Bayesian Approach to Inverse Problems
2008-01-01
Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation. The concept of inverse problems precisely originates from the idea of inverting the laws of physics to recover a quantity of interest from measurable data.Unfortunately, most inverse problems are ill-posed, which means that precise and stable solutions are not easy to devise. Regularization is the key concept to solve inverse problems.The goal of this book is to deal with inverse problems and regularized solutions using the Bayesian statistical tools, with a particular view to signal and image estimation
Inverse statistical approach in heartbeat time series
International Nuclear Information System (INIS)
Ebadi, H; Shirazi, A H; Mani, Ali R; Jafari, G R
2011-01-01
We present an investigation on heart cycle time series, using inverse statistical analysis, a concept borrowed from studying turbulence. Using this approach, we studied the distribution of the exit times needed to achieve a predefined level of heart rate alteration. Such analysis uncovers the most likely waiting time needed to reach a certain change in the rate of heart beat. This analysis showed a significant difference between the raw data and shuffled data, when the heart rate accelerates or decelerates to a rare event. We also report that inverse statistical analysis can distinguish between the electrocardiograms taken from healthy volunteers and patients with heart failure
An inverse approach for elucidating dendritic function
Directory of Open Access Journals (Sweden)
Benjamin Torben-Nielsen
2010-09-01
Full Text Available We outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a-priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a `hypothesis generator' in which we optimize dendrites for a function of general interest. The optimization yields an artificial dendrite that is subsequently compared to real neurons. This comparison potentially allows us to propose hypotheses about the function of real neurons. In this way, we investigated dendrites that optimally perform input-order detection. Second, we can use it as a `function confirmation' by optimizing dendrites for functions hypothesized to be performed by classes of neurons. If the optimized, artificial, dendrites resemble the dendrites of real neurons the artificial dendrites corroborate the hypothesized function of the real neuron. Moreover, properties of the artificial dendrites can lead to predictions about yet unmeasured properties. In this way, we investigated wide-field motion integration performed by the VS cells of the fly visual system. In outlining the inverse approach and two applications, we also elaborate on the nature of dendritic function. We furthermore discuss the role of optimality in assigning functions to dendrites and point out interesting future directions.
Approaching the Island of Inversion: 34P
Energy Technology Data Exchange (ETDEWEB)
Bender, P.C.; Hoffman, C.R.; Wiedeking, M.; Allmond, J.M.; Bernstein, L.A.; Burke, J.T.; Bleuel, D.L.; Clark, R.M.; Fallon, P.; Goldblum, B.L.; Hinners, T.A.; Jeppesen, H.B.; Lee, Sangjin; Lee, I.Y.; Lesher, S.R.; Machiavelli, A.O.; McMahan, M.A.; Morris, D.; Perry, M.; Phair, L.; Scielzo, N.D.; Tabor, S.L.; Tripathi, Vandana; Volya, A.
2011-06-14
Yrast states in 34P were investigated using the 18O(18O,pn) reaction at energies of 20, 24, 25, 30, and 44 MeV at Florida State University and at Lawrence Berkeley National Laboratory. The level scheme was expanded, ray angular distributions were measured, and lifetimes were inferred with the Doppler-shift attenuation method by detecting decay protons in coincidence with one or more rays. The results provide a clearer picture of the evolution of structure approaching the 'Island of Inversion', particularly how the 1 and 2 particle-hole (ph) states fall in energy with increasing neutro number approaching inversion. However, the agreement of the lowest few states with pure sd shell model predictions shows that the level scheme of 34P is not itself inverted. Rather, the accumulated evidence indicates that the 1-ph states start at 2.3 MeV. A good candidate for the lowest 2-ph state lies at 6236 keV, just below the neutron separation energy of 6291 keV. Shell model calculations made using a small modification of the WBP interaction reproduce the negative-parity, 1-ph states rather well.
Structured Sparsity Regularization Approach to the EEG Inverse Problem
DEFF Research Database (Denmark)
Montoya-Martinez, Jair; Artes-Rodriguez, Antonio; Hansen, Lars Kai
2012-01-01
Localization of brain activity involves solving the EEG inverse problem, which is an undetermined ill-posed problem. We propose a novel approach consisting in estimating, using structured sparsity regularization techniques, the Brain Electrical Sources (BES) matrix directly in the spatio......-temporal source space. We use proximal splitting optimization methods, which are efficient optimization techniques, with good convergence rates and with the ability to handle large nonsmooth convex problems, which is the typical scenario in the EEG inverse problem. We have evaluated our approach under a simulated...
Some numerical approaches to solving one-dimensional inverse problems
International Nuclear Information System (INIS)
Hagin, F.
1980-01-01
A class of one-dimensional inverse scattering problems are studied with the goal of reconstructing (say) propagation speed to moderate accuracy as inexpensively as possible. Three alternatives are discussed; all starting from a change to the travel-time variable and converting the problem to integral equation form. The approaches are compared as to their economy of use and the problems for which they are effective. Several numerical examples illustrate these comparisons
A nonlinear approach of elastic reflection waveform inversion
Guo, Qiang
2016-09-06
Elastic full waveform inversion (EFWI) embodies the original intention of waveform inversion at its inception as it is a better representation of the mostly solid Earth. However, compared with the acoustic P-wave assumption, EFWI for P- and S-wave velocities using multi-component data admitted mixed results. Full waveform inversion (FWI) is a highly nonlinear problem and this nonlinearity only increases under the elastic assumption. Reflection waveform inversion (RWI) can mitigate the nonlinearity by relying on transmissions from reflections focused on inverting low wavenumber components of the model. In our elastic endeavor, we split the P- and S-wave velocities into low wavenumber and perturbation components and propose a nonlinear approach to invert for both of them. The new optimization problem is built on an objective function that depends on both background and perturbation models. We utilize an equivalent stress source based on the model perturbation to generate reflection instead of demigrating from an image, which is applied in conventional RWI. Application on a slice of an ocean-bottom data shows that our method can efficiently update the low wavenumber parts of the model, but more so, obtain perturbations that can be added to the low wavenumbers for a high resolution output.
From inverse problems to learning: a Statistical Mechanics approach
Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo
2018-01-01
We present a brief introduction to the statistical mechanics approaches for the study of inverse problems in data science. We then provide concrete new results on inferring couplings from sampled configurations in systems characterized by an extensive number of stable attractors in the low temperature regime. We also show how these result are connected to the problem of learning with realistic weak signals in computational neuroscience. Our techniques and algorithms rely on advanced mean-field methods developed in the context of disordered systems.
Anthropomorphic Coding of Speech and Audio: A Model Inversion Approach
Directory of Open Access Journals (Sweden)
W. Bastiaan Kleijn
2005-06-01
Full Text Available Auditory modeling is a well-established methodology that provides insight into human perception and that facilitates the extraction of signal features that are most relevant to the listener. The aim of this paper is to provide a tutorial on perceptual speech and audio coding using an invertible auditory model. In this approach, the audio signal is converted into an auditory representation using an invertible auditory model. The auditory representation is quantized and coded. Upon decoding, it is then transformed back into the acoustic domain. This transformation converts a complex distortion criterion into a simple one, thus facilitating quantization with low complexity. We briefly review past work on auditory models and describe in more detail the components of our invertible model and its inversion procedure, that is, the method to reconstruct the signal from the output of the auditory model. We summarize attempts to use the auditory representation for low-bit-rate coding. Our approach also allows the exploitation of the inherent redundancy of the human auditory system for the purpose of multiple description (joint source-channel coding.
Inversion Approach For Thermal Data From A Convecting Hydrothermal System
Energy Technology Data Exchange (ETDEWEB)
Kasameyer, P.; Younker, L.; Hanson, J.
1985-01-01
Hydrothermal systems are often studied by collecting thermal gradient data and temperature depth curves. These data contain important information about the flow field, the evolution of the hydrothermal system, and the location and nature of the ultimate heat sources. Thermal data are conventionally interpreted by the ''forward'' method; the thermal field is calculated based on selected initial conditions and boundary conditions such as temperature and permeability distributions. If the calculated thermal field matches the data, the chosen conditions are inferred to be possibly correct. Because many sets of initial conditions may produce similar thermal fields, users of the ''forward'' method may inadvertently miss the correct set of initial conditions. Analytical methods for ''inverting'' data also allow the determination of all the possible solutions consistent with the definition of the problem. In this paper we suggest an approach for inverting thermal data from a hydrothermal system, and compare it to the more conventional approach. We illustrate the difference in the methods by comparing their application to the Salton Sea Geothermal Field by Lau (1980a) and Kasameyer, et al. (1984). In this particular example, the inverse method was used to draw conclusions about the age and total rate of fluid flow into the hydrothermal system.
Inverse Ising problem in continuous time: A latent variable approach
Donner, Christian; Opper, Manfred
2017-12-01
We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.
Forecasting wind-driven wildfires using an inverse modelling approach
Directory of Open Access Journals (Sweden)
O. Rios
2014-06-01
Full Text Available A technology able to rapidly forecast wildfire dynamics would lead to a paradigm shift in the response to emergencies, providing the Fire Service with essential information about the ongoing fire. This paper presents and explores a novel methodology to forecast wildfire dynamics in wind-driven conditions, using real-time data assimilation and inverse modelling. The forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model based on Huygens principle and solves the optimisation problem with a tangent linear approach and forward automatic differentiation. Its potential is investigated using synthetic data and evaluated in different wildfire scenarios. The results show the capacity of the method to quickly predict the location of the fire front with a positive lead time (ahead of the event in the order of 10 min for a spatial scale of 100 m. The greatest strengths of our method are lightness, speed and flexibility. We specifically tailor the forecast to be efficient and computationally cheap so it can be used in mobile systems for field deployment and operativeness. Thus, we put emphasis on producing a positive lead time and the means to maximise it.
Inverse Ising problem in continuous time: A latent variable approach.
Donner, Christian; Opper, Manfred
2017-12-01
We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.
Inverse Problem Approach for the Alignment of Electron Tomographic Series
International Nuclear Information System (INIS)
Tran, V.D.; Moreaud, M.; Thiebaut, E.; Denis, L.; Becker, J.M.
2014-01-01
In the refining industry, morphological measurements of particles have become an essential part in the characterization catalyst supports. Through these parameters, one can infer the specific physico-chemical properties of the studied materials. One of the main acquisition techniques is electron tomography (or nano-tomography). 3D volumes are reconstructed from sets of projections from different angles made by a Transmission Electron Microscope (TEM). This technique provides a real three-dimensional information at the nano-metric scale. A major issue in this method is the misalignment of the projections that contributes to the reconstruction. The current alignment techniques usually employ fiducial markers such as gold particles for a correct alignment of the images. When the use of markers is not possible, the correlation between adjacent projections is used to align them. However, this method sometimes fails. In this paper, we propose a new method based on the inverse problem approach where a certain criterion is minimized using a variant of the Nelder and Mead simplex algorithm. The proposed approach is composed of two steps. The first step consists of an initial alignment process, which relies on the minimization of a cost function based on robust statistics measuring the similarity of a projection to its previous projections in the series. It reduces strong shifts resulting from the acquisition between successive projections. In the second step, the pre-registered projections are used to initialize an iterative alignment-refinement process which alternates between (i) volume reconstructions and (ii) registrations of measured projections onto simulated projections computed from the volume reconstructed in (i). At the end of this process, we have a correct reconstruction of the volume, the projections being correctly aligned. Our method is tested on simulated data and shown to estimate accurately the translation, rotation and scale of arbitrary transforms. We
Risk evaluation of uranium mining: A geochemical inverse modelling approach
Rillard, J.; Zuddas, P.; Scislewski, A.
2011-12-01
It is well known that uranium extraction operations can increase risks linked to radiation exposure. The toxicity of uranium and associated heavy metals is the main environmental concern regarding exploitation and processing of U-ore. In areas where U mining is planned, a careful assessment of toxic and radioactive element concentrations is recommended before the start of mining activities. A background evaluation of harmful elements is important in order to prevent and/or quantify future water contamination resulting from possible migration of toxic metals coming from ore and waste water interaction. Controlled leaching experiments were carried out to investigate processes of ore and waste (leached ore) degradation, using samples from the uranium exploitation site located in Caetité-Bahia, Brazil. In experiments in which the reaction of waste with water was tested, we found that the water had low pH and high levels of sulphates and aluminium. On the other hand, in experiments in which ore was tested, the water had a chemical composition comparable to natural water found in the region of Caetité. On the basis of our experiments, we suggest that waste resulting from sulphuric acid treatment can induce acidification and salinization of surface and ground water. For this reason proper storage of waste is imperative. As a tool to evaluate the risks, a geochemical inverse modelling approach was developed to estimate the water-mineral interaction involving the presence of toxic elements. We used a method earlier described by Scislewski and Zuddas 2010 (Geochim. Cosmochim. Acta 74, 6996-7007) in which the reactive surface area of mineral dissolution can be estimated. We found that the reactive surface area of rock parent minerals is not constant during time but varies according to several orders of magnitude in only two months of interaction. We propose that parent mineral heterogeneity and particularly, neogenic phase formation may explain the observed variation of the
Appraisal of geodynamic inversion results: a data mining approach
Baumann, T. S.
2016-11-01
Bayesian sampling based inversions require many thousands or even millions of forward models, depending on how nonlinear or non-unique the inverse problem is, and how many unknowns are involved. The result of such a probabilistic inversion is not a single `best-fit' model, but rather a probability distribution that is represented by the entire model ensemble. Often, a geophysical inverse problem is non-unique, and the corresponding posterior distribution is multimodal, meaning that the distribution consists of clusters with similar models that represent the observations equally well. In these cases, we would like to visualize the characteristic model properties within each of these clusters of models. However, even for a moderate number of inversion parameters, a manual appraisal for a large number of models is not feasible. This poses the question whether it is possible to extract end-member models that represent each of the best-fit regions including their uncertainties. Here, I show how a machine learning tool can be used to characterize end-member models, including their uncertainties, from a complete model ensemble that represents a posterior probability distribution. The model ensemble used here results from a nonlinear geodynamic inverse problem, where rheological properties of the lithosphere are constrained from multiple geophysical observations. It is demonstrated that by taking vertical cross-sections through the effective viscosity structure of each of the models, the entire model ensemble can be classified into four end-member model categories that have a similar effective viscosity structure. These classification results are helpful to explore the non-uniqueness of the inverse problem and can be used to compute representative data fits for each of the end-member models. Conversely, these insights also reveal how new observational constraints could reduce the non-uniqueness. The method is not limited to geodynamic applications and a generalized MATLAB
An inverse problem approach to pattern recognition in industry
Directory of Open Access Journals (Sweden)
Ali Sever
2015-01-01
Full Text Available Many works have shown strong connections between learning and regularization techniques for ill-posed inverse problems. A careful analysis shows that a rigorous connection between learning and regularization for inverse problem is not straightforward. In this study, pattern recognition will be viewed as an ill-posed inverse problem and applications of methods from the theory of inverse problems to pattern recognition are studied. A new learning algorithm derived from a well-known regularization model is generated and applied to the task of reconstruction of an inhomogeneous object as pattern recognition. Particularly, it is demonstrated that pattern recognition can be reformulated in terms of inverse problems defined by a Riesz-type kernel. This reformulation can be employed to design a learning algorithm based on a numerical solution of a system of linear equations. Finally, numerical experiments have been carried out with synthetic experimental data considering a reasonable level of noise. Good recoveries have been achieved with this methodology, and the results of these simulations are compatible with the existing methods. The comparison results show that the Regularization-based learning algorithm (RBA obtains a promising performance on the majority of the test problems. In prospects, this method can be used for the creation of automated systems for diagnostics, testing, and control in various fields of scientific and applied research, as well as in industry.
Inverse halftoning algorithm using edge-based lookup table approach.
Chung, Kuo-Liang; Wu, Shih-Tung
2005-10-01
The inverse halftoning algorithm is used to reconstruct a gray image from an input halftone image. Based on the recently published lookup table (LUT) technique, this paper presents a novel edge-based LUT method for inverse halftoning which improves the quality of the reconstructed gray image. The proposed method first uses the LUT-based inverse halftoning method as a preprocessing step to transform the given halftone image to a base gray image, and then the edges are extracted and classified from the base gray image. According to these classified edges, a novel edge-based LUT is built up to reconstruct the gray image. Based on a set of 30 real training images with both low-and high-frequency contents, experimental results demonstrated that the proposed method achieves a better image quality when compared to the currently published two methods, by Chang et al. and Meşe and Vaidyanathan.
A general approach to posterior contraction in nonparametric inverse problems
Knapik, Bartek; Salomond, Jean Bernard
In this paper, we propose a general method to derive an upper bound for the contraction rate of the posterior distribution for nonparametric inverse problems. We present a general theorem that allows us to derive contraction rates for the parameter of interest from contraction rates of the related
INFO-RNA--a fast approach to inverse RNA folding.
Busch, Anke; Backofen, Rolf
2006-08-01
The structure of RNA molecules is often crucial for their function. Therefore, secondary structure prediction has gained much interest. Here, we consider the inverse RNA folding problem, which means designing RNA sequences that fold into a given structure. We introduce a new algorithm for the inverse folding problem (INFO-RNA) that consists of two parts; a dynamic programming method for good initial sequences and a following improved stochastic local search that uses an effective neighbor selection method. During the initialization, we design a sequence that among all sequences adopts the given structure with the lowest possible energy. For the selection of neighbors during the search, we use a kind of look-ahead of one selection step applying an additional energy-based criterion. Afterwards, the pre-ordered neighbors are tested using the actual optimization criterion of minimizing the structure distance between the target structure and the mfe structure of the considered neighbor. We compared our algorithm to RNAinverse and RNA-SSD for artificial and biological test sets. Using INFO-RNA, we performed better than RNAinverse and in most cases, we gained better results than RNA-SSD, the probably best inverse RNA folding tool on the market. www.bioinf.uni-freiburg.de?Subpages/software.html.
Solving Inverse Kinematics – A New Approach to the Extended Jacobian Technique
Directory of Open Access Journals (Sweden)
M. Šoch
2005-01-01
Full Text Available This paper presents a brief summary of current numerical algorithms for solving the Inverse Kinematics problem. Then a new approach based on the Extended Jacobian technique is compared with the current Jacobian Inversion method. The presented method is intended for use in the field of computer graphics for animation of articulated structures.
Elastic reflection based waveform inversion with a nonlinear approach
Guo, Qiang
2017-08-16
Full waveform inversion (FWI) is a highly nonlinear problem due to the complex reflectivity of the Earth, and this nonlinearity only increases under the more expensive elastic assumption. In elastic media, we need a good initial P-wave velocity and even a better initial S-wave velocity models with accurate representation of the low model wavenumbers for FWI to converge. However, inverting for the low wavenumber components of P- and S-wave velocities using reflection waveform inversion (RWI) with an objective to fit the reflection shape, rather than produce reflections, may mitigate the limitations of FWI. Because FWI, performing as a migration operator, is in preference of the high wavenumber updates along reflectors. We propose a nonlinear elastic RWI that inverts for both the low wavenumber and perturbation components of the P- and S-wave velocities. To generate the full elastic reflection wavefields, we derive an equivalent stress source made up by the inverted model perturbations and incident wavefields. We update both the perturbation and propagation parts of the velocity models in a nested fashion. Applications on synthetic isotropic models and field data show that our method can efficiently update the low and high wavenumber parts of the models.
A New Approach for Inversion of Large Random Matrices in Massive MIMO Systems
Anjum, Muhammad Ali Raza; Ahmed, Muhammad Mansoor
2014-01-01
We report a novel approach for inversion of large random matrices in massive Multiple-Input Multiple Output (MIMO) systems. It is based on the concept of inverse vectors in which an inverse vector is defined for each column of the principal matrix. Such an inverse vector has to satisfy two constraints. Firstly, it has to be in the null-space of all the remaining columns. We call it the null-space problem. Secondly, it has to form a projection of value equal to one in the direction of selected column. We term it as the normalization problem. The process essentially decomposes the inversion problem and distributes it over columns. Each column can be thought of as a node in the network or a particle in a swarm seeking its own solution, the inverse vector, which lightens the computational load on it. Another benefit of this approach is its applicability to all three cases pertaining to a linear system: the fully-determined, the over-determined, and the under-determined case. It eliminates the need of forming the generalized inverse for the last two cases by providing a new way to solve the least squares problem and the Moore and Penrose's pseudoinverse problem. The approach makes no assumption regarding the size, structure or sparsity of the matrix. This makes it fully applicable to much in vogue large random matrices arising in massive MIMO systems. Also, the null-space problem opens the door for a plethora of methods available in literature for null-space computation to enter the realm of matrix inversion. There is even a flexibility of finding an exact or approximate inverse depending on the null-space method employed. We employ the Householder's null-space method for exact solution and present a complete exposition of the new approach. A detailed comparison with well-established matrix inversion methods in literature is also given. PMID:24733148
Collage-based approaches for elliptic partial differential equations inverse problems
Yodzis, Michael; Kunze, Herb
2017-01-01
The collage method for inverse problems has become well-established in the literature in recent years. Initial work developed a collage theorem, based upon Banach's fixed point theorem, for treating inverse problems for ordinary differential equations (ODEs). Amongst the subsequent work was a generalized collage theorem, based upon the Lax-Milgram representation theorem, useful for treating inverse problems for elliptic partial differential equations (PDEs). Each of these two different approaches can be applied to elliptic PDEs in one space dimension. In this paper, we explore and compare how the two different approaches perform for the estimation of the diffusivity for a steady-state heat equation.
Numerical approach to the inverse convection-diffusion problem
International Nuclear Information System (INIS)
Yang, X-H; She, D-X; Li, J-Q
2008-01-01
In this paper, the inverse problem on source term identification in convection-diffusion equation is transformed into an optimization problem. To reduce the computational cost and improve computational accuracy for the optimization problem, a new algorithm, chaos real-coded hybrid-accelerating evolution algorithm (CRHAEA), is proposed, in which an initial population is generated by chaos mapping, and new chaos mutation and simplex evolution operation are used. With the shrinking of searching range, CRHAEA gradually directs to an optimal result with the excellent individuals obtained by real-coded evolution algorithm. Its convergence is analyzed. Its efficiency is demonstrated by 15 test functions. Numerical simulation shows that CRHAEA has some advantages over the real-coded accelerated evolution algorithm, the chaos algorithm and the pure random search algorithm
Waveform inversion of mantle Love waves - The Born seismogram approach
Tanimoto, T.
1984-01-01
Normal mode theory, extended to the slightly laterally heterogeneous earth by the first-order Born approximation, is applied to the waveform inversion of mantle Love waves (200-500 sec) for the earth's lateral heterogeneity at l = 2 and a spherically symmetric anelasticity (Q sub mu) structure. The data are from the Global Digital Seismograph Network (GDSN). The l = 2 pattern is very similar to the results of other studies that used either different methods, such as phase velocity measurements and multiplet location measurements, or a different data set, such as mantle Rayleigh waves from different instruments. The results are carefully analyzed for variance reduction and are most naturally explained by heterogeneity in the upper 420 km. Because of the poor resolution of the data set for the deep interior, however, a fairly large heterogeneity in the transition zones, of the order of up to 3.5 percent in shear wave velocity, is allowed. It is noteworthy that Love waves of this period range can not constrain the structure below 420 km and thus any model presented by similar studies below this depth are likely to be constrained by Rayleigh waves (spheroidal modes) only.
Waveform inversion of mantle Love waves: The born seismogram approach
Tanimoto, T.
1983-01-01
Normal mode theory, extended to the slightly laterally heterogeneous Earth by the first-order Born approximation, is applied to the waveform inversion of mantle Love waves (200-500 sec) for the Earth's lateral heterogeneity at l=2 and a spherically symmetric anelasticity (Q sub mu) structure. The data are from the Global Digital Seismograph Network (GDSN). The l=2 pattern is very similar to the results of other studies that used either different methods, such as phase velocity measurements and multiplet location measurements, or a different data set, such as mantle Rayleigh waves from different instruments. The results are carefully analyzed for variance reduction and are most naturally explained by heterogeneity in the upper 420 km. Because of the poor resolution of the data set for the deep interior, however, a fairly large heterogeneity in the transition zones, of the order of up to 3.5% in shear wave velocity, is allowed. It is noteworthy that Love waves of this period range can not constrain the structure below 420 km and thus any model presented by similar studies below this depth are likely to be constrained by Rayleigh waves (spheroidal modes) only.
International Nuclear Information System (INIS)
Aghasi, Alireza; Mendoza-Sanchez, Itza; Miller, Eric L; Ramsburg, C Andrew; Abriola, Linda M
2013-01-01
This paper presents a new joint inversion approach to shape-based inverse problems. Given two sets of data from distinct physical models, the main objective is to obtain a unified characterization of inclusions within the spatial domain of the physical properties to be reconstructed. Although our proposed method generally applies to many types of inverse problems, the main motivation here is to characterize subsurface contaminant source zones by processing down-gradient hydrological data and cross-gradient electrical resistance tomography observations. Inspired by Newton's method for multi-objective optimization, we present an iterative inversion scheme in which descent steps are chosen to simultaneously reduce both data-model misfit terms. Such an approach, however, requires solving a non-smooth convex problem at every iteration, which is computationally expensive for a pixel-based inversion over the whole domain. Instead, we employ a parametric level set technique that substantially reduces the number of underlying parameters, making the inversion computationally tractable. The performance of the technique is examined and discussed through the reconstruction of source zone architectures that are representative of dense non-aqueous phase liquid (DNAPL) contaminant release in a statistically homogenous sandy aquifer. In these examples, the geometric configuration of the DNAPL mass is considered along with additional information about its spatial variability within the contaminated zone, such as the identification of low and high saturation regions. Comparison of the reconstructions with the true DNAPL architectures highlights the superior performance of the model-based technique and joint inversion scheme. (paper)
A unified approach to the helioseismic forward and inverse problems of differential rotation
Ritzwoller, Michael H.; Lavely, Eugene M.
1991-01-01
A general, degenerate perturbation theoretic treatment of the helioseismic forward and inverse problem for solar differential rotation is presented. For the forward problem, differential rotation is represented as the axisymmetric component of a general toroidal flow field using velocity spherical harmonics. This approach allows each degree of differential rotation to be estimated independently from all other degrees. In the inverse problem, the splitting caused by differential rotation is expressed as an expansion in a set of orthonormal polynomials that are intimately related to the solution of the forward problem. The combined use of vector spherical harmonics as basis functions for differential ratio and the Clebsch-Gordon coefficients to represent splitting provides a unified approach to the forward and inverse problems of differential rotation which greatly simplify inversion.
Collage-type approach to inverse problems for elliptic PDEs on perforated domains
Directory of Open Access Journals (Sweden)
Herb E. Kunze
2015-02-01
Full Text Available We present a collage-based method for solving inverse problems for elliptic partial differential equations on a perforated domain. The main results of this paper establish a link between the solution of an inverse problem on a perforated domain and the solution of the same model on a domain with no holes. The numerical examples at the end of the paper show the goodness of this approach.
A novel and generalized approach in the inversion of geoelectrical ...
Indian Academy of Sciences (India)
So a powerful tool is necessary to estimate the parameters. Several researches ... tool can be used. This research paper projects a novel and generalized approach for any case study- related problem and overwhelms the confined field area application. ..... controls the network to travel in the path of con- verging the results.
New Approaches to Coding Information using Inverse Scattering Transform
Frumin, L. L.; Gelash, A. A.; Turitsyn, S. K.
2017-06-01
Remarkable mathematical properties of the integrable nonlinear Schrödinger equation (NLSE) can offer advanced solutions for the mitigation of nonlinear signal distortions in optical fiber links. Fundamental optical soliton, continuous, and discrete eigenvalues of the nonlinear spectrum have already been considered for the transmission of information in fiber-optic channels. Here, we propose to apply signal modulation to the kernel of the Gelfand-Levitan-Marchenko equations that offers the advantage of a relatively simple decoder design. First, we describe an approach based on exploiting the general N -soliton solution of the NLSE for simultaneous coding of N symbols involving 4 ×N coding parameters. As a specific elegant subclass of the general schemes, we introduce a soliton orthogonal frequency division multiplexing (SOFDM) method. This method is based on the choice of identical imaginary parts of the N -soliton solution eigenvalues, corresponding to equidistant soliton frequencies, making it similar to the conventional OFDM scheme, thus, allowing for the use of the efficient fast Fourier transform algorithm to recover the data. Then, we demonstrate how to use this new approach to control signal parameters in the case of the continuous spectrum.
Micromechanical modeling and inverse identification of damage using cohesive approaches
International Nuclear Information System (INIS)
Blal, Nawfal
2013-01-01
In this study a micromechanical model is proposed for a collection of cohesive zone models embedded between two each elements of a standard cohesive-volumetric finite element method. An equivalent 'matrix-inclusions' composite is proposed as a representation of the cohesive-volumetric discretization. The overall behaviour is obtained using homogenization approaches (Hashin Shtrikman scheme and the P. Ponte Castaneda approach). The derived model deals with elastic, brittle and ductile materials. It is available whatever the triaxiality loading rate and the shape of the cohesive law, and leads to direct relationships between the overall material properties and the local cohesive parameters and the mesh density. First, rigorous bounds on the normal and tangential cohesive stiffnesses are obtained leading to a suitable control of the inherent artificial elastic loss induced by intrinsic cohesive models. Second, theoretical criteria on damageable and ductile cohesive parameters are established (cohesive peak stress, critical separation, cohesive failure energy,... ). These criteria allow a practical calibration of the cohesive zone parameters as function of the overall material properties and the mesh length. The main interest of such calibration is its promising capacity to lead to a mesh-insensitive overall response in surface damage. (author) [fr
Zhang, Huaguang; Feng, Tao; Yang, Guang-Hong; Liang, Hongjing
2015-07-01
In this paper, the inverse optimal approach is employed to design distributed consensus protocols that guarantee consensus and global optimality with respect to some quadratic performance indexes for identical linear systems on a directed graph. The inverse optimal theory is developed by introducing the notion of partial stability. As a result, the necessary and sufficient conditions for inverse optimality are proposed. By means of the developed inverse optimal theory, the necessary and sufficient conditions are established for globally optimal cooperative control problems on directed graphs. Basic optimal cooperative design procedures are given based on asymptotic properties of the resulting optimal distributed consensus protocols, and the multiagent systems can reach desired consensus performance (convergence rate and damping rate) asymptotically. Finally, two examples are given to illustrate the effectiveness of the proposed methods.
A Space Efficient Flexible Pivot Selection Approach to Evaluate Determinant and Inverse of a Matrix
Jafree, Hafsa Athar; Imtiaz, Muhammad; Inayatullah, Syed; Khan, Fozia Hanif; Nizami, Tajuddin
2014-01-01
This paper presents new simple approaches for evaluating determinant and inverse of a matrix. The choice of pivot selection has been kept arbitrary thus they reduce the error while solving an ill conditioned system. Computation of determinant of a matrix has been made more efficient by saving unnecessary data storage and also by reducing the order of the matrix at each iteration, while dictionary notation [1] has been incorporated for computing the matrix inverse thereby saving unnecessary calculations. These algorithms are highly class room oriented, easy to use and implemented by students. By taking the advantage of flexibility in pivot selection, one may easily avoid development of the fractions by most. Unlike the matrix inversion method [2] and [3], the presented algorithms obviate the use of permutations and inverse permutations. PMID:24498300
Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches.
Directory of Open Access Journals (Sweden)
Paolo Belardinelli
Full Text Available Electro- and magnetoencephalography allow for non-invasive investigation of human brain activation and corresponding networks with high temporal resolution. Still, no correct network detection is possible without reliable source localization. In this paper, we examine four different source localization schemes under a common Variational Bayesian framework. A Bayesian approach to the Minimum Norm Model (MNM, an Empirical Bayesian Beamformer (EBB and two iterative Bayesian schemes (Automatic Relevance Determination (ARD and Greedy Search (GS are quantitatively compared. While EBB and MNM each use a single empirical prior, ARD and GS employ a library of anatomical priors that define possible source configurations. The localization performance was investigated as a function of (i the number of sources (one vs. two vs. three, (ii the signal to noise ratio (SNR; 5 levels and (iii the temporal correlation of source time courses (for the cases of two or three sources. We also tested whether the use of additional bilateral priors specifying source covariance for ARD and GS algorithms improved performance. Our results show that MNM proves effective only with single source configurations. EBB shows a spatial accuracy of few millimeters with high SNRs and low correlation between sources. In contrast, ARD and GS are more robust to noise and less affected by temporal correlations between sources. However, the spatial accuracy of ARD and GS is generally limited to the order of one centimeter. We found that the use of correlated covariance priors made no difference to ARD/GS performance.
Inverse approach for determination of the coils location during magnetic stimulation
International Nuclear Information System (INIS)
Marinova, Iliana; Kovachev, Ludmil
2002-01-01
An inverse approach using neural networks is extended and applied for determination of coils location during magnetic stimulation. The major constructions of magnetic stimulation coils have been investigated. The electric and magnetic fields are modelled using finite element method and integral equation method. The effects of changing the construction of coils and the frequency to the effect of magnetic stimulation are analysed. The results show that the coils for magnetic stimulation characterize with different focality and magnetic field concentration. The proposed inverse approach using neural networks is very useful for determination the spatial position of the stimulation coils especially when the location of the coil system is required to be changed dynamically. (Author)
Nonlinear inverse scattering methods for thermal- wave slice tomography: a wavelet domain approach
Energy Technology Data Exchange (ETDEWEB)
Miller, E.L. [Department of Electrical and Computer Engineering, Northeastern University, 235 Forsyth Building, Boston, Massachusetts02115 (United States); Nicolaides, L.; Mandelis, A. [Photothermal and Optoelectronic Diagnostics Laboratory, Department of Mechanical Engineering, University of Toronto, 5 Kings College Road, Toronto M5S3G8, Ontario (Canada)
1998-06-01
A wavelet domain, nonlinear inverse scattering approach is presented for imaging subsurface defects in a material sample, given observations of scattered thermal waves. Unlike methods using the Born linearization, our inversion scheme is based on the full wave-field model describing the propagation of thermal waves. Multiresolution techniques are employed to regularize and to lower the computational burden of this ill-posed imaging problem. We use newly developed wavelet-based regularization methods to resolve better the edge structures of defects relative to reconstructions obtained with smoothness-type regularizers. A nonlinear approximation to the exact forward-scattering model is introduced to simplify the inversion with little loss in accuracy. We demonstrate this approach on cross-section imaging problems by using synthetically generated scattering data from transmission and backprojection geometries. {copyright} 1998 Optical Society of America
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.
Irving, J.; Koepke, C.; Elsheikh, A. H.
2017-12-01
Bayesian solutions to geophysical and hydrological inverse problems are dependent upon a forward process model linking subsurface parameters to measured data, which is typically assumed to be known perfectly in the inversion procedure. However, in order to make the stochastic solution of the inverse problem computationally tractable using, for example, Markov-chain-Monte-Carlo (MCMC) methods, fast approximations of the forward model are commonly employed. This introduces model error into the problem, which has the potential to significantly bias posterior statistics and hamper data integration efforts if not properly accounted for. Here, we present a new methodology for addressing the issue of model error in Bayesian solutions to hydrogeophysical inverse problems that is geared towards the common case where these errors cannot be effectively characterized globally through some parametric statistical distribution or locally based on interpolation between a small number of computed realizations. Rather than focusing on the construction of a global or local error model, we instead work towards identification of the model-error component of the residual through a projection-based approach. In this regard, pairs of approximate and detailed model runs are stored in a dictionary that grows at a specified rate during the MCMC inversion procedure. At each iteration, a local model-error basis is constructed for the current test set of model parameters using the K-nearest neighbour entries in the dictionary, which is then used to separate the model error from the other error sources before computing the likelihood of the proposed set of model parameters. We demonstrate the performance of our technique on the inversion of synthetic crosshole ground-penetrating radar traveltime data for three different subsurface parameterizations of varying complexity. The synthetic data are generated using the eikonal equation, whereas a straight-ray forward model is assumed in the inversion
An inverse-scattering approach to the physics of transition metals ...
African Journals Online (AJOL)
A method is developed for the deduction of a transition metal ion potential from a knowledge of the phase-shift. The method used is based the distorted plane – wave scattering approximation for the deduction of non singular potentials from scattering phase shifts in an inverse scattering approach. The resulting electron ...
DEFF Research Database (Denmark)
Tordrup, Karl Woldum; Poulsen, Uffe Vestergaard; Nielsen, Carsten
2017-01-01
We use a modular approach to develop a TRNSYS model for a district heating facility by applying inverse modelling to one year of operational data for individual components. We assemble the components into a single TRNSYS model for the full system using the accumulation tanks as a central hub...
DEFF Research Database (Denmark)
Tordrup, Karl Woldum; Poulsen, Uffe Vestergaard; Nielsen, Carsten
2017-01-01
We use a modular approach to develop a TRNSYS model for a district heating facility by applying inverse modelling to one year of operational data for individual components. We assemble the components into a single TRNSYS model for the full system using the accumulation tanks as a central hub conn...
Honarvar, Mohammad; Sahebjavaher, Ramin S; Rohling, Robert; Salcudean, Septimiu E
2017-08-01
In quantitative elastography, maps of the mechanical properties of soft tissue, or elastograms, are calculated from the measured displacement data by solving an inverse problem. The model assumptions have a significant effect on elastograms. Motivated by the high sensitivity of imaging results to the model assumptions for in vivo magnetic resonance elastography of the prostate, we compared elastograms obtained with four different methods. Two finite-element method (FEM)-based methods developed by our group were compared with two other commonly used methods, local frequency estimator (LFE) and curl-based direct inversion (c-DI). All the methods assume a linear isotropic elastic model, but the methods vary in their assumptions, such as local homogeneity or incompressibility, and in the specific approach used. We report results using simulations, phantom, and ex vivo and in vivo data. The simulation and phantom studies show, for regions with an inclusion, that the contrast to noise ratio (CNR) for the FEM methods is about three to five times higher than the CNR for the LFE and c-DI and the rms error is about half. The LFE method produces very smooth results (i.e., low CNR) and is fast. c-DI is faster than the FEM methods but it is only accurate in areas where elasticity variations are small. The artifacts resulting from the homogeneity assumption in c-DI is detrimental in regions with large variations. The ex vivo and in vivo results also show similar trends as the simulation and phantom studies. The c-FEM method is more sensitive to noise compared with the mixed-FEM due to higher orders derivatives. This is especially evident at lower frequencies, where the wave curvature is smaller and it is more prone to such error, causing a discrepancy in the absolute values between the mixed-FEM and c-FEM in our in vivo results. In general, the proposed FEMs use fewer simplifying assumptions and outperform the other methods but they are computationally more expensive.
A new approach to solve inverse kinematics of a planar flexible continuum robot
Amouri, Ammar; Mahfoudi, Chawki; Zaatri, Abdelouahab; Merabti, Halim
2014-10-01
Research on the modeling of continuum robots, focused on ways to constrain the geometrical models, while maintaining maximum specificities and mechanical properties of the robot. In this paper we propose a new numerical solution for solving the inverse geometric model of a planar flexible continuum robot, we assuming that each section is curved in an arc of a circle, while having the central axis of the inextensible structure. The inverse geometric model for one section is calculated geometrically, whereas the extreme points, of each section, used in calculating the inverse geometric model for multi-section is calculated numerically using a particle swarm optimization (PSO) method. Simulation examples of this method are carried to validate the proposed approach.
Stritzel, J; Melchert, O; Wollweber, M; Roth, B
2017-09-01
The direct problem of optoacoustic signal generation in biological media consists of solving an inhomogeneous three-dimensional (3D) wave equation for an initial acoustic stress profile. In contrast, the more defiant inverse problem requires the reconstruction of the initial stress profile from a proper set of observed signals. In this article, we consider an effectively 1D approach, based on the assumption of a Gaussian transverse irradiation source profile and plane acoustic waves, in which the effects of acoustic diffraction are described in terms of a linear integral equation. The respective inverse problem along the beam axis can be cast into a Volterra integral equation of the second kind for which we explore here efficient numerical schemes in order to reconstruct initial stress profiles from observed signals, constituting a methodical progress of computational aspects of optoacoustics. In this regard, we explore the validity as well as the limits of the inversion scheme via numerical experiments, with parameters geared toward actual optoacoustic problem instances. The considered inversion input consists of synthetic data, obtained in terms of the effectively 1D approach, and, more generally, a solution of the 3D optoacoustic wave equation. Finally, we also analyze the effect of noise and different detector-to-sample distances on the optoacoustic signal and the reconstructed pressure profiles.
Stritzel, J.; Melchert, O.; Wollweber, M.; Roth, B.
2017-09-01
The direct problem of optoacoustic signal generation in biological media consists of solving an inhomogeneous three-dimensional (3D) wave equation for an initial acoustic stress profile. In contrast, the more defiant inverse problem requires the reconstruction of the initial stress profile from a proper set of observed signals. In this article, we consider an effectively 1D approach, based on the assumption of a Gaussian transverse irradiation source profile and plane acoustic waves, in which the effects of acoustic diffraction are described in terms of a linear integral equation. The respective inverse problem along the beam axis can be cast into a Volterra integral equation of the second kind for which we explore here efficient numerical schemes in order to reconstruct initial stress profiles from observed signals, constituting a methodical progress of computational aspects of optoacoustics. In this regard, we explore the validity as well as the limits of the inversion scheme via numerical experiments, with parameters geared toward actual optoacoustic problem instances. The considered inversion input consists of synthetic data, obtained in terms of the effectively 1D approach, and, more generally, a solution of the 3D optoacoustic wave equation. Finally, we also analyze the effect of noise and different detector-to-sample distances on the optoacoustic signal and the reconstructed pressure profiles.
An algebraic approach to the inverse eigenvalue problem for a quantum system with a dynamical group
International Nuclear Information System (INIS)
Wang, S.J.
1993-04-01
An algebraic approach to the inverse eigenvalue problem for a quantum system with a dynamical group is formulated for the first time. One dimensional problem is treated explicitly in detail for both the finite dimensional and infinite dimensional Hilbert spaces. For the finite dimensional Hilbert space, the su(2) algebraic representation is used; while for the infinite dimensional Hilbert space, the Heisenberg-Weyl algebraic representation is employed. Fourier expansion technique is generalized to the generator space, which is suitable for analysis of irregular spectra. The polynormial operator basis is also used for complement, which is appropriate for analysis of some simple Hamiltonians. The proposed new approach is applied to solve the classical inverse Sturn-Liouville problem and to study the problems of quantum regular and irregular spectra. (orig.)
Use of the Inverse Approach for the Manufacture and Decoration of Food Cans
International Nuclear Information System (INIS)
Duffett, G.A.; Forgas, A.; Neamtu, L.; Naceur, H.; Batoz, J.L.; Guo, Y.Q.
2005-01-01
Innovation is a key objective in the metal packaging industry in order to produce new concepts, designs, shapes and printing. Simulation technology now allows both the can design as well as the manufacturing process to be carefully analysed before any physical prototypes or dies have been manufactured. These simulations are traditionally carried out using incremental simulation methodologies. However, much information may also be attained by using the inverse approach: the initial blank format for the can body as well as its lid may be optimised much faster, the actual decoration of the can may be evaluated and even calculated when deformation printing techniques are utilised. This paper presents some of the technical details relating to the inverse approach employed in Stampack to carry out simulations important for the manufacture of food cans that are shown via industrial
An inverse approach to perturb historical rainfall data for scenario-neutral climate impact studies
Guo, Danlu; Westra, Seth; Maier, Holger R.
2018-01-01
Scenario-neutral approaches are being used increasingly for climate impact assessments, as they allow water resource system performance to be evaluated independently of climate change projections. An important element of these approaches is the generation of perturbed series of hydrometeorological variables that form the inputs to hydrologic and water resource assessment models, with most scenario-neutral studies to-date considering only shifts in the average and a limited number of other statistics of each climate variable. In this study, a stochastic generation approach is used to perturb not only the average of the relevant hydrometeorological variables, but also attributes such as the intermittency and extremes. An optimization-based inverse approach is developed to obtain hydrometeorological time series with uniform coverage across the possible ranges of rainfall attributes (referred to as the 'exposure space'). The approach is demonstrated on a widely used rainfall generator, WGEN, for a case study at Adelaide, Australia, and is shown to be capable of producing evenly-distributed samples over the exposure space. The inverse approach expands the applicability of the scenario-neutral approach in evaluating a water resource system's sensitivity to a wider range of plausible climate change scenarios.
International Nuclear Information System (INIS)
Manoli, Gabriele; Rossi, Matteo; Pasetto, Damiano; Deiana, Rita; Ferraris, Stefano; Cassiani, Giorgio; Putti, Mario
2015-01-01
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequential inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archie's law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment
Inverse modelling in estimating soil hydraulic functions: a Genetic Algorithm approach
Ines, A. V. M.; Droogers, P.
The practical application of simulation models in the field is sometimes hindered by the difficulty of deriving the soil hydraulic properties of the study area. The procedure so-called inverse modelling has been investigated in many studies to address the problem where most of the studies were limited to hypothetical soil profile and soil core samples in the laboratory. Often, the numerical approach called forward-backward simulation is employed to generate synthetic data then added with random errors to mimic the real-world condition. Inverse modelling is used to backtrack the expected values of the parameters. This study explored the potential of a Genetic Algorithm (GA) to estimate inversely the soil hydraulic functions in the unsaturated zone. Lysimeter data from a wheat experiment in India were used in the analysis. Two cases were considered: (1) a numerical case where the forward-backward approach was employed and (2) the experimental case where the real data from the lysimeter experiment were used. Concurrently, the use of soil water, evapotranspiration (ET) and the combination of both were investigated as criteria in the inverse modelling. Results showed that using soil water as a criterion provides more accurate parameter estimates than using ET. However, from a practical point of view, ET is more attractive as it can be obtained with reasonable accuracy on a regional scale from remote sensing observations. The experimental study proved that the forward-backward approach does not take into account the effects of model errors. The formulation of the problem is found to be critical for a successful parameter estimation. The sensitivity of parameters to the objective function and their zone of influence in the soil column are major determinants in the solution. Generally, their effects sometimes lead to non-uniqueness in the solution but to some extent are partly handled by GA. Overall, it was concluded that the GA approach is promising to the inverse problem
Inverse modelling in estimating soil hydraulic functions: a Genetic Algorithm approach
Directory of Open Access Journals (Sweden)
A. V. M. Ines
2002-01-01
Full Text Available The practical application of simulation models in the field is sometimes hindered by the difficulty of deriving the soil hydraulic properties of the study area. The procedure so-called inverse modelling has been investigated in many studies to address the problem where most of the studies were limited to hypothetical soil profile and soil core samples in the laboratory. Often, the numerical approach called forward-backward simulation is employed to generate synthetic data then added with random errors to mimic the real-world condition. Inverse modelling is used to backtrack the expected values of the parameters. This study explored the potential of a Genetic Algorithm (GA to estimate inversely the soil hydraulic functions in the unsaturated zone. Lysimeter data from a wheat experiment in India were used in the analysis. Two cases were considered: (1 a numerical case where the forward-backward approach was employed and (2 the experimental case where the real data from the lysimeter experiment were used. Concurrently, the use of soil water, evapotranspiration (ET and the combination of both were investigated as criteria in the inverse modelling. Results showed that using soil water as a criterion provides more accurate parameter estimates than using ET. However, from a practical point of view, ET is more attractive as it can be obtained with reasonable accuracy on a regional scale from remote sensing observations. The experimental study proved that the forward-backward approach does not take into account the effects of model errors. The formulation of the problem is found to be critical for a successful parameter estimation. The sensitivity of parameters to the objective function and their zone of influence in the soil column are major determinants in the solution. Generally, their effects sometimes lead to non-uniqueness in the solution but to some extent are partly handled by GA. Overall, it was concluded that the GA approach is promising to the
Variational approach to direct and inverse problems of atmospheric pollution studies
Penenko, Vladimir; Tsvetova, Elena; Penenko, Alexey
2016-04-01
We present the development of a variational approach for solving interrelated problems of atmospheric hydrodynamics and chemistry concerning air pollution transport and transformations. The proposed approach allows us to carry out complex studies of different-scale physical and chemical processes using the methods of direct and inverse modeling [1-3]. We formulate the problems of risk/vulnerability and uncertainty assessment, sensitivity studies, variational data assimilation procedures [4], etc. A computational technology of constructing consistent mathematical models and methods of their numerical implementation is based on the variational principle in the weak constraint formulation specifically designed to account for uncertainties in models and observations. Algorithms for direct and inverse modeling are designed with the use of global and local adjoint problems. Implementing the idea of adjoint integrating factors provides unconditionally monotone and stable discrete-analytic approximations for convection-diffusion-reaction problems [5,6]. The general framework is applied to the direct and inverse problems for the models of transport and transformation of pollutants in Siberian and Arctic regions. The work has been partially supported by the RFBR grant 14-01-00125 and RAS Presidium Program I.33P. References: 1. V. Penenko, A.Baklanov, E. Tsvetova and A. Mahura . Direct and inverse problems in a variational concept of environmental modeling //Pure and Applied Geoph.(2012) v.169: 447-465. 2. V. V. Penenko, E. A. Tsvetova, and A. V. Penenko Development of variational approach for direct and inverse problems of atmospheric hydrodynamics and chemistry, Izvestiya, Atmospheric and Oceanic Physics, 2015, Vol. 51, No. 3, p. 311-319, DOI: 10.1134/S0001433815030093. 3. V.V. Penenko, E.A. Tsvetova, A.V. Penenko. Methods based on the joint use of models and observational data in the framework of variational approach to forecasting weather and atmospheric composition
A stochastic approach for model reduction and memory function design in hydrogeophysical inversion
Hou, Z.; Kellogg, A.; Terry, N.
2009-12-01
Geophysical (e.g., seismic, electromagnetic, radar) techniques and statistical methods are essential for research related to subsurface characterization, including monitoring subsurface flow and transport processes, oil/gas reservoir identification, etc. For deep subsurface characterization such as reservoir petroleum exploration, seismic methods have been widely used. Recently, electromagnetic (EM) methods have drawn great attention in the area of reservoir characterization. However, considering the enormous computational demand corresponding to seismic and EM forward modeling, it is usually a big problem to have too many unknown parameters in the modeling domain. For shallow subsurface applications, the characterization can be very complicated considering the complexity and nonlinearity of flow and transport processes in the unsaturated zone. It is warranted to reduce the dimension of parameter space to a reasonable level. Another common concern is how to make the best use of time-lapse data with spatial-temporal correlations. This is even more critical when we try to monitor subsurface processes using geophysical data collected at different times. The normal practice is to get the inverse images individually. These images are not necessarily continuous or even reasonably related, because of the non-uniqueness of hydrogeophysical inversion. We propose to use a stochastic framework by integrating minimum-relative-entropy concept, quasi Monto Carlo sampling techniques, and statistical tests. The approach allows efficient and sufficient exploration of all possibilities of model parameters and evaluation of their significances to geophysical responses. The analyses enable us to reduce the parameter space significantly. The approach can be combined with Bayesian updating, allowing us to treat the updated ‘posterior’ pdf as a memory function, which stores all the information up to date about the distributions of soil/field attributes/properties, then consider the
Caprio, M.; Lancieri, M.; Cua, G. B.; Zollo, A.; Wiemer, S.
2011-01-01
We present an evolutionary approach for magnitude estimation for earthquake early warning based on real-time inversion of displacement spectra. The Spectrum Inversion (SI) method estimates magnitude and its uncertainty by inferring the shape of the entire displacement spectral curve based on the part of the spectra constrained by available data. The method consists of two components: 1) estimating seismic moment by finding the low frequency plateau Ω0, the corner frequency fc and attenuation factor (Q) that best fit the observed displacement spectra assuming a Brune ω2 model, and 2) estimating magnitude and its uncertainty based on the estimate of seismic moment. A novel characteristic of this method is that is does not rely on empirically derived relationships, but rather involves direct estimation of quantities related to the moment magnitude. SI magnitude and uncertainty estimates are updated each second following the initial P detection. We tested the SI approach on broadband and strong motion waveforms data from 158 Southern California events, and 25 Japanese events for a combined magnitude range of 3 ≤ M ≤ 7. Based on the performance evaluated on this dataset, the SI approach can potentially provide stable estimates of magnitude within 10 seconds from the initial earthquake detection.
An Inverse Source Problem for a One-dimensional Wave Equation: An Observer-Based Approach
Asiri, Sharefa M.
2013-05-25
Observers are well known in the theory of dynamical systems. They are used to estimate the states of a system from some measurements. However, recently observers have also been developed to estimate some unknowns for systems governed by Partial differential equations. Our aim is to design an observer to solve inverse source problem for a one dimensional wave equation. Firstly, the problem is discretized in both space and time and then an adaptive observer based on partial field measurements (i.e measurements taken form the solution of the wave equation) is applied to estimate both the states and the source. We see the effectiveness of this observer in both noise-free and noisy cases. In each case, numerical simulations are provided to illustrate the effectiveness of this approach. Finally, we compare the performance of the observer approach with Tikhonov regularization approach.
Padois, Thomas; Berry, Alain
2015-12-01
Microphone arrays and beamforming have become a standard method to localize aeroacoustic sources. Deconvolution techniques have been developed to improve spatial resolution of beamforming maps. The deconvolution approach for the mapping of acoustic sources (DAMAS) is a standard deconvolution technique, which has been enhanced via a sparsity approach called sparsity constrained deconvolution approach for the mapping of acoustic sources (SC-DAMAS). In this paper, the DAMAS inverse problem is solved using the orthogonal matching pursuit (OMP) and compared with beamforming and SC-DAMAS. The resulting noise source maps show that OMP-DAMAS is an efficient source localization technique in the case of uncorrelated or correlated acoustic sources. Moreover, the computation time is clearly reduced as compared to SC-DAMAS.
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242
Directory of Open Access Journals (Sweden)
Ahmed R. J. Almusawi
2016-01-01
Full Text Available This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot’s joint angles.
Almusawi, Ahmed R J; Dülger, L Canan; Kapucu, Sadettin
2016-01-01
This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles.
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)
Dülger, L. Canan; Kapucu, Sadettin
2016-01-01
This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles. PMID:27610129
Improvements on a non-invasive, parameter-free approach to inverse form finding
Landkammer, P.; Caspari, M.; Steinmann, P.
2017-08-01
Our objective is to determine the optimal undeformed workpiece geometry (material configuration) within forming processes when the prescribed deformed geometry (spatial configuration) is given. For solving the resulting shape optimization problem—also denoted as inverse form finding—we use a novel parameter-free approach, which relocates in each iteration the material nodal positions as design variables. The spatial nodal positions computed by an elasto-plastic finite element (FE) forming simulation are compared with their prescribed values. The objective function expresses a least-squares summation of the differences between the computed and the prescribed nodal positions. Here, a recently developed shape optimization approach (Landkammer and Steinmann in Comput Mech 57(2):169-191, 2016) is investigated with a view to enhance its stability and efficiency. Motivated by nonlinear optimization theory a detailed justification of the algorithm is given. Furthermore, a classification according to shape changing design, fixed and controlled nodal coordinates is introduced. Two examples with large elasto-plastic strains demonstrate that using a superconvergent patch recovery technique instead of a least-squares (L2 )-smoothing improves the efficiency. Updating the interior discretization nodes by solving a fictitious elastic problem also reduces the number of required FE iterations and avoids severe mesh distortions. Furthermore, the impact of the inclusion of the second deformation gradient in the Hessian of the Quasi-Newton approach is analyzed. Inverse form finding is a crucial issue in metal forming applications. As a special feature, the approach is designed to be coupled in a non-invasive fashion to arbitrary FE software.
A Direct Solution Approach to the Inverse Shallow-Water Problem
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Alelign Gessese
2012-01-01
Full Text Available The study of open channel flow modelling often requires an accurate representation of the channel bed topography to accurately predict the flow hydrodynamics. Experimental techniques are the most widely used approaches to measure the bed topographic elevation of open channels. However, they are usually cost and time consuming. Free surface measurement is, on the other hand, relatively easy to obtain using airborne photographic techniques. We present in this work an easy to implement and fast to solve numerical technique to identify the underlying bedrock topography from given free surface elevation data in shallow open channel flows. The main underlying idea is to derive explicit partial differential equations which govern this inverse reconstruction problem. The technique described here is a “one-shot technique” in the sense that the solution of the partial differential equation provides the solution to the inverse problem directly. The idea is tested on a set of artificial data obtained by first solving the forward problem governed by the shallow-water equations. Numerical results show that the channel bed topographic elevation can be reconstructed with a level of accuracy less than 3%. The method is also shown to be robust when noise is present in the input data.
Implementation of probabilistic approach in solving inverse problems as a grid-backed web service.
Kholodkov, K. I.; Aleshin, I. M.; Koryagin, V. N.; Shogin, A. N.; Sukhoroslov, O. V.
2012-04-01
In this work probabilistic approach to inverse problem was adopted. It leads to definition and sampling of a posteriori probability density function (APDF), which combines a priori system information with information, derived from observation data. Use of APDF implies significant computational resourses consumption, even for moderate model parameter count. However the computation of APDF value at different points is carried out completely independently, therefore this problem is considered ideal for loosely coupled distributed computing system. Globus Toolkit middleware was used, including the GridFTP for data transfer and GRAM for execution control, as well as TORQUE resource manager for each computing node. To reduce the hardware cost all grid services, except for GridFTP, run as virtual guests on execution nodes. Due to very insignificant resources utilization the guests make no footprint on node's computation power. To hide complex middleware interface from scientific users, user friendly web interface was created, which provides restricted but sufficient tool set. Determination of seismic anisotropy by wave form inversion was implemented as model problem. The interface allows user to edit model parameters, estimate execution time for specified parameter set, run calculation and perform result visualization. Details of start-up, management and results acquisition are hidden from user. This work was supported by Russian Foundation of Basic Research, grants 10-07-00491-a, 11-05-00988-a and 11-07-12045-ofi-m-2011
Energy Technology Data Exchange (ETDEWEB)
Tupek, Michael R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-06-30
In recent years there has been a proliferation of modeling techniques for forward predictions of crack propagation in brittle materials, including: phase-field/gradient damage models, peridynamics, cohesive-zone models, and G/XFEM enrichment techniques. However, progress on the corresponding inverse problems has been relatively lacking. Taking advantage of key features of existing modeling approaches, we propose a parabolic regularization of Barenblatt cohesive models which borrows extensively from previous phase-field and gradient damage formulations. An efficient explicit time integration strategy for this type of nonlocal fracture model is then proposed and justified. In addition, we present a C++ computational framework for computing in- put parameter sensitivities efficiently for explicit dynamic problems using the adjoint method. This capability allows for solving inverse problems involving crack propagation to answer interesting engineering questions such as: 1) what is the optimal design topology and material placement for a heterogeneous structure to maximize fracture resistance, 2) what loads must have been applied to a structure for it to have failed in an observed way, 3) what are the existing cracks in a structure given various experimental observations, etc. In this work, we focus on the first of these engineering questions and demonstrate a capability to automatically and efficiently compute optimal designs intended to minimize crack propagation in structures.
Inverse problems in nuclear engineering. Old but new approach for bottleneck removal
International Nuclear Information System (INIS)
Itagaki, Masafumi; Kurihara, Kenichi
2002-01-01
Recently, a word of 'inverse problem' can often be heard. This is a problem to search a cause brought on the phenomenon on a base of the observed data. As such idea could be found at dawn age of nuclear energy, recently by feature upgrading of computers and development of numerical analyses, the inverse problem is focused as a new interdisciplinary area. Here were introduced some cases of inverse problem at the field of nuclear energy containing recent hot topics, as well as trying to easily describe inverse problem and inverse analysis. However, there is no generalized inverse analytical method usable for every inverse problems, so it is actual state to find out optimum method corresponding to individual inverse problems. (G.K.)
Karaoulis, M.; Revil, A.; Werkema, D.D.; Minsley, B.J.; Woodruff, W.F.; Kemna, A.
2011-01-01
Induced polarization (more precisely the magnitude and phase of impedance of the subsurface) is measured using a network of electrodes located at the ground surface or in boreholes. This method yields important information related to the distribution of permeability and contaminants in the shallow subsurface. We propose a new time-lapse 3-D modelling and inversion algorithm to image the evolution of complex conductivity over time. We discretize the subsurface using hexahedron cells. Each cell is assigned a complex resistivity or conductivity value. Using the finite-element approach, we model the in-phase and out-of-phase (quadrature) electrical potentials on the 3-D grid, which are then transformed into apparent complex resistivity. Inhomogeneous Dirichlet boundary conditions are used at the boundary of the domain. The calculation of the Jacobian matrix is based on the principles of reciprocity. The goal of time-lapse inversion is to determine the change in the complex resistivity of each cell of the spatial grid as a function of time. Each model along the time axis is called a 'reference space model'. This approach can be simplified into an inverse problem looking for the optimum of several reference space models using the approximation that the material properties vary linearly in time between two subsequent reference models. Regularizations in both space domain and time domain reduce inversion artefacts and improve the stability of the inversion problem. In addition, the use of the time-lapse equations allows the simultaneous inversion of data obtained at different times in just one inversion step (4-D inversion). The advantages of this new inversion algorithm are demonstrated on synthetic time-lapse data resulting from the simulation of a salt tracer test in a heterogeneous random material described by an anisotropic semi-variogram. ?? 2011 The Authors Geophysical Journal International ?? 2011 RAS.
Control of plasma profile in microwave discharges via inverse-problem approach
Directory of Open Access Journals (Sweden)
Yasuyoshi Yasaka
2013-12-01
Full Text Available In the manufacturing process of semiconductors, plasma processing is an essential technology, and the plasma used in the process is required to be of high density, low temperature, large diameter, and high uniformity. This research focuses on the microwave-excited plasma that meets these needs, and the research target is a spatial profile control. Two novel techniques are introduced to control the uniformity; one is a segmented slot antenna that can change radial distribution of the radiated field during operation, and the other is a hyper simulator that can predict microwave power distribution necessary for a desired radial density profile. The control system including these techniques provides a method of controlling radial profiles of the microwave plasma via inverse-problem approach, and is investigated numerically and experimentally.
Inverse Kinematics of a Humanoid Robot with Non-Spherical Hip: A Hybrid Algorithm Approach
Directory of Open Access Journals (Sweden)
Rafael Cisneros Limón
2013-04-01
Full Text Available This paper describes an approach to solve the inverse kinematics problem of humanoid robots whose construction shows a small but non negligible offset at the hip which prevents any purely analytical solution to be developed. Knowing that a purely numerical solution is not feasible due to variable efficiency problems, the proposed one first neglects the offset presence in order to obtain an approximate “solution” by means of an analytical algorithm based on screw theory, and then uses it as the initial condition of a numerical refining procedure based on the Levenberg-Marquardt algorithm. In this way, few iterations are needed for any specified attitude, making it possible to implement the algorithm for real-time applications. As a way to show the algorithm's implementation, one case of study is considered throughout the paper, represented by the SILO2 humanoid robot.
A compressive sensing approach to the calculation of the inverse data space
Khan, Babar Hasan
2012-01-01
Seismic processing in the Inverse Data Space (IDS) has its advantages like the task of removing the multiples simply becomes muting the zero offset and zero time data in the inverse domain. Calculation of the Inverse Data Space by sparse inversion techniques has seen mitigation of some artifacts. We reformulate the problem by taking advantage of some of the developments from the field of Compressive Sensing. The seismic data is compressed at the sensor level by recording projections of the traces. We then process this compressed data directly to estimate the inverse data space. Due to the smaller number of data set we also gain in terms of computational complexity.
A new approach to the inverse problem for current mapping in thin-film superconductors
Zuber, J. W.; Wells, F. S.; Fedoseev, S. A.; Johansen, T. H.; Rosenfeld, A. B.; Pan, A. V.
2018-03-01
A novel mathematical approach has been developed to complete the inversion of the Biot-Savart law in one- and two-dimensional cases from measurements of the perpendicular component of the magnetic field using the well-developed Magneto-Optical Imaging technique. Our approach, especially in the 2D case, is provided in great detail to allow a straightforward implementation as opposed to those found in the literature. Our new approach also refines our previous results for the 1D case [Johansen et al., Phys. Rev. B 54, 16264 (1996)], and streamlines the method developed by Jooss et al. [Physica C 299, 215 (1998)] deemed as the most accurate if compared to that of Roth et al. [J. Appl. Phys. 65, 361 (1989)]. We also verify and streamline the iterative technique, which was developed following Laviano et al. [Supercond. Sci. Technol. 16, 71 (2002)] to account for in-plane magnetic fields caused by the bending of the applied magnetic field due to the demagnetising effect. After testing on magneto-optical images of a high quality YBa2Cu3O7 superconducting thin film, we show that the procedure employed is effective.
International Nuclear Information System (INIS)
Hoffmann, L.; Shukla, A.; Peter, M.; Barbiellini, B.; Manuel, A.A.
1993-01-01
We present linear and non-linear filters to solve the ill-posed inverse problem and we use them to extract relevant information from positron lifetime and 2D-angular correlation of the annihilation radiation of positrons in solids. A general optimal linear filter is first derived. Then a second linear approach, based on Bayes' theorem, is described. We show that these two linear approaches are indeed equivalent. Two non-linear methods are then discussed. The first is a Bayesian approach which makes use of the maximum entropy principle. The second is an iterative method derived from the general optimal linear filter. Applications of these filtering techniques to positron lifetime decay curves illustrate how lifetimes shorter than the instrumental resolution can be extracted. Finally, we apply the iterative non-linear filter to the problem of the ridge-like Fermi surface on the high temperature superconducting compound YBa 2 Cu 3 O 7-δ . For the first time a direct measurement of the ridge width through a Brillouin zone is obtained. It is compared with results of band structure calculations. (orig.)
Development of a residency program in radiation oncology physics: an inverse planning approach.
Khan, Rao F H; Dunscombe, Peter B
2016-03-08
Over the last two decades, there has been a concerted effort in North America to organize medical physicists' clinical training programs along more structured and formal lines. This effort has been prompted by the Commission on Accreditation of Medical Physics Education Programs (CAMPEP) which has now accredited about 90 residency programs. Initially the accreditation focused on standardized and higher quality clinical physics training; the development of rounded professionals who can function at a high level in a multidisciplinary environment was recognized as a priority of a radiation oncology physics residency only lately. In this report, we identify and discuss the implementation of, and the essential components of, a radiation oncology physics residency designed to produce knowledgeable and effective clinical physicists for today's safety-conscious and collaborative work environment. Our approach is that of inverse planning, by now familiar to all radiation oncology physicists, in which objectives and constraints are identified prior to the design of the program. Our inverse planning objectives not only include those associated with traditional residencies (i.e., clinical physics knowledge and critical clinical skills), but also encompass those other attributes essential for success in a modern radiation therapy clinic. These attributes include formal training in management skills and leadership, teaching and communication skills, and knowledge of error management techniques and patient safety. The constraints in our optimization exercise are associated with the limited duration of a residency and the training resources available. Without compromising the knowledge and skills needed for clinical tasks, we have successfully applied the model to the University of Calgary's two-year residency program. The program requires 3840 hours of overall commitment from the trainee, of which 7%-10% is spent in obtaining formal training in nontechnical "soft skills".
A Dynamic BI–Orthogonal Field Equation Approach to Efficient Bayesian Inversion
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Tagade Piyush M.
2017-06-01
Full Text Available This paper proposes a novel computationally efficient stochastic spectral projection based approach to Bayesian inversion of a computer simulator with high dimensional parametric and model structure uncertainty. The proposed method is based on the decomposition of the solution into its mean and a random field using a generic Karhunen-Loève expansion. The random field is represented as a convolution of separable Hilbert spaces in stochastic and spatial dimensions that are spectrally represented using respective orthogonal bases. In particular, the present paper investigates generalized polynomial chaos bases for the stochastic dimension and eigenfunction bases for the spatial dimension. Dynamic orthogonality is used to derive closed-form equations for the time evolution of mean, spatial and the stochastic fields. The resultant system of equations consists of a partial differential equation (PDE that defines the dynamic evolution of the mean, a set of PDEs to define the time evolution of eigenfunction bases, while a set of ordinary differential equations (ODEs define dynamics of the stochastic field. This system of dynamic evolution equations efficiently propagates the prior parametric uncertainty to the system response. The resulting bi-orthogonal expansion of the system response is used to reformulate the Bayesian inference for efficient exploration of the posterior distribution. The efficacy of the proposed method is investigated for calibration of a 2D transient diffusion simulator with an uncertain source location and diffusivity. The computational efficiency of the method is demonstrated against a Monte Carlo method and a generalized polynomial chaos approach.
Mertin, C.; Huse, K.; Hirt, G.
2016-08-01
Under process conditions such as bending of flat wire made from high strength spring steel, the occurring strains are many times higher than the maximum strains determined from uniaxial tensile tests. To determine the elasto-plastic material behaviour of high strength spring steel (X10CrNi18-8), an inverse modelling approach using a simple testing method is presented. A 3-point bending test with the resulting force-displacement measurements is used for the inverse analysis. The inverse approach is used for determining the Young's modulus and hardening parameters of the Ludwik-Hollomon's law for bending of high strength spring steel. FE simulations with the optimised material data meet the experimentally measured punch forces during bending. The optimised material data considerably enhances the springback prediction.
Recurrent Neural Network Approach Based on the Integral Representation of the Drazin Inverse.
Stanimirović, Predrag S; Živković, Ivan S; Wei, Yimin
2015-10-01
In this letter, we present the dynamical equation and corresponding artificial recurrent neural network for computing the Drazin inverse for arbitrary square real matrix, without any restriction on its eigenvalues. Conditions that ensure the stability of the defined recurrent neural network as well as its convergence toward the Drazin inverse are considered. Several illustrative examples present the results of computer simulations.
A new optimization approach for source-encoding full-waveform inversion
Moghaddam, P.P.; Keers, H.; Herrmann, F.J.; Mulder, W.A.
2013-01-01
Waveform inversion is the method of choice for determining a highly heterogeneous subsurface structure. However, conventional waveform inversion requires that the wavefield for each source is computed separately. This makes it very expensive for realistic 3D seismic surveys. Source-encoding waveform
Theory of waves in periodical structures in inverse problem and SUSY QM approach (in pictures)
International Nuclear Information System (INIS)
Zakhariev, B.N.; Chabanov, I.M.
2004-01-01
Full text: There is a significant progress in revealing the resonance mechanism of spectral gap formation on the finite energy intervals (exact coincidence of wave and fixed potential oscillation frequency in continuum energy points!). We have discovered the simple rules how the same potential can differently influence (perturb) the waves with different boundary conditions at the same energy. At the same total energy different waves can feel different 'effective potential energies' and have the same 'effective kinetic energy'. Some details of IP and SUSY QM formalism can be found in our new book S ubmissive quantum mechanics: new status of the theory in inverse and supersymmetry approach , see it in internet http://thsunl.jinr.ru/~zakharev/ (free access). A short presentation of the lessons on quantum intuition will be given. The new theory reveals the elementary and universal constituents ('bricks' and building blocks) for construction (at least theoretically) of quantum systems with the given properties 'as with a children toy constructor set'. We have even understood how to solve Schroedinger spectral problems 'mentally'
A robust probabilistic approach for variational inversion in shallow water acoustic tomography
International Nuclear Information System (INIS)
Berrada, M; Badran, F; Crépon, M; Thiria, S; Hermand, J-P
2009-01-01
This paper presents a variational methodology for inverting shallow water acoustic tomography (SWAT) measurements. The aim is to determine the vertical profile of the speed of sound c(z), knowing the acoustic pressures generated by a frequency source and collected by a sparse vertical hydrophone array (VRA). A variational approach that minimizes a cost function measuring the distance between observations and their modeled equivalents is used. A regularization term in the form of a quadratic restoring term to a background is also added. To avoid inverting the variance–covariance matrix associated with the above-weighted quadratic background, this work proposes to model the sound speed vector using probabilistic principal component analysis (PPCA). The PPCA introduces an optimum reduced number of non-correlated latent variables η, which determine a new control vector and a new regularization term, expressed as η T η. The PPCA represents a rigorous formalism for the use of a priori information and allows an efficient implementation of the variational inverse method
International Nuclear Information System (INIS)
Siauw, Timmy; Cunha, Adam; Atamtuerk, Alper; Hsu, I-Chow; Pouliot, Jean; Goldberg, Ken
2011-01-01
Purpose: Many planning methods for high dose rate (HDR) brachytherapy require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose plan is computed using these parameters, and if any dosimetric criteria are not met, the process is iterated until a suitable dose plan is found. In this way, the dose distribution is controlled by abstract parameters. The purpose of this study is to develop a new approach for HDR brachytherapy by directly optimizing the dose distribution based on dosimetric criteria. Methods: The authors developed inverse planning by integer program (IPIP), an optimization model for computing HDR brachytherapy dose plans and a fast heuristic for it. They used their heuristic to compute dose plans for 20 anonymized prostate cancer image data sets from patients previously treated at their clinic database. Dosimetry was evaluated and compared to dosimetric criteria. Results: Dose plans computed from IPIP satisfied all given dosimetric criteria for the target and healthy tissue after a single iteration. The average target coverage was 95%. The average computation time for IPIP was 30.1 s on an Intel(R) Core TM 2 Duo CPU 1.67 GHz processor with 3 Gib RAM. Conclusions: IPIP is an HDR brachytherapy planning system that directly incorporates dosimetric criteria. The authors have demonstrated that IPIP has clinically acceptable performance for the prostate cases and dosimetric criteria used in this study, in both dosimetry and runtime. Further study is required to determine if IPIP performs well for a more general group of patients and dosimetric criteria, including other cancer sites such as GYN.
Siauw, Timmy; Cunha, Adam; Atamtürk, Alper; Hsu, I-Chow; Pouliot, Jean; Goldberg, Ken
2011-07-01
Many planning methods for high dose rate (HDR) brachytherapy require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose plan is computed using these parameters, and if any dosimetric criteria are not met, the process is iterated until a suitable dose plan is found. In this way, the dose distribution is controlled by abstract parameters. The purpose of this study is to develop a new approach for HDR brachytherapy by directly optimizing the dose distribution based on dosimetric criteria. The authors developed inverse planning by integer program (IPIP), an optimization model for computing HDR brachytherapy dose plans and a fast heuristic for it. They used their heuristic to compute dose plans for 20 anonymized prostate cancer image data sets from patients previously treated at their clinic database. Dosimetry was evaluated and compared to dosimetric criteria. Dose plans computed from IPIP satisfied all given dosimetric criteria for the target and healthy tissue after a single iteration. The average target coverage was 95%. The average computation time for IPIP was 30.1 s on an Intel(R) Core 2 Duo CPU 1.67 GHz processor with 3 Gib RAM. IPIP is an HDR brachytherapy planning system that directly incorporates dosimetric criteria. The authors have demonstrated that IPIP has clinically acceptable performance for the prostate cases and dosimetric criteria used in this study, in both dosimetry and runtime. Further study is required to determine if IPIP performs well for a more general group of patients and dosimetric criteria, including other cancer sites such as GYN.
Energy Technology Data Exchange (ETDEWEB)
Siauw, Timmy; Cunha, Adam; Atamtuerk, Alper; Hsu, I-Chow; Pouliot, Jean; Goldberg, Ken [Department of Civil and Environmental Engineering, University of California, Berkeley, 760 Davis Hall, Berkeley, California 94720-1710 (United States); Department of Radiation Oncology, University of California, San Francisco, Comprehensive Cancer Center, 1600 Divisadero Street, Suite H1031, San Francisco, California 94143-1708 (United States); Department of Industrial Engineering and Operations, University of California, Berkeley, 4141 Etcheverry Hall, Berkeley, California 94720-1777 (United States); Department of Radiation Oncology, University of California, San Francisco, Comprehensive Cancer Center, 1600 Divisadero Street, Suite H1031, San Francisco, California 94143-1708 (United States); Department of Industrial Engineering and Operations Research and Department of Electrical Engineering and Computer Science, University of California, Berkeley, 4141 Etcheverry Hall, Berkeley, California 94720-1777 (United States)
2011-07-15
Purpose: Many planning methods for high dose rate (HDR) brachytherapy require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose plan is computed using these parameters, and if any dosimetric criteria are not met, the process is iterated until a suitable dose plan is found. In this way, the dose distribution is controlled by abstract parameters. The purpose of this study is to develop a new approach for HDR brachytherapy by directly optimizing the dose distribution based on dosimetric criteria. Methods: The authors developed inverse planning by integer program (IPIP), an optimization model for computing HDR brachytherapy dose plans and a fast heuristic for it. They used their heuristic to compute dose plans for 20 anonymized prostate cancer image data sets from patients previously treated at their clinic database. Dosimetry was evaluated and compared to dosimetric criteria. Results: Dose plans computed from IPIP satisfied all given dosimetric criteria for the target and healthy tissue after a single iteration. The average target coverage was 95%. The average computation time for IPIP was 30.1 s on an Intel(R) Core{sup TM}2 Duo CPU 1.67 GHz processor with 3 Gib RAM. Conclusions: IPIP is an HDR brachytherapy planning system that directly incorporates dosimetric criteria. The authors have demonstrated that IPIP has clinically acceptable performance for the prostate cases and dosimetric criteria used in this study, in both dosimetry and runtime. Further study is required to determine if IPIP performs well for a more general group of patients and dosimetric criteria, including other cancer sites such as GYN.
Schumacher, F.; Friederich, W.; Lamara, S.
2016-02-01
We present a new conceptual approach to scattering-integral-based seismic full waveform inversion (FWI) that allows a flexible, extendable, modular and both computationally and storage-efficient numerical implementation. To achieve maximum modularity and extendability, interactions between the three fundamental steps carried out sequentially in each iteration of the inversion procedure, namely, solving the forward problem, computing waveform sensitivity kernels and deriving a model update, are kept at an absolute minimum and are implemented by dedicated interfaces. To realize storage efficiency and maximum flexibility, the spatial discretization of the inverted earth model is allowed to be completely independent of the spatial discretization employed by the forward solver. For computational efficiency reasons, the inversion is done in the frequency domain. The benefits of our approach are as follows: (1) Each of the three stages of an iteration is realized by a stand-alone software program. In this way, we avoid the monolithic, unflexible and hard-to-modify codes that have often been written for solving inverse problems. (2) The solution of the forward problem, required for kernel computation, can be obtained by any wave propagation modelling code giving users maximum flexibility in choosing the forward modelling method. Both time-domain and frequency-domain approaches can be used. (3) Forward solvers typically demand spatial discretizations that are significantly denser than actually desired for the inverted model. Exploiting this fact by pre-integrating the kernels allows a dramatic reduction of disk space and makes kernel storage feasible. No assumptions are made on the spatial discretization scheme employed by the forward solver. (4) In addition, working in the frequency domain effectively reduces the amount of data, the number of kernels to be computed and the number of equations to be solved. (5) Updating the model by solving a large equation system can be
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
Dimensionality-reduction approach to the thermal radiative transfer equation inverse problem
Masiello, G.; Serio, C.
2004-06-01
An original algorithm is illustrated for the inversion of geophysical parameters from spectral observations in the thermal band. The algorithm exploits the Hotelling transform and projects the linearized version of the radiative transfer equation in a space of reduced dimensionality. The inversion is performed in this latter space, which speeds up the computations and makes the method attractive for real-time retrieval from high spectral resolution infrared observations.
An Inverse Modeling Approach to Investigate Past Lead Atmospheric Deposition in Southern Greenland
Massa, C.; Monna, F.; Bichet, V.; Gauthier, E.; Richard, H.
2013-12-01
The aim of this study is to model atmospheric pollution lead fluxes using two different paleoenvironmental records, covering the last 2000 years, located in southern Greenland. Fifty five sediment samples from the Lake Igaliku sequence (61°00.403'N, 45°26.494'W) were analyzed for their Pb and Al contents, and for lead isotopic compositions. The second archive consists in a previously published dataset (Shotyk et al., 2003), including Zr and Pb concentrations, and lead isotopic compositions, obtained from a minerogenic peat deposit located 16 km northwest of Lake Igaliku (61°08.314'N, 45°33.703'W). As natural background concentrations are high and obliterate most of the airborne anthropogenic lead, it is not possible to isolate this anthropogenic contribution through time with classical methods (i.e. Pb is normalized to a lithogenic and conservative element). Moreover, the background 206Pb/207Pb ratio is rather noisy because of the wide geological heterogeneity of sediment sources, which further complicated unambiguous detection of the lead pollution. To overcome these difficulties, an inverse modeling approach based on assumptions about past lead inputs was applied. This method consists of simulating a range of anthropogenic fluxes to determine the best match between measured and simulated data, both for Pb concentrations and isotopic compositions. The model is validated by the coherence of the results obtained from the two independent datasets that must reflect a similar pollution history. Although notable 206Pb/207Pb ratio shifts suggest that the first signs of anthropogenic inputs may have occurred in the 15th century, the signal-to-noise ratio was too low to significantly influence the sediment composition. Nevertheless we were able to estimate that anthropogenic lead fluxes did not exceed 2700 μg m-2 yr-1, a maximum value recorded during the 1960s. The comparison with other records from the North Atlantic Islands reveals a spatial gradient most likely due
Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun
2017-01-07
Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6 ± 15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.
International Nuclear Information System (INIS)
Russenschuck, S.; Tortschanoff, T.; Ijspeert, A.; Perin, R.; Siegel, N.
1994-01-01
After measuring the magnetic field of a model or prototype superconducting magnet for the Large Hadron Collider (LHC) an inverse field problem is formulated in order to explain the origin of the content of unwanted multipole terms. The inverse problem solving is done by means of a least-squares minimization using the Levenberg-Marquard algorithm. Although the uniqueness of the results remains uncertain, useful insights into the causes of measured field imperfections can be deduced. A model dipole magnet, a main quadrupole prototype and a combined dipole-sextupole corrector magnet are given as examples
Chang, T. W.; Ide, S.
2017-12-01
Slip inversion using empirical Green's function (EGF) method has its advantages of removing the complex path and site effect that is difficult to model theoretically. The method, which uses one "EGF event" that's smaller in magnitude for over 1.5 as the Green's function, is essentially an inversion highlighting the arrival time of the waveforms. In this study, inversions of very large earthquakes were conducted with far-field data, using non-negative-least-squares method, and taking EGF selection from Baltay et al. (2014). Objective way of screening station components is applied by evaluating the radiation pattern for the earthquakes of each stations. To better estimate model error due to the usage of empirical Green's function, which is also specific to station selection, bootstrapping is made on the station selection process, randomly selecting waveforms from P or SH components in various stations. This will give the average of inversion trials using different data components with different Green's Functions, resulting in a smoothed model with stable features of the individual results, without explicitly applying smoothing constraints. So far, the above method had been applied to the MW 8.8 2010 Maule, Chile, and the MW 9.0 2011 Tohoku-Oki, Japan earthquakes, both giving comparable slip pattern to previous studies, although slip is concentrated in very small regions with unreasonably large amount of slip. These results should be considered as an extreme case of concentrated slip, and further physical inference is necessary to understand the real rupture process.
A general approach to regularizing inverse problems with regional data using Slepian wavelets
Michel, Volker; Simons, Frederik J.
2017-12-01
Slepian functions are orthogonal function systems that live on subdomains (for example, geographical regions on the Earth’s surface, or bandlimited portions of the entire spectrum). They have been firmly established as a useful tool for the synthesis and analysis of localized (concentrated or confined) signals, and for the modeling and inversion of noise-contaminated data that are only regionally available or only of regional interest. In this paper, we consider a general abstract setup for inverse problems represented by a linear and compact operator between Hilbert spaces with a known singular-value decomposition (svd). In practice, such an svd is often only given for the case of a global expansion of the data (e.g. on the whole sphere) but not for regional data distributions. We show that, in either case, Slepian functions (associated to an arbitrarily prescribed region and the given compact operator) can be determined and applied to construct a regularization for the ill-posed regional inverse problem. Moreover, we describe an algorithm for constructing the Slepian basis via an algebraic eigenvalue problem. The obtained Slepian functions can be used to derive an svd for the combination of the regionalizing projection and the compact operator. As a result, standard regularization techniques relying on a known svd become applicable also to those inverse problems where the data are regionally given only. In particular, wavelet-based multiscale techniques can be used. An example for the latter case is elaborated theoretically and tested on two synthetic numerical examples.
A structured approach to forensic study of explosions: The TNO Inverse Explosion Analysis tool
Voort, M.M. van der; Wees, R.M.M. van; Brouwer, S.D.; Jagt-Deutekom, M.J. van der; Verreault, J.
2015-01-01
Forensic analysis of explosions consists of determining the point of origin, the explosive substance involved, and the charge mass. Within the EU FP7 project Hyperion, TNO developed the Inverse Explosion Analysis (TNO-IEA) tool to estimate the charge mass and point of origin based on observed damage
Rietbroek, R.; Uebbing, B.; Lück, C.; Kusche, J.
2017-12-01
Ocean mass content (OMC) change due to the melting of the ice-sheets in Greenland and Antarctica, melting of glaciers and changes in terrestrial hydrology is a major contributor to present-day sea level rise. Since 2002, the GRACE satellite mission serves as a valuable tool for directly measuring the variations in OMC. As GRACE has almost reached the end of its lifetime, efforts are being made to utilize the Swarm mission for the recovery of low degree time-variable gravity fields to bridge a possible gap until the GRACE-FO mission and to fill up periods where GRACE data was not existent. To this end we compute Swarm monthly normal equations and spherical harmonics that are found competitive to other solutions. In addition to directly measuring the OMC, combination of GRACE gravity data with altimetry data in a global inversion approach allows to separate the total sea level change into individual mass-driven and steric contributions. However, published estimates of OMC from the direct and inverse methods differ not only depending on the time window, but also are influenced by numerous post-processing choices. Here, we will look into sources of such differences between direct and inverse approaches and evaluate the capabilities of Swarm to derive OMC. Deriving time series of OMC requires several processing steps; choosing a GRACE (and altimetry) product, data coverage, masks and filters to be applied in either spatial or spectral domain, corrections related to spatial leakage, GIA and geocenter motion. In this study, we compare and quantify the effects of the different processing choices of the direct and inverse methods. Our preliminary results point to the GIA correction as the major source of difference between the two approaches.
Nonlinear Damping Identification in Nonlinear Dynamic System Based on Stochastic Inverse Approach
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S. L. Han
2012-01-01
Full Text Available The nonlinear model is crucial to prepare, supervise, and analyze mechanical system. In this paper, a new nonparametric and output-only identification procedure for nonlinear damping is studied. By introducing the concept of the stochastic state space, we formulate a stochastic inverse problem for a nonlinear damping. The solution of the stochastic inverse problem is designed as probabilistic expression via the hierarchical Bayesian formulation by considering various uncertainties such as the information insufficiency in parameter of interests or errors in measurement. The probability space is estimated using Markov chain Monte Carlo (MCMC. The applicability of the proposed method is demonstrated through numerical experiment and particular application to a realistic problem related to ship roll motion.
An intramolecular inverse electron demand Diels–Alder approach to annulated α-carbolines
Directory of Open Access Journals (Sweden)
Zhiyuan Ma
2012-06-01
Full Text Available Intramolecular inverse electron demand cycloadditions of isatin-derived 1,2,4-triazines with acetylenic dienophiles tethered by amidations or transesterifications proceed in excellent yields to produce lactam- or lactone-fused α-carbolines. Beginning with various isatins and alkynyl dienophiles, a pilot-scale library of eighty-eight α-carbolines was prepared by using this robust methodology for biological evaluation.
A Novel Approach to Fast SOLIS Stokes Inversion for Photospheric Vector Magnetography.
Harker, Brian; Mighell, K.
2009-05-01
The SOLIS (Synoptic Optical Long-term Investigations of the Sun) Vector Spectromagnetograph (VSM) is a full-disc spectropolarimeter, located at Kitt Peak National Observatory, which records Zeeman-induced polarization in the magnetically-sensitive FeI spectral lines at 630.15 nm and 630.25 nm. A SOLIS VSM full-disc dataset consists of 2048 scanlines, with each scanline containing the Stokes I, Q, U, and V spectral line profiles in 128 unique wavelength bins for all 2048 pixels in the scanline. These Stokes polarization profiles are inverted to obtain the magnetic and thermodynamic structure of the observations, based on a model Milne-Eddington plane-parallel atmosphere. Until recently, this has been a compute-intensive, relatively slow process. This poster presents a novel method of producing such model-based characterizations of the photospheric magnetic field by utilizing an inversion engine based on a genetic algorithm. The algorithm executes in a heterogeneous compute environment composed of both a CPU and a graphics processing unit (GPU). Using the cutting-edge NVIDIA CUDA platform, we are able to offload the compute-intensive portions of the inversion code to the GPU, which results in significant speedup. This speedup provides the impetus which has driven the development of this strategy. Currently, SOLIS vector magnetic field products are generated with a modified version of the HAO ASP inversion code developed by Skumanich & Lites (1987), and these data products are made available to the scientific community 24 hours after the actual observation(s). With this work, we aim to drastically reduce this waiting period to allow near real-time characterizations of the photospheric vector magnetic field. Here, we here detail the inversion method we have pioneered, present preliminary results on the derived full-disc magnetic field as well as timing/speedup considerations, and finally offer some outlooks on the future direction of this work.
A neural network approach for the solution of electric and magnetic inverse problems
International Nuclear Information System (INIS)
Coccorese, E.; Morabito, F.C.; Martone, R.
1994-01-01
Multilayer neural networks, trained via the back-propagation rule, are proved to provide an efficient means for solving electric and/or magnetic inverse problems. The underlying model of the system is learned by the network by means of a dataset defining the relationship between input and output parameters. The merits of the method are illustrated at the light of three example cases. The first two samples deal with inverse electrostatic problems which are relevant for nondestructive testing applications. In a first problem, a boss on an earthed plane is identified on the basis of the map of potential produced by a point charge. In the second problem, the geometric parameters of an ellipsoid carrying an electric charge are identified. In both cases, database of simulated measurements has been generated thanks to the available analytical solutions. As a sample magnetic inverse problem, the identification of a circular plasma in a tokamak device from external flux measurements is carried out. The results achieved show that the method here proposed is promising for technically meaningful applications
An optimal transport approach for seismic tomography: application to 3D full waveform inversion
Métivier, L.; Brossier, R.; Mérigot, Q.; Oudet, E.; Virieux, J.
2016-11-01
The use of optimal transport distance has recently yielded significant progress in image processing for pattern recognition, shape identification, and histograms matching. In this study, the use of this distance is investigated for a seismic tomography problem exploiting the complete waveform; the full waveform inversion. In its conventional formulation, this high resolution seismic imaging method is based on the minimization of the L 2 distance between predicted and observed data. Application of this method is generally hampered by the local minima of the associated L 2 misfit function, which correspond to velocity models matching the data up to one or several phase shifts. Conversely, the optimal transport distance appears as a more suitable tool to compare the misfit between oscillatory signals, for its ability to detect shifted patterns. However, its application to the full waveform inversion is not straightforward, as the mass conservation between the compared data cannot be guaranteed, a crucial assumption for optimal transport. In this study, the use of a distance based on the Kantorovich-Rubinstein norm is introduced to overcome this difficulty. Its mathematical link with the optimal transport distance is made clear. An efficient numerical strategy for its computation, based on a proximal splitting technique, is introduced. We demonstrate that each iteration of the corresponding algorithm requires solving the Poisson equation, for which fast solvers can be used, relying either on the fast Fourier transform or on multigrid techniques. The development of this numerical method make possible applications to industrial scale data, involving tenths of millions of discrete unknowns. The results we obtain on such large scale synthetic data illustrate the potentialities of the optimal transport for seismic imaging. Starting from crude initial velocity models, optimal transport based inversion yields significantly better velocity reconstructions than those based on
Moisan, John R.; Moisan, Tiffany A. H.; Linkswiler, Matthew A.
2011-01-01
Phytoplankton absorption spectra and High-Performance Liquid Chromatography (HPLC) pigment observations from the Eastern U.S. and global observations from NASA's SeaBASS archive are used in a linear inverse calculation to extract pigment-specific absorption spectra. Using these pigment-specific absorption spectra to reconstruct the phytoplankton absorption spectra results in high correlations at all visible wavelengths (r(sup 2) from 0.83 to 0.98), and linear regressions (slopes ranging from 0.8 to 1.1). Higher correlations (r(sup 2) from 0.75 to 1.00) are obtained in the visible portion of the spectra when the total phytoplankton absorption spectra are unpackaged by multiplying the entire spectra by a factor that sets the total absorption at 675 nm to that expected from absorption spectra reconstruction using measured pigment concentrations and laboratory-derived pigment-specific absorption spectra. The derived pigment-specific absorption spectra were further used with the total phytoplankton absorption spectra in a second linear inverse calculation to estimate the various phytoplankton HPLC pigments. A comparison between the estimated and measured pigment concentrations for the 18 pigment fields showed good correlations (r(sup 2) greater than 0.5) for 7 pigments and very good correlations (r(sup 2) greater than 0.7) for chlorophyll a and fucoxanthin. Higher correlations result when the analysis is carried out at more local geographic scales. The ability to estimate phytoplankton pigments using pigment-specific absorption spectra is critical for using hyperspectral inverse models to retrieve phytoplankton pigment concentrations and other Inherent Optical Properties (IOPs) from passive remote sensing observations.
A New Concept for Atmospheric Reentry Optimal Guidance: An Inverse Problem Inspired Approach
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Davood Abbasi
2013-01-01
Full Text Available This paper presents a new concept for atmospheric reentry online optimal guidance and control using a method called MARE G&C that exploits the different time scale featured by reentry dynamics. The new technique reaches a quasi-analytical solution and simplified computations, even considering both lift-to-drag ratio and aerodynamic roll as control variables; in addition, the paper offers a solution for the challenging path constraints issue, getting inspiration from the inverse problem methodology. The final resulting algorithm seems suitable for onboard predictive guidance, a new need for future space missions.
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Tao Min
2014-01-01
Full Text Available This paper is intended to provide a numerical algorithm involving the combined use of the Levenberg-Marquardt algorithm and the Galerkin finite element method for estimating the diffusion coefficient in an inverse heat conduction problem (IHCP. In the present study, the functional form of the diffusion coefficient is unknown a priori. The unknown diffusion coefficient is approximated by the polynomial form and the present numerical algorithm is employed to find the solution. Numerical experiments are presented to show the efficiency of the proposed method.
ORINC: a one-dimensional implicit approach to the inverse heat conduction problem. [PWR
Energy Technology Data Exchange (ETDEWEB)
Ott, L.J.; Hedrick, R.A.
1977-10-18
The report develops an implicit solution technique to determine both the transient surface temperature and the transient surface heat flux of electrically heated rods given the power input and an ''indicated'' internal temperature during a simulated loss-of-coolant accident. A digital computer program ORINC (ORNL Inverse Code) is developed which solves a one-dimensional, transient, lumped parameter, implicit formulation of the conduction equation at each bundle thermocouple position in the Thermal-Hydraulic Test Facility (THTF).
Ramirez, A. L.; Foxall, W.
2011-12-01
Surface displacements caused by reservoir pressure perturbations resulting from CO2 injection can often be measured by geodetic methods such as InSAR, tilt and GPS. We have developed a Markov Chain Monte Carlo (MCMC) approach to invert surface displacements measured by InSAR to map the pressure distribution associated with CO2 injection at the In Salah Krechba field, Algeria. The MCMC inversion entails sampling the solution space by proposing a series of trial 3D pressure-plume models. In the case of In Salah, the range of allowable models is constrained by prior information provided by well and geophysical data for the reservoir and possible fluid pathways in the overburden, and injection pressures and volumes. Each trial pressure distribution source is run through a (mathematical) forward model to calculate a set of synthetic surface deformation data. The likelihood that a particular proposal represents the true source is determined from the fit of the calculated data to the InSAR measurements, and those having higher likelihoods are passed to the posterior distribution. This procedure is repeated over typically ~104 - 105 trials until the posterior distribution converges to a stable solution. The solution to each stochastic inversion is in the form of Bayesian posterior probability density function (pdf) over the range of the alternative models that are consistent with the measured data and prior information. Therefore, the solution provides not only the highest likelihood model but also a realistic estimate of the solution uncertainty. Our InSalah work considered three flow model alternatives: 1) The first model assumed that the CO2 saturation and fluid pressure changes were confined to the reservoir; 2) the second model allowed the perturbations to occur also in a damage zone inferred in the lower caprock from 3D seismic surveys; and 3) the third model allowed fluid pressure changes anywhere within the reservoir and overburden. Alternative (2) yielded optimal
Directory of Open Access Journals (Sweden)
Jaume eForés-Martos
2015-02-01
Full Text Available Down syndrome (DS, one of the most common birth defects and the most widespread genetic cause of intellectual disabilities, is caused by extra genetic material on chromosome 21 (HSA21. The increased genomic dosage of trisomy 21 is thought to be responsible for the distinct DS phenotypes, including an increased risk of developing some types of childhood leukemia and germ cell tumors. Patients with DS, however, have a strikingly lower incidence of many other solid tumors. We hypothesized that the third copy of genes located in HSA21 may have an important role on the protective effect that DS patients show against most types of solid tumors. Focusing on Copy Number Variation (CNV array data, we have generated frequencies of deleted regions in HSA21 in four different tumor types from which DS patients have been reported to be protected. We describe three different regions of deletion pointing to a set of candidate genes that could explain the inverse comorbidity phenomenon between DS and solid tumors. In particular we found RCAN1 gene in Wilms tumors and the miR-99A, miR-125B2 and miR-LET7C in lung, breast and melanoma tumors as the main candidates for explaining the inverse comorbidity observed between solid tumors and DS.
Mijovic, S
2003-01-01
Computer-supported techniques are introduced in the evaluation of experimental data and obtaining the real profile of spectral lines. The direct and inverse approaches were used. The MINUIT program from the packets of CERN's library was used to solve direct problems. Tikhonov's regularization method was also applied to solve the same problems in an inverse manner. Model functions were introduced to check the applicability limitation of these methods and make a comparison between them as well. The advantages and disadvantages of these approaches were shown. The procedures were applied to the measured profiles of He II's spectral lines in a pulsed low-pressure arc. The chosen lines are He II Paschen-alpha (468.6 nm) in the visible region and Balmer-beta (121.5 nm) in the VUV spectral region. The range of experimental errors was determined where both approaches have given reliable results. It was found that we can obtain the real profile of He II 468.6 nm and He II 121.5 nm spectral lines, using the regularizati...
International Nuclear Information System (INIS)
Feng Weiguo; Wang Hongwei; Wu Xiang
1989-12-01
Based on the real space Correlated-Basis-Functions theory and the collective oscillation behaviour of the electron gas with effective Coulomb interaction, the many body wave function is obtained for the quasi-two-dimensional electron system in the semiconductor inversion layer. The pair-correlation function and the correlation energy of the system have been calculated by the integro-differential method in this paper. The comparison with the other previous theoretical results is also made. The new theoretical approach and its numerical results show that the pair-correlation functions are definitely positive and satisfy the normalization condition. (author). 10 refs, 2 figs
Kaban, M. K.; Stolk, W.
2014-12-01
Mass anomalies in the Earth's mantle associated with thermal and compositional heterogeneities or with deflected boundaries between layers of different density produce stresses, which initiate mantle convection, plumes, subduction and deformations of the lithosphere. In particularly, the upper mantle plays a key role in controlling surface tectonics. Therefore, knowledge of density heterogeneity of the upper mantle is principal for understanding its dynamics and ongoing tectonic processes. This is particularly important for a complicated region such as Eurasia, where nearly all types of tectonic settings are present. There exist three main problems in construction of 3-D density models of the upper mantle. First, it is necessary to remove before hand the effect of the crust, which substantially masks the upper mantle gravity field. Second, the gravity effects of thermal and compositional density variations should be separated. And finally, the inverse gravity problem is usually underdetermined. In the present study we attempt to create a density model of the upper mantle based on improved interpretation methods and updated initial data sets. The impact of the crust to the observed gravity is estimated based on a new crustal model (Stolk et al., 2013). After removing this effect, we estimate the residual mantle anomalies of the gravity field. In the same way we estimate the residual topography, which is the second principal constraint used in the inversion. The impact of the mantle below 350 km is determined and removed based on recent mantle flow models. 3D density model of the lithosphere and upper mantle is constructed in an iterative inversion with tomography data. Contrary to most of previous studies, the thermal and compositional models are self-consistent. Many principal features of the compositional variations are not resolved by seismic tomography. The obtained density and thermal models can be used to model ongoing tectonic processes. Stolk W., Kaban M
International Nuclear Information System (INIS)
Arians, S.
1997-01-01
We consider the Hamiltonian H=(p-A(x)) 2 /(2m)+V(x) of a quantum particle in a magnetic field B=rotA and a potential V in space dimensions ν≥2. If V is of short range, then the high-velocity limit of the scattering operator uniquely determines the magnetic field B and the potential V. If, in addition, long-range potentials V l are present, some knowledge of (the far out tail of) V l is needed to define a modified Dollard wave operator and a scattering operator S D . Again its high- velocity limit uniquely determines B and V=V s +V l . Moreover, we give explicit error bounds which are inverse proportional to the velocity. copyright 1997 American Institute of Physics
An inverse problem approach for structural damage detection - Finite element model refinement
Zimmerman, D. C.; Kaouk, M.
1992-01-01
In this work, a methodology for incorporating measured modal data into an existing refined finite element model is examined with the objective of detecting and locating structural damage. This same algorithm is also useful in terms of finite element model refinement. The algorithm is based on the partial inverse problem, in that only partial spectral information is required. The technique utilizes a symmetric eigenstructure assignment algorithm to perform the partial spectral assignment. Algorithms to enhance mode shape assignability and to preserve sparsity in the updated model are developed. The sparsity preservation is of particular importance when considering damage detection in truss-like structures. Several examples are presented which highlight the key points made within the paper.
EEG phase reset due to auditory attention: an inverse time-scale approach
International Nuclear Information System (INIS)
Low, Yin Fen; Strauss, Daniel J
2009-01-01
We propose a novel tool to evaluate the electroencephalograph (EEG) phase reset due to auditory attention by utilizing an inverse analysis of the instantaneous phase for the first time. EEGs were acquired through auditory attention experiments with a maximum entropy stimulation paradigm. We examined single sweeps of auditory late response (ALR) with the complex continuous wavelet transform. The phase in the frequency band that is associated with auditory attention (6–10 Hz, termed as theta–alpha border) was reset to the mean phase of the averaged EEGs. The inverse transform was applied to reconstruct the phase-modified signal. We found significant enhancement of the N100 wave in the reconstructed signal. Analysis of the phase noise shows the effects of phase jittering on the generation of the N100 wave implying that a preferred phase is necessary to generate the event-related potential (ERP). Power spectrum analysis shows a remarkable increase of evoked power but little change of total power after stabilizing the phase of EEGs. Furthermore, by resetting the phase only at the theta border of no attention data to the mean phase of attention data yields a result that resembles attention data. These results show strong connections between EEGs and ERP, in particular, we suggest that the presentation of an auditory stimulus triggers the phase reset process at the theta–alpha border which leads to the emergence of the N100 wave. It is concluded that our study reinforces other studies on the importance of the EEG in ERP genesis
Decadal-scale joint inversion of NOx and SO2 using a hybrid 4D-Var / mass balance approach
Qu, Z.; Henze, D. K.; Capps, S.; Wang, Y.; Xu, X.; Wang, J.; Keller, M.
2016-12-01
Quantifying the emissions of nitrogen oxides (NOx) and sulfur dioxide (SO2) is important for improving our understanding of acid rain, formation of aerosols, and human health problems. Traditional top-down estimates have provided valuable constraints for NOx and SO2 emission inventories in China, but are either time-consuming (e.g., 4D-Var) or only crudely represent the influence of atmospheric transport and chemistry (e.g., mass balance). We develop an approach combining mass balance and an adjoint-based four-dimensional variational (4D-Var) methods that facilitates decadal-scale emission inversions. This hybrid inversion is first evaluated with a single species inversion using NO2 pseudo observations. In a set of seven-year pseudo observation test, hybrid posterior NOx emissions have smaller normalized mean square error (by 54% to 94%) than that of mass balance when compared to true emissions in most cases, and have slightly better performance in detecting emissions magnitudes and trends. Using this hybrid method, NO2 observations from the Ozone Monitoring Instrument (OMI), and the GEOS-Chem chemical transport model, we have derived monthly top-down NOx emissions for China from 2005 to 2012. Our posterior emissions have the same seasonality as recent bottom-up inventories, and smaller emissions (by 13.4% to 23.5%) as well as emission growth rate (by 0.6% to 4.1%). The hybrid method is further implemented for long-term joint inversion of NOx and SO2 emissions in China using combined observations of OMI NO2 and SO2 column densities. A 4D-Var inversion is first performed to optimize NOx and SO2 emissions in the base year using GEOS-Chem adjoint. Mass balance scaling factor is then applied to these posterior to improve their inter-annual variation. Overall, these studies augment the utility of remote sensing data for evaluating emission control strategies and mitigating the impact of NOx and SO2 on human health and the environment.
Terekhov, Alexander V; Pesin, Yakov B; Niu, Xun; Latash, Mark L; Zatsiorsky, Vladimir M
2010-09-01
We consider the problem of what is being optimized in human actions with respect to various aspects of human movements and different motor tasks. From the mathematical point of view this problem consists of finding an unknown objective function given the values at which it reaches its minimum. This problem is called the inverse optimization problem. Until now the main approach to this problems has been the cut-and-try method, which consists of introducing an objective function and checking how it reflects the experimental data. Using this approach, different objective functions have been proposed for the same motor action. In the current paper we focus on inverse optimization problems with additive objective functions and linear constraints. Such problems are typical in human movement science. The problem of muscle (or finger) force sharing is an example. For such problems we obtain sufficient conditions for uniqueness and propose a method for determining the objective functions. To illustrate our method we analyze the problem of force sharing among the fingers in a grasping task. We estimate the objective function from the experimental data and show that it can predict the force-sharing pattern for a vast range of external forces and torques applied to the grasped object. The resulting objective function is quadratic with essentially non-zero linear terms.
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
Marjavaara, B. D.; Ebermark, S.; Lundström, T. S.
2009-09-01
A multiobjective surrogate-based inverse modeling technique to predict the spatial and temporal pressure distribution numerically during the fabrication of sheet moulding compounds (SMCs) is introduced. Specifically, an isotropic temperature-dependent Newtonian viscosity model of a SMC charge is fitted to experimental measurements via numerical simulations in order to mimic the temporal pressure distribution at two spatial locations simultaneously. The simulations are performed by using the commercial computational fluid dynamics (CFD) code ANSYS CFX-10.0, and the multiobjective surrogate-based fitting procedure proposed is carried out with a hybrid formulation of the NSGA-IIa evolutionary algorithm and the response surface methodology in Matlab. The outcome of the analysis shows the ability of the optimization framework to efficiently reduce the total computational load of the problem. Furthermore, the viscosity model assumed seems to be able to re solve the temporal pressure distribution and the advancing flow front accurately, which can not be said of the spatial pressure distribution. Hence, it is recommended to improve the CFD model proposed in order to better capture the true behaviour of the mould flow.
Minimum Time Approach to Emergency Collision Avoidance by Vehicle Handling Inverse Dynamics
Directory of Open Access Journals (Sweden)
Wang Wei
2015-01-01
Full Text Available Vehicle driving safety is the urgent key problem to be solved of automobile independent development while encountering emergency collision avoidance with high speed. And it is also the premise and one of the necessary conditions of vehicle active safety. A new technique of vehicle handling inverse dynamics which can evaluate the emergency collision avoidance performance is proposed. Based on optimal control theory, the steering angle input and the traction/brake force imposed by driver are the control variables; the minimum time required to complete the fitting biker line change is the control object. By using the improved direct multiple shooting method, the optimal control problem is converted into a nonlinear programming problem that is then solved by means of the sequential quadratic programming. The simulation results show that the proposed method can solve the vehicle minimum time maneuver problem, and can compare the maneuverability of two different vehicles that complete fitting biker line change with the minimum time and the correctness of the model is verified through real vehicle test.
Investigating local controls on soil moisture temporal stability using an inverse modeling approach
Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry
2013-04-01
A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).
An analytical approach to estimate the number of small scatterers in 2D inverse scattering problems
International Nuclear Information System (INIS)
Fazli, Roohallah; Nakhkash, Mansor
2012-01-01
This paper presents an analytical method to estimate the location and number of actual small targets in 2D inverse scattering problems. This method is motivated from the exact maximum likelihood estimation of signal parameters in white Gaussian noise for the linear data model. In the first stage, the method uses the MUSIC algorithm to acquire all possible target locations and in the next stage, it employs an analytical formula that works as a spatial filter to determine which target locations are associated to the actual ones. The ability of the method is examined for both the Born and multiple scattering cases and for the cases of well-resolved and non-resolved targets. Many numerical simulations using both the coincident and non-coincident arrays demonstrate that the proposed method can detect the number of actual targets even in the case of very noisy data and when the targets are closely located. Using the experimental microwave data sets, we further show that this method is successful in specifying the number of small inclusions. (paper)
Xu, Xiaohua; Sandwell, David T.; Bassett, Dan
2018-01-01
We have developed a data-driven spectral expansion inversion method to place bounds on the downdip rupture depth of large megathrust earthquakes having good InSAR and GPS coverage. This inverse theory approach is used to establish the set of models that are consistent with the observations. In addition, the inverse theory method demonstrates that the spatial resolution of the slip models depends on two factors, the spatial coverage and accuracy of the surface deformation measurements, and the slip depth. Application of this method to the 2010 Mw 8.8 Maule Earthquake shows a slip maximum at 19 km depth tapering to zero at ˜40 km depth. In contrast, the continent-continent megathrust earthquakes of the Himalayas, for example 2015 Mw 7.8 Gorkha Earthquake, shows a slip maximum at 9 km depth tapering to zero at ˜18 km depth. The main question is why is the maximum slip depth of the continental megathrust earthquake only 50 per cent of that observed in oceanic megathrust earthquakes. To understand this difference, we have developed a simple 1-D heat conduction model that includes the effects of uplift and surface erosion. The relatively low erosion rates above the ocean megathrust results in a geotherm where the 450-600 °C transition is centred at ˜40 km depth. In contrast, the relatively high average erosion rates in the Himalayas of ˜1 mm yr-1 results in a geotherm where the 450-600 °C transition is centred at ˜20 km. Based on these new observations and models, we suggest that the effect of erosion rate on temperature explains the difference in the maximum depth of the seismogenic zone between Chile and the Himalayas.
Pouliot, Jean; Cunha, Jason Adam; Hsu, I-Chow
2011-01-01
Purpose: Many planning methods for high dose rate (HDR) brachytherapy require an iterative approach. A set of computational parameters are hypothesized that will g ive a dose plan that meets dosimetric criteria. A dose plan is computed using these parameter
Directory of Open Access Journals (Sweden)
K. Verbist
2009-10-01
Full Text Available In arid and semi-arid zones, runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Nevertheless, few efforts were observed to quantify the water harvesting processes of these techniques and to evaluate their efficiency. In this study, a combination of detailed field measurements and modelling with the HYDRUS-2D software package was used to visualize the effect of an infiltration trench on the soil water content of a bare slope in northern Chile. Rainfall simulations were combined with high spatial and temporal resolution water content monitoring in order to construct a useful dataset for inverse modelling purposes. Initial estimates of model parameters were provided by detailed infiltration and soil water retention measurements. Four different measurement techniques were used to determine the saturated hydraulic conductivity (K_{sat} independently. The tension infiltrometer measurements proved a good estimator of the K_{sat} value and a proxy for those measured under simulated rainfall, whereas the pressure and constant head well infiltrometer measurements showed larger variability. Six different parameter optimization functions were tested as a combination of soil-water content, water retention and cumulative infiltration data. Infiltration data alone proved insufficient to obtain high model accuracy, due to large scatter on the data set, and water content data were needed to obtain optimized effective parameter sets with small confidence intervals. Correlation between the observed soil water content and the simulated values was as high as R^{2}=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for the 22 observation points equal to 0.85. The model results indicate that the infiltration trench has a
Methane in the Amazon: A forward and inverse regional modeling approach
Beck, V.; Gerbig, C.; Koch, F. T.; Karstens, U.; Chen, H.; Bela, M. M.; Longo, K.; Freitas, S.; Bergamaschi, P. M.; Kaplan, J. O.; Prigent, C.
2011-12-01
The Amazon region is an important player in the global methane (CH4) cycle, the second most important greenhouse gas after CO2. Different major CH4 sources in the Amazon region such as anaerobic microbial production in wetlands and biomass burning will be affected by changing climate. Therefore, a thorough understanding of the processes is required. Within the BARCA (Balanço Atmosférico Regional de Carbono na Amazônia) project, airborne measurements of greenhouse gases, associated tracers and aerosols were taken during the end of the dry season in November 2008 as well as during the end of the wet season in May 2009. These aircraft measurements and additional ground based measurements provide a test bed for high resolution transport simulation of CH4. Here we present a comparison of WRF-Chem passive tracer simulations of CH4 to airborne CH4 observations obtained from the BARCA campaigns in November 2008 and May 2009 using the newly established WRF Greenhouse Gas Model (WRF-GHG) in combination with two different process-based bottom-up models for the calculation of CH4 emissions from anaerobic microbial production in wetlands (Kaplan and Walter-Heimann) and three different wetland inundation maps (Kaplan, JERS-1SAR, Prigent). The comparison illustrates the importance of a wetland inundation map with inundated area changing in time, and the quality of the representation of atmospheric transport in regional models in tropical regions. In addition, we demonstrate a comparison of WRF-GHG CH4 simulations to TT34 tower observations (35 m above ground; located 60 km north-west of Manaus, Brazil) for August 2009, evaluating the performance of WRF-GHG in representing CH4 observations in the planetary boundary layer in tropical regions. Finally, we present preliminary results of a regional inversion using the TM3-STILT model together with the above mentioned observations for the estimation of the CH4 budget of the Amazon region.
Ben Abdessalem, A.; Jenson, F.; Calmon, P.
2016-02-01
This contribution provides an example of the possible advantages of adopting a Bayesian inversion approach to uncertainty quantification in nondestructive inspection methods. In such problem, the uncertainty associated to the random parameters is not always known and needs to be characterised from scattering signal measurements. The uncertainties may then correctly propagated in order to determine a reliable probability of detection curve. To this end, we establish a general Bayesian framework based on a non-parametric maximum likelihood function formulation and some priors from expert knowledge. However, the presented inverse problem is time-consuming and computationally intensive. To cope with this difficulty, we replace the real model by a surrogate one in order to speed-up the model evaluation and to make the problem to be computationally feasible for implementation. The least squares support vector regression is adopted as metamodelling technique due to its robustness to deal with non-linear problems. We illustrate the usefulness of this methodology through the control of tube with enclosed defect using ultrasonic inspection method.
CSIR Research Space (South Africa)
Evers-King, H
2014-05-01
Full Text Available ocean colour products To put these results in to the context of current ocean colour products, Fig. 5 shows an approx- imation of the maximum band ratio (MBR) approach used in the OC4 algorithm [37] using forward model output (ES) analogous to the data...], suggesting that variability in a∗φ (in our case, coincident with changes in size) may be obscured by agd , particularly at lower biomass, where the majority of the size related signal occurs in the blue and MBR approaches are typically applied (Fig. 1). Sauer...
Measurements of translation, rotation and strain: new approaches to seismic processing and inversion
Bernauer, M.; Fichtner, A.; Igel, H.
2012-01-01
We propose a novel approach to seismic tomography based on the joint processing of translation, strain and rotation measurements. Our concept is based on the apparent S and P velocities, defined as the ratios of displacement velocity and rotation amplitude, and displacement velocity and
Knoch, Tobias A; Baumgärtner, Volkmar; de Zeeuw, Luc V; Grosveld, Frank G; Egger, Kurt
2009-01-01
With ever-new technologies emerging also the amount of information to be stored and processed is growing exponentially and is believed to be always at the limit. In contrast, however, huge resources are available in the IT sector alike e.g. the renewable energy sector, which are often even not at all used. This under-usage bares any rational especially in the IT sector where e.g. virtualisation and grid approaches could be fast implemented due to the great technical and fast turnover opportunities. Here, we describe this obvious paradox for the first time as the Inverse Tragedy of the Commons, in contrast to the Classical Tragedy of the Commons where resources are overexploited. From this perspective the grid IT sector attempting to share resources for better efficiency, reveals two challenges leading to the heart of the paradox: i) From a macro perspective all grid infrastructures involve not only mere technical solutions but also dominantly all of the autopoietic social sub-systems ranging from religion to policy. ii) On the micro level the individual players and their psychology and risk behaviour are of major importance for acting within the macro autopoietic framework. Thus, the challenges of grid implementation are similar to those of e.g. climate protection. This is well described by the classic Human Ecology triangle and our extension to a rectangle: invironment-individual-society-environment. Extension of this classical interdisciplinary field of basic and applied research to an e-Human Grid Ecology rational, allows the Inverse Tragedy of the Commons of the grid sector to be understood and approached better and implies obvious guidelines in the day-to-day management for grid and other (networked) resources, which is of importance for many fields with similar paradoxes as in (e-)society.
Sliding Mode Control for Mass Moment Aerospace Vehicles Using Dynamic Inversion Approach
Directory of Open Access Journals (Sweden)
Xiao-Yu Zhang
2013-01-01
Full Text Available The moving mass actuation technique offers significant advantages over conventional aerodynamic control surfaces and reaction control systems, because the actuators are contained entirely within the airframe geometrical envelope. Modeling, control, and simulation of Mass Moment Aerospace Vehicles (MMAV utilizing moving mass actuators are discussed. Dynamics of the MMAV are separated into two parts on the basis of the two time-scale separation theory: the dynamics of fast state and the dynamics of slow state. And then, in order to restrain the system chattering and keep the track performance of the system by considering aerodynamic parameter perturbation, the flight control system is designed for the two subsystems, respectively, utilizing fuzzy sliding mode control approach. The simulation results describe the effectiveness of the proposed autopilot design approach. Meanwhile, the chattering phenomenon that frequently appears in the conventional variable structure systems is also eliminated without deteriorating the system robustness.
Siauw, Timmy; Cunha, Adam; Atamturk, Alper; Hsu, I-Chow; Pouliot, Jean; Goldberg, Ken
2010-01-01
Purpose: Many planning methods for high dose rate (HDR) brachytherapy treatment planning require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose plan is computed using these parameters, and if any dosimetric criteria are not met, the process is iterated until a suitable dose plan is found. In this way, the dose distribution is controlled by abstract parameters. The purpose of this study is to improve H...
An inversion-relaxation approach for sampling stationary points of spin model Hamiltonians
International Nuclear Information System (INIS)
Hughes, Ciaran; Mehta, Dhagash; Wales, David J.
2014-01-01
Sampling the stationary points of a complicated potential energy landscape is a challenging problem. Here, we introduce a sampling method based on relaxation from stationary points of the highest index of the Hessian matrix. We illustrate how this approach can find all the stationary points for potentials or Hamiltonians bounded from above, which includes a large class of important spin models, and we show that it is far more efficient than previous methods. For potentials unbounded from above, the relaxation part of the method is still efficient in finding minima and transition states, which are usually the primary focus of attention for atomistic systems
Kuvshinov, Alexey; Semenov, Alexey
2012-06-01
We present a novel frequency-domain inverse solution to recover the 3-D electrical conductivity distribution in the mantle. The solution is based on analysis of local C-responses. It exploits an iterative gradient-type method - limited-memory quasi-Newton method - for minimizing the penalty function consisting of data misfit and regularization terms. The integral equation code is used as a forward engine to calculate responses and data misfit gradients during inversion. An adjoint approach is implemented to compute misfit gradients efficiently. Further improvements in computational load come from parallelizing the scheme with respect to frequencies, and from setting the most time-consuming part of the forward calculations - calculation of Green's tensors - apart from the inversion loop. Convergence, performance, and accuracy of our 3-D inverse solution are demonstrated with a synthetic numerical example. A companion paper applies the strategy set forth here to real data.
Approaches in highly parameterized inversion - GENIE, a general model-independent TCP/IP run manager
Muffels, Christopher T.; Schreuder, Willem A.; Doherty, John E.; Karanovic, Marinko; Tonkin, Matthew J.; Hunt, Randall J.; Welter, David E.
2012-01-01
GENIE is a model-independent suite of programs that can be used to generally distribute, manage, and execute multiple model runs via the TCP/IP infrastructure. The suite consists of a file distribution interface, a run manage, a run executer, and a routine that can be compiled as part of a program and used to exchange model runs with the run manager. Because communication is via a standard protocol (TCP/IP), any computer connected to the Internet can serve in any of the capacities offered by this suite. Model independence is consistent with the existing template and instruction file protocols of the widely used PEST parameter estimation program. This report describes (1) the problem addressed; (2) the approach used by GENIE to queue, distribute, and retrieve model runs; and (3) user instructions, classes, and functions developed. It also includes (4) an example to illustrate the linking of GENIE with Parallel PEST using the interface routine.
Neuman, Shlomo P.
1980-04-01
Paper 1 of this sequence presented a new statistically based approach to the problem of estimating spatially varying aquifer transmissivities on the basis of steady water level and flux data. Paper 2 described a case study in which the new method had been applied to actual field data from the Cortaro Basin in Southern Arizona. The purpose of paper 3 is to introduce a new efficient method of solution which works under a much wider range of conditions than the method employed in papers 1 and 2. The new method is based on a variational theory developed by Chavent (1971), which is extended here to the case of generalized nonlinear least squares. The method is implemented numerically be a finite element scheme. The inverse problem is posed in terms of log transmissivities instead of transmissivities and is solved by a Fletcher-Reeves conjugate gradient algorithm in conjunction with Newton's method for determining the step size to be taken at each iteration. The method does not require computing sensitivity coefficients, and one may therefore expect it to result in considerable savings of both computer storage and computer time. Posing the problem in terms of log transmissivities is shown to have important advantages over the traditional approach, not the least of which is guaranteeing that the computed transmissivities will always be positive. The paper includes a theoretical analysis of the effect that various errors corrupting the data and the model may have on the final log transmissivity estimates. This analysis shows that small errors in the model and in the flow rate and sink/source data have only a minor influence on the log transmissivity estimates and therefore can often be disregarded. On the other hand, low-amplitude noise in the water level data may cause these estimates to become unstable and therefore must always be filtered out during the solution of the inverse problem. Two theoretical examples are included to demonstrate the ability of the new method to
Thompson, R. L.; Gerbig, C.; Roedenbeck, C.; Heimann, M.
2009-04-01
The nitrous oxide (N2O) mixing ratio has been increasing in the atmosphere since the industrial revolution, from 270 ppb in 1750 to 320 ppb in 2007 with a steady growth rate of around 0.26% since the early 1980's. The increase in N2O is worrisome for two main reasons. First, it is a greenhouse gas; this means that its atmospheric increase translates to an enhancement in radiative forcing of 0.16 ± 0.02 Wm-2 making it currently the fourth most important long-lived greenhouse gas and is predicted to soon overtake CFC's to become the third most important. Second, it plays an important role in stratospheric ozone chemistry. Human activities are the primary cause of the atmospheric N2O increase. The largest anthropogenic source of N2O is from the use of N-fertilizers in agriculture but fossil fuel combustion and industrial processes, such as adipic and nitric acid production, are also important. We present a Bayesian inversion approach for estimating N2O fluxes over central and western Europe using high frequency in-situ concentration data from the Ochsenkopf tall tower (50 °01â²N, 11 °48â², 1022 masl). For the inversion, we employ a Lagrangian-type transport model, STILT, which provides source-receptor relationships at 10 km using ECMWF meteorological data. The a priori flux estimates used were from IER, for anthropogenic, and GEIA, for natural fluxes. N2O fluxes were retrieved monthly at 2 x 2 degree spatial resolution for 2007. The retrieved N2O fluxes showed significantly more spatial heterogeneity than in the a priori field and considerable seasonal variability. The timing of peak emissions was different for different regions but in general the months with the strongest emissions were May and August. Overall, the retrieved flux (anthropogenic and natural) was lower than in the a priori field.
A novel approach to multi-criteria inverse planning for IMRT
International Nuclear Information System (INIS)
Breedveld, Sebastiaan; Storchi, Pascal R M; Keijzer, Marleen; Heemink, Arnold W; Heijmen, Ben J M
2007-01-01
Treatment plan optimization is a multi-criteria process. Optimizing solely on one objective or on a sum of a priori weighted objectives may result in inferior treatment plans. Manually adjusting weights or constraints in a trial and error procedure is time consuming. In this paper we introduce a novel multi-criteria optimization approach to automatically optimize treatment constraints (dose-volume and maximum-dose). The algorithm tries to meet these constraints as well as possible, but in the case of conflicts it relaxes lower priority constraints so that higher priority constraints can be met. Afterwards, all constraints are tightened, starting with the highest priority constraints. Applied constraint priority lists can be used as class solutions for patients with similar tumour types. The presented algorithm does iteratively apply an underlying algorithm for beam profile optimization, based on a quadratic objective function with voxel-dependent importance factors. These voxel-dependent importance factors are automatically adjusted to reduce dose-volume and maximum-dose constraint violations
Inverse modelling of air quality data through a neural network approach
Russo, A.; Soares, A.; Trigo, R. M.; Pereira, M. J.
2009-04-01
Air quality is usually driven by a complex combination of factors where meteorology, physical obstacles and interaction between pollutants play significant roles. Considering the characteristics of the atmospheric circulation and also the residence times of certain pollutants in the atmosphere, air pollution is, nowadays, considered to be a global problem that affects everyone. As a result, a generalized and growing interest on air quality issues led to research intensification and publication of several articles with quite different levels of scientific depth. The main objective of this work is to produce an air quality model which allows forecasting critical concentration episodes of a certain pollutant by means of neural network modelling. In this paper, we describe the development of a neural network tool to forecast the daily average NO2 concentrations in Lisbon, Portugal, one day ahead. This research is based upon measurements from 22 air quality monitoring stations during the period 2001-2005. The analysis revealed that the most significant variable in predicting NO2 daily concentration is the previous day value of NO2 concentration followed by the 5a.m. NO2 concentration. This approach shows to be very promising for urban air quality characterization, allowing further developments in order to produce an integrated air quality and health surveillance/monitoring system in the area of Lisbon.
Inversion of electrical conductivity data with Tikhonov regularization approach: some considerations
Directory of Open Access Journals (Sweden)
C. Manzi
2003-06-01
Full Text Available Electromagnetic induction measurements, which are generally used to determine lateral variations of apparent electrical conductivity, can provide quantitative estimates of the subsurface conductivity at different depths. Quantitative inference about the Earth's interior from experimental data is, however, an ill-posed problem. Using the generalised McNeill's theory for the EM38 ground conductivity meter, we generated synthetic apparent conductivity curves (input data vector simulating measurements at different heights above the soil surface. The electrical conductivity profile (the Earth model was then estimated solving a least squares problem with Tikhonov regularization optimised with a projected conjugate gradient algorithm. Although the Tikhonov approach improves the conditioning of the resulting linear system, profile reconstruction can be surprisingly far from the desired true one. On the contrary, the projected conjugate gradient provided the best solution without any explicit regularization ( a= 0 of the objective function of the least squares problem. Also, if the initial guess belongs to the image of the system matrix, Im(A, we found that it provides a unique solution in the same subspace Im(A.
Blessent, Daniela; Therrien, René; Lemieux, Jean-Michel
2011-12-01
This paper presents numerical simulations of a series of hydraulic interference tests conducted in crystalline bedrock at Olkiluoto (Finland), a potential site for the disposal of the Finnish high-level nuclear waste. The tests are in a block of crystalline bedrock of about 0.03 km3 that contains low-transmissivity fractures. Fracture density, orientation, and fracture transmissivity are estimated from Posiva Flow Log (PFL) measurements in boreholes drilled in the rock block. On the basis of those data, a geostatistical approach relying on a transitional probability and Markov chain models is used to define a conceptual model based on stochastic fractured rock facies. Four facies are defined, from sparsely fractured bedrock to highly fractured bedrock. Using this conceptual model, three-dimensional groundwater flow is then simulated to reproduce interference pumping tests in either open or packed-off boreholes. Hydraulic conductivities of the fracture facies are estimated through automatic calibration using either hydraulic heads or both hydraulic heads and PFL flow rates as targets for calibration. The latter option produces a narrower confidence interval for the calibrated hydraulic conductivities, therefore reducing the associated uncertainty and demonstrating the usefulness of the measured PFL flow rates. Furthermore, the stochastic facies conceptual model is a suitable alternative to discrete fracture network models to simulate fluid flow in fractured geological media.
Denzler, Basil; Bogdal, Christian; Henne, Stephan; Obrist, Daniel; Steinbacher, Martin; Hungerbühler, Konrad
2017-03-07
The reduction of emissions of mercury is a declared aim of the Minamata Convention, a UN treaty designed to protect human health and the environment from adverse effects of mercury. To assess the effectiveness of the convention in the future, better constraints about the current mercury emissions is a premise. In our study, we applied a top-down approach to quantify mercury emissions on the basis of atmospheric mercury measurements conducted at the remote high altitude monitoring station Jungfraujoch, Switzerland. We established the source-receptor relationships and by the means of atmospheric inversion we were able to quantify spatially resolved European emissions of 89 ± 14 t/a for elemental mercury. Our European emission estimate is 17% higher than the bottom-up emission inventory, which is within stated uncertainties. However, some regions with unexpectedly high emissions were identified. Stationary combustion, in particular in coal-fired power plants, is found to be the main responsible sector for increased emission estimates. Our top-down approach, based on measurements, provides an independent constraint on mercury emissions, helps to improve and refine reported emission inventories, and can serve for continued assessment of future changes in emissions independent from bottom-up inventories.
A probabilistic approach for the estimation of earthquake source parameters from spectral inversion
Supino, M.; Festa, G.; Zollo, A.
2017-12-01
The amplitude spectrum of a seismic signal related to an earthquake source carries information about the size of the rupture, moment, stress and energy release. Furthermore, it can be used to characterize the Green's function of the medium crossed by the seismic waves. We describe the earthquake amplitude spectrum assuming a generalized Brune's (1970) source model, and direct P- and S-waves propagating in a layered velocity model, characterized by a frequency-independent Q attenuation factor. The observed displacement spectrum depends indeed on three source parameters, the seismic moment (through the low-frequency spectral level), the corner frequency (that is a proxy of the fault length) and the high-frequency decay parameter. These parameters are strongly correlated each other and with the quality factor Q; a rigorous estimation of the associated uncertainties and parameter resolution is thus needed to obtain reliable estimations.In this work, the uncertainties are characterized adopting a probabilistic approach for the parameter estimation. Assuming an L2-norm based misfit function, we perform a global exploration of the parameter space to find the absolute minimum of the cost function and then we explore the cost-function associated joint a-posteriori probability density function around such a minimum, to extract the correlation matrix of the parameters. The global exploration relies on building a Markov chain in the parameter space and on combining a deterministic minimization with a random exploration of the space (basin-hopping technique). The joint pdf is built from the misfit function using the maximum likelihood principle and assuming a Gaussian-like distribution of the parameters. It is then computed on a grid centered at the global minimum of the cost-function. The numerical integration of the pdf finally provides mean, variance and correlation matrix associated with the set of best-fit parameters describing the model. Synthetic tests are performed to
Boukabara, S. A.; Garrett, K.; iturbide-Sanchez, F.; Moy, L.; Grassotti, C.; Chen, W.; Clough, T.
2012-12-01
A 1D variational (1DVAR) retrieval algorithm, known as the Microwave Integrated Retrieval System (MiRS), has been developed at the NOAA Center for Satellite Applications and Research (STAR) for the simultaneous retrieval of multiple surface and atmospheric parameters, including hydrometeors, from any microwave sounder/imager. At the core of the MiRS is the use of the Community Radiative Transfer Model (CRTM), which provides the forward model and jacobians for the minimization process. The retrieved state vector is composed of temperature, water vapor and hydrometeor (liquid cloud, ice cloud and rain) profiles, as well as surface emissivity and skin temperature. The inclusion of the surface emissivity allows for retrievals globally over all surface types, including ocean, land, snow, ice and mixed scenes such as coastal areas. In this presentation, we will focus on the instantaneous rainfall rate from MiRS and identify the challenges as well as characterize potential sources of error in retrieving rainfall from microwave observations using this 1DVAR approach. MiRS retrieval of the rainfall rate takes advantage of the relationship between the rainfall rate and the retrieved hydrometeor amounts. Because the relationship is not in radiometric space, the rainfall rate estimation is sensor independent. The same methodology is applied to retrieve the hydrometeors themselves, whether from an imager, a sounder, or combination imager/sounder. Fundamentally, the microwave observations must be sensitive to the hydrometeors, and the algorithm must distinguish between the surface and atmospheric signals. For example, we show that in moderately intense rainfall cases, low frequency microwave channels are sensitive to the surface and a 2% error in emissivity could translate to 20-100% error in rainfall rate estimates. Therefore, proper characterization of the surface in rainy conditions, where changes in soil moisture may change the emissivity over land up to 10% or more, is
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.
Chromatid Painting for Chromosomal Inversion Detection Project
National Aeronautics and Space Administration — We propose a novel approach to the detection of chromosomal inversions. Transmissible chromosome aberrations (translocations and inversions) have profound genetic...
Shonkwiler, K. B.; Ham, J. M.; Nash, C.
2014-12-01
from the inverse model (FIDES) using all three datasets will be compared to emissions from the bLS model (WindTrax) using only high speed data (laser; CRDS). Results may lend further validity to the conditional sampler approach for more easily and accurately monitoring NH3 fluxes from CAFOs and other strong areal sources.
Karanovic, Marinko; Muffels, Christopher T.; Tonkin, Matthew J.; Hunt, Randall J.
2012-01-01
Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files ("file management") and remote launching and termination of "slave" computers across a distributed network of computers ("run management"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the
Calculation of the inverse data space via sparse inversion
Saragiotis, Christos
2011-01-01
The inverse data space provides a natural separation of primaries and surface-related multiples, as the surface multiples map onto the area around the origin while the primaries map elsewhere. However, the calculation of the inverse data is far from trivial as theory requires infinite time and offset recording. Furthermore regularization issues arise during inversion. We perform the inversion by minimizing the least-squares norm of the misfit function by constraining the $ell_1$ norm of the solution, being the inverse data space. In this way a sparse inversion approach is obtained. We show results on field data with an application to surface multiple removal.
International Nuclear Information System (INIS)
Namatame, Hirofumi; Taniguchi, Masaki
1994-01-01
Photoelectron spectroscopy is regarded as the most powerful means since it can measure almost perfectly the occupied electron state. On the other hand, inverse photoelectron spectroscopy is the technique for measuring unoccupied electron state by using the inverse process of photoelectron spectroscopy, and in principle, the similar experiment to photoelectron spectroscopy becomes feasible. The development of the experimental technology for inverse photoelectron spectroscopy has been carried out energetically by many research groups so far. At present, the heightening of resolution of inverse photoelectron spectroscopy, the development of inverse photoelectron spectroscope in which light energy is variable and so on are carried out. But the inverse photoelectron spectroscope for vacuum ultraviolet region is not on the market. In this report, the principle of inverse photoelectron spectroscopy and the present state of the spectroscope are described, and the direction of the development hereafter is groped. As the experimental equipment, electron guns, light detectors and so on are explained. As the examples of the experiment, the inverse photoelectron spectroscopy of semimagnetic semiconductors and resonance inverse photoelectron spectroscopy are reported. (K.I.)
Sánchez-Sesma, Francisco J.
2017-07-01
Microtremor H/ V spectral ratio (MHVSR) has gained popularity to assess the dominant frequency of soil sites. It requires measurement of ground motion due to seismic ambient noise at a site and a relatively simple processing. Theory asserts that the ensemble average of the autocorrelation of motion components belonging to a diffuse field at a given receiver gives the directional energy densities (DEDs) which are proportional to the imaginary parts of the Green's function components when both source and receiver are the same point and the directions of force and response coincide. Therefore, the MHVSR can be modeled as the square root of 2 × Im G 11/Im G 33, where Im G 11 and Im G 33 are the imaginary parts of Green's functions at the load point for the horizontal (sub-index 1) and vertical (sub-index 3) components, respectively. This connection has physical implications that emerge from the duality DED force and allows understanding the behavior of the MHVSR. For a given model, the imaginary parts of the Green's functions are integrals along a radial wavenumber. To deal with these integrals, we have used either the popular discrete wavenumber method or the Cauchy's residue theorem at the poles that account for surface waves normal modes giving the contributions due to Rayleigh and Love waves. For the retrieval of the velocity structure, one can minimize the weighted differences between observations and calculated values using the strategy of an inversion scheme. In this research, we used simulated annealing but other optimization techniques can be used as well. This last approach allows computing separately the contributions of different wave types. An example is presented for the mouth of Andarax River at Almería, Spain. [Figure not available: see fulltext.
Coddington, O.; Pilewskie, P.; Schmidt, S.
2013-12-01
retrieval distributions. In this work, we apply this general inverse theory approach to extend our analysis of the spectrally-dependent impacts of overlying aerosols on cloud properties over a broad range in cloud optical thickness and droplet effective radius. We investigate the relative impacts of this error source and compare and contrast results to biases and uncertainties in cloud properties induced by varying surface conditions (ocean, land, snow). We perform the analysis for two different measurement accuracies (3% and 0.3%) that are typical of current passive imagers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) [Platnick et al., 2003], and that are expected for future passive imagers, such as the HyperSpectral Imager for Climate Science (HySICS) [Kopp et al., 2010]. Coddington, O., P. Pilewskie, et al., 2010, J. Geophys. Res., 115, doi: 10.1029/2009JD012829. Haywood, J. M., S. R. Osborne, and S. J. Abel, 2004, Q. J. R. Meteorol. Soc., 130, 779-800. Kopp, G., et al., 2010, Hyperspectral Imagery Radiometry Improvements for Visible and Near-Infrared Climate Studies, paper presented at 2010 Earth Science Technology Forum, Arlington, VA, USA. Platnick, S., et al., 2003, IEEE Trans. Geosci. Remote Sens., 41(2), 459- 473.
Ingram, WT
2012-01-01
Inverse limits provide a powerful tool for constructing complicated spaces from simple ones. They also turn the study of a dynamical system consisting of a space and a self-map into a study of a (likely more complicated) space and a self-homeomorphism. In four chapters along with an appendix containing background material the authors develop the theory of inverse limits. The book begins with an introduction through inverse limits on [0,1] before moving to a general treatment of the subject. Special topics in continuum theory complete the book. Although it is not a book on dynamics, the influen
Czech Academy of Sciences Publication Activity Database
Domesová, Simona; Beres, Michal
2017-01-01
Roč. 15, č. 2 (2017), s. 258-266 ISSN 1336-1376 R&D Projects: GA MŠk LQ1602 Institutional support: RVO:68145535 Keywords : Bayesian statistics * Cross-Entropy method * Darcy flow * Gaussian random field * inverse problem Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics http://advances.utc.sk/index.php/AEEE/article/view/2236
DEFF Research Database (Denmark)
Montoya-Martinez, Jair; Artes-Rodriguez, Antonio; Pontil, Massimiliano
2014-01-01
We consider the estimation of the Brain Electrical Sources (BES) matrix from noisy electroencephalographic (EEG) measurements, commonly named as the EEG inverse problem. We propose a new method to induce neurophysiological meaningful solutions, which takes into account the smoothness, structured...... matrix and the squared Frobenius norm of the latent source matrix. We develop an alternating optimization algorithm to solve the resulting nonsmooth-nonconvex minimization problem. We analyze the convergence of the optimization procedure, and we compare, under different synthetic scenarios...
Czech Academy of Sciences Publication Activity Database
Stoklasová, Pavla; Sedlák, Petr; Seiner, Hanuš; Landa, Michal
2015-01-01
Roč. 56, February 2015 (2015), s. 381-389 ISSN 0041-624X R&D Projects: GA ČR GPP101/12/P428 Institutional support: RVO:61388998 Keywords : surface acoustic waves * anisotropic materials * Ritz-Rayleigh method * inverse problem Subject RIV: BI - Acoustics Impact factor: 1.954, year: 2015 http://www.sciencedirect.com/science/article/pii/S0041624X14002686
International Nuclear Information System (INIS)
Abdallh, A; Crevecoeur, G; Dupré, L
2010-01-01
The measured voltage signals picked up by the needle probe method can be interpreted by a numerical method so as to identify the magnetic material properties of the magnetic circuit of an electromagnetic device. However, when solving this electromagnetic inverse problem, the uncertainties in the numerical method give rise to recovery errors since the calculated needle signals in the forward problem are sensitive to these uncertainties. This paper proposes a stochastic Cramér–Rao bound method for determining the optimal sensor placement in the experimental setup. The numerical method is computationally time efficient where the geometrical parameters need to be provided. We apply the method for the non-destructive magnetic material characterization of an EI inductor where we ascertain the optimal experiment design. This design corresponds to the highest possible resolution that can be obtained when solving the inverse problem. Moreover, the presented results are validated by comparison with the exact material characteristics. The results show that the proposed methodology is independent of the values of the material parameter so that it can be applied before solving the inverse problem, i.e. as a priori estimation stage
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....
Płonka, Agnieszka; Fichtner, Andreas
2017-04-01
Lateral density variations are the source of mass transport in the Earth at all scales, acting as drivers of convective motion. However, the density structure of the Earth remains largely unknown since classic seismic observables and gravity provide only weak constraints with strong trade-offs. Current density models are therefore often based on velocity scaling, making strong assumptions on the origin of structural heterogeneities, which may not necessarily be correct. Our goal is to assess if 3D density structure may be resolvable with emerging full-waveform inversion techniques. We have previously quantified the impact of regional-scale crustal density structure on seismic waveforms with the conclusion that reasonably sized density variations within the crust can leave a strong imprint on both travel times and amplitudes, and, while this can produce significant biases in velocity and Q estimates, the seismic waveform inversion for density may become feasible. In this study we perform principal component analyses of sensitivity kernels for P velocity, S velocity, and density. This is intended to establish the extent to which these kernels are linearly independent, i.e. the extent to which the different parameters may be constrained independently. We apply the method to data from 81 events around the Iberian Penninsula, registered in total by 492 stations. The objective is to find a principal kernel which would maximize the sensitivity to density, potentially allowing for as independent as possible density resolution. We find that surface (mosty Rayleigh) waves have significant sensitivity to density, and that the trade-off with velocity is negligible. We also show the preliminary results of the inversion.
Ishikawa, Atushi; Fujimoto, Shouji; Mizuno, Takayuki; Watanabe, Tsutomu
2014-03-01
We start from Gibrat's law and quasi-inversion symmetry for three firm size variables (i.e., tangible fixed assets K, number of employees L, and sales Y) and derive a partial differential equation to be satisfied by the joint probability density function of K and L. We then transform K and L, which are correlated, into two independent variables by applying surface openness used in geomorphology and provide an analytical solution to the partial differential equation. Using worldwide data on the firm size variables for companies, we confirm that the estimates on the power-law exponents of K, L, and Y satisfy a relationship implied by the theory.
Wu, Xingwei; Li, Cong; Wang, Yong; Wang, Zhiwei; Feng, Chunlei; Ding, Hongbin
2015-09-01
The hydrocarbon impurities formation is inevitable due to wall erosion in a long pulse high performance scenario with carbon-based plasma facing materials in fusion devices. The standard procedure to determine the chemical erosion yield in situ is by means of inverse photon efficiency D/XB. In this work, the conversion factor between CH4 flux and photon flux of CH A → X transition (effective inverse photon efficiency PE-1) was measured directly using a cascaded arc plasma simulator with argon/methane. This study shows that the measured PE-1 is different from the calculated D/XB. We compared the photon flux measured by optical emission spectroscopy (OES) and calculated by electron impact excitation of CH(X) which was diagnosed by cavity ring-down spectroscopy (CRDS). It seems that charge exchange and dissociative recombination processes are the main channels of CH(A) production and removal which lead to the inconsistency of PE -1 and D/XB at lower temperature. Meanwhile, the fraction of excited CH(A) produced by dissociative recombination processes was investigated, and we found it increased with Te in the range from 4% to 13% at Te definition instead of D/XB since the electron impact excitation is not the only channel of CH(A) production. These results have an effect on evaluating the yield of chemical erosion in divertor of fusion device.
Barki, Anum; Kendricks, Kimberly; Tuttle, Ronald F.; Bunker, David J.; Borel, Christoph C.
2013-05-01
This research highlights the results obtained from applying the method of inverse kinematics, using Groebner basis theory, to the human gait cycle to extract and identify lower extremity gait signatures. The increased threat from suicide bombers and the force protection issues of today have motivated a team at Air Force Institute of Technology (AFIT) to research pattern recognition in the human gait cycle. The purpose of this research is to identify gait signatures of human subjects and distinguish between subjects carrying a load to those subjects without a load. These signatures were investigated via a model of the lower extremities based on motion capture observations, in particular, foot placement and the joint angles for subjects affected by carrying extra load on the body. The human gait cycle was captured and analyzed using a developed toolkit consisting of an inverse kinematic motion model of the lower extremity and a graphical user interface. Hip, knee, and ankle angles were analyzed to identify gait angle variance and range of motion. Female subjects exhibited the most knee angle variance and produced a proportional correlation between knee flexion and load carriage.
Rodriguez, Brian D.
2017-03-31
This report summarizes the results of three-dimensional (3-D) resistivity inversion simulations that were performed to account for local 3-D distortion of the electric field in the presence of 3-D regional structure, without any a priori information on the actual 3-D distribution of the known subsurface geology. The methodology used a 3-D geologic model to create a 3-D resistivity forward (“known”) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was assumed to represent observed magnetotelluric data and was subsequently used as input into a 3-D resistivity inverse model that used an iterative 3-D algorithm to estimate 3-D distortions without any a priori geologic information. A publicly available inversion code, WSINV3DMT, was used for all of the simulated inversions, initially using the default parameters, and subsequently using adjusted inversion parameters. A semiautomatic approach of accounting for the static shift using various selections of the highest frequencies and initial models was also tested. The resulting 3-D resistivity inversion simulation was compared to the “known” model and the results evaluated. The inversion approach that produced the lowest misfit to the various local 3-D distortions was an inversion that employed an initial model volume resistivity that was nearest to the maximum resistivities in the near-surface layer.
Affagard, Jean-Sébastien; Bensamoun, Sabine F; Feissel, Pierre
2014-11-01
The purpose of this study was to develop an inverse method, coupling imaging techniques with numerical methods, to identify the muscle mechanical behavior. A finite element model updating (FEMU) was developed in three main interdependent steps. First, a 2D FE modeling, parameterized by a Neo-Hookean behavior (C10 and D), was developed from a segmented thigh muscle 1.5T MRI (magnetic resonance imaging). Thus, a displacement field was simulated for different static loadings (contention, compression, and indentation). Subsequently, the optimal mechanical test was determined from a sensitivity analysis. Second, ultrasound parameters (gain, dynamic, and frequency) were optimized on the thigh muscles in order to apply the digital image correlation (DIC), allowing the measurement of an experimental displacement field. Third, an inverse method was developed to identify the Neo-Hookean parameters (C10 and D) by performing a minimization of the distance between the simulated and measured displacement fields. To replace the experimental data and to quantify the identification error, a numerical example was developed. The result of the sensitivity analysis showed that the compression test was more adapted to identify the Neo-Hookean parameters. Ultrasound images were recorded with a frequency, gain, and dynamic of 9 MHz, 34 dB, 42 dB, respectively. In addition, the experimental noise on displacement field measurement was estimated to be 0.2 mm. The identification performed on the numerical example revealed a low error for the C10 (muscle behavior will help to follow treatment and to ensure accurate medical procedures during the use of robotic devices.
Energy Technology Data Exchange (ETDEWEB)
Saide, Pablo (CGRER, Center for Global and Regional Environmental Research, Univ. of Iowa, Iowa City, IA (United States)), e-mail: pablo-saide@uiowa.edu; Bocquet, Marc (Universite Paris-Est, CEREA Joint Laboratory Ecole des Ponts ParisTech and EDF RandD, Champs-sur-Marne (France); INRIA, Paris Rocquencourt Research Center (France)); Osses, Axel (Departamento de Ingeniera Matematica, Universidad de Chile, Santiago (Chile); Centro de Modelamiento Matematico, UMI 2807/Universidad de Chile-CNRS, Santiago (Chile)); Gallardo, Laura (Centro de Modelamiento Matematico, UMI 2807/Universidad de Chile-CNRS, Santiago (Chile); Departamento de Geofisica, Universidad de Chile, Santiago (Chile))
2011-07-15
When constraining surface emissions of air pollutants using inverse modelling one often encounters spurious corrections to the inventory at places where emissions and observations are colocated, referred to here as the colocalization problem. Several approaches have been used to deal with this problem: coarsening the spatial resolution of emissions; adding spatial correlations to the covariance matrices; adding constraints on the spatial derivatives into the functional being minimized; and multiplying the emission error covariance matrix by weighting factors. Intercomparison of methods for a carbon monoxide inversion over a city shows that even though all methods diminish the colocalization problem and produce similar general patterns, detailed information can greatly change according to the method used ranging from smooth, isotropic and short range modifications to not so smooth, non-isotropic and long range modifications. Poisson (non-Gaussian) and Gaussian assumptions both show these patterns, but for the Poisson case the emissions are naturally restricted to be positive and changes are given by means of multiplicative correction factors, producing results closer to the true nature of emission errors. Finally, we propose and test a new two-step, two-scale, fully Bayesian approach that deals with the colocalization problem and can be implemented for any prior density distribution
Molina-Aguilera, A.; Mancilla, F. D. L.; Julià, J.; Morales, J.
2017-12-01
Joint inversion techniques of P-receiver functions and wave dispersion data implicitly assume an isotropic radial stratified earth. The conventional approach invert stacked radial component receiver functions from different back-azimuths to obtain a laterally homogeneous single-velocity model. However, in the presence of strong lateral heterogeneities as anisotropic layers and/or dipping interfaces, receiver functions are considerably perturbed and both the radial and transverse components exhibit back azimuthal dependences. Harmonic analysis methods exploit these azimuthal periodicities to separate the effects due to the isotropic flat-layered structure from those effects caused by lateral heterogeneities. We implement a harmonic analysis method based on radial and transverse receiver functions components and carry out a synthetic study to illuminate the capabilities of the method in isolating the isotropic flat-layered part of receiver functions and constrain the geometry and strength of lateral heterogeneities. The independent of the baz P receiver function are jointly inverted with phase and group dispersion curves using a linearized inversion procedure. We apply this approach to high dense seismic profiles ( 2 km inter-station distance, see figure) located in the central Betics (western Mediterranean region), a region which has experienced complex geodynamic processes and exhibit strong variations in Moho topography. The technique presented here is robust and can be applied systematically to construct a 3-D model of the crust and uppermost mantle across large networks.
Oleksik, Mihaela; Oleksik, Valentin
2013-05-01
The current paper intends to realise a fast method for determining the material characteristics in the case of composite materials used in the airbags manufacturing. For determining the material data needed for other complex numerical simulations at macroscopic level there was used the inverse analysis method. In fact, there were carried out tensile tests for the composite material extracted along two directions - the direction of the weft and the direction of the warp and afterwards there were realised numerical simulations (using the Ls-Dyna software). A second stage consisted in the numerical simulation through the finite element method and the experimental testing for the Bias test. The material characteristics of the composite fabric material were then obtained by applying a multicriterial analysis using the Ls-Opt software, for which there was imposed a decrease of the mismatch between the force-displacement curves obtained numerically and experimentally, respectively, for both directions (weft and warp) as well as the decrease of the mismatch between the strain - extension curves for two points at the Bias test.
Kumar, R.; Bansal, A. R.; Anand, S. P.; Rao, V. K.; Singh, U. K.
2016-12-01
The central India region is having complex geology covering various geological units e.g., Precambrian Bastar Craton (including Proterozoic Chhattisgarh Basin, granitic intrusions etc.) and Eastern Ghat Mobile Belt, Gondwana Godavari and Mahanadi Grabens, Late Cretaceous Deccan Traps etc. The central India is well covered by reconnaissance scale aeromagnetic data. We analyzed this data for mapping the basement by dividing into143 overlapping blocks of 100×100km using least square nonlinear inversion method for fractal distribution of sources. The scaling exponents and depth values are optimized using grid search method. We interpreted estimated depths of anomalous sources as magnetic basement and shallow anomalous magnetic sources. The shallow magnetic anomalies are found to vary from 1 to 3km whereas magnetic basement depths are found to vary from 2km to 7km. The shallowest basement depth of 2km found corresponding to Kanker granites a part of Bastar Craton whereas deepest basement depth of 7km is associated with Godavari Graben and south eastern part of Eastern Ghat Mobile Belts near the Parvatipuram Bobbili fault. The variation of magnetic basement, shallow depths and scaling exponent in the region indicate complex tectonic, heterogeneity and intrusive bodies at different depths which is due to different tectonic processes in the region. The detailed basement depth of central India is presented in this study.
Kozunov, Vladimir V; Ossadtchi, Alexei
2015-01-01
Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis. We propose Group Analysis Leads to Accuracy (GALA)-a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects. A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face-specific evoked responses.
Directory of Open Access Journals (Sweden)
Vladimir eKozunov
2015-04-01
Full Text Available Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis.We propose Group Analysis Leads to Accuracy (GALA - a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects.A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face
Chromatid Painting for Chromosomal Inversion Detection, Phase I
National Aeronautics and Space Administration — We propose a novel approach to the detection of chromosomal inversions. Transmissible chromosome aberrations (translocations and inversions) have profound genetic...
Blöcher, Johanna; Kuraz, Michal
2017-04-01
In this contribution we propose implementations of the dual permeability model with different inter-domain exchange descriptions and metaheuristic optimization algorithms for parameter identification and mesh optimization. We compare variants of the coupling term with different numbers of parameters to test if a reduction of parameters is feasible. This can reduce parameter uncertainty in inverse modeling, but also allow for different conceptual models of the domain and matrix coupling. The different variants of the dual permeability model are implemented in the open-source objective library DRUtES written in FORTRAN 2003/2008 in 1D and 2D. For parameter identification we use adaptations of the particle swarm optimization (PSO) and Teaching-learning-based optimization (TLBO), which are population-based metaheuristics with different learning strategies. These are high-level stochastic-based search algorithms that don't require gradient information or a convex search space. Despite increasing computing power and parallel processing, an overly fine mesh is not feasible for parameter identification. This creates the need to find a mesh that optimizes both accuracy and simulation time. We use a bi-objective PSO algorithm to generate a Pareto front of optimal meshes to account for both objectives. The dual permeability model and the optimization algorithms were tested on virtual data and field TDR sensor readings. The TDR sensor readings showed a very steep increase during rapid rainfall events and a subsequent steep decrease. This was theorized to be an effect of artificial macroporous envelopes surrounding TDR sensors creating an anomalous region with distinct local soil hydraulic properties. One of our objectives is to test how well the dual permeability model can describe this infiltration behavior and what coupling term would be most suitable.
Brutovsky, B.; Horvath, D.; Lisy, V.
2008-02-01
We demonstrate the power of genetic algorithms to construct a cellular automata model simulating the growth of 2D close-to-circular clusters, revealing the desired properties, such as the growth rate and, at the same time, the fractal behavior of their contours. The possible application of the approach in the field of tumor modeling is outlined.
Omisore, Olatunji Mumini; Han, Shipeng; Ren, Lingxue; Zhang, Nannan; Ivanov, Kamen; Elazab, Ahmed; Wang, Lei
2017-08-01
Snake-like robot is an emerging form of serial-link manipulator with the morphologic design of biological snakes. The redundant robot can be used to assist medical experts in accessing internal organs with minimal or no invasion. Several snake-like robotic designs have been proposed for minimal invasive surgery, however, the few that were developed are yet to be fully explored for clinical procedures. This is due to lack of capability for full-fledged spatial navigation. In rare cases where such snake-like designs are spatially flexible, there exists no inverse kinematics (IK) solution with both precise control and fast response. In this study, we proposed a non-iterative geometric method for solving IK of lead-module of a snake-like robot designed for therapy or ablation of abdominal tumors. The proposed method is aimed at providing accurate and fast IK solution for given target points in the robot's workspace. n-1 virtual points (VPs) were geometrically computed and set as coordinates of intermediary joints in an n-link module. Suitable joint angles that can place the end-effector at given target points were then computed by vectorizing coordinates of the VPs, in addition to coordinates of the base point, target point, and tip of the first link in its default pose. The proposed method is applied to solve IK of two-link and redundant four-link modules. Both two-link and four-link modules were simulated with Robotics Toolbox in Matlab 8.3 (R2014a). Implementation result shows that the proposed method can solve IK of the spatially flexible robot with minimal error values. Furthermore, analyses of results from both modules show that the geometric method can reach 99.21 and 88.61% of points in their workspaces, respectively, with an error threshold of 1 mm. The proposed method is non-iterative and has a maximum execution time of 0.009 s. This paper focuses on solving IK problem of a spatially flexible robot which is part of a developmental project for abdominal
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
Vock, David M; Wolfson, Julian; Bandyopadhyay, Sunayan; Adomavicius, Gediminas; Johnson, Paul E; Vazquez-Benitez, Gabriela; O'Connor, Patrick J
2016-06-01
Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack in the next 5years) based on individual patient characteristics are important tools for managing patient care. Electronic health data (EHD) are appealing sources of training data because they provide access to large amounts of rich individual-level data from present-day patient populations. However, because EHD are derived by extracting information from administrative and clinical databases, some fraction of subjects will not be under observation for the entire time frame over which one wants to make predictions; this loss to follow-up is often due to disenrollment from the health system. For subjects without complete follow-up, whether or not they experienced the adverse event is unknown, and in statistical terms the event time is said to be right-censored. Most machine learning approaches to the problem have been relatively ad hoc; for example, common approaches for handling observations in which the event status is unknown include (1) discarding those observations, (2) treating them as non-events, (3) splitting those observations into two observations: one where the event occurs and one where the event does not. In this paper, we present a general-purpose approach to account for right-censored outcomes using inverse probability of censoring weighting (IPCW). We illustrate how IPCW can easily be incorporated into a number of existing machine learning algorithms used to mine big health care data including Bayesian networks, k-nearest neighbors, decision trees, and generalized additive models. We then show that our approach leads to better calibrated predictions than the three ad hoc approaches when applied to predicting the 5-year risk of experiencing a cardiovascular adverse event, using EHD from a large U.S. Midwestern healthcare system. Copyright © 2016 Elsevier Inc. All rights reserved.
Algebraic properties of generalized inverses
Cvetković‐Ilić, Dragana S
2017-01-01
This book addresses selected topics in the theory of generalized inverses. Following a discussion of the “reverse order law” problem and certain problems involving completions of operator matrices, it subsequently presents a specific approach to solving the problem of the reverse order law for {1} -generalized inverses. Particular emphasis is placed on the existence of Drazin invertible completions of an upper triangular operator matrix; on the invertibility and different types of generalized invertibility of a linear combination of operators on Hilbert spaces and Banach algebra elements; on the problem of finding representations of the Drazin inverse of a 2x2 block matrix; and on selected additive results and algebraic properties for the Drazin inverse. In addition to the clarity of its content, the book discusses the relevant open problems for each topic discussed. Comments on the latest references on generalized inverses are also included. Accordingly, the book will be useful for graduate students, Ph...
Vanderstraeten, Barbara; DeGersem, Werner; Duthoy, Wim; DeNeve, Wilfried; Thierens, Hubert
2006-08-01
The development of new biological imaging technologies offers the opportunity to further individualize radiotherapy. Biologically conformal radiation therapy (BCRT) implies the use of the spatial distribution of one or more radiobiological parameters to guide the IMRT dose prescription. Our aim was to implement BCRT in an algorithmic segmentation-based planning approach. A biology-based segmentation tool was developed to generate initial beam segments that reflect the biological signal intensity pattern. The weights and shapes of the initial segments are optimized by means of an objective function that minimizes the root mean square deviation between the actual and intended dose values within the PTV. As proof of principle, [18F]FDG-PET-guided BCRT plans for two different levels of dose escalation were created for an oropharyngeal cancer patient. Both plans proved to be dosimetrically feasible without violating the planning constraints for the expanded spinal cord and the contralateral parotid gland as organs at risk. The obtained biological conformity was better for the first (2.5 Gy per fraction) than for the second (3 Gy per fraction) dose escalation level.
International Nuclear Information System (INIS)
Meric, Ilker; Johansen, Geir A; Holstad, Marie B; Mattingly, John; Gardner, Robin P
2012-01-01
Prompt gamma-ray neutron activation analysis (PGNAA) has been and still is one of the major methods of choice for the elemental analysis of various bulk samples. This is mostly due to the fact that PGNAA offers a rapid, non-destructive and on-line means of sample interrogation. The quantitative analysis of the prompt gamma-ray data could, on the other hand, be performed either through the single peak analysis or the so-called Monte Carlo library least-squares (MCLLS) approach, of which the latter has been shown to be more sensitive and more accurate than the former. The MCLLS approach is based on the assumption that the total prompt gamma-ray spectrum of any sample is a linear combination of the contributions from the individual constituents or libraries. This assumption leads to, through the minimization of the chi-square value, a set of linear equations which has to be solved to obtain the library multipliers, a process that involves the inversion of the covariance matrix. The least-squares solution may be extremely uncertain due to the ill-conditioning of the covariance matrix. The covariance matrix will become ill-conditioned whenever, in the subsequent calculations, two or more libraries are highly correlated. The ill-conditioning will also be unavoidable whenever the sample contains trace amounts of certain elements or elements with significantly low thermal neutron capture cross-sections. In this work, a new iterative approach, which can handle the ill-conditioning of the covariance matrix, is proposed and applied to a hydrocarbon multiphase flow problem in which the parameters of interest are the separate amounts of the oil, gas, water and salt phases. The results of the proposed method are also compared with the results obtained through the implementation of a well-known regularization method, the truncated singular value decomposition. Final calculations indicate that the proposed approach would be able to treat ill-conditioned cases appropriately. (paper)
Fast computation of the inverse CMH model
Patel, Umesh D.; Della Torre, Edward
2001-12-01
A fast computational method based on differential equation approach for inverse Della Torre, Oti, Kádár (DOK) model has been extended for the inverse Complete Moving Hysteresis (CMH) model. A cobweb technique for calculating the inverse CMH model is also presented. The two techniques differ from the point of view of flexibility, accuracy, and computation time. Simulation results of the inverse computation for both methods are presented.
Chromatid Painting for Chromosomal Inversion Detection Project
National Aeronautics and Space Administration — We propose the continued development of a novel approach to the detection of chromosomal inversions. Transmissible chromosome aberrations (translocations and...
Statistical perspectives on inverse problems
DEFF Research Database (Denmark)
Andersen, Kim Emil
of the interior of an object from electrical boundary measurements. One part of this thesis concerns statistical approaches for solving, possibly non-linear, inverse problems. Thus inverse problems are recasted in a form suitable for statistical inference. In particular, a Bayesian approach for regularisation...... problem is given in terms of probability distributions. Posterior inference is obtained by Markov chain Monte Carlo methods and new, powerful simulation techniques based on e.g. coupled Markov chains and simulated tempering is developed to improve the computational efficiency of the overall simulation......Inverse problems arise in many scientific disciplines and pertain to situations where inference is to be made about a particular phenomenon from indirect measurements. A typical example, arising in diffusion tomography, is the inverse boundary value problem for non-invasive reconstruction...
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
Blein, Sophie; Bardel, Claire; Danjean, Vincent; McGuffog, Lesley; Healey, Sue; Barrowdale, Daniel; Lee, Andrew; Dennis, Joe; Kuchenbaecker, Karoline B; Soucy, Penny; Terry, Mary Beth; Chung, Wendy K; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Tihomirova, Laima; Tung, Nadine; Dorfling, Cecilia M; van Rensburg, Elizabeth J; Neuhausen, Susan L; Ding, Yuan Chun; Gerdes, Anne-Marie; Ejlertsen, Bent; Nielsen, Finn C; Hansen, Thomas Vo; Osorio, Ana; Benitez, Javier; Conejero, Raquel Andrés; Segota, Ena; Weitzel, Jeffrey N; Thelander, Margo; Peterlongo, Paolo; Radice, Paolo; Pensotti, Valeria; Dolcetti, Riccardo; Bonanni, Bernardo; Peissel, Bernard; Zaffaroni, Daniela; Scuvera, Giulietta; Manoukian, Siranoush; Varesco, Liliana; Capone, Gabriele L; Papi, Laura; Ottini, Laura; Yannoukakos, Drakoulis; Konstantopoulou, Irene; Garber, Judy; Hamann, Ute; Donaldson, Alan; Brady, Angela; Brewer, Carole; Foo, Claire; Evans, D Gareth; Frost, Debra; Eccles, Diana; Douglas, Fiona; Cook, Jackie; Adlard, Julian; Barwell, Julian; Walker, Lisa; Izatt, Louise; Side, Lucy E; Kennedy, M John; Tischkowitz, Marc; Rogers, Mark T; Porteous, Mary E; Morrison, Patrick J; Platte, Radka; Eeles, Ros; Davidson, Rosemarie; Hodgson, Shirley; Cole, Trevor; Godwin, Andrew K; Isaacs, Claudine; Claes, Kathleen; De Leeneer, Kim; Meindl, Alfons; Gehrig, Andrea; Wappenschmidt, Barbara; Sutter, Christian; Engel, Christoph; Niederacher, Dieter; Steinemann, Doris; Plendl, Hansjoerg; Kast, Karin; Rhiem, Kerstin; Ditsch, Nina; Arnold, Norbert; Varon-Mateeva, Raymonda; Schmutzler, Rita K; Preisler-Adams, Sabine; Markov, Nadja Bogdanova; Wang-Gohrke, Shan; de Pauw, Antoine; Lefol, Cédrick; Lasset, Christine; Leroux, Dominique; Rouleau, Etienne; Damiola, Francesca; Dreyfus, Hélène; Barjhoux, Laure; Golmard, Lisa; Uhrhammer, Nancy; Bonadona, Valérie; Sornin, Valérie; Bignon, Yves-Jean; Carter, Jonathan; Van Le, Linda; Piedmonte, Marion; DiSilvestro, Paul A; de la Hoya, Miguel; Caldes, Trinidad; Nevanlinna, Heli; Aittomäki, Kristiina; Jager, Agnes; van den Ouweland, Ans Mw; Kets, Carolien M; Aalfs, Cora M; van Leeuwen, Flora E; Hogervorst, Frans Bl; Meijers-Heijboer, Hanne Ej; Oosterwijk, Jan C; van Roozendaal, Kees Ep; Rookus, Matti A; Devilee, Peter; van der Luijt, Rob B; Olah, Edith; Diez, Orland; Teulé, Alex; Lazaro, Conxi; Blanco, Ignacio; Del Valle, Jesús; Jakubowska, Anna; Sukiennicki, Grzegorz; Gronwald, Jacek; Lubinski, Jan; Durda, Katarzyna; Jaworska-Bieniek, Katarzyna; Agnarsson, Bjarni A; Maugard, Christine; Amadori, Alberto; Montagna, Marco; Teixeira, Manuel R; Spurdle, Amanda B; Foulkes, William; Olswold, Curtis; Lindor, Noralane M; Pankratz, Vernon S; Szabo, Csilla I; Lincoln, Anne; Jacobs, Lauren; Corines, Marina; Robson, Mark; Vijai, Joseph; Berger, Andreas; Fink-Retter, Anneliese; Singer, Christian F; Rappaport, Christine; Kaulich, Daphne Geschwantler; Pfeiler, Georg; Tea, Muy-Kheng; Greene, Mark H; Mai, Phuong L; Rennert, Gad; Imyanitov, Evgeny N; Mulligan, Anna Marie; Glendon, Gord; Andrulis, Irene L; Tchatchou, Sandrine; Toland, Amanda Ewart; Pedersen, Inge Sokilde; Thomassen, Mads; Kruse, Torben A; Jensen, Uffe Birk; Caligo, Maria A; Friedman, Eitan; Zidan, Jamal; Laitman, Yael; Lindblom, Annika; Melin, Beatrice; Arver, Brita; Loman, Niklas; Rosenquist, Richard; Olopade, Olufunmilayo I; Nussbaum, Robert L; Ramus, Susan J; Nathanson, Katherine L; Domchek, Susan M; Rebbeck, Timothy R; Arun, Banu K; Mitchell, Gillian; Karlan, Beth Y; Lester, Jenny; Orsulic, Sandra; Stoppa-Lyonnet, Dominique; Thomas, Gilles; Simard, Jacques; Couch, Fergus J; Offit, Kenneth; Easton, Douglas F; Chenevix-Trench, Georgia; Antoniou, Antonis C; Mazoyer, Sylvie; Phelan, Catherine M; Sinilnikova, Olga M; Cox, David G
2015-04-25
Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. We genotyped 22,214 (11,421 affected, 10,793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals. We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population (that is, H and T clades), the T1a1 haplogroup has a HR of 0.62 (95% CI, 0.40 to 0.95; P = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.
Intersections, ideals, and inversion
International Nuclear Information System (INIS)
Vasco, D.W.
1998-01-01
Techniques from computational algebra provide a framework for treating large classes of inverse problems. In particular, the discretization of many types of integral equations and of partial differential equations with undetermined coefficients lead to systems of polynomial equations. The structure of the solution set of such equations may be examined using algebraic techniques.. For example, the existence and dimensionality of the solution set may be determined. Furthermore, it is possible to bound the total number of solutions. The approach is illustrated by a numerical application to the inverse problem associated with the Helmholtz equation. The algebraic methods are used in the inversion of a set of transverse electric (TE) mode magnetotelluric data from Antarctica. The existence of solutions is demonstrated and the number of solutions is found to be finite, bounded from above at 50. The best fitting structure is dominantly one dimensional with a low crustal resistivity of about 2 ohm-m. Such a low value is compatible with studies suggesting lower surface wave velocities than found in typical stable cratons
Intersections, ideals, and inversion
Energy Technology Data Exchange (ETDEWEB)
Vasco, D.W.
1998-10-01
Techniques from computational algebra provide a framework for treating large classes of inverse problems. In particular, the discretization of many types of integral equations and of partial differential equations with undetermined coefficients lead to systems of polynomial equations. The structure of the solution set of such equations may be examined using algebraic techniques.. For example, the existence and dimensionality of the solution set may be determined. Furthermore, it is possible to bound the total number of solutions. The approach is illustrated by a numerical application to the inverse problem associated with the Helmholtz equation. The algebraic methods are used in the inversion of a set of transverse electric (TE) mode magnetotelluric data from Antarctica. The existence of solutions is demonstrated and the number of solutions is found to be finite, bounded from above at 50. The best fitting structure is dominantly onedimensional with a low crustal resistivity of about 2 ohm-m. Such a low value is compatible with studies suggesting lower surface wave velocities than found in typical stable cratons.
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
Directory of Open Access Journals (Sweden)
Halis Aygün
2008-01-01
Full Text Available We introduce definitions of fuzzy inverse compactness, fuzzy inverse countable compactness, and fuzzy inverse Lindelöfness on arbitrary -fuzzy sets in -fuzzy topological spaces. We prove that the proposed definitions are good extensions of the corresponding concepts in ordinary topology and obtain different characterizations of fuzzy inverse compactness.
Statistical and Computational Inverse Problems
Kaipio, Jari
2005-01-01
Develops the statistical approach to inverse problems with an emphasis on modeling and computations. The book discusses the measurement noise modeling and Bayesian estimation, and uses Markov Chain Monte Carlo methods to explore the probability distributions. It is for researchers and advanced students in applied mathematics.
Time-reversal and Bayesian inversion
Debski, Wojciech
2017-04-01
Probabilistic inversion technique is superior to the classical optimization-based approach in all but one aspects. It requires quite exhaustive computations which prohibit its use in huge size inverse problems like global seismic tomography or waveform inversion to name a few. The advantages of the approach are, however, so appealing that there is an ongoing continuous afford to make the large inverse task as mentioned above manageable with the probabilistic inverse approach. One of the perspective possibility to achieve this goal relays on exploring the internal symmetry of the seismological modeling problems in hand - a time reversal and reciprocity invariance. This two basic properties of the elastic wave equation when incorporating into the probabilistic inversion schemata open a new horizons for Bayesian inversion. In this presentation we discuss the time reversal symmetry property, its mathematical aspects and propose how to combine it with the probabilistic inverse theory into a compact, fast inversion algorithm. We illustrate the proposed idea with the newly developed location algorithm TRMLOC and discuss its efficiency when applied to mining induced seismic data.
Inverse Kinematics with Closed Form Solution for Denso Robot Manipulator
Prasetia, Ikhsan Eka; Agustinah, Trihastuti
2015-01-01
In this paper, the forward kinematics and inverse kinematics used on the Denso robot manipulator which has a 6-DOF. The forward kinematics will result in the desired position by end-effector, while inverse kinematics produce angel on each joint. Inverse kinematics problem are very difficult, therefor to obtain the solution of inverse kinematics using closed form solution with geometry approach. The simulation result obtained from forward kinematics and inverse kinematics is determining desire...
Aydin, Umit; Dogrusoz, Yesim Serinagaoglu
2011-09-01
In this article, we aimed to reduce the effects of geometric errors and measurement noise on the inverse problem of Electrocardiography (ECG) solutions. We used the Kalman filter to solve the inverse problem in terms of epicardial potential distributions. The geometric errors were introduced into the problem via wrong determination of the size and location of the heart in simulations. An error model, which is called the enhanced error model (EEM), was modified to be used in inverse problem of ECG to compensate for the geometric errors. In this model, the geometric errors are modeled as additive Gaussian noise and their noise variance is added to the measurement noise variance. The Kalman filter method includes a process noise component, whose variance should also be estimated along with the measurement noise. To estimate these two noise variances, two different algorithms were used: (1) an algorithm based on residuals, (2) expectation maximization algorithm. The results showed that it is important to use the correct noise variances to obtain accurate results. The geometric errors, if ignored in the inverse solution procedure, yielded incorrect epicardial potential distributions. However, even with a noise model as simple as the EEM, the solutions could be significantly improved.
Inverse source problems in elastodynamics
Bao, Gang; Hu, Guanghui; Kian, Yavar; Yin, Tao
2018-04-01
We are concerned with time-dependent inverse source problems in elastodynamics. The source term is supposed to be the product of a spatial function and a temporal function with compact support. We present frequency-domain and time-domain approaches to show uniqueness in determining the spatial function from wave fields on a large sphere over a finite time interval. The stability estimate of the temporal function from the data of one receiver and the uniqueness result using partial boundary data are proved. Our arguments rely heavily on the use of the Fourier transform, which motivates inversion schemes that can be easily implemented. A Landweber iterative algorithm for recovering the spatial function and a non-iterative inversion scheme based on the uniqueness proof for recovering the temporal function are proposed. Numerical examples are demonstrated in both two and three dimensions.
Accommodating chromosome inversions in linkage analysis.
Chen, Gary K; Slaten, Erin; Ophoff, Roel A; Lange, Kenneth
2006-08-01
This work develops a population-genetics model for polymorphic chromosome inversions. The model precisely describes how an inversion changes the nature of and approach to linkage equilibrium. The work also describes algorithms and software for allele-frequency estimation and linkage analysis in the presence of an inversion. The linkage algorithms implemented in the software package Mendel estimate recombination parameters and calculate the posterior probability that each pedigree member carries the inversion. Application of Mendel to eight Centre d'Etude du Polymorphisme Humain pedigrees in a region containing a common inversion on 8p23 illustrates its potential for providing more-precise estimates of the location of an unmapped marker or trait gene. Our expanded cytogenetic analysis of these families further identifies inversion carriers and increases the evidence of linkage.
Recurrent Neural Network for Computing Outer Inverse.
Živković, Ivan S; Stanimirović, Predrag S; Wei, Yimin
2016-05-01
Two linear recurrent neural networks for generating outer inverses with prescribed range and null space are defined. Each of the proposed recurrent neural networks is based on the matrix-valued differential equation, a generalization of dynamic equations proposed earlier for the nonsingular matrix inversion, the Moore-Penrose inversion, as well as the Drazin inversion, under the condition of zero initial state. The application of the first approach is conditioned by the properties of the spectrum of a certain matrix; the second approach eliminates this drawback, though at the cost of increasing the number of matrix operations. The cases corresponding to the most common generalized inverses are defined. The conditions that ensure stability of the proposed neural network are presented. Illustrative examples present the results of numerical simulations.
Parametric optimization of inverse trapezoid oleophobic surfaces
DEFF Research Database (Denmark)
Cavalli, Andrea; Bøggild, Peter; Okkels, Fridolin
2012-01-01
In this paper, we introduce a comprehensive and versatile approach to the parametric shape optimization of oleophobic surfaces. We evaluate the performance of inverse trapezoid microstructures in terms of three objective parameters: apparent contact angle, maximum sustainable hydrostatic pressure...
Sieberling, S.; Chu, Q.P.; Mulder, J.A.
2010-01-01
This paper presents a flight control strategy based on nonlinear dynamic inversion. The approach presented, called incremental nonlinear dynamic inversion, uses properties of general mechanical systems and nonlinear dynamic inversion by feeding back angular accelerations. Theoretically, feedback of
Approximation of Bayesian Inverse Problems for PDEs
Cotter, S. L.; Dashti, M.; Stuart, A. M.
2010-01-01
Inverse problems are often ill posed, with solutions that depend sensitively on data.n any numerical approach to the solution of such problems, regularization of some form is needed to counteract the resulting instability. This paper is based on an approach to regularization, employing a Bayesian formulation of the problem, which leads to a notion of well posedness for inverse problems, at the level of probability measures. The stability which results from this well posedness may be used as t...
Picozzi, M.; Oth, A.; Parolai, S.; Bindi, D.; De Landro, G.; Amoroso, O.
2017-05-01
The accurate determination of stress drop, seismic efficiency, and how source parameters scale with earthquake size is an important issue for seismic hazard assessment of induced seismicity. We propose an improved nonparametric, data-driven strategy suitable for monitoring induced seismicity, which combines the generalized inversion technique together with genetic algorithms. In the first step of the analysis the generalized inversion technique allows for an effective correction of waveforms for attenuation and site contributions. Then, the retrieved source spectra are inverted by a nonlinear sensitivity-driven inversion scheme that allows accurate estimation of source parameters. We therefore investigate the earthquake source characteristics of 633 induced earthquakes (Mw 2-3.8) recorded at The Geysers geothermal field (California) by a dense seismic network (i.e., 32 stations, more than 17.000 velocity records). We find a nonself-similar behavior, empirical source spectra that require an ωγ source model with γ > 2 to be well fit and small radiation efficiency ηSW. All these findings suggest different dynamic rupture processes for smaller and larger earthquakes and that the proportion of high-frequency energy radiation and the amount of energy required to overcome the friction or for the creation of new fractures surface changes with earthquake size. Furthermore, we observe also two distinct families of events with peculiar source parameters that in one case suggests the reactivation of deep structures linked to the regional tectonics, while in the other supports the idea of an important role of steeply dipping faults in the fluid pressure diffusion.
Rhew, Isaac C; Oesterle, Sabrina; Coffman, Donna; Hawkins, J David
2018-01-01
Earlier intention-to-treat (ITT) findings from a community-randomized trial demonstrated effects of the Communities That Care (CTC) prevention system on reducing problem behaviors among youth. In ITT analyses, youth were analyzed according to their original study community's randomized condition even if they moved away from the community over the course of follow-up and received little to no exposure to intervention activities. Using inverse probability weights (IPWs), this study estimated effects of CTC in the same randomized trial among youth who remained in their original study communities throughout follow-up. Data were from the Community Youth Development Study, a community-randomized trial of 24 small towns in the United States. A cohort of 4,407 youth was followed from fifth grade (prior to CTC implementation) to eighth grade. IPWs for one's own moving status were calculated using fifth- and sixth-grade covariates. Results from inverse probability weighted multilevel models indicated larger effects for youth who remained in their study community for the first 2 years of CTC intervention implementation compared to ITT estimates. These effects included reduced likelihood of alcohol use, binge drinking, smokeless tobacco use, and delinquent behavior. These findings strengthen support for CTC as an efficacious system for preventing youth problem behaviors.
Inverse Kinematics using Quaternions
DEFF Research Database (Denmark)
Henriksen, Knud; Erleben, Kenny; Engell-Nørregård, Morten
In this project I describe the status of inverse kinematics research, with the focus firmly on the methods that solve the core problem. An overview of the different methods are presented Three common methods used in inverse kinematics computation have been chosen as subject for closer inspection....
Inverse logarithmic potential problem
Cherednichenko, V G
1996-01-01
The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Fast wavelet based sparse approximate inverse preconditioner
Energy Technology Data Exchange (ETDEWEB)
Wan, W.L. [Univ. of California, Los Angeles, CA (United States)
1996-12-31
Incomplete LU factorization is a robust preconditioner for both general and PDE problems but unfortunately not easy to parallelize. Recent study of Huckle and Grote and Chow and Saad showed that sparse approximate inverse could be a potential alternative while readily parallelizable. However, for special class of matrix A that comes from elliptic PDE problems, their preconditioners are not optimal in the sense that independent of mesh size. A reason may be that no good sparse approximate inverse exists for the dense inverse matrix. Our observation is that for this kind of matrices, its inverse entries typically have piecewise smooth changes. We can take advantage of this fact and use wavelet compression techniques to construct a better sparse approximate inverse preconditioner. We shall show numerically that our approach is effective for this kind of matrices.
Zakhariev, B. N.; Chabanov, V. M.
It was an important examination to give a review talk at the previous Conference on Inverse Quantum Scattering (1996, Lake Balaton) about computer visualization of this science in front of its fathers — creators, B. M. Levitan and V. A. Marchenko. We have achieved a new understanding that the discovered main rules of transformations of a single wave function bump, e.g., for the ground bound states of one dimensional quantum systems are applicable to any state of any potential with arbitrary number of bumps from finite to unlimited ones as scattering states and bound states embedded into continuum. It appeared that we need only to repeat the rule mentally the necessary number of times. That uttermost simplification and unification of physical notion of spectral, scattering and decay control for any potential have got an obligatory praise from B. M. Levitan at the conference and was a mighty stimulus for our further research After that we have written both Russian (2002) and improved English editions of “Submissive Quantum Mechanics. New Status of the Theory in Inverse Problem Approach”1 (appeared at the very end of 2007). This book was written for correction of the present defect in quantum education throughout the world. Recently the quantum IP intuition helped us to discover a new concept of permanent wave resonance with potential spatial oscillations.2 This means the constant wave swinging frequency on the whole energy intervals of spectral forbidden zones destroying physical solutions and deepening the theory of waves in periodic potentials. It also shows the other side of strengthening the fundamentally important magic structures. A ‘new language’ of wave bending will be presented to enrich our quantum intuition, e.g., the paradoxical effective attraction of barriers and repulsion of wells in multichannel systems, etc.
An application of sparse inversion on the calculation of the inverse data space of geophysical data
Saragiotis, Christos
2011-07-01
Multiple reflections as observed in seismic reflection measurements often hide arrivals from the deeper target reflectors and need to be removed. The inverse data space provides a natural separation of primaries and surface-related multiples, as the surface multiples map onto the area around the origin while the primaries map elsewhere. However, the calculation of the inverse data is far from trivial as theory requires infinite time and offset recording. Furthermore regularization issues arise during inversion. We perform the inversion by minimizing the least-squares norm of the misfit function and by constraining the 1 norm of the solution, being the inverse data space. In this way a sparse inversion approach is obtained. We show results on field data with an application to surface multiple removal. © 2011 IEEE.
Chromatid Painting for Chromosomal Inversion Detection, Phase II
National Aeronautics and Space Administration — We propose the continued development of a novel approach to the detection of chromosomal inversions. Transmissible chromosome aberrations (translocations and...
Directory of Open Access Journals (Sweden)
D. Pillai
2016-08-01
Full Text Available Currently, 52 % of the world's population resides in urban areas and as a consequence, approximately 70 % of fossil fuel emissions of CO2 arise from cities. This fact, in combination with large uncertainties associated with quantifying urban emissions due to lack of appropriate measurements, makes it crucial to obtain new measurements useful to identify and quantify urban emissions. This is required, for example, for the assessment of emission mitigation strategies and their effectiveness. Here, we investigate the potential of a satellite mission like Carbon Monitoring Satellite (CarbonSat which was proposed to the European Space Agency (ESA to retrieve the city emissions globally, taking into account a realistic description of the expected retrieval errors, the spatiotemporal distribution of CO2 fluxes, and atmospheric transport. To achieve this, we use (i a high-resolution modelling framework consisting of the Weather Research Forecasting model with a greenhouse gas module (WRF-GHG, which is used to simulate the atmospheric observations of column-averaged CO2 dry air mole fractions (XCO2, and (ii a Bayesian inversion method to derive anthropogenic CO2 emissions and their errors from the CarbonSat XCO2 observations. We focus our analysis on Berlin, Germany using CarbonSat's cloud-free overpasses for 1 reference year. The dense (wide swath CarbonSat simulated observations with high spatial resolution (approximately 2 km × 2 km permits one to map the city CO2 emission plume with a peak enhancement of typically 0.8–1.35 ppm relative to the background. By performing a Bayesian inversion, it is shown that the random error (RE of the retrieved Berlin CO2 emission for a single overpass is typically less than 8–10 Mt CO2 yr−1 (about 15–20 % of the total city emission. The range of systematic errors (SEs of the retrieved fluxes due to various sources of error (measurement, modelling, and inventories is also
An inverse method for radiation transport
Energy Technology Data Exchange (ETDEWEB)
Favorite, J. A. (Jeffrey A.); Sanchez, R. (Richard)
2004-01-01
Adjoint functions have been used with forward functions to compute gradients in implicit (iterative) solution methods for inverse problems in optical tomography, geoscience, thermal science, and other fields, but only once has this approach been used for inverse solutions to the Boltzmann transport equation. In this paper, this approach is used to develop an inverse method that requires only angle-independent flux measurements, rather than angle-dependent measurements as was done previously. The method is applied to a simplified form of the transport equation that does not include scattering. The resulting procedure uses measured values of gamma-ray fluxes of discrete, characteristic energies to determine interface locations in a multilayer shield. The method was implemented with a Newton-Raphson optimization algorithm, and it worked very well in numerical one-dimensional spherical test cases. A more sophisticated optimization method would better exploit the potential of the inverse 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.
The factorization method for inverse problems
Kirsch, Andreas
2008-01-01
The factorization method is a relatively new method for solving certain types of inverse scattering problems and problems in tomography. Aimed at students and researchers in Applied Mathematics, Physics and Engineering, this text introduces the reader to this promising approach for solving important classes of inverse problems. The wide applicability of this method is discussed by choosing typical examples, such as inverse scattering problems for the scalar Helmholtz equation, ascattering problem for Maxwell's equation, and a problem in impedance and optical tomography. The last section of the
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
Nie, Xiaokai; Coca, Daniel
2018-01-01
The paper introduces a matrix-based approach to estimate the unique one-dimensional discrete-time dynamical system that generated a given sequence of probability density functions whilst subjected to an additive stochastic perturbation with known density.
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.)
Submucous Myoma Induces Uterine Inversion
Directory of Open Access Journals (Sweden)
Yu-Li Chen
2006-06-01
Conclusion: Nonpuerperal inversion of the uterus is rarely encountered by gynecologists. Diagnosis of uterine inversion is often not easy and imaging studies might be helpful. Surgical treatment is the method of choice in nonpuerperal uterine inversion.
Energy Technology Data Exchange (ETDEWEB)
Carlos Torres-Verdin; Mrinal K. Sen
2004-03-01
The present report summarizes the work carried out between September 30, 2002 and August 30, 2003 under DOE research contract No. DE-FC26-00BC15305. During the third year of work for this project we focused primarily on improving the efficiency of inversion algorithms and on developing algorithms for direct estimation of petrophysical parameters. The full waveform inversion algorithm for elastic property estimation was tested rigorously on a personal computer cluster. For sixteen nodes on the cluster the parallel algorithm was found to be scalable with a near linear speedup. This enabled us to invert a 2D seismic line in less than five hours of CPU time. We were invited to write a paper on our results that was subsequently accepted for publication. We also carried out a rigorous study to examine the sensitivity and resolution of seismic data to petrophysical parameters. In other words, we developed a full waveform inversion algorithm that estimates petrophysical parameters such as porosity and saturation from pre-stack seismic waveform data. First we used a modified Biot-Gassmann equation to relate petrophysical parameters to elastic parameters. The transformation was validated with a suite of well logs acquired in the deepwater Gulf of Mexico. As a part of this study, we carried out a sensitivity analysis and found that the porosity is very well resolved while the fluid saturation remains insensitive to seismic wave amplitudes. Finally we conducted a joint inversion of pre-stack seismic waveform and production history data. To overcome the computational difficulties we used a simpler waveform modeling algorithm together with an efficient subspace approach. The algorithm was tested on a realistic synthetic data set. We observed that the use of pre-stack seismic data helps tremendously to improve horizontal resolution of porosity maps. Finally, we submitted four publications to refereed technical journals, two refereed extended abstracts to technical conferences
Inverse Kinematics With Closed Form Solution For Denso Robot Manipulator
Directory of Open Access Journals (Sweden)
Ikhsan Eka Prasetia
2015-03-01
Full Text Available In this paper, the forward kinematics and inverse kinematics used on the Denso robot manipulator which has a 6-DOF. The forward kinematics will result in the desired position by end-effector, while inverse kinematics produce angel on each joint. Inverse kinematics problem are very difficult, therefor to obtain the solution of inverse kinematics using closed form solution with geometry approach. The simulation result obtained from forward kinematics and inverse kinematics is determining desired position by Denso robot manipulator. Forward kinematics produce the desired position by the end-effector. Inverse kinematics produce joint angle, where the inverse kinematics produce eight conditions obtained from closed form solution with geometry approach to reach the desired position by the end-effector.
Partridge, D.G.; Vrugt, J.A.; Tunved, P.; Ekman, A.M.L.; Struthers, H.; Sorooshian, A.
2012-01-01
This paper presents a novel approach to investigate cloud-aerosol interactions by coupling a Markov Chain Monte Carlo (MCMC) algorithm to a pseudo-adiabatic cloud parcel model. Despite the number of numerical cloud-aerosol sensitivity studies previously conducted few have used statistical analysis
Inverse problem in transformation optics
DEFF Research Database (Denmark)
Novitsky, Andrey
2011-01-01
. We offer the solution of some sort of inverse problem: starting from the fields in the invisibility cloak we directly derive the permittivity and permeability tensors of the cloaking shell. This approach can be useful for finding material parameters for the specified electromagnetic fields......The straightforward method of transformation optics implies that one starts from the coordinate transformation and determines the Jacobian matrix, the fields and material parameters of the cloak. However, the coordinate transformation appears as an optional function: it is not necessary to know it...... in the cloaking shell without knowing the coordinate transformation....
Speaker independent acoustic-to-articulatory inversion
Ji, An
Acoustic-to-articulatory inversion, the determination of articulatory parameters from acoustic signals, is a difficult but important problem for many speech processing applications, such as automatic speech recognition (ASR) and computer aided pronunciation training (CAPT). In recent years, several approaches have been successfully implemented for speaker dependent models with parallel acoustic and kinematic training data. However, in many practical applications inversion is needed for new speakers for whom no articulatory data is available. In order to address this problem, this dissertation introduces a novel speaker adaptation approach called Parallel Reference Speaker Weighting (PRSW), based on parallel acoustic and articulatory Hidden Markov Models (HMM). This approach uses a robust normalized articulatory space and palate referenced articulatory features combined with speaker-weighted adaptation to form an inversion mapping for new speakers that can accurately estimate articulatory trajectories. The proposed PRSW method is evaluated on the newly collected Marquette electromagnetic articulography -- Mandarin Accented English (EMA-MAE) corpus using 20 native English speakers. Cross-speaker inversion results show that given a good selection of reference speakers with consistent acoustic and articulatory patterns, the PRSW approach gives good speaker independent inversion performance even without kinematic training data.
Atmospheric inverse modeling via sparse reconstruction
Directory of Open Access Journals (Sweden)
N. Hase
2017-10-01
Full Text Available Many applications in atmospheric science involve ill-posed inverse problems. A crucial component of many inverse problems is the proper formulation of a priori knowledge about the unknown parameters. In most cases, this knowledge is expressed as a Gaussian prior. This formulation often performs well at capturing smoothed, large-scale processes but is often ill equipped to capture localized structures like large point sources or localized hot spots. Over the last decade, scientists from a diverse array of applied mathematics and engineering fields have developed sparse reconstruction techniques to identify localized structures. In this study, we present a new regularization approach for ill-posed inverse problems in atmospheric science. It is based on Tikhonov regularization with sparsity constraint and allows bounds on the parameters. We enforce sparsity using a dictionary representation system. We analyze its performance in an atmospheric inverse modeling scenario by estimating anthropogenic US methane (CH4 emissions from simulated atmospheric measurements. Different measures indicate that our sparse reconstruction approach is better able to capture large point sources or localized hot spots than other methods commonly used in atmospheric inversions. It captures the overall signal equally well but adds details on the grid scale. This feature can be of value for any inverse problem with point or spatially discrete sources. We show an example for source estimation of synthetic methane emissions from the Barnett shale formation.
Atmospheric inverse modeling via sparse reconstruction
Hase, Nils; Miller, Scot M.; Maaß, Peter; Notholt, Justus; Palm, Mathias; Warneke, Thorsten
2017-10-01
Many applications in atmospheric science involve ill-posed inverse problems. A crucial component of many inverse problems is the proper formulation of a priori knowledge about the unknown parameters. In most cases, this knowledge is expressed as a Gaussian prior. This formulation often performs well at capturing smoothed, large-scale processes but is often ill equipped to capture localized structures like large point sources or localized hot spots. Over the last decade, scientists from a diverse array of applied mathematics and engineering fields have developed sparse reconstruction techniques to identify localized structures. In this study, we present a new regularization approach for ill-posed inverse problems in atmospheric science. It is based on Tikhonov regularization with sparsity constraint and allows bounds on the parameters. We enforce sparsity using a dictionary representation system. We analyze its performance in an atmospheric inverse modeling scenario by estimating anthropogenic US methane (CH4) emissions from simulated atmospheric measurements. Different measures indicate that our sparse reconstruction approach is better able to capture large point sources or localized hot spots than other methods commonly used in atmospheric inversions. It captures the overall signal equally well but adds details on the grid scale. This feature can be of value for any inverse problem with point or spatially discrete sources. We show an example for source estimation of synthetic methane emissions from the Barnett shale formation.
Inverse Doppler Effects in Broadband Acoustic Metamaterials.
Zhai, S L; Zhao, X P; Liu, S; Shen, F L; Li, L L; Luo, C R
2016-08-31
The Doppler effect refers to the change in frequency of a wave source as a consequence of the relative motion between the source and an observer. Veselago theoretically predicted that materials with negative refractions can induce inverse Doppler effects. With the development of metamaterials, inverse Doppler effects have been extensively investigated. However, the ideal material parameters prescribed by these metamaterial design approaches are complex and also challenging to obtain experimentally. Here, we demonstrated a method of designing and experimentally characterising arbitrary broadband acoustic metamaterials. These omni-directional, double-negative, acoustic metamaterials are constructed with 'flute-like' acoustic meta-cluster sets with seven double meta-molecules; these metamaterials also overcome the limitations of broadband negative bulk modulus and mass density to provide a region of negative refraction and inverse Doppler effects. It was also shown that inverse Doppler effects can be detected in a flute, which has been popular for thousands of years in Asia and Europe.
Inverse scale space decomposition
DEFF Research Database (Denmark)
Schmidt, Marie Foged; Benning, Martin; Schönlieb, Carola-Bibiane
2018-01-01
We investigate the inverse scale space flow as a decomposition method for decomposing data into generalised singular vectors. We show that the inverse scale space flow, based on convex and even and positively one-homogeneous regularisation functionals, can decompose data represented...... by the application of a forward operator to a linear combination of generalised singular vectors into its individual singular vectors. We verify that for this decomposition to hold true, two additional conditions on the singular vectors are sufficient: orthogonality in the data space and inclusion of partial sums...... of the subgradients of the singular vectors in the subdifferential of the regularisation functional at zero. We also address the converse question of when the inverse scale space flow returns a generalised singular vector given that the initial data is arbitrary (and therefore not necessarily in the range...
Direct and inverse scattering for viscoelastic media
International Nuclear Information System (INIS)
Ammicht, E.; Corones, J.P.; Krueger, R.J.
1987-01-01
A time domain approach to direct and inverse scattering problems for one-dimensional viscoelastic media is presented. Such media can be characterized as having a constitutive relation between stress and strain which involves the past history of the strain through a memory function, the relaxation modulus. In the approach in this article, the relaxation modulus of a material is shown to be related to the reflection properties of the material. This relation provides a constructive algorithm for direct and inverse scattering problems. A numerical implementation of this algorithm is tested on several problems involving realistic relaxation moduli
BOOK REVIEW: Inverse Problems. Activities for Undergraduates
Yamamoto, Masahiro
2003-06-01
This book is a valuable introduction to inverse problems. In particular, from the educational point of view, the author addresses the questions of what constitutes an inverse problem and how and why we should study them. Such an approach has been eagerly awaited for a long time. Professor Groetsch, of the University of Cincinnati, is a world-renowned specialist in inverse problems, in particular the theory of regularization. Moreover, he has made a remarkable contribution to educational activities in the field of inverse problems, which was the subject of his previous book (Groetsch C W 1993 Inverse Problems in the Mathematical Sciences (Braunschweig: Vieweg)). For this reason, he is one of the most qualified to write an introductory book on inverse problems. Without question, inverse problems are important, necessary and appear in various aspects. So it is crucial to introduce students to exercises in inverse problems. However, there are not many introductory books which are directly accessible by students in the first two undergraduate years. As a consequence, students often encounter diverse concrete inverse problems before becoming aware of their general principles. The main purpose of this book is to present activities to allow first-year undergraduates to learn inverse theory. To my knowledge, this book is a rare attempt to do this and, in my opinion, a great success. The author emphasizes that it is very important to teach inverse theory in the early years. He writes; `If students consider only the direct problem, they are not looking at the problem from all sides .... The habit of always looking at problems from the direct point of view is intellectually limiting ...' (page 21). The book is very carefully organized so that teachers will be able to use it as a textbook. After an introduction in chapter 1, sucessive chapters deal with inverse problems in precalculus, calculus, differential equations and linear algebra. In order to let one gain some insight
Sieberling, S.; Chu, Q.P.; Mulder, J.A.
2010-01-01
This paper presents a flight control strategy based on nonlinear dynamic inversion. The approach presented, called incremental nonlinear dynamic inversion, uses properties of general mechanical systems and nonlinear dynamic inversion by feeding back angular accelerations. Theoretically, feedback of angular accelerations eliminates sensitivity to model mismatch, greatly increasing the robust performance of the system compared with conventional nonlinear dynamic inversion. However, angular acce...
Inversion assuming weak scattering
DEFF Research Database (Denmark)
Xenaki, Angeliki; Gerstoft, Peter; Mosegaard, Klaus
2013-01-01
due to the complex nature of the field. A method based on linear inversion is employed to infer information about the statistical properties of the scattering field from the obtained cross-spectral matrix. A synthetic example based on an active high-frequency sonar demonstrates that the proposed...
Broekhuis, H.
2005-01-01
This article aims at reformulating in more current terms Hoekstra and Mulder’s (1990) analysis of the Locative Inversion (LI) construction. The new proposal is crucially based on the assumption that Small Clause (SC) predicates agree with their external argument in phi-features, which may be
Energy Technology Data Exchange (ETDEWEB)
Shin, Chang Soo; Park, Keun Pil [Korea Inst. of Geology Mining and Materials, Taejon (Korea, Republic of); Suh, Jung Hee; Hyun, Byung Koo; Shin, Sung Ryul [Seoul National University, Seoul (Korea, Republic of)
1995-12-01
The seismic reflection exploration technique which is one of the geophysical methods for oil exploration became effectively to image the subsurface structure with rapid development of computer. However, the imagining of subsurface based on the conventional data processing is almost impossible to obtain the information on physical properties of the subsurface such as velocity and density. Since seismic data are implicitly function of velocities of subsurface, it is necessary to develop the inversion method that can delineate the velocity structure using seismic topography and waveform inversion. As a tool to perform seismic inversion, seismic forward modeling program using ray tracing should be developed. In this study, we have developed the algorithm that calculate the travel time of the complex geologic structure using shooting ray tracing by subdividing the geologic model into blocky structure having the constant velocity. With the travel time calculation, the partial derivatives of travel time can be calculated efficiently without difficulties. Since the current ray tracing technique has a limitation to calculate the travel times for extremely complex geologic model, our aim in the future is to develop the powerful ray tracer using the finite element technique. After applying the pseudo waveform inversion to the seismic data of Korea offshore, we can obtain the subsurface velocity model and use the result in bring up the quality of the seismic data processing. If conventional seismic data processing and seismic interpretation are linked with this inversion technique, the high quality of seismic data processing can be expected to image the structure of the subsurface. Future research area is to develop the powerful ray tracer of ray tracing which can calculate the travel times for the extremely complex geologic model. (author). 39 refs., 32 figs., 2 tabs.
Hayes, Daniel J.; Turner, David P.; Stinson, Graham; McGuire, A. David; Wei, Yaxing; West, Tristram O.; Heath, Linda S.; de Jong, Bernardus; McConkey, Brian G.; Birdsey, Richard A.; Kurz, Werner A.; Jacobson, Andrew R.; Huntzinger, Deborah N.; Pan, Yude; Post, W. Mac; Cook, Robert B.
2012-01-01
We develop an approach for estimating net ecosystem exchange (NEE) using inventory-based information over North America (NA) for a recent 7-year period (ca. 2000–2006). The approach notably retains information on the spatial distribution of NEE, or the vertical exchange between land and atmosphere of all non-fossil fuel sources and sinks of CO2, while accounting for lateral transfers of forest and crop products as well as their eventual emissions. The total NEE estimate of a -327 ± 252 TgC yr-1 sink for NA was driven primarily by CO2 uptake in the Forest Lands sector (-248 TgC yr-1), largely in the Northwest and Southeast regions of the US, and in the Crop Lands sector (-297 TgC yr-1), predominantly in the Midwest US states. These sinks are counteracted by the carbon source estimated for the Other Lands sector (+218 TgC yr-1), where much of the forest and crop products are assumed to be returned to the atmosphere (through livestock and human consumption). The ecosystems of Mexico are estimated to be a small net source (+18 TgC yr-1) due to land use change between 1993 and 2002. We compare these inventory-based estimates with results from a suite of terrestrial biosphere and atmospheric inversion models, where the mean continental-scale NEE estimate for each ensemble is -511 TgC yr-1 and -931 TgC yr-1, respectively. In the modeling approaches, all sectors, including Other Lands, were generally estimated to be a carbon sink, driven in part by assumed CO2 fertilization and/or lack of consideration of carbon sources from disturbances and product emissions. Additional fluxes not measured by the inventories, although highly uncertain, could add an additional -239 TgC yr-1 to the inventory-based NA sink estimate, thus suggesting some convergence with the modeling approaches.
Esfandiari, Saeed; Bahadoran, Zahra; Mirmiran, Parvin; Tohidi, Maryam; Azizi, Fereidoun
2017-09-01
Beneficial effects of Dietary Approaches to Stop Hypertension trial (DASH) diet on features of metabolic syndrome have been indicated in clinical studies. In this study, we aimed to assess possible association of DASH diet score and the risk of insulin resistance in an Iranian population. In this prospective cohort study, 927 adult men and women, were recruited. Fasting serum insulin and glucose were measured at baseline and again after 3 years. Usual dietary intakes were measured using a validated 168 item semi-quantitative food frequency questionnaire and DASH score was calculated. Multivariate logistic regression models were used to estimate the occurrence of the insulin resistance across tertiles of DASH diet. To investigate possible superiority of DASH score over other scoring system, we also assessed the association of healthy eating index and Mediterranean diet score with the risk of insulin resistance. Mean age of the participants was 40.34 ± 12.14 years old. The incidence rate of insulin resistance was 12.8%. Participants with higher DASH score had also higher intakes of potassium, calcium, magnesium, fiber, and lower intakes of cholesterol ( p DASH score and the risk insulin resistance in the highest compared to the lowest tertile (OR = 0.39, 95% CI = 0.20-0.76, p for trend = 0.007). There was no significant association between healthy eating index and Mediterranean diet score with the incidence of insulin resistance. In conclusion, adherence to the DASH dietary pattern may be associated with a lower risk of insulin resistance and its related metabolic outcomes.
Inversion of GPS meteorology data
Directory of Open Access Journals (Sweden)
K. Hocke
Full Text Available The GPS meteorology (GPS/MET experiment, led by the Universities Corporation for Atmospheric Research (UCAR, consists of a GPS receiver aboard a low earth orbit (LEO satellite which was launched on 3 April 1995. During a radio occultation the LEO satellite rises or sets relative to one of the 24 GPS satellites at the Earth's horizon. Thereby the atmospheric layers are successively sounded by radio waves which propagate from the GPS satellite to the LEO satellite. From the observed phase path increases, which are due to refraction of the radio waves by the ionosphere and the neutral atmosphere, the atmospheric parameter refractivity, density, pressure and temperature are calculated with high accuracy and resolution (0.5–1.5 km. In the present study, practical aspects of the GPS/MET data analysis are discussed. The retrieval is based on the Abelian integral inversion of the atmospheric bending angle profile into the refractivity index profile. The problem of the upper boundary condition of the Abelian integral is described by examples. The statistical optimization approach which is applied to the data above 40 km and the use of topside bending angle profiles from model atmospheres stabilize the inversion. The retrieved temperature profiles are compared with corresponding profiles which have already been calculated by scientists of UCAR and Jet Propulsion Laboratory (JPL, using Abelian integral inversion too. The comparison shows that in some cases large differences occur (5 K and more. This is probably due to different treatment of the upper boundary condition, data runaways and noise. Several temperature profiles with wavelike structures at tropospheric and stratospheric heights are shown. While the periodic structures at upper stratospheric heights could be caused by residual errors of the ionospheric correction method, the periodic temperature fluctuations at heights below 30 km are most likely caused by atmospheric waves (vertically
Miles, Evan; Steiner, Jakob; Brun, Fanny; Detert, Martin; Buri, Pascal; Pellicciotti, Francesca
2016-04-01
Aerodynamic surface roughness is an essential parameter in surface energy balance studies. While actual measurements on bare ice glaciers are rare, a wide range of literature values exist for ice and snow surfaces. There are very few values suggested for debris covered glaciers and actual measurements are even scarcer - studies instead optimize z0 or use a reference value. The increased use of photogrammetry on glaciers provides an opportunity to characterize the range of z0 values meaningful for debris-covered glaciers. We apply Agisoft's Structure-from-Motion process chain to produce high resolution DEMs for five 1m x 1m plots (1mm resolution) with differing grain-size distributions, as well as a large ~180m x ~180m depression (5cm) on Lirung Glacier in the Nepalese Himalayas. For each plot, we calculate z0 according to transect-based microtopographic parameterisations. We compare individual-transect z0 estimates based on profile position and direction, and develop a grid version of the algorithms aggregating height data from all bidirectional transects. This grid approach is applied to our larger DEM to characterize the variability of z0 across the study site for each algorithm. For the plot DEMs, z0 estimated by any algorithm varies by an order of magnitude based on transect position. Although the algorithms reproduce the same variability among transects and plots, z0 estimates vary by an order of magnitude between algorithms. For any algorithm, however, we find minimal difference between cross- and down-glacier profile directions. At the basin scale, results from different algorithms are strongly correlated and results are more closely clustered with the exception of the Rounce (2015) algorithm, while any algorithm's values range by two orders of magnitude across the study depression. The Rounce algorithm consistently produced the highest z0 values, while the Lettau (1969) and Munro (1989) methods produced the lowest values, and use of the Nield (2013
Electrochemically driven emulsion inversion
International Nuclear Information System (INIS)
Johans, Christoffer; Kontturi, Kyoesti
2007-01-01
It is shown that emulsions stabilized by ionic surfactants can be inverted by controlling the electrical potential across the oil-water interface. The potential dependent partitioning of sodium dodecyl sulfate (SDS) was studied by cyclic voltammetry at the 1,2-dichlorobenzene|water interface. In the emulsion the potential control was achieved by using a potential-determining salt. The inversion of a 1,2-dichlorobenzene-in-water (O/W) emulsion stabilized by SDS was followed by conductometry as a function of added tetrapropylammonium chloride. A sudden drop in conductivity was observed, indicating the change of the continuous phase from water to 1,2-dichlorobenzene, i.e. a water-in-1,2-dichlorobenzene emulsion was formed. The inversion potential is well in accordance with that predicted by the hydrophilic-lipophilic deviation if the interfacial potential is appropriately accounted for
DEFF Research Database (Denmark)
Gale, A.S.; Surlyk, Finn; Anderskouv, Kresten
2013-01-01
Evidence from regional stratigraphical patterns in Santonian−Campanian chalk is used to infer the presence of a very broad channel system (5 km across) with a depth of at least 50 m, running NNW−SSE across the eastern Isle of Wight; only the western part of the channel wall and fill is exposed. W......−Campanian chalks in the eastern Isle of Wight, involving penecontemporaneous tectonic inversion of the underlying basement structure, are rejected....
Hybrid inverse design method for nonlifting bodies in incompressible flow
CSIR Research Space (South Africa)
Broughton, BA
2006-11-01
Full Text Available A methodology for the inverse design of non-lifting axisymmetric bodies in compressible flow is presented. In this method, an inverse design approach based on conformal mapping is used to design a set of airfoils in isolation. These airfoils...
Surface Vibration Reconstruction using Inverse Numerical Acoustics
Directory of Open Access Journals (Sweden)
F. Martinus
2003-05-01
Full Text Available This paper explores the use of inverse numerical acoustics to reconstruct the surface vibration of a noise source. Inverse numerical acoustics is mainly used for source identification. This approach uses the measured sound pressure at a set of field points and the Helmholtz integral equation to reconstruct the normal surface velocity. The number of sound pressure measurements is considerably less than the number of surface vibration nodes. An overview of inverse numerical acoustics is presented and compared with other holography techniques such as nearfield acoustical holography and the Helmholtz equation least squares method. In order to obtain an acceptable reproduction of the surface vibration, several critical factors such as the field point selection and the effect of experimental errors have to be handled properly. Other practical considerations such as the use of few measured velocities and regularization techniques will also be presented. Examples will include a diesel engine, a transmission housing and an engine cover.
FAST INVERSION OF SOLAR Ca II SPECTRA
International Nuclear Information System (INIS)
Beck, C.; Choudhary, D. P.; Rezaei, R.; Louis, R. E.
2015-01-01
We present a fast (<<1 s per profile) inversion code for solar Ca II lines. The code uses an archive of spectra that are synthesized prior to the inversion under the assumption of local thermodynamic equilibrium (LTE). We show that it can be successfully applied to spectrograph data or more sparsely sampled spectra from two-dimensional spectrometers. From a comparison to a non-LTE inversion of the same set of spectra, we derive a first-order non-LTE correction to the temperature stratifications derived in the LTE approach. The correction factor is close to unity up to log τ ∼ –3 and increases to values of 2.5 and 4 at log τ = –6 in the quiet Sun and the umbra, respectively
Applications of inverse and algebraic scattering theories
International Nuclear Information System (INIS)
Amos, K.
1997-01-01
Inverse scattering theories, algebraic scattering theory and exactly solvable scattering potentials are diverse ways by which scattering potentials can be defined from S-functions specified by fits to fixed energy, quantal scattering data. Applications have been made in nuclear (heavy ion and nucleon-nucleus scattering), atomic and molecular (electron scattering from simple molecules) systems. Three inverse scattering approaches are considered in detail; the semiclassical WKB and fully quantal Lipperheide-Fiedeldey method, than algebraic scattering theory is applied to heavy ion scattering and finally the exactly solvable Ginocchio potentials. Some nuclear results are ambiguous but the atomic and molecular inversion potentials are in good agreement with postulated forms. 21 refs., 12 figs
RUMBLE Technical Report on Inversion Models
Simons, Dick G.; Ainslie, Michael A.; Muller, Simonette H. E.; Boek, Wilco
2002-06-01
The performance of long range low frequency active sonar (LFAS) systems in shallow water is very sensitive to the properties of the sea bed, because of the impact of these on propagation, reverberation and (to a lesser extent) ambient noise. Direct measurement of sea bed parameters using cores or grab samples is impractical for covering a wide area, and instead we consider the possibility of using the LFAS system itself to measure its operating environment. The advantages of this approach are that it exploits existing (or planned) equipment and potentially offers a wide coverage. Geo-acoustic inversion methods are reviewed, with particular consideration for the problems associated with inversion of reverberation data. Three global optimisation methods are described, known as "simulated annealing", "genetic algorithms" and "differential evolution". The Levenberg-Marquardt and downhill simplex local methods are also described. The advantages and disadvantages of each individual method, as well as some hybrid combinations, are discussed in the context of geo-acoustic inversion. A new inversion method has been developed that exploits both the shape and height of the reverberation vs time curve to obtain information about the sea bed reflection loss and scattering strength separately. Tests on synthetic reverberation data show that the inversion method is able to extract parameters representing reflection loss and scattering strength, but cannot always unambiguously separate the effects of sediment sound speed and attenuation. The method is robust to small mismatches in water depth, sonar depth, sediment sound speed gradient and wind speed.
Alternating minimisation for glottal inverse filtering
Rodrigo Bleyer, Ismael; Lybeck, Lasse; Auvinen, Harri; Airaksinen, Manu; Alku, Paavo; Siltanen, Samuli
2017-06-01
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 (F0). The results show the competitive performance of the new method: With high F0, the reconstruction quality is better than that of IAIF and close to MCMC-GIF while reducing the computational complexity by two orders of magnitude.
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...... ability to produce efficient search algorithms. Such algorithms may be completely problem-independent (which is the case for the so-called 'meta-heuristics' or 'blind-search' algorithms), or they may be designed with the structure of the concrete problem in mind. We show that pure meta...
Stochastic forward and inverse groundwater flow and solute transport modeling
Janssen, G.M.C.M.
2008-01-01
Keywords: calibration, inverse modeling, stochastic modeling, nonlinear biodegradation, stochastic-convective, advective-dispersive, travel time, network design, non-Gaussian distribution, multimodal distribution, representers
This thesis offers three new approaches that contribute
Inverse planning for x-ray rotation therapy: a general solution of the inverse problem
International Nuclear Information System (INIS)
Oelfke, U.; Bortfeld, T.
1999-01-01
Rotation therapy with photons is currently under investigation for the delivery of intensity modulated radiotherapy (IMRT). An analytical approach for inverse treatment planning of this radiotherapy technique is described. The inverse problem for the delivery of arbitrary 2D dose profiles is first formulated and then solved analytically. In contrast to previously applied strategies for solving the inverse problem, it is shown that the most general solution for the fluence profiles consists of two independent solutions of different parity. A first analytical expression for both fluence profiles is derived. The mathematical derivation includes two different strategies, an elementary expansion of fluence and dose into polynomials and a more practical approach in terms of Fourier transforms. The obtained results are discussed in the context of previous work on this problem. (author)
International Nuclear Information System (INIS)
Hicks, H.R.; Dory, R.A.; Holmes, J.A.
1983-01-01
We illustrate in some detail a 2D inverse-equilibrium solver that was constructed to analyze tokamak configurations and stellarators (the latter in the context of the average method). To ensure that the method is suitable not only to determine equilibria, but also to provide appropriately represented data for existing stability codes, it is important to be able to control the Jacobian, tilde J is identical to delta(R,Z)/delta(rho, theta). The form chosen is tilde J = J 0 (rho)R/sup l/rho where rho is a flux surface label, and l is an integer. The initial implementation is for a fixed conducting-wall boundary, but the technique can be extended to a free-boundary model
Crestel, Benjamin; Alexanderian, Alen; Stadler, Georg; Ghattas, Omar
2017-07-01
The computational cost of solving an inverse problem governed by PDEs, using multiple experiments, increases linearly with the number of experiments. A recently proposed method to decrease this cost uses only a small number of random linear combinations of all experiments for solving the inverse problem. This approach applies to inverse problems where the PDE solution depends linearly on the right-hand side function that models the experiment. As this method is stochastic in essence, the quality of the obtained reconstructions can vary, in particular when only a small number of combinations are used. We develop a Bayesian formulation for the definition and computation of encoding weights that lead to a parameter reconstruction with the least uncertainty. We call these weights A-optimal encoding weights. Our framework applies to inverse problems where the governing PDE is nonlinear with respect to the inversion parameter field. We formulate the problem in infinite dimensions and follow the optimize-then-discretize approach, devoting special attention to the discretization and the choice of numerical methods in order to achieve a computational cost that is independent of the parameter discretization. We elaborate our method for a Helmholtz inverse problem, and derive the adjoint-based expressions for the gradient of the objective function of the optimization problem for finding the A-optimal encoding weights. The proposed method is potentially attractive for real-time monitoring applications, where one can invest the effort to compute optimal weights offline, to later solve an inverse problem repeatedly, over time, at a fraction of the initial cost.
Holocaust inversion and contemporary antisemitism.
Klaff, Lesley D
2014-01-01
One of the cruellest aspects of the new antisemitism is its perverse use of the Holocaust as a stick to beat 'the Jews'. This article explains the phenomenon of 'Holocaust Inversion', which involves an 'inversion of reality' (the Israelis are cast as the 'new' Nazis and the Palestinians as the 'new' Jews) and an 'inversion of morality' (the Holocaust is presented as a moral lesson for, or even a moral indictment of, 'the Jews'). Holocaust inversion is a form of soft-core Holocaust denial, yet...
Classical geometry Euclidean, transformational, inversive, and projective
Leonard, I E; Liu, A C F; Tokarsky, G W
2014-01-01
Features the classical themes of geometry with plentiful applications in mathematics, education, engineering, and science Accessible and reader-friendly, Classical Geometry: Euclidean, Transformational, Inversive, and Projective introduces readers to a valuable discipline that is crucial to understanding bothspatial relationships and logical reasoning. Focusing on the development of geometric intuitionwhile avoiding the axiomatic method, a problem solving approach is encouraged throughout. The book is strategically divided into three sections: Part One focuses on Euclidean geometry, which p
Inverse feasibility problems of the inverse maximum flow problems
Indian Academy of Sciences (India)
A linear time method to decide if any inverse maximum ﬂow (denoted General Inverse Maximum Flow problems (IMFG)) problem has solution is deduced. If IMFG does not have solution, methods to transform IMFG into a feasible problem are presented. The methods consist of modifying as little as possible the restrictions to ...
Inverse feasibility problems of the inverse maximum flow problems
Indian Academy of Sciences (India)
199–209. c Indian Academy of Sciences. Inverse feasibility problems of the inverse maximum flow problems. ADRIAN DEACONU. ∗ and ELEONOR CIUREA. Department of Mathematics and Computer Science, Faculty of Mathematics and Informatics, Transilvania University of Brasov, Brasov, Iuliu Maniu st. 50,. Romania.
Seismic Waveform Inversion by Stochastic Optimization
Directory of Open Access Journals (Sweden)
Tristan van Leeuwen
2011-01-01
Full Text Available We explore the use of stochastic optimization methods for seismic waveform inversion. The basic principle of such methods is to randomly draw a batch of realizations of a given misfit function and goes back to the 1950s. The ultimate goal of such an approach is to dramatically reduce the computational cost involved in evaluating the misfit. Following earlier work, we introduce the stochasticity in waveform inversion problem in a rigorous way via a technique called randomized trace estimation. We then review theoretical results that underlie recent developments in the use of stochastic methods for waveform inversion. We present numerical experiments to illustrate the behavior of different types of stochastic optimization methods and investigate the sensitivity to the batch size and the noise level in the data. We find that it is possible to reproduce results that are qualitatively similar to the solution of the full problem with modest batch sizes, even on noisy data. Each iteration of the corresponding stochastic methods requires an order of magnitude fewer PDE solves than a comparable deterministic method applied to the full problem, which may lead to an order of magnitude speedup for waveform inversion in practice.
Modelling and inversion of local magnetic anomalies
International Nuclear Information System (INIS)
Quesnel, Y; Langlais, B; Sotin, C; Galdéano, A
2008-01-01
We present a method—named as MILMA for modelling and inversion of local magnetic anomalies—that combines forward and inverse modelling of aeromagnetic data to characterize both magnetization properties and location of unconstrained local sources. Parameters of simple-shape magnetized bodies (cylinder, prism or sphere) are first adjusted by trial and error to predict the signal. Their parameters provide a priori information for inversion of the measurements. Here, a generalized nonlinear approach with a least-squares criterion is adopted to seek the best parameters of the sphere (dipole). This inversion step allows the model to be more objectively adjusted to fit the magnetic signal. The validity of the MILMA method is demonstrated through synthetic and real cases using aeromagnetic measurements. Tests with synthetic data reveal accurate results in terms of depth source, whatever be the number of sources. The MILMA method is then used with real measurements to constrain the properties of the magnetized units of the Champtoceaux complex (France). The resulting parameters correlate with the crustal structure and properties revealed by other geological and geophysical surveys in the same area. The MILMA method can therefore be used to investigate the properties of poorly constrained lithospheric magnetized sources
Displacement parameter inversion for a novel electromagnetic underground displacement sensor.
Shentu, Nanying; Li, Qing; Li, Xiong; Tong, Renyuan; Shentu, Nankai; Jiang, Guoqing; Qiu, Guohua
2014-05-22
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.
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.
Centered Differential Waveform Inversion with Minimum Support Regularization
Kazei, Vladimir
2017-05-26
Time-lapse full-waveform inversion has two major challenges. The first one is the reconstruction of a reference model (baseline model for most of approaches). The second is inversion for the time-lapse changes in the parameters. Common model approach is utilizing the information contained in all available data sets to build a better reference model for time lapse inversion. Differential (Double-difference) waveform inversion allows to reduce the artifacts introduced into estimates of time-lapse parameter changes by imperfect inversion for the baseline-reference model. We propose centered differential waveform inversion (CDWI) which combines these two approaches in order to benefit from both of their features. We apply minimum support regularization commonly used with electromagnetic methods of geophysical exploration. We test the CDWI method on synthetic dataset with random noise and show that, with Minimum support regularization, it provides better resolution of velocity changes than with total variation and Tikhonov regularizations in time-lapse full-waveform inversion.
Inverse problem in hydrogeology
Carrera, Jesús; Alcolea, Andrés; Medina, Agustín; Hidalgo, Juan; Slooten, Luit J.
2005-03-01
The state of the groundwater inverse problem is synthesized. Emphasis is placed on aquifer characterization, where modelers have to deal with conceptual model uncertainty (notably spatial and temporal variability), scale dependence, many types of unknown parameters (transmissivity, recharge, boundary conditions, etc.), nonlinearity, and often low sensitivity of state variables (typically heads and concentrations) to aquifer properties. Because of these difficulties, calibration cannot be separated from the modeling process, as it is sometimes done in other fields. Instead, it should be viewed as one step in the process of understanding aquifer behavior. In fact, it is shown that actual parameter estimation methods do not differ from each other in the essence, though they may differ in the computational details. It is argued that there is ample room for improvement in groundwater inversion: development of user-friendly codes, accommodation of variability through geostatistics, incorporation of geological information and different types of data (temperature, occurrence and concentration of isotopes, age, etc.), proper accounting of uncertainty, etc. Despite this, even with existing codes, automatic calibration facilitates enormously the task of modeling. Therefore, it is contended that its use should become standard practice. L'état du problème inverse des eaux souterraines est synthétisé. L'accent est placé sur la caractérisation de l'aquifère, où les modélisateurs doivent jouer avec l'incertitude des modèles conceptuels (notamment la variabilité spatiale et temporelle), les facteurs d'échelle, plusieurs inconnues sur différents paramètres (transmissivité, recharge, conditions aux limites, etc.), la non linéarité, et souvent la sensibilité de plusieurs variables d'état (charges hydrauliques, concentrations) des propriétés de l'aquifère. A cause de ces difficultés, le calibrage ne peut êtreséparé du processus de modélisation, comme c'est le
Face inversion increases attractiveness.
Leder, Helmut; Goller, Juergen; Forster, Michael; Schlageter, Lena; Paul, Matthew A
2017-07-01
Assessing facial attractiveness is a ubiquitous, inherent, and hard-wired phenomenon in everyday interactions. As such, it has highly adapted to the default way that faces are typically processed: viewing faces in upright orientation. By inverting faces, we can disrupt this default mode, and study how facial attractiveness is assessed. Faces, rotated at 90 (tilting to either side) and 180°, were rated on attractiveness and distinctiveness scales. For both orientations, we found that faces were rated more attractive and less distinctive than upright faces. Importantly, these effects were more pronounced for faces rated low in upright orientation, and smaller for highly attractive faces. In other words, the less attractive a face was, the more it gained in attractiveness by inversion or rotation. Based on these findings, we argue that facial attractiveness assessments might not rely on the presence of attractive facial characteristics, but on the absence of distinctive, unattractive characteristics. These unattractive characteristics are potentially weighed against an individual, attractive prototype in assessing facial attractiveness. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Zhang, Dongliang
2013-01-01
To increase the illumination of the subsurface and to eliminate the dependency of FWI on the source wavelet, we propose multiples waveform inversion (MWI) that transforms each hydrophone into a virtual point source with a time history equal to that of the recorded data. These virtual sources are used to numerically generate downgoing wavefields that are correlated with the backprojected surface-related multiples to give the migration image. Since the recorded data are treated as the virtual sources, knowledge of the source wavelet is not required, and the subsurface illumination is greatly enhanced because the entire free surface acts as an extended source compared to the radiation pattern of a traditional point source. Numerical tests on the Marmousi2 model show that the convergence rate and the spatial resolution of MWI is, respectively, faster and more accurate then FWI. The potential pitfall with this method is that the multiples undergo more than one roundtrip to the surface, which increases attenuation and reduces spatial resolution. This can lead to less resolved tomograms compared to conventional FWI. The possible solution is to combine both FWI and MWI in inverting for the subsurface velocity distribution.
Coin tossing and Laplace inversion
Indian Academy of Sciences (India)
MS received 5 May 1999; revised 3 April 2000. Abstract. An analysis of exchangeable sequences of coin tossings leads to inversion formulae for Laplace transforms of probability measures. Keywords. Laplace inversion; moment problem; exchangeable probabilities. 1. Introduction. There is an intimate relationship between ...
Inverse problems for Maxwell's equations
Romanov, V G
1994-01-01
The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.
Inverse problems and uncertainty quantification
Litvinenko, Alexander
2013-12-18
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)— the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Package inspection using inverse diffraction
McAulay, Alastair D.
2008-08-01
More efficient cost-effective hand-held methods of inspecting packages without opening them are in demand for security. Recent new work in TeraHertz sources,1 millimeter waves, presents new possibilities. Millimeter waves pass through cardboard and styrofoam, common packing materials, and also pass through most materials except those with high conductivity like metals which block light and are easily spotted. Estimating refractive index along the path of the beam through the package from observations of the beam passing out of the package provides the necessary information to inspect the package and is a nonlinear problem. So we use a generalized linear inverse technique that we first developed for finding oil by reflection in geophysics.2 The computation assumes parallel slices in the packet of homogeneous material for which the refractive index is estimated. A beam is propagated through this model in a forward computation. The output is compared with the actual observations for the package and an update computed for the refractive indices. The loop is repeated until convergence. The approach can be modified for a reflection system or to include estimation of absorption.
Inverse Problems and Uncertainty Quantification
Litvinenko, Alexander
2014-01-06
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) - the propagation of uncertainty through a computational (forward) modelare strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Inversion of SAR data in active volcanic areas by optimization techniques
Nunnari, G.; Puglisi, G.; Guglielmino, F.
2005-01-01
International audience; The inversion problem concerns the identification of parameters of a volcanic source causing observable changes in ground deformation data recorded in volcanic areas. In particular, this paper deals with the inversion of ground deformation measured by using SAR (Synthetic Aperture Radar) interferometry and an inversion approach formulated in terms of an optimization problem is proposed. Based on this inversion scheme, it is shown that the problem of inverting ground de...
Directory of Open Access Journals (Sweden)
Calvez V.
2010-12-01
Full Text Available We consider the radiative transfer equation (RTE with reflection in a three-dimensional domain, infinite in two dimensions, and prove an existence result. Then, we study the inverse problem of retrieving the optical parameters from boundary measurements, with help of existing results by Choulli and Stefanov. This theoretical analysis is the framework of an attempt to model the color of the skin. For this purpose, a code has been developed to solve the RTE and to study the sensitivity of the measurements made by biophysicists with respect to the physiological parameters responsible for the optical properties of this complex, multi-layered material. On étudie l’équation du transfert radiatif (ETR dans un domaine tridimensionnel infini dans deux directions, et on prouve un résultat d’existence. On s’intéresse ensuite à la reconstruction des paramètres optiques à partir de mesures faites au bord, en s’appuyant sur des résultats de Choulli et Stefanov. Cette analyse sert de cadre théorique à un travail de modélisation de la couleur de la peau. Dans cette perspective, un code à été développé pour résoudre l’ETR et étudier la sensibilité des mesures effectuées par les biophysiciens par rapport aux paramètres physiologiques tenus pour responsables des propriétés optiques de ce complexe matériau multicouche.
Frnakenstein: multiple target inverse RNA folding
Directory of Open Access Journals (Sweden)
Lyngsø Rune B
2012-10-01
Full Text Available Abstract Background RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. Results In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Conclusions Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more
Computationally efficient Bayesian inference for inverse problems.
Energy Technology Data Exchange (ETDEWEB)
Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.
2007-10-01
Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.
Geostatistical regularization operators for geophysical inverse problems on irregular meshes
Jordi, C.; Doetsch, J.; Günther, T.; Schmelzbach, C.; Robertsson, J. OA
2018-05-01
Irregular meshes allow to include complicated subsurface structures into geophysical modelling and inverse problems. The non-uniqueness of these inverse problems requires appropriate regularization that can incorporate a priori information. However, defining regularization operators for irregular discretizations is not trivial. Different schemes for calculating smoothness operators on irregular meshes have been proposed. In contrast to classical regularization constraints that are only defined using the nearest neighbours of a cell, geostatistical operators include a larger neighbourhood around a particular cell. A correlation model defines the extent of the neighbourhood and allows to incorporate information about geological structures. We propose an approach to calculate geostatistical operators for inverse problems on irregular meshes by eigendecomposition of a covariance matrix that contains the a priori geological information. Using our approach, the calculation of the operator matrix becomes tractable for 3-D inverse problems on irregular meshes. We tested the performance of the geostatistical regularization operators and compared them against the results of anisotropic smoothing in inversions of 2-D surface synthetic electrical resistivity tomography (ERT) data as well as in the inversion of a realistic 3-D cross-well synthetic ERT scenario. The inversions of 2-D ERT and seismic traveltime field data with geostatistical regularization provide results that are in good accordance with the expected geology and thus facilitate their interpretation. In particular, for layered structures the geostatistical regularization provides geologically more plausible results compared to the anisotropic smoothness constraints.
Facies Constrained Elastic Full Waveform Inversion
Zhang, Z.
2017-05-26
Current efforts to utilize full waveform inversion (FWI) as a tool beyond acoustic imaging applications, for example for reservoir analysis, face inherent limitations on resolution and also on the potential trade-off between elastic model parameters. Adding rock physics constraints does help to mitigate these issues. However, current approaches to add such constraints are based on averaged type rock physics regularization terms. Since the true earth model consists of different facies, averaging over those facies naturally leads to smoothed models. To overcome this, we propose a novel way to utilize facies based constraints in elastic FWI. A so-called confidence map is calculated and updated at each iteration of the inversion using both the inverted models and the prior information. The numerical example shows that the proposed method can reduce the cross-talks and also can improve the resolution of inverted elastic properties.
Function representation with circle inversion map systems
Boreland, Bryson; Kunze, Herb
2017-01-01
The fractals literature develops the now well-known concept of local iterated function systems (using affine maps) with grey-level maps (LIFSM) as an approach to function representation in terms of the associated fixed point of the so-called fractal transform. While originally explored as a method to achieve signal (and 2-D image) compression, more recent work has explored various aspects of signal and image processing using this machinery. In this paper, we develop a similar framework for function representation using circle inversion map systems. Given a circle C with centre õ and radius r, inversion with respect to C transforms the point p˜ to the point p˜', such that p˜ and p˜' lie on the same radial half-line from õ and d(õ, p˜)d(õ, p˜') = r2, where d is Euclidean distance. We demonstrate the results with an example.
Inverse Kinematics of Concentric Tube Steerable Needles.
Sears, Patrick; Dupont, Pierre E
2007-01-01
Prior papers have introduced steerable needles composed of precurved concentric tubes. The curvature and extent of these needles can be controlled by the relative rotation and translation of the individual tubes. Under certain assumptions on the geometry and design of these needles, the forward kinematics problem can be solved in closed form by means of algebraic equations. The inverse kinematics problem, however, is not as straightforward owing to the nonlinear map between relative tube displacements and needle tip configuration as well as to the multiplicity of solutions as the number of tubes increases. This paper presents a general approach to solving the inverse kinematics problem using a pseudoinverse solution together with gradients of nullspace potential functions to enforce geometric and mechanical constraints.
Analog fault diagnosis by inverse problem technique
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.
Magnetotelluric inversion for depth-to-basement estimation
DEFF Research Database (Denmark)
Cai, Hongzhu; Zhdanov, Michael
2015-01-01
The magnetotelluric (MT) method can be effectively applied for depth-to-basement estimation, because there exists a strong contrast in resistivity between a conductive sedimentary basin and a resistive crystalline basement. Conventional inversions of MT data are usually aimed at determining...... the volumetric distribution of the conductivity within the inversion domain. By the nature of the MT method, the recovered distribution of the subsurface conductivity is typically diffusive, which makes it difficult to select the sediment-basement interface. This paper develops a novel approach to 3D MT...... inversion for the depth-to-basement estimate. The key to this approach is selection of the model parameterization with the depth to basement being the major unknown parameter. In order to estimate the depth to the basement, the inversion algorithm recovers both the thickness and the conductivities...
Spectrogram inversion and potential applications for hearing research
DEFF Research Database (Denmark)
Decorsière, Remi Julien Blaise
on this consideration, an approach for spectrogram inversion was proposed: time-domain signals were recovered from spectrograms computed using both inner hair-cell envelope (i.e., traditional half-wave rectification followed by low-pass filtering) and Hilbert envelope definitions. The high accuracy of the inversion...... is retained by the (modeled) cochlear processing even at high audio frequencies. (2) Using the inversion framework, it is possible to manipulate signals in the modulation domain, while preserving their long-term power spectra. Thus, this enabled the creation of mixtures of speech and noise where the signal...
Theory of the inverse Faraday effect in metals
International Nuclear Information System (INIS)
Hertel, Riccardo
2006-01-01
An analytic expression is given for the inverse Faraday effect, i.e., for the magnetization occurring in a transparent medium exposed to a circularly polarized high-frequency electromagnetic wave. Using a microscopic approach based on the Drude approximation of a free-electron gas, the magnetization of the medium due to the inverse Faraday effect is identified as the result of microscopic solenoidal currents generated by the electromagnetic wave. In contrast to the better known phenomenological derivation, this microscopic treatment provides important information on the frequency dependence of the inverse Faraday effect
Contributions to Large Covariance and Inverse Covariance Matrices Estimation
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...
Testing earthquake source inversion methodologies
Page, Morgan T.
2011-01-01
Source Inversion Validation Workshop; Palm Springs, California, 11-12 September 2010; Nowadays earthquake source inversions are routinely performed after large earthquakes and represent a key connection between recorded seismic and geodetic data and the complex rupture process at depth. The resulting earthquake source models quantify the spatiotemporal evolution of ruptures. They are also used to provide a rapid assessment of the severity of an earthquake and to estimate losses. However, because of uncertainties in the data, assumed fault geometry and velocity structure, and chosen rupture parameterization, it is not clear which features of these source models are robust. Improved understanding of the uncertainty and reliability of earthquake source inversions will allow the scientific community to use the robust features of kinematic inversions to more thoroughly investigate the complexity of the rupture process and to better constrain other earthquakerelated computations, such as ground motion simulations and static stress change calculations.
Parameter estimation and inverse problems
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...
Inverse problems in classical and quantum physics
International Nuclear Information System (INIS)
Almasy, A.A.
2007-01-01
The subject of this thesis is in the area of Applied Mathematics known as Inverse Problems. Inverse problems are those where a set of measured data is analysed in order to get as much information as possible on a model which is assumed to represent a system in the real world. We study two inverse problems in the fields of classical and quantum physics: QCD condensates from tau-decay data and the inverse conductivity problem. Despite a concentrated effort by physicists extending over many years, an understanding of QCD from first principles continues to be elusive. Fortunately, data continues to appear which provide a rather direct probe of the inner workings of the strong interactions. We use a functional method which allows us to extract within rather general assumptions phenomenological parameters of QCD (the condensates) from a comparison of the time-like experimental data with asymptotic space-like results from theory. The price to be paid for the generality of assumptions is relatively large errors in the values of the extracted parameters. Although we do not claim that our method is superior to other approaches, we hope that our results lend additional confidence to the numerical results obtained with the help of methods based on QCD sum rules. EIT is a technology developed to image the electrical conductivity distribution of a conductive medium. The technique works by performing simultaneous measurements of direct or alternating electric currents and voltages on the boundary of an object. These are the data used by an image reconstruction algorithm to determine the electrical conductivity distribution within the object. In this thesis, two approaches of EIT image reconstruction are proposed. The first is based on reformulating the inverse problem in terms of integral equations. This method uses only a single set of measurements for the reconstruction. The second approach is an algorithm based on linearisation which uses more then one set of measurements. A
Inverse problems in classical and quantum physics
Energy Technology Data Exchange (ETDEWEB)
Almasy, A.A.
2007-06-29
The subject of this thesis is in the area of Applied Mathematics known as Inverse Problems. Inverse problems are those where a set of measured data is analysed in order to get as much information as possible on a model which is assumed to represent a system in the real world. We study two inverse problems in the fields of classical and quantum physics: QCD condensates from tau-decay data and the inverse conductivity problem. Despite a concentrated effort by physicists extending over many years, an understanding of QCD from first principles continues to be elusive. Fortunately, data continues to appear which provide a rather direct probe of the inner workings of the strong interactions. We use a functional method which allows us to extract within rather general assumptions phenomenological parameters of QCD (the condensates) from a comparison of the time-like experimental data with asymptotic space-like results from theory. The price to be paid for the generality of assumptions is relatively large errors in the values of the extracted parameters. Although we do not claim that our method is superior to other approaches, we hope that our results lend additional confidence to the numerical results obtained with the help of methods based on QCD sum rules. EIT is a technology developed to image the electrical conductivity distribution of a conductive medium. The technique works by performing simultaneous measurements of direct or alternating electric currents and voltages on the boundary of an object. These are the data used by an image reconstruction algorithm to determine the electrical conductivity distribution within the object. In this thesis, two approaches of EIT image reconstruction are proposed. The first is based on reformulating the inverse problem in terms of integral equations. This method uses only a single set of measurements for the reconstruction. The second approach is an algorithm based on linearisation which uses more then one set of measurements. A
Computation of inverse magnetic cascades
International Nuclear Information System (INIS)
Montgomery, D.
1981-10-01
Inverse cascades of magnetic quantities for turbulent incompressible magnetohydrodynamics are reviewed, for two and three dimensions. The theory is extended to the Strauss equations, a description intermediate between two and three dimensions appropriate to tokamak magnetofluids. Consideration of the absolute equilibrium Gibbs ensemble for the system leads to a prediction of an inverse cascade of magnetic helicity, which may manifest itself as a major disruption. An agenda for computational investigation of this conjecture is proposed
Thermal measurements and inverse techniques
Orlande, Helcio RB; Maillet, Denis; Cotta, Renato M
2011-01-01
With its uncommon presentation of instructional material regarding mathematical modeling, measurements, and solution of inverse problems, Thermal Measurements and Inverse Techniques is a one-stop reference for those dealing with various aspects of heat transfer. Progress in mathematical modeling of complex industrial and environmental systems has enabled numerical simulations of most physical phenomena. In addition, recent advances in thermal instrumentation and heat transfer modeling have improved experimental procedures and indirect measurements for heat transfer research of both natural phe
Coin tossing and Laplace inversion
Indian Academy of Sciences (India)
of a probability measure " on Е0Y 1К via the obvious change of variables e└t И xX An inversion formula for " in terms of its moments yields an inversion formula for # in terms of the values of its Laplace transform at n И 0Y 1Y 2Y ... and vice versa. In our discussion we allow " (respectively #) to have positive mass at 0 ...
Full Waveform Inversion Using Oriented Time Migration Method
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
EDITORIAL: Inverse Problems in Engineering
West, Robert M.; Lesnic, Daniel
2007-01-01
Presented here are 11 noteworthy papers selected from the Fifth International Conference on Inverse Problems in Engineering: Theory and Practice held in Cambridge, UK during 11-15 July 2005. The papers have been peer-reviewed to the usual high standards of this journal and the contributions of reviewers are much appreciated. The conference featured a good balance of the fundamental mathematical concepts of inverse problems with a diverse range of important and interesting applications, which are represented here by the selected papers. Aspects of finite-element modelling and the performance of inverse algorithms are investigated by Autrique et al and Leduc et al. Statistical aspects are considered by Emery et al and Watzenig et al with regard to Bayesian parameter estimation and inversion using particle filters. Electrostatic applications are demonstrated by van Berkel and Lionheart and also Nakatani et al. Contributions to the applications of electrical techniques and specifically electrical tomographies are provided by Wakatsuki and Kagawa, Kim et al and Kortschak et al. Aspects of inversion in optical tomography are investigated by Wright et al and Douiri et al. The authors are representative of the worldwide interest in inverse problems relating to engineering applications and their efforts in producing these excellent papers will be appreciated by many readers of this journal.
Silicon MIS/inversion-layer solar cells
Olsen, L. C.
1982-10-01
Silicon Metal-Insulator-Semiconductor/Inversion-Layer (MIS-IL) solar cells were investigated as an approach to low cost terrestrial photovoltaics. Considerable progress was made concerning the development of procedures for SiO deposition for inversion-layer formation, the characterization of the fixed charge in deposited SiO layers, surface state density at the Si-SiO interface, fabrication and characterization of MIS-IL solar cells. Improvements were also made in the theory of MIS-IL solar cells, and utilized to calculate cell performance for a range of insulator charge and base resistivities. Inversion layer formation was studied in several ways. MOS devices was analyzed to determine the magnitude of the net positive charge, Q/sub POS/, vensus surface potential, Psi/sub S/. In situ sheet resistance measurements was made to determine the charge distribution within the deposited SiO layer. Finally, estimates of Q/sub POS/ obtained by comparing experimental results for MIS-IL cells and theory are compared with values of Q/sub POS/ determined for MOS structures fabricated simultaneously with the solar cells. Cell fabrication procedures emphasized low temperature processing.
Elastic reflection waveform inversion with variable density
Li, Yuanyuan
2017-08-17
Elastic full waveform inversion (FWI) provides a better description of the subsurface than those given by the acoustic assumption. However it suffers from a more serious cycle skipping problem compared with the latter. Reflection waveform inversion (RWI) provides a method to build a good background model, which can serve as an initial model for elastic FWI. Therefore, we introduce the concept of RWI for elastic media, and propose elastic RWI with variable density. We apply Born modeling to generate the synthetic reflection data by using optimized perturbations of P- and S-wave velocities and density. The inversion for the perturbations in P- and S-wave velocities and density is similar to elastic least-squares reverse time migration (LSRTM). An incorrect initial model will lead to some misfits at the far offsets of reflections; thus, can be utilized to update the background velocity. We optimize the perturbation and background models in a nested approach. Numerical tests on the Marmousi model demonstrate that our method is able to build reasonably good background models for elastic FWI with absence of low frequencies, and it can deal with the variable density, which is needed in real cases.
2011-06-01
shape of a scatterer from re ected acoustic waves, using a Banach space setting and the Lagrangian approach. The shape Hessian is then analyzed in both H...corresponding to the inverse problem of inferring the shape of a scatterer from reflected acoustic waves, using a Banach space setting and the...compact embeddings in Hölder and Sobolev spaces . These tools allow us to state the shape derivatives in a Banach space setting, and then to analyze the
Elastic versus acoustic inversion for marine surveys
Mora, Peter
2018-04-24
Full Wavefield Inversion (FWI) is a powerful and elegant approach for seismic imaging that is on the way to becoming the method of choice when processing exploration or global seismic data. In the case of processing marine survey data, one may be tempted to assume acoustic FWI is sufficient given that only pressure waves exist in the water layer. In this paper, we pose the question as to whether or not in theory – at least for a hard water bottom case – it should be possible to resolve the shear modulus or S-wave velocity in a marine setting using large offset data. We therefore conduct numerical experiments with idealized marine data calculated with the elastic wave equation. We study two cases, FWI of data due to a diffractor model, and FWI of data due to a fault model. We find that at least in idealized situation, elastic FWI of hard waterbottom data is capable of resolving between the two Lamé parameters λ and μ. Another numerical experiment with a soft waterbottom layer gives the same result. In contrast, acoustic FWI of the synthetic elastic data results in a single image of the first Lamé parameter λ which contains severe artefacts for diffraction data and noticable artefacts for layer reflection data. Based on these results, it would appear that at least, inversions of large offset marine data should be fully elastic rather than acoustic unless it has been demonstrated that for the specific case in question (offsets, model and water depth, practical issues such as soft sediment attenuation of shear waves or computational time), that an acoustic only inversion provides a reasonably good quality of image comparable to that of an elastic inversion. Further research with real data is required to determine the degree to which practical issues such as shear wave attenuation in soft sediments may affect this result.
Interferogram analysis using the Abel inversion technique
International Nuclear Information System (INIS)
Yusof Munajat; Mohamad Kadim Suaidi
2000-01-01
High speed and high resolution optical detection system were used to capture the image of acoustic waves propagation. The freeze image in the form of interferogram was analysed to calculate the transient pressure profile of the acoustic waves. The interferogram analysis was based on the fringe shift and the application of the Abel inversion technique. An easier approach was made by mean of using MathCAD program as a tool in the programming; yet powerful enough to make such calculation, plotting and transfer of file. (Author)
Perspectives on Geoacoustic Inversion of Ocean Bottom Reflectivity Data
Directory of Open Access Journals (Sweden)
N. Ross Chapman
2016-09-01
Full Text Available This paper focuses on acoustic reflectivity of the ocean bottom, and describes inversion of reflection data from an experiment designed to study the physical properties and structure of the ocean bottom. The formalism of Bayesian inference is reviewed briefly to establish an understanding of the approach for inversion that is in widespread use. A Bayesian inversion of ocean bottom reflection coefficient versus angle data to estimate geoacoustic model parameters of young oceanic crust is presented. The data were obtained in an experiment to study the variation of sound speed in crustal basalt with age of the crust at deep water sites in the Pacific Ocean where the sediment deposits overlying the basalt are very thin. The inversion results show that sound speed of both compressional and shear waves is increasing with crustal age over the track of the experiment where age increased from 40 to 70 million years.
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
Energy Technology Data Exchange (ETDEWEB)
Hinnell, A.C.; Ferre, T.P.A.; Vrugt, J.A.; Huisman, J.A.; Moysey, S.; Rings, J.; Kowalsky, M.B.
2009-11-01
There is increasing interest in the use of multiple measurement types, including indirect (geophysical) methods, to constrain hydrologic interpretations. To date, most examples integrating geophysical measurements in hydrology have followed a three-step, uncoupled inverse approach. This approach begins with independent geophysical inversion to infer the spatial and/or temporal distribution of a geophysical property (e.g. electrical conductivity). The geophysical property is then converted to a hydrologic property (e.g. water content) through a petrophysical relation. The inferred hydrologic property is then used either independently or together with direct hydrologic observations to constrain a hydrologic inversion. We present an alternative approach, coupled inversion, which relies on direct coupling of hydrologic models and geophysical models during inversion. We compare the abilities of coupled and uncoupled inversion using a synthetic example where surface-based electrical conductivity surveys are used to monitor one-dimensional infiltration and redistribution.
Inverse comptonization vs. thermal synchrotron
International Nuclear Information System (INIS)
Fenimore, E.E.; Klebesadel, R.W.; Laros, J.G.
1983-01-01
There are currently two radiation mechanisms being considered for gamma-ray bursts: thermal synchrotron and inverse comptonization. They are mutually exclusive since thermal synchrotron requires a magnetic field of approx. 10 12 Gauss whereas inverse comptonization cannot produce a monotonic spectrum if the field is larger than 10 11 and is too inefficient relative to thermal synchrotron unless the field is less than 10 9 Gauss. Neither mechanism can explain completely the observed characteristics of gamma-ray bursts. However, we conclude that thermal synchrotron is more consistent with the observations if the sources are approx. 40 kpc away whereas inverse comptonization is more consistent if they are approx. 300 pc away. Unfortunately, the source distance is still not known and, thus, the radiation mechanism is still uncertain
Inverse comorbidity in multiple sclerosis
DEFF Research Database (Denmark)
Thormann, Anja; Koch-Henriksen, Nils; Laursen, Bjarne
2016-01-01
discovery rate and investigated each of eight pre-specified comorbidity categories: psychiatric, cerebrovascular, cardiovascular, lung, and autoimmune comorbidities, diabetes, cancer, and Parkinson's disease. Results A total of 8947 MS-cases and 44,735 controls were eligible for inclusion. We found...... This study showed a decreased risk of cancers and pulmonary diseases after onset of MS. Identification of inverse comorbidity and of its underlying mechanisms may provide important new entry points into the understanding of MS.......Background Inverse comorbidity is disease occurring at lower rates than expected among persons with a given index disease. The objective was to identify inverse comorbidity in MS. Methods We performed a combined case-control and cohort study in a total nationwide cohort of cases with clinical onset...
Inverse photoemission of uranium oxides
International Nuclear Information System (INIS)
Roussel, P.; Morrall, P.; Tull, S.J.
2009-01-01
Understanding the itinerant-localised bonding role of the 5f electrons in the light actinides will afford an insight into their unusual physical and chemical properties. In recent years, the combination of core and valance band electron spectroscopies with theoretic modelling have already made significant progress in this area. However, information of the unoccupied density of states is still scarce. When compared to the forward photoemission techniques, measurements of the unoccupied states suffer from significantly less sensitivity and lower resolution. In this paper, we report on our experimental apparatus, which is designed to measure the inverse photoemission spectra of the light actinides. Inverse photoemission spectra of UO 2 and UO 2.2 along with the corresponding core and valance electron spectra are presented in this paper. UO 2 has been reported previously, although through its inclusion here it allows us to compare and contrast results from our experimental apparatus to the previous Bremsstrahlung Isochromat Spectroscopy and Inverse Photoemission Spectroscopy investigations
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)
Inverse methods in hydrologic optics
Directory of Open Access Journals (Sweden)
Howard R. Gordon
2002-03-01
Full Text Available Methods for solving the hydrologic-optics inverse problem, i.e., estimating the inherent optical properties of a water body based solely on measurements of the apparent optical properties, are reviewed in detail. A new method is developed for the inverse problem in water bodies in which fluorescence is important. It is shown that in principle, given profiles of the spectra of up- and downwelling irradiance, estimation of the coefficient of inelastic scattering from any wave band to any other wave band can be effected.
Inverse Interval Matrix: A Survey
Czech Academy of Sciences Publication Activity Database
Rohn, Jiří; Farhadsefat, R.
2011-01-01
Roč. 22, - (2011), s. 704-719 E-ISSN 1081-3810 R&D Projects: GA ČR GA201/09/1957; GA ČR GC201/08/J020 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval matrix * inverse interval matrix * NP-hardness * enclosure * unit midpoint * inverse sign stability * nonnegative invertibility * absolute value equation * algorithm Subject RIV: BA - General Mathematics Impact factor: 0.808, year: 2010 http://www.math.technion.ac.il/iic/ela/ela-articles/articles/vol22_pp704-719.pdf
Size Estimates in Inverse Problems
Di Cristo, Michele
2014-01-06
Detection of inclusions or obstacles inside a body by boundary measurements is an inverse problems very useful in practical applications. When only finite numbers of measurements are available, we try to detect some information on the embedded object such as its size. In this talk we review some recent results on several inverse problems. The idea is to provide constructive upper and lower estimates of the area/volume of the unknown defect in terms of a quantity related to the work that can be expressed with the available boundary data.
-Dimensional Fractional Lagrange's Inversion Theorem
Directory of Open Access Journals (Sweden)
F. A. Abd El-Salam
2013-01-01
Full Text Available Using Riemann-Liouville fractional differential operator, a fractional extension of the Lagrange inversion theorem and related formulas are developed. The required basic definitions, lemmas, and theorems in the fractional calculus are presented. A fractional form of Lagrange's expansion for one implicitly defined independent variable is obtained. Then, a fractional version of Lagrange's expansion in more than one unknown function is generalized. For extending the treatment in higher dimensions, some relevant vectors and tensors definitions and notations are presented. A fractional Taylor expansion of a function of -dimensional polyadics is derived. A fractional -dimensional Lagrange inversion theorem is proved.
Linearity of Bulk-Controlled Inverter Ring VCO in Weak and Strong Inversion
DEFF Research Database (Denmark)
Wismar, Ulrik Sørensen; Wisland, Dag T.; Andreani, Pietro
2005-01-01
Frequency modulation in ring VCOs is investigated. Primarily, the linearity of conversion from input voltage to output frequency is considered. Bulk-voltage control of the threshold voltage of the VCO transistors is found to be a very promising approach for applications in frequency ΔΣ converters....... Different approaches apply in presence of high supply voltages, when transistors work in strong inversion, compared to low supply voltages, when transistors are in weak inversion. In strong inversion, second-order effects controlled by the supply voltage linearize the VCO modulation, while in weak inversion...
Rapid fabrication of 2D and 3D photonic crystals and their inversed structures
International Nuclear Information System (INIS)
Huang, C-K; Chan, C-H; Chen, C-Y; Tsai, Y-L; Chen, C-C; Han, J-L; Hsieh, K-H
2007-01-01
In this paper a new technique is proposed for the fabrication of two-dimensional (2D) and three-dimensional (3D) photonic crystals using monodisperse polystyrene microspheres as the templates. In addition, the approaches toward the creation of their corresponding inversed structures are described. The inversed structures were prepared by subjecting an introduced silica source to a sol-gel process; programmed heating was then performed to remove the template without spoiling the inversed structures. Utilizing these approaches, 2D and 3D photonic crystals and their highly ordered inversed hexagonal multilayer or monolayer structures were obtained on the substrate
Superconductivity in Pb inverse opal
International Nuclear Information System (INIS)
Aliev, Ali E.; Lee, Sergey B.; Zakhidov, Anvar A.; Baughman, Ray H.
2007-01-01
Type-II superconducting behavior was observed in highly periodic three-dimensional lead inverse opal prepared by infiltration of melted Pb in blue (D = 160 nm), green (D = 220 nm) and red (D = 300 nm) opals and followed by the extraction of the SiO 2 spheres by chemical etching. The onset of a broad phase transition (ΔT = 0.3 K) was shifted from T c = 7.196 K for bulk Pb to T c = 7.325 K. The upper critical field H c2 (3150 Oe) measured from high-field hysteresis loops exceeds the critical field for bulk lead (803 Oe) fourfold. Two well resolved peaks observed in the hysteresis loops were ascribed to flux penetration into the cylindrical void space that can be found in inverse opal structure and into the periodic structure of Pb nanoparticles. The red inverse opal shows pronounced oscillations of magnetic moment in the mixed state at low temperatures, T 0.9T c has been observed for all of the samples studied. The magnetic field periodicity of resistivity modulation is in good agreement with the lattice parameter of the inverse opal structure. We attribute the failure to observe pronounced modulation in magneto-resistive measurement to difficulties in the precision orientation of the sample along the magnetic field
Coin Tossing and Laplace Inversion
Indian Academy of Sciences (India)
An analysis of exchangeable sequences of coin tossings leads to inversion formulae for Laplace transforms of probability measures. Author Affiliations. J C Gupta1 2. Indian Statistical Institute, New Delhi 110 016, India; 32, Mirdha Tola, Budaun 243 601, India. Dates. Manuscript received: 5 May 1999; Manuscript revised: 3 ...
Givental Graphs and Inversion Symmetry
Dunin-Barkovskiy, P.; Shadrin, S.; Spitz, L.
2013-01-01
Inversion symmetry is a very non-trivial discrete symmetry of Frobenius manifolds. It was obtained by Dubrovin from one of the elementary Schlesinger transformations of a special ODE associated to a Frobenius manifold. In this paper, we review the Givental group action on Frobenius manifolds in
Wave-equation dispersion inversion
Li, Jing
2016-12-08
We present the theory for wave-equation inversion of dispersion curves, where the misfit function is the sum of the squared differences between the wavenumbers along the predicted and observed dispersion curves. The dispersion curves are obtained from Rayleigh waves recorded by vertical-component geophones. Similar to wave-equation traveltime tomography, the complicated surface wave arrivals in traces are skeletonized as simpler data, namely the picked dispersion curves in the phase-velocity and frequency domains. Solutions to the elastic wave equation and an iterative optimization method are then used to invert these curves for 2-D or 3-D S-wave velocity models. This procedure, denoted as wave-equation dispersion inversion (WD), does not require the assumption of a layered model and is significantly less prone to the cycle-skipping problems of full waveform inversion. The synthetic and field data examples demonstrate that WD can approximately reconstruct the S-wave velocity distributions in laterally heterogeneous media if the dispersion curves can be identified and picked. The WD method is easily extended to anisotropic data and the inversion of dispersion curves associated with Love waves.
Adjoint modeling for acoustic inversion
Hursky, Paul; Porter, Michael B.; Cornuelle, B. D.; Hodgkiss, W. S.; Kuperman, W. A.
2004-02-01
The use of adjoint modeling for acoustic inversion is investigated. An adjoint model is derived from a linearized forward propagation model to propagate data-model misfit at the observation points back through the medium to the medium perturbations not being accounted for in the model. This adjoint model can be used to aid in inverting for these unaccounted medium perturbations. Adjoint methods are being applied to a variety of inversion problems, but have not drawn much attention from the underwater acoustic community. This paper presents an application of adjoint methods to acoustic inversion. Inversions are demonstrated in simulation for both range-independent and range-dependent sound speed profiles using the adjoint of a parabolic equation model. Sensitivity and error analyses are discussed showing how the adjoint model enables calculations to be performed in the space of observations, rather than the often much larger space of model parameters. Using an adjoint model enables directions of steepest descent in the model parameters (what we invert for) to be calculated using far fewer modeling runs than if a forward model only were used.
Workflows for Full Waveform Inversions
Boehm, Christian; Krischer, Lion; Afanasiev, Michael; van Driel, Martin; May, Dave A.; Rietmann, Max; Fichtner, Andreas
2017-04-01
Despite many theoretical advances and the increasing availability of high-performance computing clusters, full seismic waveform inversions still face considerable challenges regarding data and workflow management. While the community has access to solvers which can harness modern heterogeneous computing architectures, the computational bottleneck has fallen to these often manpower-bounded issues that need to be overcome to facilitate further progress. Modern inversions involve huge amounts of data and require a tight integration between numerical PDE solvers, data acquisition and processing systems, nonlinear optimization libraries, and job orchestration frameworks. To this end we created a set of libraries and applications revolving around Salvus (http://salvus.io), a novel software package designed to solve large-scale full waveform inverse problems. This presentation focuses on solving passive source seismic full waveform inversions from local to global scales with Salvus. We discuss (i) design choices for the aforementioned components required for full waveform modeling and inversion, (ii) their implementation in the Salvus framework, and (iii) how it is all tied together by a usable workflow system. We combine state-of-the-art algorithms ranging from high-order finite-element solutions of the wave equation to quasi-Newton optimization algorithms using trust-region methods that can handle inexact derivatives. All is steered by an automated interactive graph-based workflow framework capable of orchestrating all necessary pieces. This naturally facilitates the creation of new Earth models and hopefully sparks new scientific insights. Additionally, and even more importantly, it enhances reproducibility and reliability of the final results.
Reducing complexity of inverse problems using geostatistical priors
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Mosegaard, Klaus; Cordua, Knud Skou
can practically never hope to generate a posterior sample, others are just ’difficult’ and require special methods to become tractable, while others again are easily solved. We discuss how difficult nonlinear inverse problems can be handled such that their complexity, i.e. the time taken to obtain......In a probabilistic formulation of inverse problems the solution can be given as a sample of the posterior probability distribution. All realizations retained in the posterior sample are consistent with both an assumed prior model and observed data. Some inverse problems are unsolvable, in that one......, and another approach makes use of conditional re-simulation to sample the prior that works for both 2-point and multiple point random models. The latter approach is shown to be superior in terms of computational efficiency. We quantify the information content given by a specific choice of prior model...
Acoustic source inversion to estimate volume flux from volcanic explosions
Kim, Keehoon; Fee, David; Yokoo, Akihiko; Lees, Jonathan M.
2015-07-01
We present an acoustic waveform inversion technique for infrasound data to estimate volume fluxes from volcanic eruptions. Previous inversion techniques have been limited by the use of a 1-D Green's function in a free space or half space, which depends only on the source-receiver distance and neglects volcanic topography. Our method exploits full 3-D Green's functions computed by a numerical method that takes into account realistic topographic scattering. We apply this method to vulcanian eruptions at Sakurajima Volcano, Japan. Our inversion results produce excellent waveform fits to field observations and demonstrate that full 3-D Green's functions are necessary for accurate volume flux inversion. Conventional inversions without consideration of topographic propagation effects may lead to large errors in the source parameter estimate. The presented inversion technique will substantially improve the accuracy of eruption source parameter estimation (cf. mass eruption rate) during volcanic eruptions and provide critical constraints for volcanic eruption dynamics and ash dispersal forecasting for aviation safety. Application of this approach to chemical and nuclear explosions will also provide valuable source information (e.g., the amount of energy released) previously unavailable.
International Nuclear Information System (INIS)
Wang, Aijun; Zeng, Yanwei; Han, Longxiang; Ding, Chuan; Cao, Liangliang; Li, Rongjie
2015-01-01
Aggregation-free spherical lanthanum-doped bismuth titanate (Bi 3.25 La 0.75 Ti 3 O 12 , BLT) gel particles with an average size of about 150 nm were successfully obtained from an inverse miniemulsion sol–gel process, with Span-80 acting as surfactant, n-butanol as co-surfactant, cyclohexane as continuous phase, and submicro-droplets of aqueous solution containing Bi 3+ , La 3+ and Ti 4+ ions as dispersed phase, and then topotactically transformed into highly dispersed spherical BLT nanocrystals after an in situ crystallization at 600 °C for 8 h. It has been found that the BLT gel particles can be obtained via a moderate sol–gel reaction inside the miniemulsion droplets at 65 °C, but their morphology and aggregation degree are strongly affected by the relative amounts of Span-80 and n-butanol. The perfect spherical BLT gel particles with no aggregation can be achieved only under the condition of 3 wt% n-butanol relative to the mass of cyclohexane, with excessive amount of n-butanol leading to the formation of ill-gelled particles with irregular shapes, while insufficient addition of n-butanol resulting in terrible aggregation of gel particles. To understand the formation of aggregation-free spherical BLT gel particles, a tentative mechanism is proposed and discussed, which reveals that a well-coordinated oil–water interfacial film made up of Span-80 and n-butanol molecules and the appropriately enhanced evaporation of water from such interfaces should be responsible for the formation of aggregation-free spherical BLT gel particles. Graphical Abstract: Aggregation-free spherical BLT (Bi 3.25 La 0.75 Ti 3 O 12 ) gel particles can be prepared from an effective inverse miniemulsion sol–gel process, and subsequently topotactically transformed into spherical BLT nanocrystals through an in situ crystallization
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)
Bilinear Inverse Problems: Theory, Algorithms, and Applications
Ling, Shuyang
We will discuss how several important real-world signal processing problems, such as self-calibration and blind deconvolution, can be modeled as bilinear inverse problems and solved by convex and nonconvex optimization approaches. In Chapter 2, we bring together three seemingly unrelated concepts, self-calibration, compressive sensing and biconvex optimization. We show how several self-calibration problems can be treated efficiently within the framework of biconvex compressive sensing via a new method called SparseLift. More specifically, we consider a linear system of equations y = DAx, where the diagonal matrix D (which models the calibration error) is unknown and x is an unknown sparse signal. By "lifting" this biconvex inverse problem and exploiting sparsity in this model, we derive explicit theoretical guarantees under which both x and D can be recovered exactly, robustly, and numerically efficiently. In Chapter 3, we study the question of the joint blind deconvolution and blind demixing, i.e., extracting a sequence of functions [special characters omitted] from observing only the sum of their convolutions [special characters omitted]. In particular, for the special case s = 1, it becomes the well-known blind deconvolution problem. We present a non-convex algorithm which guarantees exact recovery under conditions that are competitive with convex optimization methods, with the additional advantage of being computationally much more efficient. We discuss several applications of the proposed framework in image processing and wireless communications in connection with the Internet-of-Things. In Chapter 4, we consider three different self-calibration models of practical relevance. We show how their corresponding bilinear inverse problems can be solved by both the simple linear least squares approach and the SVD-based approach. As a consequence, the proposed algorithms are numerically extremely efficient, thus allowing for real-time deployment. Explicit theoretical
Kachar, H.; Mobasheri, M. R.; Abkar, A. A.; Rahim Zadegan, M.
2015-12-01
Increase of temperature with height in the troposphere is called temperature inversion. Parameters such as strength and depth are characteristics of temperature inversion. Inversion strength is defined as the temperature difference between the surface and the top of the inversion and the depth of inversion is defined as the height of the inversion from the surface. The common approach in determination of these parameters is the use of Radiosonde where these measurements are too sparse. The main objective of this study is detection and modeling the temperature inversion using MODIS thermal infrared data. There are more than 180 days per year in which the temperature inversion conditions are present in Kermanshah city. Kermanshah weather station was selected as the study area. 90 inversion days was selected from 2007 to 2008 where the sky was clear and the Radiosonde data were available. Brightness temperature for all thermal infrared bands of MODIS was calculated for these days. Brightness temperature difference between any of the thermal infrared bands of MODIS and band 31 was found to be sensitive to strength and depth of temperature inversion. Then correlation coefficients between these pairs and the inversion depth and strength both calculated from Radiosonde were evaluated. The results showed poor linear correlation. This was found to be due to the change of the atmospheric water vapor content and the relatively weak temperature inversion strength and depth occurring in Kermanshah. The polynomial mathematical models and Artificial intelligence algorithms were deployed for detection and modeling the temperature inversion. A model with the lowest terms and highest possible accuracy was obtained. The Model was tested using 20 independent test data. Results indicate that the inversion strength can be estimated with RMSE of 0.84° C and R2 of 0.90. Also inversion depth can be estimated with RMSE of 54.56 m and R2 of 0.86.
3D stochastic inversion and joint inversion of potential fields for multi scale parameters
Shamsipour, Pejman
In this thesis we present the development of new techniques for the interpretation of potential field (gravity and magnetic data), which are the most widespread economic geophysical methods used for oil and mineral exploration. These new techniques help to address the long-standing issue with the interpretation of potential fields, namely the intrinsic non-uniqueness inversion of these types of data. The thesis takes the form of three papers (four including Appendix), which have been published, or soon to be published, in respected international journals. The purpose of the thesis is to introduce new methods based on 3D stochastical approaches for: 1) Inversion of potential field data (magnetic), 2) Multiscale Inversion using surface and borehole data and 3) Joint inversion of geophysical potential field data. We first present a stochastic inversion method based on a geostatistical approach to recover 3D susceptibility models from magnetic data. The aim of applying geostatistics is to provide quantitative descriptions of natural variables distributed in space or in time and space. We evaluate the uncertainty on the parameter model by using geostatistical unconditional simulations. The realizations are post-conditioned by cokriging to observation data. In order to avoid the natural tendency of the estimated structure to lay near the surface, depth weighting is included in the cokriging system. Then, we introduce algorithm for multiscale inversion, the presented algorithm has the capability of inverting data on multiple supports. The method involves four main steps: i. upscaling of borehole parameters (It could be density or susceptibility) to block parameters, ii. selection of block to use as constraints based on a threshold on kriging variance, iii. inversion of observation data with selected block densities as constraints, and iv. downscaling of inverted parameters to small prisms. Two modes of application are presented: estimation and simulation. Finally, a novel
The Earthquake‐Source Inversion Validation (SIV) Project
Mai, Paul Martin
2016-04-27
Finite-fault earthquake source inversions infer the (time-dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, multiple source models for the same earthquake, obtained by different research teams, often exhibit remarkable dissimilarities. To address the uncertainties in earthquake-source inversion methods and to understand strengths and weaknesses of the various approaches used, the Source Inversion Validation (SIV) project conducts a set of forward-modeling exercises and inversion benchmarks. In this article, we describe the SIV strategy, the initial benchmarks, and current SIV results. Furthermore, we apply statistical tools for quantitative waveform comparison and for investigating source-model (dis)similarities that enable us to rank the solutions, and to identify particularly promising source inversion approaches. All SIV exercises (with related data and descriptions) and statistical comparison tools are available via an online collaboration platform, and we encourage source modelers to use the SIV benchmarks for developing and testing new methods. We envision that the SIV efforts will lead to new developments for tackling the earthquake-source imaging problem.
Gaining insight into food webs reconstructed by the inverse method
Kones, J.; Soetaert, K.E.R.; Van Oevelen, D.; Owino, J.; Mavuti, K.
2006-01-01
The use of the inverse method to analyze flow patterns of organic components in ecological systems has had wide application in ecological modeling. Through this approach, an infinite number of food web flows describing the food web and satisfying biological constraints are generated, from which one
Uniqueness in inverse elastic scattering with finitely many incident waves
International Nuclear Information System (INIS)
Elschner, Johannes; Yamamoto, Masahiro
2009-01-01
We consider the third and fourth exterior boundary value problems of linear isotropic elasticity and present uniqueness results for the corresponding inverse scattering problems with polyhedral-type obstacles and a finite number of incident plane elastic waves. Our approach is based on a reflection principle for the Navier equation. (orig.)
Design and Implementation of Forward and Inverse Gravity ...
African Journals Online (AJOL)
The implementation of a tool to perform two-dimensional forward and inverse gravity data modeling that can be used to interpret the subsurface geologic structure is presented in this article. The approach subdivides the subsurface into regular shape prisms and reconstructs the geologic structures by assigning variable ...
inverse gaussian model for small area estimation via gibbs sampling
African Journals Online (AJOL)
ADMIN
(1994) extended the work by Fries and. Bhattacharyya (1983) to include the maximum likelihood analysis of the two-factor inverse. Gaussian model for the unbalanced and interaction case for the estimation of small area parameters in finite populations. The object of this article is to develop a Bayesian approach for small ...
inverse correction of fourier transforms for one-dimensional strongly ...
African Journals Online (AJOL)
Hsin Ying-Fei
2016-05-01
May 1, 2016 ... As it is widely used in periodic lattice design theory and is particularly useful in aperiodic lattice design [12,13], the accuracy of the FT algorithm under strong scattering conditions is the focus of this paper. We propose an inverse correction approach for the inaccurate FT algorithm in strongly scattering ...
Hedland, D. A.; Degonia, P. K.
1974-01-01
The RAE-1 spacecraft inversion performed October 31, 1972 is described based upon the in-orbit dynamical data in conjunction with results obtained from previously developed computer simulation models. The computer simulations used are predictive of the satellite dynamics, including boom flexing, and are applicable during boom deployment and retraction, inter-phase coast periods, and post-deployment operations. Attitude data, as well as boom tip data, were analyzed in order to obtain a detailed description of the dynamical behavior of the spacecraft during and after the inversion. Runs were made using the computer model and the results were analyzed and compared with the real time data. Close agreement between the actual recorded spacecraft attitude and the computer simulation results was obtained.
Validation of OSIRIS Ozone Inversions
Gudnason, P.; Evans, W. F.; von Savigny, C.; Sioris, C.; Halley, C.; Degenstein, D.; Llewellyn, E. J.; Petelina, S.; Gattinger, R. L.; Odin Team
2002-12-01
The OSIRIS instrument onboard the Odin satellite, that was launched on February 20, 2001, is a combined optical spectrograph and infrared imager that obtains profil sets of atmospheric spectra from 280 to 800 nm when Odin scans the terrestrial limb. It has been possible to make a preliminary analysis of the ozone profiles using the Chappuis absorption feature. Three algorithms have been developed for ozone profile inversions from these limb spectra sets. We have dubbed these the Gattinger, Von Savigny-Flittner and DOAS methods. These are being evaluated against POAM and other satellite data. Based on performance, one of these will be selected for the operational algorithm. The infrared imager data have been used by Degenstein with the tomographic inversion procedure to derive ozone concentrations above 60 km. This paper will present some of these initial observations and indicate the best algorithm potential of OSIRIS to make spectacular advances in the study of terrestrial ozone.
The inverse gravimetric problem in gravity modelling
Sanso, F.; Tscherning, C. C.
1989-01-01
One of the main purposes of geodesy is to determine the gravity field of the Earth in the space outside its physical surface. This purpose can be pursued without any particular knowledge of the internal density even if the exact shape of the physical surface of the Earth is not known, though this seems to entangle the two domains, as it was in the old Stoke's theory before the appearance of Molodensky's approach. Nevertheless, even when large, dense and homogeneous data sets are available, it was always recognized that subtracting from the gravity field the effect of the outer layer of the masses (topographic effect) yields a much smoother field. This is obviously more important when a sparse data set is bad so that any smoothing of the gravity field helps in interpolating between the data without raising the modeling error, this approach is generally followed because it has become very cheap in terms of computing time since the appearance of spectral techniques. The mathematical description of the Inverse Gravimetric Problem (IGP) is dominated mainly by two principles, which in loose terms can be formulated as follows: the knowledge of the external gravity field determines mainly the lateral variations of the density; and the deeper the density anomaly giving rise to a gravity anomaly, the more improperly posed is the problem of recovering the former from the latter. The statistical relation between rho and n (and its inverse) is also investigated in its general form, proving that degree cross-covariances have to be introduced to describe the behavior of rho. The problem of the simultaneous estimate of a spherical anomalous potential and of the external, topographic masses is addressed criticizing the choice of the mixed collection approach.
Inverse problem in transformation optics
Novitsky, Andrey V.
2011-01-01
The straightforward method of transformation optics implies that one starts from the coordinate transformation and determines the Jacobian matrix, the fields and material parameters of the cloak. However, the coordinate transformation appears as an optional function: it is not necessary to know it. We offer the solution of some sort of inverse problem: starting from the fields in the invisibility cloak we directly derive the permittivity and permeability tensors of the cloaking shell. This ap...
Fourier reconstruction with sparse inversions
Zwartjes, P.M.
2005-01-01
In seismic exploration an image of the subsurface is generated from seismic data through various data processing algorithms. When the data is not acquired on an equidistantly spaced grid, artifacts may result in the final image. Fourier reconstruction is an interpolation technique that can reduce these artifacts by generating uniformly sampled data from such non-uniformly sampled data. The method works by estimating via least-squares inversion the Fourier coefficients that describe the non-un...
The Inverse of Banded Matrices
2013-01-01
for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite ...numbers of summed or subtracted terms in computing the inverse of a term of an upper (lower) triangular matrix are the generalized order-k Fibonacci ... Fibonacci numbers are the usual Fibonacci numbers, that is, f 2m = Fm (mth Fibonacci number). When also k = 3, c1 = c2 = c3 = 1, then the generalized order-3
Inverse-magnetron mass spectrometer
International Nuclear Information System (INIS)
Pakulin, V.N.
1979-01-01
Considered is the operation of a typical magnetron mass spectrometer with an internal ion source and that of an inverse magnetron mass spectrometer with an external ion source. It is found that for discrimination of the same mass using the inverse design of mass spectrometers it is possible to employ either r 2 /r 1 times lesser magnetic fields at equal accelerating source-collector voltages, or r 2 /r 1 higher accelerating voltages at equal magnetic fields, as compared to the typical design (r 1 and r 2 being radii of the internal and external electrodes of the analyser, respectively). The design of an inverse-magnetron mass spectrometer is described. The mass analyzer is formed by a cylindrical electrode of 3 mm diameter and a coaxial tubular cylinder of 55 mm diameter. External to the analyzer is an ionizing chamber at the pressure of up to 5x10 -6 torr. The magnetic field along the chamber axis produced by a solenoid was 300 Oe. At the accelerating voltage of 100 V and mass 28, the spectrometer has a resolution of 30 at a half-peak height
Modular inverse reinforcement learning for visuomotor behavior.
Rothkopf, Constantin A; Ballard, Dana H
2013-08-01
In a large variety of situations one would like to have an expressive and accurate model of observed animal or human behavior. While general purpose mathematical models may capture successfully properties of observed behavior, it is desirable to root models in biological facts. Because of ample empirical evidence for reward-based learning in visuomotor tasks, we use a computational model based on the assumption that the observed agent is balancing the costs and benefits of its behavior to meet its goals. This leads to using the framework of reinforcement learning, which additionally provides well-established algorithms for learning of visuomotor task solutions. To quantify the agent's goals as rewards implicit in the observed behavior, we propose to use inverse reinforcement learning, which quantifies the agent's goals as rewards implicit in the observed behavior. Based on the assumption of a modular cognitive architecture, we introduce a modular inverse reinforcement learning algorithm that estimates the relative reward contributions of the component tasks in navigation, consisting of following a path while avoiding obstacles and approaching targets. It is shown how to recover the component reward weights for individual tasks and that variability in observed trajectories can be explained succinctly through behavioral goals. It is demonstrated through simulations that good estimates can be obtained already with modest amounts of observation data, which in turn allows the prediction of behavior in novel configurations.
Inverse problems for difference equations with quadratic ...
African Journals Online (AJOL)
Inverse problems for difference equations with quadratic Eigenparameter dependent boundary conditions. Sonja Currie, Anne D. Love. Abstract. This paper inductively investigates an inverse problem for difference boundary value problems with boundary conditions that depend quadratically on the eigenparameter.
L∞ fitting for inverse problems with uniform noise
Clason, Christian
2012-10-01
For inverse problems where the data are corrupted by uniform noise such as arising from quantization errors, the L∞ norm is a more robust data-fitting term than the standard L2 norm. Well-posedness and regularization properties for linear inverse problems with L∞ data fitting are shown, and the automatic choice of the regularization parameter is discussed. After introducing an equivalent reformulation of the problem and a Moreau-Yosida approximation, a superlinearly convergent semi-smooth Newton method becomes applicable for the numerical solution of L∞ fitting problems. Numerical examples illustrate the performance of the proposed approach as well as the qualitative behavior of L∞ fitting.
Discrete-time inverse optimal control for nonlinear systems
Sanchez, Edgar N
2013-01-01
Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and trajectory tracking of discrete-time nonlinear systems. This avoids the need to solve the associated Hamilton-Jacobi-Bellman equation and minimizes a cost functional, resulting in a more efficient controller. Design More Efficient Controllers for Stabilization and Trajectory Tracking of Discrete-Time Nonlinear Systems The book presents two approaches for controller synthesis: the first based on passivity theory and the second on a control Lyapunov function (CLF). Th
Gradient-type methods in inverse parabolic problems
International Nuclear Information System (INIS)
Kabanikhin, Sergey; Penenko, Aleksey
2008-01-01
This article is devoted to gradient-based methods for inverse parabolic problems. In the first part, we present a priori convergence theorems based on the conditional stability estimates for linear inverse problems. These theorems are applied to backwards parabolic problem and sideways parabolic problem. The convergence conditions obtained coincide with sourcewise representability in the self-adjoint backwards parabolic case but they differ in the sideways case. In the second part, a variational approach is formulated for a coefficient identification problem. Using adjoint equations, a formal gradient of an objective functional is constructed. A numerical test illustrates the performance of conjugate gradient algorithm with the formal gradient.
Inversion algorithms for large-scale geophysical electromagnetic measurements
International Nuclear Information System (INIS)
Abubakar, A; Habashy, T M; Li, M; Liu, J
2009-01-01
Low-frequency surface electromagnetic prospecting methods have been gaining a lot of interest because of their capabilities to directly detect hydrocarbon reservoirs and to compliment seismic measurements for geophysical exploration applications. There are two types of surface electromagnetic surveys. The first is an active measurement where we use an electric dipole source towed by a ship over an array of seafloor receivers. This measurement is called the controlled-source electromagnetic (CSEM) method. The second is the Magnetotelluric (MT) method driven by natural sources. This passive measurement also uses an array of seafloor receivers. Both surface electromagnetic methods measure electric and magnetic field vectors. In order to extract maximal information from these CSEM and MT data we employ a nonlinear inversion approach in their interpretation. We present two types of inversion approaches. The first approach is the so-called pixel-based inversion (PBI) algorithm. In this approach the investigation domain is subdivided into pixels, and by using an optimization process the conductivity distribution inside the domain is reconstructed. The optimization process uses the Gauss–Newton minimization scheme augmented with various forms of regularization. To automate the algorithm, the regularization term is incorporated using a multiplicative cost function. This PBI approach has demonstrated its ability to retrieve reasonably good conductivity images. However, the reconstructed boundaries and conductivity values of the imaged anomalies are usually not quantitatively resolved. Nevertheless, the PBI approach can provide useful information on the location, the shape and the conductivity of the hydrocarbon reservoir. The second method is the so-called model-based inversion (MBI) algorithm, which uses a priori information on the geometry to reduce the number of unknown parameters and to improve the quality of the reconstructed conductivity image. This MBI approach can
Three-Dimensional Inversion of Magnetotelluric Data for the Sediment–Basement Interface
DEFF Research Database (Denmark)
Cai, Hongzhu; Zhdanov, Michael
2016-01-01
and a resistive basement. Conventional inversions of MT data are aimed at determining the volumetric distribution of the conductivity within the inversion domain. The recovered distribution of the subsurface conductivity is typically diffusive, which makes it difficult to select the sediment-basement interface....... This letter develops a novel approach to 3-D MT inversion for the depth-to-basement estimate. The key to this approach is selection of the model parameterization, with the depth to basement being the major unknown parameter. In order to estimate the depth to the basement, the inversion algorithm recovers both...... the thickness and the conductivities of the sedimentary basin. The forward modeling is based on the integral equation approach. The inverse problem is solved using a regularized conjugate gradient method. The Fréchet derivative matrix is calculated based on quasi-Born approximation. The developed method...
LA INVERSION INMOBILIARIA INDIRECTA EN ESPANA.
Joan MONTLLOR-SERRATS; Anna M. PANOSA-GUBAU
2013-01-01
En este articulo se revisan los instrumentos de inversion indirecta inmobiliaria en Espana, desde la creacion en 1992 de los Fondos y Sociedades de Inversion inmobiliaria (FII y SII) hasta la creacion de la primera Sociedad de inversion del mercado inmobiliario (SOCIMI) en 2013. Se analizan las caracteristicas de los mismos y asimismo los motivos por los cuales estas figuras de inversion no han tenido mucha demanda hasta el momento, en comparacion con los REITs (Real Estate Investment Trusts)...
Codimension zero laminations are inverse limits
Lozano Rojo, Álvaro
2013-01-01
The aim of the paper is to investigate the relation between inverse limit of branched manifolds and codimension zero laminations. We give necessary and sufficient conditions for such an inverse limit to be a lamination. We also show that codimension zero laminations are inverse limits of branched manifolds. The inverse limit structure allows us to show that equicontinuous codimension zero laminations preserves a distance function on transversals.
Inversion: A Most Useful Kind of Transformation.
Dubrovsky, Vladimir
1992-01-01
The transformation assigning to every point its inverse with respect to a circle with given radius and center is called an inversion. Discusses inversion with respect to points, circles, angles, distances, space, and the parallel postulate. Exercises related to these topics are included. (MDH)
Ray-based stochastic inversion of prestack seismic data for improved reservoir characterization
Van der Burg, D.; Verdel, A.; Wapenaar, C.P.A.
2009-01-01
Trace inversion for reservoir parameters is affected by angle averaging of seismic data and wavelet distortion on the migration image. In an alternative approach to stochastic trace inversion, the data are inverted prestack before migration using 3D dynamic ray tracing. This choice makes it possible
Losada, David E.; Barreiro, Alvaro
2003-01-01
Proposes an approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. Highlights include document representation and matching; incorporating term similarity into the measure of distance; new algorithms for implementation; inverse document frequency; and logical versus classical models of…
Solving inverse problems of mathematical physics by means of the PHOENICS software package
Energy Technology Data Exchange (ETDEWEB)
Matsevity, Y.; Lushpenko, S. [Institute for Problems in Machinery, National Academy of Sciences of Ukraine Pozharskogo, Kharkov (Ukraine)
1997-12-31
Several approaches on organizing solution of inverse problems by means of PHOENICS on the basis of the technique of automated fitting are proposing. A version of a `nondestructive` method of using PHOENICS in the inverse problem solution regime and the ways of altering the program in the case of introducing optimization facilities in it are under consideration. (author) 12 refs.
Inverse eigenvalue problems for semilinear elliptic equations
Directory of Open Access Journals (Sweden)
Tetsutaro Shibata
2009-09-01
Full Text Available We consider the inverse nonlinear eigenvalue problem for the equation $$displaylines{ -Delta u + f(u = lambda u, quad u > 0 quad hbox{in } Omega,cr u = 0 quad hbox{on } partialOmega, } where $f(u$ is an unknown nonlinear term, $Omega subset mathbb{R}^N$ is a bounded domain with an appropriate smooth boundary $partialOmega$ and $lambda > 0$ is a parameter. Under basic conditions on $f$, for any given $alpha > 0$, there exists a unique solution $(lambda, u = (lambda(alpha, u_alpha in mathbb{R}_+ imes C^2(ar{Omega}$ with $|u_alpha|_2 = alpha$. The curve $lambda(alpha$ is called the $L^2$-bifurcation branch. Using a variational approach, we show that the nonlinear term $f(u$ is determined uniquely by $lambda(alpha$.
Applications of elliptic Carleman inequalities to Cauchy and inverse problems
Choulli, Mourad
2016-01-01
This book presents a unified approach to studying the stability of both elliptic Cauchy problems and selected inverse problems. Based on elementary Carleman inequalities, it establishes three-ball inequalities, which are the key to deriving logarithmic stability estimates for elliptic Cauchy problems and are also useful in proving stability estimates for certain elliptic inverse problems. The book presents three inverse problems, the first of which consists in determining the surface impedance of an obstacle from the far field pattern. The second problem investigates the detection of corrosion by electric measurement, while the third concerns the determination of an attenuation coefficient from internal data, which is motivated by a problem encountered in biomedical imaging.
Hamieh, Tayssir; Fadlallah, Mohamed-Baker; Schultz, Jacques
2002-09-06
In this paper, the inverse gas chromatography (IGC) technique was used to calculate the acid-base superficial characteristics of some solid substrates such as oxides, polymer and polymer adsorbed on oxide. The acid-base constants were calculated for many solids: Monogal, MgO, ZnO, SiO2 and Al2O3, four different carbon fibres and polymers such as poly(methyl methacrylate) (PMMA) at various tacticities adsorbed on alumina or silica. The determination, by IGC, of the specific free enthalpy deltaG(a)sp of adsorption corresponding to the specific interactions of polar molecules with the solid, as a function of the temperature, allowed to obtain the specific enthalpy deltaH(a)sp and specific entropy deltaS(a)sp. Knowing deltaH(a)sp of the various polar molecules, we were able to determine the acidic constant K(A) and basic constant K(D), the two constants characterizing solid substrates like PMMA, PMMA-SiO2 or PMMA-Al2O3, using the following classical expression: - deltaH(a)sp = K(A)DN + K(D)AN where DN and AN are respectively the electron donor and acceptor numbers of the solid substrates. This study showed an important effect of the tacticity on the acid-base properties. On the other hand, we proved that the previous relation was not correct in many cases and especially for some oxides (as MgO, ZnO and Monogal) and carbon fibres. We proposed a new relationship by adding a third parameter K reflecting the amphoteric character of the solid according to: - deltaH(a)sp = K(A)DN + K(D)AN - KDN x AN.
Rutkevich, Sergei B; Diehl, H W
2015-06-01
The O(n) ϕ(4) model on a strip bounded by a pair of planar free surfaces at separation L can be solved exactly in the large-n limit in terms of the eigenvalues and eigenfunctions of a self-consistent one-dimensional Schrödinger equation. The scaling limit of a continuum version of this model is considered. It is shown that the self-consistent potential can be eliminated in favor of scattering data by means of appropriately extended methods of inverse scattering theory. The scattering data (Jost function) associated with the self-consistent potential are determined for the L=∞ semi-infinite case in the scaling regime for all values of the temperature scaling field t=(T-T(c))/T(c) above and below the bulk critical temperature T(c). These results are used in conjunction with semiclassical and boundary-operator expansions and a trace formula to derive exact analytical results for a number of quantities such as two-point functions, universal amplitudes of two excess surface quantities, the universal amplitude difference associated with the thermal singularity of the surface free energy, and potential coefficients. The asymptotic behaviors of the scaled eigenenergies and eigenfunctions of the self-consistent Schrödinger equation as function of x=t(L/ξ(+))(1/ν) are determined for x→-∞. In addition, the asymptotic x→-∞ forms of the universal finite-size scaling functions Θ(x) and ϑ(x) of the residual free energy and the Casimir force are computed exactly to order 1/x, including their x(-1)ln|x| anomalies.
Wang, Aijun; Zeng, Yanwei; Han, Longxiang; Ding, Chuan; Cao, Liangliang; Li, Rongjie
2015-09-01
Aggregation-free spherical lanthanum-doped bismuth titanate (Bi3.25La0.75Ti3O12, BLT) gel particles with an average size of about 150 nm were successfully obtained from an inverse miniemulsion sol-gel process, with Span-80 acting as surfactant, n-butanol as co-surfactant, cyclohexane as continuous phase, and submicro-droplets of aqueous solution containing Bi3+, La3+ and Ti4+ ions as dispersed phase, and then topotactically transformed into highly dispersed spherical BLT nanocrystals after an in situ crystallization at 600 °C for 8 h. It has been found that the BLT gel particles can be obtained via a moderate sol-gel reaction inside the miniemulsion droplets at 65 °C, but their morphology and aggregation degree are strongly affected by the relative amounts of Span-80 and n-butanol. The perfect spherical BLT gel particles with no aggregation can be achieved only under the condition of 3 wt% n-butanol relative to the mass of cyclohexane, with excessive amount of n-butanol leading to the formation of ill-gelled particles with irregular shapes, while insufficient addition of n-butanol resulting in terrible aggregation of gel particles. To understand the formation of aggregation-free spherical BLT gel particles, a tentative mechanism is proposed and discussed, which reveals that a well-coordinated oil-water interfacial film made up of Span-80 and n-butanol molecules and the appropriately enhanced evaporation of water from such interfaces should be responsible for the formation of aggregation-free spherical BLT gel particles.
Application of Extreme Learning Machines to inverse neutron kinetics
International Nuclear Information System (INIS)
Picca, Paolo; Furfaro, Roberto
2017-01-01
Highlights: • The paper applies the Extreme Learning Machines (ELMs) to inverse reactor problems. • Multi-group transport model is used for the inversion as opposed to point kinetics. • ELMs are compared against Artificial Neural Networks (ANNs). • Various options are tested to improve the reliability of the estimation. • Results highlight the potential of the ELM approach. - Abstract: The paper presents the application of Extreme Leaning Machines (ELMs) for inverse reactor kinetic applications. ELMs were proposed by Huang and co-workers (2004, 2006a,b, 2015), which showed their enhances capabilities in terms of training speed and generalization with respect to classical Artificial Neural Networks (ANNs). ELMs are here implemented for reactivity determination as an alternative to ANNs (e.g. Picca et al. (2008)) and Gaussian Processes (Picca and Furfaro, 2012). After a review of the main features of ELMs, their application to inverse kinetic problems is proposed. The ELMs performance is tested on a typical accelerator drive system configuration (Yalina reactor) and the inversion is carried out on an accurate kinetic model (multi-group transport).
Iterative optimization in inverse problems
Byrne, Charles L
2014-01-01
Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization, and statistical estimation. It incorporates recent work that has not appeared in other books and draws on the author's considerable research in the field, including his recently developed class of SUMMA algorithms. Related to sequential unconstrained minimization methods, the SUMMA class includes a wide range of iterative algorithms well known to researchers in various areas, such as statistics and image processing. Organizing the topics from general to more
Liu, Gao-Lian
1991-01-01
Advances in inverse design and optimization theory in engineering fields in China are presented. Two original approaches, the image-space approach and the variational approach, are discussed in terms of turbomachine aerodynamic inverse design. Other areas of research in turbomachine aerodynamic inverse design include the improved mean-streamline (stream surface) method and optimization theory based on optimal control. Among the additional engineering fields discussed are the following: the inverse problem of heat conduction, free-surface flow, variational cogeneration of optimal grid and flow field, and optimal meshing theory of gears.
Improving rotorcraft survivability to RPG attack using inverse methods
Anderson, D.; Thomson, D. G.
2009-09-01
This paper presents the results of a preliminary investigation of optimal threat evasion strategies for improving the survivability of rotorcraft under attack by rocket propelled grenades (RPGs). The basis of this approach is the application of inverse simulation techniques pioneered for simulation of aggressive helicopter manoeuvres to the RPG engagement problem. In this research, improvements in survivability are achieved by computing effective evasive manoeuvres. The first step in this process uses the missile approach warning system camera (MAWS) on the aircraft to provide angular information of the threat. Estimates of the RPG trajectory and impact point are then estimated. For the current flight state an appropriate evasion response is selected then realised via inverse simulation of the platform dynamics. Results are presented for several representative engagements showing the efficacy of the approach.
Energy Technology Data Exchange (ETDEWEB)
Pelle, L.
2003-12-01
The removal of multiple reflections remains a real problem in seismic imaging. Many preprocessing methods have been developed to attenuate multiples in seismic data but none of them is satisfactory in 3D. The objective of this thesis is to develop a new method to remove multiples, extensible in 3D. Contrary to the existing methods, our approach is not a preprocessing step: we directly include the multiple removal in the imaging process by means of a simultaneous inversion of primaries and multiples. We then propose to improve the standard linearized inversion so as to make it insensitive to the presence of multiples in the data. We exploit kinematics differences between primaries and multiples. We propose to pick in the data the kinematics of the multiples we want to remove. The wave field is decomposed into primaries and multiples. Primaries are modeled by the Ray+Born operator from perturbations of the logarithm of impedance, given the velocity field. Multiples are modeled by the Transport operator from an initial trace, given the picking. The inverse problem simultaneously fits primaries and multiples to the data. To solve this problem with two unknowns, we take advantage of the isometric nature of the Transport operator, which allows to drastically reduce the CPU time: this simultaneous inversion is this almost as fast as the standard linearized inversion. This gain of time opens the way to different applications to multiple removal and in particular, allows to foresee the straightforward 3D extension. (author)
Inverse design of multicomponent assemblies
Piñeros, William D.; Lindquist, Beth A.; Jadrich, Ryan B.; Truskett, Thomas M.
2018-03-01
Inverse design can be a useful strategy for discovering interactions that drive particles to spontaneously self-assemble into a desired structure. Here, we extend an inverse design methodology—relative entropy optimization—to determine isotropic interactions that promote assembly of targeted multicomponent phases, and we apply this extension to design interactions for a variety of binary crystals ranging from compact triangular and square architectures to highly open structures with dodecagonal and octadecagonal motifs. We compare the resulting optimized (self- and cross) interactions for the binary assemblies to those obtained from optimization of analogous single-component systems. This comparison reveals that self-interactions act as a "primer" to position particles at approximately correct coordination shell distances, while cross interactions act as the "binder" that refines and locks the system into the desired configuration. For simpler binary targets, it is possible to successfully design self-assembling systems while restricting one of these interaction types to be a hard-core-like potential. However, optimization of both self- and cross interaction types appears necessary to design for assembly of more complex or open structures.
LHC Report: 2 inverse femtobarns!
Mike Lamont for the LHC Team
2011-01-01
The LHC is enjoying a confluence of twos. This morning (Friday 5 August) we passed 2 inverse femtobarns delivered in 2011; the peak luminosity is now just over 2 x1033 cm-2s-1; and recently fill 2000 was in for nearly 22 hours and delivered around 90 inverse picobarns, almost twice 2010's total. In order to increase the luminosity we can increase of number of bunches, increase the number of particles per bunch, or decrease the transverse beam size at the interaction point. The beam size can be tackled in two ways: either reduce the size of the injected bunches or squeeze harder with the quadrupole magnets situated on either side of the experiments. Having increased the number of bunches to 1380, the maximum possible with a 50 ns bunch spacing, a one day meeting in Crozet decided to explore the other possibilities. The size of the beams coming from the injectors has been reduced to the minimum possible. This has brought an increase in the peak luminosity of about 50% and the 2 x 1033 cm...
Inverse problems in systems biology
International Nuclear Information System (INIS)
Engl, Heinz W; Lu, James; Müller, Stefan; Flamm, Christoph; Schuster, Peter; Kügler, Philipp
2009-01-01
Systems biology is a new discipline built upon the premise that an understanding of how cells and organisms carry out their functions cannot be gained by looking at cellular components in isolation. Instead, consideration of the interplay between the parts of systems is indispensable for analyzing, modeling, and predicting systems' behavior. Studying biological processes under this premise, systems biology combines experimental techniques and computational methods in order to construct predictive models. Both in building and utilizing models of biological systems, inverse problems arise at several occasions, for example, (i) when experimental time series and steady state data are used to construct biochemical reaction networks, (ii) when model parameters are identified that capture underlying mechanisms or (iii) when desired qualitative behavior such as bistability or limit cycle oscillations is engineered by proper choices of parameter combinations. In this paper we review principles of the modeling process in systems biology and illustrate the ill-posedness and regularization of parameter identification problems in that context. Furthermore, we discuss the methodology of qualitative inverse problems and demonstrate how sparsity enforcing regularization allows the determination of key reaction mechanisms underlying the qualitative behavior. (topical review)
Inverse problems and inverse scattering of plane waves
Ghosh Roy, Dilip N
2001-01-01
The purpose of this text is to present the theory and mathematics of inverse scattering, in a simple way, to the many researchers and professionals who use it in their everyday research. While applications range across a broad spectrum of disciplines, examples in this text will focus primarly, but not exclusively, on acoustics. The text will be especially valuable for those applied workers who would like to delve more deeply into the fundamentally mathematical character of the subject matter.Practitioners in this field comprise applied physicists, engineers, and technologists, whereas the theory is almost entirely in the domain of abstract mathematics. This gulf between the two, if bridged, can only lead to improvement in the level of scholarship in this highly important discipline. This is the book''s primary focus.
Multiparameter Elastic Full Waveform Inversion with Facies-based Constraints
Zhang, Zhen-dong; Alkhalifah, Tariq; Naeini, Ehsan Zabihi; Sun, Bingbing
2018-03-01
Full waveform inversion (FWI) incorporates all the data characteristics to estimate the parameters described by the assumed physics of the subsurface. However, current efforts to utilize full waveform inversion beyond improved acoustic imaging, like in reservoir delineation, faces inherent challenges related to the limited resolution and the potential trade-off between the elastic model parameters. Some anisotropic parameters are insufficiently updated because of their minor contributions to the surface collected data. Adding rock physics constraints to the inversion helps mitigate such limited sensitivity, but current approaches to add such constraints are based on including them as a priori knowledge mostly valid around the well or as a global constraint for the whole area. Since similar rock formations inside the Earth admit consistent elastic properties and relative values of elasticity and anisotropy parameters (this enables us to define them as a seismic facies), utilizing such localized facies information in FWI can improve the resolution of inverted parameters. We propose a novel approach to use facies-based constraints in both isotropic and anisotropic elastic FWI. We invert for such facies using Bayesian theory and update them at each iteration of the inversion using both the inverted models and a prior information. We take the uncertainties of the estimated parameters (approximated by radiation patterns) into consideration and improve the quality of estimated facies maps. Four numerical examples corresponding to different acquisition, physical assumptions and model circumstances are used to verify the effectiveness of the proposed method.
Multisource waveform inversion of marine streamer data using normalized wavefield
Choi, Yun Seok
2013-09-01
Multisource full-waveform inversion based on the L1- and L2-norm objective functions cannot be applied to marine streamer data because it does not take into account the unmatched acquisition geometries between the observed and modeled data. To apply multisource full-waveform inversion to marine streamer data, we construct the L1- and L2-norm objective functions using the normalized wavefield. The new residual seismograms obtained from the L1- and L2-norms using the normalized wavefield mitigate the problem of unmatched acquisition geometries, which enables multisource full-waveform inversion to work with marine streamer data. In the new approaches using the normalized wavefield, we used the back-propagation algorithm based on the adjoint-state technique to efficiently calculate the gradients of the objective functions. Numerical examples showed that multisource full-waveform inversion using the normalized wavefield yields much better convergence for marine streamer data than conventional approaches. © 2013 Society of Exploration Geophysicists.
Multiparameter Elastic Full Waveform Inversion with Facies-based Constraints
Zhang, Zhendong
2018-03-20
Full waveform inversion (FWI) incorporates all the data characteristics to estimate the parameters described by the assumed physics of the subsurface. However, current efforts to utilize full waveform inversion beyond improved acoustic imaging, like in reservoir delineation, faces inherent challenges related to the limited resolution and the potential trade-off between the elastic model parameters. Some anisotropic parameters are insufficiently updated because of their minor contributions to the surface collected data. Adding rock physics constraints to the inversion helps mitigate such limited sensitivity, but current approaches to add such constraints are based on including them as a priori knowledge mostly valid around the well or as a global constraint for the whole area. Since similar rock formations inside the Earth admit consistent elastic properties and relative values of elasticity and anisotropy parameters (this enables us to define them as a seismic facies), utilizing such localized facies information in FWI can improve the resolution of inverted parameters. We propose a novel approach to use facies-based constraints in both isotropic and anisotropic elastic FWI. We invert for such facies using Bayesian theory and update them at each iteration of the inversion using both the inverted models and a prior information. We take the uncertainties of the estimated parameters (approximated by radiation patterns) into consideration and improve the quality of estimated facies maps. Four numerical examples corresponding to different acquisition, physical assumptions and model circumstances are used to verify the effectiveness of the proposed method.
A finite-difference contrast source inversion method
International Nuclear Information System (INIS)
Abubakar, A; Hu, W; Habashy, T M; Van den Berg, P M
2008-01-01
We present a contrast source inversion (CSI) algorithm using a finite-difference (FD) approach as its backbone for reconstructing the unknown material properties of inhomogeneous objects embedded in a known inhomogeneous background medium. Unlike the CSI method using the integral equation (IE) approach, the FD-CSI method can readily employ an arbitrary inhomogeneous medium as its background. The ability to use an inhomogeneous background medium has made this algorithm very suitable to be used in through-wall imaging and time-lapse inversion applications. Similar to the IE-CSI algorithm the unknown contrast sources and contrast function are updated alternately to reconstruct the unknown objects without requiring the solution of the full forward problem at each iteration step in the optimization process. The FD solver is formulated in the frequency domain and it is equipped with a perfectly matched layer (PML) absorbing boundary condition. The FD operator used in the FD-CSI method is only dependent on the background medium and the frequency of operation, thus it does not change throughout the inversion process. Therefore, at least for the two-dimensional (2D) configurations, where the size of the stiffness matrix is manageable, the FD stiffness matrix can be inverted using a non-iterative inversion matrix approach such as a Gauss elimination method for the sparse matrix. In this case, an LU decomposition needs to be done only once and can then be reused for multiple source positions and in successive iterations of the inversion. Numerical experiments show that this FD-CSI algorithm has an excellent performance for inverting inhomogeneous objects embedded in an inhomogeneous background medium
Directional genomic hybridization for chromosomal inversion discovery and detection.
Ray, F Andrew; Zimmerman, Erin; Robinson, Bruce; Cornforth, Michael N; Bedford, Joel S; Goodwin, Edwin H; Bailey, Susan M
2013-04-01
Chromosomal rearrangements are a source of structural variation within the genome that figure prominently in human disease, where the importance of translocations and deletions is well recognized. In principle, inversions-reversals in the orientation of DNA sequences within a chromosome-should have similar detrimental potential. However, the study of inversions has been hampered by traditional approaches used for their detection, which are not particularly robust. Even with significant advances in whole genome approaches, changes in the absolute orientation of DNA remain difficult to detect routinely. Consequently, our understanding of inversions is still surprisingly limited, as is our appreciation for their frequency and involvement in human disease. Here, we introduce the directional genomic hybridization methodology of chromatid painting-a whole new way of looking at structural features of the genome-that can be employed with high resolution on a cell-by-cell basis, and demonstrate its basic capabilities for genome-wide discovery and targeted detection of inversions. Bioinformatics enabled development of sequence- and strand-specific directional probe sets, which when coupled with single-stranded hybridization, greatly improved the resolution and ease of inversion detection. We highlight examples of the far-ranging applicability of this cytogenomics-based approach, which include confirmation of the alignment of the human genome database and evidence that individuals themselves share similar sequence directionality, as well as use in comparative and evolutionary studies for any species whose genome has been sequenced. In addition to applications related to basic mechanistic studies, the information obtainable with strand-specific hybridization strategies may ultimately enable novel gene discovery, thereby benefitting the diagnosis and treatment of a variety of human disease states and disorders including cancer, autism, and idiopathic infertility.
Experimental characterization of methane inverse diffusion flame
Elbaz, Ayman M.
2014-06-26
This article presents 10-kHz images of OH-PLIF simultaneously with 2-D PIV measurements in an inverse methane diffusion flame. Under a constant fuel flow rate, the central air jet Re was varied, leading to air to fuel velocity ratio, Vr, to vary from 8.3 to 66.5. Starting from Vr = 20.7, the flame is commonly characterized by three distinct zones. The length of the lower fuel entrainment region is inversely proportional to Vr. The flames investigated resemble a string shear layer confining this zone, and converging into the second distinct region, the flame neck zone. The third region is the rest of the flame, which spreads in a jet-like manner. The inverse diffusion flames exhibit varying degrees of partial premixing, depending upon on the velocity ratio Vr, and this region of partial premixing evolves into a well-mixed reaction zone along the flame centerline. The OH distribution correlated with the changes in the mean characteristics of the flow through reduction in the local Reynolds number due to heat release. The existence of a flame suppresses or laminarizes the turbulence at early axial locations and promotes fluctuations at the flame tip for flames with Vr < 49.8. In addition, the flame jet width can be correlated to the OH distribution. In upstream regions of the flames, the breaks in OH are counterbalanced by flame closures and are governed by edge flame propagation. These local extinctions were found to occur at locations where large flow structures were impinging on the flame and are associated with a locally higher strain rate or correlated to the local high strain rates at the flame hole edges without this flow impinging. Another contributor to re-ignition was found to be growing flame kernels. As the flames approach global blow-off, these kernels become the main mechanism for re-ignition further downstream of the flames. At low Vr, laminarization within the early regions of the flame provides an effective shield, preventing the jet flow from
Direct Waveform Inversion: a New Recursive Scheme
Zheng, Y.
2015-12-01
The goal of the full-waveform inversion (FWI) is to find an Earth's model such that the synthetic waveforms computed using the model fit the observed ones. In practice, such a model is found in the context of the perturbation approach in an iterative fashion. Specifically, to find such a model, one starts from an initial global velocity model and perform model updating iteratively based on the Frechet derivative or single scattering by adjoint methods to minimize some cost function. However, this process often leads to local minima for the nonlinear cost function in the optimization and slow or no convergence when the starting model is far from the true model. To solve for the initial-model dependence and the convergence issue, we show a new direct waveform inversion (DWI) idea to directly invert the waveform data recursively by explicitly enforcing the causality principle. The DWI offers the advantage of assuming no global initial model and no iteration is needed for the model updating. Starting from the source-receiver region, the DWI builds the model outward recursively by fitting the earliest part of the reflection waveforms and the DWI process is always convergent. The DWI combines seismic imaging and velocity model building into one single process and this is in contrast to many industrial applications where seismic imaging/migration and velocity modeling building are done alternatively. The DWI idea is applicable to one-, two-, and three-dimensional spaces. We show numerical examples to support our idea using full waveform data including both free-surface and inter-bed multiples. Using reflection seismic data, we show that the DWI can invert for both velocity and density, separately.
Neural learning of robot inverse kinematics transformations
Gupta, M. M.
1994-06-01
The accuracy of a robot arm is determined by its ability to move in a given particular task space to specific Cartesian positions that are not necessarily pretaught. As a consequence, the inverse kinematics is an important problem as it must be solved in real-time in order to position the end-effector at an appropriate Cartesian location. However, it is a difficult and challenging problem for it involves the determination whether or not at least one mathematical set of robot joint angle values exists that will produce a desired coordinate configuration. The mathematical solutions should be checked against the physical constraints associated with the manipulator. Many times, a solution many not be physically realizable in a constrained environment. The advent of artificial neural networks has made it possible to obtain general learning schemes which can be used to arrive at feasible solutions to inverse kinematics problem in a constrained environment independent of a robotic structure. In this paper, we present such a learning scheme using a dynamic neural processor (DNP). This neural model functionally mimics the subpopulation of biological neurons. For analytical simplicity, only two subpopulations of neurons, namely excitatory and inhibitory, are assumed to coexist. The DNP is a neural network structure consisting of two dynamic neural units coupled as excitatory and inhibitory neurons. It is demonstrated in this study that the DNP would avoid time consuming numerical calculations and provide, more or less, instant recall of the learned associations. The learning and adaptive nature of this neural approach is demonstrated for two- and three-linked robots.
Sensitivity analysis of distributed volcanic source inversion
Cannavo', Flavio; Camacho, Antonio G.; González, Pablo J.; Puglisi, Giuseppe; Fernández, José
2016-04-01
A recently proposed algorithm (Camacho et al., 2011) claims to rapidly estimate magmatic sources from surface geodetic data without any a priori assumption about source geometry. The algorithm takes the advantages of fast calculation from the analytical models and adds the capability to model free-shape distributed sources. Assuming homogenous elastic conditions, the approach can determine general geometrical configurations of pressured and/or density source and/or sliding structures corresponding to prescribed values of anomalous density, pressure and slip. These source bodies are described as aggregation of elemental point sources for pressure, density and slip, and they fit the whole data (keeping some 3D regularity conditions). Although some examples and applications have been already presented to demonstrate the ability of the algorithm in reconstructing a magma pressure source (e.g. Camacho et al., 2011,Cannavò et al., 2015), a systematic analysis of sensitivity and reliability of the algorithm is still lacking. In this explorative work we present results from a large statistical test designed to evaluate the advantages and limitations of the methodology by assessing its sensitivity to the free and constrained parameters involved in inversions. In particular, besides the source parameters, we focused on the ground deformation network topology, and noise in measurements. The proposed analysis can be used for a better interpretation of the algorithm results in real-case applications. Camacho, A. G., González, P. J., Fernández, J. & Berrino, G. (2011) Simultaneous inversion of surface deformation and gravity changes by means of extended bodies with a free geometry: Application to deforming calderas. J. Geophys. Res. 116. Cannavò F., Camacho A.G., González P.J., Mattia M., Puglisi G., Fernández J. (2015) Real Time Tracking of Magmatic Intrusions by means of Ground Deformation Modeling during Volcanic Crises, Scientific Reports, 5 (10970) doi:10.1038/srep
Statistical Inversion of Seismic Noise Inversion statistique du bruit sismique
Directory of Open Access Journals (Sweden)
Adler P. M.
2006-11-01
Full Text Available A systematic investigation of wave propagation in random media is presented. Spectral analysis, inversion of codas and attenuation of the direct wave front are studied for synthetic data obtained in isotropic or anisotropic, 2D or 3D media. A coda inversion process is developed and checked on two sets of real data. In both cases, it is possible to compare the correlation lengths obtained by inversion to characteristic lengths measured on seismic logs, for the full scale seismic survey, or on a thin section, for the laboratory experiment. These two experiments prove the feasibility and the efficiency of the statistical inversion of codas. Correct characteristic lengths can be obtained which cannot be determined by another method. Le problème de la géophysique est la recherche d'informations concernant le sous-sol, dans des signaux sismiques enregistrés en surface ou dans des puits. Ces informations sont habituellement recherchées sous forme déterministe, c'est-à-dire sous la forme de la donnée en chaque point d'une valeur du paramètre étudié. Notre point de vue est différent puisque notre objectif est de déduire certaines propriétés statistiques du milieu, supposé hétérogène, à partir des sismogrammes enregistrés après propagation. Il apparaît alors deux moyens de remplir l'objectif fixé. Le premier est l'analyse spectrale des codas ; cette analyse permet de déterminer les tailles moyennes des hétérogénéités du sous-sol. La deuxième possibilité est l'étude de l'atténuation du front direct de l'onde, qui conduit aussi à la connaissance des longueurs caractéristiques du sous-sol ; contrairement à la première méthode, elle ne semble pas pouvoir être transposée efficacement à des cas réels. Dans la première partie, on teste numériquement la proportionnalité entre le facteur de rétrodiffraction, relié aux propriétés statistiques du milieu, et le spectre des codas. Les distributions de vitesse, à valeur
Solution for Ill-Posed Inverse Kinematics of Robot Arm by Network Inversion
Directory of Open Access Journals (Sweden)
Takehiko Ogawa
2010-01-01
Full Text Available In the context of controlling a robot arm with multiple joints, the method of estimating the joint angles from the given end-effector coordinates is called inverse kinematics, which is a type of inverse problems. Network inversion has been proposed as a method for solving inverse problems by using a multilayer neural network. In this paper, network inversion is introduced as a method to solve the inverse kinematics problem of a robot arm with multiple joints, where the joint angles are estimated from the given end-effector coordinates. In general, inverse problems are affected by ill-posedness, which implies that the existence, uniqueness, and stability of their solutions are not guaranteed. In this paper, we show the effectiveness of applying network inversion with regularization, by which ill-posedness can be reduced, to the ill-posed inverse kinematics of an actual robot arm with multiple joints.
Inverse problem in neutron reflection
International Nuclear Information System (INIS)
Zhou, Xiao-Lin; Felcher, G.P.; Chen, Sow-Hsin
1991-05-01
Reflectance and transmittance of neutrons from a thin film deposited on a bulk substrate are derived from solution of Schroedinger wave equation in the material medium with an optical potential. A closed-form solution for the complex reflectance and transmittance is obtained in an approximation where the curvature of the scattering length density profile in the film is small. This closed-form solution reduces to all the known approximations in various limiting cases and is shown to be more accurate than the existing approximations. The closed-form solution of the reflectance is used as a starting point for an inversion algorithm whereby the reflectance data are inverted by a matrix iteration scheme to obtain the scattering length density distribution in the film. A preliminary test showed that the inverted profile is accurate for the linear scattering length density distribution but falls short in the case of an exponential distribution. 30 refs., 7 figs., 1 tab
Development of an inverse method for coastal risk management
Directory of Open Access Journals (Sweden)
D. Idier
2013-04-01
Full Text Available Recent flooding events, like Katrina (USA, 2005 or Xynthia (France, 2010, illustrate the complexity of coastal systems and the limits of traditional flood risk analysis. Among other questions, these events raised issues such as: "how to choose flooding scenarios for risk management purposes?", "how to make a society more aware and prepared for such events?" and "which level of risk is acceptable to a population?". The present paper aims at developing an inverse approach that could seek to address these three issues. The main idea of the proposed method is the inversion of the usual risk assessment steps: starting from the maximum acceptable hazard level (defined by stakeholders as the one leading to the maximum tolerable consequences to finally obtain the return period of this threshold. Such an "inverse" approach would allow for the identification of all the offshore forcing conditions (and their occurrence probability inducing a threat for critical assets of the territory, such information being of great importance for coastal risk management. This paper presents the first stage in developing such a procedure. It focuses on estimation (through inversion of the flooding model of the offshore conditions leading to the acceptable hazard level, estimation of the return period of the associated combinations, and thus of the maximum acceptable hazard level. A first application for a simplified case study (based on real data, located on the French Mediterranean coast, is presented, assuming a maximum acceptable hazard level. Even if only one part of the full inverse method has been developed, we demonstrate how the inverse method can be useful in (1 estimating the probability of exceeding the maximum inundation height for identified critical assets, (2 providing critical offshore conditions for flooding in early warning systems, and (3 raising awareness of stakeholders and eventually enhance preparedness for future flooding events by allowing them to
Wake Vortex Inverse Model User's Guide
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
A framework for simulation and inversion in electromagnetics
Heagy, Lindsey J.; Cockett, Rowan; Kang, Seogi; Rosenkjaer, Gudni K.; Oldenburg, Douglas W.
2017-10-01
Simulations and inversions of electromagnetic geophysical data are paramount for discerning meaningful information about the subsurface from these data. Depending on the nature of the source electromagnetic experiments may be classified as time-domain or frequency-domain. Multiple heterogeneous and sometimes anisotropic physical properties, including electrical conductivity and magnetic permeability, may need be considered in a simulation. Depending on what one wants to accomplish in an inversion, the parameters which one inverts for may be a voxel-based description of the earth or some parametric representation that must be mapped onto a simulation mesh. Each of these permutations of the electromagnetic problem has implications in a numerical implementation of the forward simulation as well as in the computation of the sensitivities, which are required when considering gradient-based inversions. This paper proposes a framework for organizing and implementing electromagnetic simulations and gradient-based inversions in a modular, extensible fashion. We take an object-oriented approach for defining and organizing each of the necessary elements in an electromagnetic simulation, including: the physical properties, sources, formulation of the discrete problem to be solved, the resulting fields and fluxes, and receivers used to sample to the electromagnetic responses. A corresponding implementation is provided as part of the open source simulation and parameter estimation project SIMPEG (http://simpeg.xyz). The application of the framework is demonstrated through two synthetic examples and one field example. The first example shows the application of the common framework for 1D time domain and frequency domain inversions. The second is a field example that demonstrates a 1D inversion of electromagnetic data collected over the Bookpurnong Irrigation District in Australia. The final example is a 3D example which shows how the modular implementation is used to compute the
A comparative study of hole and electron inversion layer quantization in MOS structures
Directory of Open Access Journals (Sweden)
Chaudhry Amit
2010-01-01
Full Text Available In this paper, an analytical model has been developed to study inversion layer quantization in nanoscale Metal Oxide Semiconductor Field Effect Oxide p-(MOSFET. n-MOSFETs have been studied using the variation approach and the p-MOSFETs have been studied using the triangular well approach. The inversion charge density and gate capacitance analysis for both types of transistors has been done. There is a marked decrease in the inversion charge density and the capacitance of the p-MOSFET as compared to n-MOSFETs. The results are compared with the numerical results showing good agreement.
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 Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
Optimization and inverse problems in electromagnetism
Wiak, Sławomir
2003-01-01
From 12 to 14 September 2002, the Academy of Humanities and Economics (AHE) hosted the workshop "Optimization and Inverse Problems in Electromagnetism". After this bi-annual event, a large number of papers were assembled and combined in this book. During the workshop recent developments and applications in optimization and inverse methodologies for electromagnetic fields were discussed. The contributions selected for the present volume cover a wide spectrum of inverse and optimal electromagnetic methodologies, ranging from theoretical to practical applications. A number of new optimal and inverse methodologies were proposed. There are contributions related to dedicated software. Optimization and Inverse Problems in Electromagnetism consists of three thematic chapters, covering: -General papers (survey of specific aspects of optimization and inverse problems in electromagnetism), -Methodologies, -Industrial Applications. The book can be useful to students of electrical and electronics engineering, computer sci...
Identifiability Scaling Laws in Bilinear Inverse Problems
Choudhary, Sunav; Mitra, Urbashi
2014-01-01
A number of ill-posed inverse problems in signal processing, like blind deconvolution, matrix factorization, dictionary learning and blind source separation share the common characteristic of being bilinear inverse problems (BIPs), i.e. the observation model is a function of two variables and conditioned on one variable being known, the observation is a linear function of the other variable. A key issue that arises for such inverse problems is that of identifiability, i.e. whether the observa...
Lectures on the inverse scattering method
International Nuclear Information System (INIS)
Zakharov, V.E.
1983-06-01
In a series of six lectures an elementary introduction to the theory of inverse scattering is given. The first four lectures contain a detailed theory of solitons in the framework of the KdV equation, together with the inverse scattering theory of the one-dimensional Schroedinger equation. In the fifth lecture the dressing method is described, while the sixth lecture gives a brief review of the equations soluble by the inverse scattering method. (author)
Inverse kinematics of OWI-535 robotic arm
DEBENEC, PRIMOŽ
2015-01-01
The thesis aims to calculate the inverse kinematics for the OWI-535 robotic arm. The calculation of the inverse kinematics determines the joint parameters that provide the right pose of the end effector. The pose consists of the position and orientation, however, we will focus only on the second one. Due to arm limitations, we have created our own type of the calculation of the inverse kinematics. At first we have derived it only theoretically, and then we have transferred the derivation into...
Automatic Flight Controller With Model Inversion
Meyer, George; Smith, G. Allan
1992-01-01
Automatic digital electronic control system based on inverse-model-follower concept being developed for proposed vertical-attitude-takeoff-and-landing airplane. Inverse-model-follower control places inverse mathematical model of dynamics of controlled plant in series with control actuators of controlled plant so response of combination of model and plant to command is unity. System includes feedback to compensate for uncertainties in mathematical model and disturbances imposed from without.
3-D cross-gradient joint inversion of seismic refraction and DC resistivity data
Shi, Zhanjie; Hobbs, Richard W.; Moorkamp, Max; Tian, Gang; Jiang, Lu
2017-06-01
We present a 3-D cross-gradient joint inversion algorithm for seismic refraction and DC resistivity data. The structural similarity between seismic slowness and resistivity models is enforced by a cross-gradient term in the objective function that also includes misfit and regularization terms. A limited memory quasi-Newton approach is used to perform the optimization of the objective function. To validate the proposed methodology and its implementation, tests were performed on a typical archaeological geophysical synthetic model. The results show that the inversion model and physical parameters estimated by our joint inversion method are more consistent with the true model than those from single inversion algorithm. Moreover, our approach appears to be more robust in conditions of noise. Finally, the 3-D cross-gradient joint inversion algorithm was applied to the field data from Lin_an ancient city site in Hangzhou of China. The 3-D cross-gradient joint inversion models are consistent with the archaeological excavation results of the ancient city wall remains. However, by single inversion, seismic slowness model does not show the anomaly of city wall remains and resistivity model does not fit well with the archaeological excavation results. Through these comparisons, we conclude that the proposed algorithm can be used to jointly invert 3-D seismic refraction and DC resistivity data to reduce the uncertainty brought by single inversion scheme.
Introduction to ground penetrating radar inverse scattering and data processing
Persico, Raffaele
2014-01-01
This book presents a comprehensive treatment of ground penetrating radar using both forward and inverse scattering mathematical techniques. Use of field data instead of laboratory data enables readers to envision real-life underground imaging; a full color insert further clarifies understanding. Along with considering the practical problem of achieving interpretable underground images, this book also features significant coverage of the problem's mathematical background. This twofold approach provides a resource that will appeal both to application oriented geologists and testing specialists,
Iterative Reconstruction Methods for Hybrid Inverse Problems in Impedance Tomography
DEFF Research Database (Denmark)
Hoffmann, Kristoffer; Knudsen, Kim
2014-01-01
For a general formulation of hybrid inverse problems in impedance tomography the Picard and Newton iterative schemes are adapted and four iterative reconstruction algorithms are developed. The general problem formulation includes several existing hybrid imaging modalities such as current density...... impedance imaging, magnetic resonance electrical impedance tomography, and ultrasound modulated electrical impedance tomography, and the unified approach to the reconstruction problem encompasses several algorithms suggested in the literature. The four proposed algorithms are implemented numerically in two...
ANNIT - An Efficient Inversion Algorithm based on Prediction Principles
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
2D Inversion of Transient Electromagnetic Method (TEM)
Bortolozo, Cassiano Antonio; Luís Porsani, Jorge; Acácio Monteiro dos Santos, Fernando
2017-04-01
A new methodology was developed for 2D inversion of Transient Electromagnetic Method (TEM). The methodology consists in the elaboration of a set of routines in Matlab code for modeling and inversion of TEM data and the determination of the most efficient field array for the problem. In this research, the 2D TEM modeling uses the finite differences discretization. To solve the inversion problem, were applied an algorithm based on Marquardt technique, also known as Ridge Regression. The algorithm is stable and efficient and it is widely used in geoelectrical inversion problems. The main advantage of 1D survey is the rapid data acquisition in a large area, but in regions with two-dimensional structures or that need more details, is essential to use two-dimensional interpretation methodologies. For an efficient field acquisition we used in an innovative form the fixed-loop array, with a square transmitter loop (200m x 200m) and 25m spacing between the sounding points. The TEM surveys were conducted only inside the transmitter loop, in order to not deal with negative apparent resistivity values. Although it is possible to model the negative values, it makes the inversion convergence more difficult. Therefore the methodology described above has been developed in order to achieve maximum optimization of data acquisition. Since it is necessary only one transmitter loop disposition in the surface for each series of soundings inside the loop. The algorithms were tested with synthetic data and the results were essential to the interpretation of the results with real data and will be useful in future situations. With the inversion of the real data acquired over the Paraná Sedimentary Basin (PSB) was successful realized a 2D TEM inversion. The results indicate a robust geoelectrical characterization for the sedimentary and crystalline aquifers in the PSB. Therefore, using a new and relevant approach for 2D TEM inversion, this research effectively contributed to map the most
International Nuclear Information System (INIS)
Kılıç, Emre; Eibert, Thomas F.
2015-01-01
An approach combining boundary integral and finite element methods is introduced for the solution of three-dimensional inverse electromagnetic medium scattering problems. Based on the equivalence principle, unknown equivalent electric and magnetic surface current densities on a closed surface are utilized to decompose the inverse medium problem into two parts: a linear radiation problem and a nonlinear cavity problem. The first problem is formulated by a boundary integral equation, the computational burden of which is reduced by employing the multilevel fast multipole method (MLFMM). Reconstructed Cauchy data on the surface allows the utilization of the Lorentz reciprocity and the Poynting's theorems. Exploiting these theorems, the noise level and an initial guess are estimated for the cavity problem. Moreover, it is possible to determine whether the material is lossy or not. In the second problem, the estimated surface currents form inhomogeneous boundary conditions of the cavity problem. The cavity problem is formulated by the finite element technique and solved iteratively by the Gauss–Newton method to reconstruct the properties of the object. Regularization for both the first and the second problems is achieved by a Krylov subspace method. The proposed method is tested against both synthetic and experimental data and promising reconstruction results are obtained
Mantle conductivity obtained by 3-D inversion of magnetic satellite data
DEFF Research Database (Denmark)
Kuvshinov, A.; Olsen, Nils
and perform the most consuming-time part of the IE forward simulations (the calculation of electric and magnetic tensor Green’s functions) only once. Approximate calculation of the data sensitivities also gives essential speed up of the inversion. We validate our inversion scheme using synthetic induction......We present an approach to determine the three-dimensional (3-D) conductivity distribution of the Earth’s upper mantle from magnetic satellite data. The approach is based on a minimization of the misfit between the measured and modeled (predicted) magnetic field using a quasi-Newton method, solving...... distributed geomagnetic observatories. Due to the high computational load of a 3-D inversion (requiring thousands of forward calculations), a comprehensive numerical framework is developed to increase the efficiency of the inversion.In particular, we take an advantage of specific features of the IE approach...
Pareto joint inversion of 2D magnetotelluric and gravity data
Miernik, Katarzyna; Bogacz, Adrian; Kozubal, Adam; Danek, Tomasz; Wojdyła, Marek
2015-04-01
In this contribution, the first results of the "Innovative technology of petrophysical parameters estimation of geological media using joint inversion algorithms" project were described. At this stage of the development, Pareto joint inversion scheme for 2D MT and gravity data was used. Additionally, seismic data were provided to set some constrains for the inversion. Sharp Boundary Interface(SBI) approach and description model with set of polygons were used to limit the dimensionality of the solution space. The main engine was based on modified Particle Swarm Optimization(PSO). This algorithm was properly adapted to handle two or more target function at once. Additional algorithm was used to eliminate non- realistic solution proposals. Because PSO is a method of stochastic global optimization, it requires a lot of proposals to be evaluated to find a single Pareto solution and then compose a Pareto front. To optimize this stage parallel computing was used for both inversion engine and 2D MT forward solver. There are many advantages of proposed solution of joint inversion problems. First of all, Pareto scheme eliminates cumbersome rescaling of the target functions, that can highly affect the final solution. Secondly, the whole set of solution is created in one optimization run, providing a choice of the final solution. This choice can be based off qualitative data, that are usually very hard to be incorporated into the regular inversion schema. SBI parameterisation not only limits the problem of dimensionality, but also makes constraining of the solution easier. At this stage of work, decision to test the approach using MT and gravity data was made, because this combination is often used in practice. It is important to mention, that the general solution is not limited to this two methods and it is flexible enough to be used with more than two sources of data. Presented results were obtained for synthetic models, imitating real geological conditions, where
Laterally constrained inversion for CSAMT data interpretation
Wang, Ruo; Yin, Changchun; Wang, Miaoyue; Di, Qingyun
2015-10-01
Laterally constrained inversion (LCI) has been successfully applied to the inversion of dc resistivity, TEM and airborne EM data. However, it hasn't been yet applied to the interpretation of controlled-source audio-frequency magnetotelluric (CSAMT) data. In this paper, we apply the LCI method for CSAMT data inversion by preconditioning the Jacobian matrix. We apply a weighting matrix to Jacobian to balance the sensitivity of model parameters, so that the resolution with respect to different model parameters becomes more uniform. Numerical experiments confirm that this can improve the convergence of the inversion. We first invert a synthetic dataset with and without noise to investigate the effect of LCI applications to CSAMT data, for the noise free data, the results show that the LCI method can recover the true model better compared to the traditional single-station inversion; and for the noisy data, the true model is recovered even with a noise level of 8%, indicating that LCI inversions are to some extent noise insensitive. Then, we re-invert two CSAMT datasets collected respectively in a watershed and a coal mine area in Northern China and compare our results with those from previous inversions. The comparison with the previous inversion in a coal mine shows that LCI method delivers smoother layer interfaces that well correlate to seismic data, while comparison with a global searching algorithm of simulated annealing (SA) in a watershed shows that though both methods deliver very similar good results, however, LCI algorithm presented in this paper runs much faster. The inversion results for the coal mine CSAMT survey show that a conductive water-bearing zone that was not revealed by the previous inversions has been identified by the LCI. This further demonstrates that the method presented in this paper works for CSAMT data inversion.
Adding Image Constraints to Inverse Kinematics for Human Motion Capture
Jaume-i-Capó, Antoni; Varona, Javier; González-Hidalgo, Manuel; Perales, Francisco J.
2009-12-01
In order to study human motion in biomechanical applications, a critical component is to accurately obtain the 3D joint positions of the user's body. Computer vision and inverse kinematics are used to achieve this objective without markers or special devices attached to the body. The problem of these systems is that the inverse kinematics is "blinded" with respect to the projection of body segments into the images used by the computer vision algorithms. In this paper, we present how to add image constraints to inverse kinematics in order to estimate human motion. Specifically, we explain how to define a criterion to use images in order to guide the posture reconstruction of the articulated chain. Tests with synthetic images show how the scheme performs well in an ideal situation. In order to test its potential in real situations, more experiments with task specific image sequences are also presented. By means of a quantitative study of different sequences, the results obtained show how this approach improves the performance of inverse kinematics in this application.
Waveform inversion for acoustic VTI media in frequency domain
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.
Etude sur la prédiction de l'inversion de phase Phase Inversion Behavior for Liquid Dispersions
Directory of Open Access Journals (Sweden)
Decarre S.
2006-12-01
Full Text Available En écoulement diphasique eau-huile dans lequel une des phases est dispersée dans l'autre, il peut se produire sous certaine condition d'écoulement une inversion de phase, la phase continue devenant dispersée. Ce phénomène, qui contrôle la nature de la phase mouillant la paroi de la conduite dans laquelle s'écoulent les phases, a des conséquences importantes sur la corrosion et sur la perte de charge. Nous présentons un modèle d'inversion, basé sur une approche thermodynamique, valable pour tous les régimes d'écoulement. Les données expérimentales utilisées pour la validation du modèle sont issues d'une étude bibliographique. En écoulement laminaire, cette approche conduit à des résultats similaires à ceux du modèle de Yeh. Pour la plupart des données disponibles, ce modèle prédit bien la fraction critique pour laquelle l'inversion de phase se produit. In two phase oil-water dispersed flow, a phase inversion may occur whereby the continuous phase becomes dispersed. This phenomenon which controls the nature of the phase in contact with the pipe has a great importance on the corrosion and on the pressure drop. A model for the phase inversion is presented, it is based on a thermodynamic approach, and it is valid for all flow regimes. Experimental data from the litterature are used to validate the model. In laminar flow, this approach gives similar results to those obtained by Yeh. For most data, the model agrees well with the experimental data.
Bergamaschi, Peter; Karstens, Ute; Manning, Alistair J.; Saunois, Marielle; Tsuruta, Aki; Berchet, Antoine; Vermeulen, Alexander T.; Arnold, Tim; Janssens-Maenhout, Greet; Hammer, Samuel; Levin, Ingeborg; Schmidt, Martina; Ramonet, Michel; Lopez, Morgan; Lavric, Jost; Aalto, Tuula; Chen, Huilin; Feist, Dietrich G.; Gerbig, Christoph; Haszpra, László; Hermansen, Ove; Manca, Giovanni; Moncrieff, John; Meinhardt, Frank; Necki, Jaroslaw; Galkowski, Michal; O'Doherty, Simon; Paramonova, Nina; Scheeren, Hubertus A.; Steinbacher, Martin; Dlugokencky, Ed
2018-01-01
We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006-2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH4 emissions of 26.8 (20.2-29.7) Tg CH4 yr-1 (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006-2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH4 yr-1 (2006) to 18.8 Tg CH4 yr-1 (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3-8.2) Tg CH4 yr-1 from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon
MODEL SELECTION FOR SPECTROPOLARIMETRIC INVERSIONS
International Nuclear Information System (INIS)
Asensio Ramos, A.; Manso Sainz, R.; Martínez González, M. J.; Socas-Navarro, H.; Viticchié, B.; Orozco Suárez, D.
2012-01-01
Inferring magnetic and thermodynamic information from spectropolarimetric observations relies on the assumption of a parameterized model atmosphere whose parameters are tuned by comparison with observations. Often, the choice of the underlying atmospheric model is based on subjective reasons. In other cases, complex models are chosen based on objective reasons (for instance, the necessity to explain asymmetries in the Stokes profiles) but it is not clear what degree of complexity is needed. The lack of an objective way of comparing models has, sometimes, led to opposing views of the solar magnetism because the inferred physical scenarios are essentially different. We present the first quantitative model comparison based on the computation of the Bayesian evidence ratios for spectropolarimetric observations. Our results show that there is not a single model appropriate for all profiles simultaneously. Data with moderate signal-to-noise ratios (S/Ns) favor models without gradients along the line of sight. If the observations show clear circular and linear polarization signals above the noise level, models with gradients along the line are preferred. As a general rule, observations with large S/Ns favor more complex models. We demonstrate that the evidence ratios correlate well with simple proxies. Therefore, we propose to calculate these proxies when carrying out standard least-squares inversions to allow for model comparison in the future.
Inverse problem in radionuclide transport
International Nuclear Information System (INIS)
Yu, C.
1988-01-01
The disposal of radioactive waste must comply with the performance objectives set forth in 10 CFR 61 for low-level waste (LLW) and 10 CFR 60 for high-level waste (HLW). To determine probable compliance, the proposed disposal system can be modeled to predict its performance. One of the difficulties encountered in such a study is modeling the migration of radionuclides through a complex geologic medium for the long term. Although many radionuclide transport models exist in the literature, the accuracy of the model prediction is highly dependent on the model parameters used. The problem of using known parameters in a radionuclide transport model to predict radionuclide concentrations is a direct problem (DP); whereas the reverse of DP, i.e., the parameter identification problem of determining model parameters from known radionuclide concentrations, is called the inverse problem (IP). In this study, a procedure to solve IP is tested, using the regression technique. Several nonlinear regression programs are examined, and the best one is recommended. 13 refs., 1 tab
Reverse Universal Resolving Algorithm and inverse driving
DEFF Research Database (Denmark)
Pécseli, Thomas
2012-01-01
Inverse interpretation is a semantics based, non-standard interpretation of programs. Given a program and a value, an inverse interpreter finds all or one of the inputs, that would yield the given value as output with normal forward evaluation. The Reverse Universal Resolving Algorithm is a new v...
Third Harmonic Imaging using a Pulse Inversion
DEFF Research Database (Denmark)
Rasmussen, Joachim; Du, Yigang; Jensen, Jørgen Arendt
2011-01-01
The pulse inversion (PI) technique can be utilized to separate and enhance harmonic components of a waveform for tissue harmonic imaging. While most ultrasound systems can perform pulse inversion, only few image the 3rd harmonic component. PI pulse subtraction can isolate and enhance the 3rd...
Metaheuristic optimization of acoustic inverse problems.
van Leijen, A.V.; Rothkrantz, L.; Groen, F.
2011-01-01
Swift solving of geoacoustic inverse problems strongly depends on the application of a global optimization scheme. Given a particular inverse problem, this work aims to answer the questions how to select an appropriate metaheuristic search strategy, and how to configure it for optimal performance.
Inverse Filtering Techniques in Speech Analysis | Nwachuku ...
African Journals Online (AJOL)
inverse filtering' has been applied. The unifying features of these techniques are presented, namely: 1. a basis in the source-filter theory of speech production, 2. the use of a network whose transfer function is the inverse of the transfer function of ...
2.5D inversion of CSEM data in a vertically anisotropic earth
International Nuclear Information System (INIS)
Ramananjaona, Christophe; MacGregor, Lucy
2010-01-01
The marine Controlled-Source Electromagnetic (CSEM) method is a low frequency (diffusive) electromagnetic subsurface imaging technique aimed at mapping the electric resistivity of the earth by measuring the response to a source dipole emitting an electromagnetic field in a marine environment. Although assuming isotropy for the inversion is the most straightforward approach, in many situations horizontal layering of the earth strata and grain alignment within earth materials creates electric anisotropy. Ignoring this during interpretation may create artifacts in the inversion results. Accounting for this effect therefore requires adequate forward modelling and inversion procedures. We present here an inversion algorithm for vertically anisotropic media based on finite element modelling, the use of Frechet derivatives, and different types of regularisation. Comparisons between isotropic and anisotropic inversion results are given for the characterisation of an anisotropic earth from data measured in line with the source dipole for both synthetic and real data examples.
Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network
International Nuclear Information System (INIS)
Mai, Huanhuan; Liao, Xiaofeng; Song, Gangbing
2013-01-01
Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller. (paper)
Inverse m-matrices and ultrametric matrices
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.
Solving inverse problems of optical microlithography
Granik, Yuri
2005-05-01
The direct problem of microlithography is to simulate printing features on the wafer under given mask, imaging system, and process characteristics. The goal of inverse problems is to find the best mask and/or imaging system and/or process to print the given wafer features. In this study we will describe and compare solutions of inverse mask problems. Pixel-based inverse problem of mask optimization (or "layout inversion") is harder than inverse source problem, especially for partially-coherent systems. It can be stated as a non-linear constrained minimization problem over complex domain, with large number of variables. We compare method of Nashold projections, variations of Fienap phase-retrieval algorithms, coherent approximation with deconvolution, local variations, and descent searches. We propose electrical field caching technique to substantially speedup the searching algorithms. We demonstrate applications of phase-shifted masks, assist features, and maskless printing.
Forward modeling. Route to electromagnetic inversion
Energy Technology Data Exchange (ETDEWEB)
Groom, R.; Walker, P. [PetRos EiKon Incorporated, Ontario (Canada)
1996-05-01
Inversion of electromagnetic data is a topical subject in the literature, and much time has been devoted to understanding the convergence properties of various inverse methods. The relative lack of success of electromagnetic inversion techniques is partly attributable to the difficulties in the kernel forward modeling software. These difficulties come in two broad classes: (1) Completeness and robustness, and (2) convergence, execution time and model simplicity. If such problems exist in the forward modeling kernel, it was demonstrated that inversion can fail to generate reasonable results. It was suggested that classical inversion techniques, which are based on minimizing a norm of the error between data and the simulated data, will only be successful when these difficulties in forward modeling kernels are properly dealt with. 4 refs., 5 figs.
Stochastic Gabor reflectivity and acoustic impedance inversion
Hariri Naghadeh, Diako; Morley, Christopher Keith; Ferguson, Angus John
2018-02-01
To delineate subsurface lithology to estimate petrophysical properties of a reservoir, it is possible to use acoustic impedance (AI) which is the result of seismic inversion. To change amplitude to AI, removal of wavelet effects from the seismic signal in order to get a reflection series, and subsequently transforming those reflections to AI, is vital. To carry out seismic inversion correctly it is important to not assume that the seismic signal is stationary. However, all stationary deconvolution methods are designed following that assumption. To increase temporal resolution and interpretation ability, amplitude compensation and phase correction are inevitable. Those are pitfalls of stationary reflectivity inversion. Although stationary reflectivity inversion methods are trying to estimate reflectivity series, because of incorrect assumptions their estimations will not be correct, but may be useful. Trying to convert those reflection series to AI, also merging with the low frequency initial model, can help us. The aim of this study was to apply non-stationary deconvolution to eliminate time variant wavelet effects from the signal and to convert the estimated reflection series to the absolute AI by getting bias from well logs. To carry out this aim, stochastic Gabor inversion in the time domain was used. The Gabor transform derived the signal’s time–frequency analysis and estimated wavelet properties from different windows. Dealing with different time windows gave an ability to create a time-variant kernel matrix, which was used to remove matrix effects from seismic data. The result was a reflection series that does not follow the stationary assumption. The subsequent step was to convert those reflections to AI using well information. Synthetic and real data sets were used to show the ability of the introduced method. The results highlight that the time cost to get seismic inversion is negligible related to general Gabor inversion in the frequency domain. Also
Fast Linear Algebra Applications in Stochastic Inversion and Data Assimilation
Kitanidis, P. K.; Ambikasaran, S.; Saibaba, A.; Li, J. Y.; Darve, E. F.
2012-12-01
Inverse problems and data assimilation problems arise frequently in earth-science applications, such as hydraulic tomography, cross-well seismic travel-time tomography, electrical resistivity tomography, contaminant source identification, assimilation of weather data, etc. A common feature amongst inverse problems is that the parameters we are interested in estimating are hard to measure directly, and a crucial component of inverse modeling is using sparse data to evaluate many model parameters. To quantify uncertainty, stochastic methods such as the geostatistical approach to inverse problems and Kalman filtering are often used. The algorithms for the implementation of these methods were originally developed for small-size problems and their cost of implementation increases quickly with the size of the problem, which is usually defined by the number of observations and the number of unknowns. From a practical standpoint, it is critical to develop computational algorithms in linear algebra for which the computational effort, both in terms of storage and computational time, increases roughly linearly with the size of the problem. This is in contrast, for example, with matrix-vector products (resp. LU factorization) that scale quadratically (resp. cubically). This objective is achieved by tailoring methods to the structure of problems. We present an overview of the challenges and general approaches available for reducing computational cost and then present applications focusing on algorithms that use the hierarchical matrix approach. The hierarchical method reduces matrix vector products involving the dense covariance matrix from O(m2) to O(m log m), where m is the number of unknowns. We illustrate the performance of our algorithm on a few applications, such as monitoring CO2 concentrations using crosswell seismic tomography.
Rapid kinematic finite source inversion for Tsunamic Early Warning using high rate GNSS data
Chen, K.; Liu, Z.; Song, Y. T.
2017-12-01
Recently, Global Navigation Satellite System (GNSS) has been used for rapid earthquake source inversion towards tsunami early warning. In practice, two approaches, i.e., static finite source inversion based on permanent co-seismic offsets and kinematic finite source inversion using high-rate (>= 1 Hz) co-seismic displacement waveforms, are often employed to fulfill the task. The static inversion is relatively easy to be implemented and does not require additional constraints on rupture velocity, duration, and temporal variation. However, since most GNSS receivers are deployed onshore locating on one side of the subduction fault, there is very limited resolution on near-trench fault slip using GNSS in static finite source inversion. On the other hand, the high-rate GNSS displacement waveforms, which contain the timing information of earthquake rupture explicitly and static offsets implicitly, have the potential to improve near-trench resolution by reconciling with the depth-dependent megathrust rupture behaviors. In this contribution, we assess the performance of rapid kinematic finite source inversion using high-rate GNSS by three selected historical tsunamigenic cases: the 2010 Mentawai, 2011 Tohoku and 2015 Illapel events. With respect to the 2010 Mentawai case, it is a typical tsunami earthquake with most slip concentrating near the trench. The static inversion has little resolution there and incorrectly puts slip at greater depth (>10km). In contrast, the recorded GNSS displacement waveforms are deficit in high-frequency energy, the kinematic source inversion recovers a shallow slip patch (depth less than 6 km) and tsunami runups are predicted quite reasonably. For the other two events, slip from kinematic and static inversion show similar characteristics and comparable tsunami scenarios, which may be related to dense GNSS network and behavior of the rupture. Acknowledging the complexity of kinematic source inversion in real-time, we adopt the back
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.
Directory of Open Access Journals (Sweden)
R. Marklein
2005-01-01
Full Text Available This paper presents recent advances and future challenges of the application of different linear and nonlinear inversion algorithms in acoustics, electromagnetics, and elastodynamics. The presented material can be understood as an extension of our previous work on this topic. The inversion methods considered in this presentation vary from linear schemes, like the Synthetic Aperture Radar (SAR applied electromagnetics and the Synthetic Aperture Focussing Technique (SAFT as its counterpart in ultrasonics, and the linearized Diffraction Tomography (DT, to nonlinear schemes, like the Contrast Source Inversion (CSI combined with different regularization approaches. Inversion results of the above mentioned inversion schemes are presented and compared for instance for time-domain ultrasonic data from the Fraunhofer-Institute for Nondestructive Testing (IZFP, Saarbrücken, Germany. Convenient tools for nondestructive evaluation of solids can be electromagnetic and/or elastodynamic waves; since their governing equations, including acoustics, exhibit strong structural similarities, the same inversion concepts apply. In particular, the heuristic SAFT algorithm can be and has been utilized for all kinds of waves, once a scalar approximation can be justified. Relating SAFT to inverse scattering in terms of diffraction tomography, it turns out that linearization is the most stringent inherent approximation. A comparison of the inversion results using the linear time-domain inversion scheme SAFT and well tested nonlinear frequency-domain inversion schemes demonstrates the considerable potential to extend and improve the ultrasonic imaging technique SAFT while consulting the mathematics of wavefield inversion, yet, in particular if the underlying effort is considered, the relatively simple and effective SAFT algorithm works surprisingly well. Since SAFT is a widely accepted imaging tool in ultrasonic NDE it seems worthwhile to check its formal restrictions and
Marklein, R.; Langenberg, K. J.; Mayer, K.; Miao, J.; Shlivinski, A.; Zimmer, A.; Müller, W.; Schmitz, V.; Kohl, C.; Mletzko, U.
2005-05-01
This paper presents recent advances and future challenges of the application of different linear and nonlinear inversion algorithms in acoustics, electromagnetics, and elastodynamics. The presented material can be understood as an extension of our previous work on this topic. The inversion methods considered in this presentation vary from linear schemes, like the Synthetic Aperture Radar (SAR) applied electromagnetics and the Synthetic Aperture Focussing Technique (SAFT) as its counterpart in ultrasonics, and the linearized Diffraction Tomography (DT), to nonlinear schemes, like the Contrast Source Inversion (CSI) combined with different regularization approaches. Inversion results of the above mentioned inversion schemes are presented and compared for instance for time-domain ultrasonic data from the Fraunhofer-Institute for Nondestructive Testing (IZFP, Saarbrücken, Germany). Convenient tools for nondestructive evaluation of solids can be electromagnetic and/or elastodynamic waves; since their governing equations, including acoustics, exhibit strong structural similarities, the same inversion concepts apply. In particular, the heuristic SAFT algorithm can be and has been utilized for all kinds of waves, once a scalar approximation can be justified. Relating SAFT to inverse scattering in terms of diffraction tomography, it turns out that linearization is the most stringent inherent approximation. A comparison of the inversion results using the linear time-domain inversion scheme SAFT and well tested nonlinear frequency-domain inversion schemes demonstrates the considerable potential to extend and improve the ultrasonic imaging technique SAFT while consulting the mathematics of wavefield inversion, yet, in particular if the underlying effort is considered, the relatively simple and effective SAFT algorithm works surprisingly well. Since SAFT is a widely accepted imaging tool in ultrasonic NDE it seems worthwhile to check its formal restrictions and assumptions
Refinement monoids, equidecomposability types, and boolean inverse semigroups
Wehrung, Friedrich
2017-01-01
Adopting a new universal algebraic approach, this book explores and consolidates the link between Tarski's classical theory of equidecomposability types monoids, abstract measure theory (in the spirit of Hans Dobbertin's work on monoid-valued measures on Boolean algebras) and the nonstable K-theory of rings. This is done via the study of a monoid invariant, defined on Boolean inverse semigroups, called the type monoid. The new techniques contrast with the currently available topological approaches. Many positive results, but also many counterexamples, are provided.
Developments in inverse photoemission spectroscopy
International Nuclear Information System (INIS)
Sheils, W.; Leckey, R.C.G.; Riley, J.D.
1996-01-01
In the 1950's and 1960's, Photoemission Spectroscopy (PES) established itself as the major technique for the study of the occupied electronic energy levels of solids. During this period the field divided into two branches: X-ray Photoemission Spectroscopy (XPS) for photon energies greater than ∼l000eV, and Ultra-violet Photoemission Spectroscopy (UPS) for photon energies below ∼100eV. By the 1970's XPS and UPS had become mature techniques. Like XPS, BIS (at x-ray energies) does not have the momentum-resolving ability of UPS that has contributed much to the understanding of the occupied band structures of solids. BIS moved into a new energy regime in 1977 when Dose employed a Geiger-Mueller tube to obtain density of unoccupied states data from a tantalum sample at a photon energy of ∼9.7eV. At similar energies, the technique has since become known as Inverse Photoemission Spectroscopy (IPS), in acknowledgment of its complementary relationship to UPS and to distinguish it from the higher energy BIS. Drawing on decades of UPS expertise, IPS has quickly moved into areas of interest where UPS has been applied; metals, semiconductors, layer compounds, adsorbates, ferromagnets, and superconductors. At La Trobe University an IPS facility has been constructed. This presentation reports on developments in the experimental and analytical techniques of IPS that have been made there. The results of a study of the unoccupied bulk and surface bands of GaAs are presented
A hybrid algorithm for solving inverse problems in elasticity
Directory of Open Access Journals (Sweden)
Barabasz Barbara
2014-12-01
Full Text Available The paper offers a new approach to handling difficult parametric inverse problems in elasticity and thermo-elasticity, formulated as global optimization ones. The proposed strategy is composed of two phases. In the first, global phase, the stochastic hp-HGS algorithm recognizes the basins of attraction of various objective minima. In the second phase, the local objective minimizers are closer approached by steepest descent processes executed singly in each basin of attraction. The proposed complex strategy is especially dedicated to ill-posed problems with multimodal objective functionals. The strategy offers comparatively low computational and memory costs resulting from a double-adaptive technique in both forward and inverse problem domains. We provide a result on the Lipschitz continuity of the objective functional composed of the elastic energy and the boundary displacement misfits with respect to the unknown constitutive parameters. It allows common scaling of the accuracy of solving forward and inverse problems, which is the core of the introduced double-adaptive technique. The capability of the proposed method of finding multiple solutions is illustrated by a computational example which consists in restoring all feasible Young modulus distributions minimizing an objective functional in a 3D domain of a photo polymer template obtained during step and flash imprint lithography.
Multiparameter Elastic Full Waveform Inversion With Facies Constraints
Zhang, Zhendong
2017-08-17
Full waveform inversion (FWI) aims fully benefit from all the data characteristics to estimate the parameters describing the assumed physics of the subsurface. However, current efforts to utilize full waveform inversion as a tool beyond acoustic imaging applications, for example in reservoir analysis, faces inherent challenges related to the limited resolution and the potential trade-off between the elastic model parameters. Adding rock physics constraints does help to mitigate these issues, but current approaches to add such constraints are based on including them as a priori knowledge mostly valid around the well or as a boundary condition for the whole area. Since certain rock formations inside the Earth admit consistent elastic properties and relative values of elastic and anisotropic parameters (facies), utilizing such localized facies information in FWI can improve the resolution of inverted parameters. We propose a novel confidence map based approach to utilize the facies-based constraints in both isotropic and anisotropic elastic FWI. We invert for such a confidence map using Bayesian theory, in which the confidence map is updated at each iteration of the inversion using both the inverted models and a prior information. The numerical examples show that the proposed method can reduce the trade-offs and also can improve the resolution of the inverted elastic and anisotropic properties.
Patterning hierarchy in direct and inverse opal crystals.
Mishchenko, Lidiya; Hatton, Benjamin; Kolle, Mathias; Aizenberg, Joanna
2012-06-25
Biological strategies for bottom-up synthesis of inorganic crystalline and amorphous materials within topographic templates have recently become an attractive approach for fabricating complex synthetic structures. Inspired by these strategies, herein the synthesis of multi-layered, hierarchical inverse colloidal crystal films formed directly on topographically patterned substrates via evaporative deposition, or "co-assembly", of polymeric spheres with a silicate sol-gel precursor solution and subsequent removal of the colloidal template, is described. The response of this growing composite colloid-silica system to artificially imposed 3D spatial constraints of various geometries is systematically studied, and compared with that of direct colloidal crystal assembly on the same template. Substrates designed with arrays of rectangular, triangular, and hexagonal prisms and cylinders are shown to control crystallographic domain nucleation and orientation of the direct and inverse opals. With this bottom-up topographical approach, it is demonstrated that the system can be manipulated to either form large patterned single crystals, or crystals with a fine-tuned extent of disorder, and to nucleate distinct colloidal domains of a defined size, location, and orientation in a wide range of length-scales. The resulting ordered, quasi-ordered, and disordered colloidal crystal films show distinct optical properties. Therefore, this method provides a means of controlling bottom-up synthesis of complex, hierarchical direct and inverse opal structures designed for altering optical properties and increased functionality. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Probabilistic inverse design for self-assembling materials
Jadrich, R. B.; Lindquist, B. A.; Truskett, T. M.
2017-05-01
One emerging approach for the fabrication of complex architectures on the nanoscale is to utilize particles customized to intrinsically self-assemble into a desired structure. Inverse methods of statistical mechanics have proven particularly effective for the discovery of interparticle interactions suitable for this aim. Here we evaluate the generality and robustness of a recently introduced inverse design strategy [B. A. Lindquist et al., J. Chem. Phys. 145, 111101 (2016)] by applying this simulation-based machine learning method to optimize for interparticle interactions that self-assemble particles into a variety of complex microstructures as follows: cluster fluids, porous mesophases, and crystalline lattices. Using the method, we discover isotropic pair interactions that lead to the self-assembly of each of the desired morphologies, including several types of potentials that were not previously understood to be capable of stabilizing such systems. One such pair potential led to the assembly of the highly asymmetric truncated trihexagonal lattice and another produced a fluid containing spherical voids, or pores, of designed size via purely repulsive interactions. Through these examples, we demonstrate several advantages inherent to this particular design approach including the use of a parametrized functional form for the optimized interparticle interactions, the ability to constrain the range of said parameters, and compatibility of the inverse design strategy with a variety of simulation protocols (e.g., positional restraints).
Convex blind image deconvolution with inverse filtering
Lv, Xiao-Guang; Li, Fang; Zeng, Tieyong
2018-03-01
Blind image deconvolution is the process of estimating both the original image and the blur kernel from the degraded image with only partial or no information about degradation and the imaging system. It is a bilinear ill-posed inverse problem corresponding to the direct problem of convolution. Regularization methods are used to handle the ill-posedness of blind deconvolution and get meaningful solutions. In this paper, we investigate a convex regularized inverse filtering method for blind deconvolution of images. We assume that the support region of the blur object is known, as has been done in a few existing works. By studying the inverse filters of signal and image restoration problems, we observe the oscillation structure of the inverse filters. Inspired by the oscillation structure of the inverse filters, we propose to use the star norm to regularize the inverse filter. Meanwhile, we use the total variation to regularize the resulting image obtained by convolving the inverse filter with the degraded image. The proposed minimization model is shown to be convex. We employ the first-order primal-dual method for the solution of the proposed minimization model. Numerical examples for blind image restoration are given to show that the proposed method outperforms some existing methods in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), visual quality and time consumption.
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)
Imaging lower mantle heterogeneities by asymptotic waveform inversion
Ko, J. Y. T.; Zhan, Z.
2017-12-01
Tomographic images from full waveform inversions (FWI) are starting to reveal fine details of Earth structures. However, the constructions of mesh and kernels for broadband waveforms based on full numerical methods are still computationally expensive, and choices of initial models are critical. Here we propose an asymptotic waveform inversion (AWI) technique based on an asymptotic forward method, which are much faster than full numerical methods. While the asymptotic approach does not work for full seismograms or arbitrarily complex medium, it demonstrates high accuracy for important seismic phases (e.g., P and S) for typical/enhanced velocity anomalies considered in Earth's middle and lower mantle. This allows us to use, instead of gradient-based optimization, direct/Monte Carlo search of the model space and provides more realistic uncertainty estimates. This new AWI method can be applied to image subducted slabs and large low shear wave velocity provinces (LLSVPs) in lower mantle with broadband waveforms.
Scattering angle base filtering of the inversion gradients
Alkhalifah, Tariq Ali
2014-01-01
Full waveform inversion (FWI) requires a hierarchical approach based on the availability of low frequencies to maneuver the complex nonlinearity associated with the problem of velocity inversion. I develop a model gradient filter to help us access the parts of the gradient more suitable to combat this potential nonlinearity. The filter is based on representing the gradient in the time-lag normalized domain, in which low scattering angles of the gradient update are initially muted. The result are long-wavelength updates controlled by the ray component of the wavefield. In this case, even 10 Hz data can produce near zero wavelength updates suitable for a background correction of the model. Allowing smaller scattering angle to contribute provides higher resolution information to the model.
Effects of Induced Stress on Seismic Forward Modelling and Inversion
Tromp, Jeroen; Trampert, Jeannot
2018-01-01
We demonstrate how effects of induced stress may be incorporated in seismic modelling and inversion. Our approach is motivated by the accommodation of prestress in global seismology. Induced stress modifies both the equation of motion and the constitutive relationship. The theory predicts that induced pressure linearly affects the unstressed isotropic moduli with a slope determined by their adiabatic pressure derivatives. The induced deviatoric stress produces anisotropic compressional and shear wavespeeds; the latter result in shear-wave splitting. For forward modelling purposes, we determine the weak form of the equation of motion under induced stress. In the context of the inverse problem, we determine induced stress sensitivity kernels, which may be used for adjoint tomography. The theory is illustrated by considering 2D propagation of SH waves and related Fréchet derivatives based on a spectral-element method.
A variational Bayesian method to inverse problems with impulsive noise
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.
Numerical investigation of the inverse blackbody radiation problem
International Nuclear Information System (INIS)
Xin Tan, Guo-zhen Yang, Ben-yuan Gu
1994-01-01
A numerical algorithm for the inverse blackbody radiation problem, which is the determination of the temperature distribution of a thermal radiator (TDTR) from its total radiated power spectrum (TRPS), is presented, based on the general theory of amplitude-phase retrieval. With application of this new algorithm, the ill-posed nature of the Fredholm equation of the first kind can be largely overcome and a convergent solution to high accuracy can be obtained. By incorporation of the hybrid input-output algorithm into our algorithm, the convergent process can be substantially expedited and the stagnation problem of the solution can be averted. From model calculations it is found that the new algorithm can also provide a robust reconstruction of the TDTR from the noise-corrupted data of the TRPS. Therefore the new algorithm may offer a useful approach to solving the ill-posed inverse problem. 18 refs., 9 figs
Including geological information in the inverse problem of palaeothermal reconstruction
Trautner, S.; Nielsen, S. B.
2003-04-01
A reliable reconstruction of sediment thermal history is of central importance to the assessment of hydrocarbon potential and the understanding of basin evolution. However, only rarely do sedimentation history and borehole data in the form of present day temperatures and vitrinite reflectance constrain the past thermal evolution to a useful level of accuracy (Gallagher and Sambridge,1992; Nielsen,1998; Trautner and Nielsen,2003). This is reflected in the inverse solutions to the problem of determining heat flow history from borehole data: The recent heat flow is constrained by data while older values are governed by the chosen a prior heat flow. In this paper we reduce this problem by including geological information in the inverse problem. Through a careful analysis of geological and geophysical data the timing of the tectonic processes, which may influence heat flow, can be inferred. The heat flow history is then parameterised to allow for the temporal variations characteristic of the different tectonic events. The inversion scheme applies a Markov chain Monte Carlo (MCMC) approach (Nielsen and Gallagher, 1999; Ferrero and Gallagher,2002), which efficiently explores the model space and futhermore samples the posterior probability distribution of the model. The technique is demonstrated on wells in the northern North Sea with emphasis on the stretching event in Late Jurassic. The wells are characterised by maximum sediment temperature at the present day, which is the worst case for resolution of the past thermal history because vitrinite reflectance is determined mainly by the maximum temperature. Including geological information significantly improves the thermal resolution. Ferrero, C. and Gallagher,K.,2002. Stochastic thermal history modelling.1. Constraining heat flow histories and their uncertainty. Marine and Petroleum Geology, 19, 633-648. Gallagher,K. and Sambridge, M., 1992. The resolution of past heat flow in sedimentary basins from non-linear inversion
3rd Annual Workshop on Inverse Problem
2015-01-01
This proceeding volume is based on papers presented on the Third Annual Workshop on Inverse Problems which was organized by the Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, and took place in May 2013 in Stockholm. The purpose of this workshop was to present new analytical developments and numerical techniques for solution of inverse problems for a wide range of applications in acoustics, electromagnetics, optical fibers, medical imaging, geophysics, etc. The contributions in this volume reflect these themes and will be beneficial to researchers who are working in the area of applied inverse problems.
Inverse Raman effect: applications and detection techniques
International Nuclear Information System (INIS)
Hughes, L.J. Jr.
1980-08-01
The processes underlying the inverse Raman effect are qualitatively described by comparing it to the more familiar phenomena of conventional and stimulated Raman scattering. An experession is derived for the inverse Raman absorption coefficient, and its relationship to the stimulated Raman gain is obtained. The power requirements of the two fields are examined qualitatively and quantitatively. The assumption that the inverse Raman absorption coefficient is constant over the interaction length is examined. Advantages of the technique are discussed and a brief survey of reported studies is presented
Inverse Raman effect: applications and detection techniques
Energy Technology Data Exchange (ETDEWEB)
Hughes, L.J. Jr.
1980-08-01
The processes underlying the inverse Raman effect are qualitatively described by comparing it to the more familiar phenomena of conventional and stimulated Raman scattering. An experession is derived for the inverse Raman absorption coefficient, and its relationship to the stimulated Raman gain is obtained. The power requirements of the two fields are examined qualitatively and quantitatively. The assumption that the inverse Raman absorption coefficient is constant over the interaction length is examined. Advantages of the technique are discussed and a brief survey of reported studies is presented.
Population inversion in a stationary recombining plasma
International Nuclear Information System (INIS)
Otsuka, M.
1980-01-01
Population inversion, which occurs in a recombining plasma when a stationary He plasma is brought into contact with a neutral gas, is examined. With hydrogen as a contact gas, noticeable inversion between low-lying levels of H as been found. The overpopulation density is of the order of 10 8 cm -3 , which is much higher then that (approx. =10 5 cm -3 ) obtained previously with He as a contact gas. Relations between these experimental results and the conditions for population inversion are discussed with the CR model
Inverse design methods for radiative transfer systems
International Nuclear Information System (INIS)
Daun, K.J.; Howell, J.R.
2005-01-01
Radiant enclosures used in industrial processes have traditionally been designed by trial-and-error, a technique that usually demands considerable time to find a solution of limited quality. As an alternative, designers have recently adopted optimization and inverse methodologies to solve design problems involving radiative transfer; the optimization methodology solves the inverse problem implicitly by transforming it into a multivariable minimization problem, while the inverse design methodology solves the problem explicitly using regularization. This paper presents the details of both methodologies, and demonstrates them by solving for the optimal heater settings in an industrially relevant radiant enclosure design problem
Geoacoustic inversion using combustive sound source signals.
Potty, Gopu R; Miller, James H; Wilson, Preston S; Lynch, James F; Newhall, Arthur
2008-09-01
Combustive sound source (CSS) data collected on single hydrophone receiving units, in water depths ranging from 65 to 110 m, during the Shallow Water 2006 experiment clearly show modal dispersion effects and are suitable for modal geoacoustic inversions. CSS shots were set off at 26 m depth in 100 m of water. The inversions performed are based on an iterative scheme using dispersion-based short time Fourier transform in which each time-frequency tiling is adaptively rotated in the time-frequency plane, depending on the local wave dispersion. Results of the inversions are found to compare favorably to local core data.
Maximal zero textures in Linear and Inverse seesaw
Directory of Open Access Journals (Sweden)
Roopam Sinha
2016-08-01
Full Text Available We investigate Linear and Inverse seesaw mechanisms with maximal zero textures of the constituent matrices subjected to the assumption of non-zero eigenvalues for the neutrino mass matrix mν and charged lepton mass matrix me. If we restrict to the minimally parametrized non-singular ‘me’ (i.e., with maximum number of zeros it gives rise to only 6 possible textures of me. Non-zero determinant of mν dictates six possible textures of the constituent matrices. We ask in this minimalistic approach, what phenomenologically allowed maximum zero textures are possible. It turns out that Inverse seesaw leads to 7 allowed two-zero textures while the Linear seesaw leads to only one. In Inverse seesaw, we show that 2 is the maximum number of independent zeros that can be inserted into μS to obtain all 7 viable two-zero textures of mν. On the other hand, in Linear seesaw mechanism, the minimal scheme allows maximum 5 zeros to be accommodated in ‘m’ so as to obtain viable effective neutrino mass matrices (mν. Interestingly, we find that our minimalistic approach in Inverse seesaw leads to a realization of all the phenomenologically allowed two-zero textures whereas in Linear seesaw only one such texture is viable. Next, our numerical analysis shows that none of the two-zero textures give rise to enough CP violation or significant δCP. Therefore, if δCP=π/2 is established, our minimalistic scheme may still be viable provided we allow larger number of parameters in ‘me’.
On the choice of retrieval variables in the inversion of remotely sensed atmospheric measurements.
Ridolfi, Marco; Sgheri, Luca
2013-05-06
In this paper we introduce new variables that can be used to retrieve the atmospheric continuum emission in the inversion of remote sensing measurements. This modification tackles the so-called sloppy model problem. We test this approach on an extensive set of real measurements from the Michelson Interferometer for Passive Atmospheric Sounding. The newly introduced variables permit to achieve a more stable inversion and a smaller value of the minimum of the cost function.
Solving inverse problems for biological models using the collage method for differential equations.
Capasso, V; Kunze, H E; La Torre, D; Vrscay, E R
2013-07-01
In the first part of this paper we show how inverse problems for differential equations can be solved using the so-called collage method. Inverse problems can be solved by minimizing the collage distance in an appropriate metric space. We then provide several numerical examples in mathematical biology. We consider applications of this approach to the following areas: population dynamics, mRNA and protein concentration, bacteria and amoeba cells interaction, tumor growth.
On normalization of a class of polynomial Hamiltonians: from ordinary and inverse points of view
International Nuclear Information System (INIS)
Uwano, Y.; Chekanov, N.A.; Rostovtsev, V.A.; Vinitskij, S.I.
1999-01-01
The normalization of a class of polynomial Hamiltonians based on the symbolic computing is discussed from both the ordinary and the inverse direction points of view. The truncated three-particle Toda linear chain (3-TLC) and the regularized system of a planar hydrogen atom with the linear Stark effect (HLSE) are taken as examples to demonstrate the symbolic-computational approach to the ordinary and the inverse normalization problems
Improved Inversion of Needle Probe Data for the Determination of Rock Thermal Properties
DEFF Research Database (Denmark)
Bording, Thue Sylvester; Balling, N.; Nielsen, S.B.
Heat flow, thermal conductivity and thermal diffusivity are essential properties in subsurface temperature modelling. We present initial results of a novel inversion approach for laboratory measurements of rock thermal conductivity and thermal diffusivity by the needle probe method. Instead...... of analytical expressions, we use a numerical finite element procedure for the forward temperature response. A Markov Chain Monte Carlo Metropolis Hastings inversion procedure produces estimates of rock thermal parameters with uncertainties. .....
Ultra-Scalable Algorithms for Large-Scale Uncertainty Quantification in Inverse Wave Propagation
2016-03-04
MCMC sampling methods for posteriors for Bayesian inverse wave propagation problems. We developed a so-called randomized maximum a posteriori (rMAP...method for generating approximate samples of posteriors in high dimensional Bayesian inverse problems governed by large-scale forward problems, with...equivalent for a linear parameter-to-observable map. Nu- merical results indicated the potential of the rMAP approach in posterior sampling of nonlinear
Liu, YanBin; Li, YuHui; Jin, FeiTeng
2017-01-01
The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedb...
Inverse Problem Approach for the Alignment of Electron Tomographic Series.
Tran , Viet Dung; Moreaud , Maxime; Thiébaut , Éric; Denis , L.; Becker , Jean-Marie
2014-01-01
In the refining industry, morphological measurements of particles have become an essential part in the characterization catalyst supports. Through these parameters, one can infer the specific physicochemical properties of the studied materials. One of the main acquisition techniques is electron tomography (or nanotomography). 3D volumes are reconstructed from sets of projections from different angles made by a Transmission Elect...
A novel and generalized approach in the inversion of geoelectrical ...
Indian Academy of Sciences (India)
Corresponding author. e-mail: stanleyraj 84@yahoo.co.in. The non-linear apparent resistivity problem in the subsurface study of the earth takes into account the ... viz., resistivity and thickness (Kosinky and Kelly. 1981; Sri Niwas and Singhal 1981; Mazac et al. 1985; Yadav and Abolfazli 1998; Louis et al. 2002;. Batte et al.
A novel and generalized approach in the inversion of geoelectrical ...
Indian Academy of Sciences (India)
Here we used a single layer feed-forward neural network with fast back propagation learning algorithm. So on proper training of back propagation networks it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data with reference to the synthetic data trained in the appropriate ...
Inverse Design of Centrifugal Compressor Stages Using a Meanline Approach
Directory of Open Access Journals (Sweden)
Yuri Biba
2004-01-01
component of a stage are presented, and then described in terms of an iterative procedure which calculates the required one-dimensional geometry. A graphical user interface which facilitates user input and presentation of results is discussed briefly. The object-oriented nature of the code is highlighted as a platform which easily provides for maintainability and future extensions.
An Inverse Michaelis–Menten Approach for Interfacial Enzyme Kinetics
DEFF Research Database (Denmark)
Kari, Jeppe; Andersen, Morten; Borch, Kim
2017-01-01
Interfacial enzyme reactions are ubiquitous both in vivo and in technical applications, but analysis of their kinetics remains controversial. In particular, it is unclear whether conventional Michaelis–Menten theory, which requires a large excess of substrate, can be applied. Here, an extensive e...
Inversion approach for thermal data from a convecting hydrothermal system
Energy Technology Data Exchange (ETDEWEB)
Kasameyer, P.; Younker, L.; Hanson, J.
1983-08-01
Efforts to invert thermal data from 13 deep geothermal wells, and from additional shallow heat-flow holes, in order to determine the age and total flow rate of the Salton Sea hydrothermal system are described. The data were inverted for a very restrictive model: single-phase, horizontal flow along prescribed flowlines in a single aquifer bounded by an impermeable cap and base. With simplifying assumptions, the results are shown to depend on only two parameters, the system age, and the aquifer/cap thickness ratio. The surface gradient and temperature distribution within the cap are calculated analytically for all possible parameter values. Those parameters producing temperatures that agree with observations are identified, and the range of acceptable parameters is reduced by conclusions drawn from other geophysical data. The cap thickness is inferred to be 500m from thermal and lithologic data from the wells. The aquifer thickness is limited to less than 2500m by seismic, resistivity and magnetic data. It is concluded that if this model is valid, the system age is constrained between 3000 and 20,000 years.
An Approach to the Crustal Thickness Inversion Problem
De Marchi, F.; Di Achille, G.
2017-12-01
We describe a method to estimate the crustal thickness of a planet and we apply it to Venus. As in the method of (Parker, 1972), modified by (Wieczorek & Phillips, 1998), the gravity field anomalies of a planet are assumed to be due to the combined effect of topography and relief on the crust-mantle interface. No assumptions on isostasy are necessary. In our case, rather than using the expansion of the powers of the relief in Taylor series, we model the gravitational field of topography/relief by means of a large number of prism-shaped masses covering the whole surface of the planet. Under the hypothesis that crustal and mantle densities are the same everywhere, we solve for the relief depths on the crust-mantle interface by imposing that observed and modeled gravity field at a certain reference spherical surface (external to the planet) must be equal. This method can be extended to the case of non-uniform densities. Finally, we calculate a map of the crustal thickness of Venus and compare our results with those predicted by previous work and with the global distribution of main geological features (e.g. rift zones, tesserae, coronae). We discuss the agremeent between our results and the main geodynamical and crustal models put forth to explain the origin of such features and the applicability of this method in the context of the mission VOX (Venus Origins Explore), proposed for NASA's NF4 call.
Peptides Trapping Dioxins: A Docking-Based Inverse Screening Approach
Directory of Open Access Journals (Sweden)
German Perez
2013-01-01
Full Text Available A rapid and cost-effective computational methodology for designing and rationalizing the selection of small peptides as receptors for dioxin-like compounds was proposed. The backbone of the dioxin Ah receptor binding site was used to design a series of penta- and hexapeptide libraries, with 1400 elements in total. Peptide flexibility was considered and 10 conformers were found to be a good option to represent peptide conformational space with fair speed-accuracy ratio. Each peptide conformer was treated as a possible receptor, generating a dedicated box and then running a docking process using as ligands a family of 76 dibenzo-p-dioxins and 113 dibenzofurans mono- and polychlorinated. Significant predictions were confirmed by comparing primary structure of top and bottom ranked peptides binding dioxins confirming that scrambled positions of the same amino acids gave completely different predicted binding. The hexapeptide EWFQPW, with the best binding score, was chosen as selective sorbent material in solid-phase extraction. The retention performances were tested using the 2,3,7,8-tetrachlorodibenzo-p-dioxin and two polychlorinated biphenyls in order to verify the hexapeptide specificity. The solid-phase extraction experimental procedure was optimized, and analytical parameters of hexapeptide sorbent material were compared with the resin without hexapeptide and a commercial reversed phase cartridge.
DEFF Research Database (Denmark)
Herckenrath, Daan; Fiandaca, G.; Auken, Esben
2013-01-01
hydrogeophysical inversion approaches to inform a field-scale groundwater model with time domain electromagnetic (TDEM) and electrical resistivity tomography (ERT) data. In a sequential hydrogeophysical inversion (SHI) a groundwater model is calibrated with geophysical data by coupling groundwater model parameters...
Sensitivity analyses of acoustic impedance inversion with full-waveform inversion
Yao, Gang; da Silva, Nuno V.; Wu, Di
2018-04-01
Acoustic impedance estimation has a significant importance to seismic exploration. In this paper, we use full-waveform inversion to recover the impedance from seismic data, and analyze the sensitivity of the acoustic impedance with respect to the source-receiver offset of seismic data and to the initial velocity model. We parameterize the acoustic wave equation with velocity and impedance, and demonstrate three key aspects of acoustic impedance inversion. First, short-offset data are most suitable for acoustic impedance inversion. Second, acoustic impedance inversion is more compatible with the data generated by density contrasts than velocity contrasts. Finally, acoustic impedance inversion requires the starting velocity model to be very accurate for achieving a high-quality inversion. Based upon these observations, we propose a workflow for acoustic impedance inversion as: (1) building a background velocity model with travel-time tomography or reflection waveform inversion; (2) recovering the intermediate wavelength components of the velocity model with full-waveform inversion constrained by Gardner’s relation; (3) inverting the high-resolution acoustic impedance model with short-offset data through full-waveform inversion. We verify this workflow by the synthetic tests based on the Marmousi model.
Full traveltime inversion in source domain
Liu, Lu
2017-06-01
This paper presents a new method of source-domain full traveltime inversion (FTI). The objective of this study is automatically building near-surface velocity using the early arrivals of seismic data. This method can generate the inverted velocity that can kinetically best match the reconstructed plane-wave source of early arrivals with true source in source domain. It does not require picking first arrivals for tomography, which is one of the most challenging aspects of ray-based tomographic inversion. Besides, this method does not need estimate the source wavelet, which is a necessity for receiver-domain wave-equation velocity inversion. Furthermore, we applied our method on one synthetic dataset; the results show our method could generate a reasonable background velocity even when shingling first arrivals exist and could provide a good initial velocity for the conventional full waveform inversion (FWI).
n-Colour self-inverse compositions
Indian Academy of Sciences (India)
colour self-inverse composition. This introduces four new sequences which satisfy the same recurrence relation with different initial conditions like the famous Fibonacci and Lucas sequences. For these new sequences explicit formulas, recurrence ...
n-Colour self-inverse compositions
Indian Academy of Sciences (India)
inverse composition. This introduces four new sequences which satisfy the same recurrence relation with different initial conditions like the famous Fibonacci and Lucas sequences. For these new sequences explicit formulas, recurrence relations ...
The inverse square law of gravitation
International Nuclear Information System (INIS)
Cook, A.H.
1987-01-01
The inverse square law of gravitation is very well established over the distances of celestial mechanics, while in electrostatics the law has been shown to be followed to very high precision. However, it is only within the last century that any laboratory experiments have been made to test the inverse square law for gravitation, and all but one has been carried out in the last ten years. At the same time, there has been considerable interest in the possibility of deviations from the inverse square law, either because of a possible bearing on unified theories of forces, including gravitation or, most recently, because of a possible additional fifth force of nature. In this article the various lines of evidence for the inverse square law are summarized, with emphasis upon the recent laboratory experiments. (author)
Acoustic 2D full waveform inversion to solve gas cloud challenges
Directory of Open Access Journals (Sweden)
Srichand Prajapati
2015-09-01
Full Text Available The existing conventional inversion algorithm does not provide satisfactory results due to the complexity of propagated wavefield though the gas cloud. Acoustic full waveform inversion has been developed and applied to a realistic synthetic offshore shallow gas cloud feature with Student-t approach, with and without simultaneous sources encoding. As a modeling operator, we implemented the grid based finite-difference method in frequency domain using second order elastic wave equation. Jacobin operator and its adjoint provide a necessary platform for solving full waveform inversion problem in a reduced Hessian matrix. We invert gas cloud model in 5 frequency band selected from 1 to 12 Hz, each band contains 3 frequencies. The inversion results are highly sensitive to the misfit. The model allows better convergence and recovery of amplitude losses. This approach gives better resolution then the existing least-squares approach. In this paper, we implement the full waveform inversion for low frequency model with minimum number of iteration providing a better resolution of inversion results.
Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions
Directory of Open Access Journals (Sweden)
S. M. Miller
2014-02-01
the relative merits of each. This paper investigates the applicability of several approaches to bounded inverse problems. A common method of data transformations is found to unrealistically skew estimates for the examined example application. The method of Lagrange multipliers and two Markov chain Monte Carlo (MCMC methods yield more realistic and accurate results. In general, the examined MCMC approaches produce the most realistic result but can require substantial computational time. Lagrange multipliers offer an appealing option for large, computationally intensive problems when exact uncertainty bounds are less central to the analysis. A synthetic data inversion of US anthropogenic methane emissions illustrates the strengths and weaknesses of each approach.
Sun, J.; Li, Y.
2017-12-01
Magnetic data contain important information about the subsurface rocks that were magnetized in the geological history, which provides an important avenue to the study of the crustal heterogeneities associated with magmatic and hydrothermal activities. Interpretation of magnetic data has been widely used in mineral exploration, basement characterization and large scale crustal studies for several decades. However, interpreting magnetic data has been often complicated by the presence of remanent magnetizations with unknown magnetization directions. Researchers have developed different methods to deal with the challenges posed by remanence. We have developed a new and effective approach to inverting magnetic data for magnetization vector distributions characterized by region-wise consistency in the magnetization directions. This approach combines the classical Tikhonov inversion scheme with fuzzy C-means clustering algorithm, and constrains the estimated magnetization vectors to a specified small number of possible directions while fitting the observed magnetic data to within noise level. Our magnetization vector inversion recovers both the magnitudes and the directions of the magnetizations in the subsurface. Magnetization directions reflect the unique geological or hydrothermal processes applied to each geological unit, and therefore, can potentially be used for the purpose of differentiating various geological units. We have developed a practically convenient and effective way of assessing the uncertainty associated with the inverted magnetization directions (Figure 1), and investigated how geological differentiation results might be affected (Figure 2). The algorithm and procedures we have developed for magnetization vector inversion and uncertainty analysis open up new possibilities of extracting useful information from magnetic data affected by remanence. We will use a field data example from exploration of an iron-oxide-copper-gold (IOCG) deposit in Brazil to
Inverse odds ratio-weighted estimation for causal mediation analysis.
Tchetgen Tchetgen, Eric J
2013-11-20
An important scientific goal of studies in the health and social sciences is increasingly to determine to what extent the total effect of a point exposure is mediated by an intermediate variable on the causal pathway between the exposure and the outcome. A causal framework has recently been proposed for mediation analysis, which gives rise to new definitions, formal identification results and novel estimators of direct and indirect effects. In the present paper, the author describes a new inverse odds ratio-weighted approach to estimate so-called natural direct and indirect effects. The approach, which uses as a weight the inverse of an estimate of the odds ratio function relating the exposure and the mediator, is universal in that it can be used to decompose total effects in a number of regression models commonly used in practice. Specifically, the approach may be used for effect decomposition in generalized linear models with a nonlinear link function, and in a number of other commonly used models such as the Cox proportional hazards regression for a survival outcome. The approach is simple and can be implemented in standard software provided a weight can be specified for each observation. An additional advantage of the method is that it easily incorporates multiple mediators of a categorical, discrete or continuous nature. Copyright © 2013 John Wiley & Sons, Ltd.
Sparsity-based acoustic inversion in cross-sectional multiscale optoacoustic imaging
International Nuclear Information System (INIS)
Han, Yiyong; Tzoumas, Stratis; Nunes, Antonio; Ntziachristos, Vasilis; Rosenthal, Amir
2015-01-01
Purpose: With recent advancement in hardware of optoacoustic imaging systems, highly detailed cross-sectional images may be acquired at a single laser shot, thus eliminating motion artifacts. Nonetheless, other sources of artifacts remain due to signal distortion or out-of-plane signals. The purpose of image reconstruction algorithms is to obtain the most accurate images from noisy, distorted projection data. Methods: In this paper, the authors use the model-based approach for acoustic inversion, combined with a sparsity-based inversion procedure. Specifically, a cost function is used that includes the L1 norm of the image in sparse representation and a total variation (TV) term. The optimization problem is solved by a numerically efficient implementation of a nonlinear gradient descent algorithm. TV–L1 model-based inversion is tested in the cross section geometry for numerically generated data as well as for in vivo experimental data from an adult mouse. Results: In all cases, model-based TV–L1 inversion showed a better performance over the conventional Tikhonov regularization, TV inversion, and L1 inversion. In the numerical examples, the images reconstructed with TV–L1 inversion were quantitatively more similar to the originating images. In the experimental examples, TV–L1 inversion yielded sharper images and weaker streak artifact. Conclusions: The results herein show that TV–L1 inversion is capable of improving the quality of highly detailed, multiscale optoacoustic images obtained in vivo using cross-sectional imaging systems. As a result of its high fidelity, model-based TV–L1 inversion may be considered as the new standard for image reconstruction in cross-sectional imaging
Topological inversion for solution of geodesy-constrained geophysical problems
Saltogianni, Vasso; Stiros, Stathis
2015-04-01
Geodetic data, mostly GPS observations, permit to measure displacements of selected points around activated faults and volcanoes, and on the basis of geophysical models, to model the underlying physical processes. This requires inversion of redundant systems of highly non-linear equations with >3 unknowns; a situation analogous to the adjustment of geodetic networks. However, in geophysical problems inversion cannot be based on conventional least-squares techniques, and is based on numerical inversion techniques (a priori fixing of some variables, optimization in steps with values of two variables each time to be regarded fixed, random search in the vicinity of approximate solutions). Still these techniques lead to solutions trapped in local minima, to correlated estimates and to solutions with poor error control (usually sampling-based approaches). To overcome these problems, a numerical-topological, grid-search based technique in the RN space is proposed (N the number of unknown variables). This technique is in fact a generalization and refinement of techniques used in lighthouse positioning and in some cases of low-accuracy 2-D positioning using Wi-Fi etc. The basic concept is to assume discrete possible ranges of each variable, and from these ranges to define a grid G in the RN space, with some of the gridpoints to approximate the true solutions of the system. Each point of hyper-grid G is then tested whether it satisfies the observations, given their uncertainty level, and successful grid points define a sub-space of G containing the true solutions. The optimal (minimal) space containing one or more solutions is obtained using a trial-and-error approach, and a single optimization factor. From this essentially deterministic identification of the set of gridpoints satisfying the system of equations, at a following step, a stochastic optimal solution is computed corresponding to the center of gravity of this set of gridpoints. This solution corresponds to a
Bayesian inversion of refraction seismic traveltime data
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
An Inversion Recovery NMR Kinetics Experiment
Williams, Travis J.; Kershaw, Allan D.; Li, Vincent; Wu, Xinping
2011-01-01
A convenient laboratory experiment is described in which NMR magnetization transfer by inversion recovery is used to measure the kinetics and thermochemistry of amide bond rotation. The experiment utilizes Varian spectrometers with the VNMRJ 2.3 software, but can be easily adapted to any NMR platform. The procedures and sample data sets in this article will enable instructors to use inversion recovery as a laboratory activity in applied NMR classes and provide research students with a conveni...
Population inversion in recombining hydrogen plasma
International Nuclear Information System (INIS)
Furukane, Utaro; Yokota, Toshiaki; Oda, Toshiatsu.
1978-11-01
The collisional-radiative model is applied to a recombining hydrogen plasma in order to investigate the plasma condition in which the population inversion between the energy levels of hydrogen can be generated. The population inversion is expected in a plasma where the three body recombination has a large contribution to the recombining processes and the effective recombination rate is beyond a certain value for a given electron density and temperature. Calculated results are presented in figures and tables. (author)
On the Inversion of the Lidar Equation
1984-11-01
sectitns briefly review the major inversion methods to date and a fourth section describes the development of the modified inversion method. All four...can be seeu when It is understood ’in terms of its ,physical significance. Equation 17 states that the normalized integrated backscatter has a limit. In...still give significant errors. 4.0 VALIDATION OF AGILE In this chapter, evidence of the success of AGILE will be reviewed and compared with Klett’s
Inverse regression for ridge recovery II: Numerics
Glaws, Andrew; Constantine, Paul G.; Cook, R. Dennis
2018-01-01
We investigate the application of sufficient dimension reduction (SDR) to a noiseless data set derived from a deterministic function of several variables. In this context, SDR provides a framework for ridge recovery. In this second part, we explore the numerical subtleties associated with using two inverse regression methods---sliced inverse regression (SIR) and sliced average variance estimation (SAVE)---for ridge recovery. This includes a detailed numerical analysis of the eigenvalues of th...
Uhlmann, Gunther
2008-07-01
This volume represents the proceedings of the fourth Applied Inverse Problems (AIP) international conference and the first congress of the Inverse Problems International Association (IPIA) which was held in Vancouver, Canada, June 25 29, 2007. The organizing committee was formed by Uri Ascher, University of British Columbia, Richard Froese, University of British Columbia, Gary Margrave, University of Calgary, and Gunther Uhlmann, University of Washington, chair. The conference was part of the activities of the Pacific Institute of Mathematical Sciences (PIMS) Collaborative Research Group on inverse problems (http://www.pims.math.ca/scientific/collaborative-research-groups/past-crgs). This event was also supported by grants from NSF and MITACS. Inverse Problems (IP) are problems where causes for a desired or an observed effect are to be determined. They lie at the heart of scientific inquiry and technological development. The enormous increase in computing power and the development of powerful algorithms have made it possible to apply the techniques of IP to real-world problems of growing complexity. Applications include a number of medical as well as other imaging techniques, location of oil and mineral deposits in the earth's substructure, creation of astrophysical images from telescope data, finding cracks and interfaces within materials, shape optimization, model identification in growth processes and, more recently, modelling in the life sciences. The series of Applied Inverse Problems (AIP) Conferences aims to provide a primary international forum for academic and industrial researchers working on all aspects of inverse problems, such as mathematical modelling, functional analytic methods, computational approaches, numerical algorithms etc. The steering committee of the AIP conferences consists of Heinz Engl (Johannes Kepler Universität, Austria), Joyce McLaughlin (RPI, USA), William Rundell (Texas A&M, USA), Erkki Somersalo (Helsinki University of Technology
Fast nonlinear susceptibility inversion with variational regularization.
Milovic, Carlos; Bilgic, Berkin; Zhao, Bo; Acosta-Cabronero, Julio; Tejos, Cristian
2018-01-10
Quantitative susceptibility mapping can be performed through the minimization of a function consisting of data fidelity and regularization terms. For data consistency, a Gaussian-phase noise distribution is often assumed, which breaks down when the signal-to-noise ratio is low. A previously proposed alternative is to use a nonlinear data fidelity term, which reduces streaking artifacts, mitigates noise amplification, and results in more accurate susceptibility estimates. We hereby present a novel algorithm that solves the nonlinear functional while achieving computation speeds comparable to those for a linear formulation. We developed a nonlinear quantitative susceptibility mapping algorithm (fast nonlinear susceptibility inversion) based on the variable splitting and alternating direction method of multipliers, in which the problem is split into simpler subproblems with closed-form solutions and a decoupled nonlinear inversion hereby solved with a Newton-Raphson iterative procedure. Fast nonlinear susceptibility inversion performance was assessed using numerical phantom and in vivo experiments, and was compared against the nonlinear morphology-enabled dipole inversion method. Fast nonlinear susceptibility inversion achieves similar accuracy to nonlinear morphology-enabled dipole inversion but with significantly improved computational efficiency. The proposed method enables accurate reconstructions in a fraction of the time required by state-of-the-art quantitative susceptibility mapping methods. Magn Reson Med, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.
A projected back-tracking line-search for constrained interactive inverse kinematics
DEFF Research Database (Denmark)
Engell-Nørregård, Morten Pol; Erleben, Kenny
2011-01-01
Inverse kinematics is the problem of manipulating the pose of an articulated figure in order to achieve a desired goal disregarding inertia and forces. One can approach the problem as a non-linear optimization problem or as non-linear equation solving. The former approach is superior in its gener...
Evaluation of an Inverse Molecular Design Algorithm in a Model Binding Site
Huggins, David J.; Altman, Michael D.; Tidor, Bruce
2008-01-01
Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors [M. D. Altman et al. J. Am. Chem. Soc. 130: 6099–6013, 2008]. Here we have evaluated the new method using the well studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from non-binders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the non-binders. PMID:18831031
The Inverse Faraday Effect In Plasma
International Nuclear Information System (INIS)
Eliezer, S.; Paiss, Y.; Horovitz, Y.; Henis, Z.
1999-01-01
The existence of axial magnetic field 1-3 induced by the interaction of circularly polarized laser light with plasma is reported. Axial magnetic fields from 500 Gauss up to 2.17 MegaGauss were measured using a Nd:YAG laser with a pulse duration of 7 ns for irradiance from 10 9 to 10 14 W/cm'2 accordingly. Up to 5 - 10 13 W/cm 2 , the results are in agreement with a nonlinear model of the inverse Faraday effect dominated by the ponderomotive force. Two diagnostic methods were used to measure the axial magnetic field. At low irradiance (10 9 - 10 1 '1 W/cm 2 ) the axial magnetic field induced by the circularly polarized laser light (CPLL) in a ferrite target was measured from the voltage signal induced by the magnetic field in an output coil. At higher irradiance the axial magnetic field was measured using the Faraday rotation diagnostic. The scaling law of the measured axial magnetic field B from the experiments performed with CPLL, in the intensities range of 10 9 - 10 13 W/cm 2 , is B ∼ I / 1/2 . At higher intensities of the order of 3 . 10 1 '4 W/cm 2 a sudden increase of the axial magnetic field beyond the above scaling law is observed in the experiments performed with CPLL. This study might have interesting implications in creating a mini tokamak configuration in laser produced plasmas, with intermediate plasma densities (10 22 cm 3 ) and confinement times (100 ns). Such an approach to fusion circumvents many of the complexities of inertial confinement fusion where very symmetric implosions using many laser beams are required. Intermediate fusion density may also overcome severe requirements of tokamak fusion
Towards Exascale Seismic Imaging and Inversion
Tromp, J.; Bozdag, E.; Lefebvre, M. P.; Smith, J. A.; Lei, W.; Ruan, Y.
2015-12-01
Post-petascale supercomputers are now available to solve complex scientific problems that were thought unreachable a few decades ago. They also bring a cohort of concerns tied to obtaining optimum performance. Several issues are currently being investigated by the HPC community. These include energy consumption, fault resilience, scalability of the current parallel paradigms, workflow management, I/O performance and feature extraction with large datasets. In this presentation, we focus on the last three issues. In the context of seismic imaging and inversion, in particular for simulations based on adjoint methods, workflows are well defined.They consist of a few collective steps (e.g., mesh generation or model updates) and of a large number of independent steps (e.g., forward and adjoint simulations of each seismic event, pre- and postprocessing of seismic traces). The greater goal is to reduce the time to solution, that is, obtaining a more precise representation of the subsurface as fast as possible. This brings us to consider both the workflow in its entirety and the parts comprising it. The usual approach is to speedup the purely computational parts based on code optimization in order to reach higher FLOPS and better memory management. This still remains an important concern, but larger scale experiments show that the imaging workflow suffers from severe I/O bottlenecks. Such limitations occur both for purely computational data and seismic time series. The latter are dealt with by the introduction of a new Adaptable Seismic Data Format (ASDF). Parallel I/O libraries, namely HDF5 and ADIOS, are used to drastically reduce the cost of disk access. Parallel visualization tools, such as VisIt, are able to take advantage of ADIOS metadata to extract features and display massive datasets. Because large parts of the workflow are embarrassingly parallel, we are investigating the possibility of automating the imaging process with the integration of scientific workflow
Bayesian ISOLA: new tool for automated centroid moment tensor inversion
Vackář, Jiří; Burjánek, Jan; Gallovič, František; Zahradník, Jiří; Clinton, John
2017-04-01
Focal mechanisms are important for understanding seismotectonics of a region, and they serve as a basic input for seismic hazard assessment. Usually, the point source approximation and the moment tensor (MT) are used. We have developed a new, fully automated tool for the centroid moment tensor (CMT) inversion in a Bayesian framework. It includes automated data retrieval, data selection where station components with various instrumental disturbances and high signal-to-noise are rejected, and full-waveform inversion in a space-time grid around a provided hypocenter. The method is innovative in the following aspects: (i) The CMT inversion is fully automated, no user interaction is required, although the details of the process can be visually inspected latter on many figures which are automatically plotted.(ii) The automated process includes detection of disturbances based on MouseTrap code, so disturbed recordings do not affect inversion.(iii) A data covariance matrix calculated from pre-event noise yields an automated weighting of the station recordings according to their noise levels and also serves as an automated frequency filter suppressing noisy frequencies.(iv) Bayesian approach is used, so not only the best solution is obtained, but also the posterior probability density function.(v) A space-time grid search effectively combined with the least-squares inversion of moment tensor components speeds up the inversion and allows to obtain more accurate results compared to stochastic methods. The method has been tested on synthetic and observed data. It has been tested by comparison with manually processed moment tensors of all events greater than M≥3 in the Swiss catalogue over 16 years using data available at the Swiss data center (http://arclink.ethz.ch). The quality of the results of the presented automated process is comparable with careful manual processing of data. The software package programmed in Python has been designed to be as versatile as possible in
Transdimensional, hierarchical, Bayesian inversion of ambient seismic noise: Australia
Crowder, E.; Rawlinson, N.; Cornwell, D. G.
2017-12-01
We present models of crustal velocity structure in southeastern Australia using a novel, transdimensional and hierarchical, Bayesian inversion approach. The inversion is applied to long-time ambient noise cross-correlations. The study area of SE Australia is thought to represent the eastern margin of Gondwana. Conflicting tectonic models have been proposed to explain the formation of eastern Gondwana and the enigmatic geological relationships in Bass Strait, which separates Tasmania and the mainland. A geologically complex area of crustal accretion, Bass Strait may contain part of an exotic continental block entrained in colliding crusts. Ambient noise data recorded by an array of 24 seismometers is used to produce a high resolution, 3D shear wave velocity model of Bass Strait. Phase velocity maps in the period range 2-30 s are produced and subsequently inverted for 3D shear wave velocity structure. The transdimensional, hierarchical Bayesian, inversion technique is used. This technique proves far superior to linearised inversion. The inversion model is dynamically parameterised during the process, implicitly controlled by the data, and noise is treated as an inversion unknown. The resulting shear wave velocity model shows three sedimentary basins in Bass Strait constrained by slow shear velocities (2.4-2.9 km/s) at 2-10 km depth. These failed rift basins from the breakup of Australia-Antartica appear to be overlying thinned crust, where typical mantle velocities of 3.8-4.0 km/s occur at depths greater than 20 km. High shear wave velocities ( 3.7-3.8 km/s) in our new model also match well with regions of high magnetic and gravity anomalies. Furthermore, we use both Rayleigh and Love wave phase data to to construct Vsv and Vsh maps. These are used to estimate crustal radial anisotropy in the Bass Strait. We interpret that structures delineated by our velocity models support the presence and extent of the exotic Precambrian micro-continent (the Selwyn Block) that was
Two hybrid regularization frameworks for solving the electrocardiography inverse problem
Energy Technology Data Exchange (ETDEWEB)
Jiang Mingfeng; Xia Ling; Shou Guofa; Liu Feng [Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027 (China); Crozier, Stuart [School of Information Technology and Electrical Engineering, University of Queensland, St. Lucia, Brisbane, Queensland 4072 (Australia)], E-mail: xialing@zju.edu.cn
2008-09-21
In this paper, two hybrid regularization frameworks, LSQR-Tik and Tik-LSQR, which integrate the properties of the direct regularization method (Tikhonov) and the iterative regularization method (LSQR), have been proposed and investigated for solving ECG inverse problems. The LSQR-Tik method is based on the Lanczos process, which yields a sequence of small bidiagonal systems to approximate the original ill-posed problem and then the Tikhonov regularization method is applied to stabilize the projected problem. The Tik-LSQR method is formulated as an iterative LSQR inverse, augmented with a Tikhonov-like prior information term. The performances of these two hybrid methods are evaluated using a realistic heart-torso model simulation protocol, in which the heart surface source method is employed to calculate the simulated epicardial potentials (EPs) from the action potentials (APs), and then the acquired EPs are used to calculate simulated body surface potentials (BSPs). The results show that the regularized solutions obtained by the LSQR-Tik method are approximate to those of the Tikhonov method, the computational cost of the LSQR-Tik method, however, is much less than that of the Tikhonov method. Moreover, the Tik-LSQR scheme can reconstruct the epcicardial potential distribution more accurately, specifically for the BSPs with large noisy cases. This investigation suggests that hybrid regularization methods may be more effective than separate regularization approaches for ECG inverse problems.
Two hybrid regularization frameworks for solving the electrocardiography inverse problem
Jiang, Mingfeng; Xia, Ling; Shou, Guofa; Liu, Feng; Crozier, Stuart
2008-09-01
In this paper, two hybrid regularization frameworks, LSQR-Tik and Tik-LSQR, which integrate the properties of the direct regularization method (Tikhonov) and the iterative regularization method (LSQR), have been proposed and investigated for solving ECG inverse problems. The LSQR-Tik method is based on the Lanczos process, which yields a sequence of small bidiagonal systems to approximate the original ill-posed problem and then the Tikhonov regularization method is applied to stabilize the projected problem. The Tik-LSQR method is formulated as an iterative LSQR inverse, augmented with a Tikhonov-like prior information term. The performances of these two hybrid methods are evaluated using a realistic heart-torso model simulation protocol, in which the heart surface source method is employed to calculate the simulated epicardial potentials (EPs) from the action potentials (APs), and then the acquired EPs are used to calculate simulated body surface potentials (BSPs). The results show that the regularized solutions obtained by the LSQR-Tik method are approximate to those of the Tikhonov method, the computational cost of the LSQR-Tik method, however, is much less than that of the Tikhonov method. Moreover, the Tik-LSQR scheme can reconstruct the epcicardial potential distribution more accurately, specifically for the BSPs with large noisy cases. This investigation suggests that hybrid regularization methods may be more effective than separate regularization approaches for ECG inverse problems.
Strategies for source space limitation in tomographic inverse procedures
Energy Technology Data Exchange (ETDEWEB)
George, J.S.; Lewis, P.S.; Schlitt, H.A.; Kaplan, L.; Gorodnitsky, I.; Wood, C.C.
1994-02-01
The use of magnetic recordings for localization of neural activity requires the solution of an ill-posed inverse problem: i.e. the determination of the spatial configuration, orientation, and timecourse of the currents that give rise to a particular observed field distribution. In its general form, this inverse problem has no unique solution; due to superposition and the existence of silent source configurations, a particular magnetic field distribution at the head surface could be produced by any number of possible source configurations. However, by making assumptions concerning the number and properties of neural sources, it is possible to use numerical minimization techniques to determine the source model parameters that best account for the experimental observations while satisfying numerical or physical criteria. In this paper the authors describe progress on the development and validation of inverse procedures that produce distributed estimates of neuronal currents. The goal is to produce a temporal sequence of 3-D tomographic reconstructions of the spatial patterns of neural activation. Such approaches have a number of advantages, in principle. Because they do not require estimates of model order and parameter values (beyond specification of the source space), they minimize the influence of investigator decisions and are suitable for automated analyses. These techniques also allow localization of sources that are not point-like; experimental studies of cognitive processes and of spontaneous brain activity are likely to require distributed source models.
Wavefield reconstruction inversion with a multiplicative cost function
da Silva, Nuno V.; Yao, Gang
2018-01-01
We present a method for the automatic estimation of the trade-off parameter in the context of wavefield reconstruction inversion (WRI). WRI formulates the inverse problem as an optimisation problem, minimising the data misfit while penalising with a wave equation constraining term. The trade-off between the two terms is balanced by a scaling factor that balances the contributions of the data-misfit term and the constraining term to the value of the objective function. If this parameter is too large then it implies penalizing for the wave equation imposing a hard constraint in the inversion. If it is too small, then this leads to a poorly constrained solution as it is essentially penalizing for the data misfit and not taking into account the physics that explains the data. This paper introduces a new approach for the formulation of WRI recasting its formulation into a multiplicative cost function. We demonstrate that the proposed method outperforms the additive cost function when the trade-off parameter is appropriately scaled in the latter, when adapting it throughout the iterations, and when the data is contaminated with Gaussian random noise. Thus this work contributes with a framework for a more automated application of WRI.
Why does inverse modeling of drainage inventories work?
White, Nicky; Roberts, Gareth
2016-04-01
We describe and apply a linear inverse model which calculates spatial and temporal patterns of uplift rate by minimizing the misfit between inventories of observed and predicted longitudinal river profiles. This approach builds upon a more general, non-linear, optimization model, which suggests that shapes of river profiles are dominantly controlled by upstream advection of kinematic waves of incision produced by spatial and temporal changes in regional uplift rate. We have tested both algorithms by inverting thousands of river profiles from Africa, Eurasia, the Americas, and Australia. For each continent, the drainage network was constructed from a digital elevation model and the fidelity of river profiles extracted from this network was carefully checked using satellite imagery. Spatial and temporal patterns of both uplift rate and cumulative uplift were calibrated using independent geologic and geophysical observations. Inverse modeling of these substantial inventories of river profiles suggests that drainage networks contain coherent signals that record the regional growth of elevation. In the second part of this presentation, we use spectral analysis of river profiles to suggest why drainage networks behave in a coherent, albeit non-linear, fashion. Our analysis implies that large-scale topographic signals injected into landscapes generate spectral slopes that are usually red (i.e. Brownian). At wavelengths shorter than tens of km, spectral slopes whiten which suggests that coherent topographic signals cease to exist at these shorter length scales. Our results suggest that inverse modeling of drainage networks can reveal useful information about landscape growth through space and time.
Strategies for source space limitation in tomographic inverse procedures
International Nuclear Information System (INIS)
George, J.S.; Lewis, P.S.; Schlitt, H.A.; Kaplan, L.; Gorodnitsky, I.; Wood, C.C.
1994-01-01
The use of magnetic recordings for localization of neural activity requires the solution of an ill-posed inverse problem: i.e. the determination of the spatial configuration, orientation, and timecourse of the currents that give rise to a particular observed field distribution. In its general form, this inverse problem has no unique solution; due to superposition and the existence of silent source configurations, a particular magnetic field distribution at the head surface could be produced by any number of possible source configurations. However, by making assumptions concerning the number and properties of neural sources, it is possible to use numerical minimization techniques to determine the source model parameters that best account for the experimental observations while satisfying numerical or physical criteria. In this paper the authors describe progress on the development and validation of inverse procedures that produce distributed estimates of neuronal currents. The goal is to produce a temporal sequence of 3-D tomographic reconstructions of the spatial patterns of neural activation. Such approaches have a number of advantages, in principle. Because they do not require estimates of model order and parameter values (beyond specification of the source space), they minimize the influence of investigator decisions and are suitable for automated analyses. These techniques also allow localization of sources that are not point-like; experimental studies of cognitive processes and of spontaneous brain activity are likely to require distributed source models
Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA
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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.
Refraction traveltime tomography with irregular topography using the unwrapped phase inversion
Choi, Yun Seok
2013-01-01
Traveltime tomography has long served as a stable and efficient tool for velocity estimation, especially for the near surface. It, however, suffers from some of limitations associated with ray tracing and high-frequency traveltime in velocity inversion zones and ray shadow regions. We develop a tomographic approach based on traveltime solutions obtained by tracking the phase (instantaneous traveltime) of the wavefield solution of the Helmholtz wave equation. Since the instantaneous-traveltime does not suffer from phase wrapping, the inversion algorithm using the instantaneous-traveltime has the potential to generate robust inversion results. With a high damping factor, the instantaneous-traveltime inversion provides refraction tomography similar results, but from a single frequency. Despite the Helmholtz-based solver implementation, the tomographic inversion handles irrgular topography. The numerical examples show that our inversion algorithm generates a convergent smooth velocity model, which looks very much like a tomographic result. Next, we plan to apply the instantaneous-traveltime inversion algorithm to real seismic data acquired from the near surface with irregular topography.
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.
Shentu, Nanying; Qiu, Guohua; Li, Qing; Tong, Renyuan; Shentu, Nankai; Wang, Yanjie
2015-04-13
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.
Frequency Domain Multi-parameter Full Waveform Inversion for Acoustic VTI Media
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.
Inverse bootstrapping conformal field theories
Li, Wenliang
2018-01-01
We propose a novel approach to study conformal field theories (CFTs) in general dimensions. In the conformal bootstrap program, one usually searches for consistent CFT data that satisfy crossing symmetry. In the new method, we reverse the logic and interpret manifestly crossing-symmetric functions as generating functions of conformal data. Physical CFTs can be obtained by scanning the space of crossing-symmetric functions. By truncating the fusion rules, we are able to concentrate on the low-lying operators and derive some approximate relations for their conformal data. It turns out that the free scalar theory, the 2d minimal model CFTs, the ϕ 4 Wilson-Fisher CFT, the Lee-Yang CFTs and the Ising CFTs are consistent with the universal relations from the minimal fusion rule ϕ 1 × ϕ 1 = I + ϕ 2 + T , where ϕ 1 , ϕ 2 are scalar operators, I is the identity operator and T is the stress tensor.
Frequency domain full-waveform inversion with nonlinear descent directions
Geng, Yu; Pan, Wenyong; Innanen, Kristopher A.
2018-01-01
Full waveform inversion (FWI) is a highly nonlinear inverse problem, normally solved iteratively, with each iteration involving an update constructed through linear operations on the residuals. Incorporating a flexible degree of nonlinearity 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 nonlinear 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 nonlinear 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 nonlinear 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 nonlinear sensitivity kernel is computed in the outer loop. We examine the response of this nonlinear 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 nonlinear FWI has the capability to generate high resolution model estimates in both shallow and deep regions, and to converge rapidly, relative to a
Radiation Source Mapping with Bayesian Inverse Methods
Hykes, Joshua Michael
We present a method to map the spectral and spatial distributions of radioactive sources using a small number of detectors. Locating and identifying radioactive materials is important for border monitoring, accounting for special nuclear material in processing facilities, and in clean-up operations. Most methods to analyze these problems make restrictive assumptions about the distribution of the source. In contrast, the source-mapping method presented here allows an arbitrary three-dimensional distribution in space and a flexible group and gamma peak distribution in energy. To apply the method, the system's geometry and materials must be known. A probabilistic Bayesian approach is used to solve the resulting inverse problem (IP) since the system of equations is ill-posed. The probabilistic approach also provides estimates of the confidence in the final source map prediction. A set of adjoint flux, discrete ordinates solutions, obtained in this work by the Denovo code, are required to efficiently compute detector responses from a candidate source distribution. These adjoint fluxes are then used to form the linear model to map the state space to the response space. The test for the method is simultaneously locating a set of 137Cs and 60Co gamma sources in an empty room. This test problem is solved using synthetic measurements generated by a Monte Carlo (MCNP) model and using experimental measurements that we collected for this purpose. With the synthetic data, the predicted source distributions identified the locations of the sources to within tens of centimeters, in a room with an approximately four-by-four meter floor plan. Most of the predicted source intensities were within a factor of ten of their true value. The chi-square value of the predicted source was within a factor of five from the expected value based on the number of measurements employed. With a favorable uniform initial guess, the predicted source map was nearly identical to the true distribution
PREFACE: International Conference on Inverse Problems 2010
Hon, Yiu-Chung; Ling, Leevan
2011-03-01
Following the first International Conference on Inverse Problems - Recent Theoretical Development and Numerical Approaches held at the City University of Hong Kong in 2002, the fifth International Conference was held again at the City University during December 13-17, 2010. This fifth conference was jointly organized by Professor Yiu-Chung Hon (Co-Chair, City University of Hong Kong, HKSAR), Dr Leevan Ling (Co-Chair, Hong Kong Baptist University, HKSAR), Professor Jin Cheng (Fudan University, China), Professor June-Yub Lee (Ewha Womans University, South Korea), Professor Gui-Rong Liu (University of Cincinnati, USA), Professor Jenn-Nan Wang (National Taiwan University, Taiwan), and Professor Masahiro Yamamoto (The University of Tokyo, Japan). It was agreed to alternate holding the conference among the above places (China, Japan, Korea, Taiwan, and Hong Kong) once every two years. The next conference has been scheduled to be held at the Southeast University (Nanjing, China) in 2012. The purpose of this series of conferences is to establish a strong collaborative link among the universities of the Asian-Pacific regions and worldwide leading researchers in inverse problems. The conference addressed both theoretical (mathematics), applied (engineering) and developmental aspects of inverse problems. The conference was intended to nurture Asian-American-European collaborations in the evolving interdisciplinary areas and it was envisioned that the conference would lead to long-term commitments and collaborations among the participating countries and researchers. There was a total of more than 100 participants. A call for the submission of papers was sent out after the conference, and a total of 19 papers were finally accepted for publication in this proceedings. The papers included in the proceedings cover a wide scope, which reflects the current flourishing theoretical and numerical research into inverse problems. Finally, as the co-chairs of the Inverse Problems
An Exact Formula for Calculating Inverse Radial Lens Distortions
Directory of Open Access Journals (Sweden)
Pierre Drap
2016-06-01
Full Text Available This article presents a new approach to calculating the inverse of radial distortions. The method presented here provides a model of reverse radial distortion, currently modeled by a polynomial expression, that proposes another polynomial expression where the new coefficients are a function of the original ones. After describing the state of the art, the proposed method is developed. It is based on a formal calculus involving a power series used to deduce a recursive formula for the new coefficients. We present several implementations of this method and describe the experiments conducted to assess the validity of the new approach. Such an approach, non-iterative, using another polynomial expression, able to be deduced from the first one, can actually be interesting in terms of performance, reuse of existing software, or bridging between different existing software tools that do not consider distortion from the same point of view.
GENERALIZED INVERSE INTERVAL METHOD OF GLOBAL CONSTRAINED OPTIMIZATION
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A. V. Panteleyev
2014-01-01
Full Text Available The algorithmic and program software of inverse interval method for global constrained optimization are considered. The solution of model examples and the proof of the theorems of the algorithm’s convergence are presented. The generalized scheme of developed algorithms has been created. This scheme has two replaceable modules of compression and check. This module approach allows the users to implement their own versions of the algorithm without loss of the method convergence. This will help to tune the method according to the characteristics of the current problem.
Study of inverse methods in remote sensing with laser
International Nuclear Information System (INIS)
Jesus, Wellington Carlos de
2009-01-01
The Laboratory of Environmental Applications of Lasers at IPEN realizes a study about atmospherics properties, such as extinction and backscattering coefficient. These coefficient are estimated by an inverse method, whose estimate quality is difficult to measure. This work presents a method with good statistic approach to retrieval the same coefficients. The new method, however, offers a number of advantages compared to the first method in use, including (1) the ability to incorporate different kinds of information under a common retrieval philosophy and (2) the method provides number of ways for evaluating the quality of the retrieval. Thus we hope improve the accuracy of estimates. (author)
Recurrent DNA inversion rearrangements in the human genome
DEFF Research Database (Denmark)
Flores, Margarita; Morales, Lucía; Gonzaga-Jauregui, Claudia
2007-01-01
Several lines of evidence suggest that reiterated sequences in the human genome are targets for nonallelic homologous recombination (NAHR), which facilitates genomic rearrangements. We have used a PCR-based approach to identify breakpoint regions of rearranged structures in the human genome...... to human genomic variation is discussed........ In particular, we have identified intrachromosomal identical repeats that are located in reverse orientation, which may lead to chromosomal inversions. A bioinformatic workflow pathway to select appropriate regions for analysis was developed. Three such regions overlapping with known human genes, located...
Anisotropic parameter inversion in VTI media using diffraction data
Waheed, Umair bin
2013-09-22
Diffracted waves contain useful information regarding the subsurface geometry and velocity. They are particularly valuable for anisotropic media as they inherently possess a wide range of dips necessary to resolve angular dependence of velocity. Using this property of diffraction data to our vantage, we develop an algorithm to invert for effective η model, assuming no prior knowledge of it. The obtained effective η model is then converted to interval η model using Dix-type inversion formula. The effectiveness of this approach is tested on the VTI Marmousi model, which yields good structural match even for a highly complex media such as the Marmousi model.
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)
Application of the unwrapped phase inversion to land data without source estimation
Choi, Yun Seok
2015-08-19
Unwrapped phase inversion with a strong damping was developed to solve the phase wrapping problem in frequency-domain waveform inversion. In this study, we apply the unwrapped phase inversion to band-limited real land data, for which the available minimum frequency is quite high. An important issue of the data is a strong ambiguity of source-ignition time (or source shift) shown in a seismogram. A source-estimation approach does not fully address the issue of source shift, since the velocity model and the source wavelet are updated simultaneously and interact with each other. We suggest a source-independent unwrapped phase inversion approach instead of relying on source-estimation from this land data. In the source-independent approach, the phase of the modeled data converges not to the exact phase value of the observed data, but to the relative phase value (or the trend of phases); thus it has the potential to solve the ambiguity of source-ignition time in a seismogram and work better than the source-estimation approach. Numerical examples show the validation of the source-independent unwrapped phase inversion, especially for land field data having an ambiguity in the source-ignition time.
Huang, J.; Monteiro Santos, F. A.; Triantafilis, J.
2016-11-01
Characterization of the spatiotemporal distribution of soil volumetric water content (θ) is fundamental to agriculture, ecology, and earth science. Given the labor intensive and inefficient nature of determining θ, apparent electrical conductivity (ECa) measured by electromagnetic induction has been used as a proxy. A number of previous studies have employed inversion algorithms to convert ECa data to depth-specific electrical conductivity (σ) which could then be correlated to soil θ and other soil properties. The purpose of this study was to develop a spatiotemporal inversion algorithm which accounts for the temporal continuity of ECa. The algorithm was applied to a case study where time-lapse ECa was collected on a 350 m transect on seven different days on an alfalfa farm in the USA. Results showed that the approach was able to map the location of moving wetting front along the transect. Results also showed that the spatiotemporal inversion algorithm was more precise (RMSE = 0.0457 cm3/cm3) and less biased (ME = -0.0023 cm3/cm3) as compared with the nonspatiotemporal inversion approach (0.0483 cm3/cm3 and ME = -0.0030 cm3/cm3, respectively). In addition, the spatiotemporal inversion algorithm allows for a reduced set of ECa surveys to be used when non abrupt changes of soil water content occur with time. To apply this spatiotemporal inversion algorithm beyond low induction number condition, full solution of the EM induction phenomena can be studied in the future.
A New Wave Equation Based Source Location Method with Full-waveform Inversion
Wu, Zedong
2017-05-26
Locating the source of a passively recorded seismic event is still a challenging problem, especially when the velocity is unknown. Many imaging approaches to focus the image do not address the velocity issue and result in images plagued with illumination artifacts. We develop a waveform inversion approach with an additional penalty term in the objective function to reward the focusing of the source image. This penalty term is relaxed early to allow for data fitting, and avoid cycle skipping, using an extended source. At the later stages the focusing of the image dominates the inversion allowing for high resolution source and velocity inversion. We also compute the source location explicitly and numerical tests show that we obtain good estimates of the source locations with this approach.
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
QCD-instantons and conformal inversion symmetry
International Nuclear Information System (INIS)
Klammer, D.
2006-07-01
Instantons are an essential and non-perturbative part of Quantum Chromodynamics, the theory of strong interactions. One of the most relevant quantities in the instanton calculus is the instanton-size distribution, which can be described on the one hand within the framework of instanton perturbation theory and on the other hand investigated numerically by means of lattice computations. A rapid onset of a drastic discrepancy between these respective results indicates that the underlying physics is not yet well understood. In this work we investigate the appealing possibility of a symmetry under conformal inversion of space-time leading to this deviation. The motivation being that the lattice data seem to be invariant under an inversion of the instanton size. Since the instanton solution of a given size turns into an anti-instanton solution having an inverted size under conformal inversion of space-time, we ask in a first investigation, whether this property is transferred to the quantum level. In order to introduce a new scale, which is indicated by the lattice data and corresponds to the average instanton size as inversion radius, we project the instanton calculus onto the four-dimensional surface of a five-dimensional sphere via stereographic projection. The radius of this sphere is associated with the average instanton size. The result for the instanton size-distribution projected onto the sphere agrees surprisingly well with the lattice data at qualitative level. The resulting symmetry under an inversion of the instanton size is almost perfect. (orig.)
QCD-instantons and conformal inversion symmetry
Energy Technology Data Exchange (ETDEWEB)
Klammer, D.
2006-07-15
Instantons are an essential and non-perturbative part of Quantum Chromodynamics, the theory of strong interactions. One of the most relevant quantities in the instanton calculus is the instanton-size distribution, which can be described on the one hand within the framework of instanton perturbation theory and on the other hand investigated numerically by means of lattice computations. A rapid onset of a drastic discrepancy between these respective results indicates that the underlying physics is not yet well understood. In this work we investigate the appealing possibility of a symmetry under conformal inversion of space-time leading to this deviation. The motivation being that the lattice data seem to be invariant under an inversion of the instanton size. Since the instanton solution of a given size turns into an anti-instanton solution having an inverted size under conformal inversion of space-time, we ask in a first investigation, whether this property is transferred to the quantum level. In order to introduce a new scale, which is indicated by the lattice data and corresponds to the average instanton size as inversion radius, we project the instanton calculus onto the four-dimensional surface of a five-dimensional sphere via stereographic projection. The radius of this sphere is associated with the average instanton size. The result for the instanton size-distribution projected onto the sphere agrees surprisingly well with the lattice data at qualitative level. The resulting symmetry under an inversion of the instanton size is almost perfect. (orig.)
Unwrapped phase inversion with an exponential damping
Choi, Yun Seok
2015-07-28
Full-waveform inversion (FWI) suffers from the phase wrapping (cycle skipping) problem when the frequency of data is not low enough. Unless we obtain a good initial velocity model, the phase wrapping problem in FWI causes a result corresponding to a local minimum, usually far away from the true solution, especially at depth. Thus, we have developed an inversion algorithm based on a space-domain unwrapped phase, and we also used exponential damping to mitigate the nonlinearity associated with the reflections. We construct the 2D phase residual map, which usually contains the wrapping discontinuities, especially if the model is complex and the frequency is high. We then unwrap the phase map and remove these cycle-based jumps. However, if the phase map has several residues, the unwrapping process becomes very complicated. We apply a strong exponential damping to the wavefield to eliminate much of the residues in the phase map, thus making the unwrapping process simple. We finally invert the unwrapped phases using the back-propagation algorithm to calculate the gradient. We progressively reduce the damping factor to obtain a high-resolution image. Numerical examples determined that the unwrapped phase inversion with a strong exponential damping generated convergent long-wavelength updates without low-frequency information. This model can be used as a good starting model for a subsequent inversion with a reduced damping, eventually leading to conventional waveform inversion.
Full wave-field reflection coefficient inversion.
Dettmer, Jan; Dosso, Stan E; Holland, Charles W
2007-12-01
This paper develops a Bayesian inversion for recovering multilayer geoacoustic (velocity, density, attenuation) profiles from a full wave-field (spherical-wave) seabed reflection response. The reflection data originate from acoustic time series windowed for a single bottom interaction, which are processed to yield reflection coefficient data as a function of frequency and angle. Replica data for inversion are computed using a wave number-integration model to calculate the full complex acoustic pressure field, which is processed to produce a commensurate seabed response function. To address the high computational cost of calculating short range acoustic fields, the inversion algorithms are parallelized and frequency averaging is replaced by range averaging in the forward model. The posterior probability density is interpreted in terms of optimal parameter estimates, marginal distributions, and credibility intervals. Inversion results for the full wave-field seabed response are compared to those obtained using plane-wave reflection coefficients. A realistic synthetic study indicates that the plane-wave assumption can fail, producing erroneous results with misleading uncertainty bounds, whereas excellent results are obtained with the full-wave reflection inversion.
Multiscattering inversion for low-model wavenumbers
Alkhalifah, Tariq Ali
2016-09-21
A successful full-waveform inversion implementation updates the low-wavenumber model components first for a proper description of the wavefield propagation 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 wavefield emanating directly from the source or the transmission parts from the single- or double-scattered wavefield computed from a predicted scatter field acting as secondary sources.We use a combined inversion of data modeled from the source and those corresponding to single and double scattering to update 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 are directed to the perturbation model and the low-wavenumber (highscattering- angle) components are directed to the velocity model. As our background velocity matures, the scatteringangle divide is slowly lowered to allow for more of the higher wavenumbers to contribute the velocity model. Synthetic examples including the Marmousi model are used to demonstrate the additional illumination and improved velocity inversion obtained when including multiscattered energy. © 2016 Society of Exploration Geophysicists.
Directory of Open Access Journals (Sweden)
YanBin Liu
2017-01-01
Full Text Available The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller.
Liu, YanBin; Li, YuHui; Jin, FeiTeng
2017-01-01
The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller.
Inversion of SAR data in active volcanic areas by optimization techniques
Directory of Open Access Journals (Sweden)
G. Nunnari
2005-01-01
Full Text Available The inversion problem concerns the identification of parameters of a volcanic source causing observable changes in ground deformation data recorded in volcanic areas. In particular, this paper deals with the inversion of ground deformation measured by using SAR (Synthetic Aperture Radar interferometry and an inversion approach formulated in terms of an optimization problem is proposed. Based on this inversion scheme, it is shown that the problem of inverting ground deformation data in terms of a single source, of Mogi or Okada type, is numerically well conditioned. In the paper, two case studies of inverting actual SAR data recorded on Mt. Etna during eruptions occurring in 1998 and 2001 are investigated, showing the suitability of the proposed technique.
Efficiency of Pareto joint inversion of 2D geophysical data using global optimization methods
Miernik, Katarzyna; Bogacz, Adrian; Kozubal, Adam; Danek, Tomasz; Wojdyła, Marek
2016-04-01
Pareto joint inversion of two or more sets of data is a promising new tool of modern geophysical exploration. In the first stage of our investigation we created software enabling execution of forward solvers of two geophysical methods (2D magnetotelluric and gravity) as well as inversion with possibility of constraining solution with seismic data. In the algorithm solving MT forward solver Helmholtz's equations, finite element method and Dirichlet's boundary conditions were applied. Gravity forward solver was based on Talwani's algorithm. To limit dimensionality of solution space we decided to describe model as sets of polygons, using Sharp Boundary Interface (SBI) approach. The main inversion engine was created using Particle Swarm Optimization (PSO) algorithm adapted to handle two or more target functions and to prevent acceptance of solutions which are non - realistic or incompatible with Pareto scheme. Each inversion run generates single Pareto solution, which can be added to Pareto Front. The PSO inversion engine was parallelized using OpenMP standard, what enabled execution code for practically unlimited amount of threads at once. Thereby computing time of inversion process was significantly decreased. Furthermore, computing efficiency increases with number of PSO iterations. In this contribution we analyze the efficiency of created software solution taking under consideration details of chosen global optimization engine used as a main joint minimization engine. Additionally we study the scale of possible decrease of computational time caused by different methods of parallelization applied for both forward solvers and inversion algorithm. All tests were done for 2D magnetotelluric and gravity data based on real geological media. Obtained results show that even for relatively simple mid end computational infrastructure proposed solution of inversion problem can be applied in practice and used for real life problems of geophysical inversion and interpretation.
Ramig, Keith; Subramaniam, Gopal; Karimi, Sasan; Szalda, David J; Ko, Allen; Lam, Aaron; Li, Jeffrey; Coaderaj, Ani; Cavdar, Leyla; Bogdan, Lukasz; Kwon, Kitae; Greer, Edyta M
2016-04-15
A series of 2,4-disubstituted 1H-1-benzazepines, 2a-d, 4, and 6, were studied, varying both the substituents at C2 and C4 and at the nitrogen atom. The conformational inversion (ring-flip) and nitrogen-atom inversion (N-inversion) energetics were studied by variable-temperature NMR spectroscopy and computations. The steric bulk of the nitrogen-atom substituent was found to affect both the conformation of the azepine ring and the geometry around the nitrogen atom. Also affected were the Gibbs free energy barriers for the ring-flip and the N-inversion. When the nitrogen-atom substituent was alkyl, as in 2a-c, the geometry of the nitrogen atom was nearly planar and the azepine ring was highly puckered; the result was a relatively high-energy barrier to ring-flip and a low barrier to N-inversion. Conversely, when the nitrogen-atom substituent was a hydrogen atom, as in 2d, 4, and 6, the nitrogen atom was significantly pyramidalized and the azepine ring was less puckered; the result here was a relatively high energy barrier to N-inversion and a low barrier to ring-flip. In these N-unsubstituted compounds, it was found computationally that the lowest-energy stereodynamic process was ring-flip coupled with N-inversion, as N-inversion alone had a much higher energy barrier.
3D CSEM inversion based on goal-oriented adaptive finite element method
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
Oil core microcapsules by inverse gelation technique.
Martins, Evandro; Renard, Denis; Davy, Joëlle; Marquis, Mélanie; Poncelet, Denis
2015-01-01
A promising technique for oil encapsulation in Ca-alginate capsules by inverse gelation was proposed by Abang et al. This method consists of emulsifying calcium chloride solution in oil and then adding it dropwise in an alginate solution to produce Ca-alginate capsules. Spherical capsules with diameters around 3 mm were produced by this technique, however the production of smaller capsules was not demonstrated. The objective of this study is to propose a new method of oil encapsulation in a Ca-alginate membrane by inverse gelation. The optimisation of the method leads to microcapsules with diameters around 500 μm. In a search of microcapsules with improved diffusion characteristics, the size reduction is an essential factor to broaden the applications in food, cosmetics and pharmaceuticals areas. This work contributes to a better understanding of the inverse gelation technique and allows the production of microcapsules with a well-defined shell-core structure.