Wind tunnel model damper
Damper system for alleviating air flow shock loads on wind tunnel models.
Bryan, M. B.↗
SEARCH · Engineering Papers
Results for “Load Modeling”
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.
Joint aircraft loading/structure response statistics of time to service crack initiation
A reliability analysis for predicting the statistical distribution of time to fatigue crack initiation for aircraft structures in service is presented. The present analysis utilizes the statistical data of the specimen fatigue tests, the full-scale structure tests, and the statistical dispersion of aircraft service loads. The statistical distribution of the time to fatigue crack initiation of the full-scale structure under laboratory loading spectrum is assumed to be Weibull. The service loads for gust turbulences are modeled as Poisson processes for transport-type aircraft, while the maneuver loads are modeled as compound Poisson processes for fighter and training aircraft. It is found that the statistical distribution of time to fatigue crack initiation for aircraft structures in service is not Weibull and that the prediction on the basis of the Weibull distribution is unconservative, in particular in the early service time.
Yang, J.-N.↗
Spin-Tunnel Investigation of a 1/40-Scale Model of the F-111A Airplane with Store Loadings and with Supplementary Spin-Recovery Devices
An investigation has been made in the Langley spin tunnel to determine the spin and spin-recovery characteristics of the F-111A airplane in the symmetric and asymmetric stores loading conditions. Tests were also made with the model in the clean condition to determine whether the spin-recovery characteristics could be improved by the use of supplementary devices.
Spin-recovery parachute↗
STRUCTURAL-LOADS SURVEYS ON TWO TILT-WING VTOL CONFIGURATIONS
Structural load surveys on tilt-wing vtol aircraft airframe vibratory loads of vz-ii vtol and wing loads of research model in wind tunnel tests
WING LOADING↗
Stability analysis of spacecraft power systems
The problems in applying standard electric utility models, analyses, and algorithms to the study of the stability of spacecraft power conditioning and distribution systems are discussed. Both single-phase and three-phase systems are considered. Of particular concern are the load and generator models that are used in terrestrial power system studies, as well as the standard assumptions of load and topological balance that lead to the use of the positive sequence network. The standard assumptions regarding relative speeds of subsystem dynamic responses that are made in the classical transient stability algorithm, which forms the backbone of utility-based studies, are examined. The applicability of these assumptions to a spacecraft power system stability study is discussed in detail. In addition to the classical indirect method, the applicability of Liapunov's direct methods to the stability determination of spacecraft power systems is discussed. It is pointed out that while the proposed method uses a solution process similar to the classical algorithm, the models used for the sources, loads, and networks are, in general, more accurate. Some preliminary results are given for a linear-graph, state-variable-based modeling approach to the study of the stability of space-based power distribution networks.
Halpin, S. M.↗
Operating a commercial building HVAC load as a virtual battery through airflow control
Virtual battery (VB) is an innovative method to model flexibility of building loads and effectively coordinate them with other resources at a system level. Unlike a real battery with a dedicated power conversion system for charging control, methods are required for operating building loads to deviate from the baseline to respond to grid signals. This paper presents a VB control for a commercial heating, ventilation, and air conditioning (HVAC) system to follow the desired power consumption in real-time by adjusting zonal airflow rates. The proposed method consists of two parts. At the system level, a mixed feedforward and feedback control is used to estimate the desired total airflow rate. At the zone level, two priority-based algorithms are then proposed to distribute the total airflow rate to individual zones. In particular, a zonal airflow limit estimation method is proposed using machine-learning techniques, in contrast to physics-based thermal models in existing studies, to more accurately capture zonal thermal dynamics and improve temperature control performance. An office building on the Pacific Northwest National Laboratory campus is implemented in EnergyPlus, and used to illustrate and validate the proposed control.
Wang, Jiyu↗
Thermal Overloading Risk Mitigation With a Semi-Analytical Probabilistic Model on Branch Current
A semi-analytical formulation is presented in this paper for the probability computation of branch current in multiphase systems. The developed formula is derived based on the linear power flow model in rectangular coordinates. The system uncertainty injections can be renewable energy resources or loads and are modeled using a Gaussian mixture model (GMM). The developed formula can be used to compute the line current violation probability as well as integrate into optimal power flow problem as chance-constraint relaxation. Here, the proposed formula is first compared with the Matlab embedded numerical integration function to show its performance. Besides, the semi-analytical formula is validated and compared with the Monte Carlo simulation method using the IEEE 123-bus system, EPRI Ckt5, and Ckt7 systems.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Conjugating binary systems for spacecraft thermal control. Appendix C: Aeroassist Flight Experiment Carrier Vehicle preliminary stress analysis
An assessment of the static strength of the Aeroassist Flight Experiment (AFE) Carrier Vehicle is presented. The Carrier Vehicle is the structural component which provides the mounting platform for the experiments, on-board computers, batteries, and other black boxes. In addition, the Solid Rocket Motor (SRM), the Thrusters, and the Aerobrake are all attached directly to the Carrier Vehicle. The basic approach in this analysis was to develop a NASTRAN Finite Element Model as a parallel effort to the preliminary design, and to use the internal loads from this model to perform the stress analysis. The NASTRAN method of Inertial Relief was employed. This method involves either specifying a set of CG (center of gravity) accelerations or applying forces at the CG and representing the Carrier Vehicle and all its mounted devices with the proper stiffness and mass properties.
Ingram, J. E.↗
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.↗
Building thermal load prediction through shallow machine learning and deep learning
Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Analysis of shell-type structures subjected to time-dependent mechanical and thermal loading
A general mathematical model and solution methodologies are being developed for analyzing structural response of thin, metallic shell-type structures under large transient, cyclic, or static thermomechanical loads. Among the system responses, which were associated with these load conditions, were thermal buckling, creep buckling, and ratcheting. Thus, geometric as well as material-type nonlinearities (of high order) can be anticipated and must be considered in the development of the mathematical model. Furthermore, this must also be accommodated in the solution process.
Simitses, G. J.↗
Geometrically Nonlinear Static Analysis of 3D Trusses Using the Arc-Length Method
Rigorous analysis of geometrically nonlinear structures demands creating mathematical models that accurately include loading and support conditions and, more importantly, model the stiffness and response of the structure. Nonlinear geometric structures often contain critical points with snap-through behavior during the response to large loads. Studying the post buckling behavior during a portion of a structure's unstable load history may be necessary. Primary structures made from ductile materials will stretch enough prior to failure for loads to redistribute producing sudden and often catastrophic collapses that are difficult to predict. The responses and redistribution of the internal loads during collapses and possible sharp snap-back of structures have frequently caused numerical difficulties in analysis procedures. The presence of critical stability points and unstable equilibrium paths are major difficulties that numerical solutions must pass to fully capture the nonlinear response. Some hurdles still exist in finding nonlinear responses of structures under large geometric changes. Predicting snap-through and snap-back of certain structures has been difficult and time consuming. Also difficult is finding how much load a structure may still carry safely. Highly geometrically nonlinear responses of structures exhibiting complex snap-back behavior are presented and analyzed with a finite element approach. The arc-length method will be reviewed and shown to predict the proper response and follow the nonlinear equilibrium path through limit points.
Hrinda, Glenn A.↗
Identification Uncertainty in Inverse Material Model Parameter Determination: A Sensitivity‐Based Decision Process for Load Path Selection
This research proposes a sensitivity-based framework for selecting the optimal prescribed loading path for a biaxial cruciform specimen. Optimality here is determined by the direction and magnitude of the prescribed displacement that minimizes the influence of random noise on the material model parameter identification. Using simulated experimental data based on finite element simulation, in this work, we identify the material model parameters of a Ludwik hardening model and plane stress implementation of the Hill-48 yield criterion using finite element model updating (FEMU). Our analysis reveals that the identification (or estimator) uncertainty of model parameters depends on the displacement boundary conditions (i.e., loading sequence) and the ground-truth value of the individual parameters. Optimal experimental design (OED) criteria based on the Fisher information matrix were investigated to mitigate indecision in the choice of optimal load path when the identification uncertainty of different material model parameters optimized at different load paths. The determinant of the Fisher information matrix was chosen here as the more useful metric due to its ability to capture uncertainty of the most influential material model parameters. The proposed framework demonstrates potential for real-time automated load step selection using scalar criteria derived prior to mechanical loading. The framework can be generalized to other geometries, boundary conditions and material models, allowing this procedure to be utilized for different experimental configurations and materials.
Fayad, Samuel S. [University of Illinois at Urbana↗
Application of a Temperature-Dependent Load Prediction Method to a RUAG Six-Component Block-Type Balance
Temperature-dependent data of a RUAG six-component block-type balance was analyzed to assess the accuracy of two load prediction methods for temperature-dependent balance data. The supplied data was prepared for the analysis by splitting it into calibration and check load data subsets. The first calibration data subset was obtained at a temperature of 294 Kelvin. The second calibration data subset was obtained at a temperature of 315 Kelvin. A subset of 38 points was extracted from the second data set and used as check loads so that the accuracy of the two load prediction methods could be tested. First, the Iterative Method in combination with an extended independent and dependent variable set was used for the balance load prediction. This approach fits electrical outputs as a function of loads and the temperature and, afterwards, constructs a load iteration scheme from the regression coefficients so that loads can be predicted from outputs and the temperature during a wind tunnel test. The Non-Iterative Method was also used for the load prediction. This alternate method can more easily be implemented in a data system as loads are directly fitted as a function of electrical outputs and the temperature. Analysis results for the axial force are only discussed in the paper as similar results were obtained for the other five load components. Results for both methods clearly show that the cross-product term constructed from either a primary gage load or a primary gage output and the temperature explains the majority of the temperature-dependent part of the predicted balance load. This term models the temperature dependent nature of the gage sensitivity. Therefore, it is recommended to apply primary gage loadings at different temperatures during a balance calibration whenever temperature effects need to be described. These loadings will contain information about the temperature-dependent nature of the gage sensitivities that can be quantified by related cross-product terms in regression models of the data.
strain-gage balance↗
A crack-closure model for predicting fatigue crack growth under aircraft spectrum loading
The present paper is concerned with the development and application of an analytical model of cyclic crack growth that includes the effects of crack closure. The model was based on a concept like the Dugdale model, but was modified to leave plastically deformed material in the wake of the advancing crack tip. The model was used to correlate crack growth rates under constant-amplitude loading and to predict crack growth under aircraft spectrum loading on 2219-T851 aluminum alloy plate material. The predicted crack growth lives agreed well with experimental data. The ratio of predicted-to-experimental lives ranged from 0.66 to 1.48.
Newman, J. C., Jr.↗
Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring
The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.
Spacecraft Structural Health Monitoring↗
Evidence for active hotspots on Venus from analysis of Magellan gravity data
The 500-Myr average crater retention age for Venus has raised questions about the present-day level of tectonic activity. In this study we examine the relationship between the gravity and topography of four large volcanic swells, Beta, Atla, Bell, and Western Eistla Regiones, for clues about their stage evolution. The Magellan line-of-sight gravity data are inverted using a point mass model of the anomalous mass to solve for the local vertical gravity field. Spectral admittance calculated from both the local gravity inversions and a spherical harmonic model is compared to three models of compensation: local compensation, a 'flexural' model with local and regional compensation of surface and subsurface loads, and a 'hotspot' model of compensation that includes top loading by volcanoes and subsurface loading due to a deep, low density mass anomaly. The coherence is also calculated in each region, but yields an elastic thickness estimate only at Bell Regio. In all models, the long wavelengths are compensated locally. Our results may indicate a relatively old, possibly inactive plume.
Smrekar, Suzanne E.↗
Simulink Model of a New Energy EVG-005 5kW Hydropower Turbine
Simulink model for a New Energy 5kW hydropower turbine. ADCP data ("ds_streamwise_7_13.nc") and DC voltage, DC current, and rotor rotation observed from the New Energy EVG-005 Current Energy Converter (CEC) ("electrical_7_13_10ohms.nc") were collected at the Tanana River Test Site (TRTS) near Nenana Alaska. - Data was collected on July 13th, 2023 with a constant 10 ohms resistance applied with a DC load bank. - Simulink model is meant to resemble the electrical setup at the TRTS. - Model is initialized by running the "NewEnergy_2023_10hz.m" Matlab script. Then the Simulink model ("New_Energy_Model_PMSM.slx") can be run. - Results are processed with the "NewEnergy_2023_processing.m" Matlab code. The Matlab results are also saved in the "New_Energy_7_13_model_validation_results.mat" Matlab file. This can be directly loaded into the Matlab Workspace using the "Load()" command. - The timetable variables "electrical_model_downsampled" is the model results and the "electrical_limited" is the experimental data from the TRTS.
16 TIDAL AND WAVE POWER↗