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At least 829 records · Page 46

Aeroelastic analysis for helicopter rotors with blade appended pendulum vibration absorbers. Mathematical derivations and program user's manual

Mathematical development is presented for the expanded capabilities of the United Technologies Research Center (UTRC) G400 Rotor Aeroelastic Analysis. This expanded analysis, G400PA, simulates the dynamics of teetered rotors, blade pendulum vibration absorbers and the higher harmonic excitations resulting from prescribed vibratory hub motions and higher harmonic blade pitch control. Formulations are also presented for calculating the rotor impedance matrix appropriate to these higher harmonic blade excitations. This impedance matrix and the associated vibratory hub loads are intended as the rotor blade characteristics elements for use in the Simplified Coupled Rotor/Fuselage Vibration Analysis (SIMVIB). Sections are included presenting updates to the development of the original G400 theory, and material appropriate to the user of the G400PA computer program. This material includes: (1) a general descriptionof the tructuring of the G400PA FORTRAN coding, (2) a detaild description of the required input data and other useful information for successfully running the program, and (3) a detailed description of the output results.

Bielawa, R. L.↗

Design and control strategies for CELSS - Integrating mechanistic paradigms and biological complexities

Systems analysis and control theory consideration are given to simulations of both individual components and total systems, in order to develop a reliable control strategy for a Controlled Ecological Life Support System (CELSS) which includes complex biological components. Because of the numerous nonlinearities and tight coupling within the biological component, classical control theory may be inadequate and the statistical analysis of factorial experiments more useful. The range in control characteristics of particular species may simplify the overall task by providing an appropriate balance of stability and controllability to match species function in the overall design. The ultimate goal of this research is the coordination of biological and mechanical subsystems in order to achieve a self-supporting environment.

Moore, B., III↗

Application of the SWINT code to wing/body/tail geometries

Pressure and force calculations from the SWINT Euler code are presented and analyzed for a variety of configurations ranging from simple axisymmetric bodies to complex bodies with wings, tails, and inlets at speeds covering the supersonic Mach number range. The SWINT results are compared with both experimental data and with results from simpler computational methods to assess the increased accuracy from the Euler solution. It is shown that SWINT gives excellent results on axisymmetric bodies for attached flow; however, a better method of simulating the separation process on such bodies is needed for increased leeside accuracy. Good leeside accuracy, however, is found on a 3 to 1 elliptical body. It is shown that SWINT gives realistic downstream interference effects, resulting in good predictions of the overall aerodynamics for complex wing-body-tail geometries. The QUICK-geometry system has been coupled with SWINT code to provide a simplified geometry definition procedure for complex bodies. The QUICK method is shown to be a preferable alternative to the current method of inserting the body description directly into the code by FORTRAN statements.

Allen, J. M.↗

Disturbance and vibration isolation in space stations by means of mechanical decoupling

A decoupling approach to disturbance and vibration isolation in large space stations composed of modules interconnected by flexible members is proposed. A simplified mathematical model for the motion of the space station core and a laboratory module with both torsional vibration and translational motion decouplers is used in this study. The dynamic behavior of the model in the presence of decoupler friction is analyzed. Estimates for the maximum excursions of the laboratory module induced by various types of external disturbance are derived. The paper concludes with a simulation study involving the hard-docking of a space shuttle with a space station.

Wang, P. K. C.↗

Magnetic Susceptibility Effects and Lorentz Damping in Diamagnetic Fluids

A great number of crystals (semi-conductor and protein) grown in space are plagued by convective motions which contribute to structural flaws. The character of these instabilities is not well understood but is associated with density variations in the presence of residual gravity and g-jitter. Both static and dynamic (rotating or travelling wave) magnetic fields can be used to reduce the effects of convection in materials processing. In semi-conductor melts, due to their relatively high electrical conductivity, the induced Lorentz force can be effectively used to curtail convective effects. In melts/solutions with reduced electrical conductivity, such as aqueous solutions used in solution crystal growth, protein crystal growth and/or model fluid experiments for simulating melt growth, however, the variation of the magnetic susceptibility with temperature and/or concentration can be utilized to better damp fluid convection than the Lorentz force method. This paper presents a comprehensive, comparative numerical study of the relative damping effects using static magnetic fields and gradients in a simple geometry subjected to a thermal gradient. The governing equations are formulated in general terms and then simplified for the numerical calculations. Operational regimes, based on the best damping technique for different melts/solutions are identified based on fluid properties. Comparisons are provided between the numerical results and available results from experiments in surveyed literature.

Ramachandran, Narayanan↗

Modeling and Analysis of the Reverse Water Gas Shift Process for In-Situ Propellant Production

This report focuses on the development of mathematical models and simulation tools developed for the Reverse Water Gas Shift (RWGS) process. This process is a candidate technology for oxygen production on Mars under the In-Situ Propellant Production (ISPP) project. An analysis of the RWGS process was performed using a material balance for the system. The material balance is very complex due to the downstream separations and subsequent recycle inherent with the process. A numerical simulation was developed for the RWGS process to provide a tool for analysis and optimization of experimental hardware, which will be constructed later this year at Kennedy Space Center (KSC). Attempts to solve the material balance for the system, which can be defined by 27 nonlinear equations, initially failed. A convergence scheme was developed which led to successful solution of the material balance, however the simplified equations used for the gas separation membrane were found insufficient. Additional more rigorous models were successfully developed and solved for the membrane separation. Sample results from these models are included in this report, with recommendations for experimental work needed for model validation.

Whitlow, Jonathan E.↗

A Methodology to Assess the Capability of Engine Designs to Meet Closed-Loop Performance and Operability Requirements

Designing a closed-loop controller for an engine requires balancing trade-offs between performance and operability of the system. One such trade-off is the relationship between the 95 percent response time and minimum high-pressure compressor (HPC) surge margin (SM) attained during acceleration from idle to takeoff power. Assuming a controller has been designed to meet some specification on response time and minimum HPC SM for a mid-life (nominal) engine, there is no guarantee that these limits will not be violated as the engine ages, particularly as it reaches the end of its life. A characterization for the uncertainty in this closed-loop system due to aging is proposed that defines elliptical boundaries to estimate worst-case performance levels for a given control design point. The results of this characterization can be used to identify limiting design points that bound the possible controller designs yielding transient results that do not exceed specified limits in response time or minimum HPC SM. This characterization involves performing Monte Carlo simulation of the closed-loop system with controller constructed for a set of trial design points and developing curve fits to describe the size and orientation of each ellipse; a binary search procedure is then employed that uses these fits to identify the limiting design point. The method is demonstrated through application to a generic turbofan engine model in closed-loop with a simplified controller; it is found that the limit for which each controller was designed was exceeded by less than 4.76 percent. Extension of the characterization to another trade-off, that between the maximum high-pressure turbine (HPT) entrance temperature and minimum HPC SM, showed even better results: the maximum HPT temperature was estimated within 0.76 percent. Because of the accuracy in this estimation, this suggests another limit that may be taken into consideration during design and analysis. It also demonstrates the extension of the characterization to other attributes that contribute to the performance or operability of the engine. Metrics are proposed that, together, provide information on the shape of the trade-off between response time and minimum HPC SM, and how much each varies throughout the life cycle, at the limiting design points. These metrics also facilitate comparison of the expected transient behavior for multiple engine models.

systems analysis↗

Distortion Representation of Forecast Errors for Model Skill Assessment and Objective Analysis

We completed the formulation of the smoothness penalty functional this past quarter. We used a simplified procedure for estimating the statistics of the FCA solution spectral coefficients from the results of the unconstrained, low-truncation FCA (stopping criterion) solutions. During the current reporting period we have completed the calculation of GEOS-2 model-equivalent brightness temperatures for the 6.7 micron and 11 micron window channels used in the GOES imagery for all 10 cases from August 1999. These were simulated using the AER-developed Optimal Spectral Sampling (OSS) model.

Hoffman, Ross N.↗

Ion Thruster Discharge Performance Per Magnetic Field Topography

DC-ION is a detailed computational model for predicting the plasma characteristics of rain-cusp ion thrusters. The advanced magnetic field meshing algorithm used by DC-ION allows precise treatment of the secondary electron flow. This capability allows self-consistent estimates of plasma potential that improves the overall consistency of the results of the discharge model described in Reference [refJPC05mod1]. Plasma potential estimates allow the model to predict the onset of plasma instabilities, and important shortcoming of the previous model for optimizing the design of discharge chambers. A magnetic field mesh simplifies the plasma flow calculations, for both the ions and the secondary electrons, and significantly reduces numerical diffusion that can occur with meshes not aligned with the magnetic field. Comparing the results of this model to experimental data shows that the behavior of the primary electrons, and the precise manner of their confinement, dictates the fundamental efficiency of ring-cusp. This correlation is evident in simulations of the conventionally sized NSTAR thruster (30 cm diameter) and the miniature MiXI thruster (3 cm diameter).

plasma processes↗

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗

Consistent large-eddy simulation of a temporal mixing layer laden with evaporating drops : Part 1. Direct numerical simulation formulation and a priori analysis

This paper is organized as follows. In § 2, we present the DNS formulation. This formulation consists of a set of coupled conservation equations for the gas phase and the liquid phase (i.e. the drops). The coupling describing the interaction between the two phases is provided in the gas-phase conservation equations by source terms. In § 3, we analyse the DNS results; in particular, we evaluate the adopted form of the heat and mass fluxes. The gas-phase LES equations are developed in § 4 and assumptions that may simplify these equations are examined using the DNS database. Thereafter, the contribution of the source terms is examined by considering the budget of the LES equations. The final form of the LES equations are then presented, in which only the SGS fluxes and the FSTs need be modelled. A parallel perspective on the importance of the source terms is presented in § 5, wherein the irreversible entropy production (i.e. the dissipation) expression for two-phase flow with phase change is derived and evaluated for transitional DNS and the filtered flow fields. Models for the FSTs appearing in the LES equations are investigated in § 6, while several constantcoefficient SGS models are proposed and calibrated in § 7. The present study aims to create simple models so that the modelling approach can be validated by means of an SGS models are proposed and calibrated in § 7. The present study aims to create simple models so that the modelling approach can be validated by means of an a posteriori study.

"Okong'o, Nora A.", 'Bellan, Josette↗

Flight test of a trajectory controller using linearizing transformations with measurement feedback

The design of nonlinear controllers has relied on the use of detailed aerodynamic and engine models that must be associated with the control law in the flight system implementation. Many of these controllers have been applied to vehicle flightpath control problems and have attempted to combine both inner- and outer-loop control functions in a single controller. This paper presents an alternate approach to the design of outer-loop controllers. The approach simplifies the outer-loop design problem by separating the inner-loop (stabilization and control) from the outer-loop (guidance and navigation) functions. Linearizing transformations are applied using measurement feedback to eliminate the need for detailed aircraft models in outer-loop control applications. Also discussed is an implementation of the controller. This implementation was tested on a six-degree-of-freedom F-15 simulation and in flight on an F-15 aircraft. Proof of the concept is provided by flight test data which is presented and discussed.

Antoniewicz, Robert F.↗

Direct simulations of wall-bounded compressible turbulence

A study has been initiated on the effects of compressibility (Mach number) on turbulent boundary layers. An understanding of both qualitative (turbulence structures, physical processes) and quantitative (turbulence statistics) effects are desired. This understanding should lead to better turbulence models for applications involving supersonic wall-bounded flows. Direct numerical simulations of an idealized problem will be used to accomplish these objectives. Among several possibilities we chose plane Couette flow with constant-temperature walls as the first problem to be studied. The lack of mean streamwise pressure gradient plus isothermal walls implies that both horizontal directions can be assumed to be homogeneous and that the flow can reach a statistically steady state. Together, these features greatly simplify the calculations and analyses of the results. To date, an algorithm has been developed and implemented (but not yet fully tested) for the accurate solution of the Navier-Stokes equations with the assumptions noted above.

Buell, J. C.↗

Computational Simulation of Composite Behavior

Composite microfracture technique developed here is based on the concept of global strain energy release rate. Step-by-step procedures were outlined to evaluate composite microfracture. The technique can predict microfracture initiation/propagation, predict the "structural fracture toughness", and establish the hierarchy of fracture modes. Both unidirectional and cross-ply metal-matrix composite laminates were evaluated for microfracture, subjected to thermal and mechanical loads. Five NASA reports were published as shown in the bibliography and several presentations were made at the technical conferences/ symposia. Work was also performed to develop simplified micromechanics and macromechanics for ceramic matrix composites. A novel fiber sub-structuring technique was developed, which divides the fiber into several "slices" and applies the micromechanics equation at the "slice" level, which are then integrated upwards to get the ply and the laminate properties. It allows for a more accurate representation of interfacial conditions such as partial interface bond etc. It also predicts the stress-strain behavior of a composite up to failure by taking into account material properties dependence upon temperature as well as stress redistribution that occurs due to damage initiation and propagation. A computer code CEMCAN (Ceramic Matrix Composites Analyzer) which includes all these capabilities has been developed as a part of this research activity.

Keith, Theo G., Jr.↗

Large Eddy Simulation of Homogeneous Rotating Turbulence

Study of turbulent flows in rotating reference frames has proven to be one of the more challenging areas of turbulence research. The large number of theoretical, experimental, and computational studies performed over the years have demonstrated that the effect of solid-body rotation on turbulent flows is subtle and remains exceedingly difficult to predict. Because of the complexities associated with non-homogeneous turbulence, it is worthwhile to examine the effect of steady system rotation on the evolution of an initially isotropic turbulent flow. The assumption of statistical homogeneity considerably simplifies analysis and computation; calculation of homogeneous turbulence is further motivated since it possesses the essential physics found in more complex rotating flows. The principal objectives of the present study have therefore been to increase our fundamental understanding of turbulent flows in rotating reference frames through an examination of the asymptotic state of homogeneous rotating turbulence; particularly as to the existence of an asymptotic state which is self similar. Knowledge of an asymptotic similarity state permits prediction of the ultimate statistical evolution of the flow without requiring detailed knowledge of the complex, and not well understood, non-linear transfer processes. Aside from examination of possible similarity states in rotating turbulence, of further interest in this study has been an examination of the degree to which solid-body rotation induces a two-dimensional state in an initially isotropic flow.

Squires, Kyle D.↗

General aviation single pilot IFR autopilot study

Five levels of autopilot complexity were flown in a single engine instrument flight rules (IFR) simulation for several different IFR terminal operations. A comparison was made of the five levels of complexity ranging from no-autopilot to a fully coupled lateral and vertical guidance mode to determine the relative benefits vs. complexity/cost of state of the art autopilot capability in the IFR terminal area. Of the five levels tested, the heading select mode made the largest relative difference in decreasing workload and simplifying the approach task. It was also found that the largest number of blunders was detected with the most highly automated mode. The data also showed that, regardless of the autopilot mode, performance during an IFR approach was highly dependent on the type of approach being flown. These results indicate that automation can be useful when making IFR approaches in a high workload environment, but also that some disturbing trends are associated with some of the higher levels of automation found in state of the art autopilots.

Bergeron, H. P.↗

Modelling of polymer photodegradation for solar cell modules

A computer model including an integration routine was developed and demonstrated to simulate, in principle, the chemical changes which may occur in the photooxidation of hydrocarbons, using as input data a set of elementary reactions, corresponding rate constants and appropriate starting conditions. Application of this model to the photooxidation of pottant and plastic materials used in the LSA module designs provides a reliable predictive capability regarding the useful lifetime of these materials. An earlier mechanism consisting of 46 reactions was simplified considerably by reducing the number of formal termination steps since it became apparent that the major termination process goes via the peroxy radicals. In addition, new reactions of oxygen with acryl radicals (from Norrish type I) to form peracids, which then decompose to form carbon dioxide are included.

Somersall, A. C.↗