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Characteristics and heat transfer mechanism of low-voltage AC series arc faults under coupled ambient temperature and wind speed
Journal of Tsinghua University (Science and Technology) 2026, 66(9): 1795-1804
Published: 14 September 2026
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Objective

Electrical fires occur frequently in complex environments, where environmental factors such as ambient temperature and wind speed contribute to fire occurrence and spread by changing the behavior of series arc faults. This study investigates the patterns of low-voltage AC series arc faults under the combined effects of ambient temperature and wind speed, with a focus on temperature field evolution, spatial heat transfer, current and voltage responses, and arc energy.

Methods

A two-dimensional axisymmetric magnetohydrodynamic model is developed in COMSOL Multiphysics to simulate the thermal-fluid-electromagnetic coupling behavior of an AC series arc fault. This model integrates magnetic and electric fields, heat transfer, laminar flow, and an external circuit. The simulation domain consists of a copper electrode, a graphite electrode, a 3 mm arc gap, an ignition heat source, and the surrounding air. The circuit comprises a 5 Ω resistor and a 220 V/50 Hz AC source. Arc formation is initiated by setting the ignition heat source to 12,000 K. A two-dimensional orthogonal combined design is adopted, including three ambient temperatures (288.15, 298.15, and 308.15 K) and three wind speeds (0, 2, and 4 m·s−1). Average temperature, temperature integral, the root mean square (RMS) of current and voltage, and arc energy are selected as evaluation indicators. Observation points, arranged from the arc center to the outer region, are used to quantify spatial variations in the thermal response.

Results

The results show that the arc temperature field expands and contracts with the power-frequency cycle, and this behavior is closely associated with voltage variations. In the absence of wind, the temperature field exhibits a spindle-like shape, with heat accumulating around the arc. At a wind speed of 2 m·s−1, the temperature field shifts in the direction of airflow, and the high-temperature region moves toward the graphite electrode. The effects of wind speed on the temperature field demonstrate clear spatial dependence. In the arc core region, temperature slightly increases with rising wind speed due to thermal contraction concentrating energy near the arc column. In the peripheral region, however, convective cooling dominates. At 4 m·s−1, the average temperature in the outer region decreases by more than 12.06%, and the temperature integral at wind-cooling-dominated observation points decreases by up to 42.27%. The current RMS remains stable between 34.4 and 34.7 A. The voltage RMS is more sensitive to wind speed than ambient temperature, decreasing by approximately 2.55 V when wind speed increases to 4 m·s−1. The arc energy remains stable at 2 m·s−1 and decreases slightly at 4 m·s−1. Ambient temperature has a limited effect on arc energy, exerting only a weak influence under strong wind conditions.

Conclusions

Wind speed is the primary environmental factor controlling the temperature field and electrical response of low-voltage AC series arc faults, whereas ambient temperature has a limited effect. Wind enhances heat concentration in the arc core while increasing cooling in the outer region. The current conduction channel remains stable, but voltage and arc energy respond more distinctly to airflow disturbance. These findings provide a theoretical basis for early warning and prevention systems for electrical fires in complex environments.

Issue
Experimental study on the effects of temperature and humidity on the characteristics and energy release of alternating current series fault arcs
Journal of Tsinghua University (Science and Technology) 2026, 66(2): 223-232
Published: 27 February 2026
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Objective

Alternating current (AC) series fault arcs pose significant fire hazards in residential and industrial settings because of their high energy density and ability to ignite combustible materials. Environmental factors, such as ambient temperature and relative humidity, influence the initiation, development, and energy release of fault arcs. Existing studies have primarily utilized simplified experimental conditions or qualitative observations, providing limited quantitative evidence on the effects of ambient temperature and relative humidity on arc characteristics. This study aims to systematically quantify the effects of ambient temperature and relative humidity on the electrical characteristics and energy release of AC series fault arcs.

Methods

A multiparameter fault arc experimental platform was built by combining a temperature-and humidity-controlled chamber with high-precision electrical signal acquisition instruments. The setup included an AC power supply, a 40 Ω resistive load, voltage and current probes, an oscilloscope, and a manual electrode separation mechanism. Series fault arcs were generated between a copper cone electrode and a fixed carbon electrode under controlled separation conditions. Two series of experiments were conducted: (1) In one series, the ambient temperature varied from 5 to 30 ℃ at 45% relative humidity, (2) while in the other, the relative humidity varied from 20% to 80% at 25 ℃. For each condition, multiple repetitions of the experiment were performed to ensure statistical reliability. Electrical signals were recorded and then processed by a discrete wavelet transform to remove noise while preserving the transient characteristics. The root mean square (RMS) values of current and voltage, as well as the instantaneous power integrals, were calculated to quantify the electrical characteristics and energy release.

Results

The results revealed that RMS current generally increased from 4.64 A to 4.85 A as the ambient temperature increased from 5 to 30 ℃, indicating enhanced ionization and reduced gas density in the arc channel; meanwhile, the RMS voltage decreased from 30.55 V to 21.68 V, indicating lower arc impedance at higher temperatures. Increasing the relative humidity caused slight reductions in RMS voltage and energy release, while the RMS current remained largely stable, suggesting that higher humidity suppresses arc stability through enhanced cooling and electron recombination. These findings indicate that ambient temperature has a dominant influence on arc current, whereas voltage and energy release are moderately or weakly affected by environmental factors.

Conclusions

This study establishes a robust experimental and analytical framework to quantify the impact of ambient temperature and relative humidity on AC series fault arcs. The results demonstrate that the electrical characteristics and energy release of fault arcs are sensitive to environmental parameters and exhibit nonlinear and condition-specific responses. These findings provide quantitative evidence for understanding the mechanisms underlying fault arc behavior and highlight the importance of considering environmental factors in fire risk assessments. The framework can support the development of tailored arc-fault mitigation strategies and improve the design of electrical systems to reduce fire hazards across diverse residential and industrial environments.

Issue
Crowd counting model for evacuation scenarios based on a cascaded CNN
Journal of Tsinghua University (Science and Technology) 2023, 63(1): 146-152
Published: 15 January 2023
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Accurate crowd counts during evacuations can support real-time optimization of evacuation routes and scheduling of emergency resources. This study estimates the number of occupants in an evacuation passageway by setting a classification level and personnel density together in a cascaded convolutional neural network (CNN) crowd counting model based on analyses of existing methods. The method avoids the loss of image information and over fitting in the convolution process. The model estimates the real-time crowd count in crowded situations by learning the relationship between the number and the position of occupants in the image and by changing the image features. The model was implemented on the PyTorch platform with an identification accuracy for the validation set (612 photos) of 84.2% and for the test set (182 photos) of 83.6%, which shows that this method can accurately predict the number of evacuees in a monitoring screen.

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