Optimization method of marine engine room ventilation system

Abstract

The invention provides an optimization method of a marine engine room ventilation system. The optimization method comprises the following steps: establishing a three-dimensional physical model of the marine engine room ventilation system; performing grid division on the three-dimensional physical model; based on the three-dimensional physical model after gridding processing, a mathematical model of the marine engine room ventilation system is established, and the mathematical model comprises the air volume distribution condition, the heat source power table, the boundary condition, the control equation and the turbulence model of the left and right board air ducts; formulating various engine room ventilation system schemes; based on a three-dimensional physical model and a mathematical model, numerical simulation is carried out on the formulated schemes, temperature distribution conditions and air flow fields in the cabin and on the surface of heating equipment in the cabin under different schemes are obtained and analyzed, and evaluation indexes under all the schemes are calculated; and based on the evaluation indexes corresponding to the schemes, all the schemes are sorted by using an AHP-entropy weight evaluation method, and an optimal cabin ventilation system scheme is selected. The structure of the ship engine room ventilation system is optimized, so that it is ensured that heating equipment and personnel in an engine room can work in a proper environment, and the temperature distribution uniformity of the engine room is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ship engine room ventilation systems, and specifically designs a ship engine room ventilation system and an optimization method thereof. BACKGROUND

[0002] The engine room ventilation system plays a crucial role in devices such as ships, and its main function is to provide a suitable working environment for the equipment and personnel inside the engine room. The equipment in the engine room generates a large amount of heat during operation. If the heat cannot be dissipated in time, it will cause the engine room temperature to be too high, affecting the normal operation and service life of the equipment, and even may cause safety accidents. At the same time, the high temperature environment will have a negative impact on the physical health and work efficiency of the personnel in the engine room, and reduce the comfort of work.

[0003] In the prior art, the engine room ventilation system usually adopts forced air supply, natural air supply and other ways, and usually adopts air supply pipe, exhaust pipe and other structures to directly pass through the deck of the ship and extend into the engine room. With the help of fan devices, the ventilation inside the engine room is realized, such as CN108128436A, CN109850108A, etc. The research on the engine room ventilation system in the prior art mainly focuses on the design of the ventilation structure. Therefore, the traditional engine room ventilation and heat dissipation system still has some deficiencies in practical application, such as slow heat dissipation speed, low temperature control precision, etc., which cannot meet the high requirements of modern ships on the engine room environment. In addition, with the development of ship technology and the improvement of environmental protection requirements, higher requirements are put forward for the energy saving and environmental protection of the engine room ventilation system.

[0004] In addition, in the design of the ship engine room ventilation system, not only various factors need to be considered, but also the overall arrangement of the ship and the comfort of the personnel need to be considered; and various schemes designed need to be more accurately evaluated to select a better ship engine room ventilation scheme.

[0005] Therefore, it is urgent to find an optimization design method for the ship engine room ventilation system to ensure that the heat generating equipment and personnel in the engine room can work in a suitable environment and improve the uniformity of the engine room temperature distribution. SUMMARY

[0006] In order to solve the problems existing in the prior art, the present application provides a ship engine room ventilation system and an optimization method thereof, which optimizes the structure of the ship engine room ventilation system to ensure that the heat generating equipment and personnel in the engine room can work in a suitable environment and improve the uniformity of the engine room temperature distribution.

[0007] The technical scheme adopted by the present application is as follows:

[0008] An optimization method of a ship engine room ventilation system, comprising the following steps:

[0009] S1: Establish a three-dimensional physical model of the ship engine room ventilation system;

[0010] S2: Based on the three-dimensional physical model of the ship engine room ventilation system, the three-dimensional physical model is meshed;

[0011] S3: Based on the three-dimensional physical model after meshing, a mathematical model of the ship engine room ventilation system is established, which includes the air distribution of the left and right wind channels, the heat source power table, the boundary conditions, the control equation and the turbulence model;

[0012] S4: Develop multiple engine room ventilation system schemes;

[0013] S5: Based on the three-dimensional physical model and the mathematical model, the schemes developed in S4 are respectively simulated, the temperature distribution of the engine room and the surface of the heating equipment and the air flow field under different schemes are obtained and analyzed, and the evaluation indexes of each scheme are calculated;

[0014] S6: Based on the evaluation indexes corresponding to each scheme, the AHP-entropy weight evaluation method is used to sort all the schemes, and the optimal engine room ventilation system scheme is selected.

[0015] Further, the calculation process of the AHP-entropy weight evaluation method is:

[0016] (1) Numerical simulation and verification: numerical simulation analysis is carried out on the ship engine room, and objective evaluation factors are determined according to the numerical simulation results, including surface temperature, working area temperature, velocity and pressure distribution;

[0017] (2) Construct evaluation layer: for surface temperature, working area temperature, velocity and pressure data, prepare to determine the objective weight of each evaluation layer;

[0018] (3) Determine the objective weight: determine the objective weight of surface temperature, working area temperature, velocity and pressure respectively, and use entropy weight method to determine the weight size of surface temperature, working area temperature, velocity and pressure;

[0019] (4) Determine the subjective weight: including the subjective weight corresponding to the subjective evaluation factors, i.e. heat dissipation efficiency satisfaction, comfort satisfaction and speed uniformity satisfaction; the subjective weight obtained through questionnaire survey

[0020] (5) Construct criterion layer: construct three criterion layers, each criterion layer corresponds to a design target, and the design targets are heat dissipation efficiency, comfort and speed uniformity. In each criterion layer, subjective and objective are integrated;

[0021] (6) According to different criterion layers, the corresponding target results are obtained: each criterion layer calculates the comprehensive score corresponding to each design target, and then selects the best working condition.

[0022] Further, the satisfaction score of each objective evaluation factor is calculated, and then the satisfaction score of each factor is calculated to obtain a scoring matrix X ij , to obtain a normalized matrix Y ij , a probability matrix I ij , an information entropy matrix E j , and a weight matrix w i in turn; based on the weighted processing, the satisfaction score under each working condition is obtained, denoted as:

[0023] S wsi = W1S1 + W2S2 + W3S v + W4S T ;

[0024] The satisfaction score of the subjective evaluation factor after weighting is calculated, denoted as:

[0025] S = W a S ws1 + W b S ws2 + W c S ws3

[0026] wherein S wsi is the comfort satisfaction, i is 1, 2, and 3, respectively, indicating the comfort score, the heat dissipation efficiency score, and the speed uniformity score; S1, S2, S V , and S T are the heat dissipation efficiency, temperature, speed, and pressure satisfaction scores, respectively. W1, W2, W3, and W4 are the weights of the heat dissipation efficiency, temperature, speed, and pressure, respectively. W a is the comfort satisfaction, W b is the heat dissipation efficiency satisfaction, and W c is the speed uniformity satisfaction.

[0027] Further, the boundary conditions include: the finite volume method is selected for the solution algorithm, the standard format is adopted for the pressure discretization, the second-order upwind format is adopted for the momentum and energy discretization, and the SIMPLEC algorithm is selected for the solution calculation.

[0028] Further, the standard k-ε model is adopted for the turbulent flow simulation calculation, and the standard k-ε model includes: a turbulent flow kinetic energy k equation and a turbulent flow dissipation rate ε equation.

[0029] Further, the control equation includes a mass conservation equation, a momentum conservation equation, and an energy conservation equation.

[0030] Further, the cooling coil and the turbulence fan are taken as the design object, a plurality of alternative cabin ventilation system schemes are formulated by changing the number, position, and air volume ratio of the installed cooling coil and turbulence fan.

[0031] Further, on the basis of numerical simulation, the detection points are selected in a uniform distribution, and the performance of the ventilation system in the cabin is quantitatively analyzed according to the evaluation indexes at the detection points.

[0032] Further, the evaluation indexes include heat dissipation efficiency and speed uniformity coefficient.

[0033] A ventilation system of a ship cabin is designed by using the method.

[0034] Beneficial effects

[0035] (1) The cooling coil is added near the heat generating equipment, and the optimal distribution of the quantitative cooling capacity is performed in different proportions. The air flow organization characteristics and the temperature distribution on the surface of the heat generating equipment in the ship cabin ventilation system are analyzed based on the numerical simulation technology. The influence of different cooling capacity proportions on the temperature distribution in the cabin ventilation system is studied. The optimal scheme is selected by combining the AHP-entropy weight evaluation method.

[0036] (2) The present application provides a technical reference and theoretical basis for the optimization of the ship cabin ventilation system, and also improves the comfort of the personnel in the cabin and the safety of the heat generating equipment. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 The flow chart is designed for the cabin ventilation system.

[0038] Figure 2 In (a) and (b), the equipment in the cabin is specifically distributed.

[0039] Figure 3 In (a) and (b), the left and right wind tunnel models before the wind tunnel optimization are divided.

[0040] Figure 4 In (a) and (b), the left and right wind tunnel models are divided into unstructured grid division diagrams.

[0041] Figure 5 The flow chart of the AHP-entropy weight evaluation method

[0042] Figure 6 The schematic diagram of the cabin ventilation scheme.

[0043] Figure 7 The temperature distribution diagram of the cabin under different cabin ventilation schemes.

[0044] Figure 8 The velocity distribution diagram of the cabin under different cabin ventilation schemes.

[0045] Figure 9 The temperature distribution diagram of the heat generating equipment under different cabin ventilation schemes.

[0046] Figure 10 Fig. 1 is a schematic diagram of monitoring points in a ventilation system in a cabin. DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0048] The present application will be further described below with reference to the accompanying drawings. The technical solutions in the embodiments of the present application are described clearly and completely. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0049] With reference to the accompanying drawings Figure 1 , the present application proposes an optimization method of a ventilation system in a cabin of a ship, comprising the following steps:

[0050] S1: a three-dimensional physical model of a ventilation system in a cabin of a ship is established, and the physical model comprises the following components: 1 cabin air duct, and large heat generating components; the large heat generating components are a cabin main engine, a main diesel engine and a main generator. The cabin air duct comprises a cabin bottom layer, a cabin middle platform and a cabin upper platform, which are 9.28 m, 5.52 m and 6.4 m high respectively, and the total height of the three layers is 21.2 m; a lathe, a washroom, a ballast pump and a smoke exhaust pipe are arranged in the cabin platform. As shown in the figure, the left and right air duct models before optimization are shown in Figure 2 . The left air duct has 30 air outlets, the right air duct has 15 air outlets, a fan room is arranged at the air inlet, and a large-power fan with a wind volume of 72000 m3 / h is arranged in the fan room.

[0051] S2: the three-dimensional physical model of the ventilation system in the cabin of the ship constructed in S1 is meshed, and the number of meshing is determined through mesh independence verification.

[0052] In this embodiment, only the ventilation duct is meshed and mesh independence verification is performed, and more areas can be meshed according to actual needs.

[0053] The model is meshed by using unstructured mesh, as shown in the accompanying Figure 3 .

[0054] In order to verify the grid independence, the average velocity of the outlet of the ventilation system changes little with the increase of the number of grids when the number of grids of the wind pipe 1 (port side) is 3786, 4283, 4865, 5296, 5806 and the number of grids of the wind pipe 2 (starboard side) is 3665, 4193, 4769, 5134, 5735, respectively. The relative error of the average velocity is 1.89% and 1.63%, respectively, which shows that the simulation result tends to be stable and is no longer affected by the number of grids. Considering the calculation speed and the calculation accuracy, the number of grids of the wind pipe 1 (port side) and the wind pipe 2 (starboard side) is set to 2142 and 1932, respectively, and the simulation calculation is performed.

[0055] S3: Establish a mathematical model of the ship engine room ventilation system, which includes the air volume distribution of the port and starboard air ducts, a heat source power table, boundary conditions, control equations and a turbulence model. The feasibility of the mathematical model is verified by the error value between the experimental data and the simulation data.

[0056] The air volume distribution of the port and starboard air ducts is shown in Table 1.

[0057] Table 1 Air volume distribution of the port and starboard air ducts

[0058]

[0059] The heat source power table is shown in Table 2.

[0060] Table 2 Heat source power table

[0061]

[0062] The boundary conditions include: the solving algorithm in this paper is the finite volume method, the pressure is discretized by the standard format, the momentum and energy are discretized by the second-order upwind format, and the SIMPLEC algorithm is used for solving calculation. The radiation model needs to be opened in the setting. The heat dissipation of the heat generating equipment in this paper is relatively large, so the influence of radiation on heat dissipation needs to be considered. The wall uses the standard wall function and is set as an adiabatic wall. The pressure step of the turbulence fan is set to 400 Pa. Through calculation, the total velocity of the cooling coil outlet in the engine room is 13.24 m / s. The air volume value of each air supply outlet is shown in Table 1, the air supply temperature is set to 300 K, and the outlet of the air supply outlet is set as a pressure outlet. The heat source power of the heat generating equipment in the engine room is shown in Table 2, which is set as a heat source term in Fluent.

[0063] In the mathematical model, the determined control equations include the mass conservation equation, the momentum conservation equation and the energy conservation equation.

[0064] (1) The mass conservation equation is:

[0065] (2) The momentum conservation equation is:

[0066]

[0067] (3) The energy conservation equation is:

[0068] where ρ is the density of the fluid, U i is the velocity component of the fluid in the i direction, x i is the x, y, z direction of the orthogonal coordinate system, u is the velocity component of the fluid in the x direction, is the material derivative, indicating the acceleration with the fluid motion, is the force exerted on the fluid by the change of pressure in the x direction, μ is the dynamic viscosity coefficient, v is the velocity component of the fluid in the y direction, f y is the volume force component in the y direction, ω is the velocity component of the fluid in the z direction, h is the specific enthalpy of the fluid, λ is the thermal conductivity, c p is the specific heat capacity at constant pressure, S H is the energy source term, which can include the generation or absorption of heat such as chemical reaction heat, radiation heat, etc.

[0069] The standard k-ε model is used for turbulent flow simulation calculation, which includes the turbulent kinetic energy k equation and the turbulent dissipation rate ε equation.

[0070] (1) The turbulent kinetic energy K equation is:

[0071]

[0072] (2) The turbulent dissipation rate ε equation is:

[0073]

[0074] where T is the fluid temperature, S T is the source term, indicating the influence of other physical processes on the turbulent kinetic energy, k is the turbulent kinetic energy; μ is the turbulent viscosity (Pa*s); σ k is the turbulent Prandtl number of the k equation; G k is the turbulent kinetic energy term generated by the laminar velocity gradient; G b is the turbulent kinetic energy term generated by buoyancy; ε is the turbulent dissipation rate, Y M is the dissipation term caused by turbulent fluctuations in compressible flow; S k is the turbulent kinetic energy term; σ ε is the turbulent Prandtl number of the ε equation; S ε is the turbulent dissipation source term; C1, C2 are the transport dissipation constants.

[0075] S4: Develop a cabin ventilation system plan. Assuming there is only one cooling coil and spoiler fan in the system as the initial working condition, compare the installation of guide vanes, different installation positions and different air volumes. The cabin ventilation plan diagram is shown in the attached figure. Figure 4 As shown in the figure, the effects of different schemes on the air flow distribution in the cabin ventilation system are studied.

[0076] S5: Numerical simulations are performed on various cabin ventilation schemes to obtain and analyze the cabin temperature field, air flow field, and temperature field of heating equipment under different cabin ventilation schemes. Parameters of evaluation indicators (heat dissipation efficiency, velocity uniformity coefficient) are calculated for each cabin ventilation scheme.

[0077] The cabin temperature distribution under different cabin ventilation schemes is shown in the attached figure. Figure 5 As shown in the figure, the temperature gradient in the lower level is large for conditions 1-3, while the temperature distribution in the lower level is relatively uniform for conditions 4-6. The maximum and minimum temperatures for the six conditions are not significantly different, so the temperature of the entire cabin cannot be described based on the maximum and minimum temperatures. The simulation results for the middle level show that the temperature distribution in conditions 4-6, where the cooling capacity is more dispersed, is more dispersed, while the temperature distribution in conditions 1-3, where the cooling capacity is more concentrated, is more concentrated, with most of the temperature concentrated near the cooling coils and turbulent fans. The simulation results for the upper level show that the temperature in condition 4 is higher, while the maximum temperatures in the other conditions are similar, so the temperature differences in the upper level are not significant.

[0078] The cabin velocity distribution under different cabin ventilation schemes is shown in the attached figure. Figure 6 As shown in the figure, due to the presence of the cooling coil and the turbulent fan, and the fact that the outlet velocities of the turbulent fan and the cooling coil reach 10 m / s, the velocities at the outlets of both the turbulent fan and the cooling coil are relatively high. The high-speed airflow from the outlet collides with the wall, disrupting the boundary layer. This indicates that the greater the velocity gradient of the air near the surface of the heating device, the more significant the destructive effect on the boundary layer. The velocity gradient near the heating device is indeed very large under the highest wind speed conditions, indicating that wind speed is also related to the destructive effect on the boundary layer. In the velocity field of the upper platform, it can be seen that there are no obstacles, and the velocity gradient of the airflow is relatively flat. Therefore, the influence of obstacles on the velocity field within the entire cabin is also more significant. The overall velocity field within the cabin is not very different, but the locations of the local air outlets vary significantly, and the velocity gradient also varies significantly.

[0079] The temperature distribution of heating equipment under different cabin ventilation schemes is shown in the attached figure. Figure 7It can be seen from the figure that the more the heat is dispersed to the engine and the engine, the better the local heat dissipation effect is, and the temperature tends to be uniform. The average temperature of the engine and the generator in working condition 1 is relatively low, but the temperature distribution is uneven, and the local maximum temperature of the generator exceeds 100°C, but the surface area exceeding 100°C is the least compared with other working conditions. From the subsequent data analysis, it can be concluded that the heat dissipation effect of working condition 1 is the best. The situation of working condition 2 and working condition 3 is similar, and the average temperature and the surface area of the maximum temperature are moderate. The average temperature of working condition 4 is relatively high, and the surface area of the maximum temperature of the equipment surface is also the least. The heat dissipation effect of working condition 5 and working condition 6 is the worst.

[0080] On the basis of numerical simulation, the performance of the ventilation system in the cabin is quantitatively analyzed by selecting uniformly distributed detection points. The distribution of the detection points is shown in Figure 8 Due to the large space scale of the cabin and the compact equipment, the flow field is complex, so a total of 2000 monitoring points are selected and uniformly distributed in the fluid region, which can more truly reflect the characteristics of the flow field.

[0081] The evaluation indexes include heat dissipation efficiency and velocity uniformity coefficient. The calculation formula is as follows

[0082] (1) The calculation formula of heat dissipation efficiency is:

[0083] In the formula, ta is the average temperature of the surface of the heat generating equipment, ts is the temperature of the air supply outlet, 300K is taken, and tw is the average temperature of the working area.

[0084] (2) The calculation formula of velocity uniformity coefficient is:

[0085] In the formula, The average velocity of the sampling point; u' is the standard deviation of the velocity of the sampling point.

[0086] S6: The AHP-entropy weight evaluation method is used to sort the selected cabin ventilation system schemes and select the optimal cabin ventilation system scheme. The calculation process of the AHP-entropy weight evaluation method is as follows:

[0087] (1) Define subjective weight and objective weight

[0088] The final evaluation results of the engine room of the ship under different working conditions are affected by the weights of the subjective evaluation factors. In this paper, the analytic hierarchy process is used to determine the subjective weights. According to different design objectives, the weights of the subjective evaluation factors are determined. Through the questionnaire survey of the relevant staff in the ship, the subjective feelings of the staff when the environmental factors in the engine room change are obtained, and the relevant survey results are obtained. In this paper, three different design objectives are investigated, and the design objectives are: heat dissipation efficiency satisfaction, working area comfort and speed uniformity satisfaction. The survey results are shown in Table 3.

[0089] Table 3 Subjective weights of each factor under different objectives

[0090]

[0091] (2) When defining the objective weight, first calculate the sample percentage Pi of each objective evaluation factor that does not meet the design requirements according to the formula as follows:

[0092]

[0093] In the formula, i takes 1, 2, 3, and 4, respectively, representing four independent objective evaluation factors: surface temperature, working area temperature, speed, and pressure. i is the sample percentage of independent factor i exceeding the required range of design value. N i is the number of samples of independent factor i exceeding the required range of design value, and N is the total number of samples. Generally, when P i ≤ 5%, S i = 100%, and when P i > 5%, the satisfaction score S i of each factor is calculated by the formula as follows:

[0094]

[0095] As mentioned earlier, the entropy weight method is an objective weighting method, which is mainly based on the information entropy method to calculate the weights of the objective evaluation factors. It can be used for multi-index comprehensive evaluation, and the main advantage is that it can avoid the interference of human factors on the results, thereby ensuring the objectivity of the weights of the independent factors. Since the independent factors are not directly related to the design objectives, the weights of each independent factor can be calculated according to the entropy weight method. The calculation steps are as follows:

[0096] (1.1) Data standardization. In form, set the matrix Mm×n=(X1,X2,…Xk) as an information system, where Xi=(x1,x2,…xn), and then standardize Xi to:

[0097]

[0098] wherein: x ij represents the value of the ith index under the jth index, herein x ij is replaced by the calculated satisfaction degree Si, the greater the Si ij , the closer the value is to 1.

[0099]

[0100] wherein: I ij is the probability value of x ij , representing the contribution degree of the jth factor under the ith condition, n = 6.

[0101] (1.2) Calculate the information entropy (Ej) of each factor:

[0102]

[0103] wherein: if I ij = 0,

[0104] (1.3) To determine the weight of each objective evaluation factor, the information entropy (E1, E2, …, Ek) of each evaluation index is calculated according to the information entropy formula, and the weight of each evaluation index W i is calculated according to the formula:

[0105]

[0106] The P i values of surface temperature, working zone temperature, speed and pressure are calculated according to the formula, and the calculation results are shown in Table 4.

[0107] Table 4 Percentage of samples exceeding design requirements

[0108]

[0109]

[0110] (3) The satisfaction degree scores of each index obtained after calculation are shown in Table 5

[0111] Table 5 Satisfaction degree scores of each index i

[0112]

[0113] As shown in Table 5, after calculation, the satisfaction degree scores of each objective evaluation factor are shown in the table. After calculating the satisfaction degree scores of each factor, the scoring matrix X ij is obtained, and then the normalized matrix Y ij , the probability matrix I ij , the information entropy matrix E j , and the weight matrix w​i :

[0114]

[0115] E j = [0.85 0.89 0.85 0.85]

[0116] W i = [0.26 0.20 0.27 0.26]

[0117] After obtaining each matrix, the comfort satisfaction in this paper mainly includes heat dissipation efficiency satisfaction, temperature satisfaction, speed satisfaction and pressure satisfaction. The comfort satisfaction is quantitatively analyzed.

[0118] S wsi = W1S1 + W2S2 + W3S v + W4S T

[0119] Wherein, S1, S2, S V , S T represent heat dissipation efficiency, temperature, speed and pressure satisfaction scores respectively. W1, W2, W3, W4 are the weights of heat dissipation efficiency, temperature, speed and pressure respectively. S1, S2, S V , S T are used to quantitatively analyze the heat dissipation efficiency, temperature, speed and pressure satisfaction scores under different working conditions, and the results are the above scoring matrix X ij . The comfort satisfaction scores of personnel under different working conditions are calculated, as shown in Table 6.

[0120] Table 6 Weighted satisfaction scores

[0121]

[0122] The comprehensive score S

[0123] S = W a S ws1 + W b S ws2 + W c S ws3

[0124] In formula (6.12), W a is the comfort satisfaction, W b is the heat dissipation efficiency satisfaction, W c is the speed uniformity satisfaction, S ws1 is the comfort satisfaction score, S ws2 is the heat dissipation efficiency satisfaction score, S ws3Score for speed uniformity satisfaction. Determine the alternative according to the evaluation result to allocate resources and needs. From Figure 9 It can be seen that the scores of the three indexes of working condition one are the highest, which are 86.97, 87.89 and 86.62 respectively, and the ranking result is 1, therefore, working condition one is the optimal cabin ventilation scheme.

[0125] From the temperature distribution and the final ranking result of each evaluation index, when a cooling coil and a turbulence fan are used, the temperature and speed distribution in the cabin and the surface temperature distribution of the heating equipment are the most ideal, which is the optimal scheme for the ship cabin ventilation system. The present application provides a technical reference and theoretical basis for the optimization of the ship cabin ventilation system, and also improves the comfort of the personnel in the ship cabin and the safety of the heating equipment.

[0126] The above examples are only used to illustrate the design idea and characteristics of the present application, and its purpose is to enable those skilled in the art to understand the content of the present application and to implement it, and the protection scope of the present application is not limited to the above examples. Therefore, any equivalent changes or modifications made according to the principles and design ideas disclosed by the present application are within the protection scope of the present application.

Claims

1. A method for optimizing a ship engine room ventilation system, characterized in that: The following steps are involved: S1: Establish a three-dimensional physical model of the ship's engine room ventilation system; S2: Based on the 3D physical model of the ship engine room ventilation system, mesh the 3D physical model; S3: Based on the meshed 3D physical model, a mathematical model of the ship's engine room ventilation system is established. The mathematical model includes the air volume distribution of the port and starboard air ducts, a heat source power table, boundary conditions, control equations, and a turbulence model. S4: Develop various cabin ventilation system plans; S5: Based on the three-dimensional physical model and mathematical model, numerical simulations are performed on the schemes developed in S4 to obtain and analyze the temperature distribution inside the cabin and on the surface of the heat-generating equipment in the cabin and the air flow field under different schemes, and the evaluation indicators under each scheme are calculated; S6: Based on the evaluation indicators corresponding to each scheme, the AHP-entropy weight evaluation method is used to rank all schemes and select the optimal cabin ventilation system scheme.

2. The method for optimizing a ship engine room ventilation system according to claim 1, characterized in that: The calculation process of the AHP-entropy weight evaluation method is as follows: (1) Numerical simulation and verification: Numerical simulation analysis of the ship's engine room is carried out, and objective evaluation factors are determined based on the numerical simulation results, namely surface temperature, working area temperature, speed and pressure distribution; (2) Constructing the evaluation layer: preparing for determining the objective weight of each evaluation layer based on the surface temperature, working area temperature, velocity, and pressure data; (3) Determine the objective weights: Determine the objective weights corresponding to the surface temperature, working area temperature, speed, and pressure respectively, and use the entropy weight method to determine the weights of the surface temperature, working area temperature, speed, and pressure; (4) Determine the subjective weight: including the subjective evaluation factors, namely, the subjective weight corresponding to the satisfaction with heat dissipation efficiency, the satisfaction with comfort, and the satisfaction with speed uniformity; the subjective weight obtained through the questionnaire survey (5) Constructing criterion layers: Construct three criterion layers, each corresponding to a design goal, namely, heat dissipation efficiency, comfort, and speed uniformity. In each criterion layer, subjective and objective factors are integrated; (6) Obtain corresponding target results according to different criterion layers: Each criterion layer calculates the comprehensive score corresponding to each design target, and then selects the optimal working condition.

3. The method for optimizing a ship engine room ventilation system according to claim 2, characterized in that: After calculating the satisfaction scores of each objective evaluation factor, the satisfaction scores of each factor are calculated to obtain the scoring matrix X ij , and then get the standardized matrix Y ij , probability matrix I ij , information entropy matrix E j , weight matrix w i After weighted processing, the satisfaction scores for each working condition are obtained, which are recorded as: S wsi =W1S1+W2S2+W3S ν +W4S T ; Calculate the satisfaction score after weighting the subjective evaluation factors, which is recorded as: S=W a S ws1 +W b S ws2 +W c S ws3 Among them, S wsi is the comfort satisfaction, i takes 1, 2, and 3, representing the comfort score, heat dissipation efficiency score, and speed uniformity score, respectively; S1, S2, S V 、S T Respectively represent the satisfaction scores of heat dissipation efficiency, temperature, speed and pressure; W1, W2, W3, W4 are the weights of heat dissipation efficiency, temperature, speed and pressure respectively, a is comfort satisfaction, W b is the heat dissipation efficiency satisfaction, W c Satisfaction with speed uniformity.

4. The method for optimizing a ship engine room ventilation system according to claim 1, characterized in that: The boundary conditions include: the finite volume method is used as the solution algorithm, the standard format is used to discretize the pressure, the second-order upwind format is used to discretize the momentum and energy, and the SIMPLEC algorithm is used for solution calculation.

5. The method for optimizing a ship engine room ventilation system according to claim 1, characterized in that: The turbulence model adopts the standard k-ε model to perform turbulence simulation calculations. The standard k-ε model includes: a turbulence kinetic energy k equation and a turbulence dissipation rate ε equation.

6. The method for optimizing a ship engine room ventilation system according to claim 1, characterized in that: The control equations include a mass conservation equation, a momentum conservation equation, and an energy conservation equation.

7. The method for optimizing a ship engine room ventilation system according to claim 1, characterized in that: Taking cooling coils and spoiler fans as design objects, various alternative cabin ventilation system solutions are developed by changing the number, position and air volume ratio of installed cooling coils and spoiler fans.

8. The method for optimizing a ship engine room ventilation system according to claim 1, characterized in that: Based on numerical simulation, evenly distributed test points are selected, and the performance of the cabin ventilation system is quantitatively analyzed according to the evaluation indicators at the test points.

9. The method for optimizing a ship engine room ventilation system according to claim 1, characterized in that: The evaluation indicators include: heat dissipation efficiency and speed uniformity coefficient.

10. A ship engine room ventilation system, characterized in that: A ship cabin ventilation system designed using the ship cabin ventilation system optimization method described in claim 1.

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