐term changes in railroad transportation.

Route Optimization of Hazardous Material (Hazmat) Transportation with Risk Equity and Time-Varying Risk

This paper strives for route optimization of hazardous material (hazmat) for given probabilities and consequences. We aim to not only develop a model to determine the route with the least total risk and cost, but also pursue risk equity from three perspectives of government, enterprises, and society in the route optimization. Specifically, this paper reduces the differences of population exposure risk among road segments by using the threshold setting method and decreases the differences of environmental risk by minimizing the risk compensation cost caused by the additional environmental risk exceeding its average for each road segment. In addition, this paper analyzes the impact of the time-varying characteristics of risk and risk equity and proposes a multi-objective route optimization model which considers the minimization of total risk, cost, and risk differences under time-varying conditions. Finally, the ε-constraint method and an improved genetic algorithm are used to optimize the model, which is applied to a case study involving hazardous materials transportation route optimization in Shanghai, China. The resulting analyses indicate that risk equity can be improved by setting a proper threshold to acquire feasible paths and by minimizing the compensation cost to control the differences of environmental risk. Considering variance of time in the route optimization may lead to a route with lower risk and better risk equity.

ESTIMATING THE SPREADING RATES OF HAZARDOUS MATERIALS ON UNMODIFIED CELLULOSE FILTER PAPER: IMPLICATIONS ON RISK ASSESSMENT OF TRANSPORTING HAZARDOUS MATERIALS

The transportation of hazardous materials (HAZMATs) poses an inherent threat to human health and the environment. To comprehensively grasp the environmental impacts of HAZMAT accidents, it is vital to estimate their potential spread. Although numerous studies have addressed associated risks, there is a need to distinguish the spread area of key HAZMATs. We conducted diffusion tests on an unmodified alpha-cellulose filter paper for four HAZMAT compounds: methanol, ethanol, hydrochloric acid, and sodium hydroxide, at set temperatures. We employed an analytical solution based on an amplitude diffusing mass model to compute the diffusion coefficients for each analyte with respect to temperature. Fick's second law was applied using the derived diffusion coefficient values to determine the maximum spread. A finite element model with a Crank-Nicolson formulation was used to assess the consistency between analytical and numerical models for each analyte. Two-way analysis of variance (ANOVA) and the Kolmogorov-Smirnov (K-S) tests were utilized to validate the model. We can adduce that even HAZMATs with similar functional groups may have different exposure pathway risks with temperature as a key factor. Key parameters, such as spread area, diffusion time, porosity, temperature, and retention factors, may be important spill-site characterization parameters.

DETERMINATION OF THE RELATIONSHIP BETWEEN VOLUME AND DIFFUSION AREAS OF HAZARDOUS MATERIALS ON POROUS MEDIA

One of the focused areas that transportation industry has to overcome is safe transportation of hazardous materials (HAZMATs). The low probability/high consequence nature of the HAZMAT transportation necessitates assessing the risk associated with HAZMAT transportation. To fully understand the potential consequences of HAZMAT accidents, estimating the diffusion area under different spill volumes for various HAZMATs is needed for a complete risk assessment. The main purpose of this study is to develop a relationship between the volume and the diffusion area for six analytes: 75% methanol, 70% ethanol, 36% HCL, 40% NaOH, Bakken, and Niobrara crude oils. We evaluate the distribution of the diffusion area with respect to 11 volume categories at five temperatures. This study also utilizes a circular chromatography approach to identify the diffusion area with respect to 11 volume levels. The findings of the study show that analytes diffusion can be explicitly explained by linear regression, polynomial regression, and power regression. Methanol at 0°C to 30°C, ethanol at 10°C and 20°C, HCL at 20°C, and NaOH at 10°C can be explained by linear regression, while methanol at 40°C can be explained by power regression. All other analytes followed polynomial regression trends. One notable finding is that NaOH, Bakken, and Niobrara crude oils' diffusion times decrease with temperature increase.

A Decision Support Scheme for Safe and Efficient Transportation of Hazardous Materials

A Decision Support Scheme for Safe and Efficient Transportation of Hazardous Materials

Multimodal logistics chains for international transportation of dangerous and perishable goods

The overview article delves into the critical area of emergency logistics and supply chain management. Analyzing research conducted by experts in the field, the authors explore the potential benefits and challenges associated with the use of multimodal and intermodal international transportation of dangerous and perishable goods, and assess the potential challenges as well as the importance of emergency logistics for disaster relief and recovery. It is noted that traditional unimodal transport systems may be insufficient for swift and efficient response to emergency situations, which makes the integration of multimodal and intermodal chains an increasingly attractive alternative. Emergency logistics play a key role in ensuring the uninterrupted flow of goods during crises and disasters, especially when it comes to dangerous and perishable goods. One of the purposes of this article is to highlight the importance of vehicle diversification during such disasters. Multimodal transport involves the use of several modes of transport, such as road, rail, sea and air, under the direction of one transport operator or several carriers that cooperate in a coordinated manner. On the other hand, such transportation involves the use of standardized containers that can be easily moved between different modes of transport, offering increased flexibility and cost-effectiveness. The article provides an overview of the challenges faced by emergency logistics and the potential problems when transporting dangerous and perishable goods. It emphasizes the importance of building robust supply chains that can withstand disruptions and provide rapid response to effectively mitigate risks. The need to increase the stability and efficiency of emergency logistics chains is emphasized. The study aims to shed light on which approach offers the best balance between timeliness, adaptability and overall efficiency in the international transport of hazardous materials and perishable goods. The article refers to case studies and real-world cases of emergency logistics operations where multimodal and intermodal transport systems have been successfully applied. These cases highlight their practicality and effectiveness in mitigating potential disasters and minimizing the negative impact of accidents such as spills, explosions or spoilage, and the consequences of war. The authors note the special relevance of multimodal container transportation of dangerous and perishable goods, especially during the war that Ukraine is waging against russian aggression, since in these conditions the principle of logistics “just in time” is most in demand, and modern containers allow to ensure complete safety, speed and accuracy, and in necessary cases, the secrecy of the delivery of goods in the conditions of hostilities and other emergency situations.

A new hybrid MCDM approach for mitigating risks of hazardous material road transportation.

Given the ongoing development of the global economy, the demand for hazardous materials, which serve as essential components for numerous industrial products, is steadily increasing. Consequently, it becomes imperative to devise a methodology for mitigating the risks associated with the road transportation of hazardous materials. The objective of this study is to establish an integrated quality function deployment and multicriteria decision-making (QFD-MCDM) framework and identify the pivotal factors that propel Industry 5.0 (I5.0), thus fortifying supply chain resilience (SCR) and ameliorating the hazardous material transportation risks (HMTR). These measures encompass various strategic areas, including "establish a safe and inclusive work environment", "customized products and services", "enhance production flexibility and strengthen control redundancy", and "real-time data collection and analysis". By adopting these measures, enterprises can lead to sustainable and stable business operations. The findings of this study demonstrate the synergistic potential of integrating I5.0 and SCR in effectively mitigating HMTR. Additionally, these findings offer valuable insights and practical implications for enterprises across diverse industries.

Simultaneous consideration of the accident and terror risks for hazardous materials transportation

Simultaneous consideration of the accident and terror risks for hazardous materials transportation

Optimal Design of a Hazardous Materials Transportation Network considering Uncertainty in Accident Consequences

Optimal Design of a Hazardous Materials Transportation Network considering Uncertainty in Accident Consequences

Hazardous materials facility siting optimization and ranking: A transportation risk mitigation framework

Hazardous material transportation problems have widely been studied in the past especially in the context of routing, scheduling, and network design problems. Yet, the combined hazardous material facility location-routing problem has not been studied adequately. We emphasize that locating a hazardous material facility is a rich process, and a good site can mitigate the potential transportation risk beforehand. A methodological framework is proposed which allows evaluation and ranking of potential sites based on hierarchical relationship utilities. The proposed method attempts to improve the risk functions and applies a stochastic analysis to measure the risk, which relaxes some assumptions in deterministic analysis, and is more realistic while avoiding overestimation of the risk. The study covers multi-objective optimization considering the decision-makers’ preferences on network segments and risk to the population and water bodies. Potential hazardous material facility sites’ rank is determined by the probability of optimality and one-to-one relationship utilities with the points of interests. Results show that the proposed stochastic analysis offers more flexibility to select and rank the potential sites.