Execution time

The computer subroutines for calculation of vapor-phase and liquid-phase fugacity (activity) coefficients, reference fugac-ities, and molar enthalpies, as well as vapor-liquid and liquid-liquid equilibrium ratios, are described and listed in this Appendix. These are source routines written in American National Standard FORTRAN (FORTRAN IV), ANSI X3.9-1978, and, as such, should be compatible with most computer systems with FORTRAN IV compilers. Approximate storage requirements and CDC 6400 execution times for these subroutines are given in Appendix J. 

EXECUTION TIME AND STORAGE REQUIREMENTS OF THERMODYNAMIC SUBROUTINES... 

Also included in this table are some average execution times for the thermodynamic subroutines measured for the CDC 6400 of the Computer Center, University of California, Berkeley. 

The program storage requirements will depend somewhat on the computer and FORTRAN compiler involved. The execution times can be corrected approximately to those for other computer systems by use of factors based upon bench-mark programs representative of floating point manipulations. For example, execution times on a CDC 6600 would be less by a factor of roughly 4 than those given in the tcible and on a CDC 7600 less by a factor of roughly 24. 

Execution times for the higher level subroutines FLASH and ELIPS will be highly dependent on the problems involved. The times required per iteration can be estimated from times for lower level subroutines and the descriptions given for FLASH and ELIPS. Computation times for two specific cases calculated with FLASH and one case claculated with ELIPS are included in Table J-1 to show approximate magnitudes required. 

TABLE J-1 Computer Storage and Execution Time Requirements for Thermodynamic Subroutines ... 

SCREEN will run on an IBM-PC compatible personal computer with at least 2S6K of RAM. The program will run with or without a math coprocessor chip. Execution time will be greatly enhanced with a math coprocessor chip present (about a factor of S in computer time) and will also benefit from the use of a hard disk drive. 

Sponsor/Developing Organization LLNL. Developer. Laurence E. Fried LLNL, P.O. Box 808 Livermore, CA 94551, E-mail cheetah llnl.gov. Hardware-. IBM-PC or clone, Windows 3.1, Windows 95, Mac OS 7.x or later, SUN and SGI workstations, 4.3 MB of hard disk. Software ANSI C. Run execution time for typical problem (CPU or real time). Standard run About 30 seconds on a Power Macintosh 6100/80. Cost None from LLNL. Source code is available, with the stipulations that all modifications be preapproved and forwarded to the sponsor for tracking... 

Bennett ([benn86], [benn88b], [bemi87b], [benn90c]) has recently introduced a measure of dynamic complexity he calls logical depth. The logical depth of an object O, denoted by is defined to be the execution time required by a universal... 

The gain in accuracy provided by refining the step h is limited by requirements of economy. Such an approach is equivalent to minimizing the execution time necessary in this connection in obtaining the solution. But if the solution of the original problem u and / both are smooth functions of X, the accuracy of numerical solution can be increased by performing calculations for the same problem (12) on a sequence of grids, , < h ... 

Table II contains a rough comparison of execution times for the generation of one data point 6x10 random conformations of chains of 100 mass-points were placed each at 100 equally spaced radial positions of a pore with Aq=0.8. It is obvious that the increase in performance, i.e., a reduction in execution time to 20%, is an excellent return on the investment required to change five lines of a FORTRAN program. We fear, however, that this is a relatively rare situation.

Fig. 31.14. Performance of three computer algorithms for eigenvalue decomposition as a function of the dimension of the input matrix. The horizontal and vertical scales are scaled logarithmically. Execution time is proportional to a power 2.6 of the dimension.

The CD that accompanies this book contains a well-studied set of data known as the Iris dataset. A brief description of the data is included on the CD. Write a GCS to analyze the Iris data. If you have SOM software available, compare the performance and execution time of the SOM and the GCS on this dataset. 

In the next step, all feasible equipment triples consisting of a vessel, a station and an AGV are taken into consideration. The overall execution times, including necessary waiting times, docking times, transfer times and processing times, are calculated for each equipment triple. 

After sorting the overall execution times, the availability of the equipment triples is checked. The first combination that is available during the required period of time is allocated, the starting times of subsequent basic operations are updated and the next basic operation(s) of the master list are processed. 

Resources are used to model assets or on a more general level to model every unit on which time consuming or quantity producing operations can be performed. Quants are assigned to resources and have executing times and costs on resources. A shift model and also lockup times can be assigned to a resource. 

A constant time dependency on the resource and the product is added to model none quantity dependent execution times, for example re-purchase times. 

Shift models and lockup times Every shift may have a performance factor f that changes an execution time T of a quant to T/f. The shift model may change after a few weeks or months. Therefore after this time the shift model can be simplified to the availability factor that expresses how much percent of the time can be used for production. It is possible to specify if a quant is interruptible by a shift pause or a lockup. This may depend on the product that is produced by the quant. Using the maximum allowed break for a quant is also a technique to model multiple single resources as one multiple resource. 

At the heart of the model are the heat and mass balance equations governing the chlorine gas, brine and amalgam layers within the cell as illustrated by Fig. 20.3. At a more detailed level each cell is divided into eight zones. Conditions within each zone are assumed to be constant and there is a trade-off between model accuracy and execution time associated with the number of zones. Typically eight zones have been found to be a good compromise. 

After the model is built, the program can be generated and compiled. At execution time, the user has considerable flexibility and we chose to predict the bubble point pressure for a fixed temperature and specified total svstem composition in order to compare some of our results with the data of Otsuku (14). Figure 3 presents the results for a system composed of 10.14 wt% CO2 and NH3 at a temperature of 80° where the %C02 in the CO2 and NH3 was varied. 

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