Modeling the Cost Effectiveness of Fire Protection Resource Allocation in the United States: Models and a 1980–2014 Case Study

The estimated cost of fire in the United States is about $329 billion a year, yet there are gaps in the literature to measure the effectiveness of investment and to allocate resources optimally in fire protection. This article fills these gaps by creating data‐driven empirical and theoretical models to study the effectiveness of nationwide fire protection investment in reducing economic and human losses. The regression between investment and loss vulnerability shows high R² values (≈0.93). This article also contributes to the literature by modeling strategic (national‐level or state‐level) resource allocation (RA) for fire protection with equity‐efficiency trade‐off considerations, while existing literature focuses on operational‐level RA. This model and its numerical analyses provide techniques and insights to aid the strategic decision‐making process. The results from this model are used to calculate fire risk scores for various geographic regions, which can be used as an indicator of fire risk. A case study of federal fire grant allocation is used to validate and show the utility of the optimal RA model. The results also identify potential underinvestment and overinvestment in fire protection in certain regions. This article presents scenarios in which the model presented outperforms the existing RA scheme, when compared in terms of the correlation of resources allocated with actual number of fire incidents. This article provides some novel insights to policymakers and analysts in fire protection and safety that would help in mitigating economic costs and saving lives.     

Which Fire to Extinguish First? A Risk‐Informed Approach to Emergency Response in Oil Terminals

The performance of fire protection measures plays a key role in the prevention and mitigation of fire escalation (fire domino effect) in process plants. In addition to passive and active safety measures, the intervention of firefighting teams can have a great impact on fire propagation. In the present study, we have demonstrated an application of dynamic Bayesian network to modeling and safety assessment of fire domino effect in oil terminals while considering the effect of safety measures in place. The results of the developed dynamic Bayesian network—prior and posterior probabilities—have been combined with information theory, in the form of mutual information, to identify optimal firefighting strategies, especially when the number of fire trucks is not sufficient to handle all the vessels in danger.     

浅谈古建筑消防安全问题及对策

我国古建筑众多,且具有自身的消防安全特性。本文结合当前古建筑消防安全形势,从消防管理、防火设计及火灾扑救三个方面,对我国古建筑消防安全问题进行系统的阐述,并提出相关对策。     

Scheduling aerial resource operations for the extinction of large-scale wildfires

The significant increase in large-scale wildfire events in recent decades, caused primarily by climate change, has resulted in a growing number of aerial resources being used in suppression efforts. Present-day management lacks efficient and scalable algorithms for complex aerial resource allocation and scheduling for the extinction of such fires, which is crucial to ensuring safety while maximizing the efficiency of operations. In this work, we present a Mixed Integer Linear Programming (MILP) optimization model tailored to large-scale wildfires for the daily scheduling of aerial operations. The main objective is to achieve a prioritized target water flow over all areas of operation and all time periods. Minimal target completion across individual areas and time periods and total water output are also maximized as secondary and ternary objectives, respectively. An efficient and scalable multi-start heuristic, combining a randomized greedy approach with simulated annealing employing large neighborhood search techniques, is proposed for larger instances. A diverse set of problem instances is generated with varying sizes and extinction strategies to test the approaches. Results indicate that the heuristic can achieve (near)-optimal solutions for smaller instances solvable by the MILP, and gives solutions approaching target water flows for larger problem sizes. The algorithm is parallelizable and has been shown to give promising results in a small number of iterations, making it applicable for both night-before planning and, more time-sensitive, early-morning scheduling.     

Women Constructing Masculinity in Voluntary Firefighting

Within gender studies, research and theorizing have used archetypal ‘masculine’ occupations to explore how masculinity is accomplished and practised in social interaction. In contrast, little work has explored how masculinity is constructed in the voluntary sector. In this paper, we address this gap by exploring how masculinity is constructed and experienced by women volunteers who are active firefighters in rural and regional Victoria. Firefighting is widely recognized as a non‐traditional occupation for women and they are underrepresented as volunteers as well as paid employees. We explore masculinity from the perspective of women volunteers because this can enhance our understanding of masculinity as a relational achievement as well as help to identify practices that they experience as problematic. Our research shows how voluntary work can afford a distinct range of resources for the ‘doing’ of gender and how this reflects the specific organizational and geographical contexts in which such volunteering occurs.     

用积极心理学构建消防院校思想政治教育新模式

在阐述积极心理学基本内涵的基础上,深切认识其对消防院校思想政治教育的重要启示和意义,进而针对消防院校的实际,提出运用积极心理学的基本理念指导消防院校的思想政治教育,在新的思想政治教育模式探索中,体现思想政治教育的价值功能。