Abstracts and Publications of Current Research

 

 

Analyzing Similarity of Chemical Compounds and Prediction of Pure Component Properties Using Molecular Descriptors

An Applicability Domain Oriented framework for selection of groups of similar compounds (similarity groups) and for prediction of properties is being developed. The various methods included in this framework are based on the use of a large database of compounds, which includes the molecular descriptors and the available (if any) measured properties for every compound. The database can be considered as row vectors of descriptors and properties for every compound, or as column vectors of the same descriptor (or property) for the various compounds. The analysis and property prediction for a new target compound starts by identifying its similarity group using the vectors of descriptors of the target and the predictive compounds. The similarity is measured by the partial correlation coefficient, between the vector of the molecular descriptors of the target compound, and that of a potential predictive compound.

If there are high levels of similarity (as measured by the partial correlation coefficients) between the target and other compounds in the database for which measured property values are available, the use of the "rigorous" QS2PR method (see references 1, and 3-5) is most appropriate for property prediction. Using this method a stepwise regression algorithm is employed to identify the structure-structure correlation, which represents the vector of descriptors of a target compound as linear combination of the vectors descriptors of predictive compounds. By replacing the molecular descriptors in the structure-structure correlation with pure component properties, the structure-structure correlation becomes a property-property correlation.

It has been demonstrated that the latter can predict most properties of the target compound, needed for design. In cases where the similarity group contains several members of the homologous series of the target compound (for which measured values of the desired properties are available) the short cut QS2PR method (reference 2) can be used. Prediction of the properties using this technique requires minimal amount of information and no specific, dedicated software is needed for carrying out the calculations. The resultant linear property-property relationship can be used for prediction of many different properties.

 

  1. N. Brauner and M. Shacham, "Property prediction subject to insufficient reliable data for the training set". Paper P5.74, presented at the 22nd International Congress of Chemical and Process Engineering, CHISA 2016, 27 – 31 August 2016, Prague, Czech Republic

  2. M. Shacham, G.St. Cholakov, N. Brauner, R. P. Stateva, Estimation of the uncertainty of predicted thermophysical property data, paper O – 18, Presented  at EQUIFASE 2015, Alicante (SPAIN), 28 June - 1 July, 2015
  3. N. Brauner and M. Shacham, Combining Constant Property Prediction Techniques for Wider Applicability and Improved Accuracy, in Proceedings of the 12th Joint European Thermodynamics Conference, JETC 2013, Eds. M. Pilotelli and G.P. Beretta (ISBN 978-88-89252-22-2, Snoopy, Brescia, Italy, 2013), pp.370-376.
  4. N. Brauner, M. Shacham, "Prediction of Normal Melting Point of Pure Substances by a Reference Series Method", AIChE J. 59(1), 3730–3740 (2013).
  5. M. Shacham, M. Elly, I. Paster, N. Brauner, "Evaluation and refinement of the property prediction stage of the targeted QSPR method for 15 constant properties and 80 groups of compounds", Chemical Engineering Science,  97, 186–197, 2013.
  6. M. Shacham, I. Paster and N. Brauner, " Property Prediction and Consistency Analysis by a Reference Series Method",AIChE J., 59(2), 420–428 (2013)
  7. M. Shacham, M. Elly,  I. Paster, and N. Brauner, " Self-Consistency Analysis of Physical Property and Molecular Descriptor Databases Using a Variety of Prediction Techniques", paper 181b, Presented at the 2012 AIChE Annual Meeting, Pittsburgh, PA, Oct. 28 – Nov. 2, 2012
  8. I. Paster, M. Shacham, and N. Brauner, "Predicting a Wide Variety of Constant Pure Compound Properties for Long Chain Substances Using a “Reference Series” Method", pp. 602-606 in I. D. L. Bogle and M. Fairweather (Editors), Proceedings of the 22nd European Symposium on Computer Aided Process Engineering, 17 - 20 June 2012, London, © 2012 Elsevier B.V.
  9. I. Paster, N. Brauner and M. Shacham, "A "Reference Series" Method for Prediction of Properties of Long-Chain Substances", paper 720h, Presented at the 11AIChE Annual Meeting, Minneapolis, MN, Oct. 16-21, 2011
  10. I. Paster, M. Shacham and N. Brauner, " Adjustable QSPRs for Prediction of Properties of Long-chain Substances", AIChE J, 57(2), 423–433 (2011)
  11. M. Shacham and N. Brauner, " Analysis and Refinement of the Training set in Predicting a Variety of Constant Pure Compound Properties by the Targeted QSPR Method" , Chem. Eng. Sci., 66, 2606–2615 (2011)
  12. I. Paster, N. Brauner and M. Shacham, " High Precision Prediction of Vapor Pressure with a TRC QSPR Method", The Open Thermodynamics Journal, 2011, 5, (Suppl 1-M3) 29-39
  13. M. Shacham and N. Brauner, " Predicting a Variety of Constant Pure Compound Properties by the Targeted QSPR Method", pp. 1623 -1627 in E.N. Pistikopoulos, M.C. Georgiadis and A.C. Kokossis (Eds), 21st European Symposium on Computer Aided Process Engineering – ESCAPE 21, May 29 – June 1, 2011, Chalkidiki, Greece
  14. M. Shacham, I. Paster, R. L. Rowley, G. Tovarovski and N. Brauner, "Evaluation of a Targeted-QSPR Based Pure Compound Property Prediction System", paper 191a, Presented at the 10AIChE Annual Meeting, Salt Lake City, UT, Nov. 7-12, 2010
  15. N. Brauner, I. Paster and M. Shacham, "Linear QSPRs for the Prediction of Acentric Factor and Critical Volume of Long-Chain Substances", paper 672e, Presented at the 10AIChE Annual Meeting, Salt Lake City, UT, Nov. 7-12, 2010
  16. M. Shacham, G. St. Cholakov, R. P. Stateva and N. Brauner, "Quantitative Structure−Property Relationships for Prediction of Phase Equilibrium Related Properties", Ind. Eng. Chem. Res. 49, 900-912 (2010)
  17. I. Paster, G. Tovarovski, M. Shacham and N. Brauner, " Combining Statistical and Physical Considerations in Deriving Targeted QSPRs Using Very Large Molecular Descriptor Databases", pp. 61 - 66 in S. Pierucci and G. Buzzi Ferraris (Eds),20th European Symposium on Computer Aided Process Engineering – ESCAPE 20, June 6- 9, 2010, Ischia, Naples, Italy
  18. N. Brauner and M. Shacham, " Prediction of Saturated Vapor Pressure with Simple Structure Property- Property Relationships", Paper 180ab, Presented at the 09AIChE Annual Meeting, Nashville, TN, Nov. 8-13, 2009
  19. N. Brauner, M. Shacham, R. P. Stateva and G. St. Cholakov, " Prediction of Phase Equilibrium Related Properties by Correlations Based on Similarity of Molecular Structures", pp. 69 - 74 in J. Jezowski and J. Thullie (Eds),19th European Symposium on Computer Aided Process Engineering – ESCAPE 19, June 13 - 17, 2009, Krakow, Poland
  20. 18.  I. Paster, M. Shacham and N. Brauner, " Investigation of the Relationships between Molecular Structure, Molecular Descriptors and Physical Properties", Ind. Eng. Chem. Res. 48, 9723–9734(2009)
  21. I. Paster, N. Brauner and M. Shacham, " Selection of Molecular Descriptor Subsets for Property Prediction", Paper 124g, Presented at the AIChE100 Annual Meeting, Philadelphia, PA, Nov. 16-21, 2008
  22. G. St. Cholakov, R. P. Stateva, Brauner, N. and Shacham M., " Estimation of Properties of Homologous Series with  Targeted Quantitative Structure – Property Relationships (TQSPRs)", Journal of Chemical and Engineering Data, 53, 2510–2520 (2008)
  23. I. Paster,M. Shacham and N. Brauner,Prediction of the Melting Point Temperature Using a Linear QSPR for Homologous Series, pp. 895 - 900 in B. Braunschweig and X. Joulia (Eds),18th European Symposium on Computer Aided Process Engineering – ESCAPE 18, June 1 - 4, 2008, Lyon, France
  24. N. Brauner, G. St. Cholakov, R. P. Stateva and  M. Shacham, "Prediction of Thermophysical Properties By Methods Based On Similarity Of Molecular Structures", in G. de Vahl Davis and E. Leonardi (Eds), Proceedings of CHT-08 ICHMT International Symposium on Advances in Computational Heat Transfer, May 11-16, 2008, Marrakech, Morocco
  25. Shacham, M., Brauner, N., Shore. H and Benson-Karhi, D., "Predicting Temperature-Dependent Properties by Correlations Based on Similarity of Molecular Structures – Application to Liquid Density", Ind. Eng. Chem. Res. 47, 4496-4504 (2008)
  26. Brauner, N., Cholakov, G. St., Kahrs, O., Stateva, R.P. and Shacham, M, "Linear QSPRs for Predicting Pure Compound Properties in Homologous Series", AIChE J, 54(4), 978-990 (2008).
  27. Kahrs, O., N. Brauner, G. St. Cholakov, R. P. Stateva, W. Marquardt and M. Shacham, " Analysis and Refinement of the Targeted QSPR Method", Computers chem. Engng., Vol 32, No.7 pp 1397-1410 (2008)
  28. Shacham, M, O. Kahrs, G.St. Cholakov, R. P. Stateva, W. Marquardt and N. Brauner, " The Role of the Dominant Descriptor in Targeted Quantitative Structure Property Relationships", Chem. Eng. Sci. 62 (22), 6222-6233 (2007)
  29. G. St. Cholakov, R. P. Stateva, Shacham M. and N. Brauner, " Prediction of Properties in Homologous Series with a Shortcut QS2PR Method", AIChE J ,  53(1), 150-159 (2007)
  30. N. Brauner, R. P. Stateva, G.St. Cholakov and M. Shacham, " Structurally “Targeted” Quantitative Structure-Property Relationship Method for Property Prediction", Ind. Eng. Chem. Res., 45, 8430-8437 (2006 )
  31. N. Brauner, R. P. Stateva, G. St. Cholakov and M. Shacham, "A "Targeted" QSPR for Prediction of Properties", pp. 149-154 in W. Marquardt, C. Pantelides (Editors), Proceedings of the 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering, Elsevier, 2006.
  32. Shacham, M. , Brauner, N., Cholakov, G. St. and Stateva R. P., ”Using Similarity between Molecular Structures for Property Prediction ", pp. 352-355 in Proceedings of the EMCC -4 conference, 9-11 January, 2006, Dead Sea, Israel
  33. Brauner, N., Shacham, M., Cholakov, G.St. and Stateva, R.P., “Property Prediction by Similarity of Molecular Structures – Practical Application and Consistency Analysis”, Chem. Eng. Sci. 60, 5458 – 5471 (2005)
  34. G. St. Cholakov, R. P. Stateva, Shacham M. and N. Brauner, " Identifying Equations that Represent Properties in Homologous Series using Structure-Structure Relations", pp. 277-282 in L. Puigjaner and A. Espuna (Eds), Proceedings of the European Symposium on Computer Aided Process Engineering – 15, Elsevier, Amsterdam, 2005
  35. G. St. Cholakov, R. P. Stateva, M. Shacham and N. Brauner," Consistency analysis of pure component property data based on structure-structure correlations", Presented at the 7th World Congress of Chemical Engineering, Glasgow, Scotland, 10- 14 July, 2005.
  36. Shacham, M. , Brauner, N., Cholakov, G. St. and Stateva R. P., ” Property Prediction by Correlations Based on Similarity of Molecular Structures", AIChE J. 50(10), 2481-2492(2004)
  37. Shacham M., N. Brauner, G. St. Cholakov and R. P. Stateva, " A Unified Correlation For Prediction of Pure Component Properties Based on Similarity of Molecular Descriptors of Various Compounds", pp. 391-394 in C.A. Floudas and R. Agrawal (Eds.), proceedings of the 6th International Conference on Foundations of Computer Aided Process Design,  Princeton, New Jersey, July 11-16, 2004.

 

 

Considering precision of experimental data in construction of optimal regression models.

In this research project the construction of optimal (stable and of the highest possible accuracy) regression models comprising of linear combination of independent variables and their non-linear functions is being considered. It has been shown that estimates of the experimental error, which are most often available for engineers and experimental scientists, are useful in identifying the set of variables to be included in an optimal regression model. Two diagnostic indicators, which are based on experimental error estimates, have been incorporated in an orthogonalized-variable-based stepwise regression (SROV) procedure. This procedure has been utilized to determine the number of terms (parameters) to be included in optimal regression models, to identify the most influential terms and to detect the dominant cause limiting the precision of the model. Various correlations and regression models, published in the literature, have been examined using the SROV procedure and in most cases the accuracy and stability of the models could be considerably improved using this new technique. The SROV algorithm was implemented as a collection of MATLAB m-files.

 

  1. Shacham, M., N. Brauner and H. Shore, " A New Procedure to Identify Linear and Quadratic Regression Models Based on Signal-to-Noise-Ratio Indicators", Mathematical and Computer Modeling  46, 235-250 (2007)
  1. Morad, S., Shacham, M. and Brenner, A., Utilization of Collinearity in Regression Modeling of Activated Sludge Processes", Chemical Engineering and Processing 46, 222-229 (2007)
  1. D. Benson-Karhi, H. Shore and M. Shacham, "Applying Response Modeling Methodology to Model Temperature-Dependency of Vapor Pressure", Lecture Series on Computer and Computational Sciences, 4, 835-838, 2005, Brill Academic Publishers, The Netherlands
  1. M. Shacham, N. Brauner, G. St. Cholakov, R. P. Stateva, "Combining Stepwise Regression with Outlier Detection for Identification of Collinear Groups", Presented at the 7th World Congress of Chemical Engineering, Glasgow, Scotland, 10 - 14 July, 2005.

 

  1. Shacham, M. and N. Brauner, " High Precision Correlations of Thermo-physical Properties", pp. 1129 – 1134 in A. Barbosa-Povoa and H. Matos (Eds.), Proceedings of the European Symposium on Computer Aided Process Engineering-14, Elsevier, 2004
  1. Shacham, M., H. Shore and N. Brauner, "A General Procedure for Linear and Quadratic Model Identification", pp. 674-676 in T. Simos and G. Maroulis (Eds.), Lecture Series on Computer and Computational Sciences, VSP International Science Publishers, 2004.
  1. Shacham, M. and N. Brauner, "The SROV Program for Data Analysis and Regression Model Identification", Computers chem. Engng. 27(5), 701-714(2003)
  1. Brauner, N. and M. Shacham, " A Procedure for Constructing Optimal Regression Models in Conjunction with a Web-based Stepwise Regression Library", pp. 587 – 592 in A. Kraslawski and I. Turunen (Eds.), Proceedings of the European Symposium on Computer Aided Process Engineering-13, Elsevier, 2003
  1. Shore, H., N. Brauner and M. Shacham, “Modeling Physical and Thermodynamic Properties via Inverse Normalizing Transformation”, Ind. Eng. Chem. Res. 41(3), 651-656 (2002)
  1. Brauner, N. and M. Shacham., “Considering Precision of Data in Reduction of Dimensionality and PCA”, Computers chem. Engng., 24(12),  2603-2611 (2000).
  1. Brauner, N. and Shacham, M., “Considering Error Propagation in Stepwise Polynomial Regression”, Ind. Eng. Chem. Res., 38(11), 4477-4485(1999)
  1. Shacham, M. and N. Brauner, “Considering  Precision of Experimental Data in Construction of Optimal Regression Models”, Chemical Engineering and Processing, 38, 477-486(1999)
  1. Brauner, N. and M. Shacham., “ Regression Diagnostic Using an Orthogonalized Variable Based Stepwise Regression Procedure”, Computers chem. Engng., 23(suppl.), S327-S331 (1999)
  1. Shacham, M. and N. Brauner, “ A General Framework for Considering Data Precision in Construction of Optimal Regression Models”, proceedings of the 5th International Conference on Foundations of  Computer Aided Process Design, Breckenridge, Colorado, July 18-23, 1999
  1. Shacham, M. and N. Brauner, “Identifying and Removing Sources of Imprecision in Polynomial Regression”, Journal of Mathematics and Computers in Simulation, 48(1), 77-93  (1998)
  1. Brauner, N. and M. Shacham, “Role of Range and Precision of the Independent Variable in Regression of Data”, AIChE Journal, 44(3), 603-611(1998)
  1. Shacham, M. and N. Brauner, “Minimizing the Effects of Collinearity in Polynomial Regression", Ind.  Eng. Chem. Res., 36(10), 4405-4412(1997)
  1. Brauner, N. and  M. Shacham, “Reducing the Effects of Collinearity in  Regression of Heat Transfer Data”, Proceedings of the 11th International  Heat Transfer Conference, Kyongju, Korea, 23-28 August 1998

  

 

Problem solving in chemical engineering with numerical methods.

For the last 20 years we have been involved in a research effort to replace the traditional graphical, trial and error etc. design techniques with numerical computation, using interactive software packages. A dedicated software package: POLYMATH has been developed for engineering design calculations and a new book (Cutlip, M. B. and Shacham, M., "Problem Solving in Chemical and Biochemical Engineering with POLYMATH, Excel and MATLAB", 2nd Ed. Prentice Hall PTR, Upper Saddle River, NJ, 2008) has been published. The book demonstrates the use of numerical software packages for solving various types of design problems such as material and energy balances, mass heat and momentum transfer, reaction engineering and thermodynamics. Excel, MATLAB and POLYMATH solutions for the first three chapters of the book are available An ASEE workshop on the subject of "Application of Mathematical Software Packages in Chemical Engineering Education and Practice" has been conducted during the 2002 Summer School For Chemical Engineering Faculty, Boulder, CO, July 27 - Aug. 1, 2002 .

 

 

  1. M. Shacham and N. Brauner, “Comparison of Various Techniques for Solving Complex Chemical Equilibrium Problems”, paper 186n, presented at the 2017 AIChE Annual Meeting, Minneapolis, MN, October, 29 - November 3, 2017

  2. M. Shacham and N. Brauner, “A Systematic Procedure for Analysis and Modification of Chemical Equilibrium Related Equation Sets to Enable  Convergence to Physically Meaningful Solutions”, Presented at the EMCC - 8 conference, February 26 - March 1, 2017, Haifa, Israel

  3. M. Shacham, M. B. Cutlip and M. Elly, "Don't Take the Difficult Path in Solving Systems of Nonlinear Equations", paper 294f, presented at the 2016 AIChE Annual Meeting, San-Francisco, Nov. 13-18, 2016.

  4. N. Brauner and  M. Shacham, "A Systematic Procedure for Analysis and Modification of Nonlinear Equation Sets to Enhance Convergence and Reduce Computational Effort", Paper 245r, Presented at the 2016 AIChE Annual Meeting, San-Francisco, Nov. 13-18, 2016

  5. M. Shacham and N. Brauner, " A hundred years of chemical equilibrium calculations – The case of ammonia synthesis, Education for Chemical Engineers, 13, 17–23 ( 2015)
  6. Shacham, M.  and N. Brauner, "Identification and Estimation of the Influential Parameters in Bioreaction Systems",  paper 317a, Presented at the 2014 AIChE Annual Meeting, Atlanta, GA, Nov. 16-21, 2014.
  7. M. Shacham and N. Brauner," Application of Stepwise Regression for Dynamic Parameter Estimation", Computers chem. Engng.,  69, 26-38 (2014)
  8. N. Brauner and M. Shacham, Problem Diagnostics and Model Refinement in Dynamic Parameter Estimation, pp. 343 - 348 in J. J. Klemeš, P. S. Varbanov and P. Y. Liew (Editors), Proceedings of the 24th European Symposium on Computer Aided Process Engineering – ESCAPE 24, June 15-18, 2014, Budapest, Hungary.
  9. M. Shacham, M. B. Cutlip  and M. Elly, The Role of Mobile Devices in Computer Aided Process Engineering, pp. 349 - 354 in J. J. Klemeš, P. S. Varbanov and P. Y. Liew (Editors), Proceedings of the 24th European Symposium on Computer Aided Process Engineering – ESCAPE 24, June 15-18, 2014, Budapest, Hungary.
  10. M. Elly, M. Shacham and M. B. Cutlip, "The Role of Smartphones and  Tablets in Numerical Problem Solving", paper 668b, Presented at the 2013 AIChE Annual Meeting, San-Francisco, Nov. 3-8, 2013.
  11. Shacham, M.  and N. Brauner, " The Role of the Confidence Intervals in Parameter Estimation and Model Refinement for Dynamical Systems",  paper 200d, Presented at the 2013 AIChE Annual Meeting, San-Francisco, Nov. 3-8, 2013.
  12. M. Shacham, M. Elly and J. C. Merchuk, " Co-current Parameter Estimation and Model Refinement in Dynamical Systems ", paper 202e, Presented at the 2012 AIChE Annual Meeting, Pittsburgh, PA, Oct. 28 – Nov. 2, 2012
  13. Shacham, M., Cutlip, M. B. and Elly, M., "Semi-Batch Steam Distillation of a Binary Organic Mixture – a Demonstration of Advanced Problem Solving Techniques and Tools", Chemical Engineering Education,  46(3), 173-181(2012)
  14. Shacham, M., Cutlip, M. B. and N. Brauner, "From Numerical Problem Solving to Model Based Experimentation – Incorporationg Computer Based Tools of Various Scales into the ChE Curriculum", Chemical Engineering Education, Vol. 43. No. 4, 299- 305 (2009)
  15. Shacham, M., Cutlip, M. B. and Elly, M., " Beware of Errors in Numerical Problem-Solving", Chemical Engineering Progress, Vol. 105, No. 11, 21-25 (2009)
  16. M. Shacham, M. B. Cutlip and M. Elly, Detecting and Preventing Common Errors during Numerical Problem Solving, Paper 225c, Presented at the AIChE100 Annual Meeting, Philadelphia, PA, Nov. 16-21, 2008
  17. M. Shacham, M. B. Cutlip and N. Brauner,"What is "In" and What is "Out" in Engineering Problem Solving", pp. 1187 - 1192 in B. Braunschweig and X. Joulia (Eds),18th European Symposium on Computer Aided Process Engineering – ESCAPE 18, June 1 - 4, 2008, Lyon, France
  18. M. Shacham, N. Brauner and M. B. Cutlip, "From Numerical Problem Solving to Model Based Experimentation – Incorporating Computer Based Tools of Multiscale Modeling into the ChE Curriculum", pp. 32 - 35 in F. Scura, M. Liberti, G. Barbieri, and E. Drioli (Eds), 5th Chemical Engineering Conference for Collaborative Research In Eastern Mediterranean Countries (EMCC5), May 24-29, 2008, Cetraro (CS) – Italy
  19. Shacham, M., N. Brauner, W. R. Ashurst and M. B. Cutlip, "Can I Trust this Software Package? – An Exercise in Validation of Computational Results ", Chemical Engineering Education, 42(1), 53-59 (2008)
  20. M. B. Cutlip, M. Shacham and M. A. Elly, "Enhancing Problem Solving with Excel and MATLAB with Polymath 6.1", Invited Paper 206g,  Presented at the AIChE 2006 Annual Meeting, San-Francisco, Nov. 12-17, 2006
  21. M. B. Cutlip, M. Shacham and M. A. Elly, "Combining Numerical Problem Solving with Access to Physical Property Data – a New Paradigm in ChE Education", pp. 197-200 in Proceedings of the EMCC -4 conference, 9-11 January, 2006, Dead Sea, Israel
  22. Brenner, A., M. Shacham and M. B. Cutlip, “Applications of Mathematical Software Packages for Modeling and Simulations in Environmental Engineering Education”, Environment Modeling and Software, 20, 1307-1313(2005)
  23. Shacham, M., "An Introductory Course of Modeling and Computation for Chemical Engineers", Comput. Appl. Eng. Educ. 13, 137 – 145 (2005)
  24. M. B. Cutlip, M. Shacham and M. A. Elly, "Combining Numerical Problem Solving with Access to Physical Property Data – a New Paradigm in ChE Education", Presented at the 2005 ASEE Annual Conference and Exposition, Portland, Oregon, June 12-15, 2005
  25. M. Shacham, M. B. Cutlip, and M. A. Elly, "Closing the Gap between Numerical Software Package and Spreadsheet Users in Process Computations", Presented at the 2005 ASEE Annual Conference and Exposition, Portland, Oregon, June 12-15, 2005
  26. M. B. Cutlip, M. Shacham and M. A. Elly, "Efficient Solution of Numerical Problems within Polymath and Excel", Presented at the 7th World Congress of Chemical Engineering, Glasgow, Scotland, 10- 14 July, 2005.
  27. Shacham, M. and M. B. Cutlip, "Combining Engineering Problem Solving with Numerical Methods to Enhance Learning Effectiveness", pp. 959-968 in the proceedings of the  iCEER 2004 conference;  International Conference on Engineering Education and Research, Olomouc and Bouzov Castle, Czech Republic, June 27-30, 2004.
  28. Shacham, M., Book review, Scientific Computing with MATLAB, by A. Qarteroni and F. Saleri (Springler, Berlin, 2003), Computer Physics Communications, 161(3), 183-185(2004)
  29. Shacham, M., "Combining Engineering Problem Solving with Programming in One Course to Enhance Learning Effectiveness", presented at the Escape-14 conference, Lisbon, Portugal, 16-19 May 2004.
  30. Shacham, M. and M. B. Cutlip, " Enhancing Computer-Based Problem Solving Skills by Combination of Software Packages", presented in the 2004 ASEE Annual Conference, Salt Lake City, Utah, June 20-23, 2004.
  31. Shacham, M., "Numerical Problem Solving in Chemical Engineering", invited plenary lecture, Altinci Ulusal Kimya Muhendisligi Kongresi (UKMK-6), Izmir, Turkey, 7-10 Sept. 2004.
  32. Shacham, M and M. B. Cutlip, "Reactor Design within Excel Enabled by Rigorous Physical Properties and Advanced Numerical Computation Package", presented at Aspen Word 2004, Orlando, Florida, Oct. 10-15, 2004.
  33. Cutlip, M. B. and M. Shacham, “Numerical Problem Solving with Access to Accurate Physical Property Data – a New Paradigm in ChE Education”, invited paper at the AIChE 2004 Annual Meeting, Austin, TX, 7-12 November 2004
  34. Cutlip, M. B. and M. Shacham, “POLYMATH – A Numerical Analysis Package that now Supports Execution in Excel®”, presented at the AIChE 2004 Annual Meeting, Austin, TX, 7-12 November 2004
  35. Shacham, M. , Brauner, N. and M. B. Cutlip, "An Exercise for Practicing Programming in the ChE Curriculum--Calculation of Thermodynamic Properties Using the Redlich-Kwong Equation of State.", Chem. Eng. Educ., 27(2), 148 (2003)
  36. Shacham, M. , Brauner, N. and M. B. Cutlip, "Efficiently Solve Complex Calculations", Chemical Engineering Progress, 99(10), 100-105 (2003)
  37. Shacham, M. and N. Brauner, "Letter to the Editor", Chem. Eng. Educ., 36(4), 263, 277(2002)
  38. Cutlip, M. B. and Shacham, M., "Problem Solving in Chemical Engineering with Numerical Methods". Prentice Hall PTR, Upper Saddle River, NJ, 1999)
  39. Shacham, M. and M.B. Cutlip, “A Comparison of Six Numerical Software Packages for Educational Use in the Chemical Engineering Curriculum”, Computers in Education Journal, IX(3), 9-15 (1999)
  40. Shacham, M. and M. B. Cutlip, “Selecting the Appropriate Numerical Software for a Chemical Engineering Course”, Computers chem. Engng., 23(suppl.), S645-S649(1999)
  41. Cutlip, M., Hwalek, J.J., Nuttall, H.E., Shacham, M., Brule, J., Widman, J., Han, T., Finlayson, B., Rosen, E. M. and Taylor, R., “A Collection of Ten Numerical Problems in Chemical Engineering Solved by Various Mathematical Software Packages.” Comput. Appl. Eng. Educ., 6(3), 169-180(1998)
  42. Brauner N. and M. Shacham, “Considering Numerical Error Propagation in Modeling and Regression of Data”, Proceedings of the 1998 ASEE Annual Conference, Seattle, Washington, June 27 - July 1, 1998.
  43. Shacham, M. and M.B. Cutlip, “A Comparison of Six Numerical Software Packages for Educational Use in the Chemical Engineering Curriculum”, Proceedings of the 1998 ASEE Annual  Conference, Seattle, Washington, June 27 - July 1, 1998
  44. Shacham, M. and  N.  Brauner,  "What To Do if Relative Volatilities Cannot Be Assumed To Be Constant ?- Differential-Algebraic Equation Systems in Undergraduate Education", Chem. Eng. Educ., 31(2), 86-93(1997)
  45. Shacham, M., N. Brauner and M. B. Cutlip, "Replacing the Graph Paper by Interactive Software in Modeling and Analysis of Experimental Data", Comput. Appl. Eng. Educ.,4(3), 241-251(1996)
  46. Brauner, N. and M. Shacham, "The Wind-Chill Paradox: Four Problems in Heat Transfer", Chem. Eng. Educ., 30(4), 256-261(1996)
  47. N. Brauner, M. Shacham and M. B. Cutlip, ``Computational Results: How Reliable Are They? A Systematic Approach to Modal Validation'', Chem. Eng. Educ., 30 (1), 20-25 (1996).
  48. Shacham, M., M. B. Cutlip, and N. Brauner, "General Purpose Software for Equation Solving and Modeling of Data", pp. 73-84 in Carnahan, B. (Ed), “Computers in Chemical Engineering Education”, CACHE Corporation, Austin, TX, 1996.
  49. Shacham, M., N. Brauner and M.  B.  Cutlip, "Response to Letter to the Editor", Chem. Eng. Educ., 29(1), 6-7 (1995).
  50. Shacham, M. and N. Brauner, "Correlation and Over-correlation of Heterogeneous Reaction Rate Data", Chem. Eng. Educ, 29(1)   22-25, 45 (1995).
  51. Shacham, M.,  N.  Brauner  and  M.  B.  Cutlip,  "Critical Analysis  of  Experimental Data, Regression Models and Regression Coefficients in Data Correlation", AIChE Symposium  Series, No. 304, vol. 91, pp 305-308 (1995)
  52. Brauner, N. and  M .  Shacham, "Numerical Experiments in Fluid Mechanics  with a Tank and Draining Pipe",  Comput. Appl. Eng. Educ, 2(3), 175-183 (1994).
  53. Brauner, N., M. Shacham, and M. B. Cutlip, "Application of an  Interactive  ODE Simulation Program in Process Control Education", Chem. Eng. Educ., 28 (2), 130-135 (1994).
  54. Shacham, M., N. Brauner, and  M.  B.  Cutlip, "Exothermic CSTRs  - Just How Stable are the Multiple Steady States?", Chem. Eng. Educ, 28(1), 30-35(1994).


 

Solution of linear algebraic, non-linear algebraic, differential-algebraic and ordinary differential 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 "continuing homotopy" type method for finding all solutions of a system 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 not require dedicated software.

A new technique for solving non-linear equations with discontinuities has been developed and a web-based library for testing performance of numerical software has been prepared.

 

  1. Shacham, M., N. Brauner, W. R. Ashurst and M. B. Cutlip, "Can I Trust this Software Package? – An Exercise in Validation of Computational Results ", Chemical Engineering Education, 42(1), 53-59 (2008)
  2. Shacham, M. and N. Brauner, "Preventing oscillatory behavior in error control for ODEs", Comp.  chem. Engng.,  Vol 32, No. 3 pp 409-419 (2008)
  1. Shacham, M., N.Brauner, M. B. Cutlip and M. Elly, "Design and Validation of a Numerical Problem Solving Environment for Ordinary Differential Equations", Presented at the AIChE 2006 Annual Meeting, San-Francisco, Nov. 12-17, 2006
  1. T. Alva, M. Shacham, N. Brauner and M. B. Cutlip, "Construction of a Web–Based Library for Testing the Performance of Numerical Software for ODEs", pp. 109-114 in L. Puigjaner and A. Espuna (Eds), Proceedings of the European Symposium on Computer Aided Process Engineering – 15, Elsevier, Amsterdam, 2005
  1. Shacham, M., N. Brauner and M. B. Cutlip, “A Web-based Library for Testing Performance of Numerical Software for Solving Nonlinear Algebraic Equations”, Computers chem. Engng. 26(4-5), 547-554(2002)
  2. Shacham, M. and  N.  Brauner,” Numerical Solution of Nonlinear Algebraic Equations with Discontinuities”, Computers chem. Engng. 26 1449-1457 (2002)
  1. Shacham, M., N. Brauner and M. B. Cutlip, “ A Web-based Library for Testing Performance of Numerical Software for Solving Nonlinear Algebraic Equations”, pp. 291-296 in Gani R. and S.B Jorgensen (Eds.) Proceedings of the 11th European Symposium on Computer Aided Process Engineering, May 27-30, 2001, Kolding, Denmark
  1. Brauner, N. and Shacham, M., “Physically Feasible Modeling and Simulation of Chemical Processes”, Presented at the 3rd European Congress of Chemical Engineering, Nurenberg, 26-28 June 2001.
  1. Shacham, M., N. Brauner and M. Pozin, "Comparing  Software for Interactive Solution of Systems of Nonlinear Algebraic Equations", Computers chem. Engng., 22,321-323(1998)
  1. Shacham, M., N. Brauner, and M. Pozin, "Application of Feedback Control Principles for Solving Differential-Algebraic Systems of Equations in Process Control Education", Computers chem. Engng. 20(Suppl), s1329-s1334 (1996)
  1. Shacham, O. and M. Shacham, "Finding Boundaries of the Domain of Definition for Functions along a One Dimensional Ray", ACM Tran. Math. Softw., 16 (3),   258-268 (1990).
  1. Shacham, M. and E. Kehat, "A Direct Method for  the  Solution  of  Large Sparse  Systems of Linear Equations," The Computer  Journal, 19 (4),  353-359 (1976).

 

Prediction and prevention of chemical reaction hazards - learning by simulation

Dynamic simulation assignments, based on of batch and a semi-batch reactors in which exothermic reactions are conducted have been developed. These assignments are used to teach students the various aspects of process safety. The students can observe temperature runaway taking place because of incidents, such as overcharging, cooling water failure, pipe blockage and excessive initial heating. They can derive various strategies to prevent temperature runaway developing as the result of such incidents and suggest operational and structural changes of the process to make it more resilient to component failures and incidents.

 

  1. M. Shacham, M. B. Cutlip and M. Elly, " Safety Analysis with Model-Based Dynamic Simulation in Mobile Devices", paper 743d, Presented at the 2014 AIChE Annual Meeting, Atlanta, GA, Nov. 16-21, 2014.
  1. M. Shacham and N. Brauner, Considering parameter uncertainties in the design of safe processes, pp. 429-434 in M. R. Eden, J. D. Siirola and G. P. Towler (Editors) Proceedings of the 8th International Conference on Foundations of Computer-Aided Process Design – FOCAPD 2014, July 13-17, 2014, Cle Elum, WA, USA
  1. Eisenberg, S., M. Shacham and N. Brauner, "Combining HAZOP with Dynamic Simulation - Applications for Safety Education", Journal of Loss Prevention in the Process Industries 19, 754–761(2006)
  1. S. Eizenberg, M. Shacham and N. Brauner, "Combining HAZOP with Dynamic Process Model Development for Safety Analysis", pp. 389-394 in W. Marquardt, C. Pantelides (Editors), Proceedings of the 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering, Elsevier, 2006.
  1. Eisenberg, S., M. Shacham and N. Brauner, “Evaluation of Kinetic Parameters and Critical Runaway Conditions in the Reaction System of Hexamine-Nitiric Acid to Produce REDX in non-Isothemal Batch Reactors”, Letter to the Editor,  Journal of Loss Prevention in the Process Industries 17(6), 513-514(2004).
  1. Shacham, M., N. Brauner and M. B. Cutlip, " Modular and Sequential Construction of Complex Process Models – Applications to Process Hazard Assessment", pp. 41 – 52 in A. Kraslawski and I. Turunen (Eds.), Proceedings Supplement Volume of the European Symposium on Computer Aided Process Engineering-13, Lappenranta University of Technology, Lappenranta, Finland, 2003
  1. Shacham, M.,  N.  Brauner and M. B. Cutlip,  "Prediction and Prevention of Chemical Reaction Hazards – Learning by Simulation", Chem. Eng. Educ., 35(4), 268-273(2001)
  1. Shacham, M., N. Brauner and M. B. Cutlip, "Prediction and Prevention of Chemical Reaction Hazards – Learning by Simulation”, Presented at the 3rd European Congress of Chemical Engineering, Nurenberg, 26-28 June 2001.
  1. Shacham, M., N. Brauner and M. B. Cutlip, “ Open Architecture Modeling and Simulation in Process Hazard Assessment”, Computers chem. Engng, 24(2-7), 415-419 (2000)
  1. Zaarur, N and M. Shacham, “A Layers Architecture Based Process Simulator”, proceedings of the 5th International Conference on Foundations of Computer Aided Process Design, Breckenridge, Colorado, July 18-23, 1999

 

 

Computer applications in engineering education.

The development of new technologies enable enhancement of the teaching techniques used in order to increase the learning efficiency. The new techniques are being continuously monitored, evaluated and class tested. The publications in this section present results of such evaluations

 

  1. M. Shacham and N. Brauner, “Solving a System of Nonlinear Algebraic Equations You Only Get Error Messages— What to do Next?”, Chemical Engineering Education,  51(2), 75-82(2017)

  2. M. B. Cutlip, M. Shacham and M. Elly, "Enabling Numerical Analysis Calculations within Educational Materials Delivered via PCs and Smartphones", paper 64c, presented at the 2016 AIChE Annual Meeting, San-Francisco, Nov. 13-18, 2016.

  3. M. Shacham and M. B. Cutlip, Using Templates for Demonstrating Good Programming Practices, Paper 510f,  Presented at the 2015 AIChE Annual Meeting, Salt Lake City, UT , Nov. 8-13, 2015.
  4. M. Shacham, M. B. Cutlip and M. Elly, " The Role of Physical Property Databases in Ch. E. Education", paper 148a, Presented at the 11AIChE Annual Meeting, Minneapolis, MN, Oct. 16-21, 2011
  5. M. Shacham, "Use of Advanced Educational Technologies in a Process Simulation Course", pp. 1135-1139 in E.N. Pistikopoulos, M.C. Georgiadis and A.C. Kokossis (Eds), 21st European Symposium on Computer Aided Process Engineering – ESCAPE 21, May 29 – June 1, 2011, Chalkidiki, Greece
  6. M. Shacham and M. B. Cutlip, "The Process Simulation Course - the Culmination of Core Undergraduate Coursework in Chemcial Engineering", paper 534b, Presented at the 10AIChE Annual Meeting, Salt Lake City, UT, Nov. 7-12, 2010
  7. M. B. Cutlip and M. Shacham, "POLYMATH – the Present, the New DIPPR Database Option and the Future of This Popular CACHE Numerical Problem-Solving Package", paper 388b,  Presented at the 10AIChE Annual Meeting, Salt Lake City, UT, Nov. 7-12, 2010
  8. M. Shacham, "Rapid Generation of Videotaped Lectures For a Course of "Introduction To Modeling and Computation", Using Tablet Pc and the Camtasia Recorder", Paper 247e, Presented at the 09AIChE Annual Meeting, Nashville, TN, Nov. 8-13, 2009
  9. M. B. Cutlip, M. Shacham, N. Lott and M. Elly, "Access and Utilization of the DIPPR Physical Property Database", Paper 329f, Presented at the 09AIChE Annual Meeting, Nashville, TN, Nov. 8-13, 2009
  10. E. Skorzinski, M. Shacham and N. Brauner, " A Simulation Program for Modelling Pollutant Dispersion for Educational Applications", pp. 1233 - 1238 in J. Jezowski and J. Thullie (Eds),19th European Symposium on Computer Aided Process Engineering – ESCAPE 19, June 13 - 17, 2009, Krakow, Poland
  11. Shacham, M., Cutlip, M. B. and Elly, M., "Live Problem Solving via Computer in the Classroom to Avoid "Death by PowerPoint"", Computer Applications in Engineering Education Vol 17, No. 3, 285-294(2009)
  12. Cutlip, M. B.,  Brauner, N. and M. Shacham, " Biokinetic Modeling of Imperfect Mixing in a Chemostat – an Example of Multiscale Modeling", Chemical Engineering Education , Vol. 43. No. 3, 243-248 (summer 2009)
  13. M. Shacham, "Applying New Technologies to the Classroom- What Have We Learned from Past Experience, Paper 133a, Presented at the AIChE100 Annual Meeting, Philadelphia, PA, Nov. 16-21, 2008
  14. Shacham, M., “Computer Based Exams in Mathematical Modeling and Simulation Courses”, Computers chem. Engng., 23(suppl.), S645-S649(1999)
  15. Shacham, M., “Computer Based Exams in Undergraduate Engineering Courses”, Comput. Appl. Eng. Educ, 6(3), 201-209(1998)


Additional Recent Publications

 

1.     Jose C. Merchuk, Asterio Sánchez-Mirón, Sebastian Asurmendi, Mordechai Shacham, "Modeling Tobacco Mosaic Virus Proliferation in Protoplasts", International Journal of Biology and Biomedical Engineering, 10, 202-210 (2016)

 

2.     M. Shacham, N. Brauner and M. B. Cutlip, "Considering Physical Property Uncertainties in Process Design", pp. 607-611 in I. D. L. Bogle and M. Fairweather (Editors), Proceedings of the 22nd European Symposium on Computer Aided Process Engineering, 17 - 20 June 2012, London, © 2012 Elsevier B.V.

 

3.     Dimitrova, E., N. Brauner, Chr. Boyadjiev and M. Shacham, "An Iterative Method for Model Parameter Identification of Thermodynamical Models", Transactions of Academenergo (Russian Academy of Sciences), No. 1, 69-89(2010)

4.     Spivak, T., Shacham, M. and N. Brauner, "A Dynamic Library For Physical And Thermodynamic Properties Correlations", Presented at the 3rd Chemical Engineering Conference for Collaborative Research in Eastern Mediterranean, May 13 –15, 2003, Thessaloniki, Greece.

5.     Shacham, M. and  N.  Brauner, "The Effect of Publication Rate Profile on Citation Statistics", Chem. Eng. Educ., 35(1). 32-35,45 (2001).

6.     Shacham, M. and Brauner, N., “A Dynamic Library for Physical and Thermodynamic Properties Correlations”, Ind. Eng. Chem. Res., 39(6), 1649-1657 (2000).

7.     Brauner, N. and M.  Shacham, "Statistical Analysis of Linear and Nonlinear Correlation of the Arrhenius Equation Constants", Chemical Engineering and Processing, 36(3), 243-249(1997).

8.     Shacham, M. and N. Brauner, "Using the Power-Law Rate Expression for Assessment of Rate.
Data and Detection of Infeasible Mechanisms for Reversible Reactions", Ind. Eng. Chem. Res. 35, 2790-2794 (1996).

9.   Brauner, N. and M. Shacham, "Using Power-Law Rate Expression Parameters for Discrimination Among Mechanistic Models in Rate Data Regression", Chem.Eng.Comm.155,1-18(1996).

10.  Shacham, M. and N. Brauner, "Danger by the Numbers-Two Meaningful Cold Weather Indicators”, Weatherwise, 48(5), 27-28(1995).

11.  Shacham, M., N. Brauner and M. Pozin, "Potential  Pitfalls in Using General Purpose Software for Interactive Solution of Ordinary Differential Equations", Acta Chimica Slovenica, 42(1), 119-124 (1995).

12.  Brauner, N. and M. Shacham, “ Meaningful Wind Chill Indicators Derived from Heat Transfer Principles”, Int. J. Biometeorol., 39(1), 46-52(1995).
      

13. Shacham, M., J. Wisniak and N. Brauner, "Error Analysis of Linearization Methods in Regression of Data for the Van-Laar and Margules Equations", Ind. Eng.  Chem.  Res., 32, 2820-2825 (1993).


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