Small-aperture leakage working condition simulation and risk assessment device in fuel cabin of gas turbine

Abstract

The invention relates to the technical field of safety monitoring and risk assessment of gas turbines, in particular to a working condition simulation and risk assessment device for small-aperture leakage in a fuel cabin of a gas turbine. According to the technical scheme, the system comprises a model construction module, a transient simulation module, a diffusion feature recognition module, a multi-moment evaluation module and a risk level judgment module, wherein the model construction module constructs a fuel cabin three-dimensional model and sets a small-aperture leakage source; the transient simulation module is used for acquiring gas mass fraction distribution in the gas leakage and diffusion process; the diffusion characteristic identification module is used for identifying high-speed jet flow, top enrichment and wall surface diffusion characteristics; the multi-moment evaluation module compares the gas mass fractions at different positions with an alarm threshold value; and the risk level determination module outputs a corresponding risk level based on the comparison result. According to the invention, rapid simulation and risk grading evaluation of the gas small-aperture leakage working condition in the fuel cabin are realized, and a basis is provided for safety monitoring and protection.

Description

Technical Field

[0001] This invention relates to the field of gas turbine safety monitoring and risk assessment technology, and in particular to a device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine. Background Technology

[0002] Gas turbines are widely used in power, energy, and industrial power systems. Their fuel supply systems are typically housed in enclosed or semi-enclosed fuel tanks. The fuel tanks integrate gas pipelines, valves, joints, as well as purge pipes, louvers, and other structures. In the event of a gas leak, flammable gases can easily accumulate in the confined space, posing a significant risk of combustion and explosion.

[0003] Existing safety assessment methods for gas turbine fuel tanks mainly include leak detection, concentration monitoring, and experience-based hazard level assessment. Some studies analyze the gas leakage and diffusion process using numerical simulation, but most of these studies focus on large-aperture leaks, lacking sufficient accuracy for small-aperture leaks. They only present results at a single moment or the overall concentration field, lacking systematic identification and structured analysis of gas diffusion characteristics at different spatial locations and time points. Furthermore, they fail to control a reasonable simulation time step, making it difficult to capture the high-speed jet dynamics in the initial stage of small-aperture leaks, resulting in insufficient transient simulation accuracy.

[0004] Meanwhile, existing simulation analysis methods typically focus on outputting gas concentration distribution cloud maps, lacking a mechanism to automatically compare simulation results with alarm thresholds, and also lacking the ability to automatically identify key diffusion behaviors such as high-speed jet formation, top enrichment, wall diffusion, and external channel leakage, making it difficult to generate risk level assessment results that can be directly used for engineering decisions.

[0005] Furthermore, existing technologies for assessing gas leak risk are mostly based on single-point concentration or a single threshold, failing to comprehensively consider the proportion of gas diffusion range within the fuel tank, the concentration in key hazardous areas, and the evolution trend over time. This makes it difficult to accurately reflect the dynamic characteristics of the risk development within the fuel tank over time under small-aperture leak conditions.

[0006] To address this issue, we propose a device for simulating and assessing the risk of small-aperture leakage in the fuel tank of a gas turbine. Summary of the Invention

[0007] The purpose of this invention is to address the problems existing in the background art by proposing a device for simulating and assessing the operating conditions and risks of small-diameter leakage in the fuel tank of a gas turbine.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a device for simulating and assessing the operating conditions and risks of small-diameter leakage in the fuel tank of a gas turbine, comprising: The model building module is used to build a three-dimensional spatial model of the gas turbine fuel tank and to set a small-aperture gas leakage source facing the top of the fuel tank in the spatial model; The transient simulation module is used to perform transient numerical simulation of the diffusion process after a gas leak, and to obtain the gas mass fraction distribution along the preset X and Y directions in the fuel tank at different times. The diffusion feature identification module is used to identify the diffusion features of the gas after leakage, such as the gas forming a high-speed jet and being sprayed to the top of the fuel tank, and the gas spreading along the inner wall of the fuel tank, based on the gas mass fraction distribution. The multi-time assessment module is used to compare the fuel mass fraction at different spatial locations in the fuel tank with the alarm threshold at times including at least 2.5s, 5s, 7.5s and 50s. The risk level determination module is used to output the risk level of gas leakage in the fuel tank based on the comparison results of the multi-time assessment module.

[0009] Furthermore, the model building module includes a fuel tank geometry modeling unit and a leak source parameter setting unit; the leak source parameter setting unit is used to set the leak orifice diameter to a small orifice diameter and the leak direction to vertically upward; the three-dimensional space model built by the fuel tank geometry modeling unit includes the inlet and outlet of the purge pipe and louvers that are connected to the outside.

[0010] Furthermore, the transient simulation module includes a time step control unit and a multi-time data acquisition unit; the time step control unit is used to control the simulation time step to be no more than 0.1s in order to capture the dynamics of the rapid jet at the initial stage of leakage; the multi-time data acquisition unit is used to extract the gas mass fraction field corresponding to multiple times, and specifically collect the distribution data in the X and Y directions.

[0011] Furthermore, the diffusion feature identification module includes a jet identification unit, a top enrichment identification unit, and a wall diffusion identification unit; the top enrichment identification unit is used to identify that the mass fraction of gas in the area directly above the leak is greater than the maximum value of the high alarm threshold of 0.022 in the early stage of the leak; the wall diffusion identification unit is used to identify that the gas first diffuses laterally along the top wall and then diffuses downward along the side wall, and to identify that there is a phenomenon of gas diffusing out of the cabin through the inlet and outlet of the purging pipe during the diffusion process, and the maximum value of the high alarm threshold of 0.022 is calculated based on the lower explosion limit of gas.

[0012] Furthermore, the multi-time evaluation module is configured to perform the following spatiotemporal comparison logic: At 2.5s, it is determined whether the gas mass fraction in both the X and Y directions at the top of the fuel tank is greater than the minimum low alarm threshold of 0.0022; at 5s, it is determined whether the gas mass fraction in the lower left area of ​​the Y direction in the fuel tank reaches 0.0022, and whether there is gas diffusing out of the tank through the purge pipe inlet / outlet in the X direction; after 7.5s, it is determined whether the gas mass fraction in the remaining areas of the fuel tank, except for the areas on both sides near the louvers, is greater than 0.0022; at 50s, it is determined whether the gas mass fraction in most areas of the fuel tank reaches the minimum high alarm threshold of 0.011, and whether the top area reaches or exceeds the maximum high alarm threshold of 0.022.

[0013] Furthermore, the risk level determination module includes a threshold conversion unit and a classification determination unit. The threshold conversion unit is used to convert the lower limit of gas explosion into the corresponding mass fraction threshold. The classification determination unit is used to generate safe, low alarm, high alarm, and extremely high risk levels based on the range of mass fraction. The classification determination unit is also used to comprehensively determine the overall risk level by combining the proportion of gas diffusion range and the concentration at key locations.

[0014] Furthermore, the mass fraction thresholds include: 0.0022 corresponds to the minimum low alarm threshold; 0.011 corresponds to the minimum high alarm threshold; and 0.022 corresponds to the maximum high alarm threshold. The extremely high risk level determination criteria include: the concentration in the top area exceeds 0.022 and the diffusion range covers most of the cabin area.

[0015] Furthermore, the risk level determination module is used to output the risk level result and the corresponding spatial distribution map; the device also includes a report generation module, which is used to automatically generate a numerical simulation report containing the comparison results of the multi-time assessment module, the identification results of the diffusion feature identification module, and the final risk level determination.

[0016] Furthermore, the device also includes a trend prediction module, used to predict the distribution of gas mass fraction and risk level changes in the fuel tank at a future specified time based on the time series data obtained by the transient simulation module.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention sets up a model building module and a transient simulation module to perform three-dimensional spatial modeling of the gas turbine fuel tank and execute transient numerical simulation, thereby realizing the dynamic reproduction of the diffusion process after gas leakage through a small aperture. It can accurately obtain the gas mass fraction distribution at different times and in different spatial directions, and improve the spatiotemporal resolution of the simulation results. This invention uses a diffusion feature recognition module to automatically identify the high-speed jet formed after a gas leak, the phenomenon of top enrichment, and the behavior of lateral diffusion along the top wall and downward diffusion along the side wall. It can also identify the phenomenon of gas diffusion to the outside of the cabin through the inlet and outlet of the purge pipe, and can identify the characteristic that there is only a trace amount of gas infiltration and no obvious enrichment at the louvers, so that the diffusion mechanism is transformed from manual interpretation to automatic identification by the system. This invention uses a multi-time assessment module to compare the gas mass fraction at different spatial locations in the fuel tank with the alarm threshold at multiple key moments, thereby achieving phased assessment of the early, middle and late dangerous states of a leak and comprehensively reflecting the evolution of risk over time. This invention converts the lower limit of gas explosion into the corresponding mass fraction threshold by setting a threshold conversion unit and a classification judgment unit, and generates safe, low alarm, high alarm and extremely high risk levels according to the mass fraction range, so that risk judgment has a unified quantitative standard. In the process of risk level determination, this invention combines the proportion of gas diffusion range and the concentration information at key locations for comprehensive judgment, avoiding risk assessment based solely on the concentration at a single point, and improving the accuracy and reliability of the overall risk level determination. The present invention can also automatically generate a numerical simulation report containing diffusion characteristics, time comparison results and risk level determination, and can predict the distribution of gas mass fraction and risk change trend at a specified time in the future based on time series data, thereby improving the practicality and engineering guidance value of the device. In summary, this invention enables refined simulation and multi-dimensional risk assessment of gas diffusion behavior under small-aperture leakage conditions in gas turbine fuel tanks, providing reliable technical support for the safe design, operation monitoring, and emergency decision-making of gas turbine fuel tanks. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall architecture of the present invention; Figure 2 This is a schematic diagram of the overall workflow of the present invention; Figure 3 This is a schematic diagram of the multi-time evaluation logic flow of the present invention; Figure 4 This is a schematic diagram of the risk classification and determination process of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] like Figures 1-4 As shown, the present invention proposes a device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine, comprising: The model building module consists of a fuel tank geometry modeling unit and a leak source parameter setting unit, wherein: The fuel tank geometric modeling unit uses 3D modeling software to construct a 1:1 3D spatial model of the actual gas turbine fuel tank. This model not only restores the main cavity structure of the fuel tank, but also accurately sets the inlet and outlet of the purge pipe and louvers that connect with the outside. The louvers are symmetrically arranged in the middle of the two side walls of the fuel tank, and the inlet and outlet of the purge pipe are respectively set at both ends of the top of the fuel tank, connecting with the external ventilation system. The leakage source parameter setting unit sets the leakage orifice diameter to a small orifice diameter (specifically 1mm, which falls under the category of small orifice leakage), the leakage direction to vertically upward, and the leakage source to be located at the center of the bottom of the fuel tank, corresponding to the potential leakage point of the fuel delivery pipeline in the actual fuel tank. The vertical distance between the leakage source and the top of the fuel tank is 3m, simulating the injection path of the gas when the actual pipeline leaks.

[0021] The transient simulation module includes a time step control unit and a multi-time data acquisition unit. During implementation: The time step control unit sets the simulation time step to 0.05s to accurately capture the rapid jet dynamics of the gas in the early stages of the leak, avoiding the omission of initial diffusion characteristics due to excessively large time steps. The multi-moment data acquisition unit simulates the entire diffusion process after the gas leak using transient numerical simulation software (such as Fluent), extracting the gas mass fraction field corresponding to multiple key moments. It focuses on collecting the gas mass fraction distribution data in the preset X direction (horizontal direction of the fuel tank, i.e., the horizontal direction perpendicular to the direction of the leak source injection) and Y direction (longitudinal direction of the fuel tank, i.e., the horizontal direction parallel to the direction of the leak source injection), and stores it in real time to the data processing terminal to provide data support for subsequent diffusion characteristic identification and multi-moment evaluation.

[0022] The diffusion feature recognition module consists of a jet recognition unit, a top enrichment recognition unit, and a wall diffusion recognition unit. Its specific recognition process is as follows: Due to the high pressure in the actual fuel tank pipeline, the gas leaked from the leak source and rapidly formed a high-speed jet under pressure. The jet identification unit detected that the high-speed jet was spraying vertically upwards and quickly reached the top of the fuel tank. The top enrichment identification unit detected that in the initial stage of the leak (t < 2.5s), the gas mass fraction in the area directly above the leak point was greater than the maximum value of the high alarm threshold of 0.022 (this maximum value of the high alarm threshold of 0.022 is calculated based on the lower explosive limit of gas), and the gas mass fraction in the area near the leak point was greater than the minimum value of the low alarm threshold of 0.0022, while the gas mass fraction far from the leak point was small, almost close to 0. The wall diffusion identification unit detected that after the gas reached the top of the fuel tank, it first diffused along the horizontal X direction of the top wall to form a gas enrichment layer at the top. Then it diffused downwards along the inner walls of the fuel tank, including the side walls and the front and rear walls. At the same time, during the diffusion process, some gas diffused out of the tank through the inlet and outlet of the purge pipe, forming a small amount of gas leakage. No obvious gas enrichment was observed at the louvers, only a trace amount of gas infiltration.

[0023] The multi-time evaluation module uses 2.5s, 5s, 7.5s, and 50s as the core evaluation times, while also considering other intermediate times. It executes the following spatiotemporal comparison logic, marking each evaluation region. The specific implementation process is as follows: At t=2.5s: The multi-time assessment module comprehensively compares the gas mass fraction in the X and Y directions at the top of the fuel tank. The result shows that the gas mass fraction in this area is greater than the minimum low alarm threshold of 0.0022, and the gas mass fraction in some areas (the area directly above the leak) has exceeded the maximum high alarm threshold of 0.022, which is dangerous. At this time, the gas has begun to slowly diffuse downwards along the fuel tank wall.

[0024] At t=5s: Comparing the gas mass fraction in the lower left area of ​​the fuel tank in the Y direction, it is determined that the gas mass fraction in this area has reached 0.0022. At the same time, it is determined that there is gas diffusion to the outside of the tank in the X direction through the inlet and outlet of the purging pipe, and the mass fraction of the leaked gas is about 0.0015 (not reaching the low alarm threshold).

[0025] At t=7.5s and thereafter: the gas mass fraction in all areas of the fuel tank is compared. It is determined that except for the areas on both sides near the louvers (within 0.3m around the louvers), the gas mass fraction in the remaining areas is greater than 0.0022, reaching the minimum value of the low alarm threshold. At this time, the gas has diffused downwards along the wall to the middle height of the fuel tank, forming a relatively uniform gas distribution layer.

[0026] At t=50s: By comparing the overall gas mass fraction in the fuel tank, it is determined that the gas mass fraction in most areas of the fuel tank has reached the minimum high alarm threshold of 0.011, and the gas mass fraction in the middle area of ​​the top of the fuel tank in the X direction has exceeded 0.022, which exceeds the maximum high alarm threshold. At this time, the gas has basically filled the entire fuel tank, and only the area around the louvers still maintains a low concentration.

[0027] The risk level determination module includes a threshold conversion unit and a classification determination unit. The implementation process is as follows: The threshold conversion unit first converts the gas (natural gas in this embodiment) into the corresponding mass fraction threshold. Specifically, after conversion, 0.0022 corresponds to the minimum low alarm threshold, 0.011 corresponds to the minimum high alarm threshold, and 0.022 corresponds to the maximum high alarm threshold. The classification and determination unit generates four risk levels based on the range of gas mass fraction: safe level (mass fraction < 0.0022), low alarm level (0.0022 ≤ mass fraction < 0.011), high alarm level (0.011 ≤ mass fraction < 0.022), and extremely high risk level (mass fraction ≥ 0.022). At the same time, it combines the proportion of gas diffusion range and the concentration at key locations to comprehensively determine the overall risk level.

[0028] Based on the assessment results at multiple time points, the risk level at each time point is determined as follows: At t=2.5s, the overall level is low alarm level, while the local area (high concentration area at the top) is at an extremely high risk level. At t=5s, the overall alarm level is low, and a new low alarm area is added to the lower left of the Y direction; After t=7.5s, the overall alarm level is low, and the spread range covers most areas inside the cabin; At t=50s, the top area is at an extremely high risk level (concentration exceeds 0.022), and most areas inside the cabin are at a high alarm level. Based on the overall assessment, the risk level is extremely high.

[0029] The risk level determination module outputs the risk level results and corresponding spatial distribution maps in real time.

[0030] Meanwhile, the device's report generation module automatically generates a numerical simulation report, which includes all comparison results from the multi-time evaluation module, the identification results from the diffusion feature identification module (including jet features, wall diffusion features, and gas leakage features), and the final risk level determination results. It also includes gas mass fraction distribution curves in the X and Y directions at each time point, providing staff with a comprehensive basis for leak safety assessment.

[0031] The trend prediction module, based on time-series data (gas mass fraction distribution data from t=0 to t=50s) obtained by the transient simulation module, uses neural network prediction algorithms (such as LSTM long short-term memory neural network / BP neural network) to predict the gas mass fraction distribution and risk level changes in the fuel tank at a specified future time. For example, it predicts that at t=60s, the gas mass fraction in all areas of the fuel tank (including around the louvers) will exceed 0.0022, and the concentration in the top area will rise to 0.025, maintaining an overall extremely high risk level. It predicts that at t=80s, the gas mass fraction will tend to stabilize, with the average concentration in the tank remaining around 0.018, still at an extremely high risk level, providing advance prediction support for emergency response by personnel.

[0032] The above specific embodiments are merely several further embodiments of the present invention. Based on the technical solutions of the present invention and the relevant teachings of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

[0033] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of equivalents of the claims be included within the present invention.

Claims

1. A device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine, characterized in that, include: The model building module is used to build a three-dimensional spatial model of the gas turbine fuel tank and to set a small-aperture gas leakage source facing the top of the fuel tank in the spatial model; The transient simulation module is used to perform transient numerical simulation of the diffusion process after a gas leak, and to obtain the gas mass fraction distribution along the preset X and Y directions in the fuel tank at different times. The diffusion feature identification module is used to identify the diffusion features of the gas after leakage, such as the gas forming a high-speed jet and being sprayed to the top of the fuel tank, and the gas spreading along the inner wall of the fuel tank, based on the gas mass fraction distribution. The multi-time assessment module is used to compare the fuel mass fraction at different spatial locations in the fuel tank with the alarm threshold at times including at least 2.5s, 5s, 7.5s and 50s. The risk level determination module is used to output the risk level of gas leakage in the fuel tank based on the comparison results of the multi-time assessment module.

2. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 1, characterized in that: The model building module includes a fuel tank geometry modeling unit and a leak source parameter setting unit; the leak source parameter setting unit is used to set the leak orifice diameter to a small orifice diameter and the leak direction to vertically upward; the three-dimensional space model built by the fuel tank geometry modeling unit includes the inlet and outlet of the purge pipe and louvers that are connected to the outside.

3. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 1, characterized in that: The transient simulation module includes a time step control unit and a multi-time data acquisition unit; the time step control unit is used to control the simulation time step to be no more than 0.1s in order to capture the dynamics of the rapid jet at the initial stage of leakage; the multi-time data acquisition unit is used to extract the gas mass fraction field corresponding to multiple times, and specifically collect the distribution data in the X and Y directions.

4. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 1, characterized in that: The diffusion feature identification module includes a jet identification unit, a top enrichment identification unit, and a wall diffusion identification unit. The top enrichment identification unit is used to identify that the mass fraction of gas in the area directly above the leak point is greater than the maximum high alarm threshold of 0.022 in the early stage of the leak. The wall diffusion identification unit is used to identify that the gas first diffuses laterally along the top wall and then diffuses downward along the side wall, and to identify that there is a phenomenon of gas diffusing out of the cabin through the inlet and outlet of the purging pipe during the diffusion process. The maximum high alarm threshold of 0.022 is calculated based on the lower explosion limit of gas.

5. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 1, characterized in that: The multi-time evaluation module is configured to perform the following spatiotemporal comparison logic: At 2.5s, it is determined whether the gas mass fraction in both the X and Y directions at the top of the fuel tank is greater than the minimum low alarm threshold of 0.0022; at 5s, it is determined whether the gas mass fraction in the lower left area of ​​the Y direction in the fuel tank reaches 0.0022, and whether there is gas diffusing out of the tank through the purge pipe inlet / outlet in the X direction; after 7.5s, it is determined whether the gas mass fraction in the remaining areas of the fuel tank, except for the areas on both sides near the louvers, is greater than 0.0022; at 50s, it is determined whether the gas mass fraction in most areas of the fuel tank reaches the minimum high alarm threshold of 0.011, and whether the top area reaches or exceeds the maximum high alarm threshold of 0.

022.

6. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 1, characterized in that: The risk level determination module includes a threshold conversion unit and a classification determination unit. The threshold conversion unit is used to convert the lower limit of gas explosion into the corresponding mass fraction threshold. The classification determination unit is used to generate safe, low alarm, high alarm, and extremely high risk levels based on the range of mass fraction. The classification determination unit is also used to comprehensively determine the overall risk level by combining the proportion of gas diffusion range and the concentration at key locations.

7. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 6, characterized in that: The mass fraction thresholds include: 0.0022 corresponds to the minimum low alarm threshold; 0.011 corresponds to the minimum high alarm threshold; and 0.022 corresponds to the maximum high alarm threshold. The extremely high risk level determination criteria include: the concentration in the top area exceeds 0.022 and the diffusion range covers most of the cabin area.

8. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 1, characterized in that: The risk level determination module is used to output the risk level result and the corresponding spatial distribution map; the device also includes a report generation module, which is used to automatically generate a numerical simulation report containing the comparison results of the multi-time assessment module, the identification results of the diffusion feature identification module, and the final risk level determination.

9. The device for simulating and assessing the risk of small-diameter leakage in the fuel tank of a gas turbine according to claim 1, characterized in that: The device also includes a trend prediction module, which is used to predict the distribution of gas mass fraction and risk level changes in the fuel tank at a future specified time based on the time series data obtained by the transient simulation module.

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