A multi-physical field coupling cable fire hot smoke spread simulation method and system

Abstract

The application discloses a kind of multi-physical field coupling cable fire hot flue gas spread simulation method and system.The method is constructed cable electromagnetic field model by finite element method, in combination with Fourier heat conduction equation, Arrhenius pyrolysis model and LES large eddy simulation, realize the cross-scale modeling of treeing growth dynamics (accuracy ±0.01mm / s) and insulation pyrolysis process (temperature resolution ±2 ℃), can be early 10-30 minutes warning local hot spot (such as 280 ℃ critical temperature) before insulation breakdown, system integration parameter input, multi-field calculation, visual analysis and experimental verification module, support BIM collaborative design, through small scale combustion experiment calibration (10 group sample average error 3.8%), can optimize cable tunnel fire prevention zoning, fire sprinkler layout and other engineering scheme, make flue gas spread speed reduce 42%.The scheme covers power, traffic, data center and other multiple scenes, provides high-precision multi-physical field coupling simulation technology for cable fire risk assessment and safety design.

Description

Technical Field

[0001] This invention relates to the field of cable fire safety, and in particular to a multi-physics field coupled cable fire thermal smoke propagation simulation method and system. Background Technology

[0002] Traditional cable fire simulation technology suffers from the following core bottlenecks: Limitations of single-physics-field analysis: Existing methods are mostly based on single heat conduction or electromagnetic models. For example, the cable temperature field simulation disclosed in CN112328765A only considers Joule heat conduction and does not model the positive feedback mechanism between electrical tree discharge heat generation and the temperature field (experiments show that for every 1kV / mm increase in local electric field strength, the discharge heat generation rate increases by 15%). Lack of initial fire evolution mechanism: The pyrolysis of insulation materials and the growth process of electrical trees are not effectively coupled. For example, when the pyrolysis initiation temperature of XLPE insulation is 250℃, the CO production rate increases exponentially with increasing temperature, but existing technologies (such as CN113156243B) do not quantify the impact of this process on flue gas composition. The simulation of hot smoke and gas spread is crude: the fluid simulation is not coupled with the cable temperature field, resulting in a buoyancy drive calculation error of up to 28%, and it cannot simulate the diffusion characteristics of multi-component gases (such as CO and HCl), making it difficult to accurately predict the height of the smoke layer and the distribution of toxic gas concentrations. The existing technology has not achieved dynamic coupling of the entire chain of "electric tree growth - partial discharge - temperature field - pyrolysis - smoke diffusion", resulting in delayed early fire warning and large deviations in the prediction of the spread path.

[0003] Based on this, a multi-physics field coupled cable fire thermal smoke propagation simulation method and system is provided, which can eliminate the drawbacks of existing devices. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-physics field coupled cable fire thermal smoke propagation simulation method and system, which solves the problem of inconvenience in the use of existing technologies.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A multi-physics coupled cable fire thermal smoke propagation simulation method includes the following steps:

[0007] Step 1: Construct a four-field coupling model of electro-thermal-chemical-fluid, specifically including:

[0008] An electromagnetic field model of the cable was established based on the finite element method to calculate the power frequency electric field distribution, partial discharge quantity Q(t), and Joule thermal power P. J =I 2 R, where I is the load current and R is the conductor resistance;

[0009] Using the Fourier heat conduction equation Construct a temperature field model and couple it with Joule heating PJ and the heat generated by electric tree discharge P D The temperature distribution T(x,y,z,t) inside the cable is simulated, where k is the thermal conductivity coefficient and ρc is the volumetric heat capacity.

[0010] Based on the Arrhenius equation r=Aexp(-E a / RT) Establish a pyrolysis kinetic model for insulating materials, and calculate the pyrolysis rate r and the concentration fields C of combustion products such as CO and HCl. i (x,y,z,t), where A is the pre-exponential factor, E a Activation energy;

[0011] A fluid field model was constructed using the Navier-Stokes equations coupled with the Boussinesq assumption to calculate the velocity field u(x,y,z,t) of the hot smoke flow, considering buoyancy. and diffusion of combustion products

[0012] Step 2: Establish the coupling mechanism between electrical tree growth and temperature field, using the electrical tree growth rate model v d =k d E n exp(-E c / RT) Quantify the effects of local electric field strength E and temperature T on electric tree growth, where k d Let n be a material constant, n be the electric field index, and E be a constant. c The activation energy is the heat generation power P of the electric tree channel. D =0.5Q(t)V is coupled to the temperature field model, where V is the discharge gap volume;

[0013] Based on LES large eddy simulation, the turbulent diffusion of hot flue gas is analyzed, defining the flue gas layer interface height h(t) and the CO volume fraction threshold φ. CO For key environmental characteristic parameters, establish their spatiotemporal variation expressions:

[0014] h(t) = f1(u0,T0,C0,t),φ CO (x,y,z,t)=f2(h(t),u(x,y,z,t))

[0015] Where u0, T0, and C0 represent the initial wind speed, temperature, and concentration of combustion products, respectively.

[0016] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0017] In one alternative: the electric tree growth rate model is fitted to parameter k using experimental data. d n, E cWhen the electric field strength E≥10kV / mm, the growth rate of electric tree increases by 3 times.

[0018] In one alternative: In the pyrolysis kinetic model, the pyrolysis initiation temperature of XLPE insulation material is 250℃, and the CO yield increases exponentially with increasing temperature, reaching 0.12 g / g XLPE at 500℃.

[0019] A multi-physics coupled cable fire thermal smoke propagation simulation system includes:

[0020] Parameter input module: Used to input cable structure parameters, operating parameters and environmental parameters. It has a built-in database of 20 typical cable materials and supports the input of parameters such as conductor radius, insulation thickness, voltage level, load current, ambient temperature, and wind speed.

[0021] Data acquisition module: Connects to partial discharge monitoring devices, temperature sensors, and DSC / TGA experimental equipment to acquire data on discharge quantity, temperature field, and material pyrolysis characteristics;

[0022] Multi-field coupling calculation module: Based on COMSOL Multiphysics secondary development, it realizes transient coupling solution of four fields: electro-thermal-chemical-fluid, with a time step Δt = 0.1-1s, spatial grid accuracy ≤1mm, and supports GPU acceleration;

[0023] Visualization and analysis module: Generates 3D temperature cloud maps, flue gas flow vector maps, and spatiotemporal curves of key parameters, supports VR panoramic display and 3D fusion with BIM models, with an accuracy of ±20mm;

[0024] Experimental verification module: Conduct small-scale cable combustion experiments based on the IEC 60332-3 standard, and use error correction factors. Calibrate model parameters.

[0025] In one alternative: the multi-field coupling calculation module includes an electric tree growth-temperature field coupling algorithm, which can simulate the positive feedback effect of "discharge heat generation-temperature increase-discharge intensification". For every 10°C increase in temperature, the electric tree growth rate increases by 20%.

[0026] In one alternative: the visualization analysis module integrates an early warning algorithm, which can detect local hot spots (temperature resolution ±2℃) before insulation breakdown 10-30 minutes in advance and trigger an audible and visual alarm.

[0027] In one alternative: the system supports seamless integration with BIM software such as Revit, and outputs engineering solutions such as fire compartment design for cable tunnels and layout of fire sprinkler systems, so that the control height error of the smoke layer is ≤0.5m.

[0028] In one alternative: the fluid field module uses LES large eddy simulation to analyze the effect of turbulent eddies on flue gas diffusion, reducing the CO concentration prediction error from 28% to 9% in high wind speed (>5m / s) scenarios.

[0029] In one alternative approach: the model can be adapted to special scenarios such as high altitude and seabed, and by correcting environmental parameters such as air density and pressure, it can realize the simulation of hot flue gas propagation in multiple scenarios.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0031] This technical solution fills the technological gap in multi-field coupled simulation of cable fires through multidisciplinary integration and engineering innovation. It not only improves the timeliness and accuracy of initial fire prediction, but also provides precise safety design tools for fields such as power, transportation, and data centers through system integration and scenario adaptation, demonstrating significant scientific value and promising industrial application prospects. Attached Figure Description

[0032] Figure 1 This is a diagram illustrating the simulation method of the present invention.

[0033] Figure 2 This is a logic block diagram of the system of the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Please see Figure 1 and Figure 2 The specific content of the experiment is as follows:

[0036] 1. Experimental setup and parameters

[0037] Combustion chamber: Dimensions 3m×2m×2m, built-in wind speed regulation system (adjustable from 0-5m / s), equipped with an infrared thermal imager (resolution 0.1℃) to monitor the cable surface temperature in real time;

[0038] Test cable: YJV22-8.7 / 10kV, conductor cross-sectional area 185mm² 2 Insulation thickness 8mm, length 2m;

[0039] Sensor placement:

[0040] Temperature sensor: K-type thermocouples (accuracy ±0.5°C) are embedded every 50mm in the cable insulation layer;

[0041] Gas sampling: A sampling port is set on the top of the combustion chamber and connected to a gas chromatograph (GC-FID) to monitor the concentrations of CO and HCl in real time (detection limits: CO: 1ppm, HCl: 0.1ppm).

[0042] 2. Experimental Procedure

[0043] Pretreatment: Apply 1.2 times the rated voltage (12kV) to one end of the cable, and gradually increase the load current to 200A through a voltage regulator, and run it stably for 30 minutes;

[0044] Electrical tree initiation: A 0.1mm electrical tree defect is artificially pre-fabricated in the middle of the cable insulation layer. The discharge quantity is monitored by a partial discharge detector (accuracy ±5pC). When the discharge quantity is ≥100pC, the ignition device in the combustion chamber is triggered.

[0045] Data collection:

[0046] First 100 seconds: Record temperature, discharge amount, and gas concentration every 10 seconds;

[0047] 100-600s: Record data every 5 seconds until the pyrolysis gas production stabilizes.

[0048] 3. Experimental Results and Model Calibration

[0049]

[0050] Calibration method: Adjust the pyrolysis kinetic parameter A to 8×10 based on the experimental data. 11 s -1 This reduced the simulation error rate from the initial 7.2% to 3.8%.

[0051] Application scenarios of simulation methods are being expanded:

[0052] 1. Simulation of complex scenarios in cable tunnels

[0053] Scenario description: An underground cable tunnel in a city (500m long, 4m wide, and 3m high), containing 3 layers of cable racks with a spacing of 0.3m, an ambient wind speed of 2m / s, and a cable load current of 150A.

[0054] Simulation focus:

[0055] Impact of curves: A 90° curve was set at 200m in the tunnel to simulate the turbulent diffusion of flue gas when passing through the curve. The results showed that the CO concentration 50m downstream of the curve was 18% higher than that of the straight section.

[0056] Impact of cable layout density: Comparing single-layer (10 cables / m) and three-layer (30 cables / m) layouts, the hot flue gas velocity is reduced by 25% and the flue gas layer height is reduced by 0.6m when the three-layer layout is used.

[0057] Recommended output: Install deflectors (45° angle) at bends; install forced exhaust systems (2000m³ / h) every 30m in the three-layer layout area. 3 / h).

[0058] 2. Simulation of Thermal Runaway Coupling in High-Voltage Wiring Harnesses for New Energy Vehicles

[0059] Scenario Description: A high-voltage wiring harness (800V, 300A) is located 0.2m from the battery module in the battery compartment of a certain vehicle. During battery thermal runaway, the heat generation rate is 10kW / m. 3 Duration: 100 seconds.

[0060] Coupled model:

[0061] The heat generated by the battery is transferred to the wiring harness via radiative heat transfer (Stephen Boltzmann's law), with a radiative heat flux density of [missing information].

[0062] When the wire harness temperature field reaches 350℃, insulation pyrolysis is triggered, reaching the critical temperature 150 seconds earlier than the single wire harness model.

[0063] Safety design: It is recommended to add an aerogel insulation layer (thermal conductivity 0.015W / (m·K)) between the battery and the wiring harness, which can extend the time for the wiring harness to reach the critical temperature to 300s.

[0064] 3. Data Center Cable Tray Simulation

[0065] Scenario description: Data center server room cable tray (20m long, 1.5m wide), with 50 communication cables (10A / cable), and air conditioning fan speed of 1m / s.

[0066] Simulation content:

[0067] The temperature in the densely packed cable area (middle of the cable tray) reached 65℃, triggering a partial discharge risk warning (threshold 60℃);

[0068] When the angle between the air conditioner outlet and the cable tray is 30°, the fluctuation range of the flue gas layer height is reduced by 32% compared to an angle of 90°.

[0069] Optimization solution: Adjust the angle of the air conditioner vent to 45° and add temperature monitoring nodes (2m apart) in the middle of the cable tray.

[0070] In-depth analysis of system application scenarios:

[0071] 1. Onboard cable system for rail transit vehicles

[0072] Scenario requirement: The cables at the bottom of high-speed train carriages (voltage 25kV, current 500A) need to simulate the impact of a sudden increase in current (1.5 times the rated current) on fire risk during emergency braking.

[0073] Simulation results:

[0074] During emergency braking, the cable temperature rose from 70°C to 120°C within 30 seconds, and the growth rate of electrical tree branches increased to 0.08 mm / s.

[0075] It is recommended to add a graphite heat dissipation coating to the cable joint (which increases the thermal diffusivity by 2 times), which can reduce the peak temperature by 20°C.

[0076] 2. Offshore wind power submarine cables

[0077] Special modeling:

[0078] Seawater pressure correction: ρ=ρ0+0.0005×h (h is the seawater depth, m), the seawater density increases by 0.5% at a depth of 1000m;

[0079] Ocean current influence: Introducing the Coriolis force term F C =2ρ(u×Ω) (Ω is the Earth's rotational angular velocity), simulating the offset effect of ocean current velocity of 1m / s on the diffusion of flue gas (offset distance ±1.2m).

[0080] Application value: It provides a basis for submarine cable route planning and recommends avoiding areas with strong ocean currents (current velocity > 2m / s) to reduce the risk of fire spread.

[0081] This method and system achieve a breakthrough across the entire technological chain, from "microscopic defect evolution" to "macroscopic disaster prevention and control," through experimentally calibrated high-precision models (error ≤ 3.8%), multi-scenario dynamic parameter correction (such as pressure and ocean currents), and engineering optimization tools (BIM collaboration and early warning algorithms). Compared with traditional solutions, it has significant advantages in complex environment adaptability (covering 90% of scenarios), risk early warning timeliness (30 minutes in advance), and design optimization efficiency (40% reduction in project cycle), providing an integrated solution for cable fire prevention and control that combines "precise simulation, scientific decision-making, and efficient implementation."

[0082] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multi-physics coupled cable fire thermal smoke propagation simulation method, characterized in that, Includes the following steps: Step 1: Construct a four-field coupling model of electro-thermal-chemical-fluid, specifically including: An electromagnetic field model of the cable was established based on the finite element method to calculate the power frequency electric field distribution, partial discharge quantity Q(t), and Joule thermal power P. J =I 2 R, where I is the load current and R is the conductor resistance; Using the Fourier heat conduction equation Construct a temperature field model and couple it with Joule heating P J and the heat generated by electric tree discharge P D The temperature distribution T(x,y,z,t) inside the cable is simulated, where k is the thermal conductivity coefficient and ρc is the volumetric heat capacity. Based on the Arrhenius equation r=Aexp(-E a / RT) Establish a pyrolysis kinetic model for insulating materials, and calculate the pyrolysis rate r and the concentration field C of CO and HCl combustion products. i (x,y,z,t), where A is the pre-exponential factor, E a Activation energy; A fluid field model was constructed using the Navier-Stokes equations coupled with the Boussinesq assumption to calculate the velocity field u(x,y,z,t) of the hot smoke flow, considering buoyancy. and diffusion of combustion products Step 2: Establish the coupling mechanism between electrical tree growth and temperature field, using the electrical tree growth rate model v d =k d E n exp(-E c / RT) Quantify the effects of local electric field strength E and temperature T on electric tree growth, where k d Let n be a material constant, n be the electric field index, and E be a constant. c The activation energy is the heat generation power P of the electric tree channel. D =0.5Q(t)V is coupled to the temperature field model, where V is the discharge gap volume; Based on LES large eddy simulation, the turbulent diffusion of hot flue gas is analyzed, defining the flue gas layer interface height h(t) and the CO volume fraction threshold φ. CO Key environmental characteristic parameters, and their spatiotemporal variation expressions are established: h(t)=f1(u0,T0,C0,t),φ CO (x,y,z,t)=f2(h(t),u(x,y,z,t)) Where u0, T0, and C0 represent the initial wind speed, temperature, and concentration of combustion products, respectively.

2. The multiphysics field coupled cable fire thermal smoke propagation simulation method according to claim 1, characterized in that, The electric tree growth rate model was fitted to parameter k using experimental data. d n, E c When the electric field strength E≥10kV / mm, the growth rate of electric tree increases by 3 times.

3. The multiphysics field coupled cable fire thermal smoke propagation simulation method according to claim 1, characterized in that, In the pyrolysis kinetic model, the pyrolysis initiation temperature of XLPE insulation material is 250℃, and the CO yield increases exponentially with increasing temperature, reaching 0.12 g / g XLPE at 500℃.

4. A multi-physics coupled cable fire thermal smoke propagation simulation system, characterized in that, include: Parameter input module: Used to input cable structure parameters, operating parameters and environmental parameters. It has a built-in database of 20 typical cable materials and supports the input of parameters such as conductor radius, insulation thickness, voltage level, load current, ambient temperature and wind speed. Data acquisition module: Connects to partial discharge monitoring devices, temperature sensors, and DSC / TGA experimental equipment to acquire data on discharge quantity, temperature field, and material pyrolysis characteristics; Multi-field coupling calculation module: Based on COMSOL Multiphysics secondary development, it realizes transient coupling solution of four fields: electro-thermal-chemical-fluid, with a time step Δt = 0.1-1s, spatial grid accuracy ≤1mm, and supports GPU acceleration; Visualization and analysis module: Generates 3D temperature cloud maps, flue gas flow vector maps, and spatiotemporal curves of key parameters, supports VR panoramic display and 3D fusion with BIM models, with an accuracy of ±20mm; Experimental verification module: Conduct small-scale cable combustion experiments based on the IEC 60332-3 standard, and use error correction factors. Calibrate model parameters.

5. The multiphysics field coupled cable fire thermal smoke propagation simulation system according to claim 4, characterized in that, The multi-field coupling calculation module includes an electric tree growth-temperature field coupling algorithm, which can simulate the positive feedback effect of "discharge heat generation-temperature increase-discharge intensification". For every 10°C increase in temperature, the electric tree growth rate increases by 20%.

6. The multiphysics field coupled cable fire thermal smoke propagation simulation system according to claim 4, characterized in that, The visualization analysis module integrates an early warning algorithm, which can detect local hot spots before insulation breakdown 10-30 minutes in advance and trigger an audible and visual alarm.

7. The multiphysics field coupled cable fire thermal smoke propagation simulation system according to claim 6, characterized in that, The system supports seamless integration with BIM software, outputting fire compartment design for cable tunnels and layout engineering schemes for fire sprinkler systems, ensuring that the smoke layer control height error is ≤0.5m.

8. The multiphysics field coupled cable fire thermal smoke propagation simulation system according to claim 7, characterized in that, The fluid field module uses LES large eddy simulation to analyze the influence of turbulent eddies on flue gas diffusion, reducing the CO concentration prediction error from 28% to 9% in scenarios with wind speeds >5m / s.

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