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At least 127 records · Page 7

Machine-learning based model reduction for partial differential equations

We develop a novel synergistic approach between model reduction and machine learning. The specific goal of this project is to aid in the construction of reduced order models for basis functions that are custom-made to represent the solution of partial differential equations. Partial differential equations (PDEs) are one of the main mathematical tools for describing physical phenomena. However, due to either efficiency or necessity, for many real-world problems, we are interested in constructing reduced order models (ROMs) which focus only on the explicit computation of subsets of the active spatio-temporal scales in the problem, while treating the interaction with the rest of the scales approximately. The task of accurate representation of such interactions (usually called memory terms) constitutes a vast area of research known as model reduction. PI Stinis has significant expertise in the construction of ROMs for complex systems. In addition, in recent work with the project key participant Qadeer, they have utilized machine learning to acquire custom-made basis functions (CBFs) to expand the solutions of PDEs. In the proposed work, we will merge the two concepts by constructing ROMs for subsets of the CBFs needed to represent the solution of a PDE. Specifically, we will use the Mori-Zwanzig model reduction formalism to construct ROMs for subsets of CBFs for nonlinear PDEs of various complexity, as well as investigate the usage of CBFs in the spectral vanishing viscosity method for problems that can form shocks in finite time. The outcome of the research is aimed to be proof-of-concept about a novel synergistic approach between model reduction and machine learning, thus advancing the field of scientific machine learning. Such a capability will benefit the efficient modeling of physical systems appearing in various areas of interest to the DOE.

97 MATHEMATICS AND COMPUTING

An electrochemical series of redox couples in silicate melts - A review and applications to geochemistry

An electrochemical series for redox couples in a glass-forming oxide melt is developed. This series is a quantitative numerical scale of reference reduction potentials of the redox couples in a silicate melt that is a model for basaltic magmas. The redox couples are ordered in terms of their reference reduction potentials; the order appears to be relatively independent of the exact melt composition and temperature. Thus, upon calibration to a desired composition, oxygen fugacity, and temperature, this electrochemical series can provide estimates of redox state proportions in basaltic magmas on different planetary bodies. The geochemical electrochemical series can also be used to understand the interrelationship of the redox state of the magma and the presence of volatile species such as oxygen, water, sulfur gases, and carbon gases.

Schreiber, Henry D.

Modeling and control of flexible structures

This monograph presents integrated modeling and controller design methods for flexible structures. The controllers, or compensators, developed are optimal in the linear-quadratic-Gaussian sense. The performance objectives, sensor and actuator locations and external disturbances influence both the construction of the model and the design of the finite dimensional compensator. The modeling and controller design procedures are carried out in parallel to ensure compatibility of these two aspects of the design problem. Model reduction techniques are introduced to keep both the model order and the controller order as small as possible. A linear distributed, or infinite dimensional, model is the theoretical basis for most of the text, but finite dimensional models arising from both lumped-mass and finite element approximations also play an important role. A central purpose of the approach here is to approximate an optimal infinite dimensional controller with an implementable finite dimensional compensator. Both convergence theory and numerical approximation methods are given. Simple examples are used to illustrate the theory.

Gibson, J. S.

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

The research performed consisted of three stages: (1) identification of sensitive IML-1 experiments and sensitivity ranges by order of magnitude estimates, numerical modeling, and investigator input; (2) research and development towards reduction, supplementation, and dissemination of residual acceleration data; and (3) implementation of the plan on existing acceleration databases.

Rogers, Melissa J. B.

A layered approach to structural control system design for the JPL phase B testbed

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.

Chu, Cheng-Chih

Extended dynamic mode decomposition for model reduction in fluid dynamics simulations

High computational cost and storage/memory requirements of fluid dynamics simulations constrain their usefulness as a predictive tool. Reduced-order models (ROMs) provide a viable solution to this challenge by extracting the key underlying dynamics of a complex system directly from data. We investigate the efficacy and robustness of an extended dynamic mode decomposition (xDMD) algorithm in constructing ROMs of three-dimensional cardiovascular computations. Focusing on the ROMs' accuracy in representation and interpolation, we relate these metrics to the truncation rank of singular value decomposition, which underpins xDMD and other approaches to ROM construction. Our key innovation is to relate the truncation rank to the singular values of the original flow problem. This result establishes a priori guidelines for the xDMD deployment and its likely success as a means of data compression and reconstruction of the system's dynamics from dominant spatiotemporal structures present in the data.

Mechanics

Optimization-Based Model Reduction Scheme for Renewable Energy Power Plants Using Standardized Testing Scenarios

This paper presents an optimization-based model reduction scheme for renewable energy (RE) power plants consisting of inverter-based resources (IBRs) operating in grid-following (GFL) or grid-forming (GFM) modes. More importantly, the datasets feeding the optimization-based model reduction scheme are generated and re-used through the standardized grid-interactive testing scenarios. Particularly, the proposed scheme makes use of the power plant point of common coupling (PCC) measurements of various quantities specified by standardized tests (e.g., voltage and frequency ride through) as per IEEE 2800, to estimate the parameters of the reduced-order model such that its dynamic performance aligns with the original detailed power plant model. The proposed model reduction approach does not require the parameters of individual IBRs and using standardized test data as input to the formulated optimization problem simplifies the reduced-order modelling scheme. Extensive case studies following standardized test scenarios verified the remarkable accuracy of the proposed approach.

Yallamilli, Ram S. [Purdue University]

Reduction Of Sizes Of Semi-Markov Reliability Models

Trimming technique reduces computational effort by order of magnitude while introducing negligible error. Error bound depends on only three parameters from semi-Markov model: maximum sum of rates for failure transitions leaving any state, maximum average holding time for recovery-mode state, and operating time for system. Error bound computed before any model generated, enabling modeler to decide immediately whether or not model can be trimmed. Trimming procedure specified by precise and easy description, making it easy to include trimming procedure in program generating mathematical models for use in assessing reliability. Typical application of technique in design of digital control systems required to be extremely reliable. In addition to aerospace applications, fault-tolerant design has growing importance in wide range of industrial applications.

White, Allan L.

An application of the IMC software to controller design for the JPL LSCL Experiment Facility

A software package which Integrates Model reduction and Controller design (The IMC software) is applied to design controllers for the JPL Large Spacecraft Control Laboratory Experiment Facility. Modal Cost Analysis is used for the model reduction, and various Output Covariance Constraints are guaranteed by the controller design. The main motivation is to find the controller with the 'best' performance with respect to output variances. Indeed it is shown that by iterating on the reduced order design model, the controller designed does have better performance than that obtained with the first model reduction.

Zhu, Guoming

A decentralized linear quadratic control design method for flexible structures

A decentralized suboptimal linear quadratic control design procedure which combines substructural synthesis, model reduction, decentralized control design, subcontroller synthesis, and controller reduction is proposed for the design of reduced-order controllers for flexible structures. The procedure starts with a definition of the continuum structure to be controlled. An evaluation model of finite dimension is obtained by the finite element method. Then, the finite element model is decomposed into several substructures by using a natural decomposition called substructuring decomposition. Each substructure, at this point, still has too large a dimension and must be reduced to a size that is Riccati-solvable. Model reduction of each substructure can be performed by using any existing model reduction method, e.g., modal truncation, balanced reduction, Krylov model reduction, or mixed-mode method. Then, based on the reduced substructure model, a subcontroller is designed by an LQ optimal control method for each substructure independently. After all subcontrollers are designed, a controller synthesis method called substructural controller synthesis is employed to synthesize all subcontrollers into a global controller. The assembling scheme used is the same as that employed for the structure matrices. Finally, a controller reduction scheme, called the equivalent impulse response energy controller (EIREC) reduction algorithm, is used to reduce the global controller to a reasonable size for implementation. The EIREC reduced controller preserves the impulse response energy of the full-order controller and has the property of matching low-frequency moments and low-frequency power moments. An advantage of the substructural controller synthesis method is that it relieves the computational burden associated with dimensionality. Besides that, the SCS design scheme is also a highly adaptable controller synthesis method for structures with varying configuration, or varying mass and stiffness properties.

Su, Tzu-Jeng

Development of a residual acceleration data reduction and dissemination plan

A major obstacle in evaluating the residual acceleration environment in an orbiting space laboratory is the amount of data collected during a given mission: gigabytes of data will be available as SAMS units begin to fly regularly. Investigators taking advantage of the reduced gravity conditions of space should not be overwhelmed by the accelerometer data which describe these conditions. We are therefore developing a data reduction and analysis plan that will allow principal investigators of low-g experiments to create experiment-specific residual acceleration data bases for post-flight analysis. The basic aspects of the plan can also be used to characterize the acceleration environment of earth orbiting laboratories. Our development of the reduction plan is based on the following program of research: the identification of experiment sensitivities by order of magnitude estimates and numerical modelling; evaluation of various signal processing techniques appropriate for the reduction, supplementation, and dissemination of residual acceleration data; and testing and implementation of the plan on existing acceleration data bases. The orientation of the residual acceleration vector with respect to some set of coordinate axes is important for experiments with known directional sensitivity. Orientation information can be obtained from the evaluation of direction cosines. Fourier analysis is commonly used to transform time history data into the frequency domain. Common spectral representations are the amplitude spectrum which gives the average of the components of the time series at each frequency and the power spectral density which indicates the power or energy present in the series per unit frequency interval. The data reduction and analysis scheme developed involves a two tiered structure to: (1) identify experiment characteristics and mission events that can be used to limit the amount of accelerator data an investigator should be interested in; and (2) process the data in a way that will be meaningful to the experiment objectives. A general outline of the plan is given.

Rogers, Melissa J. B.

Simplified Modeling of Oxidation of Hydrocarbons

A method of simplified computational modeling of oxidation of hydrocarbons is undergoing development. This is one of several developments needed to enable accurate computational simulation of turbulent, chemically reacting flows. At present, accurate computational simulation of such flows is difficult or impossible in most cases because (1) the numbers of grid points needed for adequate spatial resolution of turbulent flows in realistically complex geometries are beyond the capabilities of typical supercomputers now in use and (2) the combustion of typical hydrocarbons proceeds through decomposition into hundreds of molecular species interacting through thousands of reactions. Hence, the combination of detailed reaction- rate models with the fundamental flow equations yields flow models that are computationally prohibitive. Hence, further, a reduction of at least an order of magnitude in the dimension of reaction kinetics is one of the prerequisites for feasibility of computational simulation of turbulent, chemically reacting flows. In the present method of simplified modeling, all molecular species involved in the oxidation of hydrocarbons are classified as either light or heavy; heavy molecules are those having 3 or more carbon atoms. The light molecules are not subject to meaningful decomposition, and the heavy molecules are considered to decompose into only 13 specified constituent radicals, a few of which are listed in the table. One constructs a reduced-order model, suitable for use in estimating the release of heat and the evolution of temperature in combustion, from a base comprising the 13 constituent radicals plus a total of 26 other species that include the light molecules and related light free radicals. Then rather than following all possible species through their reaction coordinates, one follows only the reduced set of reaction coordinates of the base. The behavior of the base was examined in test computational simulations of the combustion of heptane in a stirred reactor at various initial pressures ranging from 0.1 to 6 MPa. Most of the simulations were performed for stoichiometric mixtures; some were performed for fuel/oxygen mole ratios of 1/2 and 2.

Bellan, Josette

Design of turbofan engine controls using output feedback regulator theory

A multivariable control design procedure based on output feedback regulator (OFR) theory is applied to the F100 turbofan engine. Results for the OFR design are compared to a design based on linear quadratic regulator (LQR) theory. The OFR feedback control is designed in the full order state space and thus eliminates any need for model reduction techniques. Using the performance measure and control structure of the LQR design, an equivalent OFR feedback control is obtained. The flexibility of the OFR as a control design procedure is demonstrated, and differing feedback control structures are evaluated.

Merrill, W. C.

Design of turbofan engine controls using output feedback regulator theory

A multivariable control design procedure based on output feedback regulator (OFR) theory is applied to the F100 turbofan engine. Results for the OFR design are compared to a design based on linear quadratic regulator (LQR) theory. This LQR design was obtained as part of the F100 Multivariable Control Synthesis (MVCS) program. In the MVCS program the LQR feedback control was designed in a reduced dimension state space and then applied to the original system. However, the OFR feedback control is designed in the full order state space and thus eliminates any need for model reduction techniques. Using the performance measure and control structure of the MVCS program LQR design, an equivalent OFR feedback control is obtained. The flexibility of the OFR as a control design procedure is demonstrated and differing feedback control structures are evaluated.

Merrill, W. C.

Alternatives for jet engine control

The technical progress of researches on alternatives for jet engine control, is reported. The principal new activities involved the initial testing of an input design method for choosing the inputs to a non-linear system to aid the approximation of its tensor parameters, and the beginning of order reduction studies designed to remove unnecessary monomials from tensor models.

Sain, M. K.

Effect of Temperature Gradient on Thick Film Selective Emitter Emittance

A temperature gradient across a thick (greater than or equal to .1 mm) film selective emitter will produce a significant reduction in the spectral emittance from the no temperature gradient case. Thick film selective emitters of rare earth doped host materials such as yttrium-aluminum-garnet (YAG) are examples where temperature gradient effects are important. In this paper a model is developed for the spectral emittance assuming a linear temperature gradient across the film. Results of the model indicate that temperature gradients will result in reductions the order of 20% or more in the spectral emittance.

Chubb, Donald L.

Ozone reduction in the 1980's - A model simulation of anthropogenic and solar perturbations

An interpretation of global ozone changes deduced from satellite data obtained since 1979 is presented, based on two-dimensional model simulations. The study shows that a depletion in total ozone of the order of 2 percent and a reduction in ozone density near 40 km of 7 to 12 percent over the 1979-1986 period are consistent with the observed increase in trace gas densities (chlorofluorocarbons, methane, nitrous oxide, carbon dioxide) and the simultaneous decrease in solar activity during this period. The model also suggests that ozone variations of solar and anthropogenic origins between 1979 and 1986 were of similar magnitude but that the ozone response to trace gas emissions increases substantially with latitude while the solar signal in ozone is present lower in the atmosphere and is nearly independent of latitude.

Brasseur, Guy