Control of Interface Order by Inverse Quasi-Epitaxial Growth of Squaraine/Fullerene Thin Film Photovoltaics
Explore the source record for details and available documents.
charge transport↗
SEARCH · Engineering Papers
Results for “inversion”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Bayesian Inversion of Seismic and Electromagnetic Data for Marine Gas Reservoir Characterization Using Multi-chain Markov Chain Monte Carlo Sampling
In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.
Ren, Huiying↗
Inverse load calculation procedure for offshore wind turbines and application to a 5‐MW wind turbine support structure
Abstract A significant number of wind turbines installed today have reached their designed service life of 20 years, and the number will rise continuously. Most of these turbines promise a more economical performance if they operate for more than 20 years. To assess a continued operation, we have to analyze the load‐bearing capacity of the support structure with respect to site‐specific conditions. Such an analysis requires the comparison of the loads used for the design of the support structure with the actual loads experienced. This publication presents the application of a so‐called inverse load calculation to a 5‐MW wind turbine support structure. The inverse load calculation determines external loads derived from a mechanical description of the support structure and from measured structural responses. Using numerical simulations with the software fast , we investigated the influence of wind‐turbine‐specific effects such as the wind turbine control or the dynamic interaction between the loads and the support structure to the presented inverse load calculation procedure. fast is used to study the inverse calculation of simultaneously acting wind and wave loads, which has not been carried out until now. Furthermore, the application of the inverse load calculation procedure to a real 5‐MW wind turbine support structure is demonstrated. In terms of this practical application, setting up the mechanical system for the support structure using measurement data is discussed. The paper presents results for defined load cases and assesses the accuracy of the inversely derived dynamic loads for both the simulations and the practical application. Copyright © 2017 John Wiley & Sons, Ltd.
Pahn, T.↗
A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion
In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by three steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Estimating the trace of the matrix inverse by interpolating from the diagonal of an approximate inverse
Not provided.
Computer Science↗
Basis set expansion for inverse problems in plasma diagnostic analysis
A basis set expansion method [V. Dribinski, A. Ossadtchi, V. A. Mandelshtam, and H. Reisler, Rev. Sci. Instrum. 73, 2634 (2002)] is applied to recover physical information about plasma radiation sources from instrument data, which has been forward transformed due to the nature of the measurement technique. This method provides a general approach for inverse problems, and we discuss two specific examples relevant to diagnosing fast z pinches on the 20–25 MA Z machine [M. E. Savage, L. F. Bennett, D. E. Bliss, W. T. Clark, R. S. Coats, J. M. Elizondo, K. R. LeChien, H. C. Harjes, J. M. Lehr, J. E. Maenchen, D. H. McDaniel, M. F. Pasik, T. D. Pointon, A. C. Owen, D. B. Seidel, D. L. Smith, B. S. Stoltzfus, K. W. Struve, W. A. Stygar, L. K. Warne, J. R. Woodworth, C. W. Mendel, K. R. Prestwich, R. W. Shoup, D. L. Johnson, J. P. Corley, K. C. Hodge, T. C. Wagoner, and P. E. Wakeland, in Proceedings of the Pulsed Power Plasma Sciences Conference (IEEE, 2007), p. 979]. First, Abel inversion of time-gated, self-emission x-ray images from a wire array implosion is studied. Second, we present an approach for unfolding neutron time-of-flight measurements from a deuterium gas puff z pinch to recover information about emission time history and energy distribution. Through these examples, we discuss how noise in the measured data limits the practical resolution of the inversion, and how the method handles discontinuities in the source function and artifacts in the projected image. We add to the method a propagation of errors calculation for estimating uncertainties in the inverted solution.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Spread Spectrum Time Domain Reflectometry and Steepest Descent Inversion to Measure Complex Impedance
In this paper, we present a method for estimating complex impedances using reflectometry and a modified steepest descent inversion algorithm. We simulate spread spectrum time domain reflectometry (SSTDR), which can measure complex impedances on energized systems for an experimental setup with resistive and capacitive loads. A parametric function, which includes both a misfit function and stabilizer function, is created. The misfit function is a least squares estimate of how close the model data matches observed data. The stabilizer function prevents the steepest descent algorithm from becoming unstable and diverging. Steepest descent iteratively identifies the model parameters that minimize the parametric function. We validate the algorithm by correctly identifying the model parameters (capacitance and resistance) associated with simulated SSTDR data, with added 3 dB white Gaussian noise. With the stabilizer function, the steepest descent algorithm estimates of the model parameters are bounded within a specified range. Furthermore, the errors for capacitance (220pF to 820pF) and resistance (50 Ω to 270 Ω) are < 10%, corresponding to a complex impedance magnitude |R +1/jωC| of 53 Ω to 510 Ω.
14 SOLAR ENERGY↗
Tomographic inversion techniques incorporating physical constraints for line integrated spectroscopy in stellarators and tokamaks
Accurate tomographic inversion is important for diagnostic systems on stellarators and tokamaks which rely on measurements of line integrated emission spectra. A tomographic inversion technique based on spline optimization with enforcement of constraints is described that can produce unique and physically relevant inversions even in situations with noisy or incomplete input data. This inversion technique is routinely used in the analysis of data from the x-ray imaging crystal spectrometer (XICS) installed at the Large Helical Device. The XICS diagnostic records a 1D image of line integrated emission spectra from impurities in the plasma. Through the use of Doppler spectroscopy and tomographic inversion, XICS can provide profile measurements of the local emissivity, temperature, and plasma flow. Tomographic inversion requires the assumption that these measured quantities are flux surface functions, and that a known plasma equilibrium reconstruction is available. In the case of low signal levels or partial spatial coverage of the plasma cross-section, standard inversion techniques utilizing matrix inversion and linear-regularization often cannot produce unique and physically relevant solutions. The addition of physical constraints, such as parameter ranges, derivative directions, and boundary conditions, allow for unique solutions to be reliably found. The constrained inversion technique described here utilizes a modified Levenberg-Marquardt optimization scheme, which introduces a condition avoidance mechanism by selective reduction of search directions. The constrained inversion technique also allows for the addition of more complicated parameter dependencies, for example, geometrical dependence of the emissivity due to asymmetries in the plasma density arising from fast rotation. The accuracy of this constrained inversion technique is discussed, with an emphasis on its applicability to systems with limited plasma coverage.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
New insights into the enigma of boron carbide inverse molecular behavior
Abstract not provided
Dera, Przemyslaw↗
Fabrication of Transparent-Conducting-Oxide-Coated Inverse Opals as Mesostructured Architectures for Electrocatalysis Applications: A Case Study with NiO
Highly ordered, and conductive inverse opal arrays were made with silica and subsequently coated with tin-doped indium oxide (ITO) via atomic layer deposition (ALD). We demonstrate the utility of the resulting mesostructured electrodes by further coating them with nickel oxide via ALD. The NiO-coated arrays are capable of efficiently electrochemically evolving oxygen from water. These modular, crack-free, transparent, high surface area, and conducting structures show promise for many applications including electrocatalysis, photocatalysis, and dye-sensitized solar cells.
Williams, Vennesa O.↗
Characterizing the inverses of block tridiagonal, block Toeplitz matrices
We consider the inversion of block tridiagonal, block Toeplitz matrices and comment on the behaviour of these inverses as one moves away from the diagonal. Using matrix Möbius transformations, we first present an O(1) representation (with respect to the number of block rows and block columns) for the inverse matrix and subsequently use this representation to characterize the inverse matrix. There are four symmetry-distinct cases where the blocks of the inverse matrix (i) decay to zero on both sides of the diagonal, (ii) oscillate on both sides, (iii) decay on one side and oscillate on the other and (iv) decay on one side and grow on the other. This characterization exposes the necessary conditions for the inverse matrix to be numerically banded and may also aid in the design of preconditioners and fast algorithms. Finally, we present numerical examples of these matrix types.
block Toeplitz matrices↗
Fast inversion, preconditioned quantum linear system solvers, fast Green's-function computation, and fast evaluation of matrix functions
Preconditioning is the most widely used and effective way for treating ill-conditioned linear systems in the context of classical iterative linear system solvers. We introduce a quantum primitive called fast inversion, which can be used as a preconditioner for solving quantum linear systems. The key idea of fast inversion is to directly block encode a matrix inverse through a quantum circuit implementing the inversion of eigenvalues via classical arithmetics. We demonstrate the application of preconditioned linear system solvers for computing single-particle Green's functions of quantum many-body systems, which are widely used in quantum physics, chemistry, and materials science. We analyze the complexities in three scenarios: the Hubbard model, the quantum many-body Hamiltonian in the plane-wave-dual basis, and the Schwinger model. We also provide a method for performing Green's function calculation in second quantization within a fixed-particle manifold and note that this approach may be valuable for simulation more broadly. Aside from solving linear systems, fast inversion also allows us to develop fast algorithms for computing matrix functions, such as the efficient preparation of Gibbs states. Furthermore, we introduce two efficient approaches for such a task, based on the contour-integral formulation and the inverse transform, respectively.
97 MATHEMATICS AND COMPUTING↗
On the Ill-Posed Nature of Inverse Problems: An Exactly Solvable Paradigm Inverse Neutron Diffusion Problem Illustrating the Solution's Non-Computability - Paper 48
In general, a physical system and/or the result of an indirect experimental measurement are modeled mathematically in terms of: (a) A system of linear and/or nonlinear equations that relate the system's independent variables and parameters to the system's state (i.e., dependent) variables; (b) Probability distributions, moments thereof, inequality and/or equality constraints that define the range of variations of the system's parameters; (c) One or several quantities, customarily referred to as system responses (or objective functions, or indices of performance), which are computed using the mathematical model. The 'direct problem' solves the 'parameter-to-output' mapping that describes the 'cause-to-effect' relationship in the respective physical process. In practice, the model parameters and/or responses are experimentally measured quantities and are therefore subject to uncertainties. Many measurement problems are 'inverse' to the direct problem in that they seek to determine the properties of the medium (i.e., various cross sections), or the properties of the source, and/or the size of the medium on its boundaries from measurements of quantities that depend on the neutron flux (or from direct measurements of the neutron flux). In general, two problems are called inverses of one another if the formulation of each involves all or part of the solution of the other. Some authors further group such inverse problems into 'invasive', when the interior flux is accessible for measurements as opposed to 'non-invasive', in which only fluxes on the boundary of (or exterior to) the medium can be measured. Examples of inverse radiative transfer problems have been reviewed by McCormick, while examples of inverse source problems for neutron transport have been provided by Sanchez and McCormick. More recently, Bledsoe et al., have presented two methods (the Levenberg-Marquard, and 'differential evolution method') for addressing numerically inverse transport problems. However, although these works (as well as other works cited therein) mentioned the detrimental effects of 'small perturbations in the input data', none of the works published thus far on inverse problems for particle transport or diffusion actually showed explicitly the effects that uncertainties in the measured responses (e.g., detector measurements) would actually have on the 'inverse' deduction (from such measurements) of the underlying medium's properties, sources, etc. This work highlights explicitly the nature of the difficulties encountered in so-called 'inverse problems' by presenting a paradigm inverse neutron diffusion problem admitting an exact solution, in which the 'inverse problem' is to determine the medium's diffusion coefficient from flux measurements. It will be shown explicitly (analytically) that this is not possible to achieve in a unique manner, even in the absence of measurement uncertainties, unless additional error-free information is provided about the quantity to be determined (in this case, the medium's diffusion coefficient). It if further shown that, even if this additional error-free information about the diffusion coefficient to be determined is available, the unavoidable experimental measurements errors, albeit it vanishingly small, in the measured flux render the 'exact solution' useless for computational purposes, since the exact solution turns out to be a divergent series. As discussed in this paper's ENDNOTES section, the paradigm problem presented in this work also underscores the need for 'regularization', which is a qualifier indicating that the inverse problem is to be solved in some approximate manner. (authors)
61 RADIATION PROTECTION AND DOSIMETRY↗
Inverse scattering theory: Inverse scattering series method for one dimensional non-compact support potential
The reversion of the Born-Neumann series of the Lippmann-Schwinger equation is one of the standard ways to solve the inverse acoustic scattering problem. One limitation of the current inversion methods based on the reversion of the Born-Neumann series is that the velocity potential should have compact support. However, this assumption cannot be satisfied in certain cases, especially in seismic inversion. Based on the idea of distorted wave scattering, we explore an inverse scattering method for velocity potentials without compact support. The strategy is to decompose the actual medium as a known single interface reference medium, which has the same asymptotic form as the actual medium and a perturbative scattering potential with compact support. After introducing the method to calculate the Green’s function for the known reference potential, the inverse scattering series and Volterra inverse scattering series are derived for the perturbative potential. Analytical and numerical examples demonstrate the feasibility and effectiveness of this method. Besides, to ensure stability of the numerical computation, the Lanczos averaging method is employed as a filter to reduce the Gibbs oscillations for the truncated discrete inverse Fourier transform of each order. Our method provides a rigorous mathematical framework for inverse acoustic scattering with a non-compact support velocity potential.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
WHISTLER TURBULENCE FORWARD CASCADE VERSUS INVERSE CASCADE: THREE-DIMENSIONAL PARTICLE-IN-CELL SIMULATIONS
We present the results of the first fully three-dimensional particle-in-cell simulations of decaying whistler turbulence in a magnetized, homogeneous, collisionless plasma in which both forward cascades to shorter wavelengths, and inverse cascades to longer wavelengths are allowed to proceed. For the electron beta β {sub e} = 0.10 initial value considered here, the early-time rate of inverse cascade is very much smaller than the rate of forward cascade, so that at late times the fluctuation energy in the regime of the inverse cascade is much weaker than that in the forward cascade regime. Similarly, the wavevector anisotropy in the inverse cascade regime is much weaker than that in the forward cascade regime.
79 ASTRONOMY AND ASTROPHYSICS↗
Source-encoded waveform inversion in the Northern Hemisphere
SUMMARY We use source-encoded waveform inversion to image Earth’s Northern Hemisphere. The encoding method is based on measurements of Laplace coefficients of stationary wavefields. By assigning to each event a unique frequency, we compute Fréchet derivatives for all events simultaneously based on one ‘super’ forward and one ‘super’ adjoint simulation for a small fraction of the computational cost of classical waveform inversion with the same data set. No cross-talk noise is introduced in the process, and the method does not require all events to be recorded by all stations. Starting from global model GLAD_M25, we performed 100 conjugate gradient iterations using a data set consisting of 786 earthquakes recorded by 9846 stations. Synthetic inversion tests show that we achieve good convergence based on this data set, and we see a consistent misfit reduction during the inversion. The new model, named SE100, has much higher spatial resolution than GLAD_M25, revealing details of the Yellowstone and Iceland hotspots, subduction beneath the Western United States and the upper mantle structure beneath the Arctic Ocean.
Cui, Congyue↗
Atmospheric inversion of surface carbon flux with consideration of the spatial distribution of US crop production and consumption
In order to improve quantification of the spatial distribution of carbon sinks and sources in the conterminous US, we conduct a nested global atmospheric inversion with detailed spatial information on crop production and consumption. County-level cropland net primary productivity, harvested biomass, soil carbon change, and human and livestock consumption data over the conterminous US are used for this purpose. Time-dependent Bayesian synthesis inversions are conducted based on CO₂ observations at 210 stations to infer CO₂ fluxes globally at monthly time steps with a nested focus on 30 regions in North America. Prior land surface carbon fluxes are first generated using a biospheric model, and the inversions are constrained using prior fluxes with and without adjustments for crop production and consumption over the 2002–2007 period. After these adjustments, the inverted regional carbon sink in the US Midwest increases from 0.25 ± 0.03 to 0.42 ± 0.13 Pg C yr⁻¹, whereas the large sink in the US southeast forest region is weakened from 0.41 ± 0.12 to 0.29 ± 0.12 Pg C yr⁻¹. These adjustments also reduce the inverted sink in the west region from 0.066 ± 0.04 to 0.040 ± 0.02 Pg C yr⁻¹ because of high crop consumption and respiration by humans and livestock. The general pattern of sink increases in crop production areas and sink decreases (or source increases) in crop consumption areas highlights the importance of considering the lateral carbon transfer in crop products in atmospheric inverse modeling, which provides a reliable atmospheric perspective of the overall carbon balance at the continental scale but is unreliable for separating fluxes from different ecosystems.
54 ENVIRONMENTAL SCIENCES↗
Large-scale inverse model analyses employing fast randomized data reduction: INVERSE MODELING WITH DATA REDUCTION
When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 10 7 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called “sketching” matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Moreover, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Thus, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.
54 ENVIRONMENTAL SCIENCES↗