Discontinuous Regions Research Articles

Hydrogen embrittlement in dissimilar welded joints interfaces – Influence of manufacturing parameters and evaluation of methodologies

The resistance of dissimilar joints to hydrogen was assessed using fracture toughness in an aggressive environment and slow strain rate tests. Six weld joint conditions were evaluated. To determine the distribution of microconstituents and elements along the interfaces, techniques such as optical and scanning electron microscopy, tomography, and nano hardness were employed. The results demonstrated that the susceptibility to hydrogen embrittlement is directly linked to the fraction of discontinuous regions present along the dissimilar interface. Additionally, a critical evaluation of the methodology concerning the positioning of stress concentration at the dissimilar interface was carried out, and alternative approaches were presented.

Characteristics of Microbial Abundance in Rhizosphere and Non-Rhizosphere Soils of Permafrost Peatland, Northeast China

The rhizosphere microenvironment is crucial to plant–soil physiological processes. The differences among microbial communities in the rhizosphere and non-rhizosphere peatland topsoil (0–15 cm) and subsoil (15–30 cm) in five plant communities dominated by Carex schmidtii, Chamaedaphne calyculata, Ledum palustre, Betula fruticosa, and Vaccinium uliginosum, as well as non-rhizosphere soil in discontinuous and continuous permafrost regions, were studied. We found that the bacteria and nifH gene abundances in the C. calyculata rhizosphere soil in the discontinuous permafrost region were higher than those in continuous permafrost region, while the nirK and nifH gene abundances in the non-rhizosphere soil of the discontinuous permafrost region were lower than those in the continuous permafrost region. The ratio of bacteria to fungi decreased and that of nirK to nirS increased significantly from the discontinuous to the continuous permafrost region, indicating that permafrost degradation can change soil microbial community composition. Fungal abundance was higher in the rhizosphere than the non-rhizosphere soils, suggesting that plant roots provide a more suitable environment for fungi. Moreover, the abundances of the topsoil bacteria; the fungi; and the nirK, nirS, and nifH genes were higher than those in the subsoil because of the organic matter from plant litter as a source of nutrients. The microbial abundance in the subsoil was also more affected by nutrient availability. To sum up, the microbial abundance varied among the different types of rhizosphere and non-rhizosphere soils, and the carbon and nitrogen cycling processes mediated by soil microorganisms may be greatly altered due to permafrost degradation under climate warming.

Genomic Complexity and Complex Chromosomal Rearrangements in Genetic Diagnosis: Two Illustrative Cases on Chromosome 7.

Complex chromosomal rearrangements are rare events compatible with survival, consisting of an imbalance and/or position effect of one or more genes, that contribute to a range of clinical presentations. The investigation and diagnosis of these cases are often difficult. The interpretation of the pattern of pairing and segregation of these chromosomes during meiosis is important for the assessment of the risk and the type of imbalance in the offspring. Here, we investigated two unrelated pediatric carriers of complex rearrangements of chromosome 7. The first case was a 2-year-old girl with a severe phenotype. Conventional cytogenetics evidenced a duplication of part of the short arm of chromosome 7. By array-CGH analysis, we found a complex rearrangement with three discontinuous trisomy regions (7p22.1p21.3, 7p21.3, and 7p21.3p15.3). The second case was a newborn investigated for hypodevelopment and dimorphisms. The karyotype analysis promptly revealed a structurally altered chromosome 7. The array-CGH analysis identified an even more complex rearrangement consisting of a trisomic region at 7q11.23q22 and a tetrasomic region of 4.5 Mb spanning 7q21.3 to q22.1. The mother's karyotype examination revealed a complex rearrangement of chromosome 7: the 7q11.23q22 region was inserted in the short arm at 7p15.3. Finally, array-CGH analysis showed a trisomic region that corresponds to the tetrasomic region of the son. Our work proved that the integration of several technical solutions is often required to appropriately analyze complex chromosomal rearrangements in order to understand their implications and offer appropriate genetic counseling.

Estimation of snow bulk density and snow water equivalent on the Tibetan Plateau using snow cover duration and snow depth

Study regionTibetan Plateau (TP), China. Study focusSnow water equivalent (SWE) measurements is few compared with snow depth (SD) but combining with snow bulk density (SBD) can convert SD to SWE. No robust model has been established to estimate SBD and SWE for the TP. In this study, we aims to develop a model capable of obtaining SBD and SWE on the TP based on a significant dataset of simultaneously measured SD and SWE over nearly four decades. New hydrological insights for the regionWe found unique seasonal characteristics and elevation differences in the SBD on the TP. The newly introduced factor snow cover duration (SCD) can reflect the beginning and status of each snowfall-snowmelt cycle in this type of discontinuous snow region. The developed artificial neural network (ANN) model based on two-factor of SCD and SD can capture these unique characteristics, with minimal errors and the best performance in simulating SBD and then estimating SWE on the TP. Our method improves the underestimation of the widely used regional average density during the heavy snow period, enables a reasonable conversion of the large amount of historical and growing SDs into critical SWEs, and thus improves our ability to assess snow water resources on the TP.

High-fidelity simulation of blade vortex interaction of helicopter rotor based upon TENO scheme

Numerical simulation methods for unsteady vortex field of helicopter rotor with high resolution and low dissipation TENO8-AA primitive variables reconstruction schemes are established based on moving-embedded grid and Navier-Stokes equations. Firstly, the Targeted Essentially Non-Oscillatory (TENO) scheme are developed by employing ENO-like candidate stencil selection strategy, and the candidate stencil is adopted with optimal weight in smooth region while it is discarded completely in discontinuous region, which reduces the dissipation and dispersion errors and approaches better spectral properties. Then, the aerodynamic characteristics of Helishape-7A model rotor in Blade Vortex Interaction (BVI) state and the flowfield of Lynx rotor in hover are simulated, which validates that the blade tip vortex trajectory with larger wake age and more details of vortex can be captured by TENO8-AA scheme with only a quarter of grid points and half time comparing to WENO-JS scheme. Moreover, the simulation accuracy of thrust coefficient is improved by up to 36%. Finally, the analyses for BVI and aeroacoustic characteristics of Operational Loads Survey (OLS) rotor are conducted, and the different forms of interaction mechanism are explored, such as oblique and parallel interactions. The results indicate that TENO scheme not only ensures the resolution of simulation in discontinuous region, but also minimizes the numerical dissipation in smooth region dominated by blade tip vortex. Therefore, the acoustic pressure peak prediction error of rotor in BVI state is significantly reduced to 5.6% and 0.8% at two microphone locations, respectively.

Evaluation of ground surface deformation in discontinuous permafrost regions along the China-Russia Crude Oil Pipelines in Northeast China using InSAR and ground surveys

Adequately and timely measuring and evaluating the ground surface deformation (GSD) are keys to the prudent mitigation of frost hazards of foundation soils and thus to the safe and cost-effective operation of oil pipelines in permafrost regions. Thus, it is crucial to accurately evaluate the GSD along the route of China-Russia Crude Oil Pipelines (CRCOPs) for a better understanding of frequent and substantial (differential) frost heave and thaw settlement of pipeline foundation soils in permafrost regions. In this study, GSDs along the CRCOPs from Xiufeng town to Jinsong town, northern Heilongjiang Province were monitored in discontinuous permafrost regions in the northern Da Xing'anling Mountains, Northeast China. The Sentinel-1B images from 2017 to 2021 and the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology were used in combination with the Geographical Detector (GeoDetector) for identifying the drivers for GSDs and with ground survey data for validation analysis of GSD at chosen sites (e.g., MDX304 and others). InSAR results show that most of the annual GSD rates along the CRCOPs range from −10 to 0 mm/a, with larger deformation rates in Ta’he, Cuigang, and Jinsong. GeoDetector analysis shows that latitude and soil types are the most important contributors to GSDs along the CRCOPs, and; GSDs are closely related to elevation, ground temperature at the depth of 1 m (GT1m), normalized difference vegetation index (NDVI), annual precipitation (AP), and slope aspects. Analyses of ground and oil-flow temperatures and survey results of electrical resistivity tomography (ERT) show that permafrost along CRCOPs has been degrading and thawing, resulting in thaw settlement, consolidation, and deformation of pipeline foundation soils and underlying/lateral permafrost layers and subsequently, the ground surface subsidence. This study provides key deformation data for the assessment and mitigation of frost hazards along the CRCOPs.

Beyond Trade-Off: An Optimized Binocular Stereo Vision Based Depth Estimation Algorithm for Designing Harvesting Robot in Orchards

Depth estimation is one of the bottleneck parts for harvesting robots to determine whether the operation of grasping or picking succeeds or not directly. This paper proposed a novel disparity completion method combined with bilateral filtering and pyramid fusion to improve the issues of incorrect outputs due to the missed or wrong matching when achieving 3D position from 2D images in open-world environments. Briefly, our proposed method has two significant advantages in general. Firstly, occlusion between leaves, branches, and fruits is a universal phenomenon in unstructured orchard environments, which results in the most depth estimation algorithms facing great challenges to obtain accurate outputs in these occluded regions. To alleviate these issues, unlike other research efforts that already exist, we optimized the semi-global matching algorithm to obtain high accuracy sparse values as an initial disparity map; then, an improved bilateral filtering algorithm is proposed to eliminate holes and discontinuous regions caused by occlusion to obtain precise and density disparity outputs. Secondly, due to taking the practical high-efficiency requirements of the automated harvesting robot in its working status into consideration, we attempted to merge multiple low-resolution bilateral filtering results through the pyramid fusion model which goes beyond the trade-off mechanism to improve the performance of both accuracy and time cost. Finally, a prototype harvesting robot was designed to conduct experiments at three kinds of different distances (0.6~0.75 m, 1~1.2 m, and 1.6~1.9 m). Experiment results showed that our proposed method achieved density disparity maps and eliminated holes and discontinuous defects in the disparity map effectively. The average absolute error of our proposed method is 3.2 mm, and the average relative error is 1.79%. In addition, the time cost is greatly reduced more than 90%. Comprehensive experimental results demonstrate that our proposed algorithm provides a potential possibility for designing harvesting.

Numerical Simulation of Downward Flame Propagation in Discontinuous Region of Solid Fuel

This paper presents a numerical model that investigates the characteristics of flow, heat, and mass transfer on downward flame propagation in the discontinuous region of solid fuel. Simulations were carried out for various discontinuous distances to analyze the morphology of the flame front and the competition between the “jump” of flame spread and heat transfer from the flame to the unburned area. The results demonstrate that there is a “jump” in the flame propagation in the discontinuous zone, with the flame front exhibiting a defined “acute angle” that undergoes a process from large to small during the flame spreading in the discontinuous area and deflects towards the discontinuous area of the material. The temperature in the discontinuous zone reaches a peak, and the average flame spread rate initially increases and then decreases with the increase of discontinuity distance until the flame spread stops. The study provides valuable insights into the growth and development of fires involving discretely distributed combustible materials.

Weighted compact nonlinear hybrid scheme based on a family of mapping functions for aeroacoustics problem

The study of differential schemes with high accuracy and low dispersion is of great significance for the numerical simulation of aeroacoustics over complex geometries. The midpoint-and-node-to-node explicit finite difference is employed to solve the flux derivatives of the linear Euler equations for improving the robustness. To obtain the numerical flux at the center of the grid element, we adopted a hybrid interpolation method of center and upwind interpolations, combined with a symmetrical conservative metric method, to achieve high-resolution discretization of the acoustic field variables and geometric variables of the structural grid. To suppress spurious oscillations and improve the resolution of discontinuous regions, a family of mapping functions is developed to establish different smoothness indicators and applied to the sixth-order weighted compact nonlinear hybrid scheme (WCNHS), forming a new WCNHS scheme based on piecewise exponential mapping functions (WCNHS-Pe). The approximate dispersion relation shows that the dispersion error and numerical dissipation of WCNHS-Pe are smaller than those of WCNHS with a simple mapping function to the original weights in Jiang and Shu and other mapping function-weighted WCNHS schemes. We have applied various WCNHS schemes to the numerical simulation of the Shu–Osher problem, propagation of Gaussian impulses on two-dimensional wavy grids, sound transmission at discontinuous interfaces, propagation of Gaussian impulses on three-dimensional wavy grids, etc. Numerical results indicate that the WCNHS-Pe scheme has better discontinuity capture capability, higher resolution, and lower dispersion under the same differential stencil, and is suitable for computational aeroacoustics of complex geometries.

Spatial distribution of permafrost degradation and its impact on vegetation phenology from 2000 to 2020

As global temperatures rise, permafrost is degraded. Permafrost degradation alters vegetation phenology and community composition, thereby affecting local and regional ecosystems. The Xing'an Mountains, located on the southern edge of the Eurasian permafrost region, are very sensitive to the impact of permafrost degradation on ecosystems. Climate change has direct effects on permafrost and vegetation growth, and analysis of the indirect effects of permafrost degradation on vegetation phenology based on the normalized difference vegetation index (NDVI) can explain the internal impact mechanisms of ecosystem components. Based on the temperature at the top of permafrost (TTOP) model, which was used to simulate the spatial distribution of permafrost areas in the Xing'an Mountains from 2000 to 2020, the areas of the three permafrost types showed a decreasing trend. The mean annual surface temperature (MAST) increased significantly at a rate of 0.008 °C year−1 from 2000 to 2020, and the southern boundary of the permafrost region moved north by 0.1–1 degrees. The average NDVI value of the permafrost region increased significantly in 8.34 % of the region. The significant correlations between NDVI and permafrost degradation, temperature and precipitation in the permafrost degradation region were 92.06 % (80.19 % positive, 11.87 % negative), 50.37 % (42.72 % positive, 7.65 % negative), and 81.59 % (36.25 % positive, 45.34 % negative), and were mainly distributed along the southern boundary of the permafrost region. A significance test of phenology in the Xing'an Mountains showed that the end of the growing season (EOS) and the length of the growing season (GLS) were significantly delayed and prolonged in the southern sparse island permafrost region. Sensitivity analysis showed that permafrost degradation was the main factor that affected the start of the growing season (SOS) and GLS. When the effects of temperature, precipitation, and sunshine duration were excluded, the regions with a significant positive correlation between permafrost degradation and SOS (20.96 %) and GLS (28.55 %) were located in both continuous and discontinuous permafrost regions. The regions with a significant negative correlation between permafrost degradation and SOS (21.11 %) and GLS (8.98 %) were mainly distributed on the southern edge of the island permafrost region. In summary, the NDVI changed significantly in the southern boundary of the permafrost region, and this change was mainly attributed to permafrost degradation.

Phase Unwrapping Error Correction Based on Multiple Linear Regression Analysis

Fringe projection profilometry (FPP) is prone to phase unwrapping error (PUE) due to phase noise and measurement conditions. Most of the existing PUE-correction methods detect and correct PUE on a pixel-by-pixel or partitioned block basis and do not make full use of the correlation of all information in the unwrapped phase map. In this study, a new method for detecting and correcting PUE is proposed. First, according to the low rank of the unwrapped phase map, multiple linear regression analysis is used to obtain the regression plane of the unwrapped phase, and thick PUE positions are marked on the basis of the tolerance set according to the regression plane. Then, an improved median filter is used to mark random PUE positions and finally correct marked PUE. Experimental results show that the proposed method is effective and robust. In addition, this method is progressive in the treatment of highly abrupt or discontinuous regions.

A deep learning based stereo matching model for autonomous vehicle

<p><span lang="EN-US">Autonomous vehicle is one the prominent area of research in computer vision. In today’s AI world, the concept of autonomous vehicles has become popular largely to avoid accidents due to negligence of driver. Perceiving the depth of the surrounding region accurately is a challenging task in autonomous vehicles. Sensors like light detection and ranging can be used for depth estimation but these sensors are expensive. Hence stereo matching is an alternate solution to estimate the depth. The main difficulties observed in stereo matching is to minimize mismatches in the ill-posed regions, like occluded, texture less and discontinuous regions. This paper presents an efficient deep stereo matching technique for estimating disparity map from stereo images in ill-posed regions. The images from Middlebury stereo data set are used to assess the efficacy of the model proposed. The experimental outcome dipicts that the proposed model generates reliable results in the occluded, texture less and discontinuous regions as compared to the existing techniques.</span></p>

Accurate edge-preserving stereo matching by enhancing anisotropy

Stereo matching has attracted substantial research attention, as it plays an important role in many visual tasks such as autonomous driving. Despite the remarkable progress has been made by all kinds of stereo matching methods, they still suffer in some challenging scenes like disparity discontinuities. The root cause of blurred depth boundaries lies in information diffusion across edge boundaries. Aiming at this problem, this paper presents a novel edge-preserving stereo matching method by enforcing anisotropy, where information is allowed to propagate throughout the image except through large discontinuities. Specifically, we propose an intra-scale cost aggregation algorithm to smooth out noise in homogeneous regions while well preserving strong edges in the guided image. And weighted averaging scheme, where weights are calculated according to the variances of pixels in different overlapping support windows, is utilized for enhancing anisotropy to improve accuracy at disparity discontinuities. We carry out comprehensive experiments on Middlebury public datasets to demonstrate the accuracy and edge-preserving property of our method. Qualitative and quantitative performance evaluation on Middlebury data sets demonstrate the superior performance of our method for strong edge preservation with 20.77% decreases in wrong matching ratios in discontinuous regions.

Flow field modeling of airfoil based on convolutional neural networks from transform domain perspective

For complex flow problems such as wall-bounded turbulence with multi-scale and strongly nonlinear characteristics, the non-orthogonal and non-uniform meshes commonly used in numerical simulation limit the direct use of Convolutional Neural Networks (CNNs). The flow field is usually projected onto a uniform Cartesian mesh to use the convolution operation, which inevitably leads to the problem of missing information about the turbulent flow field in the near-wall region. To address this limitation, a method is proposed for flow field modeling using CNN from the perspective of the transform domain. Specifically, the flow field is transformed from the non-uniform physical plane to the uniform computational plane. From the view of the transform domain, the flow governing equations will naturally generate variables used to characterize the geometry through the coordinate transformation without the need to design specific features. Moreover, since the computational plane is uniform and orthogonal, the convolution can be used directly without interpolation preprocessing. For the case of shape-based flow field modeling of the 2D airfoil and 3D wing under high Reynolds number conditions, the velocity and pressure of the turbulent boundary layer can be predicted very well by this method, even in the discontinuous shock wave region. In addition, the pros and cons of two different but common modeling frameworks represented by CNN and proper orthogonal decomposition (POD) are presented. The modeling error of CNN is one order of magnitude smaller than that of POD, and the relative error of the integral force of CNN is less than 1%. This work shows that the proposed method has significant advantages of high accuracy and interpretability, and provides an efficient solution for parameter space research.

Ultralow voltage (1 μV) electrical switching of SnS thin films driven by a vertical electric field

In this paper, we show in a series of experiments on 10 nm thick SnS thin film-based back-gate transistors that in the absence of the gate voltage, the drain current versus drain voltage (I D–V D) dependence is characterized by a weak drain current and by an ambipolar transport mechanism. When we apply a gate voltage as low as 1 μV, the current increases by several orders of magnitude and the I D–V D dependence changes drastically, with the SnS behaving as a p-type semiconductor. This happens because the current flows from the source (S) to the drain (D) electrode through a discontinuous superficial region of the SnS film when no gate voltage is applied. On the contrary, when minute gate voltages are applied, the vertical electric field applied to the multilayer SnS induces a change in the flow path of the charge carriers, involving the inner and continuous SnS layer in the electrical conduction. Moreover, we show that high gate voltages can tune significantly the SnS bandgap.

An efficient finite difference IFWENO-THINC hybrid scheme for capturing discontinuities

The weighted essentially non-oscillatory (WENO) scheme is a famous shock-capturing scheme, but for high-precision numerical simulation, the classical WENO scheme is always considered to have excessive dissipation and insufficient resolution near discontinuities. Improving the accuracy order or reducing the dissipation of the WENO by optimizing the linear weights can effectively improve the resolution of this scheme in the smooth regions. However, under the same method, the improvement of shock-capturing abilities is generally limited and may lead to numerical oscillations. In order to simultaneously improve the resolution in discontinuous regions and ensure the performance of the smooth regions, this study uses the shock detector to combine the tangent of hyperbola for interface capturing (THINC) scheme, which is a better discontinuity-capturing scheme, with a given WENO discretization, such as the improved fast WENO (IFWENO) scheme that equips with high economy and does not loss accuracy at any critical point. The hybrid method in this study is an apriori algorithm, which is more efficient and universal than the method in (Takagi et al. J. Comput. Phys. 452(2022)110899). Additionally, the performance of the THINC scheme in different regions near the discontinuity is analyzed in detail through numerical experiments, and a shock detector that can fully exploit the advantages of the THINC scheme is provided. By using this shock detector, several one-dimensional and two-dimensional numerical cases are employed to verify that the hybrid scheme can greatly improve the performance in discontinuities without affecting the flow structure in the smooth regions, which proves the effectiveness of the proposed shock detector and the excellence of the hybrid IFWENO-THINC scheme.

Discontinuous precipitation in Mg-Al alloy studied in 3-dimensions

Discontinuous precipitation (DP) is a commonly observed mechanism by which solid solutions decompose. It results from layers of precipitate and solute depleted matrix forming across a moving boundary. The morphology of the discontinuous regions can be highly complex, and the way dislocations or twins navigate such a structure during deformation is poorly understood. Only through 3-dimensional (3D) analysis can the true morphology of discontinuous precipitation be revealed. This work presents the first 3D study of DP using a novel PFIB based serial sectioning method. The material studied is AZ80, an industrially important class of Mg-Al-Zn alloy where DP is commonly observed. The structure is revealed to consist of an interconnected network of DP regions within an interconnected matrix. The width of the DP regions show strong local variations. This structure is expected to be readily penetrated by twins and dislocations.

MfeeU-Net: A multi-scale feature extraction and enhancement U-Net for automatic liver segmentation from CT Images.

Medical image segmentation of the liver is an important prerequisite for clinical diagnosis and evaluation of liver cancer. For automatic liver segmentation from Computed Tomography (CT) images, we proposed a Multi-scale Feature Extraction and Enhancement U-Net (mfeeU-Net), incorporating Res2Net blocks, Squeeze-and-Excitation (SE) blocks, and Edge Attention (EA) blocks. The Res2Net blocks which are conducive to extracting multi-scale features of the liver were used as the backbone of the encoder, while the SE blocks were also added to the encoder to enhance channel information. The EA blocks were introduced to skip connections between the encoder and the decoder, to facilitate the detection of blurred liver edges where the intensities of nearby organs are close to the liver. The proposed mfeeU-Net was trained and evaluated using a publicly available CT dataset of LiTS2017. The average dice similarity coefficient, intersection-over-union ratio, and sensitivity of the mfeeU-Net for liver segmentation were 95.32%, 91.67%, and 95.53%, respectively, and all these metrics were better than those of U-Net, Res-U-Net, and Attention U-Net. The experimental results demonstrate that the mfeeU-Net can compete with and even outperform recently proposed convolutional neural networks and effectively overcome challenges, such as discontinuous liver regions and fuzzy liver boundaries.

Performance and changes of high‐resolution (1 km) surface air temperature in Northern Hemisphere permafrost regions

AbstractSurface air temperatures are significant indicators of environmental and climatic change that affect a diverse set of physical systems including permafrost. Most temperature products, such as gridded or reanalysis data, are still at a relatively low spatial resolution, limiting the ability to simulate heterogeneous permafrost changes and leading to large uncertainties. Here we apply a downscaling method based on elevation to obtain high‐resolution surface air temperatures from the sixth Coupled Model Intercomparison Project in Northern Hemisphere permafrost regions. Root‐mean‐square errors and mean absolute errors after downscaling are reduced by 34 and 37%, respectively, relative to meteorological site data and gridded observations from the Climatic Research Unit. Compared to the downscaled surface air temperature data, nondownscaled model projections overestimate by 0.12–0.39°C in the discontinuous, isolated, and sporadic permafrost regions and underestimate up to 0.18°C in the continuous permafrost region under different emission scenarios. The warming rates in Northern Hemisphere permafrost regions were 0.093°C/10 year during the historical (1850–2014) period and are projected to be 0.22°C/10 year for SSP1‐2.6, 0.48°C/10 year for SSP2‐4.5, 0.75°C/10 year for SSP3‐7.0, and 0.95°C/10 year for SSP5‐8.5 during 2015–2100, which is 1.4–1.6 times the warming of nonpermafrost regions. Warming rates in high latitudes are 1.2–1.7 times higher than those in high‐elevation regions. Continuous permafrost regions' warming will be 1.2–1.4 times higher than in other permafrost regions. For permafrost with high ground ice content, warming will be 1.1 times greater than in permafrost regions with medium or low ground ice content.

A class of high-order improved fast weighted essentially non-oscillatory schemes for achieving optimal order at any critical points

The weighted essentially non-oscillatory (WENO) scheme is one of the most popular shock-capturing schemes, and constructing a more efficient and higher-order WENO scheme has always been an intention of optimization design. In the general WENO reconstruction framework, the smoothness indicator plays an important role in identifying whether the sub-stencils are in discontinuous or smooth regions. However, the classical smoothness indicator is the most expensive one in the whole reconstruction algorithm, and its computational complexity increases sharply with the improvement of the accuracy order. Therefore, a class of efficient and superior WENO schemes called improved fast WENO (IFWENO) are proposed based on the fast WENO (FWENO). To improve efficiency, the smoothness indicator of the IFWENO scheme is simplified from the traditional version, and the nonlinear weight calculation method is modified. The parameter ε is carefully designed to obtain the superior property that the accuracy of the spatial derivatives will not degrade at any order critical point in smooth regions. The reason for the instability occurring in the high-order FWENO is revealed, and the parameter p is likewise specifically selected to improve robustness at discontinuities. The excellent multi-scale resolution of the proposed IFWENO scheme is proven by theoretical analyses and numerical experiments. Through several typical examples, the consistently high accuracy and efficiency of the designed scheme in both smooth and discontinuous regions are verified.