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Papers on the following subjects are presented: (1) multivariable flight control synthesis and literal robustness analysis for an aeroelastic vehicles; (2) numerical and literal aeroelastic-vehicle-model reduction for feedback control synthesis; and (3) dynamics of aerospace vehicles.
An order (n) multiflex body Space Station simulation tool is introduced. The flex multibody modeling is generic enough to model all phases of Space Station from build up through to Assembly Complete configuration and beyond. Multibody subsystems such as the Mobile Servicing System (MSS) undergoing a prescribed translation and rotation are also allowed. The software includes aerodynamic, gravity gradient, and magnetic field models. User defined controllers can be discrete or continuous. Extensive preprocessing of 'body by body' NASTRAN flex data is built in. A significant aspect, too, is the integrated controls design capability which includes model reduction and analytic linearization.
In situ gravimetric measurements and microscopic examinations were used to determine the mechanisms of oxygen removal from synthetic ilmenite disks between 823 and 1353 K. Under a hydrogen atmosphere, iron was observed to form a layer of low porosity on the surface of samples early in the reduction. This created diffusion limitations for hydrogen to the reaction front and for the escape of water vapor. A shrinking core reduction model, modified to include the growth of this iron film, was capable of predicting the conversion-time relationships of ilmenite samples. An activation energy of 43.2 +/- 2.6 kcal/gmole was determined to be representative of reaction control over the temperature range 823-1023 K.
The underlying mathematical formulation and issues associated with integrated control, structure, and optical design are discussed. Topics addressed include the development of cost functionals, optimization in the vector objective setting, and computational aspects of the optimization problem with special emphasis on model reduction strategies. Results on simple design problems are presented.
A general discrete methodology for modeling the dynamics of a mass that moves on the surface of a flexible structure is developed. This problem was motivated by the Space Station/Mobile Transporter system. A model reduction approach is developed to make the methodology applicable to large structural systems. To validate the discrete methodology, continuous formulations are also developed. Three different systems are examined: (1) simply-supported beam, (2) free-free beam, and (3) free-free beam with two points of contact between the mass and the flexible beam. In addition to validating the methodology, parametric studies were performed to examine how the system's physical properties affect its dynamics.
This paper presents a general methodology for modeling the dynamics of a flexible structure which moves on the surface of another flexible structure. The relative motion of the two bodies need not follow a straight line, nor need the contact surfaces be planar in their undeformed state. A model reduction approach is also developed, which makes the methodology applicable to large structural systems. The Space Station Freedom Mobile Transporter represents one such system, when attached to the Shuttle Orbiter. Numerical examples are provided.
Relationships between Hankel singular values of a structure with a proof-mass actuator to those of a structure with an ideal actuator are analyzed. They indicate that the proof-mass actuator has little influence on Hankel singular values of a structure if the natural frequency of the actuator is much lower than the structural frequencies. This fact significantly simplifies controllability/observability analysis and model reduction of flexible structures. Results from numerical simulations verify the conclusions.
Embedded piezoelectric devices may be ideally suited for vibration control of space structures, which lack an inertial ground. When subjected to an input voltage, an embedded piezoelectric actuator changes its dimensions, which in turn generates a pair of forces exerted on adjacent structural members. From the direct piezoelectric effect, an embedded piezoelectric transducer generates an electric charge proportional to the structural dynamic response. In this paper, the implementation, testing and modeling of an active truss structure consisting of piezoelectric sensors and actuators are described. Linear quadratic Gaussian (LQG), second-order, and direct rate feedback control schemes are designed to suppress the vibrations of the active structure. Simulation and test results are presented. It is shown that special model reduction considerations are required to achieve good correlation between test and analysis.
An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations.
This paper describes our efforts in structural control experiments for a flexible precision structure using both passive and active control. Specifically, a layered structural control approach utilizing passive viscous dampers, colocated and noncolocated active control is used. The passive dampers and active colocated control loops are used to enhance stability and robustness and the noncolocated multivariable controller is designed with respect to a partially controlled structure to further improve the performance. Our approach to the multivariable design problem requires not only a state space model description of the plant, but also an accompanying uncertainty model. To support the multivariable robust control design development, a significant effort in system identification was undertaken. The process of identification and identified results are discussed. Noncolocated controllers are designed using the H(infinity)/mu-synthesis methodology. The order of the controller is typically large, hence, model reduction is performed for practical digital implementation on a real-time control system developed at JPL. Finally, experimental results are presented and some of lessons are discussed.
A dynamics and controls analyst is typically presented with a structural dynamics model and must perform various input/output tests and design control laws. The required time/frequency simulations need to be done many times as models change and control designs evolve. This paper examines some simple ways that open and closed loop frequency and time domain simulations can be done using the special structure of the system equations usually available. Routines were developed to run under Pro-Matlab in a mixture of the Pro-Matlab interpreter and FORTRAN (using the .mex facility). These routines are often orders of magnitude faster than trying the typical 'brute force' approach of using built-in Pro-Matlab routines such as bode. This makes the analyst's job easier since not only does an individual run take less time, but much larger models can be attacked, often allowing the whole model reduction step to be eliminated.
Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.
The interdisciplinary field of reactive flow control is one that holds a great deal of promise for the optimization of complex phenomena occurring in many practical systems, ranging from automobile and gas turbine engines to environmental thermal destruction systems. The fundamental underpinnings of combustion control, however, require a detailed level of understanding of complex reactive flow phenomena, and, in the case of closed-loop active control, require the ability to sense (monitor) and actuate (manipulate) flow processes in a spatially distributed manner in "near real time". Hence the ultimate growth and success of the field of reactive flow control is intimately linked: 1) to advances in the understanding, simulation, and model reduction for complex reactive flows, 2) to the development of experimental diagnostic techniques, in particular, to the development of physically robust sensors, and 3) to the development of a framework or frameworks for generation of closed loop control algorithms suitable for unsteady, nonlinear reactive flow systems. The present paper seeks to outline the potential benefits and technical challenges that exist for mixing and combustion control in fundamental as well as practical systems and to identify promising research directions that could help meet these challenges.
Very tight distortion requirements are imposed on the JWST's ISM structure due to the sensitivity of the telescope's mirror segment and science instrument positioning. The ISIM structure is a three dimensional truss with asymmetric gusseting and metal fittings. One of the primary challenges for ISIM's analysis team is predicting the thermal distortion of the structure both from the bulk cooldown from ambient to cryo, and the smaller temperature changes within the cryogenic operating environment. As a first cut to estimate thermal distortions, a finite element model of bar elements was created. Elements representing joint areas and metal fittings use effective properties that match the behavior of the stack-up of the composite tube, gusset and adhesive under mechanical and thermal loads. These properties were derived by matching tip deflections of a solid model simplified T-joint. Because of the structure s asymmetric gusseting, this effective property model is a first attempt at predicting rotations that cannot be captured with a smeared CTE approach. In addition to the finite element analysis, several first order calculations have been performed to gauge the feasibility of the material design. Because of the stringent thermal distortion requirements at cryogenic temperatures, a composite tube material with near zero or negative CTE is required. A preliminary hand analysis of the contribution of the various components along the distortion path between FGS and the other instruments, neglecting second order effects were examined. A plot of bounding tube longitudinal and transverse CTEs for thermal stability requirements was generated to help determine the feasibility of meeting these requirements. This analysis is a work in progress en route to a large degree of freedom hi-fidelity FEA model for distortion analysis. Methods of model reduction, such as superelements, are currently being investigated.
Main-group pallasites (PMG) are mixtures of iron-nickel metal and magnesian olivine thought to have been formed at the core-mantle boundary of an asteroid [1]. Some have anomalous metal compositions (PMG-am) and a few have atypically ferroan olivines (PMG-as) [2]. PMG metal is consistent with an origin as a late fractionate of the IIIAB iron core [2]. Most PMG olivines have very similar Fe/Mg ratios, likely due to subsolidus redox reaction with the metal [3]. In contrast, minor and trace elements show substantial variation, which may be explained by either: (i) PMG were formed at a range of depths in the parent asteroid; the element variations reflect variations in igneous evolution with depth, (ii) the pallasite parent asteroid was chemically heterogeneous; the heterogeneity partially survived igneous processing, or (iii) PMG represent the core-mantle boundaries of several distinct parent asteroids [4, 5]. We have continued doing major, minor and trace elements by EMPA and INAA on a wider suite of PMG olivines, and have begun doing precise oxygen isotope analyses to test these hypotheses. Manganese is homologous with Fe(2+), and can be used to distinguish between magmatic and redox processes as causes for Fe/Mg variations. PMG olivines have a range in molar 1000*Mn/Mg of 2.3-4.6 indicating substantial igneous fractionation in olivines with very similar Fe/Mg (0.138-0.148). The Mg-Mn-Fe distributions can be explained by a fractional crystallization-reduction model; higher Mn/Mg ratios reflect more evolved olivines while Fe/Mg is buffered by redox reactions with the metal. There is a positive association between Mn/Mg and Sc content that is consistent with igneous fractionation. However, most PMG olivines fall within a narrow Mn/Mg range (3.0-3.6), but these show a substantial range in Sc (1.00-2.29 micro-g/g). Assuming fractional crystallization, this Sc range could have resulted from approx.65% crystallization of an ultramafic magma. This is inconsistent with formation at the core-mantle boundary of a single asteroid [4]. One alternative is that the PMG are fragments of several asteroids, and these could have had different initial Sc contents, Mn/Mg and differences in igneous history. Our preliminary O isotope data and those of [6, 7] do not support this, although the coverage of PMG olivines is incomplete. The PMG-as Springwater is not easily fit in any scenario. Its olivine has among the highest Mn/Mg suggesting it is one of the most evolved, but the lowest Sc content suggesting it is the least evolved. The O isotopic composition of Springwater olivine is the same as that of other PMG. Thus there is no indication that it represents a distinct parent asteroid. Our preliminary O isotopic data favor a single PMG parent asteroid. In this case, the olivines are more likely melt-residues, and that the parent asteroid was initially heterogeneous in chemical, but not isotopic, composition.
Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.
Bolted structural joints often exhibit load-dependent stiffness and energy dissipation that leads to nonlinear, amplitude dependent frequency and damping in the structure. As an alternative to direct integration of the nonlinear equations of motion, quasi-static modal analysis (QSMA) determines the dependence of frequency and damping on response amplitude using loading behavior from nonlinear static analyses. QSMA has previously been demonstrated to substantially reduce computational cost and maintain accuracy relative to full nonlinear dynamic simulation. This work explores the applicability of QSMA to a complex, large-scale aerospace structure. QSMA is employed to analyze a nonlinear model of test hardware developed to support the Orion Multi-Purpose Crew Vehicle program, which exhibited nonlinear behavior during dynamic testing at flight-like load levels. In addition to the extraction of amplitude-dependent frequency and damping curves, a Bouc-Wen hysteresis model was used in conjunction with the quasi-static results to develop nonlinear, uncoupled, time-domain modal equations of motion for the structure. Excellent agreement was observed between the reduced and full-order nonlinear models, encouraging future employment of QSMA to support accurate and efficient model reduction of structures with bolted joint nonlinearities.
Under the background of climate change, vast regions of the world will face a hotter and probably drier future that favors ignition and spread of wildfires. This poses additional challenges to the communities who are fighting the ever-larger wildfires. Fire and smoke models are valuable tools to fire managers and decision-makers to mitigate the impact of fires. Existing fire modeling systems bear large uncertainties due to the difficulty in collecting data to characterize fire behavior and smoke transport. More observations are urgently needed for improvement of fire modeling and reduction in model uncertainty. The coordinated prescribed burn experiment, such as the Fire and Smoke Model and Measurement Evaluation Experiment (FSMMEE), will allow the concurrent collection of critical measurements of fuel, fire behavior, smoke, and meteorology to better understand and model fires. In this preliminary investigation, we employed the data from the prescribed burn experiment at Langdon Mountain, Utah, in November 2019, to reconstruct the fire emissions and characterize the smoke transport. The NASA Unified Weather Research and Forecasting Model (NU-WRF) was utilized to assist in identifying the potential pre-fire remote sensing capabilities, such as fuel load, moisture, and fire radiative power, which are helpful to model development and advancement. Along the way, two sets of NU-WRF experiments would be done by applying either a default fire emissions inventory (i.e., NASA’s Quick Fire Emissions Dataset, QFED) or reconstructed fire emissions using the data collected from the prescribed fire. The results would help answer the questions such as “How do reconstructed emissions compare to QFED emissions and their impact on plume transport”.