Prediction of the Magnetic State of Ferromagnetic Objects by Assimilating Data into a Physical Model

This paper presents a hybrid model to estimate the magnetic behaviour of a ferromagnetic structure. The mathematical-physical model has been developed using the Method of Moments combined with a hysteresis model. The mathematical model was derived by a linearisation of the hysteresis curve. The initial magnetic state of a ferromagnetic object is...

Quantifying methane emissions from the largest oil-producing basin in the United States from space

Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world's most prolific oil-producing regions and accounts for >30% of total U.S. oil production. Based on satellite measurements from May 2018 to March 2019, Permian methane emissions from oil and natural gas...

Dust Emission Inversion Using Himawari-8 AODs Over East Asia: An Extreme Dust Event in May 2017

Aerosol optical depths (AODs) from the new Himawari-8 satellite instrument have been assimilated in a dust simulation model over East Asia. This advanced geostationary instrument is capable of monitoring the East Asian dust storms which usually have great spatial and temporal variability. The quality of the data has been verified through a...

Evaluation of deep neural networks for single image super-resolution in a maritime context

High resolution imagery is of crucial importance for the performance on visual recognition tasks. Super-resolution (SR) reconstruction algorithms aim to enhance the image resolution beyond the capability of the image sensor being used. Traditional SR algorithms approach this inverse problem using physical models for the image formation combined...

Decentralized data fusion with inverse covariance intersection

In distributed and decentralized state estimation systems, fusion methods are employed to systematically combine multiple estimates of the state into a single, more accurate estimate. An often encountered problem in the fusion process relates to unknown common information that is shared by the estimates to be fused and is responsible for...

Inverse covariance intersection: New insights and properties

Decentralized data fusion is a challenging task. Either it is too difficult to maintain and track the information required to perform fusion optimally, or too much information is discarded to obtain informative fusion results. A well-known solution is Covariance Intersection, which may provide too conservative fusion results. A less conservative...

Performance indicator of a bridge expansion joint

In general the condition of a structure can be assessed in terms of a performance indicator. For example, this can be the strength of a structure. An asset manager is concerned with ensuring that the performance of a structure does not fall below a given minimum level. This can be achieved by inspecting or monitoring the structure. As the...

Downscaling: A complement to homogenization

A groundwater flow model based on a specified hydraulic conductivity field in the modeling domain has a unique solution only if either the head or the normal flux component is specified on the boundary. On the other hand, specification of both head and flux as boundary conditions may be used to determine the conductivity field, or at least...

Forward and inverse modeling of near-well flow using discrete edge-based vector potentials

Homogeneous effective permeabilities in the near-well region are generally obtained using analytical solutions for transient flow. In contrast, this paper focuses on heterogeneous permeability obtained from steady flow solutions, although extensions to unsteady flow are introduced too. Exterior calculus and its discretized form have been used as...

Ill-posed inverse problem in diffraction optics: Tolerance analysis of diffractive lenses and gratings

A method is proposed for the prediction of deviations of the phase polynomial coefficients of diffractive optical elements from their nominal values due to fabrication errors. This problem represents an ill-posed inverse problem in diffraction optics. Its solution is based on the regularization technique resulting in an approximate stable ...

Inverse modeling of groundwater flow using model reduction

Numerical groundwater flow models often have a very high number of model cells (greater than a million). Such models are computationally very demanding, which is disadvantageous for inverse modeling. This paper describes a low-dimensional formulation for groundwater flow that reduces the computational burden necessary for inverse modeling. The...

A representer-based inverse method for groundwater flow and transport applications

Groundwater inverse problems are concerned with the estimation of uncertain model parameters, such as hydraulic conductivity, from field or laboratory measurements. In practice, model and measurement errors compromise the ability of inverse procedures to provide accurate results. It is important to account for such errors in order to determine...

Time-domain gradient-type methods for inversion of the subsurface

The inverse problem of reconstructing a scattering object in a two-media background was analyzed using time-domain gradient-type method. The scattering object was illuminated successively by line sources located in the upper medium. The incident field from the line source was calculated using a spatial Fourier transforms in the x1-direction and...