Search Results (2,807)

In this paper, we address the extremal inverse eigenvalue problem for pentadiagonal matrices. We provide sufficient conditions for their existence and realizability through new constructions that consider spectral data of its leading principal submatrices. Finally, we present some examples generated from the algorithmic procedures derived from our results. Full article

In the modelling of hydrological processes on a regional scale, remote-sensing snow depth products with a high spatial and temporal resolution are essential for climate change studies and for scientific decision-making by management. The existing snow depth products have low spatial resolution and are mostly applicable to large-scale studies; however, they are insufficiently accurate for the estimation of snow depth on a regional scale, especially in shallow snow areas and mountainous regions. In this study, we coupled SSM/I, SSMIS, and AMSR2 passive microwave brightness temperature data and MODIS, TM, and Landsat 8 OLI fractional snow cover area (fSCA) data, based on Python, with 30 m spatially resolved fractional snow cover area (fSCA) data obtained by the spatio-temporal dynamic warping algorithm to invert the low-resolution passive microwave snow depths, and we developed a spatially downscaled snow depth inversion method suitable for the Turpan–Hami region. However, due to the long data-processing time and the insufficient arithmetical power of the hardware, this study had to set the spatial resolution of the result output to 250 m. As a result, a day-by-day 250 m spatial resolution snow depth dataset for 20 hydrological years (1 August 2000–31 July 2020) was generated, and the accuracy was evaluated using the measured snow depth data from the meteorological stations, with the results of r = 0.836 (p ≤ 0.01), MAE = 1.496 cm, and RMSE = 2.597 cm, which are relatively reliable and more applicable to the Turpan–Hami area. Based on the spatially downscaled snow depth data produced, this study found that the snow in the Turpan–Hami area is mainly distributed in the northern part of Turpan (Bogda Mountain), the northwestern part of Hami (Barkun Autonomous Prefecture), and the central part of the area (North Tianshan Mountain, Barkun Mountain, and Harlik Mountain). The average annual snow depth in the Turpan–Hami area is only 0.89 cm, and the average annual snow depth increases with elevation, in line with the obvious law of vertical progression. The annual mean snow depth in the Turpan–Hami area showed a “fluctuating decreasing” trend with a rate of 0.01 cm·a⁻¹ over the 20 hydrological years in the Turpan–Hami area. Overall, the spatially downscaled snow depth inversion algorithm developed in this study not only solves the problem of coarse spatial resolution of microwave brightness temperature data and the difficulty of obtaining accurate shallow snow depth but also solves the problem of estimating the shallow snow depth on a regional scale, which is of great significance for gaining a further understanding of the snow accumulation information in the Tuha region and for promoting the investigation and management of water resources in arid zones. Full article

We propose an artificial intelligence approach based on deep neural networks to tackle a canonical 2D scalar inverse source problem. The learned singular value decomposition (L-SVD) based on hybrid autoencoding is considered. We compare the reconstruction performance of L-SVD to the Truncated SVD (TSVD) regularized inversion, which is a canonical regularization scheme, to solve an ill-posed linear inverse problem. Numerical tests referring to far-field acquisitions show that L-SVD provides, with proper training on a well-organized dataset, superior performance in terms of reconstruction errors as compared to TSVD, allowing for the retrieval of faster spatial variations of the source. Indeed, L-SVD accommodates a priori information on the set of relevant unknown current distributions. Different from TSVD, which performs linear processing on a linear problem, L-SVD operates non-linearly on the data. A numerical analysis also underlines how the performance of the L-SVD degrades when the unknown source does not match the training dataset. Full article

This work investigates the inverse coupled radiation–conduction problem for estimating thermophysical parameters and source terms by an improved grey wolf optimization (GWO). The transient coupled radiation–conduction heat transfer problem in participating slab media is solved by the finite volume method. The radiative intensities on both boundaries are adopted as known measurement information in the inverse model. To overcome the disadvantages of the original GWO algorithm, an improved grey wolf algorithm (IGWO) is developed by introducing the weight strategy and nonlinear factors. Three benchmark functions are adopted to prove that the IGWO has a faster convergence speed and higher estimation accuracy than the original one. The IGWO is applied to inverse the thermophysical parameters and source terms based on the coupled radiation–conduction model; the results indicate that the IGWO is accurate and effective for estimating refractive index, absorption coefficient, and source terms. Full article

To realize the design process of bionic mechatronic systems, involving mapping from engineering to biology and inversion from biology to engineering, a novel design paradigm is introduced that integrates BioTRIZ with multi-factor coupling bionics. In the mapping stage from engineering to biology, BioTRIZ is employed to frame the concrete engineering issue as a general conflicting problem. The biological solution is refined by amalgamating the BioTRIZ solution derived from the contradiction matrix with biological instances. In the inversion stage of biology to engineering, a novel approach is proposed for constructing a bionic multi-factor coupling model, drawing inspiration from the establishment of biological multi-factor coupling model. This allows for a seamless correspondence between biological elements, such as morphology and behavior, and their respective engineering counterparts, including structure and algorithms. This correspondence ultimately achieves the engineering conceptual model that is rooted in biological principles. The practical application of this methodology is exemplified through a multi-biometric fusion bionic active vision system, underscoring its feasibility and efficacy. Full article

Contactless inductive flow tomography (CIFT) is a flow measurement technique allowing for visualization of the global flow in electrically conducting fluids. The method is based on the principle of induction by motion: very weak induced magnetic fields arise from the fluid motion under the influence of a primary excitation magnetic field and can be measured precisely outside of the fluid volume. The structure of the causative flow field can be reconstructed from the induced magnetic field values by solving the according linear inverse problem using appropriate regularization methods. The concurrent use of more than one excitation magnetic field is necessary to fully reconstruct three-dimensional liquid metal flows. In our laboratory demonstrator experiment, we impose two excitation magnetic fields perpendicular to each other to a mechanically driven flow of the liquid metal alloy GaInSn. In the first approach, the excitation fields are multiplexed. Here, the temporal resolution of the measurement needs to be kept as high as possible. Consecutive application by multiplexing enables determining the flow structure in the liquid with a temporal resolution down to 3 s with the existing equipment. In another approach, we concurrently apply two sinusoidal excitation fields with different frequencies. The signals are disentangled on the basis of the lock-in principle, enabling a successful reconstruction of the liquid metal flow. Full article

This paper presents a new semi-explicit algorithm for parameters estimation in a time-fractional generalization of a dual-phase-lag heat conduction model with Caputo fractional derivatives. It is shown that this model can be derived from a general linear constitutive relation for the heat transfer by conduction when the heat conduction relaxation kernel contains the Mittag–Leffler function. The model can be used to describe heat conduction phenomena in a material with power-law memory. The proposed algorithm of parameters estimation is based on the time integral characteristics method. The explicit representations of the thermal diffusivity and the fractional analogues of the thermal relaxation time and the thermal retardation are obtained via a Laplace transform of the temperature field and utilized in the algorithm. An implicit relation is derived for the order of fractional differentiation. In the algorithm, this relation is resolved numerically. An example illustrates the proposed technique. Full article

Casing damage is a common problem encountered during oil and gas field development due to the complex stress state of the casing. Despite the large number of studies focusing on this problem, the mechanism of non-uniform in-situ stress-induced casing damage in a low-permeability reservoir is still unclear. In this study, casing damage due to non-uniform in-situ stress variations was investigated, and then the tectonic stress coefficients in the study area were determined by an in-situ stress inversion technique, which led to the derivation of formulas for calculating the maximum and minimum horizontal in-situ stresses. Subsequently, finite element numerical simulations were performed to assess the stress distribution during the formation of the casing cement sheath in a G155 block, a typical low-permeability reservoir. The results indicate that casing damage is caused not only by non-uniform in-situ stresses but also by various additional creep-induced loads. Subsequent finite element investigations into casing behavior under mudstone creep conditions indicated that immersion of mudstone in water instigated further shearing and deformation of the casing, culminating in premature well failure prior to water inundation. Notably, Von Mises stress levels exhibited a positive correlation with injection production ratios, with values exceeding critical thresholds leading to distinct modes of mechanical failure including shear-induced deformations, longitudinal tensile stress, and localized yielding near water wells. Maintenance of an optimal injection production ratio is identified as a key strategy for prolonging casing longevity in the region. To this end, recommendations include augmenting the casing wall thickness or enhancing the steel pressure specifications to mitigate casing damage progression, thereby extending the operational lifespan. This research serves as a pivotal theoretical framework for informing future development strategies aimed at mitigating and preempting casing failures in a low-permeability reservoir. Full article

This paper examines the theoretical foundations of electrical resistivity tomography (ERT) technology, followed by the finite element analysis method, for the positive problem and the linear back-projection (LBP) procedure for the inverse problem. The conductivity distribution image of the modeled concrete is then reconstructed, which includes one circular aggregate and the surrounding mortar. It is discovered that the conductivity obtained can be used to find the inclusive aggregate, mortar, and interfacial transition zone (ITZ). Natural aggregate and mortar have conductivities of 0.046 ms/cm and 0.115 ms/cm, respectively. Additionally, the conductivity of the ITZ, which is always regarded as the initial damage, is about 0.081 ms/cm. ERT is a cost-effective and readily available technique for determining the initial distribution of the aggregate and related ITZ. Therefore, ERT is a promising tool for determining inclusions and initial damage in concrete. Full article

This study explores the potential of using Unmanned Aircraft Vehicles (UAVs) as a measurement platform for estimating greenhouse gas (GHG) fluxes over complex terrain. We proposed and tested an inverse modeling approach for retrieving GHG fluxes based on two-level measurements of GHG concentrations and airflow properties over complex terrain with high spatial resolution. Our approach is based on a three-dimensional hydrodynamic model capable of determining the airflow parameters that affect the spatial distribution of GHG concentrations within the atmospheric boundary layer. The model is primarily designed to solve the forward problem of calculating the steady-state distribution of GHG concentrations and fluxes at different levels over an inhomogeneous land surface within the model domain. The inverse problem deals with determining the unknown surface GHG fluxes by minimizing the difference between measured and modeled GHG concentrations at two selected levels above the land surface. Several numerical experiments were conducted using surrogate data that mimicked UAV observations of varying accuracies and density of GHG concentration measurements to test the robustness of the approach. Our primary modeling target was a 6 km² forested area in the foothills of the Greater Caucasus Mountains in Russia, characterized by complex topography and mosaic vegetation. The numerical experiments show that the proposed inverse modeling approach can effectively solve the inverse problem, with the resulting flux distribution having the same spatial pattern as the required flux. However, the approach tends to overestimate the mean value of the required flux over the domain, with the maximum errors in flux estimation associated with areas of maximum steepness in the surface topography. The accuracy of flux estimates improves as the number of points and the accuracy of the concentration measurements increase. Therefore, the density of UAV measurements should be adjusted according to the complexity of the terrain to improve the accuracy of the modeling results. Full article

The mathematical analysis of viscous magnetohydrodynamics (MHD) models is of great interest in recent years. In this paper, a finite element Galerkin method is employed for the estimation of an unknown time-dependent convection coefficient and source in a 1D magnetohydrodynamics flow system. In this inverse problem, two integral observations are posed and used to transform the inverse problem to a non-classical direct problem with a non-local parabolic operator. Then, the non-classical strongly coupled parabolic system is studied in various settings. The equivalence of the inverse problem (IP) and the direct one are proven. The Galerkin procedure is analyzed to proove the existence and uniqueness of the solution. The finite element method (FEM) has been developed for the solution of the variational problem. Test examples are discussed. Full article

In this paper, an inverse problem of determining a source in a time-fractional diffusion equation is investigated. A Fourier extension scheme is used to approximate the solution to avoid the impact on smoothness caused by directly using singular system eigenfunctions for approximation. A modified implicit iteration method is proposed as a regularization technique to stabilize the solution process. The convergence rates are derived when a discrepancy principle serves as the principle for choosing the regularization parameters. Numerical tests are provided to further verify the efficacy of the proposed method. Full article

In the field of wireless strain monitoring, it is difficult for the traditional metal-made antenna sensor to conform well with steel structures and monitor large strain deformation. To solve this problem, this study proposes a flexible antenna strain sensor based on a ductile graphene film, which features a 6.7% elongation at break and flexibility due to the microscopic wrinkle structure and layered stacking structure of the graphene film. Because of the use of eccentric embedding in the feeding form, the sensor can be miniaturized and can simultaneously monitor strain in two directions. The sensing mechanism of the antenna is analyzed using a void model, and an antenna is designed based on operating frequencies of 3 GHz and 3.5 GHz. The embedding size is optimized using a Smith chart and impedance matching principle. Both the simulation and experimental results verify that the resonant frequency and strain magnitude are linearly inversely proportional. The experimental results show that the strain sensitivity is 1.752 kHz/με along the geometric length and 1.780 kHz/με along the width, with correlation coefficients of 0.99173 and 0.99295, respectively. Full article

Sea Surface Temperature (SST) is of great importance to study several major phenomena due to ocean interactions with other earth systems. Previous studies on SST based on statistical inference methods were less accurate for longer prediction lengths. A considerable number of studies in recent years involve machine learning for SST modeling. These models were able to mitigate this problem to some length by modeling SST patterns and trends. Sequence analysis by decomposition is used for SST forecasting in several studies. Ensemble Empirical Mode Decomposition (EEMD) has been proven in previous studies as a useful method for this. The application of EEMD in spatiotemporal modeling has been introduced as Multidimensional EEMD (MEEMD). The aim of this study is to employ fast MEEMD methods to decompose the SST spatiotemporal dataset and apply a Convolutional Long Short-Term Memory (ConvLSTM)-based model to model and forecast SST. The results show that the fast MEEMD method is capable of enhancing spatiotemporal SST modeling compared to the Linear Inverse Model (LIM) and ConvLSTM model without decomposition. The model was further validated by making predictions from April to May 2023 and comparing them to original SST values. There was a high consistency between predicted and real SST values. Full article

Background and Objectives: Irritable bowel syndrome (IBS) is an invasive and potentially disabling syndrome characterized by a multitude of symptoms capable of reducing the quality of life of patients. Among the most disabling symptoms of IBS is certainly physical pain, which manifests itself mainly at the abdominal level but can also appear in other areas of the body, particularly in the form of chronic low-back pain (CLBP). Among the non-invasive methods of treating organ-specific pathologies and organ-related musculoskeletal problems, the use of Bioresonance Therapy (BT)—based on the administration of self-modulating Extremely Low-Frequency Electromagnetic Fields, capable of determining a rebalance of bio-electrical and metabolic activity in the presence of various functional alterations—is currently gaining acceptance. Therefore, we decided to monitor results obtained from patients suffering from IBS and CLBP subjected to a cycle of treatments with BT. Materials and Methods: We monitored 20 patients (12 women and 8 men, average age of 51 years) suffering from CLBP and other visceral symptoms related to IBS. Patients were monitored through the use of the Bristol Stool Form Scale (BSFS), the Fecal Calprotectin test and the Short-Form Health Survey 36 (SF-36), collected before (T0) and after (T1) the execution of the cycle of treatments. They undertook a treatment protocol consisting of eight sessions of BT carried out over about a month. Results: At the end of the treatments with BT, it was possible to observe a general and significant improvement in all the parameters observed, as well as a close inversely proportional correlation between the Calprotectin values detected and the quality of life experienced by the patients in relation to their perceived IBS symptoms. Conclusions: Overall, our pilot study would seem to suggest a potential beneficial effect of BT in modulating organic and musculoskeletal symptoms derived from IBS. Full article