logging in or signing up nexus Umberto Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 330 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: January 22, 2008 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript NEXUS Spacecraft Integrated Modeling and Simulation: NEXUS Spacecraft Integrated Modeling and Simulation Olivier L. de Weck July 2001 Sponsor: Gary E. Mosier, NASA GSFCBackground and Motivation : HST - 1990 NEXUS-2004 SIM-2006 NGST-2008 Deployable Cold Optics NGST Precursor Mission Faint Star Interferometer Precision Astrometry Lightweight 8m-Optics IR Deep Field Observations Space-Based Observatory Multipurpose UV/Visual/IR Imaging and Spectroscopy Science Requirements Functional Requirements Subsystem Requirements TPF-2011 5 year wide-angle astro- metric accuracy of 4 masec for 20th Magnitude stars Fringe Visibility > 0.8 for astrometry Science Interferometer OPD < 10 nm RMS Achieve stringent requirements in a cost-effective manner with predictable risk level. Nulling Interferometer Planet Detection Background and Motivation Requirements Flowdown Process “Performance”Nexus Case Study: Nexus Case Study on-orbit configuration OTA NGST Precursor Mission 2.8 m diameter aperture Mass: 752.5 kg Cost: 105.88 M$ (FY00) Target Orbit: L2 Sun/Earth Projected Launch: 2004 Demonstrate the usefulness of Isoperformance on a realistic conceptual design model of a high-performance spacecraft Instrument Module Sunshield Delta II Fairing launch configuration Integrated Modeling Nexus Block Diagram Baseline Performance Assessment Sensitivity Analysis Isoperformance Analysis (2) Multiobjective Optimization Error Budgeting Deployable PM petal Purpose of this case study: The following results are shown: Details are contained in CH7 Nexus Spacecraft Concept Pro/E models © NASA GSFCNexus Integrated Model: Nexus Integrated Model 8 m2 solar panel RWA and hex isolator (79-83) SM (202) sunshield 2 fixed PM petals deployable PM petal (129) SM spider (I/O Nodes) Design Parameters Instrument Spacecraft bus (84) t_sp I_ss Structural Model (FEM) (Nastran, IMOS) Legend: m_SM K_zpet m_bus K_rISO K_yPM Cassegrain Telescope: PM (2.8 m) PM f/# 1.25 SM (0.27 m) f/24 OTA (149,169) (207)Nexus Block Diagram: Nexus Block Diagram Number of performances: nz=2 Number of design parameters: np=25 Number of states ns= 320 Number of disturbance sources: nd=4Initial Performance Assessment Jz(po): Initial Performance Assessment Jz(po) Time [sec] Critical Mode 23.1 HzNexus Sensitivity Analysis: Nexus Sensitivity Analysis Graphical Representation of Jacobian evaluated at design po, normalized for comparison. RMMS WFE most sensitive to: Ru - upper op wheel speed [RPM] Sst - star track noise 1s [asec] K_rISO - isolator joint stiffness [Nm/rad] K_zpet - deploy petal stiffness [N/m] RSS LOS most sensitive to: Ud - dynamic wheel imbalance [gcm2] K_rISO - isolator joint stiffness [Nm/rad] zeta - proportional damping ratio [-] Mgs - guide star magnitude [mag] Kcf - FSM controller gain [-]2D-Isoperformance Analysis: 2D-Isoperformance Analysis Ud=mrd [gcm2] CAD Model K_rISO [Nm/rad] isolator strut joint E-wheelMultiobjective Design Optimization: Multiobjective Design Optimization Control effort Implementation Cost (mid-bound) System Mass Dissipated Power Closeness to “cheap” bound Cost Objectives Jc Risk Objectives Jr Since solutions piso in the isoperformance set I do not distinguish them- selves via their performance, we may satisfy additional objectives: Stability Margins (SISO) max SV of sensitivity function / mvar Nyquist Sensitivity of performance to parameter variations Knowledge Error Can scalarize NLP problem with preference order (weightings) h,Qcc,Qrr as shown on the left or can look for efficient set E of pareto-optimal solutions, piso*. Performance Jz(piso) =Jz,reqNexus Multivariable Isoperformance np=10: Nexus Multivariable Isoperformance np=10 Design A 20.0000 5.2013 0.6324 0.4668 +/- 14.3218 % Design B 20.0012 5.0253 0.8960 0.0017 +/- 8.7883 % Design C 20.0001 4.8559 1.5627 1.0000 +/- 5.3067 % Design A Design B Design C Best “mid-range” compromise Smallest FSM control gain Smallest performance uncertainty Pareto-Optimal Designs p*iso Jz,1 Jz,2 Jc,1 Jc,2 Jr,1 Performance Cost and Risk ObjectivesNexus Error Budgeting: Nexus Error Budgeting Isoperformance Toolbox Error Source Contributions LTI System , Jz,req, p_bounds, p_nom piso var_contr Allocated Budget Plot Error Contribution Sphere Capability Budget LOS Budget Capability (Design A) Note: ACS sensor noise contributions not shown 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 RWA Cryo FGS A Budget B CNexus Initial po vs. Final Design p**iso: Nexus Initial po vs. Final Design p**iso +X +Z +Y secondary hub SM Deployable segment SM Spider Support tsp Spider wall thickness Dsp Kzpet Initial Final Improvements are achieved by a well balanced mix of changes in the disturbance parameters, structural redesign and increase in control gain of the FSM fine pointing loop. Ru 3000 3845 [RPM] Us 1.8 1.45 [gcm] Ud 60 47.2 [gcm2] Qc 0.005 0.014 [-] Tgs 0.040 0.196 [sec] KrISO 3000 2546 [Nm/rad] Kzpet 0.9E+8 8.9E+8 [N/m] tsp 0.003 0.003 [m] Mgs 15 18.6 [Mag] Kcf 2E+3 4.7E+5 [-] -50 0 50 -50 -40 -30 -20 -10 0 10 20 30 40 50 Centroid X Centroid Y Centroid Jitter on Focal Plane [RSS LOS] T=5 sec Initial: 14.97 m m Final: 5.155 m m Parameters You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
nexus Umberto Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 330 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: January 22, 2008 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript NEXUS Spacecraft Integrated Modeling and Simulation: NEXUS Spacecraft Integrated Modeling and Simulation Olivier L. de Weck July 2001 Sponsor: Gary E. Mosier, NASA GSFCBackground and Motivation : HST - 1990 NEXUS-2004 SIM-2006 NGST-2008 Deployable Cold Optics NGST Precursor Mission Faint Star Interferometer Precision Astrometry Lightweight 8m-Optics IR Deep Field Observations Space-Based Observatory Multipurpose UV/Visual/IR Imaging and Spectroscopy Science Requirements Functional Requirements Subsystem Requirements TPF-2011 5 year wide-angle astro- metric accuracy of 4 masec for 20th Magnitude stars Fringe Visibility > 0.8 for astrometry Science Interferometer OPD < 10 nm RMS Achieve stringent requirements in a cost-effective manner with predictable risk level. Nulling Interferometer Planet Detection Background and Motivation Requirements Flowdown Process “Performance”Nexus Case Study: Nexus Case Study on-orbit configuration OTA NGST Precursor Mission 2.8 m diameter aperture Mass: 752.5 kg Cost: 105.88 M$ (FY00) Target Orbit: L2 Sun/Earth Projected Launch: 2004 Demonstrate the usefulness of Isoperformance on a realistic conceptual design model of a high-performance spacecraft Instrument Module Sunshield Delta II Fairing launch configuration Integrated Modeling Nexus Block Diagram Baseline Performance Assessment Sensitivity Analysis Isoperformance Analysis (2) Multiobjective Optimization Error Budgeting Deployable PM petal Purpose of this case study: The following results are shown: Details are contained in CH7 Nexus Spacecraft Concept Pro/E models © NASA GSFCNexus Integrated Model: Nexus Integrated Model 8 m2 solar panel RWA and hex isolator (79-83) SM (202) sunshield 2 fixed PM petals deployable PM petal (129) SM spider (I/O Nodes) Design Parameters Instrument Spacecraft bus (84) t_sp I_ss Structural Model (FEM) (Nastran, IMOS) Legend: m_SM K_zpet m_bus K_rISO K_yPM Cassegrain Telescope: PM (2.8 m) PM f/# 1.25 SM (0.27 m) f/24 OTA (149,169) (207)Nexus Block Diagram: Nexus Block Diagram Number of performances: nz=2 Number of design parameters: np=25 Number of states ns= 320 Number of disturbance sources: nd=4Initial Performance Assessment Jz(po): Initial Performance Assessment Jz(po) Time [sec] Critical Mode 23.1 HzNexus Sensitivity Analysis: Nexus Sensitivity Analysis Graphical Representation of Jacobian evaluated at design po, normalized for comparison. RMMS WFE most sensitive to: Ru - upper op wheel speed [RPM] Sst - star track noise 1s [asec] K_rISO - isolator joint stiffness [Nm/rad] K_zpet - deploy petal stiffness [N/m] RSS LOS most sensitive to: Ud - dynamic wheel imbalance [gcm2] K_rISO - isolator joint stiffness [Nm/rad] zeta - proportional damping ratio [-] Mgs - guide star magnitude [mag] Kcf - FSM controller gain [-]2D-Isoperformance Analysis: 2D-Isoperformance Analysis Ud=mrd [gcm2] CAD Model K_rISO [Nm/rad] isolator strut joint E-wheelMultiobjective Design Optimization: Multiobjective Design Optimization Control effort Implementation Cost (mid-bound) System Mass Dissipated Power Closeness to “cheap” bound Cost Objectives Jc Risk Objectives Jr Since solutions piso in the isoperformance set I do not distinguish them- selves via their performance, we may satisfy additional objectives: Stability Margins (SISO) max SV of sensitivity function / mvar Nyquist Sensitivity of performance to parameter variations Knowledge Error Can scalarize NLP problem with preference order (weightings) h,Qcc,Qrr as shown on the left or can look for efficient set E of pareto-optimal solutions, piso*. Performance Jz(piso) =Jz,reqNexus Multivariable Isoperformance np=10: Nexus Multivariable Isoperformance np=10 Design A 20.0000 5.2013 0.6324 0.4668 +/- 14.3218 % Design B 20.0012 5.0253 0.8960 0.0017 +/- 8.7883 % Design C 20.0001 4.8559 1.5627 1.0000 +/- 5.3067 % Design A Design B Design C Best “mid-range” compromise Smallest FSM control gain Smallest performance uncertainty Pareto-Optimal Designs p*iso Jz,1 Jz,2 Jc,1 Jc,2 Jr,1 Performance Cost and Risk ObjectivesNexus Error Budgeting: Nexus Error Budgeting Isoperformance Toolbox Error Source Contributions LTI System , Jz,req, p_bounds, p_nom piso var_contr Allocated Budget Plot Error Contribution Sphere Capability Budget LOS Budget Capability (Design A) Note: ACS sensor noise contributions not shown 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 RWA Cryo FGS A Budget B CNexus Initial po vs. Final Design p**iso: Nexus Initial po vs. Final Design p**iso +X +Z +Y secondary hub SM Deployable segment SM Spider Support tsp Spider wall thickness Dsp Kzpet Initial Final Improvements are achieved by a well balanced mix of changes in the disturbance parameters, structural redesign and increase in control gain of the FSM fine pointing loop. Ru 3000 3845 [RPM] Us 1.8 1.45 [gcm] Ud 60 47.2 [gcm2] Qc 0.005 0.014 [-] Tgs 0.040 0.196 [sec] KrISO 3000 2546 [Nm/rad] Kzpet 0.9E+8 8.9E+8 [N/m] tsp 0.003 0.003 [m] Mgs 15 18.6 [Mag] Kcf 2E+3 4.7E+5 [-] -50 0 50 -50 -40 -30 -20 -10 0 10 20 30 40 50 Centroid X Centroid Y Centroid Jitter on Focal Plane [RSS LOS] T=5 sec Initial: 14.97 m m Final: 5.155 m m Parameters