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At least 415 records · Page 23

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗

Probabilistic system identification in the time domain

The objective of system identification is to determine reliable dynamical models of a structure by systematically using its measured excitation and response. It brings together in an integrated fashion, experimental, analytical, and computational techniques in structural dynamics. Areas of application for system identification include the following: (1) Model Evaluation--assessing assumptions (linearity and equivalent viscous damping) and techniques (finite-element modeling) used to construct theoretical models of a structure; (2) Model Improvement--updating of a theoretical model to enable more accurate response predictions for possible future loads on the structure, or for control of the structure; (3) Empirical Modelling--developing empirical relationships (nonlinear models) or empirical parameter values (modal damping) because the present state of the art does not provide theoretical results; and (4) Damage Detection and Assessment--continual or episodic updating of a structural model through vibration monitoring to detect and locate any structural damage. It can be argued that since the construction or modification of models using test data is subject to inherent uncertainties, the above problems should be properly treated within a Bayesian probabilistic framework. Such a methodology is presented which allows the precision of the estimates of the model parameters to be computed. It also leads to a guiding principle in applications. Namely, when selecting a single model from a given class of models, one should take the most probable model in the class based on the experimental data. Practical applications of this principle are given which are based on the utilization of measured seismic motions in large civil structures. Examples include the application of a computer program MODE-ID to identify modal properties directly from seismic excitation and response time histories from a nine-story steel-frame building at JPL and from a freeway overpass bridge.

Beck, James L.↗

Aircraft interior noise prediction using a structural-acoustic analogy in NASTRAN modal synthesis

The noise induced inside a cylindrical fuselage model by shaker excitation is investigated theoretically and experimentally. The NASTRAN modal-synthesis program is used in the theoretical analysis, and the predictions are compared with experimental measurements in extensive graphs. Good general agreement is obtained, but the need for further refinements to account for acoustic-cavity damping and structural-acoustic interaction is indicated.

Grosveld, Ferdinand W.↗

Comparing Free-Free and Shaker Table Model Correlation Methods Using Jim Beam

Finite element model correlation as part of a spacecraft program has always been a challenge. For any NASA mission, the coupled system response of the spacecraft and launch vehicle can be determined analytically through a Coupled Loads Analysis (CLA), as it is not possible to test the spacecraft and launch vehicle coupled system before launch. The value of the CLA is highly dependent on the accuracy of the frequencies and mode shapes extracted from the spacecraft model. NASA standards require the spacecraft model used in the final Verification Loads Cycle to be correlated by either a modal test or by comparison of the model with Frequency Response Functions (FRFs) obtained during the environmental qualification test. Due to budgetary and time constraints, most programs opt to correlate the spacecraft dynamic model during the environmental qualification test, conducted on a large shaker table. For any model correlation effort, the key has always been finding a proper definition of the boundary conditions. This paper is a correlation case study to investigate the difference in responses of a simple structure using a free-free boundary, a fixed boundary on the shaker table, and a base-drive vibration test, all using identical instrumentation. The NAVCON Jim Beam test structure, featured in the IMAC round robin modal test of 2009, was selected as a simple, well recognized and well characterized structure to conduct this investigation. First, a free-free impact modal test of the Jim Beam was done as an experimental control. Second, the Jim Beam was mounted to a large 20,000 lbf shaker, and an impact modal test in this fixed configuration was conducted. Lastly, a vibration test of the Jim Beam was conducted on the shaker table. The free-free impact test, the fixed impact test, and the base-drive test were used to assess the effect of the shaker modes, evaluate the validity of fixed-base modeling assumptions, and compare final model correlation results between these boundary conditions.

Modal Test↗

A Frequency-Domain Substructure System Identification Algorithm

A new frequency-domain system identification algorithm is presented for system identification of substructures, such as payloads to be flown aboard the Space Shuttle. In the vibration test, all interface degrees of freedom where the substructure is connected to the carrier structure are either subjected to active excitation or are supported by a test stand with the reaction forces measured. The measured frequency-response data is used to obtain a linear, viscous-damped model with all interface-degree of freedom entries included. This model can then be used to validate analytical substructure models. This procedure makes it possible to obtain not only the fixed-interface modal data associated with a Craig-Bampton substructure model, but also the data associated with constraint modes. With this proposed algorithm, multiple-boundary-condition tests are not required, and test-stand dynamics is accounted for without requiring a separate modal test or finite element modeling of the test stand. Numerical simulations are used in examining the algorithm's ability to estimate valid reduced-order structural models. The algorithm's performance when frequency-response data covering narrow and broad frequency bandwidths is used as input is explored. Its performance when noise is added to the frequency-response data and the use of different least squares solution techniques are also examined. The identified reduced-order models are also compared for accuracy with other test-analysis models and a formulation for a Craig-Bampton test-analysis model is also presented.

Blades, Eric L.↗

Modal Filtering for Control of Flexible Aircraft

Modal regulators and deformation trackers are designed for an open-loop fluttering wing model. The regulators are designed with modal coordinate and accelerometer inputs respectively. The modal coordinates are estimated with simulated fiber optics. The robust stability of the closed-loop systems is compared in a structured singular-value vector analysis. Performance is evaluated and compared in a gust alleviation and flutter suppression simulation. For the same wing and flight condition two wing-shape-tracking control architectures are presented, which achieve deformation control at any point on the wing.

Shape Control↗

Dynamic testing of a two-dimensional box truss beam

Testing to determine the effects of joint freeplay and pretensioning of diagonal members on the dynamic characteristics of a two-dimensional box truss beam was conducted. The test article was ten bays of planar truss suspended by long wires at each joint. Each bay measured 2 meters per side. Pins of varying size were used to simulate various joint freeplay conditions. Single-point random excitation was the primary method of test. The rational fraction polynomial method was used to extract modal characteristics from test data. A finite element model of the test article was generated from which modal characteristics were predicted. These were compared with those obtained from tests. With the exception of the fundamental mode, correlation of theoretical and experimental results was poor, caused by the resonant coupling of local truss member bending modes with global truss beam modes. This coupling introduced many modes in the frequency range of interest whose frequencies were sensitive to joint boundary conditions. It was concluded that local/global coupling must be avoided in the frequency range where accurate modal characteristics are required.

White, Charles W.↗

NASTRAN Modeling of Flight Test Components for UH-60A Airloads Program Test Configuration

Based upon the recommendations of the UH-60A Airloads Program Review Committee, work towards a NASTRAN remodeling effort has been conducted. This effort modeled and added the necessary structural/mass components to the existing UH-60A baseline NASTRAN model to reflect the addition of flight test components currently in place on the UH-60A Airloads Program Test Configuration used in NASA-Ames Research Center's Modern Technology Rotor Airloads Program. These components include necessary flight hardware such as instrument booms, movable ballast cart, equipment mounting racks, etc. Recent modeling revisions have also been included in the analyses to reflect the inclusion of new and updated primary and secondary structural components (i.e., tail rotor shaft service cover, tail rotor pylon) and improvements to the existing finite element mesh (i.e., revisions of material property estimates). Mode frequency and shape results have shown that components such as the Trimmable Ballast System baseplate and its respective payload ballast have caused a significant frequency change in a limited number of modes while only small percent changes in mode frequency are brought about with the addition of the other MTRAP flight components. With the addition of the MTRAP flight components, update of the primary and secondary structural model, and imposition of the final MTRAP weight distribution, modal results are computed representative of the 'best' model presently available.

Idosor, Florentino R.↗

Grammians and model reduction in limited time and frequency intervals

In this paper the controllability and observability grammians in limited time and frequency intervals are studied, and used for model reduction. In balanced and modal coordinates a near-optimal reduction procedure is developed, yielding the reduction error (norm of the difference between the output of the original system and the reduced model) almost minimal. Several examples are given to illustrate the concept for model reduction of continuous- and discrete-time systems, stable and unstable systems, in limited tim or/and frequency interval. Finally, the model reduction of a flexible truss structure is presented.

Gawronski, Wodek↗

Data-driven recovery of hidden physics in reduced order modeling of fluid flows

In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant to fluid dynamics. The hybrid ROM framework is based on using first principles to model the known physics in conjunction with utilizing the data-driven machine learning tools to model the remaining residual that is hidden in data. This framework employs proper orthogonal decomposition as a compression tool to construct orthonormal bases and Galerkin projection (GP) as a model to build the dynamical core of the system. Our proposed methodology hence compensates structural or epistemic uncertainties in models and utilizes the observed data snapshots to compute true modal coefficients spanned by these bases. The GP model is then corrected at every time step with a data-driven rectification using a long short-term memory (LSTM) neural network architecture to incorporate hidden physics. A Grassmannian manifold approach is also adopted for interpolating basis functions to unseen parametric conditions. The control parameter governing the system's behavior is thus implicitly considered through true modal coefficients as input features to the LSTM network. The effectiveness of the HAM approach is then discussed through illustrative examples that are generated synthetically to take hidden physics into account. Furthermore, our approach thus provides insights addressing a fundamental limitation of the physics-based models when the governing equations are incomplete to represent underlying physical processes.

42 ENGINEERING↗

Multi-Body Analysis of the 1/5 Scale Wind Tunnel Model of the V-22 Tiltrotor

The paper presents a multi-body analysis of the 1/5 scale wind tunnel model of the V-22 tiltrotor, the Wing and Rotor Aeroelastic Testing System (WRATS), currently tested at NASA Langley Research Center. An original multi-body formulation has been developed at the Dipartimento di Ingegneria Aerospaziale of the Politecnico di Milano, Italy. It is based on the direct writing of the equilibrium equations of independent rigid bodies, connected by kinematic constraints that result in the addition of algebraic constraint equations, and by dynamic constraints, that directly contribute to the equilibrium equations. The formulation has been extended to the simultaneous solution of interdisciplinary problems by modeling electric and hydraulic networks, for aeroservoelastic problems. The code has been tailored to the modeling of rotorcrafts while preserving a complete generality. A family of aerodynamic elements has been introduced to model high aspect aerodynamic surfaces, based on the strip theory, with quasi-steady aerodynamic coefficients, compressibility, post-stall interpolation of experimental data, dynamic stall modeling, and radial flow drag. Different models for the induced velocity of the rotor can be used, from uniform velocity to dynamic in flow. A complete dynamic and aeroelastic analysis of the model of the V-22 tiltrotor has been performed, to assess the validity of the formulation and to exploit the unique features of multi-body analysis with respect to conventional comprehensive rotorcraft codes; These are the ability to model the exact kinematics of mechanical systems, and the possibility to simulate unusual maneuvers and unusual flight conditions, that are particular to the tiltrotor, e.g. the conversion maneuver. A complete modal validation of the analytical model has been performed, to assess the ability to reproduce the correct dynamics of the system with a relatively coarse beam model of the semispan wing, pylon and rotor. Particular care has been used to model the kinematics of the gimbal joint, that characterizes the rotor hub, and of the control system, consisting in the entire swashplate mechanism. The kinematics of the fixed and the rotating plates have been modeled, with variable length control links used to input the controls, the rotating flexible links, the pitch horns and the pitch bearings. The investigations took advantage of concurring wind tunnel test runs, that were performed in August 1998, and allowed the acquisition of data specific to the multi-body analysis.

Ghiringhelli, G. L.↗

Comparison of candidate methods to distinguish noise modes from system modes in structural identification

In modal identification, nonphysical noise or computation modes always appear to help match the input-output data. This paper studies the ability of four criteria to distinguish which modes in a model are noise modes: (1) modal amplitude coherency, (2) the relative contribution of each mode to the pulse response indicated by the mode singular value, (3) the variances of the mode frequencies and damping factors produced by a chosen measurement noise level, and (4) identification of the backward-time in order to let the shift from positive to negative damping of the true system modes distinguish these modes from noise modes. Both simulated and experimental data are used to study the four criteria.

Longman, Richard W.↗

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

Seybert, A. F.↗

Rotor Design Options for Improving V-22 Whirl-Mode Stability

With current tilt-rotor technology, very stiff, thick wings of limited aspect ratio are essential to meet aeroelastic stability requirements, which severely limits cruise efficiency and maximum speed. Larger and more efficient tiltrotors; will need longer and lighter wings, for which whirl-mode flutter is a serious design issue. Numerous approaches to improving the whirl-mode airspeed boundary have been investigated, typically focusing on wing design, active stability augmentation, and variable geometry rotors. The research to be reported applies the much simpler approaches of sweeping the outboard blade sections and extending balance weights at the tip. Improving proprotor whirl-mode stability margins is an ongoing research activity at NASA Ames Research Center. Previous efforts focussed on the XV-15 rotor. This is the first application of these design principles to a full V-22 rotor model in CAMRAD II (a previous publication presented results for a preliminary analytical model). The analysis to be discussed in the proposed paper includes a dual load-path blade model, a compressible-flow aerodynamic model, a representation of swashplate/rotor modal coupling, and other new features. The paper will include discussions of the mechanisms by which blade sweep and tip-mass offsets improve whirl-flutter margins. The V-22 was modeled with CAMRAD II; the rotor model is shown. It is also shows an example swept blade derived from the V-22 rotor system. For this rotor, the primary significance of sweep is the improved whirl-flutter boundary, not the reduced Mach-number effects. An offset tip mass is also shown.

Acree, C. W., Jr.↗

Modal test and analysis correlation

Modal testing plays a significant role in experimentally measuring the modal parameters used directly for response analysis of spacecraft or indirectly to update a mathematical model for use in response analysis. Developments in modal testing and correlation of results to analytical models are discussed. Several procedures to semi-automate correlation of resonant frequency and mode shape test data to the model have been shown to be valid for hypothetical problems but have not been successful in practice. Improving the correlation of frequencies and mode shapes does not necessarily improve the correlation of modal force coefficients. The paper discusses other parameters, such as kinetic energy and strain energy, which may be more significant in the correlation process. Because the most demanding requirement of a modal test is in determining dynamic loads, the authors asssume that objective, minimally discussing theoretical developments, summarizing their results, and giving sample data.

Wada, B. K.↗

Affinity propagation clustering of full-field, high-spatial-dimensional measurements for robust output-only modal identification: A proof-of-concept study

Determination of the model order is a challenging problem in system identification, especially in output-only or operational modal identification where some modes are weakly excited. While existing methods such as the stabilization diagram method (spectral information) are effective, they do not scale to high-dimensional data, which is usually needed for high-fidelity characterization of structural dynamics and has been made available in the emerging full-field measurement techniques using optical methods such as photogrammetry and laser vibrometers. In this proof-of-concept study we present a new non-parametric, data-driven approach for robust output-only identification of high-spatial-dimensional modal parameters of basic structures by efficiently processing and interactively exploiting the full-field measurement (i.e., very dense spatial measurement points). Specifically, we first over-estimate the system model once, producing a pool of candidate modes associated with their modal frequencies and full-field, high-spatial-dimensional mode shapes. This is accomplished by a data-driven method termed affinity propagation clustering (APC), where the active clusters, which are the active modes in our formulations, emerge from the "message-passing" procedure and does not require a pre-determination of the cluster number (mode or model order). Next, rather than using the spectral information to distinguish the physical and spurious modes in the stabilization diagram method, we exploit and visualize the spatial, full-field mode shape associated with each candidate mode to do so. We conduct extensive experiments on basic structural models with comparisons to a few existing methods. The results indicate that the new method is computationally efficient for identifying high-spatial-dimensional modal parameters, and robust to identify weak modes by exploiting the full-field measurement. We also discuss its applicability and limitations for structures with complex geometry (shapes).

42 ENGINEERING↗

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗

Identifying approximate linear models for simple nonlinear systems

This paper addresses the identification (realization) of approximate linear models from response data for certain nonlinear dynamic systems. Response characteristics for several typical nonlinear joints are analyzed mathematically and represented by series expansions. The parameters of the series expansion are then compared with the modal parameters of a linear model identified by the Eigensystem Realization Algorithm. The agreement of the identified model and the analytically derived representation is excellent for the cases studied. Also laboratory data from a model which exhibited stiffening behavior was analyzed using the Eigensystem Realization algorithm and Fast Fourier Transform. The laboratory experiment demonstrated the ability of the technique to recover the model characteristics using real data.

Horta, L. G.↗