Buildings.Utilities.Math.Functions.Examples

Collection of models that illustrate model use and test models

Information

This package contains examples for the use of models that can be found in Buildings.Utilities.Math.Functions.

Extends from Modelica.Icons.ExamplesPackage (Icon for packages containing runnable examples).

Package Content

Name	Description
BesselJ0	Test case for Bessel function J0
BesselJ1	Test case for Bessel function J1
BesselY0	Test case for Bessel function Y0
BesselY1	Test case for Bessel function Y1
Binomial	Test case for evaluation of binomial coefficients
CubicHermite	Test problem for cubic hermite splines
ExponentialIntegralE1	Test case for the exponential integral, E1
Factorial	Test case for evaluation of factorials
FallingFactorial	Test case for evaluation of falling factorials
InverseXDerivativeCheck	Model that checks the correct implementation of the 1st order derivative of InverseXRegularized
InverseXDerivative_2_Check	Model that checks the correct implementation of the 2nd order derivative of InverseXRegularized
InverseXRegularized	Test problem for function that replaces 1/x around the origin by a twice continuously differentiable function
IsMonotonic	Tests the correct implementation of the function isMonotonic
Polynomial
PowerLinearized	Test problem for function that linearizes y=x^n below some threshold
QuinticHermite	Example model using quintic Hermite spline
RegNonZeroPower
RegNonZeroPowerDerivativeCheck
RegNonZeroPowerDerivative_2_Check
RegStep	Example for inlined regStep function
Round	Example for round function
SmoothExponentialDerivativeCheck
SmoothHeavisideDerivatives	Test model for the derivatives of the smoothHeavisidefunction
SmoothInterpolation	Test problem for cubic hermite splines that takes a vector of values as an argument
SpliceFunction
SpliceFunctionDerivativeCheck
TrapezoidalIntegration	Tests the correct implementation of the function trapezoidalIntegration

Buildings.Utilities.Math.Functions.Examples.BesselJ0

Test case for Bessel function J0

Information

This example demonstrates the use of the function for Bessel functions of the first kind of order 0, J0.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model BesselJ0 "Test case for Bessel function J0" extends Modelica.Icons.Example; Real J0 "Bessel function J0"; equation J0 = Buildings.Utilities.Math.Functions.besselJ0(time); end BesselJ0;

Buildings.Utilities.Math.Functions.Examples.BesselJ1

Test case for Bessel function J1

Information

This example demonstrates the use of the function for Bessel functions of the first kind of order 1, J1.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model BesselJ1 "Test case for Bessel function J1" extends Modelica.Icons.Example; Real J1 "Bessel function J1"; equation J1 = Buildings.Utilities.Math.Functions.besselJ1(time); end BesselJ1;

Buildings.Utilities.Math.Functions.Examples.BesselY0

Test case for Bessel function Y0

Information

This example demonstrates the use of the function for Bessel functions of the second kind of order 0, Y0.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model BesselY0 "Test case for Bessel function Y0" extends Modelica.Icons.Example; Real Y0 "Bessel function Y0"; equation Y0 = Buildings.Utilities.Math.Functions.besselY0(time); end BesselY0;

Buildings.Utilities.Math.Functions.Examples.BesselY1

Test case for Bessel function Y1

Information

This example demonstrates the use of the function for Bessel functions of the second kind of order 1, Y1.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model BesselY1 "Test case for Bessel function Y1" extends Modelica.Icons.Example; Real Y1 "Bessel function Y1"; equation Y1 = Buildings.Utilities.Math.Functions.besselY1(time); end BesselY1;

Buildings.Utilities.Math.Functions.Examples.Binomial

Test case for evaluation of binomial coefficients

Information

This example demonstrates the use of the function for the evaluation of the binomial coefficient "n choose k".

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model Binomial "Test case for evaluation of binomial coefficients" extends Modelica.Icons.Example; Real bin[10] "Binomial coefficient"; Integer n "Size of set"; equation n = integer(if time >= 1 then floor(time) else 1); for k in 1:10 loop if n >= k then bin[k] = Buildings.Utilities.Math.Functions.binomial(n,k); else bin[k] = 0.0; end if; end for; end Binomial;

Buildings.Utilities.Math.Functions.Examples.CubicHermite

Test problem for cubic hermite splines

Information

This example demonstrates the use of the function for cubic hermite interpolation and linear extrapolation. The example use interpolation with two different settings: One settings produces a monotone cubic hermite, whereas the other setting does not enforce monotonicity. The resulting plot should look as shown below, where for better visibility, the support points have been marked with black dots. Notice that the red curve is monotone increasing.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	xd[:]	{-1,1,5,6}	Support points
Real	yd[size(xd, 1)]	{-1,1,2,10}	Support points
Real	d[size(xd, 1)]		Derivatives at the support points
Real	dMonotone[size(xd, 1)]		Derivatives at the support points
Boolean	ensureMonotonicity	true

Modelica definition

model CubicHermite "Test problem for cubic hermite splines" extends Modelica.Icons.Example; parameter Real[:] xd={-1,1,5,6} "Support points"; parameter Real[size(xd, 1)] yd={-1,1,2,10} "Support points"; parameter Real[size(xd, 1)] d(each fixed=false) "Derivatives at the support points"; parameter Real[size(xd, 1)] dMonotone(each fixed=false) "Derivatives at the support points"; parameter Boolean ensureMonotonicity=true; Real x "Independent variable"; Real y "Dependent variable without monotone interpolation"; Real yMonotone "Dependent variable with monotone interpolation"; Integer i "Integer to select data interval"; initial algorithm // Get the derivative values at the support points d := Buildings.Utilities.Math.Functions.splineDerivatives( x=xd, y=yd, ensureMonotonicity=false); dMonotone := Buildings.Utilities.Math.Functions.splineDerivatives(x=xd, y=yd, ensureMonotonicity=true); algorithm x := xd[1] + time*1.2*(xd[size(xd, 1)] - xd[1]) - 0.5; // i is a counter that is used to pick the derivative of d or dMonotonic // that correspond to the interval that contains x i := 1; for j in 1:size(xd, 1) - 1 loop if x > xd[j] then i := j; end if; end for; // Extrapolate or interpolate the data y := Buildings.Utilities.Math.Functions.cubicHermiteLinearExtrapolation( x=x, x1=xd[i], x2=xd[i + 1], y1=yd[i], y2=yd[i + 1], y1d=d[i], y2d=d[i + 1]); yMonotone := Buildings.Utilities.Math.Functions.cubicHermiteLinearExtrapolation( x=x, x1=xd[i], x2=xd[i + 1], y1=yd[i], y2=yd[i + 1], y1d=dMonotone[i], y2d=dMonotone[i + 1]); end CubicHermite;

Buildings.Utilities.Math.Functions.Examples.ExponentialIntegralE1

Test case for the exponential integral, E1

Information

This example demonstrates the use of the function for the exponential integral, E1.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model ExponentialIntegralE1 "Test case for the exponential integral, E1" extends Modelica.Icons.Example; Real E1 "Exponential integral E1"; equation E1 = Buildings.Utilities.Math.Functions.exponentialIntegralE1(time); end ExponentialIntegralE1;

Buildings.Utilities.Math.Functions.Examples.Factorial

Test case for evaluation of factorials

Information

This example demonstrates the use of the function for the evaluation of factorials.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model Factorial "Test case for evaluation of factorials" extends Modelica.Icons.Example; Integer fac "Factorial of n"; Integer n "n"; equation n = integer(floor(time)); fac = Buildings.Utilities.Math.Functions.factorial(n); end Factorial;

Buildings.Utilities.Math.Functions.Examples.FallingFactorial

Test case for evaluation of falling factorials

Information

This example demonstrates the use of the function for the evaluation of falling factorials.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model FallingFactorial "Test case for evaluation of falling factorials" extends Modelica.Icons.Example; Integer falFac[10] "Falling factorial of n"; Integer n "n"; equation n = integer(floor(time)); for k in 1:10 loop falFac[k] = Buildings.Utilities.Math.Functions.fallingFactorial(n,k); end for; end FallingFactorial;

Buildings.Utilities.Math.Functions.Examples.InverseXDerivativeCheck

Model that checks the correct implementation of the 1st order derivative of InverseXRegularized

Information

This model validates the implementation of Buildings.Utilities.Math.Functions.inverseXRegularized and its first order derivative Buildings.Utilities.Math.Functions.BaseClasses.der_smoothTransition. If the derivative implementation is wrong, the simulation will stop with an error.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	delta	0.7	Smoothing coefficient

Modelica definition

model InverseXDerivativeCheck "Model that checks the correct implementation of the 1st order derivative of InverseXRegularized" extends Modelica.Icons.Example; constant Real gain = 4 "Gain for computing the mass flow rate"; parameter Real delta = 0.7 "Smoothing coefficient"; Real x "Independent variable"; Real y_comp "Comparison value"; Real y "Dependent variable"; Real err "Integration error"; initial equation y = y_comp; equation x = time^3*gain; y = Buildings.Utilities.Math.Functions.inverseXRegularized( x = x, delta = delta); der(y_comp) = Buildings.Utilities.Math.Functions.BaseClasses.der_inverseXRegularized(x=x,delta=delta,x_der=der(x)); err = y-y_comp; assert(abs(err) < 1E-3, "Error in implementation."); end InverseXDerivativeCheck;

Buildings.Utilities.Math.Functions.Examples.InverseXDerivative_2_Check

Model that checks the correct implementation of the 2nd order derivative of InverseXRegularized

Information

This model validates the implementation of Buildings.Utilities.Math.Functions.inverseXRegularized and its second order derivative Buildings.Utilities.Math.Functions.BaseClasses.der_2_smoothTransition. If the derivative implementation is wrong, the simulation will stop with an error.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	delta	0.7	Smoothing coefficient

Modelica definition

model InverseXDerivative_2_Check "Model that checks the correct implementation of the 2nd order derivative of InverseXRegularized" extends Modelica.Icons.Example; Buildings.Utilities.Diagnostics.CheckEquality cheEqu1( threShold=1e-3) "Block for checking integration error"; Buildings.Utilities.Diagnostics.CheckEquality cheEqu2( threShold=1e-3) "Block for checking integration error"; constant Real gain = 4 "Gain for computing the mass flow rate"; parameter Real delta = 0.7 "Smoothing coefficient"; Real x "Independent variable"; Real y_comp "Comparison value"; Real y "Dependent variable"; Real der_y_comp "1st order derivative of comparison value"; Real der_y "1st order derivative of dependent variable"; Real err "Integration error"; Real der_err "Integration error"; initial equation y = y_comp; der_y = der_y_comp; equation x = time^3*gain; y = Buildings.Utilities.Math.Functions.inverseXRegularized( x = x, delta = delta); der_y = der(y); der_y_comp = der(y_comp); der(der_y) = der(der_y_comp); cheEqu1.u1 = y; cheEqu1.u2 = y_comp; err = cheEqu1.y; cheEqu2.u1 = der_y; cheEqu2.u2 = der_y_comp; der_err = cheEqu2.y; assert(abs(err) < 1E-3, "Error in implementation."); assert(abs(der_err) < 1E-3, "Error in implementation."); end InverseXDerivative_2_Check;

Buildings.Utilities.Math.Functions.Examples.InverseXRegularized

Test problem for function that replaces 1/x around the origin by a twice continuously differentiable function

Information

This example tests the implementation of Buildings.Utilities.Math.Functions.inverseXRegularized.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	delta	0.5	Small value for approximation

Modelica definition

model InverseXRegularized "Test problem for function that replaces 1/x around the origin by a twice continuously differentiable function" extends Modelica.Icons.Example; Real x "Independent variable"; parameter Real delta = 0.5 "Small value for approximation"; final parameter Real deltaInv = 1/delta "Inverse value of delta"; final parameter Real a = -15*deltaInv "Polynomial coefficient"; final parameter Real b = 119*deltaInv^2 "Polynomial coefficient"; final parameter Real c = -361*deltaInv^3 "Polynomial coefficient"; final parameter Real d = 534*deltaInv^4 "Polynomial coefficient"; final parameter Real e = -380*deltaInv^5 "Polynomial coefficient"; final parameter Real f = 104*deltaInv^6 "Polynomial coefficient"; Real y "Function value"; Real xInv "Function value"; Real dy_dt "First derivative of y with respect to t"; Real d2y_dt2 "Second derivative of y with respect to t"; equation x=2*time-1; xInv = if ( abs(x) > 0.1) then 1 / x else 0; y = Buildings.Utilities.Math.Functions.inverseXRegularized( x=x, delta=delta, deltaInv=deltaInv, a=a, b=b, c=c, d=d, e=e, f=f); dy_dt=der(y); d2y_dt2=der(dy_dt); end InverseXRegularized;

Buildings.Utilities.Math.Functions.Examples.IsMonotonic

Tests the correct implementation of the function isMonotonic

Information

This example tests the correct implementation of the function Buildings.Utilities.Math.Functions.isMonotonic. If the function is implemented incorrect, the example will stop with an error.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model IsMonotonic "Tests the correct implementation of the function isMonotonic" extends Modelica.Icons.Example; Real x_incStrict[3] = {0, 1, 2} "strictly increasing"; Real x_notMon[3] = {0, 3, 2} "not monotonic"; Real x_incWeak[4] = {0, 1, 1, 2} "weakly increasing"; Real x_notWeak[4] = {0, 3, 3, 2} "not weakly monotonic"; Real x_decStrict[3] = {2.5, 2, 0.1} "strictly decreasing"; Real x_decWeak[4] = {3, 1, 1, 0.5} "weakly decreasing"; equation // Tests with weak monotonicity //strictly increasing assert(Buildings.Utilities.Math.Functions.isMonotonic(x_incStrict, strict=false), "Error. Function should have returned true."); //not monotonic assert(false == Buildings.Utilities.Math.Functions.isMonotonic(x_notMon, strict=false), "Error. Function should have returned true."); //weakly increasing assert(Buildings.Utilities.Math.Functions.isMonotonic(x_incWeak, strict=false), "Error. Function should have returned true."); //not weakly monotonic assert(false == Buildings.Utilities.Math.Functions.isMonotonic(x_notWeak, strict=false), "Error. Function should have returned true."); //strictly decreasing assert(Buildings.Utilities.Math.Functions.isMonotonic({2.5, 2, 0.1}, strict=false), "Error. Function should have returned true."); //weakly decreasing assert(Buildings.Utilities.Math.Functions.isMonotonic({3, 1, 1, 0.5}, strict=false), "Error. Function should have returned true."); // Tests with strict monotonicity //strictly increasing assert(Buildings.Utilities.Math.Functions.isMonotonic(x_incStrict, strict=true), "Error. Function should have returned true."); //not monotonic assert(false == Buildings.Utilities.Math.Functions.isMonotonic(x_notMon, strict=true), "Error. Function should have returned true."); //weakly increasing assert(false == Buildings.Utilities.Math.Functions.isMonotonic(x_incWeak, strict=true), "Error. Function should have returned true."); //not weakly monotonic assert(false == Buildings.Utilities.Math.Functions.isMonotonic(x_notWeak, strict=true), "Error. Function should have returned true."); //strictly decreasing assert(Buildings.Utilities.Math.Functions.isMonotonic(x_decStrict, strict=true), "Error. Function should have returned true."); //weakly decreasing assert(false == Buildings.Utilities.Math.Functions.isMonotonic(x_decWeak, strict=true), "Error. Function should have returned true."); end IsMonotonic;

Buildings.Utilities.Math.Functions.Examples.Polynomial

Information

This example verifies the correct implementation of Buildings.Utilities.Math.Functions.polynomial.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model Polynomial extends Modelica.Icons.Example; Real x "Function value"; equation x=Buildings.Utilities.Math.Functions.polynomial(x=time^3-2, a={2, 4, -4, 5}); end Polynomial;

Buildings.Utilities.Math.Functions.Examples.PowerLinearized

Test problem for function that linearizes y=x^n below some threshold

Information

This example tests the implementation of Buildings.Utilities.Math.Functions.powerLinearized.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model PowerLinearized "Test problem for function that linearizes y=x^n below some threshold" extends Modelica.Icons.Example; Real T4(start=300^4) "Temperature raised to 4-th power"; Real T "Temperature"; Real TExact "Temperature"; equation T = (1+500*time); T = Buildings.Utilities.Math.Functions.powerLinearized(x=T4, x0=243.15^4, n=0.25); TExact = abs(T4)^(1/4); end PowerLinearized;

Buildings.Utilities.Math.Functions.Examples.QuinticHermite

Example model using quintic Hermite spline

Information

Demonstration of the use of a quintic Hermite spline interpolation function.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	a	0.5	Exponential argument coefficient
Real	x1	1	Lower abscissa value
Real	x2	2.6	Upper abscissa value
Real	y1	-x1	Lower ordinate value
Real	y1d	-1	Lower derivative
Real	y2d	aexp(ax2)	Upper derivative
Real	y1dd	0	Lower second derivative
Real	y2dd	a^2exp(ax2)	Upper second derivative

Modelica definition

model QuinticHermite "Example model using quintic Hermite spline" extends Modelica.Icons.Example; parameter Real a = 0.5 "Exponential argument coefficient"; parameter Real x1 = 1 "Lower abscissa value"; parameter Real x2 = 2.6 "Upper abscissa value"; parameter Real y1 = -x1 "Lower ordinate value"; parameter Real y1d = -1 "Lower derivative"; parameter Real y2d = a*exp(a*x2) "Upper derivative"; parameter Real y1dd = 0 "Lower second derivative"; parameter Real y2dd= a^2*exp(a*x2) "Upper second derivative"; Real x = time "Abscissa value"; Real y "Ordinate value"; Real dy "Time derivative of ordinate value"; Real ddy "Second time derivative of ordinate value"; Real y2 "Second ordinate section"; equation y2 = exp(a*x2); y= noEvent(smooth(2,if x>x2 then exp(a*x) elseif x<x1 then -time else Buildings.Utilities.Math.Functions.quinticHermite(x=x,x1=x1,x2=x2,y1=y1,y2=y2,y1d=y1d,y2d=y2d,y1dd=y1dd,y2dd=y2dd))); dy=der(y); ddy=der(dy); end QuinticHermite;

Buildings.Utilities.Math.Functions.Examples.RegNonZeroPower

Information

This example tests the implementation of Buildings.Utilities.Math.Functions.regNonZeroPower.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model RegNonZeroPower extends Modelica.Icons.Example; Real y "Function value"; equation y=Buildings.Utilities.Math.Functions.regNonZeroPower( time, 0.3, 0.5); end RegNonZeroPower;

Buildings.Utilities.Math.Functions.Examples.RegNonZeroPowerDerivativeCheck

Information

This example checks whether the function derivative is implemented correctly. If the derivative implementation is not correct, the model will stop with an assert statement.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	n	0.33	Exponent
Real	delta	0.1	Abscissa value where transition occurs

Modelica definition

model RegNonZeroPowerDerivativeCheck extends Modelica.Icons.Example; parameter Real n=0.33 "Exponent"; parameter Real delta = 0.1 "Abscissa value where transition occurs"; Real x; Real y; initial equation y=x; equation x=Buildings.Utilities.Math.Functions.regNonZeroPower( time^3,n, delta); der(y)=der(x); assert(abs(x-y) < 1E-2, "Model has an error"); end RegNonZeroPowerDerivativeCheck;

Buildings.Utilities.Math.Functions.Examples.RegNonZeroPowerDerivative_2_Check

Information

This example checks whether the function derivative is implemented correctly. If the derivative implementation is not correct, the model will stop with an assert statement.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	n	0.33	Exponent
Real	delta	0.7	Smoothing coefficient

Modelica definition

model RegNonZeroPowerDerivative_2_Check extends Modelica.Icons.Example; parameter Real n=0.33 "Exponent"; constant Real gain = 4 "Gain for computing the mass flow rate"; parameter Real delta = 0.7 "Smoothing coefficient"; Real x "Independent variable"; Real y_comp "Comparison value"; Real y "Dependent variable"; Real der_y_comp "1st order derivative of comparison value"; Real der_y "1st order derivative of dependent variable"; Real err "Integration error"; Real der_err "Integration error"; initial equation y = y_comp; der_y = der_y_comp; equation x = time^3*gain; y = Buildings.Utilities.Math.Functions.regNonZeroPower( x = x, n = n, delta = delta); der_y = der(y); der_y_comp = der(y_comp); der(der_y) = der(der_y_comp); err = y-y_comp; der_err = der_y-der_y_comp; assert(abs(err) < 1E-3, "Error in implementation."); assert(abs(der_err) < 1E-3, "Error in implementation."); end RegNonZeroPowerDerivative_2_Check;

Buildings.Utilities.Math.Functions.Examples.RegStep

Example for inlined regStep function

Information

This example tests the implementation of Buildings.Utilities.Math.Functions.regStep.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model RegStep "Example for inlined regStep function" extends Modelica.Icons.Example; Real y "Function value"; equation y=Buildings.Utilities.Math.Functions.regStep(time, 1, -1, 1e-5); end RegStep;

Buildings.Utilities.Math.Functions.Examples.Round

Example for round function

Information

This example tests the implementation of Buildings.Utilities.Math.Functions.round for different values of n. Arguments and return values are scale to simplify the show that the scaling for the rounding is implemented correctly.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model Round "Example for round function" extends Modelica.Icons.Example; Real ym2 "Function value"; Real ym1 "Function value"; Real y "Function value"; Real y1 "Function value"; Real y2 "Function value"; equation ym2=Buildings.Utilities.Math.Functions.round(x=time*100, n=-2)/100; ym1=Buildings.Utilities.Math.Functions.round(x=time*10, n=-1)/10; y=Buildings.Utilities.Math.Functions.round(x=time, n=0); y1=Buildings.Utilities.Math.Functions.round(x=time/10, n=1)*10; y2=Buildings.Utilities.Math.Functions.round(x=time/100, n=2)*100; end Round;

Buildings.Utilities.Math.Functions.Examples.SmoothExponentialDerivativeCheck

Information

This example checks whether the function derivative is implemented correctly. If the derivative implementation is not correct, the model will stop with an assert statement.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	delta	0.5	Smoothing area

Modelica definition

model SmoothExponentialDerivativeCheck extends Modelica.Icons.Example; parameter Real delta = 0.5 "Smoothing area"; Real x "Independent variable"; Real y "Approximate function value"; Real y_comp "Approximate function value"; Real ex "Exact function value"; Real err "Error"; initial equation y=y_comp; equation x = time^3; y_comp=Buildings.Utilities.Math.Functions.smoothExponential( x=x, delta=delta); der(y)=der(y_comp); err = y_comp-y; assert(abs(err) < 1E-2, "Model has an error"); ex=exp(-abs(x)); end SmoothExponentialDerivativeCheck;

Buildings.Utilities.Math.Functions.Examples.SmoothHeavisideDerivatives

Test model for the derivatives of the smoothHeavisidefunction

Information

This model tests the first and second derivative of the twice Lipschitz continuously differentiable function Buildings.Utilities.Math.Functions.smoothHeaviside.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model SmoothHeavisideDerivatives "Test model for the derivatives of the smoothHeavisidefunction" extends Modelica.Icons.Example; Real y = Buildings.Utilities.Math.Functions.smoothHeaviside(x=time, delta=0.2) "Function value"; Real der_y = der(y) "First derivative"; Real der2_y = der(der_y) "Second derivative"; equation end SmoothHeavisideDerivatives;

Buildings.Utilities.Math.Functions.Examples.SmoothInterpolation

Test problem for cubic hermite splines that takes a vector of values as an argument

Information

This example also tests the function for the situation where only 2 or only 1 support points are provided. In the first case, the result will be linear function and in the second case, a constant value.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	xSup[:]	{-1,1,5,6}	Support points
Real	ySup[size(xSup, 1)]	{-1,1,2,10}	Support points

Modelica definition

model SmoothInterpolation "Test problem for cubic hermite splines that takes a vector of values as an argument" extends Modelica.Icons.Example; parameter Real[:] xSup={-1,1,5,6} "Support points"; parameter Real[size(xSup, 1)] ySup={-1,1,2,10} "Support points"; Real x "Independent variable"; Real y "Dependent variable without monotone interpolation"; Real yMonotone "Dependent variable with monotone interpolation"; Real y2 "Dependent variable without monotone interpolation for n=2"; Real y2Monotone "Dependent variable with monotone interpolation for n=2"; Real y1 "Dependent variable without monotone interpolation for n=1"; Real y1Monotone "Dependent variable with monotone interpolation for n=1"; algorithm x := xSup[1] + time*1.2*(xSup[size(xSup, 1)] - xSup[1]) - 0.5; // Extrapolate or interpolate the data y := Buildings.Utilities.Math.Functions.smoothInterpolation( x=x, xSup=xSup, ySup=ySup, ensureMonotonicity=false); yMonotone := Buildings.Utilities.Math.Functions.smoothInterpolation( x=x, xSup=xSup, ySup=ySup, ensureMonotonicity=true); // Case with n = 2 y2 := Buildings.Utilities.Math.Functions.smoothInterpolation( x=x, xSup=xSup[1:2], ySup=ySup[1:2], ensureMonotonicity=false); y2Monotone := Buildings.Utilities.Math.Functions.smoothInterpolation( x=x, xSup=xSup[1:2], ySup=ySup[1:2], ensureMonotonicity=true); // Case with n = 1 y1 := Buildings.Utilities.Math.Functions.smoothInterpolation( x=x, xSup={xSup[1]}, ySup={ySup[1]}, ensureMonotonicity=false); y1Monotone := Buildings.Utilities.Math.Functions.smoothInterpolation( x=x, xSup={xSup[1]}, ySup={ySup[1]}, ensureMonotonicity=true); end SmoothInterpolation;

Buildings.Utilities.Math.Functions.Examples.SpliceFunction

Information

This example checks whether the function derivative is implemented correctly. If the derivative implementation is not correct, the model will stop with an assert statement.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model SpliceFunction extends Modelica.Icons.Example; Real y "Function value"; equation y=Buildings.Utilities.Math.Functions.spliceFunction( pos=10, neg=-10, x=time-0.4, deltax=0.2); end SpliceFunction;

Buildings.Utilities.Math.Functions.Examples.SpliceFunctionDerivativeCheck

Information

This example checks whether the function derivative is implemented correctly. If the derivative implementation is not correct, the model will stop with an assert statement.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Parameters

Type	Name	Default	Description
Real	delta	0.2	Smoothing area

Modelica definition

model SpliceFunctionDerivativeCheck extends Modelica.Icons.Example; parameter Real delta = 0.2 "Smoothing area"; Real deltax "Smoothing area as a function of x"; Real x "Independent variable"; Real y "Approximate function value"; Real y_comp "Approximate function value"; Real err "Error"; Real d1y "First derivative"; Real d2y "Second derivative"; Real d3y "Third derivative"; initial equation y=y_comp; equation x = time^3; deltax=delta*10*time^8+0.1; // Because the derivative is implemented for all arguments, // we make pos, neg and deltax also functions of time y=Buildings.Utilities.Math.Functions.spliceFunction( pos=10*x^3, neg=-10*x^2, x=x, deltax=deltax); der(y)=der(y_comp); err = y-y_comp; assert(abs(err) < 1E-2, "Model has an error"); d1y = der(y); d2y = der(d1y); d3y = der(d2y); end SpliceFunctionDerivativeCheck;

Buildings.Utilities.Math.Functions.Examples.TrapezoidalIntegration

Tests the correct implementation of the function trapezoidalIntegration

Information

Tests the correct implementation of function Buildings.Utilities.Math.Functions.trapezoidalIntegration.

Integrands y1[7]={72, 70, 64, 54, 40, 22, 0} are the function values of y = -2*x^2-72 for x = {0,1,2,3,4,5,6}. The trapezoidal integration over the 7 integrand points should give a result of 286.

Extends from Modelica.Icons.Example (Icon for runnable examples).

Modelica definition

model TrapezoidalIntegration "Tests the correct implementation of the function trapezoidalIntegration" extends Modelica.Icons.Example; Real y1[7] = {72, 70, 64, 54, 40, 22, 0}; //function values of y = -2*x^2-72 for x={0,1,2,3,4,5,6} Real y "Integration result"; //Real y2[7] = {0.3333, 1.0, 3.0, 9.9, 27.0, 81.0, 243.0}; // //function values of y = 3^(3x-1) for x=0:0.3333:2 algorithm y := Buildings.Utilities.Math.Functions.trapezoidalIntegration(N=7, f=y1, deltaX=1); assert(y - 286.0 < 1E-4, "Error. Function should have returned 286."); end TrapezoidalIntegration;