key: cord-0862583-nlq364ua
authors: Verma, Tikendra Nath; Sahu, Arvind Kumar; Sinha, Shobha Lata
title: Study of Particle Dispersion on One Bed Hospital using Computational Fluid Dynamics
date: 2017-12-31
journal: Materials Today: Proceedings
DOI: 10.1016/j.matpr.2017.06.323
sha: 646b1368cd3353e7f6f7984eaf365ef6340753f2
doc_id: 862583
cord_uid: nlq364ua

Abstract Increasing concerns about the spread of airborne disease in hospital such as severe acute respiratory syndrome (SARS), chickenpox, measles, tuberculosis and novel swine-origin influenza A (H1N1) have attracted public attention. A present study was carried out to look for the source of contamination (patient itself) and examine the route of contaminant transfer in the hospital. This article provides recommendation for future work to improve the yield and save the energy consumption simultaneously. The risk of airborne infection can be minimized in hospital wards by using a high air change rate. The Local mean age of air will decrease with an increasing flow rate because the source must be considered to be constant. The location of the outlet openings plays an important role for the transfer of the contaminant particle in the hospital.

The average person inhales in around 16,000 quarts of air per day. Each quart of air contains some 70,000 visible and invisible particles, which equates to a total intake of over a billion particles per day. The necessity of air cleaning solutions is especially critical in healthcare environments, where higher concentrations of harmful or infectious microorganisms are being emitted into the air. The presence of contaminant particles may cause discomfort to the eyes, irritation of the respiratory system, and may even spread disease.

CFD is the analysis of system involving fluid flow, heat transfer & associate phenomena such as chemical reactions by means of computer based equation. It is very powerful & spans a wide range of industrial & non industrial application area. It has to be proven to be an efficient approach for analyzing indoor airflow, heat transfer and contaminant dispersion process. The prediction of airflow in an ICU, the flow equation must account for turbulence and buoyancy. Conservation equations for mass, momentum & energy can be established for each cell. Two major concerns in ventilation scheme design, operation and malfunction analysis have been identified: (i) indoor air quality (IAQ) and thermal comfort, (ii) energy consumption and efficiency.

Xiaojun et al. [1] have presented that there is no direct relationship to quantify the transient influence of different boundary conditions including contaminant in supply air, contaminant source and initial condition on indoor contaminant distribution. The proposed expression can explicitly and quantitatively reflect the impact of supply air, contaminant source and initial condition on the contaminant distribution indoors. An experimental measurement is employed to validate the reliability of the analytical expression. It is shown that the results from the expression agree well with experimental measurement. Kim et al. [2] have presented a study, carried out to look for the source of contamination and examined the route of contaminant transfer in the mini-environment applied in liquid crystal display (LCD) process clean room of Korea. It was revealed that the critical contamination source was the stocker and the contaminants were transferred by the airflow pattern. The velocity distribution was improved and the particle concentration was reduced in the target minienvironment. King et al. [3] have used aerobiology test room arranged in three different layouts-an empty room, a single-bed and a two-bed hospital room. Comparison with CFD simulations using Lagrangian particle tracking demonstrates that a realistic prediction of spatial deposition is feasible, and that a Reynolds Stress (RSM) turbulence model yields significantly better results than the k-ɛ RNG turbulence model used in most indoor air simulations. Results for all layouts demonstrate that small particle bio aerosols are deposited throughout a room with no clear correlation between relative surface concentration and distance from the source.

Villafruela et al. [4] have analyzed the dispersion of the exhaled contaminants by humans in indoor environments; with special attention to the exhalation jet and its interaction with the indoor airflow pattern in both mixing and displacement ventilation conditions. The objectives of this study are to increase knowledge regarding the exhaled contaminant distribution under different environmental conditions and to validate whether a steady boundary condition of the exhalation flow may simulate human breathing in an effective and accurate way. The results show a very good agreement of the numerical results obtained for test and the experimental data. The fact confirms the use of numerical simulation as a powerful tool to predict the contaminant distribution exhaled by a human. Hang et al. [5] have investigated how the walking motion of health care worker (HCW) influences gaseous dispersion in a six bed isolation room with nine downward supplies and six ceiling-level or floor-level exhausts. The flow near and behind HCW is easily affected by the motion of HCW. The flow disturbance induced by HCW walking with swinging arms and legs is a mixing process. HCW motion indeed affects airborne transmission, but its effect is less important than ventilation design. No matter with or without HCW motion, the ceiling-level exhausts perform much better in controlling airborne transmission than the floor-level exhausts with the same air change rate (12.9 ACH). Smaller air change rate of 6 ACH experiences higher concentration and more gaseous spread than 12.9 ACH. The realistic human walking which is the simplified motion of a rectangular block produces stronger flow disturbance. Finally surface heating of HCW produces a stronger thermal body plume and enhances turbulence near HCW, thus slightly strengthens airborne transmission.

Goncalvesa et al. [6] has studied the aerodynamic sealing of doorways of refrigerated rooms, obtained by vertical and horizontal air curtain devices (ACD). The sealing efficiency is estimated for different situations, with the ACD installed inside, outside or on both sides of the door. The buoyancy induced airflow field when the ACD is turned off and the "opened door" was taken as a reference to assess the sealing efficiency. According to Goncalvesa, downward blowing air curtains present better sealing efficiency (over 70%) compared to horizontal jet air curtains (about 55%). The direct air recirculation provides a better sealing efficiency (over 80%). Bhamjee et al. [7] have investigated that the temperature rise and heat gain are higher in the natural flow case than in the forced flow cases. The models have been experimentally validated in terms of velocity field, flow field and temperature rise. The velocity field was measured using Laser Doppler Velocimetry (LDV) and the overall flow field was captured using smoke for flow visualization.

Nielsen et al. [8] have presented a two-bed hospital ward with one standing healthcare person and a ceilingmounted low impulse semicircular inlet diffuser and have simulated in a full-scale room. Tracer gas is used for simulating gaseous contaminants, and the concentration is measured at different air change rates and different postures of the patients. A textile partition between the beds, which is typical in a hospital ward, is used for protection of the patients in some of the experiments. Three different layouts of return openings are tested for one layout with one opening at the ceiling, another with four openings at the wall opposite to the inlet diffuser, and one with a high location of these four openings. The downward recalculating flow is on average parallel with the partition, and in most cases the partition does not decrease cross-infection. A high location of the four return openings decreases the risk of cross-infection.

The equations describing the room airflow are conservation of mass, conservation of momentum and conservation of energy. The governing equations can be written in the General Transport Equation (Eq. format and given as follows:

Three dimensional General Transport equations for turbulent flow are given below:

The movement of contaminated particles in ventilated areas is influenced by many factors, such as airflow pattern, particle properties, geometry configurations, ventilation rates, supply and exhaust diffuser locations, internal partitions, thermal buoyancy due to the heat generated by occupants and / or equipment, etc. There are two methods to calculate the trajectory of particle (a) Lagrangian method (b) Eulerian method. The equations of individual particle movement come directly from Newton's second law:

Re 24

The following assumptions have been used during computation: (a) All contaminated particles are of spherical solid shape; (b) Heat and mass transfer between air and contaminated particles trajectory are neglected; (c) No particle rebounds on solid surfaces, such as walls, floors and ceilings have been considered; (d) Contaminated particles are assumed to be of uniform diameter.

Total nine cases have to be run. The inlet velocity considered is 1.0 m/sec, air change rate per hour (ACH) of 12 and inlet temperature is 20˙C. Case 1.In this case inlet position is 600 mm in front of west wall & 2300 mm above the floor. Outlet position is 300 mm above the floor & 1700 mm in front of west wall as shown in Fig.1 (a) .Case 2.In this case, inlet position is 1700 mm in front of west wall & 2300 mm above the floor, outlet position is 1400 mm above the floor & 1700 mm in front of west wall as shown in Fig. 1(b) . Case 3.In this case, inlet position is 2800 mm in front of west wall & 2300 mm above the floor, outlet position is 2300 mm above the floor & 1700 mm in front of west wall as shown in Fig. 1(c) . Fig. 2 (a) shows the movement of mass less contaminated particle. The contaminated particle coming from the mouth of patient and moves through tortuous path leaves through the outlet without affecting the doctor and patient. Path of mass less particle is more tortuous Fig. 2 (b) shows the movement of mass less contaminated particle from the mouth of patient. Fig. 2 (c) shows the movement of mass less contaminated particle from the mouth of patient. The contaminated particle coming from the mouth of patient and moves through tortuous path leaves through the outlet without affecting the doctor and patient. The total time taken by the mass less contaminated particle is approximately 2.2 minutes to leave the ICU room. Fig. 3 (a) shows the velocity vector plot on plane x = 1.0 m. The clean cold air is entering through the inlet, moves in region above the occupied zone and directly strikes on opposite wall i.e. north wall. After striking it comes to the lower portion of the room. One clockwise re-circulating zone is formed approximately 4.0 m from the south wall. Fig. 3 (b) shows the velocity vector plot on plane x= 2.0 m.

Most of the clean cold air stream passes through the region above the patient. The major directions of airflow are indicated by arrows. The recirculation zone is formed in the right side of bed touching the floor and the distance travelled by it is approximately at 4 m from south wall or 2 m from west wall. The stagnation zone is formed in the top right corner of the ICU. The airflow is uniform and stable, and has the same flow direction near the patient. Some smaller circulation with a slower velocity exits in the region immediately in the exit side and it can be clearly seen that the recirculation zone is formed in the top left corner. The cold air leaving the ICU through outlet has been observed clearly. Fig. 3 (c) shows the velocity vector plot on plane x = 3.0 m. One small clockwise recirculation zone has been observed in top left corner of the ICU i.e. approximately at a distance 0.5 m from the south wall or 3 m from the west wall. It is clearly seen from the velocity vector that almost all the air is travelling from north wall to south wall and striking the doctor.

The studies have been carried out for inlet velocity 1.0 m/sec in hospital for three cases having different position of inlet & outlet. Table 1 shows the time taken by contaminant to leave the ICU room for different cases of ventilation. It is clear from the table 1, maximum time required by the contaminant to leave the ICU, when inlet position is 600 mm in front of west wall & 2300 mm above the floor. Outlet position is 300 mm above the floor & 1700 mm in front of west wall. Also minimum time required by the contaminant to leave the ICU, when inlet position is 1700 mm in front of west wall & 2300 mm above the floor, outlet position is 300 mm above the floor & 1700 mm in front of west wall. 

An Analytical Expression for Transient Distribution of Passive Contaminant Under Steady Flow Field

Study on Contamination Control in a Minienvironment inside Clean Room for Yield Enhancement based on Particle Concentration Measurement and Airflow CFD Simulation

Bio aerosol Deposition in Single and Two-bed Hospital Rooms: A numerical and Experimental study

CFD Analysis of the Human Exhalation flow using Different Boundary Conditions and Ventilation Strategies

The Influence of Human Walking on the flow and Airborne Transmission in a Six-Bed Isolation Room: Tracer Gas Simulation

CFD Modelling of Aerodynamic Sealing by Vertical and Horizontal Air Curtains, Energy and Buildings

An Experimentally Validated Mathematical and CFD Model of a Supply Air Window: Forced and Natural Flow

Risk of Cross-Infection in a Hospital Ward with Downward Ventilation