How do I fix my model - Revision history

Jpye: /* 'catch_Word_model' */

2024-01-11T11:18:19Z

'catch_Word_model'

← Older revision		Revision as of 11:18, 11 January 2024
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	* If you see this error when trying to load your model in ASCEND, it usually means you have made a serious syntax error. A good way to fix such errors is to pare your model back to basics, and then to gradually add bits back again until you see identify the cause of the problem.		* If you see this error when trying to load your model in ASCEND, it usually means you have made a serious syntax error. A good way to fix such errors is to pare your model back to basics, and then to gradually add bits back again until you see identify the cause of the problem.
	* Occasionally, it seems that this error messages goes away simply by reloading your model file (ctrl-F5 in PyGTK GUI). This is probably a bug.		* Occasionally, it seems that this error messages goes away simply by reloading your model file (ctrl-F5 in PyGTK GUI). This is probably a bug.
			* This error message's name comes from an early attempt in the ASCEND code to give users a helpful suggestion when they inadvertently entered their model into Microsoft Word instead of a text editor!

	== Integer arithmetic ==		== Integer arithmetic ==

Jpye: /* Function range error */

2024-01-11T11:16:55Z

Function range error

← Older revision		Revision as of 11:16, 11 January 2024
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	== Function range error ==		== Function range error ==

	* If you receive errors/warnings like "Function range error" and/or "pow_d0: -0.111803 raised to power 0.7 undefined: returning 0.215" then ASCEND is warning you that evaluation of certain functions in your model are causing range errors. For example, one can not calculate the square root of negative numbers (in ASCEND: there is no support for complex numbers). There are some so-called "safe-mode" functions that provide numerically sensible behaviour in these cases that can still sometimes allow the solver to 'find its way home', however this doesn't always work. In those cases, the problem can be resolved by looking at which variables and functions (X^Y, sqrt, ln, etc) could be causing the problem, and set upper and/or lower bounds for that variable such that ASCEND doesn't set those variables in invalid regions.		* If you receive errors/warnings like "Function range error" and/or "pow_d0: -0.111803 raised to power 0.7 undefined: returning 0.215" then ASCEND is warning you that evaluation of certain functions in your model are causing range errors. For example, one can not calculate the square root of negative numbers (in ASCEND: there is no support for complex numbers). There are some so-called "safe-mode" functions that provide numerically sensible behaviour in these cases that can still sometimes allow the solver to 'find its way home', however this doesn't always work. In those cases, the problem can be resolved by looking at which variables and functions (<tt>X^Y</tt>, <tt>sqrt</tt>, <tt>ln</tt>, etc) could be causing the problem, and set upper and/or lower bounds for that variable such that ASCEND doesn't set those variables in invalid regions.
	* Often these problems can be avoided by using physically meaningful variable declarations. For example "T IS_A temperature" will automatically given you a variable whose lower bound is set to zero.		* Often these problems can be avoided by using physically meaningful variable declarations. For example "<tt>T IS_A temperature</tt>" will automatically given you a variable whose lower bound is set to zero.
	* Use <tt>[[upper_bound]]</tt> and <tt>[[lower_bound]]</tt> statements in your [[METHODS]] to make such initialisations permanent, but you can test using the PyGTK GUI by right-clicking a variable and manually setting the bounds, then attempting to re-solve.		* Use <tt>[[upper_bound]]</tt> and <tt>[[lower_bound]]</tt> statements in your [[METHODS]] to make such initialisations permanent, but you can test using the PyGTK GUI by right-clicking a variable and manually setting the bounds, then attempting to re-solve.

Jpye: /* Function range error */

2024-01-11T11:16:20Z

Function range error

← Older revision		Revision as of 11:16, 11 January 2024
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	* If you receive errors/warnings like "Function range error" and/or "pow_d0: -0.111803 raised to power 0.7 undefined: returning 0.215" then ASCEND is warning you that evaluation of certain functions in your model are causing range errors. For example, one can not calculate the square root of negative numbers (in ASCEND: there is no support for complex numbers). There are some so-called "safe-mode" functions that provide numerically sensible behaviour in these cases that can still sometimes allow the solver to 'find its way home', however this doesn't always work. In those cases, the problem can be resolved by looking at which variables and functions (X^Y, sqrt, ln, etc) could be causing the problem, and set upper and/or lower bounds for that variable such that ASCEND doesn't set those variables in invalid regions.		* If you receive errors/warnings like "Function range error" and/or "pow_d0: -0.111803 raised to power 0.7 undefined: returning 0.215" then ASCEND is warning you that evaluation of certain functions in your model are causing range errors. For example, one can not calculate the square root of negative numbers (in ASCEND: there is no support for complex numbers). There are some so-called "safe-mode" functions that provide numerically sensible behaviour in these cases that can still sometimes allow the solver to 'find its way home', however this doesn't always work. In those cases, the problem can be resolved by looking at which variables and functions (X^Y, sqrt, ln, etc) could be causing the problem, and set upper and/or lower bounds for that variable such that ASCEND doesn't set those variables in invalid regions.
	* Often these problems can be avoided by using physically meaningful variable declarations. For example "T IS_A temperature" will automatically given you a variable whose lower bound is set to zero.		* Often these problems can be avoided by using physically meaningful variable declarations. For example "T IS_A temperature" will automatically given you a variable whose lower bound is set to zero.
	* Use [[upper_bound]] and [[lower_bound]] statements in your [[METHODS]] to make such initialisations permanent, but you can test using the PyGTK GUI by right-clicking a variable and manually setting the bounds, then attempting to re-solve.		* Use <tt>[[upper_bound]]</tt> and <tt>[[lower_bound]]</tt> statements in your [[METHODS]] to make such initialisations permanent, but you can test using the PyGTK GUI by right-clicking a variable and manually setting the bounds, then attempting to re-solve.

	== 'catch_Word_model' ==		== 'catch_Word_model' ==

Jpye: /* Row rank deficiency */

2024-01-11T11:15:16Z

Row rank deficiency

← Older revision		Revision as of 11:15, 11 January 2024
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	* If you look at the incidence matrix for your system, there will be some unassigned relations at the bottom of the window. These are the 'redundant' equations. Maybe you inadvertently wrote equivalent versions of the same equations more than once. For example, if you have equations "a=b", "b=c" and "c=a" then the third equation is redundant and should be removed from your model.		* If you look at the incidence matrix for your system, there will be some unassigned relations at the bottom of the window. These are the 'redundant' equations. Maybe you inadvertently wrote equivalent versions of the same equations more than once. For example, if you have equations "a=b", "b=c" and "c=a" then the third equation is redundant and should be removed from your model.
	* This issue could also arise when you have an error relating to conditional logic in your model, such as [[CASE]] or [[WHEN]] statements.		* This issue could also arise when you have an error relating to conditional logic in your model, such as [[CASE]] or [[WHEN]] statements.
	* Note that this error comes from a structural rather than numerical analysis of the equations in your system.		* Note that this error comes from a ''structural'' rather than ''numerical'' analysis of the equations in your system.

	== Failure to converge ==		== Failure to converge ==

Jpye: /* Row rank deficiency */

2024-01-11T11:14:57Z

Row rank deficiency

← Older revision		Revision as of 11:14, 11 January 2024
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	* If you look at the incidence matrix for your system, there will be some unassigned relations at the bottom of the window. These are the 'redundant' equations. Maybe you inadvertently wrote equivalent versions of the same equations more than once. For example, if you have equations "a=b", "b=c" and "c=a" then the third equation is redundant and should be removed from your model.		* If you look at the incidence matrix for your system, there will be some unassigned relations at the bottom of the window. These are the 'redundant' equations. Maybe you inadvertently wrote equivalent versions of the same equations more than once. For example, if you have equations "a=b", "b=c" and "c=a" then the third equation is redundant and should be removed from your model.
	* This issue could also arise when you have an error relating to conditional logic in your model, such as [[CASE]] or [[WHEN]] statements.		* This issue could also arise when you have an error relating to conditional logic in your model, such as [[CASE]] or [[WHEN]] statements.
			* Note that this error comes from a structural rather than numerical analysis of the equations in your system.

	== Failure to converge ==		== Failure to converge ==

Jpye at 11:13, 11 January 2024

2024-01-11T11:13:00Z

← Older revision		Revision as of 11:13, 11 January 2024
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	* Check that you don't somehow have the same equation written twice in two different ways.		* Check that you don't somehow have the same equation written twice in two different ways.
	* Check for redundant mass conservations and energy conservation equations. This is an especially easy mistake to make when writing equations containing flow loops.		* Check for redundant mass conservations and energy conservation equations. This is an especially easy mistake to make when writing equations containing flow loops.

			== Row rank deficiency ==

			* For example: "System is row rank deficient (12 dependent equations)"
			* This error arises during block decomposition of your model -- trying to figure out which equations will be used to solve which free variables.
			* The error is saying that there are more equations than needed based on the number of equations.
			* If you look at the incidence matrix for your system, there will be some unassigned relations at the bottom of the window. These are the 'redundant' equations. Maybe you inadvertently wrote equivalent versions of the same equations more than once. For example, if you have equations "a=b", "b=c" and "c=a" then the third equation is redundant and should be removed from your model.
			* This issue could also arise when you have an error relating to conditional logic in your model, such as [[CASE]] or [[WHEN]] statements.

	== Failure to converge ==		== Failure to converge ==

Jpye: /* Structural singularity errors */

2013-01-24T02:38:19Z

Structural singularity errors

← Older revision		Revision as of 02:38, 24 January 2013
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	== Structural singularity errors ==		== Structural singularity errors ==

			* This kind of error means that, from the the way the variables are arranged in the particular relations present in your model, it is possible to see that a solution can not be determined.
	* Check that you don't somehow have the same equation written twice in two different ways.		* Check that you don't somehow have the same equation written twice in two different ways.
	* Check for redundant mass conservations and energy conservation equations. This is an especially easy mistake to make when writing equations containing flow loops.		* Check for redundant mass conservations and energy conservation equations. This is an especially easy mistake to make when writing equations containing flow loops.

Jpye: /* Failure to converge */

2013-01-24T02:36:47Z

Failure to converge

← Older revision		Revision as of 02:36, 24 January 2013
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	== Failure to converge ==		== Failure to converge ==

			* Make sure your model is 'square' first of all. If the number of unknowns does not match the number of equations, ASCEND's solvers like [[QRSlv]] may still attempt to proceed with an under/overspecified problem, but that is almost always ''not'' what you want. Get the problem square first, by [[FIX]]ing or [[FREE]]ing more variables to get it right.
	* A model that does not converge may be simply a wrong model. Check that your equations all makes sense first of all.		* A model that does not converge may be simply a wrong model. Check that your equations all makes sense first of all.
	* Make sure you initialise your variables to have variables within the ballpark of the values you expect for their solution (see [[METHOD\|METHODs]] and [[default_self]]) This can be especially important when your problem has non-smooth equations such as thermodynamic property relationship eg T(p,h).		* Make sure you initialise your variables to have variables within the ballpark of the values you expect for their solution (see [[METHOD\|METHODs]] and [[default_self]]) This can be especially important when your problem has non-smooth equations such as thermodynamic property relationship eg T(p,h).

Jpye: /* Pivoting errors */

2012-05-18T15:47:18Z

Pivoting errors

← Older revision		Revision as of 15:47, 18 May 2012
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	* Pivoting errors arise when your NLA's jacobian matrix is singular. This happens as a result of multiply linearly dependent equations, which essentially means that you may have written the same equation twice, or expressions that are in some way redundant.		* Pivoting errors arise when your NLA's jacobian matrix is singular. This happens as a result of multiply linearly dependent equations, which essentially means that you may have written the same equation twice, or expressions that are in some way redundant.
	* Pivoting errors can also arise due to badly-initialised variables. This happens, for example, when attempting to solve for a temperature in a superheated region by varying an enthalpy value set ~~intitialling~~ in the saturation region: changing enthalpy causes no change in temperature, ~~resulting in~~ a pivoting problem.		* Pivoting errors can also arise due to badly-initialised variables. This happens, for example, when attempting to solve for a temperature in a superheated region by varying an enthalpy value set with its initial guess in the saturation region: in that case, changing enthalpy causes no change in temperature, leading ASCEND to think that temperature is not related to enthalpy -- a pivoting problem.

	== Structural singularity errors ==		== Structural singularity errors ==

Jpye at 23:46, 1 February 2012

2012-02-01T23:46:16Z

← Older revision		Revision as of 23:46, 1 February 2012
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			{{DISPLAYTITLE:How do I fix my model?}}
	<div>''This article is incomplete or needs expanding. Please help out by adding your comments.''</div>		<div>''This article is incomplete or needs expanding. Please help out by adding your comments.''</div>