Method and apparatus for generating fire simulation results for nuclear power plants

Abstract

The application discloses a method and device for generating fire simulation results of a nuclear power plant, and belongs to the technical field of fire simulation. The method comprises the following steps: updating a first gas state and a second gas state according to gas physical properties and a gas compression factor, so as to obtain an updated first gas state of a hot smoke layer and an updated second gas state of a cold air layer; updating the gas physical properties and the gas compression factor according to the updated gas pressure, the first gas state and the second gas state, and updating the thermal parameters according to the updated gas physical properties and the gas compression factor, so as to obtain updated thermal parameters; iteratively performing a simulation process until a preset time step is reached, and generating fire simulation results of a target space according to the first gas state, the second gas state, the gas pressure and the thermal parameters at each target time step. The application can improve the accuracy of the generation of the fire simulation results of the nuclear power plant.

Description

Technical Field

[0001] This application relates to the field of fire simulation technology, specifically to a method and apparatus for generating fire simulation results for nuclear power plants. Background Technology

[0002] Fire remains one of the major hazards threatening human life and property. Taking nuclear power plants as an example, fires can damage buildings, systems, or equipment, thereby affecting reactor core safety. Therefore, fire-resistant design of buildings is particularly important. Related technologies, assuming the mixed gas in the fire scene is an absolutely ideal gas, generate fire simulation results based on the ideal gas law.

[0003] However, the gases produced during a fire are actually non-ideal gases, especially under complex conditions such as high temperatures, confined pressures, and multi-component mixing in a fire. Various parameters in the mixed gas undergo non-linear evolution over time. The fire simulation methods used in related technologies oversimplify the microscopic thermodynamic evolution of the gas, thus failing to accurately simulate the real state of a fire. Consequently, the generated fire simulation results are insufficient to meet the engineering requirements of high-level safety buildings such as nuclear power plants for accurate prediction of fire hazards. In other words, the related technologies suffer from poor accuracy in generating fire simulation results. Summary of the Invention

[0004] This application provides a method and apparatus for generating fire simulation results for nuclear power plants, which can improve the accuracy of generating fire simulation results for nuclear power plants.

[0005] To achieve the above objectives, one embodiment of this application provides a method for generating fire simulation results for nuclear power plants, comprising: The gas pressure and thermal parameters of the mixed gas in the target space are obtained, as well as the first gas state of the hot flue gas layer and the second gas state of the cold air layer below the hot flue gas layer in the target space. The gas physical properties of the mixed gas are determined based on the thermal parameters, and the gas compressibility factor of the mixed gas is determined based on the gas pressure. Based on the gas physical properties and gas compressibility factor, the first gas state and the second gas state are updated respectively to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step. The gas pressure is also updated based on the gas physical properties and gas compressibility factor to obtain the updated gas pressure. Based on the updated gas pressure, the updated first gas state, and the updated second gas state, the gas physical properties and gas compressibility factor are updated respectively to obtain the updated gas physical properties and the updated gas compressibility factor. Based on the updated gas physical properties and the updated gas compressibility factor, the thermal parameters are updated to obtain the updated thermal parameters at the target time step. Return to the execution step of updating the first gas state and the second gas state according to the gas physical properties and gas compressibility factor, until the preset time step is reached. Then, generate the fire simulation result of the target space according to the first gas state, the second gas state, the gas pressure and the thermal parameters at each target time step.

[0006] In some embodiments, determining the gas physical properties of the mixed gas based on thermal parameters includes: The gas composition of the gas mixture is determined based on thermal parameters. The gas composition includes at least the molar mass, molar fraction, specific heat capacity at constant volume, and specific heat capacity at constant pressure of each gas in the gas mixture. Based on the gas composition, the physical properties of the mixed gas are determined.

[0007] In some embodiments, determining the gas physical properties of the gas mixture based on its gas composition includes: The average specific gas constant of the mixture is determined based on the molar mass and molar fraction of all gases. The average specific heat capacity of the mixed gas is determined based on the mole fraction and specific heat capacity at constant volume of all gases. The average isobaric specific heat capacity of the gas mixture is determined based on the mole fraction and isobaric specific heat capacity of all gases. The gas physical properties of the mixed gas are determined based on the average specific gas constant, average constant volume specific heat capacity, and average constant pressure specific heat capacity.

[0008] In some embodiments, determining the gas compressibility factor of the gas mixture based on the gas pressure includes: Obtain the thermodynamic temperature of the gas mixture; The temperature-dependent intermolecular attraction parameters are determined based on thermodynamic temperature; Obtain the intrinsic volume parameters of the molecules, and determine the molar volume of the gas mixture based on the intrinsic volume parameters of the molecules and the intermolecular attraction parameters; The gas compressibility factor of the gas mixture is determined based on the gas pressure, thermodynamic temperature, and gas molar volume.

[0009] In some embodiments, the first gas state and the second gas state are updated according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step, including: Based on the physical properties of the gas, the gas compressibility factor, the first gas state, and the second gas state, the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer are determined. The first residual is determined based on the first mass-energy change rate and the first gas state, and the second residual is determined based on the second mass-energy change rate and the second gas state. The first gas state is updated based on the first residual to obtain the updated first gas state, and the second gas state is updated based on the second residual to obtain the updated second gas state. Return to the step of determining the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer based on the gas physical properties, gas compressibility factor, first gas state and second gas state; Until both the first residual and the second residual satisfy the preset first convergence condition, the first gas state of the hot flue gas layer after the update at the target time step and the second gas state of the cold air layer after the update at the target time step are obtained.

[0010] In some embodiments, determining the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer based on gas physical properties, gas compressibility factor, a first gas state, and a second gas state includes: Based on the physical properties of the gas, the gas compressibility factor, and the first gas state, the first estimated temperature, the first density, and the first internal energy of the hot flue gas layer are determined. Based on the physical properties of the gas, the gas compressibility factor, and the second gas state, the second estimated temperature, second density, and second internal energy of the cold air layer are determined. The first estimated temperature, first density, and first internal energy are input into the pre-trained constitutive model to output the first mass-energy change rate of the hot flue gas layer, and the second estimated temperature, second density, and second internal energy are input into the pre-trained constitutive model to output the second mass-energy change rate of the cold air layer. The pre-trained constitutive model is trained based on the sample gas's estimated temperature, sample density, and sample internal energy.

[0011] In some embodiments, updating the gas pressure based on gas physical properties and gas compressibility factor to obtain an updated gas pressure includes: Obtain the spatial geometric parameters of the target space; The gas pressure is updated based on spatial geometric parameters, gas compressibility factor, gas physical properties, the first mass-energy change rate of the hot flue gas layer, and the second mass-energy change rate of the cold air layer, resulting in the updated gas pressure.

[0012] In some embodiments, the thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated thermal parameters at the target time step, including: The first thermal parameters of the hot flue gas layer and the second thermal parameters of the cold air layer were determined based on the thermal parameters. The first thermal parameter and the second thermal parameter are updated respectively to obtain the updated first thermal parameter and the updated second thermal parameter; Based on the updated first thermal parameters and the updated second thermal parameters, the thermal parameters at the target time step are determined.

[0013] In some embodiments, updating the first thermal parameter and the second thermal parameter respectively to obtain updated first thermal parameters and updated second thermal parameters includes: With the mass-energy conservation of the hot flue gas layer at the target time step as a constraint, the first thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated first thermal parameters. With the mass-energy conservation of the cold air layer at the target time step as a constraint, the second thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated second thermal parameters.

[0014] To achieve the above objectives, one embodiment of this application provides an apparatus for generating fire simulation results for nuclear power plants, comprising: The acquisition module is used to acquire the gas pressure and thermal parameters of the mixed gas in the target space, and to acquire the first gas state of the hot flue gas layer in the target space and the second gas state of the cold air layer below the hot flue gas layer. The mixed gas characteristic determination module is used to determine the gas physical properties of the mixed gas based on thermal parameters and to determine the gas compressibility factor of the mixed gas based on gas pressure. The first update module is used to update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer and the updated second gas state of the cold air layer at the target time step, and to update the gas pressure according to the gas physical properties and the gas compressibility factor to obtain the updated gas pressure. The second update module is used to update the gas physical properties and gas compressibility factor according to the updated gas pressure, the updated first gas state and the updated second gas state, respectively, to obtain the updated gas physical properties and the updated gas compressibility factor, and to update the thermal parameters according to the updated gas physical properties and the updated gas compressibility factor, to obtain the updated thermal parameters at the target time step. The fire simulation result generation module is used to return to the steps of updating the first gas state and the second gas state according to the gas physical properties and gas compressibility factor, until the preset time step is reached. Then, based on the first gas state, the second gas state, gas pressure and thermal parameters at each target time step, the fire simulation result of the target space is generated.

[0015] The method and apparatus for generating fire simulation results in nuclear power plants proposed in this application obtain the gas pressure and thermal parameters of a mixed gas in a target space, and obtain the first gas state of the hot flue gas layer and the second gas state of the cold air layer below the hot flue gas layer in the target space; determine the gas physical properties of the mixed gas based on the thermal parameters, and determine the gas compressibility factor of the mixed gas based on the gas pressure; update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step, and adjust the gas pressure according to the gas physical properties and the gas compressibility factor. Update the gas pressure to obtain the updated gas pressure; based on the updated gas pressure, the updated first gas state, and the updated second gas state, update the gas physical properties and gas compressibility factor respectively to obtain the updated gas physical properties and gas compressibility factor, and update the thermal parameters based on the updated gas physical properties and gas compressibility factor to obtain the updated thermal parameters at the target time step; return to execute the step of updating the first gas state and the second gas state based on the gas physical properties and gas compressibility factor respectively, until the preset time step is reached, and generate the fire simulation results of the target space based on the first gas state, the second gas state, the gas pressure, and the thermal parameters at each target time step.

[0016] This application embodiment acquires the gas pressure, thermal parameters, and gas states of the hot flue gas layer and cold air layer of the mixed gas in the target space, and introduces the gas compressibility factor to participate in the iterative update of each parameter over time. This incorporates non-ideal gas behavior into the simulation, fully considering the nonlinear evolution of gas-related parameters under complex fire conditions. Therefore, the final fire simulation results can more realistically reflect the impact of actual gas property changes on the fire development process. Thus, this application embodiment can improve the accuracy of nuclear power plant fire simulation results, meeting the high-precision fire hazard prediction requirements of high-level safety buildings such as nuclear power plants.

[0017] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the system framework corresponding to the method for generating fire simulation results for nuclear power plants provided in the embodiments of this application; Figure 2 This is a flowchart illustrating the method for generating fire simulation results for nuclear power plants provided in an embodiment of this application. Figure 3 This is a schematic diagram of an initial region provided in an embodiment of this application; Figure 4 This is a schematic diagram of a target space provided in an embodiment of this application; Figure 5 This is a schematic diagram of the module structure of the device for generating fire simulation results for nuclear power plants provided in an embodiment of this application; Figure 6 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0020] To enable those skilled in the art to better understand the solutions of this application, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] It should be noted that in all specific embodiments of this application, when it is necessary to obtain thermal parameters of the mixed gas in the target space, permission or consent from relevant personnel in the target space will be obtained first. Furthermore, the collection, use, and processing of this data will comply with relevant laws, regulations, and standards. In addition, when this application embodiment needs to obtain sensitive personal information of relevant personnel, separate permission or consent from the relevant personnel will be obtained through pop-up windows or redirection to a confirmation page. Only after obtaining the separate permission or consent of the relevant personnel will the necessary thermal parameters for the normal operation of this application embodiment be obtained. Other data obtained in this application embodiment are all authorized and legal data, and will not be elaborated upon here.

[0022] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, programmable consumer computer devices, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0023] The technical problems existing in the related technologies are as follows: Fire remains one of the major hazards threatening human life and property. Taking nuclear power plants as an example, fires can damage buildings, systems, or equipment, thereby affecting reactor core safety. Therefore, fire-resistant design of buildings is particularly important. Related technologies, assuming the mixed gas in the fire scene is an absolutely ideal gas, generate fire simulation results based on the ideal gas law.

[0024] However, the gases produced during a fire are actually non-ideal gases, especially under complex conditions such as high temperatures, confined pressures, and multi-component mixing in a fire. Various parameters in the mixed gas undergo non-linear evolution over time. The fire simulation methods used in related technologies oversimplify the microscopic thermodynamic evolution of the gas, thus failing to accurately simulate the real state of a fire. Consequently, the generated fire simulation results are insufficient to meet the engineering requirements of high-level safety buildings such as nuclear power plants for accurate prediction of fire hazards. In other words, the related technologies suffer from poor accuracy in generating fire simulation results.

[0025] For example, in scenarios requiring precise assessment, such as cable interlayer fires, hydrogen accumulation and deflagration, or flue gas spread due to ventilation system failure within nuclear reactor buildings, the relevant technologies often fail to capture the true physical phenomena under extreme conditions because they only linearly calculate the pressure and temperature of hot flue gas in the fire scene based on the ideal gas law. This results in poor robustness of the final fire protection design scheme and emergency response strategy. Especially when facing constantly changing and complex fire environments, such as the thermal feedback effect of high-radioactive areas, overpressure transient impacts in confined spaces, or turbulent diffusion of multiphase fluids, the simulation results generated by the relevant technologies often cannot fully predict and correctly match the actual fire's temperature rise rate and pressure peak. This leads to serious insufficient design margins in the smoke extraction system, or even misjudgments of critical safety equipment, and may even trigger a chain reaction of structural damage or radioactive material leakage accidents. Ultimately, this reduces the overall safety of the nuclear power plant, and the surrounding ecological environment and public health are also seriously threatened.

[0026] The method and apparatus for generating fire simulation results in nuclear power plants proposed in this application obtain the gas pressure and thermal parameters of a mixed gas in a target space, and obtain the first gas state of the hot flue gas layer and the second gas state of the cold air layer below the hot flue gas layer in the target space; determine the gas physical properties of the mixed gas based on the thermal parameters, and determine the gas compressibility factor of the mixed gas based on the gas pressure; update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step, and adjust the gas pressure according to the gas physical properties and the gas compressibility factor. Update the gas pressure to obtain the updated gas pressure; based on the updated gas pressure, the updated first gas state, and the updated second gas state, update the gas physical properties and gas compressibility factor respectively to obtain the updated gas physical properties and gas compressibility factor, and update the thermal parameters based on the updated gas physical properties and gas compressibility factor to obtain the updated thermal parameters at the target time step; return to execute the step of updating the first gas state and the second gas state based on the gas physical properties and gas compressibility factor respectively, until the preset time step is reached, and generate the fire simulation results of the target space based on the first gas state, the second gas state, the gas pressure, and the thermal parameters at each target time step.

[0027] This application embodiment acquires the gas pressure, thermal parameters, and gas states of the hot flue gas layer and cold air layer of the mixed gas in the target space, and introduces the gas compressibility factor to participate in the iterative update of each parameter over time. This incorporates non-ideal gas behavior into the simulation, fully considering the nonlinear evolution of gas-related parameters under complex fire conditions. Therefore, the final fire simulation results can more realistically reflect the impact of actual gas property changes on the fire development process. Thus, this application embodiment can improve the accuracy of nuclear power plant fire simulation results, meeting the high-precision fire hazard prediction requirements of high-level safety buildings such as nuclear power plants.

[0028] The specific details of the method and apparatus for generating fire simulation results for nuclear power plants provided in the embodiments of this application will be described in detail below.

[0029] Please see Figure 1 , Figure 1 This is a schematic diagram of the system framework corresponding to the method for generating fire simulation results for nuclear power plants provided in the embodiments of this application. The method for generating fire simulation results for nuclear power plants provided in the embodiments of this application can be applied to this system framework, and the device proposed in the embodiments of this application is deployed in this system.

[0030] It includes terminal 140, Internet 130, gateway 120, server 110, etc.

[0031] Terminal 140 or server 110 may be a device that executes a method for generating fire simulation results for a nuclear power plant.

[0032] Terminal 140 includes, but is not limited to, mobile phones, computers, and smart voice interaction devices. Furthermore, terminal 140 can be a single device or a collection of multiple devices. For example, multiple desktop computers connected to each other via a local area network, sharing a single monitor, and working collaboratively together constitute a terminal 140. Terminal 140 can communicate with the Internet 130 via wired or wireless means to exchange data.

[0033] Server 110 refers to a computer system that can provide certain services to terminal 140. Compared to ordinary terminal 140, server 110 has higher requirements in terms of stability, security, and performance. Server 110 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0034] Gateway 120, also known as an internetwork connector or protocol converter, is a computer system or device that acts as a translator, enabling network interconnection at the transport layer. It bridges the gap between two systems using different communication protocols, data formats, languages, or even completely different architectures. Gateways can also provide filtering and security functions. Messages sent from terminal 140 to server 110 are forwarded to the corresponding server 110 via gateway 120. Messages sent from server 110 to terminal 140 are also forwarded to the corresponding terminal 140 via gateway 120.

[0035] The method for generating fire simulation results for nuclear power plants in this application embodiment can be applied to various fire simulation result generation scenarios, such as fire simulation in nuclear power plants and high-level safety buildings, fire simulation in enclosed underground projects (such as underground commercial complexes), and fire simulation in petrochemical plants and hazardous chemical storage rooms. This application does not impose limitations on the scenarios in which the method for generating fire simulation results for nuclear power plants can be applied; specific scenarios can be set according to actual conditions.

[0036] Next, we will describe the device used to generate fire simulation results for nuclear power plants from the perspective of its function, such as... Figure 2 As shown, Figure 2This is a schematic flowchart illustrating a method for generating fire simulation results for nuclear power plants, provided in an embodiment of this application. The method for generating fire simulation results for nuclear power plants is applied to an apparatus for generating fire simulation results for nuclear power plants. Figure 2 The method may include, but is not limited to, steps 210 to 250. When the device for generating fire simulation results for nuclear power plants executes the method for generating fire simulation results for nuclear power plants, the specific process is as follows. It should be noted first that this embodiment... Figure 2 The order of steps 210 to 250 is not specifically limited. The order of steps can be adjusted or some steps can be reduced or added according to actual needs.

[0037] Step 210: Obtain the gas pressure and thermal parameters of the mixed gas in the target space, and obtain the first gas state of the hot flue gas layer and the second gas state of the cold air layer below the hot flue gas layer in the target space. Step 220: Determine the gas physical properties of the mixed gas based on the thermal parameters, and determine the gas compressibility factor of the mixed gas based on the gas pressure. Step 230: Update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor to obtain the updated first gas state of the hot flue gas layer and the updated second gas state of the cold air layer at the target time step. Update the gas pressure according to the gas physical properties and the gas compressibility factor to obtain the updated gas pressure. Step 240: Based on the updated gas pressure, the updated first gas state, and the updated second gas state, update the gas physical properties and the gas compressibility factor respectively to obtain the updated gas physical properties and the updated gas compressibility factor. Then, based on the updated gas physical properties and the updated gas compressibility factor, update the thermal parameters to obtain the updated thermal parameters at the target time step. Step 250: Return to the step of updating the first gas state and the second gas state according to the gas physical properties and gas compressibility factor, until the preset time step is reached. Then, generate the fire simulation result of the target space according to the first gas state, the second gas state, the gas pressure and the thermal parameters at each target time step.

[0038] Steps 210 to 250 are described in detail below.

[0039] In step 210, the gas pressure and thermal parameters of the mixed gas in the target space are obtained, and the first gas state of the hot flue gas layer and the second gas state of the cold air layer below the hot flue gas layer in the target space are obtained.

[0040] The target space refers to the physical area used for fire simulation calculations. In model calculations, the initial area is typically divided into different control volumes (such as independent rooms or compartments within a building) using methods like fixed meshes. These control volumes correspond to the target space and facilitate discretization analysis and numerical solutions for the fire evolution process. For example... Figure 3 As shown, Figure 3 This is a schematic diagram of an initial region provided in an embodiment of this application. The initial region includes control body 1, control body 2 and control body 3. Each control body corresponds to a target space. Using the method proposed in this embodiment, fire simulation results can be generated for each target space to obtain the fire simulation results corresponding to the initial region.

[0041] Among them, mixed gas refers to a complex gaseous mixture that fills the target space when a fire occurs, consisting of the original air, high-temperature smoke generated by combustion, unburned volatiles and other gaseous products. It exhibits strong non-ideal gas characteristics under high temperature and high pressure in the fire scene.

[0042] Among them, gas pressure refers to the pressure exerted on the surrounding boundaries by the mixed gas within the target space during its thermodynamic evolution. During a fire, this parameter fluctuates drastically with changes in temperature and composition. Thermal parameters refer to the collection of various physical quantities that control the thermodynamic state of the gas within the space, mainly including parameters such as gas temperature and composition.

[0043] The mixed gas is further divided into a hot flue gas layer and a cold air layer. For example... Figure 4 As shown, Figure 4 This is a schematic diagram of a target space provided in an embodiment of this application. Each target space is divided into two main physical layers: an upper region is a hot smoke layer where high-temperature gases accumulate, and a lower region is a cold air layer less directly affected by the fire. A combustion source is located at the center of the bottom of the target space, releasing heat to the surrounding area. The high-temperature substances produced by combustion form a vertically upward plume, continuously transporting heat and combustion products to the top hot smoke layer. During this upward movement, the plume draws in surrounding cooler gases, resulting in air entrainment. The target space also has horizontal ventilation on the side walls, where fresh external air flows into the cold air layer from below, while the internal high-temperature smoke is discharged to the outside from above. Vertical vents are provided at the top structure for vertical gas exchange. The causes of "horizontal ventilation" and "vertical ventilation" correspond to... Figure 3 The doors and windows between different control units are interconnected; additionally, there is a heat conduction process between the current target space and other target spaces on the side of the wall, and the cause of "heat conduction" corresponds to... Figure 3 Different control bodies are separated by walls, and walls have a certain degree of thermal conductivity.

[0044] The hot flue gas layer refers to a relatively independent gaseous stratification formed above the control volume due to the thermal expansion of the high-temperature mixed gas produced by combustion, which rises and converges under the action of thermal buoyancy. This stratification is characterized by high temperature and is rich in combustion products. The first gas state is a general term for the overall physical characteristics of the hot flue gas layer at a specific time step. It specifically includes the real-time numerical values ​​of the layer's volume, mass, and other parameters at the current moment.

[0045] The cold air layer refers to the gaseous stratification formed in the space below the control body due to the rising of hot smoke. It is less affected by direct heating from the fire, has a relatively low temperature, and is mainly composed of unburned air. During the fire's evolution, it continuously exchanges mass and energy with the upper hot smoke layer. The second gas state is a general term for the overall physical characteristics of the cold air layer at a specific time step, correspondingly including the real-time numerical values ​​of the cold air layer's mass, temperature, and other parameters at that moment.

[0046] In step 220, the gas physical properties of the mixed gas are determined based on the thermal parameters, and the gas compressibility factor of the mixed gas is determined based on the gas pressure.

[0047] Among them, gas physical properties mainly include parameters such as isobaric specific heat capacity, isochoric specific heat capacity, specific gas constant, and molar mass. In a real fire environment, with the rapid increase in temperature and the continuous mixing of various complex combustion products, the gas physical properties of the mixed gas will undergo significant dynamic changes. The gas physical properties at each target time step are one of the keys to recreating the fire occurrence process. The gas compressibility factor is used to measure the degree to which real gas deviates from the behavior of an absolutely ideal gas under specific temperature and pressure conditions. In the embodiments of this application, by introducing the gas compressibility factor to correct the traditional ideal gas equation of state, the nonlinear volume and pressure changes caused by high temperature, closed high pressure, and multi-component mixing in the fire scene can be accurately included in the calculation scope, thereby significantly improving the accuracy of fire simulation under complex conditions.

[0048] In some embodiments, determining the gas physical properties of the mixed gas based on thermal parameters includes: (1.1) Determine the gas composition of the mixed gas based on the thermal parameters. The gas composition shall include at least the molar mass, molar fraction, specific heat capacity at constant volume and specific heat capacity at constant pressure of each gas in the mixed gas. (1.2) Determine the physical properties of the gas mixture based on its composition.

[0049] In some embodiments, thermal parameters reflect the physical environment of the gas within the target space. By analyzing the thermal parameters, the specific chemical composition and products contained in the gas mixture under the current environmental conditions can be obtained, i.e., the gas composition. The gas composition includes at least: Molar mass refers to the mass of a unit amount of a substance, usually represented by the symbol M, and commonly measured in grams per mole (g / mol) or kilograms per mole (kg / mol). In calculations involving gas mixtures, the molar mass of a single-component gas is a fundamental physical quantity for establishing the relationship between macroscopic mass and the number of microscopic particles. By combining the molar masses of each component and their proportions, the average molar mass of the entire gas mixture can be further derived and calculated.

[0050] Mole fraction refers to the ratio of the amount of a specific component in a gas mixture to the total amount of the mixture. It is a dimensionless, purely numerical value. In multi-component gas systems, mole fraction is used to accurately characterize the concentration or compositional proportion of each gas component. It is a core fundamental parameter for weighted solutions to the overall macroscopic physical properties of gas mixtures (such as equivalent gas constant, specific heat capacity of mixing, etc.).

[0051] Specific heat capacity at constant volume refers to the amount of heat absorbed or released when the temperature of a unit mass of a gas changes by 1 K (or 1 °C) under the condition that the volume of the gas mixture remains strictly constant. From a thermodynamic perspective, since the gas does not perform volume expansion work during a constant-volume process, all the heat absorbed is converted into an increase in the system's thermodynamic energy (internal energy). Therefore, specific heat capacity at constant volume is a direct physical property parameter characterizing the rate of change of the gas's internal thermodynamic energy with temperature.

[0052] The isobaric specific heat capacity refers to the amount of heat absorbed or released when the temperature of a unit mass of a gas changes by 1 K (or 1 °C) under constant pressure conditions. In isobaric heating, the heat absorbed by the gas mixture is not only used to increase the thermodynamic energy of the gas, but also must overcome the external constant pressure to do expansion work. Therefore, the isobaric specific heat capacity of the same gas is necessarily greater than the isochoric specific heat capacity.

[0053] In some embodiments, determining the gas physical properties of the gas mixture based on its gas composition includes: (1.2.1) Determine the average specific gas constant of the mixture based on the molar mass and mole fraction of all gases; (1.2.2) Determine the average specific heat capacity of the mixed gas based on the mole fraction and constant volume specific heat capacity of all gases; (1.2.3) Determine the average isobaric specific heat capacity of the mixed gas based on the mole fraction and isobaric specific heat capacity of all gases; (1.2.4) Determine the gas physical properties of the mixed gas based on the average specific gas constant, average constant volume specific heat capacity and average constant pressure specific heat capacity.

[0054] Furthermore, the average specific gas constant is determined using the following formula. : .in, R This represents the gas constant, and its value is usually 8.314 J / (mol-K); y i This represents the mole fraction of the i-th gas; M i The molar mass of the i-th gas is represented. The same parameters have the same meaning in the embodiments of this application and will not be repeated hereafter.

[0055] Furthermore, the average constant-volume specific heat capacity is determined using the following formula. : .in, Indicates the first i Specific heat capacity at constant volume. Specific heat capacity at constant volume represents the amount of heat required to raise the temperature of a unit mass of a substance by 1 Kelvin (K) or 1 degree Celsius (°C) while keeping the volume of the corresponding gas constant. Its SI unit is joules per kilogram of Kelvin (J / (mol-K)).

[0056] Furthermore, the average isobaric specific heat capacity is determined using the following formula. : .in, Indicates the first i The specific heat capacity at constant pressure is the amount of heat required to raise the temperature of a unit mass of a substance by 1 Kelvin (K) or 1 degree Celsius (°C) under constant pressure.

[0057] In addition, the adiabatic index can be further determined using the following formula. : The adiabatic index is used to characterize the thermodynamic energy conversion properties of a non-ideal gas mixture during thermal expansion, compression, and heat absorption / release processes within a closed control body.

[0058] It is understood that the embodiments of this application start from the microscopic composition level of the gas, and deconstruct the specific components of the mixed gas and its corresponding multiple basic thermodynamic parameters through thermal parameters; furthermore, the discrete properties of a single gas at the microscopic level are aggregated into average parameters that characterize the overall macroscopic properties, so that the parameters of the hot flue gas layer and the cold air layer can be updated according to the average parameters of the mixed gas.

[0059] In some embodiments, determining the gas compressibility factor of the gas mixture based on the gas pressure includes: (2.1) Obtain the thermodynamic temperature of the mixed gas; (2.2) Determine the temperature-related intermolecular attraction parameters based on the thermodynamic temperature; (2.3) Obtain the intrinsic volume parameters of the molecules, and determine the molar volume of the gas mixture based on the intrinsic volume parameters of the molecules and the intermolecular attraction parameters; (2.4) Determine the gas compressibility factor of the gas mixture based on the gas pressure, thermodynamic temperature and gas molar volume.

[0060] In some embodiments, the gas molar volume of the gas mixture is determined by the following formula. : .in, Indicates the thermodynamic temperature of the gas mixture; This represents the intermolecular attraction parameter, which is related to thermodynamic temperature; Indicates the intrinsic volume parameter of a molecule; This indicates gas pressure.

[0061] Furthermore, the gas compressibility factor of the gas mixture is determined using the following formula. Z : .

[0062] It is understood that the embodiments of this application accurately derive the gas molar volume of the mixed gas by considering the interaction forces between gas molecules and the nonlinear influence of the physical volume of the molecules themselves on the macroscopic state under extreme fire conditions, and then calculate the actual gas compressibility factor at the current time step, so as to update the gas state of each gas layer at the current time step based on the gas compressibility factor that affects the nonlinear transformation of the gas.

[0063] In step 230, the first gas state and the second gas state are updated according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step. The gas pressure is also updated according to the gas physical properties and the gas compressibility factor to obtain the updated gas pressure.

[0064] In some embodiments, after determining the gas physical properties and gas compressibility factor of the mixed gas, the changes in the gas physical properties and gas compressibility factor of each gas layer in each time step are ignored. The updated gas state changes of each gas layer in the current time step (target time step) are solved based on the gas physical properties and gas compressibility factor. This allows for iterative updates of various gas state parameters of the hot smoke layer and cold air layer at the time step level, thereby characterizing the dynamic migration of matter and energy inside the fire scene.

[0065] It should be noted that the first gas state, the second gas state, and the gas pressure are obtained through synchronous updates.

[0066] In some embodiments, the first gas state and the second gas state are updated according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step, including: (3.1) Based on the physical properties of the gas, the gas compressibility factor, the first gas state and the second gas state, determine the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer; (3.2) Determine the first residual based on the first mass-energy change rate and the first gas state, and determine the second residual based on the second mass-energy change rate and the second gas state; (3.3) Update the first gas state according to the first residual to obtain the updated first gas state, and update the second gas state according to the second residual to obtain the updated second gas state; (3.4) Return to the step of determining the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer based on the gas physical properties, gas compressibility factor, first gas state and second gas state; (3.5) Until both the first residual and the second residual satisfy the preset first convergence condition, the first gas state of the hot flue gas layer after the target time step and the second gas state of the cold air layer after the target time step are obtained.

[0067] In some embodiments, the first mass-energy change rate and the second mass-energy change rate refer to the rate of change of mass and energy of the hot flue gas layer and the cold air layer in the target space per unit time due to physical phenomena such as ventilation, heat transfer, and combustion. The first mass-energy change rate includes a first mass change rate and a first energy change rate, and the second mass-energy change rate includes a second mass change rate and a second energy change rate.

[0068] First, the steps (3.1) will be explained in detail: In some embodiments, determining the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer based on gas physical properties, gas compressibility factor, a first gas state, and a second gas state includes: (3.1.1) Based on the physical properties of the gas, the gas compressibility factor, and the first gas state, determine the first estimated temperature, the first density, and the first internal energy of the hot flue gas layer; (3.1.2) Based on the physical properties of the gas, the gas compressibility factor, and the second gas state, determine the second estimated temperature, the second density, and the second internal energy of the cold air layer; (3.1.3) Input the first estimated temperature, the first density and the first internal energy into the pre-trained constitutive model and output the first mass-energy change rate of the hot flue gas layer. Input the second estimated temperature, the second density and the second internal energy into the pre-trained constitutive model and output the second mass-energy change rate of the cold air layer. The pre-trained constitutive model is trained based on the sample estimated temperature, sample density and sample internal energy of the sample gas.

[0069] In some embodiments, the first estimated temperature of the hot flue gas layer is determined by the following formula. : .in, This represents the volume of the hot flue gas layer in the previous time step. This indicates the mass of the hot flue gas layer in the previous time step. and It was determined based on the first gas state.

[0070] Furthermore, the first density of the thermal flue gas layer is determined using the following formula. : .

[0071] Furthermore, the first internal energy of the hot flue gas layer is determined using the following formula. : 。

[0072] In some embodiments, the first estimated temperature of the cold air layer is determined using the following formula. : .in, This represents the volume of the cold air layer at the previous time step. This indicates the mass of the cold air layer at the previous time step. and It was determined based on the state of the second gas.

[0073] Furthermore, the second density of the cold air layer is determined using the following formula. : .

[0074] Furthermore, the second internal energy of the cold air layer is determined using the following formula. : .

[0075] In some embodiments, a first estimated temperature, a first density, and a first internal energy are input into a pre-trained constitutive model to output a first mass-energy equivalence rate of change for the hot flue gas layer; then, a second estimated temperature, a second density, and a second internal energy are input into the pre-trained constitutive model to output a second mass-energy equivalence rate of change for the cold air layer. The constitutive model is used to describe the macroscopic state evolution of matter in response to external physical effects. The constitutive model is pre-trained using a large amount of historical sample gas data containing the sample's estimated temperature, density, and internal energy. Furthermore, by inputting the various state parameters of the current hot flue gas layer and the cold air layer into the pre-trained model, the pre-trained constitutive model can calculate the dynamic changes in each compartment caused by physical phenomena such as ventilation, heat transfer, and combustion, and output the first and second mass-energy equivalence rates of change that cause the changes in mass and energy of these two regions over time.

[0076] It is understood that, by combining non-ideal gas parameters such as gas compressibility factor, the embodiments of this application first accurately calculate the local estimated temperature, density and internal energy of each layer in the dual-region model, and then use the pre-trained constitutive model to output the first mass-energy change rate used to update the first gas state and the second mass-energy change rate used to update the second gas state, thereby reducing the difficulty of solving complex fluid dynamics coupling equations.

[0077] Next, steps (3.2) to (3.3) will be described: Furthermore, a first residual is determined based on the first mass-energy equivalence rate and the first gas state. The residual refers to the difference between the left-hand and right-hand terms of the pre-defined conservation equation; theoretically, the residual should approach zero when the equation fully converges. In this embodiment, the aforementioned first and second mass-energy equivalence rates, along with the first gas state of the hot flue gas layer and the second gas state of the cold air layer, are substituted into the differential-algebraic conservation equations of each control volume to calculate the first and second residuals corresponding to the equations solved at the current time step. This allows for a precise assessment of the deviation between the current state and the physical conservation laws.

[0078] Among them, the volume of the hot flue gas layer is solved. The conservation equations are as follows: .in, Z Indicates the gas compressibility factor. The adiabatic index is determined by both the average isochoric specific heat capacity and the average isobaric specific heat capacity. P Indicates gas pressure; This represents the first energy change rate of the hot flue gas layer.

[0079] The conservation equation for the mass of the hot flue gas layer is as follows: .in, This represents the first rate of change of mass in the hot flue gas layer.

[0080] Furthermore, the conservation equations for the masses of each component in the hot flue gas layer are solved as follows: .in, This represents the rate of change of the mass of the i-th gas in the hot flue gas layer.

[0081] Furthermore, by obtaining the spatial geometric parameters of the target space, namely its length, width, and height, the volume of the target space can be determined. Based on this, and knowing the volume of the thermal flue gas layer... In this case, the volume of the cold air layer can be calculated using the following formula: .in, Indicates the volume of the cold air layer; It represents the spatial volume of the target space.

[0082] Furthermore, the mass of the cold air layer is determined. The conservation equations are as follows: .in, This represents the second rate of change of mass in the cold air layer.

[0083] Furthermore, the mass of each component in the cold air layer is calculated. The conservation equations are as follows: .in, This represents the rate of change of the mass of the i-th gas in the hot flue gas layer.

[0084] Furthermore, the specific process of solving for the first and second residuals essentially involves calculating the difference between the estimated values ​​of the time derivatives of each state variable and the theoretically calculated values. Specifically, for the hot flue gas layer, the estimated values ​​of the time derivative terms of the layer's volume, total mass, and the mass of each component are first calculated using numerical discretization methods (i.e., the values ​​on the left side of the conservation equation). , , Subtract the theoretical algebraic terms on the right side of the corresponding equation from each of the two residuals to obtain the set of differences. Similarly, the second residual is calculated for the cold air layer.

[0085] Next, proceed with steps (3.4) to (3.5): In some embodiments, within a set target time step, the device constructs a cyclic feedback calculation loop to call up the current gas physical properties, gas compressibility factor, and instantaneous state quantities of the two gas layers in real time, thereby continuously calculating and correcting the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer.

[0086] Furthermore, during the continuous iterative calculations described above, the device will simultaneously monitor and evaluate the first and second residuals of the current equation solution. Once both residuals satisfy the preset first convergence condition, it is determined that the numerical approximation within the current time step has reached the set accuracy requirement, thereby triggering the termination of the iteration. Finally, the system solidifies and outputs the updated first gas state of the hot flue gas layer and the updated second gas state of the cold air layer at the target time step, which can be used as reliable initial boundary conditions for the simulation of the next time step.

[0087] In some embodiments, updating the gas pressure based on gas physical properties and gas compressibility factor to obtain an updated gas pressure includes: (4.1) Obtain the spatial geometric parameters of the target space; (4.2) The gas pressure is updated based on the spatial geometric parameters, gas compressibility factor, gas physical properties, the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer to obtain the updated gas pressure.

[0088] In some embodiments, the updated gas pressure is obtained using the following formula: .in, V table Indicate spatial geometric parameters; The adiabatic index is determined based on the physical properties of the gas. This represents the first mass-energy change rate of the hot flue gas layer; This represents the rate of change of the second mass-energy of the cold air layer.

[0089] It is understood that the embodiments of this application combine the gas compressibility factor and gas physical properties, which reflect the true properties of non-ideal gases, with the first mass-energy change rate of the hot smoke layer and the second mass-energy change rate of the cold air layer, which characterize the dynamic evolution of the two regions, to quantify the gas state of the two independent gas layers at the corresponding time step in the fire evolution, thereby being able to realistically reproduce the fire simulation results under extreme conditions such as high temperature and confinement in the fire scene.

[0090] In step 240, the gas physical properties and gas compressibility factor are updated according to the updated gas pressure, the updated first gas state, and the updated second gas state, respectively, to obtain the updated gas physical properties and the updated gas compressibility factor. The thermal parameters are then updated according to the updated gas physical properties and the updated gas compressibility factor to obtain the updated thermal parameters at the target time step.

[0091] During the fire evolution process, the drastic changes in the temperature, pressure and composition of the gas can cause its physical properties to evolve nonlinearly. In the aforementioned steps, the embodiments of this application update the first gas state and the second gas state while ignoring the changes in the gas physical properties and gas compressibility factors in each gas layer at each time step. After completing the update of the first gas state and the second gas state at the target time step, it is necessary to update the gas physical properties and gas compressibility factors so that in the next time step, the updated gas physical properties and updated gas compressibility factors can be used to continue to update the relevant parameters of the fire simulation results.

[0092] In some embodiments, the thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated thermal parameters at the target time step, including: (5.1) Determine the first thermal parameters of the hot flue gas layer and the second thermal parameters of the cold air layer based on the thermal parameters; (5.2) Update the first thermal parameter and the second thermal parameter respectively to obtain the updated first thermal parameter and the updated second thermal parameter; (5.3) Determine the thermal parameters at the target time step based on the updated first thermal parameters and the updated second thermal parameters.

[0093] In some embodiments, the first thermal parameters of the hot flue gas layer and the second thermal parameters of the cold air layer are further refined and allocated based on the thermal parameters of the mixed gas. The first thermal parameters include local state parameters such as the temperature of the hot flue gas layer, and the second thermal parameters include local state parameters such as the temperature of the cold air layer.

[0094] It should be noted that the first and second estimated temperatures determined in steps (3.1.1) to (3.1.3) are actually intermediate transitional parameters derived from the initial state before the update. Their core function is merely to provide the constitutive model with prerequisite input conditions so as to calculate the mass-energy change rate that triggers the physical evolution.

[0095] However, after solving for the rate of change of mass-energy, iterating the residuals, and dynamically updating the core independent variables, the distribution of matter and energy in the target space has undergone a real nonlinear shift. The original predicted temperature can no longer represent the updated physical state. Based on this, this embodiment will, after completing a round of dynamic time step extrapolation, combine the synchronously updated gas compressibility factor and gas physical properties to perform a final recalculation and calibration of local thermodynamic parameters such as temperature, thereby ensuring that all microscopic state parameters output by the entire dual-region model at the end of the current target time step are consistent with the macroscopic physical laws.

[0096] In some embodiments, updating the first thermal parameter and the second thermal parameter respectively to obtain updated first thermal parameters and updated second thermal parameters includes: (5.2.1) Taking the mass-energy conservation of the hot flue gas layer at the target time step as a constraint, the first thermal parameters are updated according to the updated gas physical properties and the updated gas compressibility factor to obtain the updated first thermal parameters at the target time step. (5.2.2) Taking the mass-energy conservation of the cold air layer at the target time step as a constraint, the second thermal parameters are updated according to the updated gas physical properties and the updated gas compressibility factor to obtain the updated second thermal parameters at the target time step. In some embodiments, based on the laws of conservation of mass and energy, and utilizing the latest updated gas physical properties and gas compressibility factors, the estimated temperature, internal energy, and other state variables of the hot flue gas layer are recalculated and corrected, thereby outputting the actual first thermal parameters of the layer at the current time step. Similarly, with the mass-energy conservation of the cold air layer at the target time step as a constraint, the second thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factors to obtain the updated second thermal parameters at the target time step.

[0097] Furthermore, due to the highly nonlinear and strongly coupled relationship between the gas compressibility factor, physical properties, and thermal parameters such as pressure and temperature of the mixed gas under complex fire conditions (for example, the calculation of the compressibility factor is highly dependent on the current temperature and pressure, and the updating of temperature and pressure, in turn, must depend on the compressibility factor), it is impossible to obtain an accurate solution directly through a single algebraic operation. Therefore, this embodiment of the application requires iterative solution loops for step 240, using the thermal parameters obtained from the previous round of back-calculation as the baseline input for the new round of calculation, and continuously updating the gas compressibility factor and various thermal parameters alternately. The convergence criterion here refers to a pre-set, extremely small error allowable threshold. When the system detects that the difference in the numerical changes of all thermal parameters in two adjacent iterations has narrowed to within this threshold, it determines that the current iteration process has found a stable and true numerical solution that conforms to the physical conservation law, and terminates the cyclic update within this time step.

[0098] It is understood that the embodiments of this application construct a rigorous parameter iteration mechanism from macro to local and then from local back to macro. By decoupling the thermal parameters of the overall space into first thermal parameters and second thermal parameters, and introducing updated gas compressibility factors and gas physical properties, the precise correction of gas state variables at each layer is achieved under the premise of complying with the dual-region mass-energy conservation law. This effectively avoids global numerical distortion caused by drastic changes in local parameters in traditional single-region or constant property models. It not only ensures physical consistency within a very short time step, but also significantly improves the overall accuracy and reliability of the thermal parameters output by the building fire simulation system when dealing with extreme non-ideal gas conditions.

[0099] In step 250, the process returns to updating the first gas state and the second gas state according to the gas physical properties and gas compressibility factor, until a preset time step is reached. Then, based on the first gas state, the second gas state, gas pressure, and thermal parameters at each target time step, the fire simulation results of the target space are generated.

[0100] In some embodiments, within a preset time step, the iterative loop of the numerical calculation of the entire transient non-ideal gas dual-region model is controlled, and after the closed-loop calculation of the entire time period is completed, the first gas state, second gas state, gas pressure and thermal parameters that are constantly evolving under all time steps are summarized. Since these parameters are the key parameters of the fire simulation results, based on these parameters, the fire simulation results that fully reflect the transient changes of thermal and hydraulic parameters under specific fire conditions can be finally output.

[0101] It is understood that the embodiments of this application creatively introduce and continuously update the gas compressibility factor and gas physical properties in both directions during the iterative loop of the time step, thereby incorporating non-ideal gas behavior into the model scope. Based on the gas compressibility factor and gas physical properties, the nonlinear evolution of the hot smoke layer and the cold air layer under complex fire conditions is characterized. As a result, the embodiments of this application improve the accuracy and reliability of building fire simulation results, and can effectively meet the engineering needs of high-level safety buildings such as nuclear power plants for accurate prediction of fire hazards.

[0102] like Figure 5 As shown, Figure 5 This is a schematic diagram of the module structure of a device for generating fire simulation results for nuclear power plants, provided in an embodiment of this application. The device 300 for generating fire simulation results for nuclear power plants may include the following modules 310 to 360: The acquisition module 310 is used to acquire the gas pressure and thermal parameters of the mixed gas in the target space, and to acquire the first gas state of the hot flue gas layer in the target space and the second gas state of the cold air layer below the hot flue gas layer. The mixed gas characteristic determination module 320 is used to determine the gas physical properties of the mixed gas based on thermal parameters and to determine the gas compressibility factor of the mixed gas based on gas pressure. The first update module 330 is used to update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer and the updated second gas state of the cold air layer at the target time step, and to update the gas pressure according to the gas physical properties and the gas compressibility factor to obtain the updated gas pressure. The second update module 340 is used to update the gas physical properties and gas compressibility factor according to the updated gas pressure, the updated first gas state and the updated second gas state, respectively, to obtain the updated gas physical properties and the updated gas compressibility factor, and to update the thermal parameters according to the updated gas physical properties and the updated gas compressibility factor, to obtain the updated thermal parameters at the target time step. The fire simulation result generation module 350 is used to return to the execution steps of updating the first gas state and the second gas state according to the gas physical properties and gas compressibility factor, until the preset time step is reached. Then, based on the first gas state, the second gas state, the gas pressure and the thermal parameters at each target time step, the fire simulation result of the target space is generated.

[0103] In some embodiments, the gas mixture characteristic determination module 320 is used for: The gas composition of the gas mixture is determined based on thermal parameters. The gas composition includes at least the molar mass, molar fraction, specific heat capacity at constant volume, and specific heat capacity at constant pressure of each gas in the gas mixture. Based on the gas composition, the physical properties of the mixed gas are determined.

[0104] In some embodiments, the gas mixture characteristic determination module 320 is further configured to: The average specific gas constant of the mixture is determined based on the molar mass and molar fraction of all gases. The average specific heat capacity of the mixed gas is determined based on the mole fraction and specific heat capacity at constant volume of all gases. The average isobaric specific heat capacity of the gas mixture is determined based on the mole fraction and isobaric specific heat capacity of all gases. The gas physical properties of the mixed gas are determined based on the average specific gas constant, average constant volume specific heat capacity, and average constant pressure specific heat capacity.

[0105] In some embodiments, the gas mixture characteristic determination module 320 is further configured to: Obtain the thermodynamic temperature of the gas mixture; The temperature-dependent intermolecular attraction parameters are determined based on thermodynamic temperature; Obtain the intrinsic volume parameters of the molecules, and determine the molar volume of the gas mixture based on the intrinsic volume parameters of the molecules and the intermolecular attraction parameters; The gas compressibility factor of the gas mixture is determined based on the gas pressure, thermodynamic temperature, and gas molar volume.

[0106] In some embodiments, the first update module 330 is used for: Based on the physical properties of the gas, the gas compressibility factor, the first gas state, and the second gas state, the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer are determined. The first residual is determined based on the first mass-energy change rate and the first gas state, and the second residual is determined based on the second mass-energy change rate and the second gas state. The first gas state is updated based on the first residual to obtain the updated first gas state, and the second gas state is updated based on the second residual to obtain the updated second gas state. Return to the step of determining the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer based on the gas physical properties, gas compressibility factor, first gas state and second gas state; Until both the first residual and the second residual satisfy the preset first convergence condition, the first gas state of the hot flue gas layer after the update at the target time step and the second gas state of the cold air layer after the update at the target time step are obtained.

[0107] In some embodiments, the first update module 330 is further configured to: Based on the physical properties of the gas, the gas compressibility factor, and the first gas state, the first estimated temperature, the first density, and the first internal energy of the hot flue gas layer are determined. Based on the physical properties of the gas, the gas compressibility factor, and the second gas state, the second estimated temperature, second density, and second internal energy of the cold air layer are determined. The first estimated temperature, first density, and first internal energy are input into the pre-trained constitutive model to output the first mass-energy change rate of the hot flue gas layer, and the second estimated temperature, second density, and second internal energy are input into the pre-trained constitutive model to output the second mass-energy change rate of the cold air layer. The pre-trained constitutive model is trained based on the sample gas's estimated temperature, sample density, and sample internal energy.

[0108] In some embodiments, the first update module 330 is further configured to: Obtain the spatial geometric parameters of the target space; The gas pressure is updated based on spatial geometric parameters, gas compressibility factor, gas physical properties, the first mass-energy change rate of the hot flue gas layer, and the second mass-energy change rate of the cold air layer, resulting in the updated gas pressure.

[0109] In some embodiments, the second update module 330 is further configured to: The first thermal parameters of the hot flue gas layer and the second thermal parameters of the cold air layer were determined based on the thermal parameters. The first thermal parameter and the second thermal parameter are updated respectively to obtain the updated first thermal parameter and the updated second thermal parameter; Based on the updated first thermal parameters and the updated second thermal parameters, the thermal parameters at the target time step are determined.

[0110] In some embodiments, the second update module 330 is further configured to: With the mass-energy conservation of the hot flue gas layer at the target time step as a constraint, the first thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated first thermal parameters at the target time step. With the mass-energy conservation of the cold air layer at the target time step as a constraint, the second thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated second thermal parameters at the target time step. The method and apparatus for generating fire simulation results in nuclear power plants proposed in this application obtain the gas pressure and thermal parameters of a mixed gas in a target space, and obtain the first gas state of the hot flue gas layer and the second gas state of the cold air layer below the hot flue gas layer in the target space; determine the gas physical properties of the mixed gas based on the thermal parameters, and determine the gas compressibility factor of the mixed gas based on the gas pressure; update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step, and adjust the gas pressure according to the gas physical properties and the gas compressibility factor. Update the gas pressure to obtain the updated gas pressure; based on the updated gas pressure, the updated first gas state, and the updated second gas state, update the gas physical properties and gas compressibility factor respectively to obtain the updated gas physical properties and gas compressibility factor, and update the thermal parameters based on the updated gas physical properties and gas compressibility factor to obtain the updated thermal parameters at the target time step; return to execute the step of updating the first gas state and the second gas state based on the gas physical properties and gas compressibility factor respectively, until the preset time step is reached, and generate the fire simulation results of the target space based on the first gas state, the second gas state, the gas pressure, and the thermal parameters at each target time step.

[0111] This application embodiment acquires the gas pressure, thermal parameters, and gas states of the hot flue gas layer and cold air layer of the mixed gas in the target space, and introduces the gas compressibility factor to participate in the iterative update of each parameter over time. This incorporates non-ideal gas behavior into the simulation, fully considering the nonlinear evolution of gas-related parameters under complex fire conditions. Therefore, the final fire simulation results can more realistically reflect the impact of actual gas property changes on the fire development process. Thus, this application embodiment can improve the accuracy of nuclear power plant fire simulation results, meeting the high-precision fire hazard prediction requirements of high-level safety buildings such as nuclear power plants.

[0112] like Figure 6 As shown, Figure 6 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. The electronic device includes: The processor 401 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 402 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 402 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 402 and is called and executed by the processor 401 to execute the method for generating fire simulation results for nuclear power plants according to the embodiments of this application. Input / output interface 403 is used to implement information input and output; The communication interface 404 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 405 transmits information between various components of the device (e.g., processor 401, memory 402, input / output interface 403, and communication interface 404); The processor 401, memory 402, input / output interface 403 and communication interface 404 are connected to each other within the device via bus 405.

[0113] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for generating fire simulation results for nuclear power plants.

[0114] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0115] The method and apparatus for generating fire simulation results in nuclear power plants proposed in this application obtain the gas pressure and thermal parameters of a mixed gas in a target space, and obtain the first gas state of the hot flue gas layer and the second gas state of the cold air layer below the hot flue gas layer in the target space; determine the gas physical properties of the mixed gas based on the thermal parameters, and determine the gas compressibility factor of the mixed gas based on the gas pressure; update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step, and adjust the gas pressure according to the gas physical properties and the gas compressibility factor. Update the gas pressure to obtain the updated gas pressure; based on the updated gas pressure, the updated first gas state, and the updated second gas state, update the gas physical properties and gas compressibility factor respectively to obtain the updated gas physical properties and gas compressibility factor, and update the thermal parameters based on the updated gas physical properties and gas compressibility factor to obtain the updated thermal parameters at the target time step; return to execute the step of updating the first gas state and the second gas state based on the gas physical properties and gas compressibility factor respectively, until the preset time step is reached, and generate the fire simulation results of the target space based on the first gas state, the second gas state, the gas pressure, and the thermal parameters at each target time step.

[0116] This application embodiment acquires the gas pressure, thermal parameters, and gas states of the hot flue gas layer and cold air layer of the mixed gas in the target space, and introduces the gas compressibility factor to participate in the iterative update of each parameter over time. This incorporates non-ideal gas behavior into the simulation, fully considering the nonlinear evolution of gas-related parameters under complex fire conditions. Therefore, the final fire simulation results can more realistically reflect the impact of actual gas property changes on the fire development process. Thus, this application embodiment can improve the accuracy of nuclear power plant fire simulation results, meeting the high-precision fire hazard prediction requirements of high-level safety buildings such as nuclear power plants.

[0117] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0118] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0119] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0120] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0121] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0122] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0124] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0125] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0126] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0127] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for generating fire simulation results for nuclear power plants, characterized in that, include: The gas pressure and thermal parameters of the mixed gas in the target space are obtained, and the first gas state of the hot flue gas layer in the target space and the second gas state of the cold air layer below the hot flue gas layer are obtained. The gas physical properties of the mixed gas are determined based on the thermal parameters, and the gas compressibility factor of the mixed gas is determined based on the gas pressure. Based on the gas physical properties and the gas compressibility factor, the first gas state and the second gas state are updated respectively to obtain the first gas state of the hot flue gas layer after the update at the target time step and the second gas state of the cold air layer after the update at the target time step. The gas pressure is also updated based on the gas physical properties and the gas compressibility factor to obtain the updated gas pressure. Based on the updated gas pressure, the updated first gas state, and the updated second gas state, the gas physical properties and the gas compressibility factor are updated respectively to obtain the updated gas physical properties and the updated gas compressibility factor. Based on the updated gas physical properties and the updated gas compressibility factor, the thermal parameters are updated to obtain the updated thermal parameters at the target time step. Return to the step of updating the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, until a preset time step is reached. Then, generate the fire simulation result of the target space according to the first gas state, the second gas state, the gas pressure and the thermal parameters at each target time step.

2. The method for generating fire simulation results for nuclear power plants according to claim 1, characterized in that, The determination of the gas physical properties of the mixed gas based on the thermal parameters includes: The gas composition of the mixed gas is determined based on the thermal parameters, and the gas composition includes at least the molar mass, molar fraction, specific heat capacity at constant volume, and specific heat capacity at constant pressure of each gas in the mixed gas. Based on the gas composition, the gas physical properties of the mixed gas are determined.

3. The method for generating fire simulation results for nuclear power plants according to claim 2, characterized in that, Determining the gas physical properties of the mixed gas based on the gas composition includes: The average specific gas constant of the gas mixture is determined based on the molar mass and molar fraction of all the gases. The average specific heat capacity of the mixed gas is determined based on the mole fraction and specific heat capacity at constant volume of all the gases. The average isobaric specific heat capacity of the gas mixture is determined based on the mole fraction and isobaric specific heat capacity of all the gases. The gas physical properties of the mixed gas are determined based on the average specific gas constant, the average constant volume specific heat capacity, and the average constant pressure specific heat capacity.

4. The method for generating fire simulation results for nuclear power plants according to claim 1, characterized in that, Determining the gas compressibility factor of the mixed gas based on the gas pressure includes: Obtain the thermodynamic temperature of the gas mixture; The temperature-dependent intermolecular attraction parameters are determined based on the thermodynamic temperature. Obtain the intrinsic volume parameters of the molecules, and determine the molar volume of the mixed gas based on the intrinsic volume parameters of the molecules and the intermolecular attraction parameters; The gas compressibility factor of the mixed gas is determined based on the gas pressure, the thermodynamic temperature, and the gas molar volume.

5. The method for generating fire simulation results for nuclear power plants according to claim 1, characterized in that, The step of updating the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the updated first gas state of the hot flue gas layer at the target time step and the updated second gas state of the cold air layer at the target time step, includes: Based on the physical properties of the gas, the gas compressibility factor, the first gas state, and the second gas state, the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer are determined. The first residual is determined based on the first mass-energy change rate and the first gas state, and the second residual is determined based on the second mass-energy change rate and the second gas state. The first gas state is updated based on the first residual to obtain the updated first gas state, and the second gas state is updated based on the second residual to obtain the updated second gas state. Return to the step of determining the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer based on the gas physical properties, the gas compressibility factor, the first gas state, and the second gas state; Until both the first residual and the second residual satisfy the preset first convergence condition, the first gas state of the hot flue gas layer after the update at the target time step and the second gas state of the cold air layer after the update at the target time step are obtained.

6. The method for generating fire simulation results for nuclear power plants according to claim 5, characterized in that, The step of determining the first mass-energy change rate of the hot flue gas layer and the second mass-energy change rate of the cold air layer based on the gas physical properties, the gas compressibility factor, the first gas state, and the second gas state includes: Based on the physical properties of the gas, the gas compressibility factor, and the first gas state, the first estimated temperature, the first density, and the first internal energy of the hot flue gas layer are determined. Based on the physical properties of the gas, the gas compressibility factor, and the second gas state, the second estimated temperature, the second density, and the second internal energy of the cold air layer are determined. The first estimated temperature, first density, and first internal energy are input into the pre-trained constitutive model to output the first mass-energy change rate of the hot flue gas layer, and the second estimated temperature, second density, and second internal energy are input into the pre-trained constitutive model to output the second mass-energy change rate of the cold air layer. The pre-trained constitutive model is trained based on the sample gas's estimated temperature, sample density, and sample internal energy.

7. The method for generating fire simulation results for nuclear power plants according to claim 6, characterized in that, The step of updating the gas pressure based on the gas physical properties and the gas compressibility factor to obtain the updated gas pressure includes: Obtain the spatial geometric parameters of the target space; The gas pressure is updated based on the spatial geometric parameters, the gas compressibility factor, the gas physical properties, the first mass-energy change rate of the hot flue gas layer, and the second mass-energy change rate of the cold air layer, to obtain the updated gas pressure.

8. The method for generating fire simulation results for nuclear power plants according to claim 1, characterized in that, The step of updating the thermal parameters based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated thermal parameters at the target time step includes: The first thermal parameters of the hot flue gas layer and the second thermal parameters of the cold air layer are determined based on the thermal parameters. The first thermal parameter and the second thermal parameter are updated respectively to obtain the updated first thermal parameter and the updated second thermal parameter; Based on the updated first thermal parameters and the updated second thermal parameters, the thermal parameters at the target time step are determined.

9. The method for generating fire simulation results for nuclear power plants according to claim 8, characterized in that, The step of updating the first thermal parameter and the second thermal parameter respectively to obtain the updated first thermal parameter and the updated second thermal parameter includes: Using the mass-energy conservation of the hot flue gas layer at the target time step as a constraint, the first thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated first thermal parameters. Using the conservation of mass-energy of the cold air layer at the target time step as a constraint, the second thermal parameters are updated based on the updated gas physical properties and the updated gas compressibility factor to obtain the updated second thermal parameters.

10. An apparatus for generating fire simulation results in a nuclear power plant, characterized in that, include: The acquisition module is used to acquire the gas pressure and thermal parameters of the mixed gas in the target space, and to acquire the first gas state of the hot flue gas layer in the target space and the second gas state of the cold air layer below the hot flue gas layer. A mixed gas characteristic determination module is used to determine the gas physical properties of the mixed gas based on the thermal parameters, and to determine the gas compressibility factor of the mixed gas based on the gas pressure. The first update module is used to update the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, to obtain the first gas state of the hot flue gas layer after the update at the target time step and the second gas state of the cold air layer after the update at the target time step, and to update the gas pressure according to the gas physical properties and the gas compressibility factor to obtain the updated gas pressure. The second update module is used to update the gas physical properties and the gas compressibility factor according to the updated gas pressure, the updated first gas state and the updated second gas state, respectively, to obtain the updated gas physical properties and the updated gas compressibility factor, and to update the thermal parameters according to the updated gas physical properties and the updated gas compressibility factor, to obtain the updated thermal parameters at the target time step. The fire simulation result generation module is used to return to the step of updating the first gas state and the second gas state according to the gas physical properties and the gas compressibility factor, respectively, until a preset time step is reached, and generate the fire simulation result of the target space according to the first gas state, the second gas state, the gas pressure and the thermal parameters at each target time step.

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