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CLVTOPS Liftoff and Separation Analysis Validation Using Ares I-X Flight Data

CLVTOPS is a multi-body time domain flight dynamics simulation tool developed by NASA s Marshall Space Flight Center (MSFC) for a space launch vehicle and is based on the TREETOPS simulation tool. CLVTOPS is currently used to simulate the flight dynamics and separation/jettison events of the Ares I launch vehicle including liftoff and staging separation. In order for CLVTOPS to become an accredited tool, validation against other independent simulations and real world data is needed. The launch of the Ares I-X vehicle (first Ares I test flight) on October 28, 2009 presented a great opportunity to provide validation evidence for CLVTOPS. In order to simulate the Ares I-X flight, specific models were implemented into CLVTOPS. These models include the flight day environment, reconstructed thrust, reconstructed mass properties, aerodynamics, and the Ares I-X guidance, navigation and control models. The resulting simulation output was compared to Ares I-X flight data. During the liftoff region of flight, trajectory states from the simulation and flight data were compared. The CLVTOPS results were used to make a semi-transparent animation of the vehicle that was overlaid directly on top of the flight video to provide a qualitative measure of the agreement between the simulation and the actual flight. During ascent, the trajectory states of the vehicle were compared with flight data. For the stage separation event, the trajectory states of the two stages were compared to available flight data. Since no quantitative rotational state data for the upper stage was available, the CLVTOPS results were used to make an animation of the two stages to show a side-by-side comparison with flight video. All of the comparisons between CLVTOPS and the flight data show good agreement. This paper documents comparisons between CLVTOPS and Ares I-X flight data which serve as validation evidence for the eventual accreditation of CLVTOPS.

Burger, Ben↗

The CLVTOPS Toolchain for NASA Space Launch System Liftoff Analysis and Post Flight Validation

This paper showcases the unique technical capabilities of the CLVTOPS multi-body flight dynamics toolchain developed by Marshall Space Flight Center (MSFC) for analyzing NASA’s Space Launch System (SLS) liftoff events. The CLVTOPS toolchain integrates high-fidelity simulations, geometric algorithms, advanced data analytics, and post-flight telemetry to demonstrate positive clearance between separating bodies and inform design decisions that enhance mission reliability. Proper liftoff separation is crucial to the success of the launch vehicle’s mission; vehicle impacts with the launch tower and supporting components incur a heightened risk of mission failure. For liftoff analysis, the CLVTOPS toolchain enables the integration of vehicle, launch pad, and environmental input models for the investigation of key clearance effectors. Furthermore, recent enhancements to the CLVTOPS toolchain allow for validation via photogrammetric trajectory reconstruction and plume pressure impingement estimation on the tower. The following sections will walk through the tool-chain, SLS liftoff ground rules and assumptions, key models, standard analysis, recent enhancements, and post-flight validation of the Artemis I mission liftoff event.

CLVTOPS↗

Space Launch System: CLVTOPS Toolchain for SLS Liftoff Separation Analysis

This presentation showcases the unique technical capabilities of the CLVTOPS multi-body flight dynamics tool chain developed by Marshall Space Flight Center (MSFC) for analyzing NASA’s Space Launch System (SLS) liftoff events. The CLVTOPS tool chain integrates high-fidelity simulations, geometric algorithms, advanced data analytics, and post-flight telemetry to demonstrate positive clearance between separating bodies and inform design decisions that enhance mission reliability. Proper liftoff separation is crucial to the success of the launch vehicle’s mission; vehicle impacts with the launch tower and supporting components incur a heightened risk of mission failure. For liftoff analysis, the CLVTOPS tool chain enables the integration of vehicle, launch pad, and environmental input models for the investigation of key clearance effectors. Furthermore, a novel capability of the CLVTOPS tool chain allows for verification and validation of trajectory reconstruction via photogrammetric imagery analysis. The following sections will walk through the tool chain, SLS liftoff ground rules and assumptions, model integration, pre-flight verification, and post-flight validation of the Artemis I mission liftoff event.

CLVTOPS↗

Mars Sample Return Mars Ascent Vehicle Separation Analysis Utilizing the CLVTOPS Toolchain

A key element of the joint NASA and European Space Agency (ESA) Mars Sample Return (MSR) Campaign is the Mars Ascent Vehicle (MAV), which is being developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA’s Jet Propulsion Laboratory (JPL) and Langley Research Center (LaRC). The MAV is a Mars-launched rocket that is responsible for transporting soil samples collected by the Perseverance rover from the Martian surface into orbit, where they will be captured by ESA's Earth Return Orbiter (ERO) for the return journey to Earth. The MAV design concept developed during the MAV Systems Requirement Cycle (SRC) and Preliminary Design Cycle (PDC) consisted of a two-solid-stage configuration, where the second stage is completely unguided in order to reduce vehicle and overall mission mass. The unguided second stage design presents technical challenges for the stage separation event, as the second stage trajectory and the payload’s ability to rendezvous with the ERO is extremely sensitive to disturbances during vehicle staging. The MSFC-developed CLVTOPS multibody dynamics toolchain was utilized to quickly assess multiple stage separation hardware options and to optimize the separation Concept of Operations (ConOps) in order to ensure successful near-field stage separation performance and maximize the orbital accuracy of the payload. This paper will describe how the CLVTOPS toolchain was used to assess the MAV stage separation event and help inform and optimize the MAV design and ConOps.

MSR↗

Space Launch System Block-1b USA Separation Analysis and Requirements Derivation From CLVTOPS Toolchain

Ensuring that rocket stage separation events provide positive clearance is critical to avoid loss of mission or crew. NASA's Marshall Space Flight Center (MSFC) has developed a cutting-edge toolchain to address this type of problem and it was used to set abstracted impulse requirements on, and to analyze the results of, the in-space separation event of the Universal Stage Adapter (USA) and the Exploration Upper Stage (EUS) of NASA's Space Launch System (SLS) Block-1B configuration. The toolchain is used as a hardware simulation to confirm positive body-to-body clearance during the separation event. It is also used to create a requirements-space simulation, which helps inform requirements as the hardware design matures.

Zachary T Muscha↗

SLS Block-1B USA Separation Analysis and Requirements Evaluation Using the CLVTOPS Toolchain

Ensuring that rocket stage separation events provide positive clearance is critical to avoid loss of mission or crew. NASA's Marshall Space Flight Center (MSFC) has developed a cutting-edge toolchain to address this type of problem and it was used to set abstracted impulse requirements on, and to analyze the results of, the in-space separation event of the Universal Stage Adapter (USA) and the Exploration Upper Stage (EUS) of NASA's Space Launch System (SLS) Block-1B configuration. The toolchain is used as a hardware simulation to confirm positive body-to-body clearance during the separation event. It is also used to create a requirements-space simulation, which helps inform requirements as the hardware design matures.

Zach Muscha↗

Near-Field Separation and Dynamics Analysis of NASA's Space Launch System Block-1 and Block-1B Secondary Payloads

The NASA Space Launch System (SLS) Program Block-1 and Block-1B missions are expected to carry a number of CubeSat secondary payloads (SPL) to space, where they will be ejected from internal SLS structures to begin their own missions. This near-field ejection process must be closely evaluated to ensure that no SPL contacts the SLS structures, as contacts could result in SPL component damage, mission loss, or aberrant SPL trajectories. To this end, multiple SPL ejection events were analyzed for both Block-1 and Block-1B mission configurations using CLVTOPS, a NASA Marshall Space Flight Center (MSFC) developed multi-body dynamics, proximity analysis, and visualization toolchain. This paper details the SPL-to-SLS clearance assessment process, with a focus on simulation setup and results as well as SPL design requirement analysis. Relevant CLVTOPS, statistics, and mission backgrounds are covered; important constraints, difficulties, and assumptions are also documented. Furthermore, the importance of SPL housing geometry on near-field vehicle clearance is highlighted, and examples are shown.

Jared T Rucker↗

Dynamics and Clearance Analysis of NASA's Space Launch System Block-1 and Block 1B Solid Rocket Booster Separation Event

NASA’s Space Launch System (SLS) solid rocket booster separation event is an essential area of study requiring high fidelity modelling to capture the complexity of an intra-atmospheric stage separation event. The setup and analysis for this event leveraged the NASA-developed CLVTOPS multi-body dynamics toolchain to model aerodynamics at the separation event, booster thrust tailoff, and Core Stage engine throttling in addition to the separation system itself (booster separation motors (BSMs), pyrotechnic bolts and struts). The approach documented here will give a brief background on the CLVTOPS toolchain, how key input models are integrated and verified, and how results are quantified using an ordered-statistics approach. Specific areas discussed herein address the performance-to-orbit realized by adjusting the delay time between the separation cue and the actual separation event, and how the orientation of the aft BSMs was tuned to address small clearances between the aft diagonal attach struts and the Core Stage. Post-flight results from the inaugural Artemis I flight are also shown, and validation is performed between predicted vs. actual separation dynamics and clearances. Challenging night launch conditions necessitated comparisons that were more qualitative in nature, but still showed very good agreement to pre-flight predictions.

Carole J Addona↗

Near-Field Separation Analysis of SLS Block-1 and Block-1B Secondary Payloads

The NASA Space Launch System (SLS) Program Block-1 and Block-1B missions are expected to carry a number of CubeSat secondary payloads (SPL) to space, where they will be ejected from internal SLS structures to begin their own missions. This near-field ejection process must be closely evaluated to ensure that no SPL contacts the SLS structures, as contacts could result in SPL component damage, mission loss, or aberrant SPL trajectories. To this end, multiple SPL ejection events were analyzed for both Block-1 and Block-1B mission configurations using CLVTOPS, a NASA Marshall Space Flight Center (MSFC) developed multi-body dynamics, proximity analysis, and visualization toolchain. This paper details the SPL-to-SLS clearance assessment process, with a focus on simulation setup and results as well as SPL design requirement analysis. Relevant CLVTOPS, statistics, and mission backgrounds are covered; important constraints, difficulties, and assumptions are also documented. Furthermore, the importance of SPL housing geometry on near-field vehicle clearance is highlighted, and examples are shown.

Jared Rucker↗

Space Launch System Liftoff and Separation Dynamics Analysis Tool Chain

A flexible, hierarchical tool chain that is being applied to NASA’s Space Launch System (SLS) for critical dynamics phenomena is described. This tool chain, called CLVTOPS, is used to investigate lateral liftoff movement of the vehicle as it departs and clears the mobile launch tower and separation of the two solid rocket boosters without collision with the core stage and payload. The toolset’s architecture was configured to take advantage of a modern software-engineering approach for maximum flexibility and utilization of open-source simulations and associated tools. As opposed to a “monolithic” approach, scripting languages were used to “bind” together a tool chain to configure and organize input data, execute and produce analysis results, and post-process these results to facilitate a rapid iterative analysis process to quickly address issues and pursue alternatives with emphasis on analysis automation. Key capabilities in the tool chain include processing and mining of very large data sets, a wide range of graphical depictions, and high-fidelity, physics-based simulations. The paper begins with a problem description and the motivation for liftoff and separation dynamics analysis followed by a historical survey of dynamics analyses for previous NASA human-rated launch vehicles. Details of the tool chain and its components are then introduced divided, first, into description of the scripting language architecture used to “bind” the simulation tools, programs, and scripts together and, second, the physics models and simulations. Representative analyses and data products are shown for liftoff and booster separation dynamics that provide in-depth insight to the tool chain’s capabilities. Supporting activities such as simulation tool chain verification, version archiving and data management, and training are addressed. The paper concludes with case examples on how the tool chain can be tailored to related aerospace dynamics analyses, both large and small. These patterns and techniques for SLS dynamics tool construction can be applied for other aerospace simulations.

6DOF↗

Space Launch System Liftoff and Separation Dynamics Analysis Tool Chain

A flexible, hierarchical tool chain that is being applied to NASA’s Space Launch System (SLS) for critical dynamics phenomena is described. This tool chain, called CLVTOPS, is used to investigate lateral liftoff movement of the vehicle as it departs and clears the mobile launch tower and separation of the two solid rocket boosters without collision with the core stage and payload. The toolset’s architecture was configured to take advantage of a modern software engineering approach for maximum flexibility and utilization of open-source simulations and associated tools. As opposed to a “monolithic” approach, scripting languages were used to “bind” together a tool chain to configure and organize input data, execute and produce analysis results, and post-process these results to facilitate a rapid, iterative analysis process to quickly address issues and pursue alternatives with emphasis on analysis automation. Key capabilities in the tool chain include processing and mining of very large data sets, a wide range of graphical depictions, and high-fidelity, physics-based simulations. The paper begins with a problem description and the motivation for liftoff and separation dynamics analysis followed by a historical survey of dynamics analyses for previous NASA human-rated launch vehicles. Details of the tool chain and its components are then introduced and divided, first, into description of the scripting language architecture used to “bind” the simulation tools, programs, and scripts together and, second, the physics models and simulations. Representative analyses and data products for liftoff and booster separation dynamics are shown in order to provide in-depth insight into the tool chain’s capabilities. Supporting activities such as simulation tool chain verification, version archiving and data management, and training are addressed. The paper concludes with case examples on how the tool chain can be tailored to related aerospace dynamics analyses, both large and small. The flexibility and versatility of this tool chain in supporting analyses of such a diverse range of aerospace applications demonstrates the feasibility of applying these patterns and techniques for tool construction to other aerospace simulations.

6DOF↗

Time and Frequency-Domain Cross-Verification of SLS 6DOF Trajectory Simulations

The SLS GNC team and its partners have developed several time- and frequency-based simulations for development and analysis of the proposed SLS launch vehicle. The simulations differ in fidelity and some have unique functionality that allows them to perform specific analyses. Some examples of the purposes of the various models are: trajectory simulation, multi-body separation, Monte Carlo, hardware in the loop, loads, and frequency domain stability analyses. While no two simulations are identical, many of the models are essentially six degree-of-freedom (6DOF) representations of the SLS plant dynamics, hardware implementation, and flight software. Thus at a high level all of those models should be in agreement. Comparison of outputs from several SLS trajectory and stability analysis tools are ongoing as part of the program's current verification effort. The purpose of these comparisons is to highlight modeling and analysis differences, verify simulation data sources, identify inconsistencies and minor errors, and ultimately to verify output data as being a good representation of the vehicle and subsystem dynamics. This paper will show selected verification work in both the time and frequency domain from the current design analysis cycle of the SLS for several of the design and analysis simulations. In the time domain, the tools that will be compared are MAVERIC, CLVTOPS, SAVANT, STARS, ARTEMIS, and POST 2. For the frequency domain analysis, the tools to be compared are FRACTAL, SAVANT, and STARS. The paper will include discussion of these tools including their capabilities, configurations, and the uses to which they are put in the SLS program. Determination of the criteria by which the simulations are compared (matching criteria) requires thoughtful consideration, and there are several pitfalls that may occur that can severely punish a simulation if not considered carefully. The paper will discuss these considerations and will present a framework for responding to these issues when they arise. For example, small event timing differences can lead to large differences in mass properties if the criteria are to measure those properties at the same time, or large differences in altitude if the criteria are to measure those properties when the simulation experiences a staging event. Similarly, a tiny difference in phase can lead to large gain margin differences for frequency-domain comparisons of gain margins.

VanZwieten, Tannen↗

Time and Frequency-Domain Cross-Verification of SLS 6DOF Trajectory Simulations

The Space Launch System (SLS) Guidance, Navigation, and Control (GNC) team and its partners have developed several time- and frequency-based simulations for development and analysis of the proposed SLS launch vehicle. The simulations differ in fidelity and some have unique functionality that allows them to perform specific analyses. Some examples of the purposes of the various models are: trajectory simulation, multi-body separation, Monte Carlo, hardware in the loop, loads, and frequency domain stability analyses. While no two simulations are identical, many of the models are essentially six degree-of-freedom (6DOF) representations of the SLS plant dynamics, hardware implementation, and flight software. Thus at a high level all of those models should be in agreement. Comparison of outputs from several SLS trajectory and stability analysis tools are ongoing as part of the program's current verification effort. The purpose of these comparisons is to highlight modeling and analysis differences, verify simulation data sources, identify inconsistencies and minor errors, and ultimately to verify output data as being a good representation of the vehicle and subsystem dynamics. This paper will show selected verification work in both the time and frequency domain from the current design analysis cycle of the SLS for several of the design and analysis simulations. In the time domain, the tools that will be compared are MAVERIC, CLVTOPS, SAVANT, STARS, ARTEMIS, and POST 2. For the frequency domain analysis, the tools to be compared are FRACTAL, SAVANT, and STARS. The paper will include discussion of these tools including their capabilities, configurations, and the uses to which they are put in the SLS program. Determination of the criteria by which the simulations are compared (matching criteria) requires thoughtful consideration, and there are several pitfalls that may occur that can severely punish a simulation if not considered carefully. The paper will discuss these considerations and will present a framework for responding to these issues when they arise. For example, small event timing differences can lead to large differences in mass properties if the criteria are to measure those properties at the same time, or large differences in altitude if the criteria are to measure those properties when the simulation experiences a staging event. Similarly, a tiny difference in phase can lead to large gain margin differences for frequency-domain comparisons of gain margins.

Johnson, Matthew↗