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At least 271 records · Page 15

Physics-Based Modeling and Simulation of Self-Reacting Friction Stir Welding Using Computational Fluid Dynamics

A physics-based model was developed to simulate the behavior of material in a self-reacting friction stir welding (SR-FSW) process for the joining of metals. This steady-state model builds upon fundamental computational fluid dynamic (CFD) principles within Ansys Fluent to solve the discretized equations. The effective viscosity is calculated using a viscoplastic model using a Sheppard-Wright formulation of flow stress. Numerous advancements have been made in the incorporated physics including (1) temperature-dependent material properties; (2) locally adaptable flow and thermal boundary conditions; and (3) adapting material properties in nugget in response to microstructural changes. Simulation strategies to accelerate computation and improve numerical stability include adapting the mesh refinement and solver relaxation factors during simulation. The result is a highly robust and computationally efficient model capable of providing the material flow and temperature history across the domain. As material history determines the local microstructure and ultimately weld strength, an accurate and detailed physics-based model has the potential to accelerate SR-FSW process development. The model is highly adaptable to changes in process parameters, tool design, or alloy.

Process Modeling↗

An improved output feedback control of flexible large space structures

A special output feedback control design technique for flexible large space structures is proposed. It is shown that the technique will increase both the damping and frequency of selected modes for more effective control. It is also able to effect integrated control of elastic and rigid-body modes and, in particular, closed-loop system stability and robustness to modal truncation and parameter variation. The technique is seen as marking an improvement over previous work concerning large space structures output feedback control.

Lin, Y. H.↗

Guaranteed properties for nonlinear gain scheduled control systems

An analysis is presented of two types of nonlinear gain-scheduled control systems: scheduling on a reference trajectory and scheduling on the plant output. Conditions are given which guarantee stability, robustness, and performance properties of the global gain-scheduled designs. These conditions confirm and formalize popular notions regarding gain-scheduled designs; e.g., that the scheduling variable should vary slowly and capture the plant's nonlinearities. These results extend the work of Shamma and Athans (1987), which addressed the case of linear plants whose dynamics depends on exogenous parameters.

Shamma, Jeff S.↗

Design of optimally normal minimum gain controllers by continuation method

A measure of the departure from normality is investigated for system robustness. An attractive feature of the normality index is its simplicity for pole placement designs. To allow a tradeoff between system robustness and control effort, a cost function consisting of the sum of a norm of weighted gain matrix and a normality index is minimized. First- and second-order necessary conditions for the constrained optimization problem are derived and solved by a Newton-Raphson algorithm imbedded into a one-parameter family of neighboring zero problems. The method presented allows the direct computation of optimal gains in terms of robustness and control effort for pole placement problems.

Lim, K. B.↗

On-Orbit Model Refinement for Controller Redesign

High performance control design for a flexible space structure is challenging since high fidelity plant models are difficult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. A new procedure for refining a multivariable open loop plant model based on closed-loop response data is presented. Using a minimal representation of the state space dynamics, a least squares prediction error method is employed to estimate the plant parameters. This control-relevant system identification procedure stresses the joint nature of the system identification and control design problem by seeking to obtain a model that minimizes the difference between the predicted and actual closed-loop performance. This paper presents an algorithm for iterative closed-loop system identification and controller redesign along with illustrative examples.

Whorton, Mark S.↗

Design of a robust multivariable proportional plus integral controller via spectral assignment

A new design procedure for a class of multivariable integral plus proportional servo control systems is presented. The procedure utilizes a null space formulation of the eigensystem assignment problem assuming complete state feedback. Reduced order observers are used to estimate unavailable states. The resulting system realizes arbitrary closed-loop eigenvalues, approximates specified modal behavior and achieves low eigensystem sensitivity with respect to plant parameter variations. A tutorial example to illustrate the design procedure is included.

Mielke, R. R.↗

Imaging spectrometry in the post-EOS era

It is argued that the next generation of imaging spectrometers will need greater capabilities and more flexibility than the High Resolution Imaging Spectrometer (HIRIS) and the Moderate Resolution Imaging Spectrometer (MODIS), which were designed for the first Earth Observation System platform. The emerging technology that represents a major advance in the scientific utility of imaging spectrometry is the acoustooptic tunable filters, (AOTFs). AOTFs are compact robust solid-state crystals which provide rapid (millisecond) electronically-controlled spectral tunability. This paper discusses the evolving requirements of imaging spectrometers and examines the basic system parameters of the HIRIS and the MODIS concepts involving the use of AOTFs, which will satisfy these requirements.

Duval, Valerie G.↗

Predictive and Neural Predictive Control of Uncertain Systems

Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

Kelkar, Atul G.↗

Asymptotic Linearity of Optimal Control Modification Adaptive Law with Analytical Stability Margins

Optimal control modification has been developed to improve robustness to model-reference adaptive control. For systems with linear matched uncertainty, optimal control modification adaptive law can be shown by a singular perturbation argument to possess an outer solution that exhibits a linear asymptotic property. Analytical expressions of phase and time delay margins for the outer solution can be obtained. Using the gradient projection operator, a free design parameter of the adaptive law can be selected to satisfy stability margins.

Nguyen, Nhan T.↗

Hypersonic vehicle model and control law development using H(infinity) and micron synthesis

The control system design for a Single Stage To Orbit (SSTO) air breathing vehicle will be central to a successful mission because a precise ascent trajectory will preserve narrow payload margins. The air breathing propulsion system requires the vehicle to fly roughly halfway around the Earth through atmospheric turbulence. The turbulence, the high sensitivity of the propulsion system to inlet flow conditions, the relatively large uncertainty of the parameters characterizing the vehicle, and continuous acceleration make the problem especially challenging. Adequate stability margins must be provided without sacrificing payload mass since payload margins are critical. Therefore, a multivariable control theory capable of explicitly including both uncertainty and performance is needed. The H(infinity) controller in general provides good robustness but can result in conservative solutions for practical problems involving structured uncertainty. Structured singular value mu framework for analysis and synthesis is potentially much less conservative and hence more appropriate for problems with tight margins. An SSTO control system requires: highly accurate tracking of velocity and altitude commands while limiting angle-of-attack oscillations, minimized control power usage, and a stabilized vehicle when atmospheric turbulence and system uncertainty are present. The controller designs using H(infinity) and mu-synthesis procedures were compared. An integrated flight/propulsion dynamic mathematical model of a conical accelerator vehicle was linearized as the vehicle accelerated through Mach 8. Vehicle acceleration through the selected flight condition gives rise to parametric variation that was modeled as a structured uncertainty. The mu-analysis approach was used in the frequency domain to conduct controller analysis and was confirmed by time history plots. Results demonstrate the inherent advantages of the mu framework for this class of problems.

Gregory, Irene M.↗

Cassini Attitude Control Fault Protection Design: Launch to End of Prime Mission Performance

The Cassini Attitude and Articulation Control Subsystem (AACS) Fault Protection (FP) has been successfully supporting operations for over 10 years from launch through the end of the prime mission. Cassini's AACS FP is complex, containing hundreds of error monitors and thousands of tunable parameters. Since launch there have been environmental, hardware, personnel and mission event driven changes which have required AACS FP to adapt and be robust to a variety of scenarios. This paper will discuss the process of monitoring, maintaining and updating the AACS FP during Cassini's lengthy prime mission as well as provide some insight into lessons learned during tour operations.

Meakin, Peter C.↗

Closed Loop System Identification with Genetic Algorithms

High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

Whorton, Mark S.↗

Ejecta Management in a Safe Lithium Ion Battery Design

As lithium-ion battery energy densities continue to rise, managing the heat and pressure generated during failure events has become increasingly critical. Safety systems must effectively relieve pressure without releasing sparks, flames, or particulate matter, requiring robust filtration solutions. The challenge is compounded by the reduced free volume available for gas expansion in high-density designs, which increases the demands on these filters. While significant progress has been made through experimental studies and modeling efforts to understand the behavior of ejecta during battery failures, there remains a pressing need for practical, rule-of-thumb sizing parameters. These parameters would help correlate high-energy waste streams with appropriate filter design, ensuring reliable containment and safety. This talk will explore recent experimental findings in this area and discuss the potential pathways for developing these essential sizing guidelines.

Ejecta Management↗

Exercise Equipment Usability Assessment for a Deep Space Concept Vehicle

With international aspirations to send astronauts to deep space, the world is now faced with the complex problem of keeping astronauts healthy in unexplored hostile environments for durations of time never before attempted by humans. The great physical demands imparted by space exploration compound the problem of astronaut health, as the astronauts must not only be healthy, but physically fit upon destination arrival in order to perform the scientific tasks required of them. Additionally, future deep space exploration necessitates the development of environments conducive to long-duration habitation that would supplement propulsive vehicles. Space Launch System (SLS) core stage barrel sections present large volumes of robust structure that can be recycled and used for long duration habitation. This assessment will focus on one such conceptual craft, referred to as the SLS Derived Habitat (SLS-DH). Marshall Space Flight Center's (MSFC) Advanced Concepts Office (ACO) has formulated a high-level layout of this SLS-DH with parameters such as floor number and orientation, floor designations, grid dimensions, wall placement, etc. Yet to be determined, however, is the layout of the exercise area. Currently the SLS-DH features three floors laid out longitudinally, leaving 2m of height between the floor and ceilings. This short distance between levels introduces challenges for proper placement of exercise equipment such as treadmills and stationary bicycles, as the dynamic envelope for the 95th percentile male astronauts is greater than 2m. This study aims to assess the optimal equipment layout and sizing for the exercise area of this habitat. Figure 1 illustrates the layout of the DSH concept demonstrator located at MSFC. The exercise area is located on the lower level, seen here as the front half of the level occupied by a crew member. This small volume does not allow for numerous or bulky exercise machines, so the conceptual equipment has been limited to a treadmill and stationary bicycle. With the most current treadmill aboard the International Space Station (ISS), the Combined Operational Load-Bearing External Resistance Treadmill (COLBERT), being located in an International Standard Payload Rack (ISPR), the bottom of the conceptual treadmill features a height of 38in. Making the treadmill flush with the floor would be impossible in this rack configuration, as the distance from the outer wall of the spacecraft to the bottom floor would be too shallow. From preliminary sizing, the 38in required for the bottom of the treadmill combined with a 78in operational envelope for a 95th percentile may not be accommodated in the exercise area in a vertical orientation. Figure 2 demonstrates the volume required (in maroon) for an ISPR-bound treadmill in the concept demonstrator. Early indications as seen in this figure indicate that the crew members would contact the ceiling in such an arrangement. An assessment will be conducted to evaluate various orientations of exercise equipment in the concept demonstrator. Orientations to be tested include putting the bottom of the treadmill on the wall, having the treadmill at an angle in the floor both horizontally and vertically, and having a shorter (non-rack bound) treadmill in a vertical orientation on the floor. This assessment will yield findings regarding sizing of the area and how well participants feel they could exercise in such an environment. Due to the restrictions of assessing a microgravity vehicle in a normal-gravity environment, simulations in MSFC's Virtual Environments Lab (VEL) may be necessary. Final deliverables will include recommendations regarding the location and size of possible exercise equipment aboard the SLS-Derived DSH.

Rhodes, Brooke M.↗

Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics

This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.

Rohrs, C. E.↗

Hard Constraints in Optimization Under Uncertainty

This paper proposes a methodology for the analysis and design of systems subject to parametric uncertainty where design requirements are specified via hard inequality constraints. Hard constraints are those that must be satisfied for all parameter realizations within a given uncertainty model. Uncertainty models given by norm-bounded perturbations from a nominal parameter value, i.e., hyper-spheres, and by sets of independently bounded uncertain variables, i.e., hyper-rectangles, are the focus of this paper. These models, which are also quite practical, allow for a rigorous mathematical treatment within the proposed framework. Hard constraint feasibility is determined by sizing the largest uncertainty set for which the design requirements are satisfied. Analytically verifiable assessments of robustness are attained by comparing this set with the actual uncertainty model. Strategies that enable the comparison of the robustness characteristics of competing design alternatives, the description and approximation of the robust design space, and the systematic search for designs with improved robustness are also proposed. Since the problem formulation is generic and the tools derived only require standard optimization algorithms for their implementation, this methodology is applicable to a broad range of engineering problems.

Crespo, Luis G.↗

An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval

Machine learning (ML) is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using ML algorithms for atmospheric retrieval by implementing a random forest (RF) to perform retrievals in seconds that are consistent with the traditional, computationally expensive nested-sampling retrieval method. We expand upon their approach by presenting a new ML model, plan-net, based on an ensemble of Bayesian neural networks (BNNs) that yields more accurate inferences than the RF for the same data set of synthetic transmission spectra. We demonstrate that an ensemble provides greater accuracy and more robust uncertainties than a single model. In addition to being the first to use BNNs for atmospheric retrieval, we also introduce a new loss function for BNNs that learns correlations between the model outputs. Importantly, we show that designing ML models to explicitly incorporate domain-specific knowledge both improves performance and provides additional insight by inferring the covariance of the retrieved atmospheric parameters. We apply plan-net to the Hubble Space Telescope Wide Field Camera 3 transmission spectrum for WASP-12b and retrieve an isothermal temperature and water abundance consistent with the literature. We highlight that our method is flexible and can be expanded to higher resolution spectra and a larger number of atmospheric parameters.

Adam D. Cobb↗

Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter: Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics - Pt. 2

A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

Menard, Richard↗