Intelligent self-evacuation path planning for fire emergencies in underground coal mines

煤矿开采 采矿工程 工程类 路径(计算) 法律工程学 土木工程 建筑工程 废物管理 计算机科学 程序设计语言
作者
Vasilis Androulakis,Shawn Kingman,Hassan Khaniani,Mostafa Hassanalian,Sihua Shao,Pedram Roghanchi
出处
期刊:Tunnelling and Underground Space Technology [Elsevier BV]
卷期号:162: 106623-106623 被引量:6
标识
DOI:10.1016/j.tust.2025.106623
摘要

In the case of fire emergencies in underground mines, the mine workers undergo significant psychological and physical stress in their battle with time to self-evacuate safely. This can impart their ability to correctly assess the fire-induced hazards in the vicinity of their location and therefore to choose the safest action or the safest escape route. At the same time, the workers do not have any way to know the state of the mine tunnels beyond the immediate vicinity that their senses can provide information about potential hazards. Moreover, the highly dynamic state of a mine, especially under a fire emergency, can render previously safe routes extremely dangerous in the blink of an eye. This study proposes a framework and presents proof of concept for a real-time smart evacuation route-planning approach based on graph theory. In the effort to assist mine workers to safely reach the surface or a refuge chamber, a smart system could provide invaluable acquisition of mine-wide situational awareness to the workers. An IoT of sensors, such as gas concentration, temperature, smoke, oxygen, and air speed sensors, combined with a real-time path planning algorithm could be a powerful tool to such situations. A mine can be represented by a topological map and every location can be assigned a real-time updated value that quantifies the fire-induced hazard based on data collected by a mine-wide IoT. This combinatory risk considers parameters such as concentrations of toxic gases, oxygen levels, heat, and visibility. Safety and health exposure limits as defined from the various regulatory entities are combined with simulated IoT data to calculate the combined risk. The optimized escape routes could significantly assist mine workers to reach a safe location. • Mine-wide real-time data optimize evacuations in underground mines. • Fire hazards data and MSHA criteria are integrated into MCF path-finding algorithms. • Optimized paths minimize exposure to fire-induced hazards. • User-friendly, network flow approach provides reliable evacuation paths. • Proposed mine ventilation evaluation tool can improve mine preparedness.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
zclm完成签到,获得积分20
刚刚
DJC完成签到,获得积分10
1秒前
橙子完成签到,获得积分10
1秒前
开心没烦恼完成签到,获得积分10
1秒前
huazhangchina完成签到,获得积分10
1秒前
大模型应助猫小咪采纳,获得10
2秒前
阿北完成签到,获得积分10
2秒前
lllllsy完成签到,获得积分10
2秒前
领导范儿应助malistm采纳,获得10
2秒前
RRui完成签到,获得积分10
4秒前
艾路完成签到,获得积分10
4秒前
动听的小白菜完成签到,获得积分10
5秒前
舒心雅柔完成签到 ,获得积分10
5秒前
liangliang完成签到,获得积分10
6秒前
kol完成签到,获得积分10
6秒前
7秒前
亲爱的小肥羊们完成签到,获得积分10
7秒前
酷酷卡卡完成签到 ,获得积分10
8秒前
雨寒完成签到 ,获得积分10
8秒前
微笑面包完成签到,获得积分10
8秒前
现实的小蚂蚁完成签到,获得积分10
9秒前
何一非完成签到,获得积分10
9秒前
bluehand完成签到,获得积分10
9秒前
223311完成签到,获得积分10
10秒前
正直的雨双完成签到,获得积分10
10秒前
含糊的水卉完成签到,获得积分10
10秒前
wzy完成签到,获得积分10
11秒前
甜甜的满天完成签到,获得积分10
12秒前
蘑菇完成签到,获得积分10
12秒前
SABUBU完成签到,获得积分10
12秒前
wyy完成签到,获得积分10
12秒前
12秒前
982289172完成签到,获得积分10
13秒前
萌萌发布了新的文献求助10
13秒前
出海流浪完成签到,获得积分10
13秒前
Camellia完成签到 ,获得积分10
13秒前
打打应助wjw采纳,获得10
14秒前
HuangShuting完成签到,获得积分10
15秒前
15秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
化工安全与环保 1000
Autoparametric Resonance in Mechanical Systems 1000
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 800
Effects of Two Weeks of Red Light Therapy on Choroidal Thickness and Axial Length in Young Adults 700
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 600
Management and the Arts 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7656698
求助须知:如何正确求助?哪些是违规求助? 9227378
关于积分的说明 19829344
捐赠科研通 7223213
什么是DOI,文献DOI怎么找? 3280340
关于科研通互助平台的介绍 2440621
邀请新用户注册赠送积分活动 2280188