Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Modal Testing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Some test/analysis issues for the space station structural characterization experiment

The Space Station Structural Characterization Experiment (SSSCE) 1,2 is an early space flight experiment that uses the space station as a generic structure to study the dynamic characteristics of Large Space Structures (LSS). On-orbit modal testing will be conducted to determine natural frequencies, mode shapes and damping of dominant structural modes of the space structure assembly. This experiment will utimately support the development of system identification and analytical modeling techniques for Large Space Structures. In order to ensure the success of SSSCE (in-space validation of modeling techniques for LSS), adequate measurement and instrumentation requirements have to be established during the experiment-definition study. Among the issues affecting these requirements, spatial and modal coverages of the modal test data are of particular interest. Topics such as total number of sensors, type of measurements (translation and rotation), optimal sensor locations (measurement degrees-of-freedom), selection of target modes, effects of modal superposition and truncation, separation of global and local modes, etc., are all a fundamental importance and must be investigated.

Chou, Chaur-Ming↗
NASA NTRS2018

Quantification of Dynamic Model Validation Metrics Using Uncertainty Propagation from Requirements

The Space Launch System, NASA's new large launch vehicle for long range space exploration, is presently in the final design and construction phases, with the first launch scheduled for 2019. A dynamic model of the system has been created and is critical for calculation of interface loads and natural frequencies and mode shapes for guidance, navigation, and control (GNC). Because of the program and schedule constraints, a single modal test of the SLS will be performed while bolted down to the Mobile Launch Pad just before the first launch. A Monte Carlo and optimization scheme will be performed to create thousands of possible models based on given dispersions in model properties and to determine which model best fits the natural frequencies and mode shapes from modal test. However, the question still remains as to whether this model is acceptable for the loads and GNC requirements. An uncertainty propagation and quantification (UP and UQ) technique to develop a quantitative set of validation metrics that is based on the flight requirements has therefore been developed and is discussed in this paper. There has been considerable research on UQ and UP and validation in the literature, but very little on propagating the uncertainties from requirements, so most validation metrics are "rules-of-thumb;" this research seeks to come up with more reason-based metrics. One of the main assumptions used to achieve this task is that the uncertainty in the modeling of the fixed boundary condition is accurate, so therefore that same uncertainty can be used in propagating the fixed-test configuration to the free-free actual configuration. The second main technique applied here is the usage of the limit-state formulation to quantify the final probabilistic parameters and to compare them with the requirements. These techniques are explored with a simple lumped spring-mass system and a simplified SLS model. When completed, it is anticipated that this requirements-based validation metric will provide a quantified confidence and probability of success for the final SLS dynamics model, which will be critical for a successful launch program, and can be applied in the many other industries where an accurate dynamic model is required.

Brown, Andrew M.↗
NASA NTRS2018

Natural Frequency Testing and Model Correlation of Rocket Engine Structures in Liquid Hydrogen - Phase I, Cantilever Beam

Many structures in the launch vehicle industry operate in liquid hydrogen (LH2), from the hydrogen fuel tanks through the ducts and valves and into the pump sides of the turbopumps. Calculating the structural dynamic response of these structures is critical for successful qualification of this hardware, but accurate knowledge of the natural frequencies is based entirely on numerical or analytical predictions of frequency reduction due to the added-fluid-mass effect because testing in LH2 has always been considered too difficult and dangerous. This fluid effect is predicted to be approximately 4-5% using analytical formulations for simple cantilever beams. As part of a comprehensive test/analysis program to more accurately assess pump inducers operating in LH2, a series of frequency tests in LH2 were performed at NASA/Marshall Space Flight Center's unique cryogenic test facility. These frequency tests are coupled with modal tests in air and water to provide critical information not only on the mass effect of LH2, but also the cryogenic temperature effect on Young's Modulus for which the data is not extensive. The authors are unaware of any other reported natural frequency testing in this media. In addition to the inducer, a simple cantilever beam was also tested in the tank to provide a more easily modeled geometry as well as one that has an analytical solution for the mass effect. This data will prove critical for accurate structural dynamic analysis of these structures, which operate in a highly-dynamic environment.

Brown, Andrew M.↗
NASA NTRS1978

Modal confidence factor in vibration testing

The modal confidence factor (MCF) is a number calculated for every identified mode for a structure under test. The MCF varies from 0.00 for a distorted nonlinear, or noise mode to 100.0 for a pure structural mode. The theory of the MCF is based on the correlation that exists between the modal deflection at a certain station and the modal deflection at the same station delayed in time. The theory and application of the MCF are illustrated by two experiments. The first experiment deals with simulated responses from a two-degree-of-freedom system with 20%, 40%, and 100% noise added. The second experiment was run on a generalized payload model. The free decay response from the payload model contained 22% noise.

Ibrahim, S. R.↗
NASA NTRS1991

High temperature ground vibration test techniques

This paper describes the experimental modal test techniques and procedures used to conduct uniform, nonuniform, and transient thermoelastic vibration tests. Experimental setup and elevated temperature instrumentation considerations are also discussed. Modal data for a 30.48- by 127-cm aluminum plate heated to a temperature of 371.1 C are presented. These data show the effect of heat on the plate's modal characteristics.

Kehoe, Michael W.↗
NASA NTRS1993

Estimating free-body modal parameters from tests of a constrained structure

Hardware advances in suspension technology for ground tests of large space structures provide near on-orbit boundary conditions for modal testing. Further advances in determining free-body modal properties of constrained large space structures have been made, on the analysis side, by using time domain parameter estimation and perturbing the stiffness of the constraints over multiple sub-tests. In this manner, passive suspension constraint forces, which are fully correlated and therefore not usable for spectral averaging techniques, are made effectively uncorrelated. The technique is demonstrated with simulated test data.

Cooley, Victor M.↗
NASA NTRS1989

On-orbit vibration testing for space structures

A simulated on-orbit modal test using active members as the excitation source has been performed on the Precision Truss. Using the step sine testing technique, the frequency response functions are obtained and the modal parameters are extracted by the curve-fitting method. A total of 10 global modes and 3 local modes are obtained. The results are compared with those obtained by the conventional external excitation test.

Chen, Jay-Chung↗
NASA NTRSDate not supplied

TPSAS-NF1676L-31853-DND

Risk that Orion arrives later than Space Launch System (SLS). MSO mitigates this risk by using a mass simulator for SLS’ tests. An Orion simulator for the Integrated Modal Test (IMT) and Umbilical Release and Retraction Tests (URRT) mitigates schedule risk by significant timeframe. A clean sheet alternate being pursued - analysis shows matching modal characteristics unnecessary; rigid simulator is acceptable wrt existing SLS accelerometer locations and shaker placement/size. Key Simulator Requirements: Representative mass, CG, rigid modal characteristics, high fidelity interface at MSA. Pre-test analyses show that MSO vertical CG could be up to 40” low without affecting IMT.

Steve Cutright↗
NASA NTRS1993

System identification of the JPL micro-precision interferometer truss - Test-analysis reconciliation

The JPL Micro-Precision Interferometer (MPI) is a testbed for studying the use of control-structure interaction technology in the design of space-based interferometers. A layered control architecture will be employed to regulate the interferometer optical system to tolerances in the nanometer range. An important aspect of designing and implementing the control schemes for such a system is the need for high fidelity, test-verified analytical structural models. This paper focuses on one aspect of the effort to produce such a model for the MPI structure, test-analysis model reconciliation. Pretest analysis, modal testing, and model refinement results are summarized for a series of tests at both the component and full system levels.

Red-Horse, J. R.↗
NASA NTRS1996

Force Measurements in Vibration and Acoustic Tests

The advent of triaxial, piezoelectric force gages and the associated signal processing is a precursor to several dynamics testing innovations. This new technology is applicable to spacecraft programs that JPL manages. An application of force measurement is force limiting (when testing spacecraft in random vibration tests). Base-drive and acoustic modal testing is a potential application.

vibration tests acoustic tests spacecraft testing ↗
NASA NTRSDate not supplied

Feasibility Study to Extract Artemis-1 Fixed Base Modes While Mounted on a Dynamically Active Mobile Launch Platform

There are several challenges associated with the scheduled integrated modal test (IMT)of the Space Launch System (SLS) Artemis-1flight vehicle mounted on the mobile launcher (ML). While the goal of the test is to characterize the Artemis-1, the inclusion of the ML as the support stand for the test means that the entire system must be well characterized. A considerable amount of effort and schedule will have to be devoted to understanding both the test stand (the ML) and the Artemis-1 flight vehicle, and there is a risk that the effort may not be completed in time for a successful launch. NASA has requested that alternative methods be investigated to generate test results that can remove the effects of the ML from the test. ATA Engineering, Inc., (ATA)was given a reduced model f theArtemis-1 flight vehicle’s IMT configuration containing the candidate set of accelerometers and interface degrees of freedom (DOF). The model was used to determine how well ATA’s fixed base correction technique is able to estimate fixed base modes from test data collected on the IMT. This paper presents the fixed base correction method results.

modal testing↗
NASA NTRS2003

Hybrid Residual Flexibility/Mass-Additive Method for Structural Dynamic Testing

A large fixture was designed and constructed for modal vibration testing of International Space Station elements. This fixed-base test fixture, which weighs thousands of pounds and is anchored to a massive concrete floor, initially utilized spherical bearings and pendulum mechanisms to simulate Shuttle orbiter boundary constraints for launch of the hardware. Many difficulties were encountered during a checkout test of the common module prototype structure, mainly due to undesirable friction and excessive clearances in the test-article-to-fixture interface bearings. Measured mode shapes and frequencies were not representative of orbiter-constrained modes due to the friction and clearance effects in the bearings. As a result, a major redesign effort for the interface mechanisms was undertaken. The total cost of the fixture design, construction and checkout, and redesign was over $2 million. Because of the problems experienced with fixed-base testing, alternative free-suspension methods were studied, including the residual flexibility and mass-additive approaches. Free-suspension structural dynamics test methods utilize soft elastic bungee cords and overhead frame suspension systems that are less complex and much less expensive than fixed-base systems. The cost of free-suspension fixturing is on the order of tens of thousands of dollars as opposed to millions, for large fixed-base fixturing. In addition, free-suspension test configurations are portable, allowing modal tests to be done at sites without modal test facilities. For example, a mass-additive modal test of the ASTRO-1 Shuttle payload was done at the Kennedy Space Center launch site. In this Technical Memorandum, the mass-additive and residual flexibility test methods are described in detail. A discussion of a hybrid approach that combines the best characteristics of each method follows and is the focus of the study.

Tinker, M. L.↗
NASA NTRS2000

Ground Vibration Test Planning and Pre-Test Analysis for the X-33 Vehicle

This paper describes the results of the modal test planning and the pre-test analysis for the X-33 vehicle. The pre-test analysis included the selection of the target modes, selection of the sensor and shaker locations and the development of an accurate Test Analysis Model (TAM). For target mode selection, four techniques were considered, one based on the Modal Cost technique, one based on Balanced Singular Value technique, a technique known as the Root Sum Squared (RSS) method, and a Modal Kinetic Energy (MKE) approach. For selecting sensor locations, four techniques were also considered; one based on the Weighted Average Kinetic Energy (WAKE), one based on Guyan Reduction (GR), one emphasizing engineering judgment, and one based on an optimum sensor selection technique using Genetic Algorithm (GA) search technique combined with a criteria based on Hankel Singular Values (HSV's). For selecting shaker locations, four techniques were also considered; one based on the Weighted Average Driving Point Residue (WADPR), one based on engineering judgment and accessibility considerations, a frequency response method, and an optimum shaker location selection based on a GA search technique combined with a criteria based on HSV's. To evaluate the effectiveness of the proposed sensor and shaker locations for exciting the target modes, extensive numerical simulations were performed. Multivariate Mode Indicator Function (MMIF) was used to evaluate the effectiveness of each sensor & shaker set with respect to modal parameter identification. Several TAM reduction techniques were considered including, Guyan, IRS, Modal, and Hybrid. Based on a pre-test cross-orthogonality checks using various reduction techniques, a Hybrid TAM reduction technique was selected and was used for all three vehicle fuel level configurations.

Bedrossian, Herand↗
NASA NTRSDate not supplied

Machine Learning for Dynamic Test Sensor Placement

There are multiple different algorithms to perform modal test sensor placement optimization: effective independence, residual kinetic energy, iterative Guyan reduction, genetic algorithms, or a brute-force methodology. However, any of these methods may be computationally expensive, especially for structural models with a large number of degrees of freedom. Given the high-cost and the need to optimize the solution, modal sensor placement is a great application for machine learning (ML) algorithms. In this paper, we will apply ML algorithms to determine the optimal sensor locations for simple and complex structures. We will also discuss the benefits and drawbacks of using machine learning over other sensor placement algorithms.

Kelsey Buckles↗
NASA NTRS2007

Calculating Nozzle Side Loads using Acceleration Measurements of Test-Based Models

As part of a NASA/MSFC research program to evaluate the effect of different nozzle contours on the well-known but poorly characterized "side load" phenomena, we attempt to back out the net force on a sub-scale nozzle during cold-flow testing using acceleration measurements. Because modeling the test facility dynamics is problematic, new techniques for creating a "pseudo-model" of the facility and nozzle directly from modal test results are applied. Extensive verification procedures were undertaken, resulting in a loading scale factor necessary for agreement between test and model based frequency response functions. Side loads are then obtained by applying a wide-band random load onto the system model, obtaining nozzle response PSD's, and iterating both the amplitude and frequency of the input until a good comparison of the response with the measured response PSD for a specific time point is obtained. The final calculated loading can be used to compare different nozzle profiles for assessment during rocket engine nozzle development and as a basis for accurate design of the nozzle and engine structure to withstand these loads. The techniques applied within this procedure have extensive applicability to timely and accurate characterization of all test fixtures used for modal test.A viewgraph presentation on a model-test based pseudo-model used to calculate side loads on rocket engine nozzles is included. The topics include: 1) Side Loads in Rocket Nozzles; 2) Present Side Loads Research at NASA/MSFC; 3) Structural Dynamic Model Generation; 4) Pseudo-Model Generation; 5) Implementation; 6) Calibration of Pseudo-Model Response; 7) Pseudo-Model Response Verification; 8) Inverse Force Determination; 9) Results; and 10) Recent Work.

Brown, Andrew M.↗