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Although Eq (1612) is based on an intermolecular potential function that is in detail unrealistic, it nevertheless often provides an excellent fit of second-virial-coefficientdata An example is provided by argon, for which reliable data for B are available over a wide temperature ~ range, from about 85 to 1000 K The correlation of these data by Eq (1612) as shown in Fig 163 results from the parameter values 1 = 952 K, I = 169, and d = 307 x k cm This empirical success depends at least in part on the availability of three adjustable parameters, and is no more than a limited validation of the square-well potential Use of this potential does illustrate by a very simple calculation how the second virial coefficient (and hence the volume of a gas) may be related to molecular parameters

Define the Sales table as follows: StoreNumber, number, primary key Sales, number Estimate, number SalesRepNumber, number

The following example illustrates the usage of the behavior element:

7 ~H Dymond and E B Smith, The Wrial CoefJicients of Pure Gases and Mixtures, pp 1-10, Clarendon Press, Oxford, 1980

<faces-config> <behavior> <behavior-id> testbehavior </behavior-id> <behavior-class> comexamplejsfTestBehavior </behavior-class> </behavior> </faces-config>

The GROUP BY clause specifies the name of the column whose values are used to group rows in the ResultSet Listing 11-81 illustrates this technique In this example, the StoreNumber column and the sum of the values in the Sales column from the Sales table are returned The GROUP BY clause organizes the ResultSet by the value in the StoreNumber column This means that the ResultSet contains the sum of the Sales column for each StoreNumber Listing 11-82 contains the DownRow() method that is used to retrieve and display values from the ResultSet

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Such calculations carried out for more-realistic potential functions, though of greater complexity, also lead to values for molecular parameters For example, experimental volumetric data for many gases have been regressed to yield values of a and E for the Lennard-Jones potential [Eq (161)] Values from several potential functions are given by R L ~ o w l e ~ ~ This is an essential source of values, because theory does not provide the means for their prediction One must remember, however, that potential functions are empirical models, and as such are approximations The deficiency of a model is reflected by the values of the molecular parameters regressed from the model, and they must therefore be regarded as effective values of the parameters Different effective values result from the use of different potential functions Since transport properties, such as viscosity and diffusivity, are also related to these same potential functions, data for the transport properties, particularly viscosity, are also used to provide values for E and a Note, however, that any deficiency in the potential function influences the calculation of values in different ways, and the same molecular parameters obtained from different data sources are rarely in exact agreement

The following example illustrates equivalent configuration via the @FacesBehavior annotation:

try { String query = new String (" SELECT StoreNumber, SUM(Sales) " + " FROM Sales " + " Group By StoreNumber"); DataRequest = DatabasecreateStatement(); Results = DataRequestexecuteQuery (query); Systemoutprintln("Store Sales"); Systemoutprintln("---------"); DisplayResults (Results); DataRequestclose(); }

@FacesBehavior(value="testbehavior") public class TestBehavior extends BehaviorBase { }

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The behavior-class element specifies the fully qualified class name of a javaxfacescomponent behaviorBehavior implementation class

private void DownRow ( ResultSet DisplayResults ) throws SQLException { long Store; long Sum; Store = DisplayResultsgetLong ( 1 ) ; Sum = DisplayResultsgetLong ( 2 ) ; Systemoutprintln(Store + " " + Sum); }

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