linearized multi-parameters inversion: Topics by WorldWideScience.org

Sample records for linearized multi-parameters inversion

Estimation of biological parameters of marine organisms using linear and nonlinear acoustic scattering model-based inversion methods.

Science.gov (United States)

Chu, Dezhang; Lawson, Gareth L; Wiebe, Peter H

2016-05-01

The linear inversion commonly used in fisheries and zooplankton acoustics assumes a constant inversion kernel and ignores the uncertainties associated with the shape and behavior of the scattering targets, as well as other relevant animal parameters. Here, errors of the linear inversion due to uncertainty associated with the inversion kernel are quantified. A scattering model-based nonlinear inversion method is presented that takes into account the nonlinearity of the inverse problem and is able to estimate simultaneously animal abundance and the parameters associated with the scattering model inherent to the kernel. It uses sophisticated scattering models to estimate first, the abundance, and second, the relevant shape and behavioral parameters of the target organisms. Numerical simulations demonstrate that the abundance, size, and behavior (tilt angle) parameters of marine animals (fish or zooplankton) can be accurately inferred from the inversion by using multi-frequency acoustic data. The influence of the singularity and uncertainty in the inversion kernel on the inversion results can be mitigated by examining the singular values for linear inverse problems and employing a non-linear inversion involving a scattering model-based kernel.
Frequency Domain Multi-parameter Full Waveform Inversion for Acoustic VTI Media

KAUST Repository

Djebbi, Ramzi

2017-05-26

Multi-parameter full waveform inversion (FWI) for transversely isotropic (TI) media with vertical axis of symmetry (VTI) suffers from the trade-off between the parameters. The trade-off results in the leakage of one parameter\\'s update into the other during the inversion. It affects the accuracy and convergence of the inversion. The sensitivity analyses suggested a parameterisation using the horizontal velocity vh, epsilon and eta to reduce the trade-off for surface recorded seismic data.We test the (vh, epsilon, eta) parameterisation for acoustic VTI media using a scattering integral (SI) based inversion. The data is modeled in frequency domain and the model is updated using a preconditioned conjugate gradient method. We applied the method to the VTI Marmousi II model and in the inversion, we keep eta parameter fixed as the background initial model and we invert simultaneously for both vh and epsilon. The results show the suitability of the parameterisation for multi-parameter VTI acoustic inversion as well as the accuracy of the inversion approach.
Frequency Domain Multi-parameter Full Waveform Inversion for Acoustic VTI Media

KAUST Repository

Djebbi, Ramzi; Alkhalifah, Tariq Ali

2017-01-01

Multi-parameter full waveform inversion (FWI) for transversely isotropic (TI) media with vertical axis of symmetry (VTI) suffers from the trade-off between the parameters. The trade-off results in the leakage of one parameter's update into the other
Truncated Gauss-Newton Implementation for Multi-Parameter Full Waveform Inversion

Science.gov (United States)

Liu, Y.; Yang, J.; Dong, L.; Wang, Y.

2014-12-01

Full waveform inversion (FWI) is a numerical optimization method which aims at minimizing the difference between the synthetic and recorded seismic data to obtain high resolution subsurface images. A practical implementation for FWI is the adjoint-state method (AD), in which the data residuals at receiver locations are simultaneously back-propagated to form the gradient. Scattering-integral method (SI) is an alternative way which is based on the explicit building of the sensitivity kernel (Fréchet derivative matrix). Although it is more memory-consuming, SI is more efficient than AD when the number of the sources is larger than the number of the receivers. To improve the convergence of FWI, the information carried out by the inverse Hessian operator is crucial. Taking account accurately of the effect of this operator in FWI can correct illumination deficits, reserve the amplitude of the subsurface parameters, and remove artifacts generated by multiple reflections. In multi-parameter FWI, the off-diagonal blocks of the Hessian operator reflect the coupling between different parameter classes. Therefore, incorporating its inverse could help to mitigate the trade-off effects. In this study, we focus on the truncated Gauss-Newton implementation for multi-parameter FWI. The model update is computed through a matrix-free conjugate gradient solution of the Newton linear system. Both the gradient and the Hessian-vector product are calculated using the SI approach instead of the first- and second-order AD. However, the gradient expressed by kernel-vector product is calculated through the accumulation of the decomposed vector-scalar products. Thus, it's not necessary to store the huge sensitivity matrix beforehand. We call this method the matrix decomposition approach (MD). And the Hessian-vector product is replaced by two kernel-vector products which are then calculated by the above MD. By this way, we don't need to solve two additional wave propagation problems as in the
Multi-parameter full waveform inversion using Poisson

KAUST Repository

Oh, Juwon

2016-07-21

In multi-parameter full waveform inversion (FWI), the success of recovering each parameter is dependent on characteristics of the partial derivative wavefields (or virtual sources), which differ according to parameterisation. Elastic FWIs based on the two conventional parameterisations (one uses Lame constants and density; the other employs P- and S-wave velocities and density) have low resolution of gradients for P-wave velocities (or ). Limitations occur because the virtual sources for P-wave velocity or (one of the Lame constants) are related only to P-P diffracted waves, and generate isotropic explosions, which reduce the spatial resolution of the FWI for these parameters. To increase the spatial resolution, we propose a new parameterisation using P-wave velocity, Poisson\\'s ratio, and density for frequency-domain multi-parameter FWI for isotropic elastic media. By introducing Poisson\\'s ratio instead of S-wave velocity, the virtual source for the P-wave velocity generates P-S and S-S diffracted waves as well as P-P diffracted waves in the partial derivative wavefields for the P-wave velocity. Numerical examples of the cross-triangle-square (CTS) model indicate that the new parameterisation provides highly resolved descent directions for the P-wave velocity. Numerical examples of noise-free and noisy data synthesised for the elastic Marmousi-II model support the fact that the new parameterisation is more robust for noise than the two conventional parameterisations.
Multi-parameter Analysis and Inversion for Anisotropic Media Using the Scattering Integral Method

KAUST Repository

Djebbi, Ramzi

2017-01-01

the model. I study the prospect of applying a scattering integral approach for multi-parameter inversion for a transversely isotropic model with a vertical axis of symmetry. I mainly analyze the sensitivity kernels to understand the sensitivity of seismic
Mixed linear-nonlinear fault slip inversion: Bayesian inference of model, weighting, and smoothing parameters

Science.gov (United States)

Fukuda, J.; Johnson, K. M.

2009-12-01

Studies utilizing inversions of geodetic data for the spatial distribution of coseismic slip on faults typically present the result as a single fault plane and slip distribution. Commonly the geometry of the fault plane is assumed to be known a priori and the data are inverted for slip. However, sometimes there is not strong a priori information on the geometry of the fault that produced the earthquake and the data is not always strong enough to completely resolve the fault geometry. We develop a method to solve for the full posterior probability distribution of fault slip and fault geometry parameters in a Bayesian framework using Monte Carlo methods. The slip inversion problem is particularly challenging because it often involves multiple data sets with unknown relative weights (e.g. InSAR, GPS), model parameters that are related linearly (slip) and nonlinearly (fault geometry) through the theoretical model to surface observations, prior information on model parameters, and a regularization prior to stabilize the inversion. We present the theoretical framework and solution method for a Bayesian inversion that can handle all of these aspects of the problem. The method handles the mixed linear/nonlinear nature of the problem through combination of both analytical least-squares solutions and Monte Carlo methods. We first illustrate and validate the inversion scheme using synthetic data sets. We then apply the method to inversion of geodetic data from the 2003 M6.6 San Simeon, California earthquake. We show that the uncertainty in strike and dip of the fault plane is over 20 degrees. We characterize the uncertainty in the slip estimate with a volume around the mean fault solution in which the slip most likely occurred. Slip likely occurred somewhere in a volume that extends 5-10 km in either direction normal to the fault plane. We implement slip inversions with both traditional, kinematic smoothing constraints on slip and a simple physical condition of uniform stress
Multi-parameter Analysis and Inversion for Anisotropic Media Using the Scattering Integral Method

KAUST Repository

Djebbi, Ramzi

2017-10-24

The main goal in seismic exploration is to identify locations of hydrocarbons reservoirs and give insights on where to drill new wells. Therefore, estimating an Earth model that represents the right physics of the Earth\\'s subsurface is crucial in identifying these targets. Recent seismic data, with long offsets and wide azimuth features, are more sensitive to anisotropy. Accordingly, multiple anisotropic parameters need to be extracted from the recorded data on the surface to properly describe the model. I study the prospect of applying a scattering integral approach for multi-parameter inversion for a transversely isotropic model with a vertical axis of symmetry. I mainly analyze the sensitivity kernels to understand the sensitivity of seismic data to anisotropy parameters. Then, I use a frequency domain scattering integral approach to invert for the optimal parameterization. The scattering integral approach is based on the explicit computation of the sensitivity kernels. I present a new method to compute the traveltime sensitivity kernels for wave equation tomography using the unwrapped phase. I show that the new kernels are a better alternative to conventional cross-correlation/Rytov kernels. I also derive and analyze the sensitivity kernels for a transversely isotropic model with a vertical axis of symmetry. The kernels structure, for various opening/scattering angles, highlights the trade-off regions between the parameters. For a surface recorded data, I show that the normal move-out velocity vn, ƞ and δ parameterization is suitable for a simultaneous inversion of diving waves and reflections. Moreover, when seismic data is inverted hierarchically, the horizontal velocity vh, ƞ and ϵ is the parameterization with the least trade-off. In the frequency domain, the hierarchical inversion approach is naturally implemented using frequency continuation, which makes vh, ƞ and ϵ parameterization attractive. I formulate the multi-parameter inversion using the
3D stochastic inversion and joint inversion of potential fields for multi scale parameters

Science.gov (United States)

Shamsipour, Pejman

stochastic joint inversion method based on cokriging is applied to estimate density and magnetic susceptibility distributions from gravity and total magnetic field data. The method fully integrates the physical relations between the properties (density and magnetic susceptibility) and the indirect observations (gravity and total magnetic field). As a consequence, when the data are considered noise-free, the inverted fields exactly reproduce the observed data. The required density and magnetic susceptibility auto- and cross covariance are assumed to follow a linear model of coregionalization (LCM). In all the methods presented in this thesis, compact and stochastic synthetic models are investigated. The results show the ability of the methods to invert surface and borehole data simultaneously on multiple scale parameters. A case study using ground measurements of total magnetic field and gravity data at the Perseverance mine (Quebec, Canada) is selected and tested with the 3 approaches presented. The recovered 3D susceptibility and density model provides beneficial information that can be used to analyze the geology of massive sulfides for the domain under study.
Study on orthorhombic parameters for 3D elastic full waveform inversion

KAUST Repository

Oh, Juwon

2015-08-21

For a better understanding of the influence of the parameterizations on the multi-parameter full waveform inversion (FWI) for 3D elastic orthorhombic media, we analyze the virtual sources for each cij parameter. Because the virtual sources for cij parameters can be regarded as bases of the virtual sources for other parameterizations, the insights developed here explains many of the scattering phenomena of the different parameters. The resulting radiation patterns provide insights on which parameter set is the best in the multi-parameter FWI for 3D elastic orthorhombic media. In this study, we analyze the virtual source for each cij parameter as a linear combination of several moment tensors. After that, we analyze the strain fields deformed by incident waves as momenta of the virtual source and their influences on sensitivity kernels of each cij parameter.
Study on orthorhombic parameters for 3D elastic full waveform inversion

KAUST Repository

Oh, Juwon; Alkhalifah, Tariq Ali

2015-01-01

For a better understanding of the influence of the parameterizations on the multi-parameter full waveform inversion (FWI) for 3D elastic orthorhombic media, we analyze the virtual sources for each cij parameter. Because the virtual sources for cij parameters can be regarded as bases of the virtual sources for other parameterizations, the insights developed here explains many of the scattering phenomena of the different parameters. The resulting radiation patterns provide insights on which parameter set is the best in the multi-parameter FWI for 3D elastic orthorhombic media. In this study, we analyze the virtual source for each cij parameter as a linear combination of several moment tensors. After that, we analyze the strain fields deformed by incident waves as momenta of the virtual source and their influences on sensitivity kernels of each cij parameter.
Inverse scattering problems with multi-frequencies

International Nuclear Information System (INIS)

Bao, Gang; Li, Peijun; Lin, Junshan; Triki, Faouzi

2015-01-01

This paper is concerned with computational approaches and mathematical analysis for solving inverse scattering problems in the frequency domain. The problems arise in a diverse set of scientific areas with significant industrial, medical, and military applications. In addition to nonlinearity, there are two common difficulties associated with the inverse problems: ill-posedness and limited resolution (diffraction limit). Due to the diffraction limit, for a given frequency, only a low spatial frequency part of the desired parameter can be observed from measurements in the far field. The main idea developed here is that if the reconstruction is restricted to only the observable part, then the inversion will become stable. The challenging task is how to design stable numerical methods for solving these inverse scattering problems inspired by the diffraction limit. Recently, novel recursive linearization based algorithms have been presented in an attempt to answer the above question. These methods require multi-frequency scattering data and proceed via a continuation procedure with respect to the frequency from low to high. The objective of this paper is to give a brief review of these methods, their error estimates, and the related mathematical analysis. More attention is paid to the inverse medium and inverse source problems. Numerical experiments are included to illustrate the effectiveness of these methods. (topical review)
Inverse eigenvalue problems for Sturm-Liouville equations with spectral parameter linearly contained in one of the boundary conditions

OpenAIRE

Guliyev, Namig J.

2008-01-01

International audience; Inverse problems of recovering the coefficients of Sturm–Liouville problems with the eigenvalue parameter linearly contained in one of the boundary conditions are studied: 1) from the sequences of eigenvalues and norming constants; 2) from two spectra. Necessary and sufficient conditions for the solvability of these inverse problems are obtained.
Multi-parameter Full-waveform Inversion for Acoustic VTI Medium with Surface Seismic Data

Science.gov (United States)

Cheng, X.; Jiao, K.; Sun, D.; Huang, W.; Vigh, D.

2013-12-01

Full-waveform Inversion (FWI) attracts wide attention recently in oil and gas industry as a new promising tool for high resolution subsurface velocity model building. While the traditional common image point gather based tomography method aims to focus post-migrated data in depth domain, FWI aims to directly fit the observed seismic waveform in either time or frequency domain. The inversion is performed iteratively by updating the velocity fields to reduce the difference between the observed and the simulated data. It has been shown the inversion is very sensitive to the starting velocity fields, and data with long offsets and low frequencies is crucial for the success of FWI to overcome this sensitivity. Considering the importance of data with long offsets and low frequencies, in most geologic environment, anisotropy is an unavoidable topic for FWI especially at long offsets, since anisotropy tends to have more pronounced effects on waves traveled for a great distance. In VTI medium, this means more horizontal velocity will be registered in middle-to-long offset data, while more vertical velocity will be registered in near-to-middle offset data. Up to date, most of real world applications of FWI still remain in isotropic medium, and only a few studies have been shown to account for anisotropy. And most of those studies only account for anisotropy in waveform simulation, but not invert for those anisotropy fields. Multi-parameter inversion for anisotropy fields, even in VTI medium, remains as a hot topic in the field. In this study, we develop a strategy for multi-parameter FWI for acoustic VTI medium with surface seismic data. Because surface seismic data is insensitivity to the delta fields, we decide to hold the delta fields unchanged during our inversion, and invert only for vertical velocity and epsilon fields. Through parameterization analysis and synthetic tests, we find that it is more feasible to invert for the parameterization as vertical and horizontal
Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.
Solution of axisymmetric transient inverse heat conduction problems using parameter estimation and multi block methods

International Nuclear Information System (INIS)

Azimi, A.; Hannani, S.K.; Farhanieh, B.

2005-01-01

In this article, a comparison between two iterative inverse techniques to solve simultaneously two unknown functions of axisymmetric transient inverse heat conduction problems in semi complex geometries is presented. The multi-block structured grid together with blocked-interface nodes is implemented for geometric decomposition of physical domain. Numerical scheme for solution of transient heat conduction equation is the finite element method with frontal technique to solve algebraic system of discrete equations. The inverse heat conduction problem involves simultaneous unknown time varying heat generation and time-space varying boundary condition estimation. Two parameter-estimation techniques are considered, Levenberg-Marquardt scheme and conjugate gradient method with adjoint problem. Numerically computed exact and noisy data are used for the measured transient temperature data needed in the inverse solution. The results of the present study for a configuration including two joined disks with different heights are compared to those of exact heat source and temperature boundary condition, and show good agreement. (author)
Optimal Inversion Parameters for Full Waveform Inversion using OBS Data Set

Science.gov (United States)

Kim, S.; Chung, W.; Shin, S.; Kim, D.; Lee, D.

2017-12-01

In recent years, full Waveform Inversion (FWI) has been the most researched technique in seismic data processing. It uses the residuals between observed and modeled data as an objective function; thereafter, the final subsurface velocity model is generated through a series of iterations meant to minimize the residuals.Research on FWI has expanded from acoustic media to elastic media. In acoustic media, the subsurface property is defined by P-velocity; however, in elastic media, properties are defined by multiple parameters, such as P-velocity, S-velocity, and density. Further, the elastic media can also be defined by Lamé constants, density or impedance PI, SI; consequently, research is being carried out to ascertain the optimal parameters.From results of advanced exploration equipment and Ocean Bottom Seismic (OBS) survey, it is now possible to obtain multi-component seismic data. However, to perform FWI on these data and generate an accurate subsurface model, it is important to determine optimal inversion parameters among (Vp, Vs, ρ), (λ, μ, ρ), and (PI, SI) in elastic media. In this study, staggered grid finite difference method was applied to simulate OBS survey. As in inversion, l2-norm was set as objective function. Further, the accurate computation of gradient direction was performed using the back-propagation technique and its scaling was done using the Pseudo-hessian matrix.In acoustic media, only Vp is used as the inversion parameter. In contrast, various sets of parameters, such as (Vp, Vs, ρ) and (λ, μ, ρ) can be used to define inversion in elastic media. Therefore, it is important to ascertain the parameter that gives the most accurate result for inversion with OBS data set.In this study, we generated Vp and Vs subsurface models by using (λ, μ, ρ) and (Vp, Vs, ρ) as inversion parameters in every iteration, and compared the final two FWI results.This research was supported by the Basic Research Project(17-3312) of the Korea Institute of
Blocky inversion of multichannel elastic impedance for elastic parameters

Science.gov (United States)

Mozayan, Davoud Karami; Gholami, Ali; Siahkoohi, Hamid Reza

2018-04-01

Petrophysical description of reservoirs requires proper knowledge of elastic parameters like P- and S-wave velocities (Vp and Vs) and density (ρ), which can be retrieved from pre-stack seismic data using the concept of elastic impedance (EI). We propose an inversion algorithm which recovers elastic parameters from pre-stack seismic data in two sequential steps. In the first step, using the multichannel blind seismic inversion method (exploited recently for recovering acoustic impedance from post-stack seismic data), high-resolution blocky EI models are obtained directly from partial angle-stacks. Using an efficient total-variation (TV) regularization, each angle-stack is inverted independently in a multichannel form without prior knowledge of the corresponding wavelet. The second step involves inversion of the resulting EI models for elastic parameters. Mathematically, under some assumptions, the EI's are linearly described by the elastic parameters in the logarithm domain. Thus a linear weighted least squares inversion is employed to perform this step. Accuracy of the concept of elastic impedance in predicting reflection coefficients at low and high angles of incidence is compared with that of exact Zoeppritz elastic impedance and the role of low frequency content in the problem is discussed. The performance of the proposed inversion method is tested using synthetic 2D data sets obtained from the Marmousi model and also 2D field data sets. The results confirm the efficiency and accuracy of the proposed method for inversion of pre-stack seismic data.
Linearized inversion of two components seismic data; Inversion linearisee de donnees sismiques a deux composantes

Energy Technology Data Exchange (ETDEWEB)

Lebrun, D.

1997-05-22

The aim of the dissertation is the linearized inversion of multicomponent seismic data for 3D elastic horizontally stratified media, using Born approximation. A Jacobian matrix is constructed; it will be used to model seismic data from elastic parameters. The inversion technique, relying on single value decomposition (SVD) of the Jacobian matrix, is described. Next, the resolution of inverted elastic parameters is quantitatively studies. A first use of the technique is shown in the frame of an evaluation of a sea bottom acquisition (synthetic data). Finally, a real data set acquired with conventional marine technique is inverted. (author) 70 refs.
Frequency-domain full-waveform inversion with non-linear descent directions

Science.gov (United States)

Geng, Yu; Pan, Wenyong; Innanen, Kristopher A.

2018-05-01

Full-waveform inversion (FWI) is a highly non-linear inverse problem, normally solved iteratively, with each iteration involving an update constructed through linear operations on the residuals. Incorporating a flexible degree of non-linearity within each update may have important consequences for convergence rates, determination of low model wavenumbers and discrimination of parameters. We examine one approach for doing so, wherein higher order scattering terms are included within the sensitivity kernel during the construction of the descent direction, adjusting it away from that of the standard Gauss-Newton approach. These scattering terms are naturally admitted when we construct the sensitivity kernel by varying not the current but the to-be-updated model at each iteration. Linear and/or non-linear inverse scattering methodologies allow these additional sensitivity contributions to be computed from the current data residuals within any given update. We show that in the presence of pre-critical reflection data, the error in a second-order non-linear update to a background of s0 is, in our scheme, proportional to at most (Δs/s0)3 in the actual parameter jump Δs causing the reflection. In contrast, the error in a standard Gauss-Newton FWI update is proportional to (Δs/s0)2. For numerical implementation of more complex cases, we introduce a non-linear frequency-domain scheme, with an inner and an outer loop. A perturbation is determined from the data residuals within the inner loop, and a descent direction based on the resulting non-linear sensitivity kernel is computed in the outer loop. We examine the response of this non-linear FWI using acoustic single-parameter synthetics derived from the Marmousi model. The inverted results vary depending on data frequency ranges and initial models, but we conclude that the non-linear FWI has the capability to generate high-resolution model estimates in both shallow and deep regions, and to converge rapidly, relative to a

A New Linearization Technique Using Multi-sinh Doublet

Directory of Open Access Journals (Sweden)

CEHAN, V.

2009-06-01

Full Text Available In this paper a new linearization technique using multi-sinh doublet, implemented with a second generation current conveyor is presented. This new linearization technique is compared with the one based on multi-tanh doublets with linearization series connected diodes on the branches. The comparative study of the two linearization techniques is carried out using both dynamic range analysis, expressed by linearity error and the THD value calculation of output current, and the noise behavior of the two analyzed doublets. For the multi-sinh linearization technique proposed in the paper a method which assures the increase of the dynamic range, keeping the transconductance value constant is presented. This is done by using two design parameters: the number of series connected diodes N, which specifies the desired linear operating range and the k emitters areas ratio of the input stage transistors, which establishes the transconductance value. In the paper is also shown that if the transconductances of the two analyzed doublets are identical, and for the same values of N and k parameters, respectively, the current consumption of the multi-sinh doublet is always smaller than for the multi-tanh doublet.
Efficient Inversion of Mult-frequency and Multi-Source Electromagnetic Data

Energy Technology Data Exchange (ETDEWEB)

Gary D. Egbert

2007-03-22

The project covered by this report focused on development of efficient but robust non-linear inversion algorithms for electromagnetic induction data, in particular for data collected with multiple receivers, and multiple transmitters, a situation extremely common in eophysical EM subsurface imaging methods. A key observation is that for such multi-transmitter problems each step in commonly used linearized iterative limited memory search schemes such as conjugate gradients (CG) requires solution of forward and adjoint EM problems for each of the N frequencies or sources, essentially generating data sensitivities for an N dimensional data-subspace. These multiple sensitivities allow a good approximation to the full Jacobian of the data mapping to be built up in many fewer search steps than would be required by application of textbook optimization methods, which take no account of the multiplicity of forward problems that must be solved for each search step. We have applied this idea to a develop a hybrid inversion scheme that combines features of the iterative limited memory type methods with a Newton-type approach using a partial calculation of the Jacobian. Initial tests on 2D problems show that the new approach produces results essentially identical to a Newton type Occam minimum structure inversion, while running more rapidly than an iterative (fixed regularization parameter) CG style inversion. Memory requirements, while greater than for something like CG, are modest enough that even in 3D the scheme should allow 3D inverse problems to be solved on a common desktop PC, at least for modest (~ 100 sites, 15-20 frequencies) data sets. A secondary focus of the research has been development of a modular system for EM inversion, using an object oriented approach. This system has proven useful for more rapid prototyping of inversion algorithms, in particular allowing initial development and testing to be conducted with two-dimensional example problems, before
Time-domain induced polarization - an analysis of Cole-Cole parameter resolution and correlation using Markov Chain Monte Carlo inversion

Science.gov (United States)

Madsen, Line Meldgaard; Fiandaca, Gianluca; Auken, Esben; Christiansen, Anders Vest

2017-12-01

The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole-Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo (MCMC) inversion algorithm, a full non-linear uncertainty analysis of the parameters and the parameter correlations can be accessed. This is essential to understand to what degree the spectral Cole-Cole parameters can be resolved from TDIP data. MCMC inversions of synthetic TDIP data, which show bell-shaped probability distributions with a single maximum, show that the Cole-Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole-Cole parameters are observed and by decreasing the acquisitions ranges, the correlations increase and become non-linear. It is further investigated how waveform and parameter values influence the resolution of the Cole-Cole parameters. A limiting factor is the value of the frequency exponent, C. As C decreases, the resolution of all the Cole-Cole parameters decreases and the results become increasingly non-linear. While the values of the time constant, τ, must be in the acquisition range to resolve the parameters well, the choice between a 50 per cent and a 100 per cent duty cycle for the current injection does not have an influence on the parameter resolution. The limits of resolution and linearity are also studied in a comparison between the MCMC and a linearized gradient-based inversion approach. The two methods are consistent for resolved models, but the linearized approach tends to underestimate the uncertainties for poorly resolved parameters due to the corresponding non-linear features. Finally, an MCMC inversion of 1-D field data verifies that spectral Cole-Cole parameters can also be resolved from TD field measurements.
An Entropic Estimator for Linear Inverse Problems

Directory of Open Access Journals (Sweden)

Amos Golan

2012-05-01

Full Text Available In this paper we examine an Information-Theoretic method for solving noisy linear inverse estimation problems which encompasses under a single framework a whole class of estimation methods. Under this framework, the prior information about the unknown parameters (when such information exists, and constraints on the parameters can be incorporated in the statement of the problem. The method builds on the basics of the maximum entropy principle and consists of transforming the original problem into an estimation of a probability density on an appropriate space naturally associated with the statement of the problem. This estimation method is generic in the sense that it provides a framework for analyzing non-normal models, it is easy to implement and is suitable for all types of inverse problems such as small and or ill-conditioned, noisy data. First order approximation, large sample properties and convergence in distribution are developed as well. Analytical examples, statistics for model comparisons and evaluations, that are inherent to this method, are discussed and complemented with explicit examples.
Microlocal analysis of a seismic linearized inverse problem

NARCIS (Netherlands)

Stolk, C.C.

1999-01-01

The seismic inverse problem is to determine the wavespeed c x in the interior of a medium from measurements at the boundary In this paper we analyze the linearized inverse problem in general acoustic media The problem is to nd a left inverse of the linearized forward map F or equivalently to nd the
An linear matrix inequality approach to global synchronisation of non-parameter perturbations of multi-delay Hopfield neural network

International Nuclear Information System (INIS)

Shao Hai-Jian; Cai Guo-Liang; Wang Hao-Xiang

2010-01-01

In this study, a successful linear matrix inequality approach is used to analyse a non-parameter perturbation of multi-delay Hopfield neural network by constructing an appropriate Lyapunov-Krasovskii functional. This paper presents the comprehensive discussion of the approach and also extensive applications
Large Scale Document Inversion using a Multi-threaded Computing System.

Science.gov (United States)

Jung, Sungbo; Chang, Dar-Jen; Park, Juw Won

2017-06-01

Current microprocessor architecture is moving towards multi-core/multi-threaded systems. This trend has led to a surge of interest in using multi-threaded computing devices, such as the Graphics Processing Unit (GPU), for general purpose computing. We can utilize the GPU in computation as a massive parallel coprocessor because the GPU consists of multiple cores. The GPU is also an affordable, attractive, and user-programmable commodity. Nowadays a lot of information has been flooded into the digital domain around the world. Huge volume of data, such as digital libraries, social networking services, e-commerce product data, and reviews, etc., is produced or collected every moment with dramatic growth in size. Although the inverted index is a useful data structure that can be used for full text searches or document retrieval, a large number of documents will require a tremendous amount of time to create the index. The performance of document inversion can be improved by multi-thread or multi-core GPU. Our approach is to implement a linear-time, hash-based, single program multiple data (SPMD), document inversion algorithm on the NVIDIA GPU/CUDA programming platform utilizing the huge computational power of the GPU, to develop high performance solutions for document indexing. Our proposed parallel document inversion system shows 2-3 times faster performance than a sequential system on two different test datasets from PubMed abstract and e-commerce product reviews. •Information systems➝Information retrieval • Computing methodologies➝Massively parallel and high-performance simulations.
Combining vegetation index and model inversion methods for theextraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data

DEFF Research Database (Denmark)

Houborg, Rasmus Møller; Søgaard, Henrik; Bøgh, Eva

2007-01-01

for the inversion of a canopy reflectance model using Terra and Aqua MODIS multi-spectral, multi-temporal, and multi-angle reflectance observations to aid the determination of vegetation-specific physiological and structural canopy parameters. Land cover and site-specific inversion modeling was applied...
Combined genetic algorithm and multiple linear regression (GA-MLR) optimizer: Application to multi-exponential fluorescence decay surface.

Science.gov (United States)

Fisz, Jacek J

2006-12-07

The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares problems in which the model functions are linear combinations of nonlinear functions. GA optimizes the nonlinear parameters, and the linear parameters are calculated from MLR. GA-MLR is an intuitive optimization approach and it exploits all advantages of the genetic algorithm technique. This optimization method results from an appropriate combination of two well-known optimization methods. The MLR method is embedded in the GA optimizer and linear and nonlinear model parameters are optimized in parallel. The MLR method is the only one strictly mathematical "tool" involved in GA-MLR. The GA-MLR approach simplifies and accelerates considerably the optimization process because the linear parameters are not the fitted ones. Its properties are exemplified by the analysis of the kinetic biexponential fluorescence decay surface corresponding to a two-excited-state interconversion process. A short discussion of the variable projection (VP) algorithm, designed for the same class of the optimization problems, is presented. VP is a very advanced mathematical formalism that involves the methods of nonlinear functionals, algebra of linear projectors, and the formalism of Fréchet derivatives and pseudo-inverses. Additional explanatory comments are added on the application of recently introduced the GA-NR optimizer to simultaneous recovery of linear and weakly nonlinear parameters occurring in the same optimization problem together with nonlinear parameters. The GA-NR optimizer combines the GA method with the NR method, in which the minimum-value condition for the quadratic approximation to chi(2), obtained from the Taylor series expansion of chi(2), is recovered by means of the Newton-Raphson algorithm. The application of the GA-NR optimizer to model functions which are multi-linear
Analysis of the multi-component pseudo-pure-mode qP-wave inversion in vertical transverse isotropic (VTI) media

KAUST Repository

Djebbi, Ramzi; Alkhalifah, Tariq Ali

2014-01-01

Multi-parameter inversion in anisotropic media suffers from the inherent trade-off between the anisotropic parameters, even under the acoustic assumption. Multi-component data, often acquired nowadays in ocean bottom acquisition and land data
Large Scale Document Inversion using a Multi-threaded Computing System

Science.gov (United States)

Jung, Sungbo; Chang, Dar-Jen; Park, Juw Won

2018-01-01

Current microprocessor architecture is moving towards multi-core/multi-threaded systems. This trend has led to a surge of interest in using multi-threaded computing devices, such as the Graphics Processing Unit (GPU), for general purpose computing. We can utilize the GPU in computation as a massive parallel coprocessor because the GPU consists of multiple cores. The GPU is also an affordable, attractive, and user-programmable commodity. Nowadays a lot of information has been flooded into the digital domain around the world. Huge volume of data, such as digital libraries, social networking services, e-commerce product data, and reviews, etc., is produced or collected every moment with dramatic growth in size. Although the inverted index is a useful data structure that can be used for full text searches or document retrieval, a large number of documents will require a tremendous amount of time to create the index. The performance of document inversion can be improved by multi-thread or multi-core GPU. Our approach is to implement a linear-time, hash-based, single program multiple data (SPMD), document inversion algorithm on the NVIDIA GPU/CUDA programming platform utilizing the huge computational power of the GPU, to develop high performance solutions for document indexing. Our proposed parallel document inversion system shows 2-3 times faster performance than a sequential system on two different test datasets from PubMed abstract and e-commerce product reviews. CCS Concepts •Information systems➝Information retrieval • Computing methodologies➝Massively parallel and high-performance simulations.
Stability Analysis for Multi-Parameter Linear Periodic Systems

DEFF Research Database (Denmark)

Seyranian, A.P.; Solem, Frederik; Pedersen, Pauli

1999-01-01

This paper is devoted to stability analysis of general linear periodic systems depending on real parameters. The Floquet method and perturbation technique are the basis of the development. We start out with the first and higher-order derivatives of the Floquet matrix with respect to problem...
Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

Energy Technology Data Exchange (ETDEWEB)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

2017-12-01

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.
Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

International Nuclear Information System (INIS)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

2017-01-01

In this paper we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated — reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.
Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

Science.gov (United States)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

2017-12-01

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated - reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.
Parameter estimation and inverse problems

CERN Document Server

Aster, Richard C; Thurber, Clifford H

2005-01-01

Parameter Estimation and Inverse Problems primarily serves as a textbook for advanced undergraduate and introductory graduate courses. Class notes have been developed and reside on the World Wide Web for faciliting use and feedback by teaching colleagues. The authors'' treatment promotes an understanding of fundamental and practical issus associated with parameter fitting and inverse problems including basic theory of inverse problems, statistical issues, computational issues, and an understanding of how to analyze the success and limitations of solutions to these probles. The text is also a practical resource for general students and professional researchers, where techniques and concepts can be readily picked up on a chapter-by-chapter basis.Parameter Estimation and Inverse Problems is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who may not have an extensive mathematical background. It is accompanied by a Web site that...
Multi-stage full waveform inversion strategy for 2D elastic VTI media

KAUST Repository

Oh, Juwon; Alkhalifah, Tariq Ali; Min, Dong-Joo

2015-01-01

One of the most important issues in the multi-parametric full waveform inversion (FWI) is to find an optimal parameterization, which helps us recover the subsurface anisotropic parameters as well as seismic velocities, with minimal tradeoff. As a
Interactive Approach for Multi-Level Multi-Objective Fractional Programming Problems with Fuzzy Parameters

Directory of Open Access Journals (Sweden)

M.S. Osman

2018-03-01

Full Text Available In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997. In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.
Online Energy Management of City Cars with Multi-Objective Linear Parameter-Varying L2-Gain Control

Directory of Open Access Journals (Sweden)

Boe-Shong Hong

2015-09-01

Full Text Available This work aims at online regulating transient current out of the batteries of small-sized electric cars that transport people and goods around cities. In a city with heavy traffic, transient current dominates the energy economy and propulsion capability, which are in opposition to each other. In order to manage the trade-off between energy consumption per distance and propulsion capability in transience, the authors improve on previous work on multi-objective linear parameter-varying (LPV L2-gain control. The observer embedded into this multi-objective controller no longer assumes Kalman-filtering structure, and structural conservatism is thus removed. A full-spectrum set of experiments is performed. The results reveal that the feedback design significantly improves energy-motion management.
A genetic meta-algorithm-assisted inversion approach: hydrogeological study for the determination of volumetric rock properties and matrix and fluid parameters in unsaturated formations

Science.gov (United States)

Szabó, Norbert Péter

2018-03-01

An evolutionary inversion approach is suggested for the interpretation of nuclear and resistivity logs measured by direct-push tools in shallow unsaturated sediments. The efficiency of formation evaluation is improved by estimating simultaneously (1) the petrophysical properties that vary rapidly along a drill hole with depth and (2) the zone parameters that can be treated as constant, in one inversion procedure. In the workflow, the fractional volumes of water, air, matrix and clay are estimated in adjacent depths by linearized inversion, whereas the clay and matrix properties are updated using a float-encoded genetic meta-algorithm. The proposed inversion method provides an objective estimate of the zone parameters that appear in the tool response equations applied to solve the forward problem, which can significantly increase the reliability of the petrophysical model as opposed to setting these parameters arbitrarily. The global optimization meta-algorithm not only assures the best fit between the measured and calculated data but also gives a reliable solution, practically independent of the initial model, as laboratory data are unnecessary in the inversion procedure. The feasibility test uses engineering geophysical sounding logs observed in an unsaturated loessy-sandy formation in Hungary. The multi-borehole extension of the inversion technique is developed to determine the petrophysical properties and their estimation errors along a profile of drill holes. The genetic meta-algorithmic inversion method is recommended for hydrogeophysical logging applications of various kinds to automatically extract the volumetric ratios of rock and fluid constituents as well as the most important zone parameters in a reliable inversion procedure.

Fast non-linear extraction of plasma equilibrium parameters using a neural network mapping

International Nuclear Information System (INIS)

Lister, J.B.; Schnurrenberger, H.

1990-07-01

The shaping of non-circular plasmas requires a non-linear mapping between the measured diagnostic signals and selected equilibrium parameters. The particular configuration of Neural Network known as the multi-layer perceptron provides a powerful and general technique for formulating an arbitrary continuous non-linear multi-dimensional mapping. This technique has been successfully applied to the extraction of equilibrium parameters from measurements of single-null diverted plasmas in the DIII-D tokamak; the results are compared with a purely linear mapping. The method is promising, and hardware implementation is straightforward. (author) 15 refs., 7 figs
Time-domain induced polarization - an analysis of Cole-Cole parameter resolution and correlation using Markov Chain Monte Carlo inversion

DEFF Research Database (Denmark)

Madsen, Line Meldgaard; Fiandaca, Gianluca; Auken, Esben

2017-01-01

The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole-Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo......-shaped probability distributions with a single maximum, show that the Cole-Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole-Cole parameters are observed and by decreasing the acquisitions ranges, the correlations...
Multi-stage full waveform inversion strategy for 2D elastic VTI media

KAUST Repository

Oh, Juwon

2015-08-19

One of the most important issues in the multi-parametric full waveform inversion (FWI) is to find an optimal parameterization, which helps us recover the subsurface anisotropic parameters as well as seismic velocities, with minimal tradeoff. As a result, we analyze three different parameterizations for elastic VTI media in terms of the influence of the S-waves on the gradient direction for c13, the spatial coverage of gradient direction and the degree of trade-offs between the parameters. Based on the dependency results, we design a multi-stage elastic VTI FWI strategy to enhance both the spatial coverage of the FWI and the robustness to the trade-offs among the parameters as well as FWI for the c13 structure.
Inverse chaos synchronization in linearly and nonlinearly coupled systems with multiple time-delays

International Nuclear Information System (INIS)

Shahverdiev, E.M.; Hashimov, R.H.; Nuriev, R.A.; Hashimova, L.H.; Huseynova, E.M.; Shore, K.A.

2005-04-01

We report on inverse chaos synchronization between two unidirectionally linearly and nonlinearly coupled chaotic systems with multiple time-delays and find the existence and stability conditions for different synchronization regimes. We also study the effect of parameter mismatches on synchonization regimes. The method is tested on the famous Ikeda model. Numerical simulations fully support the analytical approach. (author)
Fuzzy Multi Objective Linear Programming Problem with Imprecise Aspiration Level and Parameters

Directory of Open Access Journals (Sweden)

Zahra Shahraki

2015-07-01

Full Text Available This paper considers the multi-objective linear programming problems with fuzzygoal for each of the objective functions and constraints. Most existing works deal withlinear membership functions for fuzzy goals. In this paper, exponential membershipfunction is used.
Inverse Modelling Problems in Linear Algebra Undergraduate Courses

Science.gov (United States)

Martinez-Luaces, Victor E.

2013-01-01

This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Waveform inversion in acoustic orthorhombic media with a practical set of parameters

KAUST Repository

Masmoudi, Nabil; Alkhalifah, Tariq Ali

2017-01-01

Full-waveform inversion (FWI) in anisotropic media is overall challenging, mainly because of the large computational cost, especially in 3D, and the potential trade-offs between the model parameters needed to describe such a media. We propose an efficient 3D FWI implementation for orthorhombic anisotropy under the acoustic assumption. Our modeling is based on solving the pseudo-differential orthorhombic wave equation split into a differential operator and a scalar one. The modeling is computationally efficient and free of shear wave artifacts. Using the adjoint state method, we derive the gradients with respect to a practical set of parameters describing the acoustic orthorhombic model, made of one velocity and five dimensionless parameters. This parameterization allows us to use a multi-stage model inversion strategy based on the continuity of the scattering potential of the parameters as we go from higher symmetry anisotropy to lower ones. We apply the proposed approach on a modified SEG-EAGE overthrust synthetic model. The quality of the inverted model suggest that we may recover only 4 parameters, with different resolution scales depending on the scattering potential of these parameters.
Waveform inversion in acoustic orthorhombic media with a practical set of parameters

KAUST Repository

Masmoudi, Nabil

2017-08-17

Full-waveform inversion (FWI) in anisotropic media is overall challenging, mainly because of the large computational cost, especially in 3D, and the potential trade-offs between the model parameters needed to describe such a media. We propose an efficient 3D FWI implementation for orthorhombic anisotropy under the acoustic assumption. Our modeling is based on solving the pseudo-differential orthorhombic wave equation split into a differential operator and a scalar one. The modeling is computationally efficient and free of shear wave artifacts. Using the adjoint state method, we derive the gradients with respect to a practical set of parameters describing the acoustic orthorhombic model, made of one velocity and five dimensionless parameters. This parameterization allows us to use a multi-stage model inversion strategy based on the continuity of the scattering potential of the parameters as we go from higher symmetry anisotropy to lower ones. We apply the proposed approach on a modified SEG-EAGE overthrust synthetic model. The quality of the inverted model suggest that we may recover only 4 parameters, with different resolution scales depending on the scattering potential of these parameters.
Linear System of Equations, Matrix Inversion, and Linear Programming Using MS Excel

Science.gov (United States)

El-Gebeily, M.; Yushau, B.

2008-01-01

In this note, we demonstrate with illustrations two different ways that MS Excel can be used to solve Linear Systems of Equation, Linear Programming Problems, and Matrix Inversion Problems. The advantage of using MS Excel is its availability and transparency (the user is responsible for most of the details of how a problem is solved). Further, we…
AI-guided parameter optimization in inverse treatment planning

International Nuclear Information System (INIS)

Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

2003-01-01

An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach
Inverse problems in linear transport theory

International Nuclear Information System (INIS)

Dressler, K.

1988-01-01

Inverse problems for a class of linear kinetic equations are investigated. The aim is to identify the scattering kernel of a transport equation (corresponding to the structure of a background medium) by observing the 'albedo' part of the solution operator for the corresponding direct initial boundary value problem. This means to get information on some integral operator in an integrodifferential equation through on overdetermined boundary value problem. We first derive a constructive method for solving direct halfspace problems and prove a new factorization theorem for the solutions. Using this result we investigate stationary inverse problems with respect to well posedness (e.g. reduce them to classical ill-posed problems, such as integral equations of first kind). In the time-dependent case we show that a quite general inverse problem is well posed and solve it constructively. (orig.)
Angle-domain inverse scattering migration/inversion in isotropic media

Science.gov (United States)

Li, Wuqun; Mao, Weijian; Li, Xuelei; Ouyang, Wei; Liang, Quan

2018-07-01

The classical seismic asymptotic inversion can be transformed into a problem of inversion of generalized Radon transform (GRT). In such methods, the combined parameters are linearly attached to the scattered wave-field by Born approximation and recovered by applying an inverse GRT operator to the scattered wave-field data. Typical GRT-style true-amplitude inversion procedure contains an amplitude compensation process after the weighted migration via dividing an illumination associated matrix whose elements are integrals of scattering angles. It is intuitional to some extent that performs the generalized linear inversion and the inversion of GRT together by this process for direct inversion. However, it is imprecise to carry out such operation when the illumination at the image point is limited, which easily leads to the inaccuracy and instability of the matrix. This paper formulates the GRT true-amplitude inversion framework in an angle-domain version, which naturally degrades the external integral term related to the illumination in the conventional case. We solve the linearized integral equation for combined parameters of different fixed scattering angle values. With this step, we obtain high-quality angle-domain common-image gathers (CIGs) in the migration loop which provide correct amplitude-versus-angle (AVA) behavior and reasonable illumination range for subsurface image points. Then we deal with the over-determined problem to solve each parameter in the combination by a standard optimization operation. The angle-domain GRT inversion method keeps away from calculating the inaccurate and unstable illumination matrix. Compared with the conventional method, the angle-domain method can obtain more accurate amplitude information and wider amplitude-preserved range. Several model tests demonstrate the effectiveness and practicability.
Multi-objective optimization in quantum parameter estimation

Science.gov (United States)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.
Choice of parameters for linear colliders in multi-bunch mode

International Nuclear Information System (INIS)

Claus, J.

1987-01-01

The energy efficiency of a linear collider in multi-bunch mode is calculated for the case that the bunches in each of the two interacting beams are identical in all interaction points, a configuration which can be realized by taking advantage of the beam-beam effect between beams of opposite electric charge. The maximization of the efficiency is discussed, the maximum appears to increase nearly linearly with beam brightness and accelerating gradient, and about quadratically with the length of the ir. The optimum operating frequency for the linacs increases also, while the pulse repetition rate and the beam current needed for fixed luminosity, decrease. The increasing brightness and the decreasing current needed for higher efficiency lead to smaller transverse spotsizes in the crossing points; this imposes tighter tolerances on the relative transverse coordinates of the two beam-axes. Pillbox or similar resonators, excited in the TM01 mode, may be preferable to quadrupoles for transverse focusing, at the high frequencies and gradients that seem desirable, particularly in the final focus. 4 refs., 7 figs
Radionuclide release rate inversion of nuclear accidents in nuclear facility based on Kalman filter

International Nuclear Information System (INIS)

Tang Xiuhuan; Bao Lihong; Li Hua; Wan Junsheng

2014-01-01

The rapidly and continually back-calculating source term is important for nuclear emergency response. The Gaussian multi-puff atmospheric dispersion model was used to produce regional environment monitoring data virtually, and then a Kalman filter was designed to inverse radionuclide release rate of nuclear accidents in nuclear facility and the release rate tracking in real time was achieved. The results show that the Kalman filter combined with Gaussian multi-puff atmospheric dispersion model can successfully track the virtually stable, linear or nonlinear release rate after being iterated about 10 times. The standard error of inversion results increases with the true value. Meanwhile extended Kalman filter cannot inverse the height parameter of accident release as interceptive error is too large to converge. Kalman filter constructed from environment monitoring data and Gaussian multi-puff atmospheric dispersion model can be applied to source inversion in nuclear accident which is characterized by static height and position, short and continual release in nuclear facility. Hence it turns out to be an alternative source inversion method in nuclear emergency response. (authors)
Utilizing High-Performance Computing to Investigate Parameter Sensitivity of an Inversion Model for Vadose Zone Flow and Transport

Science.gov (United States)

Fang, Z.; Ward, A. L.; Fang, Y.; Yabusaki, S.

2011-12-01

High-resolution geologic models have proven effective in improving the accuracy of subsurface flow and transport predictions. However, many of the parameters in subsurface flow and transport models cannot be determined directly at the scale of interest and must be estimated through inverse modeling. A major challenge, particularly in vadose zone flow and transport, is the inversion of the highly-nonlinear, high-dimensional problem as current methods are not readily scalable for large-scale, multi-process models. In this paper we describe the implementation of a fully automated approach for addressing complex parameter optimization and sensitivity issues on massively parallel multi- and many-core systems. The approach is based on the integration of PNNL's extreme scale Subsurface Transport Over Multiple Phases (eSTOMP) simulator, which uses the Global Array toolkit, with the Beowulf-Cluster inspired parallel nonlinear parameter estimation software, BeoPEST in the MPI mode. In the eSTOMP/BeoPEST implementation, a pre-processor generates all of the PEST input files based on the eSTOMP input file. Simulation results for comparison with observations are extracted automatically at each time step eliminating the need for post-process data extractions. The inversion framework was tested with three different experimental data sets: one-dimensional water flow at Hanford Grass Site; irrigation and infiltration experiment at the Andelfingen Site; and a three-dimensional injection experiment at Hanford's Sisson and Lu Site. Good agreements are achieved in all three applications between observations and simulations in both parameter estimates and water dynamics reproduction. Results show that eSTOMP/BeoPEST approach is highly scalable and can be run efficiently with hundreds or thousands of processors. BeoPEST is fault tolerant and new nodes can be dynamically added and removed. A major advantage of this approach is the ability to use high-resolution geologic models to preserve
Seismic Anisotropy Beneath Eastern North America: Results from Multi-Event Inversion

Science.gov (United States)

Li, Y.; Levin, V. L.; Chen, X.

2017-12-01

Seismic anisotropy observed from the split core-refracted shear phases reflects upper mantle deformation. To characterize anisotropic signatures beneath eastern North America, we collected observations along a 1300 km long array from James Bay to the Fundy Basin. The averaged splitting parameters of individual sites show uniform fast polarization orientation of 80° and delay times linearly decreasing from 1.0 s in the Appalachians to 0.5 s in the Superior Province. We also see directional variation of fast polarizations at most sites, which is a likely effect of vertical changes in anisotropic properties. For sites with 10 or more observations, we used a multi-event inversion technique to solve for the underlying anisotropic structure. The technique considers the NULL observations from single-event analysis that are excluded from the averaged splitting parameters. For models with a single 100 km thick anisotropic layer with a horizontal fast axis, we find up to 6% of anisotropy in the Appalachian Orogen, equivalent to a splitting delay time of 1.5 s. Anisotropy strength reduces to 1.8% in the Superior Province, equivalent to delay times under 0.5 s. The overall decrease in anisotropic strength is modified by local changes of up to 2%, suggesting small-scale local variations near the surface. Orientations of the fast axes change from 60° in the Appalachian Orogen to 90° in the Superior Province, and are also modulated by local deviations. In the Appalachian Orogen the fast axes are close to the absolute plate motion in a hot-spot reference frame, while those in the Superior Province differ from it by almost 30°. Average values of splitting delays agree well with results of inversions in the Superior Province, and diverge in the Appalachians. Conversely, averaged fast polarizations match inversion results in the Appalachians, and are systematically different in the Superior Province. For an set of sites with recording periods exceeding 5 years, we will test more
Anisotropic wave-equation traveltime and waveform inversion

KAUST Repository

Feng, Shihang

2016-09-06

The wave-equation traveltime and waveform inversion (WTW) methodology is developed to invert for anisotropic parameters in a vertical transverse isotropic (VTI) meidum. The simultaneous inversion of anisotropic parameters v0, ε and δ is initially performed using the wave-equation traveltime inversion (WT) method. The WT tomograms are then used as starting background models for VTI full waveform inversion. Preliminary numerical tests on synthetic data demonstrate the feasibility of this method for multi-parameter inversion.
Linearized versus non-linear inverse methods for seismic localization of underground sources

DEFF Research Database (Denmark)

Oh, Geok Lian; Jacobsen, Finn

2013-01-01

The problem of localization of underground sources from seismic measurements detected by several geophones located on the ground surface is addressed. Two main approaches to the solution of the problem are considered: a beamforming approach that is derived from the linearized inversion problem, a...
Application of decomposition method and inverse prediction of parameters in a moving fin

International Nuclear Information System (INIS)

Singla, Rohit K.; Das, Ranjan

2014-01-01

Highlights: • Adomian decomposition is used to study a moving fin. • Effects of different parameters on the temperature and efficiency are studied. • Binary-coded GA is used to solve an inverse problem. • Sensitivity analyses of important parameters are carried out. • Measurement error up to 8% is found to be tolerable. - Abstract: The application of the Adomian decomposition method (ADM) is extended to study a conductive–convective and radiating moving fin having variable thermal conductivity. Next, through an inverse approach, ADM in conjunction with a binary-coded genetic algorithm (GA) is also applied for estimation of unknown properties in order to satisfy a given temperature distribution. ADM being one of the widely-used numerical methods for solving non-linear equations, the required temperature field has been obtained using a forward method involving ADM. In the forward problem, the temperature field and efficiency are investigated for various parameters such as convection–conduction parameter, radiation–conduction parameter, Peclet number, convection sink temperature, radiation sink temperature, and dimensionless thermal conductivity. Additionally, in the inverse problem, the effect of random measurement errors, iterative variation of parameters, sensitivity coefficients of unknown parameters are investigated. The performance of GA is compared with few other optimization methods as well as with different temperature measurement points. It is found from the present study that the results obtained from ADM are in good agreement with the results of the differential transformation method available in the literature. It is also observed that for satisfactory reconstruction of the temperature field, the measurement error should be within 8% and the temperature field is strongly dependent on the speed than thermal parameters of the moving fin

Multi-Parameter Estimation for Orthorhombic Media

KAUST Repository

Masmoudi, Nabil

2015-08-19

Building reliable anisotropy models is crucial in seismic modeling, imaging and full waveform inversion. However, estimating anisotropy parameters is often hampered by the trade off between inhomogeneity and anisotropy. For instance, one way to estimate the anisotropy parameters is to relate them analytically to traveltimes, which is challenging in inhomogeneous media. Using perturbation theory, we develop travel-time approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2 and a parameter Δγ in inhomogeneous background media. Specifically, our expansion assumes inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. This approach has two main advantages: in one hand, it provides a computationally efficient tool to solve the orthorhombic eikonal equation, on the other hand, it provides a mechanism to scan for the best fitting anisotropy parameters without the need for repetitive modeling of traveltimes, because the coefficients of the traveltime expansion are independent of the perturbed parameters. Furthermore, the coefficients of the traveltime expansion provide insights on the sensitivity of the traveltime with respect to the perturbed parameters. We show the accuracy of the traveltime approximations as well as an approach for multi-parameter scanning in orthorhombic media.
Multi-Parameter Estimation for Orthorhombic Media

KAUST Repository

Masmoudi, Nabil; Alkhalifah, Tariq Ali

2015-01-01

Building reliable anisotropy models is crucial in seismic modeling, imaging and full waveform inversion. However, estimating anisotropy parameters is often hampered by the trade off between inhomogeneity and anisotropy. For instance, one way to estimate the anisotropy parameters is to relate them analytically to traveltimes, which is challenging in inhomogeneous media. Using perturbation theory, we develop travel-time approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2 and a parameter Δγ in inhomogeneous background media. Specifically, our expansion assumes inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. This approach has two main advantages: in one hand, it provides a computationally efficient tool to solve the orthorhombic eikonal equation, on the other hand, it provides a mechanism to scan for the best fitting anisotropy parameters without the need for repetitive modeling of traveltimes, because the coefficients of the traveltime expansion are independent of the perturbed parameters. Furthermore, the coefficients of the traveltime expansion provide insights on the sensitivity of the traveltime with respect to the perturbed parameters. We show the accuracy of the traveltime approximations as well as an approach for multi-parameter scanning in orthorhombic media.
Fast non-linear extraction of plasma equilibrium parameters using a neural network mapping

International Nuclear Information System (INIS)

Lister, J.B.; Schnurrenberger, H.

1991-01-01

The shaping of non-circular plasmas requires a non-linear mapping between the measured diagnostic signals and selected equilibrium parameters. The particular configuration of neural network known as the multilayer perceptron provides a powerful and general technique for formulating an arbitrary continuous non-linear multi-dimensional mapping. This technique has been successfully applied to the extraction of equilibrium parameters from measurements of single-null diverted plasmas in the DIII-D tokamak; the results are compared with a purely linear mapping. The method is promising, and hardware implementation is straightforward. (author). 17 refs, 8 figs, 2 tab
Multi-objective optimization of inverse planning for accurate radiotherapy

International Nuclear Information System (INIS)

Cao Ruifen; Pei Xi; Cheng Mengyun; Li Gui; Hu Liqin; Wu Yican; Jing Jia; Li Guoli

2011-01-01

The multi-objective optimization of inverse planning based on the Pareto solution set, according to the multi-objective character of inverse planning in accurate radiotherapy, was studied in this paper. Firstly, the clinical requirements of a treatment plan were transformed into a multi-objective optimization problem with multiple constraints. Then, the fast and elitist multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) was introduced to optimize the problem. A clinical example was tested using this method. The results show that an obtained set of non-dominated solutions were uniformly distributed and the corresponding dose distribution of each solution not only approached the expected dose distribution, but also met the dose-volume constraints. It was indicated that the clinical requirements were better satisfied using the method and the planner could select the optimal treatment plan from the non-dominated solution set. (authors)
Metamodel-based inverse method for parameter identification: elastic-plastic damage model

Science.gov (United States)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.
Numerical simulation of electro-osmotic consolidation coupling non-linear variation of soil parameters

Science.gov (United States)

Wu, Hui; Hu, Liming; Wen, Qingbo

2017-06-01

Electro-osmotic consolidation is an effective method for soft ground improvement. A main limitation of previous numerical models on this technique is the ignorance of the non-linear variation of soil parameters. In the present study, a multi-field numerical model is developed with the consideration of the non-linear variation of soil parameters during electro-osmotic consolidation process. The numerical simulations on an axisymmetric model indicated that the non-linear variation of soil parameters showed remarkable impact on the development of the excess pore water pressure and degree of consolidation. A field experiment with complex geometry, boundary conditions, electrode configuration and voltage application was further simulated with the developed numerical model. The comparison between field and numerical data indicated that the numerical model coupling of the non-linear variation of soil parameters gave more reasonable results. The developed numerical model is capable to analyze engineering cases with complex operating conditions.
Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

NARCIS (Netherlands)

Baak, M.; Gadatsch, S.; Harrington, R.; Verkerke, W.

2015-01-01

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model׳s parameters and transformed according to a specific
Taming waveform inversion non-linearity through phase unwrapping of the model and objective functions

KAUST Repository

Alkhalifah, Tariq Ali

2012-09-25

Traveltime inversion focuses on the geometrical features of the waveform (traveltimes), which is generally smooth, and thus, tends to provide averaged (smoothed) information of the model. On other hand, general waveform inversion uses additional elements of the wavefield including amplitudes to extract higher resolution information, but this comes at the cost of introducing non-linearity to the inversion operator, complicating the convergence process. We use unwrapped phase-based objective functions in waveform inversion as a link between the two general types of inversions in a domain in which such contributions to the inversion process can be easily identified and controlled. The instantaneous traveltime is a measure of the average traveltime of the energy in a trace as a function of frequency. It unwraps the phase of wavefields yielding far less non-linearity in the objective function than that experienced with conventional wavefields, yet it still holds most of the critical wavefield information in its frequency dependency. However, it suffers from non-linearity introduced by the model (or reflectivity), as reflections from independent events in our model interact with each other. Unwrapping the phase of such a model can mitigate this non-linearity as well. Specifically, a simple modification to the inverted domain (or model), can reduce the effect of the model-induced non-linearity and, thus, make the inversion more convergent. Simple numerical examples demonstrate these assertions.
Taming waveform inversion non-linearity through phase unwrapping of the model and objective functions

KAUST Repository

Alkhalifah, Tariq Ali; Choi, Yun Seok

2012-01-01

Traveltime inversion focuses on the geometrical features of the waveform (traveltimes), which is generally smooth, and thus, tends to provide averaged (smoothed) information of the model. On other hand, general waveform inversion uses additional elements of the wavefield including amplitudes to extract higher resolution information, but this comes at the cost of introducing non-linearity to the inversion operator, complicating the convergence process. We use unwrapped phase-based objective functions in waveform inversion as a link between the two general types of inversions in a domain in which such contributions to the inversion process can be easily identified and controlled. The instantaneous traveltime is a measure of the average traveltime of the energy in a trace as a function of frequency. It unwraps the phase of wavefields yielding far less non-linearity in the objective function than that experienced with conventional wavefields, yet it still holds most of the critical wavefield information in its frequency dependency. However, it suffers from non-linearity introduced by the model (or reflectivity), as reflections from independent events in our model interact with each other. Unwrapping the phase of such a model can mitigate this non-linearity as well. Specifically, a simple modification to the inverted domain (or model), can reduce the effect of the model-induced non-linearity and, thus, make the inversion more convergent. Simple numerical examples demonstrate these assertions.
Study of 1D complex resistivity inversion using digital linear filter technique; Linear filter ho wo mochiita fukusohi teiko no gyakukaisekiho no kento

Energy Technology Data Exchange (ETDEWEB)

Sakurai, K; Shima, H [OYO Corp., Tokyo (Japan)

1996-10-01

This paper proposes a modeling method of one-dimensional complex resistivity using linear filter technique which has been extended to the complex resistivity. In addition, a numerical test of inversion was conducted using the monitoring results, to discuss the measured frequency band. Linear filter technique is a method by which theoretical potential can be calculated for stratified structures, and it is widely used for the one-dimensional analysis of dc electrical exploration. The modeling can be carried out only using values of complex resistivity without using values of potential. In this study, a bipolar method was employed as a configuration of electrodes. The numerical test of one-dimensional complex resistivity inversion was conducted using the formulated modeling. A three-layered structure model was used as a numerical model. A multi-layer structure with a thickness of 5 m was analyzed on the basis of apparent complex resistivity calculated from the model. From the results of numerical test, it was found that both the chargeability and the time constant agreed well with those of the original model. A trade-off was observed between the chargeability and the time constant at the stage of convergence. 3 refs., 9 figs., 1 tab.
The time-lapse AVO difference inversion for changes in reservoir parameters

Science.gov (United States)

Longxiao, Zhi; Hanming, Gu; Yan, Li

2016-12-01

The result of conventional time-lapse seismic processing is the difference between the amplitude and the post-stack seismic data. Although stack processing can improve the signal-to-noise ratio (SNR) of seismic data, it also causes a considerable loss of important information about the amplitude changes and only gives the qualitative interpretation. To predict the changes in reservoir fluid more precisely and accurately, we also need the quantitative information of the reservoir. To achieve this aim, we develop the method of time-lapse AVO (amplitude versus offset) difference inversion. For the inversion of reservoir changes in elastic parameters, we apply the Gardner equation as the constraint and convert the three-parameter inversion of elastic parameter changes into a two-parameter inversion to make the inversion more stable. For the inversion of variations in the reservoir parameters, we infer the relation between the difference of the reflection coefficient and variations in the reservoir parameters, and then invert reservoir parameter changes directly. The results of the theoretical modeling computation and practical application show that our method can estimate the relative variations in reservoir density, P-wave and S-wave velocity, calculate reservoir changes in water saturation and effective pressure accurately, and then provide reference for the rational exploitation of the reservoir.
Constraint on Parameters of Inverse Compton Scattering Model for ...

Indian Academy of Sciences (India)

B2319+60, two parameters of inverse Compton scattering model, the initial Lorentz factor and the factor of energy loss of relativistic particles are constrained. Key words. Pulsar—inverse Compton scattering—emission mechanism. 1. Introduction. Among various kinds of models for pulsar radio emission, the inverse ...
Effect of objective function on multi-objective inverse planning of radiation therapy

International Nuclear Information System (INIS)

Li Guoli; Wu Yican; Song Gang; Wang Shifang

2006-01-01

There are two kinds of objective functions in radiotherapy inverse planning: dose distribution-based and Dose-Volume Histogram (DVH)-based functions. The treatment planning in our days is still a trial and error process because the multi-objective problem is solved by transforming it into a single objective problem using a specific set of weights for each object. This work investigates the problem of objective function setting based on Pareto multi-optimization theory, and compares the effect on multi-objective inverse planning of those two kinds of objective functions including calculation time, converge speed, etc. The basis of objective function setting on inverse planning is discussed. (authors)
Numerical solution to a multi-dimensional linear inverse heat conduction problem by a splitting-based conjugate gradient method

International Nuclear Information System (INIS)

Dinh Nho Hao; Nguyen Trung Thanh; Sahli, Hichem

2008-01-01

In this paper we consider a multi-dimensional inverse heat conduction problem with time-dependent coefficients in a box, which is well-known to be severely ill-posed, by a variational method. The gradient of the functional to be minimized is obtained by aids of an adjoint problem and the conjugate gradient method with a stopping rule is then applied to this ill-posed optimization problem. To enhance the stability and the accuracy of the numerical solution to the problem we apply this scheme to the discretized inverse problem rather than to the continuous one. The difficulties with large dimensions of discretized problems are overcome by a splitting method which only requires the solution of easy-to-solve one-dimensional problems. The numerical results provided by our method are very good and the techniques seem to be very promising.
Probabilistic inversion in priority setting of emerging zoonoses.

NARCIS (Netherlands)

Kurowicka, D.; Bucura, C.; Cooke, R.; Havelaar, A.H.

2010-01-01

This article presents methodology of applying probabilistic inversion in combination with expert judgment in priority setting problem. Experts rank scenarios according to severity. A linear multi-criteria analysis model underlying the expert preferences is posited. Using probabilistic inversion, a
Non-Linear Metamodeling Extensions to the Robust Parameter Design of Computer Simulations

Science.gov (United States)

2016-09-15

The combined-array RSM approach has been applied to a piston simulation [11] and an economic order quantity inventory model [12, 13]. A textbook ...are limited when applied to simulations. In the former case, the mean and variance models can be inadequate due to a high level of non-linearity...highly non-linear nature of typical simulations. In the multi-response RPD problem, the objective is to find the optimal control parameter levels
LinvPy : a Python package for linear inverse problems

OpenAIRE

Beaud, Guillaume François Paul

2016-01-01

The goal of this project is to make a Python package including the tau-estimator algorithm to solve linear inverse problems. The package must be distributed, well documented, easy to use and easy to extend for future developers.
Treating experimental data of inverse kinetic method by unitary linear regression analysis

International Nuclear Information System (INIS)

Zhao Yusen; Chen Xiaoliang

2009-01-01

The theory of treating experimental data of inverse kinetic method by unitary linear regression analysis was described. Not only the reactivity, but also the effective neutron source intensity could be calculated by this method. Computer code was compiled base on the inverse kinetic method and unitary linear regression analysis. The data of zero power facility BFS-1 in Russia were processed and the results were compared. The results show that the reactivity and the effective neutron source intensity can be obtained correctly by treating experimental data of inverse kinetic method using unitary linear regression analysis and the precision of reactivity measurement is improved. The central element efficiency can be calculated by using the reactivity. The result also shows that the effect to reactivity measurement caused by external neutron source should be considered when the reactor power is low and the intensity of external neutron source is strong. (authors)
Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

Energy Technology Data Exchange (ETDEWEB)

Baak, M., E-mail: max.baak@cern.ch [CERN, CH-1211 Geneva 23 (Switzerland); Gadatsch, S., E-mail: stefan.gadatsch@nikhef.nl [Nikhef, PO Box 41882, 1009 DB Amsterdam (Netherlands); Harrington, R. [School of Physics and Astronomy, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JZ, Scotland (United Kingdom); Verkerke, W. [Nikhef, PO Box 41882, 1009 DB Amsterdam (Netherlands)

2015-01-21

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates are often required to model the impact of systematic uncertainties.
Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

International Nuclear Information System (INIS)

Baak, M.; Gadatsch, S.; Harrington, R.; Verkerke, W.

2015-01-01

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates are often required to model the impact of systematic uncertainties

Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

CERN Document Server

Baak, Max; Harrington, Robert; Verkerke, Wouter

2014-01-01

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates is often required to model the impact of systematic uncertainties.
Interpolation between multi-dimensional histograms using a new non-linear moment morphing method

CERN Document Server

Baak, Max; Harrington, Robert; Verkerke, Wouter

2015-01-01

A prescription is presented for the interpolation between multi-dimensional distribution templates based on one or multiple model parameters. The technique uses a linear combination of templates, each created using fixed values of the model's parameters and transformed according to a specific procedure, to model a non-linear dependency on model parameters and the dependency between them. By construction the technique scales well with the number of input templates used, which is a useful feature in modern day particle physics, where a large number of templates is often required to model the impact of systematic uncertainties.
Simultaneous retrieval of aerosols and ocean properties: A classic inverse modeling approach. I. Analytic Jacobians from the linearized CAO-DISORT model

International Nuclear Information System (INIS)

Spurr, Robert; Stamnes, Knut; Eide, Hans; Li Wei; Zhang Kexin; Stamnes, Jakob

2007-01-01

In this paper and the sequel, we investigate the application of classic inverse methods based on iterative least-squares cost-function minimization to the simultaneous retrieval of aerosol and ocean properties from visible and near infrared spectral radiance measurements such as those from the SeaWiFS and MODIS instruments. Radiance measurements at the satellite are simulated directly using an accurate coupled atmosphere-ocean-discrete-ordinate radiative transfer (CAO-DISORT) code as the main component of the forward model. For this kind of cost-function inverse problem, we require the forward model to generate weighting functions (radiance partial derivatives) with respect to the aerosol and marine properties to be retrieved, and to other model parameters which are sources of error in the retrievals. In this paper, we report on the linearization of the CAO-DISORT model. This linearization provides a complete analytic differentiation of the coupled-media radiative transfer theory, and it allows the model to generate analytic weighting functions for any atmospheric or marine parameter. For high solar zenith angles, we give an implementation of the pseudo-spherical (P-S) approach to solar beam attenuation in the atmosphere in the linearized model. We summarize a number of performance enhancements such as the use of an exact single-scattering calculation to improve accuracy. We derive inherent optical property inputs for the linearized CAO-DISORT code for a simple 2-parameter bio-optical model for the marine environment coupled to a 2-parameter bimodal atmospheric aerosol medium
Adaptive discretizations for the choice of a Tikhonov regularization parameter in nonlinear inverse problems

International Nuclear Information System (INIS)

Kaltenbacher, Barbara; Kirchner, Alana; Vexler, Boris

2011-01-01

Parameter identification problems for partial differential equations usually lead to nonlinear inverse problems. A typical property of such problems is their instability, which requires regularization techniques, like, e.g., Tikhonov regularization. The main focus of this paper will be on efficient methods for determining a suitable regularization parameter by using adaptive finite element discretizations based on goal-oriented error estimators. A well-established method for the determination of a regularization parameter is the discrepancy principle where the residual norm, considered as a function i of the regularization parameter, should equal an appropriate multiple of the noise level. We suggest to solve the resulting scalar nonlinear equation by an inexact Newton method, where in each iteration step, a regularized problem is solved at a different discretization level. The proposed algorithm is an extension of the method suggested in Griesbaum A et al (2008 Inverse Problems 24 025025) for linear inverse problems, where goal-oriented error estimators for i and its derivative are used for adaptive refinement strategies in order to keep the discretization level as coarse as possible to save computational effort but fine enough to guarantee global convergence of the inexact Newton method. This concept leads to a highly efficient method for determining the Tikhonov regularization parameter for nonlinear ill-posed problems. Moreover, we prove that with the so-obtained regularization parameter and an also adaptively discretized Tikhonov minimizer, usual convergence and regularization results from the continuous setting can be recovered. As a matter of fact, it is shown that it suffices to use stationary points of the Tikhonov functional. The efficiency of the proposed method is demonstrated by means of numerical experiments. (paper)
Inverse Boundary Value Problem for Non-linear Hyperbolic Partial Differential Equations

OpenAIRE

Nakamura, Gen; Vashisth, Manmohan

2017-01-01

In this article we are concerned with an inverse boundary value problem for a non-linear wave equation of divergence form with space dimension $n\\geq 3$. This non-linear wave equation has a trivial solution, i.e. zero solution. By linearizing this equation at the trivial solution, we have the usual linear isotropic wave equation with the speed $\\sqrt{\\gamma(x)}$ at each point $x$ in a given spacial domain. For any small solution $u=u(t,x)$ of this non-linear equation, we have the linear isotr...
Imaging disturbance zones ahead of a tunnel by elastic full-waveform inversion: Adjoint gradient based inversion vs. parameter space reduction using a level-set method

Directory of Open Access Journals (Sweden)

Andre Lamert

2018-03-01

Full Text Available We present and compare two flexible and effective methodologies to predict disturbance zones ahead of underground tunnels by using elastic full-waveform inversion. One methodology uses a linearized, iterative approach based on misfit gradients computed with the adjoint method while the other uses iterative, gradient-free unscented Kalman filtering in conjunction with a level-set representation. Whereas the former does not involve a priori assumptions on the distribution of elastic properties ahead of the tunnel, the latter introduces a massive reduction in the number of explicit model parameters to be inverted for by focusing on the geometric form of potential disturbances and their average elastic properties. Both imaging methodologies are validated through successful reconstructions of simple disturbances. As an application, we consider an elastic multiple disturbance scenario. By using identical synthetic time-domain seismograms as test data, we obtain satisfactory, albeit different, reconstruction results from the two inversion methodologies. The computational costs of both approaches are of the same order of magnitude, with the gradient-based approach showing a slight advantage. The model parameter space reduction approach compensates for this by additionally providing a posteriori estimates of model parameter uncertainty. Keywords: Tunnel seismics, Full waveform inversion, Seismic waves, Level-set method, Adjoint method, Kalman filter
A Projected Non-linear Conjugate Gradient Method for Interactive Inverse Kinematics

DEFF Research Database (Denmark)

Engell-Nørregård, Morten; Erleben, Kenny

2009-01-01

Inverse kinematics is the problem of posing an articulated figure to obtain a wanted goal, without regarding inertia and forces. Joint limits are modeled as bounds on individual degrees of freedom, leading to a box-constrained optimization problem. We present A projected Non-linear Conjugate...... Gradient optimization method suitable for box-constrained optimization problems for inverse kinematics. We show application on inverse kinematics positioning of a human figure. Performance is measured and compared to a traditional Jacobian Transpose method. Visual quality of the developed method...
Multiparameter Optimization for Electromagnetic Inversion Problem

Directory of Open Access Journals (Sweden)

M. Elkattan

2017-10-01

Full Text Available Electromagnetic (EM methods have been extensively used in geophysical investigations such as mineral and hydrocarbon exploration as well as in geological mapping and structural studies. In this paper, we developed an inversion methodology for Electromagnetic data to determine physical parameters of a set of horizontal layers. We conducted Forward model using transmission line method. In the inversion part, we solved multi parameter optimization problem where, the parameters are conductivity, dielectric constant, and permeability of each layer. The optimization problem was solved by simulated annealing approach. The inversion methodology was tested using a set of models representing common geological formations.
Multi-source waveform inversion of marine streamer data using the normalized wavefield

KAUST Repository

Choi, Yun Seok

2012-01-01

Even though the encoded multi-source approach dramatically reduces the computational cost of waveform inversion, it is generally not applicable to marine streamer data. This is because the simultaneous-sources modeled data cannot be muted to comply with the configuration of the marine streamer data, which causes differences in the number of stacked-traces, or energy levels, between the modeled and observed data. Since the conventional L2 norm does not account for the difference in energy levels, multi-source inversion based on the conventional L2 norm does not work for marine streamer data. In this study, we propose the L2, approximated L2, and L1 norm using the normalized wavefields for the multi-source waveform inversion of marine streamer data. Since the normalized wavefields mitigate the different energy levels between the observed and modeled wavefields, the multi-source waveform inversion using the normalized wavefields can be applied to marine streamer data. We obtain the gradient of the objective functions using the back-propagation algorithm. To conclude, the gradient of the L2 norm using the normalized wavefields is exactly the same as that of the global correlation norm. In the numerical examples, the new objective functions using the normalized wavefields generate successful results whereas conventional L2 norm does not.
A unified inversion scheme to process multifrequency measurements of various dispersive electromagnetic properties

Science.gov (United States)

Han, Y.; Misra, S.

2018-04-01

Multi-frequency measurement of a dispersive electromagnetic (EM) property, such as electrical conductivity, dielectric permittivity, or magnetic permeability, is commonly analyzed for purposes of material characterization. Such an analysis requires inversion of the multi-frequency measurement based on a specific relaxation model, such as Cole-Cole model or Pelton's model. We develop a unified inversion scheme that can be coupled to various type of relaxation models to independently process multi-frequency measurement of varied EM properties for purposes of improved EM-based geomaterial characterization. The proposed inversion scheme is firstly tested in few synthetic cases in which different relaxation models are coupled into the inversion scheme and then applied to multi-frequency complex conductivity, complex resistivity, complex permittivity, and complex impedance measurements. The method estimates up to seven relaxation-model parameters exhibiting convergence and accuracy for random initializations of the relaxation-model parameters within up to 3-orders of magnitude variation around the true parameter values. The proposed inversion method implements a bounded Levenberg algorithm with tuning initial values of damping parameter and its iterative adjustment factor, which are fixed in all the cases shown in this paper and irrespective of the type of measured EM property and the type of relaxation model. Notably, jump-out step and jump-back-in step are implemented as automated methods in the inversion scheme to prevent the inversion from getting trapped around local minima and to honor physical bounds of model parameters. The proposed inversion scheme can be easily used to process various types of EM measurements without major changes to the inversion scheme.
A fully general and adaptive inverse analysis method for cementitious materials

DEFF Research Database (Denmark)

Jepsen, Michael S.; Damkilde, Lars; Lövgren, Ingemar

2016-01-01

The paper presents an adaptive method for inverse determination of the tensile σ - w relationship, direct tensile strength and Young’s modulus of cementitious materials. The method facilitates an inverse analysis with a multi-linear σ - w function. Usually, simple bi- or tri-linear functions...... are applied when modeling the fracture mechanisms in cementitious materials, but the vast development of pseudo-strain hardening, fiber reinforced cementitious materials require inverse methods, capable of treating multi-linear σ - w functions. The proposed method is fully general in the sense that it relies...... of notched specimens and simulated data from a nonlinear hinge model. The paper shows that the results obtained by means of the proposed method is independent on the initial shape of the σ - w function and the initial guess of the tensile strength. The method provides very accurate fits, and the increased...
Scanning Electron Microscope Calibration Using a Multi-Image Non-Linear Minimization Process

Science.gov (United States)

Cui, Le; Marchand, Éric

2015-04-01

A scanning electron microscope (SEM) calibrating approach based on non-linear minimization procedure is presented in this article. A part of this article has been published in IEEE International Conference on Robotics and Automation (ICRA), 2014. . Both the intrinsic parameters and the extrinsic parameters estimations are achieved simultaneously by minimizing the registration error. The proposed approach considers multi-images of a multi-scale calibration pattern view from different positions and orientations. Since the projection geometry of the scanning electron microscope is different from that of a classical optical sensor, the perspective projection model and the parallel projection model are considered and compared with distortion models. Experiments are realized by varying the position and the orientation of a multi-scale chessboard calibration pattern from 300× to 10,000×. The experimental results show the efficiency and the accuracy of this approach.
Carbon 13 nuclear magnetic resonance chemical shifts empiric calculations of polymers by multi linear regression and molecular modeling

International Nuclear Information System (INIS)

Da Silva Pinto, P.S.; Eustache, R.P.; Audenaert, M.; Bernassau, J.M.

1996-01-01

This work deals with carbon 13 nuclear magnetic resonance chemical shifts empiric calculations by multi linear regression and molecular modeling. The multi linear regression is indeed one way to obtain an equation able to describe the behaviour of the chemical shift for some molecules which are in the data base (rigid molecules with carbons). The methodology consists of structures describer parameters definition which can be bound to carbon 13 chemical shift known for these molecules. Then, the linear regression is used to determine the equation significant parameters. This one can be extrapolated to molecules which presents some resemblances with those of the data base. (O.L.). 20 refs., 4 figs., 1 tab
Bayesian inversion of microtremor array dispersion data in southwestern British Columbia

Science.gov (United States)

Molnar, Sheri; Dosso, Stan E.; Cassidy, John F.

2010-11-01

This paper applies Bayesian inversion, with evaluation of data errors and model parametrization, to produce the most-probable shear-wave velocity profile together with quantitative uncertainty estimates from microtremor array dispersion data. Generally, the most important property for characterizing earthquake site response is the shear-wave velocity (VS) profile. The microtremor array method determines phase velocity dispersion of Rayleigh surface waves from multi-instrument recordings of urban noise. Inversion of dispersion curves for VS structure is a non-unique and non-linear problem such that meaningful evaluation of confidence intervals is required. Quantitative uncertainty estimation requires not only a non-linear inversion approach that samples models proportional to their probability, but also rigorous estimation of the data error statistics and an appropriate model parametrization. This paper applies a Bayesian formulation that represents the solution of the inverse problem in terms of the posterior probability density (PPD) of the geophysical model parameters. Markov-chain Monte Carlo methods are used with an efficient implementation of Metropolis-Hastings sampling to provide an unbiased sample from the PPD to compute parameter uncertainties and inter-relationships. Nonparametric estimation of a data error covariance matrix from residual analysis is applied with rigorous a posteriori statistical tests to validate the covariance estimate and the assumption of a Gaussian error distribution. The most appropriate model parametrization is determined using the Bayesian information criterion, which provides the simplest model consistent with the resolving power of the data. Parametrizations considered vary in the number of layers, and include layers with uniform, linear and power-law gradients. Parameter uncertainties are found to be underestimated when data error correlations are neglected and when compressional-wave velocity and/or density (nuisance
LMI-based gain scheduled controller synthesis for a class of linear parameter varying systems

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Anderson, Brian; Lanzon, Alexander

2006-01-01

This paper presents a novel method for constructing controllers for a class of single-input multiple-output (SIMO) linear parameter varying (LPV) systems. This class of systems encompasses many physical systems, in particular systems where individual components vary with time, and is therefore...... of significant practical relevance to control designers. The control design presented in this paper has the properties that the system matrix of the closed loop is multi-affine in the various scalar parameters, and that the resulting controller ensures a certain degree of stability for the closed loop even when...... as a standard linear time-invariant (LTI) design combined with a set of linear matrix inequalities, which can be solved efficiently with software tools. The design procedure is illustrated by a numerical example....
Application of multi-source waveform inversion to marine streamer data using the global correlation norm

KAUST Repository

Choi, Yun Seok

2012-05-02

Conventional multi-source waveform inversion using an objective function based on the least-square misfit cannot be applied to marine streamer acquisition data because of inconsistent acquisition geometries between observed and modelled data. To apply the multi-source waveform inversion to marine streamer data, we use the global correlation between observed and modelled data as an alternative objective function. The new residual seismogram derived from the global correlation norm attenuates modelled data not supported by the configuration of observed data and thus, can be applied to multi-source waveform inversion of marine streamer data. We also show that the global correlation norm is theoretically the same as the least-square norm of the normalized wavefield. To efficiently calculate the gradient, our method employs a back-propagation algorithm similar to reverse-time migration based on the adjoint-state of the wave equation. In numerical examples, the multi-source waveform inversion using the global correlation norm results in better inversion results for marine streamer acquisition data than the conventional approach. © 2012 European Association of Geoscientists & Engineers.
On the Resolution of Inversion for Orthorhombic Anisotropy

KAUST Repository

Kazei, Vladimir

2017-05-26

We investigate the resolution of elastic anisotropic inversion for orthorhombic media with P-waves by remapping classic radiation patterns into the wavenumber domain. We show analytically that dynamic linearized inversion (linearized reverse-time migration and full-waveform inversion) for orthorhombic anisotropy based on longitudinal waves is fundamentally sensitive to emph{six} parameters only and density, in which the perturbing effects can be represented by particular anisotropy configuration. Singular value decomposition of spectral sensitivities allows us to provide estimates of the number of parameters one could invert in specific acquisition settings, and with certain parametrization. In most acquisition scenarios, a hierarchical parameterization based on the $P$, and $S$-wave velocities, along with dimensionless parameters that describe the anisotropy as velocity ratio in the radial and azimuthal directions, minimizes the tradeoff and increases the sensitivity of the data to velocity compared to the standard (stiffness, density) parametrization. These features yield more robust velocity estimation, by focusing the inversion on a subset of invertible parameters.
On the Resolution of Inversion for Orthorhombic Anisotropy

KAUST Repository

Kazei, Vladimir; Alkhalifah, Tariq Ali

2017-01-01

We investigate the resolution of elastic anisotropic inversion for orthorhombic media with P-waves by remapping classic radiation patterns into the wavenumber domain. We show analytically that dynamic linearized inversion (linearized reverse-time migration and full-waveform inversion) for orthorhombic anisotropy based on longitudinal waves is fundamentally sensitive to emph{six} parameters only and density, in which the perturbing effects can be represented by particular anisotropy configuration. Singular value decomposition of spectral sensitivities allows us to provide estimates of the number of parameters one could invert in specific acquisition settings, and with certain parametrization. In most acquisition scenarios, a hierarchical parameterization based on the $P$, and $S$-wave velocities, along with dimensionless parameters that describe the anisotropy as velocity ratio in the radial and azimuthal directions, minimizes the tradeoff and increases the sensitivity of the data to velocity compared to the standard (stiffness, density) parametrization. These features yield more robust velocity estimation, by focusing the inversion on a subset of invertible parameters.
Multi-objective optimization of linear multi-state multiple sliding window system

International Nuclear Information System (INIS)

Konak, Abdullah; Kulturel-Konak, Sadan; Levitin, Gregory

2012-01-01

This paper considers the optimal element sequencing in a linear multi-state multiple sliding window system that consists of n linearly ordered multi-state elements. Each multi-state element can have different states: from complete failure up to perfect functioning. A performance rate is associated with each state. The failure of type i in the system occurs if for any i (1≤i≤I) the cumulative performance of any r i consecutive elements is lower than w i . The element sequence strongly affects the probability of any type of system failure. The sequence that minimizes the probability of certain type of failure can provide high probability of other types of failures. Therefore the optimization problem for the multiple sliding window system is essentially multi-objective. The paper formulates and solves the multi-objective optimization problem for the multiple sliding window systems. A multi-objective Genetic Algorithm is used as the optimization engine. Illustrative examples are presented.
Inverse kinematics of a dual linear actuator pitch/roll heliostat

Science.gov (United States)

Freeman, Joshua; Shankar, Balakrishnan; Sundaram, Ganesh

2017-06-01

This work presents a simple, computationally efficient inverse kinematics solution for a pitch/roll heliostat using two linear actuators. The heliostat design and kinematics have been developed, modeled and tested using computer simulation software. A physical heliostat prototype was fabricated to validate the theoretical computations and data. Pitch/roll heliostats have numerous advantages including reduced cost potential and reduced space requirements, with a primary disadvantage being the significantly more complicated kinematics, which are solved here. Novel methods are applied to simplify the inverse kinematics problem which could be applied to other similar problems.

Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data

Directory of Open Access Journals (Sweden)

Andrew Wallace

2012-02-01

Full Text Available We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC and reversible jump MCMC (RJMCMC methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI, which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion.
The possibilities of linearized inversion of internally scattered seismic data

KAUST Repository

Aldawood, Ali

2014-08-05

Least-square migration is an iterative linearized inversion scheme that tends to suppress the migration artifacts and enhance the spatial resolution of the migrated image. However, standard least-square migration, based on imaging single scattering energy, may not be able to enhance events that are mainly illuminated by internal multiples such as vertical and nearly vertical faults. To alleviate this problem, we propose a linearized inversion framework to migrate internally multiply scattered energy. We applied this least-square migration of internal multiples to image a vertical fault. Tests on synthetic data demonstrate the ability of the proposed method to resolve a vertical fault plane that is poorly resolved by least-square imaging using primaries only. We, also, demonstrate the robustness of the proposed scheme in the presence of white Gaussian random observational noise and in the case of imaging the fault plane using inaccurate migration velocities.
The possibilities of linearized inversion of internally scattered seismic data

KAUST Repository

Aldawood, Ali; Alkhalifah, Tariq Ali; Hoteit, Ibrahim; Zuberi, Mohammad; Turkiyyah, George

2014-01-01

Least-square migration is an iterative linearized inversion scheme that tends to suppress the migration artifacts and enhance the spatial resolution of the migrated image. However, standard least-square migration, based on imaging single scattering energy, may not be able to enhance events that are mainly illuminated by internal multiples such as vertical and nearly vertical faults. To alleviate this problem, we propose a linearized inversion framework to migrate internally multiply scattered energy. We applied this least-square migration of internal multiples to image a vertical fault. Tests on synthetic data demonstrate the ability of the proposed method to resolve a vertical fault plane that is poorly resolved by least-square imaging using primaries only. We, also, demonstrate the robustness of the proposed scheme in the presence of white Gaussian random observational noise and in the case of imaging the fault plane using inaccurate migration velocities.
A Sparse Approximate Inverse Preconditioner for Nonsymmetric Linear Systems

Czech Academy of Sciences Publication Activity Database

Benzi, M.; Tůma, Miroslav

1998-01-01

Roč. 19, č. 3 (1998), s. 968-994 ISSN 1064-8275 R&D Projects: GA ČR GA201/93/0067; GA AV ČR IAA230401 Keywords : large sparse systems * interative methods * preconditioning * approximate inverse * sparse linear systems * sparse matrices * incomplete factorizations * conjugate gradient -type methods Subject RIV: BA - General Mathematics Impact factor: 1.378, year: 1998
Lattice Designs in Standard and Simple Implicit Multi-linear Regression

OpenAIRE

Wooten, Rebecca D.

2016-01-01

Statisticians generally use ordinary least squares to minimize the random error in a subject response with respect to independent explanatory variable. However, Wooten shows illustrates how ordinary least squares can be used to minimize the random error in the system without defining a subject response. Using lattice design Wooten shows that non-response analysis is a superior alternative rotation of the pyramidal relationship between random variables and parameter estimates in multi-linear r...
Bayesian seismic AVO inversion

Energy Technology Data Exchange (ETDEWEB)

Buland, Arild

2002-07-01

A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Reconstruction of constitutive parameters in isotropic linear elasticity from noisy full-field measurements

International Nuclear Information System (INIS)

Bal, Guillaume; Bellis, Cédric; Imperiale, Sébastien; Monard, François

2014-01-01

Within the framework of linear elasticity we assume the availability of internal full-field measurements of the continuum deformations of a non-homogeneous isotropic solid. The aim is the quantitative reconstruction of the associated moduli. A simple gradient system for the sought constitutive parameters is derived algebraically from the momentum equation, whose coefficients are expressed in terms of the measured displacement fields and their spatial derivatives. Direct integration of this system is discussed to finally demonstrate the inexpediency of such an approach when dealing with noisy data. Upon using polluted measurements, an alternative variational formulation is deployed to invert for the physical parameters. Analysis of this latter inversion procedure provides existence and uniqueness results while the reconstruction stability with respect to the measurements is investigated. As the inversion procedure requires differentiating the measurements twice, a numerical differentiation scheme based on an ad hoc regularization then allows an optimally stable reconstruction of the sought moduli. Numerical results are included to illustrate and assess the performance of the overall approach. (paper)
Elastic orthorhombic anisotropic parameter inversion: An analysis of parameterization

KAUST Repository

Oh, Juwon

2016-09-15

The resolution of a multiparameter full-waveform inversion (FWI) is highly influenced by the parameterization used in the inversion algorithm, as well as the data quality and the sensitivity of the data to the elastic parameters because the scattering patterns of the partial derivative wavefields (PDWs) vary with parameterization. For this reason, it is important to identify an optimal parameterization for elastic orthorhombic FWI by analyzing the radiation patterns of the PDWs for many reasonable model parameterizations. We have promoted a parameterization that allows for the separation of the anisotropic properties in the radiation patterns. The central parameter of this parameterization is the horizontal P-wave velocity, with an isotropic scattering potential, influencing the data at all scales and directions. This parameterization decouples the influence of the scattering potential given by the P-wave velocity perturbation fromthe polar changes described by two dimensionless parameter perturbations and from the azimuthal variation given by three additional dimensionless parameters perturbations. In addition, the scattering potentials of the P-wave velocity perturbation are also decoupled from the elastic influences given by one S-wave velocity and two additional dimensionless parameter perturbations. The vertical S-wave velocity is chosen with the best resolution obtained from S-wave reflections and converted waves, little influence on P-waves in conventional surface seismic acquisition. The influence of the density on observed data can be absorbed by one anisotropic parameter that has a similar radiation pattern. The additional seven dimensionless parameters describe the polar and azimuth variations in the P- and S-waves that we may acquire, with some of the parameters having distinct influences on the recorded data on the earth\\'s surface. These characteristics of the new parameterization offer the potential for a multistage inversion from high symmetry
Elastic orthorhombic anisotropic parameter inversion: An analysis of parameterization

KAUST Repository

Oh, Juwon; Alkhalifah, Tariq Ali

2016-01-01

The resolution of a multiparameter full-waveform inversion (FWI) is highly influenced by the parameterization used in the inversion algorithm, as well as the data quality and the sensitivity of the data to the elastic parameters because the scattering patterns of the partial derivative wavefields (PDWs) vary with parameterization. For this reason, it is important to identify an optimal parameterization for elastic orthorhombic FWI by analyzing the radiation patterns of the PDWs for many reasonable model parameterizations. We have promoted a parameterization that allows for the separation of the anisotropic properties in the radiation patterns. The central parameter of this parameterization is the horizontal P-wave velocity, with an isotropic scattering potential, influencing the data at all scales and directions. This parameterization decouples the influence of the scattering potential given by the P-wave velocity perturbation fromthe polar changes described by two dimensionless parameter perturbations and from the azimuthal variation given by three additional dimensionless parameters perturbations. In addition, the scattering potentials of the P-wave velocity perturbation are also decoupled from the elastic influences given by one S-wave velocity and two additional dimensionless parameter perturbations. The vertical S-wave velocity is chosen with the best resolution obtained from S-wave reflections and converted waves, little influence on P-waves in conventional surface seismic acquisition. The influence of the density on observed data can be absorbed by one anisotropic parameter that has a similar radiation pattern. The additional seven dimensionless parameters describe the polar and azimuth variations in the P- and S-waves that we may acquire, with some of the parameters having distinct influences on the recorded data on the earth's surface. These characteristics of the new parameterization offer the potential for a multistage inversion from high symmetry
Materials analysis using x-ray linear attenuation coefficient measurements at four photon energies

International Nuclear Information System (INIS)

Midgley, S M

2005-01-01

The analytical properties of an accurate parameterization scheme for the x-ray linear attenuation coefficient are examined. The parameterization utilizes an additive combination of N compositional- and energy-dependent coefficients. The former were derived from a parameterization of elemental cross-sections using a polynomial in atomic number. The compositional-dependent coefficients are referred to as the mixture parameters, representing the electron density and higher order statistical moments describing elemental distribution. Additivity is an important property of the parameterization, allowing measured x-ray linear attenuation coefficients to be written as linear simultaneous equations, and then solved for the unknown coefficients. The energy-dependent coefficients can be determined by calibration from measurements with materials of known composition. The inverse problem may be utilized for materials analysis, whereby the simultaneous equations represent multi-energy linear attenuation coefficient measurements, and are solved for the mixture parameters. For in vivo studies, the choice of measurement energies is restricted to the diagnostic region (approximately 20 keV to 150 keV), where the parameterization requires N ≥ 4 energies. We identify a mathematical pathology that must be overcome in order to solve the inverse problem in this energy regime. An iterative inversion strategy is presented for materials analysis using four or more measurements, and then tested against real data obtained at energies 32 keV to 66 keV. The results demonstrate that it is possible to recover the electron density to within ±4% and fourth mixture parameter. It is also a key finding that the second and third mixture parameters cannot be recovered, as they are of minor importance in the parameterization at diagnostic x-ray energies
Analysis of the multi-component pseudo-pure-mode qP-wave inversion in vertical transverse isotropic (VTI) media

KAUST Repository

Djebbi, Ramzi

2014-08-05

Multi-parameter inversion in anisotropic media suffers from the inherent trade-off between the anisotropic parameters, even under the acoustic assumption. Multi-component data, often acquired nowadays in ocean bottom acquisition and land data, provide additional information capable of resolving anisotropic parameters under the acoustic approximation assumption. Based on Born scattering approximation, we develop formulas capable of characterizing the radiation patterns for the acoustic pseudo-pure mode P-waves. Though commonly reserved for the elastic fields, we use displacement fields to constrain the acoustic vertical transverse isotropic (VTI) representation of the medium. Using the asymptotic Green\\'s functions and a horizontal reflector we derive the radiation patterns for perturbations in the anisotropic media. The radiation pattern for the anellipticity parameter η is identically zero for the horizontal displacement. This allows us to dedicate this component to invert for velocity and δ. Computing the traveltime sensitivity kernels based on the unwrapped phase confirms the radiation patterns observations, and provide the model wavenumber behavior of the update.
Continuity and general perturbation of the Drazin inverse for closed linear operators

Directory of Open Access Journals (Sweden)

N. Castro González

2002-01-01

Full Text Available We study perturbations and continuity of the Drazin inverse of a closed linear operator A and obtain explicit error estimates in terms of the gap between closed operators and the gap between ranges and nullspaces of operators. The results are used to derive a theorem on the continuity of the Drazin inverse for closed operators and to describe the asymptotic behavior of operator semigroups.
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method

KAUST Repository

Desmal, Abdulla

2014-07-01

A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method

KAUST Repository

Desmal, Abdulla; Bagci, Hakan

2014-01-01

A contrast-source inversion scheme is proposed for microwave imaging of domains with sparse content. The scheme uses inexact Newton and linear shrinkage methods to account for the nonlinearity and ill-posedness of the electromagnetic inverse scattering problem, respectively. Thresholded shrinkage iterations are accelerated using a preconditioning technique. Additionally, during Newton iterations, the weight of the penalty term is reduced consistently with the quadratic convergence of the Newton method to increase accuracy and efficiency. Numerical results demonstrate the applicability of the proposed method.
Optimization for nonlinear inverse problem

International Nuclear Information System (INIS)

Boyadzhiev, G.; Brandmayr, E.; Pinat, T.; Panza, G.F.

2007-06-01

The nonlinear inversion of geophysical data in general does not yield a unique solution, but a single model, representing the investigated field, is preferred for an easy geological interpretation of the observations. The analyzed region is constituted by a number of sub-regions where the multi-valued nonlinear inversion is applied, which leads to a multi-valued solution. Therefore, combining the values of the solution in each sub-region, many acceptable models are obtained for the entire region and this complicates the geological interpretation of geophysical investigations. In this paper are presented new methodologies, capable to select one model, among all acceptable ones, that satisfies different criteria of smoothness in the explored space of solutions. In this work we focus on the non-linear inversion of surface waves dispersion curves, which gives structural models of shear-wave velocity versus depth, but the basic concepts have a general validity. (author)
Displacement Parameter Inversion for a Novel Electromagnetic Underground Displacement Sensor

Directory of Open Access Journals (Sweden)

Nanying Shentu

2014-05-01

Full Text Available Underground displacement monitoring is an effective method to explore deep into rock and soil masses for execution of subsurface displacement measurements. It is not only an important means of geological hazards prediction and forecasting, but also a forefront, hot and sophisticated subject in current geological disaster monitoring. In previous research, the authors had designed a novel electromagnetic underground horizontal displacement sensor (called the H-type sensor by combining basic electromagnetic induction principles with modern sensing techniques and established a mutual voltage measurement theoretical model called the Equation-based Equivalent Loop Approach (EELA. Based on that work, this paper presents an underground displacement inversion approach named “EELA forward modeling-approximate inversion method”. Combining the EELA forward simulation approach with the approximate optimization inversion theory, it can deduce the underground horizontal displacement through parameter inversion of the H-type sensor. Comprehensive and comparative studies have been conducted between the experimentally measured and theoretically inversed values of horizontal displacement under counterpart conditions. The results show when the measured horizontal displacements are in the 0–100 mm range, the horizontal displacement inversion discrepancy is generally tested to be less than 3 mm under varied tilt angles and initial axial distances conditions, which indicates that our proposed parameter inversion method can predict underground horizontal displacement measurements effectively and robustly for the H-type sensor and the technique is applicable for practical geo-engineering applications.
Multi-Body Ski Jumper Model with Nonlinear Dynamic Inversion Muscle Control for Trajectory Optimization

Directory of Open Access Journals (Sweden)

Patrick Piprek

2018-02-01

Full Text Available This paper presents an approach to model a ski jumper as a multi-body system for an optimal control application. The modeling is based on the constrained Newton-Euler-Equations. Within this paper the complete multi-body modeling methodology as well as the musculoskeletal modeling is considered. For the musculoskeletal modeling and its incorporation in the optimization model, we choose a nonlinear dynamic inversion control approach. This approach uses the muscle models as nonlinear reference models and links them to the ski jumper movement by a control law. This strategy yields a linearized input-output behavior, which makes the optimal control problem easier to solve. The resulting model of the ski jumper can then be used for trajectory optimization whose results are compared to literature jumps. Ultimately, this enables the jumper to get a very detailed feedback of the flight. To achieve the maximal jump length, exact positioning of his body with respect to the air can be displayed.
Model-Checking of Linear-Time Properties in Multi-Valued Systems

OpenAIRE

Li, Yongming; Droste, Manfred; Lei, Lihui

2012-01-01

In this paper, we study model-checking of linear-time properties in multi-valued systems. Safety property, invariant property, liveness property, persistence and dual-persistence properties in multi-valued logic systems are introduced. Some algorithms related to the above multi-valued linear-time properties are discussed. The verification of multi-valued regular safety properties and multi-valued $\\omega$-regular properties using lattice-valued automata are thoroughly studied. Since the law o...
A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

Science.gov (United States)

Marzban, Hamid Reza

2018-05-01

In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.
EXAFS Phase Retrieval Solution Tracking for Complex Multi-Component System: Synthesized Topological Inverse Computation

International Nuclear Information System (INIS)

Lee, Jay Min; Yang, Dong-Seok; Bunker, Grant B

2013-01-01

Using the FEFF kernel A(k,r), we describe the inverse computation from χ(k)-data to g(r)-solution in terms of a singularity regularization method based on complete Bayesian statistics process. In this work, we topologically decompose the system-matched invariant projection operators into two distinct types, (A + AA + A) and (AA + AA + ), and achieved Synthesized Topological Inversion Computation (STIC), by employing a 12-operator-closed-loop emulator of the symplectic transformation. This leads to a numerically self-consistent solution as the optimal near-singular regularization parameters are sought, dramatically suppressing instability problems connected with finite precision arithmetic in ill-posed systems. By statistically correlating a pair of measured data, it was feasible to compute an optimal EXAFS phase retrieval solution expressed in terms of the complex-valued χ(k), and this approach was successfully used to determine the optimal g(r) for a complex multi-component system.

Isotropic-resolution linear-array-based photoacoustic computed tomography through inverse Radon transform

Science.gov (United States)

Li, Guo; Xia, Jun; Li, Lei; Wang, Lidai; Wang, Lihong V.

2015-03-01

Linear transducer arrays are readily available for ultrasonic detection in photoacoustic computed tomography. They offer low cost, hand-held convenience, and conventional ultrasonic imaging. However, the elevational resolution of linear transducer arrays, which is usually determined by the weak focus of the cylindrical acoustic lens, is about one order of magnitude worse than the in-plane axial and lateral spatial resolutions. Therefore, conventional linear scanning along the elevational direction cannot provide high-quality three-dimensional photoacoustic images due to the anisotropic spatial resolutions. Here we propose an innovative method to achieve isotropic resolutions for three-dimensional photoacoustic images through combined linear and rotational scanning. In each scan step, we first elevationally scan the linear transducer array, and then rotate the linear transducer array along its center in small steps, and scan again until 180 degrees have been covered. To reconstruct isotropic three-dimensional images from the multiple-directional scanning dataset, we use the standard inverse Radon transform originating from X-ray CT. We acquired a three-dimensional microsphere phantom image through the inverse Radon transform method and compared it with a single-elevational-scan three-dimensional image. The comparison shows that our method improves the elevational resolution by up to one order of magnitude, approaching the in-plane lateral-direction resolution. In vivo rat images were also acquired.
MINIMUM ENTROPY DECONVOLUTION OF ONE-AND MULTI-DIMENSIONAL NON-GAUSSIAN LINEAR RANDOM PROCESSES

Institute of Scientific and Technical Information of China (English)

程乾生

1990-01-01

The minimum entropy deconvolution is considered as one of the methods for decomposing non-Gaussian linear processes. The concept of peakedness of a system response sequence is presented and its properties are studied. With the aid of the peakedness, the convergence theory of the minimum entropy deconvolution is established. The problem of the minimum entropy deconvolution of multi-dimensional non-Gaussian linear random processes is first investigated and the corresponding theory is given. In addition, the relation between the minimum entropy deconvolution and parameter method is discussed.
On The Structure of The Inverse of a Linear Constant Multivariable ...

African Journals Online (AJOL)

On The Structure of The Inverse of a Linear Constant Multivariable System. ... It is shown that the use of this representation has certain advantages in the design of multivariable feedback systems. typical examples were considered to indicate the corresponding application. Keywords: Stability Functions, multivariable ...
The improved ET calculation for semiarid region based on an innovative aerodynamic roughness inversion method using multi-source remote sensing data

International Nuclear Information System (INIS)

Xing, Qiang; Wu, Bingfang; Zhu, Weiwei

2014-01-01

The aerodynamic roughness is one of the major parameters in describing the turbulent exchange process between terrestrial and atmosphere. Remote Sensing is recognized as an effective way to inverse this parameter at the regional scale. However, in the long time the inversion method is either dependent on the lookup table for different land covers or the Normalized Difference Vegetation Index (NDVI) factor only, which plays a very limited role in describing the spatial heterogeneity of this parameter and the evapotranspiration (ET) for different land covers. In fact, the aerodynamic roughness is influenced by different factors at the same time, including the roughness unit for hard surfaces, the vegetation dynamic growth and the undulating terrain. Therefore, this paper aims at developing an innovative aerodynamic roughness inversion method based on multi-source remote sensing data in a semiarid region, within the upper and middle reaches of Heihe River Basin. The radar backscattering coefficient was used to inverse the micro-relief of the hard surface. The NDVI was utilized to reflect the dynamic change of vegetated surface. Finally, the slope extracted from SRTM DEM (Shuttle Radar Topography Mission Digital Elevation Model) was used to correct terrain influence. The inversed aerodynamic roughness was imported into ETWatch system to validate the availability. The inversed and tested results show it plays a significant role in improving the spatial heterogeneity of the aerodynamic roughness and related ET for the experimental site
In-Pile Instrumentation Multi- Parameter System Utilizing Photonic Fibers and Nanovision

Energy Technology Data Exchange (ETDEWEB)

Burgett, Eric [Idaho State Univ., Pocatello, ID (United States)

2015-10-13

An advanced in-pile multi-parameter reactor monitoring system is being proposed in this funding opportunity. The proposed effort brings cutting edge, high fidelity optical measurement systems into the reactor environment in an unprecedented fashion, including in-core, in-cladding and in-fuel pellet itself. Unlike instrumented leads, the proposed system provides a unique solution to a multi-parameter monitoring need in core while being minimally intrusive in the reactor core. Detector designs proposed herein can monitor fuel compression and expansion in both the radial and axial dimensions as well as monitor linear power profiles and fission rates during the operation of the reactor. In addition to pressure, stress, strain, compression, neutron flux, neutron spectra, and temperature can be observed inside the fuel bundle and fuel rod using the proposed system. The proposed research aims at developing radiation-hard, harsh-environment multi-parameter systems for insertion into the reactor environment. The proposed research holds the potential to drastically increase the fidelity and precision of in-core instrumentation with little or no impact in the neutron economy in the reactor environment while providing a measurement system capable of operation for entire operating cycles.
In-Pile Instrumentation Multi- Parameter System Utilizing Photonic Fibers and Nanovision

International Nuclear Information System (INIS)

Burgett, Eric

2015-01-01

An advanced in-pile multi-parameter reactor monitoring system is being proposed in this funding opportunity. The proposed effort brings cutting edge, high fidelity optical measurement systems into the reactor environment in an unprecedented fashion, including in-core, in-cladding and in-fuel pellet itself. Unlike instrumented leads, the proposed system provides a unique solution to a multi-parameter monitoring need in core while being minimally intrusive in the reactor core. Detector designs proposed herein can monitor fuel compression and expansion in both the radial and axial dimensions as well as monitor linear power profiles and fission rates during the operation of the reactor. In addition to pressure, stress, strain, compression, neutron flux, neutron spectra, and temperature can be observed inside the fuel bundle and fuel rod using the proposed system. The proposed research aims at developing radiation-hard, harsh-environment multi-parameter systems for insertion into the reactor environment. The proposed research holds the potential to drastically increase the fidelity and precision of in-core instrumentation with little or no impact in the neutron economy in the reactor environment while providing a measurement system capable of operation for entire operating cycles.
Identification of Constitutive Parameters Using Inverse Strategy Coupled to an ANN Model

International Nuclear Information System (INIS)

Aguir, H.; Chamekh, A.; BelHadjSalah, H.; Hambli, R.

2007-01-01

This paper deals with the identification of material parameters using an inverse strategy. In the classical methods, the inverse technique is generally coupled with a finite element code which leads to a long computing time. In this work an inverse strategy coupled with an ANN procedure is proposed. This method has the advantage of being faster than the classical one. To validate this approach an experimental plane tensile and bulge tests are used in order to identify material behavior. The ANN model is trained from finite element simulations of the two tests. In order to reduce the gap between the experimental responses and the numerical ones, the proposed method is coupled with an optimization procedure to identify material parameters for the AISI304. The identified material parameters are the hardening curve and the anisotropic coefficients
Study on hybrid multi-objective optimization algorithm for inverse treatment planning of radiation therapy

International Nuclear Information System (INIS)

Li Guoli; Song Gang; Wu Yican

2007-01-01

Inverse treatment planning for radiation therapy is a multi-objective optimization process. The hybrid multi-objective optimization algorithm is studied by combining the simulated annealing(SA) and genetic algorithm(GA). Test functions are used to analyze the efficiency of algorithms. The hybrid multi-objective optimization SA algorithm, which displacement is based on the evolutionary strategy of GA: crossover and mutation, is implemented in inverse planning of external beam radiation therapy by using two kinds of objective functions, namely the average dose distribution based and the hybrid dose-volume constraints based objective functions. The test calculations demonstrate that excellent converge speed can be achieved. (authors)
Physics-based Inverse Problem to Deduce Marine Atmospheric Boundary Layer Parameters

Science.gov (United States)

2017-03-07

knowledge and capabilities in the use and development of inverse problem techniques to deduce atmospheric parameters. WORK COMPLETED The research completed...please find the Final Technical Report with SF 298 for Dr. Erin E. Hackett’s ONR grant entitled Physics -based Inverse Problem to Deduce Marine...From- To) 07/03/2017 Final Technica l Dec 2012- Dec 2016 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Physics -based Inverse Problem to Deduce Marine
The formaldehyde budget as seen by a global-scale multi-constraint and multi-species inversion system

Directory of Open Access Journals (Sweden)

A. Fortems-Cheiney

2012-08-01

Full Text Available For the first time, carbon monoxide (CO and formaldehyde (HCHO satellite retrievals are used together with methane (CH₄ and methyl choloroform (CH₃CCl₃ or MCF surface measurements in an advanced inversion system. The CO and HCHO are respectively from the MOPITT and OMI instruments. The multi-species and multi-satellite dataset inversion is done for the 2005–2010 period. The robustness of our results is evaluated by comparing our posterior-modeled concentrations with several sets of independent measurements of atmospheric mixing ratios. The inversion leads to significant changes from the prior to the posterior, in terms of magnitude and seasonality of the CO and CH₄ surface fluxes and of the HCHO production by non-methane volatile organic compounds (NMVOC. The latter is significantly decreased, indicating an overestimation of the biogenic NMVOC emissions, such as isoprene, in the GEIA inventory. CO and CH₄ surface emissions are increased by the inversion, from 1037 to 1394 TgCO and from 489 to 529 TgCH₄ on average for the 2005–2010 period. CH₄ emissions present significant interannual variability and a joint CO-CH₄ fluxes analysis reveals that tropical biomass burning probably played a role in the recent increase of atmospheric methane.
Analog fault diagnosis by inverse problem technique

KAUST Repository

Ahmed, Rania F.

2011-12-01

A novel algorithm for detecting soft faults in linear analog circuits based on the inverse problem concept is proposed. The proposed approach utilizes optimization techniques with the aid of sensitivity analysis. The main contribution of this work is to apply the inverse problem technique to estimate the actual parameter values of the tested circuit and so, to detect and diagnose single fault in analog circuits. The validation of the algorithm is illustrated through applying it to Sallen-Key second order band pass filter and the results show that the detecting percentage efficiency was 100% and also, the maximum error percentage of estimating the parameter values is 0.7%. This technique can be applied to any other linear circuit and it also can be extended to be applied to non-linear circuits. © 2011 IEEE.
Limits to Nonlinear Inversion

DEFF Research Database (Denmark)

Mosegaard, Klaus

2012-01-01

For non-linear inverse problems, the mathematical structure of the mapping from model parameters to data is usually unknown or partly unknown. Absence of information about the mathematical structure of this function prevents us from presenting an analytical solution, so our solution depends on our......-heuristics are inefficient for large-scale, non-linear inverse problems, and that the 'no-free-lunch' theorem holds. We discuss typical objections to the relevance of this theorem. A consequence of the no-free-lunch theorem is that algorithms adapted to the mathematical structure of the problem perform more efficiently than...... pure meta-heuristics. We study problem-adapted inversion algorithms that exploit the knowledge of the smoothness of the misfit function of the problem. Optimal sampling strategies exist for such problems, but many of these problems remain hard. © 2012 Springer-Verlag....
Multi-resolution inversion algorithm for the attenuated radon transform

KAUST Repository

Barbano, Paolo Emilio

2011-09-01

We present a FAST implementation of the Inverse Attenuated Radon Transform which incorporates accurate collimator response, as well as artifact rejection due to statistical noise and data corruption. This new reconstruction procedure is performed by combining a memory-efficient implementation of the analytical inversion formula (AIF [1], [2]) with a wavelet-based version of a recently discovered regularization technique [3]. The paper introduces all the main aspects of the new AIF, as well numerical experiments on real and simulated data. Those display a substantial improvement in reconstruction quality when compared to linear or iterative algorithms. © 2011 IEEE.
Multidisciplinary Inverse Reliability Analysis Based on Collaborative Optimization with Combination of Linear Approximations

Directory of Open Access Journals (Sweden)

Xin-Jia Meng

2015-01-01

Full Text Available Multidisciplinary reliability is an important part of the reliability-based multidisciplinary design optimization (RBMDO. However, it usually has a considerable amount of calculation. The purpose of this paper is to improve the computational efficiency of multidisciplinary inverse reliability analysis. A multidisciplinary inverse reliability analysis method based on collaborative optimization with combination of linear approximations (CLA-CO is proposed in this paper. In the proposed method, the multidisciplinary reliability assessment problem is first transformed into a problem of most probable failure point (MPP search of inverse reliability, and then the process of searching for MPP of multidisciplinary inverse reliability is performed based on the framework of CLA-CO. This method improves the MPP searching process through two elements. One is treating the discipline analyses as the equality constraints in the subsystem optimization, and the other is using linear approximations corresponding to subsystem responses as the replacement of the consistency equality constraint in system optimization. With these two elements, the proposed method realizes the parallel analysis of each discipline, and it also has a higher computational efficiency. Additionally, there are no difficulties in applying the proposed method to problems with nonnormal distribution variables. One mathematical test problem and an electronic packaging problem are used to demonstrate the effectiveness of the proposed method.
MULTI-LINE STOKES INVERSION FOR PROMINENCE MAGNETIC-FIELD DIAGNOSTICS

International Nuclear Information System (INIS)

Casini, R.; Lopez Ariste, A.; Paletou, F.; Leger, L.

2009-01-01

We present test results on the simultaneous inversion of the Stokes profiles of the He I lines at 587.6 nm (D 3 ) and 1083.0 nm in prominences (90 deg. scattering). We created data sets of synthetic Stokes profiles for the case of quiescent prominences (B -3 of the peak intensity for the polarimetric sensitivity of the simulated observations. In this work, we focus on the error analysis for the inference of the magnetic field vector, under the usual assumption that the prominence can be assimilated to a slab of finite optical thickness with uniform magnetic and thermodynamic properties. We find that the simultaneous inversion of the two lines significantly reduces the errors on the inference of the magnetic field vector, with respect to the case of single-line inversion. These results provide a solid justification for current and future instrumental efforts with multi-line capabilities for the observations of solar prominences and filaments.
Complexity analysis of accelerated MCMC methods for Bayesian inversion

International Nuclear Information System (INIS)

Hoang, Viet Ha; Schwab, Christoph; Stuart, Andrew M

2013-01-01

The Bayesian approach to inverse problems, in which the posterior probability distribution on an unknown field is sampled for the purposes of computing posterior expectations of quantities of interest, is starting to become computationally feasible for partial differential equation (PDE) inverse problems. Balancing the sources of error arising from finite-dimensional approximation of the unknown field, the PDE forward solution map and the sampling of the probability space under the posterior distribution are essential for the design of efficient computational Bayesian methods for PDE inverse problems. We study Bayesian inversion for a model elliptic PDE with an unknown diffusion coefficient. We provide complexity analyses of several Markov chain Monte Carlo (MCMC) methods for the efficient numerical evaluation of expectations under the Bayesian posterior distribution, given data δ. Particular attention is given to bounds on the overall work required to achieve a prescribed error level ε. Specifically, we first bound the computational complexity of ‘plain’ MCMC, based on combining MCMC sampling with linear complexity multi-level solvers for elliptic PDE. Our (new) work versus accuracy bounds show that the complexity of this approach can be quite prohibitive. Two strategies for reducing the computational complexity are then proposed and analyzed: first, a sparse, parametric and deterministic generalized polynomial chaos (gpc) ‘surrogate’ representation of the forward response map of the PDE over the entire parameter space, and, second, a novel multi-level Markov chain Monte Carlo strategy which utilizes sampling from a multi-level discretization of the posterior and the forward PDE. For both of these strategies, we derive asymptotic bounds on work versus accuracy, and hence asymptotic bounds on the computational complexity of the algorithms. In particular, we provide sufficient conditions on the regularity of the unknown coefficients of the PDE and on the
An improved fast and elitist multi-objective genetic algorithm-ANSGA-II for multi-objective optimization of inverse radiotherapy treatment planning

International Nuclear Information System (INIS)

Cao Ruifen; Li Guoli; Song Gang; Zhao Pan; Lin Hui; Wu Aidong; Huang Chenyu; Wu Yican

2007-01-01

Objective: To provide a fast and effective multi-objective optimization algorithm for inverse radiotherapy treatment planning system. Methods: Non-dominated Sorting Genetic Algorithm-NSGA-II is a representative of multi-objective evolutionary optimization algorithms and excels the others. The paper produces ANSGA-II that makes use of advantage of NSGA-II, and uses adaptive crossover and mutation to improve its flexibility; according the character of inverse radiotherapy treatment planning, the paper uses the pre-known knowledge to generate individuals of every generation in the course of optimization, which enhances the convergent speed and improves efficiency. Results: The example of optimizing average dose of a sheet of CT, including PTV, OAR, NT, proves the algorithm could find satisfied solutions in several minutes. Conclusions: The algorithm could provide clinic inverse radiotherapy treatment planning system with selection of optimization algorithms. (authors)
Approximation Of Multi-Valued Inverse Functions Using Clustering And Sugeno Fuzzy Inference

Science.gov (United States)

Walden, Maria A.; Bikdash, Marwan; Homaifar, Abdollah

1998-01-01

Finding the inverse of a continuous function can be challenging and computationally expensive when the inverse function is multi-valued. Difficulties may be compounded when the function itself is difficult to evaluate. We show that we can use fuzzy-logic approximators such as Sugeno inference systems to compute the inverse on-line. To do so, a fuzzy clustering algorithm can be used in conjunction with a discriminating function to split the function data into branches for the different values of the forward function. These data sets are then fed into a recursive least-squares learning algorithm that finds the proper coefficients of the Sugeno approximators; each Sugeno approximator finds one value of the inverse function. Discussions about the accuracy of the approximation will be included.
On the observability of turbulent transport rates by Argo: supporting evidence from an inversion experiment

Directory of Open Access Journals (Sweden)

G. Forget

2015-10-01

Full Text Available Although estimation of turbulent transport parameters using inverse methods is not new, there is little evaluation of the method in the literature. Here, it is shown that extended observation of the broad-scale hydrography by Argo provides a path to improved estimates of regional turbulent transport rates. Results from a 20-year ocean state estimate produced with the ECCO v4 (Estimating the Circulation and Climate of the Ocean, version 4 non-linear inverse modeling framework provide supporting evidence. Turbulent transport parameter maps are estimated under the constraints of fitting the extensive collection of Argo profiles collected through 2011. The adjusted parameters dramatically reduce misfits to in situ profiles as compared with earlier ECCO solutions. They also yield a clear reduction in the model drift away from observations over multi-century-long simulations, both for assimilated variables (temperature and salinity and independent variables (biogeochemical tracers. Despite the minimal constraints imposed specifically on the estimated parameters, their geography is physically plausible and exhibits close connections with the upper-ocean stratification as observed by Argo. The estimated parameter adjustments furthermore have first-order impacts on upper-ocean stratification and mixed layer depths over 20 years. These results identify the constraint of fitting Argo profiles as an effective observational basis for regional turbulent transport rate inversions. Uncertainties and further improvements of the method are discussed.
Realization of multi-parameter and multi-state in fault tree computer-aided building software

International Nuclear Information System (INIS)

Guo Xiaoli; Tong Jiejuan; Xue Dazhi

2004-01-01

More than one parameter and more than one failed state of a parameter are often involved in building fault tree, so it is necessary for fault tree computer-aided building software to deal with multi-parameter and multi-state. Fault Tree Expert System (FTES) has the target of aiding the FT-building work of hydraulic systems. This paper expatiates on how to realize multi-parameter and multi-state in FTES with focus on Knowledge Base and Illation Engine. (author)

Sliding mode control of photoelectric tracking platform based on the inverse system method

Directory of Open Access Journals (Sweden)

Yao Zong Chen

2016-01-01

Full Text Available In order to improve the photoelectric tracking platform tracking performance, an integral sliding mode control strategy based on inverse system decoupling method is proposed. The electromechanical dynamic model is established based on multi-body system theory and Newton-Euler method. The coupled multi-input multi-output (MIMO nonlinear system is transformed into two pseudo-linear single-input single-output (SISO subsystems based on the inverse system method. An integral sliding mode control scheme is designed for the decoupled pseudo-linear system. In order to eliminate system chattering phenomenon caused by traditional sign function in sliding-mode controller, the sign function is replaced by the Sigmoid function. Simulation results show that the proposed decoupling method and the control strategy can restrain the influences of internal coupling and disturbance effectively, and has better robustness and higher tracking accuracy.
Robust control and linear parameter varying approaches application to vehicle dynamics

CERN Document Server

Gaspar, Peter; Bokor, József

2013-01-01

Vehicles are complex systems (non-linear, multi-variable) where the abundance of embedded controllers should ensure better security. This book aims at emphasizing the interest and potential of Linear Parameter Varying methods within the framework of vehicle dynamics, e.g. · proposed control-oriented model, complex enough to handle some system non linearities but still simple for control or observer design, · take into account the adaptability of the vehicle's response to driving situations, to the driver request and/or to the road sollicitations, · manage interactions between various actuators to optimize the dynamic behavior of vehicles. This book results from the 32th International Summer School in Automatic that held in Grenoble, France, in September 2011, where recent methods (based on robust control and LPV technics), then applied to the control of vehicle dynamics, have been presented. After some theoretical background and a view on so...
Inverse scattering solution of non-linear evolution equations in one space dimension: an introduction

International Nuclear Information System (INIS)

Alvarez-Estrada, R.F.

1979-01-01

A comprehensive review of the inverse scattering solution of certain non-linear evolution equations of physical interest in one space dimension is presented. We explain in some detail the interrelated techniques which allow to linearize exactly the following equations: (1) the Korteweg and de Vries equation; (2) the non-linear Schrodinger equation; (3) the modified Korteweg and de Vries equation; (4) the Sine-Gordon equation. We concentrate in discussing the pairs of linear operators which accomplish such an exact linearization and the solution of the associated initial value problem. The application of the method to other non-linear evolution equations is reviewed very briefly
Introduction of a priori information in the elastic linearized inversion of seismic data before stacking; Introduction d'informations a priori dans l'inversion linearisee elastique de donnees sismiques de surface avant sommation

Energy Technology Data Exchange (ETDEWEB)

Tonellot, Th.L.

2000-03-24

In this thesis, we propose a method which takes into account a priori information (geological, diagraphic and stratigraphic knowledge) in linearized pre-stack seismic data inversion. The approach is based on a formalism in which the a priori information is incorporated in an a priori model of elastic parameters - density, P and S impedances - and a model covariance operator which describes the uncertainties in the model. The first part of the thesis is dedicated to the study of this covariance operator and to the norm associated to its inverse. We have generalized the exponential covariance operator in order to describe the uncertainties in the a priori model elastic parameters and their correlations at each location. We give the analytical expression of the covariance operator inverse in 1-D, 2-D, and 3-D, and we discretized the associated norm with a finite element method. The second part is dedicated to synthetic and real examples. In a preliminary step, we have developed a pre-stack data well calibration method which allows the estimation of the source signal. The impact of different a priori information is then demonstrated on synthetic and real data. (author)
Stabilizing inverse problems by internal data. II: non-local internal data and generic linearized uniqueness

KAUST Repository

Kuchment, Peter

2015-05-10

© 2015, Springer Basel. In the previous paper (Kuchment and Steinhauer in Inverse Probl 28(8):084007, 2012), the authors introduced a simple procedure that allows one to detect whether and explain why internal information arising in several novel coupled physics (hybrid) imaging modalities could turn extremely unstable techniques, such as optical tomography or electrical impedance tomography, into stable, good-resolution procedures. It was shown that in all cases of interest, the Fréchet derivative of the forward mapping is a pseudo-differential operator with an explicitly computable principal symbol. If one can set up the imaging procedure in such a way that the symbol is elliptic, this would indicate that the problem was stabilized. In the cases when the symbol is not elliptic, the technique suggests how to change the procedure (e.g., by adding extra measurements) to achieve ellipticity. In this article, we consider the situation arising in acousto-optical tomography (also called ultrasound modulated optical tomography), where the internal data available involves the Green’s function, and thus depends globally on the unknown parameter(s) of the equation and its solution. It is shown that the technique of (Kuchment and Steinhauer in Inverse Probl 28(8):084007, 2012) can be successfully adopted to this situation as well. A significant part of the article is devoted to results on generic uniqueness for the linearized problem in a variety of situations, including those arising in acousto-electric and quantitative photoacoustic tomography.
Multi-GPU parallel algorithm design and analysis for improved inversion of probability tomography with gravity gradiometry data

Science.gov (United States)

Hou, Zhenlong; Huang, Danian

2017-09-01

In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.
Inversion for atmosphere duct parameters using real radar sea clutter

International Nuclear Information System (INIS)

Sheng Zheng; Fang Han-Xian

2012-01-01

This paper addresses the problem of estimating the lower atmospheric refractivity (M profile) under nonstandard propagation conditions frequently encountered in low altitude maritime radar applications. The vertical structure of the refractive environment is modeled using five parameters and the horizontal structure is modeled using five parameters. The refractivity model is implemented with and without a priori constraint on the duct strength as might be derived from soundings or numerical weather-prediction models. An electromagnetic propagation model maps the refractivity structure into a replica field. Replica fields are compared with the observed clutter using a squared-error objective function. A global search for the 10 environmental parameters is performed using genetic algorithms. The inversion algorithm is implemented on the basis of S-band radar sea-clutter data from Wallops Island, Virginia (SPANDAR). Reference data are from range-dependent refractivity profiles obtained with a helicopter. The inversion is assessed (i) by comparing the propagation predicted from the radar-inferred refractivity profiles with that from the helicopter profiles, (ii) by comparing the refractivity parameters from the helicopter soundings with those estimated. This technique could provide near-real-time estimation of ducting effects. (geophysics, astronomy, and astrophysics)
Multi-source waveform inversion of marine streamer data using the normalized wavefield

KAUST Repository

Choi, Yun Seok; Alkhalifah, Tariq Ali

2012-01-01

Even though the encoded multi-source approach dramatically reduces the computational cost of waveform inversion, it is generally not applicable to marine streamer data. This is because the simultaneous-sources modeled data cannot be muted to comply
Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G.

1993-11-01

The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.
Multidimensional inversion

International Nuclear Information System (INIS)

Desesquelles, P.

1997-01-01

Computer Monte Carlo simulations occupy an increasingly important place between theory and experiment. This paper introduces a global protocol for the comparison of model simulations with experimental results. The correlated distributions of the model parameters are determined using an original recursive inversion procedure. Multivariate analysis techniques are used in order to optimally synthesize the experimental information with a minimum number of variables. This protocol is relevant in all fields if physics dealing with event generators and multi-parametric experiments. (authors)
Soil moisture estimation using multi linear regression with terraSAR-X data

Directory of Open Access Journals (Sweden)

G. García

2016-06-01

Full Text Available The first five centimeters of soil form an interface where the main heat fluxes exchanges between the land surface and the atmosphere occur. Besides ground measurements, remote sensing has proven to be an excellent tool for the monitoring of spatial and temporal distributed data of the most relevant Earth surface parameters including soil’s parameters. Indeed, active microwave sensors (Synthetic Aperture Radar - SAR offer the opportunity to monitor soil moisture (HS at global, regional and local scales by monitoring involved processes. Several inversion algorithms, that derive geophysical information as HS from SAR data, were developed. Many of them use electromagnetic models for simulating the backscattering coefficient and are based on statistical techniques, such as neural networks, inversion methods and regression models. Recent studies have shown that simple multiple regression techniques yield satisfactory results. The involved geophysical variables in these methodologies are descriptive of the soil structure, microwave characteristics and land use. Therefore, in this paper we aim at developing a multiple linear regression model to estimate HS on flat agricultural regions using TerraSAR-X satellite data and data from a ground weather station. The results show that the backscatter, the precipitation and the relative humidity are the explanatory variables of HS. The results obtained presented a RMSE of 5.4 and a R2 of about 0.6
Point source reconstruction principle of linear inverse problems

International Nuclear Information System (INIS)

Terazono, Yasushi; Matani, Ayumu; Fujimaki, Norio; Murata, Tsutomu

2010-01-01

Exact point source reconstruction for underdetermined linear inverse problems with a block-wise structure was studied. In a block-wise problem, elements of a source vector are partitioned into blocks. Accordingly, a leadfield matrix, which represents the forward observation process, is also partitioned into blocks. A point source is a source having only one nonzero block. An example of such a problem is current distribution estimation in electroencephalography and magnetoencephalography, where a source vector represents a vector field and a point source represents a single current dipole. In this study, the block-wise norm, a block-wise extension of the l p -norm, was defined as the family of cost functions of the inverse method. The main result is that a set of three conditions was found to be necessary and sufficient for block-wise norm minimization to ensure exact point source reconstruction for any leadfield matrix that admit such reconstruction. The block-wise norm that satisfies the conditions is the sum of the cost of all the observations of source blocks, or in other words, the block-wisely extended leadfield-weighted l 1 -norm. Additional results are that minimization of such a norm always provides block-wisely sparse solutions and that its solutions form cones in source space
Application of separable parameter space techniques to multi-tracer PET compartment modeling

International Nuclear Information System (INIS)

Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J

2016-01-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg–Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models. (paper)
H-Shaped Multiple Linear Motor Drive Platform Control System Design Based on an Inverse System Method

Directory of Open Access Journals (Sweden)

Caiyan Qin

2017-12-01

Full Text Available Due to its simple mechanical structure and high motion stability, the H-shaped platform has been increasingly widely used in precision measuring, numerical control machining and semiconductor packaging equipment, etc. The H-shaped platform is normally driven by multiple (three permanent magnet synchronous linear motors. The main challenges for H-shaped platform-control include synchronous control between the two linear motors in the Y direction as well as total positioning error of the platform mover, a combination of position deviation in X and Y directions. To deal with the above challenges, this paper proposes a control strategy based on the inverse system method through state feedback and dynamic decoupling of the thrust force. First, mechanical dynamics equations have been deduced through the analysis of system coupling based on the platform structure. Second, the mathematical model of the linear motors and the relevant coordinate transformation between dq-axis currents and ABC-phase currents are analyzed. Third, after the main concept of inverse system method being explained, the inverse system model of the platform control system has been designed after defining relevant system variables. Inverse system model compensates the original nonlinear coupled system into pseudo-linear decoupled linear system, for which typical linear control methods, like PID, can be adopted to control the system. The simulation model of the control system is built in MATLAB/Simulink and the simulation result shows that the designed control system has both small synchronous deviation and small total trajectory tracking error. Furthermore, the control program has been run on NI controller for both fixed-loop-time and free-loop-time modes, and the test result shows that the average loop computation time needed is rather small, which makes it suitable for real industrial applications. Overall, it proves that the proposed new control strategy can be used in
A Joint Method of Envelope Inversion Combined with Hybrid-domain Full Waveform Inversion

Science.gov (United States)

CUI, C.; Hou, W.

2017-12-01

Full waveform inversion (FWI) aims to construct high-precision subsurface models by fully using the information in seismic records, including amplitude, travel time, phase and so on. However, high non-linearity and the absence of low frequency information in seismic data lead to the well-known cycle skipping problem and make inversion easily fall into local minima. In addition, those 3D inversion methods that are based on acoustic approximation ignore the elastic effects in real seismic field, and make inversion harder. As a result, the accuracy of final inversion results highly relies on the quality of initial model. In order to improve stability and quality of inversion results, multi-scale inversion that reconstructs subsurface model from low to high frequency are applied. But, the absence of very low frequencies (time domain and inversion in the frequency domain. To accelerate the inversion, we adopt CPU/GPU heterogeneous computing techniques. There were two levels of parallelism. In the first level, the inversion tasks are decomposed and assigned to each computation node by shot number. In the second level, GPU multithreaded programming is used for the computation tasks in each node, including forward modeling, envelope extraction, DFT (discrete Fourier transform) calculation and gradients calculation. Numerical tests demonstrated that the combined envelope inversion + hybrid-domain FWI could obtain much faithful and accurate result than conventional hybrid-domain FWI. The CPU/GPU heterogeneous parallel computation could improve the performance speed.
Observer-based linear parameter varying H∞ tracking control for hypersonic vehicles

Directory of Open Access Journals (Sweden)

Yiqing Huang

2016-11-01

Full Text Available This article aims to develop observer-based linear parameter varying output feedback H∞ tracking controller for hypersonic vehicles. Due to the complexity of an original nonlinear model of the hypersonic vehicle dynamics, a slow–fast loop linear parameter varying polytopic model is introduced for system stability analysis and controller design. Then, a state observer is developed by linear parameter varying technique in order to estimate the unmeasured attitude angular for slow loop system. Also, based on the designed linear parameter varying state observer, a kind of attitude tracking controller is presented to reduce tracking errors for all bounded reference attitude angular inputs. The closed-loop linear parameter varying system is proved to be quadratically stable by Lypapunov function technique. Finally, simulation results show that the developed linear parameter varying H∞ controller has good tracking capability for reference commands.
Indirect synthesis of multi-degree of freedom transient systems. [linear programming for a kinematically linear system

Science.gov (United States)

Pilkey, W. D.; Chen, Y. H.

1974-01-01

An indirect synthesis method is used in the efficient optimal design of multi-degree of freedom, multi-design element, nonlinear, transient systems. A limiting performance analysis which requires linear programming for a kinematically linear system is presented. The system is selected using system identification methods such that the designed system responds as closely as possible to the limiting performance. The efficiency is a result of the method avoiding the repetitive systems analyses accompanying other numerical optimization methods.
Two-Dimensional Linear Inversion of GPR Data with a Shifting Zoom along the Observation Line

Directory of Open Access Journals (Sweden)

Raffaele Persico

2017-09-01

Full Text Available Linear inverse scattering problems can be solved by regularized inversion of a matrix, whose calculation and inversion may require significant computing resources, in particular, a significant amount of RAM memory. This effort is dependent on the extent of the investigation domain, which drives a large amount of data to be gathered and a large number of unknowns to be looked for, when this domain becomes electrically large. This leads, in turn, to the problem of inversion of excessively large matrices. Here, we consider the problem of a ground-penetrating radar (GPR survey in two-dimensional (2D geometry, with antennas at an electrically short distance from the soil. In particular, we present a strategy to afford inversion of large investigation domains, based on a shifting zoom procedure. The proposed strategy was successfully validated using experimental radar data.
Full-waveform inversion with reflected waves for 2D VTI media

KAUST Repository

Pattnaik, Sonali; Tsvankin, Ilya; Wang, Hui; Alkhalifah, Tariq

2016-01-01

Full-waveform inversion in anisotropic media using reflected waves suffers from the strong non-linearity of the objective function and trade-offs between model parameters. Estimating long-wavelength model components by fixing parameter perturbations
Multi-frequency direct sampling method in inverse scattering problem

Science.gov (United States)

Kang, Sangwoo; Lambert, Marc; Park, Won-Kwang

2017-10-01

We consider the direct sampling method (DSM) for the two-dimensional inverse scattering problem. Although DSM is fast, stable, and effective, some phenomena remain unexplained by the existing results. We show that the imaging function of the direct sampling method can be expressed by a Bessel function of order zero. We also clarify the previously unexplained imaging phenomena and suggest multi-frequency DSM to overcome traditional DSM. Our method is evaluated in simulation studies using both single and multiple frequencies.

OTRA-Based Multi-Function Inverse Filter Configuration

Directory of Open Access Journals (Sweden)

Abdhesh Kumar Singh

2017-01-01

Full Text Available A new OTRA-based multifunction Inverse filter configuration is presented which is capable of realizing low pass, high pass and band pass filters using only two OTRAs and five to six passive elements. To the best knowledge of the authors, any inverse filter configuration using OTRAs has not been reported in the literature earlier. The effect of the major parasitics of the OTRAs and their effect on the performance filter have been investigated and measured through simulation results and Monte-Carlo analysis. The workability of the proposed circuits has been confirmed by SPICE simulations using CMOS-based-OTRA realizable in 0.18 µm CMOS technology. The proposed circuits are the only ones which provide simultaneously the following features: use of reasonable number of active elements (only 2, realizability of all the three basic filter functions, employment of all virtually grounded resistors and capacitors and tunability of all filter parameters (except gain factor, H_0 for inverse high pass. The centre/cut-off frequency of the various filter circuits lying in the vicinity of 1 MHz have been found to be realizable, which has been verified through SPICE simulation results and have been found to be in good agreement with the theoretical results.
Computer-Aided Numerical Inversion of Laplace Transform

Directory of Open Access Journals (Sweden)

Umesh Kumar

2000-01-01

Full Text Available This paper explores the technique for the computer aided numerical inversion of Laplace transform. The inversion technique is based on the properties of a family of three parameter exponential probability density functions. The only limitation in the technique is the word length of the computer being used. The Laplace transform has been used extensively in the frequency domain solution of linear, lumped time invariant networks but its application to the time domain has been limited, mainly because of the difficulty in finding the necessary poles and residues. The numerical inversion technique mentioned above does away with the poles and residues but uses precomputed numbers to find the time response. This technique is applicable to the solution of partially differentiable equations and certain classes of linear systems with time varying components.
Recursive Matrix Inverse Update On An Optical Processor

Science.gov (United States)

Casasent, David P.; Baranoski, Edward J.

1988-02-01

A high accuracy optical linear algebraic processor (OLAP) using the digital multiplication by analog convolution (DMAC) algorithm is described for use in an efficient matrix inverse update algorithm with speed and accuracy advantages. The solution of the parameters in the algorithm are addressed and the advantages of optical over digital linear algebraic processors are advanced.
A METHOD FOR SOLVING LINEAR PROGRAMMING PROBLEMS WITH FUZZY PARAMETERS BASED ON MULTIOBJECTIVE LINEAR PROGRAMMING TECHNIQUE

OpenAIRE

M. ZANGIABADI; H. R. MALEKI

2007-01-01

In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...
Generalised linear models for correlated pseudo-observations, with applications to multi-state models

DEFF Research Database (Denmark)

Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne

2003-01-01

Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...
TRANSFER-FUNCTIONS OF A LINEARIZED MULTI-REGION REACTOR

Energy Technology Data Exchange (ETDEWEB)

Higgins, Thomas J.

1963-09-15

The development of the transfer functions for a linearized multi-region reactor is studied, and an illustration is made of application of the corresponding theory by a numerical illustrative example. (auth)
Normal form of linear systems depending on parameters

International Nuclear Information System (INIS)

Nguyen Huynh Phan.

1995-12-01

In this paper we resolve completely the problem to find normal forms of linear systems depending on parameters for the feedback action that we have studied for the special case of controllable linear systems. (author). 24 refs
Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

Science.gov (United States)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.
Non-linear interactions of multi-level atoms with a near-resonant standing wave

International Nuclear Information System (INIS)

O'Kane, T.J.; Scholten, R.E.; Walkiewicz, M.R.; Farrell, P.M.

1998-01-01

Using a semiclassical density matrix formalism we have calculated the behavior of multi-level atoms interacting with a standing wave field, and show how complex non-linear phenomena, including multi-photon effects, combine to produce saturation spectra as observed in experiments. We consider both 20-level sodium and 24-level rubidium models, contrasting these with a simple 2-level case. The influence of parameters such as atomic trajectory and the time the atom remains in the beam are shown to have a critical effect on the lineshape of these resonances and the emission/absorption processes. Stable oscillations in the excited state populations for both the two-level and multi-level cases are shown to be limit cycles. These limit cycles undergo period doubling as the system evolves into chaos. Finally, using a Monte Carlo treatment, these processes average to produce saturated absorption spectra complete with power and Doppler broadening effects consistent with experiment. (authors)
NLSE: Parameter-Based Inversion Algorithm

Science.gov (United States)

Sabbagh, Harold A.; Murphy, R. Kim; Sabbagh, Elias H.; Aldrin, John C.; Knopp, Jeremy S.

Chapter 11 introduced us to the notion of an inverse problem and gave us some examples of the value of this idea to the solution of realistic industrial problems. The basic inversion algorithm described in Chap. 11 was based upon the Gauss-Newton theory of nonlinear least-squares estimation and is called NLSE in this book. In this chapter we will develop the mathematical background of this theory more fully, because this algorithm will be the foundation of inverse methods and their applications during the remainder of this book. We hope, thereby, to introduce the reader to the application of sophisticated mathematical concepts to engineering practice without introducing excessive mathematical sophistication.
Optimized nonlinear inversion of surface-wave dispersion data

International Nuclear Information System (INIS)

Raykova, Reneta B.

2014-01-01

A new code for inversion of surface wave dispersion data is developed to obtain Earth’s crustal and upper mantle velocity structure. The author developed Optimized Non–Linear Inversion ( ONLI ) software, based on Monte-Carlo search. The values of S–wave velocity VS and thickness h for a number of horizontal homogeneous layers are parameterized. Velocity of P–wave VP and density ρ of relevant layers are calculated by empirical or theoretical relations. ONLI explores parameters space in two modes, selective and full search, and the main innovation of software is evaluation of tested models. Theoretical dispersion curves are calculated if tested model satisfied specific conditions only, reducing considerably the computation time. A number of tests explored impact of parameterization and proved the ability of ONLI approach to deal successfully with non–uniqueness of inversion problem. Key words: Earth’s structure, surface–wave dispersion, non–linear inversion, software
Non-Linear Multi-Physics Analysis and Multi-Objective Optimization in Electroheating Applications

Czech Academy of Sciences Publication Activity Database

di Barba, P.; Doležel, Ivo; Mognaschi, M. E.; Savini, A.; Karban, P.

2014-01-01

Roč. 50, č. 2 (2014), s. 7016604-7016604 ISSN 0018-9464 Institutional support: RVO:61388998 Keywords : coupled multi-physics problems * finite element method * non-linear equations Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.386, year: 2014
Inverse transition radiation

International Nuclear Information System (INIS)

Steinhauer, L.C.; Romea, R.D.; Kimura, W.D.

1997-01-01

A new method for laser acceleration is proposed based upon the inverse process of transition radiation. The laser beam intersects an electron-beam traveling between two thin foils. The principle of this acceleration method is explored in terms of its classical and quantum bases and its inverse process. A closely related concept based on the inverse of diffraction radiation is also presented: this concept has the significant advantage that apertures are used to allow free passage of the electron beam. These concepts can produce net acceleration because they do not satisfy the conditions in which the Lawson-Woodward theorem applies (no net acceleration in an unbounded vacuum). Finally, practical aspects such as damage limits at optics are employed to find an optimized set of parameters. For reasonable assumptions an acceleration gradient of 200 MeV/m requiring a laser power of less than 1 GW is projected. An interesting approach to multi-staging the acceleration sections is also presented. copyright 1997 American Institute of Physics
Linear versus non-linear structural information limit in high-resolution transmission electron microscopy

International Nuclear Information System (INIS)

Van Aert, S.; Chen, J.H.; Van Dyck, D.

2010-01-01

A widely used performance criterion in high-resolution transmission electron microscopy (HRTEM) is the information limit. It corresponds to the inverse of the maximum spatial object frequency that is linearly transmitted with sufficient intensity from the exit plane of the object to the image plane and is limited due to partial temporal coherence. In practice, the information limit is often measured from a diffractogram or from Young's fringes assuming a weak phase object scattering beyond the inverse of the information limit. However, for an aberration corrected electron microscope, with an information limit in the sub-angstrom range, weak phase objects are no longer applicable since they do not scatter sufficiently in this range. Therefore, one relies on more strongly scattering objects such as crystals of heavy atoms observed along a low index zone axis. In that case, dynamical scattering becomes important such that the non-linear and linear interaction may be equally important. The non-linear interaction may then set the experimental cut-off frequency observed in a diffractogram. The goal of this paper is to quantify both the linear and the non-linear information transfer in terms of closed form analytical expressions. Whereas the cut-off frequency set by the linear transfer can be directly related with the attainable resolution, information from the non-linear transfer can only be extracted using quantitative, model-based methods. In contrast to the historic definition of the information limit depending on microscope parameters only, the expressions derived in this paper explicitly incorporate their dependence on the structure parameters as well. In order to emphasize this dependence and to distinguish from the usual information limit, the expressions derived for the inverse cut-off frequencies will be referred to as the linear and non-linear structural information limit. The present findings confirm the well-known result that partial temporal coherence has
Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment
Geodynamic inversion to constrain the non-linear rheology of the lithosphere

Science.gov (United States)

Baumann, T. S.; Kaus, Boris J. P.

2015-08-01

One of the main methods to determine the strength of the lithosphere is by estimating it's effective elastic thickness. This method assumes that the lithosphere is a thin elastic plate that floats on the mantle and uses both topography and gravity anomalies to estimate the plate thickness. Whereas this seems to work well for oceanic plates, it has given controversial results in continental collision zones. For most of these locations, additional geophysical data sets such as receiver functions and seismic tomography exist that constrain the geometry of the lithosphere and often show that it is rather complex. Yet, lithospheric geometry by itself is insufficient to understand the dynamics of the lithosphere as this also requires knowledge of the rheology of the lithosphere. Laboratory experiments suggest that rocks deform in a viscous manner if temperatures are high and stresses low, or in a plastic/brittle manner if the yield stress is exceeded. Yet, the experimental results show significant variability between various rock types and there are large uncertainties in extrapolating laboratory values to nature, which leaves room for speculation. An independent method is thus required to better understand the rheology and dynamics of the lithosphere in collision zones. The goal of this paper is to discuss such an approach. Our method relies on performing numerical thermomechanical forward models of the present-day lithosphere with an initial geometry that is constructed from geophysical data sets. We employ experimentally determined creep-laws for the various parts of the lithosphere, but assume that the parameters of these creep-laws as well as the temperature structure of the lithosphere are uncertain. This is used as a priori information to formulate a Bayesian inverse problem that employs topography, gravity, horizontal and vertical surface velocities to invert for the unknown material parameters and temperature structure. In order to test the general methodology
Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

Science.gov (United States)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.
Invariant-Based Inverse Engineering of Crane Control Parameters

Science.gov (United States)

González-Resines, S.; Guéry-Odelin, D.; Tobalina, A.; Lizuain, I.; Torrontegui, E.; Muga, J. G.

2017-11-01

By applying invariant-based inverse engineering in the small-oscillation regime, we design the time dependence of the control parameters of an overhead crane (trolley displacement and rope length) to transport a load between two positions at different heights with minimal final-energy excitation for a microcanonical ensemble of initial conditions. The analogy between ion transport in multisegmented traps or neutral-atom transport in moving optical lattices and load manipulation by cranes opens a route for a useful transfer of techniques among very different fields.
On the calibration process of film dosimetry: OLS inverse regression versus WLS inverse prediction

International Nuclear Information System (INIS)

Crop, F; Thierens, H; Rompaye, B Van; Paelinck, L; Vakaet, L; Wagter, C De

2008-01-01

The purpose of this study was both putting forward a statistically correct model for film calibration and the optimization of this process. A reliable calibration is needed in order to perform accurate reference dosimetry with radiographic (Gafchromic) film. Sometimes, an ordinary least squares simple linear (in the parameters) regression is applied to the dose-optical-density (OD) curve with the dose as a function of OD (inverse regression) or sometimes OD as a function of dose (inverse prediction). The application of a simple linear regression fit is an invalid method because heteroscedasticity of the data is not taken into account. This could lead to erroneous results originating from the calibration process itself and thus to a lower accuracy. In this work, we compare the ordinary least squares (OLS) inverse regression method with the correct weighted least squares (WLS) inverse prediction method to create calibration curves. We found that the OLS inverse regression method could lead to a prediction bias of up to 7.3 cGy at 300 cGy and total prediction errors of 3% or more for Gafchromic EBT film. Application of the WLS inverse prediction method resulted in a maximum prediction bias of 1.4 cGy and total prediction errors below 2% in a 0-400 cGy range. We developed a Monte-Carlo-based process to optimize calibrations, depending on the needs of the experiment. This type of thorough analysis can lead to a higher accuracy for film dosimetry
Linear and Non-linear Multi-Input Multi-Output Model Predictive Control of Continuous Stirred Tank Reactor

Directory of Open Access Journals (Sweden)

Muayad Al-Qaisy

2015-02-01

Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.

MARE2DEM: a 2-D inversion code for controlled-source electromagnetic and magnetotelluric data

Science.gov (United States)

Key, Kerry

2016-10-01

This work presents MARE2DEM, a freely available code for 2-D anisotropic inversion of magnetotelluric (MT) data and frequency-domain controlled-source electromagnetic (CSEM) data from onshore and offshore surveys. MARE2DEM parametrizes the inverse model using a grid of arbitrarily shaped polygons, where unstructured triangular or quadrilateral grids are typically used due to their ease of construction. Unstructured grids provide significantly more geometric flexibility and parameter efficiency than the structured rectangular grids commonly used by most other inversion codes. Transmitter and receiver components located on topographic slopes can be tilted parallel to the boundary so that the simulated electromagnetic fields accurately reproduce the real survey geometry. The forward solution is implemented with a goal-oriented adaptive finite-element method that automatically generates and refines unstructured triangular element grids that conform to the inversion parameter grid, ensuring accurate responses as the model conductivity changes. This dual-grid approach is significantly more efficient than the conventional use of a single grid for both the forward and inverse meshes since the more detailed finite-element meshes required for accurate responses do not increase the memory requirements of the inverse problem. Forward solutions are computed in parallel with a highly efficient scaling by partitioning the data into smaller independent modeling tasks consisting of subsets of the input frequencies, transmitters and receivers. Non-linear inversion is carried out with a new Occam inversion approach that requires fewer forward calls. Dense matrix operations are optimized for memory and parallel scalability using the ScaLAPACK parallel library. Free parameters can be bounded using a new non-linear transformation that leaves the transformed parameters nearly the same as the original parameters within the bounds, thereby reducing non-linear smoothing effects. Data
Incorporating modelled subglacial hydrology into inversions for basal drag

Directory of Open Access Journals (Sweden)

C. P. Koziol

2017-12-01

Full Text Available A key challenge in modelling coupled ice-flow–subglacial hydrology is initializing the state and parameters of the system. We address this problem by presenting a workflow for initializing these values at the start of a summer melt season. The workflow depends on running a subglacial hydrology model for the winter season, when the system is not forced by meltwater inputs, and ice velocities can be assumed constant. Key parameters of the winter run of the subglacial hydrology model are determined from an initial inversion for basal drag using a linear sliding law. The state of the subglacial hydrology model at the end of winter is incorporated into an inversion of basal drag using a non-linear sliding law which is a function of water pressure. We demonstrate this procedure in the Russell Glacier area and compare the output of the linear sliding law with two non-linear sliding laws. Additionally, we compare the modelled winter hydrological state to radar observations and find that it is in line with summer rather than winter observations.
Pareto-Optimal Multi-objective Inversion of Geophysical Data

Science.gov (United States)

Schnaidt, Sebastian; Conway, Dennis; Krieger, Lars; Heinson, Graham

2018-01-01

In the process of modelling geophysical properties, jointly inverting different data sets can greatly improve model results, provided that the data sets are compatible, i.e., sensitive to similar features. Such a joint inversion requires a relationship between the different data sets, which can either be analytic or structural. Classically, the joint problem is expressed as a scalar objective function that combines the misfit functions of multiple data sets and a joint term which accounts for the assumed connection between the data sets. This approach suffers from two major disadvantages: first, it can be difficult to assess the compatibility of the data sets and second, the aggregation of misfit terms introduces a weighting of the data sets. We present a pareto-optimal multi-objective joint inversion approach based on an existing genetic algorithm. The algorithm treats each data set as a separate objective, avoiding forced weighting and generating curves of the trade-off between the different objectives. These curves are analysed by their shape and evolution to evaluate data set compatibility. Furthermore, the statistical analysis of the generated solution population provides valuable estimates of model uncertainty.
Testing for one Generalized Linear Single Order Parameter

DEFF Research Database (Denmark)

Ellegaard, Niels Langager; Christensen, Tage Emil; Dyre, Jeppe

We examine a linear single order parameter model for thermoviscoelastic relaxation in viscous liquids, allowing for a distribution of relaxation times. In this model the relaxation of volume and entalpy is completely described by the relaxation of one internal order parameter. In contrast to prior...... work the order parameter may be chosen to have a non-exponential relaxation. The model predictions contradict the general consensus of the properties of viscous liquids in two ways: (i) The model predicts that following a linear isobaric temperature step, the normalized volume and entalpy relaxation...... responses or extrapolate from measurements of a glassy state away from equilibrium. Starting from a master equation description of inherent dynamics, we calculate the complex thermodynamic response functions. We device a way of testing for the generalized single order parameter model by measuring 3 complex...
Contributions to Large Covariance and Inverse Covariance Matrices Estimation

OpenAIRE

Kang, Xiaoning

2016-01-01

Estimation of covariance matrix and its inverse is of great importance in multivariate statistics with broad applications such as dimension reduction, portfolio optimization, linear discriminant analysis and gene expression analysis. However, accurate estimation of covariance or inverse covariance matrices is challenging due to the positive definiteness constraint and large number of parameters, especially in the high-dimensional cases. In this thesis, I develop several approaches for estimat...
Inverse problem theory methods for data fitting and model parameter estimation

CERN Document Server

Tarantola, A

2002-01-01

Inverse Problem Theory is written for physicists, geophysicists and all scientists facing the problem of quantitative interpretation of experimental data. Although it contains a lot of mathematics, it is not intended as a mathematical book, but rather tries to explain how a method of acquisition of information can be applied to the actual world.The book provides a comprehensive, up-to-date description of the methods to be used for fitting experimental data, or to estimate model parameters, and to unify these methods into the Inverse Problem Theory. The first part of the book deals wi
FAST INTEGER AMBIGUITY RESOLUTION IN GPS KINEMATIC POSITIONING USING LEFT NULL SPACE AND MULTI-TIME (INVERSE PAIRED CHOLESKY DECORRELATION

Directory of Open Access Journals (Sweden)

Rong Duan

Full Text Available Aiming at the problems that huge amount of computation in ambiguity resolution with multiple epochs and high-order matrix inversion occurred in the GPS kinematic relative positioning, a modified algorithm for fast integer ambiguity resolution is proposed. Firstly, Singular Value Decomposition (SVD is applied to construct the left null space matrix in order to eliminate the baselines components, which is able to separate ambiguity parameters from the position parameters efficiently. Kalman filter is applied only to estimate the ambiguity parameters so that the real-time ambiguity float solution is obtained. Then, sorting and multi-time (inverse paired Cholesky decomposition are adopted for decorrelation of ambiguity. After diagonal elements preprocessing and diagonal elements sorting according to the results of Cholesky decomposition, the efficiency of decomposition and decorrelation is improved. Lastly, the integer search algorithm implemented in LAMBDA method is used for searching the integer ambiguity. To verify the validity and efficacy of the proposed algorithm, static and kinematic tests are carried out. Experimental results show that this algorithm has good performance of decorrelation and precision of float solution, with computation speed also increased effectively. The final positioning accuracy result with static baseline error less than 1 cm and kinematic error less than 2 cm, which indicates that it can be used for fast kinematic positioning of high precision carrier.
Implementation of a multi-layer perception for a non-linear control problem

International Nuclear Information System (INIS)

Lister, J.B.; Schnurrenberger, H.; Marmillod, P.

1990-12-01

We present the practical application of a 1-hidden-layer multilayer perception (MLP) to provide a non-linear continuous multi-variable mapping with 42 inputs and 13 outputs. The problem resolved is one of extracting information from experimental signals with a bandwidth of many kilohertz. We have an exact model of the inverse mapping of this problem, but we have no explicit form of the required forward mapping. This is the typical situation in data interpretation. The MLP was trained to provide this mapping by learning on 500 input-output examples. The success of the off-line solution to this problem using an MLP led us to examine the robustness of the MLP to different noise sources. We found that the MLP is more robust than an approximate linear mapping of the same problem. 12 bits of resolution in the weights are necessary to avoid a significant loss of precision. The practical implementation of large analog weight matrices using DAS-multipliers and a simple segmented sigmoid is also presented. A General Adaptive Recipe (GAR) for improving the performance of conventional back-propagation was developed. The GAR uses an adaptive step length and both the bias terms and the initial weight seeding are determined by the network size. The GAR was found to be robust and much faster than conventional back-propagation. (author) 20 figs., 1 tab., 15 refs
Nonlinear inversion of resistivity sounding data for 1-D earth models using the Neighbourhood Algorithm

Science.gov (United States)

Ojo, A. O.; Xie, Jun; Olorunfemi, M. O.

2018-01-01

To reduce ambiguity related to nonlinearities in the resistivity model-data relationships, an efficient direct-search scheme employing the Neighbourhood Algorithm (NA) was implemented to solve the 1-D resistivity problem. In addition to finding a range of best-fit models which are more likely to be global minimums, this method investigates the entire multi-dimensional model space and provides additional information about the posterior model covariance matrix, marginal probability density function and an ensemble of acceptable models. This provides new insights into how well the model parameters are constrained and make assessing trade-offs between them possible, thus avoiding some common interpretation pitfalls. The efficacy of the newly developed program is tested by inverting both synthetic (noisy and noise-free) data and field data from other authors employing different inversion methods so as to provide a good base for comparative performance. In all cases, the inverted model parameters were in good agreement with the true and recovered model parameters from other methods and remarkably correlate with the available borehole litho-log and known geology for the field dataset. The NA method has proven to be useful whilst a good starting model is not available and the reduced number of unknowns in the 1-D resistivity inverse problem makes it an attractive alternative to the linearized methods. Hence, it is concluded that the newly developed program offers an excellent complementary tool for the global inversion of the layered resistivity structure.
A test for the parameters of multiple linear regression models ...

African Journals Online (AJOL)

A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
Full-waveform inversion with reflected waves for 2D VTI media

KAUST Repository

Pattnaik, Sonali

2016-09-06

Full-waveform inversion in anisotropic media using reflected waves suffers from the strong non-linearity of the objective function and trade-offs between model parameters. Estimating long-wavelength model components by fixing parameter perturbations, referred to as reflection-waveform inversion (RWI), can mitigate nonlinearity-related inversion issues. Here, we extend RWI to acoustic VTI (transversely isotropic with a vertical symmetry axis) media. To minimize trade-offs between the model parameters, we employ a new hierarchical two-stage approach that operates with the P-wave normal-moveout velocity and anisotropy coefficents ζ and η. First, is estimated using a fixed perturbation in ζ, and then we invert for η by fixing the updated perturbation in . The proposed 2D algorithm is tested on a horizontally layered VTI model.
On the internal stability of non-linear dynamic inversion: application to flight control

Czech Academy of Sciences Publication Activity Database

Alam, M.; Čelikovský, Sergej

2017-01-01

Roč. 11, č. 12 (2017), s. 1849-1861 ISSN 1751-8644 R&D Projects: GA ČR(CZ) GA17-04682S Institutional support: RVO:67985556 Keywords : flight control * non-linear dynamic inversion * stability Subject RIV: BC - Control Systems Theory OBOR OECD: Automation and control systems Impact factor: 2.536, year: 2016 http://library.utia.cas.cz/separaty/2017/TR/celikovsky-0476150.pdf
Resolution limits of migration and linearized waveform inversion images in a lossy medium

KAUST Repository

Schuster, Gerard T.; Dutta, Gaurav; Li, Jing

2017-01-01

The vertical-and horizontal-resolution limits Delta x(lossy) and Delta z(lossy) of post-stack migration and linearized waveform inversion images are derived for lossy data in the far-field approximation. Unlike the horizontal resolution limit Delta x proportional to lambda z/L in a lossless medium which linearly worsens in depth z, Delta x(lossy) proportional to z(2)/QL worsens quadratically with depth for a medium with small Q values. Here, Q is the quality factor, lambda is the effective wavelength, L is the recording aperture, and loss in the resolution formulae is accounted for by replacing lambda with z/Q. In contrast, the lossy vertical-resolution limit Delta z(lossy) only worsens linearly in depth compared to Delta z proportional to lambda for a lossless medium. For both the causal and acausal Q models, the resolution limits are linearly proportional to 1/Q for small Q. These theoretical predictions are validated with migration images computed from lossy data.
Resolution limits of migration and linearized waveform inversion images in a lossy medium

KAUST Repository

Schuster, Gerard T.

2017-03-10

The vertical-and horizontal-resolution limits Delta x(lossy) and Delta z(lossy) of post-stack migration and linearized waveform inversion images are derived for lossy data in the far-field approximation. Unlike the horizontal resolution limit Delta x proportional to lambda z/L in a lossless medium which linearly worsens in depth z, Delta x(lossy) proportional to z(2)/QL worsens quadratically with depth for a medium with small Q values. Here, Q is the quality factor, lambda is the effective wavelength, L is the recording aperture, and loss in the resolution formulae is accounted for by replacing lambda with z/Q. In contrast, the lossy vertical-resolution limit Delta z(lossy) only worsens linearly in depth compared to Delta z proportional to lambda for a lossless medium. For both the causal and acausal Q models, the resolution limits are linearly proportional to 1/Q for small Q. These theoretical predictions are validated with migration images computed from lossy data.
Application of multi-source waveform inversion to marine streamer data using the global correlation norm

KAUST Repository

Choi, Yun Seok; Alkhalifah, Tariq Ali

2012-01-01

Conventional multi-source waveform inversion using an objective function based on the least-square misfit cannot be applied to marine streamer acquisition data because of inconsistent acquisition geometries between observed and modelled data
The study of NMR relaxation time spectra multi-exponential inversion based on Lloyd–Max optimal quantization

International Nuclear Information System (INIS)

Li, Xuewei; Kong, Li; Cheng, Jingjing; Wu, Lei

2015-01-01

The multi-exponential inversion of a NMR relaxation signal plays a key role in core analysis and logging interpretation in the formation of porous media. To find an efficient metod of inverting high-resolution relaxation time spectra rapidly, this paper studies the effect of inversion which is based on the discretization of the original echo in a time domain by using a simulation model. This paper analyzes the ill-condition of discrete equations on the basis of the NMR inversion model and method, determines the appropriate number of discrete echoes and acquires the optimal distribution of discrete echo points by the Lloyd–Max optimal quantization method, in considering the inverse precision and computational complexity comprehensively. The result shows that this method can effectively improve the efficiency of the relaxation time spectra inversion while guaranteeing inversed accuracy. (paper)
Evaluation of Body Weight and Other Linear Parameters of Marshall ...

African Journals Online (AJOL)

This study was designed to evaluate the body weight and other linear parameters of Marshall Broiler for repeatability estimates. A total of one hundred (100) broiler chickens (Marshall) was used in estimating the repeatability of body weight and linear parameters of day old from 2 to 8 weeks of age. Body weight (BW) and ...
Inverse planning and optimization: a comparison of solutions

Energy Technology Data Exchange (ETDEWEB)

Ringor, Michael [School of Health Sciences, Purdue University, West Lafayette, IN (United States); Papiez, Lech [Department of Radiation Oncology, Indiana University, Indianapolis, IN (United States)

1998-09-01

The basic problem in radiation therapy treatment planning is to determine an appropriate set of treatment parameters that would induce an effective dose distribution inside a patient. One can approach this task as an inverse problem, or as an optimization problem. In this presentation, we compare both approaches. The inverse problem is presented as a dose reconstruction problem similar to tomography reconstruction. We formulate the optimization problem as linear and quadratic programs. Explicit comparisons are made between the solutions obtained by inversion and those obtained by optimization for the case in which scatter and attenuation are ignored (the NS-NA approximation)
Full Waveform Inversion Using Oriented Time Migration Method

KAUST Repository

Zhang, Zhendong

2016-04-12

Full waveform inversion (FWI) for reflection events is limited by its linearized update requirements given by a process equivalent to migration. Unless the background velocity model is reasonably accurate the resulting gradient can have an inaccurate update direction leading the inversion to converge into what we refer to as local minima of the objective function. In this thesis, I first look into the subject of full model wavenumber to analysis the root of local minima and suggest the possible ways to avoid this problem. And then I analysis the possibility of recovering the corresponding wavenumber components through the existing inversion and migration algorithms. Migration can be taken as a generalized inversion method which mainly retrieves the high wavenumber part of the model. Conventional impedance inversion method gives a mapping relationship between the migration image (high wavenumber) and model parameters (full wavenumber) and thus provides a possible cascade inversion strategy to retrieve the full wavenumber components from seismic data. In the proposed approach, consider a mild lateral variation in the model, I find an analytical Frechet derivation corresponding to the new objective function. In the proposed approach, the gradient is given by the oriented time-domain imaging method. This is independent of the background velocity. Specifically, I apply the oriented time-domain imaging (which depends on the reflection slope instead of a background velocity) on the data residual to obtain the geometrical features of the velocity perturbation. Assuming that density is constant, the conventional 1D impedance inversion method is also applicable for 2D or 3D velocity inversion within the process of FWI. This method is not only capable of inverting for velocity, but it is also capable of retrieving anisotropic parameters relying on linearized representations of the reflection response. To eliminate the cross-talk artifacts between different parameters, I
Compact multi-energy electron linear accelerators

International Nuclear Information System (INIS)

Tanabe, E.; Hamm, R.W.

1985-01-01

Two distinctly different concepts that have been developed for compact multi-energy, single-section, standing-wave electron linear accelerator structures are presented. These new concepts, which utilize (a) variable nearest neighbor couplings and (b) accelerating field phase switching, provide the capability of continuously varying the electron output energy from the accelerator without degrading the energy spectrum. These techniques also provide the means for continuously varying the energy spectrum while maintaining a given average electron energy, and have been tested successfully with several accelerators of length from 0.1 m to 1.9 m. Theoretical amd experimental results from these accelerators, and demonstrated applications of these techniques to medical and industrial linear accelerator technology will be described. In addition, possible new applications available to research and industry from these techniques are presented. (orig.)

3D CSEM inversion based on goal-oriented adaptive finite element method

Science.gov (United States)

Zhang, Y.; Key, K.

2016-12-01

We present a parallel 3D frequency domain controlled-source electromagnetic inversion code name MARE3DEM. Non-linear inversion of observed data is performed with the Occam variant of regularized Gauss-Newton optimization. The forward operator is based on the goal-oriented finite element method that efficiently calculates the responses and sensitivity kernels in parallel using a data decomposition scheme where independent modeling tasks contain different frequencies and subsets of the transmitters and receivers. To accommodate complex 3D conductivity variation with high flexibility and precision, we adopt the dual-grid approach where the forward mesh conforms to the inversion parameter grid and is adaptively refined until the forward solution converges to the desired accuracy. This dual-grid approach is memory efficient, since the inverse parameter grid remains independent from fine meshing generated around the transmitter and receivers by the adaptive finite element method. Besides, the unstructured inverse mesh efficiently handles multiple scale structures and allows for fine-scale model parameters within the region of interest. Our mesh generation engine keeps track of the refinement hierarchy so that the map of conductivity and sensitivity kernel between the forward and inverse mesh is retained. We employ the adjoint-reciprocity method to calculate the sensitivity kernels which establish a linear relationship between changes in the conductivity model and changes in the modeled responses. Our code uses a direcy solver for the linear systems, so the adjoint problem is efficiently computed by re-using the factorization from the primary problem. Further computational efficiency and scalability is obtained in the regularized Gauss-Newton portion of the inversion using parallel dense matrix-matrix multiplication and matrix factorization routines implemented with the ScaLAPACK library. We show the scalability, reliability and the potential of the algorithm to deal with
One Year assessment of shielding for a multi-energy linear accelerator

International Nuclear Information System (INIS)

Lee, Jae Gi; Carlson, Joel; Lee, Hyun Seok; Ye, Sung Joon; Chung, Jin Beom; Kim, Jae Sung; Kim, Jung In

2014-01-01

In 2005, the publication of Report No. 151 of the National Council on Radiation Protection and Measurements (NCRP) suggested shielding methodologies along with shielding data. Recently, intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) have become more widely used for cancer treatment. Thus, we analyzed shielding parameters for a multi-energy medical linear accelerator using the VMAT technique. Calculated total workload was similar to the recommendation of NCRP Report No. 49 and No. 51. However, these results were higher than the previous results in the NCRP Report No. 151. Also, the VMAT technique uses an intensity modulated beams with various gantry angles so that scattered and leakage doses should be carefully considered by retrospective analysis using the treatment data from each facility
One Year assessment of shielding for a multi-energy linear accelerator

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Gi; Carlson, Joel; Lee, Hyun Seok; Ye, Sung Joon [Seoul National University Graduate School of Convergence Science and Technology, Seoul (Korea, Republic of); Chung, Jin Beom; Kim, Jae Sung [Dept. of Radiation Oncology, Seoul National University Bundang Hospital, Seoul (Korea, Republic of); Kim, Jung In [Dept. of of Radiation Oncology, Seoul National University Hospital, Seoul (Korea, Republic of)

2014-11-15

In 2005, the publication of Report No. 151 of the National Council on Radiation Protection and Measurements (NCRP) suggested shielding methodologies along with shielding data. Recently, intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) have become more widely used for cancer treatment. Thus, we analyzed shielding parameters for a multi-energy medical linear accelerator using the VMAT technique. Calculated total workload was similar to the recommendation of NCRP Report No. 49 and No. 51. However, these results were higher than the previous results in the NCRP Report No. 151. Also, the VMAT technique uses an intensity modulated beams with various gantry angles so that scattered and leakage doses should be carefully considered by retrospective analysis using the treatment data from each facility.
Parameter identifiability of linear dynamical systems

Science.gov (United States)

Glover, K.; Willems, J. C.

1974-01-01

It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.
Linear parameter varying representations for nonlinear control design

Science.gov (United States)

Carter, Lance Huntington

Linear parameter varying (LPV) systems are investigated as a framework for gain-scheduled control design and optimal hybrid control. An LPV system is defined as a linear system whose dynamics depend upon an a priori unknown but measurable exogenous parameter. A gain-scheduled autopilot design is presented for a bank-to-turn (BTT) missile. The method is novel in that the gain-scheduled design does not involve linearizations about operating points. Instead, the missile dynamics are brought to LPV form via a state transformation. This idea is applied to the design of a coupled longitudinal/lateral BTT missile autopilot. The pitch and yaw/roll dynamics are separately transformed to LPV form, where the cross axis states are treated as "exogenous" parameters. These are actually endogenous variables, so such a plant is called "quasi-LPV." Once in quasi-LPV form, a family of robust controllers using mu synthesis is designed for both the pitch and yaw/roll channels, using angle-of-attack and roll rate as the scheduling variables. The closed-loop time response is simulated using the original nonlinear model and also using perturbed aerodynamic coefficients. Modeling and control of engine idle speed is investigated using LPV methods. It is shown how generalized discrete nonlinear systems may be transformed into quasi-LPV form. A discrete nonlinear engine model is developed and expressed in quasi-LPV form with engine speed as the scheduling variable. An example control design is presented using linear quadratic methods. Simulations are shown comparing the LPV based controller performance to that using PID control. LPV representations are also shown to provide a setting for hybrid systems. A hybrid system is characterized by control inputs consisting of both analog signals and discrete actions. A solution is derived for the optimal control of hybrid systems with generalized cost functions. This is shown to be computationally intensive, so a suboptimal strategy is proposed that
The development of computational algorithms for manipulator inverse kinematics

International Nuclear Information System (INIS)

Sasaki, Shinobu

1989-10-01

A solution technique of the inverse kinematics for multi-joint robot manipulators has been considered to be one of the most cumbersome treatment due to non-linearity properties inclusive of trigonometric functions. The most traditional approach is to use the Jacobian matrix on linearization assumptions. This iterative technique, however, is attended with numerical problems having significant influences on the solution characteristics such as initial guess dependence and singularities. Taking these facts into consideration, new approaches have been proposed from different standpoints, which are based on polynomial transformation of kinematic model, the minimization technique in mathematical programming, vector-geometrical concept, and the separation of joint variables associated with the optimization problem. In terms of computer simulations, each approach was identified to be a useful algorithm which leads to theoretically accurate solutions to complicated inverse problems. In this way, the short-term goal of our studies on manipulator inverse problem in the R and D project of remote handling technology was accomplished with success, and consequently the present report sums up the results of basic studies on this matter. (author)
Multi-objective genetic optimization of linear construction projects

Directory of Open Access Journals (Sweden)

Fatma A. Agrama

2012-08-01

Full Text Available In the real world, the majority cases of optimization problems, met by engineers, are composed of several conflicting objectives. This paper presents an approach for a multi-objective optimization model for scheduling linear construction projects. Linear construction projects have many identical units wherein activities repeat from one unit to another. Highway, pipeline, and tunnels are good examples that exhibit repetitive characteristics. These projects represent a large portion of the construction industry. The present model enables construction planners to generate optimal/near-optimal construction plans that minimize project duration, total work interruptions, and total number of crews. Each of these plans identifies, from a set of feasible alternatives, optimal crew synchronization for each activity and activity interruptions at each unit. This model satisfies the following aspects: (1 it is based on the line of balance technique; (2 it considers non-serial typical activities networks with finish–start relationship and both lag or overlap time between activities is allowed; (3 it utilizes a multi-objective genetic algorithms approach; (4 it is developed as a spreadsheet template that is easy to use. Details of the model with visual charts are presented. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the scheduling of linear construction projects.
Multi-parameter sensor based on random fiber lasers

Directory of Open Access Journals (Sweden)

Yanping Xu

2016-09-01

Full Text Available We demonstrate a concept of utilizing random fiber lasers to achieve multi-parameter sensing. The proposed random fiber ring laser consists of an erbium-doped fiber as the gain medium and a random fiber grating as the feedback. The random feedback is effectively realized by a large number of reflections from around 50000 femtosecond laser induced refractive index modulation regions over a 10cm standard single mode fiber. Numerous polarization-dependent spectral filters are formed and superimposed to provide multiple lasing lines with high signal-to-noise ratio up to 40dB, which gives an access for a high-fidelity multi-parameter sensing scheme. The number of sensing parameters can be controlled by the number of the lasing lines via input polarizations and wavelength shifts of each peak can be explored for the simultaneous multi-parameter sensing with one sensing probe. In addition, the random grating induced coupling between core and cladding modes can be potentially used for liquid medical sample sensing in medical diagnostics, biology and remote sensing in hostile environments.
Inverse modeling for the determination of hydrogeological parameters of a two-phase system

International Nuclear Information System (INIS)

Finsterle, S.

1993-02-01

Investigations related to the disposal of radioactive wastes in Switzerland consider formations containing natural gas as potential rocks for a repository. Moreover, gas generation in the repository itself may lead to an unsaturated zone of significant extent and impact on the system's performance. The site characterization procedure requires the estimation of hydraulic properties being used as input parameters for a two-phase two-component numerical simulator. In this study, estimates of gas-related formation parameters are obtained by inverse modeling. Based on discrete observations of the system's state, model parameters can be estimated within the framework of a given conceptual model by means of optimization techniques. This study presents the theoretical background that related field data to the model parameters. A parameter estimation procedure is proposed and implemented in a computer code for automatic model calibration. This tool allows identification of key parameters affecting flow of water and gas in porous media. The inverse modeling approach is verified using data from a synthetic laboratory experiment. In addition, the Gas test performed at the Grimsel Test Site is analyzed in order to demonstrate the applicability of the proposed procedure when used with data from a real geologic environment. Estimation of hydrogeologic parameters by automatic model calibration improves the understanding of the two-phase flow processes and therefore increases the reliability of the subsequent simulation runs. (author) figs., tabs., refs
Inverse modeling for the determination of hydrogeological parameters of a two-phase system

International Nuclear Information System (INIS)

Finsterle, S.

1993-01-01

Investigations related to the disposal of radioactive wastes in Switzerland are dealing with formations containing natural gas as potential host rock for a repository. Moreover, gas generation in the repository itself may lead to an unsaturated zone of significant extent and impact on the system's performance. The site characterization procedure requires the estimation of hydraulic properties being used as input parameters for a two-phase two-component numerical simulator. In this study, estimates of gas related formation parameters are obtained by inverse modeling. Based on discrete observations of the system's state, model parameters can be estimated within the framework of a given conceptual model by means of optimization techniques. This study presents the theoretical background that relates field data to the model parameters. A parameter estimation procedure is proposed and implemented in a computer code for automatic model calibration. This tool allows to identify key parameters affecting flow of water and gas in porous media. The inverse modeling approach is verified using data from a synthetic laboratory experiment. In addition, the Gastest performed at the Grimsel Test Site is analyzed in order to demonstrate the applicability of the proposed procedure when used with data from a real geologic environment. Estimation of hydrogeologic parameters by automatic model calibration improves the understanding of the two-phase flow processes and therefore increases the reliability of the subsequent simulation runs. (author) figs., tabs., 100 refs
Bayesian inversion of refraction seismic traveltime data

Science.gov (United States)

Ryberg, T.; Haberland, Ch

2018-03-01

We apply a Bayesian Markov chain Monte Carlo (McMC) formalism to the inversion of refraction seismic, traveltime data sets to derive 2-D velocity models below linear arrays (i.e. profiles) of sources and seismic receivers. Typical refraction data sets, especially when using the far-offset observations, are known as having experimental geometries which are very poor, highly ill-posed and far from being ideal. As a consequence, the structural resolution quickly degrades with depth. Conventional inversion techniques, based on regularization, potentially suffer from the choice of appropriate inversion parameters (i.e. number and distribution of cells, starting velocity models, damping and smoothing constraints, data noise level, etc.) and only local model space exploration. McMC techniques are used for exhaustive sampling of the model space without the need of prior knowledge (or assumptions) of inversion parameters, resulting in a large number of models fitting the observations. Statistical analysis of these models allows to derive an average (reference) solution and its standard deviation, thus providing uncertainty estimates of the inversion result. The highly non-linear character of the inversion problem, mainly caused by the experiment geometry, does not allow to derive a reference solution and error map by a simply averaging procedure. We present a modified averaging technique, which excludes parts of the prior distribution in the posterior values due to poor ray coverage, thus providing reliable estimates of inversion model properties even in those parts of the models. The model is discretized by a set of Voronoi polygons (with constant slowness cells) or a triangulated mesh (with interpolation within the triangles). Forward traveltime calculations are performed by a fast, finite-difference-based eikonal solver. The method is applied to a data set from a refraction seismic survey from Northern Namibia and compared to conventional tomography. An inversion test
Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.

2011-01-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques
Estimating Soil and Root Parameters of Biofuel Crops using a Hydrogeophysical Inversion

Science.gov (United States)

Kuhl, A.; Kendall, A. D.; Van Dam, R. L.; Hyndman, D. W.

2017-12-01

Transpiration is the dominant pathway for continental water exchange to the atmosphere, and therefore a crucial aspect of modeling water balances at many scales. The root water uptake dynamics that control transpiration are dependent on soil water availability, as well as the root distribution. However, the root distribution is determined by many factors beyond the plant species alone, including climate conditions and soil texture. Despite the significant contribution of transpiration to global water fluxes, modelling the complex critical zone processes that drive root water uptake remains a challenge. Geophysical tools such as electrical resistivity (ER), have been shown to be highly sensitive to water dynamics in the unsaturated zone. ER data can be temporally and spatially robust, covering large areas or long time periods non-invasively, which is an advantage over in-situ methods. Previous studies have shown the value of using hydrogeophysical inversions to estimate soil properties. Others have used hydrological inversions to estimate both soil properties and root distribution parameters. In this study, we combine these two approaches to create a coupled hydrogeophysical inversion that estimates root and retention curve parameters for a HYDRUS model. To test the feasibility of this new approach, we estimated daily water fluxes and root growth for several biofuel crops at a long-term ecological research site in Southwest Michigan, using monthly ER data from 2009 through 2011. Time domain reflectometry data at seven depths was used to validate modeled soil moisture estimates throughout the model period. This hydrogeophysical inversion method shows promise for improving root distribution and transpiration estimates across a wide variety of settings.
Peak thrust operation of linear induction machines from parameter identification

Energy Technology Data Exchange (ETDEWEB)

Zhang, Z.; Eastham, T.R.; Dawson, G.E. [Queen`s Univ., Kingston, Ontario (Canada). Dept. of Electrical and Computer Engineering

1995-12-31

Various control strategies are being used to achieve high performance operation of linear drives. To maintain minimum volume and weight of the power supply unit on board the transportation vehicle, peak thrust per unit current operation is a desirable objective. True peak thrust per unit current through slip control is difficult to achieve because the parameters of linear induction machines vary during normal operation. This paper first develops a peak thrust per unit current control law based on the per-phase equivalent circuit for linear induction machines. The algorithm for identification of the variable parameters in induction machines is then presented. Application to an operational linear induction machine (LIM) demonstrates the utility of this algorithm. The control strategy is then simulated, based on an operational transit LIM, to show the capability of achieving true peak thrust operation for linear induction machines.
Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

Science.gov (United States)

Cui, Tiangang; Marzouk, Youssef; Willcox, Karen

2016-06-01

Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.
Inversion aided systems for stratigraphic models; Systemes d'aide a l'inversion des modeles stratigraphiques

Energy Technology Data Exchange (ETDEWEB)

Dobranszky, G.

2005-12-15

Stratigraphic modeling aims at rebuilding the history of the sedimentary basins by simulating the processes of erosion, transport and deposit of sediments using physical models. The objective is to determine the location of the bed-rocks likely to contain the organic matter, the location of the porous rocks that could trap the hydrocarbons during their migration and the location of the impermeable rocks likely to seal the reservoir. The model considered within this thesis is based on a multi-lithological diffusive transport model and applies to large scales of time and space. Due to the complexity of the phenomena and scales considered, none of the model parameters is directly measurable. Therefore it is essential to inverse them. The standard approach, which consists in inverting all the parameters by minimizing a cost function using a gradient method, proved very sensitive to the choice of the parameterization, to the weights given to the various terms of the cost function (hearing on data of very diverse nature) and to the numerical noise. These observations led us to give up this method and to carry out the in-version step by step by decoupling the parameters. This decoupling is not obtained by fixing the parameters but by making several assumptions on the model resulting in a range of reduced but relevant models. In this thesis, we show how these models enable us to inverse all the parameters in a robust and interactive way. (author)
Multi-Objective Optimization of Moving-magnet Linear Oscillatory Motor Using Response Surface Methodology with Quantum-Behaved PSO Operator

Science.gov (United States)

Lei, Meizhen; Wang, Liqiang

2018-01-01

To reduce the difficulty of manufacturing and increase the magnetic thrust density, a moving-magnet linear oscillatory motor (MMLOM) without inner-stators was Proposed. To get the optimal design of maximum electromagnetic thrust with minimal permanent magnetic material, firstly, the 3D finite element analysis (FEA) model of the MMLOM was built and verified by comparison with prototype experiment result. Then the influence of design parameters of permanent magnet (PM) on the electromagnetic thrust was systematically analyzed by the 3D FEA to get the design parameters. Secondly, response surface methodology (RSM) was employed to build the response surface model of the new MMLOM, which can obtain an analytical model of the PM volume and thrust. Then a multi-objective optimization methods for design parameters of PM, using response surface methodology (RSM) with a quantum-behaved PSO (QPSO) operator, was proposed. Then the way to choose the best design parameters of PM among the multi-objective optimization solution sets was proposed. Then the 3D FEA of the optimal design candidates was compared. The comparison results showed that the proposed method can obtain the best combination of the geometric parameters of reducing the PM volume and increasing the thrust.
Linearized inversion frameworks toward high-resolution seismic imaging

KAUST Repository

Aldawood, Ali

2016-09-01

internally multiply scattered seismic waves to obtain highly resolved images delineating vertical faults that are otherwise not easily imaged by primaries. Seismic interferometry is conventionally based on the cross-correlation and convolution of seismic traces to transform seismic data from one acquisition geometry to another. The conventional interferometric transformation yields virtual data that suffers from low temporal resolution, wavelet distortion, and correlation/convolution artifacts. I therefore incorporate a least-squares datuming technique to interferometrically transform vertical-seismic-profile surface-related multiples to surface-seismic-profile primaries. This yields redatumed data with high temporal resolution and less artifacts, which are subsequently imaged to obtain highly resolved subsurface images. Tests on synthetic examples demonstrate the efficiency of the proposed techniques, yielding highly resolved migrated sections compared with images obtained by imaging conventionally redatumed data. I further advance the recently developed cost-effective Generalized Interferometric Multiple Imaging procedure, which aims to not only image first but also higher-order multiples as well. I formulate this procedure as a linearized inversion framework and solve it as a least-squares problem. Tests of the least-squares Generalized Interferometric Multiple imaging framework on synthetic datasets and demonstrate that it could provide highly resolved migrated images and delineate vertical fault planes compared with the standard procedure. The results support the assertion that this linearized inversion framework can illuminate subsurface zones that are mainly illuminated by internally scattered energy.
An investigation on the solutions for the linear inverse problem in gamma ray tomography

International Nuclear Information System (INIS)

Araujo, Bruna G.M.; Dantas, Carlos C.; Santos, Valdemir A. dos; Finkler, Christine L.L.; Oliveira, Eric F. de; Melo, Silvio B.; Santos, M. Graca dos

2009-01-01

This paper the results obtained in single beam gamma ray tomography are investigated according to direct problem formulation and the applied solution for the linear system of equations. By image reconstruction based algebraic computational algorithms are used. The sparse under and over-determined linear system of equations was analyzed. Build in functions of Matlab software were applied and optimal solutions were investigate. Experimentally a section of the tube is scanned from various positions and at different angles. The solution, to find the vector of coefficients μ, from the vector of measured p values through the W matrix inversion, constitutes an inverse problem. A industrial tomography process requires a numerical solution of the system of equations. The definition of inverse problem according to Hadmard's is considered and as well the requirement of a well posed problem to find stable solutions. The formulation of the basis function and the computational algorithm to structure the weight matrix W were analyzed. For W full rank matrix the obtained solution is unique as expected. Total Least Squares was implemented which theory and computation algorithm gives adequate treatment for the problems due to non-unique solutions of the system of equations. Stability of the solution was investigating by means of a regularization technique and the comparison shows that it improves the results. An optimal solution as a function of the image quality, computation time and minimum residuals were quantified. The corresponding reconstructed images are shown in 3D graphics in order to compare with the solution. (author)
Estimation of semolina dough rheological parameters by inversion of a finite elements model

Directory of Open Access Journals (Sweden)

Angelo Fabbri

2015-10-01

Full Text Available The description of the rheological properties of food material plays an important role in food engineering. Particularly for the optimisation of pasta manufacturing process (extrusion is needful to know the rheological properties of semolina dough. Unfortunately characterisation of non-Newtonian fluids, such as food doughs, requires a notable time effort, especially in terms of number of tests to be carried out. The present work proposes an alternative method, based on the combination of laboratory measurement, made with a simplified tool, with the inversion of a finite elements numerical model. To determine the rheological parameters, an objective function, defined as the distance between simulation and experimental data, was considered and the well-known Levenberg-Marqard optimisation algorithm was used. In order to verify the feasibility of the method, the rheological characterisation of the dough was carried also by a traditional procedure. Results shown that the difference between measurements of rheological parameters of the semolina dough made with traditional procedure and inverse methods are very small (maximum percentage error equal to 3.6%. This agreement supports the coherence of the inverse method that, in general, may be used to characterise many non-Newtonian materials.

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and
Sharp spatially constrained inversion

DEFF Research Database (Denmark)

Vignoli, Giulio G.; Fiandaca, Gianluca G.; Christiansen, Anders Vest C A.V.C.

2013-01-01

We present sharp reconstruction of multi-layer models using a spatially constrained inversion with minimum gradient support regularization. In particular, its application to airborne electromagnetic data is discussed. Airborne surveys produce extremely large datasets, traditionally inverted...... by using smoothly varying 1D models. Smoothness is a result of the regularization constraints applied to address the inversion ill-posedness. The standard Occam-type regularized multi-layer inversion produces results where boundaries between layers are smeared. The sharp regularization overcomes...... inversions are compared against classical smooth results and available boreholes. With the focusing approach, the obtained blocky results agree with the underlying geology and allow for easier interpretation by the end-user....
On the null distribution of Bayes factors in linear regression

Science.gov (United States)

We show that under the null, the 2 log (Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and...
Parameterization analysis and inversion for orthorhombic media

KAUST Repository

Masmoudi, Nabil

2018-05-01

Accounting for azimuthal anisotropy is necessary for the processing and inversion of wide-azimuth and wide-aperture seismic data because wave speeds naturally depend on the wave propagation direction. Orthorhombic anisotropy is considered the most effective anisotropic model that approximates the azimuthal anisotropy we observe in seismic data. In the framework of full wave form inversion (FWI), the large number of parameters describing orthorhombic media exerts a considerable trade-off and increases the non-linearity of the inversion problem. Choosing a suitable parameterization for the model, and identifying which parameters in that parameterization could be well resolved, are essential to a successful inversion. In this thesis, I derive the radiation patterns for different acoustic orthorhombic parameterization. Analyzing the angular dependence of the scattering of the parameters of different parameterizations starting with the conventionally used notation, I assess the potential trade-off between the parameters and the resolution in describing the data and inverting for the parameters. In order to build practical inversion strategies, I suggest new parameters (called deviation parameters) for a new parameterization style in orthorhombic media. The novel parameters denoted ∈d, ƞd and δd are dimensionless and represent a measure of deviation between the vertical planes in orthorhombic anisotropy. The main feature of the deviation parameters consists of keeping the scattering of the vertical transversely isotropic (VTI) parameters stationary with azimuth. Using these scattering features, we can condition FWI to invert for the parameters which the data are sensitive to, at different stages, scales, and locations in the model. With this parameterization, the data are mainly sensitive to the scattering of 3 parameters (out of six that describe an acoustic orthorhombic medium): the horizontal velocity in the x1 direction, ∈1 which provides scattering mainly near
Tsunami waveform inversion by numerical finite-elements Green’s functions

Directory of Open Access Journals (Sweden)

A. Piatanesi

2001-01-01

Full Text Available During the last few years, the steady increase in the quantity and quality of the data concerning tsunamis has led to an increasing interest in the inversion problem for tsunami data. This work addresses the usually ill-posed problem of the hydrodynamical inversion of tsunami tide-gage records to infer the initial sea perturbation. We use an inversion method for which the data space consists of a given number of waveforms and the model parameter space is represented by the values of the initial water elevation field at a given number of points. The forward model, i.e. the calculation of the synthetic tide-gage records from an initial water elevation field, is based on the linear shallow water equations and is simply solved by applying the appropriate Green’s functions to the known initial state. The inversion of tide-gage records to determine the initial state results in the least square inversion of a rectangular system of linear equations. When the inversions are unconstrained, we found that in order to attain good results, the dimension of the data space has to be much larger than that of the model space parameter. We also show that a large number of waveforms is not sufficient to ensure a good inversion if the corresponding stations do not have a good azimuthal coverage with respect to source directivity. To improve the inversions we use the available a priori information on the source, generally coming from the inversion of seismological data. In this paper we show how to implement very common information about a tsunamigenic seismic source, i.e. the earthquake source region, as a set of spatial constraints. The results are very satisfactory, since even a rough localisation of the source enables us to invert correctly the initial elevation field.
Estimation of fracture parameters using elastic full-waveform inversion

KAUST Repository

Zhang, Zhendong

2017-08-17

Current methodologies to characterize fractures at the reservoir scale have serious limitations in spatial resolution and suffer from uncertainties in the inverted parameters. Here, we propose to estimate the spatial distribution and physical properties of fractures using full-waveform inversion (FWI) of multicomponent surface seismic data. An effective orthorhombic medium with five clusters of vertical fractures distributed in a checkboard fashion is used to test the algorithm. A shape regularization term is added to the objective function to improve the estimation of the fracture azimuth, which is otherwise poorly constrained. The cracks are assumed to be penny-shaped to reduce the nonuniqueness in the inverted fracture weaknesses and achieve a faster convergence. To better understand the inversion results, we analyze the radiation patterns induced by the perturbations in the fracture weaknesses and orientation. Due to the high-resolution potential of elastic FWI, the developed algorithm can recover the spatial fracture distribution and identify localized “sweet spots” of intense fracturing. However, the fracture azimuth can be resolved only using long-offset data.
Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT)

Science.gov (United States)

Xing, Lei; Li, Ruijiang

2014-03-01

The last few years have seen a number of technical and clinical advances which give rise to a need for innovations in dose optimization and delivery strategies. Technically, a new generation of digital linac has become available which offers features such as programmable motion between station parameters and high dose-rate Flattening Filter Free (FFF) beams. Current inverse planning methods are designed for traditional machines and cannot accommodate these features of new generation linacs without compromising either dose conformality and/or delivery efficiency. Furthermore, SBRT is becoming increasingly important, which elevates the need for more efficient delivery, improved dose distribution. Here we will give an overview of our recent work in SPORT designed to harness the digital linacs and highlight the essential components of SPORT. We will summarize the pros and cons of traditional beamlet-based optimization (BBO) and direct aperture optimization (DAO) and introduce a new type of algorithm, compressed sensing (CS)-based inverse planning, that is capable of automatically removing the redundant segments during optimization and providing a plan with high deliverability in the presence of a large number of station control points (potentially non-coplanar, non-isocentric, and even multi-isocenters). We show that CS-approach takes the interplay between planning and delivery into account and allows us to balance the dose optimality and delivery efficiency in a controlled way and, providing a viable framework to address various unmet demands of the new generation linacs. A few specific implementation strategies of SPORT in the forms of fixed-gantry and rotational arc delivery are also presented.
Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT)

International Nuclear Information System (INIS)

Xing, Lei; Li, Ruijiang

2014-01-01

The last few years have seen a number of technical and clinical advances which give rise to a need for innovations in dose optimization and delivery strategies. Technically, a new generation of digital linac has become available which offers features such as programmable motion between station parameters and high dose-rate Flattening Filter Free (FFF) beams. Current inverse planning methods are designed for traditional machines and cannot accommodate these features of new generation linacs without compromising either dose conformality and/or delivery efficiency. Furthermore, SBRT is becoming increasingly important, which elevates the need for more efficient delivery, improved dose distribution. Here we will give an overview of our recent work in SPORT designed to harness the digital linacs and highlight the essential components of SPORT. We will summarize the pros and cons of traditional beamlet-based optimization (BBO) and direct aperture optimization (DAO) and introduce a new type of algorithm, compressed sensing (CS)-based inverse planning, that is capable of automatically removing the redundant segments during optimization and providing a plan with high deliverability in the presence of a large number of station control points (potentially non-coplanar, non-isocentric, and even multi-isocenters). We show that CS-approach takes the interplay between planning and delivery into account and allows us to balance the dose optimality and delivery efficiency in a controlled way and, providing a viable framework to address various unmet demands of the new generation linacs. A few specific implementation strategies of SPORT in the forms of fixed-gantry and rotational arc delivery are also presented.
Multi-parameter variational calculations for the (2+1)-dimensional U(1) lattice gauge theory and the XY model

International Nuclear Information System (INIS)

Heys, D.W.; Stump, D.R.

1987-01-01

Variational calculations are described that use multi-parameter trial wave functions for the U(1) lattice gauge theory in two space dimensions, and for the XY model. The trial functions are constructed as the exponential of a linear combination of states from the strong-coupling basis of the model, with the coefficients treated as variational parameters. The expectation of the hamiltonian is computed by the Monte Carlo method, using a reweighting technique to evaluate expectation values in finite patches of the parameter space. The trial function for the U(1) gauge theory involves six variational parameters, and its weak-coupling behaviour is in reasonable agreement with theoretical expectations. (orig.)
Generalized inverses theory and computations

CERN Document Server

Wang, Guorong; Qiao, Sanzheng

2018-01-01

This book begins with the fundamentals of the generalized inverses, then moves to more advanced topics. It presents a theoretical study of the generalization of Cramer's rule, determinant representations of the generalized inverses, reverse order law of the generalized inverses of a matrix product, structures of the generalized inverses of structured matrices, parallel computation of the generalized inverses, perturbation analysis of the generalized inverses, an algorithmic study of the computational methods for the full-rank factorization of a generalized inverse, generalized singular value decomposition, imbedding method, finite method, generalized inverses of polynomial matrices, and generalized inverses of linear operators. This book is intended for researchers, postdocs, and graduate students in the area of the generalized inverses with an undergraduate-level understanding of linear algebra.
Sheared Layers in the Continental Crust: Nonlinear and Linearized inversion for Ps receiver functions

Science.gov (United States)

Park, J. J.

2017-12-01

Sheared Layers in the Continental Crust: Nonlinear and Linearized inversion for Ps receiver functions Jeffrey Park, Yale University The interpretation of seismic receiver functions (RFs) in terms of isotropic and anisotropic layered structure can be complex. The relationship between structure and body-wave scattering is nonlinear. The anisotropy can involve more parameters than the observations can readily constrain. Finally, reflectivity-predicted layer reverberations are often not prominent in data, so that nonlinear waveform inversion can search in vain to match ghost signals. Multiple-taper correlation (MTC) receiver functions have uncertainties in the frequency domain that follow Gaussian statistics [Park and Levin, 2016a], so grid-searches for the best-fitting collections of interfaces can be performed rapidly to minimize weighted misfit variance. Tests for layer-reverberations can be performed in the frequency domain without reflectivity calculations, allowing flexible modelling of weak, but nonzero, reverberations. Park and Levin [2016b] linearized the hybridization of P and S body waves in an anisotropic layer to predict first-order Ps conversion amplitudes at crust and mantle interfaces. In an anisotropic layer, the P wave acquires small SV and SH components. To ensure continuity of displacement and traction at the top and bottom boundaries of the layer, shear waves are generated. Assuming hexagonal symmetry with an arbitrary symmetry axis, theory confirms the empirical stacking trick of phase-shifting transverse RFs by 90 degrees in back-azimuth [Shiomi and Park, 2008; Schulte-Pelkum and Mahan, 2014] to enhance 2-lobed and 4-lobed harmonic variation. Ps scattering is generated by sharp interfaces, so that RFs resemble the first derivative of the model. MTC RFs in the frequency domain can be manipulated to obtain a first-order reconstruction of the layered anisotropy, under the above modeling constraints and neglecting reverberations. Examples from long
Practical waveform inversion in anisotropic media: The natural combination of the data and image objectives

KAUST Repository

Alkhalifah, Tariq Ali

2016-09-06

Addressing anisotropy in full wavenumber inversion (FWI) is crucial to obtaining credible models, and it is extremely challenging considering the multi parameter nature of the inversion. A successful FWI in anisotropic media takes into account the sensitivity of the data (or the wave) to the long and short wavelength components of the anisotropic parameters. Considering the low sensitivity of FWI to the anellipticity parameter ? when parametrizing the acoustic transversely isotropic model with the horizontal velocity, η and ε, we develop a combined FWI and reflection waveform inversion (RWI) to invert for the anisotropic parameters that influence surface seismic data. This practical waveform inversion (PWI) separates the parameters to their resolvable scales, with information accessed from the data fitting (FWI) and the image focusing (RWI) objectives. With this parametrization, the RWI role is to obtain a smooth ηmodel, as well as velocity, while FWI focusses on the scattering potential of the horizontal velocity. The parameter η is used to produce the Born scattered wavefield for the RWI part and eventually fit the amplitude for the imperfect physics in the FWI part.
Inverse Free Electron Laser accelerator

International Nuclear Information System (INIS)

Fisher, A.; Gallardo, J.; van Steenbergen, A.; Sandweiss, J.

1992-09-01

The study of the INVERSE FREE ELECTRON LASER, as a potential mode of electron acceleration, is being pursued at Brookhaven National Laboratory. Recent studies have focussed on the development of a low energy, high gradient, multi stage linear accelerator. The elementary ingredients for the IFEL interaction are the 50 MeV Linac e - beam and the 10 11 Watt CO 2 laser beam of BNL's Accelerator Test Facility (ATF), Center for Accelerator Physics (CAP) and a wiggler. The latter element is designed as a fast excitation unit making use of alternating stacks of Vanadium Permendur (VaP) ferromagnetic laminations, periodically interspersed with conductive, nonmagnetic laminations, which act as eddy current induced field reflectors. Wiggler parameters and field distribution data will be presented for a prototype wiggler in a constant period and in a ∼ 1.5 %/cm tapered period configuration. The CO 2 laser beam will be transported through the IFEL interaction region by means of a low loss, dielectric coated, rectangular waveguide. Short waveguide test sections have been constructed and have been tested using a low power cw CO 2 laser. Preliminary results of guide attenuation and mode selectivity will be given, together with a discussion of the optical issues for the IFEL accelerator. The IFEL design is supported by the development and use of 1D and 3D simulation programs. The results of simulation computations, including also wiggler errors, for a single module accelerator and for a multi-module accelerator will be presented
SU-E-J-161: Inverse Problems for Optical Parameters in Laser Induced Thermal Therapy

International Nuclear Information System (INIS)

Fahrenholtz, SJ; Stafford, RJ; Fuentes, DT

2014-01-01

Purpose: Magnetic resonance-guided laser-induced thermal therapy (MRgLITT) is investigated as a neurosurgical intervention for oncological applications throughout the body by active post market studies. Real-time MR temperature imaging is used to monitor ablative thermal delivery in the clinic. Additionally, brain MRgLITT could improve through effective planning for laser fiber's placement. Mathematical bioheat models have been extensively investigated but require reliable patient specific physical parameter data, e.g. optical parameters. This abstract applies an inverse problem algorithm to characterize optical parameter data obtained from previous MRgLITT interventions. Methods: The implemented inverse problem has three primary components: a parameter-space search algorithm, a physics model, and training data. First, the parameter-space search algorithm uses a gradient-based quasi-Newton method to optimize the effective optical attenuation coefficient, μ-eff. A parameter reduction reduces the amount of optical parameter-space the algorithm must search. Second, the physics model is a simplified bioheat model for homogeneous tissue where closed-form Green's functions represent the exact solution. Third, the training data was temperature imaging data from 23 MRgLITT oncological brain ablations (980 nm wavelength) from seven different patients. Results: To three significant figures, the descriptive statistics for μ-eff were 1470 m −1 mean, 1360 m −1 median, 369 m −1 standard deviation, 933 m −1 minimum and 2260 m −1 maximum. The standard deviation normalized by the mean was 25.0%. The inverse problem took <30 minutes to optimize all 23 datasets. Conclusion: As expected, the inferred average is biased by underlying physics model. However, the standard deviation normalized by the mean is smaller than literature values and indicates an increased precision in the characterization of the optical parameters needed to plan MRgLITT procedures. This investigation
A recipe for practical full-waveform inversion in orthorhombic anisotropy

KAUST Repository

Alkhalifah, Tariq Ali; Masmoudi, Nabil; Oh, Juwon

2016-01-01

Multi parameter full waveform inversion (FWI) usually suffers from the inherent tradeoffin the multi parameter nature of the model space. In orthorhombic anisotropy, such tradeoffis magnified by the large number of parameters involved in representing the elastic or even the acoustic approximation of such a medium. However, using a new parameterization with distinctive scattering features, we can condition FWI to invert for the parameters the data are sensitive to at different stages, scales, and locations in the model. Specifically, with a combination made up of a velocity and particular dimensionless ratios of the elastic coefficients, the scattering potential of the anisotropic parameters have stationary scattering radiation patterns as a function of the type of anisotropy. With our new parametrization, the data is mainly sensitive to the scattering potential of 4 parameters: the horizontal velocity in the x direction, x, which provides scattering mainly near zero offset in the x vertical plane, εd, which is the ratio of the horizontal velocity squared in the x and x direction, and δ3 describing the anellipticity in the horizontal plane. Since, with this parametrization, the radiation pattern for the horizontal velocity and ε is azimuth independent, we can perform an initial VTI inversion for these two parameters, and then use the other two parameters to fit the azimuth variation in the data. This can be done at the reservoir level or any region of the model. Including the transmission from reflections, the migration velocity analysis (MVA) component, into the picture, the multi azimuth surface seismic data are mainly sensitive to the long wavelength components of uh, δ3, and εd through the diving waves, and η1, ηd, and δ3, in the transmission to or from reflectors (especially, in the presence of large offsets). They are also sensitive to the short wavelength component of uh and ε.
A recipe for practical full-waveform inversion in orthorhombic anisotropy

KAUST Repository

Alkhalifah, Tariq Ali

2016-09-06

Multi parameter full waveform inversion (FWI) usually suffers from the inherent tradeoffin the multi parameter nature of the model space. In orthorhombic anisotropy, such tradeoffis magnified by the large number of parameters involved in representing the elastic or even the acoustic approximation of such a medium. However, using a new parameterization with distinctive scattering features, we can condition FWI to invert for the parameters the data are sensitive to at different stages, scales, and locations in the model. Specifically, with a combination made up of a velocity and particular dimensionless ratios of the elastic coefficients, the scattering potential of the anisotropic parameters have stationary scattering radiation patterns as a function of the type of anisotropy. With our new parametrization, the data is mainly sensitive to the scattering potential of 4 parameters: the horizontal velocity in the x direction, x, which provides scattering mainly near zero offset in the x vertical plane, εd, which is the ratio of the horizontal velocity squared in the x and x direction, and δ3 describing the anellipticity in the horizontal plane. Since, with this parametrization, the radiation pattern for the horizontal velocity and ε is azimuth independent, we can perform an initial VTI inversion for these two parameters, and then use the other two parameters to fit the azimuth variation in the data. This can be done at the reservoir level or any region of the model. Including the transmission from reflections, the migration velocity analysis (MVA) component, into the picture, the multi azimuth surface seismic data are mainly sensitive to the long wavelength components of uh, δ3, and εd through the diving waves, and η1, ηd, and δ3, in the transmission to or from reflectors (especially, in the presence of large offsets). They are also sensitive to the short wavelength component of uh and ε.
Uncertainty Estimation of Shear-wave Velocity Structure from Bayesian Inversion of Microtremor Array Dispersion Data

Science.gov (United States)

Dosso, S. E.; Molnar, S.; Cassidy, J.

2010-12-01

Bayesian inversion of microtremor array dispersion data is applied, with evaluation of data errors and model parameterization, to produce the most-probable shear-wave velocity (VS) profile together with quantitative uncertainty estimates. Generally, the most important property characterizing earthquake site response is the subsurface VS structure. The microtremor array method determines phase velocity dispersion of Rayleigh surface waves from multi-instrument recordings of urban noise. Inversion of dispersion curves for VS structure is a non-unique and nonlinear problem such that meaningful evaluation of confidence intervals is required. Quantitative uncertainty estimation requires not only a nonlinear inversion approach that samples models proportional to their probability, but also rigorous estimation of the data error statistics and an appropriate model parameterization. A Bayesian formulation represents the solution of the inverse problem in terms of the posterior probability density (PPD) of the geophysical model parameters. Markov-chain Monte Carlo methods are used with an efficient implementation of Metropolis-Hastings sampling to provide an unbiased sample from the PPD to compute parameter uncertainties and inter-relationships. Nonparametric estimation of a data error covariance matrix from residual analysis is applied with rigorous a posteriori statistical tests to validate the covariance estimate and the assumption of a Gaussian error distribution. The most appropriate model parameterization is determined using the Bayesian information criterion (BIC), which provides the simplest model consistent with the resolving power of the data. Parameter uncertainties are found to be under-estimated when data error correlations are neglected and when compressional-wave velocity and/or density (nuisance) parameters are fixed in the inversion. Bayesian inversion of microtremor array data is applied at two sites in British Columbia, the area of highest seismic risk in
Full waveform inversion using envelope-based global correlation norm

KAUST Repository

Oh, Juwon

2018-01-28

Various parameterizations have been suggested to simplify inversions of first arrivals, or P −waves, in orthorhombic anisotropic media, but the number and type of retrievable parameters have not been decisively determined. We show that only six parameters can be retrieved from the dynamic linearized inversion of P −waves. These parameters are different from the six parameters needed to describe the kinematics of P −waves. Reflection-based radiation patterns from the P − P scattered waves are remapped into the spectral domain to allow for our resolution analysis based on the effective angle of illumination concept. Singular value decomposition of the spectral sensitivities from various azimuths, offset coverage scenarios, and data bandwidths allows us to quantify the resolution of different parameterizations, taking into account the signal-to-noise ratio in a given experiment. According to our singular value analysis, when the primary goal of inversion is determining the velocity of the P −waves, gradually adding anisotropy of lower orders (isotropic, vertically transversally isotropic, orthorhombic) in hierarchical parameterization is the best choice. Hierarchical parametrization reduces the tradeoff between the parameters and makes gradual introduction of lower anisotropy orders straightforward. When all the anisotropic parameters affecting P −wave propagation need to be retrieved simultaneously, the classic parameterization of orthorhombic medium with elastic stiffness matrix coefficients and density is a better choice for inversion. We provide estimates of the number and set of parameters that can be retrieved from surface seismic data in different acquisition scenarios. To set up an inversion process, the singular values determine the number of parameters that can be inverted and the resolution matrices from the parameterizations can be used to ascertain the set of parameters that can be resolved.
Resolution enhancement of robust Bayesian pre-stack inversion in the frequency domain

Science.gov (United States)

Yin, Xingyao; Li, Kun; Zong, Zhaoyun

2016-10-01

AVO/AVA (amplitude variation with an offset or angle) inversion is one of the most practical and useful approaches to estimating model parameters. So far, publications on AVO inversion in the Fourier domain have been quite limited in view of its poor stability and sensitivity to noise compared with time-domain inversion. For the resolution and stability of AVO inversion in the Fourier domain, a novel robust Bayesian pre-stack AVO inversion based on the mixed domain formulation of stationary convolution is proposed which could solve the instability and achieve superior resolution. The Fourier operator will be integrated into the objective equation and it avoids the Fourier inverse transform in our inversion process. Furthermore, the background constraints of model parameters are taken into consideration to improve the stability and reliability of inversion which could compensate for the low-frequency components of seismic signals. Besides, the different frequency components of seismic signals can realize decoupling automatically. This will help us to solve the inverse problem by means of multi-component successive iterations and the convergence precision of the inverse problem could be improved. So, superior resolution compared with the conventional time-domain pre-stack inversion could be achieved easily. Synthetic tests illustrate that the proposed method could achieve high-resolution results with a high degree of agreement with the theoretical model and verify the quality of anti-noise. Finally, applications on a field data case demonstrate that the proposed method could obtain stable inversion results of elastic parameters from pre-stack seismic data in conformity with the real logging data.
Joint Inversion of Earthquake Source Parameters with local and teleseismic body waves

Science.gov (United States)

Chen, W.; Ni, S.; Wang, Z.

2011-12-01

In the classical source parameter inversion algorithm of CAP (Cut and Paste method, by Zhao and Helmberger), waveform data at near distances (typically less than 500km) are partitioned into Pnl and surface waves to account for uncertainties in the crustal models and different amplitude weight of body and surface waves. The classical CAP algorithms have proven effective for resolving source parameters (focal mechanisms, depth and moment) for earthquakes well recorded on relatively dense seismic network. However for regions covered with sparse stations, it is challenging to achieve precise source parameters . In this case, a moderate earthquake of ~M6 is usually recorded on only one or two local stations with epicentral distances less than 500 km. Fortunately, an earthquake of ~M6 can be well recorded on global seismic networks. Since the ray paths for teleseismic and local body waves sample different portions of the focal sphere, combination of teleseismic and local body wave data helps constrain source parameters better. Here we present a new CAP mothod (CAPjoint), which emploits both teleseismic body waveforms (P and SH waves) and local waveforms (Pnl, Rayleigh and Love waves) to determine source parameters. For an earthquake in Nevada that is well recorded with dense local network (USArray stations), we compare the results from CAPjoint with those from the traditional CAP method involving only of local waveforms , and explore the efficiency with bootstraping statistics to prove the results derived by CAPjoint are stable and reliable. Even with one local station included in joint inversion, accuracy of source parameters such as moment and strike can be much better improved.

Stratigraphic inversion of pre-stack multicomponent data; Inversion stratigraphique multicomposante avant sommation

Energy Technology Data Exchange (ETDEWEB)

Agullo, Y.

2005-09-15

This thesis present the extension of mono-component seismic pre-stack data stratigraphical inversion method to multicomponent data, with the objective of improving the determination of reservoir elastic parameters. In addiction to the PP pressure waves, the PS converted waves proved their interest for imaging under gas clouds; and their potential is highly significant for the characterization of lithologies, fluids, fractures... Nevertheless the simultaneous use ol PP and PS data remains problematic because of their different the time scales. To jointly use the information contained in PP and PS data, we propose a method in three steps first, mono-component stratigraphic inversions of PP then PS data; second, estimation of the PP to PS time conversion law; third, multicomponent stratigraphic inversion. For the second point, the estimation of the PP to PS conversion law is based on minimizing the difference between the S impedances obtained from PP and PS mono-component stratigraphic inversion. The pre-stack mono-component stratigraphic inversions was adapted to the case of multicomponent data by leaving each type of data in its own time scale in order to avoid the distortion of the seismic wavelet. The results obtained on a realistic synthetic PP-PS case show on one hand that determining PP to PS conversion law (from the mono-component inversion results) is feasible, and on the other hand that the joint inversion of PP and PS data with this conversion law improves the results compared to the mono-component inversion ones. Although this is presented within the framework of the PP and PS multi-component data, the developed methodology adapts directly to PP and SS data for example. (author)
Clustered iterative stochastic ensemble method for multi-modal calibration of subsurface flow models

KAUST Repository

Elsheikh, Ahmed H.

2013-05-01

A novel multi-modal parameter estimation algorithm is introduced. Parameter estimation is an ill-posed inverse problem that might admit many different solutions. This is attributed to the limited amount of measured data used to constrain the inverse problem. The proposed multi-modal model calibration algorithm uses an iterative stochastic ensemble method (ISEM) for parameter estimation. ISEM employs an ensemble of directional derivatives within a Gauss-Newton iteration for nonlinear parameter estimation. ISEM is augmented with a clustering step based on k-means algorithm to form sub-ensembles. These sub-ensembles are used to explore different parts of the search space. Clusters are updated at regular intervals of the algorithm to allow merging of close clusters approaching the same local minima. Numerical testing demonstrates the potential of the proposed algorithm in dealing with multi-modal nonlinear parameter estimation for subsurface flow models. © 2013 Elsevier B.V.
Determination of beam characteristic parameters for a linear accelerator

International Nuclear Information System (INIS)

Lima, D.A. de.

1978-01-01

A mechanism to determine electron beam characteristic parameters of a linear accelerator was constructed. The mechanism consists in an electro-calorimeter and an accurate optical densitometer. The following parameters: mean power, mean current, mean energy/particle, pulse Width, pulse amplitude dispersion, and pulse frequency, operating the 2 MeV linear accelerator of CBPF (Brazilian Center pf Physics Researches). The optical isodensity curves of irradiated glass lamellae were obtained, providing information about focus degradation penetration direction in material and the reach of particle. The point to point dose distribution in the material from optical density curves were obtained, using a semi empirical and approached model. (M.C.K.) [pt
Estimation of G-renewal process parameters as an ill-posed inverse problem

International Nuclear Information System (INIS)

Krivtsov, V.; Yevkin, O.

2013-01-01

Statistical estimation of G-renewal process parameters is an important estimation problem, which has been considered by many authors. We view this problem from the standpoint of a mathematically ill-posed, inverse problem (the solution is not unique and/or is sensitive to statistical error) and propose a regularization approach specifically suited to the G-renewal process. Regardless of the estimation method, the respective objective function usually involves parameters of the underlying life-time distribution and simultaneously the restoration parameter. In this paper, we propose to regularize the problem by decoupling the estimation of the aforementioned parameters. Using a simulation study, we show that the resulting estimation/extrapolation accuracy of the proposed method is considerably higher than that of the existing methods
Concept for a solid-state multi-parameter sensor system for cell-culture monitoring

International Nuclear Information System (INIS)

Baecker, M.; Beging, S.; Biselli, M.; Poghossian, A.; Wang, J.; Zang, W.; Wagner, P.; Schoening, M.J.

2009-01-01

In this study, a concept for a silicon-based modular solid-state sensor system for inline multi-parameter monitoring of cell-culture fermentation processes is presented. The envisaged multi-parameter sensor system consists of two identical sensor modules and is intended for continuous quantification of up to five (bio-)chemical and physical parameters, namely, glucose and glutamine concentration, pH value, electrolyte conductivity and temperature by applying different transducer principles and/or different operation modes. Experimental results for the field-effect electrolyte-insulator-semiconductor (EIS) sterilisable pH sensor and electrolyte conductivity sensor based on interdigitated electrodes are presented. The ongoing autoclaving does not have any significant impact on the pH-sensitive properties of a Ta 2 O 5 -gate EIS sensor. Even after 30 autoclaving cycles, the pH sensors show a clear pH response and nearly linear calibration curve with a slope of 57 ± 1 mV/pH. Additional scanning electron microscopy and ellipsometric investigations do not show any visible surface degradation or changes in the thickness of the pH-sensitive Ta 2 O 5 layer. The preliminary results demonstrate the suitability of the developed EIS sensor for an inline pH measurement during a fermentation process. In addition, interdigitated electrodes of different geometries serving as electrolyte conductivity sensor have been tested for measurements in relatively high ionic-strength solutions.
Multi-parameter CAMAC compatible ADC scanner

Energy Technology Data Exchange (ETDEWEB)

Midttun, G J; Ingebretsen, F [Oslo Univ. (Norway). Fysisk Inst.; Johnsen, P J [Norsk Data A.S., Box 163, Oekern, Oslo 5, Norway

1979-02-15

A fast ADC scanner for multi-parameter nuclear physics experiments is described. The scanner is based on a standard CAMAC crate, and data from several different experiments can be handled simultaneously through a direct memory access (DMA) channel. The implementation on a PDP-7 computer is outlined.
The linearized inversion of the generalized interferometric multiple imaging

KAUST Repository

Aldawood, Ali

2016-09-06

The generalized interferometric multiple imaging (GIMI) procedure can be used to image duplex waves and other higher order internal multiples. Imaging duplex waves could help illuminate subsurface zones that are not easily illuminated by primaries such as vertical and nearly vertical fault planes, and salt flanks. To image first-order internal multiple, the GIMI framework consists of three datuming steps, followed by applying the zero-lag cross-correlation imaging condition. However, the standard GIMI procedure yields migrated images that suffer from low spatial resolution, migration artifacts, and cross-talk noise. To alleviate these problems, we propose a least-squares GIMI framework in which we formulate the first two steps as a linearized inversion problem when imaging first-order internal multiples. Tests on synthetic datasets demonstrate the ability to localize subsurface scatterers in their true positions, and delineate a vertical fault plane using the proposed method. We, also, demonstrate the robustness of the proposed framework when imaging the scatterers or the vertical fault plane with erroneous migration velocities.
A procedure for multi-objective optimization of tire design parameters

Directory of Open Access Journals (Sweden)

Nikola Korunović

2015-04-01

Full Text Available The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method.
Some Properties of Multiple Parameters Linear Programming

Directory of Open Access Journals (Sweden)

Maoqin Li

2010-01-01

Full Text Available We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function f can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of f at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.
Some Properties of Multiple Parameters Linear Programming

Directory of Open Access Journals (Sweden)

Yan Hong

2010-01-01

Full Text Available Abstract We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.
Parameter Scaling in Non-Linear Microwave Tomography

DEFF Research Database (Denmark)

Jensen, Peter Damsgaard; Rubæk, Tonny; Talcoth, Oskar

2012-01-01

Non-linear microwave tomographic imaging of the breast is a challenging computational problem. The breast is heterogeneous and contains several high-contrast and lossy regions, resulting in large differences in the measured signal levels. This implies that special care must be taken when the imag......Non-linear microwave tomographic imaging of the breast is a challenging computational problem. The breast is heterogeneous and contains several high-contrast and lossy regions, resulting in large differences in the measured signal levels. This implies that special care must be taken when...... the imaging problem is formulated. Under such conditions, microwave imaging systems will most often be considerably more sensitive to changes in the electromagnetic properties in certain regions of the breast. The result is that the parameters might not be reconstructed correctly in the less sensitive regions...... introduced as a measure of the sensitivity. The scaling of the parameters is shown to improve performance of the microwave imaging system when applied to reconstruction of images from 2-D simulated data and measurement data....
On the preservation of single- and multi-bunch emittance in linear accelerators

International Nuclear Information System (INIS)

Drevlak, M.

1995-11-01

This document is concentrated on the investigation of the dynamics of a particle beam in a linear accelerator. We numerically simulate a number of effects and evaluate the severity of their impact on the beam. Furthermore, we examine the applicability of several correction techniques aiming at the suppression or correction of the effects diluting the beam emittance. First, there is the issue of single-bunch dynamics : we see that wake field effects and dispersive errors can cause a significant emittance growth. Secondly, long range dipole wakes and dispersive effects arising from the energy spread between different bunches will cause relative offsets between the individual bunches and likewise result in emittance growth. Finally, we observe interactions between the single-bunch and multi-bunch dynamics in a bunch train, which further aggravate these effects. The corrective measures against emittance growth are first tested with respect to individual effects relating to issues of single- or multi-bunch dynamics. Later, these different correction techniques are joined to one machine tuning procedure that will be applied in order to achieve good emittance preservation for operation of the accelerator with a full beam consisting of the full number of bunches. The performance of this procedure is tested in simulations of the combined single- and multi-bunch dynamics. Finally, tolerances on the machine alignment as well as machine and beam parameters are established. (orig.)
Asymptotic behavior of solutions of linear multi-order fractional differential equation systems

OpenAIRE

Diethelm, Kai; Siegmund, Stefan; Tuan, H. T.

2017-01-01

In this paper, we investigate some aspects of the qualitative theory for multi-order fractional differential equation systems. First, we obtain a fundamental result on the existence and uniqueness for multi-order fractional differential equation systems. Next, a representation of solutions of homogeneous linear multi-order fractional differential equation systems in series form is provided. Finally, we give characteristics regarding the asymptotic behavior of solutions to some classes of line...
Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

Energy Technology Data Exchange (ETDEWEB)

Thimmisetty, Charanraj A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; Zhao, Wenju [Florida State Univ., Tallahassee, FL (United States). Dept. of Scientific Computing; Chen, Xiao [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; Tong, Charles H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; White, Joshua A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Atmospheric, Earth and Energy Division

2017-10-18

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even when gradient information can be computed efficiently. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this paper, we propose a novel Bayesian stochastic inversion methodology, which is characterized by a tight coupling between the gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). This approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated parameter space. In addition, non-Gaussian posterior distributions are estimated via an efficient LMCMC method on the projected low-dimensional feature space. We will demonstrate this computational framework by integrating and adapting our recent data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to a linear elasticity model.
Azimuthal Seismic Amplitude Variation with Offset and Azimuth Inversion in Weakly Anisotropic Media with Orthorhombic Symmetry

Science.gov (United States)

Pan, Xinpeng; Zhang, Guangzhi; Yin, Xingyao

2018-01-01

Seismic amplitude variation with offset and azimuth (AVOaz) inversion is well known as a popular and pragmatic tool utilized to estimate fracture parameters. A single set of vertical fractures aligned along a preferred horizontal direction embedded in a horizontally layered medium can be considered as an effective long-wavelength orthorhombic medium. Estimation of Thomsen's weak-anisotropy (WA) parameters and fracture weaknesses plays an important role in characterizing the orthorhombic anisotropy in a weakly anisotropic medium. Our goal is to demonstrate an orthorhombic anisotropic AVOaz inversion approach to describe the orthorhombic anisotropy utilizing the observable wide-azimuth seismic reflection data in a fractured reservoir with the assumption of orthorhombic symmetry. Combining Thomsen's WA theory and linear-slip model, we first derive a perturbation in stiffness matrix of a weakly anisotropic medium with orthorhombic symmetry under the assumption of small WA parameters and fracture weaknesses. Using the perturbation matrix and scattering function, we then derive an expression for linearized PP-wave reflection coefficient in terms of P- and S-wave moduli, density, Thomsen's WA parameters, and fracture weaknesses in such an orthorhombic medium, which avoids the complicated nonlinear relationship between the orthorhombic anisotropy and azimuthal seismic reflection data. Incorporating azimuthal seismic data and Bayesian inversion theory, the maximum a posteriori solutions of Thomsen's WA parameters and fracture weaknesses in a weakly anisotropic medium with orthorhombic symmetry are reasonably estimated with the constraints of Cauchy a priori probability distribution and smooth initial models of model parameters to enhance the inversion resolution and the nonlinear iteratively reweighted least squares strategy. The synthetic examples containing a moderate noise demonstrate the feasibility of the derived orthorhombic anisotropic AVOaz inversion method, and the
A study of operating parameters on the linear spark ignition engine

International Nuclear Information System (INIS)

Lim, Ocktaeck; Hung, Nguyen Ba; Oh, Seokyoung; Kim, Gangchul; Song, Hanho; Iida, Norimasa

2015-01-01

Highlights: • An experimental and simulation study of a linear engine is conducted. • The effects of operating parameters on the generating power are investigated. • The air gap length has a significant influence on the generating power. • The generating power of the linear engine is optimized with the value of 111.3 W. • There are no problems for the linear engine after 100 h of durable test. - Abstract: In this paper, we present our experiment and simulation study of a free piston linear engine based on operating conditions and structure of the linear engine for generating electric power. The free piston linear engine includes a two-stroke free piston engine, linear generators, and compressors. In the experimental study, the effects of key parameters such as input caloric value, equivalence ratio, spark timing delay, electrical resistance, and air gap length on the piston dynamics and electric power output are investigated. Propane is used as a fuel in the free piston linear engine, and it is premixed with the air to make a homogeneous charge before go into the cylinder. The air and fuel mass flow rate are varied by a mass flow controller. The experimental results show that the maximum generating power is found with the value of 111 W at the input caloric value of 5.88 kJ/s, spark timing delay of 1.5 ms, equivalence ratio of 1.0, electric resistance of 30 Ω, and air gap length of 1.0 mm. In order to check the durability of the linear engine, a durable test is conducted during 100 h. The experimental results show that there are no problems for the linear engine after about one hundred hours of the durable test. Beside experimental study, a simulation study is conducted to predict operating behavior of the linear engine. In the simulation study, the two-stroke free piston linear engine is modeled and simulated through a combination of three mathematical models including a dynamic model, a linear alternator model and a thermodynamic model. These
Multi-objective thermodynamic optimization of combined Brayton and inverse Brayton cycles using genetic algorithms

International Nuclear Information System (INIS)

Besarati, S.M.; Atashkari, K.; Jamali, A.; Hajiloo, A.; Nariman-zadeh, N.

2010-01-01

This paper presents a simultaneous optimization study of two outputs performance of a previously proposed combined Brayton and inverse Brayton cycles. It has been carried out by varying the upper cycle pressure ratio, the expansion pressure of the bottom cycle and using variable, above atmospheric, bottom cycle inlet pressure. Multi-objective genetic algorithms are used for Pareto approach optimization of the cycle outputs. The two important conflicting thermodynamic objectives that have been considered in this work are net specific work (w s ) and thermal efficiency (η th ). It is shown that some interesting features among optimal objective functions and decision variables involved in the Baryton and inverse Brayton cycles can be discovered consequently.
Research on Joint Parameter Inversion for an Integrated Underground Displacement 3D Measuring Sensor

Directory of Open Access Journals (Sweden)

Nanying Shentu

2015-04-01

Full Text Available Underground displacement monitoring is a key means to monitor and evaluate geological disasters and geotechnical projects. There exist few practical instruments able to monitor subsurface horizontal and vertical displacements simultaneously due to monitoring invisibility and complexity. A novel underground displacement 3D measuring sensor had been proposed in our previous studies, and great efforts have been taken in the basic theoretical research of underground displacement sensing and measuring characteristics by virtue of modeling, simulation and experiments. This paper presents an innovative underground displacement joint inversion method by mixing a specific forward modeling approach with an approximate optimization inversion procedure. It can realize a joint inversion of underground horizontal displacement and vertical displacement for the proposed 3D sensor. Comparative studies have been conducted between the measured and inversed parameters of underground horizontal and vertical displacements under a variety of experimental and inverse conditions. The results showed that when experimentally measured horizontal displacements and vertical displacements are both varied within 0 ~ 30 mm, horizontal displacement and vertical displacement inversion discrepancies are generally less than 3 mm and 1 mm, respectively, under three kinds of simulated underground displacement monitoring circumstances. This implies that our proposed underground displacement joint inversion method is robust and efficient to predict the measuring values of underground horizontal and vertical displacements for the proposed sensor.
Application of optical deformation analysis system on wedge splitting test and its inverse analysis

DEFF Research Database (Denmark)

Skocek, Jan; Stang, Henrik

2010-01-01

. Results of the inverse analysis are compared with traditional inverse analysis based on clip gauge data. Then the optically measured crack profile and crack tip position are compared with predictions done by the non-linear hinge model and a finite element analysis. It is shown that the inverse analysis...... based on the optically measured data can provide material parameters of the fictitious crack model matching favorably those obtained by classical inverse analysis based on the clip gauge data. Further advantages of using of the optical deformation analysis lie in identification of such effects...
Waveform inversion for orthorhombic anisotropy with P-waves: feasibility & resolution

KAUST Repository

Kazei, Vladimir

2018-01-27

Various parameterizations have been suggested to simplify inversions of first arrivals, or P −waves, in orthorhombic anisotropic media, but the number and type of retrievable parameters have not been decisively determined. We show that only six parameters can be retrieved from the dynamic linearized inversion of P −waves. These parameters are different from the six parameters needed to describe the kinematics of P −waves. Reflection-based radiation patterns from the P − P scattered waves are remapped into the spectral domain to allow for our resolution analysis based on the effective angle of illumination concept. Singular value decomposition of the spectral sensitivities from various azimuths, offset coverage scenarios, and data bandwidths allows us to quantify the resolution of different parameterizations, taking into account the signal-to-noise ratio in a given experiment. According to our singular value analysis, when the primary goal of inversion is determining the velocity of the P −waves, gradually adding anisotropy of lower orders (isotropic, vertically transversally isotropic, orthorhombic) in hierarchical parameterization is the best choice. Hierarchical parametrization reduces the tradeoff between the parameters and makes gradual introduction of lower anisotropy orders straightforward. When all the anisotropic parameters affecting P −wave propagation need to be retrieved simultaneously, the classic parameterization of orthorhombic medium with elastic stiffness matrix coefficients and density is a better choice for inversion. We provide estimates of the number and set of parameters that can be retrieved from surface seismic data in different acquisition scenarios. To set up an inversion process, the singular values determine the number of parameters that can be inverted and the resolution matrices from the parameterizations can be used to ascertain the set of parameters that can be resolved.

Inversion of the Jacobi-Porstendorfer room model for the radon progeny

International Nuclear Information System (INIS)

Thomas, J.; Jilek, K.; Brabec, M.

2010-01-01

The Jacobi-Porstendoerfer (J-P) room model describes the behaviour of radon progeny in the atmosphere of a room. It distinguishes between free and attached radon progeny in air. It has been successfully used without substantial changes for nearly 40 years. There have been several attempts to invert the model approximately to determine the parameters describing the physical processes. Here, an exact solution is aimed at as an algebraic inversion of the system of six linear equations for the five unknown physical parameters k, X, R, q f , q a of the room model. Two strong linear dependencies in this system, unfortunately do not allow to obtain a general solution (especially not for the ventilation coefficient k), but only a parameterized one or for reduced sets of unknown parameters. More, the impossibility to eliminate one of the two linear dependencies and the departures of the measured concentrations forces to solve a set of allowed combinations of equations of the algebraic system and to accept its mean values (therefore with variances) as a result of the algebraic inversion. These results are in agreement with results of the least squares method as well as of a sophisticated modern statistical approach. The algebraic approach provides, of course, a lot of analytical relations to study the mutual dependencies between the model parameters and the measurable quantities. (authors)
Parameters of the SLAC Next Linear Collider

International Nuclear Information System (INIS)

Raubenheimer, T.; Adolphsen, C.; Burke, D.

1995-05-01

In this paper, the authors present the parameters and layout of the Next Linear Collider (NLC). The NLC is the SLAC design of a future linear collider using X-band RF technology in the main linacs. The collider would have an initial center-of-mass energy of 0.5 TeV which would be upgraded to 1 TeV and then 1.5 TeV in two stages. The design luminosity is > 5 x 10 33 cm -2 sec -1 at 0.5 TeV and > 10 34 cm -2 sec -1 at 1.0 and 1.5 TeV. They briefly describe the components of the collider and the proposed energy upgrade scenario
A procedure for multi-objective optimization of tire design parameters

OpenAIRE

Nikola Korunović; Miloš Madić; Miroslav Trajanović; Miroslav Radovanović

2015-01-01

The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zo...
Plasma diagnostics by Abel inversion in hyperbolic geometry

International Nuclear Information System (INIS)

Alhasi, A.S.; Elliott, J.A.

1992-01-01

Plasma confined in the UMIST linear quadrupole adopts a configuration with approximately hyperbolic symmetry. The normal diagnostic is a Langmuir probe, but we have developed an alternative method using optical emission tomography based upon an analytic Abel inversion. Plasma radiance is obtained as a function of a parameter identifying magnetic flux surfaces. The inversion algorithm has been tested using artificial data. Experimentally, the results show that ionizing collisions cause the confined plasma distribution to broaden as the plasma travels through the confining field. This is shown to be a consequence of the approximate incompressibility of the E x B flow. (author)
Stability margin of linear systems with parameters described by fuzzy numbers.

Science.gov (United States)

Husek, Petr

2011-10-01

This paper deals with the linear systems with uncertain parameters described by fuzzy numbers. The problem of determining the stability margin of those systems with linear affine dependence of the coefficients of a characteristic polynomial on system parameters is studied. Fuzzy numbers describing the system parameters are allowed to be characterized by arbitrary nonsymmetric membership functions. An elegant solution, graphical in nature, based on generalization of the Tsypkin-Polyak plot is presented. The advantage of the presented approach over the classical robust concept is demonstrated on a control of the Fiat Dedra engine model and a control of the quarter car suspension model.
Electrochemical parameters of ethamsylate at multi-walled carbon nanotube modified glassy carbon electrodes.

Science.gov (United States)

Wang, Sheng-Fu; Xu, Qiao

2007-05-01

In this paper, some electrochemical parameters of ethamsylate at a multi-walled carbon nanotube modified glassy carbon electrode, such as the charge number, exchange current density, standard heterogeneous rate constant and diffusion coefficient, were measured by cyclic voltammetry, chronoamperometry and chronocoulometry. The modified electrode exhibits good promotion of the electrochemical reaction of ethamsylate and increases the standard heterogeneous rate constant of ethamsylate greatly. The differential pulse voltammetry responses of ethamsylate were linearly dependent on its concentrations in a range from 2.0 x 10(-6) to 6.0 x 10(-5) mol L(-1), with a detection limit of 4.0 x 10(-7) mol L(-1).
Born reflection kernel analysis and wave-equation reflection traveltime inversion in elastic media

KAUST Repository

Wang, Tengfei

2017-08-17

Elastic reflection waveform inversion (ERWI) utilize the reflections to update the low and intermediate wavenumbers in the deeper part of model. However, ERWI suffers from the cycle-skipping problem due to the objective function of waveform residual. Since traveltime information relates to the background model more linearly, we use the traveltime residuals as objective function to update background velocity model using wave equation reflected traveltime inversion (WERTI). The reflection kernel analysis shows that mode decomposition can suppress the artifacts in gradient calculation. We design a two-step inversion strategy, in which PP reflections are firstly used to invert P wave velocity (Vp), followed by S wave velocity (Vs) inversion with PS reflections. P/S separation of multi-component seismograms and spatial wave mode decomposition can reduce the nonlinearity of inversion effectively by selecting suitable P or S wave subsets for hierarchical inversion. Numerical example of Sigsbee2A model validates the effectiveness of the algorithms and strategies for elastic WERTI (E-WERTI).
Research on Parameter Design of Multi - axis Hydrostatic Transmission Vehicle

Directory of Open Access Journals (Sweden)

Zhao Liang

2017-01-01

Full Text Available In order to obtain reasonable parameters in the design of driving system of multi-axis hydrostatic transmission vehicle, the working principle of single-side drive of hydrostatic transmission vehicle is introduced. The matching and control of engine and hydraulic pump are analyzed. According to the driving equation of vehicle, The driving force required for driving system is determined, and the parameters of hydraulic motor, hydraulic pump, system working pressure and braking system are designed and calculated, which provides the parameter design for driving system of multi-axis hydrostatic transmission Reliable theoretical basis.
Measuring the linear and nonlinear elastic properties of brain tissue with shear waves and inverse analysis.

Science.gov (United States)

Jiang, Yi; Li, Guoyang; Qian, Lin-Xue; Liang, Si; Destrade, Michel; Cao, Yanping

2015-10-01

We use supersonic shear wave imaging (SSI) technique to measure not only the linear but also the nonlinear elastic properties of brain matter. Here, we tested six porcine brains ex vivo and measured the velocities of the plane shear waves induced by acoustic radiation force at different states of pre-deformation when the ultrasonic probe is pushed into the soft tissue. We relied on an inverse method based on the theory governing the propagation of small-amplitude acoustic waves in deformed solids to interpret the experimental data. We found that, depending on the subjects, the resulting initial shear modulus [Formula: see text] varies from 1.8 to 3.2 kPa, the stiffening parameter [Formula: see text] of the hyperelastic Demiray-Fung model from 0.13 to 0.73, and the third- [Formula: see text] and fourth-order [Formula: see text] constants of weakly nonlinear elasticity from [Formula: see text]1.3 to [Formula: see text]20.6 kPa and from 3.1 to 8.7 kPa, respectively. Paired [Formula: see text] test performed on the experimental results of the left and right lobes of the brain shows no significant difference. These values are in line with those reported in the literature on brain tissue, indicating that the SSI method, combined to the inverse analysis, is an efficient and powerful tool for the mechanical characterization of brain tissue, which is of great importance for computer simulation of traumatic brain injury and virtual neurosurgery.
Estimating kinetic mechanisms with prior knowledge I: Linear parameter constraints.

Science.gov (United States)

Salari, Autoosa; Navarro, Marco A; Milescu, Mirela; Milescu, Lorin S

2018-02-05

To understand how ion channels and other proteins function at the molecular and cellular levels, one must decrypt their kinetic mechanisms. Sophisticated algorithms have been developed that can be used to extract kinetic parameters from a variety of experimental data types. However, formulating models that not only explain new data, but are also consistent with existing knowledge, remains a challenge. Here, we present a two-part study describing a mathematical and computational formalism that can be used to enforce prior knowledge into the model using constraints. In this first part, we focus on constraints that enforce explicit linear relationships involving rate constants or other model parameters. We develop a simple, linear algebra-based transformation that can be applied to enforce many types of model properties and assumptions, such as microscopic reversibility, allosteric gating, and equality and inequality parameter relationships. This transformation converts the set of linearly interdependent model parameters into a reduced set of independent parameters, which can be passed to an automated search engine for model optimization. In the companion article, we introduce a complementary method that can be used to enforce arbitrary parameter relationships and any constraints that quantify the behavior of the model under certain conditions. The procedures described in this study can, in principle, be coupled to any of the existing methods for solving molecular kinetics for ion channels or other proteins. These concepts can be used not only to enforce existing knowledge but also to formulate and test new hypotheses. © 2018 Salari et al.
Linear Parameter Varying Versus Linear Time Invariant Reduced Order Controller Design of Turboprop Aircraft Dynamics

Directory of Open Access Journals (Sweden)

Widowati

2012-07-01

Full Text Available The applicability of parameter varying reduced order controllers to aircraft model is proposed. The generalization of the balanced singular perturbation method of linear time invariant (LTI system is used to reduce the order of linear parameter varying (LPV system. Based on the reduced order model the low-order LPV controller is designed by using synthesis technique. The performance of the reduced order controller is examined by applying it to lateral-directional control of aircraft model having 20th order. Furthermore, the time responses of the closed loop system with reduced order LPV controllers and reduced order LTI controller is compared. From the simulation results, the 8th order LPV controller can maintain stability and to provide the same level of closed-loop systems performance as the full-order LPV controller. It is different with the reduced-order LTI controller that cannot maintain stability and performance for all allowable parameter trajectories.
Control of multi-machine using adaptive fuzzy

Directory of Open Access Journals (Sweden)

Bouchiba Bousmaha

2011-01-01

Full Text Available An indirect Adaptive fuzzy excitation control (IAFLC of power systems based on multi-input-multi-output linearization technique is developed in this paper. The power system considered in this paper consists of two generators and infinite bus connected through a network of transformers and transmission lines. The fuzzy controller is constructed from fuzzy feedback linearization controller whose parameters are adjusted indirectly from the estimates of plant parameters. The adaptation law adjusts the controller parameters on-line so that the plant output tracks the reference model output. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system.
Filtering techniques for efficient inversion of two-dimensional Nuclear Magnetic Resonance data

Science.gov (United States)

Bortolotti, V.; Brizi, L.; Fantazzini, P.; Landi, G.; Zama, F.

2017-10-01

The inversion of two-dimensional Nuclear Magnetic Resonance (NMR) data requires the solution of a first kind Fredholm integral equation with a two-dimensional tensor product kernel and lower bound constraints. For the solution of this ill-posed inverse problem, the recently presented 2DUPEN algorithm [V. Bortolotti et al., Inverse Problems, 33(1), 2016] uses multiparameter Tikhonov regularization with automatic choice of the regularization parameters. In this work, I2DUPEN, an improved version of 2DUPEN that implements Mean Windowing and Singular Value Decomposition filters, is deeply tested. The reconstruction problem with filtered data is formulated as a compressed weighted least squares problem with multi-parameter Tikhonov regularization. Results on synthetic and real 2D NMR data are presented with the main purpose to deeper analyze the separate and combined effects of these filtering techniques on the reconstructed 2D distribution.
Interdependence of parameters for TeV linear colliders

International Nuclear Information System (INIS)

Palmer, R.B.

1987-01-01

Approximate formulae for many of the relations governing the design of linear colliders are gathered together in this review. Expressions are discussed under the following headings: damping ring, acceleration, emittance preservation, final focus, interaction point and beamstrahlung. Using these formulae a consistent parameter set is derived
An analysis of the electromagnetic field in multi-polar linear induction system

International Nuclear Information System (INIS)

Chervenkova, Todorka; Chervenkov, Atanas

2002-01-01

In this paper a new method for determination of the electromagnetic field vectors in a multi-polar linear induction system (LIS) is described. The analysis of the electromagnetic field has been done by four dimensional electromagnetic potentials in conjunction with theory of the magnetic loops . The electromagnetic field vectors are determined in the Minkovski's space as elements of the Maxwell's tensor. The results obtained are compared with those got from the analysis made by the finite elements method (FEM).With the method represented in this paper one can determine the electromagnetic field vectors in the multi-polar linear induction system using four-dimensional potential. A priority of this method is the obtaining of analytical results for the electromagnetic field vectors. These results are also valid for linear media. The dependencies are valid also at high speeds of movement. The results of the investigated linear induction system are comparable to those got by the finite elements method. The investigations may be continued in the determination of other characteristics such as drag force, levitation force, etc. The method proposed in this paper for an analysis of linear induction system can be used for optimization calculations. (Author)
The numerical solution of linear multi-term fractional differential equations: systems of equations

Science.gov (United States)

Edwards, John T.; Ford, Neville J.; Simpson, A. Charles

2002-11-01

In this paper, we show how the numerical approximation of the solution of a linear multi-term fractional differential equation can be calculated by reduction of the problem to a system of ordinary and fractional differential equations each of order at most unity. We begin by showing how our method applies to a simple class of problems and we give a convergence result. We solve the Bagley Torvik equation as an example. We show how the method can be applied to a general linear multi-term equation and give two further examples.
Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models

Science.gov (United States)

Butler, T.; Graham, L.; Estep, D.; Dawson, C.; Westerink, J. J.

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.
Semi-Inversion of Functional Parameters

DEFF Research Database (Denmark)

Mogensen, Torben Ægidius

2008-01-01

Semi-invertering er en generalisering af invertering: Et programs semi-inverse tager nogle af dets inddata og nogen af dets uddata og returnerer de resterende ind- og uddata. Tidligere arbejder har beskrevet semi-invertering af et førsteordens funktionssprog. Vi udvider nu med funktionelle...
Impact reduction of the uncertain geometrical parameters on magnetic material identification of an EI electromagnetic inductor using an adaptive inverse algorithm

International Nuclear Information System (INIS)

Abdallh, A.; Crevecoeur, G.; Dupré, L.

2012-01-01

The magnetic characteristics of the electromagnetic devices' core materials can be recovered by solving an inverse problem, where sets of measurements need to be properly interpreted using a forward numerical model of the device. However, the uncertainties of the geometrical parameter values in the forward model lead to appreciable recovery errors in the recovered values of the material parameters. In this paper, we propose an effective inverse approach technique, in which the influences of the uncertainties in the geometrical model parameters are minimized. In this proposed approach, the cost function that needs to be minimized is adapted with respect to the uncertain geometrical model parameters. The proposed methodology is applied onto the identification of the magnetizing B–H curve of the magnetic material of an EI core inductor. The numerical results show a significant reduction of the recovery errors in the identified magnetic material parameter values. Moreover, the proposed methodology is validated by solving an inverse problem starting from real magnetic measurements. - Highlights: ► A new method to minimize the influence of the uncertain parameters in inverse problems is proposed. ► The technique is based on adapting iteratively the objective function that needs to be minimized. ► The objective function is adapted by the model response sensitivity to the uncertain parameters. ► The proposed technique is applied for recovering the B–H curve of an EI core inductor material. ► The error in the inverse problem solution is dramatically reduced using the proposed methodology.
Predicting minimum uncertainties in the inversion of ocean color geophysical parameters based on Cramer-Rao bounds.

Science.gov (United States)

Jay, Sylvain; Guillaume, Mireille; Chami, Malik; Minghelli, Audrey; Deville, Yannick; Lafrance, Bruno; Serfaty, Véronique

2018-01-22

We present an analytical approach based on Cramer-Rao Bounds (CRBs) to investigate the uncertainties in estimated ocean color parameters resulting from the propagation of uncertainties in the bio-optical reflectance modeling through the inversion process. Based on given bio-optical and noise probabilistic models, CRBs can be computed efficiently for any set of ocean color parameters and any sensor configuration, directly providing the minimum estimation variance that can be possibly attained by any unbiased estimator of any targeted parameter. Here, CRBs are explicitly developed using (1) two water reflectance models corresponding to deep and shallow waters, resp., and (2) four probabilistic models describing the environmental noises observed within four Sentinel-2 MSI, HICO, Sentinel-3 OLCI and MODIS images, resp. For both deep and shallow waters, CRBs are shown to be consistent with the experimental estimation variances obtained using two published remote-sensing methods, while not requiring one to perform any inversion. CRBs are also used to investigate to what extent perfect a priori knowledge on one or several geophysical parameters can improve the estimation of remaining unknown parameters. For example, using pre-existing knowledge of bathymetry (e.g., derived from LiDAR) within the inversion is shown to greatly improve the retrieval of bottom cover for shallow waters. Finally, CRBs are shown to provide valuable information on the best estimation performances that may be achieved with the MSI, HICO, OLCI and MODIS configurations for a variety of oceanic, coastal and inland waters. CRBs are thus demonstrated to be an informative and efficient tool to characterize minimum uncertainties in inverted ocean color geophysical parameters.

Inverse problems of geophysics

International Nuclear Information System (INIS)

Yanovskaya, T.B.

2003-07-01

This report gives an overview and the mathematical formulation of geophysical inverse problems. General principles of statistical estimation are explained. The maximum likelihood and least square fit methods, the Backus-Gilbert method and general approaches for solving inverse problems are discussed. General formulations of linearized inverse problems, singular value decomposition and properties of pseudo-inverse solutions are given
ANNIT - An Efficient Inversion Algorithm based on Prediction Principles

Science.gov (United States)

Růžek, B.; Kolář, P.

2009-04-01

Solution of inverse problems represents meaningful job in geophysics. The amount of data is continuously increasing, methods of modeling are being improved and the computer facilities are also advancing great technical progress. Therefore the development of new and efficient algorithms and computer codes for both forward and inverse modeling is still up to date. ANNIT is contributing to this stream since it is a tool for efficient solution of a set of non-linear equations. Typical geophysical problems are based on parametric approach. The system is characterized by a vector of parameters p, the response of the system is characterized by a vector of data d. The forward problem is usually represented by unique mapping F(p)=d. The inverse problem is much more complex and the inverse mapping p=G(d) is available in an analytical or closed form only exceptionally and generally it may not exist at all. Technically, both forward and inverse mapping F and G are sets of non-linear equations. ANNIT solves such situation as follows: (i) joint subspaces {pD, pM} of original data and model spaces D, M, resp. are searched for, within which the forward mapping F is sufficiently smooth that the inverse mapping G does exist, (ii) numerical approximation of G in subspaces {pD, pM} is found, (iii) candidate solution is predicted by using this numerical approximation. ANNIT is working in an iterative way in cycles. The subspaces {pD, pM} are searched for by generating suitable populations of individuals (models) covering data and model spaces. The approximation of the inverse mapping is made by using three methods: (a) linear regression, (b) Radial Basis Function Network technique, (c) linear prediction (also known as "Kriging"). The ANNIT algorithm has built in also an archive of already evaluated models. Archive models are re-used in a suitable way and thus the number of forward evaluations is minimized. ANNIT is now implemented both in MATLAB and SCILAB. Numerical tests show good
A new analytical method for estimating lumped parameter constants of linear viscoelastic models from strain rate tests

Science.gov (United States)

Mattei, G.; Ahluwalia, A.

2018-04-01

We introduce a new function, the apparent elastic modulus strain-rate spectrum, E_{app} ( \\dot{ɛ} ), for the derivation of lumped parameter constants for Generalized Maxwell (GM) linear viscoelastic models from stress-strain data obtained at various compressive strain rates ( \\dot{ɛ}). The E_{app} ( \\dot{ɛ} ) function was derived using the tangent modulus function obtained from the GM model stress-strain response to a constant \\dot{ɛ} input. Material viscoelastic parameters can be rapidly derived by fitting experimental E_{app} data obtained at different strain rates to the E_{app} ( \\dot{ɛ} ) function. This single-curve fitting returns similar viscoelastic constants as the original epsilon dot method based on a multi-curve global fitting procedure with shared parameters. Its low computational cost permits quick and robust identification of viscoelastic constants even when a large number of strain rates or replicates per strain rate are considered. This method is particularly suited for the analysis of bulk compression and nano-indentation data of soft (bio)materials.
Sorting signed permutations by inversions in O(nlogn) time.

Science.gov (United States)

Swenson, Krister M; Rajan, Vaibhav; Lin, Yu; Moret, Bernard M E

2010-03-01

The study of genomic inversions (or reversals) has been a mainstay of computational genomics for nearly 20 years. After the initial breakthrough of Hannenhalli and Pevzner, who gave the first polynomial-time algorithm for sorting signed permutations by inversions, improved algorithms have been designed, culminating with an optimal linear-time algorithm for computing the inversion distance and a subquadratic algorithm for providing a shortest sequence of inversions--also known as sorting by inversions. Remaining open was the question of whether sorting by inversions could be done in O(nlogn) time. In this article, we present a qualified answer to this question, by providing two new sorting algorithms, a simple and fast randomized algorithm and a deterministic refinement. The deterministic algorithm runs in time O(nlogn + kn), where k is a data-dependent parameter. We provide the results of extensive experiments showing that both the average and the standard deviation for k are small constants, independent of the size of the permutation. We conclude (but do not prove) that almost all signed permutations can be sorted by inversions in O(nlogn) time.
Seismic wave propagation in heterogeneous multiphasic media: numerical modelling, sensibility and inversion of poro-elastic parameters

International Nuclear Information System (INIS)

Dupuy, B.

2011-11-01

Seismic wave propagation in multiphasic porous media have various environmental (natural risks, geotechnics, groundwater pollutions...) and resources (aquifers, oil and gas, CO 2 storage...) issues. When seismic waves are crossing a given material, they are distorted and thus contain information on fluid and solid phases. This work focuses on the characteristics of seismic waves propagating in multiphasic media, from the physical complex description to the parameter characterisation by inversion, including 2D numerical modelling of the wave propagation. The first part consists in the description of the physics of multiphasic media (each phase and their interactions), using several up-scaling methods, in order to obtain an equivalent mesoscale medium defined by seven parameters. Thus, in simple porosity saturated media and in complex media (double porosity, patchy saturation, visco-poro-elasticity), I can compute seismic wave propagation without any approximation. Indeed, I use a frequency-space domain for the numerical method, which allows to consider all the frequency dependent terms. The spatial discretization employs a discontinuous finite elements method (discontinuous Galerkin), which allows to take into account complex interfaces.The computation of the seismic attributes (velocities and attenuations) of complex porous media shows strong variations in respect with the frequency. Waveforms, computed without approximation, are strongly different if we take into account the full description of the medium or an homogenisation by averages. The last part of this work deals with the poro-elastic parameters characterisation by inversion. For this, I develop a two-steps method: the first one consists in a classical inversion (tomography, full waveform inversion) of seismograms data to obtain macro-scale parameters (seismic attributes). The second step allows to recover, from the macro-scale parameters, the poro-elastic micro-scale properties. This down-scaling step
Waveform inversion for orthorhombic anisotropy with P waves: feasibility and resolution

Science.gov (United States)

Kazei, Vladimir; Alkhalifah, Tariq

2018-05-01

Various parametrizations have been suggested to simplify inversions of first arrivals, or P waves, in orthorhombic anisotropic media, but the number and type of retrievable parameters have not been decisively determined. We show that only six parameters can be retrieved from the dynamic linearized inversion of P waves. These parameters are different from the six parameters needed to describe the kinematics of P waves. Reflection-based radiation patterns from the P-P scattered waves are remapped into the spectral domain to allow for our resolution analysis based on the effective angle of illumination concept. Singular value decomposition of the spectral sensitivities from various azimuths, offset coverage scenarios and data bandwidths allows us to quantify the resolution of different parametrizations, taking into account the signal-to-noise ratio in a given experiment. According to our singular value analysis, when the primary goal of inversion is determining the velocity of the P waves, gradually adding anisotropy of lower orders (isotropic, vertically transversally isotropic and orthorhombic) in hierarchical parametrization is the best choice. Hierarchical parametrization reduces the trade-off between the parameters and makes gradual introduction of lower anisotropy orders straightforward. When all the anisotropic parameters affecting P-wave propagation need to be retrieved simultaneously, the classic parametrization of orthorhombic medium with elastic stiffness matrix coefficients and density is a better choice for inversion. We provide estimates of the number and set of parameters that can be retrieved from surface seismic data in different acquisition scenarios. To set up an inversion process, the singular values determine the number of parameters that can be inverted and the resolution matrices from the parametrizations can be used to ascertain the set of parameters that can be resolved.
A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion

Energy Technology Data Exchange (ETDEWEB)

Li, Jinglai, E-mail: jinglaili@sjtu.edu.cn [Institute of Natural Sciences, Department of Mathematics, and MOE Key Laboratory of Scientific and Engineering Computing, Shanghai Jiao Tong University, Shanghai 200240 (China); Lin, Guang, E-mail: lin491@purdue.edu [Department of Mathematics, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States); Computational Sciences and Mathematics Division, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Yang, Xu, E-mail: xuyang@math.ucsb.edu [Department of Mathematics, University of California, Santa Barbara, CA 93106 (United States)

2015-09-01

In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by three steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.
Linear least squares compartmental-model-independent parameter identification in PET

International Nuclear Information System (INIS)

Thie, J.A.; Smith, G.T.; Hubner, K.F.

1997-01-01

A simplified approach involving linear-regression straight-line parameter fitting of dynamic scan data is developed for both specific and nonspecific models. Where compartmental-model topologies apply, the measured activity may be expressed in terms of: its integrals, plasma activity and plasma integrals -- all in a linear expression with macroparameters as coefficients. Multiple linear regression, as in spreadsheet software, determines parameters for best data fits. Positron emission tomography (PET)-acquired gray-matter images in a dynamic scan are analyzed: both by this method and by traditional iterative nonlinear least squares. Both patient and simulated data were used. Regression and traditional methods are in expected agreement. Monte-Carlo simulations evaluate parameter standard deviations, due to data noise, and much smaller noise-induced biases. Unique straight-line graphical displays permit visualizing data influences on various macroparameters as changes in slopes. Advantages of regression fitting are: simplicity, speed, ease of implementation in spreadsheet software, avoiding risks of convergence failures or false solutions in iterative least squares, and providing various visualizations of the uptake process by straight line graphical displays. Multiparameter model-independent analyses on lesser understood systems is also made possible
UAV-based multi-angular measurements for improved crop parameter retrieval

NARCIS (Netherlands)

Roosjen, Peter P.J.

2017-01-01

Optical remote sensing enables the estimation of crop parameters based on reflected light through empirical-statistical methods or inversion of radiative transfer models. Natural surfaces, however, reflect light anisotropically, which means that the intensity of reflected light depends on the
3D inversion based on multi-grid approach of magnetotelluric data from Northern Scandinavia

Science.gov (United States)

Cherevatova, M.; Smirnov, M.; Korja, T. J.; Egbert, G. D.

2012-12-01

In this work we investigate the geoelectrical structure of the cratonic margin of Fennoscandian Shield by means of magnetotelluric (MT) measurements carried out in Northern Norway and Sweden during summer 2011-2012. The project Magnetotellurics in the Scandes (MaSca) focuses on the investigation of the crust, upper mantle and lithospheric structure in a transition zone from a stable Precambrian cratonic interior to a passive continental margin beneath the Caledonian Orogen and the Scandes Mountains in western Fennoscandia. Recent MT profiles in the central and southern Scandes indicated a large contrast in resistivity between Caledonides and Precambrian basement. The alum shales as a highly conductive layers between the resistive Precambrian basement and the overlying Caledonian nappes are revealed from this profiles. Additional measurements in the Northern Scandes were required. All together data from 60 synchronous long period (LMT) and about 200 broad band (BMT) sites were acquired. The array stretches from Lofoten and Bodo (Norway) in the west to Kiruna and Skeleftea (Sweden) in the east covering an area of 500x500 square kilometers. LMT sites were occupied for about two months, while most of the BMT sites were measured during one day. We have used new multi-grid approach for 3D electromagnetic (EM) inversion and modelling. Our approach is based on the OcTree discretization where the spatial domain is represented by rectangular cells, each of which might be subdivided (recursively) into eight sub-cells. In this simplified implementation the grid is refined only in the horizontal direction, uniformly in each vertical layer. Using multi-grid we manage to have a high grid resolution near the surface (for instance, to tackle with galvanic distortions) and lower resolution at greater depth as the EM fields decay in the Earth according to the diffusion equation. We also have a benefit in computational costs as number of unknowns decrease. The multi-grid forward
Portfolio optimization using fuzzy linear programming

Science.gov (United States)

Pandit, Purnima K.

2013-09-01

Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.
On the role of density and attenuation in 3D multi-parameter visco-acoustic VTI frequency-domain FWI: an OBC case study from the North Sea

Science.gov (United States)

Operto, S.; Miniussi, A.

2018-03-01

Three-dimensional frequency-domain full waveform inversion (FWI) is applied on North Sea wide-azimuth ocean-bottom cable data at low frequencies (≤ 10 Hz) to jointly update vertical wavespeed, density and quality factor Q in the visco-acoustic VTI approximation. We assess whether density and Q should be viewed as proxy to absorb artefacts resulting from approximate wave physics or are valuable for interpretation in presence of saturated sediments and gas. FWI is performed in the frequency domain to account for attenuation easily. Multi-parameter frequency-domain FWI is efficiently performed with a few discrete frequencies following a multi-scale frequency continuation. However, grouping a few frequencies during each multi-scale step is necessary to mitigate acquisition footprint and match dispersive shallow guided waves. Q and density absorb a significant part of the acquisition footprint hence cleaning the velocity model from this pollution. Low Q perturbations correlate with low velocity zones associated with soft sediments and gas cloud. However, the amplitudes of the Q perturbations show significant variations when the inversion tuning is modified. This dispersion in the Q reconstructions is however not passed on the velocity parameter suggesting that cross-talks between first-order kinematic and second-order dynamic parameters are limited. The density model shows a good match with a well log at shallow depths. Moreover, the impedance built a posteriori from the FWI velocity and density models shows a well-focused image with however local differences with the velocity model near the sea bed where density might have absorbed elastic effects. The FWI models are finally assessed against time-domain synthetic seismogram modelling performed with the same frequency-domain modelling engine used for FWI.
Linear least squares approach for evaluating crack tip fracture parameters using isochromatic and isoclinic data from digital photoelasticity

Science.gov (United States)

Patil, Prataprao; Vyasarayani, C. P.; Ramji, M.

2017-06-01

In this work, digital photoelasticity technique is used to estimate the crack tip fracture parameters for different crack configurations. Conventionally, only isochromatic data surrounding the crack tip is used for SIF estimation, but with the advent of digital photoelasticity, pixel-wise availability of both isoclinic and isochromatic data could be exploited for SIF estimation in a novel way. A linear least square approach is proposed to estimate the mixed-mode crack tip fracture parameters by solving the multi-parameter stress field equation. The stress intensity factor (SIF) is extracted from those estimated fracture parameters. The isochromatic and isoclinic data around the crack tip is estimated using the ten-step phase shifting technique. To get the unwrapped data, the adaptive quality guided phase unwrapping algorithm (AQGPU) has been used. The mixed mode fracture parameters, especially SIF are estimated for specimen configurations like single edge notch (SEN), center crack and straight crack ahead of inclusion using the proposed algorithm. The experimental SIF values estimated using the proposed method are compared with analytical/finite element analysis (FEA) results, and are found to be in good agreement.
multi-scale data assimilation approaches and error characterisation applied to the inverse modelling of atmospheric constituent emission fields

International Nuclear Information System (INIS)

Koohkan, Mohammad Reza

2012-01-01

Data assimilation in geophysical sciences aims at optimally estimating the state of the system or some parameters of the system's physical model. To do so, data assimilation needs three types of information: observations and background information, a physical/numerical model, and some statistical description that prescribes uncertainties to each component of the system. In my dissertation, new methodologies of data assimilation are used in atmospheric chemistry and physics: the joint use of a 4D-Var with a sub-grid statistical model to consistently account for representativeness errors, accounting for multiple scale in the BLUE estimation principle, and a better estimation of prior errors using objective estimation of hyper-parameters. These three approaches will be specifically applied to inverse modelling problems focusing on the emission fields of tracers or pollutants. First, in order to estimate the emission inventories of carbon monoxide over France, in-situ stations which are impacted by the representativeness errors are used. A sub-grid model is introduced and coupled with a 4D-Var to reduce the representativeness error. Indeed, the results of inverse modelling showed that the 4D-Var routine was not fit to handle the representativeness issues. The coupled data assimilation system led to a much better representation of the CO concentration variability, with a significant improvement of statistical indicators, and more consistent estimation of the CO emission inventory. Second, the evaluation of the potential of the IMS (International Monitoring System) radionuclide network is performed for the inversion of an accidental source. In order to assess the performance of the global network, a multi-scale adaptive grid is optimised using a criterion based on degrees of freedom for the signal (DFS). The results show that several specific regions remain poorly observed by the IMS network. Finally, the inversion of the surface fluxes of Volatile Organic Compounds
Waveform inversion for acoustic VTI media in frequency domain

KAUST Repository

Wu, Zedong

2016-09-06

Reflected waveform inversion (RWI) provides a method to reduce the nonlinearity of the standard full waveform inversion (FWI) by inverting for the background model using a single scattered wavefield from an inverted perturbation. However, current RWI methods are mostly based on isotropic media assumption. We extend the idea of the combining inversion for the background model and perturbations to address transversely isotropic with a vertical axis of symmetry (VTI) media taking into consideration of the optimal parameter sensitivity information. As a result, we apply Born modeling corresponding to perturbations in only for the variable e to derive the relative reflected waveform inversion formulation. To reduce the number of parameters, we assume the background part of η = ε and work with a single variable to describe the anisotropic part of the wave propagation. Thus, the optimization variables are the horizontal velocity v, η = ε and the e perturbation. Application to the anisotropic version of Marmousi model with a single frequency of 2.5 Hz shows that this method can converge to the accurate result starting from a linearly increasing isotropic initial velocity. Application to a real dataset demonstrates the versatility of the approach.
Inverse Modeling of Soil Hydraulic Parameters Based on a Hybrid of Vector-Evaluated Genetic Algorithm and Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Yi-Bo Li

2018-01-01

Full Text Available The accurate estimation of soil hydraulic parameters (θs, α, n, and Ks of the van Genuchten–Mualem model has attracted considerable attention. In this study, we proposed a new two-step inversion method, which first estimated the hydraulic parameter θs using objective function by the final water content, and subsequently estimated the soil hydraulic parameters α, n, and Ks, using a vector-evaluated genetic algorithm and particle swarm optimization (VEGA-PSO method based on objective functions by cumulative infiltration and infiltration rate. The parameters were inversely estimated for four types of soils (sand, loam, silt, and clay under an in silico experiment simulating the tension disc infiltration at three initial water content levels. The results indicated that the method is excellent and robust. Because the objective function had multilocal minima in a tiny range near the true values, inverse estimation of the hydraulic parameters was difficult; however, the estimated soil water retention curves and hydraulic conductivity curves were nearly identical to the true curves. In addition, the proposed method was able to estimate the hydraulic parameters accurately despite substantial measurement errors in initial water content, final water content, and cumulative infiltration, proving that the method was feasible and practical for field application.
Joint Model and Parameter Dimension Reduction for Bayesian Inversion Applied to an Ice Sheet Flow Problem

Science.gov (United States)

Ghattas, O.; Petra, N.; Cui, T.; Marzouk, Y.; Benjamin, P.; Willcox, K.

2016-12-01

Model-based projections of the dynamics of the polar ice sheets play a central role in anticipating future sea level rise. However, a number of mathematical and computational challenges place significant barriers on improving predictability of these models. One such challenge is caused by the unknown model parameters (e.g., in the basal boundary conditions) that must be inferred from heterogeneous observational data, leading to an ill-posed inverse problem and the need to quantify uncertainties in its solution. In this talk we discuss the problem of estimating the uncertainty in the solution of (large-scale) ice sheet inverse problems within the framework of Bayesian inference. Computing the general solution of the inverse problem--i.e., the posterior probability density--is intractable with current methods on today's computers, due to the expense of solving the forward model (3D full Stokes flow with nonlinear rheology) and the high dimensionality of the uncertain parameters (which are discretizations of the basal sliding coefficient field). To overcome these twin computational challenges, it is essential to exploit problem structure (e.g., sensitivity of the data to parameters, the smoothing property of the forward model, and correlations in the prior). To this end, we present a data-informed approach that identifies low-dimensional structure in both parameter space and the forward model state space. This approach exploits the fact that the observations inform only a low-dimensional parameter space and allows us to construct a parameter-reduced posterior. Sampling this parameter-reduced posterior still requires multiple evaluations of the forward problem, therefore we also aim to identify a low dimensional state space to reduce the computational cost. To this end, we apply a proper orthogonal decomposition (POD) approach to approximate the state using a low-dimensional manifold constructed using ``snapshots'' from the parameter reduced posterior, and the discrete
Full waveform inversion using oriented time-domain imaging method for vertical transverse isotropic media

KAUST Repository

Zhang, Zhendong

2017-07-11

Full waveform inversion for reection events is limited by its linearized update re-quirements given by a process equivalent to migration. Unless the background velocity model is reasonably accurate, the resulting gradient can have an inaccurate update direction leading the inversion to converge what we refer to as local minima of the objective function. In our approach, we consider mild lateral variation in the model, and thus, use a gradient given by the oriented time-domain imaging method. Specifically, we apply the oriented time-domain imaging on the data residual to obtain the geometrical features of the velocity perturbation. After updating the model in the time domain, we convert the perturbation from the time domain to depth using the average velocity. Considering density is constant, we can expand the conventional 1D impedance inversion method to 2D or 3D velocity inversion within the process of full waveform inversion. This method is not only capable of inverting for velocity, but it is also capable of retrieving anisotropic parameters relying on linearized representations of the reection response. To eliminate the cross-talk artifacts between different parameters, we utilize what we consider being an optimal parametrization for this step. To do so, we extend the prestack time-domain migration image in incident angle dimension to incorporate angular dependence needed by the multiparameter inversion. For simple models, this approach provides an efficient and stable way to do full waveform inversion or modified seismic inversion and makes the anisotropic inversion more practicable. The proposed method still needs kinematically accurate initial models since it only recovers the high-wavenumber part as conventional full waveform inversion method does. Results on synthetic data of isotropic and anisotropic cases illustrate the benefits and limitations of this method.
Analysis of the efficiency of the linearization techniques for solving multi-objective linear fractional programming problems by goal programming

Directory of Open Access Journals (Sweden)

Tunjo Perić

2017-01-01

Full Text Available This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1 Taylor’s polynomial linearization approximation, (2 the method of variable change, and (3 a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a using the optimal value of the objective functions as the decision makers’ aspirations, and (b the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem.
Hyperchaotic encryption based on multi-scroll piecewise linear Systems

Czech Academy of Sciences Publication Activity Database

García-Martínez, M.; Ontanon-García, L.J.; Campos-Cantón, E.; Čelikovský, Sergej

2015-01-01

Roč. 270, č. 1 (2015), s. 413-424 ISSN 0096-3003 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Hyperchaotic encryption * Piecewise linear systems * Stream cipher * Pseudo-random bit generator * Chaos theory * Multi-scrollattractors Subject RIV: BC - Control Systems Theory Impact factor: 1.345, year: 2015 http://library.utia.cas.cz/separaty/2015/TR/celikovsky-0446895.pdf

Inhomogeneous Quantum Invariance Group of Multi-Dimensional Multi-parameter Deformed Boson Algebra

International Nuclear Information System (INIS)

Altintas Azmi Ali; Arik Metin; Arikan Ali Serdar; Dil Emre

2012-01-01

We investigate the inhomogeneous invariance quantum group of the d-dimensional d-parameter deformed boson algebra. It is found that the homogeneous part of this quantum group is given by the d-parameter deformed general linear group. We construct the R-matrix which collects all information about the non-commuting structure of the quantum group for the two-dimensional case. (general)
Multi-frequency accelerating strategy for the contrast source inversion method of ultrasound waveform tomography using pulse data

Science.gov (United States)

Lin, Hongxiang; Azuma, Takashi; Qu, Xiaolei; Takagi, Shu

2017-03-01

In this work, we construct a multi-frequency accelerating strategy for the contrast source inversion (CSI) method using pulse data in the time domain. CSI is a frequency-domain inversion method for ultrasound waveform tomography that does not require the forward solver through the process of reconstruction. Several prior researches show that the CSI method has a good performance of convergence and accuracy in the low-center-frequency situation. In contrast, utilizing the high-center-frequency data leads to a high-resolution reconstruction but slow convergence on large numbers of grid. Our objective is to take full advantage of all low frequency components from pulse data with the high-center-frequency data measured by the diagnostic device. First we process the raw data in the frequency domain. Then multi-frequency accelerating strategy helps restart CSI in the current frequency using the last iteration result obtained from the lower frequency component. The merit of multi- frequency accelerating strategy is that computational burden decreases at the first few iterations. Because the low frequency component of dataset computes on the coarse grid with assuming a fixed number of points per wavelength. In the numerical test, the pulse data were generated by the K-wave simulator and have been processed to meet the computation of the CSI method. We investigate the performance of the multi-frequency and single-frequency reconstructions and conclude that the multi-frequency accelerating strategy significantly enhances the quality of the reconstructed image and simultaneously reduces the average computational time for any iteration step.
Towards the mechanical characterization of abdominal wall by inverse analysis.

Science.gov (United States)

Simón-Allué, R; Calvo, B; Oberai, A A; Barbone, P E

2017-02-01

The aim of this study is to characterize the passive mechanical behaviour of abdominal wall in vivo in an animal model using only external cameras and numerical analysis. The main objective lies in defining a methodology that provides in vivo information of a specific patient without altering mechanical properties. It is demonstrated in the mechanical study of abdomen for hernia purposes. Mechanical tests consisted on pneumoperitoneum tests performed on New Zealand rabbits, where inner pressure was varied from 0mmHg to 12mmHg. Changes in the external abdominal surface were recorded and several points were tracked. Based on their coordinates we reconstructed a 3D finite element model of the abdominal wall, considering an incompressible hyperelastic material model defined by two parameters. The spatial distributions of these parameters (shear modulus and non linear parameter) were calculated by inverse analysis, using two different types of regularization: Total Variation Diminishing (TVD) and Tikhonov (H 1 ). After solving the inverse problem, the distribution of the material parameters were obtained along the abdominal surface. Accuracy of the results was evaluated for the last level of pressure. Results revealed a higher value of the shear modulus in a wide stripe along the craneo-caudal direction, associated with the presence of linea alba in conjunction with fascias and rectus abdominis. Non linear parameter distribution was smoother and the location of higher values varied with the regularization type. Both regularizations proved to yield in an accurate predicted displacement field, but H 1 obtained a smoother material parameter distribution while TVD included some discontinuities. The methodology here presented was able to characterize in vivo the passive non linear mechanical response of the abdominal wall. Copyright © 2016 Elsevier Ltd. All rights reserved.
Kinematic inversion of the 2008 Mw7 Iwate-Miyagi (Japan) earthquake by two independent methods: Sensitivity and resolution analysis

Science.gov (United States)

Gallovic, Frantisek; Cirella, Antonella; Plicka, Vladimir; Piatanesi, Alessio

2013-04-01

On 14 June 2008, UTC 23:43, the border of Iwate and Miyagi prefectures was hit by an Mw7 reverse-fault type crustal earthquake. The event is known to have the largest ground acceleration observed to date (~4g), which was recorded at station IWTH25. We analyze observed strong motion data with the objective to image the event rupture process and the associated uncertainties. Two different slip inversion approaches are used, the difference between the two methods being only in the parameterization of the source model. To minimize mismodeling of the propagation effects we use crustal model obtained by full waveform inversion of aftershock records in the frequency range between 0.05-0.3 Hz. In the first method, based on linear formulation, the parameters are represented by samples of slip velocity functions along the (finely discretized) fault in a time window spanning the whole rupture duration. Such a source description is very general with no prior constraint on the nucleation point, rupture velocity, shape of the velocity function. Thus the inversion could resolve very general (unexpected) features of the rupture evolution, such as multiple rupturing, rupture-propagation reversals, etc. On the other hand, due to the relatively large number of model parameters, the inversion result is highly non-unique, with possibility of obtaining a biased solution. The second method is a non-linear global inversion technique, where each point on the fault can slip only once, following a prescribed functional form of the source time function. We invert simultaneously for peak slip velocity, slip angle, rise time and rupture time by allowing a given range of variability for each kinematic model parameter. For this reason, unlike to the linear inversion approach, the rupture process needs a smaller number of parameters to be retrieved, and is more constrained with a proper control on the allowed range of parameter values. In order to test the resolution and reliability of the
Bayesian Estimation of the Scale Parameter of Inverse Weibull Distribution under the Asymmetric Loss Functions

Directory of Open Access Journals (Sweden)

Farhad Yahgmaei

2013-01-01

Full Text Available This paper proposes different methods of estimating the scale parameter in the inverse Weibull distribution (IWD. Specifically, the maximum likelihood estimator of the scale parameter in IWD is introduced. We then derived the Bayes estimators for the scale parameter in IWD by considering quasi, gamma, and uniform priors distributions under the square error, entropy, and precautionary loss functions. Finally, the different proposed estimators have been compared by the extensive simulation studies in corresponding the mean square errors and the evolution of risk functions.
A NEW METHOD OF CHANNEL FRICTION INVERSION BASED ON KALMAN FILTER WITH UNKNOWN PARAMETER VECTOR

Institute of Scientific and Technical Information of China (English)

CHENG Wei-ping; MAO Gen-hai; LIU Guo-hua

2005-01-01

Channel friction is an important parameter in hydraulic analysis.A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed.Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the solution is hardly affected.In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state.For the nonlinear equations, computations of sensitivity matrices are time-costly.Two simplified measures can reduce computing time, but not influence the results.One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.
Classifying the Sizes of Explosive Eruptions using Tephra Deposits: The Advantages of a Numerical Inversion Approach

Science.gov (United States)

Connor, C.; Connor, L.; White, J.

2015-12-01

Explosive volcanic eruptions are often classified by deposit mass and eruption column height. How well are these eruption parameters determined in older deposits, and how well can we reduce uncertainty using robust numerical and statistical methods? We describe an efficient and effective inversion and uncertainty quantification approach for estimating eruption parameters given a dataset of tephra deposit thickness and granulometry. The inversion and uncertainty quantification is implemented using the open-source PEST++ code. Inversion with PEST++ can be used with a variety of forward models and here is applied using Tephra2, a code that simulates advective and dispersive tephra transport and deposition. The Levenburg-Marquardt algorithm is combined with formal Tikhonov and subspace regularization to invert eruption parameters; a linear equation for conditional uncertainty propagation is used to estimate posterior parameter uncertainty. Both the inversion and uncertainty analysis support simultaneous analysis of the full eruption and wind-field parameterization. The combined inversion/uncertainty-quantification approach is applied to the 1992 eruption of Cerro Negro (Nicaragua), the 2011 Kirishima-Shinmoedake (Japan), and the 1913 Colima (Mexico) eruptions. These examples show that although eruption mass uncertainty is reduced by inversion against tephra isomass data, considerable uncertainty remains for many eruption and wind-field parameters, such as eruption column height. Supplementing the inversion dataset with tephra granulometry data is shown to further reduce the uncertainty of most eruption and wind-field parameters. We think the use of such robust models provides a better understanding of uncertainty in eruption parameters, and hence eruption classification, than is possible with more qualitative methods that are widely used.
Full-waveform inversion of GPR data acquired between boreholes in Rustrel carbonates

Directory of Open Access Journals (Sweden)

Pinard Hugo

2016-01-01

Full Text Available Full waveform inversion (FWI of seismic or Ground Penetrating Radar data provides high-resolution quantitative images of the constitutive parameters of the rock/soil which control seismic/GPR wave propagation. We developed a 2D inversion tool in the frequency domain adapted to the multi-parameter physics controlling GPR propagation in isotropic non dispersive media, i.e. dielectric permittivity and electrical conductivity. This inversion engine was previously tested using synthetic 2D data to mitigate the trade-off between the two parameter classes. In this paper, we present the required processing techniques and first inversion results obtained on a real GPR dataset acquired in carbonates with a cross-hole configuration. The presence of the 2 m diameter underground gallery at depth constitutes a nice target to test the robustness, efficiency and resolution of the inversion in such high-contrasts context. Starting from a time tomographic image for the dielectric permittivity and from a homogeneous conductivity, we show that FWI is efficient to retrieve high resolution images of dielectric permittivity but struggles with electrical conductivity. As a quality control, we compare real and synthetic radargrams computed from the tomography and final images, showing the efficiency of the process to reconstruct some events but also underlying some issues, particularly on large incidence angles amplitude traces.
Stability and uncertainty of finite-fault slip inversions: Application to the 2004 Parkfield, California, earthquake

Science.gov (United States)

Hartzell, S.; Liu, P.; Mendoza, C.; Ji, C.; Larson, K.M.

2007-01-01

The 2004 Parkfield, California, earthquake is used to investigate stability and uncertainty aspects of the finite-fault slip inversion problem with different a priori model assumptions. We utilize records from 54 strong ground motion stations and 13 continuous, 1-Hz sampled, geodetic instruments. Two inversion procedures are compared: a linear least-squares subfault-based methodology and a nonlinear global search algorithm. These two methods encompass a wide range of the different approaches that have been used to solve the finite-fault slip inversion problem. For the Parkfield earthquake and the inversion of velocity or displacement waveforms, near-surface related site response (top 100 m, frequencies above 1 Hz) is shown to not significantly affect the solution. Results are also insensitive to selection of slip rate functions with similar duration and to subfault size if proper stabilizing constraints are used. The linear and nonlinear formulations yield consistent results when the same limitations in model parameters are in place and the same inversion norm is used. However, the solution is sensitive to the choice of inversion norm, the bounds on model parameters, such as rake and rupture velocity, and the size of the model fault plane. The geodetic data set for Parkfield gives a slip distribution different from that of the strong-motion data, which may be due to the spatial limitation of the geodetic stations and the bandlimited nature of the strong-motion data. Cross validation and the bootstrap method are used to set limits on the upper bound for rupture velocity and to derive mean slip models and standard deviations in model parameters. This analysis shows that slip on the northwestern half of the Parkfield rupture plane from the inversion of strong-motion data is model dependent and has a greater uncertainty than slip near the hypocenter.
Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

Science.gov (United States)

Doherty, John E.; Hunt, Randall J.; Tonkin, Matthew J.

2010-01-01

Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in
Sensitivities of surface wave velocities to the medium parameters in a radially anisotropic spherical Earth and inversion strategies

Directory of Open Access Journals (Sweden)

Sankar N. Bhattacharya

2015-11-01

Full Text Available Sensitivity kernels or partial derivatives of phase velocity (c and group velocity (U with respect to medium parameters are useful to interpret a given set of observed surface wave velocity data. In addition to phase velocities, group velocities are also being observed to find the radial anisotropy of the crust and mantle. However, sensitivities of group velocity for a radially anisotropic Earth have rarely been studied. Here we show sensitivities of group velocity along with those of phase velocity to the medium parameters VSV, VSH , VPV, VPH , h and density in a radially anisotropic spherical Earth. The peak sensitivities for U are generally twice of those for c; thus U is more efficient than c to explore anisotropic nature of the medium. Love waves mainly depends on VSH while Rayleigh waves is nearly independent of VSH . The sensitivities show that there are trade-offs among these parameters during inversion and there is a need to reduce the number of parameters to be evaluated independently. It is suggested to use a nonlinear inversion jointly for Rayleigh and Love waves; in such a nonlinear inversion best solutions are obtained among the model parameters within prescribed limits for each parameter. We first choose VSH, VSV and VPH within their corresponding limits; VPV and h can be evaluated from empirical relations among the parameters. The density has small effect on surface wave velocities and it can be considered from other studies or from empirical relation of density to average P-wave velocity.
Robust and Fault-Tolerant Linear Parameter-Varying Control of Wind Turbines

DEFF Research Database (Denmark)

Sloth, Christoffer; Esbensen, Thomas; Stoustrup, Jakob

2011-01-01

High performance and reliability are required for wind turbines to be competitive within the energy market. To capture their nonlinear behavior, wind turbines are often modeled using parameter-varying models. In this paper we design and compare multiple linear parameter-varying (LPV) controllers,...
On the identifiability of inertia parameters of planar Multi-Body Space Systems

Science.gov (United States)

Nabavi-Chashmi, Seyed Yaser; Malaek, Seyed Mohammad-Bagher

2018-04-01

This work describes a new formulation to study the identifiability characteristics of Serially Linked Multi-body Space Systems (SLMBSS). The process exploits the so called "Lagrange Formulation" to develop a linear form of Equations of Motion w.r.t the system Inertia Parameters (IPs). Having developed a specific form of regressor matrix, we aim to expedite the identification process. The new approach allows analytical as well as numerical identification and identifiability analysis for different SLMBSSs' configurations. Moreover, the explicit forms of SLMBSSs identifiable parameters are derived by analyzing the identifiability characteristics of the robot. We further show that any SLMBSS designed with Variable Configurations Joint allows all IPs to be identifiable through comparing two successive identification outcomes. This feature paves the way to design new class of SLMBSS for which accurate identification of all IPs is at hand. Different case studies reveal that proposed formulation provides fast and accurate results, as required by the space applications. Further studies might be necessary for cases where planar-body assumption becomes inaccurate.
GBIS (Geodetic Bayesian Inversion Software): Rapid Inversion of InSAR and GNSS Data to Estimate Surface Deformation Source Parameters and Uncertainties

Science.gov (United States)

Bagnardi, M.; Hooper, A. J.

2017-12-01

Inversions of geodetic observational data, such as Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) measurements, are often performed to obtain information about the source of surface displacements. Inverse problem theory has been applied to study magmatic processes, the earthquake cycle, and other phenomena that cause deformation of the Earth's interior and of its surface. Together with increasing improvements in data resolution, both spatial and temporal, new satellite missions (e.g., European Commission's Sentinel-1 satellites) are providing the unprecedented opportunity to access space-geodetic data within hours from their acquisition. To truly take advantage of these opportunities we must become able to interpret geodetic data in a rapid and robust manner. Here we present the open-source Geodetic Bayesian Inversion Software (GBIS; available for download at http://comet.nerc.ac.uk/gbis). GBIS is written in Matlab and offers a series of user-friendly and interactive pre- and post-processing tools. For example, an interactive function has been developed to estimate the characteristics of noise in InSAR data by calculating the experimental semi-variogram. The inversion software uses a Markov-chain Monte Carlo algorithm, incorporating the Metropolis-Hastings algorithm with adaptive step size, to efficiently sample the posterior probability distribution of the different source parameters. The probabilistic Bayesian approach allows the user to retrieve estimates of the optimal (best-fitting) deformation source parameters together with the associated uncertainties produced by errors in the data (and by scaling, errors in the model). The current version of GBIS (V1.0) includes fast analytical forward models for magmatic sources of different geometry (e.g., point source, finite spherical source, prolate spheroid source, penny-shaped sill-like source, and dipping-dike with uniform opening) and for dipping faults with uniform
It's the parameters, stupid! Moving beyond multi-model and multi-physics approaches to characterize and reduce predictive uncertainty in process-based hydrological models

Science.gov (United States)

Clark, Martyn; Samaniego, Luis; Freer, Jim

2014-05-01

Multi-model and multi-physics approaches are a popular tool in environmental modelling, with many studies focusing on optimally combining output from multiple model simulations to reduce predictive errors and better characterize predictive uncertainty. However, a careful and systematic analysis of different hydrological models reveals that individual models are simply small permutations of a master modeling template, and inter-model differences are overwhelmed by uncertainty in the choice of the parameter values in the model equations. Furthermore, inter-model differences do not explicitly represent the uncertainty in modeling a given process, leading to many situations where different models provide the wrong results for the same reasons. In other cases, the available morphological data does not support the very fine spatial discretization of the landscape that typifies many modern applications of process-based models. To make the uncertainty characterization problem worse, the uncertain parameter values in process-based models are often fixed (hard-coded), and the models lack the agility necessary to represent the tremendous heterogeneity in natural systems. This presentation summarizes results from a systematic analysis of uncertainty in process-based hydrological models, where we explicitly analyze the myriad of subjective decisions made throughout both the model development and parameter estimation process. Results show that much of the uncertainty is aleatory in nature - given a "complete" representation of dominant hydrologic processes, uncertainty in process parameterizations can be represented using an ensemble of model parameters. Epistemic uncertainty associated with process interactions and scaling behavior is still important, and these uncertainties can be represented using an ensemble of different spatial configurations. Finally, uncertainty in forcing data can be represented using ensemble methods for spatial meteorological analysis. Our systematic
Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

Science.gov (United States)

Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

2017-10-01

Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations
Genetic algorithm–based varying parameter linear quadratic regulator control for four-wheel independent steering vehicle

Directory of Open Access Journals (Sweden)

Linlin Gao

2015-11-01

Full Text Available From the perspective of vehicle dynamics, the four-wheel independent steering vehicle dynamics stability control method is studied, and a four-wheel independent steering varying parameter linear quadratic regulator control system is proposed with the help of expert control method. In the article, a four-wheel independent steering linear quadratic regulator controller for model following purpose is designed first. Then, by analyzing the four-wheel independent steering vehicle dynamic characteristics and the influence of linear quadratic regulator control parameters on control performance, a linear quadratic regulator control parameter adjustment strategy based on vehicle steering state is proposed to achieve the adaptive adjustment of linear quadratic regulator control parameters. In addition, to further improve the control performance, the proposed varying parameter linear quadratic regulator control system is optimized by genetic algorithm. Finally, simulation studies have been conducted by applying the proposed control system to the 8-degree-of-freedom four-wheel independent steering vehicle dynamics model. The simulation results indicate that the proposed control system has better performance and robustness and can effectively improve the stability and steering safety of the four-wheel independent steering vehicle.
Design of a multi beam klystron cavity from its single beam parameters

Energy Technology Data Exchange (ETDEWEB)

Kant, Deepender, E-mail: dkc@ceeri.ernet.in; Joshi, L. M. [CSIR-Central Electronics Engineering Research Institute, Pilani (India); Janyani, Vijay [Department of ECE, MNIT, Jaipur (India)

2016-03-09

The klystron is a well-known microwave amplifier which uses kinetic energy of an electron beam for amplification of the RF signal. There are some limitations of conventional single beam klystron such as high operating voltage, low efficiency and bulky size at higher power levels, which are very effectively handled in Multi Beam Klystron (MBK) that uses multiple low purveyance electron beams for RF interaction. Each beam propagates along its individual transit path through a resonant cavity structure. Multi-Beam klystron cavity design is a critical task due to asymmetric cavity structure and can be simulated by 3D code only. The present paper shall discuss the design of multi beam RF cavities for klystrons operating at 2856 MHz (S-band) and 5 GHz (C-band) respectively. The design approach uses some scaling laws for finding the electron beam parameters of the multi beam device from their single beam counter parts. The scaled beam parameters are then used for finding the design parameters of the multi beam cavities. Design of the desired multi beam cavity can be optimized through iterative simulations in CST Microwave Studio.
Design of a multi beam klystron cavity from its single beam parameters

International Nuclear Information System (INIS)

Kant, Deepender; Joshi, L. M.; Janyani, Vijay

2016-01-01

The klystron is a well-known microwave amplifier which uses kinetic energy of an electron beam for amplification of the RF signal. There are some limitations of conventional single beam klystron such as high operating voltage, low efficiency and bulky size at higher power levels, which are very effectively handled in Multi Beam Klystron (MBK) that uses multiple low purveyance electron beams for RF interaction. Each beam propagates along its individual transit path through a resonant cavity structure. Multi-Beam klystron cavity design is a critical task due to asymmetric cavity structure and can be simulated by 3D code only. The present paper shall discuss the design of multi beam RF cavities for klystrons operating at 2856 MHz (S-band) and 5 GHz (C-band) respectively. The design approach uses some scaling laws for finding the electron beam parameters of the multi beam device from their single beam counter parts. The scaled beam parameters are then used for finding the design parameters of the multi beam cavities. Design of the desired multi beam cavity can be optimized through iterative simulations in CST Microwave Studio.
Fully probabilistic seismic source inversion – Part 1: Efficient parameterisation

Directory of Open Access Journals (Sweden)

S. C. Stähler

2014-11-01

Full Text Available Seismic source inversion is a non-linear problem in seismology where not just the earthquake parameters themselves but also estimates of their uncertainties are of great practical importance. Probabilistic source inversion (Bayesian inference is very adapted to this challenge, provided that the parameter space can be chosen small enough to make Bayesian sampling computationally feasible. We propose a framework for PRobabilistic Inference of Seismic source Mechanisms (PRISM that parameterises and samples earthquake depth, moment tensor, and source time function efficiently by using information from previous non-Bayesian inversions. The source time function is expressed as a weighted sum of a small number of empirical orthogonal functions, which were derived from a catalogue of >1000 source time functions (STFs by a principal component analysis. We use a likelihood model based on the cross-correlation misfit between observed and predicted waveforms. The resulting ensemble of solutions provides full uncertainty and covariance information for the source parameters, and permits propagating these source uncertainties into travel time estimates used for seismic tomography. The computational effort is such that routine, global estimation of earthquake mechanisms and source time functions from teleseismic broadband waveforms is feasible.

Identification of Affine Linear Parameter Varying Models for Adaptive Interventions in Fibromyalgia Treatment.

Science.gov (United States)

Dos Santos, P Lopes; Deshpande, Sunil; Rivera, Daniel E; Azevedo-Perdicoúlis, T-P; Ramos, J A; Younger, Jarred

2013-12-31

There is good evidence that naltrexone, an opioid antagonist, has a strong neuroprotective role and may be a potential drug for the treatment of fibromyalgia. In previous work, some of the authors used experimental clinical data to identify input-output linear time invariant models that were used to extract useful information about the effect of this drug on fibromyalgia symptoms. Additional factors such as anxiety, stress, mood, and headache, were considered as additive disturbances. However, it seems reasonable to think that these factors do not affect the drug actuation, but only the way in which a participant perceives how the drug actuates on herself. Under this hypothesis the linear time invariant models can be replaced by State-Space Affine Linear Parameter Varying models where the disturbances are seen as a scheduling signal signal only acting at the parameters of the output equation. In this paper a new algorithm for identifying such a model is proposed. This algorithm minimizes a quadratic criterion of the output error. Since the output error is a linear function of some parameters, the Affine Linear Parameter Varying system identification is formulated as a separable nonlinear least squares problem. Likewise other identification algorithms using gradient optimization methods several parameter derivatives are dynamical systems that must be simulated. In order to increase time efficiency a canonical parametrization that minimizes the number of systems to be simulated is chosen. The effectiveness of the algorithm is assessed in a case study where an Affine Parameter Varying Model is identified from the experimental data used in the previous study and compared with the time-invariant model.
Soft-sensing Modeling Based on MLS-SVM Inversion for L-lysine Fermentation Processes

Directory of Open Access Journals (Sweden)

Bo Wang

2015-06-01

Full Text Available A modeling approach 63 based on multiple output variables least squares support vector machine (MLS-SVM inversion is presented by a combination of inverse system and support vector machine theory. Firstly, a dynamic system model is developed based on material balance relation of a fed-batch fermentation process, with which it is analyzed whether an inverse system exists or not, and into which characteristic information of a fermentation process is introduced to set up an extended inversion model. Secondly, an initial extended inversion model is developed off-line by the use of the fitting capacity of MLS-SVM; on-line correction is made by the use of a differential evolution (DE algorithm on the basis of deviation information. Finally, a combined pseudo-linear system is formed by means of a serial connection of a corrected extended inversion model behind the L-lysine fermentation processes; thereby crucial biochemical parameters of a fermentation process could be predicted on-line. The simulation experiment shows that this soft-sensing modeling method features very high prediction precision and can predict crucial biochemical parameters of L-lysine fermentation process very well.
Multi-parameters scanning in HTI media

KAUST Repository

Masmoudi, Nabil

2014-08-05

Building credible anisotropy models is crucial in imaging. One way to estimate anisotropy parameters is to relate them analytically to traveltime, which is challenging in inhomogeneous media. Using perturbation theory, we develop traveltime approximations for transversely isotropic media with horizontal symmetry axis (HTI) as explicit functions of the anellipticity parameter η and the symmetry axis azimuth ϕ in inhomogeneous background media. Specifically, our expansion assumes an inhomogeneous elliptically anisotropic background medium, which may be obtained from well information and stacking velocity analysis in HTI media. This formulation has advantages on two fronts: on one hand, it alleviates the computational complexity associated with solving the HTI eikonal equation, and on the other hand, it provides a mechanism to scan for the best fitting parameters η and ϕ without the need for repetitive modeling of traveltimes, because the traveltime coefficients of the expansion are independent of the perturbed parameters η and ϕ. The accuracy of our expansion is further enhanced by the use of shanks transform. We show the effectiveness of our scheme with tests on a 3D model and we propose an approach for multi-parameters scanning in TI media.
Multi-parameters scanning in HTI media

KAUST Repository

Masmoudi, Nabil; Alkhalifah, Tariq Ali

2014-01-01

Building credible anisotropy models is crucial in imaging. One way to estimate anisotropy parameters is to relate them analytically to traveltime, which is challenging in inhomogeneous media. Using perturbation theory, we develop traveltime approximations for transversely isotropic media with horizontal symmetry axis (HTI) as explicit functions of the anellipticity parameter η and the symmetry axis azimuth ϕ in inhomogeneous background media. Specifically, our expansion assumes an inhomogeneous elliptically anisotropic background medium, which may be obtained from well information and stacking velocity analysis in HTI media. This formulation has advantages on two fronts: on one hand, it alleviates the computational complexity associated with solving the HTI eikonal equation, and on the other hand, it provides a mechanism to scan for the best fitting parameters η and ϕ without the need for repetitive modeling of traveltimes, because the traveltime coefficients of the expansion are independent of the perturbed parameters η and ϕ. The accuracy of our expansion is further enhanced by the use of shanks transform. We show the effectiveness of our scheme with tests on a 3D model and we propose an approach for multi-parameters scanning in TI media.
Massively Parallel Geostatistical Inversion of Coupled Processes in Heterogeneous Porous Media

Science.gov (United States)

Ngo, A.; Schwede, R. L.; Li, W.; Bastian, P.; Ippisch, O.; Cirpka, O. A.

2012-04-01

The quasi-linear geostatistical approach is an inversion scheme that can be used to estimate the spatial distribution of a heterogeneous hydraulic conductivity field. The estimated parameter field is considered to be a random variable that varies continuously in space, meets the measurements of dependent quantities (such as the hydraulic head, the concentration of a transported solute or its arrival time) and shows the required spatial correlation (described by certain variogram models). This is a method of conditioning a parameter field to observations. Upon discretization, this results in as many parameters as elements of the computational grid. For a full three dimensional representation of the heterogeneous subsurface it is hardly sufficient to work with resolutions (up to one million parameters) of the model domain that can be achieved on a serial computer. The forward problems to be solved within the inversion procedure consists of the elliptic steady-state groundwater flow equation and the formally elliptic but nearly hyperbolic steady-state advection-dominated solute transport equation in a heterogeneous porous medium. Both equations are discretized by Finite Element Methods (FEM) using fully scalable domain decomposition techniques. Whereas standard conforming FEM is sufficient for the flow equation, for the advection dominated transport equation, which rises well known numerical difficulties at sharp fronts or boundary layers, we use the streamline diffusion approach. The arising linear systems are solved using efficient iterative solvers with an AMG (algebraic multigrid) pre-conditioner. During each iteration step of the inversion scheme one needs to solve a multitude of forward and adjoint problems in order to calculate the sensitivities of each measurement and the related cross-covariance matrix of the unknown parameters and the observations. In order to reduce interprocess communications and to improve the scalability of the code on larger clusters
Non-linearity parameter of binary liquid mixtures at elevated pressures

Indian Academy of Sciences (India)

. Ultrasonic studies in liquid mixtures provide valuable information about structure and interaction in such systems. The present investigation comprises of theoretical evaluation of the acoustic non-linearity parameter / of four binary liquid ...
Linear transform of the multi-target survival curve

Energy Technology Data Exchange (ETDEWEB)

Watson, J V [Cambridge Univ. (UK). Dept. of Clinical Oncology and Radiotherapeutics

1978-07-01

A completely linear transform of the multi-target survival curve is presented. This enables all data, including those on the shoulder region of the curve, to be analysed. The necessity to make a subjective assessment about which data points to exclude for conventional methods of analysis is, therefore, removed. The analysis has also been adapted to include a 'Pike-Alper' method of assessing dose modification factors. For the data cited this predicts compatibility with the hypothesis of a true oxygen 'dose-modification' whereas the conventional Pike-Alper analysis does not.
Inverse and Ill-posed Problems Theory and Applications

CERN Document Server

Kabanikhin, S I

2011-01-01

The text demonstrates the methods for proving the existence (if et all) and finding of inverse and ill-posed problems solutions in linear algebra, integral and operator equations, integral geometry, spectral inverse problems, and inverse scattering problems. It is given comprehensive background material for linear ill-posed problems and for coefficient inverse problems for hyperbolic, parabolic, and elliptic equations. A lot of examples for inverse problems from physics, geophysics, biology, medicine, and other areas of application of mathematics are included.
Estimation of soil hydraulic parameters by integrated hydrogeophysical inversion of time-lapse GPR data measured at Selhausen, Germany

KAUST Repository

Jadoon, Khan

2012-06-01

We present an integrated hydrogeophysical inversion approach that uses time-lapse off-ground ground-penetrating radar (GPR) data to estimate soil hydraulic parameters, and apply it to a dataset collected in the field. Off-ground GPR data are mainly sensitive to the near-surface water content profile and dynamics, and are thus related to soil hydraulic parameters, such as the parameters of the hydraulic conductivity and water retention functions. The hydrological simulator HYDRUS 1-D was used with a two-layer single- and dual-porosity model. To monitor the soil water content dynamics, time-lapse GPR and time domain reflectometry (TDR) measurements were performed, whereby only GPR data was used in the inversion. The dual porosity model provided better results compared to the single porosity model for describing the soil water dynamics, which is supported by field observations of macropores. Furthermore, the GPR-derived water content profiles reconstructed from the integrated hydrogeophysical inversion were in good agreement with TDR observations. These results suggest that the proposed method is promising for non-invasive characterization of the shallow subsurface hydraulic properties and monitoring water dynamics at the field scale.
A simple method for identifying parameter correlations in partially observed linear dynamic models.

Science.gov (United States)

Li, Pu; Vu, Quoc Dong

2015-12-14

Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a
Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.

2011-08-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.
Bulk and interface quantum states of electrons in multi-layer heterostructures with topological materials

Science.gov (United States)

Nikolic, Aleksandar; Zhang, Kexin; Barnes, C. H. W.

2018-06-01

In this article we describe the bulk and interface quantum states of electrons in multi-layer heterostructures in one dimension, consisting of topological insulators (TIs) and topologically trivial materials. We use and extend an effective four-band continuum Hamiltonian by introducing position dependence to the eight material parameters of the Hamiltonian. We are able to demonstrate complete conduction-valence band mixing in the interface states. We find evidence for topological features of bulk states of multi-layer TI heterostructures, as well as demonstrating both complete and incomplete conduction-valence band inversion at different bulk state energies. We show that the linear k z terms in the low-energy Hamiltonian, arising from overlap of p z orbitals between different atomic layers in the case of chalcogenides, control the amount of tunneling from TIs to trivial insulators. Finally, we show that the same linear k z terms in the low-energy Hamiltonian affect the material’s ability to form the localised interface state, and we demonstrate that due to this effect the spin and probability density localisation in a thin film of Sb2Te3 is incomplete. We show that changing the parameter that controls the magnitude of the overlap of p z orbitals affects the transport characteristics of the topologically conducting states, with incomplete topological state localisation resulting in increased backscattering.
Data inversion in coupled subsurface flow and geomechanics models

International Nuclear Information System (INIS)

Iglesias, Marco A; McLaughlin, Dennis

2012-01-01

We present an inverse modeling approach to estimate petrophysical and elastic properties of the subsurface. The aim is to use the fully coupled geomechanics-flow model of Girault et al (2011 Math. Models Methods Appl. Sci. 21 169–213) to jointly invert surface deformation and pressure data from wells. We use a functional-analytic framework to construct a forward operator (parameter-to-output map) that arises from the geomechanics-flow model of Girault et al. Then, we follow a deterministic approach to pose the inverse problem of finding parameter estimates from measurements of the output of the forward operator. We prove that this inverse problem is ill-posed in the sense of stability. The inverse problem is then regularized with the implementation of the Newton-conjugate gradient (CG) algorithm of Hanke (1997 Numer. Funct. Anal. Optim. 18 18–971). For a consistent application of the Newton-CG scheme, we establish the differentiability of the forward map and characterize the adjoint of its linearization. We provide assumptions under which the theory of Hanke ensures convergence and regularizing properties of the Newton-CG scheme. These properties are verified in our numerical experiments. In addition, our synthetic experiments display the capabilities of the proposed inverse approach to estimate parameters of the subsurface by means of data inversion. In particular, the added value of measurements of surface deformation in the estimation of absolute permeability is quantified with respect to the standard history matching approach of inverting production data with flow models. The proposed methodology can be potentially used to invert satellite geodetic data (e.g. InSAR and GPS) in combination with production data for optimal monitoring and characterization of the subsurface. (paper)
Characterization and optimized control by means of multi-parameter controllers

Energy Technology Data Exchange (ETDEWEB)

Nielsen, Carsten; Hoeg, S.; Thoegersen, A. (Dan-Ejendomme, Hellerup (Denmark)) (and others)

2009-07-01

Poorly functioning HVAC systems (Heating, Ventilation and Air Conditioning), but also separate heating, ventilation and air conditioning systems are costing the Danish society billions of kroner every year: partly because of increased energy consumption and high operational and maintenance costs, but mainly due to reduced productivity and absence due to illness because of a poor indoor climate. Typically, the operation of buildings and installations takes place today with traditional build-ing automation, which is characterised by 1) being based on static considerations 2) the individual sensor being coupled with one actuator/valve, i.e. the sensor's signal is only used in one place in the system 3) subsystems often being controlled independently of each other 4) the dynamics in building constructions and systems which is very important to the system and comfort regulation is not being considered. This, coupled with the widespread tendency to use large glass areas in the facades without sufficient sun shading, means that it is difficult to optimise comfort and energy consumption. Therefore, the last 10-20 years have seen a steady increase in the complaints of the indoor climate in Danish buildings and, at the same time, new buildings often turn out to be considerably higher energy consuming than expected. The purpose of the present project is to investigate the type of multi parameter sensors which may be generated for buildings and further to carry out a preliminary evaluation on how such multi parameter controllers may be utilized for optimal control of buildings. The aim of the project isn't to develop multi parameter controllers - this requires much more effort than possible in the present project. The aim is to show the potential of using multi parameter sensors when controlling buildings. For this purpose a larger office building has been chosen - an office building with at high energy demand and complaints regarding the indoor climate. In order to
Inverse analyses of effective diffusion parameters relevant for a two-phase moisture model of cementitious materials

DEFF Research Database (Denmark)

Addassi, Mouadh; Johannesson, Björn; Wadsö, Lars

2018-01-01

Here we present an inverse analyses approach to determining the two-phase moisture transport properties relevant to concrete durability modeling. The purposed moisture transport model was based on a continuum approach with two truly separate equations for the liquid and gas phase being connected...... test, and, (iv) capillary suction test. Mass change over time, as obtained from the drying test, the two different cup test intervals and the capillary suction test, was used to obtain the effective diffusion parameters using the proposed inverse analyses approach. The moisture properties obtained...
Evaluation for Bearing Wear States Based on Online Oil Multi-Parameters Monitoring

Science.gov (United States)

Hu, Hai-Feng

2018-01-01

As bearings are critical components of a mechanical system, it is important to characterize their wear states and evaluate health conditions. In this paper, a novel approach for analyzing the relationship between online oil multi-parameter monitoring samples and bearing wear states has been proposed based on an improved gray k-means clustering model (G-KCM). First, an online monitoring system with multiple sensors for bearings is established, obtaining oil multi-parameter data and vibration signals for bearings through the whole lifetime. Secondly, a gray correlation degree distance matrix is generated using a gray correlation model (GCM) to express the relationship of oil monitoring samples at different times and then a KCM is applied to cluster the matrix. Analysis and experimental results show that there is an obvious correspondence that state changing coincides basically in time between the lubricants’ multi-parameters and the bearings’ wear states. It also has shown that online oil samples with multi-parameters have early wear failure prediction ability for bearings superior to vibration signals. It is expected to realize online oil monitoring and evaluation for bearing health condition and to provide a novel approach for early identification of bearing-related failure modes. PMID:29621175
Linear Parameter Varying Control of Induction Motors

DEFF Research Database (Denmark)

Trangbæk, Klaus

The subject of this thesis is the development of linear parameter varying (LPV) controllers and observers for control of induction motors. The induction motor is one of the most common machines in industrial applications. Being a highly nonlinear system, it poses challenging control problems...... for high performance applications. This thesis demonstrates how LPV control theory provides a systematic way to achieve good performance for these problems. The main contributions of this thesis are the application of the LPV control theory to induction motor control as well as various contributions...
Multi-parameter optimization design of parabolic trough solar receiver

International Nuclear Information System (INIS)

Guo, Jiangfeng; Huai, Xiulan

2016-01-01

Highlights: • The optimal condition can be obtained by multi-parameter optimization. • Exergy and thermal efficiencies are employed as objective function. • Exergy efficiency increases at the expense of heat losses. • The heat obtained by working fluid increases as thermal efficiency grows. - Abstract: The design parameters of parabolic trough solar receiver are interrelated and interact with one another, so the optimal performance of solar receiver cannot be obtained by the convectional single-parameter optimization. To overcome the shortcoming of single-parameter optimization, a multi-parameter optimization of parabolic trough solar receiver is employed based on genetic algorithm in the present work. When the thermal efficiency is taken as the objective function, the heat obtained by working fluid increases while the average temperature of working fluid and wall temperatures of solar receiver decrease. The average temperature of working fluid and the wall temperatures of solar receiver increase while the heat obtained by working fluid decreases generally by taking the exergy efficiency as an objective function. Assuming that the solar radiation intensity remains constant, the exergy obtained by working fluid increases by taking exergy efficiency as the objective function, which comes at the expense of heat losses of solar receiver.
Multi-scattering inversion for low model wavenumbers

KAUST Repository

Alkhalifah, Tariq Ali

2015-08-19

A successful full wavenumber inversion (FWI) implementation updates the low wavenumber model components first for proper wavefield propagation description, and slowly adds the high-wavenumber potentially scattering parts of the model. The low-wavenumber components can be extracted from the transmission parts of the recorded data given by direct arrivals or the transmission parts of the single and double-scattering wave-fields developed from a predicted scatter field. We develop a combined inversion of data modeled from the source and those corresponding to single and double scattering to update both the velocity model and the component of the velocity (perturbation) responsible for the single and double scattering. The combined inversion helps us access most of the potential model wavenumber information that may be embedded in the data. A scattering angle filter is used to divide the gradient of the combined inversion so initially the high wavenumber (low scattering angle) components of the gradient is directed to the perturbation model and the low wavenumber (high scattering angle) components to the velocity model. As our background velocity matures, the scattering angle divide is slowly lowered to allow for more of the higher wavenumbers to contribute the velocity model.
A nuclear radiation multi-parameter measurement system based on pulse-shape sampling

International Nuclear Information System (INIS)

Qiu Xiaolin; Fang Guoming; Xu Peng; Di Yuming

2007-01-01

In this paper, A nuclear radiation multi-parameter measurement system based on pulse-shape sampling is introduced, including the system's characteristics, composition, operating principle, experiment data and analysis. Compared with conventional nuclear measuring apparatus, it has some remarkable advantages such as the synchronous detection using multi-parameter measurement in the same measurement platform and the general analysis of signal data by user-defined program. (authors)

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

Science.gov (United States)

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.
Three-dimensional gravity modeling and focusing inversion using rectangular meshes.

Energy Technology Data Exchange (ETDEWEB)

Commer, M.

2011-03-01

Rectangular grid cells are commonly used for the geophysical modeling of gravity anomalies, owing to their flexibility in constructing complex models. The straightforward handling of cubic cells in gravity inversion algorithms allows for a flexible imposition of model regularization constraints, which are generally essential in the inversion of static potential field data. The first part of this paper provides a review of commonly used expressions for calculating the gravity of a right polygonal prism, both for gravity and gradiometry, where the formulas of Plouff and Forsberg are adapted. The formulas can be cast into general forms practical for implementation. In the second part, a weighting scheme for resolution enhancement at depth is presented. Modelling the earth using highly digitized meshes, depth weighting schemes are typically applied to the model objective functional, subject to minimizing the data misfit. The scheme proposed here involves a non-linear conjugate gradient inversion scheme with a weighting function applied to the non-linear conjugate gradient scheme's gradient vector of the objective functional. The low depth resolution due to the quick decay of the gravity kernel functions is counteracted by suppressing the search directions in the parameter space that would lead to near-surface concentrations of gravity anomalies. Further, a density parameter transformation function enabling the imposition of lower and upper bounding constraints is employed. Using synthetic data from models of varying complexity and a field data set, it is demonstrated that, given an adequate depth weighting function, the gravity inversion in the transform space can recover geologically meaningful models requiring a minimum of prior information and user interaction.
Accelerated whole-brain multi-parameter mapping using blind compressed sensing.

Science.gov (United States)

Bhave, Sampada; Lingala, Sajan Goud; Johnson, Casey P; Magnotta, Vincent A; Jacob, Mathews

2016-03-01

To introduce a blind compressed sensing (BCS) framework to accelerate multi-parameter MR mapping, and demonstrate its feasibility in high-resolution, whole-brain T1ρ and T2 mapping. BCS models the evolution of magnetization at every pixel as a sparse linear combination of bases in a dictionary. Unlike compressed sensing, the dictionary and the sparse coefficients are jointly estimated from undersampled data. Large number of non-orthogonal bases in BCS accounts for more complex signals than low rank representations. The low degree of freedom of BCS, attributed to sparse coefficients, translates to fewer artifacts at high acceleration factors (R). From 2D retrospective undersampling experiments, the mean square errors in T1ρ and T2 maps were observed to be within 0.1% up to R = 10. BCS was observed to be more robust to patient-specific motion as compared to other compressed sensing schemes and resulted in minimal degradation of parameter maps in the presence of motion. Our results suggested that BCS can provide an acceleration factor of 8 in prospective 3D imaging with reasonable reconstructions. BCS considerably reduces scan time for multiparameter mapping of the whole brain with minimal artifacts, and is more robust to motion-induced signal changes compared to current compressed sensing and principal component analysis-based techniques. © 2015 Wiley Periodicals, Inc.
Period-dependent source rupture behavior of the 2011 Tohoku earthquake estimated by multi period-band Bayesian waveform inversion

Science.gov (United States)

Kubo, H.; Asano, K.; Iwata, T.; Aoi, S.

2014-12-01

Previous studies for the period-dependent source characteristics of the 2011 Tohoku earthquake (e.g., Koper et al., 2011; Lay et al., 2012) were based on the short and long period source models using different method. Kubo et al. (2013) obtained source models of the 2011 Tohoku earthquake using multi period-bands waveform data by a common inversion method and discussed its period-dependent source characteristics. In this study, to achieve more in detail spatiotemporal source rupture behavior of this event, we introduce a new fault surface model having finer sub-fault size and estimate the source models in multi period-bands using a Bayesian inversion method combined with a multi-time-window method. Three components of velocity waveforms at 25 stations of K-NET, KiK-net, and F-net of NIED are used in this analysis. The target period band is 10-100 s. We divide this period band into three period bands (10-25 s, 25-50 s, and 50-100 s) and estimate a kinematic source model in each period band using a Bayesian inversion method with MCMC sampling (e.g., Fukuda & Johnson, 2008; Minson et al., 2013, 2014). The parameterization of spatiotemporal slip distribution follows the multi-time-window method (Hartzell & Heaton, 1983). The Green's functions are calculated by the 3D FDM (GMS; Aoi & Fujiwara, 1999) using a 3D velocity structure model (JIVSM; Koketsu et al., 2012). The assumed fault surface model is based on the Pacific plate boundary of JIVSM and is divided into 384 subfaults of about 16 * 16 km^2. The estimated source models in multi period-bands show the following source image: (1) First deep rupture off Miyagi at 0-60 s toward down-dip mostly radiating relatively short period (10-25 s) seismic waves. (2) Shallow rupture off Miyagi at 45-90 s toward up-dip with long duration radiating long period (50-100 s) seismic wave. (3) Second deep rupture off Miyagi at 60-105 s toward down-dip radiating longer period seismic waves then that of the first deep rupture. (4) Deep
Comparative Study of Evolutionary Multi-objective Optimization Algorithms for a Non-linear Greenhouse Climate Control Problem

DEFF Research Database (Denmark)

Ghoreishi, Newsha; Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard

2015-01-01

Non-trivial real world decision-making processes usually involve multiple parties having potentially conflicting interests over a set of issues. State-of-the-art multi-objective evolutionary algorithms (MOEA) are well known to solve this class of complex real-world problems. In this paper, we...... compare the performance of state-of-the-art multi-objective evolutionary algorithms to solve a non-linear multi-objective multi-issue optimisation problem found in Greenhouse climate control. The chosen algorithms in the study includes NSGAII, eNSGAII, eMOEA, PAES, PESAII and SPEAII. The performance...... of all aforementioned algorithms is assessed and compared using performance indicators to evaluate proximity, diversity and consistency. Our insights to this comparative study enhanced our understanding of MOEAs performance in order to solve a non-linear complex climate control problem. The empirical...
Design of a Multi-Bunch BPM for the Next Linear Collider

International Nuclear Information System (INIS)

Young, Andrew

2003-01-01

The Next Linear Collider (NLC) design requires precise control of colliding trains of high-intensity (1.4 x 10 10 particles/bunch) and low-emittance beams. High-resolution multi-bunch beam position monitors (BPMs) are required to ensure uniformity across the bunch trains with bunch spacing of 1.4ns. A high bandwidth (∼350 MHz) multi-bunch BPM has been designed based on a custom-made stripline sum and difference hybrid on a Teflon-based material. High bandwidth RF couplers were included to allow injection of a calibration tone. Three prototype BPMs were fabricated at SLAC and tested in the Accelerator Test Facility at KEK and in the PEP-II ring at SLAC. Tone calibration data and single-bunch and multi-bunch beam data were taken with high-speed (5Gsa/s) digitizers. Offline analysis determined the deconvolution of individual bunches in the multi-bunch mode by using the measured single bunch response. The results of these measurements are presented in this paper
Calculation of high-temperature insulation parameters and heat transfer behaviors of multilayer insulation by inverse problems method

Directory of Open Access Journals (Sweden)

Huang Can

2014-08-01

Full Text Available In the present paper, a numerical model combining radiation and conduction for porous materials is developed based on the finite volume method. The model can be used to investigate high-temperature thermal insulations which are widely used in metallic thermal protection systems on reusable launch vehicles and high-temperature fuel cells. The effective thermal conductivities (ECTs which are measured experimentally can hardly be used separately to analyze the heat transfer behaviors of conduction and radiation for high-temperature insulation. By fitting the effective thermal conductivities with experimental data, the equivalent radiation transmittance, absorptivity and reflectivity, as well as a linear function to describe the relationship between temperature and conductivity can be estimated by an inverse problems method. The deviation between the calculated and measured effective thermal conductivities is less than 4%. Using the material parameters so obtained for conduction and radiation, the heat transfer process in multilayer thermal insulation (MTI is calculated and the deviation between the calculated and the measured transient temperatures at a certain depth in the multilayer thermal insulation is less than 6.5%.
Multi-Parameter Measurement in Unseeded Flows using Femtosecond Lasers

Data.gov (United States)

National Aeronautics and Space Administration — Our approach is to use new turn-key femtosecond laser technology along with new high-speed CMOS camera technology to build a multi-parameter measurement system based...
Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

Energy Technology Data Exchange (ETDEWEB)

Jing, Yaqi; Meng, Qinghao, E-mail: qh-meng@tju.edu.cn; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen [Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

2014-05-15

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.
Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

International Nuclear Information System (INIS)

Jing, Yaqi; Meng, Qinghao; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen

2014-01-01

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively
Approximate inverse preconditioning of iterative methods for nonsymmetric linear systems

Energy Technology Data Exchange (ETDEWEB)

Benzi, M. [Universita di Bologna (Italy); Tuma, M. [Inst. of Computer Sciences, Prague (Czech Republic)

1996-12-31

A method for computing an incomplete factorization of the inverse of a nonsymmetric matrix A is presented. The resulting factorized sparse approximate inverse is used as a preconditioner in the iterative solution of Ax = b by Krylov subspace methods.
Genetic parameters for racing records in trotters using linear and generalized linear models.

Science.gov (United States)

Suontama, M; van der Werf, J H J; Juga, J; Ojala, M

2012-09-01

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.
Probabilistic teleportation via multi-parameter measurements and partially entangled states

Science.gov (United States)

Wei, Jiahua; Shi, Lei; Han, Chen; Xu, Zhiyan; Zhu, Yu; Wang, Gang; Wu, Hao

2018-04-01

In this paper, a novel scheme for probabilistic teleportation is presented with multi-parameter measurements via a non-maximally entangled state. This is in contrast to the fact that the measurement kinds for quantum teleportation are usually particular in most previous schemes. The detail implementation producers for our proposal are given by using of appropriate local unitary operations. Moreover, the total success probability and classical information of this proposal are calculated. It is demonstrated that the success probability and classical cost would be changed with the multi-measurement parameters and the entanglement factor of quantum channel. Our scheme could enlarge the research range of probabilistic teleportation.
Forward modelling of multi-component induction logging tools in layered anisotropic dipping formations

International Nuclear Information System (INIS)

Gao, Jie; Xu, Chenhao; Xiao, Jiaqi

2013-01-01

Multi-component induction logging provides great assistance in the exploration of thinly laminated reservoirs. The 1D parametric inversion following an adaptive borehole correction is the key step in the data processing of multi-component induction logging responses. To make the inversion process reasonably fast, an efficient forward modelling method is necessary. In this paper, a modelling method has been developed to simulate the multi-component induction tools in deviated wells drilled in layered anisotropic formations. With the introduction of generalized reflection coefficients, the analytic expressions of magnetic field in the form of a Sommerfeld integral were derived. The fast numerical computation of the integral has been completed by using the fast Fourier–Hankel transform and fast Hankel transform methods. The latter is so time efficient that it is competent enough for real-time multi-parameter inversion. In this paper, some simulated results have been presented and they are in excellent agreement with the finite difference method code's solution. (paper)
Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

Science.gov (United States)

Li, Chuanfeng; Wang, Yongji; Deng, Zhixiang; Wu, Hao

2009-10-01

A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.
Gravity inversion code

International Nuclear Information System (INIS)

Burkhard, N.R.

1979-01-01

The gravity inversion code applies stabilized linear inverse theory to determine the topography of a subsurface density anomaly from Bouguer gravity data. The gravity inversion program consists of four source codes: SEARCH, TREND, INVERT, and AVERAGE. TREND and INVERT are used iteratively to converge on a solution. SEARCH forms the input gravity data files for Nevada Test Site data. AVERAGE performs a covariance analysis on the solution. This document describes the necessary input files and the proper operation of the code. 2 figures, 2 tables
Millimeter-Wave Radar Field Measurements and Inversion of Cloud Parameters for the 1999 Mt. Washington Icing Sensors Project

Science.gov (United States)

Pazmany, Andrew L.; Reehorst, Andrew (Technical Monitor)

2001-01-01

The Mount Washington Icing Sensors Project (MWISP) was a multi-investigator experiment with participants from Quadrant Engineering, NOAA Environmental Technology Laboratory (NOAA/ETL), the Microwave Remote Sensing Laboratory (MIRSL) of the University of Massachusetts (UMass), and others. Radar systems from UMass and NOAA/ETL were used to measure X-, Ka-, and W-band backscatter data from the base of Mt. Washington, while simultaneous in-situ particle measurements were made from aircraft and from the observatory at the summit. This report presents range and time profiles of liquid water content and particle size parameters derived from range profiles of radar reflectivity as measured at X-, Ka-, and W-band (9.3, 33.1, and 94.9 GHz) using an artificial neural network inversion algorithm. In this report, we provide a brief description of the experiment configuration, radar systems, and a review of the artificial neural network used to extract cloud parameters from the radar data. Time histories of liquid water content (LWC), mean volume diameter (MVD) and mean Z diameter (MZD) are plotted at 300 m range intervals for slant ranges between 1.1 and 4 km. Appendix A provides details on the extraction of radar reflectivity from measured radar power, and Appendix B provides summary logs of the weather conditions for each day in which we processed data.
A novel approach to linearization of the electromagnetic parameters of tokamaks with an iron core

Energy Technology Data Exchange (ETDEWEB)

Fu, P. E-mail: fupeng@mail.ipp.ac.cn; Liu, Z.Z.; Zou, J.H

2002-05-01

The equivalent model of an iron core tokamak is developed, in which the electromagnetic parameters of several pairs of coils in opposite series (PCOS) are not dependent on the saturation of the iron core during tokamak operation. With this the electromagnetic parameters of all the coils in an iron core tokamak can be linearized, As an example, the electromagnetic parameters of Hefei Super-conductive Tokamak with iron core (HT-7) are linearized, and it is in good agreement with the experimental results. The linearization approach can be applied in real time plasma control and electromagnetic analysis.
Efficient full decay inversion of MRS data with a stretched-exponential approximation of the ? distribution

Science.gov (United States)

Behroozmand, Ahmad A.; Auken, Esben; Fiandaca, Gianluca; Christiansen, Anders Vest; Christensen, Niels B.

2012-08-01

We present a new, efficient and accurate forward modelling and inversion scheme for magnetic resonance sounding (MRS) data. MRS, also called surface-nuclear magnetic resonance (surface-NMR), is the only non-invasive geophysical technique that directly detects free water in the subsurface. Based on the physical principle of NMR, protons of the water molecules in the subsurface are excited at a specific frequency, and the superposition of signals from all protons within the excited earth volume is measured to estimate the subsurface water content and other hydrological parameters. In this paper, a new inversion scheme is presented in which the entire data set is used, and multi-exponential behaviour of the NMR signal is approximated by the simple stretched-exponential approach. Compared to the mono-exponential interpretation of the decaying NMR signal, we introduce a single extra parameter, the stretching exponent, which helps describe the porosity in terms of a single relaxation time parameter, and helps to determine correct initial amplitude and relaxation time of the signal. Moreover, compared to a multi-exponential interpretation of the MRS data, the decay behaviour is approximated with considerably fewer parameters. The forward response is calculated in an efficient numerical manner in terms of magnetic field calculation, discretization and integration schemes, which allows fast computation while maintaining accuracy. A piecewise linear transmitter loop is considered for electromagnetic modelling of conductivities in the layered half-space providing electromagnetic modelling of arbitrary loop shapes. The decaying signal is integrated over time windows, called gates, which increases the signal-to-noise ratio, particularly at late times, and the data vector is described with a minimum number of samples, that is, gates. The accuracy of the forward response is investigated by comparing a MRS forward response with responses from three other approaches outlining
Evaluation for Bearing Wear States Based on Online Oil Multi-Parameters Monitoring

Directory of Open Access Journals (Sweden)

Si-Yuan Wang

2018-04-01

Full Text Available As bearings are critical components of a mechanical system, it is important to characterize their wear states and evaluate health conditions. In this paper, a novel approach for analyzing the relationship between online oil multi-parameter monitoring samples and bearing wear states has been proposed based on an improved gray k-means clustering model (G-KCM. First, an online monitoring system with multiple sensors for bearings is established, obtaining oil multi-parameter data and vibration signals for bearings through the whole lifetime. Secondly, a gray correlation degree distance matrix is generated using a gray correlation model (GCM to express the relationship of oil monitoring samples at different times and then a KCM is applied to cluster the matrix. Analysis and experimental results show that there is an obvious correspondence that state changing coincides basically in time between the lubricants’ multi-parameters and the bearings’ wear states. It also has shown that online oil samples with multi-parameters have early wear failure prediction ability for bearings superior to vibration signals. It is expected to realize online oil monitoring and evaluation for bearing health condition and to provide a novel approach for early identification of bearing-related failure modes.

Modelling Loudspeaker Non-Linearities

DEFF Research Database (Denmark)

Agerkvist, Finn T.

2007-01-01

This paper investigates different techniques for modelling the non-linear parameters of the electrodynamic loudspeaker. The methods are tested not only for their accuracy within the range of original data, but also for the ability to work reasonable outside that range, and it is demonstrated...... that polynomial expansions are rather poor at this, whereas an inverse polynomial expansion or localized fitting functions such as the gaussian are better suited for modelling the Bl-factor and compliance. For the inductance the sigmoid function is shown to give very good results. Finally the time varying...
LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

Directory of Open Access Journals (Sweden)

O. Tichý

2016-11-01

Full Text Available Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. It is typically formalized as an inverse problem using a linear model that can explain observable quantities (e.g., concentrations or deposition values as a product of the source-receptor sensitivity (SRS matrix obtained from an atmospheric transport model multiplied by the unknown source-term vector. Since this problem is typically ill-posed, current state-of-the-art methods are based on regularization of the problem and solution of a formulated optimization problem. This procedure depends on manual settings of uncertainties that are often very poorly quantified, effectively making them tuning parameters. We formulate a probabilistic model, that has the same maximum likelihood solution as the conventional method using pre-specified uncertainties. Replacement of the maximum likelihood solution by full Bayesian estimation also allows estimation of all tuning parameters from the measurements. The estimation procedure is based on the variational Bayes approximation which is evaluated by an iterative algorithm. The resulting method is thus very similar to the conventional approach, but with the possibility to also estimate all tuning parameters from the observations. The proposed algorithm is tested and compared with the standard methods on data from the European Tracer Experiment (ETEX where advantages of the new method are demonstrated. A MATLAB implementation of the proposed algorithm is available for download.
LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

Science.gov (United States)

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek; Stohl, Andreas

2016-11-01

Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. It is typically formalized as an inverse problem using a linear model that can explain observable quantities (e.g., concentrations or deposition values) as a product of the source-receptor sensitivity (SRS) matrix obtained from an atmospheric transport model multiplied by the unknown source-term vector. Since this problem is typically ill-posed, current state-of-the-art methods are based on regularization of the problem and solution of a formulated optimization problem. This procedure depends on manual settings of uncertainties that are often very poorly quantified, effectively making them tuning parameters. We formulate a probabilistic model, that has the same maximum likelihood solution as the conventional method using pre-specified uncertainties. Replacement of the maximum likelihood solution by full Bayesian estimation also allows estimation of all tuning parameters from the measurements. The estimation procedure is based on the variational Bayes approximation which is evaluated by an iterative algorithm. The resulting method is thus very similar to the conventional approach, but with the possibility to also estimate all tuning parameters from the observations. The proposed algorithm is tested and compared with the standard methods on data from the European Tracer Experiment (ETEX) where advantages of the new method are demonstrated. A MATLAB implementation of the proposed algorithm is available for download.
Stability of multi-objective bi-level linear programming problems under fuzziness

Directory of Open Access Journals (Sweden)

Abo-Sinna Mahmoud A.

2013-01-01

Full Text Available This paper deals with multi-objective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multi-objective bi-level linear programming problems. An algorithm for obtaining any subset of the parametric space, which has the same corresponding Pareto optimal solution, is presented. Also, this paper established the model for the supply-demand interaction in the age of electronic commerce (EC. First of all, the study uses the individual objectives of both parties as the foundation of the supply-demand interaction. Subsequently, it divides the interaction, in the age of electronic commerce, into the following two classifications: (i Market transactions, with the primary focus on the supply demand relationship in the marketplace; and (ii Information service, with the primary focus on the provider and the user of information service. By applying the bi-level programming technique of interaction process, the study will develop an analytical process to explain how supply-demand interaction achieves a compromise or why the process fails. Finally, a numerical example of information service is provided for the sake of illustration.
Ultra-Weak Fiber Bragg Grating Sensing Network Coated with Sensitive Material for Multi-Parameter Measurements

Directory of Open Access Journals (Sweden)

Wei Bai

2017-06-01

Full Text Available A multi-parameter measurement system based on ultra-weak fiber Bragg grating (UFBG array with sensitive material was proposed and experimentally demonstrated. The UFBG array interrogation principle is time division multiplex technology with two semiconductor optical amplifiers as timing units. Experimental results showed that the performance of the proposed UFBG system is almost equal to that of traditional FBG, while the UFBG array system has obvious superiority with potential multiplexing ability for multi-point and multi-parameter measurement. The system experimented on a 144 UFBG array with the reflectivity of UFBG ~0.04% for the four target parameters: hydrogen, humidity, temperature and salinity. Moreover, a uniform solution was customized to divide the cross-sensitivity between temperature and other target parameters. It is expected that this scheme will be capable of handling thousands of multi-parameter sensors in a single fiber.
Ultra-Weak Fiber Bragg Grating Sensing Network Coated with Sensitive Material for Multi-Parameter Measurements.

Science.gov (United States)

Bai, Wei; Yang, Minghong; Hu, Chenyuan; Dai, Jixiang; Zhong, Xuexiang; Huang, Shuai; Wang, Gaopeng

2017-06-26

A multi-parameter measurement system based on ultra-weak fiber Bragg grating (UFBG) array with sensitive material was proposed and experimentally demonstrated. The UFBG array interrogation principle is time division multiplex technology with two semiconductor optical amplifiers as timing units. Experimental results showed that the performance of the proposed UFBG system is almost equal to that of traditional FBG, while the UFBG array system has obvious superiority with potential multiplexing ability for multi-point and multi-parameter measurement. The system experimented on a 144 UFBG array with the reflectivity of UFBG ~0.04% for the four target parameters: hydrogen, humidity, temperature and salinity. Moreover, a uniform solution was customized to divide the cross-sensitivity between temperature and other target parameters. It is expected that this scheme will be capable of handling thousands of multi-parameter sensors in a single fiber.
Consensus for linear multi-agent system with intermittent information transmissions using the time-scale theory

Science.gov (United States)

Taousser, Fatima; Defoort, Michael; Djemai, Mohamed

2016-01-01

This paper investigates the consensus problem for linear multi-agent system with fixed communication topology in the presence of intermittent communication using the time-scale theory. Since each agent can only obtain relative local information intermittently, the proposed consensus algorithm is based on a discontinuous local interaction rule. The interaction among agents happens at a disjoint set of continuous-time intervals. The closed-loop multi-agent system can be represented using mixed linear continuous-time and linear discrete-time models due to intermittent information transmissions. The time-scale theory provides a powerful tool to combine continuous-time and discrete-time cases and study the consensus protocol under a unified framework. Using this theory, some conditions are derived to achieve exponential consensus under intermittent information transmissions. Simulations are performed to validate the theoretical results.
Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling

Directory of Open Access Journals (Sweden)

Shirmohammadi Adel

2006-10-01

Full Text Available Abstract Background Quantification of in-vivo biomolecule mass transport and reaction rate parameters from experimental data obtained by Fluorescence Recovery after Photobleaching (FRAP is becoming more important. Methods and results The Osborne-Moré extended version of the Levenberg-Marquardt optimization algorithm was coupled with the experimental data obtained by the Fluorescence Recovery after Photobleaching (FRAP protocol, and the numerical solution of a set of two partial differential equations governing macromolecule mass transport and reaction in living cells, to inversely estimate optimized values of the molecular diffusion coefficient and binding rate parameters of GFP-tagged glucocorticoid receptor. The results indicate that the FRAP protocol provides enough information to estimate one parameter uniquely using a nonlinear optimization technique. Coupling FRAP experimental data with the inverse modeling strategy, one can also uniquely estimate the individual values of the binding rate coefficients if the molecular diffusion coefficient is known. One can also simultaneously estimate the dissociation rate parameter and molecular diffusion coefficient given the pseudo-association rate parameter is known. However, the protocol provides insufficient information for unique simultaneous estimation of three parameters (diffusion coefficient and binding rate parameters owing to the high intercorrelation between the molecular diffusion coefficient and pseudo-association rate parameter. Attempts to estimate macromolecule mass transport and binding rate parameters simultaneously from FRAP data result in misleading conclusions regarding concentrations of free macromolecule and bound complex inside the cell, average binding time per vacant site, average time for diffusion of macromolecules from one site to the next, and slow or rapid mobility of biomolecules in cells. Conclusion To obtain unique values for molecular diffusion coefficient and
Determination of temperature dependency of material parameters for lead-free alkali niobate piezoceramics by the inverse method

Directory of Open Access Journals (Sweden)

K. Ogo

2016-06-01

Full Text Available Sodium potassium niobate (NKN piezoceramics have been paid much attention as lead-free piezoelectric materials in high temperature devices because of their high Curie temperature. The temperature dependency of their material parameters, however, has not been determined in detail up to now. For this purpose, we exploit the so-called Inverse Method denoting a simulation-based characterization approach. Compared with other characterization methods, the Inverse Method requires only one sample shape of the piezoceramic material and has further decisive advantages. The identification of material parameters showed that NKN is mechanically softer in shear direction compared with lead zirconate titanate (PZT at room temperature. The temperature dependency of the material parameters of NKN was evaluated in the temperature range from 30 °C to 150 °C. As a result, we figured out that dielectric constants and piezoelectric constants show a monotonous and isotropic increment with increasing temperature. On the other hand, elastic stiffness constant c 44 E of NKN significantly decreased in contrast to other elastic stiffness constants. It could be revealed that the decrement of c 44 E is associated with an orthorhombic-tetragonal phase transition. Furthermore, ratio of elastic compliance constants s 44 E / s 33 E exhibited similar temperature dependent behavior to the ratio of piezoelectric constants d15/d33. It is suspected that mechanical softness in shear direction is one origin of the large piezoelectric shear mode of NKN. Our results show that NKN are suitable for high temperature devices, and that the Inverse Method should be a helpful approach to characterize material parameters under their practical operating conditions for NKN.
Source Estimation by Full Wave Form Inversion

Energy Technology Data Exchange (ETDEWEB)

Sjögreen, Björn [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing; Petersson, N. Anders [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing

2013-08-07

Given time-dependent ground motion recordings at a number of receiver stations, we solve the inverse problem for estimating the parameters of the seismic source. The source is modeled as a point moment tensor source, characterized by its location, moment tensor components, the start time, and frequency parameter (rise time) of its source time function. In total, there are 11 unknown parameters. We use a non-linear conjugate gradient algorithm to minimize the full waveform misfit between observed and computed ground motions at the receiver stations. An important underlying assumption of the minimization problem is that the wave propagation is accurately described by the elastic wave equation in a heterogeneous isotropic material. We use a fourth order accurate finite difference method, developed in [12], to evolve the waves forwards in time. The adjoint wave equation corresponding to the discretized elastic wave equation is used to compute the gradient of the misfit, which is needed by the non-linear conjugated minimization algorithm. A new source point moment source discretization is derived that guarantees that the Hessian of the misfit is a continuous function of the source location. An efficient approach for calculating the Hessian is also presented. We show how the Hessian can be used to scale the problem to improve the convergence of the non-linear conjugated gradient algorithm. Numerical experiments are presented for estimating the source parameters from synthetic data in a layer over half-space problem (LOH.1), illustrating rapid convergence of the proposed approach.
Inverse Theory for Petroleum Reservoir Characterization and History Matching

Science.gov (United States)

Oliver, Dean S.; Reynolds, Albert C.; Liu, Ning

This book is a guide to the use of inverse theory for estimation and conditional simulation of flow and transport parameters in porous media. It describes the theory and practice of estimating properties of underground petroleum reservoirs from measurements of flow in wells, and it explains how to characterize the uncertainty in such estimates. Early chapters present the reader with the necessary background in inverse theory, probability and spatial statistics. The book demonstrates how to calculate sensitivity coefficients and the linearized relationship between models and production data. It also shows how to develop iterative methods for generating estimates and conditional realizations. The text is written for researchers and graduates in petroleum engineering and groundwater hydrology and can be used as a textbook for advanced courses on inverse theory in petroleum engineering. It includes many worked examples to demonstrate the methodologies and a selection of exercises.
The linear parameters and the decoupling matrix for linearly coupled motion in 6 dimensional phase space

International Nuclear Information System (INIS)

Parzen, G.

1997-01-01

It will be shown that starting from a coordinate system where the 6 phase space coordinates are linearly coupled, one can go to a new coordinate system, where the motion is uncoupled, by means of a linear transformation. The original coupled coordinates and the new uncoupled coordinates are related by a 6 x 6 matrix, R. It will be shown that of the 36 elements of the 6 x 6 decoupling matrix R, only 12 elements are independent. A set of equations is given from which the 12 elements of R can be computed form the one period transfer matrix. This set of equations also allows the linear parameters, the β i , α i , i = 1, 3, for the uncoupled coordinates, to be computed from the one period transfer matrix
A Smart Multi-parameter Sensor with Online Monitoring for the Aquaculture in China

OpenAIRE

Peng , Fa; Wang , Jinxing; Liu , Shuangxi; Li , Daoliang; Xu , Dan; Wang , Yang

2013-01-01

International audience; PH, DO,ORP, EC and water-level are important parameters of the aquaculture monitoring. But the high cost of foreign sensors and high-energy consumption of Chinese sensors make it impossible for wide use in China. This paper uses MCU STM8L152 to realize the ultralow power design. With simple hardware structure design, the cost of the multi-parameter sensor can be reduced .The experiment data of the multi-parameter sensor contrasting with the results obtained by Hach mul...
Linear orbit parameters for the exact equations of motion

International Nuclear Information System (INIS)

Parzen, G.

1995-01-01

This paper defines the beta function and other linear orbit parameters using the exact equations of motion. The β, α and ψ functions are redefined using the exact equations. Expressions are found for the transfer matrix and the emittance. The differential equations for η = x/β 1/2 is found. New relationships between α, β, ψ and ν are derived
Seismic inverse scattering in the downward continuation approach

NARCIS (Netherlands)

Stolk, C.C.; de Hoop, M.V.

Seismic data are commonly modeled by a linearization around a smooth background medium in combination with a high frequency approximation. The perturbation of the medium coefficient is assumed to contain the discontinuities. This leads to two inverse problems, first the linearized inverse problem
Wake Vortex Inverse Model User's Guide

Science.gov (United States)

Lai, David; Delisi, Donald

2008-01-01

NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input
Sensor module design and forward and inverse kinematics analysis of 6-DOF sorting transferring robot

Science.gov (United States)

Zhou, Huiying; Lin, Jiajian; Liu, Lei; Tao, Meng

2017-09-01

To meet the demand of high strength express sorting, it is significant to design a robot with multiple degrees of freedom that can sort and transfer. This paper uses infrared sensor, color sensor and pressure sensor to receive external information, combine the plan of motion path in advance and the feedback information from the sensors, then write relevant program. In accordance with these, we can design a 6-DOF robot that can realize multi-angle seizing. In order to obtain characteristics of forward and inverse kinematics, this paper describes the coordinate directions and pose estimation by the D-H parameter method and closed solution. On the basis of the solution of forward and inverse kinematics, geometric parameters of links and link parameters are optimized in terms of application requirements. In this way, this robot can identify route, sort and transfer.
The response of a linear monostable system and its application in parameters estimation for PSK signals

International Nuclear Information System (INIS)

Duan, Chaowei; Zhan, Yafeng

2016-01-01

The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance. - Highlights: • The response of a linear monostable system driven with a periodic signal and an additive white Gaussian noise is analyzed. • The optimal parameter of this linear monostable system to maximum the output SNR-gain is obtained. • Application of this linear monostable system in parameters estimation algorithm for PSK signals obtains performance improvement.
A new approach to the inverse kinematics of a multi-joint robot manipulator using a minimization method

International Nuclear Information System (INIS)

Sasaki, Shinobu

1987-01-01

This paper proposes a new approach to solve the inverse kinematics of a type of sixlink manipulator. Directing our attention to features of joint structures of the manipulator, the original problem is first formulated by a system of equations with four variables and solved by means of a minimization technique. The remaining two variables are determined from constrained conditions involved. This is the basic idea in the present approach. The results of computer simulation of the present algorithm showed that the accuracies of solutions and convergence speed are much higher and quite satisfactory for practical purposes, as compared with the linearization-iteration method based on the conventional inverse Jacobian matrix. (author)
Forest parameter estimation using polarimetric SAR interferometry techniques at low frequencies

International Nuclear Information System (INIS)

Lee, Seung-Kuk

2013-01-01

Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) is an active radar remote sensing technique based on the coherent combination of both polarimetric and interferometric observables. The Pol-InSAR technique provided a step forward in quantitative forest parameter estimation. In the last decade, airborne SAR experiments evaluated the potential of Pol-InSAR techniques to estimate forest parameters (e.g., the forest height and biomass) with high accuracy over various local forest test sites. This dissertation addresses the actual status, potentials and limitations of Pol-InSAR inversion techniques for 3-D forest parameter estimations on a global scale using lower frequencies such as L- and P-band. The multi-baseline Pol-InSAR inversion technique is applied to optimize the performance with respect to the actual level of the vertical wave number and to mitigate the impact of temporal decorrelation on the Pol-InSAR forest parameter inversion. Temporal decorrelation is a critical issue for successful Pol-InSAR inversion in the case of repeat-pass Pol-InSAR data, as provided by conventional satellites or airborne SAR systems. Despite the limiting impact of temporal decorrelation in Pol-InSAR inversion, it remains a poorly understood factor in forest height inversion. Therefore, the main goal of this dissertation is to provide a quantitative estimation of the temporal decorrelation effects by using multi-baseline Pol-InSAR data. A new approach to quantify the different temporal decorrelation components is proposed and discussed. Temporal decorrelation coefficients are estimated for temporal baselines ranging from 10 minutes to 54 days and are converted to height inversion errors. In addition, the potential of Pol-InSAR forest parameter estimation techniques is addressed and projected onto future spaceborne system configurations and mission scenarios (Tandem-L and BIOMASS satellite missions at L- and P-band). The impact of the system parameters (e.g., bandwidth

Linearly decoupled energy-stable numerical methods for multi-component two-phase compressible flow

KAUST Repository

Kou, Jisheng; Sun, Shuyu; Wang, Xiuhua

2017-01-01

involved in the discrete momentum equation to ensure a consistency relationship with the mass balance equations. Moreover, we propose a component-wise SAV approach for a multi-component fluid, which requires solving a sequence of linear, separate mass
Alternating minimisation for glottal inverse filtering

International Nuclear Information System (INIS)

Bleyer, Ismael Rodrigo; Lybeck, Lasse; Auvinen, Harri; Siltanen, Samuli; Airaksinen, Manu; Alku, Paavo

2017-01-01

A new method is proposed for solving the glottal inverse filtering (GIF) problem. The goal of GIF is to separate an acoustical speech signal into two parts: the glottal airflow excitation and the vocal tract filter. To recover such information one has to deal with a blind deconvolution problem. This ill-posed inverse problem is solved under a deterministic setting, considering unknowns on both sides of the underlying operator equation. A stable reconstruction is obtained using a double regularization strategy, alternating between fixing either the glottal source signal or the vocal tract filter. This enables not only splitting the nonlinear and nonconvex problem into two linear and convex problems, but also allows the use of the best parameters and constraints to recover each variable at a time. This new technique, called alternating minimization glottal inverse filtering (AM-GIF), is compared with two other approaches: Markov chain Monte Carlo glottal inverse filtering (MCMC-GIF), and iterative adaptive inverse filtering (IAIF), using synthetic speech signals. The recent MCMC-GIF has good reconstruction quality but high computational cost. The state-of-the-art IAIF method is computationally fast but its accuracy deteriorates, particularly for speech signals of high fundamental frequency ( F 0). The results show the competitive performance of the new method: With high F 0, the reconstruction quality is better than that of IAIF and close to MCMC-GIF while reducing the computational complexity by two orders of magnitude. (paper)
Linearly decoupled energy-stable numerical methods for multi-component two-phase compressible flow

KAUST Repository

Kou, Jisheng

2017-12-06

In this paper, for the first time we propose two linear, decoupled, energy-stable numerical schemes for multi-component two-phase compressible flow with a realistic equation of state (e.g. Peng-Robinson equation of state). The methods are constructed based on the scalar auxiliary variable (SAV) approaches for Helmholtz free energy and the intermediate velocities that are designed to decouple the tight relationship between velocity and molar densities. The intermediate velocities are also involved in the discrete momentum equation to ensure a consistency relationship with the mass balance equations. Moreover, we propose a component-wise SAV approach for a multi-component fluid, which requires solving a sequence of linear, separate mass balance equations. We prove that the methods have the unconditional energy-dissipation feature. Numerical results are presented to verify the effectiveness of the proposed methods.
Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment

Science.gov (United States)

Karimzadehgan, Maryam; Zhai, ChengXiang

2011-01-01

Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching. PMID:22711970
Regularized inversion of controlled source and earthquake data

International Nuclear Information System (INIS)

Ramachandran, Kumar

2012-01-01

Estimation of the seismic velocity structure of the Earth's crust and upper mantle from travel-time data has advanced greatly in recent years. Forward modelling trial-and-error methods have been superseded by tomographic methods which allow more objective analysis of large two-dimensional and three-dimensional refraction and/or reflection data sets. The fundamental purpose of travel-time tomography is to determine the velocity structure of a medium by analysing the time it takes for a wave generated at a source point within the medium to arrive at a distribution of receiver points. Tomographic inversion of first-arrival travel-time data is a nonlinear problem since both the velocity of the medium and ray paths in the medium are unknown. The solution for such a problem is typically obtained by repeated application of linearized inversion. Regularization of the nonlinear problem reduces the ill posedness inherent in the tomographic inversion due to the under-determined nature of the problem and the inconsistencies in the observed data. This paper discusses the theory of regularized inversion for joint inversion of controlled source and earthquake data, and results from synthetic data testing and application to real data. The results obtained from tomographic inversion of synthetic data and real data from the northern Cascadia subduction zone show that the velocity model and hypocentral parameters can be efficiently estimated using this approach. (paper)
Surface waves tomography and non-linear inversion in the southeast Carpathians

International Nuclear Information System (INIS)

Raykova, R.B.; Panza, G.F.

2005-11-01

A set of shear-wave velocity models of the lithosphere-asthenosphere system in the southeast Carpathians is determined by the non-linear inversion of surface wave group velocity data, obtained from a tomographic analysis. The local dispersion curves are assembled for the period range 7 s - 150 s, combining regional group velocity measurements and published global Rayleigh wave dispersion data. The lithosphere-asthenosphere velocity structure is reliably reconstructed to depths of about 250 km. The thickness of the lithosphere in the region varies from about 120 km to 250 km and the depth of the asthenosphere between 150 km and 250 km. Mantle seismicity concentrates where the high velocity lid is detected just below the Moho. The obtained results are in agreement with recent seismic refraction, receiver function, and travel time P-wave tomography investigations in the region. The similarity among the results obtained from different kinds of structural investigations (including the present work) highlights some new features of the lithosphere-asthenosphere system in southeast Carpathians, as the relatively thin crust under Transylvania basin and Vrancea zone. (author)
Inverse m-matrices and ultrametric matrices

CERN Document Server

Dellacherie, Claude; San Martin, Jaime

2014-01-01

The study of M-matrices, their inverses and discrete potential theory is now a well-established part of linear algebra and the theory of Markov chains. The main focus of this monograph is the so-called inverse M-matrix problem, which asks for a characterization of nonnegative matrices whose inverses are M-matrices. We present an answer in terms of discrete potential theory based on the Choquet-Deny Theorem. A distinguished subclass of inverse M-matrices is ultrametric matrices, which are important in applications such as taxonomy. Ultrametricity is revealed to be a relevant concept in linear algebra and discrete potential theory because of its relation with trees in graph theory and mean expected value matrices in probability theory. Remarkable properties of Hadamard functions and products for the class of inverse M-matrices are developed and probabilistic insights are provided throughout the monograph.
Quantitative multi-parameter mapping of R1, PD*, MT and R2* at 3T: a multi-center validation

Directory of Open Access Journals (Sweden)

Nikolaus eWeiskopf

2013-06-01

Full Text Available Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1mm high-resolution maps of the longitudinal relaxation rate (R1=1/T1, effective proton density (PD*, magnetization transfer saturation (MT and effective transverse relaxation rate (R2*=1/T2*. MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV for typical morphometric measures (i.e., gray matter probability maps used in voxel-based morphometry and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1% and 8%, respectively, except for the inter-site CoV of R2* (< 20%. The gray matter probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived gray matter probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.
Optimizing Photosynthetic and Respiratory Parameters Based on the Seasonal Variation Pattern in Regional Net Ecosystem Productivity Obtained from Atmospheric Inversion

Science.gov (United States)

Chen, Z.; Chen, J.; Zheng, X.; Jiang, F.; Zhang, S.; Ju, W.; Yuan, W.; Mo, G.

2014-12-01

In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation pattern of the net carbon flux. An optimization scheme is proposed to estimate two key parameters (Vcmax and Q10) by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate Vcmax and Q10 of the Boreal Ecosystem Productivity Simulator (BEPS) to improve its NEP simulation in the Boreal North America (BNA) region. Simultaneously, in-situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results have the implication on using atmospheric CO2 data for optimizing ecosystem parameters through atmospheric inversion or data assimilation techniques.
Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

Science.gov (United States)

Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

2017-11-01

Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.
An accurate solver for forward and inverse transport

International Nuclear Information System (INIS)

Monard, Francois; Bal, Guillaume

2010-01-01

This paper presents a robust and accurate way to solve steady-state linear transport (radiative transfer) equations numerically. Our main objective is to address the inverse transport problem, in which the optical parameters of a domain of interest are reconstructed from measurements performed at the domain's boundary. This inverse problem has important applications in medical and geophysical imaging, and more generally in any field involving high frequency waves or particles propagating in scattering environments. Stable solutions of the inverse transport problem require that the singularities of the measurement operator, which maps the optical parameters to the available measurements, be captured with sufficient accuracy. This in turn requires that the free propagation of particles be calculated with care, which is a difficult problem on a Cartesian grid. A standard discrete ordinates method is used for the direction of propagation of the particles. Our methodology to address spatial discretization is based on rotating the computational domain so that each direction of propagation is always aligned with one of the grid axes. Rotations are performed in the Fourier domain to achieve spectral accuracy. The numerical dispersion of the propagating particles is therefore minimal. As a result, the ballistic and single scattering components of the transport solution are calculated robustly and accurately. Physical blurring effects, such as small angular diffusion, are also incorporated into the numerical tool. Forward and inverse calculations performed in a two-dimensional setting exemplify the capabilities of the method. Although the methodology might not be the fastest way to solve transport equations, its physical accuracy provides us with a numerical tool to assess what can and cannot be reconstructed in inverse transport theory.
An analysis of AVO inversion for postcritical offsets in HTI media

KAUST Repository

Skopintseva, Lyubov

2013-04-12

Azimuthal variations of wavefield characteristics, such as traveltime or reflection amplitude, play an important role in the identification of fractured media. A transversely isotropic medium with a horizontal symmetry axis (HTI medium) is the simplest azimuthally anisotropic model typically used to describe one set of vertical fractures. There exist many techniques in industry to recover anisotropic parameters based on moveout equations and linearized reflection coefficients using such a model. However, most of the methods have limitations in defining properties of the fractures due to linearizations and physical approximations used in their development. Thus, azimuthal analysis of traveltimes based on normal moveout ellipses recovers a maximum of three medium parameters instead of the required five. Linearizations made in plane-wave reflection coefficients (PWRCs) limit the amplitude-versus-offset (AVO) analysis to small incident angles and weak-contrast interfaces. Inversion based on azimuthal AVO for small offsets encounters nonuniqueness in the resolving power of the anisotropy parameters. Extending the AVO analysis and inversion to and beyond the critical reflection angle increases the amount of information recovered from the medium. However, well-accepted PWRCs are not valid in the vicinity of the critical angle and beyond it, due to frequency and spherical wave effects. Recently derived spherical and effective reflection coefficient (ERC) methods overcome this problem. We extended the ERCs approach to HTI media to analyze the potential of near- and postcritical reflections in azimuthal AVO analysis. From the sensitivity analysis, we found that ERCs are sensitive to different sets of parameters prior to and beyond the critical angle, which is useful in enhancing our resolution of the anisotropy parameters. Additionally, the resolution of the parameters depends on a sufficient azimuthal coverage in the acquisition setup. The most stable AVO results for the
An analysis of AVO inversion for postcritical offsets in HTI media

KAUST Repository

Skopintseva, Lyubov; Alkhalifah, Tariq Ali

2013-01-01

Azimuthal variations of wavefield characteristics, such as traveltime or reflection amplitude, play an important role in the identification of fractured media. A transversely isotropic medium with a horizontal symmetry axis (HTI medium) is the simplest azimuthally anisotropic model typically used to describe one set of vertical fractures. There exist many techniques in industry to recover anisotropic parameters based on moveout equations and linearized reflection coefficients using such a model. However, most of the methods have limitations in defining properties of the fractures due to linearizations and physical approximations used in their development. Thus, azimuthal analysis of traveltimes based on normal moveout ellipses recovers a maximum of three medium parameters instead of the required five. Linearizations made in plane-wave reflection coefficients (PWRCs) limit the amplitude-versus-offset (AVO) analysis to small incident angles and weak-contrast interfaces. Inversion based on azimuthal AVO for small offsets encounters nonuniqueness in the resolving power of the anisotropy parameters. Extending the AVO analysis and inversion to and beyond the critical reflection angle increases the amount of information recovered from the medium. However, well-accepted PWRCs are not valid in the vicinity of the critical angle and beyond it, due to frequency and spherical wave effects. Recently derived spherical and effective reflection coefficient (ERC) methods overcome this problem. We extended the ERCs approach to HTI media to analyze the potential of near- and postcritical reflections in azimuthal AVO analysis. From the sensitivity analysis, we found that ERCs are sensitive to different sets of parameters prior to and beyond the critical angle, which is useful in enhancing our resolution of the anisotropy parameters. Additionally, the resolution of the parameters depends on a sufficient azimuthal coverage in the acquisition setup. The most stable AVO results for the
(abstract) Using an Inversion Algorithm to Retrieve Parameters and Monitor Changes over Forested Areas from SAR Data

Science.gov (United States)

Moghaddam, Mahta

1995-01-01

In this work, the application of an inversion algorithm based on a nonlinear opimization technique to retrieve forest parameters from multifrequency polarimetric SAR data is discussed. The approach discussed here allows for retrieving and monitoring changes in forest parameters in a quantative and systematic fashion using SAR data. The parameters to be inverted directly from the data are the electromagnetic scattering properties of the forest components such as their dielectric constants and size characteristics. Once these are known, attributes such as canopy moisture content can be obtained, which are useful in the ecosystem models.
Adaptive distributed parameter and input estimation in linear parabolic PDEs

KAUST Repository

Mechhoud, Sarra

2016-01-01

In this paper, we discuss the on-line estimation of distributed source term, diffusion, and reaction coefficients of a linear parabolic partial differential equation using both distributed and interior-point measurements. First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.
New Insights on the Uncertainties in Finite-Fault Earthquake Source Inversion

KAUST Repository

Razafindrakoto, Hoby

2015-04-01

New Insights on the Uncertainties in Finite-Fault Earthquake Source Inversion Hoby Njara Tendrisoa Razafindrakoto Earthquake source inversion is a non-linear problem that leads to non-unique solutions. The aim of this dissertation is to understand the uncertainty and reliability in earthquake source inversion, as well as to quantify variability in earthquake rupture models. The source inversion is performed using a Bayesian inference. This technique augments optimization approaches through its ability to image the entire solution space which is consistent with the data and prior information. In this study, the uncertainty related to the choice of source-time function and crustal structure is investigated. Three predefined analytical source-time functions are analyzed; isosceles triangle, Yoffe with acceleration time of 0.1 and 0.3 s. The use of the isosceles triangle as source-time function is found to bias the finite-fault source inversion results. It accelerates the rupture to propagate faster compared to that of the Yoffe function. Moreover, it generates an artificial linear correlation between parameters that does not exist for the Yoffe source-time functions. The effect of inadequate knowledge of Earth’s crustal structure in earthquake rupture models is subsequently investigated. The results show that one-dimensional structure variability leads to parameters resolution changes, with a broadening of the posterior 5 PDFs and shifts in the peak location. These changes in the PDFs of kinematic parameters are associated with the blurring effect of using incorrect Earth structure. As an application to real earthquake, finite-fault source models for the 2009 L’Aquila earthquake are examined using one- and three-dimensional crustal structures. One- dimensional structure is found to degrade the data fitting. However, there is no significant effect on the rupture parameters aside from differences in the spatial slip extension. Stable features are maintained for both
Estimation of Physical Parameters in Linear and Nonlinear Dynamic Systems

DEFF Research Database (Denmark)

Knudsen, Morten

variance and confidence ellipsoid is demonstrated. The relation is based on a new theorem on maxima of an ellipsoid. The procedure for input signal design and physical parameter estimation is tested on a number of examples, linear as well as nonlinear and simulated as well as real processes, and it appears...
MicroCT parameters for multi material elements assessment

Energy Technology Data Exchange (ETDEWEB)

Araújo, Olga M.O. de; Machado, Alessandra S.; Santos, Thaís M.P. dos; Ferreira, Cintia G.; Lopes, Ricardo T., E-mail: olgaufrjlin@gmail.com [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear; Bastos, Jaqueline Silva [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), São Paulo, SP (Brazil)

2017-07-01

Microtomography is a non-destructive testing technique for quantitative and qualitative analysis. The investigation of multi material elements with great difference of density can result in artifacts that degrade image quality depending on combination of additional filter. The aim of this study is the selection of parameters most appropriate for analysis of bone tissue with metallic implant. The results show the simulation with MCNPX code for the distribution of energy without additional filter, with use of aluminum, copper and brass filters and their respective reconstructed images showing the importance of the choice of these parameters in image acquisition process on computed microtomography. (author)
Design and Analysis of MEMS Linear Phased Array

Directory of Open Access Journals (Sweden)

Guoxiang Fan

2016-01-01

Full Text Available A structure of micro-electro-mechanical system (MEMS linear phased array based on “multi-cell” element is designed to increase radiation sound pressure of transducer working in bending vibration mode at high frequency. In order to more accurately predict the resonant frequency of an element, the theoretical analysis of the dynamic equation of a fixed rectangular composite plate and finite element method simulation are adopted. The effects of the parameters both in the lateral and elevation direction on the three-dimensional beam directivity characteristics are comprehensively analyzed. The key parameters in the analysis include the “cell” number of element, “cell” size, “inter-cell” spacing and the number of elements, element width. The simulation results show that optimizing the linear array parameters both in the lateral and elevation direction can greatly improve the three-dimensional beam focusing for MEMS linear phased array, which is obviously different from the traditional linear array.
Parameter identification in a generalized time-harmonic Rayleigh damping model for elastography.

Directory of Open Access Journals (Sweden)

Elijah E W Van Houten

Full Text Available The identifiability of the two damping components of a Generalized Rayleigh Damping model is investigated through analysis of the continuum equilibrium equations as well as a simple spring-mass system. Generalized Rayleigh Damping provides a more diversified attenuation model than pure Viscoelasticity, with two parameters to describe attenuation effects and account for the complex damping behavior found in biological tissue. For heterogeneous Rayleigh Damped materials, there is no equivalent Viscoelastic system to describe the observed motions. For homogeneous systems, the inverse problem to determine the two Rayleigh Damping components is seen to be uniquely posed, in the sense that the inverse matrix for parameter identification is full rank, with certain conditions: when either multi-frequency data is available or when both shear and dilatational wave propagation is taken into account. For the multi-frequency case, the frequency dependency of the elastic parameters adds a level of complexity to the reconstruction problem that must be addressed for reasonable solutions. For the dilatational wave case, the accuracy of compressional wave measurement in fluid saturated soft tissues becomes an issue for qualitative parameter identification. These issues can be addressed with reasonable assumptions on the negligible damping levels of dilatational waves in soft tissue. In general, the parameters of a Generalized Rayleigh Damping model are identifiable for the elastography inverse problem, although with more complex conditions than the simpler Viscoelastic damping model. The value of this approach is the additional structural information provided by the Generalized Rayleigh Damping model, which can be linked to tissue composition as well as rheological interpretations.

Sparse PDF maps for non-linear multi-resolution image operations

KAUST Repository

Hadwiger, Markus

2012-11-01

We introduce a new type of multi-resolution image pyramid for high-resolution images called sparse pdf maps (sPDF-maps). Each pyramid level consists of a sparse encoding of continuous probability density functions (pdfs) of pixel neighborhoods in the original image. The encoded pdfs enable the accurate computation of non-linear image operations directly in any pyramid level with proper pre-filtering for anti-aliasing, without accessing higher or lower resolutions. The sparsity of sPDF-maps makes them feasible for gigapixel images, while enabling direct evaluation of a variety of non-linear operators from the same representation. We illustrate this versatility for antialiased color mapping, O(n) local Laplacian filters, smoothed local histogram filters (e.g., median or mode filters), and bilateral filters. © 2012 ACM.
Inverse planning IMRT

International Nuclear Information System (INIS)

Rosenwald, J.-C.

2008-01-01

The lecture addressed the following topics: Optimizing radiotherapy dose distribution; IMRT contributes to optimization of energy deposition; Inverse vs direct planning; Main steps of IMRT; Background of inverse planning; General principle of inverse planning; The 3 main components of IMRT inverse planning; The simplest cost function (deviation from prescribed dose); The driving variable : the beamlet intensity; Minimizing a 'cost function' (or 'objective function') - the walker (or skier) analogy; Application to IMRT optimization (the gradient method); The gradient method - discussion; The simulated annealing method; The optimization criteria - discussion; Hard and soft constraints; Dose volume constraints; Typical user interface for definition of optimization criteria; Biological constraints (Equivalent Uniform Dose); The result of the optimization process; Semi-automatic solutions for IMRT; Generalisation of the optimization problem; Driving and driven variables used in RT optimization; Towards multi-criteria optimization; and Conclusions for the optimization phase. (P.A.)
Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

Science.gov (United States)

Sanz, E.; Voss, C.I.

2006-01-01

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only
A numerical study of non-linear crack tip parameters

Directory of Open Access Journals (Sweden)

F.V. Antunes

2015-07-01

Full Text Available Crack closure concept has been widely used to explain different issues of fatigue crack propagation. However, different authors have questioned the relevance of crack closure and have proposed alternative concepts. The main objective here is to check the effectiveness of crack closure concept by linking the contact of crack flanks with non-linear crack tip parameters. Accordingly, 3D-FE numerical models with and without contact were developed for a wide range of loading scenarios and the crack tip parameters usually linked to fatigue crack growth, namely range of cyclic plastic strain, crack tip opening displacement, size of reversed plastic zone and total plastic dissipation per cycle, were investigated. It was demonstrated that: i LEFM concepts are applicable to the problem under study; ii the crack closure phenomenon has a great influence on crack tip parameters decreasing their values; iii the Keff concept is able to explain the variations of crack tip parameters produced by the contact of crack flanks; iv the analysis of remote compliance is the best numerical parameter to quantify the crack opening level; v without contact there is no effect of stress ratio on crack tip parameters. Therefore it is proved that the crack closure concept is valid.
Towards lexicographic multi-objective linear programming using grossone methodology

Science.gov (United States)

Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.

2016-10-01

Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.
Rectified-Linear-Unit-Based Deep Learning for Biomedical Multi-label Data.

Science.gov (United States)

Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Cai, Yunpeng; Wang, Guoqing; Zhou, Fengfeng

2017-09-01

Disease diagnosis is one of the major data mining questions by the clinicians. The current diagnosis models usually have a strong assumption that one patient has only one disease, i.e. a single-label data mining problem. But the patients, especially when at the late stages, may have more than one disease and require a multi-label diagnosis. The multi-label data mining is much more difficult than a single-label one, and very few algorithms have been developed for this situation. Deep learning is a data mining algorithm with highly dense inner structure and has achieved many successful applications in the other areas. We propose a hypothesis that rectified-linear-unit-based deep learning algorithm may also be good at the clinical questions, by revising the last layer as a multi-label output. The proof-of-concept experimental data support the hypothesis, and the community may be interested in trying more applications.
The Inverse System Method Applied to the Derivation of Power System Non—linear Control Laws

Institute of Scientific and Technical Information of China (English)

DonghaiLI; XuezhiJIANG; 等

1997-01-01

The differential geometric method has been applied to a series of power system non-linear control problems effectively.However a set of differential equations must be solved for obtaining the required diffeomorphic transformation.Therefore the derivation of control laws is very complicated.In fact because of the specificity of power system models the required diffeomorphic transformation may be obtained directly,so it is unnecessary to solve a set of differential equations.In addition inverse system method is equivalent to differential geometric method in reality and not limited to affine nonlinear systems,Its physical meaning is able to be viewed directly and its deduction needs only algebraic operation and derivation,so control laws can be obtained easily and the application to engineering is very convenient.Authors of this paper take steam valving control of power system as a typical case to be studied.It is demonstrated that the control law deduced by inverse system method is just the same as one by differential geometric method.The conclusion will simplify the control law derivations of steam valving,excitation,converter and static var compensator by differential geometric method and may be suited to similar control problems in other areas.
Model Based Beamforming and Bayesian Inversion Signal Processing Methods for Seismic Localization of Underground Source

DEFF Research Database (Denmark)

Oh, Geok Lian

properties such as the elastic wave speeds and soil densities. One processing method is casting the estimation problem into an inverse problem to solve for the unknown material parameters. The forward model for the seismic signals used in the literatures include ray tracing methods that consider only...... density values of the discretized ground medium, which leads to time-consuming computations and instability behaviour of the inversion process. In addition, the geophysics inverse problem is generally ill-posed due to non-exact forward model that introduces errors. The Bayesian inversion method through...... the first arrivals of the reflected compressional P-waves from the subsurface structures, or 3D elastic wave models that model all the seismic wave components. The ray tracing forward model formulation is linear, whereas the full 3D elastic wave model leads to a nonlinear inversion problem. In this Ph...
Primitive-path statistics of entangled polymers: mapping multi-chain simulations onto single-chain mean-field models

International Nuclear Information System (INIS)

Steenbakkers, Rudi J A; Schieber, Jay D; Tzoumanekas, Christos; Li, Ying; Liu, Wing Kam; Kröger, Martin

2014-01-01

We present a method to map the full equilibrium distribution of the primitive-path (PP) length, obtained from multi-chain simulations of polymer melts, onto a single-chain mean-field ‘target’ model. Most previous works used the Doi–Edwards tube model as a target. However, the average number of monomers per PP segment, obtained from multi-chain PP networks, has consistently shown a discrepancy of a factor of two with respect to tube-model estimates. Part of the problem is that the tube model neglects fluctuations in the lengths of PP segments, the number of entanglements per chain and the distribution of monomers among PP segments, while all these fluctuations are observed in multi-chain simulations. Here we use a recently proposed slip-link model, which includes fluctuations in all these variables as well as in the spatial positions of the entanglements. This turns out to be essential to obtain qualitative and quantitative agreement with the equilibrium PP-length distribution obtained from multi-chain simulations. By fitting this distribution, we are able to determine two of the three parameters of the model, which govern its equilibrium properties. This mapping is executed for four different linear polymers and for different molecular weights. The two parameters are found to depend on chemistry, but not on molecular weight. The model predicts a constant plateau modulus minus a correction inversely proportional to molecular weight. The value for well-entangled chains, with the parameters determined ab initio, lies in the range of experimental data for the materials investigated. (paper)
Support minimized inversion of acoustic and elastic wave scattering

International Nuclear Information System (INIS)

Safaeinili, A.

1994-01-01

This report discusses the following topics on support minimized inversion of acoustic and elastic wave scattering: Minimum support inversion; forward modelling of elastodynamic wave scattering; minimum support linearized acoustic inversion; support minimized nonlinear acoustic inversion without absolute phase; and support minimized nonlinear elastic inversion
Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

Science.gov (United States)

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.
Multi-Model Adaptive Fuzzy Controller for a CSTR Process

Directory of Open Access Journals (Sweden)

Shubham Gogoria

2015-09-01

Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.
Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

Science.gov (United States)

Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

2017-12-01

This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.
Novel type of linear mitochondrial genomes with dual flip-flop inversion system in apicomplexan parasites, Babesia microti and Babesia rodhaini

Directory of Open Access Journals (Sweden)

Hikosaka Kenji

2012-11-01

Full Text Available Abstract Background Mitochondrial (mt genomes vary considerably in size, structure and gene content. The mt genomes of the phylum Apicomplexa, which includes important human pathogens such as the malaria parasite Plasmodium, also show marked diversity of structure. Plasmodium has a concatenated linear mt genome of the smallest size (6-kb; Babesia and Theileria have a linear monomeric mt genome (6.5-kb to 8.2-kb with terminal inverted repeats; Eimeria, which is distantly related to Plasmodium and Babesia/Theileria, possesses a mt genome (6.2-kb with a concatemeric form similar to that of Plasmodium; Cryptosporidium, the earliest branching lineage within the phylum Apicomplexa, has no mt genome. We are interested in the evolutionary origin of linear mt genomes of Babesia/Theileria, and have investigated mt genome structures in members of archaeopiroplasmid, a lineage branched off earlier from Babesia/Theileria. Results The complete mt genomes of archaeopiroplasmid parasites, Babesia microti and Babesia rodhaini, were sequenced. The mt genomes of B. microti (11.1-kb and B. rodhaini (6.9-kb possess two pairs of unique inverted repeats, IR-A and IR-B. Flip-flop inversions between two IR-As and between two IR-Bs appear to generate four distinct genome structures that are present at an equi-molar ratio. An individual parasite contained multiple mt genome structures, with 20 copies and 2 – 3 copies per haploid nuclear genome in B. microti and B. rodhaini, respectively. Conclusion We found a novel linear monomeric mt genome structure of B. microti and B. rhodhaini equipped with dual flip-flop inversion system, by which four distinct genome structures are readily generated. To our knowledge, this study is the first to report the presence of two pairs of distinct IR sequences within a monomeric linear mt genome. The present finding provides insight into further understanding of evolution of mt genome structure.
Soil parameter retrieval under vegetation cover using SAR polarimetery

Energy Technology Data Exchange (ETDEWEB)

Jagdhuber, Thomas

2012-07-01

Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, {lambda}{sub c}=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.% for the soil moisture (range of in situ
Conditioning the full waveform inversion gradient to welcome anisotropy

KAUST Repository

Alkhalifah, Tariq Ali

2014-01-01

Multi-parameter full waveform inversion (FWI) suffers from the complex nonlinearity in the objective function, compounded by the eventual tradeoff between the model parameters. A hierarchical approach based on frequency and arrival time data decimation to maneuver the complex nonlinearity associated with this problem usually falls short in anisotropic media. In place of data decimation, I use a model gradient filter approach to access the parts of the gradient more suitable to combat the potential nonlinearity and parameter trade off. The filter is based on representing the gradient in the time-lag normalized domain in which the small scattering angles of the gradient update is initially muted out. A model update hierarchical filtering strategy includes applying varying degree of filtering to the different parameter updates. A feature not easily accessible to simple data decimation. Using both FWI and reection based FWI (RFWI), two strategies to combat the tradeoff between anisotropic parameters are outlined.
Conditioning the full waveform inversion gradient to welcome anisotropy

KAUST Repository

Alkhalifah, Tariq Ali

2014-08-05

Multi-parameter full waveform inversion (FWI) suffers from the complex nonlinearity in the objective function, compounded by the eventual tradeoff between the model parameters. A hierarchical approach based on frequency and arrival time data decimation to maneuver the complex nonlinearity associated with this problem usually falls short in anisotropic media. In place of data decimation, I use a model gradient filter approach to access the parts of the gradient more suitable to combat the potential nonlinearity and parameter trade off. The filter is based on representing the gradient in the time-lag normalized domain in which the small scattering angles of the gradient update is initially muted out. A model update hierarchical filtering strategy includes applying varying degree of filtering to the different parameter updates. A feature not easily accessible to simple data decimation. Using both FWI and reection based FWI (RFWI), two strategies to combat the tradeoff between anisotropic parameters are outlined.
Feasibility Demonstration of a Multi-Cylinder Stirling Convertor with a Duplex Linear Alternator, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Stirling Technology Company (STC) proposes to integrate an existing Multi-Cylinder Free-Piston Stirling Engine (MPFPSE) with innovative compact linear alternators....
Multi-Repeated Projection Lithography for High-Precision Linear Scale Based on Average Homogenization Effect

Directory of Open Access Journals (Sweden)

Dongxu Ren

2016-04-01

Full Text Available A multi-repeated photolithography method for manufacturing an incremental linear scale using projection lithography is presented. The method is based on the average homogenization effect that periodically superposes the light intensity of different locations of pitches in the mask to make a consistent energy distribution at a specific wavelength, from which the accuracy of a linear scale can be improved precisely using the average pitch with different step distances. The method’s theoretical error is within 0.01 µm for a periodic mask with a 2-µm sine-wave error. The intensity error models in the focal plane include the rectangular grating error on the mask, static positioning error, and lithography lens focal plane alignment error, which affect pitch uniformity less than in the common linear scale projection lithography splicing process. It was analyzed and confirmed that increasing the repeat exposure number of a single stripe could improve accuracy, as could adjusting the exposure spacing to achieve a set proportion of black and white stripes. According to the experimental results, the effectiveness of the multi-repeated photolithography method is confirmed to easily realize a pitch accuracy of 43 nm in any 10 locations of 1 m, and the whole length accuracy of the linear scale is less than 1 µm/m.
Risk adjusted receding horizon control of constrained linear parameter varying systems

NARCIS (Netherlands)

Sznaier, M.; Lagoa, C.; Stoorvogel, Antonie Arij; Li, X.

2005-01-01

In the past few years, control of Linear Parameter Varying Systems (LPV) has been the object of considerable attention, as a way of formalizing the intuitively appealing idea of gain scheduling control for nonlinear systems. However, currently available LPV techniques are both computationally

Genetic parameters and correlations among linear type traits in the ...

African Journals Online (AJOL)

The main objective of this study was to estimate the genetic parameters and relationships of 10 linear type traits in the first lactation of Holstein dairy cows. 3274 records for type traits was used (Ag, angularity; Sta, stature; Bdp, body depth; Rw, rump width; Rs, rear leg side view; Fa, foot angle; Fu, fore udder attachment; Ruh, ...
Planktonic food webs revisited: Reanalysis of results from the linear inverse approach

Science.gov (United States)

Hlaili, Asma Sakka; Niquil, Nathalie; Legendre, Louis

2014-01-01

Identification of the trophic pathway that dominates a given planktonic assemblage is generally based on the distribution of biomasses among food-web compartments, or better, the flows of materials or energy among compartments. These flows are obtained by field observations and a posteriori analyses, including the linear inverse approach. In the present study, we re-analysed carbon flows obtained by inverse analysis at 32 stations in the global ocean and one large lake. Our results do not support two "classical" views of plankton ecology, i.e. that the herbivorous food web is dominated by mesozooplankton grazing on large phytoplankton, and the microbial food web is based on microzooplankton significantly consuming bacteria; our results suggest instead that phytoplankton are generally grazed by microzooplankton, of which they are the main food source. Furthermore, we identified the "phyto-microbial food web", where microzooplankton largely feed on phytoplankton, in addition to the already known "poly-microbial food web", where microzooplankton consume more or less equally various types of food. These unexpected results led to a (re)definition of the conceptual models corresponding to the four trophic pathways we found to exist in plankton, i.e. the herbivorous, multivorous, and two types of microbial food web. We illustrated the conceptual trophic pathways using carbon flows that were actually observed at representative stations. The latter can be calibrated to correspond to any field situation. Our study also provides researchers and managers with operational criteria for identifying the dominant trophic pathway in a planktonic assemblage, these criteria being based on the values of two carbon ratios that could be calculated from flow values that are relatively easy to estimate in the field.
Sensitivity analysis in multi-parameter probabilistic systems

International Nuclear Information System (INIS)

Walker, J.R.

1987-01-01

Probabilistic methods involving the use of multi-parameter Monte Carlo analysis can be applied to a wide range of engineering systems. The output from the Monte Carlo analysis is a probabilistic estimate of the system consequence, which can vary spatially and temporally. Sensitivity analysis aims to examine how the output consequence is influenced by the input parameter values. Sensitivity analysis provides the necessary information so that the engineering properties of the system can be optimized. This report details a package of sensitivity analysis techniques that together form an integrated methodology for the sensitivity analysis of probabilistic systems. The techniques have known confidence limits and can be applied to a wide range of engineering problems. The sensitivity analysis methodology is illustrated by performing the sensitivity analysis of the MCROC rock microcracking model
Inverse gas chromatography determination of some physicochemical parameters of a high rank Colombian coal

Energy Technology Data Exchange (ETDEWEB)

Baquero-Haeberlin, M.C.; Rincon, J.M. [Universidad Nacional de Colombia, Santafe de Bogota (Colombia). Departamento de Quimica

1997-12-31

Dispersive component of the free surface energy of a Colombian semianthracite type coal - Paramo de Guerrero - was determined by Inverse Gas Chromatography (IGC), at zero coverage injecting the series of n-alkanes at 313, 333, 353 and 373 K. For the retention time, the mass center determination was used instead of the maximum peak in the chromatograms. The free surface energy (-{Delta}G{sub A}) increase linearly with the carbon atom number to the alkanes but is not constant due, probably to the conformational structure of the probes. The IGC study of the adsorption process in function of the temperature, provides the respective Enthalpy and Entropy values. (orig.)
A Successful Attempt to Obtain the Linear Dependence Between One-Photon and Two-Photon Spectral Properties and Hammett Parameters of Various Aromatic Substituents in New π-Extended Asymmetric Organic Chromophores.

Science.gov (United States)

Hu, Nvdan; Gong, Yulong; Wang, Xinchao; Lu, Yao; Peng, Guangyue; Yang, Long; Zhang, Shengtao; Luo, Ziping; Li, Hongru; Gao, Fang

2015-11-01

A series of new asymmetric chromophores containing aromatic substituents and possessing the excellent π-extension in space were prepared through multi-steps routes. One-photon and two-photon spectral properties of these new chromophores could be tuned by these substituents finely and simultaneously. The linear correlation of the wave numbers of the one-photon absorption and emission maxima to Hammett parameters of these substituents was presented. Near infrared two-photon absorption emission integrated areas of the target chromophores were correlated linearly to Hammett constants of these substituted groups.
Solving inverse problems through a smooth formulation of multiple-point geostatistics

DEFF Research Database (Denmark)

Melnikova, Yulia

be inferred, for instance, from a conceptual geological model termed a training image.The main motivation for this study was the challenge posed by history matching, an inverse problem aimed at estimating rock properties from production data. We addressed two main difficulties of the history matching problem...... corresponding inverse problems. However, noise in data, non-linear relationships and sparse observations impede creation of realistic reservoir models. Including complex a priori information on reservoir parameters facilitates the process of obtaining acceptable solutions. Such a priori knowledge may...... strategies including both theoretical motivation and practical aspects of implementation. Finally, it is complemented by six research papers submitted, reviewed and/or published in the period 2010 - 2013....
Convection methodology for fission track annealing: direct and inverse numerical simulations in the multi-exponential case

International Nuclear Information System (INIS)

Miellou, J.C.; Igli, H.; Grivet, M.; Rebetez, M.; Chambaudet, A.

1994-01-01

In minerals, the uranium fission tracks are sensitive to temperature and time. The consequence is that the etchable lengths are reduced. To simulate the phenomenon, at the last International Conference on Nuclear Tracks in solids at Beijing in 1992, we proposed a convection model for fission track annealing based on a reaction situation associated with only one activation energy. Moreover a simple inverse method based on the resolution of an ordinary differential equation was described, making it possible to retrace the thermal history in this mono-exponential situation. The aim of this paper is to consider a more involved class of models including multi-exponentials associated with several activation energies. We shall describe in this framework the modelling of the direct phenomenon and the resolution of the inverse problem. Results of numerical simulations and comparison with the mono-exponential case will be presented. 5 refs. (author)
Germinal Center Optimization Applied to Neural Inverse Optimal Control for an All-Terrain Tracked Robot

Directory of Open Access Journals (Sweden)

Carlos Villaseñor

2017-12-01

Full Text Available Nowadays, there are several meta-heuristics algorithms which offer solutions for multi-variate optimization problems. These algorithms use a population of candidate solutions which explore the search space, where the leadership plays a big role in the exploration-exploitation equilibrium. In this work, we propose to use a Germinal Center Optimization algorithm (GCO which implements temporal leadership through modeling a non-uniform competitive-based distribution for particle selection. GCO is used to find an optimal set of parameters for a neural inverse optimal control applied to all-terrain tracked robot. In the Neural Inverse Optimal Control (NIOC scheme, a neural identifier, based on Recurrent High Orden Neural Network (RHONN trained with an extended kalman filter algorithm, is used to obtain a model of the system, then, a control law is design using such model with the inverse optimal control approach. The RHONN identifier is developed without knowledge of the plant model or its parameters, on the other hand, the inverse optimal control is designed for tracking velocity references. Applicability of the proposed scheme is illustrated using simulations results as well as real-time experimental results with an all-terrain tracked robot.
Optimization of machining parameters of turning operations based on multi performance criteria

Directory of Open Access Journals (Sweden)

N.K.Mandal

2013-01-01

Full Text Available The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA. Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.
SU-E-T-628: A Cloud Computing Based Multi-Objective Optimization Method for Inverse Treatment Planning.

Science.gov (United States)

Na, Y; Suh, T; Xing, L

2012-06-01

Multi-objective (MO) plan optimization entails generation of an enormous number of IMRT or VMAT plans constituting the Pareto surface, which presents a computationally challenging task. The purpose of this work is to overcome the hurdle by developing an efficient MO method using emerging cloud computing platform. As a backbone of cloud computing for optimizing inverse treatment planning, Amazon Elastic Compute Cloud with a master node (17.1 GB memory, 2 virtual cores, 420 GB instance storage, 64-bit platform) is used. The master node is able to scale seamlessly a number of working group instances, called workers, based on the user-defined setting account for MO functions in clinical setting. Each worker solved the objective function with an efficient sparse decomposition method. The workers are automatically terminated if there are finished tasks. The optimized plans are archived to the master node to generate the Pareto solution set. Three clinical cases have been planned using the developed MO IMRT and VMAT planning tools to demonstrate the advantages of the proposed method. The target dose coverage and critical structure sparing of plans are comparable obtained using the cloud computing platform are identical to that obtained using desktop PC (Intel Xeon® CPU 2.33GHz, 8GB memory). It is found that the MO planning speeds up the processing of obtaining the Pareto set substantially for both types of plans. The speedup scales approximately linearly with the number of nodes used for computing. With the use of N nodes, the computational time is reduced by the fitting model, 0.2+2.3/N, with r̂2>0.99, on average of the cases making real-time MO planning possible. A cloud computing infrastructure is developed for MO optimization. The algorithm substantially improves the speed of inverse plan optimization. The platform is valuable for both MO planning and future off- or on-line adaptive re-planning. © 2012 American Association of Physicists in Medicine.
Quasiclassical description of multi-band superconductors with two order parameters

Energy Technology Data Exchange (ETDEWEB)

Moor, Andreas

2014-05-19

This Thesis deals with multi-band superconductors with two order parameters, i.e., the superconductivity and the spin-density wave, also touching on one-band superconductors with a charge-density wave, as well as with only the superconducting order parameter. Quasiclassical description of suchlike structures is developed and applied to investigation of various effects, inter alia, the Josephson and the proximity effects, the Knight shift, the Larkin-Ovchinnikov-Fulde-Ferrell-like state, and the interplay of the order parameters in coexistence regime. The applicability of the developed approach to pnictides is discussed.
A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification

Directory of Open Access Journals (Sweden)

Wei Gao

2016-01-01

Full Text Available According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration. Finally, numerical and experimental examples are utilized to validate the performance of the QFM. Furthermore, the Generalized Cross-Validation (GCV method and the L-curve method are taken as the comparison methods. The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load.
Economic planning for electric energy systems: a multi objective linearized approach for solution

International Nuclear Information System (INIS)

Mata Medeiros Branco, T. da.

1986-01-01

The economic planning problem associated to the expansion and operation of electrical power systems is considered in this study, represented for a vectorial objective function in which the minimization of resources involved and maximization of attended demand constitute goals to be satisfied. Supposing all the variables involved with linear characteristic and considering the conflict existing among the objectives to be achieved, in order to find a solution, a multi objective linearized approach is proposed. This approximation utilizes the compromise programming technique and linear programming methods. Generation and transmission are simultaneously considered into the optimization process in which associated losses and the capacity of each line are included. Illustrated examples are also presented with results discussed. (author)
Sensitivity-based virtual fields for the non-linear virtual fields method

Science.gov (United States)

Marek, Aleksander; Davis, Frances M.; Pierron, Fabrice

2017-09-01

The virtual fields method is an approach to inversely identify material parameters using full-field deformation data. In this manuscript, a new set of automatically-defined virtual fields for non-linear constitutive models has been proposed. These new sensitivity-based virtual fields reduce the influence of noise on the parameter identification. The sensitivity-based virtual fields were applied to a numerical example involving small strain plasticity; however, the general formulation derived for these virtual fields is applicable to any non-linear constitutive model. To quantify the improvement offered by these new virtual fields, they were compared with stiffness-based and manually defined virtual fields. The proposed sensitivity-based virtual fields were consistently able to identify plastic model parameters and outperform the stiffness-based and manually defined virtual fields when the data was corrupted by noise.
A large inversion in the linear chromosome of Streptomyces griseus caused by replicative transposition of a new Tn3 family transposon.

Science.gov (United States)

Murata, M; Uchida, T; Yang, Y; Lezhava, A; Kinashi, H

2011-04-01

We have comprehensively analyzed the linear chromosomes of Streptomyces griseus mutants constructed and kept in our laboratory. During this study, macrorestriction analysis of AseI and DraI fragments of mutant 402-2 suggested a large chromosomal inversion. The junctions of chromosomal inversion were cloned and sequenced and compared with the corresponding target sequences in the parent strain 2247. Consequently, a transposon-involved mechanism was revealed. Namely, a transposon originally located at the left target site was replicatively transposed to the right target site in an inverted direction, which generated a second copy and at the same time caused a 2.5-Mb chromosomal inversion. The involved transposon named TnSGR was grouped into a new subfamily of the resolvase-encoding Tn3 family transposons based on its gene organization. At the end, terminal diversity of S. griseus chromosomes is discussed by comparing the sequences of strains 2247 and IFO13350.
Analyses of Effects of Cutting Parameters on Cutting Edge Temperature Using Inverse Heat Conduction Technique

Directory of Open Access Journals (Sweden)

Marcelo Ribeiro dos Santos

2014-01-01

Full Text Available During machining energy is transformed into heat due to plastic deformation of the workpiece surface and friction between tool and workpiece. High temperatures are generated in the region of the cutting edge, which have a very important influence on wear rate of the cutting tool and on tool life. This work proposes the estimation of heat flux at the chip-tool interface using inverse techniques. Factors which influence the temperature distribution at the AISI M32C high speed steel tool rake face during machining of a ABNT 12L14 steel workpiece were also investigated. The temperature distribution was predicted using finite volume elements. A transient 3D numerical code using irregular and nonstaggered mesh was developed to solve the nonlinear heat diffusion equation. To validate the software, experimental tests were made. The inverse problem was solved using the function specification method. Heat fluxes at the tool-workpiece interface were estimated using inverse problems techniques and experimental temperatures. Tests were performed to study the effect of cutting parameters on cutting edge temperature. The results were compared with those of the tool-work thermocouple technique and a fair agreement was obtained.
Analysis of pumping tests of partially penetrating wells in an unconfined aquifer using inverse numerical optimization

Science.gov (United States)

Hvilshøj, S.; Jensen, K. H.; Barlebo, H. C.; Madsen, B.

1999-08-01

Inverse numerical modeling was applied to analyze pumping tests of partially penetrating wells carried out in three wells established in an unconfined aquifer in Vejen, Denmark, where extensive field investigations had previously been carried out, including tracer tests, mini-slug tests, and other hydraulic tests. Drawdown data from multiple piezometers located at various horizontal and vertical distances from the pumping well were included in the optimization. Horizontal and vertical hydraulic conductivities, specific storage, and specific yield were estimated, assuming that the aquifer was either a homogeneous system with vertical anisotropy or composed of two or three layers of different hydraulic properties. In two out of three cases, a more accurate interpretation was obtained for a multi-layer model defined on the basis of lithostratigraphic information obtained from geological descriptions of sediment samples, gammalogs, and flow-meter tests. Analysis of the pumping tests resulted in values for horizontal hydraulic conductivities that are in good accordance with those obtained from slug tests and mini-slug tests. Besides the horizontal hydraulic conductivity, it is possible to determine the vertical hydraulic conductivity, specific yield, and specific storage based on a pumping test of a partially penetrating well. The study demonstrates that pumping tests of partially penetrating wells can be analyzed using inverse numerical models. The model used in the study was a finite-element flow model combined with a non-linear regression model. Such a model can accommodate more geological information and complex boundary conditions, and the parameter-estimation procedure can be formalized to obtain optimum estimates of hydraulic parameters and their standard deviations.
A Comparison of Closed-Loop Performance of Multirotor Configurations Using Non-Linear Dynamic Inversion Control

Directory of Open Access Journals (Sweden)

Murray L. Ireland

2015-06-01

Full Text Available Multirotor is the umbrella term for the family of unmanned aircraft, which include the quadrotor, hexarotor and other vertical take-off and landing (VTOL aircraft that employ multiple main rotors for lift and control. Development and testing of novel multirotor designs has been aided by the proliferation of 3D printing and inexpensive flight controllers and components. Different multirotor configurations exhibit specific strengths, while presenting unique challenges with regards to design and control. This article highlights the primary differences between three multirotor platforms: a quadrotor; a fully-actuated hexarotor; and an octorotor. Each platform is modelled and then controlled using non-linear dynamic inversion. The differences in dynamics, control and performance are then discussed.
Planning under uncertainty solving large-scale stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G. [Stanford Univ., CA (United States). Dept. of Operations Research]|[Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft

1992-12-01

For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.
Parameter estimation and hypothesis testing in linear models

CERN Document Server

Koch, Karl-Rudolf

1999-01-01

The necessity to publish the second edition of this book arose when its third German edition had just been published. This second English edition is there fore a translation of the third German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1997. It differs from the first English edition by the addition of a new chapter on robust estimation of parameters and the deletion of the section on discriminant analysis, which has been more completely dealt with by the author in the book Bayesian In ference with Geodetic Applications, Springer-Verlag, Berlin Heidelberg New York, 1990. Smaller additions and deletions have been incorporated, to im prove the text, to point out new developments or to eliminate errors which became apparent. A few examples have been also added. I thank Springer-Verlag for publishing this second edition and for the assistance in checking the translation, although the responsibility of errors remains with the author. I also want to express my thanks...

Standard Test Method for Determining the Linearity of a Photovoltaic Device Parameter with Respect To a Test Parameter

CERN Document Server

American Society for Testing and Materials. Philadelphia

2005-01-01

1.1 This test method determines the degree of linearity of a photovoltaic device parameter with respect to a test parameter, for example, short-circuit current with respect to irradiance. 1.2 The linearity determined by this test method applies only at the time of testing, and implies no past or future performance level. 1.3 This test method applies only to non-concentrator terrestrial photovoltaic devices. 1.4 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard. 1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
Resolution of VTI anisotropy with elastic full-waveform inversion: theory and basic numerical examples

Science.gov (United States)

Podgornova, O.; Leaney, S.; Liang, L.

2018-03-01

Extracting medium properties from seismic data faces some limitations due to the finite frequency content of the data and restricted spatial positions of the sources and receivers. Some distributions of the medium properties make low impact on the data (including none). If these properties are used as the inversion parameters, then the inverse problem becomes over-parametrized, leading to ambiguous results. We present an analysis of multiparameter resolution for the linearized inverse problem in the framework of elastic full-waveform inversion. We show that the spatial and multiparameter sensitivities are intertwined and non-sensitive properties are spatial distributions of some non-trivial combinations of the conventional elastic parameters. The analysis accounts for the Hessian information and frequency content of the data; it is semi-analytical (in some scenarios analytical), easy to interpret, and enhances results of the widely used radiation pattern analysis. Single-type scattering is shown to have limited sensitivity, even for full-aperture data. Finite-frequency data lose multiparameter sensitivity at smooth and fine spatial scales. Also, we establish ways to quantify a spatial-multiparameter coupling and demonstrate that the theoretical predictions agree well with the numerical results.
The inverse problem for Schwinger pair production

Directory of Open Access Journals (Sweden)

F. Hebenstreit

2016-02-01

Full Text Available The production of electron–positron pairs in time-dependent electric fields (Schwinger mechanism depends non-linearly on the applied field profile. Accordingly, the resulting momentum spectrum is extremely sensitive to small variations of the field parameters. Owing to this non-linear dependence it is so far unpredictable how to choose a field configuration such that a predetermined momentum distribution is generated. We show that quantum kinetic theory along with optimal control theory can be used to approximately solve this inverse problem for Schwinger pair production. We exemplify this by studying the superposition of a small number of harmonic components resulting in predetermined signatures in the asymptotic momentum spectrum. In the long run, our results could facilitate the observation of this yet unobserved pair production mechanism in quantum electrodynamics by providing suggestions for tailored field configurations.
Retrieving rupture history using waveform inversions in time sequence

Science.gov (United States)

Yi, L.; Xu, C.; Zhang, X.

2017-12-01

The rupture history of large earthquakes is generally regenerated using the waveform inversion through utilizing seismological waveform records. In the waveform inversion, based on the superposition principle, the rupture process is linearly parameterized. After discretizing the fault plane into sub-faults, the local source time function of each sub-fault is usually parameterized using the multi-time window method, e.g., mutual overlapped triangular functions. Then the forward waveform of each sub-fault is synthesized through convoluting the source time function with its Green function. According to the superposition principle, these forward waveforms generated from the fault plane are summarized in the recorded waveforms after aligning the arrival times. Then the slip history is retrieved using the waveform inversion method after the superposing of all forward waveforms for each correspond seismological waveform records. Apart from the isolation of these forward waveforms generated from each sub-fault, we also realize that these waveforms are gradually and sequentially superimposed in the recorded waveforms. Thus we proposed a idea that the rupture model is possibly detachable in sequent rupture times. According to the constrained waveform length method emphasized in our previous work, the length of inverted waveforms used in the waveform inversion is objectively constrained by the rupture velocity and rise time. And one essential prior condition is the predetermined fault plane that limits the duration of rupture time, which means the waveform inversion is restricted in a pre-set rupture duration time. Therefore, we proposed a strategy to inverse the rupture process sequentially using the progressively shift rupture times as the rupture front expanding in the fault plane. And we have designed a simulation inversion to test the feasibility of the method. Our test result shows the prospect of this idea that requiring furthermore investigation.
hMuLab: A Biomedical Hybrid MUlti-LABel Classifier Based on Multiple Linear Regression.

Science.gov (United States)

Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Zhou, Manli; Zhou, Fengfeng

2017-01-01

Many biomedical classification problems are multi-label by nature, e.g., a gene involved in a variety of functions and a patient with multiple diseases. The majority of existing classification algorithms assumes each sample with only one class label, and the multi-label classification problem remains to be a challenge for biomedical researchers. This study proposes a novel multi-label learning algorithm, hMuLab, by integrating both feature-based and neighbor-based similarity scores. The multiple linear regression modeling techniques make hMuLab capable of producing multiple label assignments for a query sample. The comparison results over six commonly-used multi-label performance measurements suggest that hMuLab performs accurately and stably for the biomedical datasets, and may serve as a complement to the existing literature.
Linear Determination of a Camera's Intrinsic Parameters Using Two Intersecting Circles

Directory of Open Access Journals (Sweden)

Xu Chen

2014-03-01

Full Text Available An approach using two intersecting circles is proposed as a linear approach for determining a camera's intrinsic parameters. The two intersecting coplanar circles have four intersection points in the projective plane: two real points and two circular points. In the image plane, the diagonal triangle - on which the image of the four intersection points composes a complete quadrangle - is a self-polar triangle for the projection curves of the circles. The vertex of the self-polar triangle is the null space of the degenerate conic formed by the image of the four intersection points. By solving the three vertices of the self-polar triangle using the image coordinates of the two real intersection points, the degenerate conic can be obtained. The image of the two circular points is then computed from the intersection points of the degenerate conic. Using the image of the circular points from the three images of the same planar pattern with different directions, the intrinsic parameters can be linearly determined.
Sensitivity analysis for elastic full-waveform inversion in VTI media

KAUST Repository

Kamath, Nishant

2014-08-05

Multiparameter full-waveform inversion (FWI) is generally nonunique, and the results are strongly influenced by the geometry of the experiment and the type of recorded data. Studying the sensitivity of different subsets of data to the model parameters may help in choosing an optimal acquisition design, inversion workflow, and parameterization. Here, we derive the Fréchet kernel for FWI of multicomponent data from a 2D VTI (tranversely isotropic with a vertical symmetry axis) medium. The kernel is obtained by linearizing the elastic wave equation using the Born approximation and employing the asymptotic Green\\'s function. The amplitude of the kernel (‘radiation pattern’) yields the angle-dependent energy scattered by a perturbation in a certain model parameter. The perturbations are described in terms of the P- and S-wave vertical velocities and the P-wave normal-moveout and horizontal velocities. The background medium is assumed to be homogeneous and isotropic, which allows us to obtain simple expressions for the radiation patterns corresonding to all four velocities. These patterns help explain the FWI results for multicomponent transmission data generated for Gaussian anomalies in the Thomsen parameters inserted into a homogeneous VTI medium.
Sensitivity analysis for elastic full-waveform inversion in VTI media

KAUST Repository

Kamath, Nishant; Tsvankin, Ilya

2014-01-01

Multiparameter full-waveform inversion (FWI) is generally nonunique, and the results are strongly influenced by the geometry of the experiment and the type of recorded data. Studying the sensitivity of different subsets of data to the model parameters may help in choosing an optimal acquisition design, inversion workflow, and parameterization. Here, we derive the Fréchet kernel for FWI of multicomponent data from a 2D VTI (tranversely isotropic with a vertical symmetry axis) medium. The kernel is obtained by linearizing the elastic wave equation using the Born approximation and employing the asymptotic Green's function. The amplitude of the kernel (‘radiation pattern’) yields the angle-dependent energy scattered by a perturbation in a certain model parameter. The perturbations are described in terms of the P- and S-wave vertical velocities and the P-wave normal-moveout and horizontal velocities. The background medium is assumed to be homogeneous and isotropic, which allows us to obtain simple expressions for the radiation patterns corresonding to all four velocities. These patterns help explain the FWI results for multicomponent transmission data generated for Gaussian anomalies in the Thomsen parameters inserted into a homogeneous VTI medium.
Numerical inverse Laplace transformation for determining the system response of linear systems in the time domain

Science.gov (United States)

Friedrich, R.; Drewelow, W.

1978-01-01

An algorithm is described that is based on the method of breaking the Laplace transform down into partial fractions which are then inverse-transformed separately. The sum of the resulting partial functions is the wanted time function. Any problems caused by equation system forms are largely limited by appropriate normalization using an auxiliary parameter. The practical limits of program application are reached when the degree of the denominator of the Laplace transform is seven to eight.
Estimation of soil hydraulic parameters in the field by integrated hydrogeophysical inversion of time-lapse ground-penetrating radar data

KAUST Repository

Jadoon, Khan; Weihermü ller, Lutz; Scharnagl, Benedikt; Kowalsky, Michael B.; Bechtold, Michel; Hubbard, Susan S.; Vereecken, Harry; Lambot, Sé bastien

2012-01-01

An integrated hydrogeophysical inversion approach was used to remotely infer the unsaturated soil hydraulic parameters from time-lapse ground-penetrating radar (GPR) data collected at a fixed location over a bare agricultural field. The GPR model
INVERSION SYMMETRY, ARCHITECTURE AND DISPERSITY, AND THEIR EFFECTS ON THERMODYNAMICS IN BULK AND CONFINED REGIONS: FROM RANDOMLY BRANCHED POLYMERS TO LINEAR CHAINS, STARS AND DENDRIMERS

Directory of Open Access Journals (Sweden)

P.D.Gujrati

2002-01-01

Full Text Available Theoretical evidence is presented in this review that architectural aspects can play an important role, not only in the bulk but also in confined geometries by using our recursive lattice theory, which is equally applicable to fixed architectures (regularly branched polymers, stars, dendrimers, brushes, linear chains, etc. and variable architectures, i.e. randomly branched structures. Linear chains possess an inversion symmetry (IS of a magnetic system (see text, whose presence or absence determines the bulk phase diagram. Fixed architectures possess the IS and yield a standard bulk phase diagram in which there exists a theta point at which two critical lines C and C' meet and the second virial coefficient A2 vanishes. The critical line C appears only for infinitely large polymers, and an order parameter is identified for this criticality. The critical line C' exists for polymers of all sizes and represents phase separation criticality. Variable architectures, which do not possess the IS, give rise to a topologically different phase diagram with no theta point in general. In confined regions next to surfaces, it is not the IS but branching and monodispersity, which becomes important in the surface regions. We show that branching plays no important role for polydisperse systems, but become important for monodisperse systems. Stars and linear chains behave differently near a surface.
Inversion Estimate of California Methane Emissions Using a Bayesian Inverse Model with Multi-Tower Greenhouse Gas Monitoring Network and Aircraft Measurements

Science.gov (United States)

Cui, Y.; Falk, M.; Chen, Y.; Herner, J.; Croes, B. E.; Vijayan, A.

2017-12-01

Methane (CH4) is an important short-lived climate pollutant (SLCP), and the second most important greenhouse gas (GHG) in California which accounts for 9% of the statewide GHG emissions inventory. Over the years, California has enacted several ambitious climate change mitigation goals, including the California Global Warming Solutions Act of 2006 which requires ARB to reduce statewide GHG emissions to 1990 emission level by 2020, as well as Assembly Bill 1383 which requires implementation of a climate mitigation program to reduce statewide methane emissions by 40% below the 2013 levels. In order to meet these requirements, ARB has proposed a comprehensive SLCP Strategy with goals to reduce oil and gas related emissions and capture methane emissions from dairy operations and organic waste. Achieving these goals will require accurate understanding of the sources of CH4 emissions. Since direct monitoring of CH4 emission sources in large spatial and temporal scales is challenging and resource intensive, we developed a complex inverse technique combined with atmospheric three-dimensional (3D) transport model and atmospheric observations of CH4 concentrations from a regional tower network and aircraft measurements, to gain insights into emission sources in California. In this study, develop a comprehensive inversion estimate using available aircraft measurements from CalNex airborne campaigns (May-June 2010) and three years of hourly continuous measurements from the ARB Statewide GHG Monitoring Network (2014-2016). The inversion analysis is conducted using two independent 3D Lagrangian models (WRF-STILT and WRF-FLEXPART), with a variety of bottom-up prior inputs from national and regional inventories, as well as two different probability density functions (Gaussian and Lognormal). Altogether, our analysis provides a detailed picture of the spatially resolved CH4 emission sources and their temporal variation over a multi-year period.
Parameter optimisation for a better representation of drought by LSMs: inverse modelling vs. sequential data assimilation

Science.gov (United States)

Dewaele, Hélène; Munier, Simon; Albergel, Clément; Planque, Carole; Laanaia, Nabil; Carrer, Dominique; Calvet, Jean-Christophe

2017-09-01

Soil maximum available water content (MaxAWC) is a key parameter in land surface models (LSMs). However, being difficult to measure, this parameter is usually uncertain. This study assesses the feasibility of using a 15-year (1999-2013) time series of satellite-derived low-resolution observations of leaf area index (LAI) to estimate MaxAWC for rainfed croplands over France. LAI interannual variability is simulated using the CO2-responsive version of the Interactions between Soil, Biosphere and Atmosphere (ISBA) LSM for various values of MaxAWC. Optimal value is then selected by using (1) a simple inverse modelling technique, comparing simulated and observed LAI and (2) a more complex method consisting in integrating observed LAI in ISBA through a land data assimilation system (LDAS) and minimising LAI analysis increments. The evaluation of the MaxAWC estimates from both methods is done using simulated annual maximum above-ground biomass (Bag) and straw cereal grain yield (GY) values from the Agreste French agricultural statistics portal, for 45 administrative units presenting a high proportion of straw cereals. Significant correlations (p value Bag and GY are found for up to 36 and 53 % of the administrative units for the inverse modelling and LDAS tuning methods, respectively. It is found that the LDAS tuning experiment gives more realistic values of MaxAWC and maximum Bag than the inverse modelling experiment. Using undisaggregated LAI observations leads to an underestimation of MaxAWC and maximum Bag in both experiments. Median annual maximum values of disaggregated LAI observations are found to correlate very well with MaxAWC.
Analysis of Low Frequency Oscillation Using the Multi-Interval Parameter Estimation Method on a Rolling Blackout in the KEPCO System

Directory of Open Access Journals (Sweden)

Kwan-Shik Shim

2017-04-01

Full Text Available This paper describes a multiple time interval (“multi-interval” parameter estimation method. The multi-interval parameter estimation method estimates a parameter from a new multi-interval prediction error polynomial that can simultaneously consider multiple time intervals. The root of the multi-interval prediction error polynomial includes the effect on each time interval, and the important mode can be estimated by solving one polynomial for multiple time intervals or signals. The algorithm of the multi-interval parameter estimation method proposed in this paper is applied to the test function and the data measured from a PMU (phasor measurement unit installed in the KEPCO (Korea Electric Power Corporation system. The results confirm that the proposed multi-interval parameter estimation method accurately and reliably estimates important parameters.
GPI-repetitive control for linear systems with parameter uncertainty / variation

Directory of Open Access Journals (Sweden)

John A. Cortés-Romero

2015-01-01

Full Text Available Robust repetitive control problems for uncertain linear systems have been considered by different approaches. This article proposes the use of Repetitive Control and Generalized Proportional Integral (GPI Control in a complementary fashion. The conditioning and coupling of these techniques has been done in a time discrete context. Repetitive control is a control technique, based on the internal model principle, which yields perfect asymptotic tracking and rejection of periodic signals. On the other hand, GPI control is established as a robust linear control system design technique that is able to reject structured time polynomial additive perturbation, in particular, parameter uncertainty that can be locally approximated by time polynomial signal. GPI control provides a suitable stability and robustness conditions for the proper Repetitive Control operation. A stability analysis is presented under the frequency response framework using plant samples for different parameter uncertainty conditions. We carry out some comparative stability analysis with other complementary control approaches that has been effective for this kind of task, enhancing a better robustness and an improved performance for the GPI case. Illustrative simulation examples are presented which validate the proposed approach.
NON-LTE INVERSIONS OF THE Mg ii h and k AND UV TRIPLET LINES

Energy Technology Data Exchange (ETDEWEB)

De la Cruz Rodríguez, Jaime; Leenaarts, Jorrit [Institute for Solar Physics, Dept. of Astronomy, Stockholm University, AlbaNova University Centre, SE-106 91 Stockholm Sweden (Sweden); Ramos, Andrés Asensio [Instituto de Astrofísica de Canarias, E-38205, La Laguna, Tenerife (Spain)

2016-10-20

The Mg ii h and k lines are powerful diagnostics for studying the solar chromosphere. They have become particularly popular with the launch of the Interface Region Imaging Spectrograph ( IRIS ) satellite, and a number of studies that include these lines have lead to great progress in understanding chromospheric heating, in many cases thanks to the support from 3D MHD simulations. In this study, we utilize another approach to analyze observations: non-LTE inversions of the Mg ii h and k and UV triplet lines including the effects of partial redistribution. Our inversion code attempts to construct a model atmosphere that is compatible with the observed spectra. We have assessed the capabilities and limitations of the inversions using the FALC atmosphere and a snapshot from a 3D radiation-MHD simulation. We find that Mg ii h and k allow reconstructing a model atmosphere from the middle photosphere to the transition region. We have also explored the capabilities of a multi-line/multi-atom setup, including the Mg ii h and k, the Ca ii 854.2 nm, and the Fe i 630.25 lines to recover the full stratification of physical parameters, including the magnetic field vector, from the photosphere to the chromosphere. Finally, we present the first inversions of observed IRIS spectra from quiet-Sun, plage, and sunspot, with very promising results.
Advanced linear algebra for engineers with Matlab

CERN Document Server

Dianat, Sohail A

2009-01-01

Matrices, Matrix Algebra, and Elementary Matrix OperationsBasic Concepts and NotationMatrix AlgebraElementary Row OperationsSolution of System of Linear EquationsMatrix PartitionsBlock MultiplicationInner, Outer, and Kronecker ProductsDeterminants, Matrix Inversion and Solutions to Systems of Linear EquationsDeterminant of a MatrixMatrix InversionSolution of Simultaneous Linear EquationsApplications: Circuit AnalysisHomogeneous Coordinates SystemRank, Nu
Introduction to the mathematics of inversion in remote sensing and indirect measurements

CERN Document Server

Twomey, S

2013-01-01

Developments in Geomathematics, 3: Introduction to the Mathematics of Inversion in Remote Sensing and Indirect Measurements focuses on the application of the mathematics of inversion in remote sensing and indirect measurements, including vectors and matrices, eigenvalues and eigenvectors, and integral equations. The publication first examines simple problems involving inversion, theory of large linear systems, and physical and geometric aspects of vectors and matrices. Discussions focus on geometrical view of matrix operations, eigenvalues and eigenvectors, matrix products, inverse of a matrix, transposition and rules for product inversion, and algebraic elimination. The manuscript then tackles the algebraic and geometric aspects of functions and function space and linear inversion methods, as well as the algebraic and geometric nature of constrained linear inversion, least squares solution, approximation by sums of functions, and integral equations. The text examines information content of indirect sensing m...
Numerical solution of a coefficient inverse problem with multi-frequency experimental raw data by a globally convergent algorithm

Science.gov (United States)

Nguyen, Dinh-Liem; Klibanov, Michael V.; Nguyen, Loc H.; Kolesov, Aleksandr E.; Fiddy, Michael A.; Liu, Hui

2017-09-01

We analyze in this paper the performance of a newly developed globally convergent numerical method for a coefficient inverse problem for the case of multi-frequency experimental backscatter data associated to a single incident wave. These data were collected using a microwave scattering facility at the University of North Carolina at Charlotte. The challenges for the inverse problem under the consideration are not only from its high nonlinearity and severe ill-posedness but also from the facts that the amount of the measured data is minimal and that these raw data are contaminated by a significant amount of noise, due to a non-ideal experimental setup. This setup is motivated by our target application in detecting and identifying explosives. We show in this paper how the raw data can be preprocessed and successfully inverted using our inversion method. More precisely, we are able to reconstruct the dielectric constants and the locations of the scattering objects with a good accuracy, without using any advanced a priori knowledge of their physical and geometrical properties.
Using linear time-invariant system theory to estimate kinetic parameters directly from projection measurements

International Nuclear Information System (INIS)

Zeng, G.L.; Gullberg, G.T.

1995-01-01

It is common practice to estimate kinetic parameters from dynamically acquired tomographic data by first reconstructing a dynamic sequence of three-dimensional reconstructions and then fitting the parameters to time activity curves generated from the time-varying reconstructed images. However, in SPECT, the pharmaceutical distribution can change during the acquisition of a complete tomographic data set, which can bias the estimated kinetic parameters. It is hypothesized that more accurate estimates of the kinetic parameters can be obtained by fitting to the projection measurements instead of the reconstructed time sequence. Estimation from projections requires the knowledge of their relationship between the tissue regions of interest or voxels with particular kinetic parameters and the project measurements, which results in a complicated nonlinear estimation problem with a series of exponential factors with multiplicative coefficients. A technique is presented in this paper where the exponential decay parameters are estimated separately using linear time-invariant system theory. Once the exponential factors are known, the coefficients of the exponentials can be estimated using linear estimation techniques. Computer simulations demonstrate that estimation of the kinetic parameters directly from the projections is more accurate than the estimation from the reconstructed images

Estimation of ground water hydraulic parameters

Energy Technology Data Exchange (ETDEWEB)

Hvilshoej, Soeren

1998-11-01

The main objective was to assess field methods to determine ground water hydraulic parameters and to develop and apply new analysis methods to selected field techniques. A field site in Vejen, Denmark, which previously has been intensively investigated on the basis of a large amount of mini slug tests and tracer tests, was chosen for experimental application and evaluation. Particular interest was in analysing partially penetrating pumping tests and a recently proposed single-well dipole test. Three wells were constructed in which partially penetrating pumping tests and multi-level single-well dipole tests were performed. In addition, multi-level slug tests, flow meter tests, gamma-logs, and geologic characterisation of soil samples were carried out. In addition to the three Vejen analyses, data from previously published partially penetrating pumping tests were analysed assuming homogeneous anisotropic aquifer conditions. In the present study methods were developed to analyse partially penetrating pumping tests and multi-level single-well dipole tests based on an inverse numerical model. The obtained horizontal hydraulic conductivities from the partially penetrating pumping tests were in accordance with measurements obtained from multi-level slug tests and mini slug tests. Accordance was also achieved between the anisotropy ratios determined from partially penetrating pumping tests and multi-level single-well dipole tests. It was demonstrated that the partially penetrating pumping test analysed by and inverse numerical model is a very valuable technique that may provide hydraulic information on the storage terms and the vertical distribution of the horizontal and vertical hydraulic conductivity under both confined and unconfined aquifer conditions. (EG) 138 refs.
Parameter identification for continuous point emission source based on Tikhonov regularization method coupled with particle swarm optimization algorithm.

Science.gov (United States)

Ma, Denglong; Tan, Wei; Zhang, Zaoxiao; Hu, Jun

2017-03-05

In order to identify the parameters of hazardous gas emission source in atmosphere with less previous information and reliable probability estimation, a hybrid algorithm coupling Tikhonov regularization with particle swarm optimization (PSO) was proposed. When the source location is known, the source strength can be estimated successfully by common Tikhonov regularization method, but it is invalid when the information about both source strength and location is absent. Therefore, a hybrid method combining linear Tikhonov regularization and PSO algorithm was designed. With this method, the nonlinear inverse dispersion model was transformed to a linear form under some assumptions, and the source parameters including source strength and location were identified simultaneously by linear Tikhonov-PSO regularization method. The regularization parameters were selected by L-curve method. The estimation results with different regularization matrixes showed that the confidence interval with high-order regularization matrix is narrower than that with zero-order regularization matrix. But the estimation results of different source parameters are close to each other with different regularization matrixes. A nonlinear Tikhonov-PSO hybrid regularization was also designed with primary nonlinear dispersion model to estimate the source parameters. The comparison results of simulation and experiment case showed that the linear Tikhonov-PSO method with transformed linear inverse model has higher computation efficiency than nonlinear Tikhonov-PSO method. The confidence intervals from linear Tikhonov-PSO are more reasonable than that from nonlinear method. The estimation results from linear Tikhonov-PSO method are similar to that from single PSO algorithm, and a reasonable confidence interval with some probability levels can be additionally given by Tikhonov-PSO method. Therefore, the presented linear Tikhonov-PSO regularization method is a good potential method for hazardous emission
Parameter Identification of Piecewise Linear Plasticity Metal Models Used in Numerical Modeling of Structures Under Plastic Deformation and Failure

Directory of Open Access Journals (Sweden)

A. V. Shmeliov

2016-01-01

Full Text Available The article describes the models of metallic materials used in the calculation of deformation and destruction of engineering structures. The reliability of material models can adequately assess the strength characteristics of the designs of new technology in its designing and certification.The article deals with contingencies and true mechanical properties of materials and presents equations of their relationship. It notes that in the software systems mechanical characteristics of materials are given in the true sense.The paper considers the linear and exponential models of materials, their characteristics, and methods to implement them. It considers the models of Johnson-Cook Steinberg-Guinan, Zerilli-Armstrong, Cowper-Symonds, Gurson-Tvergaard that take into account the strain rate and temperature of the material. Describes their applications, advantages and disadvantages. Considers single- and multi-parameter criteria of materials fracture, the prospects for their use. Gives a rational justification for using a piecewise linear plasticity material model *MAT_PIECEWISE_LINEAR_PLASTICITY (024, LS-DYNA software package for the engineering industry, and presents its main parameters.A technique to identify parameters of piecewise linear plasticity metal material models has been developed. The technique consists of the stages, based on the equations of transition from the conventional stress and strain values to the true ones. Taking into consideration the stressstrain state in the neck of the sample is a distinctive feature of the technique.Tensile tests of the round material samples have been conducted. To test the developed technique in the software package ANSYS LS-DYNA PC have been made tensile sample modeling and results comparison to show high convergence.Further improvement of the technique can be achieved through the development of a statistical approach to the analysis of the results of a series of tests. This will allow a kind of
3D elastic full-waveform inversion for OBC data using the P-wave excitation amplitude

KAUST Repository

Oh, Juwon

2017-08-17

We suggest a fast and efficient 3D elastic full waveform inversion (FWI) algorithm based on the excitation amplitude (maximum energy arrival) of the P-wave in the source wavefield. It evaluates the gradient direction significantly faster than its conventional counterpart. In addition, it removes the long-wavelength artifacts from the gradient, which are often originated from SS correlation process. From these advantages, the excitation approach offers faster convergence not only for the S wave velocity, but also for the entire process of multi-parameter inversion, compared to the conventional FWI. The feasibility of the proposed method is demonstrated through the synthetic Marmousi and a real OBC data from North Sea.
3D elastic full-waveform inversion for OBC data using the P-wave excitation amplitude

KAUST Repository

Oh, Juwon; Kalita, Mahesh; Alkhalifah, Tariq Ali

2017-01-01

We suggest a fast and efficient 3D elastic full waveform inversion (FWI) algorithm based on the excitation amplitude (maximum energy arrival) of the P-wave in the source wavefield. It evaluates the gradient direction significantly faster than its conventional counterpart. In addition, it removes the long-wavelength artifacts from the gradient, which are often originated from SS correlation process. From these advantages, the excitation approach offers faster convergence not only for the S wave velocity, but also for the entire process of multi-parameter inversion, compared to the conventional FWI. The feasibility of the proposed method is demonstrated through the synthetic Marmousi and a real OBC data from North Sea.
Admissible Estimators in the General Multivariate Linear Model with Respect to Inequality Restricted Parameter Set

Directory of Open Access Journals (Sweden)

Shangli Zhang

2009-01-01

Full Text Available By using the methods of linear algebra and matrix inequality theory, we obtain the characterization of admissible estimators in the general multivariate linear model with respect to inequality restricted parameter set. In the classes of homogeneous and general linear estimators, the necessary and suffcient conditions that the estimators of regression coeffcient function are admissible are established.
Matrix-Inversion-Free Compressed Sensing With Variable Orthogonal Multi-Matching Pursuit Based on Prior Information for ECG Signals.

Science.gov (United States)

Cheng, Yih-Chun; Tsai, Pei-Yun; Huang, Ming-Hao

2016-05-19

Low-complexity compressed sensing (CS) techniques for monitoring electrocardiogram (ECG) signals in wireless body sensor network (WBSN) are presented. The prior probability of ECG sparsity in the wavelet domain is first exploited. Then, variable orthogonal multi-matching pursuit (vOMMP) algorithm that consists of two phases is proposed. In the first phase, orthogonal matching pursuit (OMP) algorithm is adopted to effectively augment the support set with reliable indices and in the second phase, the orthogonal multi-matching pursuit (OMMP) is employed to rescue the missing indices. The reconstruction performance is thus enhanced with the prior information and the vOMMP algorithm. Furthermore, the computation-intensive pseudo-inverse operation is simplified by the matrix-inversion-free (MIF) technique based on QR decomposition. The vOMMP-MIF CS decoder is then implemented in 90 nm CMOS technology. The QR decomposition is accomplished by two systolic arrays working in parallel. The implementation supports three settings for obtaining 40, 44, and 48 coefficients in the sparse vector. From the measurement result, the power consumption is 11.7 mW at 0.9 V and 12 MHz. Compared to prior chip implementations, our design shows good hardware efficiency and is suitable for low-energy applications.
An approximate inversion method of geoelectrical sounding data using linear and bayesian statistical approaches. Examples of Tritrivakely volcanic lake and Mahitsy area (central part of Madagascar)

International Nuclear Information System (INIS)

Ranaivo Nomenjanahary, F.; Rakoto, H.; Ratsimbazafy, J.B.

1994-08-01

This paper is concerned with resistivity sounding measurements performed from single site (vertical sounding) or from several sites (profiles) within a bounded area. The objective is to present an accurate information about the study area and to estimate the likelihood of the produced quantitative models. The achievement of this objective obviously requires quite relevant data and processing methods. It also requires interpretation methods which should take into account the probable effect of an heterogeneous structure. In front of such difficulties, the interpretation of resistivity sounding data inevitably involves the use of inversion methods. We suggest starting the interpretation in simple situation (1-D approximation), and using the rough but correct model obtained as an a-priori model for any more refined interpretation. Related to this point of view, special attention should be paid for the inverse problem applied to the resistivity sounding data. This inverse problem is nonlinear, while linearity inherent in the functional response used to describe the physical experiment. Two different approaches are used to build an approximate but higher dimensional inversion of geoelectrical data: the linear approach and the bayesian statistical approach. Some illustrations of their application in resistivity sounding data acquired at Tritrivakely volcanic lake (single site) and at Mahitsy area (several sites) will be given. (author). 28 refs, 7 figs
Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

Science.gov (United States)

Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-01

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048
Total water production capacity inversion phenomenon in multi-stage direct contact membrane distillation: A theoretical study

KAUST Repository

Lee, Jung Gil

2017-09-09

The low thermal efficiency and low water production are among the major challenges that prevent membrane distillation (MD) process from being commercialized. In an effort to design an efficient multi-stage direct contact MD (DCMD) unit through mathematical simulation, a new phenomenon that we refer to as total water production capacity inversion (WPI) has been detected. It is represented by a decrease in the total water production beyond a number of stages or a certain module length. WPI phenomenon, which was confirmed by using two different mathematical models validated experimentally, was found to take place due to the decrease in water vapor flux across the membrane as well as the increase in heat loss by conduction as the membrane length increases. Therefore, WPI should be considered as a critical MD design-criterion, especially for large scale units. Investigations conducted for a simulated multi-stage DCMD process showed that inlet feed and permeate temperatures difference, feed and permeate flow rates, and feed salinity have different effects on WPI. The number of stages (or module length at constant width) that leads to a maximum water production has been determined for different operating parameters. Decreasing inlet feed and permeate temperatures difference, or inlet feed and permeate flow rates and increasing inlet feed temperature at constant temperature difference or inlet feed salinity cause the WPI to take place at lower number of stages. Even though the feed salinity affects negligibly the mean permeate flux, it was clearly shown that it can affect WPI. The results presented herein unveil a hidden phenomenon that is likely to occur during process scale-up procedures and should be considered by process engineers for a proper choice of system design and operating conditions.
Anisotropic wave-equation traveltime and waveform inversion

KAUST Repository

Feng, Shihang; Schuster, Gerard T.

2016-01-01

The wave-equation traveltime and waveform inversion (WTW) methodology is developed to invert for anisotropic parameters in a vertical transverse isotropic (VTI) meidum. The simultaneous inversion of anisotropic parameters v0, ε and δ is initially
Evaluation of a Linear Mixing Model to Retrieve Soil and Vegetation Temperatures of Land Targets

International Nuclear Information System (INIS)

Yang, Jinxin; Jia, Li; Cui, Yaokui; Zhou, Jie; Menenti, Massimo

2014-01-01

A simple linear mixing model of heterogeneous soil-vegetation system and retrieval of component temperatures from directional remote sensing measurements by inverting this model is evaluated in this paper using observations by a thermal camera. The thermal camera was used to obtain multi-angular TIR (Thermal Infra-Red) images over vegetable and orchard canopies. A whole thermal camera image was treated as a pixel of a satellite image to evaluate the model with the two-component system, i.e. soil and vegetation. The evaluation included two parts: evaluation of the linear mixing model and evaluation of the inversion of the model to retrieve component temperatures. For evaluation of the linear mixing model, the RMSE is 0.2 K between the observed and modelled brightness temperatures, which indicates that the linear mixing model works well under most conditions. For evaluation of the model inversion, the RMSE between the model retrieved and the observed vegetation temperatures is 1.6K, correspondingly, the RMSE between the observed and retrieved soil temperatures is 2.0K. According to the evaluation of the sensitivity of retrieved component temperatures on fractional cover, the linear mixing model gives more accurate retrieval accuracies for both soil and vegetation temperatures under intermediate fractional cover conditions
Temporal rainfall estimation using input data reduction and model inversion

Science.gov (United States)

Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

2016-12-01

Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a
LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

Czech Academy of Sciences Publication Activity Database

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek; Stohl, A.

2016-01-01

Roč. 9, č. 11 (2016), s. 4297-4311 ISSN 1991-959X R&D Projects: GA MŠk(CZ) 7F14287 Institutional support: RVO:67985556 Keywords : Linear inverse problem * Bayesian regularization * Source-term determination * Variational Bayes method Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.458, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/tichy-0466029.pdf
A variational Bayesian method to inverse problems with impulsive noise

KAUST Repository

Jin, Bangti

2012-01-01

We propose a novel numerical method for solving inverse problems subject to impulsive noises which possibly contain a large number of outliers. The approach is of Bayesian type, and it exploits a heavy-tailed t distribution for data noise to achieve robustness with respect to outliers. A hierarchical model with all hyper-parameters automatically determined from the given data is described. An algorithm of variational type by minimizing the Kullback-Leibler divergence between the true posteriori distribution and a separable approximation is developed. The numerical method is illustrated on several one- and two-dimensional linear and nonlinear inverse problems arising from heat conduction, including estimating boundary temperature, heat flux and heat transfer coefficient. The results show its robustness to outliers and the fast and steady convergence of the algorithm. © 2011 Elsevier Inc.
Multi-parameter full waveform inversion using Poisson

KAUST Repository

Oh, Juwon; Min, Dong-Joo

2016-01-01

on the two conventional parameterisations (one uses Lame constants and density; the other employs P- and S-wave velocities and density) have low resolution of gradients for P-wave velocities (or ). Limitations occur because the virtual sources for P
Inverse transport theory of photoacoustics

International Nuclear Information System (INIS)

Bal, Guillaume; Jollivet, Alexandre; Jugnon, Vincent

2010-01-01

We consider the reconstruction of optical parameters in a domain of interest from photoacoustic data. Photoacoustic tomography (PAT) radiates high-frequency electromagnetic waves into the domain and measures acoustic signals emitted by the resulting thermal expansion. Acoustic signals are then used to construct the deposited thermal energy map. The latter depends on the constitutive optical parameters in a nontrivial manner. In this paper, we develop and use an inverse transport theory with internal measurements to extract information on the optical coefficients from knowledge of the deposited thermal energy map. We consider the multi-measurement setting in which many electromagnetic radiation patterns are used to probe the domain of interest. By developing an expansion of the measurement operator into singular components, we show that the spatial variations of the intrinsic attenuation and the scattering coefficients may be reconstructed. We also reconstruct coefficients describing anisotropic scattering of photons, such as the anisotropy coefficient g(x) in a Henyey–Greenstein phase function model. Finally, we derive stability estimates for the reconstructions
Surface parameter characterization of surface vibrations in linear chains

International Nuclear Information System (INIS)

Majlis, N.; Selzer, S.; Puszkarski, H.; Diep-The-Hung

1982-12-01

We consider the vibrations of a linear monatomic chain with a complex surface potential defined by the surface pinning parameter a=Aesup(-i psi). It is found that in the case of a semi-infinite chain a is connected with the surface vibration wave number k=s+it by the exact relations: s=psi, t=lnA. We also show that the solutions found can be regarded as approximate ones (in the limit L>>1) for surface vibrations of a finite chain consisting of L atoms. (author)
Creep and inverse stress relaxation behaviors of carbon nanotube yarns.

Science.gov (United States)

Misak, H E; Sabelkin, V; Miller, L; Asmatulu, R; Mall, S

2013-12-01

Creep, creep recovery and inverse stress relaxation behaviors of carbon nanotube yarns that consisted of 1-, 30-, and 100-yarn(s) were characterized. Primary and secondary creep stages were observed over the duration of 336 h. The primary creep stage lasted for about 4 h at an applied load equal to 75% of the ultimate tensile strength. The total strain in the primary stage was significantly larger in the carbon nanotube multi-yarn than in the carbon nanotube 1-yarn. In the secondary stage, 1-yarn also had a smaller steady state strain rate than the multi-yarn, and it was independent of number of yarns in multi-yarn. Strain response under cyclic creep loading condition was comparable to its counterpart in non-cyclic (i.e., standard) creep test except that strain response during the first cycle was slightly different from the subsequent cycles. Inverse creep (i.e., strain recovery) was observed in the 100-yarn during the cyclic creep tests after the first unloading cycle. Furthermore, inverse stress relaxation of the multi-yarns was characterized. Inverse stress relaxation was larger and for longer duration with the larger number of yarns.
Strong Maximum Principle for Multi-Term Time-Fractional Diffusion Equations and its Application to an Inverse Source Problem

OpenAIRE

Liu, Yikan

2015-01-01

In this paper, we establish a strong maximum principle for fractional diffusion equations with multiple Caputo derivatives in time, and investigate a related inverse problem of practical importance. Exploiting the solution properties and the involved multinomial Mittag-Leffler functions, we improve the weak maximum principle for the multi-term time-fractional diffusion equation to a stronger one, which is parallel to that for its single-term counterpart as expected. As a direct application, w...

Remote and Local Influences in Forecasting Pacific SST: a Linear Inverse Model and a Multimodel Ensemble Study

Science.gov (United States)

Faggiani Dias, D.; Subramanian, A. C.; Zanna, L.; Miller, A. J.

2017-12-01

Sea surface temperature (SST) in the Pacific sector is well known to vary on time scales from seasonal to decadal, and the ability to predict these SST fluctuations has many societal and economical benefits. Therefore, we use a suite of statistical linear inverse models (LIMs) to understand the remote and local SST variability that influences SST predictions over the North Pacific region and further improve our understanding on how the long-observed SST record can help better guide multi-model ensemble forecasts. Observed monthly SST anomalies in the Pacific sector (between 15oS and 60oN) are used to construct different regional LIMs for seasonal to decadal prediction. The forecast skills of the LIMs are compared to that from two operational forecast systems in the North American Multi-Model Ensemble (NMME) revealing that the LIM has better skill in the Northeastern Pacific than NMME models. The LIM is also found to have comparable forecast skill for SST in the Tropical Pacific with NMME models. This skill, however, is highly dependent on the initialization month, with forecasts initialized during the summer having better skill than those initialized during the winter. The forecast skill with LIM is also influenced by the verification period utilized to make the predictions, likely due to the changing character of El Niño in the 20th century. The North Pacific seems to be a source of predictability for the Tropics on seasonal to interannual time scales, while the Tropics act to worsen the skill for the forecast in the North Pacific. The data were also bandpassed into seasonal, interannual and decadal time scales to identify the relationships between time scales using the structure of the propagator matrix. For the decadal component, this coupling occurs the other way around: Tropics seem to be a source of predictability for the Extratropics, but the Extratropics don't improve the predictability for the Tropics. These results indicate the importance of temporal
Trimming and procrastination as inversion techniques

Science.gov (United States)

Backus, George E.

1996-12-01

By examining the processes of truncating and approximating the model space (trimming it), and by committing to neither the objectivist nor the subjectivist interpretation of probability (procrastinating), we construct a formal scheme for solving linear and non-linear geophysical inverse problems. The necessary prior information about the correct model xE can be either a collection of inequalities or a probability measure describing where xE was likely to be in the model space X before the data vector y0 was measured. The results of the inversion are (1) a vector z0 that estimates some numerical properties zE of xE; (2) an estimate of the error δz = z0 - zE. As y0 is finite dimensional, so is z0, and hence in principle inversion cannot describe all of xE. The error δz is studied under successively more specialized assumptions about the inverse problem, culminating in a complete analysis of the linear inverse problem with a prior quadratic bound on xE. Our formalism appears to encompass and provide error estimates for many of the inversion schemes current in geomagnetism, and would be equally applicable in geodesy and seismology if adequate prior information were available there. As an idealized example we study the magnetic field at the core-mantle boundary, using satellite measurements of field elements at sites assumed to be almost uniformly distributed on a single spherical surface. Magnetospheric currents are neglected and the crustal field is idealized as a random process with rotationally invariant statistics. We find that an appropriate data compression diagonalizes the variance matrix of the crustal signal and permits an analytic trimming of the idealized problem.
Theory and Simulation of an Inverse Free Electron Laser Experiment

Science.gov (United States)

Guo, S. K.; Bhattacharjee, A.; Fang, J. M.; Marshall, T. C.

1996-11-01

An experimental demonstration of the acceleration of electrons using a high power CO2 laser in an inverse free electron laser (IFEL) is underway at the Brookhaven National Laboratory. This experiment has generated data, which we are attempting to simulate. Included in our studies are such effects as: a low-loss metallic waveguide with a dielectric coating on the walls; multi-mode coupling due to self-consistent interaction between the electrons and the optical wave; space charge (which is significant at lower laser power); energy-spread of the electrons; arbitrary wiggler field profile; and slippage. Two types of wiggler profile have been considered: a linear taper of the period, and a step-taper of the period (the period is ~ 3cm, the field is ~ 1T, and the wiggler length is 47cm). The energy increment of the electrons ( ~ 1-2%) is analyzed in detail as a function of laser power, wiggler parameters, and the initial beam energy (40MeV). For laser power ~ 0.5GW, the predictions of the simulations are in good accord with experimental results. A matter currently under study is the discrepancy between theory and observations for the electron energy distribution observed at the end of the IFEL. This work is supported by the Department of Energy.
Finite-dimensional linear algebra

CERN Document Server

Gockenbach, Mark S

2010-01-01

Some Problems Posed on Vector SpacesLinear equationsBest approximationDiagonalizationSummaryFields and Vector SpacesFields Vector spaces Subspaces Linear combinations and spanning sets Linear independence Basis and dimension Properties of bases Polynomial interpolation and the Lagrange basis Continuous piecewise polynomial functionsLinear OperatorsLinear operatorsMore properties of linear operatorsIsomorphic vector spaces Linear operator equations Existence and uniqueness of solutions The fundamental theorem; inverse operatorsGaussian elimination Newton's method Linear ordinary differential eq
Three-dimensional inversion of multisource array electromagnetic data

Science.gov (United States)

Tartaras, Efthimios

Three-dimensional (3-D) inversion is increasingly important for the correct interpretation of geophysical data sets in complex environments. To this effect, several approximate solutions have been developed that allow the construction of relatively fast inversion schemes. One such method that is fast and provides satisfactory accuracy is the quasi-linear (QL) approximation. It has, however, the drawback that it is source-dependent and, therefore, impractical in situations where multiple transmitters in different positions are employed. I have, therefore, developed a localized form of the QL approximation that is source-independent. This so-called localized quasi-linear (LQL) approximation can have a scalar, a diagonal, or a full tensor form. Numerical examples of its comparison with the full integral equation solution, the Born approximation, and the original QL approximation are given. The objective behind developing this approximation is to use it in a fast 3-D inversion scheme appropriate for multisource array data such as those collected in airborne surveys, cross-well logging, and other similar geophysical applications. I have developed such an inversion scheme using the scalar and diagonal LQL approximation. It reduces the original nonlinear inverse electromagnetic (EM) problem to three linear inverse problems. The first of these problems is solved using a weighted regularized linear conjugate gradient method, whereas the last two are solved in the least squares sense. The algorithm I developed provides the option of obtaining either smooth or focused inversion images. I have applied the 3-D LQL inversion to synthetic 3-D EM data that simulate a helicopter-borne survey over different earth models. The results demonstrate the stability and efficiency of the method and show that the LQL approximation can be a practical solution to the problem of 3-D inversion of multisource array frequency-domain EM data. I have also applied the method to helicopter-borne EM
Inversion of double-difference measurements from optical levelling for the Groningen gas field

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P. A. Fokker

2015-11-01

Full Text Available Hydrocarbon extraction lead to compaction of the gas reservoir which is visible as subsidence on the surface. Subsidence measurements can therefore be used to better estimate reservoir parameters. Total subsidence is derived from the result of the measurement of height differences between optical benchmarks. The procedure from optical height difference measurements to absolute subsidence is an inversion, and the result is often used as an input for consequent inversions on the reservoir. We have used the difference measurements directly to invert for compaction of the Groningen gas reservoir in the Netherlands. We have used a linear inversion exercise to update an already existing reservoir compaction model of the field. This procedure yielded areas of increased and decreased levels of compaction compared to the existing compaction model in agreement with observed discrepancies in porosity and aquifer activity.
Spectral inversion of frequency-domain IP data obtained in Haenam, South Korea

Science.gov (United States)

Kim, B.; Nam, M. J.; Son, J. S.

2017-12-01

Spectral induced polarization (SIP) method using a range of source frequencies have been performed for not only exploring minerals resources, but also engineering or environmental application. SIP interpretation first makes inversion of individual frequency data to obtain complex resistivity structures, which will further analyzed employing Cole-Cole model to explain the frequency-dependent characteristics. However, due to the difficulty in fitting Cole-Cole model, there is a movement to interpret complex resistivity structure inverted only from a single frequency data: that is so-called "complex resistivity survey". Further, simultaneous inversion of multi-frequency SIP data, rather than making a single frequency SIP data, has been studied to improve ambiguity and artefacts of independent single frequency inversion in obtaining a complex resistivity structure, even though the dispersion characteristics of complex resistivity with respect to source frequency. Employing the simultaneous inversion method, this study makes inversion of field SIP data obtained over epithermal mineralized area, Haenam, in the southernmost tip of South Korea. The area has a polarizable structure because of extensive hydrothermal alteration, gold-silver deposits. After the inversion, we compare between inversion results considering multi-frequency data and single frequency data set to evaluate the performance of simultaneous inversion of multi-frequency SIP data.
Multi-year Estimates of Methane Fluxes in Alaska from an Atmospheric Inverse Model

Science.gov (United States)

Miller, S. M.; Commane, R.; Chang, R. Y. W.; Miller, C. E.; Michalak, A. M.; Dinardo, S. J.; Dlugokencky, E. J.; Hartery, S.; Karion, A.; Lindaas, J.; Sweeney, C.; Wofsy, S. C.

2015-12-01

We estimate methane fluxes across Alaska over a multi-year period using observations from a three-year aircraft campaign, the Carbon Arctic Reservoirs Vulnerability Experiment (CARVE). Existing estimates of methane from Alaska and other Arctic regions disagree in both magnitude and distribution, and before the CARVE campaign, atmospheric observations in the region were sparse. We combine these observations with an atmospheric particle trajectory model and a geostatistical inversion to estimate surface fluxes at the model grid scale. We first use this framework to estimate the spatial distribution of methane fluxes across the state. We find the largest fluxes in the south-east and North Slope regions of Alaska. This distribution is consistent with several estimates of wetland extent but contrasts with the distribution in most existing flux models. These flux models concentrate methane in warmer or more southerly regions of Alaska compared to the estimate presented here. This result suggests a discrepancy in how existing bottom-up models translate wetland area into methane fluxes across the state. We next use the inversion framework to explore inter-annual variability in regional-scale methane fluxes for 2012-2014. We examine the extent to which this variability correlates with weather or other environmental conditions. These results indicate the possible sensitivity of wetland fluxes to near-term variability in climate.
CIMI simulations with recently developed multi-parameter chorus and plasmaspheric hiss models

Science.gov (United States)

Aryan, Homayon; Sibeck, David; Kang, Suk-bin; Balikhin, Michael; Fok, Mei-ching

2017-04-01

Simulation studies of the Earth's radiation belts are very useful in understanding the acceleration and loss of energetic particles. The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model considers the effects of the ring current and plasmasphere on the radiation belts. CIMI was formed by merging the Comprehensive Ring Current Model (CRCM) and the Radiation Belt Environment (RBE) model to solves for many essential quantities in the inner magnetosphere, including radiation belt enhancements and dropouts. It incorporates chorus and plasmaspheric hiss wave diffusion of energetic electrons in energy, pitch angle, and cross terms. Usually the chorus and plasmaspheric hiss models used in CIMI are based on single-parameter geomagnetic index (AE). Here we integrate recently developed multi-parameter chorus and plasmaspheric hiss wave models based on geomagnetic index and solar wind parameters. We then perform CIMI simulations for different storms and compare the results with data from the Van Allen Probes and the Two Wide-angle Imaging Neutral-atom Spectrometers and Akebono satellites. We find that the CIMI simulations with multi-parameter chorus and plasmaspheric hiss wave models are more comparable to data than the single-parameter wave models.
Point-source inversion techniques

Science.gov (United States)

Langston, Charles A.; Barker, Jeffrey S.; Pavlin, Gregory B.

1982-11-01

A variety of approaches for obtaining source parameters from waveform data using moment-tensor or dislocation point source models have been investigated and applied to long-period body and surface waves from several earthquakes. Generalized inversion techniques have been applied to data for long-period teleseismic body waves to obtain the orientation, time function and depth of the 1978 Thessaloniki, Greece, event, of the 1971 San Fernando event, and of several events associated with the 1963 induced seismicity sequence at Kariba, Africa. The generalized inversion technique and a systematic grid testing technique have also been used to place meaningful constraints on mechanisms determined from very sparse data sets; a single station with high-quality three-component waveform data is often sufficient to discriminate faulting type (e.g., strike-slip, etc.). Sparse data sets for several recent California earthquakes, for a small regional event associated with the Koyna, India, reservoir, and for several events at the Kariba reservoir have been investigated in this way. Although linearized inversion techniques using the moment-tensor model are often robust, even for sparse data sets, there are instances where the simplifying assumption of a single point source is inadequate to model the data successfully. Numerical experiments utilizing synthetic data and actual data for the 1971 San Fernando earthquake graphically demonstrate that severe problems may be encountered if source finiteness effects are ignored. These techniques are generally applicable to on-line processing of high-quality digital data, but source complexity and inadequacy of the assumed Green's functions are major problems which are yet to be fully addressed.
A Comparison of Alternative Estimators of Linearly Aggregated Macro Models

Directory of Open Access Journals (Sweden)

Fikri Akdeniz

2012-07-01

Full Text Available Normal 0 false false false TR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif"; mso-ansi-language:TR; mso-fareast-language:TR;} This paper deals with the linear aggregation problem. For the true underlying micro relations, which explain the micro behavior of the individuals, no restrictive rank conditions are assumed. Thus the analysis is presented in a framework utilizing generalized inverses of singular matrices. We investigate several estimators for certain linear transformations of the systematic part of the corresponding macro relations. Homogeneity of micro parameters is discussed. Best linear unbiased estimation for micro parameters is described.
Mathematical model for the contribution of individual organs to non-zero y-intercepts in single and multi-compartment linear models of whole-body energy expenditure.

Science.gov (United States)

Kaiyala, Karl J

2014-01-01

Mathematical models for the dependence of energy expenditure (EE) on body mass and composition are essential tools in metabolic phenotyping. EE scales over broad ranges of body mass as a non-linear allometric function. When considered within restricted ranges of body mass, however, allometric EE curves exhibit 'local linearity.' Indeed, modern EE analysis makes extensive use of linear models. Such models typically involve one or two body mass compartments (e.g., fat free mass and fat mass). Importantly, linear EE models typically involve a non-zero (usually positive) y-intercept term of uncertain origin, a recurring theme in discussions of EE analysis and a source of confounding in traditional ratio-based EE normalization. Emerging linear model approaches quantify whole-body resting EE (REE) in terms of individual organ masses (e.g., liver, kidneys, heart, brain). Proponents of individual organ REE modeling hypothesize that multi-organ linear models may eliminate non-zero y-intercepts. This could have advantages in adjusting REE for body mass and composition. Studies reveal that individual organ REE is an allometric function of total body mass. I exploit first-order Taylor linearization of individual organ REEs to model the manner in which individual organs contribute to whole-body REE and to the non-zero y-intercept in linear REE models. The model predicts that REE analysis at the individual organ-tissue level will not eliminate intercept terms. I demonstrate that the parameters of a linear EE equation can be transformed into the parameters of the underlying 'latent' allometric equation. This permits estimates of the allometric scaling of EE in a diverse variety of physiological states that are not represented in the allometric EE literature but are well represented by published linear EE analyses.
Multi-scattering inversion for low model wavenumbers

KAUST Repository

Alkhalifah, Tariq Ali; Wu, Zedong

2015-01-01

modeled from the source and those corresponding to single and double scattering to update both the velocity model and the component of the velocity (perturbation) responsible for the single and double scattering. The combined inversion helps us access most
Parameter-dependent PWQ Lyapunov function stability criteria for uncertain piecewise linear systems

Directory of Open Access Journals (Sweden)

Morten Hovd

2018-01-01

Full Text Available The calculation of piecewise quadratic (PWQ Lyapunov functions is addressed in view of stability analysis of uncertain piecewise linear dynamics. As main contribution, the linear matrix inequality (LMI approach proposed in (Johansson and Rantzer, 1998 for the stability analysis of PWL and PWA dynamics is extended to account for parametric uncertainty based on a improved relaxation technique. The results are applied for the analysis of a Phase Locked Loop (PLL benchmark and the ability to guarantee a stability region in the parameter space well beyond the state of the art is demonstrated.
Experimental researches and comparison on aerodynamic parameters and cleaning efficiency of multi-level multi-channel cyclone

Directory of Open Access Journals (Sweden)

Aleksandras Chlebnikovas

2015-10-01

Full Text Available Multi-level multi-channel cyclone – the lately designed air cleaning device that can remove ultra-fine 20 μm particulatematter (PM from dusted air and reach over 95% of the overall cleaning efficiency. Multi-channel cyclone technology is based on centrifugal forces and has the resulting additional filtering process operation. Multi-level structure of cyclone allows to achieve higher air flow cleaning capacity at the same dimensions of the device, thus saving installation space required for the job, production and operating costs. Studies have examined the air flow parameters change in one–, two– and three–levels multichannel cyclone. These constructions differ according to the productivity of cleaned air under the constant peripheral and transitional (50/50 case air flow relations. Accordance with the results of air flow dynamics – velocity distribution of multi-channel cyclone, aerodynamic resistance and efficiency can be judged on the flow turbulence, the flow channel cross-section and select the most appropriate application. Cleaning efficiency studies were carried out using fine granite and wood ashes PM. The maximum cleaning efficiency was 93.3%, at an average of 4.5 g/m3, the aerodynamic resistance was equal to 1525 Pa.
Moment Tensor Inversion with 3D sensor configuration of Mining Induced Seismicity (Kiruna mine, Sweden)

Science.gov (United States)

Ma, Ju; Dineva, Savka; Cesca, Simone; Heimann, Sebastian

2018-03-01

Mining induced seismicity is an undesired consequence of mining operations, which poses significant hazard to miners and infrastructures and requires an accurate analysis of the rupture process. Seismic moment tensors of mining-induced events help to understand the nature of mining-induced seismicity by providing information about the relationship between the mining, stress redistribution and instabilities in the rock mass. In this work, we adapt and test a waveform-based inversion method on high frequency data recorded by a dense underground seismic system in one of the largest underground mines in the world (Kiruna mine, Sweden). Stable algorithm for moment tensor inversion for comparatively small mining induced earthquakes, resolving both the double couple and full moment tensor with high frequency data is very challenging. Moreover, the application to underground mining system requires accounting for the 3D geometry of the monitoring system. We construct a Green's function database using a homogeneous velocity model, but assuming a 3D distribution of potential sources and receivers. We first perform a set of moment tensor inversions using synthetic data to test the effects of different factors on moment tensor inversion stability and source parameters accuracy, including the network spatial coverage, the number of sensors and the signal-to-noise ratio. The influence of the accuracy of the input source parameters on the inversion results is also tested. Those tests show that an accurate selection of the inversion parameters allows resolving the moment tensor also in presence of realistic seismic noise conditions. Finally, the moment tensor inversion methodology is applied to 8 events chosen from mining block #33/34 at Kiruna mine. Source parameters including scalar moment, magnitude, double couple, compensated linear vector dipole and isotropic contributions as well as the strike, dip, rake configurations of the double couple term were obtained. The orientations
Moment tensor inversion with three-dimensional sensor configuration of mining induced seismicity (Kiruna mine, Sweden)

Science.gov (United States)

Ma, Ju; Dineva, Savka; Cesca, Simone; Heimann, Sebastian

2018-06-01

Mining induced seismicity is an undesired consequence of mining operations, which poses significant hazard to miners and infrastructures and requires an accurate analysis of the rupture process. Seismic moment tensors of mining-induced events help to understand the nature of mining-induced seismicity by providing information about the relationship between the mining, stress redistribution and instabilities in the rock mass. In this work, we adapt and test a waveform-based inversion method on high frequency data recorded by a dense underground seismic system in one of the largest underground mines in the world (Kiruna mine, Sweden). A stable algorithm for moment tensor inversion for comparatively small mining induced earthquakes, resolving both the double-couple and full moment tensor with high frequency data, is very challenging. Moreover, the application to underground mining system requires accounting for the 3-D geometry of the monitoring system. We construct a Green's function database using a homogeneous velocity model, but assuming a 3-D distribution of potential sources and receivers. We first perform a set of moment tensor inversions using synthetic data to test the effects of different factors on moment tensor inversion stability and source parameters accuracy, including the network spatial coverage, the number of sensors and the signal-to-noise ratio. The influence of the accuracy of the input source parameters on the inversion results is also tested. Those tests show that an accurate selection of the inversion parameters allows resolving the moment tensor also in the presence of realistic seismic noise conditions. Finally, the moment tensor inversion methodology is applied to eight events chosen from mining block #33/34 at Kiruna mine. Source parameters including scalar moment, magnitude, double-couple, compensated linear vector dipole and isotropic contributions as well as the strike, dip and rake configurations of the double-couple term were obtained
Multi-Parameter Analysis of Surface Finish in Electro-Discharge Machining of Tool Steels

Directory of Open Access Journals (Sweden)

Cornelia Victoria Anghel

2006-10-01

Full Text Available The paper presents a multi- parameter analysis of surface finish imparted to tool-steel plates by electro-discharge machining (EDM is presented. The interrelationship between surface texture parameters and process parameters is emphasized. An increased number of parameters is studied including amplitude, spacing, hybrid and fractal parameters,, as well. The correlation of these parameters with the machining conditions is investigated. Observed characteristics become more pronounced, when intensifying machining conditions. Close correlation exists between certain surface finish parameters and EDM input variables and single and multiple statistical regression models are developed.
Real-time multi-parameter cell-based analysis platform

DEFF Research Database (Denmark)

Caviglia, Claudia

biomedical diagnostic techniques, drug discovery and screening. My project focused on the further development, improvement and exploration of the EXCELL microfluidic platform with particular interest in drug kinetic monitoring and neurotransmitter detection. The aim was to perform multi-parameter real...... of protocols and procedures for performing different cellular assays. (2) Electrochemical impedance spectroscopy (EIS) applied for drug screening and drug delivery in cancer research and wound healing studies. (3) Amperometry for monitoring of neurotransmitter exocytosis, relevant in research on Parkinson...
Correlating Gas Transport Parameters and X-ray Computed Tomography Measurements in Porous Media

DEFF Research Database (Denmark)

Naveed, Muhammad; Hamamoto, Shoichiro; Kawamoto, Ken

2013-01-01

physical processes. The objective of this study was to characterize the relationships between gas transport parameters and soil-pore geometry revealed by X-ray CT. Sands of different shapes with a mean particle diameter (d50) ranging from 0.19 to 1.51 mm were used as porous media under both air...... was found between α and tortuosity calculated from gas transport parameters (Equation (Uncited) Image Tools), indicating that gas dispersivity has a linear and inverse relationship with gas diffusivity. A linear relationship was also found between ka and d50/TUMS2, indicating a strong dependency of ka...

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