Configure prescribed motion effector for select effector branching

docs/source/Support/bskReleaseNotes.rst

@@ -74,6 +74,12 @@ Version |release|
   The new option is useful when the user wants to ensure that the simulation runs for at least the specified time,
   instead of at most the specified time.
 - Fixed documentation quote typos that caused documentation build errors with doxygen version 1.15 and newer.
+- Configured the :ref:`prescribedMotionStateEffector` module for attachment of other state effectors to it
+  rather than the spacecraft hub.
+- Configured the :ref:`spinningBodyOneDOFStateEffector`, :ref:`spinningBodyTwoDOFStateEffector`, and
+  :ref:`linearTranslationOneDOFStateEffector` modules for optional attachment to the prescribed motion state effector.
+- Added two example branching scenarios to illustrate the prescribed motion branching capability. See
+  :ref:`scenarioPrescribedMotionWithTranslationBranching` and :ref:`scenarioPrescribedMotionWithRotationBranching`.
 
 
 Version 2.8.0 (August 30, 2025)

examples/_default.rst

@@ -244,6 +244,15 @@ Complex Spacecraft Dynamics Simulations
    Robotic Arm Effector with Profiler <scenarioRoboticArm>
    Spacecraft with an multi-link extending component <scenarioExtendingBoom>
 
+Multi-Body Dynamics Simulations with Prescribed Motion Branching
+----------------------------------------------------------------
+
+.. toctree::
+   :maxdepth: 1
+
+   Prescribed Motion with Translating Effector Branching <scenarioPrescribedMotionWithTranslationBranching>
+   Prescribed Motion with Rotating Effector Branching <scenarioPrescribedMotionWithRotationBranching>
+
 Mission Simulations
 ---------------------------------------
 

examples/scenarioDeployingSolarArrays.py

@@ -252,36 +252,32 @@ def run(show_plots):
         array2ElementList.append(prescribedMotionStateEffector.PrescribedMotionStateEffector())
         array1ElementList[i].ModelTag = "array1Element" + str(i + 1)
         array2ElementList[i].ModelTag = "array2Element" + str(i + 1)
-        array1ElementList[i].mass = mass_element  # [kg]
-        array2ElementList[i].mass = mass_element  # [kg]
-        array1ElementList[i].IPntPc_P = IElement_PntPc_P  # [kg m^2]
-        array2ElementList[i].IPntPc_P = IElement_PntPc_P  # [kg m^2]
-        array1ElementList[i].r_MB_B = r_M1B_B  # [m]
-        array2ElementList[i].r_MB_B = r_M2B_B  # [m]
-        array1ElementList[i].r_PcP_P = [- radius_array * np.cos(72 * macros.D2R),
+        array1ElementList[i].setMass(mass_element)  # [kg]
+        array2ElementList[i].setMass(mass_element)  # [kg]
+        array1ElementList[i].setIPntPc_P(IElement_PntPc_P)  # [kg m^2]
+        array2ElementList[i].setIPntPc_P(IElement_PntPc_P)  # [kg m^2]
+        array1ElementList[i].setR_MB_B(r_M1B_B)  # [m]
+        array2ElementList[i].setR_MB_B(r_M2B_B)  # [m]
+        array1ElementList[i].setR_PcP_P([- radius_array * np.cos(72 * macros.D2R),
                                         0.0,
-                                        (1/3) * radius_array * np.sin(72 * macros.D2R)]  # [m] For triangular wedge
-        array2ElementList[i].r_PcP_P = [radius_array * np.cos(72 * macros.D2R),
+                                        (1/3) * radius_array * np.sin(72 * macros.D2R)])  # [m] For triangular wedge
+        array2ElementList[i].setR_PcP_P([radius_array * np.cos(72 * macros.D2R),
                                         0.0,
-                                        (1/3) * radius_array * np.sin(72 * macros.D2R)]  # [m] For triangular wedge
-        array1ElementList[i].r_PM_M = r_PM1_M1Init1  # [m]
-        array2ElementList[i].r_PM_M = r_PM2_M2Init1  # [m]
-        array1ElementList[i].rPrime_PM_M = np.array([0.0, 0.0, 0.0])  # [m/s]
-        array2ElementList[i].rPrime_PM_M = np.array([0.0, 0.0, 0.0])  # [m/s]
-        array1ElementList[i].rPrimePrime_PM_M = np.array([0.0, 0.0, 0.0])  # [m/s^2]
-        array2ElementList[i].rPrimePrime_PM_M = np.array([0.0, 0.0, 0.0])  # [m/s^2]
-        array1ElementList[i].omega_PM_P = np.array([0.0, 0.0, 0.0])  # [rad/s]
-        array2ElementList[i].omega_PM_P = np.array([0.0, 0.0, 0.0])  # [rad/s]
-        array1ElementList[i].omegaPrime_PM_P = np.array([0.0, 0.0, 0.0])  # [rad/s^2]
-        array2ElementList[i].omegaPrime_PM_P = np.array([0.0, 0.0, 0.0])  # [rad/s^2]
-        array1ElementList[i].sigma_PM = sigma_PM1Init1
-        array2ElementList[i].sigma_PM = sigma_PM2Init1
-        array1ElementList[i].omega_MB_B = [0.0, 0.0, 0.0]  # [rad/s]
-        array2ElementList[i].omega_MB_B = [0.0, 0.0, 0.0]  # [rad/s]
-        array1ElementList[i].omegaPrime_MB_B = [0.0, 0.0, 0.0]  # [rad/s^2]
-        array2ElementList[i].omegaPrime_MB_B = [0.0, 0.0, 0.0]  # [rad/s^2]
-        array1ElementList[i].sigma_MB = [0.0, 0.0, 0.0]
-        array2ElementList[i].sigma_MB = [0.0, 0.0, 0.0]
+                                        (1/3) * radius_array * np.sin(72 * macros.D2R)])  # [m] For triangular wedge
+        array1ElementList[i].setR_PM_M(r_PM1_M1Init1)  # [m]
+        array2ElementList[i].setR_PM_M(r_PM2_M2Init1)  # [m]
+        array1ElementList[i].setRPrime_PM_M(np.array([0.0, 0.0, 0.0]))  # [m/s]
+        array2ElementList[i].setRPrime_PM_M(np.array([0.0, 0.0, 0.0]))  # [m/s]
+        array1ElementList[i].setRPrimePrime_PM_M(np.array([0.0, 0.0, 0.0]))  # [m/s^2]
+        array2ElementList[i].setRPrimePrime_PM_M(np.array([0.0, 0.0, 0.0]))  # [m/s^2]
+        array1ElementList[i].setOmega_PM_P(np.array([0.0, 0.0, 0.0]))  # [rad/s]
+        array2ElementList[i].setOmega_PM_P(np.array([0.0, 0.0, 0.0]))  # [rad/s]
+        array1ElementList[i].setOmegaPrime_PM_P(np.array([0.0, 0.0, 0.0]))  # [rad/s^2]
+        array2ElementList[i].setOmegaPrime_PM_P(np.array([0.0, 0.0, 0.0]))  # [rad/s^2]
+        array1ElementList[i].setSigma_PM(sigma_PM1Init1)
+        array2ElementList[i].setSigma_PM(sigma_PM2Init1)
+        array1ElementList[i].setSigma_MB([0.0, 0.0, 0.0])
+        array2ElementList[i].setSigma_MB([0.0, 0.0, 0.0])
 
         scObject.addStateEffector(array1ElementList[i])
         scObject.addStateEffector(array2ElementList[i])
@@ -463,9 +459,9 @@ def run(show_plots):
     array1ElementRefMsgList2 = list()
     for i in range(num_elements):
         array1ElementList[i].prescribedTranslationInMsg.subscribeTo(array1ElementTranslationMessage)
-        array1ElementList[i].r_PcP_P = [0.0, 0.0, - (2/3) * radius_array * np.sin(72 * macros.D2R)]
-        array1ElementList[i].r_PM_M = r_PM1_M1Init2  # [m]
-        array1ElementList[i].sigma_PM = sigma_PM1Init2
+        array1ElementList[i].setR_PcP_P([0.0, 0.0, - (2/3) * radius_array * np.sin(72 * macros.D2R)])
+        array1ElementList[i].setR_PM_M(r_PM1_M1Init2)  # [m]
+        array1ElementList[i].setSigma_PM(sigma_PM1Init2)
 
         array1RotProfilerList[i].setThetaInit(array1ThetaInit2)  # [rad]
         array1RotProfilerList[i].setThetaDDotMax(array1MaxRotAccelList2[i])  # [rad/s^2]
@@ -527,9 +523,9 @@ def run(show_plots):
     array2ElementRefMsgList3 = list()
     for i in range(num_elements):
         array2ElementList[i].prescribedTranslationInMsg.subscribeTo(array2ElementTranslationMessage)
-        array2ElementList[i].r_PcP_P = [0.0, 0.0, - (2/3) * radius_array * np.sin(72 * macros.D2R)]
-        array2ElementList[i].r_PM_M = r_PM2_M2Init2  # [m]
-        array2ElementList[i].sigma_PM = sigma_PM2Init2
+        array2ElementList[i].setR_PcP_P([0.0, 0.0, - (2/3) * radius_array * np.sin(72 * macros.D2R)])
+        array2ElementList[i].setR_PM_M(r_PM2_M2Init2)  # [m]
+        array2ElementList[i].setSigma_PM(sigma_PM2Init2)
 
         array2RotProfilerList[i].setThetaInit(array2ThetaInit2)  # [rad]
         array2RotProfilerList[i].setThetaDDotMax(array2MaxRotAccelList3[i])  # [rad/s^2]