SEARCH · Engineering Papers
Results for “Nonlinear projection”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
IC Project: w19_hossfault “Modelling of stick-slip behavior in sheared granular fault gouge & nonlinear elasticity behavior in cracked solid”
Low frequency earthquakes, non-volcanic tremor, and acoustic emissions are examples of weak seismic signals that may help detect major seismic events, i.e., earthquakes. In a laboratory setting, in which stick-slip events are simulated, acoustic emissions are detected far from the stick-slip events. In both, field and laboratory scale cases, the acoustic emission signals are sourced or detected in a volume remote from the volume that spawns the earthquake. Therefore, it is relevant to establish the causal relationship between signals detected on passive, remote monitors and the dynamics of the elastic structures that launch important seismic events. The work conducted under this IC allocation allowed us to utilize a numerical model that let us follow this causality, i.e., examine and connect the dynamics in a granular system (fault gouge), to signals detected on passive remote monitors. It was demonstrated that stress chains are key in the dynamics of granular systems and that their evolution is the source of the acoustic emission.
Identification of a linear system from sampled noisy data, part C Final project report
Step input linear system modeling from nonlinear system sampled noisy data based on method of perturbation or quasilinearization of automatic control system data
Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)
The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems
In this work, we present Lift & Learn, a physics-informed method for learning low-dimensional models for large-scale dynamical systems. The method exploits knowledge of a system’s governing equations to identify a coordinate transformation in which the system dynamics have quadratic structure. This transformation is called a lifting map because it often adds auxiliary variables to the system state. The lifting map is applied to data obtained by evaluating a model for the original nonlinear system. This lifted data is projected onto its leading principal components, and low-dimensional linear and quadratic matrix operators are fit to the lifted reduced data using a least-squares operator inference procedure. Analysis of our method shows that the Lift & Learn models are able to capture the system physics in the lifted coordinates at least as accurately as traditional intrusive model reduction approaches. This preservation of system physics makes the Lift & Learn models robust to changes in inputs. Numerical experiments on the FitzHugh–Nagumo neuron activation model and the compressible Euler equations demonstrate the generalizability of our model.
Augmented reduced order models for turbulence
The authors introduce an augmented-basis method (ABM) to stabilize reduced-order models (ROMs) of turbulent incompressible flows. The method begins with standard basis functions derived from proper orthogonal decomposition (POD) of snapshot sets taken from a full-order model. These are then augmented with divergence-free projections of a subset of the nonlinear interaction terms that constitute a significant fraction of the time-derivative of the solution. The augmenting bases, which are rich in localized high wavenumber content, are better able to dissipate turbulent kinetic energy than the standard POD bases. Several examples illustrate that the ABM significantly out-performs L 2 -, H 1 - and Leray-stabilized POD ROM approaches. The ABM yields accuracy that is comparable to constraint-based stabilization approaches yet is suitable for parametric model-order reduction in which one uses the ROM to evaluate quantities of interests at parameter values that differ from those used to generate the full-order model snapshots. Several numerical experiments point to the importance of localized high wavenumber content in the generation of stable, accurate, and efficient ROMs for turbulent flows.
Precise computer controlled positioning of robot end effectors using force sensors
A major problem in space applications of robotics and docking of spacecraft is the development of technology for automated precise positioning of mating components with smooth motion and soft contact. To achieve the above objective, a design method was developed for optimally placing the closed-loop poles of a discretized robotic control system at exact prescribed locations inside the unit circle of the complex z-plane. The design method combines the merits of the pole placement and the linear quadratic design approaches. The proposed design procedure is based on the assignment of one real eigenvalue or two complex conjugate (or real) eigenvalues at each design step. The method involves solutions of simple algebraic equations and this is considered to be efficient for on-line or off-line computations. Also, two methods for the linearization of the nonlinear model of a robotic manipulator were presented. Since automatic control of multi-degree freedom robotic manipulators involves high nonlinear equations of systems, a pilot project was proposed involving the control of a one-dimensional system. This simple system can be readily implemented for testing the concepts and algorithms.
The Schwarz Alternating Method for the Seamless Coupling of Nonlinear Reduced Order Models and Full Order Models
Projection-based model order reduction allows for the parsimonious representation of full order models (FOMs), typically obtained through the discretization of a set of partial differential equations (PDEs) using conventional techniques (e.g., finite element, finite volume, finite difference methods) where the discretization may contain a very large number of degrees of freedom. As a result of this more compact representation, the resulting projection-based reduced order models (ROMs) can achieve considerable computational speedups, which are especially useful in real-time or multi-query analyses. One known deficiency of projection-based ROMs is that they can suffer from a lack of robustness, stability and accuracy, especially in the predictive regime, which ultimately limits their useful application. Another research gap that has prevented the widespread adoption of ROMs within the modeling and simulation community is the lack of theoretical and algorithmic foundations necessary for the “plug-and-play” integration of these models into existing multi-scale and multi-physics frameworks. This paper describes a new methodology that has the potential to address both of the aforementioned deficiencies by coupling projection-based ROMs with each other as well as with conventional FOMs by means of the Schwarz alternating method [41]. Leveraging recent work that adapted the Schwarz alternating method to enable consistent and concurrent multiscale coupling of finite element FOMs in solid mechanics [35, 36], we present a new extension of the Schwarz framework that enables FOM-ROM and ROM-ROM coupling, following a domain decomposition of the physical geometry on which a PDE is posed. In order to maintain efficiency and achieve computation speed-ups, we employ hyper-reduction via the Energy-Conserving Sampling and Weighting (ECSW) approach [13]. We evaluate the proposed coupling approach in the reproductive as well as in the predictive regime on a canonical test case that involves the dynamic propagation of a traveling wave in a nonlinear hyper-elastic material.
The method of projected characteristics for the evolution of magnetic arches
A numerical method of solving fully nonlinear MHD equation is described. In particular, the formulation based on the newly developed method of projected characteristics (Nakagawa, 1981) suitable to study the evolution of magnetic arches due to motions of their foot-points is presented. The final formulation is given in the form of difference equations; therefore, the analysis of numerical stability is also presented. Further, the most important derivation of physically self-consistent, time-dependent boundary conditions (i.e. the evolving boundary equations) is given in detail, and some results obtained with such boundary equations are reported.
Aeroelastic Modeling and Behavior of Lifting Surfaces Incorporating Aerodynamic and Structural Nonlinearities: Volterra Series and Indicial Function Approach
Within this NASA Grant, the following points should be emphasized: 1) All the objectives stated in the proposal of the grant have been accomplished. Moreover, the activity within the project has addressed additional issues, of the linear and nonlinear aeroelasticity, not included in the objectives of the grant. 2) During the activities within the grant, we have been in a permanent contact with Dr. Walter A. Silva, the monitor of the NASA Project, to whom we have reported continuously our achievements. 3) As a result of the activities within the grant a number of papers: a. have been submitted for publication to the AIAA Journals, namely the AIAA Journal and the Journal of Guidance, Control, and Dynamics, b. have been presented at the specialized National Conferences and an International Congress, and have appeared in the proceedings of these Conferences, 4) A list of papers submitted for publication and presented at Conferences is appended herewith. 5) In all these papers, an acknowledgment to NASA Langley Research Center was included.
Aeroelastic Modeling and Behavior of Lifting Surfaces Incorporating Aerodynamic and Structural Nonlinearities: Volterra Series and Indicial Function Approach
Within this NASA Grant, the following points should be emphasized: 1) All the objectives stated in the proposal of the grant have been accomplished. Moreover. the activity within the project has addressed additional issues, of the linear and nonlinear aeroelasticity, not included in the objectives of the grant. 2) During the activities within the grant, we have been in a permanent contact with Dr. Walter A. Silva, the monitor of the NASA Project, to whom we have reported continuously our achievements. 3) As a result of the activities within the grant a number of papers: a. have been submitted for publication to the AIAA Journals, namely the AIAA Journal and the Journal of Guidance, Control, and Dynamics, and b. have been presented at the specialized National Conferences and an International Congress, and have appeared in the proceedings of these Conferences. 4) A list of papers submitted for publication and presented at Conferences is appended herewith. 5) In all these papers, an acknowledgment to NASA Langley Research Center was included.
The Response of Precipitation Extremes to the Twentieth- and Twenty-First-Century Global Temperature Change in a Comprehensive Suite of CESM1 Large Ensemble Simulation: Revisiting the Role of Forcing Agents Vs. the Role of Forcing Magnitudes
The response of precipitation extremes (PEs) to global warming is found to be nonlinear in Community Earth System Model version 1 (CESM1) and other global climate models (Pendergrass et al., 2019), which led to the concern that it is not accurate to approximate the response of PE to a single forcing as the difference between simulations with all forcing agents and those that exclude one specific forcing. This calls into question previous model-based results that the sensitivity of PE with warming due to aerosol forcing is significantly larger than that due to greenhouse gases (GHGs). We reevaluate the PE sensitivity to GHGs and aerosols using available CESM1 ensemble simulations. We show that although the PE response to warming is nonlinear in CESM1, especially for the high warming projected in the twenty-first-century, PE sensitivity to aerosols is still significantly stronger than that due to GHGs when the comparison is made within similar warming regimes to avoid the bias induced by the nonlinear behavior. But the difference is smaller than previously estimated. We also conclude that the additivity assumption is largely valid to isolate the PE response due to aerosol forcing from the paired simulations including the “all forcing” experiment when the warming regime is small (e.g., 1°C–2°C in the next few decades when aerosol forcing is projected to decline and becomes a major source of uncertainty for model projection).
Linearized Aeroelastic Solver Applied to the Flutter Prediction of Real Configurations
A fast-running unsteady aerodynamics code, LINFLUX, was previously developed for predicting turbomachinery flutter. This linearized code, based on a frequency domain method, models the effects of steady blade loading through a nonlinear steady flow field. The LINFLUX code, which is 6 to 7 times faster than the corresponding nonlinear time domain code, is suitable for use in the initial design phase. Earlier, this code was verified through application to a research fan, and it was shown that the predictions of work per cycle and flutter compared well with those from a nonlinear time-marching aeroelastic code, TURBO-AE. Now, the LINFLUX code has been applied to real configurations: fans developed under the Energy Efficient Engine (E-cubed) Program and the Quiet Aircraft Technology (QAT) project. The LINFLUX code starts with a steady nonlinear aerodynamic flow field and solves the unsteady linearized Euler equations to calculate the unsteady aerodynamic forces on the turbomachinery blades. First, a steady aerodynamic solution is computed for given operating conditions using the nonlinear unsteady aerodynamic code TURBO-AE. A blade vibration analysis is done to determine the frequencies and mode shapes of the vibrating blades, and an interface code is used to convert the steady aerodynamic solution to a form required by LINFLUX. A preprocessor is used to interpolate the mode shapes from the structural dynamics mesh onto the computational fluid dynamics mesh. Then, LINFLUX is used to calculate the unsteady aerodynamic pressure distribution for a given vibration mode, frequency, and interblade phase angle. Finally, a post-processor uses the unsteady pressures to calculate the generalized aerodynamic forces, eigenvalues, an esponse amplitudes. The eigenvalues determine the flutter frequency and damping. Results of flutter calculations from the LINFLUX code are presented for (1) the E-cubed fan developed under the E-cubed program and (2) the Quiet High Speed Fan (QHSF) developed under the Quiet Aircraft Technology project. The results are compared with those obtained from the TURBO-AE code. A graph of the work done per vibration cycle for the first vibration mode of the E-cubed fan is shown. It can be seen that the LINFLUX results show a very good comparison with TURBO-AE results over the entire range of interblade phase angle. The work done per vibration cycle for the first vibration mode of the QHSF fan is shown. Once again, the LINFLUX results compare very well with the results from the TURBOAE code.
Assumed--stress hybrid elements with drilling degrees of freedom for nonlinear analysis of composite structures
The goal of this research project is to develop assumed-stress hybrid elements with rotational degrees of freedom for analyzing composite structures. During the first year of the three-year activity, the effort was directed to further assess the AQ4 shell element and its extensions to buckling and free vibration problems. In addition, the development of a compatible 2-node beam element was to be accomplished. The extensions and new developments were implemented in the Computational Structural Mechanics Testbed COMET. An assessment was performed to verify the implementation and to assess the performance of these elements in terms of accuracy. During the second and third years, extensions to geometrically nonlinear problems were developed and tested. This effort involved working with the nonlinear solution strategy as well as the nonlinear formulation for the elements. This research has resulted in the development and implementation of two additional element processors (ES22 for the beam element and ES24 for the shell elements) in COMET. The software was developed using a SUN workstation and has been ported to the NASA Langley Convex named blackbird. Both element processors are now part of the baseline version of COMET.
Laboratory Study of Nonlinear QED in Intense Laser-Matter Interactions
The goal of the project was to investigate the interaction of powerful laser light with matter, which is of fundamental interest to electrodynamics, thermonuclear fusion plasmas, and high-energy-density physics for DOE. Experiments on highly nonlinear relativistic interactions were performed using the state-of-the-art DIOCLES laser at the Extreme Light Laboratory of the University of Nebraska–Lincoln (UNL). We have demonstrated a novel testbed for laser-plasma interactions in which laser pulses collided in plasma with femtosecond and micron-scale accuracy under extreme experiment conditions. This capability is crucial for future radiation reaction experiments and nonlinear QED studies. Moreover, this is also a milestone towards the efficient generation of GeV electron beams via travelling wave laser wakefield accelerator. We proposed a novel idea for measuring the radiation reaction process using travelling wave Thomson scattering, which was studied in numerical simulations. This method allows unambiguous measurement of radiation reaction in a single shot, therefore, surpassing the conventional methods, which suffer severely from the shot-to-shot fluctuations, due to the instability of laser wavefield acceleration.
Nonlinear Interactions of Alfven Waves in Multi-ion Plasmas (Final Report)
Alfven waves are of fundamental importance in magnetized plasmas, such as the solar wind and Earth’s magnetosphere. When the wave amplitude is large, nonlinear interactions among waves, such as three wave resonance, dominate the dynamics. The nonlinear process can be used as a diagnosis of the plasma composition because the composition affects the dispersion relation of Alfven waves, especially when the wave frequency is close to ion cyclotron frequencies. Previous experiments on the Large Plasma Device (LAPD) had demonstrated that the relative density of two ion species can be determined by examining nonlinear interaction of two counter-propagating Alfven waves. In this project we extended the study to a plasma with three ion species, where multiple wave bands exist, and more nonlinear interactions are possible. We also investigated the feasibility of launching two co-propagating waves to measure the ion composition. The findings of this study have implication in developing new technology to measure cold ion populations in space plasmas.
Residue Specific Characterization of Electrostatics, Conformational Heterogeneity, and Dynamics of Electron Transfer Proteins with Linear and Nonlinear Infrared Spectroscopy. Final Report
The goal of this research project was to further our understanding of biological electron transfer through the development and application of new methods for studying proteins and their complexes with high spatial and temporal detail. The approach was based on incorporation of reporter bonds with distinct vibrational frequencies at specific locations in proteins and their characterization through the interaction of the bonds with pulses of infrared light. The project focused on the proteins plastocyanin (Pc) and cytochrome (cyt) f, two electron transfer partners in photosynthesis. The first thrust of the project was the incorporation of carbon deuterium bonds as non-perturbative probes at a ligand to the copper ion of Pc and their use to detect changes in the bonding due to the number of electrons at the metal and how the bonding changes upon association with cyt f. Toward developing more advanced approaches to characterize proteins, we incorporated a stronger reporter, the cyano group of cyanophenylalanine, at several locations in Pc and measured the frequency dynamics in the absence and presence of cyt f. The acquired data improved the current model for the protein complex. Notably, the data indicated that the majority of the population is involved in a loosely bound complex, providing insight into the nature of the ensembles formed by electron transfer protein complexes that is not available via other approaches. In addition to learning about the protein complex, we made strides toward developing and improving the new experimental approach to study highly dynamic behaviors of proteins.
Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders
Data assimilation is a Bayesian inference process that obtains an enhanced understanding of a physical system of interest by fusing information from an inexact physics-based model, and from noisy sparse observations of reality. The multifidelity ensemble Kalman filter (MFEnKF) recently developed by the authors combines a full-order physical model and a hierarchy of reduced order surrogate models in order to increase the computational efficiency of data assimilation. The standard MFEnKF uses linear couplings between models, and is statistically optimal in case of Gaussian probability densities. This work extends the MFEnKF into to make use of a broader class of surrogate model such as those based on machine learning methods such as autoencoders non-linear couplings in between the model hierarchies. We identify the right-invertibility property for autoencoders as being a key predictor of success in the forecasting power of autoencoder-based reduced order models. We propose a methodology that allows us to construct reduced order surrogate models that are more accurate than the ones obtained via conventional linear methods. Numerical experiments with the canonical Lorenz'96 model illustrate that nonlinear surrogates perform better than linear projection-based ones in the context of multifidelity ensemble Kalman filtering. We additionality show a large-scale proof-of-concept result with the quasi-geostrophic equations, showing the competitiveness of the method with a traditional reduced order model-based MFEnKF.