8/6/2019 Bufalo Gennaro- A Novel Approach for Recognizing of Workplace Hazards

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In the present case, the gradual thickening of the grid between the source and the area where

there is a fixed sampling allows us to control a greater convergence of the solution until the

desired approximations.

We have then tested, in different points in space, changes in the convergence of the

numerical solution. The process crashed when the accuracy was within 4% for the floor, and

25% for the ceiling.

The solution is characterized by the following parameters:

- Lattice of tetrahedral elements of second order (quadratic Lagrange)

- 284,559 total degrees of freedom

- 39,203 total points in the lattice

- 194,415 tetrahedral elements for the subdomain Sub1

- 5017 tetrahedral elements for the subdomain Sub2

The simulation indicates that the total amount of acetone introduced into the environment

after 8 hours, is equal to 365 g. This value, calculated under the worst conditions, it is still far

below the range of variation of the data derived from actual consumption (672-917 g).

Performing the simulation with the 6-functioning hood, gives a gure of about 282 g of ac-

etone. It must be assumed that most consumed acetone evaporates from other points as, for

example, the paint laid on the article, from the brushes, etc.. This conrms the view taken

about the suction present and, therefore, should be otherwise is in line to collect the majority

of acetone evaporated.

Figure 5 shows the simulation results for the acetone concentration, a function of the time,

on the vertical. The concentration of pollutant reaches, even after eight hours, the maxi-

mum value of 0.34 mg/m3 (does not affect the opening or closing the inlet), a value much

lower than the experimental ones (ranging between 4.5 and 156 mg/m3),. This might in-

dicate a real inadequacy, for positions close to the xed sampling, of the actual ventila -

tion-suction obtained conditions. One should assume the presence of additional sourc-

es not considered in the simulatio n, for example the presence of manufacts just painted.

A simulation where, in eight hours the sources produce a total quantity of acetone of the

same order of magnitude as those experimentally determined, suggests that the concen-

tration at the xed sampler would be lower than those recorded. Indeed, for a simulationwhere 770 grams of acetone were produced, on the vertical position of the xed sam-

pling, only 2 mg/m3 reached. Further, we must consider that the xed sampler gives val-

ues averaged over the whole sampling time. Experimental data should be compared,

therefore, with the average integrated obtained from simulations, which are still low.

Figures 6, 7 and 8 show the trends of concentrations at different times over a vertical line

placed in front of the work-station 2C, at 1.2 and 2.6 to 0.20 m, respectively. These values

have to be compared with data from the mobile sampler of work-station 2C. In the case of 0.2

m from the work table after eight hours, the maximum concentration is about 12,350 mg/m3,

that is to say two orders of magnitude higher than experimental value. However, at 1.2 m from

the table we have a value of 544 mg/m3 (Figure 7), while 2.6 m is 2.2 mg/m3 (Fig. 8), values

comparable with those measured experimentally.

Figure 9 illustrates an environmental perspective, where are some iso-surfaces showing the

distribution of aceton concentrations after 8 hours.

Results and discussion

A rst set of simulations showed that a large portion of the acetone concentration is zero for the

time working considered . It is signicant only in the area the closest to the sources (see Fig. 3

and Fig. 4).

With this information, we was able to delete a part of the environment by limiting the calcula-

tion grid (mesh) with a smaller space (see Fig.1 area enclosed by the dash-dot line containing

the source), dening two zones with different grids. Sub1 indicates the area circumscribed by

the wall of the north (top) and partitions, SUB2 are the remaining areas (see. Fig. 1). These two

regions are considered physical domain on which we impose the boundaries conditions (opened

systems).

The simulations (Fig ures 6, 7 and 8) show that the concentratio n above the hight of 3.5 m (5

m altitude ceiling) remains practically zero.

The convergence of the solution (for the spatial distribution of concentrations) is conditioned

by the size of the grid.

. crr, G. Bf (*), l. ambr (*)

Bf: i sprr pr Prvz srzz lvr (isPesl),

prm f np, v lm 3, 80121 np iy, -m r, rg54@br.

crr: dprm Prvz u.F.Prvz ig lg lvr,

lz, 55022 Bg l, l, -m r, prz.rr@fwb.

ambr: crz pr vpp sm Gr irf (c.s.G.i.)

dp. F tgy-distaaM uvr M, v d s 86100 cmpb,

rrpg r: mbr@m.

) t wrk w rr r frmwrk grm bw isPesl csGi

industrial hygiene is of prime importance, for verifying the degree of exposure of workers

contaminants, the solution of the sampling problem. That is to say to obtain information

out the exposure of workers with the least possible number of samples.the case of workplaces where there are sources of substances (toxic or harmful) detectable

the gas phase, their high diffusivity, and the presence of an unsuitable ventilation may re-

lt in exposure of employees also places a considerable distance from the source ; in these

rcumstances (very common) an adequate sampling plan would be too expensive and the

nclusions could be drawn from the data would always be closely linked to specic environ -

ental conditions at sampling.

he precise knowledge of spatial and temporal distribution of the concentration of contami-

ants is, in all cases of primary importance to correctly dene the degree of workers exposure.

his, at present, it is practically impossible and the concentrations are then usually determined

time averages, by means of probabilistic analysis. The inadequacy of the sampled data

uld be resolved in part through the use of physical and mathematical simulation models

f transport of matter. Unfortunately, the use of these methods is often expensive in terms of

rocessing capacity due to the large spatial dimensions and the complexity of transport pro-

sses.

he purpose of this work is to use a simulation method that knowing the sources of pollu-

on involves the exposure of workers in the workplace. An extreme situation was simulated,

hich can be used as a reference for all real cases. With this approach, using an appropriate

nalysis strategy that also works on the spatial characteristics of this system is possible in sev-

al cases, calculate with a Personal Computer solutions of transport equations without also

ducing the dimensionality of the problem.

major simplication of calculation can be obtained by considering the diffusive transport

one. This is because the objective is the knowledge of a critical situation that can happen in

n environment where there are sources of pollutants and therefore the environment is simi-r to a closed system, ie without any ow of matter. In this case the presence of convection

r contained in the environment has basically only relevant for the times to homogenize the

ncentration.

MateRials and Methods

he case under study is a factory semi-manufactures handmade painting (g. 1 and three-

mensional reconstruction used by the simulation program Fig. 2).

or this work there is a solvent, acetone, considered as a pollutant, which is tapped by six

mall open containers placed on a work table (Fig. 1 and 2). The simulations were performed

ing the nite elements method using COMSOL Multiphysics software application, applied

nder Windows XP 64-bit, while the hardware used is an HP with dual core processors, at 1.6

Hz, with memory RAM (DDR2) 4 GB and 500 GB SATA HD. For the different simulations

ere carried out calculation times ranging from 1 to 9 h, with a total memory usage (RAM-

D) with peaks up to 9 GB (the composition of the lattice, the relative degrees of freedom

hieved and the% of error, are detailed below). Also an experimental study was conducted

ith passive samplers type ring (Aquaria) and a xed location and in a personal location on

e painting ofcers (see tab. 1 and 2).

Time

[ h ]

z [ m]

8h

z [ m]

Time[ h ]

8 h

8 h

z [ m]

Time[ h ]

. .

.

7

6

8

52B2A

2C

3

4

1

SUB2

SUB1

Lato Nord

X

Y

2.3

0m

.. .

. .

. ,

,

.

Time[h ]

0 10 30 50 70 80Y (cm)

Sorgente Cappa Cappa Sorgente

. ,,

.

0 1 0 3 0 5 0 7 0 8 0Y (cm)

Sorgente Cappa Cappa Sorgente

Time[h ]

conclusions

The present work shows how to obtain useful information about the spatial and temporal

distribut ion of the concentrat ion of contaminants in a workplace using an appropriate testing

strategy. In certain cases, the simulation, of a purely diffusive situation, can allow you to use

the concentration of a pollutant without losing the three-dimensional characteristics of the

working environment under consideration. The results of this simulation can be used as refer-

ence to assess a real situation.

Particularly a condition of pure diffusion can give an indication of zones where it should be

low concentrations and, therefore, if one measures, in these areas, a higher concentration gives

a clear indication of inefcient operation of ventilation- evacuation. The same model of pure

diffusion, may indicate those areas for which the effective operation of ventilation-evacuation

should show a corresponding decrease in concentration.

This approach can also be used in a preliminary stage as a support to prepare an adequate sam-

pling surveys or design of prevention interventions (risk assessment).

ReFeRences

1) Weizhen Lu et al., Numerical Analysis of indoor aerosol particle deposition and distribution in

two-zone ventilation system, Building and Envionmental Vol. 31, 1996

2) Weizhen Lu et al., Modelling and measurement of airow and aerosol particle distribution in a

ventilated two zone chamber, Building and Envionmental vol 31, 1996

3) A.W.M. van Schijndel, Modeling and solving building physics problems with FemLab Building

and Environment, vol 38, 2003

4) Z. Zhang, Q. Chen, Comparison of the Eulerian and Lagrangian methods for

predicting particle transport in enclosed spaces, Atmospheric Environment, vol 41, 2007

5) J.D. Posner, C.R. Buchanan, D. Dumn-Rankin, Measurement and prediction of indoor air ow in

a model room, Energy and Buildings, vol 35, 2003

6) Akinori Hashimoto, Akiko Matsuo, Numerical analysis of gas explosion inside two rooms connec-

ted by ducts, Jurnal of Loss Prevention in the Process Industries, vol 20, 2007

A novel approach for recognizing of workplace hazards

8 h

6 h

7 h

9 h

10 h

z [ m]

Tempo[h]

INTERNATIONAL OCCUPATIONAL HYGIENE ASSOCIATION

g2. Three-dimensional reconstruction of working environments (oor plan shown in Fig. 1) used

the simulation program. The gure shows the two lattices (X, Y, Z, units in meters), with diffe-

nt densities, corresponding to Sub1 and SUB2 areas indicated in the plan of g. 1.

g.1 Plans of the workplace (not to scale).

egend

xed position sampler

Positions samplers personal (wearable), 2A, 2B, 2C, location workstations used

containers of acetone (6 sources)

Suction nozzles 4 resting on the bench (No. 6 corresponding to each container of acetone)

Cloak

Door of next door

Door of external environment

Additional local

-- SUB1 limit the area of the rst calculation grid (more dense mesh)

-- SUB2 limit the area of the second calculation grid (mesh less dense)

-- Maximum height, z, ceiling: 5 m

Fig.3 Pollutant concentrations, calculatedusing suction closed (inactive) on a horizontal

(y) passing through the hoods and the board of

the sources (at the bottom of the gure repre-

senting the position of hoods and sources).

Fig.4 Contaminant concentrations, calculatedusing suction open (active) on a horizontal (y)

passing through the hoods and the board of the

sources (at the bottom of the gure representing

the position of hoods and sources).

Fig.6 Pollutant concentrations calculated for a vertical (z) of 0.20 m from the edge of the work table

(at position 2C).

.

.

.

.

.

.

.

-

.

Average concentration aceton (mg/m3)

Covering a pariod of 8 hours Time line Samplers

Fixed sampler Personal sampler

1 2 2B 2C1 20,3 130,5 39,6 60,9

2 9,4 76,6 160,3 70,3

3 8 81,6 421,1 260,1

4 4,7 70,9 140,2 26,15 22,6 152,4 100,5 118,7

6 57,3 187,7 297,5 546,1

7 144,7 257,6 328,1 206,4

8 4,5 211,4 112,0 364,8

9 52,9 86,2 241,9 79,310 35,1 137,8 170,8 158,0

11 70,6 291,3 101,9 343,2

12 28,6 314,3 59,5 n.d.13 84,9 206,7 181,5 120,6

14 n.d. 150,4 n.d. 257,9

15 n.d. 97,9 472,5 102,8

16 n.d. 387,8 259 154,617 116,40 265,2 200,4 139,7

Geometricmean 28.4 160.4 169.4 145.9

Min. 4,5 70,9 39,6 26,1Max. 144,7 387,8 472,5 546,1

n.d.= not determined

Timeline

Dispersed Aceton Aceton concentrationmeasured

days

Total(amount

consumed,measured at

the end ofprocessing

Calcolatedon the

environmentof 1000 m

3

Calcolatedon the

environment2000 m

3

Fixedsampler

Personalsampler

(min-max)

g mg/m3 mg/m3 mg/m3 mg/m3

1 735 735 367,7 n.d. 97,9 - 472,5

2 917 917 458,7 n.d. 154,6 -387,8

3 672 672 336,1 116,4 139,7 -265,2

4 475

n.d.= not determined

Fig.7 Pollutant concentrations calculated for a vertical (z) to 1.2 m from the edge of the work table

(at position 2C).

Fig.8 Pollutant concentrations calculated for a vertical (z) to 2.6 m from the edge of the work table

(at position 2C).

Fig.5 Contaminant concentrations calculated on a vertical (z) passing through the position of the

xed specimen (point 1 in Figure 1).

Fig.9 Prospective relief work environment with simulated evidence, in color, some iso-surfaces of

pollutant concentrations after 8 hours (X, Y, Z units in meters).

Tab. 1

Tab. 2