Method for designing negative pressure chamber having open structure with optimized gas flow, device therefor, and same negative pressure chamber

Abstract

The present invention provides a method for designing a negative pressure chamber of a design device operated by at least one processor, the method comprising the steps of: performing a computational fluid dynamics (CFD) analysis with respect to a negative pressure chamber; designing the negative pressure chamber to have a structure and a shape capable of minimizing gas leakage on the basis of the CFD analysis; designing a location and a size of an inlet / outlet; and performing performance verification by measuring a gas leakage rate of the designed negative pressure chamber by using a poly alpha olefin (PAO) particle test.

Description

Method for designing an open-structure negative pressure chamber with optimized gas flow, the apparatus, and the negative pressure chamber

[0001] The present invention relates to a method for designing an open-structure negative pressure chamber with optimized gas flow, an apparatus thereof, and the negative pressure chamber thereof.

[0002] When treating patients with airborne infectious diseases, there is a high possibility of transmission through the air. Therefore, it is necessary to block the transmission routes of infectious diseases through negative pressure treatment, and a negative pressure chamber is used for this purpose.

[0003] A negative pressure chamber is a protective chamber used to isolate, transport, or treat infected patients, preventing the spread of infection.

[0004] Conventional negative pressure chambers often fail to adequately consider internal gas flow, making it difficult to determine specific blocking power or leakage prevention performance.

[0005] In particular, there are many cases where they are unable to cope with changes caused by coughing, breathing, or the patient's movement.

[0006] Closed chambers offer poor patient accessibility, and cloth barriers are vulnerable to contamination or the accumulation of infectious materials, often making internal control difficult.

[0007] The present disclosure provides a negative pressure chamber of a shape and structure capable of minimizing gas leakage based on the prediction of a path where gas leakage is expected by simulating air flow and pressure changes in a negative pressure chamber through computational fluid dynamics (CFD) analysis, a method for designing said negative pressure chamber, and an apparatus thereof.

[0008] According to one feature, a method for designing a negative pressure chamber of a design device operated by at least one processor comprises the steps of performing a Computational Fluid Dynamics (CFD) analysis on the negative pressure chamber, and designing a negative pressure chamber of a shape and structure capable of minimizing gas leakage based on the CFD analysis.

[0009] The above design step can design a negative pressure chamber of a shape and structure that increases the treatment space and eliminates the high-pressure area that causes internal droplets to flow out.

[0010] The above design step can design a negative pressure chamber in which ceiling curvature is generated.

[0011] The above design step can design an open-type negative pressure chamber without a shield on the patient's chest.

[0012] In the above designing step, an intake port may be positioned below the patient's head, in a location opposite to the open direction of the above open structure and close to the direction of droplet discharge during coughing.

[0013] The above design step can design a negative pressure chamber with a mesh structure having a mesh size of 5 mm.

[0014] The above-mentioned analysis step simulates airflow and pressure changes inside the negative pressure chamber to predict the expected path of gas leakage and simulates droplet behavior to predict potential external leakage of the negative pressure chamber, and the above-mentioned design step can design a negative pressure chamber with a structure and shape capable of minimizing the external leakage.

[0015] The above analysis step uses a turbulence model to simulate internal airflow and pressure changes in the negative pressure chamber and can derive an adverse pressure gradient to predict the gas outflow path.

[0016] After the above designing step, the method may further include a step of verifying the performance of the designed negative pressure chamber by measuring the gas leakage amount through a PAO (Poly Alpha Olefin) particle test on the designed negative pressure chamber.

[0017] According to another feature, the design device includes a memory for storing at least one instruction and a processor for executing said instruction. By executing said instruction, the processor includes an analysis unit that performs a Computational Fluid Dynamics (CFD) analysis of a negative pressure chamber and a design unit that designs a negative pressure chamber of a shape and structure capable of minimizing gas leakage based on said CFD analysis.

[0018] The analysis unit simulates airflow and pressure changes inside the negative pressure chamber to predict the expected path of gas leakage and simulates droplet behavior to predict potential external leakage of the negative pressure chamber, and the design unit can design a negative pressure chamber with a structure and shape capable of minimizing the external leakage.

[0019] The above design unit can design a negative pressure chamber that is open in structure without a shield on the patient's chest, has a ceiling curvature that can increase the treatment space and eliminate high-pressure areas that cause internal droplets to flow out, and has an intake port positioned opposite to the open direction and close to the direction of droplets when coughing, and is positioned below the patient's head.

[0020] The above processor may further include a simulation unit that verifies the performance of the designed negative pressure chamber by measuring the amount of gas leakage through a PAO (Poly Alpha Olefin) particle test targeting the designed negative pressure chamber.

[0021] According to another feature, the negative pressure chamber is equipped with an internal space for endotracheal intubation of a patient and includes a hood that covers the head and neck area of ​​the patient to protect it from the surrounding environment and has an open chest area of ​​the patient, and the hood may have a ceiling curvature formed to increase the procedure space and eliminate a high-pressure area that allows internal droplets to flow out.

[0022] The above hood may have an intake port positioned below the patient's head, in a location opposite to the opening direction of the hood and close to the direction of droplet discharge during coughing.

[0023] According to the present disclosure, airflow within a negative pressure chamber can be analyzed through CFD analysis, and based on this, a negative pressure chamber of a shape and structure capable of minimizing gas leakage even in an open state can be designed. By improving the design through CFD simulation, droplet leakage is reduced and the impact of airflow on the patient is minimized.

[0024] In addition, by controlling internal airflow through the analysis of internal gas flow in the negative pressure chamber, the barrier can be minimized to create an open design, thereby increasing ease of use and enhancing safety. This not only ensures the safety of patients and medical staff but also leads to economic savings on additional products.

[0025] FIG. 1 is a block diagram showing the configuration of a design device for a negative pressure chamber according to one embodiment.

[0026] FIG. 2a is a side view of a negative pressure chamber according to one embodiment.

[0027] FIG. 2b is a photograph showing a perspective view of a negative pressure chamber according to one embodiment.

[0028] FIG. 3a is a side view of a conventional negative pressure chamber for comparison with an embodiment of the present invention.

[0029] FIG. 3b is a photograph showing a perspective view of a conventional negative pressure chamber for comparison with an embodiment of the present invention.

[0030] Figure 4 is an example of an inlet velocity profile in the mouth caused by coughing used in the simulation of the present invention.

[0031] FIG. 5 is an example showing an unstructured mesh of a negative pressure chamber according to one embodiment.

[0032] Figure 6 shows the results of a mesh independence test using average total pressure according to one embodiment.

[0033] FIG. 7 is a diagram illustrating an aerosol leakage simulation according to one embodiment.

[0034] FIG. 8 is a flowchart illustrating a method for designing a negative pressure chamber according to one embodiment.

[0035] FIG. 9 is a configuration diagram of a computing device according to an embodiment.

[0036] Figure 10 is a photograph showing an example of a negative pressure chamber (tracheal intubation hood) and a negative pressure generator with a patient.

[0037] Figures 11a, 11b, 12a, 12b, 13a, and 13b show the results of comparing CFD simulation and real-time measurement of droplet leakage.

[0038] Figure 14 is a simulation domain for the verification and definition of distance and convection velocity.

[0039] Figure 15 is a diagram comparing the distance between the CFD results and the empirical equation.

[0040] Figure 16 is a diagram comparing the convection velocity between CFD results and empirical equations.

[0041] Figure 17 is a graph showing the relationship between time and pressure according to the simulation.

[0042] Figure 18a shows the relationship between X[m] at the beginning of coughing and particle number density (m-3) according to simulation.

[0043] Figure 18b shows the relationship between particle number density (m-3) and Z[m] at the beginning of coughing according to simulation.

[0044] Figure 19a shows the relationship between X[m] and particle number density (m-3) during the middle of coughing according to simulation.

[0045] Figure 19b shows the relationship between particle number density (m-3) and Z[m] during the middle of cough according to simulation.

[0046] Figure 20a shows the relationship between X[m] at the end of a cough and particle number density (m-3) according to simulation.

[0047] Figure 20b shows the relationship between particle number density (m-3) and Z[m] at the end of a cough according to simulation.

[0048] Figure 21 shows a comparison of total leakage through the relationship between time and particle total mass flow (kg / s) according to the simulation.

[0049] Figure 22 shows the Outler mass flow by comparing the relationship between time and particle total mass flow (kg / s) according to the simulation.

[0050] Embodiments of the present disclosure are described below with reference to the attached drawings so that those skilled in the art can easily implement them. However, the present disclosure may be embodied in various different forms and is not limited to the embodiments described herein. Furthermore, in order to clearly explain the present disclosure in the drawings, parts unrelated to the explanation have been omitted, and similar parts throughout the specification are denoted by similar reference numerals.

[0051] Throughout the specification, when a part is described as "including" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0052] Additionally, terms such as “…part,” “…unit,” and “…module” described in the specification refer to a unit that processes at least one function or operation, and this may be implemented in hardware, software, or a combination of hardware and software.

[0053] In this specification, "transmission or provision" may include not only direct transmission or provision but also indirect transmission or provision through another device or by using an alternative route.

[0054] Expressions described in the singular in this specification may be interpreted as singular or plural unless explicit expressions such as "one" or "single" are used.

[0055] In this specification, the same reference numeral refers to the same component regardless of the drawing, and "and / or" includes each of the mentioned components and all combinations of one or more.

[0056] In this specification, terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but said components are not limited by said terms. Such terms are used solely for the purpose of distinguishing one component from another. For example, without departing from the scope of the present disclosure, the first component may be named the second component, and similarly, the second component may be named the first component.

[0057] In the flowchart described with reference to the drawings in this specification, the order of operations may be changed, several operations may be merged or some operations may be divided, and certain operations may not be performed.

[0058] The devices described in the present invention are composed of hardware including at least one processor, a memory device, a communication device, etc., and a program that is executed in combination with the hardware is stored in a designated location. The hardware has a configuration and performance capable of executing the method of the present invention. The program includes instructions that implement the method of operation of the present invention described with reference to the drawings, and executes the present invention in combination with hardware such as a processor and a memory device. The program includes instructions described to enable a processor to execute the operation of the present disclosure, and may be stored on a non-transitory computer-readable storage medium. The computer program may be downloaded via a network or sold in the form of a product.

[0059]

[0060] FIG. 1 is a block diagram showing the configuration of a design device for a negative pressure chamber according to one embodiment, FIG. 2a is a side view of a negative pressure chamber according to one embodiment, FIG. 2b is a photograph showing a perspective view of a negative pressure chamber according to one embodiment, FIG. 3a is a side view of a conventional negative pressure chamber for comparison with an embodiment of the present invention, FIG. 3b is a photograph showing a perspective view of a conventional negative pressure chamber for comparison with an embodiment of the present invention, FIG. 4 is an example of an inlet velocity profile in the mouth due to coughing used in the simulation of the present invention, FIG. 5 is an example showing an unstructured mesh of a negative pressure chamber according to one embodiment, FIG. 6 shows the results of a mesh independence test using average total pressure according to one embodiment, and FIG. 7 is a diagram explaining an aerosol leakage simulation according to one embodiment.

[0061] A negative pressure chamber, or intubation hood, is a hood-shaped system that traps aerosols and is designed to contain them. Negative pressure chambers are transparent and are used to isolate aerosolized viruses during tracheal intubation procedures and to protect healthcare workers from transmission.

[0062] Referring to FIG. 1, the design device (100) may be a computing device operated by at least one processor. The design device (100) may include an analysis unit (110), a design unit (120), and a simulation unit (130).

[0063] The analysis unit (110) can predict the path of gas (or aerosol) leakage by simulating air flow and pressure changes inside the negative pressure chamber through computational fluid dynamics (hereinafter collectively referred to as 'CFD') analysis.

[0064] The analysis unit (110) can predict potential external leakage of the negative pressure chamber by simulating the behavior of droplets (or aerosols) through CFD analysis.

[0065] The design department (120) can design a negative pressure chamber of a shape and structure that minimizes gas leakage based on the CFD analysis results of the analysis department (110). That is, the design department (120) can design a negative pressure chamber of a shape and structure that minimizes gas leakage, which is improved over the existing negative pressure chamber, through CFD analysis of the existing negative pressure chamber that has already been developed.

[0066] The design unit (120) designs a shape and structure that can minimize gas leakage based on the analysis results of the path where gas leakage is expected, which is predicted through the simulation of air flow and pressure changes inside the existing negative pressure chamber by the analysis unit (110).

[0067] The design unit (120) can design a negative pressure chamber with a structure capable of effectively controlling turbulence generated during coughing or breathing based on the CFD analysis results of the analysis unit (110).

[0068] The design unit (120) can adjust the location and size of the intake and exhaust ports of the negative pressure chamber based on the CFD analysis results of the analysis unit (110).

[0069] The design unit (120) can design the shape of the negative pressure chamber by size based on the CFD analysis results of the analysis unit (110).

[0070] The design department (120) can reduce costs and time required for direct manufacturing by utilizing CFD analysis when increasing or decreasing the size of the negative pressure chamber.

[0071] The design unit (120) can design the negative pressure chamber as an open structure to ensure convenience for medical personnel during the procedure.

[0072] According to the CFD analysis of the analysis unit (110), a CFD simulation was performed on a legacy negative pressure chamber, that is, a conventional negative pressure chamber (original hood), and the result was that when coughing, the slope of the ceiling creates a high-pressure area, causing droplets to flow out.

[0073] Based on this CFD analysis, the design unit (120) can design a negative pressure chamber with a structure that eliminates the slope structure of a conventional negative pressure chamber, creates a ceiling curvature to increase the treatment space, and eliminates high-pressure areas. The design unit (120) can reduce the risk of infection to medical staff and patients by minimizing the leakage of droplets and aerosols generated inside the negative pressure chamber.

[0074] The design section (120) can be designed with dimensions limited to the width, length, and height of the negative pressure chamber, all of which are approximately 500 mm, thereby increasing usability for medical personnel.

[0075] The design section (120) can be designed as an open-type negative pressure chamber without a shield on the patient's chest.

[0076] The design section (120) may have four access ports for medical personnel formed at multiple points covering the patient's head and neck in the negative pressure chamber.

[0077] As a result of CFD simulation, some aerosol particles leak through the lower part of the negative pressure chamber, and more particles leak from the opposite side of the cough direction. Additionally, it was found that the number of particles leaked when coughing toward the intake port is small. Based on these results, the design unit (120) can place the intake port in an open-structure negative pressure chamber in a position opposite to the open direction and close to the direction of droplet discharge during coughing, and below the patient's head.

[0078] Referring to FIGS. 2a and 2b, the negative pressure chamber (100) is provided with an internal space for endotracheal intubation of a patient and is in the form of a hood with a structure that covers the patient's head and neck area to protect them from the surrounding environment while leaving the patient's chest area open. The hood has a ceiling curvature formed to increase the procedure space and eliminate high-pressure areas that allow internal droplets to flow out to the outside.

[0079] The negative pressure chamber (100) is designed to cover the patient's head and neck area to protect it from the surrounding environment. The negative pressure chamber (100) can be designed with dimensions limited to a width, length, and height of approximately 500 mm.

[0080] The negative pressure chamber (100) is in the form of a hood capable of accommodating the patient's head and neck area, with the point where the patient's neck is located being open (101) and the point where the patient's head is located and the patient's left and right sides being closed.

[0081] Four patient access ports (102) may be formed in the negative pressure chamber (100).

[0082] At this time, the location of the patient access port (102) can be determined by evaluating the optimal elbow height of a medical worker during a procedure such as tracheal intubation or bag-valve-mask ventilation. For example, two patient access ports (102) may be formed at the airway operator's position, that is, at the point where the patient's head is located, and two may be formed at predetermined locations on both sides.

[0083] An intake port / exhaust port (103) is formed on the side of the negative pressure chamber (100). Such intake ports / exhaust ports (103) can be formed on both sides.

[0084] A hose for connecting a negative pressure generator is attached to an intake / outlet (103) formed on one side of a negative pressure chamber (100), and a ventilation fan is attached to each end of the hose.

[0085] The intake port / exhaust port (103) includes an intake port for the negative pressure generator to draw in air inside the negative pressure chamber (100) and an exhaust port for discharging air into the negative pressure chamber (100) to maintain the negative pressure of the negative pressure chamber (100) at a constant state.

[0086] The intake port (103) can be positioned close to where droplets are ejected due to coughing.

[0087] Additionally, the intake port (103) can be positioned at a lower point close to the floor.

[0088] The intake port (103) can be positioned opposite to the open direction of the patient's chest and close to the direction of droplet discharge when coughing, and below the patient's head.

[0089] The negative pressure chamber (100) according to the embodiment of FIG. 2a has a structure in which the slope formed on the upper part of the existing negative pressure chamber (Fig. 3a) is removed and the ceiling curvature (104) is applied to increase the treatment space.

[0090] Referring to Figures 3a and 3b, the structure of a conventional negative pressure chamber has a slope formed at the top. Consequently, there is a problem where the end of the endotracheal tube frequently touches the ceiling of the hood, interfering with the procedure.

[0091] On the other hand, the negative pressure chamber (100) according to the embodiment of the present invention of FIG. 2a and 2b has a ceiling curvature (round curve) (104) formed to increase the height of the central part of the negative pressure chamber (100) and, at the same time, reduce the overall length compared to the existing negative pressure chamber (Fig. 3a, 3b) to improve usability for medical personnel. The structure of this negative pressure chamber (100) was guided and verified through CFD simulation to confirm that it does not affect the blocking performance of the negative pressure chamber (100).

[0092] Air inside a small space, such as a negative pressure chamber, exhibits turbulent characteristics due to low viscosity and perturbations caused by the repetitive cycles of exhalation and inhalation. Turbulence refers to a flow that includes random and chaotic vortices.

[0093] The gas outflow path can be predicted using a turbulence model from CFD analysis. For this prediction, the adverse pressure gradient (APG) can be derived through CFD analysis.

[0094] The analysis unit (110) uses a turbulence model to simulate internal air flow and pressure changes in the negative pressure chamber (100) and derives an adverse pressure gradient to predict the gas outflow path.

[0095] At this time, the analysis unit (110) can perform CFD analysis using commercial flow simulation software.

[0096] In CFD analysis, a shear stress transport model based on the Reynolds-averaged Navier-Stokes equation (k-ω) is used as the turbulence model. This shear stress transport model is useful for predicting the adverse pressure gradient (APG).

[0097] A turbulence model can be used to predict the expected path of gas (or aerosol) leakage by simulating airflow and pressure changes inside a negative pressure chamber.

[0098] The turbulence model solves a total of four transport equations: the continuous equation, the momentum transport equation based on the Reynolds-averaged Navier-Stokes equations, and two equations for turbulent kinetic energy (k) and the turbulent frequency (ω). The stress tensor is calculated from the vorticity-viscosity concept.

[0099] Equation 1 below represents the continuity equation, Equation 2 represents the momentum transport equation, Equation 3 represents the equation for turbulent kinetic energy (k), and Figure 4 represents the equation for turbulent frequency (ω).

[0100] [Mathematical Formula 1]

[0101]

[0102] [Mathematical Formula 2]

[0103]

[0104] [Mathematical Formula 3]

[0105]

[0106] [Mathematical Formula 4]

[0107]

[0108] ρ is density. t is time. x is spatial displacement, and j is an arbitrary direction j. is the velocity vector. i is an arbitrary direction i. is the turbulence generation amount. τ is the molecular stress tensor. is the velocity vector for any direction i, and is the velocity vector for an arbitrary direction j, and is the turbulent eddy viscosity. b is the Boussinesq buoyancy term.

[0109] S P is the source term of momentum by particle. P k is the turbulence generation velocity calculated from the k-ω model.

[0110] The model variables are β'=0.09, α=5 / 9, β=0.075, σ k =2, σ ω It is given as =2.

[0111] In addition to independent variables, the density ρ and the velocity vector is treated as a known quantity in the Reynolds mean Navier-Stokes equation.

[0112] It is calculated as in mathematical formula 5.

[0113] [Mathematical Formula 5]

[0114]

[0115] F2 is a blending function that limits the limiter to the wall boundary layer because the basic assumption does not fit free shear flow. S is an invariant measure of the strain rate. is a numerical constant, and its value is 5 / 9.

[0116] [Mathematical Formula 6]

[0117]

[0118] is an unknown Reynolds stress tensor, calculated as in Equation 7.

[0119] [Mathematical Formula 7]

[0120]

[0121] is the Kronecker delta operator.

[0122] Just as a fluid influences the behavior of particles through forces such as convective heat transfer, particles also exert an opposing influence on the fluid; this is called coupling.

[0123] The analysis unit (110) simulates two-way coupling, which is a case where particles also influence fluid behavior. To use two-way coupling, a particle source term must be included in the fluid momentum equation. The momentum source is attributed to drag, and the particle source term is generated for each particle while tracking the flow. The particle source is applied to the control volume where the particle is located during the time step. The particle source for the fluid momentum equation is obtained by solving the transport equation for the source. A typical equation for the particle source is Equation 8.

[0124] [Mathematical Formula 8]

[0125]

[0126] is the contribution of a particle that is linear in the solution variable, and R S is the mass transfer term where appropriate. Includes all other contributions, including

[0127] This equation has the same form as general particle transport and can be solved in the same way as described above. Then, the source to be added to the continuum is multiplied by the particle flow rate. The particle flow rate is the mass flow rate of the corresponding particle divided by the particle mass.

[0128] In flow simulation software, the particle source term is recalculated whenever particles are injected. The source term is then stored in memory and can be applied whenever fluid coefficients are calculated. This allows the particle source to be applied in the current flow rate calculation even if no particles are being injected.

[0129] The forces acting on a discrete particle moving in a continuous fluid medium that affect the particle's acceleration are due to the velocity difference between the particle and the fluid and the displacement of the fluid caused by the particle. The equation of motion for this particle was derived from the Basset-Boussinesq-Oseen equation (BBO equation) in fluid dynamics for a rotating reference frame and is given by Equation 9.

[0130] [Mathematical Formula 9]

[0131]

[0132] m p is the particle mass and U p is the particle speed.

[0133] F D is the drag force acting on the particle.

[0134] F B is the buoyancy force due to gravity.

[0135] F R is the force due to domain rotation (centripetal and Coriolis forces).

[0136] F VM is a virtual (or added) mass force. F VM is a force that accelerates the virtual mass of the fluid in the volume occupied by the particle, and this term is important when the displaced fluid mass exceeds the particle mass (e.g., the movement of bubbles).

[0137] F P is the pressure gradient force. F Pε is the force exerted on a particle due to the pressure gradient of the fluid surrounding the particle caused by fluid acceleration, and is important only when the fluid density is similar to or greater than the particle density.

[0138] F, the aerodynamic drag force acting on the particle D U is the slip velocity between the particle and the fluid velocity. S It is proportional to and is equal to mathematical formula 10.

[0139] [Mathematical Formula 10]

[0140]

[0141] C D is the drag coefficient and d P is the particle diameter. C D is introduced to explain the experimental results for the viscous drag of a solid sphere, and a value of 0.44 can be used.

[0142] is the fluid density.

[0143] Buoyancy is a force acting on a particle submerged in a fluid, equal to the weight of the displaced fluid, and is given by Equation 11.

[0144] [Mathematical Formula 11]

[0145]

[0146] is the gravity vector. is the particle density, and is the fluid density.

[0147] Rotation term (F) in the rotating reference frame R ) is an essential part of acceleration and is the sum of the Coriolis force and the centripetal force, as shown in Equation 12.

[0148] [Mathematical Formula 12]

[0149]

[0150] F R This occurs because the particle must accelerate a portion of the surrounding fluid, which results in additional drag in the form of the following mathematical equation 13.

[0151] [Mathematical Formula 13]

[0152]

[0153] If virtual mass force is included, coefficient C VM It is generally set to 1.

[0154] The pressure gradient force F P It occurs at the local fluid pressure gradient around the particle and is defined as in Equation 14.

[0155] [Mathematical Formula 14]

[0156]

[0157] A cough, which is an inlet condition, can be modeled as shown in Fig. 4.

[0158] Figure 4 shows the entry velocity profile in the mouth caused by coughing. The cough droplet size distribution is modeled by applying the Rosin-Rammler model.

[0159] Each cough droplet was applied to a particle break model. The Taylor Analogy Breakup (TAB) model, a classical method for calculating droplet breakdown, was used as the particle break model.

[0160] The time-dependent particle distortion equation according to the TAB model is given by Equation 15.

[0161] [Mathematical Formula 15]

[0162]

[0163] We Cis the newly calculated Weber number. t, t D t is a time constant calculated based on the time variable, density, drag coefficient, and viscosity. d is the characteristic breakup time. is the particle vibration frequency. P represents the particle. r is the radius of the particle. μ p ε is the viscosity of the particle. σ is the surface tension.

[0164] C d is the damping coefficient.

[0165] C k is the restoring force coefficient.

[0166] C f is the external force coefficient.

[0167] C b is the critical amplitude coefficient.

[0168] C ν is a new droplet velocity factor.

[0169] K is the energy ratio factor.

[0170] Here, the analysis unit (110) is C b =0.5, C d =0.5, C f 1 / 3 of C k =8.0, C ν =1.0, C ν You can use 10 / 3.

[0171] The analysis unit (110) can set the element size to 5 mm so that the total number of meshes in the case of the negative pressure chamber mesh is 3,780,013, as shown in FIG. 5.

[0172] The analysis unit (110) performed a grid independence test to check the sensitivity of the aerosol generating solution with a mesh element size generated as in FIG. 5.

[0173] Referring to Figure 6, the grid independence test results show the average total pressure change (Average total pressure, Pa) at various mesh element sizes.

[0174] As the mesh size decreases from 12.5 mm to 5 mm, the total pressure becomes more stable. Specifically, reducing the mesh size from 12.5 mm to 10 mm changes the average total pressure by 26.11%. Further reducing the mesh size from 10 mm to 7.5 mm results in a 12.13% change. Finally, reducing the mesh size from 7.5 mm to 5 mm results in only a 1.26% change.

[0175] This indicates that beyond a mesh size of 7.5 mm, the aerosol generation solution becomes almost independent of mesh resolution, and confirms that a mesh size of 5 mm is sufficient to derive an accurate aerosol generation solution with minimal computational cost. Here, mesh resolution is the resolution of the computational grid.

[0176] The simulation unit (130) verifies the performance of the negative pressure chamber by measuring the amount of gas outflow within the designed negative pressure chamber using a PAO (Poly Alpha Olefin) particle test.

[0177] The simulation unit (130) tested real-time droplet leakage or flow by performing PAO particle tests under various conditions on a negative pressure chamber designed to improve user convenience and reduce gas (or droplet) leakage.

[0178] According to the simulation, polyalphaolefin (PAO) particles were generated inside a negative pressure chamber, and leakage measurements were taken every 10 seconds for 90 seconds.

[0179] To ensure consistent leak measurements, the open side of the negative pressure chamber was divided into nine sections, and tests were conducted in a standardized structure to guarantee accuracy.

[0180] Referring to Fig. 7, to identify the area with the most aerosol leakage, the open part of the negative pressure chamber, i.e., the patient's chest side, is divided into 9 sections (1, 2, 3, 4, 5, 6, 7, 8, 9).

[0181] Using an aerosol generator with a valve, PAO particles were dispersed in three directions: the same side, directly toward the center of the ceiling, and opposite the inlet (opposite side).

[0182] At this time, the suction hole is located on the inside of the right side of the negative pressure chamber.

[0183] The simulation unit (130) can be guided and verified through CFD simulation to ensure that the changes do not affect the blocking performance of the hood.

[0184] Measurements of leaked mass flow were performed through simulation analysis of droplet leakage in three types of droplet diffusion scenarios with a suction force of -10 Pa using a modified hood design.

[0185] Simulation results show that the highest leakage areas are on the opposite side of the cough direction and on both sides under mid-to-upper diffusion conditions.

[0186] Furthermore, some particles leaked through the lower part of the negative pressure chamber, and when droplets were sprayed at high pressure, more particles leaked from the opposite side of the cough direction. Similarly, CFD simulations showed that fewer particles leaked when coughing towards the inhalation port.

[0187] According to the simulation results, the performance was verified to maintain a gas leakage rate of less than 0.3% under cough and breathing conditions.

[0188] The simulation unit (130) confirmed that, despite reducing the size of the negative pressure chamber, the leakage rate decreased by 36.2% and the aerosol extraction efficiency increased by approximately 3204.6%. That is, even in an open structure, a droplet leakage rate of less than 0.3% was maintained.

[0189] These results demonstrate the potential of CFD-guided design in developing respiratory barriers that effectively reduce the risk of aerosol transmission during high-risk medical procedures. This approach not only improves safety for both patients and healthcare providers but also provides a scalable solution that enables safer execution of aerosol-generating procedures (AGPs) in various medical settings.

[0190] CFD analysis showed that the protective effect of the negative pressure chamber is sufficient even without a chest shield for the patient, that is, in an open structure. While the slanted ceiling of conventional negative pressure chambers generates a high-pressure area during coughing, leading to increased droplet leakage, the negative pressure chamber of the present invention, designed with a ceiling curvature design, showed a 36.2% reduction in leakage and a 3204.68% improvement in droplet discharge. Specifically, the maximum leakage during breathing was 0.0536%, and during coughing was 0.3067%, with total leakage being less than 0.3%, effectively reducing droplet leakage and improving both safety and procedure efficiency.

[0191] The simulation unit (130) can adjust the negative pressure level of the negative pressure chamber based on the droplet dispersion simulation.

[0192] Droplet flow simulation results showed that droplets remain near the open part of the negative pressure chamber due to the high-pressure region created by the ceiling slope, delaying their movement to the intake port. Additionally, the high pressure generated by coughing exceeds the suction force. Based on these results, the negative pressure level of the negative pressure chamber can be adjusted. For example, the suction pressure at the intake port can be increased.

[0193]

[0194] FIG. 8 is a flowchart illustrating a method for designing a negative pressure chamber according to one embodiment.

[0195] Referring to FIG. 8, the analysis unit (110) performs a CFD analysis on the negative pressure chamber (S101). At this time, the analysis unit (110) simulates the air flow and pressure changes inside the negative pressure chamber through a CFD analysis on the original negative pressure chamber, that is, the previously constructed negative pressure chamber.

[0196] The analysis unit (110) can determine that when a patient coughs, the slope of the ceiling of the original negative pressure chamber creates a high-pressure area, causing droplets to flow out, some aerosol particles to leak through the lower part of the negative pressure chamber, and more particles to leak from the opposite side of the cough direction.

[0197] The design department (120) designs the shape and structure of the negative pressure chamber and the location and size of the intake / exhaust port to minimize the leakage of aerosols based on the CFD analysis results of S101 (S102).

[0198] That is, the design section (120) can increase the operating space and eliminate high-pressure areas by removing the ceiling slope structure and creating a ceiling curvature structure from the structure of the original negative pressure chamber. Additionally, the design section (120) can reduce the total length of the negative pressure chamber to within 500 mm while having an open structure for the convenience of the procedure. Furthermore, the design section (120) can place the suction port below the patient's head, in a position opposite to the open direction toward the patient's chest and close to the direction of droplet discharge when coughing.

[0199] The simulation unit (130) performs performance verification by measuring the gas outflow of the designed negative pressure chamber using a PAO particle test (S103).

[0200]

[0201] FIG. 9 is a configuration diagram of a computing device according to an embodiment.

[0202] Referring to FIG. 9, the design device (100) described in FIG. 1 to FIG. 8 can be implemented as a computing device (200) operated by at least one processor.

[0203] A computing device (200) may include one or more processors (210), a memory (220) for loading a computer program executed by the processor (210), a storage device (230) for storing the computer program and various data, a communication interface (240), and a bus (250) connecting them. In addition, the computing device (200) may include various additional components. The processor (210) is a device that controls the operation of the computing device (200) and may be a processor of various types that processes instructions included in a computer program, and may be configured to include, for example, at least one of a CPU (Central Processing Unit), MPU (Micro Processor Unit), MCU (Micro Controller Unit), GPU (Graphic Processing Unit), or any type of processor well known in the art of the present disclosure.

[0204] The memory (220) stores various data, instructions and / or information. The memory (220) may load a corresponding computer program from a storage device (230) so that instructions described to execute the operation of the present disclosure are processed by a processor (210). The memory (220) may be, for example, ROM (read only memory), RAM (random access memory), etc.

[0205] The storage device (230) can store computer programs and various data non-temporarily. The storage device (230) may be configured to include non-volatile memory such as ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), flash memory, a hard disk, a removable disk, or any form of computer-readable recording medium well known in the art to which this disclosure belongs.

[0206] The communication interface (240) may be a wired / wireless communication module that supports wired / wireless communication.

[0207] The bus (250) provides communication between components of the computing device (200).

[0208] A computer program includes instructions executed by a processor (210) and is stored in a non-transitory computer-readable storage medium, wherein the instructions cause the processor (210) to execute the operation of the present disclosure. The computer program may be downloaded over a network or sold as a product.

[0209] The computer program may include instructions for executing the analysis unit (110), the design unit (120), and the simulation unit (130).

[0210]

[0211] The present invention will be described in detail below through experimental examples. These experimental examples are merely for illustrating the present invention and are not limited thereto.

[0212] Experimental Example

[0213] Figure 10 is an example of a negative pressure chamber (tracheal intubation hood) with a patient and a negative pressure generator, and Figures 11a, 11b, 12a, 12b, 13a, and 13b show the results of a comparison of CFD simulation and real-time measurement of droplet leakage.

[0214] As shown in Fig. 10, the negative pressure generator is connected to a negative pressure chamber in which a patient is accommodated, i.e., an intubation hood, and generates negative pressure inside the negative pressure chamber.

[0215] The negative pressure generator can be designed to achieve 99.7% efficiency by continuously drawing air from inside the negative pressure chamber through an 80mm diameter duct and passing it through a HEPA filter.

[0216] The ventilation fan is installed inside the negative pressure generator and can be designed to operate up to 4 levels of boosters depending on the difference in negative pressure between the inside and outside of the negative pressure chamber.

[0217] To verify the safety of the negative pressure chamber equipped with a negative pressure generator, a PAO particle leakage test was conducted for 90 seconds at 10-second intervals in each of the 9 zones of the negative pressure chamber (Fig. 7).

[0218] Under breathing conditions where PAO particles were continuously sprayed for 90 seconds, the maximum leakage was less than 0.1%. However, under coughing conditions where PAO particles were sprayed six times over 15 seconds, the maximum leakage was nearly 0.8%.

[0219] As a result of the experiment and simulation analysis measuring the leakage mass flow, the highest leakage zones were observed on the opposite side of the cough direction and on both sides under mid-to-upper diffusion conditions.

[0220] When droplets were dispersed under high pressure, more particles leaked from the opposite direction of the cough.

[0221] CFD simulation results showed that fewer particles were leaked when coughing toward the inhalation port.

[0222] Fine dust leakage under breathing conditions showed minimal leakage, peaking at about 0.0536% at 10 seconds and rapidly decreasing to nearly 0 by 50 seconds.

[0223] There is a noticeable initial spike, but it drops quickly. However, under coughing conditions, fine dust leakage is significantly high, showing a peak value of 0.3067% at 10 seconds before gradually decreasing, but the total exposure appears higher than during breathing.

[0224] Increasing the suction power of the negative pressure chamber fan to enhance the protective effect can lead to greater airflow inside the chamber, potentially causing patient discomfort or obstructing breathing. To address this, CFD analysis was utilized.

[0225] Using a modified negative pressure chamber design, a simulation analysis of droplet leakage was performed in three types of droplet diffusion scenarios with a suction force of -10 Pa.

[0226] It can be programmed to activate an additional booster when the pressure difference drops below -10 Pa and to disable the booster when the pressure difference exceeds -20 Pa.

[0227] The pressure difference can be continuously monitored using a sensor during suction.

[0228] Although droplet leakage under cough conditions varied and exceeded the efficiency threshold of 0.3% for HEPA filters, our test conditions were much stricter, using particle concentrations 105 times higher than actual cough scenarios. Additionally, the density of PAO (0.82–0.86 g / cm3) is lower than the density of droplets (1 g / cm3) generated during coughing, which consist mainly of water. Therefore, it is assumed that the actual leakage amount in real scenarios will be lower than that observed under experimental conditions.

[0229] During simulation, particle leakage measurements can be taken in a negative pressure chamber using an aerosol photometer. In this case, the measurement position of the aerosol photometer can be consistently maintained by using a stabilizing bar that fixes and supports the aerosol photometer at a specific point.

[0230] When the patient's chest shield is not present, the internal and external pressure difference is maintained at -10 Pa or less, keeping all four boosters in operation. When the negative pressure chamber is completely closed, the pressure difference exceeds -80 Pa with all four boosters operating.

[0231] At this time, the negative pressure chamber was kept open, and the simulation unit (130) evaluated the blocking efficiency under conditions where all four boosters were operating automatically.

[0232] Particle leakage from inside to outside of the negative pressure chamber (100) was evaluated by adopting the PAO particle method commonly used for HEPA filter integrity testing.

[0233] Particle leak assessment is performed by referring to standards such as ISO (International Organization for Standardization) 14644-3, which accurately detect leaks. ISO 14644-3 specifies test methods for determining the designated air cleanliness grades and performance of clean rooms and clean zones.

[0234] PAO particles were generated inside a negative pressure chamber using an aerosol generator, and the PAO concentration was maintained between 100 and 120 μg / L, unlike the ISO standard which recommends a concentration of 20 to 30 μg / L to ensure more robust test conditions.

[0235] Aerosol leakage was detected using an aerosol photometer, and significant leakage was defined as exceeding 0.3% of the particles generated inside the negative pressure chamber, and leakage of 0.1% or more was also recorded.

[0236] Aerosol measurements were performed 9 times at 10-second intervals for 90 seconds at a distance of 15 cm from the open part of the negative pressure chamber. This entire process was repeated 5 times. Then, the leakage pattern was further evaluated by comparing these results with CFD analysis.

[0237] The PAO particle injection method was adjusted to simulate both the coughing and normal breathing of a patient inside a negative pressure chamber.

[0238] In the cough scenario, the concentration of PAO particles in the central region of the negative pressure chamber was increased to reach 100–120 μg / L over 90 seconds. This amount of PAO particle concentration was released six times to simulate the cough model.

[0239] In addition, a valve was used to control the release of an equal amount of aerosol, slowly dispersing it over 90 seconds to simulate particle release during normal breathing.

[0240] Considering the total number of droplets typically exhaled by a patient (approximately 7,200 particles per liter with an early volume of 450 mL per breath at 15 breaths per minute), the droplets dispersed in the negative pressure chamber would reach approximately 780 particles / L over 90 seconds. This corresponds to a PAO particle concentration of less than 0.0001 μg / L, indicating that the simulated particle concentration was significantly higher than that typically generated by humans, thereby ensuring more rigorous testing of system performance.

[0241]

[0242] FIG. 11a includes graphs showing the CFD simulation results of droplet leakage in the opposite side coughing direction (Opposite side coughing direction in FIG. 7), that is, the results predicted through CFD analysis, and FIG. 11b includes graphs showing the real-time measurement results of droplet leakage in the opposite side coughing direction (Opposite side coughing direction in FIG. 7).

[0243] Referring to Fig. 11a, time (x-axis, Times[s], interval: 10) and droplet mass flow density (y-axis, Droplet mass flow density, kg m⁻²) are shown. 2 s 1 Represents the relationship of , interval: 0.002).

[0244] Each graph represents the results of simulating the leakage rate by region in the open area of ​​the negative pressure chamber. That is, the nine graphs show the droplet mass flow density detected in each section (1, 2, 3, 4, 5, 6, 7, 8, 9) over time for each of the nine sections (1, 2, 3, 4, 5, 6, 7, 8, 9) of Fig. 7.

[0245] Referring to Fig. 11b, the horizontal axis (x-axis) represents time in the range of 10s to 100s (interval: 10s), and the vertical axis (y-axis) represents leakage rate in the range of 0 to 0.8 (interval: 0.1).

[0246] Similar to Fig. 11a, each graph represents the results of actual measurements of the leakage rates in different parts of the open area of ​​the negative pressure chamber, that is, the leakage rates of each of the nine sections (1, 2, 3, 4, 5, 6, 7, 8, 9) of Fig. 7.

[0247] FIG. 12a includes graphs showing the results of CFD simulation of droplet leakage in the ceiling coughing direction (Ceiling coughing direction in FIG. 7), that is, the results predicted through CFD analysis, and FIG. 12b includes graphs showing the results of real-time measurement of droplet leakage in the ceiling coughing direction (Ceiling coughing direction in FIG. 7).

[0248] Referring to Fig. 12a, time (x-axis, Times[s]) and droplet mass flow density (y-axis, Droplet mass flow density, kg m⁻²) are shown. 2 s 1 It represents the relationship of ). The x-axis ranges from 0 to 40 (interval: 10), and the y-axis ranges from 0 to 0.01 (interval: 0.002).

[0249] Each graph represents the results of simulating the leakage rates of each open area of ​​the negative pressure chamber, that is, the leakage rates of each of the nine sections (1, 2, 3, 4, 5, 6, 7, 8, 9) in Fig. 7.

[0250] Referring to Fig. 12b, the horizontal axis (x-axis) represents time in the range of 10s to 100s (interval: 10s), and the vertical axis (y-axis) represents leakage rate in the range of 0 to 0.8 (interval: 0.1).

[0251] Each graph shows the results of actual measurements of the leakage rates in each open area of ​​the negative pressure chamber, that is, the leakage rates of each of the nine sections (1, 2, 3, 4, 5, 6, 7, 8, 9) in Fig. 7.

[0252] FIG. 13a includes graphs showing the results of CFD simulation of droplet leakage in the coughing direction of the inhaler (same side coughing direction in FIG. 7), that is, the results predicted through CFD analysis, and FIG. 13b includes graphs showing the results of real-time measurement of droplet leakage in the coughing direction of the inhaler (same side coughing direction in FIG. 7).

[0253] Referring to Fig. 13a, time (x-axis, Times[s]) and droplet mass flow density (y-axis, Droplet mass flow density, kg m⁻²) are shown. 2 s 1 It represents the relationship of ). The x-axis ranges from 0 to 40 (interval: 10), and the y-axis ranges from 0 to 0.01 (interval: 0.002).

[0254] Each graph represents the results of simulating the leakage rates of each open area of ​​the negative pressure chamber, that is, the leakage rates of each of the nine sections (1, 2, 3, 4, 5, 6, 7, 8, 9) in Fig. 7.

[0255] Referring to Fig. 13b, the horizontal axis represents time in the range of 10s to 100s (interval: 10s), and the vertical axis represents leakage rate in the range of 0 to 0.8 (interval: 0.1).

[0256] Each graph shows the results of actual measurements of the leakage rates in each open area of ​​the negative pressure chamber, that is, the leakage rates of each of the nine sections (1, 2, 3, 4, 5, 6, 7, 8, 9) of Fig. 7.

[0257]

[0258] Figure 14 is a simulation domain for the verification and definition of distance and convective velocity, Figure 15 is a diagram comparing the distance between the CFD results and the empirical equation, and Figure 16 is a diagram comparing the convective velocity between the CFD results and the empirical equation.

[0259] The progression of coughing was measured within a 1m × 0.3m × 0.3m negative pressure chamber. The coughing was designed to be initiated by a person as close as possible to a 60cm square opening. Each experiment was performed by four healthy male volunteers, and each volunteer repeated the experiment three times. Cough and saliva droplet velocities were measured using particle imaging velocity measurement.

[0260] The coughing process is visualized as a column of smoke being emitted as in Fig. 14, and the horizontal distance from the end of the column to the coughing start point is defined as distance 's'.

[0261] In addition, convection velocity (U c ) is the time derivative of s, i.e., ' It is defined as '

[0262] The experimental data consists of a time function averaged over 11 cases, and the CFD model of the analysis unit (110) was verified by comparing it with the time function.

[0263] Referring to Figure 15, the distance(s) over time is shown and compared with the CFD model and the empirical equation (Wang, Hongping, et al.), and the average accuracy is 81.27%.

[0264] Referring to Fig. 16, the convection velocity (U) over time c ...and compared the CFD model with the empirical equation (Wang, Hongping, et al.), and the average accuracy is 95.35%.

[0265] As can be seen in Figures 15 and 16, the comparison between the CFD model and the empirical equation (Wang, Hongping, et al.) shows high accuracy in the trend and value of the distance, and the average accuracy achieved 81.27% despite the low accuracy due to the low initial absolute value.

[0266] In addition, the convection velocity also shows high accuracy, achieving an average accuracy of 95.35%, indicating that the CFD model is reliable overall.

[0267] As a result of performing CFD simulations on a negative pressure chamber of the existing structure, it was determined through Figures 17 to 19 that when coughing, the slope of the ceiling creates a high-pressure area, causing droplets to flow out.

[0268] Figure 17 is a graph showing the relationship between time and pressure according to the simulation, where pressure includes outlet pressure and coughing-induced pressure.

[0269] The area where pressure caused by coughing is concentrated is the red-colored area of ​​the ceiling. According to Figure 17, the coughing-induced pressure is shown to significantly exceed the suction force, i.e., the outlet pressure.

[0270] Figure 18a shows the relationship between X[m] and particle number density (m-3) at the beginning of coughing according to simulation, and Figure 18b shows the relationship between particle number density (m-3) and Z[m] at the beginning of coughing according to simulation.

[0271] X[m] is the directional variable parallel to the direction in which the patient is lying. Z[m] is the directional variable perpendicular to the direction in which the patient is lying.

[0272] Aerosols are concentrated towards the center of the ceiling.

[0273] According to Fig. 18a, aerosols are concentrated around the patient's mouth during the initial cough (0.15 seconds).

[0274] According to Fig. 18b, aerosols are concentrated on the ceiling during the initial cough (0.15 seconds).

[0275] Figure 19a shows the relationship between X[m] and particle number density (m-3) during the middle of a cough according to simulation, and Figure 19b shows the relationship between particle number density (m-3) and Z[m] during the middle of a cough according to simulation.

[0276] X[m] is the directional variable parallel to the direction in which the patient is lying. Z[m] is the directional variable perpendicular to the direction in which the patient is lying.

[0277] Figures 19a and 19b differ from Figures 18a and 18b in that they represent the mid-stage of coughing (0.46 seconds).

[0278] When the cough reaches the middle stage, the aerosol flows downward.

[0279] According to Fig. 19a, it shows that the aerosol moves toward the patient's chest during the mid-stage of coughing (0.46 seconds).

[0280] According to Fig. 19b, during the mid-stage of coughing (0.46 seconds), the aerosol moves from the ceiling downwards along with the movement of the flow.

[0281] Figure 20a shows the relationship between X[m] and particle number density (m-3) at the end of a cough according to simulation, and Figure 20b shows the relationship between particle number density (m-3) and Z[m] at the end of a cough according to simulation.

[0282] X[m] is the directional variable parallel to the direction in which the patient is lying. Z[m] is the directional variable perpendicular to the direction in which the patient is lying.

[0283] Figures 20a and 20b differ from Figures 18a, 18b, 19a, and 19b in that they represent the end of the cough (1.8 seconds).

[0284] At the end of the cough, the aerosol flows down and reaches the floor.

[0285] According to Fig. 20a, at the end of the cough, aerosols are distributed in all directions, including the patient's chest as well as the head.

[0286] According to Figure 20b, the aerosol at the end of the cough flows downward but still shows the highest distribution at the ceiling.

[0287] As shown in Figs. 17, 18a, 18b, 19a, 19b, 20a, and 20b, the results of the aerosol flow simulation showed that the droplets remained near the open part of the negative pressure chamber due to the high-pressure region created by the ceiling slope, delaying their movement to the intake port.

[0288] In addition, the high pressure generated by coughing exceeds the suction force.

[0289] Based on these simulation results, a structure of a negative pressure chamber was derived in which the inclined structure of the existing negative pressure chamber was removed, a curvature was created on the ceiling to increase the treatment space, and the high-pressure area was removed, i.e., a structure as shown in Fig. 2a.

[0290]

[0291] When comparing the efficiency of the existing negative pressure chamber (old chamber) and the negative pressure chamber according to the embodiment of the present invention (new chamber) by performing CFD analysis, the results are as shown in FIGS. 21 and FIGS. 22.

[0292] Figure 21 shows a comparison of total leakage through the relationship between time and particle total mass flow (kg / s) according to simulation, and Figure 22 shows a comparison of outler mass flow through the relationship between time and particle total mass flow (kg / s) according to simulation.

[0293] At this time, through Fig. 21, it can be seen that the total droplet leakage in the negative pressure chamber of the present invention has decreased by 36.2% compared to a conventional negative pressure chamber.

[0294] In addition, through Fig. 22, it can be seen that the droplet discharge mass flow in the negative pressure chamber of the present invention increases by 3204.68% compared to a conventional negative pressure chamber.

[0295]

[0296] According to the above simulation, a design for a negative pressure chamber that maintains an aerosol leakage rate of less than 0.3% was derived.

[0297] Analysis was performed using a lower pressure of 10 Pa, and it was predicted that removal efficiency would be improved and leakage reduced through design modifications.

[0298] In addition, real-time droplet measurement was performed and the results were compared with CFD analysis, and it was confirmed that it is possible to perform procedures such as intubation, cardiopulmonary resuscitation, and patient monitoring using an open negative pressure chamber, and that the protective effect is superior to recommended PPE.

[0299] In addition, through CFD analysis, a physical prototype of a negative pressure chamber can be fabricated during design and condition changes.

[0300] CFD analysis indicates that the previously tested new intubation hood—namely, the negative pressure chamber—can provide sufficient protection even without a shield on the patient's chest. It was found that airflow inside the hood is kept to a minimum even when the suction force is sufficiently strong.

[0301] The negative pressure chamber with a curved design reduced total leakage by 36.2% and improved droplet discharge by 3204.68%. Real-time measurements showed a maximum leakage of 0.0536% during breathing and 0.3067% during coughing, with total leakage being less than 0.3%. Therefore, the structure of the negative pressure chamber of the present invention effectively reduces droplet leakage, thereby improving both safety and procedure efficiency.

[0302] In addition, an analysis was performed using a lower pressure of 10 Pa, and it was predicted that removal efficiency would be improved and leakage reduced through design modifications.

[0303] In addition, real-time droplet measurements were performed, and these results were compared with CFD analysis. Significant leakage was observed during the early stages of coughing, but the leakage decreased more rapidly.

[0304]

[0305] Although embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements by those skilled in the art using the basic concept of the present invention as defined in the following claims also fall within the scope of the present invention.

Claims

1. A method for designing a negative pressure chamber of a design device operated by at least one processor, wherein A step of performing CFD (Computational Fluid Dynamics) analysis on a negative pressure chamber, and Based on the above CFD analysis, the step of designing a negative pressure chamber with a shape and structure capable of minimizing gas leakage. A method including 2. In Paragraph 1, The above designing step is, A method for designing a negative pressure chamber of a shape and structure that increases the treatment space and eliminates the high-pressure area that causes internal droplets to flow out.

3. In Paragraph 2, The above designing step is, Method for designing a negative pressure chamber with ceiling curvature.

4. In Paragraph 1, The above designing step is, A method for designing an open-type negative pressure chamber without a shield on the patient's chest.

5. In Paragraph 4, The above designing step is, A method of positioning an intake port below the patient's head, in a location opposite to the open direction in the above-mentioned open structure and close to the direction of droplet discharge during coughing.

6. In Paragraph 1, The above designing step is, Method for designing a negative pressure chamber with a mesh structure having a mesh size of 5 mm.

7. In Paragraph 1, The above-mentioned analysis step is, By simulating airflow and pressure changes inside the negative pressure chamber, it predicts the expected path of gas leakage, and by simulating droplet behavior, it predicts potential external leakage of the negative pressure chamber, The above designing step is, A method for designing a negative pressure chamber of a structure and shape capable of minimizing the above-mentioned external leakage.

8. In Paragraph 7, The above-mentioned analysis step is, A method for using a turbulence model to simulate internal airflow and pressure changes in a negative pressure chamber and deriving an adverse pressure gradient to predict the gas outflow path.

9. In Paragraph 1, After the above design step, A step of verifying the performance of the designed negative pressure chamber by measuring the gas leakage amount through a PAO (Poly Alpha Olefin) particle test on the designed negative pressure chamber. A method that further includes.

10. Memory for storing at least one instruction, and It includes a processor that executes the above instructions, By executing the above instruction, the processor, Analysis unit that performs CFD (Computational Fluid Dynamics) analysis on a negative pressure chamber, A design department that designs a negative pressure chamber of a shape and structure capable of minimizing gas leakage based on the above CFD analysis. A design device including 11. In Paragraph 10, The above analysis unit is, By simulating airflow and pressure changes inside the negative pressure chamber, it predicts the expected path of gas leakage, and by simulating droplet behavior, it predicts potential external leakage of the negative pressure chamber, The above design unit is, A design device for designing a negative pressure chamber of a structure and shape capable of minimizing the above-mentioned external leakage.

12. In Paragraph 11, The above design unit is, A design device for designing a negative pressure chamber that creates a ceiling curvature capable of increasing the procedure space and eliminating a high-pressure area that causes internal droplets to flow out, has an open structure without a shield on the patient's chest side, and has an intake port positioned opposite to the open direction and close to the direction of droplets during coughing, and is positioned below the patient's head.

13. In Paragraph 11, The above processor is, A simulation unit that verifies the performance of the designed negative pressure chamber by measuring the gas leakage amount through a PAO (Poly Alpha Olefin) particle test on the designed negative pressure chamber. A design device that further includes 14. An internal space for endotracheal intubation of the admitted patient is provided, and the device includes a hood that covers the head and neck area of ​​the patient to protect it from the surrounding environment, with the chest area of ​​the patient open. The above hood is, A negative pressure chamber with a ceiling curvature formed to increase the treatment space and eliminate high-pressure areas that allow internal droplets to flow out.

15. In Paragraph 14, The above hood is, A negative pressure chamber having an intake port positioned below the patient's head, in a direction opposite to the opening direction of the hood and close to the direction of droplet discharge during coughing.

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