TECHNOLOGY
Portable Analog Characterizes Processes Monsanto simulates processes using computer model with coefficients that are not interdependent A portable analog computer is now being used to determine process characteristics at Monsanto. With the computer, Monsanto engineers can rapidly develop analog models of operating processes. They can then use the models to determine what must be done to improve the process—redesign for instance, or adjustment of control. Many of the sophisticated techniques of process analysis which Monsanto has incorporated into its analog computer had already been available. However, Monsanto has incorporated these techniques into its computer in
such a way that it has held on to the advantages of these techniques and bypassed most of the disadvantages, L. H. Fricke, a senior systems engineer in Monsanto's control engineering department, told the Fall Joint Computer Conference in San Francisco. Pulses. All of today's analyses of operating chemical processes involve disturbing the process and seeing how it reacts. However, operating chemical processes can rarely be tested by the sinusoidal kind of process change used in earlier attempts at process characterization, Mr. Fricke points
PORTABLE. L. H. Fricke feeds the portable analog computer the same input or disturbance as the process under study. He will then adjust the coefficients of the polynomial terms until the computer output matches the process output 40
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out. Delays and time constants between input and output of the process can run two or three days. Complete tests can take months. Upsets to production often result. The newer method of disturbing a process is a pulse. A pulse is very brief, and its nature and shape can be selected so that the pulse or some of its harmonics can produce a response of the process output which yields all of the information that the sinusoidal technique did. This new technique has lately been pioneered by Dr. J. O. Hougen at Monsanto. Pulse inputs and outputs can be recorded. Then these data are changed mathematically to Fourier transforms. Ratio of output to input in this form is called the performance function and is a measure of the frequency response of the system. This frequency response can in turn be represented as a Bode diagram, which depicts linearly the relationship of input to output. Some further mathematics then fit the Bode diagram to a polynomial equation. The equation is, in turn, the model for analog simulation. This procedure—fitting a linear model to a nonlinear system—is usually sufficient to permit devising the correct control system, according to Mr. Fricke. A single model obtained this way doesn't cover a process at all levels of operation. But within the range of normal operating conditions, generally small, it is adequate. With the advantages of minimum time for test and minimum disturbance to operation come some disadvantages. The Fourier transform pairs must be generated by a large digital computer or special purpose device, or time advantage is lost as the engineer spends a major amount of time at this chore. Also, chart readings must be converted to digital data by hand or through an analog to digital converter—a source of error. Furthermore, the Bode plots finally obtained must be fitted to a known linear model for an analog representation.
Orthonormal. This is where Monsanto's computer comes in. The final result of the complex mathematical procedure is a polynomial equation which can be programed on an analog computer to model the process. In turn, the final step in getting this polynomial equation involves fitting the test results to a known linear polynomial equation. The technique adopted by Mr. Fricke and R. A. Walsh, a mathematician in the applied mathematics section of Monsanto's central research department, is to program a small analog computer with a general model or polynomial equation, leaving each of the terms in the polynomial with adjustable coefficients. Then they trundle this computer out into the plant, feed it the same input or disturbance as the process, and adjust the coefficients of the polynomial terms until the computer output fits the process output. This yields the model that can be put through its paces for whatever purposes engineers have in mind. The Monsanto contribution does not lie entirely in devising this procedure, however. In fact, one and possibly more manufacturers in today's burgeoning computer business offer instruments designed to compare process and model as a means of characterizing the process. However, those devices that Mr. Fricke and Mr. Walsh are familiar with contain models or polynomial equations whose coefficients are interdependent. The disadvantage of interdependent coefficients shows up in the way in which the model is adjusted to fit the process. To get a fit, coefficients of each term in the polynomial model are adjusted serially. With interdependent coefficients, Mr. Fricke says, adjustment of a second coefficient is likely to mean that the first one must be readjusted to get best agreement of process and model before proceeding to adjust the third coefficient, and so on. This is time consuming. To overcome this disadvantage, Mr. Fricke and Mr. Walsh have given considerable time to devising their models so that the coefficients are not interdependent. These models are described as orthonormal polynomials. With orthonormal polynomials making up the model, each coefficient can be adjusted to give progressively better fit of model to process without having to readjust prior coefficients. This overcomes the time disadvantage, where coefficients are interdependent,
Du Pont Develops New Photographie Process Photosolubilization leads to positive image rather than negative image as in conventional photography The basic chemical reaction sequence of conventional photography is expose-develop-fix, resulting in a negative image. Photosolubilization, the new image-forming process from Du Pont, has changed this sequence to expose-fix-develop to give a positive image. Du Pont believes that the photosolubilization process not only provides a new route for image formation but that it will aid in the understanding of the chemistry and phenomena of conventional photography. Photosolubilization provides a tool for separating the dissolution process from the reduction step in development. It is also useful in studying the cation effect of metal ions in developers. Improvements in photographic sensitivity, image fidelity, and processing have evolved since 1871, when R. C. Maddox first prepared a practical photographic film based on silver halide dispersed in gelatin. But the basic
chemical reactions have remained the same—selective reduction of silver halide, removal of undeveloped grains through complex formation, and solution- or diffusion-transfer development. With photosolubilization, two basic steps—insolubilization and photosolubilization—are actually involved. Insolubilization is modification of silver halide to decrease its rate of dissolution in photographic solvents. Photosolubilization occurs when a substance which contains the modified silver halide is exposed and then immersed in a solvent solution, forming a direct image in silver halide. Six patents (U.S. 3,155,507 and 3,155,515 through 3,155,519) covering the new process have just been issued to Du Pont. However, details were given for the first time a week earlier in Washington, D.C., at the Symposium on Unconventional Photographic Systems, which was spon-
Photosolubilization Process Gives Positive Copy Light Image to be Copied Photosolubilization Photography
Conventional Photography
Exposure
Thiosulfate
Hydroquinone (Hypo)
Production of Visible Image
Hydroquinone (Hypo)
Thiosulfate Silver Halide Conversion —
Removal (Fixation)
Reduction (Intensification) Positive Copy
Negative Copy Silver
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