Height Direction Research Articles

Mean wave direction and wave height in the ERA5 reanalysis dataset: Comparison with measured data in the coastal waters of India

Information on wave direction and height is an important input to the coastal engineers. The availability of measured data at every location in the ocean makes maritime operations smoother. However, the practical impossibility makes it to look for alternative datasets like ERA5 reanalysis data. In this study, we compare the significant wave height and mean wave direction in the ERA5 with the buoy-measured data available at the nearest locations in the coastal waters of India. Even though the ERA5 overestimates the measured significant wave heights at certain instances, they both are in good agreement at most of the locations. The correlation coefficient varies from 0.82 to 0.99, with the RMSE falling between 0.15 and 0.31 m. However, the ERA5 wave direction deviates significantly from the measured buoy data at certain locations due to the substantial difference between the measured and ERA5 mean direction of wind-seas. The ERA5 dataset matches the measured mean wave direction when swell dominates i.e., during the southwest monsoon for the locations in the Arabian Sea and during post-monsoon season for the locations in the western Bay of Bengal.

Adaptive-tracking laser differential confocal freeform surface measurement with high accuracy

This study introduces an adaptive-tracking method for high-precision measurement of freeform surfaces with unknown angles and normal directions. By integrating the laser differential confocal technology with the normal tracking method through a position sensitive detector (PSD), the proposed method achieves precise fixed-focus scanning over large angles. Subsequently, by establishing the zero-crossing and normal constraints, an adaptive-tracking method based on the height and normal direction of the freeform surfaces is presented to realize the adaptive-tracking measurement of freeform surface profiles. Experimental results demonstrate that the peak-to-valley (PV) (3σ) and the root-mean-square (RMS) (3σ) of surface profiles are superior to 39 nm and 13 nm, respectively. This method provides an effective approach for the high-precision and large-angle measurement of freeform surfaces without known expression equations.

Stability analysis and design methods of steel pipe piles under non-uniform corrosion

Steel pipe piles (SPPs) are commonly applied for marine platform foundations due to high bearing capacity. However, for SPPs in corrosive marine environments, the corrosion on the steel tube is severe and shows a non-uniform distribution along the height direction, resulting in the significantdecrease of the stability bearing capacity. To investigate the stability performance of SPPs in marine corrosive environments, the corroded SPPs are simplified into five-segment stepped columns, and the equilibrium differential equations are established to obtain the rotational stiffness relationship. The analytical solutions of the critical buckling loads of five-segment stepped columns under arbitrary boundary conditions are obtained by iterative methods. Besides, considering the material and geometrical nonlinearity, the finite element (FE) model of corroded SPPs is established and then verified based on existing test results. The effects of the number of segments and stiffness ratios among different segments on the bearing capacity are analysed. Furthermore, considering the interactions among different segments, the calculation methods for the stability bearing capacity of stepped columns under axial compression and combined compression-bending are proposed respectively. The comparison between calculated and FE results indicates that the proposed calculation methods have good prediction accuracy and can be available for practical engineering reference.

Growth and transition of dendrites in steel strands under different electromagnetic stirring methods

In the industrial continuous casting process, some central defects such as shrinkage cavity, porosity, segregation and crack are generated especially at the final solidification zone of steel strands because of the poor fluidity and feeding ability of molten steel in the center of strand, especially for the special steel strand. In this paper, a new type of vertical linear electromagnetic stirring (V-LEMS) was proposed to apply in the casting of Incoloy 825 alloy ingot and investigate the growth and transition of dendrites, distribution of Ti in the special steel, and compare its effect with the generally conventional industrial rotary electromagnetic stirring (R-EMS). The results shown that the growth direction of primary dendrite under R-EMS is perpendicular to the mold wall, but the primary dendrite growth under V-LEMS have present an upstream dendrite growth state. It proves that the V-LEMS can generate a longitudinal circulation convection in the height direction of ingot, which can strengthen the temperature and composition mixing of the upper and lower melts of the ingot and promote the homogenization of the overall melt temperature and composition. The radial macrosegregation of Ti under V-LEMS is slightly higher than that of R-EMS, but R-EMS tends to increase the longitudinal macrosegregation of Ti element. The longitudinal macrosegregation degree of Ti element under V-LEMS is less than that without EMS and with R-EMS. V-LEMS makes the longitudinal distribution of Ti element in Incoloy 825 alloy ingot more uniform. The research results give some beneficial suggestions for improving the central quality of special steel continuous casting billet.

PSVMLP: Point and Shifted Voxel MLP for 3D deep learning

We propose a high-performance 3D feature extraction deep learning network based on point cloud and shifted voxel, named Point and Shifted Voxel MLP (PSVMLP). The main component of PSVMLP is simple Multi-Layer Perceptron (MLP) structure. PSVMLP achieves effective extraction of multi-scale features from 3D data. Specifically, we combine point cloud and voxel-based feature extraction methods. In voxel representation learning, we propose a wide-range geometric feature extraction method based on axial shifting operations and simple MLP structure. The axial shifting operations allow shifting voxels in the depth, height, and width directions, capturing more geometric information. In point cloud representation learning, we use simple MLP structure to extract local features, and we also extract global features by combining transformer structure. By combining point cloud and voxel feature extraction methods, we obtain rich feature representations from different scales, enhancing the model’s expressive power and generalization performance. Applying our designed model to basic geometric feature learning tasks, we achieve excellent results. Despite being built primarily on a simple MLP framework, our model demonstrates remarkable performance on both shape classification and shape part segmentation tasks. Our code is available at https://github.com/hitxraz/psvmlp.

Multi-class identification of tonal contrasts in Chokri using supervised machine learning algorithms

This study examines and explores the effectiveness of various Machine Learning Algorithms (MLAs) in identifying intricate tonal contrasts in Chokri (ISO 639-3), an under-documented and endangered Tibeto-Burman language of the Sino-Tibetan language family spoken in Nagaland, India. Seven different supervised MLAs, viz., [Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Naive Bayes (NB)], and one neural network (NN)-based algorithms [Artificial Neural Network (ANN)] are implemented to explore five-way tonal contrasts in Chokri. Acoustic correlates of tonal contrasts, encompassing fundamental frequency fluctuations, viz., f0 height and f0 direction, are examined. Contrary to the prevailing notion of NN supremacy, this study underscores the impressive accuracy achieved by the RF. Additionally, it reveals that combining f0 height and directionality enhances tonal contrast recognition for female speakers, while f0 directionality alone suffices for male speakers. The findings demonstrate MLAs’ potential to attain accuracy rates of 84–87% for females and 95–97% for males, showcasing their applicability in deciphering the intricate tonal systems of Chokri. The proposed methodology can be extended to predict multi-class problems in diverse fields such as image processing, speech classification, medical diagnosis, computer vision, and social network analysis.

Improved Analytic Learned Iterative Shrinkage Thresholding Algorithm and Its Application to Tomographic Synthetic Aperture Radar Building Object Height Inversion

Tomographic Synthetic Aperture Radar (TomoSAR) building object height inversion is a sparse reconstruction problem that utilizes the data obtained from several spacecraft passes to invert the scatterer position in the height direction. In practical applications, the number of passes is often small, and the observation data are also small due to the objective conditions, so this study focuses on the inversion under the restricted observation data conditions. The Analytic Learned Iterative Shrinkage Thresholding Algorithm (ALISTA) is a kind of deep unfolding network algorithm, which is a combination of the Iterative Shrinkage Thresholding Algorithm (ISTA) and deep learning technology, and it has the advantages of both. The ALISTA is one of the representative algorithms for TomoSAR building object height inversion. However, the structure of the ALISTA algorithm is simple, which has neither the excellent connection structure of a deep learning network nor the acceleration format combined with the ISTA algorithm. Therefore, this study proposes two directions of improvement for the ALISTA algorithm: firstly, an improvement in the inter-layer connection of the network by introducing a connection similar to residual networks obtains the Extragradient Analytic Learned Iterative Shrinkage Thresholding Algorithm (EALISTA) and further proves that the EALISTA achieves linear convergence; secondly, there is an improvement in the iterative format of the intra-layer iteration of the network by introducing the Nesterov momentum acceleration, which obtains the Fast Analytic Learned Iterative Shrinkage Thresholding Algorithm (FALISTA). We first performed inversion experiments on simulated data, which verified the effectiveness of the two proposed algorithms. Then, we conducted TomoSAR building object height inversion experiments on limited measured data and used the deviation metric P to measure the robustness of the algorithms to invert under restricted observation data. The results show that both proposed algorithms have better robustness, which verifies the superior performance of the two algorithms. In addition, we further analyze how to choose the most suitable algorithms for inversion in engineering practice applications based on the results of the experiments on measured data.

Automatic height measurement of central serous chorioretinopathy lesion using a deep learning and adaptive gradient threshold based cascading strategy

Accurately quantifying the height of central serous chorioretinopathy (CSCR) lesion is of great significance for assisting ophthalmologists in diagnosing CSCR and evaluating treatment efficacy. The manual measurement results dominated by single optical coherence tomography (OCT) B-scan image in clinical practice face the dilemma of weak reference, poor reproducibility, and experience dependence. In this context, this paper constructs two schemes: Scheme Ⅰ draws on the idea of ensemble learning, namely, integrating multiple models for locating starting key point in the height direction of lesion in the inference stage, which appropriately improves the performance of a single model. Scheme Ⅱ designs an adaptive gradient threshold (AGT) technique, followed by the construction of cascading strategy, which involves preliminary location of starting key point through deep learning, and then employs AGT for precise adjustment. This strategy not only achieves effective location for starting key point, but also significantly reduces the large appetite of deep learning model for training samples. Subsequently, AGT continues to play a crucial role in locating the terminal key point in the height direction of lesion, further demonstrating its feasibility and effectiveness. Quantitative and qualitative key point location experiments in the height direction of lesion on 1152 samples, as well as the final height measurement display, consistently conveys the superiority of the constructed schemes, especially the cascading strategy, expanding another potential tool for the comprehensive analysis of CSCR.

A new tube forging process for manufacturing hollow parts with inner flange at an arbitrary location

The forging of hollow parts faces a great challenge as folding and buckling always occur during the forging process. To overcome these problems, a novel tube forging process combining upsetting and shear forging is developed to manufacture hollow parts with an inner flange at an arbitrary location. Firstly, two flow modes are introduced to analyze the deformation behavior of a hollow cylinder during internal thickening by upsetting, where the geometric limits associated with different deformation modes and the critical upsetting ratio with no folding defects are determined. The results clearly show the occurrence of a mode transition for some cylinders during the upsetting process; furthermore, the cylinder is less prone to folding in some cases due to the appearance of a third deformation zone located mid-way up the cylinder. Then, the forming mechanism of this novel process is analyzed, and its feasibility is demonstrated through finite element simulations and experiments. Results show that the flange can be moved to an arbitrary location on the inner wall in the height direction by controlling the stroke of the punch, and shear deformation can enhance the strength of the flange. Additionally, it is found that the shear depth, corner radius of the counter punch, and supporting force on the counter punch are the key parameters affecting the product quality.

Deep learning assisted fabrication of metallic components using the robotic wire arc additive manufacturing

PurposeBecause of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.Design/methodology/approachInstead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.FindingsThe mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.Originality/valueThe fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.

Finite element (FE) analysis of thermal stress in production process of multi-layer lining ladle

This paper presented the development of the thermo-mechanical coupling model and simulation analysis of a composite refractory layer ladle. The thermomechanical modeling of the ladle was carried out using the Finite Element Method (FEM), taking into account the joints between the slag line bricks as well as the contact between the composite refractory layers. The temperature and thermal stress characteristics of the overall ladle structure under different transit conditions were investigated using the finite element analysis software ANSYS. We also performed a comparative analysis on the improvement effect of thermal stresses by expansion joints of different sizes. The simulation results were validated with previous studies. The results showed that the installation of expansion joints within a suitable range did not significantly change the thermal expansion characteristics of the refractory lining, but it also reduced the thermal stress level of the lining to a large extent. A larger temperature gradient produced higher thermal stresses, and in the direction of the ladle height, the more downward the position of its maximum compressive stress was greater. Under different working conditions, compared with the axial and hoop stress, the radial stress was small in magnitude. Axial stress exhibited a greater degree of sensitivity to pressure variations than hoop stress. The developed thermodynamic model considering the full contact between the bricks and the refractory layer gave us a more complete view of the physical field laws inside the ladle.

Experimental and numerical study of the interaction between tempered glass fallout and enclosure fire dynamics

Tempered glass, as an important type of safety glazing, is extensively used in high-rise buildings. However, little is known about the fallout behavior of tempered glass in the compartment with different fire locations. Therefore, in this work, the exposed framed glass panes with the dimension of 815 × 815 × 6 mm3 were heated by a pool fire in the compartment. The fuel pans were placed at six different locations in the compartment. It was found that the fallout time of tempered glass increased with a decrease in the distance between the fuel pan and glass panes; when the fire was moved to the wall side, the fallout time of tempered glass was longer. Besides, the temperature gradient of the glass surface at the exposed area was insignificant when the fire source was at the center line of the doorway opening, while there was an evident temperature gradient of the glass surface on the height direction due to the apparent smoke layer in the upper of the compartment for near wall fire locations. In addition, CFD numerical simulations were conducted using FDS software to observe the temperature and velocity fields inside the compartment with different fire locations. It was found that when the fire was moved to the wall side, the circulation flow was formed at both the high-temperature region near the fire source and the low-temperature region on the left of the compartment.

Effects of contaminant diffusion on the fresh air inlets of a clean room workshop

In this study, a clean workshop is the subject of our research study, and computational fluid dynamics methods are applied to investigate the effect of exhaust pipe height, exhaust velocity, barrier structure, and wind direction on contaminant diffusion from the clean workshop. Results show that an increase in exhaust pipe height and exhaust velocity or a decrease in barrier height can effectively reduce the pollutant concentration at each fresh air inlet (FAI). Along the wind direction, the contaminant concentration initially increases and then decreases as distance increases. When the height of the exhaust pipe reaches 45 m, the effect of pollutants on the FAI is insignificant. When the exhaust velocity reaches 12 m/s, the effect of pollutants on the FAI weakens as the emission speed of flue gas increases. Reducing the height of the barrier to 29–31 m can effectively improve the concentration of pollutants at each FAI. Practical implications The mechanism by which the exhaust pipe height, exhaust velocity, barrier structure, and wind direction affect pollutant diffusion from a clean room workshop is systematically investigated by combining the CFD methods with an actual clean workshop as the research object, and the optimal pollutant reduction conditions are presented, thus providing scientific guidance for the construction of clean plants and the reduction of pollutant emissions.

SOME PHYSICAL AND MECHANICAL PROPERTIES OF COCONUT PALM (COCOS NUCIFERA) STEM IN HAINAN ISLAND, CHINA

The physical and mechanical properties of 40-year-old coconut stem were investigated in different radial directions and height positions. The results showed that in the radial direction, the properties of the number of vascular bundles (NVB), density, shrinkage, compressive strength parallel to the grain (CS), modulus of rupture (MOR), and modulus of elasticity (MOE) decreased continuously from the outer area to the inner area, except for the water absorption (WA) value which increased from the outer area to the inner area. The density and MOE decreased from the bottom to the top in the height direction while NVB and WA increased. The shrinkage, CS, and MOE first increased and then decreased from the bottom to the top. NVB in coconut stem affects the density and determines the main mechanical properties of CS, MOR, and MOE. The analysis of variance (two-way ANOVA) showed a significant difference in density, NVB, WA, CS, MOR, and MOE in radial direction and height position. These findings can be useful for the development of new applications for coconut stems, such as in construction, landscaping, or furniture manufacturing, as well as for improving our understanding of their structural characteristics.

Reduction of Fine Dust and Alleviation of Heat Island Effect: An Analysis of Cold Air Flow in Pohang City, South Korea

The urban heat island (UHI) effect poses a significant challenge for cities like Pohang, South Korea, which suffer from environmental pollution. Integrating a ventilation corridor into city planning can mitigate this issue. Despite wind’s potential as a resource for urban areas, its role remains under-studied in urban planning and design. To address this gap, this study analyzes the wind environment of Pohang City to identify effective strategies for reducing the UHI effect through the implementation of wind corridors, thereby enhancing the city’s thermal environment and sustainability. We used the KLAM_21 model to simulate and analyze the cold airflow. The results indicate that the land cover of Pohang, including residential and commercial areas, consists of urbanized dry areas. The wind direction over the past 10 years (2013–2022) has generally been west–southwest (247.5°). The cold air height and flow direction range expanded around the Hyeongsan River, eventually affecting the central city after 5 h. In the simulations, cold air accumulated above 30 m at specific locations near the valley’s base. After 2 h, the flow range of the cold air height increased. The green area ratio (GAR) and cold air speed positively correlated (+0.153). Thus, creating a wind-corridor forest could effectively address Pohang’s fine dust and UHI phenomena.

Microstructure evolution and mechanical properties of wire-arc-additively manufactured Al–Cu–Mg–Ag alloy

In this article, Al–Cu–Mg–Ag specimens were successfully wire-arc-additive-manufactured based on by gas metal arc process to investigate the evolution of microstructure and mechanical properties. The results showed that the grain morphology and pore size in the printed specimens varied in height direction. Under the influence of repeated thermal cycling, which affected the solid-state diffusion of the deviated elements at the grain boundaries, the distribution of the nanoscale second phase appeared significantly different in the height direction. The precipitation phase changes caused the microhardness of the printed specimens to decrease gradually from a peak of 125 HV and stabilise at around 100 HV. The changes in the printed specimens’ horizontal mechanical properties were insignificant mainly due to interlayer porosity.

Distribution of coarse aggregate and steel fibers in ultra-high performance concrete containing coarse aggregate (UHPC-CA) and their effect on the flexural performance

The addition of coarse aggregate in ultra-high performance concrete offers several benefits, including the reduction of self-shrinkage, cost reduction, and increased modulus of elasticity. However, it also affects the dispersion space of steel fibers, resulting in a combined effect that both enhances and limits their respective advantages. An image method was used to describe the dispersion of steel fibers and coarse aggregate in the specimens along their length, width and height directions, respectively. The impact of dispersion of steel fibers and coarse aggregate on bending performance was investigated by four-point bending tests using various surfaces as the bottom tensile zone. Furthermore, the damage occurrence mode and crack development process are discussed using micro-morphology and cross-sectional graphs. The results show that the combined effect of steel fibers and coarse aggregate is not conducive to dispersion in the length direction but prevents settling due to gravity during vibration. Differences in bending properties among various surfaces in the bottom tension zone was significant, but the synergy between steel fibers and coarse aggregate reduced these differences by 1.5–2.4 times. Steel fibers in ultra-high performance concrete containing coarse aggregate act as crack arrestors, resulting in ductile damage. Cracks develop partly through the coarse aggregate and partly along the interface transition zone, indicating that the addition of coarse aggregate does not compromise flexural strength.

Novel bulk triaxial residual stress mapping in an additive manufactured bridge sample by coupling energy dispersive X-ray diffraction and contour method measurements

A novel approach for determining triaxial residual stress states by coupling energy dispersive X-ray diffraction and contour method measurements is provided and validated in a Ti‐5Al‐5V‐5Mo‐3Cr additive manufactured (AM) bridge sample. Synchrotron X-ray diffraction (SXRD) can provide relatively fine spatial resolution (on the order of 10–100 µm) for mapping 3D elastic strain fields within a sample. However, for samples with dimensions larger than one or two centimeters the path length can get prohibitive as both constant wavelength and energy dispersive SXRD are based upon transmission measurements. As an example, for a plate-like sample geometry where the thickness is limited (less than a centimeter) it is trivial to measure the longitudinal and height direction elastic strain components with excellent in-plane spatial resolution (∼100 µm) and a somewhat lower through-thickness resolution (10–15 times larger) but obtaining the through thickness component is often not possible as the beam path must be parallel to one of the large dimensions of the plate. While small samples of low Z-number alloys (e.g., Ti or Al) allow determination of the three elastic strain components, this is often not the case for higher Z alloys (e.g., Fe or Ni) or large samples where some strain components can be indeterminable. To overcome these limitations, this work applies a combination of synchrotron X-ray diffraction and the contour method (a mechanical relaxation technique), to determine the triaxial stress state. This novel combination is demonstrated and validated in a relatively small additive manufactured sample where all three orthogonal strain components are accessible via X-ray diffraction for stress determination. The paper also explores methods for determining the strain-free lattice parameter, typically obtained from a small stress-free reference sample. This work shows that a small size AM sample is not stress free, producing unreliable magnitudes of strain and stress. Instead, a strain-free lattice parameter is determined using residual stress equilibrium conditions, which gives consistent strain and stress trends for both X-ray diffraction (alone) and the new diffraction-contour coupling technique. This demonstrates that the coupling technique can be confidently applied to samples to determine stress when path length (size or Z-number) prohibit determination of three orthogonal strain components via diffraction.

Impact-Aware Foot Motion Reconstruction and Ramp/Stair Detection Using One Foot-Mounted Inertial Measurement Unit.

Motion reconstruction using wearable sensors enables broad opportunities for gait analysis outside laboratory environments. Inertial Measurement Unit (IMU)-based foot trajectory reconstruction is an essential component of estimating the foot motion and user position required for any related biomechanics metrics. However, limitations remain in the reconstruction quality due to well-known sensor noise and drift issues, and in some cases, limited sensor bandwidth and range. In this work, to reduce drift in the height direction and handle the impulsive velocity error at heel strike, we enhanced the integration reconstruction with a novel kinematic model that partitions integration velocity errors into estimates of acceleration bias and heel strike vertical velocity error. Using this model, we achieve reduced height drift in reconstruction and simultaneously accomplish reliable terrain determination among level ground, ramps, and stairs. The reconstruction performance of the proposed method is compared against the widely used Error State Kalman Filter-based Pedestrian Dead Reckoning and integration-based foot-IMU motion reconstruction method with 15 trials from six subjects, including one prosthesis user. The mean height errors per stride are 0.03±0.08 cm on level ground, 0.95±0.37 cm on ramps, and 1.27±1.22 cm on stairs. The proposed method can determine the terrain types accurately by thresholding on the model output and demonstrates great reconstruction improvement in level-ground walking and moderate improvement on ramps and stairs.

CFD–DEM Simulation of Heat Transfer and Reaction Characteristics of Pyrolysis Process of MSW Heated by High-Temperature Flue Gas

Pyrolysis is a promising disposal method for municipal solid waste (MSW) due to the high-value utilization of the organic components of MSW. Traditional indirect heating has low heat transfer efficiency and requires an increase in the heat exchange area. In this study, a refined numerical simulation model for the pyrolysis of four typical MSW components with high-temperature flue gas was established to study the influence of flue gas on the heat transfer and reaction characteristics of MSW. The temperature distribution and particle size change in different components were obtained, and the effects of flue gas temperature and velocity on the pyrolysis process were analyzed. It was found that the temperature difference of the four components along the bed height direction was about 1.36–1.81 K/mm, and the energy efficiency was about 55–61%. When the four components were uniformly mixed, the temperature increase rates of each component were similar during the pyrolysis process. As the flue gas temperature increased, the amount of gas consumption decreased and the energy efficiency increased. When the flue gas velocity increased, the flue gas consumption increased and the energy efficiency decreased. The research results are of great significance for the promotion and application of pyrolysis technology to MSW with high-temperature flue gas.