Professor Emeritus
Professor Emeritus
- D.Sc.: 1973, Technion, Israel Institute of Technology; Professor 1989.
- Chemical process; simulation: design; optimization and synthesis; Modeling and Regression of Data;Applied numerical methods; Computer aided instruction
- Steady state simulation of an inorganic process on a microcomputer; Identifying and removing sources of imprecision in regression of data;Dynamic simulation of an inorganic process; Application of small scale numerical simula-tion packages in process design andoperations; Solution of differential and algebraic systems of equations; Correlationof phase equilibrium; reaction rate; thermodynamic and transport data.
- Problem solving in chemical engineering with numerical methods For the last 20 years we have been involved in a re-search effort to replace the traditional graphical, trial and error etc. design techniques with numerical computation, using inter-active software packages. A dedicated software package: POLYMATH has been developed for engineering design calcu-lations and a new book ( Cutlip, M. B. and Shacham, M., ``Problem Solving in Chemical Engineering with Numerical Methods``, Prentice Hall PTR, Upper Saddle River, NJ, 1999) has been published. The book demonstrates the use of numeri-cal software packages for solving various types of design prob-lems such as material and energy balances, mass heat and mo-mentum transfer, reaction engineering and thermodynamics. Detailed information about the POLYMATH software and the associated book can be found in the author`s personal WWW site. Identifying and removing sources of imprecision in regres-sion and modeling of data Selection of an optimal regression model comprising of linear combination of independent vari-ables and their functions is considered. Optimal model is de-fined as the one that yields minimal variance while keeping the parameter values stable under data perturbations. Two data precision based indicators: TNR which measures the extend of collinearity among the independent variables, and RTN, that measures signal to noise ratio in the product of a dependent and the independent variables have been developed. These indica-tors can be used to determine the number of terms (parameters) to be included in an optimal regression model and to identify the dominant cause limiting the precision of the model. The proposed techniques have been applied to various models used to regress thermophysical property data and regression of heat transfer data using dimentionless groups. In many instances the proposed technique enabled improving the accuracy and stabil-ity of the correlations published in the literature. Solution of differential-algebraic and non-linear algebraic systems of equations A new method for solving mixed systems of differential and algebraic equations has been developed. This method is based on the use of a feedback controller to adjust the value of a variable, so that the residual of the non-linear algebraic equation is kept very close to zero during integration. Any standard integration algorithm can be used to solve the mixed system of equations. This new method has been applied to index one problems (such as batch distillation and batch reactor simulation) as well as to a high index problem (ideal pendulum) and yielded very accurate results. A new ``continu-ing homotopy`` type method for finding all solutions of a sys-tem of non-linear algebraic equations has been developed. The unique feature of this method is that standard, widely available numerical software can be used for its implementation and it does nor require dedicated software.