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At least 19 records

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗

Operational Modal Analysis of the Space Launch System Mobile Launcher on the Crawler Transporter ISVV-010 Rollout

NASA is developing an expendable heavy lift launch vehicle capability, the Space Launch System, to support lunar and deep space exploration. To support this capability, an updated ground infrastructure is required including modifying an existing Mobile Launcher system. The Mobile Launcher is a very large heavy beam/truss steel structure designed to support the Space Launch System during its buildup and integration in the Vehicle Assembly Building, transportation between the Vehicle Assembly Building and launch pad 39B by the Crawler Transporter, and provides the launch platform at the launch pad. As part of the Verification and Validation of the Mobile Launcher and Crawler Transporter, two rollouts of the Mobile Launcher transported by the Crawler Transporter, Integrated System Verification and Validation (ISVV) 005 and 010, have been performed to demonstrate the Crawler Transporter’s ability to transport the Mobile Launcher. ISVV-005 occurred in September 2018 and ISVV-010 occurred in late June 2019. ISVV-005 and ISVV-010 also provided the opportunity to gather data that can be used identify the Mobile Launcher on the Crawler Transporter rollout modal characteristics and refine the estimates of the Artemis I integrated launch vehicle rollout forcing functions. While the rollout environment has historically produced relatively small launch vehicle structural loads for the Saturn/Apollo and Space Shuttle programs in comparison to launch and ascent loads, these relatively small structural loads are inputs to structural fatigue analyses. The same holds true for the Space Launch System. Because the rollout forces acting on the Mobile Launcher and the Crawler Transporter are not directly measurable, Operational Modal Analysis techniques, instead of traditional Experimental Modal Analysis techniques, provide an empirical means to identify the Mobile Launcher on the Crawler Transporter rollout modal characteristics. The ISVV-010 rollout modal characteristics provide important supplemental modal information, which along with the Mobile Launcher modal test that was performed in June 2019 immediately prior to ISVV-010 rollout, combine to reduce uncertainty in the test correlated Mobile Launcher on the Crawler Transporter finite element model. A well test correlated finite element model will play a key role in the Building Block approach the Space Launch System program has implemented as part of its certification process for the Artemis I flight and in refining the Artemis I rollout forcing functions. At the time of the ISVV-005 rollout in September 2018, the Mobile Launcher was still undergoing construction, and therefore its modal characteristics are not directly comparable to those of the Mobile Launcher during the June 2019 Mobile Launcher modal test and subsequent ISVV-010 rollout. Hence the ISVV-005 rollout modal characteristics will not be looked at in this paper. This paper will briefly describe the Mobile Launcher and Crawler Transporter physical characteristics, ISVV-010 rollout data collection, the challenges in implementing Operational Modal Analysis techniques due in part to the Crawler Transporter harmonics, and how these challenges were overcome to obtain the ISVV-010 Mobile Launcher on the Crawler Transporter rollout modal characteristics.

Apollo↗

Operational Modal Analysis of the Space Launch System Mobile Launcher on the Crawler Transporter ISVV-010 Rollout

NASA is developing an expendable heavy lift launch vehicle capability, the Space Launch System, to support lunar and deep space exploration. To support this capability, an updated ground infrastructure is required including modifying an existing Mobile Launcher system. The Mobile Launcher is a very large heavy beam/truss steel structure designed to support the Space Launch System during its buildup and integration in the Vehicle Assembly Building, transportation between the Vehicle Assembly Building and launch pad 39B by the Crawler Transporter, and provides the launch platform at the launch pad. As part of the Verification and Validation of the Mobile Launcher and Crawler Transporter, two rollouts of the Mobile Launcher transported by the Crawler Transporter, Integrated System Verification and Validation (ISVV) 005 and 010, have been performed to demonstrate the Crawler Transporter’s ability to transport the Mobile Launcher. ISVV-005 occurred in September 2018 and ISVV-010 occurred in late June 2019. ISVV-005 and ISVV-010 also provided the opportunity to gather data that can be used identify the Mobile Launcher on the Crawler Transporter rollout modal characteristics and refine the estimates of the Artemis I integrated launch vehicle rollout forcing functions. While the rollout environment has historically produced relatively small launch vehicle structural loads for the Saturn/Apollo and Space Shuttle programs in comparison to launch and ascent loads, these relatively small structural loads are inputs to structural fatigue analyses. The same holds true for the Space Launch System. Because the rollout forces acting on the Mobile Launcher and the Crawler Transporter are not directly measurable, Operational Modal Analysis techniques, instead of traditional Experimental Modal Analysis techniques, provide an empirical means to identify the Mobile Launcher on the Crawler Transporter rollout modal characteristics. The ISVV-010 rollout modal characteristics provide important supplemental modal information, which along with the Mobile Launcher modal test that was performed in June 2019 immediately prior to ISVV-010 rollout, combine to reduce uncertainty in the test correlated Mobile Launcher on the Crawler Transporter finite element model. A well test correlated finite element model will play a key role in the Building Block approach the Space Launch System program has implemented as part of its certification process for the Artemis I flight and in refining the Artemis I rollout forcing functions. At the time of the ISVV-005 rollout in September 2018, the Mobile Launcher was still undergoing construction, and therefore its modal characteristics are not directly comparable to those of the Mobile Launcher during the June 2019 Mobile Launcher modal test and subsequent ISVV-010 rollout. Hence the ISVV-005 rollout modal characteristics will not be looked at in this paper. This paper will briefly describe the Mobile Launcher and Crawler Transporter physical characteristics, ISVV-010 rollout data collection, the challenges in implementing Operational Modal Analysis techniques due in part to the Crawler Transporter harmonics, and how these challenges were overcome to obtain the ISVV-010 Mobile Launcher on the Crawler Transporter rollout modal characteristics.

Apollo↗

Operational Modal Analysis of the Artemis I Dynamic Rollout Test and Wet Dress Rehearsal

NASA has developed an expendable heavy lift launch vehicle capability, the Space Launch System (SLS), to support lunar and deep space exploration. The uncrewed Artemis I was the first flight of this new launch vehicle and tested critical systems for the upcoming crewed Artemis II flight to the moon. Accelerations were recorded at a multitude of locations on Artemis, the Mobile Launcher (ML), and the Crawler Transporter (CT)during the rollout of Artemis I from the Vehicle Assembly Building (VAB) to Launch Pad 39B March 2022 and is referred to as the Artemis I Dynamic Rollout Test (DRT). While Artemis I was at Launch Pad 39B, the Wet Dress Rehearsal (WDR) was performed to demonstrate launch readiness and acceleration measurements were also recorded. Finally, Artemis I rolled back from Launch Pad 39B to the VAB in April 2022, where acceleration measurements were also recorded and is referred to as the rollback portion of DRT. Because the forces during rollout and at the launch pad acting on Artemis I, the ML, and the CT are not directly measurable, Operational Modal Analysis (OMA) techniques, instead of traditional Experimental Modal Analysis (EMA) techniques, were used to identify modal characteristics. The OMA analysis of DRT and WDR directly builds upon the lessons learned from the OMA analysis of an earlier rollout of the ML from the VAB. DRT and WDR dynamic characteristics will be used to support SLS Integrated Modal Test finite element model correlation efforts and Exploration Ground System ML and CT finite element model verification and validation, which are part of the Building Block approach the Space Launch System program has implemented. The dynamic characteristics extracted from DRT as well as the rollout acceleration time histories themselves will be used in the development of generic rollout forcing functions that will provide refined estimates of the Artemis IV rollout forces, which will have the heavier and larger SLS Block 1B launch vehicle and Mobile Launcher 2 (ML-2). This paper briefly describes Artemis I, the ML, and the CT physical characteristics, DRT rollout/rollback and WDR data collection, the challenges in implementing OMA techniques due in part to the CT harmonics, and how these challenges were overcome to obtain the Artemis I DRT configuration and WDR configuration modal characteristics.

Apollo↗

Operational Modal Analysis of the Artemis I Dynamic Rollout Test and Wet Dress Rehearsal

NASA has developed an expendable heavy lift launch vehicle capability, the Space Launch System (SLS), to support lunar and deep space exploration. The uncrewed Artemis I was the first flight of this new launch vehicle and tested critical systems for the upcoming crewed Artemis II flight to the moon. Accelerations were recorded at a multitude of locations on Artemis, the Mobile Launcher (ML), and the Crawler Transporter (CT)during the rollout of Artemis I from the Vehicle Assembly Building (VAB) to Launch Pad 39B March 2022 and is referred to as the Artemis I Dynamic Rollout Test (DRT). While Artemis I was at Launch Pad 39B, the Wet Dress Rehearsal (WDR) was performed to demonstrate launch readiness and acceleration measurements were also recorded. Finally, Artemis I rolled back from Launch Pad 39B to the VAB in April 2022, where acceleration measurements were also recorded and is referred to as the rollback portion of DRT. Because the forces during rollout and at the launch pad acting on Artemis I, the ML, and the CT are not directly measurable, Operational Modal Analysis (OMA) techniques, instead of traditional Experimental Modal Analysis (EMA) techniques, were used to identify modal characteristics. The OMA analysis of DRT and WDR directly builds upon the lessons learned from the OMA analysis of an earlier rollout of the ML from the VAB. DRT and WDR dynamic characteristics will be used to support SLS Integrated Modal Test finite element model correlation efforts and Exploration Ground System ML and CT finite element model verification and validation, which are part of the Building Block approach the Space Launch System program has implemented. The dynamic characteristics extracted from DRT as well as the rollout acceleration time histories themselves will be used in the development of generic rollout forcing functions that will provide refined estimates of the Artemis IV rollout forces, which will have the heavier and larger SLS Block 1B launch vehicle and Mobile Launcher 2 (ML-2). This paper briefly describes Artemis I, the ML, and the CT physical characteristics, DRT rollout/rollback and WDR data collection, the challenges in implementing OMA techniques due in part to the CT harmonics, and how these challenges were overcome to obtain the Artemis I DRT configuration and WDR configuration modal characteristics.

Apollo↗

Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data

Chatter, a self-excited vibration phenomenon, is a critical challenge in high-speed machining operations, affecting tool life, product surface quality, and overall process efficiency. While machine learning models trained on simulated data have shown promise in detecting chatter, their real-world applicability remains uncertain due to discrepancies between simulated and actual machining environments. The primary goal of this study is to bridge the gap between simulation-based machine learning models and real-world applications by developing and validating a Random Forest-based chatter detection system. This research focuses on improving manufacturing efficiency through reliable chatter detection by integrating Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL). The study applies a Random Forest classification model trained on over 140,000 simulated machining datasets, incorporating techniques like Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL) to adapt the model for real-world operational data. The model is validated against 1600 real-world machining datasets, achieving an accuracy of 86.1%, with strong precision and recall scores. The results demonstrate the model’s robustness and potential for practical implementation in industrial settings, highlighting challenges such as sensor noise and variability in machining conditions. This work advances the use of predictive analytics in machining processes, offering a data-driven solution to improve manufacturing efficiency through more reliable chatter detection.

42 ENGINEERING↗

Ares I-X In-Flight Modal Identification

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Bartkowicz, Theodore J.↗

Feasibility Study of SDAS Instrumentation's Ability to Identify Mobile Launcher (ML)/Crawler-Transporter (CT) Modes During Rollout Operations

The Space Launch System (SLS) and its Mobile Launcher (ML) will be transported to the launch pad via the Crawler-Transporter (CT) system. Rollout (i.e., transportation) loads produce structural loads on the integrated SLS/Orion Multi-Purpose Crew Vehicle (MPCV) launch vehicle which are of a concern with respect to fatigue. As part of the risk reduction process and in addition to the modal building block test approach that has been adopted by the SLS Program, acceleration data will be obtained during rollout for use in modal parameter estimation. There are several occurrences where the ML/CT will be transported either into the Vertical Assembly Building (VAB) or to the launch pad and back without the SLS stack as part of the Kennedy Space Center (KSC) Exploration Ground Systems (EGS) Integrated Test and Checkout (ITCO). NASA KSC EGS has instrumentation installed on both the ML and CT to record data during rollout, at the launch pad, and during liftoff. The EGS instrumentation on the ML, which includes accelerometers, is referred to as the Sensor Data Acquisition System (SDAS). The EGS instrumentation on the CT, which also includes accelerometers, is referred to as the CT Data Acquisition System (CTDAS). The forces and accelerations applied to the ML and CT during a rollout event will be higher than any of the planned building block modal tests. This can be very beneficial in helping identify nonlinear behavior in the structure. Developing modal parameters from the same test hardware in multiple boundary conditions and under multiple levels of excitation is a key step in developing a well correlated FEM. The purpose of this study was three fold. First, determine the target modes of the ML/CT in its rollout configuration. Second, determine if the test degrees of freedom (DOF) corresponding to the layout of the SDAS/CTDAS accelerometers (i.e. position and orientation) is sufficient to identify the target modes. Third, determine if the Generic Rollout Forcing Functions (GRFF's) is sufficient for identifying the ML/CT target modes accounting for variations in CT speed, modal damping, and sensor/ambient background noise levels. The finding from the first part of this study identified 28 target modes of the ML/CT rollout configuration based upon Modal Effective Mass Fractions (MEFF) and engineering judgement. The finding from the second part of this study showed that the SDAS/CTDAS accelerometers (i.e. position and orientation) are able to identify a sufficient number of the target modes to support model correlation of the ML/CT FEM. The finding from the third part of this study confirms the GRFFs sufficiently excite the ML/CT such that varying quantities of the defined target modes should be able to be extracted when utilizing an Experimental Modal Analysis (EMA) Multi-Input Multi-Output (MIMO) analysis approach. An EMA analysis approach was used because Operational Modal Analysis (OMA) tools were not available and the GRFFs were sufficiently uncorrelated. Two key findings from this third part of the study are that the CT speed does not show a significant impact on the ability to extract the modal parameters and that keeping the ambient background noise observed at each accelerometer location at or below 30 µgrms is essential to the success of this approach.

Winkel, James P.↗

Progress in Operational Analysis of Launch Vehicles in Nonstationary Flight

This paper presents recent results in an ongoing effort to understand and develop techniques to process launch vehicle data, which is extremely challenging for modal parameter identification. The primary source of difficulty is due to the nonstationary nature of the situation. The system is changing, the environment is not steady, and there is an active control system operating. Hence, the primary tool for producing clean operational results (significant data lengths and data averaging) is not available to the user. This work reported herein uses a correlation-based two step operational modal analysis approach to process the relevant data sets for understanding and development of processes. A significant drawback for such processing of short time histories is a series of beating phenomena due to the inability to average out random modal excitations. A recursive correlation process coupled to a new convergence metric (designed to mitigate the beating phenomena) is the object of this study. It has been found in limited studies that this process creates clean modal frequency estimates but numerically alters the damping.

James, George↗

Space Launch System: SLS Real Time Rollout Monitoring for MPCV

The NASA Space Launch System (SLS) rocket, Orion spacecraft, and Mobile Launcher (ML) are transported to Pad 39B from the Vehicle Assembly Building on a large, tracked vehicle known as the Crawler Transporter (CT). The CT is a holdover from the Apollo and Space Shuttle programs but has been extensively upgraded to accommodate the SLS. The Dynamic Rollout Test (DRT) on March 17, 2022 marked the first full rollout of the SLS and ML. Analysis indicated that loads and vibrations would be well below design limits, but out of an abundance of caution it was decided to monitor the response in real time during the rollout to assure that loads remained within predicted limits. This first rollout was outfitted with extensive test instrumentation such as accelerometers, pressure sensors, and strain gauges. This instrumentation remained in place following the integrated vehicle modal test and was being used for additional Operational Modal Analysis (OMA) during the rollout in addition to the real-time monitoring. This presentation discusses the specific loads and accelerations monitored during the rollout, how and why those responses were chosen, and how the system was implemented. Finally, a post-rollout loads reconstruction is used to assess the process and the analysis tools used for the rollout analysis.

SLS↗

Extracting Damping Ratio from Dynamic Data and Numerical Solutions

There are many ways to extract damping parameters from data or models. This Technical Memorandum provides a quick reference for some of the more common approaches used in dynamics analysis. Described are six methods of extracting damping from data: the half-power method, logarithmic decrement (decay rate) method, an autocorrelation/power spectral density fitting method, a frequency response fitting method, a random decrement fitting method, and a newly developed half-quadratic gain method. Additionally, state-space models and finite element method modeling tools, such as COMSOL Multiphysics (COMSOL), provide a theoretical damping via complex frequency. Each method has its advantages which are briefly noted. There are also likely many other advanced techniques in extracting damping within the operational modal analysis discipline, where an input excitation is unknown; however, these approaches discussed here are objective, direct, and can be implemented in a consistent manner.

Casiano, M. J.↗

Multidisciplinary Dynamic Testing Challenges in Validating the NASA Artemis Architecture

NASA is in the midst of bold and exciting next steps in human exploration and spaceflight. The designs of the new Space Launch System (SLS), the Orion spacecraft and the Exploration Ground Systems (EGS) for vehicle processing and launch are essentially complete and there has been significant progress in manufacturing and assembly of specific hardware for the Artemis I and Artemis II missions. Equally as important, the program level and integrated system level testing and analyses are also well underway to support integrated verification, validation, and certificate of flight readiness (CoFR) for the first Artemis mission. Testing and analysis are key to addressing technical challenges that the Artemis missions offer. Building block approaches are required that provide the right balance between component, system, and/or element level testing that satisfies verification and validation objectives and where, uncertainties are quantified and minimized. Artemis I is a system of systems that requires a fusion of test and analysis that adeptly characterizes critical interfaces between major program elements. NASA is implementing new in-situ testing that fuse traditional aerospace structures with civil structures, such as the Integrated Modal Test for the Artemis I vehicle where the Mobile Launcher and Crawler Transporter serve as a support structure whose dynamics couple with that of the Artemis I vehicle. This new paradigm requires a closer inspection of structural behavior of the Crawler Transporter and the Mobile Launcher as they now serve multiple purposes. This requires a paradigm shift to look beyond experimental modal techniques and incorporates operational modal analysis techniques to validate dynamic models from data collected during rollout to the launch pad. A further complicating factor is the Crawler Transporter generated ground forces have numerous harmonics making extracting dynamic responses of the Artemis I, Mobile Launcher, and Crawler Transporter coupled system challenging. This discussion explores all these challenges with and attempts to understand how we best build confidence in systems and system-of-systems performance capabilities and margins and understand uncertainties.

Joel W Sills↗

Extraction of Vibration Data with Imaging

To date, the primary sensing technology used to measure the vibration response has been accelerometers and strain gages mounted directly to the structure and using either wired or, more recently, wireless telemetry. Cost issues with these sensors and the associated data acquisition systems typically limit the numbers that are deployed on in situ structures. Although there are a few structures with larger sensing counts that in some cases exceed over 1000 sensors, more typical numbers range from ten to one hundred sensors resulting in low spatial resolution when they are applied to physically large systems. When one considers that nuclear power plant structures usually have complex geometries, material properties, connectivity and boundary conditions, it is clear these current approaches to vibration measurements can only provide limited information about a system’s dynamics response characteristics. As an alternative, many non-contact measurement technologies have emerged, including point wise measurement methods such as Global Positioning System (GPS), microwave interferometry, and laser Doppler vibrometry (LDV), as well as simultaneous full-field measurement methods such as electronic speckle pattern interferometry, holography interferometry, and muon tomography, some of which can provide high spatial resolution measurements. Among these methods, digital video imaging techniques have emerged as a feasible solution for full-field vibration measurements that provide significantly more detailed dynamic response information because every pixel becomes a measurement point. Furthermore, recent advances in image processing and computer vision algorithms have been successfully used to process video data for experimental and operational modal analysis. Such full-field measurements have the potential to significantly improve many current structural assessment procedures including system identification (modal parameter estimation), structural health monitoring, load reconstruction, model validation, and model updating. Furthermore, more recent full-field imaging techniques can be accomplished with relatively low-cost, commercially-available off-the-shelf cameras. However, these measurement procedures have other limitations that must be considered such as the ability to only measure visibly accessible points on a structure and a more limited dynamic range and bandwidth than can be achieved with accelerometers or strain gages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Extraction of Modal Parameters from Spacecraft Flight Data

The modeled response of spacecraft systems must be validated using flight data as ground tests cannot adequately represent the flight. Tools from the field of operational modal analysis would typically be brought to bear on such structures. However, spacecraft systems have several complicated issues: 1. High amplitudes of loads; 2. Compressive loads on the vehicle in flight; 3. Lack of generous time-synchronized flight data; 4. Changing properties during the flight; and 5. Major vehicle changes due to staging. A particularly vexing parameter to extract is modal damping. Damping estimation has become a more critical issue as new mass-driven vehicle designs seek to use the highest damping value possible. The paper will focus on recent efforts to utilize spacecraft flight data to extract system parameters, with a special interest on modal damping. This work utilizes the analysis of correlation functions derived from a sliding window technique applied to the time record. Four different case studies are reported in the sequence that drove the authors understanding. The insights derived from these four exercises are preliminary conclusions for the general state-of-the-art, but may be of specific utility to similar problems approached with similar tools.

James, George H.↗

Sensor-Only System Identification for Structural Health Monitoring of Advanced Aircraft

Environmental conditions, cyclic loading, and aging contribute to structural wear and degradation, and thus potentially catastrophic events. The challenge of health monitoring technology is to determine incipient changes accurately and efficiently. This project addresses this challenge by developing health monitoring techniques that depend only on sensor measurements. Since actively controlled excitation is not needed, sensor-to-sensor identification (S2SID) provides an in-flight diagnostic tool that exploits ambient excitation to provide advance warning of significant changes. S2SID can subsequently be followed up by ground testing to localize and quantify structural changes. The conceptual foundation of S2SID is the notion of a pseudo-transfer function, where one sensor is viewed as the pseudo-input and another is viewed as the pseudo-output, is approach is less restrictive than transmissibility identification and operational modal analysis since no assumption is made about the locations of the sensors relative to the excitation.

Kukreja, Sunil L.↗

Performing a Large-Scale Modal Test on the B2 Stand Crane at NASA's Stennis Space Center

A modal test of NASA's Space Launch System (SLS) Core Stage is scheduled to occur at the Stennis Space Center B2 test stand. A derrick crane with a 150-ft long boom, located at the top of the stand, will be used to suspend the Core Stage in order to achieve defined boundary conditions. During this suspended modal test, it is expected that dynamic coupling will occur between the crane and the Core Stage. Therefore, a separate modal test was performed on the B2 crane itself, in order to evaluate the varying dynamic characteristics and correlate math models of the crane. Performing a modal test on such a massive structure was challenging and required creative test setup and procedures, including implementing both AC and DC accelerometers, and performing both classical hammer and operational modal analysis. This paper describes the logistics required to perform this large-scale test, as well as details of the test setup, the modal test methods used, and an overview and application of the results.

Stasiunas, Eric C.↗

Performing a Large-Scale Modal Test on the B2 Stand Crane at NASA's Stennis Space Center

A modal test of NASA’s Space Launch System (SLS) Core Stage is scheduled to occur prior to propulsion system verification testing at the Stennis Space Center B2 test stand. A derrick crane with a 180-ft long boom, located at the top of the stand, will be used to suspend the Core Stage in order to achieve defined boundary conditions. During this suspended modal test, it is expected that dynamic coupling will occur between the crane and the Core Stage. Therefore, a separate modal test was performed on the B2 crane itself, in order to evaluate the varying dynamic characteristics and correlate math models of the crane. Performing a modal test on such a massive structure was challenging and required creative test setup and procedures, including implementing both AC and DC accelerometers, and performing both classical hammer and operational modal analysis. This paper describes the logistics required to perform this large-scale test, as well as details of the test setup, the modal test methods used, and an overview of the results.

Stasiunas, Eric C.↗