Boundary Tracking Research Articles

Turbulent models of shallow-water equations-based smoothed particle hydrodynamics

The depth-averaged models such as those based on the shallow water equations (SWEs) are commonly used to simulate the large-scale flows with engineering importance. The smoothed particle hydrodynamics (SPH) approach has been documented to solve the SWEs due to its mesh-free superiority in treating the free surfaces and wet-dry boundaries. However, nearly all SWE-SPH models were developed without a turbulent model, which seriously limited the model applications where the flows are complex and where the turbulent parameters are explicitly needed. For the first time, this paper includes a depth-averaged turbulent k̂-ε̂ model in the SWE-SPH solver, making the model more capable of treating the turbulent flows in the practical field. For comparison purpose, a sub-particle-scale turbulent model widely adopted in three-dimensional (3D) SPH was also included in the present SWE-SPH scheme. To evaluate the performance of the two proposed turbulent SWE-SPH models, various open channel flows of increasing complexity were simulated, and the SPH computations were compared with the reported data in the literature. Through the analysis of results for a rough riverbed, L-shaped and sudden expansion channels, it is demonstrated that the present turbulent SWE-SPH models are equipped with good robustness and accuracy in capturing the shallow water turbulent dynamics, with the potential to be used in practical river and coastal flows. In summary, there are two distinct novelties in the proposed work. First, the mesh-free numerical modeling technique SPH is used to solve the shallow water equations, which enable the model to work in large engineering field through simple and effective tracking of free surfaces and wet-dry boundaries. Second, the proposed research expands the shallow water SPH modeling technique by including robust turbulence simulation capacity. The newly developed model can address more challenging engineering scenarios such as the sediment and pollutant transports when the flow turbulence plays an important role and where the turbulent parameters are explicitly required in the relevant transport equations.

Stabilization of interconnected models with Nitsche's interface conditions using the two-grid approach: A finite element study

In this paper, a stabilized Stokes–Stokes system with Nitsche's type interface conditions is presented. These conditions are commonly employed in many multi-physical fields, including fluid–fluid interaction, fluid–structure interaction, oceanographic modeling, and atmospheric forecasting. For multi-physical domain modeling purposes, Nitsche's interface conditions provide useful benefits over classical conditions via addressing the complicated nature of fluid phase interface mathematical modeling, phase boundary tracking, interface interactions, and mass and energy transportation. It is not easy to find analytical and numerical solutions for models with these characteristics. We use more accurate interface conditions to solve the fluid–fluid interaction model to accomplish this numerically. This is achieved by including new terms at the interface and decoupling the domain through the two-grid technique, which ultimately reduces the main issue into several smaller problems. Comparing this method to existing models, we find that it is computationally feasible because it uses less memory and operates with a coarse grid instead of a fine grid and thus improves convergence rates for complex and nonlinear problems. Furthermore, it shows mesh independence, supports potential parallelization, and is crucial for advanced multigrid techniques. The optimality of the error is confirmed both theoretically and numerically. The numerical experimental section validates the model through three types of numerical experiments.

Rate-independent mechanism of deformation twinning in single crystal magnesium

The dynamics of {101‾2}〈101‾1〉 extension twins in a single crystal of pure magnesium are studied through uniaxial compression experiments coupled with direct optical imaging. The experiments covered a seven orders of magnitude strain rate, between 10−5−102s−1, covering all rates of engineering applications of magnesium and its alloys. Under uniaxial compression along a direction perpendicular to prismatic planes, only two variants of extension twins are activated, facilitating in-situ tracking of individual twin boundaries throughout the deformation process. Across the entire strain rate range, the twinning transformation evolves in a self-similar pattern of twin nucleation and thickening. Deformation fronts initiate at the edges of the sample and propagate toward the center, creating parallel twins with characteristic thicknesses and distances from each other. The velocity of the deformation fronts scales linearly with the imposed external strain rate and a nearly uniform resolved shear stress is measured over the entire strain rate range. We show that this unique process is attributed to the constant ratio between the nucleation rate and sideways velocity of individual twin boundaries, where both processes are proportional to the imposed strain rate. These findings indicate that, within the large strain rate range investigated in this study, the evolution mechanism of extension twinning is practically rate-independent.

Imaging sensor band comparison for situational awareness in wildfires

In recent decades, wildfires have become increasingly widespread and hazardous. Dryer, hotter weather combined with more frequent heat waves leave forest areas susceptible to sudden, intense, and fast-growing forest fires. To protect private property and mitigate the damage, Hotshot firefighters are deployed into these dangerous situations. Extensive satellite and aerial platforms possess optical techniques for monitoring wildfire risks and boundary tracking. Small unmanned aerial system (sUAS)-based EO/IR systems provide a solution for real-time, high resolution, targeted response to acquire information critical to the safety and efficacy of wildfire mitigation. Real-time imagery from a sUAS of the position of Hotshots and the progression of the fire boundary would be easily obtained and offer a method of ensuring safe deployment. An ideal sensor system for situational awareness in this environment would be able to image the ambient terrain and firefighters with good contrast while also detecting fire signatures and imaging through the smoke. Longer wavelength infrared bands have demonstrated imaging through the smoke of forest fires. However, near the wildfire where the Hotshots work, they also receive strong radiometric signals from the temperature of the smoke. The emitted signal of the smoke can obscure the line of sight similarly to the scattering effect of wildfire smoke in the visible spectrum. The reflective and emissive components of a wildfire scene are studied and compared in the visible (VIS, 0.4–0.7 µm), shortwave infrared (SWIR, 1.0–1.7 µm), extended SWIR (eSWIR, 2.0–2.5 µm), and longwave infrared (LWIR, 8–14 µm). Both a radiometric model and calibrated field measurements find a band that has the highest, to our knowledge, probability for a continuous line of sight for terrain, firefighters, and fire signatures in a wildfire scene.

Dynamic object detection using sparse LiDAR data for autonomous machine driving and road safety applications

Light Detection And Ranging (LiDAR) sensor offers solutions to extract real-time information of vehicle’s surroundings and can provide a new opportunity to improve the road safety related issues in mixed traffic conditions. This paper explores fundamental principles and combination of algorithms, to accurately detect, classify and track surrounding vehicles on expressways using a vehicle mounted cost-effective LiDAR sensor in dynamic conditions. The proposed approach employs algorithms such as Density-Based Spatial Clustering of Applications with Noise, Random sample consensus, and Kalman filter on 3D LiDAR data for ground and non-ground points segmentation, object clustering, road boundary identification, vehicle classification and tracking. Trajectory data of the tracked vehicles is used to estimate their relative positions and speeds. The surrounding vehicles were classified into three categories: two-wheelers, four-wheelers and heavy-vehicles. The proposed method achieves an accuracy, precision, recall, and F1-score above 94 %, demonstrating its robustness. The resilience and versatility of the proposed algorithm were validated through comprehensive evaluations on a significant dataset spanning over 8000 km (around 3.6 million frames) of driving data collected under varied environmental scenarios on expressway. Further, various applications of proposed methodology in road safety studies are discussed. The approach can extract real-time micro-level trajectory data for surrounding vehicles on expressways in any lighting condition, which is useful for researchers and can be used in connected and autonomous vehicles. It also provides valuable information for assessing surrogate safety measures and identifying road safety issues and suggesting countermeasures, including advanced and cost-effective driver assistance system applications.

Volume-of-fluid-based method for three-dimensional shape prediction during the construction of horizontal salt caverns energy storage

Construction prediction is the key for the shape control of energy storage salt caverns, which benefits with the storage capacity and long-term operational safety. However, the conventional grid discretization methods using elastic grid could not accurately tracking the three-dimensional boundary movements of salt cavern. This paper introduced a novel construction prediction model of salt cavern using a Volume-of-fluid based method. The tracking of the salt caverns’ dissolving boundary is successfully reconstructed and tracked by the fluid volume fractions (0-1) in structural grids. The model was validated by indoor experiment and field data. In the simulation of indoor experiment, the lateral expansion, which was difficult to reproduce in previous models, is successfully simulated. The volume of the simulation chamber is 392.8 ml with an error of 1.9 %. During the simulation of Volgograd horizontal cavern construction, the simulated cavern shape is close to the sonar detection, with an average error in radius about 3.6 %. And the brine-discharge concentration is consistent with the site monitoring, with an average error about 4.5 %. These results validate the capability of the proposed method in three-dimensional dynamic boundary tracking and shape prediction of salt cavern.

NON-INVASIVE ASSESSMENT OF HEMODYNAMIC FORCES AND PRESSURE-VOLUME RELATION ANALYSIS IN TWIN PREGNANCY

Objective: This aim of the study was to prospectively investigate pattern of intraventricular Hemo-Dynamic Forces (HDF) associated with Left Ventricular (LV) function and remodeling in women with uncomplicated twin pregnancy. Design and method: Prospective, cohort study. Transthoracic echocardiography was performed on 35 women (aged 35.9±4.7 years) during gestation (<14 w, T1; 14–27 w, T2; >28 w, T3), and 6–7 months after delivery (T0). LV HDF were computed from echocardiography long axis data sets using a novel technique based on endocardial boundary tracking, both in apex-base (A-B) and latero-septal (L-S) directions. HDF distribution was evaluated by L-S over A-B HDF ratio (L-S/A-B HDF ratio). Results: At T1, L-S/A-B HDF ratio was higher than in T0 (p<0.05) indicating HDF misalignment. At T2, a slight impairment of cardiac function was then recorded with a reduction of Global Longitudinal Strain (GLS) and left ventricular End-Systolic Elastance (Ees) at pressure-volume relationship analysis versus T1 (both p<0.05). Finally, at T3, when HDF misalignment and LV contractility reduction (GLS and Ees) were all restored, a rightward shift of the End Diastolic Pressure-Volume Relationship (EDPVR) with an increase of ventricular capacitance were documented. Conclusions: In twin pregnancy, HDF misalignment in the first trimester precedes the slight temporary decrease in left ventricular systolic function in the second trimester; at the third trimester a rightward shift of the EDPVR was associated with a realignment of HDF and normalization of ventricular contractility indexes. These coordinated changes that occur in the maternal heart during twin pregnancy suggests the role of HDF in cardiac remodelling.

Uniform boundary conditions on models of spherical particles through alpha shape surface tracking and Laguerre–Voronoi diagrams

This study describes the adaptation of the alpha-shape three-dimensional surface reconstruction technique to boundaries of spherical particle packings, such as those modeled using Discrete Elements. The alpha shape technique is employed to reconstruct a boundary surface for a packing as well as to assemble a Laguerre–Voronoi Diagram of the packing's boundary. The reconstructed surface can be used to track the evolution of the packing surface, while the surface diagram can be used to directly obtain the discrete force vectors that result from applying a uniform stress tensor (Static Uniform Boundary Condition), as well as the discrete velocity vectors that result from applying a uniform velocity gradient tensor (Kinematic Uniform Boundary Condition) to a model of spherical discrete particles. Doing so continuously throughout a simulation allows for the application of uniform boundary conditions on spherical discrete particles, whilst enabling precise tracking of stress and deformation tensors of the packing. An implementation of this novel approach in the Yade open-source DEM code is detailed here. The power and versatility of the real-time boundary tracking approach is demonstrated using some boundary value problem simulations on polydisperse spherical particle models.

Boundary tracking control of a structure supporting a vibrational moving-mass-carrying string with unknown prescribed tension

This paper contributes to the problem of tracking control for nonlinearly vibrating structure supporting a vibrational mass-carrying string with unknown string tension. The control scheme is constructed based on optimally designed reaching law considering actuator force limit, parametric uncertainties and Lyapunov stability conditions. The reaching law is designed through real-time detection of stability margins and analyzing actuator capabilities such that system dynamics are either driven into reaching or attraction phase in finite time. The control algorithm boasts robustness against parametric uncertainty by narrowing stability bounds and features an online string tension estimation engine based on data analysis obtained from acceleration and proximity sensors measurements. In order to provide smooth tracking, string vibration suppression is achieved by incorporating corresponding dynamical terms in construction of control algorithm. The closed-loop system is simulated alongside conventional discrete sliding mode technique, the results of which are compared and analyzed to pinpoint viable advantages.

Left ventricular remodeling in twin pregnancy, noninvasively assessed using hemodynamic forces and pressure-volume relation analysis: prospective, cohort study.

This study was designed to prospectively investigate the pattern of intraventricular hemodynamic forces (HDFs) associated with left ventricular (LV) function and remodeling in women with uncomplicated twin pregnancy. Transthoracic echocardiography was performed on 35 women (aged 35.9 ± 4.7-yr old) during gestation (T1, <14 wk; T2, 14-27 wk; T3, >28 wk) and 6-7 mo after delivery (T0). LV HDFs were computed from echocardiography long-axis data sets using a novel technique based on endocardial boundary tracking, both in apex-base (A-B) and latero-septal (L-S) directions. HDF distribution was evaluated by L-S over A-B HDF ratio (L-S:A-B HDF ratio). At T1, L-S:A-B HDF ratio was higher than in T0 (P < 0.05) indicating HDF misalignment. At T2, a slight impairment of cardiac function was then recorded with a reduction of global longitudinal strain (GLS) and left ventricular end-systolic elastance (Ees) at pressure-volume relationship analysis versus T1 (both P < 0.05). Finally, at T3, when HDF misalignment and LV contractility reduction (GLS and Ees) were all restored, a rightward shift of the end-diastolic pressure-volume relationship (EDPVR) with an increase of ventricular capacitance was documented. In twin pregnancy, HDF misalignment in the first trimester precedes the slight temporary decrease in left ventricular systolic function in the second trimester; at the third trimester, a rightward shift of the EDPVR was associated with a realignment of HDF and normalization of ventricular contractility indexes. These coordinated changes that occur in the maternal heart during twin pregnancy suggest the role of HDFs in cardiac remodeling.NEW & NOTEWORTHY These changes indicate that 1) the misalignment of hemodynamic forces (HDFs) precedes a mild reduction in systolic function in twin pregnancy and 2) the positive left ventricular (LV) response to hemodynamic stress is mainly due to an improved diastolic function with enhanced LV cavity compliance.

Image segmentation for automatic detection and detectability evaluation of thinning defects using LSM-based induction thermography

The infrared thermography (IRT) technique is a highly reliable and attractive technique that can evaluate a large area in real-time without destroying the inspection object. This study used the line scanning method (LSM)-based induction thermography (IT) technique among active IRT to detect thinning defects in S275 steel specimens. Unlike the dynamic mode, LSM was applied to perform sequence processing so that the copper coil shape was removed in the 2D thermal images processed. After image segmentation, a binary image was acquired using the Otsu algorithm. By utilizing image segmentation, the applied threshold for each defect is different when performing the Otsu algorithm. This makes it possible to compare defect detection according to the presence or absence of image Segmentation. Automatic defect detection was performed using a Boundary Tracking algorithm, and 12 defect detections were confirmed. Accuracy was evaluated through pixel calculation, and defects in A, B, and D columns showed high detection accuracy. This study presented the principle of LSM in which includes the relative movement between the IR camera and the specimen. In addition, a mechanism to increase the number of defects detected through image segmentation was presented.

Topology optimisation for robust design of large composite structures

The manufacturing of composite structures can lead to material defects. Some of these defects, due to their small size, can go undetected by current non-destructive testing techniques; especially in very large and geometrically complex components. Therefore, it is of paramount importance to design composite components to resist defects by accounting for them as early as possible. Topology optimisation is a methodology whereby complex features, such as cracks and debonds, can be accounted for in the design. Therefore, this work proposes a new approach for the design of very large composite structures. This new approach is enabled by a solid shell element formulation with boundary tracking capabilities (through the floating node and the level-set methods) and optimisation capabilities (through design sensitivity analysis of an energy release rate objective function). Furthermore, this work proposes a new algorithm and modelling workflow that has the ability to handle large multi-scale models. The proposed methodology shows advantages as the ability to track the topology explicitly, and the ability to increase defect tolerance of the design. This works shows the new methodology is capable of handling complex structures, such as a multi-scale stringer run-out model from an aircraft wing-box, while a kissing bond defect is present.

Autonomous boundary inspection of Posidonia oceanica meadows using an underwater robot

Monitoring provides important information for the planning and execution of marine environment preservation operations. Posidonia oceanica is one of the principal bioindicators in Mediterranean coastal areas and regular monitoring activities play a crucial role in its conservation. However, an efficient observation of vast areas colonised with P. oceanica is extremely challenging and it currently requires tedious and time consuming diving activities. Autonomous Underwater Vehicles (AUVs) endowed with optical sensors could represent a viable solution in carrying out visual inspection surveys. Nevertheless, AUVs are usually programmed to perform pre-defined trajectories, which are not effective for seagrass monitoring applications, as meadows may be fragmented and their contours may be irregular. This work proposes a framework based on machine learning and computer vision that enables an AUV equipped with a down-looking camera to autonomously inspect the boundary of P. oceanica meadows to obtain an initial estimate of the meadow size. The proposed boundary inspection solution is composed of three main modules: (1) an image segmentation relying on a Mask R-CNN model to recognise P. oceanica in underwater images, (2) a boundary tracking strategy that generates guidance references to track P. oceanica contours, (3) a loop closure detector fusing visual and navigation information to identify when a meadow boundary has been completely explored. The image segmentation model and the visual part of the loop closure detection module were validated on real underwater images. The overall inspection framework was tested in a realistic simulation environment, using mosaics obtained from real images to replicate the actual monitoring scenarios. The results show that the proposed solution enables the AUV to autonomously accomplish the boundary inspection task of P. oceanica meadows, therefore representing an effective tool towards the conservation and protection of marine environments.

Comparative Evaluation of the Immersed-Solid Method for Simulating the Flow Field around Hydrofoil

The wall boundary is important in computational-fluid-dynamics simulations. If extremely small leakage, changing leakage or a moving body exists in the simulation case, the difficulty in meshing and solving near-wall flow increases. The immersed-solid method, which inserts a rigid, solid body into the entire fluid domain, was a choice to solve the wall-boundary-solution problems mentioned above, without considering mesh deformation. The purpose of this paper is to verify the effectiveness of the immersed-solid method in the simulation of extremely small leakage, changing leakage or a moving body, and to provide a theoretical basis for the use of the submerged-solid method in engineering. In this study, the NACA0015 hydrofoil was used to check the hydrodynamic characteristics in using the immersed-solid method. The comparative study was conducted at the incidence angle of 8 degrees and a Reynolds number of 5.0 × 105, by using the immersed-solid and traditional no-slip-wall boundary. The results show that the flow striking and separation with pressure rise and drop can be correctly captured using an immersed-solid setup with boundary tracking. However, the accuracy of pressure and velocity field using the immersed-solid method was insufficient. The turbulence-kinetic energy was much higher around the immersed-solid foil body. Generally, the immersed-solid method can qualitatively predict the correct hydrodynamic characteristics. Its convergence ability is better, and it can save approximately 20% of CPU time, even if the grid density is 4.39 times of the traditional no-slip wall. Therefore, the immersed-solid method can be a good choice for engineering-flow cases with complex wall problems.

The imposition of nonconforming Neumann boundary condition in the material point method without boundary representation

Since its original formulation, the material point method (MPM) has been repeatedly further developed to become a powerful tool for simulating large deformation problems. However, the imposition of boundary condition in the MPM remains a challenge since most material points are not located at the boundary and regular background mesh is most commonly used. Therefore, the existing methods to impose boundary condition always require a boundary tracking or reconstruction algorithm, which is not always efficient or accurate. In the current work, a novel strategy to apply nonconforming Neumann boundary condition is proposed that does not require the exact boundary position. The original problem with a nonconforming traction boundary condition is transformed into an equivalent problem with a prescribed virtual stress field. Importantly, both the original and the transformed problems produce the exact same response within the material domain. To solve the equivalent problem, a modified governing equation without boundary representation is subsequently constructed, where the volume integral terms are computed by both particle quadrature and cell quadrature. Several numerical examples are investigated to assess the accuracy and demonstrate the capability of the proposed approach in simulating different engineering problems. These numerical examples include mesh refinement to illustrate the method’s good convergence and a 3D complex surface to illustrate the method’s capability.

A phase-field method for elastic mechanics with large deformation

Boundary tracking is a challenging numerical problem for elastic mechanics problems with large deformation. In particular, when the boundary conditions rely on the boundary shape, iteration is required between tracking boundaries and solving the elasticity equations. Stability of this iteration brings additional difficulty for designing efficient numerical methods. In this work, we introduce phase-field variables to represent different elastic domains and track the movement of boundaries. Furthermore, boundary conditions relying on the boundary shape can also be easily applied with the phase-field variables. Second-order compact finite difference schemes are used to solve the coupled system on a square-mesh staggered grid. Our numerical results show that the phase-field method can be conveniently used to solve complex elastic mechanics problems accurately.

Mapping Large Strains in Phase-Sensitive OCT: Key Role of Supra-Pixel Displacement Tracking in Incremental Strain Evaluation

Displacement tracking is an important step in realization of compression optical coherence elastography (C-OCE), especially in the context of obtaining nonlinear stress-strain dependences and subsequent evaluation of the tissue Young’s modulus. The rapidly progressing phase-sensitive C-OCE, however, enables direct measurements of only rather small interframe strains (below 1%), for which displacements are also small. Obtaining stress-strain curves for larger strains (~10% and greater) in phase-sensitive C-OCE can be made via cumulation of interframe strains and particle displacements. The resultant values of the so-found cumulative displacements may significantly exceed the pixel size, whereas measurements of the phase variations in C-OCE are usually performed by comparing the signals from the same pixel in a series of compared scans. When displacements of particles in a series of acquired scans reach supra-pixel values, simple pixel-to-pixel estimation of interframe phase variations may lead to significant errors in evaluating linear and nonlinear elastic properties of tissues. Thus, for large strains, adequate accounting for the resultant supra-pixel displacements of order of several pixels and greater is of key importance for undistorted mapping of elastic properties of heterogeneous materials, as well as for correct tracking of boundaries separating tissue regions with different elastic properties. In this paper we discuss the elastographic procedures of correct tracking of supra-pixel displacements in phase-sensitive C-OCE and give real examples demonstrating the importance of such displacement tracking for undistorted reconstruction of two-dimensional maps of linear and nonlinear elastic properties of real biological tissues .

Studying a matching method combining distance proximity and buffer constraints

Abstract In order to achieve fast matching of global navigation satellite system (GNSS) track data and vector road network data, a rough-to-fine matching method combining distance proximity and buffer constraints is studied. The GNSS track data is preprocessed: A rasterisation method is used to eliminate the low-quality track data and obtain the binary graph; then, the road centrelines are obtained by a skeleton extraction method; the thinning data is converted into line segments or closed lines starting from nodes by the boundary tracking method, which is stored in the vector form. Finally, the boundary tracking method is used to convert the thinning data into closed lines and store them in the vector form. A two-layer rough-to-fine matching strategy is applied: First, the changing state of the road arc is determined according to the rough matching strategy of road segment distance. Next, according to the buffer constraint criterion, a rectangular or circular buffer is selected to achieve precise matching of road network data. The results show that the proposed method has good matching effect, which is especially suitable for working with more GNSS track data.

Review of UAV-based autonomous search algorithms for hazardous sources

Autonomous search plays an important role in a wide range of applications, such as environmental protection, industrial monitoring, and search and rescue. Sensor platforms based on unmanned aerial vehicles (UAVs) have been regarded as one of the most efficient methods for achieving fully autonomous searching because of their superior flexibility and motility. This paper reviews existing algorithms for two important subjects, i.e., source seeking and boundary tracking, based on which their design principles are revealed. Although control-oriented and information-driven approaches are the two mainstream state-of-the-art methods for source seeking, their hybrids have been poorly studied. Regarding boundary tracking, existing solutions can be allocated into two classes: single-agent tracking and multiagent cooperative tracking. From the perspective of dual control for exploration and exploitation, this review outlines the fundamental insights into algorithm design and presents several visions for future research.

Cross-Layer Optimization for Industrial Internet of Things in Real Scene Digital Twins

The development of the Industrial Internet of Things (IIoT) and digital twins (DTs) technology brings new opportunities and challenges to all walks of life. The work aims to study the cross-layer optimization of DTs in IIoT. The specific application scenarios of hazardous gas leakage boundary tracking in the industry is explored. The work proposes an industrial hazardous gas tracking algorithm based on a parallel optimization framework, establishes a three-layer network of distributed edge computing based on IIoT, and develops a two-stage industrial hazardous gas tracking algorithm based on a state transition model. The performance of different algorithms is analyzed. The results indicate that the tracking state transition and target wake-up module can effectively track the gas boundary and reduce the network energy consumption. The task success rate of the parallel optimization algorithm exceeds 0.9 in 5 s. When the number of network nodes in the state transition algorithm is N = 600, the energy consumption is only 2.11 J. The minimum tracking error is 0.31, which is at least 1.33 lower than that of the exact conditional tracking algorithm. Therefore, the three-layer network edge computing architecture proposed here has an excellent performance in industrial gas diffusion boundary tracking.