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It is shown that Jacobi elliptic function solutions of the nonlinear Duffing equation model the radiation field in a high-gain free electron laser through early saturation. After initial start-up, the field can be expressed equivalently with a hyperbolic secant. The model is derived for arbitrary detuning from resonance, which enables study of the spectral properties in the early nonlinear regime.
Wintertime Ural blocking (UB) has been shown to play an important role in cold extremes over Eurasia, and thus it is useful to investigate the impact of warming over the Barents–Kara Seas (BKS) on the behavior of Ural blocking. In our study the response of UB to stepwise tropospheric warming over the BKS is examined using a dry dynamic core model. Nonlinear responses are found in the frequency and local persistence of UB. The frequency and local persistence of the UB increase with the strength of BKS warming in a less strong range and decrease with the further increase of BKS warming, which is linked to the UB propagation influenced by upstream background atmospheric circulation. For a weak BKS warming, the UB becomes more persistent due to its less westward movement associated with intensified upstream zonal wind and meridional potential vorticity gradient (PVy) in the North Atlantic mid-high latitudes, which corresponds to a negative height response over the North Atlantic high latitudes. When BKS warming is strong, a positive height response appears in the early winter stratosphere, and its subsequent downward propagation leads to a negative NAO response or increased Greenland blocking events, which reduces zonal wind and PVy in the high latitudes from North Atlantic to Europe, thus enhancing the westward propagation of UB and reducing its local persistence. The transition to the negative NAO phase and the retrogression of UB are not found when numerically suppressing the downward influence of weakened stratospheric polar vortex, suggesting a crucial role of the stratospheric pathway in nonlinear responses of UB to the early winter BKS warming.
The nonlinear progressive wave equation (NPE) model was developed by the Naval Ocean Research and Development Activity during 1982 to 1987 to study nonlinear effects in long range oceanic propagation of finite amplitude acoustic waves, including weak shocks. The NPE model was applied to propagation of a generic shock wave (initial condition provided by Sandia Division 1533) in a few illustrative environments. The following consequences of nonlinearity are seen by comparing linear and nonlinear NPE results: (1) a decrease in shock strength versus range (a well-known result of entropy increases at the shock front); (2) an increase in the convergence zone range; and (3) a vertical meandering of the energy path about the corresponding linear ray path. Items (2) and (3) are manifestations of self-refraction.
Management of the electrical grid is becoming more complex due to the increased penetration of alternative energy generation technologies and a broadening diversity of electric loads. This complexity creates challenges in balancing demand and generation that can increase the potential for grid instabilities. One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. The novelty in ANPV-MPC is the use of a physics-inspired Bayesian neural network to estimate the coefficients of the parameter-varying linear control model. The Bayesian neural network additionally provides uncertainty estimates, triggering online training to capture evolving building system conditions. We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. ANPV-MPC also adapts in real time to previously unseen conditions using online learning, further improving its performance.
Linear acoustic calculations are compared with previously reported data for a small-scale hovering rotor operated at high tip Mach numbers. A detailed calculated description of the distributions of blade surface pressure and shear stress due to skin friction is presented. The noise due to skin friction and loading, in the rotor disk plane, is small compared to thickness noise. The basic conclusions of Boxwell et al about the importance of nonlinear effects are upheld. Some approximations involved in the current theories for the inclusion of nonlinear effects are discussed. Using a model nonlinear problem, it is shown that to use the acoustic analogy, good knowledge of the flowfield is required.
Existing and new models for the rapid and the return terms in the Reynolds stress equations were tested in two ways. One, by direct comparison of the model with simulation data. The other, by simulating the flows using the models and comparing the predicted Reynolds stresses with the data. It was found that existing linear models can be improved and that nonlinear models are in better agreement with the simulation data for a wide variety of flows.
Turbulence models for the pressure-strain term of the Reynolds-stress equations in the vicinity of a moving wall are evaluated for a high Reynolds number flow using decaying grid turbulence as a model problem. The data of Thomas and Hancock are used as a base for evaluating the different turbulence models. In particular, the Rotta model for return-to-isotropy is evaluated both in its inclusion into the Reynolds-stress equation model and in comparison to a nonlinear model advanced by Sarkar and Speziale. Further, models for the wall correction to the transfer term advanced by Launder et al., Shir, and Shih and Lumley are compared. Initial data using the decaying grid turbulence experiment as a base suggests that the coefficients proposed for these models are high perhaps by as much as an order of magnitude. The Shih and Lumley model which satisfies realizability constraints, in particular, seems to hold promise in adequately modeling the Reynolds stress components of this flow. Extensions of this work are to include testing the homogeneous transfer model by Shih and Lumley and the testing of the wall transfer models using their proposed coefficients and the coefficients chosen from this work in a flow with mean shear component.
The authors find the probabilities of detection and false alarm of the pseudonoise (PN) sequence code lock detector when strong radio frequency interference (RFI) hits the communications link. Both a linear model and a soft-limiter nonlinear model for a transponder receiver are considered. In addition, both continuous wave (CW) RFI and pulse RFI are analyzed, and a discussion is included of how strong CW RFI can knock out the PN code lock detector in a linear or a soft-limiter transponder. As an example, the Space Station Freedom forward S-band PN system is evaluated. It is shown that a soft-limiter transponder can protect the PN code lock detector against a typical pulse RFI, but it can degrade the PN code lock detector performance more than a linear transponder if CW RFI hits the link.
For flywheel rotors or other rotors with significant ratios of moments of inertia, the influence of gyroscopic effects has to be considered. While conservative or damped systems remain stable even under gyroscopic effects, magnetically suspended rotors can be destabilized with increasing rotational speed. The influence of gyroscopic effects on the stability and behavior of a magnetic bearing system is analyzed. The analysis is carried out with a rigid body model for the rotor and a nonlinear model for the magnetic bearing and its amplifier. Cross feedback control can compensate gyroscopic effects. This compensation leads to better system performance and can avoid instability. Furthermore, the implementation of this compensation is simple. The main structure of a decentralized controller can still be used. It has only to be expanded by the cross feedback path.
Computational analyses such as computational fluid dynamics and computational structural dynamics have made major advances toward maturity as engineering tools. Computational aeroelasticity is the integration of these disciplines. As computational aeroelasticity matures it too finds an increasing role in the design and analysis of aerospace vehicles. This paper presents a survey of the current state of computational aeroelasticity with a discussion of recent research, success and continuing challenges in its progressive integration into multidisciplinary aerospace design. This paper approaches computational aeroelasticity from the perspective of the two main areas of application: airframe and turbomachinery design. An overview will be presented of the different prediction methods used for each field of application. Differing levels of nonlinear modeling will be discussed with insight into accuracy versus complexity and computational requirements. Subjects will include current advanced methods (linear and nonlinear), nonlinear flow models, use of order reduction techniques and future trends in incorporating structural nonlinearity. Examples in which computational aeroelasticity is currently being integrated into the design of airframes and turbomachinery will be presented.
An efficient method for the load analysis of Shuttle-payload systems with linear or nonlinear attachment interfaces is presented which allows the kinematics of the interface degrees of freedom at a given time to be evaluated without calculating the combined system modal representation of the Space Shuttle and its payload. For the case of a nonlinear dynamic model, an iterative procedure is employed to converge the nonlinear terms of the equations of motion to reliable values. Results are presented for a Shuttle abort landing event.
A study of stable periodic solutions to a simple nonlinear model of the ocean-atmosphere-ice system is presented. The model has two dependent variables: ocean-atmosphere temperature and latitudinal extent of the ice cover. No explicit dependence on latitude is considered in the model. Hence all variables depend only on time and the model consists of a coupled set of nonlinear ordinary differential equations. The globally averaged ocean-atmosphere temperature in the model is governed by the radiation balance. The reflectivity to incoming solar radiation, i.e., the planetary albedo, includes separate contributions from sea ice and from continental ice sheets. The major physical mechanisms active in the model are (1) albedo-temperature feedback, (2) continental ice-sheet dynamics and (3) precipitation-rate variations. The model has three-equilibrium solutions, two of which are linearly unstable, while one is linearly stable. For some choices of parameters, the stability picture changes and sustained, finite-amplitude oscillations obtain around the previously stable equilibrium solution. The physical interpretation of these oscillations points to the possibility of internal mechanisms playing a role in glaciation cycles.
Reconstructing the initial conditions of the Universe from late-time observations has the potential to optimally extract cosmological information. Due to the high dimensionality of the parameter space, a differentiable forward model is needed for convergence, and recent advances have made it possible to perform reconstruction with nonlinear models based on galaxy (or halo) positions. In addition to positions, future surveys will provide measurements of galaxies' peculiar velocities through the kinematic Sunyaev-Zel'dovich effect (kSZ), type Ia supernovae, the fundamental plane relation, and the Tully-Fisher relation. Here we develop the formalism for including halo velocities, in addition to halo positions, to enhance the reconstruction of the initial conditions. We show that using velocity information can significantly improve the reconstruction accuracy compared to using only the halo density field. Here we study this improvement as a function of shot noise, velocity measurement noise, and angle to the line of sight. We also show how halo velocity data can be used to improve the reconstruction of the final nonlinear matter overdensity and velocity fields. We have built our pipeline into the differentiable Particle-Mesh FlowPM package, paving the way to perform field-level cosmological inference with joint velocity and density reconstruction. This is especially useful given the increased ability to measure peculiar velocities in the near future.
An efficient nonlinear equivalent beam finite-element method for the application of a full state feedback design is described, which is robust to plant uncertainties to a beamlike truss structure with nonlinear elements. The method may be extended to model nonlinear structures with other types of control systems, such as model-based compensators.
Aerosol jet printing (AJP) has emerged as a promising noncontact additive manufacturing method for high-resolution printing for a wide range of material systems. A key challenge limiting the broader adoption of AJP in the material science community is the lack of methods to precisely control thickness. Herein, we develop a model-based design of experiment (MBDoE) framework that integrates physics-informed models, nonlinear regression, and information criteria to postulate, select and calibrate the best model to describe and optimize the AJP manufacturing process. Starting with already available data from system commissioning (e.g., prior single variable sensitivity analysis), four candidate physics-informed models are postulated and trained. MBDoE identifies a single additional optimal experiment to validate these predictive models with quantified uncertainties, which are then used to determine the best experimental conditions to control printed film thickness. As a comparative benchmark, the analysis is repeated using the same dataset with nonparametric Gaussian process regression (GPR) model that does not incorporate physical information. Using MBDoE principles, we find that only five experiments are necessary to calibrate the nonlinear physics-informed parametric model, and with said limited data, this model outperforms the black-box machine learning GPR model. This key result underscores an emerging trend in the data science community: incorporating physical information into predictive models often drastically reduces the data requirements. Leveraging MBDoE further increased the data efficiency. By design, the proposed data science framework is general in nature and can be easily extended to other experimental and additive manufacturing systems beyond AJP.
In the Space Station era, more operations will be performed robotically in space in the areas of servicing, assembly, and experiment tending among others. These robots may have various sets of requirements for accuracy, speed, and force generation, but there will be design constraints such as size, mass, and power dissipation limits. For actuation, a leading motor candidate is a dc brushless type, and there are numerous potential drive trains each with its own advantages and disadvantages. This experiment uses a harmonic drive and addresses some inherent limitations, namely its backdriveability and low frequency structural resonances. These effects are controlled and diminished by instrumenting the actuator system with a torque transducer on the output shaft. This noncollocated loop is closed to ensure that the commanded torque is accurately delivered to the manipulator link. The actuator system is modelled and its essential parameters identified. The nonlinear model for simulations will include inertias, gearing, stiction, flexibility, and the effects of output load variations. A linear model is extracted and used for designing the noncollocated torque and position feedback loops. These loops are simulated with the structural frequency encountered in the testbed system. Simulation results are given for various commands in position. The use of torque feedback is demonstrated to yield superior performance in settling time and positioning accuracy. An experimental setup being finished consists of a bench mounted motor and harmonic drive actuator system. A torque transducer and two position encoders, each with sufficient resolution and bandwidth, will provide sensory information. Parameters of the physical system are being identified and matched to analytical predictions. Initial feedback control laws will be incorporated in the bench test equipment and various experiments run to validate the designs. The status of these experiments is given.
An interactive FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models is documented in this report. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.
'Debris disks' around young stars (analogues of the Kuiper Belt in our Solar System) show a variety of non-trivial structures attributed to planetary perturbations and used to constrain the properties of those planets. However, these analyses have largely ignored the fact that some debris disks are found to contain small quantities of gas, a component that all such disks should contain at some level. Several debris disks have been measured with a dust-to-gas ratio of about unity, at which the effect of hydrodynamics on the structure of the disk cannot be ignored. Here we report linear and nonlinear modelling that shows that dust-gas interactions can produce some of the key patterns attributed to planets. We find a robust clumping instability that organizes the dust into narrow, eccentric rings, similar to the Fomalhaut debris disk. The conclusion that such disks might contain planets is not necessarily required to explain these systems.