Application of magneto-optical method for detection of material structure changes

The possibilities of magneto-optical sensors to control the damage of ferromagnetic and para-magnetic materials and products are considered. In the introduction it is shown that modern magneto-optical materials used in creating sensors have a high sensitivity and spatial resolution. So, on their basis it is possible to develop sensitive and informative means of non-destructive testing for a wide range of applications. For example, it is used to detect microcracks, corrosion damage, degradation changes in the material structure, surface deformations, and subsurface defects. The method ability to detect appearance of magnetic phases in paramagnetic materials, that are precursors of fracture, is of a special importance. The advantage of magneto-optic sensors is a large observation area and high spatial resolution. Resolution of the sensor is determined by the period and size of the domain structure, which averages 13...50 micrometres. High sensitivity of the sensor is due to a small saturation field of the magneto-optic material from 0.1 mT to 0.7 mT. In addition, these parameters are controlled by changing the temperature of the sensor, direction and intensity of the magnetic field. In this paper an optical scheme based on magneto-optical garnet film for visualization of fatigue cracks, which are formed in compact samples during their experimental investigation on fatigue failure is described. The developed scheme allowed us to visualize and fix position of the crack and determine its actual length, considering the closed part of the crack. A further direction of research will be to increase the sensitivity of the developed scheme and reduce the noise of magneto-optical images to identify the initial stages of the degradation process of ferromagnetic and paramagnetic materials and products.

Magnetic behavior of Magneto-Rheological Foam under Uniaxial Compression Strain

This study reports the development of a Magneto-Rheological Foam, which consists in a porous matrix filled by ferromagnetic particles. The porous matrix of such a composite being easily deformable, large magnetic properties changes are expected. The measurements of the magnetic properties of such a Magneto-Rheological Foam submitted to a compressive strain are reported. Main aspect of the magnetic properties is the low field magnetic permeability as the function of the compression and filling factor. Then, larger field magnetization measurement allowed to investigate the saturation field as a function of the filling factor. Because of the large amount of pores in the material, the magnetic relative permeability, µr, is quite small (µr ~1). However, these materials can be easily deformed over a large range of strain providing important relative variation of the magnetic properties under mechanical solicitation. The composite magnetic permeability is increasing under compression for all the considered filling factors. A model is then developed to understand the variation of the permeability with the strain. Hence, from a simple concept consisting of taking advantage of high deformation of foams, the present study demonstrates the interest of such a highly compressible while cheap composite for obtaining a large magneto-rheological effect.

Experimental and modeling investigations on the quasi-static compression properties of isotropic silicone rubber-based magnetorheological elastomers under the magnetic fields ranging from zero to saturation field

The isotropic magnetorheological elastomers (MREs) containing three different contents of carbonyl iron particles (CIPs) based on silicone rubber were prepared, and their quasi-static compression properties under various magnetic fields were characterized by a material testing machine with specialized electromagnet. The magneto-induced actuation stress at zero strain condition as well as the deformation stress during compression process of MREs were tested. According to the magnetization model and demagnetizing energy theory, a magneto-induced actuation model of isotropic MREs was proposed. Meanwhile, a magneto-hyperelastic model was established for calculating the magnetic field- and strain-dependent deformation stress of MREs via combining the Neo–Hookean model, the magnetization model, and the magnetic dipole theory. Therefore, a new constitutive model was established to describe compression properties of isotropic MREs by considering the magneto-induced actuation and the magneto-hyperelastic behaviors. Finally, the effect of CIP content and model applicability were analyzed. It is verified that the developed compression model was able to exactly predict the compression properties of isotropic MREs with various CIP contents over the magnetic field range varying from zero field to saturation field by adopting a set of unified model parameters.

Tunable gigahertz dynamics of low-temperature skyrmion lattice in a chiral magnet

Recently, it has been shown that the chiral magnetic insulator Cu2OSeO3 hosts skyrmions in two separated pockets in temperature and magnetic field phase space. It has also been shown that the predominant stabilization mechanism for the low-temperature skyrmions (LTS) phase is the crystalline anisotropy in contrast to temperature fluctuations, which stabilize the well established high-temperature skyrmion (HTS) lattice. Here, we report on the gigahertz dynamics in the LTS phase in Cu2OSeO3. The LTS phase is populated via a field cycling protocol with the static magnetic field applied parallel to the h100i crystalline direction of plate and cuboid-shaped bulk crystals. By analyzing temperature-dependent broadband spectroscopy data, clear evidence of low-temperature skyrmion excitations with clockwise (CW), counterclockwise (CCW), and breathing mode (BR) character at temperatures below T = 40 K are shown. We find that the modes’ intensities can be tuned with the number of field-cycles below the saturation field, and by tracking the resonance frequencies, the LTS phase diagram can be established. From our experiments, we conclude that the LTS phase is well separated from the high-temperature phase. Furthermore, by monitoring the strength of the observed hybridization between a dark CW mode and the BR as a function of temperature for the two differently shaped crystals, we unambiguously conclude that the magnetocrystalline anisotropy governs the hybridization.

The Study of Magnetoimpedance Effect for Magnetoelectric Laminate Composites with Different Magnetostrictive Layers

The rectangular magnetoelectric (ME) composites of Metglas/PZT and Terfenol-D/PZT are prepared, and the effects of a magnetostrictive layer’s material characteristics on the magnetoimpedance of ME composite are discussed and experimentally investigated. The theoretical analyses show that the impedance is not only dependent on Young’s modulus and the magnetostrictive strain of magnetostrictive material but is also influenced by its relative permeability. Compared with Terfenol-D, Metglas possesses significantly higher magnetic permeability and larger magnetostrictive strain at quite low Hdc due to the small saturation field, resulting in the larger magnetoimpedance ratio. The experimental results demonstrate that the maximum magnetoimpedance ratios (i.e., ΔZ/Z) of Metglas/PZT composite are about 605.24% and 239.98% at the antiresonance and resonance, respectively. Specifically, the maximum ΔZ/Z of Metglas/PZT is 8.6 times as high as that of Terfenol-D/PZT at the antiresonance. Such results provide the fundamental guidance in the design and fabrication of novel multifunction devices based on the magnetoimpedance effect of ME composites.

Magnetostatic reciprocity for MR magnet design

Electromagnetic reciprocity has long been a staple in magnetic resonance (MR) radio-frequency development, offering geometrical insights and a figure of merit for various resonator designs. In a similar manner, we use magnetostatic reciprocity to compute manufacturable solutions of complex magnet geometries, by establishing a quantitative metric for the placement and subsequent orientation of discrete pieces of permanent magnetic material. Based on magnetostatic theory and non-linear finite element modelling (FEM) simulations, it is shown how assembled permanent magnet setups perform in the embodiment of a variety of designs and how magnetostatic reciprocity is leveraged in the presence of difficulties associated with self-interactions, to fulfil various design objectives, including self-assembled micro-magnets, adjustable magnetic arrays, and an unbounded magnetic field intensity in a small volume, despite realistic saturation field strengths.

Physical Simulation Experimental Technology and Mechanism of Water Invasion in Fractured-Porous Gas Reservoir: A Review

In the development process for a fractured-porous gas reservoir with developed fracture and active water, edge water or bottom water easily bursts rapidly along the fracture to the production well, and the reservoir matrix will absorb water, reducing the gas percolation channel and increasing the gas phase percolation resistance of the reservoir matrix, therefor reducing the stable production capacity and recovery efficiency of the gas reservoir. For this reason, this paper investigates physical simulation experimental technology and mechanisms as reported by both domestic and foreign scholars regarding water invasion in fractured-porous gas reservoirs. In this paper, it is considered that the future trend and focus of water invasion experiments will be to establish a more realistic three-dimensional physical model on the basis of fine geological description, combined with gas reservoir well pattern deployment and production characteristics, and to fully consider the difference between horizontal and vertical water invasion along the reservoir side; at the same time, dynamic parameters such as model pressure field and water saturation field can be obtained in real time. Based on this understanding of the water invasion mechanism of fractured-porous gas reservoirs, we propose the next research direction and the development countermeasures such as water controls, drainage, and dissolved water seals and water locks to combat water invasion in reservoirs, along with the injection of gas to replenish formation energy, etc., so as to slow down and control the influence of water invasion.

Magnetostatic reciprocity for MR magnet design

Electromagnetic reciprocity has long been a staple in MR radio-frequency development, offering geometrical insights and a figure of merit for various resonator designs. In a similar manner, we use magnetostatic reciprocity to compute manufacturable solutions of complex magnet geometries, by establishing a quantitative metric for the placement and subsequent orientation of discrete pieces of permanent magnetic material. Based on magnetostatic theory and nonlinear FEM simulations, it is shown how assembled permanent magnet setups perform in the embodiment of a variety of designs, and how magnetostatic reciprocity is leveraged in the presence of difficulties associated with self-interactions, to fulfil various design objectives, including self-assembled micro magnets, adjustable magnetic arrays, and an unbounded magnetic field intensity in a small volume, despite realistic saturation field strengths.

Well Control Optimization of Waterflooding Oilfield Based on Deep Neural Network

A well control optimization method is a key technology to adjust the flow direction of waterflooding and improve the effect of oilfield development. The existing well control optimization method is mainly based on optimization algorithms and numerical simulators. In the face of larger models, longer optimization periods, or reservoir models with a large number of optimized wells, there are many optimization variables, which will cause algorithm convergence difficulties and optimization costs. The application effect is not good because of the problems of time length, few comparison schemes, and only fixed control frequency. This paper proposes a new method of a well control optimization method based on a multi-input deep neural network. This method takes the production history data of the reservoir as the main input and the saturation field as the auxiliary input and establishes a multi-input deep neural network for learning, forming a production dynamic prediction model instead of conventional numerical simulators. Based on the production dynamic prediction model, a series of model generation, production prediction, comparison, and optimization are carried out to find the best production plan of the reservoir. The calculation results of the examples show that (1) compared with the single-input production dynamic prediction model, the production dynamic prediction model based on multiple inputs has better prediction accuracy, and the results are close to the calculation results of the conventional numerical simulator; (2) the well control optimization method based on the multiple-input deep neural network has a fast optimization speed, with many comparison schemes and good optimization effect.