Estimation Of Penetration Depth Research Articles

MI-Sensor Element Features and Estimation of Penetration Depth and Magnetic Permeability by Magnetoresistance and Magnetoreactance of CoFeSiB Amorphous Wires

The magnetoimpedance (MI) of amorphous soft magnetic Co <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68.15</sub> Fe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4.35</sub> Si <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">12.5</sub> B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">15</sub> wires produced by the in-rotating water quenching technique was systematically studied. The behavior of the MI-element designed for magnetic sensors was examined in an external longitudinal dc magnetic field in the low-frequency range (f ≤ 1 MHz) and at the beginning of the intermediate frequency range (2 MHz ≤ f ≤ 5 MHz). A critical frequency of about 5 kHz - 7 kHz was observed with an initial increase in the MI effect. A maximum MI ratio of 334% was recorded at 0.95 MHz in a magnetically saturated MI-element. The intermediate frequency range is explored using the magnetoresistive - MR and magnetoreactive - MX components of magnetoimpedance Z. The MI anisotropy field profile occurs in the MHz operating frequency range with values increasing up to 25 A/m, exhibiting frequency dependence. The magnetic penetration depth was calculated using experimental magnetoresistance data, and the values obtained were about 3 μm - 4 μm for 5 MHz, showing a saturation trend. The magnetic permeability is analyzed in the framework of the electromagnetic classical high-limit model of a cylinder, which includes penetration depth and magnetoreactance. In our experiments and calculations, the classical high limit is satisfied in the operating frequency range of a few MHz. The magnetic permeability peak value is about 35% lower than the comparable data of amorphous CoFeNiMoSiB glass-coated microwires.

Weld-penetration-depth estimation using deep learning models and multisensor signals in Al/Cu laser overlap welding

Al/Cu laser-welded overlap joints, in which weld-penetration depth significantly influences both joint strength and electrical conductivity, are widely applied in automotive battery cells. In this study, a unisensor convolutional neural network (CNN) model that predicts penetration depth using coaxial weld-pool images as input and multisensor CNN models that utilize additional photodiode signals are proposed. The penetration depth was estimated using an optical coherence tomography sensor. The coefficient of determination values for the unisensor and multisensor CNN models were between 0.982 and 0.985, and their mean absolute errors were between 0.0278 and 0.0302 mm. The short-term Fourier transform multisensor model presented the best performance in terms of prediction of penetration depth when applied to the photodiode signal. The proposed prediction models were validated using a gradually varying laser power experiment, which demonstrated the efficacy of this approach and its potential use in automotive applications. Keywords: Laser welding, Al/Cu overlap joint, Penetration-depth estimation, Image sensor, Photodiode, CNN, Deep learning.

Remote Sensing of Complex Permittivity and Penetration Depth of Soils Using P-Band SAR Polarimetry

A P-band SAR moisture estimation method is introduced for complex soil permittivity and penetration depth estimation using fully polarimetric P-band SAR signals. This method combines eigen- and model-based decomposition techniques for separation of the total backscattering signal into three scattering components (soil, dihedral, and volume). The incorporation of a soil scattering model allows for the first time the estimation of complex soil permittivity and permittivity-based penetration depth. The proposed method needs no prior assumptions on land cover characteristics and is applicable to a variety of vegetation types. The technique is demonstrated for airborne P-band SAR measurements acquired during the AirMOSS campaign (2012–2015). The estimated complex permittivity agrees well with climate and soil conditions at different monitoring sites. Based on frequency and permittivity, P-band penetration depths vary from 5 cm to 35 cm. This value range is in accordance with previous studies in the literature. Comparison of the results is challenging due to the sparsity of vertical soil in situ sampling. It was found that the disagreement between in situ measurements and SAR-based estimates originates from the discrepancy between the in situ measuring depth of the top-soil layer (0–5 cm) and the median penetration depth of the P-band waves (24.5–27 cm).

The role of granular buoyant force of projectile in determining the penetration depth

This research develops a new formulation for final penetration depth of projectile on granular material. Although several relevant researches exist to estimate final penetration depths of blunt projectiles, estimation of final penetration depth of sharp projectiles is still difficult. Direct application of the formulation of blunt projectile cannot be applicable for sharp projectile. It is possible to employ heuristic and empirical formulations to predict the penetration depth of projectiles. Through several experimental studies, this research, however, finds out that buoyant force of sharp projectiles can be included in the existing formula for the final penetration depth of blunt projectiles. In order to verify the hypothesis, first of all several experiments with cylinder and ball were carried out to validate the existing theory. After sharp projectiles are experimented, the effect of the buoyant force is formulated as initial penetration depth. By adding this initial penetration depth determined by balancing between the buoyant force and weight, it is possible to adjust the existing formula for sharp projectiles. To show the validity of the present formulation, several cone shape projectiles are modeled and tested.

Errata for “Autofocus-Based Estimation of Penetration Depth and Permittivity of Ice Volumes and Snow Using Single SAR Images”

In the above article <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , references [21] and [29] incorrectly provide the publication years. Reference [21] was published in 2020; reference [29] was published in 2021. The references appear in full here:

Autofocus-Based Estimation of Penetration Depth and Permittivity of Ice Volumes and Snow Using Single SAR Images

An intrinsic challenge in the geophysical interpretation of low-frequency synthetic aperture radar (SAR) imagery of semitransparent media, such as ice sheets, is the position ambiguity of the scattering structures within the glacial volume. Commonly tackled by applying interferometric and tomographic techniques, their spaceborne implementation exhibits by orders higher complexity compared to missions relying on single SAR images, making them cost expensive or, in the context of planetary missions, even impossible due to limited navigation capability. Besides, even these sophisticated techniques are commonly biased due to inaccurate permittivity estimates, leading to geometric distortions up to several meters. We present a novel inversion procedure to estimate volume parameters of ice sheets, namely, the depth of the scattering layer within the glacial volume and the dielectric permittivity of the ice, based on single-image single-polarization SAR acquisitions. The information is inherent in the processed SAR data as phase errors on the azimuth signals resulting from uncompensated nonlinear propagation of the radar echoes through ice. We suggest a local map-drift autofocus approach to quantify and spatially resolve the phase errors and an inversion model to relate them to the penetration depth and permittivity. Testing the proposed technique using P-band SAR data acquired using DLR’s airborne sensor F-SAR during the ARCTIC15 campaign in Greenland shows promising results and good agreement with tomographic products of the analyzed test site.

A calibration tool for weld penetration depth estimation based on dimensional and thermal sensor fusion

A calibration tool for weld penetration depth estimation based on dimensional and thermal sensor fusion

Modeling of weld penetration control system in GMAW-P using NARMAX methods

Abstract This study introduces the nonlinear identification of a weld penetration control system in pulsed gas metal arc welding system (GMAW-P) characterized with the fused characteristic signal. It was found that both the change in arc voltage during the peak current period and the average arc voltage during the peak current period can be used for condition monitoring of weld pool surface and thus for the estimation of weld penetration depth in GMAW-P. By fusing these two signals through a Kalman filter, filtered fluctuation of arc voltage during peak current period, Δ U k f , is proposed to estimate weld penetration more reasonably. A second order NARMAX (nonlinear autoregressive moving average model with exogenous inputs) model is identified thorough forward regression orthogonal least squares (FROLS) algorithm and the error reduction ratio (ERR) criterion, and then validated in statistical validation. After simplification, the obtained model structure is a bilinear model, and is proved to be superior than linear models thorough model prediction tests. The proposed bilinear model is used to design a gain-scheduled model predictive controller, which shows the ability in weld penetration control in an experiment with a set point change.

Resistance of cement-based materials against high-velocity small caliber deformable projectile impact

This paper presents an experimental study on the resistance of cement-based materials across a wide range of compositions and material properties, against the impact of 8.0-mm-diameter, 7.8-g-mass, conical-nosed deformable ASSAB XW-42 steel and copper projectiles at velocities of approximately 400 m/s, in terms of the penetration depth. The cement-based materials investigated include cement pastes, mortars, concretes, engineered cementitious composites (ECCs), and ultra-high performance concretes (UHPCs) with compressive strengths from 37.9 to 229.4 MPa and elastic moduli from 18.7 to 108.8 GPa. For the range of relative characteristic properties between projectile and target considered, the relative effective hardness index (REH) is shown to provide a good characterization of the penetration depth as well as the projectile deformation including relative length change, diameter change, and mass loss. For the deformable penetration regime investigated, two sub-regimes are identified corresponding to a decreasing REH, i.e. regime I with projectile penetration mechanism and regime II with projectile deformation mechanism. It is also found that UHPCs exhibit better impact resistance against deformable projectiles than high performance concretes (HPCs) with granite coarse aggregate, whereas a reversed trend is observed when non-deformable projectiles are considered. The experimental results of this study provide insights into the quick estimation of penetration depth and guidance on the selection of protective materials for practical engineering applications.

Application of sorptivity–diffusivity relationship for the refinement of hydraulic diffusivity function parameters obtained through inverse analysis

The modelling of water absorption in porous building materials is critical to the rational assessment of their performance during service. The non-linear diffusion equation has been extensively used to describe the phenomena with a two-parameter, moisture–dependent hydraulic diffusivity function, $$ D(\theta_{n} ) $$ , as the transport parameter. For a given material, the parameters of $$ D(\theta_{n} ) $$ are often fitted through inverse modelling, which requires the non-destructive measurement of moisture profiles with expensive equipment. An alternative to this approach, is to use a sorptivity–diffusivity model which quantifies the parameters of $$ D(\theta_{n} ) $$ on the basis of sorptivity determined through simple gravimetric measurements made in the course of a water-absorption test. However, the latter approach requires assuming the value of one of the two parameters to quantify the other. The objective of this paper is to demonstrate a novel combination of the two methods for obtaining refined estimates of parameters in $$ D(\theta_{n} ) $$ . The idea has been demonstrated by considering the instances of OPC–lime–sand mortar, fired clay brick, Lepine stone and sand specimen for which the moisture intrusion profiles and $$ D(\theta_{n} ) $$ modelled through inverse analysis have been reported previously by independent researchers. Analysis reveals that, the sorptivity–diffusivity model when used as a refinement tool for the parameters of $$ D(\theta_{n} ) $$ fitted through inverse analysis leads to improvements of up to about 12% and 5% in the estimation of moisture content and penetration depth respectively.

Control of weld penetration depth using relative fluctuation coefficient as feedback

The monitoring and control of weld penetration in pulsed gas metal arc welding (GMAW-P) is considerably challenging, especially in field applications. The metal transfer and pulse current in GMAW-P complicate the identification of weld penetration. In previous studies, the authors found that both the change in arc voltage during the peak current period and the average arc voltage during the peak current period can be used for condition monitoring of weld pool surface and thus for the estimation of GMAW-P penetration depth. In the present work, the relative fluctuation coefficient (CRF) of weld pool surface is proposed by combining these two signals to predict the weld penetration depth. Model predictive control using this coefficient as feedback is employed to control the penetration depth. The experimental results show that uniform weld penetration depth can be obtained by the adaptive control algorithm. The practice attempted in this work can be expected to be a candidate solution for GMAW-P penetration control, which is easy to implement in field applications.

Effects of deep geological environments for nuclear waste disposal on the hydrogen entry into titanium

Abstract The surface of nuclear waste container will be completely wetted by the groundwater infiltrating through the bentonite or concrete buffer after the closure of its deep geological disposal. Because of its excellent corrosion resistance, titanium is one of the candidates for the container materials for high-level nuclear waste (HLNW) disposal. However, once oxygen depleted in the large time scale deep geological disposal, titanium container will suffer from hydrogen embrittlement (HE). Therefore, in order to predict the potential danger of the HLNW container caused by HE, the hydrogen entry into titanium was studied at different temperatures in simulated deep geological environment of Beishan, which is the preselected HLNW disposal area in China. Devanathan-Stachurski cell methods were firstly implemented in measuring apparent hydrogen diffusivity in titanium with hydrides being formed during hydrogen charging at low temperature ranges (298–373 K). Given the characteristic of the Devanathan-Stachurski cell method's capable of getting apparent diffusivity with combined influencing factors easily, the technique provides a simple way to measure the parameter that is necessary for the estimation of hydrogen penetration depth, facilitating the design of HLNW containers.

Introducing Fiji and ICY image processing techniques in ichnological research as a tool for sedimentary basin analysis

In recent years, image treatment has been appraised as a very powerful tool to facilitate ichnological analysis, especially in marine cores of modern sediments, supporting the determination of certain ichnological features. However, it is still a new approach and detailed research is necessary to encounter a faster and more efficient method. The present study focuses on two image processing techniques, Fiji and ICY, and their comparison with a refined version of the well-established high-resolution image treatment. Strengths and weaknesses of the methodologies for the determination of three main features were explored: i) visibility of trace fossils; ii) quantification of the percentage of bioturbated surface, and iii) penetration depth estimation. Refined high-resolution image treatment gives the best results for enhanced visibility of trace fossils, whereas Fiji is found to be a sound and rapid option. One disadvantage shared by Fiji and ICY is the binary character of the produced images, which may impede later ichnotaxonomical differentiation. Both Fiji and ICY (+ Fiji) are rapid alternatives for quantifying the bulk amount of bioturbated surface. The Magic Wand Method (+ RefineEdge), based on high-resolution image treatment, provides good results regardless of the contrast of the images, and it additionally allows for a more detailed quantification. The semi-automatic character of ICY favors quick estimation of penetration depth and facilitates differentiation between distinct tracemaker communities, based on a rapid quantification of pixel values. Thus, Fiji and ICY methods offer good results and are much less time-consuming than high-resolution image treatment. They are proposed as faster alternatives for the estimation of ichnological features, especially useful at the beginning stages of research, when a large number of samples must be analyzed.

Canopy penetration depth estimation with TanDEM-X and its compensation in temperate forests

The potential of X-band interferometric synthetic aperture radar (InSAR) heights (e.g. from the TanDEM-X mission) for vegetation canopy height estimation has long been recognized. However, the penetration of the X-band into the canopy results in a height bias and substantially affects this estimation. The aim of the study was to apply a physical model to compensate the penetration depth (i.e. height bias) in canopy height estimation and evaluate its performance. We applied a penetration depth model on different TanDEM-X data in three German forests. This model is based on the volume coherence and imaging geometry of the InSAR acquisitions. We extracted the volume coherence from the TanDEM-X data and retrieved the height bias based on the penetration depth compared to actual surface heights. The modeled height bias was used to compensate the height bias in InSAR heights. The corrected TanDEM-X heights were evaluated with LiDAR data. In general, the penetration depth compensation in the InSAR heights improved the performance compared to the original InSAR heights resulting in elevations with a lower root mean squared error and the mean error decreased to less than 1 m with the LiDAR heights used as reference. This suggested that the height bias was accurately modeled for temperate forests, which can be of high relevance when InSAR heights are used for canopy height estimation or used in multi-temporal analysis such as forest growth, degradation and deforestation monitoring.

Estimation of Penetration Depth from Soil Effective Temperature in Microwave Radiometry

Soil moisture is an essential variable in Earth surface modeling. Two dedicated satellite missions, the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP), are currently in operation to map the global distribution of soil moisture. However, at the longer L-band wavelength of these satellites, the emitting behavior of the land becomes very complex due to the unknown deeper penetration depth. This complexity leads to more uncertainty in calibration and validation of satellite soil moisture product and their applications. In the framework of zeroth-order incoherent microwave radiative transfer model, the soil effective temperature is the only component that contains depth information and thus provides the necessary link to quantify the penetration depth. By means of the multi-layer soil effective temperature (Lv’s T e f f ) scheme, we have determined the relationship between the penetration depth and soil effective temperature and verified it against field observations at the Maqu Network. The key findings are that the penetration depth can be estimated according to Lv’s T e f f scheme with the assumption of linear soil temperature gradient along the optical depth; and conversely, the soil temperature at the penetration depth should be equal to the soil effective temperature with the same linear assumption. The accuracy of this inference depends on to what extent the assumption of linear soil temperature gradient is satisfied. The result of this study is expected to advance understanding of the soil moisture products retrieved by SMOS and SMAP and improve the techniques in data assimilation and climate research.

Distinct element method analysis of jointed rock fragmentation induced by TBM cutting

The mechanism of rock breaking and optimal design of the cutters are especially significant in tunnel excavation by Tunnel Boring Machine (TBM). In order to investigate the jointed rock fragmentation induced by TBM cutting, and to improve the capability and efficiency in rock breaking, a series models of jointed rock cutting were simulated by the Distinct Element Method, where an improved zero-thickness bond contact model was implanted to capture the main mechanical behaviour of the hard and brittle rocks. The fragmentation of intact and jointed rock induced by TBM cutting with double cutters was simulated to investigate the influence of jointed angle, spacing and cutter penetration depth on the rock breaking. The main results show that: the process of intact rock or jointed rock fragmentation can be divided into loading stage, unloading stage and residual leaping broken stage and the existence of the joint will make unloading phase in advance; the failure modes for jointed rock breaking can be classified into four types: joint-prevent failure mode, joint-propagation failure mode, joint-tendency failure mode and joint-initiation failure mode; the optimum cutter spacing can be found in the process of jointed rock fragmentation. The result will be useful in the optimisation design of cutters and estimation of penetration depth.

Laboratory air‐entraining breaking waves: Imaging visible foam signatures to estimate energy dissipation

AbstractOceanic air‐entraining breaking waves fundamentally influence weather and climate through bubble‐mediated ocean‐atmosphere exchanges, and influence marine engineering design by impacting statistics of wave heights, crest heights, and wave loading. However, estimating individual breaking wave energy dissipation in the field remains a fundamental problem. Using laboratory experiments, we introduce a new method to estimate energy dissipation by individual breaking waves using above‐water images of evolving foam. The data show the volume of the breaking wave two‐phase flow integrated in time during active breaking scales linearly with wave energy dissipated. To determine the volume time‐integral, above‐water images of surface foam provide the breaking wave timescale and horizontal extent of the submerged bubble plume, and the foam decay time provides an estimate of the bubble plume penetration depth. We anticipate that this novel remote sensing method will improve predictions of air‐sea exchanges, validate models of wave energy dissipation, and inform ocean engineering design.

Evaluation of vibrational spectroscopic techniques for consolidants’ penetration depth determination

Abstract The penetration depth of consolidants applied to cultural heritage objects plays a crucial role in a successful conservation and protection of them. In the frame of HEROMAT FP7 project new consolidants for carbonate and silicate based materials were developed. Among many other investigated properties, the penetration depth was defined by Raman and FTIR spectroscopies, for which their ability was also evaluated. Due to the formation of calcium carbonate in the consolidation process of carbonate forming consolidants, the addition of sodium nitroprusside indicator supported Raman differentiation of treated and non-treated areas in the calcium carbonate based substrate. Furthermore, the combination of the indicator reaction and Raman results gave much more precise penetration depth estimation than the visual assessment alone. For following the penetration depth of modified TEOS based consolidants for silicate based substrates, FTIR spectroscopy turned out to be very successful without any indicator application or pre-treatment of samples. Furthermore, the penetration depth related to different application methods, such as brush, cellulose pulp, airless spray and roller, was also studied. The deepest penetration was achieved by 8 h of application of consolidants in cellulose pulp, while in comparing one application by roller, airless spray and brush within the same substrate, the deepest penetration can be achieved by brush.

Using microwave near-field reflection measurements as a non-destructive test to determine water penetration depth of concrete

A non-destructive version of a standard test for concrete permeability has been demonstrated. The method is based on water penetration depth estimation from near-field microwave measurements using an open-ended rectangular waveguide. In particular, water penetration is determined from the differential measurement of reflection coefficient in the S-band before and after injection of water under pressure. Experimental results show a good correlation between the standard destructive test and the new method. Microwave measurements simplify the standard test avoiding the need of drilling out a sample from the structure and thus reducing both the cost and time needed in the analysis.

Neural Network Approach for Estimation of Penetration Depth in Concrete Targets by Ogive-nose Steel Projectiles

Despite the availability of large number of empirical and semi-empirical models, the problem of penetration depth prediction for concrete targets has remained inconclusive partly due to the complexity of the phenomenon involved and partly because of the limitations of the statistical regression employed. Conventional statistical analysis is now being replaced in many fields by the alternative approach of neural networks. Neural networks have advantages over statistical models like their data-driven nature, model-free form of predictions, and tolerance to data errors. The objective of this study is to reanalyze the data for the prediction of penetration depth by employing the technique of neural networks with a view towards seeing if better predictions are possible. The data used in the analysis pertains to the ogive-nose steel projectiles on concrete targets and the neural network models result in very low errors and high correlation coefficients as compared to the regression based models.