错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Modeling Fire Company Staffing to Investigate its Effect on Effective Response Force Times to Structure Fires Using Local Incident Data

  • Evgeniy P. Ivanov

摘要

Fighting structure fires necessitates the deployment of an effective response force (ERF) capable of ensuring both effective firefighting and the safety of firefighters. The article aims to investigate the effect of company staffing on ERF response times and to compare these findings with data from the National Institute of Standards and Technology’s (NIST) Report on residential fireground field experiments. The investigation revolves around modeling the crew size of fire engines and ladder trucks through a 4-step approach. Given the challenges of obtaining publicly available apparatus response data at the national level needed for any ERF time calculations, the approach taken is based on utilizing local incident and apparatus response data from a single fire department. Three datasets are developed, corresponding to 3-person, 4-person, and 5-person crews. Comparison among these datasets hinges on calculating the 90th percentile of ERF assembly times and total response times, as well as assessing the percentage of times the target response times are met. The results show improvements in response times across all up-staffing scenarios, underscoring the direct positive effect of crew size up-staffing on ERF response times. Specifically, when transitioning from 3-person to 4-person crews, the biggest improvements occur in moderate and high-risk structure fire incidents, with moderate-risk fires seeing a reduction of over 2 full minutes in all response time segments. Elevating crew sizes from 4-person to 5-person teams yields the most significant gains in special risk structure fires, resulting in a remarkable 10-min improvement in both ERF assembly time and total response time. In conclusion, this study provides recommendations for optimizing incident data quality and considerations to take into account when making decisions for crew upstaffing.