A monitoring method and system for CH4 unorganized escape flux of LNG ships

Abstract

The present invention relates to the technical field of ship methane monitoring, and discloses a monitoring method and system for the unorganized escape flux of CH4 from LNG ships. By acquiring the ship's speed, heading, and wind speed data in real time, a monitoring system that is adaptive to the ship's motion state and environmental conditions is constructed to ensure that the monitoring equipment is always in the optimal sampling position, significantly improving the spatial capture capability of diffuse methane leakage. Secondly, the CO2 concentration is innovatively introduced as a marker of exhaust gas interference, and the concentration ratio of CH4 to CO2 in the exhaust gas is used to achieve accurate elimination of methane emissions from combustion sources, effectively separating the pure leakage concentration data of unorganized escape. Finally, combined with the dynamically corrected diffusion coefficient and diffusion equation, the discrete concentration distribution data is converted into accurate escape flux values, overcoming the applicability limitations of the traditional static diffusion model in ship motion scenarios, and providing reliable technical support for the quantitative supervision of ship methane leakage.

Description

Technical Field

[0001] The present invention relates to the technical field of ship methane monitoring, and in particular to a method and system for monitoring the unorganized CH4 escape flux of an LNG ship. Background Art

[0002] The use of liquefied natural gas (LNG) as a marine fuel is rapidly increasing, and its promotion plays a vital role in the decarbonization of the shipping industry. However, the fugitive methane emissions associated with this transition are posing a new environmental challenge. During ship operation, there is a risk of trace methane leaks from fuel supply systems, engine combustion chambers, and natural gas storage and transportation equipment. These emissions are dispersed and intermittent, making them difficult to fully capture using traditional exhaust gas treatment systems. Especially during the loading and unloading operations of LNG carriers, conditions such as changes in tank pressure and seal failures at pipeline connections can exacerbate the escape of gaseous methane, creating a source of fugitive emissions that is difficult to accurately measure.

[0003] Methane's properties as a potent greenhouse gas make its environmental impact significantly different from that of carbon dioxide. Although its atmospheric lifetime is relatively short, its ability to absorb solar radiation in the initial phase after release is exceptionally high. This short-term, high-intensity warming effect directly exacerbates the risk of imbalances in the global climate system. The continued expansion of the international shipping industry, coupled with the shift toward cleaner fuels for ships, has transformed the issue of methane escape from a local environmental impact to a critical factor in controlling the global carbon budget.

[0004] The existing regulatory system for monitoring methane emissions from ships has significant limitations. Traditional onboard testing is not only constrained by the willingness of ship operators to cooperate, but also makes real-time dynamic monitoring difficult. The diffuse nature of fugitive emission sources means that fixed monitoring points cannot effectively capture instantaneous concentration fluctuations, while manual sampling has inherent limitations in terms of spatial coverage and timeliness.

[0005] Therefore, how to accurately and quickly monitor the unorganized CH4 escape flux from LNG ships has become an urgent problem to be solved. Summary of the Invention

[0006] In order to accurately and quickly monitor the CH4 fugitive escape flux of an LNG ship, the present invention provides a method for monitoring the CH4 fugitive escape flux of an LNG ship, comprising the following steps:

[0007] S1: Obtaining navigation information and wind speed of the LNG ship; the navigation information includes the speed and heading of the ship;

[0008] S2: adjusting the real-time distance between the monitoring equipment and the LNG ship according to the navigation information and wind speed, and determining a sampling path for the monitoring equipment;

[0009] S3: The monitoring device collects data along the sampling path, and the obtained sampling information includes CH4 concentration and CO2 concentration;

[0010] S4: Based on the CO2 concentration, the concentration ratio of CH4 and CO2 in the exhaust gas is used to eliminate the CH4 concentration in the exhaust gas in the sampling information to obtain the concentration distribution of unorganized CH4 escaping from the LNG ship;

[0011] S5: According to the concentration distribution of the unorganized escaped CH4 from the LNG ship and the modified diffusion coefficient, the unorganized escape flux of CH4 from the LNG ship is obtained through the diffusion equation.

[0012] Furthermore, according to the navigation information and wind speed, the real-time distance between the monitoring equipment and the LNG ship is adjusted to determine the sampling path of the monitoring equipment, including the following steps:

[0013] S21: Calculate the effective length of the forward-looking smoke plume based on the ship's speed and wind speed at the future moment;

[0014] S22: Determine a sampling path coverage range based on the forward-looking smoke plume effective length and the preset coverage range;

[0015] S23: Calculate the plume compensation factor based on the actual ship speed and the real-time distance between the monitoring equipment and the LNG ship;

[0016] S24: According to the plume compensation factor, the sampling path coverage is adjusted to determine the sampling path of the monitoring equipment.

[0017] Furthermore, adjusting the sampling path coverage according to the plume compensation factor includes:

[0018] S241: Adjusting the sampling path coverage according to the plume compensation factor to obtain an optimized sampling path coverage;

[0019] S242: Determine the main axis direction of the smoke plume based on the vector synthesis of the heading and wind speed direction;

[0020] S243: Based on the main axis direction, the monitoring equipment is positioned within the coverage range of the optimized sampling path downwind of the ship.

[0021] Furthermore, the determining of the sampling path of the monitoring equipment is specifically as follows:

[0022] S244: Determine the horizontal boundary and the vertical boundary of the sampling path according to the optimized sampling path coverage;

[0023] S245: Calculating the horizontal boundary and the vertical boundary of the sampling path according to the preset spacing and the plume compensation factor to obtain the number of horizontal path points and the number of vertical path points;

[0024] S246: According to the number of the horizontal path points and the number of the vertical path points, the coordinates of the horizontal path points of each layer and the coordinates of the vertical path points of each column are determined in the ship coordinate system to obtain the sampling path of the monitoring equipment.

[0025] Furthermore, in S21, the forward-looking effective length of the smoke plume is calculated based on the ship's speed and wind speed at the future time, and the calculation formula is:

[0026] ;

[0027] Where, represents the effective length of the forward-looking plume, Indicates the ship's speed at a future time. represents wind speed, and L0 represents static plume length.

[0028] Furthermore, in S23, the plume compensation factor is calculated based on the actual ship speed and the real-time distance between the monitoring equipment and the LNG ship. The calculation formula is:

[0029] ;

[0030] Where, r represents the plume compensation factor, m represents the diffusion coupling coefficient, Indicates the monitoring time interval, Indicates the real-time distance between the monitoring equipment and the LNG ship. Indicates actual speed.

[0031] Furthermore, in S5, according to the concentration distribution of the unorganized CH4 escaping from the LNG ship, combined with the modified diffusion coefficient, the unorganized CH4 escaping flux of the LNG ship is obtained through the diffusion equation, including:

[0032] S51: Use fluid dynamics to simulate the wake flow field of a ship and establish a mapping relationship between ship speed and turbulence field distribution;

[0033] S52: Correcting the diffusion coefficient according to the mapping relationship between the ship speed and the turbulence field distribution and the real-time ship speed;

[0034] S53: According to the concentration distribution of the unorganized escaped CH4 from the LNG ship and the corrected diffusion coefficient, the unorganized escape flux of CH4 from the LNG ship is obtained through the diffusion equation.

[0035] Furthermore, in S51, the ship wake flow field is simulated by fluid dynamics to establish a mapping relationship between the ship speed and the turbulence field distribution, including:

[0036] Determine the reference speed of LNG carriers based on ship design requirements;

[0037] At a reference speed, the ship wake flow field is simulated by fluid dynamics to determine the basic diffusion coefficient at the reference speed, and obtain a mapping relationship between the speed and the turbulence field distribution;

[0038] The calculation formula of the basic diffusion coefficient is:

[0039] ;

[0040] Where, represents the basic diffusion coefficient, represents the turbulence model constant, represents the turbulent kinetic energy, represents the dissipation rate.

[0041] Furthermore, the correction formula for the correction diffusion coefficient is:

[0042] ;

[0043] Where, represents the corrected diffusion coefficient, represents the basic diffusion coefficient, Indicates the reference speed, Indicates the real-time speed.

[0044] Another aspect of the present invention provides a monitoring system for CH4 unorganized escape flux of an LNG ship, which is used to implement the above-mentioned monitoring method for CH4 unorganized escape flux of an LNG ship, comprising: an information acquisition module, an adopted path determination module, a monitoring device, a sampling information processing module, and a flux calculation module;

[0045] An information acquisition module is used to obtain navigation information and wind speed of the LNG ship; the navigation information includes the speed and heading of the ship;

[0046] A path determination module is used to adjust the real-time distance between the monitoring equipment and the LNG ship according to the navigation information and wind speed, and determine the sampling path of the monitoring equipment;

[0047] A monitoring device is used to collect data along the sampling path, and the obtained sampling information includes CH4 concentration and CO2 concentration;

[0048] A sampling information processing module is used to remove the CH4 concentration of the exhaust gas from the sampling information based on the CO2 concentration and the concentration ratio of CH4 and CO2 in the exhaust gas, so as to obtain the concentration distribution of unorganized CH4 escaping from the LNG ship;

[0049] The flux calculation module is used to obtain the unorganized escape flux of CH4 from the LNG ship through the diffusion equation according to the concentration distribution of the unorganized escape CH4 from the LNG ship and the modified diffusion coefficient.

[0050] The embodiments of the present invention have the following technical effects:

[0051] The present invention provides a monitoring method for the unorganized CH4 escape flux of LNG ships. By acquiring the ship's speed, heading and wind speed data in real time, the method constructs a monitoring system that is adaptive to the ship's motion state and environmental conditions, ensuring that the monitoring equipment is always in the optimal sampling position, and significantly improving the spatial capture capability of diffuse methane leakage. Secondly, the method innovatively introduces CO2 concentration as a marker of exhaust gas interference, and utilizes the concentration ratio of CH4 to CO2 in the exhaust gas to achieve accurate elimination of methane emissions from combustion sources, and effectively separates the pure leakage concentration data of unorganized escape. Finally, the method combines the dynamically corrected diffusion coefficient and diffusion equation to convert discrete concentration distribution data into accurate escape flux values, overcoming the applicability limitations of traditional static diffusion models in ship motion scenarios, and providing reliable technical support for the quantitative supervision of ship methane leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 This is a flowchart of a method for monitoring the unorganized CH4 escape flux of an LNG ship provided by an embodiment of the present invention;

[0054] Figure 2 This is a schematic diagram of a sensor mounted on a drone provided by an embodiment of the present invention;

[0055] Figure 3 This is a schematic diagram of the sampling path of the monitoring equipment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0057] The existing regulatory system has limitations in its monitoring of methane emissions from ships: traditional onboard inspection methods are not only subject to the willingness of ship operators to cooperate, but also make it difficult to achieve real-time dynamic monitoring; the diffuse characteristics of unorganized emission sources make it impossible for fixed monitoring points to effectively capture instantaneous concentration fluctuations, and manual sampling has inherent deficiencies in spatial coverage and timeliness.

[0058] Based on this problem, the present invention provides a method for monitoring the CH4 unorganized escape flux of LNG ships, such as Figure 1 As shown, the following steps are included:

[0059] S1: Obtaining navigation information and wind speed of the LNG carrier; the navigation information includes the ship's speed and heading; the speed and heading include both the current actual speed and actual navigation, and the predicted speed and heading at a future time;

[0060] During the operation of LNG carriers, monitoring for unorganized methane leaks requires comprehensive consideration of the interaction between ship dynamics and environmental factors. Therefore, navigation units installed at multiple locations on the hull can be used to collect real-time actual speed and navigation data, combined with real-time wind speed information from weather stations. Ships typically have automatic identification systems (AISs) that predict track data, so predicted speed and heading for future moments can be directly obtained from the AISs.

[0061] S2: Adjust the real-time distance between the monitoring equipment and the LNG ship based on navigation information and wind speed, and determine the sampling path of the monitoring equipment;

[0062] For example, the monitoring equipment can be a drone equipped with a sensor to extract air samples to analyze the richness and mixed ratio of target species, such as Figure 2 Its compact size and light weight allow it to be used as a payload on a drone. Figure 2 Figure 1 is a wind speed monitoring device used for wind speed monitoring, and figure 2 is a gas collection device used for collecting gas. The location of the sampling inlet prevents it from being affected by the drone itself. The black long rod at the front end of this part extracts the gas to be monitored into the box at the rear end, in which a laser CO2 sensor and a laser CH4 sensor are installed.

[0063] Laser CO2 sensors and laser CH4 sensors use advanced tunable laser absorption spectrum (TDLAS) detection technology. The detection range of the CH4 sensor is: 3%-100%LEL; the detection range of the CO2 sensor is: 0-1000PPM.

[0064] CO2 and CH4 share a detection chamber and are tested in the same chamber with a consistent sampling frequency, ensuring that the CO2 and CH4 concentration curves maintain good synchronization, which is used to subsequently evaluate methane escape in ship exhaust by calculating the CH4 / CO2 ratio.

[0065] The CO2 concentration in the air is monitored in real time using monitoring equipment. Once the CO2 concentration is found to be higher than the preset air background value, indicating that ship exhaust has been detected, sampling will begin based on the sampling path of the following steps. The methane detected at this time includes methane produced by the exhaust gas and methane from unorganized escape. Until the CO2 concentration returns to no higher than the preset air background value, the drone equipped with the monitoring equipment will continue to fly downwind of the ship's chimney. For example, the preset value can be 50ppm, which can be set according to the monitoring accuracy. If the monitoring accuracy requirement is high, the value can be appropriately lowered.

[0066] In some embodiments, adjusting the real-time distance between the monitoring device and the LNG ship and determining the sampling path of the monitoring device based on navigation information and wind speed includes the following steps:

[0067] S21: Calculate the effective length of the forward-looking smoke plume based on the ship's speed and wind speed at the future moment;

[0068] In some embodiments, in S21, the forward-looking effective length of the smoke plume is calculated based on the ship's speed and wind speed at the future time, and the calculation formula is:

[0069] ;

[0070] Where, It represents the effective length of the forward-looking plume and is used to quantify the physical deformation of the plume stretched by the ship speed. Indicates the ship's speed at a future time. represents wind speed, and L0 represents static plume length.

[0071] The forward-looking plume length formula is based on a simplified solution of the convection-diffusion equation, equating the ship's speed to an additional wind speed component. The static plume length, L0, in the formula is calibrated through wind tunnel testing and reflects the typical diffusion characteristics of a specific ship type at rest. The ratio of the ship's speed to the wind speed at a future time characterizes the extent to which the ship's motion affects the plume's stretching effect.

[0072] When a ship sails against the wind, the ship's speed component and the natural wind speed have a superimposed effect, significantly increasing the effective extension of the smoke plume. This formula quantifies this motion-enhancing effect through a linear combination relationship, allowing the monitoring system to predict the development of the smoke plume in advance.

[0073] The forward-looking plume length calculation fully considers the impact of the ship's future trajectory on the spread of the leak. Based on the predicted track data from the ship's automatic identification system, the ship's speed and wind speed at future moments are superimposed and analyzed to calculate the effective length of the plume. This length value is input into the monitoring path planning algorithm as a basic parameter to ensure that the sampling range always covers the front line of the leak spread. This prevents the risk of lag or inaccuracy caused by sudden acceleration or deceleration of the ship, which could cause the drone to leave the core of the plume due to the ship's acceleration.

[0074] S22: Determine the sampling path coverage based on the forward-looking effective length of the smoke plume and the preset coverage;

[0075] For example, based on historical navigation and wind direction data, the coverage range is preset. For example, the horizontal coverage range is set to [0.8L eff-future , 1.2L eff-future ], and the vertical coverage is [-0.2L eff-future , 0.2L eff-future ].

[0076] S23: Calculate the plume compensation factor based on the actual ship speed and the real-time distance between the monitoring equipment and the LNG ship;

[0077] In some embodiments, in S23, the plume compensation factor is calculated based on the actual ship speed and the real-time distance between the monitoring equipment and the LNG ship. The calculation formula is:

[0078] ;

[0079] Where, r represents the plume compensation factor, m represents the diffusion coupling coefficient, Indicates the monitoring time interval, Indicates the real-time distance between the monitoring equipment and the LNG ship. Indicates actual speed.

[0080] The calculation formula of the plume compensation factor reveals the dynamic balance between monitoring delay and spatial coverage. kThe dimensionless coefficient reflects the coupling characteristics of the ship wake flow field and the diffusion of the smoke plume. It is calibrated by experiments and comprehensively reflects the complex factors such as the atmospheric turbulence intensity and the diffusion rate of gas molecules. It is used to quantify the nonlinear influence of the ship speed on the stretching effect of the smoke plume. Its value is determined by multi-condition tests and regression analysis is performed on multiple sets of experimental data (different speeds, wind speeds, and distances) to determine k The optimal value of can adapt the formula to different ship types (such as the difference in wake between container ships and tankers) and environmental conditions (such as open waters and narrow channels). The time interval parameter is directly related to the sampling frequency of the monitoring equipment, ensuring that the data update rate matches the ship's motion status. The real-time distance between the monitoring equipment and the LNG ship in the formula is in the inverse form, reflecting the regulatory effect of the proximity of the monitoring equipment on the compensation intensity. When the time is shortened, the compensation factor increment decreases, avoiding the waste of resources caused by over-compensation. It successfully solves the problem of spatiotemporal synchronization in mobile monitoring and can maintain continuous coverage of the sampling grid under the condition of sudden speed changes.

[0081] The plume compensation factor r is used to correct the effective length of the plume, which directly affects the coverage of the UAV sampling path. r is used to scale the effective length of the forward-looking plume and adjust the coverage. and monitoring intervals , compensating for the spatial coverage deviation caused by dynamic tracking.

[0082] S24: Adjust the sampling path coverage according to the plume compensation factor to determine the sampling path of the monitoring equipment.

[0083] In some implementations, adjusting the sampling path coverage based on the plume compensation factor includes:

[0084] S241: adjusting the sampling path coverage according to the plume compensation factor to obtain an optimized sampling path coverage;

[0085] Exemplarily, the coverage is optimized by multiplying the sampling path coverage by the plume compensation factor.

[0086] S242: Determine the main axis direction of the smoke plume based on the vector synthesis of the heading and wind speed direction;

[0087] For example, the main axis of smoke plume diffusion is determined using a vector synthesis method, which superimposes the ship's heading and real-time wind direction into a spatial vector. By establishing a three-dimensional coordinate system, the heading vector is projected onto the horizontal plane and synthesized with the wind speed vector to determine the dominant direction of smoke plume diffusion. This direction serves as the reference axis for monitoring path layout, ensuring that sampling points are distributed along the direction of maximum concentration gradient.

[0088] S243: Based on the main axis direction, the monitoring equipment is positioned within the coverage range of the optimized sampling path downwind of the ship.

[0089] By tracking the changes in the main diffusion axis in real time, the system can quickly capture the spatial migration trajectory of sudden leakage events and significantly improve the response capability to transient leakage events.

[0090] By first setting the path coverage (step S22): based on the predicted speed of the ship at the future time Plan the monitoring area of the monitoring equipment in advance to avoid path lag caused by ship movement; then correct the plume parameters (steps S23 and S24): based on the real-time distance between the monitoring equipment and the LNG ship and actual speed , determine the plume compensation factor, adjust the sampling path coverage, and ensure that the path matches the current plume morphology.

[0091] In some implementations, determining the sampling path of the monitoring device is specifically as follows:

[0092] S244: Determine the horizontal boundary and the vertical boundary of the sampling path according to the optimized sampling path coverage;

[0093] S245: Calculate the horizontal boundary and the vertical boundary of the sampling path according to the preset spacing and the plume compensation factor to obtain the number of horizontal path points and the number of vertical path points;

[0094] S246: According to the number of horizontal path points and the number of vertical path points, the coordinates of the horizontal path points of each layer and the coordinates of the vertical path points of each column are determined in the ship coordinate system to obtain the sampling path of the monitoring equipment. Figure 3 As shown in , at point a, the CO2 concentration is detected to be 50 ppm higher than the air background, and sampling is performed by traversing the coordinates of the horizontal path points of each layer and the coordinates of the vertical path points of each column.

[0095] Exemplary:

[0096] (1) Establishing the real-time coordinate system of the ship

[0097] Origin setting: The real-time position of the ship (obtained by differential GPS) is used as the coordinate origin O(0,0,0);

[0098] Axial definition:

[0099] X-axis: along the real-time heading of the ship θ ship ;

[0100] Y axis: perpendicular to the X axis and pointing to the starboard direction;

[0101] Z axis: vertical to sea level and upward.

[0102] (2) Determine the horizontal cross-section boundary

[0103] Coverage correction: Adjust the path coverage R based on the compensation factor r cover-new =[0.8×L eff-future ×r,1.2×L eff-future ×r];

[0104] Horizontal cross section definition:

[0105] The length range is: along the X-axis, the plume diffusion direction covers X∈[0.8×L eff-future ×r,1.2×L eff-future ×r];

[0106] Width range: the lateral diffusion range along the Y axis, according to the effective width W of the smoke plume eff =0.2×L eff-future ×r, set Y∈[−Weff,Weff].

[0107] (3) Generate equally spaced path points

[0108] Path point density calculation:

[0109] ;

[0110] in, is the number of path points in the X-axis direction, is the number of path points in the Y-axis direction, d base is the reference distance (e.g. 10 meters).

[0111] Path point coordinate generation:

[0112] Along the X axis at a spacing of d x =d base ×r generates a point sequence x i =0.8×L eff-future ×r+i×d x (i=0,1,...,N x );

[0113] Along the Y axis at a spacing of d y =d base ×r generates point sequence y j = −W eff +j×d y (j=0,1,...,N y );

[0114] The horizontal cross-section path point set is P horizontal ={(x i ,y j,z0)}, where z0 is the current sampling height.

[0115] (4) Dynamic path optimization

[0116] Heading adaptation adjustment: according to real-time heading θ ship , for the path point coordinates ( x,y ) to perform rotation transformation and obtain the transformed path point coordinates ( , ):

[0117] ;

[0118] ;

[0119] Obstacle avoidance correction is achieved through rotation changes. If a path point collides with an obstacle (such as another ship), the conflict point is deleted and re-interpolated.

[0120] S3: The monitoring equipment collects data along the sampling path. The sampling information obtained includes CH4 concentration and CO2 concentration; it also includes the location information of the sampling point.

[0121] S4: Based on the CO2 concentration, the concentration ratio of CH4 and CO2 in the exhaust gas is used to eliminate the CH4 concentration in the exhaust gas in the sampling information to obtain the concentration distribution of unorganized CH4 escaping from the LNG ship;

[0122] In some embodiments, in S4, based on the CO2 concentration, the concentration ratio of CH4 and CO2 in the exhaust gas is used to eliminate the CH4 concentration in the exhaust gas in the sampling information to obtain the concentration distribution of unorganized CH4 escaping from the LNG ship, including:

[0123] S41: Obtain the historical concentrations of CH4 and CO2 in the exhaust gas, and fit the ratio of the concentrations of CH4 and CO2 in the exhaust gas;

[0124] S42: determining the concentration of CH4 in the tail gas based on the CO2 concentration and the ratio of the concentrations of CH4 and CO2 in the tail gas;

[0125] S43: The concentration of CH4 in the exhaust gas is removed from the sampling information to obtain the concentration of unorganized CH4 escaping from the LNG ship;

[0126] S44: Obtaining a concentration distribution of the unorganized CH4 escape from the LNG ship based on the concentration of the unorganized CH4 escape from the LNG ship and the location information in the sampling information.

[0127] Although the absolute concentration of the target gas decreases with increasing distance from the chimney due to dilution of the exhaust plume, the concentrations of the two gases maintain a certain proportional relationship in the mixed, turbulent chimney exhaust plume. Therefore, the method in step S4 effectively solves the problem of component aliasing between the combustion source and the leakage source, and maintains stable separation accuracy even under conditions of frequent host load fluctuations.

[0128] S5: Based on the concentration distribution of CH4 fugitive escape from LNG ships and the modified diffusion coefficient, the CH4 fugitive escape flux from LNG ships is obtained through the diffusion equation.

[0129] In some embodiments, in S5, the concentration distribution of CH4 fugitive escape from the LNG ship is combined with the modified diffusion coefficient to obtain the CH4 fugitive escape flux from the LNG ship through the diffusion equation, including:

[0130] S51: Use fluid dynamics to simulate the wake flow field of a ship and establish a mapping relationship between ship speed and turbulence field distribution;

[0131] In some embodiments, in S51, simulating the wake flow field of the ship by fluid dynamics to establish a mapping relationship between the ship speed and the turbulence field distribution includes:

[0132] S511: Determine the reference speed for LNG carriers based on ship design requirements. For example, the reference speed may be the design speed required during ship design, which is the speed with the highest efficiency or most stable emissions determined during ship design. Alternatively, the reference speed may be the speed corresponding to a specific emission standard, or the most energy-efficient speed.

[0133] S512: Under the reference speed, the ship wake flow field is simulated by fluid dynamics to determine the basic diffusion coefficient under the reference speed and obtain the mapping relationship between the speed and the turbulence field distribution;

[0134] The mapping relationship of the turbulence field distribution is constructed by using computational fluid dynamics simulation technology. The existing simulation technology can be directly used, and the specific simulation process will not be described here.

[0135] Taking the reference speed as the benchmark working condition and as the only input speed, the turbulence parameters (k, ϵ) of the ship wake flow field at this speed can be obtained by solving the Navier-Stokes equation. Based on this, the basic diffusion coefficient is obtained, forming a mapping relationship between the speed and the turbulence field distribution. The calculation formula is:

[0136] ;

[0137] Where, represents the basic diffusion coefficient, represents the turbulence model constant, represents the turbulent kinetic energy, represents the dissipation rate.

[0138] The calculation of the basic diffusion coefficient is based on the standard turbulence model, which is a fluid dynamics simulation model established at a reference speed. The turbulent kinetic energy Characterizes the irregular motion intensity and dissipation rate of fluid particles Reflects the conversion rate of kinetic energy to thermal energy. By introducing the turbulence model constant , simplifying the complex turbulent transport process into a computable algebraic relationship.

[0139] S52: Correct the diffusion coefficient based on the mapping relationship between ship speed and turbulence field distribution and the real-time ship speed;

[0140] In some embodiments, the correction formula for correcting the diffusion coefficient is:

[0141] ;

[0142] Where, represents the corrected diffusion coefficient, Indicates the basic diffusion coefficient, which is fixed at the reference speed The diffusion coefficient under Indicates the reference speed, which is calibrated The base speed, Indicates the real-time speed.

[0143] The real-time correction of the diffusion coefficient uses a logarithmic function, a mathematical expression that effectively captures the nonlinear effects of speed changes on turbulence intensity. This logarithmic function effectively smooths parameter jumps caused by sudden changes in speed, avoiding numerical instability during the calculation process. As the ship accelerates, the growth rate of the correction term gradually slows, consistent with the physical laws of kinetic energy conversion in fluid mechanics. The corrected diffusion coefficient more accurately reflects the flow field disturbance effects caused by ship motion.

[0144] Although , which is a fixed and static parameter, but in actual application it needs to be adjusted according to the real-time speed of the ship. To modify it dynamically:

[0145] when hour, , use the benchmark value directly;

[0146] when When the formula is modified, the , get the speed that matches the current speed .

[0147] S53: Based on the concentration distribution of CH4 fugitive escape from LNG ships and the corrected diffusion coefficient, the CH4 fugitive escape flux from LNG ships is obtained through the diffusion equation.

[0148] For example, based on Fick's second law, a diffusion equation can be set to obtain the CH4 unorganized escape flux at each point of the LNG ship.

[0149] When monitoring the unorganized CH4 escape flux from LNG ships, the present invention acquires real-time ship speed, heading, and wind speed data to construct a monitoring system that adapts to the ship's motion state and environmental conditions. This ensures that the monitoring equipment is always in the optimal sampling position, significantly improving the spatial capture capability of diffuse methane leaks. Secondly, the present invention innovatively introduces CO2 concentration as a marker for exhaust gas interference and utilizes the concentration ratio of CH4 to CO2 in the exhaust gas to accurately eliminate methane emissions from combustion sources and effectively separate the pure leakage concentration data of unorganized escape. Finally, by combining the dynamically corrected diffusion coefficient and diffusion equation, the discrete concentration distribution data is converted into accurate escape flux values, overcoming the applicability limitations of traditional static diffusion models in ship motion scenarios and providing reliable technical support for the quantitative regulation of ship methane leaks. Each step works synergistically to achieve accurate and rapid monitoring of the unorganized CH4 escape flux from LNG ships.

[0150] Another aspect of the present invention provides a monitoring system for CH4 unorganized escape flux of an LNG ship, which is used to implement the above-mentioned monitoring method for CH4 unorganized escape flux of an LNG ship, comprising: an information acquisition module, an adopted path determination module, a monitoring device, a sampling information processing module, and a flux calculation module;

[0151] An information acquisition module is used to obtain navigation information and wind speed of the LNG ship; the navigation information includes the speed and heading of the ship;

[0152] A path determination module is used to adjust the real-time distance between the monitoring equipment and the LNG ship according to the navigation information and wind speed, and determine the sampling path of the monitoring equipment;

[0153] A monitoring device is used to collect data along the sampling path, and the obtained sampling information includes CH4 concentration and CO2 concentration;

[0154] A sampling information processing module is used to remove the CH4 concentration of the exhaust gas from the sampling information based on the CO2 concentration and the concentration ratio of CH4 and CO2 in the exhaust gas, so as to obtain the concentration distribution of unorganized CH4 escaping from the LNG ship;

[0155] The flux calculation module is used to obtain the unorganized escape flux of CH4 from the LNG ship through the diffusion equation according to the concentration distribution of the unorganized escape CH4 from the LNG ship and the modified diffusion coefficient.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the unorganized CH4 escape flux of an LNG ship, characterized in that: The steps include: S1: Obtaining navigation information and wind speed of the LNG ship; the navigation information includes the speed and heading of the ship; S2: adjusting the real-time distance between the monitoring equipment and the LNG ship according to the navigation information and wind speed, and determining a sampling path for the monitoring equipment; S3: The monitoring device collects data along the sampling path, and the obtained sampling information includes CH4 concentration and CO2 concentration; S4: Based on the CO2 concentration, the concentration ratio of CH4 and CO2 in the exhaust gas is used to eliminate the CH4 concentration in the exhaust gas in the sampling information to obtain the concentration distribution of unorganized CH4 escaping from the LNG ship; S5: According to the concentration distribution of the unorganized escaped CH4 from the LNG ship and the modified diffusion coefficient, the unorganized escape flux of CH4 from the LNG ship is obtained through the diffusion equation; In S2, adjusting the real-time distance between the monitoring equipment and the LNG ship and determining the sampling path of the monitoring equipment according to the navigation information and wind speed includes the following steps: S21: Calculate the effective length of the forward-looking smoke plume based on the ship's speed and wind speed at the future moment; S22: Determine a sampling path coverage range based on the forward-looking smoke plume effective length and the preset coverage range; S23: Calculate the plume compensation factor based on the actual ship speed and the real-time distance between the monitoring equipment and the LNG ship; S24: According to the plume compensation factor, the sampling path coverage is adjusted to determine the sampling path of the monitoring equipment.

2. The method for monitoring the CH4 unorganized escape flux of an LNG ship according to claim 1, characterized in that: The adjusting the sampling path coverage according to the plume compensation factor includes: S241: Adjusting the sampling path coverage according to the plume compensation factor to obtain an optimized sampling path coverage; S242: Determine the main axis direction of the smoke plume based on the vector synthesis of the heading and wind speed direction; S243: Based on the main axis direction, the monitoring equipment is positioned within the coverage range of the optimized sampling path downwind of the ship.

3. The method for monitoring the CH4 unorganized escape flux of an LNG ship according to claim 2, characterized in that: The determination of the sampling path of the monitoring equipment is specifically as follows: S244: Determine the horizontal boundary and the vertical boundary of the sampling path according to the optimized sampling path coverage; S245: Calculating the horizontal boundary and the vertical boundary of the sampling path according to the preset spacing and the plume compensation factor to obtain the number of horizontal path points and the number of vertical path points; S246: According to the number of the horizontal path points and the number of the vertical path points, the coordinates of the horizontal path points of each layer and the coordinates of the vertical path points of each column are determined in the ship coordinate system to obtain the sampling path of the monitoring equipment.

4. The method for monitoring the CH4 unorganized escape flux of an LNG ship according to claim 1, characterized in that: In S21, the forward-looking effective length of the smoke plume is calculated based on the ship's speed and wind speed at the future time. The calculation formula is: ； Where, represents the effective length of the forward-looking plume, Indicates the ship's speed at a future time. represents wind speed, and L0 represents static plume length.

5. The method for monitoring the CH4 unorganized escape flux of an LNG ship according to claim 1, characterized in that: In S23, the plume compensation factor is calculated based on the actual ship speed and the real-time distance between the monitoring equipment and the LNG ship. The calculation formula is: ； Where, r represents the plume compensation factor, m represents the diffusion coupling coefficient, Indicates the monitoring time interval, Indicates the real-time distance between the monitoring equipment and the LNG ship. Indicates actual speed.

6. The method for monitoring the CH4 unorganized escape flux of an LNG ship according to claim 1, characterized in that: In S5, the concentration distribution of the CH4 fugitive escape from the LNG ship is combined with the modified diffusion coefficient to obtain the CH4 fugitive escape flux from the LNG ship through the diffusion equation, including: S51: Use fluid dynamics to simulate the wake flow field of a ship and establish a mapping relationship between ship speed and turbulence field distribution; S52: Correcting the diffusion coefficient according to the mapping relationship between the ship speed and the turbulence field distribution and the real-time ship speed; S53: According to the concentration distribution of the unorganized escaped CH4 from the LNG ship and the corrected diffusion coefficient, the unorganized escape flux of CH4 from the LNG ship is obtained through the diffusion equation.

7. The method for monitoring the unorganized CH4 escape flux of an LNG ship according to claim 6, characterized in that: In the above S51, the ship wake flow field is simulated by fluid dynamics to establish a mapping relationship between the ship speed and the turbulence field distribution, including: Determine the reference speed of LNG carriers based on ship design requirements; At a reference speed, the ship wake flow field is simulated by fluid dynamics to determine the basic diffusion coefficient at the reference speed, and obtain a mapping relationship between the speed and the turbulence field distribution; The calculation formula of the basic diffusion coefficient is: ； Where, represents the basic diffusion coefficient, represents the turbulence model constant, represents the turbulent kinetic energy, represents the dissipation rate.

8. The method for monitoring the CH4 fugitive escape flux of an LNG ship according to claim 6, characterized in that: The correction formula for the corrected diffusion coefficient is: ； Where, represents the corrected diffusion coefficient, represents the basic diffusion coefficient, Indicates the reference speed, Indicates the real-time speed.

9. A monitoring system for CH4 unorganized escape flux of LNG carrier, characterized by: A method for monitoring the CH4 unorganized escape flux of an LNG ship according to any one of claims 1 to 8, comprising: an information acquisition module, a path determination module, monitoring equipment, a sampling information processing module, and a flux calculation module; An information acquisition module is used to obtain navigation information and wind speed of the LNG ship; the navigation information includes the speed and heading of the ship; A path determination module is used to adjust the real-time distance between the monitoring equipment and the LNG ship according to the navigation information and wind speed, and determine the sampling path of the monitoring equipment; A monitoring device is used to collect data along the sampling path, and the obtained sampling information includes CH4 concentration and CO2 concentration; A sampling information processing module is used to remove the CH4 concentration of the exhaust gas from the sampling information based on the CO2 concentration and the concentration ratio of CH4 and CO2 in the exhaust gas, so as to obtain the concentration distribution of unorganized CH4 escaping from the LNG ship; The flux calculation module is used to obtain the unorganized escape flux of CH4 from the LNG ship through the diffusion equation according to the concentration distribution of the unorganized escape CH4 from the LNG ship and the modified diffusion coefficient.

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