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Search Publications by: Wai Cheong Tam (Fed)

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Displaying 26 - 50 of 51

Real-time Forecast of Compartment Fire and Flashover based on Deep Learning

April 6, 2022
Author(s)
Tianhang Zhang, Zilong Wang, Ho Yin Wong, Wai Cheong Tam, Xinyan Huang, Fu Xiao
Forecasting building fire development and critical fire events in real-time is of great significance for firefighting and rescue operations. This work proposes an artificial intelligence (AI) system to fast forecast the compartment fire development and

Report on High Energy Arcing Fault Experiments - Experimental Results from Low Voltage Switchgear Enclosures

December 29, 2021
Author(s)
Gabriel Taylor, Anthony D. Putorti Jr., Scott Bareham, Christopher U. Brown, Wai Cheong Tam, Edward Hnetkovsky, Andre Thompson, Michael Selepak, Philip Deardorff, Kenneth Hamburger, Nicholas Melly, Kenneth Miller
This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena for low-voltage metal enclosed switchgear containing aluminum conductors. This report covers full-scale laboratory experiments using

Report on High Energy Arcing Fault Experiments - Experimental Results from Open Box Enclosures

December 29, 2021
Author(s)
Gabriel Taylor, Anthony D. Putorti Jr., Scott Bareham, Christopher U. Brown, Wai Cheong Tam, Edward Hnetkovsky, Andre Thompson, Michael Selepak, Philip Deardorff, Kenneth Hamburger, Nicholas Melly, Kenneth Miller, Kenneth Armijo, Paul Clem, Alvaro Cruz-Cabrera, Byron Demosthenous, Austin Glover, Chris LaFleur, Raymond Martinez, James Taylor, Rana Weaver, Caroline Winters
This report documents an experimental program to investigate High Energy Arcing Fault (HEAF) phenomena. The experiments provide data to better characterize the arc to improve the prediction of arc energy emitted during a HEAF event. An open box allows for

Report on High Energy Arc Fault Experiments: Experimental Results from Medium Voltage Electrical Enclosures

November 29, 2021
Author(s)
Gabriel Taylor, Anthony D. Putorti Jr., Scott Bareham, Edward Hnetkovsky, Kenneth Hamburger, Nicholas Melly, Mark Henry Salley, Christopher U. Brown, Wai Cheong Tam, Eric Link, Michael Selepak, Philip Deardorff, Kenneth Miller, Paul Clem, Byron Demosthenous, Austin Glover, Chris LaFleur, Raymond Martinez, Anthony Tanbakuchi
This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena for medium voltage electrical switchgear containing aluminum conductors. This report covers full-scale laboratory experiments using

A Generic Flashover Prediction Model for Residential Buildings Using Graph Neural Network

November 11, 2021
Author(s)
Wai Cheong Tam, Eugene Yujun Fu, Paul A. Reneke, Richard D. Peacock, Thomas Cleary
A generic graph neural network-based model is developed to predict the potential occurrence of flashover for different building structures. The proposed model transforms multivariate temperature data into graph-structure data. Utilizing graph convolution

Sensors and Machine Learning Models to Prevent Cooktop Ignition and Ignore Normal Cooking

July 28, 2021
Author(s)
Amy Mensch, Anthony Hamins, Wai Cheong Tam, John Lu, Kathryn Markell, Christina You, Matthew Kupferschmid
According to a recent NFPA report, 49 % of reported home fires involve cooking equipment, with cooktops accounting for 87 % of cooking-fire deaths and 80 % of the civilian injuries [1, 2]. Between 2014–2018, U.S. fire departments responded to an estimated

The Evolving Temperature Field in a 1 m Methanol Pool Fire

June 4, 2021
Author(s)
Jian Chen, Kunhyuk Sung, Zhigang Wang, Andy Tam, Ki Yong Lee, Anthony Hamins
Thin filament pyrometry is used to measure the time-varying temperature field in a 1 m methanol pool fire. A digital camera with optical filters and zoom lens recorded the emission intensity of an array of 12 µm Silicon-Carbide filaments oriented

Sensors and Machine Learning Models to Prevent Cooktop Ignition and Ignore Normal Cooking

March 18, 2021
Author(s)
Amy Mensch, Anthony Hamins, Andy Tam, John Lu, Kathryn Markell, Christina You, Matthew Kupferschmid
Cooking equipment is involved in nearly half of home fires in the United States, with cooktop fires the leading cause of deaths and injuries in cooking-related fires. In this study, we evaluate 16 electrochemical, optical, temperature and humidity sensors

Predicting Flashover Occurrence using Surrogate Temperature Data

February 9, 2021
Author(s)
Andy Tam, Eugene Yujun Fu, Richard Peacock, Paul A. Reneke, Jun Wang, Grace Ngai, Hong Va Leong, Thomas Cleary
Fire fighter fatalities and injuries in the U.S. remain too high and fire fighting too hazardous. Until now, fire fighters rely only on their experience to avoid life-threatening fire events, such as flashover. In this paper, we describe the development of

On the Use of Machine Learning Models to Forecast Flashover Occurrence in a Compartment

September 15, 2020
Author(s)
Jun Wang, Andy Tam, Paul A. Reneke, Richard Peacock, Thomas Cleary, Eugene Yujun Fu, Grace Ngai, Hong Va Leong
This paper presents a study to examine the potential use of machine learning algorithms to build a model to forecast the likelihood of flashover occurrence for a single-floor multi-room compartment. Synthetic temperature data for heat detectors from

Time Series Feature Extraction and Selection Tool for Fire Data

September 15, 2020
Author(s)
Jun Wang, Youwei Jia, Eugene Yujun Fu, Jiajia Li, Andy Tam
This paper aims to facilitate the use of machine learning to carry out supervised classification/regression tasks for time series data in fire research. Specifically, a feature engineering tool, FAST (Feature extrAction and Selection for Time-series), is

Estimation of the critical external heat leading to the failure of lithium-ion batteries

June 29, 2020
Author(s)
Wei Tang, Andy Tam, Liming Yuan, Thomas Dubaniewicz, Richard Thomas, John Soles
A detailed experimental investigation on the critical external heat leading to the failure of lithium-ion (Li-ion) batteries was conducted using an Accelerating Rate Calorimeter (ARC) at the National Institute for Occupational Safety and Health (NIOSH)

Effect of Pressure on the Heat Transfer of Pool Fire in a Closed Chamber

June 15, 2020
Author(s)
Jian Chen, Yubo Bi, Yanli Zhao, Andy Tam, Changhai Li, Shouxiang Lu
A combined analytical and experimental study was performed to determine the effect of pressure on the heat transfer of pool fire in a closed chamber. A series of ethanol pool fires with diameters from 4 cm to 10 cm were carried out in the pressure chamber

Prevention of Cooktop Ignition Using Detection and Multi-Step Machine Learning Algorithms

May 8, 2020
Author(s)
Wai Cheong Tam, Eugene Yujun Fu, Amy E. Mensch, Anthony P. Hamins, Christina Yu, Grace Ngai, Hong va Leong
This paper presents a study to examine the potential use of machine learning models to build a real-time detection algorithm for prevention of kitchen cooktop fires. Sixteen sets of time- dependent sensor signals were obtained from 60 normal/ignition

Prevention of Cooktop Ignition Using Detection and Multi-Step Machine Learning Algorithms

April 27, 2020
Author(s)
Wai Cheong Tam, Eugene Yujun Fu, Amy E. Mensch, Anthony P. Hamins, Christina Yu, Grace Ngai, Hong va Leong
This paper presents a study to examine the potential use of machine learning models to build a real-time detection algorithm for prevention of unattended cooking fires. 16 sets of time- dependent sensor signals were obtained from 60 normal/ignition cooking

Thin Filament Pyrometry Field Measurements in a Medium-Scale Pool Fire.

September 13, 2019
Author(s)
Zhigang Wang, Andy Tam, Jian Chen, Ki Y. Lee, Anthony Hamins
This paper presents the development of a thin filament pyrometry method to characterize the time- varying temperature field in a medium-scale pool fire in a quiescent environment. A digital camera with optical filters and zoom lens was used to record the