EXPERIMENTAL TECHNIQUES

12.1 INTRODUCTION

The use of experimental techniques is one method of designing, testing, and commissioning ventilation systems. A variety of complex problems are en­countered in the wide field of industrial ventilation, the most common being the acceptability of airflow and temperature related to a new or rebuilt sys­tem. A complicated problem would be to experimentally investigate the influ­ence of a hot oven on the airflow patterns in a large hall and how it influences the thermal conditions at the workplace. Ventilation engineers require an­swers to many difficult questions not only at the design stage, but at the com­missioning and operating stage as well.

The carrying out of visualization techniques or measurements is one ap­proach to obtain answers to these questions. Computer simulation is another method that is now becoming a more exact science. A third, essential ap­proach is to depend on experience and good engineering judgment. All the above methods may eventually lead to success; however, the effort and cost of the work may differ considerably. This chapter describes the measurement and visualization techniques that can be applied in industrial ventilation problems.

In planning experimental work, the following approach can be used:

1. Set goals: What information is required as an output of the exercise?

2. Select an experimental approach: visualization, full-scale measurements, reduced-scale measurements

3. Select measurement methods

4. Ensure reliable analysis of results

5. Select instruments

6. Install and test the instrumentation

7. Carry out the measurements

8. Treat basic data to achieve the desired information

Careful planning of how the measurements are taken is essential, and is described in detail in the following chapters. First, however, the most effective approach for the specific case, experiment, or simulation has to be decided. Or should they be used side by side? Experience or good guidance is essential in making the correct decision. The following is given as an analysis and support for engineers dealing with problems of this nature.

Experiment or simulationП A decision may be based on the following con­siderations, but the final choice rests with the ventilation engineer:

Design or trouble shooting: During the design stage an on-site experiment with the actual equipment is not usually possible. Numerical prediction may then be simpler. However, for trouble shooting, field measurements are strongly recommended, ideally complemented by simulations techniques.

Available facilities and expertise: Are test facilities, instrumentation, and data acquisition systems available? Are simulation tools, hardware, and specialized staff for numerical simulation available? The final decision depends on answers to these important questions.

Scaling laws: If a full-scale test is not possible, reduced-scale experiments provide a good alternative. However, certain scaling laws must be observed (see Section 12.4). Correct scaling for isothermal flow is normally possible. Scaling of buoyant flows in large rooms may be difficult or impossible, so numerical simulation is the better choice.

Ventilation components of small geometric detail: It is difficult to model the geometry of diffusers that have complex geometry. Therefore, it is more reliable to measure airflow around such devices of the actual size.

Accident simulation: Large-scale accident situations cannot normally be staged for experimental purposes. It is impossible to set a building on fire, just to see how smoke spreads. In this case, numerical simulation is the only sensible approach.

Parameter variation and optimization: If parameter sensitivity is to be investigated, the simulation approach is cheaper and quicker than experiments. Trends are normally well predicted by the use ot computer models.

Time available: It takes considerable time to set up a simulation case. After ensuring that a basic configuration has run successfully, it is easy and quick to carry out additional computer simulations with changed boundary conditions. Experiments, on the other hand, are generally more time-consuming.

Accuracy and reliability: If maximum quantitative accuracy and reliability are desired, full-scale measurements are the best approach. Simulations are recommended when meaningful trends are noted or to have a qualitative picture of the situation.

Cos?.- Whether measurement or a computation technique is cheaper depends on the situation in question. In small and simple problems, it is usually more profitable to use measurement techniques. In large and complex problems, where parametric/sensitivity study is the objective, computation may be a better alternative.

Ideally, experiments and simulations are carried out side by side and their results complement each other.

Approach

подпись: approachApplicability

Visualization (Section 12.2)

Measurements (in general) (Section 12.3)

Scale mode) experiments (Section 12.4)

To determine the characteristics and qualitative nature of a phenomenon/problem, when no quantitative information (numbers) is needed.

Any problem in which the framework to carry out the measurements exists.

In the case where there is no site to carry out full-scale measurements (planning phase), or it would be too expensive or space-demanding to construct a full-scale experiment (large facilities/rooms/buildings).

In case experiments have been selected, the next step is to decide on the method: visualization, full-scale measurements, or scale model experiments. Some features of these are listed in Table 12.1.

In most cases, visualization combined with measurements is the most ef­fective method. Visualization is carried out first to obtain some idea what is happening and to select the source of relevant information. This approach as­sists in planning the measurement stage.

Scale model experiments are chosen for several reasons, the most obvious being that the intended building or space does not exist. For example, during the planning phase, it is possible to obtain measured information by building a scale model and carrying out measurements using the model. Another rea­son for selecting the scale model approach is that it is more practical, more convenient, and simpler to work with a reduced-scale model than with large full-scale objects. Reduced-scale models can also be positioned in the labora­tory, where the conditions are under better control than in the field.

All three experimental approaches are presented in this chapter: visualiza­tion of airflow and contaminant dispersion (Section 12.2), measurement tech­niques including laser-based-techniques (Section 12.3), and scale model experiments (Section 12.4).

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