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At least 865 records · Page 48

Modeling of Non-Isothermal Cryogenic Fluid Sloshing

A computational fluid dynamic model was used to simulate the thermal destratification in an upright self-pressurized cryostat approximately half-filled with liquid nitrogen and subjected to forced sinusoidal lateral shaking. A full three-dimensional computational grid was used to model the tank dynamics, fluid flow and thermodynamics using the ANSYS Fluent code. A non-inertial grid was used which required the addition of momentum and energy source terms to account for the inertial forces, energy transfer and wall reaction forces produced by the shaken tank. The kinetics-based Schrage mass transfer model provided the interfacial mass transfer due to evaporation and condensation at the sloshing interface. The dynamic behavior of the sloshing interface, its amplitude and transition to different wave modes, provided insight into the fluid process at the interface. The tank pressure evolution and temperature profiles compared relatively well with the shaken cryostat experimental test data provided by the Centre National D'Etudes Spatiales.

Cryogenics↗

Advanced superposition methods for high speed turbopump vibration analysis

The small, high pressure Mark 48 liquid hydrogen turbopump was analyzed and dynamically tested to determine the cause of high speed vibration at an operating speed of 92,400 rpm. This approaches the design point operating speed of 95,000 rpm. The initial dynamic analysis in the design stage and subsequent further analysis of the rotor only dynamics failed to predict the vibration characteristics found during testing. An advanced procedure for dynamics analysis was used in this investigation. The procedure involves developing accurate dynamic models of the rotor assembly and casing assembly by finite element analysis. The dynamically instrumented assemblies are independently rap tested to verify the analytical models. The verified models are then combined by modal superposition techniques to develop a completed turbopump model where dynamic characteristics are determined. The results of the dynamic testing and analysis obtained are presented and methods of moving the high speed vibration characteristics to speeds above the operating range are recommended. Recommendations for use of these advanced dynamic analysis procedures during initial design phases are given.

Nielson, C. E.↗

Active vibration control using a modal-domain fiber optic sensor

A closed-loop control experiment is described in which vibrations of a cantilevered beam are suppressed using measurements from a modal-domain fiber optic sensor. Modal-domain sensors are interference between the modes of a few-mode optical waveguide to detect strain. The fiber is bonded along the length of the beam and provides a measurement related to the strain distribution on the surface of the beam. A model for the fiber optic sensor is derived, and this model is integrated with the dynamic model of the beam. A piezoelectric actuator is also bonded to the beam and used to provide control forces. Control forces are obtained through dynamic compensation of the signal from the fiber optic sensor. The compensator is implemented with a real-time digital controller. Analytical models are verified by comparing simulations to experimental results for both open-loop and closed-loop configurations.

Cox, David E.↗

Engineering Risk Assessment of Space Thruster Challenge Problem

The Engineering Risk Assessment (ERA) team at NASA Ames Research Center utilizes dynamic models with linked physics-of-failure analyses to produce quantitative risk assessments of space exploration missions. This paper applies the ERA approach to the baseline and extended versions of the PSAM Space Thruster Challenge Problem, which investigates mission risk for a deep space ion propulsion system with time-varying thruster requirements and operations schedules. The dynamic mission is modeled using a combination of discrete and continuous-time reliability elements within the commercially available GoldSim software. Loss-of-mission (LOM) probability results are generated via Monte Carlo sampling performed by the integrated model. Model convergence studies are presented to illustrate the sensitivity of integrated LOM results to the number of Monte Carlo trials. A deterministic risk model was also built for the three baseline and extended missions using the Ames Reliability Tool (ART), and results are compared to the simulation results to evaluate the relative importance of mission dynamics. The ART model did a reasonable job of matching the simulation models for the baseline case, while a hybrid approach using offline dynamic models was required for the extended missions. This study highlighted that state-of-the-art techniques can adequately adapt to a range of dynamic problems.

Assessment↗

Quasi One-Dimensional Unsteady Modeling of External Compression Supersonic Inlets

The AeroServoElasticity task under the NASA Supersonics Project is developing dynamic models of the propulsion system and the vehicle in order to conduct research for integrated vehicle dynamic performance. As part of this effort, a nonlinear quasi 1-dimensional model of an axisymmetric external compression supersonic inlet is being developed. The model utilizes compressible flow computational fluid dynamics to model the internal inlet segment as well as the external inlet portion between the cowl lip and normal shock, and compressible flow relations with flow propagation delay to model the oblique shocks upstream of the normal shock. The external compression portion between the cowl-lip and the normal shock is also modeled with leaking fluxes crossing the sonic boundary, with a moving CFD domain at the normal shock boundary. This model has been verified in steady state against tunnel inlet test data and it s a first attempt towards developing a more comprehensive model for inlet dynamics.

Kopasakis, George↗

A large-signal dynamic simulation for the series resonant converter

A simple nonlinear discrete-time dynamic model for the series resonant dc-dc converter is derived using approximations appropriate to most power converters. This model is useful for the dynamic simulation of a series resonant converter using only a desktop calculator. The model is compared with a laboratory converter for a large transient event.

King, R. J.↗

Dynamic Altitude Simulation System Performance Modeling

The "Dynamic Altitude Simulation Prediction Program," DASSPP, is a program to predict the transient response of an engine, test cell, ejector system under engine shutdown conditions. These transients are important to know so that corrective modifications can be adapted to prevent any damage to the engine or test cell. The "Dynamic Altitude System Simulation Prediction Program," DASSPP, is a major rewrite of the existing program "RL-1000" written in BASIC. The RL-1000 program was written to analyze the transients of the RL-10 system only. The new program is written to run in Excell 97 and utilizes the Visual BASIC language in Excell. The program has many added features not included in the original "Rl-1000" program. The program utilizes the ejector models developed during the summer of 1997. The new program is very user friendly and utilizes a dialog box for data input.

LaFrance, Leo J.↗

Investigation of turbulent processes in magnetospheric boundary layers

A self-consistent non-evolving two dimensional slab model of a viscous low-latitude boundary layer (LLBL) coupled to the ionosphere was developed by Phan, et al., (1989). Numerical results from the model and possible use of observations to determine the model parameters are discussed. The dynamical model developed by Lotko, et al., (1987) was used by Lotko and Shen (1991) to examine dynamical processes relevant to the LLBL with particular application to post-noon auroral shear layers. Initial results from a magnetohydrodynamic study of flank-side mangetopause boundary configuration are described. Effects of compressibility, scalar viscosity, and electrical resistivity are included in the MHD equations.

Lotko, William↗

Integration of finite element modeling with solid modeling through a dynamic interface

Finite element modeling is dominated by geometric modeling type operations. Therefore, an effective interface to geometric modeling requires access to both the model and the modeling functionality used to create it. The use of a dynamic interface that addresses these needs through the use of boundary data structures and geometric operators is discussed.

Shephard, Mark S.↗

Flight-Test Validation and Flying Qualities Evaluation of a Rotorcraft UAV Flight Control System

This paper presents a process of design and flight-test validation and flying qualities evaluation of a flight control system for a rotorcraft-based unmanned aerial vehicle (RUAV). The keystone of this process is an accurate flight-dynamic model of the aircraft, derived by using system identification modeling. The model captures the most relevant dynamic features of our unmanned rotorcraft, and explicitly accounts for the presence of a stabilizer bar. Using the identified model we were able to determine the performance margins of our original control system and identify limiting factors. The performance limitations were addressed and the attitude control system was 0ptimize.d for different three performance levels: slow, medium, fast. The optimized control laws will be implemented in our RUAV. We will first determine the validity of our control design approach by flight test validating our optimized controllers. Subsequently, we will fly a series of maneuvers with the three optimized controllers to determine the level of flying qualities that can be attained. The outcome enable us to draw important conclusions on the flying qualities requirements for small-scale RUAVs.

Mettler, Bernard↗

Dynamic wind-tunnel tests of an aeromechanical gust-alleviation system using several different combinations of control surfaces

Some experimental results are presented from wind tunnel studies of a dynamic model equipped with an aeromechanical gust alleviation system for reducing the normal acceleration response of light airplanes. The gust alleviation system consists of two auxiliary aerodynamic surfaces that deflect the wing flaps through mechanical linkages when a gust is encountered to maintain nearly constant airplane lift. The gust alleviation system was implemented on a 1/6-scale, rod mounted, free flying model that is geometrically and dynamically representative of small, four place, high wing, single engine, light airplanes. The effects of flaps with different spans, two size of auxiliary aerodynamic surfaces, plain and double hinged flaps, and a flap elevator interconnection were studied. The model test results are presented in terms of predicted root mean square response of the full scale airplane to atmospheric turbulence. The results show that the gust alleviation system reduces the root mean square normal acceleration response by 30 percent in comparison with the response in the flaps locked condition. Small reductions in pitch-rate response were also obtained. It is believed that substantially larger reductions in normal acceleration can be achieved by reducing the rather high levels of mechanical friction which were extant in the alleviation system of the present model.

Stewart, E. C.↗

Effects of model deficiencies on parameter estimation

Reliable structural dynamic models will be required as a basis for deriving the reduced-order plant models used in control systems for large space structures. Ground vibration testing and model verification will play an important role in the development of these models; however, fundamental differences between the space environment and earth environment, as well as variations in structural properties due to as-built conditions, will make on-orbit identification essential. The efficiency, and perhaps even the success, of on-orbit identification will depend on having a valid model of the structure. It is envisioned that the identification process will primarily involve parametric methods. Given a correct model, a variety of estimation algorithms may be used to estimate parameter values. This paper explores the effects of modeling errors and model deficiencies on parameter estimation by reviewing previous case histories. The effects depend at least to some extent on the estimation algorithm being used. Bayesian estimation was used in the case histories presented here. It is therefore conceivable that the behavior of an estimation algorithm might be useful in detecting and possibly even diagnosing deficiencies. In practice, the task is complicated by the presence of systematic errors in experimental procedures and data processing and in the use of the estimation procedures themselves.

Hasselman, T. K.↗

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗

Development of a Linear Stirling System Model with Varying Heat Inputs

The linear model of the Stirling system developed by NASA Glenn Research Center (GRC) has been extended to include a user-specified heat input. Previously developed linear models were limited to the Stirling convertor and electrical load. They represented the thermodynamic cycle with pressure factors that remained constant. The numerical values of the pressure factors were generated by linearizing GRC's nonlinear System Dynamic Model (SDM) of the convertor at a chosen operating point. The pressure factors were fixed for that operating point, thus, the model lost accuracy if a transition to a different operating point were simulated. Although the previous linear model was used in developing controllers that manipulated current, voltage, and piston position, it could not be used in the development of control algorithms that regulated hot-end temperature. This basic model was extended to include the thermal dynamics associated with a hot-end temperature that varies over time in response to external changes as well as to changes in the Stirling cycle. The linear model described herein includes not only dynamics of the piston, displacer, gas, and electrical circuit, but also the transient effects of the heater head thermal inertia. The linear version algebraically couples two separate linear dynamic models, one model of the Stirling convertor and one model of the thermal system, through the pressure factors. The thermal system model includes heat flow of heat transfer fluid, insulation loss, and temperature drops from the heat source to the Stirling convertor expansion space. The linear model was compared to a nonlinear model, and performance was very similar. The resulting linear model can be implemented in a variety of computing environments, and is suitable for analysis with classical and state space controls analysis techniques.

Regan, Timothy F.↗

Stage Separation Performance Analysis Project

Stage separation process is an important phenomenon in multi-stage launch vehicle operation. The transient flowfield coupled with the multi-body systems is a challenging problem in design analysis. The thermodynamics environment with burning propellants during the upper-stage engine start in the separation processes adds to the complexity of the-entire system. Understanding the underlying flow physics and vehicle dynamics during stage separation is required in designing a multi-stage launch vehicle with good flight performance. A computational fluid dynamics model with the capability to coupling transient multi-body dynamics systems will be a useful tool for simulating the effects of transient flowfield, plume/jet heating and vehicle dynamics. A computational model using generalize mesh system will be used as the basis of this development. The multi-body dynamics system will be solved, by integrating a system of six-degree-of-freedom equations of motion with high accuracy. Multi-body mesh system and their interactions will be modeled using parallel computing algorithms. Adaptive mesh refinement method will also be employed to enhance solution accuracy in the transient process.

Chen, Yen-Sen↗

Development of a Linear Stirling Model with Varying Heat Inputs

The linear model of the Stirling system developed by NASA Glenn Research Center (GRC) has been extended to include a user-specified heat input. Previously developed linear models were limited to the Stirling convertor and electrical load. They represented the thermodynamic cycle with pressure factors that remained constant. The numerical values of the pressure factors were generated by linearizing GRC s non-linear System Dynamic Model (SDM) of the convertor at a chosen operating point. The pressure factors were fixed for that operating point, thus, the model lost accuracy if a transition to a different operating point were simulated. Although the previous linear model was used in developing controllers that manipulated current, voltage, and piston position, it could not be used in the development of control algorithms that regulated hot-end temperature. This basic model was extended to include the thermal dynamics associated with a hot-end temperature that varies over time in response to external changes as well as to changes in the Stirling cycle. The linear model described herein includes not only dynamics of the piston, displacer, gas, and electrical circuit, but also the transient effects of the heater head thermal inertia. The linear version algebraically couples two separate linear dynamic models, one model of the Stirling convertor and one model of the thermal system, through the pressure factors. The thermal system model includes heat flow of heat transfer fluid, insulation loss, and temperature drops from the heat source to the Stirling convertor expansion space. The linear model was compared to a nonlinear model, and performance was very similar. The resulting linear model can be implemented in a variety of computing environments, and is suitable for analysis with classical and state space controls analysis techniques.

Regan, Timothy F.↗