Large-scale Measurements Research Articles

Identification of global main cable line shape parameters of suspension bridges based on local 3D point cloud

Main cable line shape measurement and parameter identification are a critical task in the construction monitoring and service maintenance of suspension bridges. 3D LiDAR scanning can simultaneously obtain the coordinates of multiple points on the target, offering high accuracy and efficiency. As a result, it is expected to be used in applications requiring rapid, large-scale measurements, such as main cable line shape measurement for suspension bridges. However, due to the large span and tall main towers of suspension bridges, the LiDAR field of view often encounters obstructions, making it difficult to obtain high-quality point clouds for the entire bridge. The collected point clouds are typically unevenly distributed and of poor quality. Therefore, LiDAR is used to monitor the local cable line shape. This paper proposes an innovative non-uniform sampling method that adjusts the sampling density based on the main cable’s rate of change. Additionally, the Random Sample Consensus (RANSAC) algorithm, the ordinary least squares, and center-of-mass calibration are applied to identify and optimize the geometric parameters of the cross-section point cloud of the main cable. Given the strong design prior information available during suspension bridge construction, Bayesian theory is applied to predict and adjust the global line shape of the main cable. The study shows that using LiDAR for cable point cloud measurement enables rapid acquisition of high-precision point cloud data, significantly enhancing data collection efficiency. The method proposed in this paper offers advantages such as highly automated, low risk, low cost, and sustainability, making it suitable for green monitoring throughout the entire main cable construction process.

Massively parallel characterization of transcriptional regulatory elements.

The human genome contains millions of candidate cis-regulatory elements (cCREs) with cell-type-specific activities that shape both health and many disease states1. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these cCREs. Here we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of more than 680,000 sequences, representing an extensive set of annotated cCREs among three cell types (HepG2, K562 and WTC11), and found that 41.7% of these sequences were active. By testing sequences in both orientations, we find promoters to have strand-orientation biases and their 200-nucleotide cores to function as non-cell-type-specific 'on switches' that provide similar expression levels to their associated gene. By contrast, enhancers have weaker orientation biases, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict cCRE function and variant effects with high accuracy, delineate regulatory motifs and model their combinatorial effects. Testing a lentiMPRA library encompassing 60,000 cCREs in all three cell types further identified factors that determine cell-type specificity. Collectively, our work provides an extensive catalogue of functional CREs in three widely used cell lines and showcases how large-scale functional measurements can be used to dissect regulatory grammar.

Direct assessment of the influence of pose repeatability on the accuracy of dimensional measurements for computed tomography systems with high degrees of freedom

Abstract Industrial x-ray computed tomography (CT) systems with high geometric flexibility are increasingly utilized for large-scale measurement objects or challenging measurement tasks. To maintain high accuracy when deviating from the established circular scan trajectory, trajectory calibration methods using multi-sphere reference objects with known marker positions are commonly employed. These multi-sphere objects can either be scanned together with the measurement object (online trajectory calibration) or in a separate scan (offline trajectory calibration). While offline calibration increases machine time, it generally results in higher scan quality. However, a sufficient pose repeatability is necessary to ensure comparable or even superior accuracy to online calibration. In this contribution, we present a straightforward procedure to compare both types of trajectory calibration in a way that the differences of the results can directly be traced back to the influence of the pose repeatability. The multi-sphere reference object is not only used for trajectory calibration, but simultaneously as a measurement object for repeated measurements. The methodology is tested on both a twin robotic CT system and a conventional CT system that is additionally equipped with a hexapod manipulator for adaptive object tilting. Results showed, independent from the type of trajectory calibration, systematic measurement errors in the order of 10−5–10−4 of measured sphere distances and sphericity values below 50 μ m . For sphere distances, random errors were increased by a factor of 5 due to the offline trajectory calibration, but were still low ( < 1 μ m ) in comparison to systematic errors and the spread of different measurement features. Overall, both investigated systems demonstrated sufficient positioning repeatability for offline trajectory calibration. The method is in general also applicable to any other types of manipulator systems used for CT devices. It provides a workflow for the decision which type of trajectory calibration is preferable for a given CT system.

A review of error analysis and calibration techniques for spherical coordinate 3D laser scanners: Focus on non-instrumental and non-geometric factors

Both Terrestrial Laser Scanners (TLSs) and Metrological Laser Radars (MLRs) are typical Spherical Coordinate Laser Scanners (SCLSs), which are used for various fields requiring surface 3D scanning. TLSs are popular in historical preservation and archiving, reverse engineering, surveying geographic modeling, and digital cities, etc. MLRs, on the other hand, are primarily applied in large-scale precision measurements in industrial manufacturing due to their high accuracy in scanned 3D points. The 3D point precision of both TLSs and MLRs is affected significantly by geometric errors inside instruments. While the geometric errors of SCLSs have been reviewed in some studies, a systematic review of external non-instrumental errors and internal non-geometric errors for TLSs and MLRs is still lacking. These error sources also affect the measurement accuracy of SCLSs. This paper aims to review the quantitative and qualitative analysis of external non-instrumental errors and internal non-geometric errors in TLSs and MLRs. The external non-instrumental errors are further classified into surface properties, scanning geometry, and working environment in this review. For internal non-geometric errors, current research primarily focuses on laser signal processing but lacks studies on error mechanisms and their impact on accuracy. Most existing studies address Time-of-Flight (ToF)-based TLSs, with limited attention given to MLRs. While external factors such as scan depth and surface reflectance are well-studied, environmental factors like temperature remain underexplored. Additionally, there is insufficient research on error compensation models for external factors. Future research on MLRs may focus on several aspects. These include analyzing external non-instrument error factors qualitatively and quantitatively, developing error compensation models, studying the impact of the working environment, and evaluating uncertainty using large-scale standard objects. This review may be beneficial for understanding the research development about the non-instrumental and non-geometric errors of SCLSs.

Tools for planning large-scale measurement surveys for the assessment of indoor environmental pollutants: the case of radon

Risks from indoor pollutants require the implementation of effective policies to prevent and reduce exposure. To take decisions and actions, competent authorities need relevant information. In the case of indoor radon exposure, surveys are carried out by installing detectors in buildings (homes, workplaces) that measure radon concentration in rooms. Conducting national or large-scale surveys in buildings requires addressing both technical complexities of implementation and economic costs. In order to support the implementation of large-scale radon surveys, procedure and tools are described for defining the sample size of buildings to be measured according to available resources, for planning the sampling of buildings in relation to the specific objectives of the survey, and for obtaining a tool for management and control of sample recruitment and installation of radon detectors in buildings, reducing sources of bias. A particular application is shown for the case of the EU radon regulation.

Comparative profiling of white matter development in the human and mouse brain reveals volumetric deficits and delayed myelination in Angelman syndrome

BackgroundAngelman syndrome (AS), a severe neurodevelopmental disorder resulting from the loss of the maternal UBE3A gene, is marked by changes in the brain’s white matter (WM). The extent of WM abnormalities seems to correlate with the severity of clinical symptoms, but these deficits are still poorly characterized or understood. This study provides the first large-scale measurement of WM volume reduction in children with AS. Furthermore, we probed the possibility of underlying WM neuropathology by examining the progression of myelination in an AS mouse model.MethodsWe conducted magnetic resonance imaging (MRI) on children with AS (n = 32) and neurotypical controls (n = 99) aged 0.5–12 years. In parallel, we examined myelination in postnatal Ube3a maternal-null mice (Ube3am−/p+; AS model), Ube3a paternal-null mice (Ube3am+/p−), and wildtype controls (Ube3am+/p+) using MRI, immunohistochemistry, western blotting, and electron microscopy.ResultsOur data revealed that AS individuals exhibit significant reductions in brain volume by ~ 1 year of age, and by 6–12 years of age WM is reduced by 26% and gray matter by 21%—approximately twice the reductions observed in the adult AS mouse model. Our AS mouse model saw a global delay in the onset of myelination, which normalized within days (likely corresponding to months or years in human development). This myelination delay is caused by the loss of UBE3A in neurons rather than UBE3A haploinsufficiency in oligodendrocytes. Interestingly, ultrastructural analyses did not reveal abnormalities in myelinated or unmyelinated axons.LimitationsIt is difficult to extrapolate the timing and duration of the myelination delay observed in AS model mice to individuals with AS.ConclusionsThis study reveals WM deficits as a hallmark in children with AS, demonstrating for the first time that these deficits are already apparent at 1 year of age. Parallel studies in a mouse model of AS show these deficits occur alongside the delayed onset of myelination, which results from the loss of neuronal (but not glial) UBE3A, though the causal relationship between these phenotypes remains to be determined. These findings emphasize the potential of WM as both a therapeutic target for interventions and a valuable biomarker for tracking the progression of AS and the effectiveness of potential treatments.

Addiction treatment and harm reduction programs in prisons: lessons from Iran.

Substance use disorder is one of the most prevalent health issues among prison populations. In this regard, addiction treatment and harm reduction programs have been implemented in Iranian prisons since 2002. The purpose was to describe the practical experience of implementing harm reduction programs in Iran's prisons, emphasizing the impact of policy decisions on it. The study was qualitative study. In addition to analyzing 16 documents, the authors conducted face-to-face semi-structured interviews with 11 key informants who were asked questions about the evolution of treatment and harm reduction programs in prisons. The authors analyzed the data using the content analysis method and MAXQDA-10 software. The HIV outbreak in Iranian prisons in the late 20th century posed a significant challenge. Initially, policymakers' responses were varied from denying the issue to solving it, reflecting the prevailing abstinence paradigm among drug experts and politicians. However, a legal amendment was eventually issued based on evidence-based health literature. Despite initial obstacles such as financial constraints and lack of human resources, the successful implementation of large-scale harm reduction measures, including methadone maintenance treatment and interventions targeting infectious diseases, has led to the development of a unique health model in the Persian Gulf region. This model, born out of the Iranian experience, offers hope for the future of prison health. Lessons from the Iran case could provide valuable insight for countries about the role of policy in implementing harm reduction programs in prisons. Policy advocacy and reform is one of the main measures to provide evidence-based health interventions in prisons.

Constraining dark energy with the integrated Sachs-Wolfe effect

We use the integrated Sachs-Wolfe (ISW) effect, by now detectable at ∼5σ within the context of Λ cold dark matter (ΛCDM) cosmologies, to place strong constraints on dynamical dark energy theories. Working within an effective field theory (EFT) framework for dark energy we find that including ISW constraints from galaxy–cosmic microwave background (CMB) cross-correlations significantly strengthens existing large-scale structure constraints, yielding bounds consistent with ΛCDM and approximately reducing the viable parameter space by ∼70%. This is a direct consequence of O(1) changes induced in these cross-correlations by otherwise viable dark energy models, which we discuss in detail. We compute constraints by adapting the ΛCDM ISW likelihood from Stölzner [] for dynamical dark energy models using galaxy data from 2 MASS, wide-field infrared survey explorer (WISE) × SuperCOSMOS, Sloan Digital Sky Survey Data Release 12, the catalog of photometric quasars and NRAO Very Large Array Sky Survey, CMB data from Planck 18, and baryon acoustic oscillation and redshift space distortion large-scale structure measurements from BOSS and 6dF. We show constraints both in terms of EFT-inspired αi and phenomenological μ/Σ parametrizations. Furthermore we discuss the approximations involved and related aspects of bias modeling in detail and highlight what these constraints imply for the underlying dark energy theories. Published by the American Physical Society 2024

Cosmological Constraints from Combining Photometric Galaxy Surveys and Gravitational Wave Observatories

Spatial variations in survey properties due to selection effects generate substantial systematic errors in large-scale structure measurements in optical galaxy surveys on very large scales. On such scales, the statistical sensitivity of optical surveys is also limited by their finite sky coverage. By contrast, gravitational wave (GW) sources appear to be relatively free of these issues, provided the angular sensitivity of GW experiments can be accurately characterized. We quantify the expected cosmological information gain from combining the forecast LSST 3x2pt analysis (combination of three 2-point correlations of galaxy density and weak lensing shear fields) with the large-scale auto-correlation of GW sources from proposed next-generation GW experiments. We find that in ΛCDM and wCDM models, there is no significant improvement in cosmological constraints from combining GW with LSST 3x2pt over LSST alone, due to the large shot noise for the former; however, this combination does enable a ∼6% constraint on the linear galaxy bias of GW sources. More interestingly, the optical-GW data combination provides tight constraints on models with primordial non-Gaussianity (PNG), due to the predicted scale-dependent bias in PNG models on large scales. Assuming that the largest angular scales that LSST will probe are comparable to those in Stage III surveys (), the inclusion of next-generation GW measurements could improve constraints on the PNG parameter by up to a factor of ≃6.6 compared to LSST alone, yielding . These results assume the expected capability of a network of Einstein Telescope-like GW observatories, with a detection rate of 106 events/year. We investigate the sensitivity of our results to different assumptions about future GW detectors as well as different LSST analysis choices.

Sickle cell disease in India: the journey and hope for the future.

India, the most populous nation in the world, also has a high frequency of the sickle hemoglobin (HbS) allele globally. The Arab Indian HbS haplotype in India is characterized by a relatively high percentage of fetal Hb, with widely varying frequencies of α-thalassemia. Hence, sickle cell disease (SCD) in India was perceived to be mild. Advances in the past decade in screening and SCD management have revealed that the severity of SCD in India is comparable to many other parts of the world. Clinical features in India include vaso-occlusive crisis, acute chest syndrome, avascular necrosis, renal involvement, stroke, etc, at a relatively young age. Once a fatal disease of childhood, the majority of patients born with SCD are expected to survive into adulthood, largely because of improvements in comprehensive care programs including newborn screening, penicillin prophylaxis, transcranial Doppler, and hydroxyurea therapy. Several centers are performing hematopoietic stem cell transplants successfully for SCD. To address the urgent need to control and manage SCD in India's population, the Government of India launched the National Sickle Cell Anaemia Elimination Mission, with significant funding for large-scale measures to screen, treat, counsel, educate, and develop technologies and novel therapies and gene therapies.

Comparison of Airborne Magnetic and Ground Magnetic for Identification of Sub-surface Condition Study Case Sand Caldera of Bromo-Tengger Volcanic Complex : Preliminary Study

Abstract The Bromo-Tengger Volcano Complex is a popular geotourism destination characterized by volcanic activity also unique geological and geomorphology settings. However, limited geophysical investigations have been conducted in this area, particularly using magnetic methods, to understand the subsurface conditions. Thus, this study aims to compare geophysical methods which are airborne and ground magnetic survey methods to identify the sub-surface conditions of Bromo-Tengger Volcano Complex. Airborne magnetic measurements were conducted using a Geotron Proton Precision Magnetometer G5 as the base and a Sensys Magdrone R3 with a DJI M600 drone as the rover with 5 ms of spacing, providing rapid coverage of large areas and minimizing interference. Ground magnetic measurements were taken using only a Geotron Proton Precision Magnetometer G5 for base and rover with 200 meters of spacing. Ground magnetic measurements serve as a comparison to assess resolution and potential data loss caused by factors such as flight altitude and data sampling rate. Combining both magnetic survey measurements enables a comprehensive understanding of the magnetic properties of the surveyed area. The airborne magnetic survey produced 2,097,134 data points in just two days, while the ground magnetic survey produced only 174 points in ten days. Although the airborne magnetic survey is less detailed, it can effectively interpret the subsurface conditions. On the other hand, the ground magnetic survey provides high-resolution results but is affected by local noise and temporal changes. Both surveys identified high anomalies in the southern and northeastern regions, which were interpreted as basalt lava flows. Medium anomalies are believed to be early pyroclastic fall deposits, while low anomalies indicate subsurface volcanic activity. Overall, the results of the airborne magnetic survey correlate well with the ground magnetic survey, making it a viable and time-saving alternative to large-scale magnetic measurements.

Saving Private WAN: Using Internet Paths to Offload WAN Traffic in Conferencing Services

Large-scale video conferencing services incur significant network cost while serving surging global demands. Our work systematically explores the opportunity to offload a fraction of this traffic to the Internet, a cheaper routing option offered already by cloud providers, from WAN without drop in application performance. First, with a large-scale latency measurement study with 3.5 million data points per day spanning 241K source cities and 21 data centers across the globe, we demonstrate that Internet paths perform comparable to or better than the private WAN for parts of the world (e.g., Europe and North America). Next, we present Titan, a live (12+ months) production system that carefully moves a fraction of the conferencing traffic to the Internet using the above observation. Finally, we propose Titan-Next - a research prototype that jointly assigns the conferencing server and routing option (Internet or WAN) for individual calls. With 5 weeks of production data, we show Titan-Next reduces the sum of peak bandwidth on WAN links that defines the operational network cost by up to 61% compared to state-of-the-art baselines.

Measuring DNS-over-HTTPS Downgrades: Prevalence, Techniques, and Bypass Strategies

DNS-over-HTTPS (DoH) is a privacy-enhancing protocol that encrypts plaintext query data in DNS resolution. However, DoH often faces accessibility challenges due to phenomena known as DoH downgrades, where DoH queries are reverted to plaintext DNS queries. Unlike downgrades in other security protocols, which are undoubtedly malicious, the act of downgrading DoH queries can be both desirable and undesirable depending on the context; e.g., enterprise networks are officially advised to avoid or downgrade DoH for security reasons. Recent research has drawn attention to the deeper examination of the phenomena of DoH downgrades, focusing on the prevalence, techniques, and potential bypass strategies. However, existing studies on DoH downgrades have several limitations, notably that they severely overestimate the severity of DoH downgrades across the globe as they lack any distinction between desirable and undesirable downgrades of DoH. In this work, we conduct a large-scale measurement study to provide a more accurate depiction of the DoH downgrade landscape. By minimizing the influence of desirable downgrades of DoH in our measurement probes, we show a skewed long-tail distribution of DoH downgrades across the globe. Our stateful probing techniques also reveal hidden DoH filtering mechanisms that were previously undetected. Furthermore, we design near perfect bypass strategies against existing DoH downgrades. Our study expands our limited understanding of DoH downgrades, offering a more accurate, fine-grained, and comprehensive view of the phenomena.

Precision compensation method for large-scale measurements based on full-space refractive index field reconstruction with vibratory mirror background oriented schlieren (VMBOS)

With the development of the large-scale equipment manufacturing industry, such as aircraft component assembly, wind turbine rotor blade measurement and large ship assembly the demand for optical measurement accuracy in large-dimensional spaces within industrial environments has become increasingly stringent. However, due to the presence of internal interference sources, light will no longer propagate in a straight line, thereby introducing measurement errors that cannot be ignored. To compensate for the measurement error, the refractive index field distribution within the large-dimensional measurement space must be reconstructed. Therefore, this paper proposed a vibratory mirror background oriented schlieren (VMBOS) based on vibratory scanning. This method scans the measurement space through the rotation of vibratory mirror to obtain light deflection angles at different directions. Subsequently, the refractive index field of the large-dimensional space is reconstructed by using the tomographic reconstruction algorithm. Then the optical path of the light in the optical measurement can be corrected through the Hamiltonian ray tracing algorithm, thereby achieving compensation for the measurement error. Finally, the VMBOS method has been verified through both simulation and experimental methods. The experimental results demonstrated that the method proposed in this paper can be applied to optical path correction and error compensation in large scale spaces.

Hesitant fuzzy linguistic preference consistency-driven consensus model with large-scale group interaction measure for venture capital investment selection

Recently, consensus-based large-scale group decision making (LSGDM) has been widely interactive with the study of social network, clustering and trust-based concepts. This study develops a novel hesitant fuzzy linguistic preference consistency-driven consensus model with interaction measure for large-scale group decision makers (DMs) in social networks. Firstly, directed social network is constructed by measuring the similarity between incomplete hesitant fuzzy linguistic preference relation (HFLPR) matrices. Community detection method is further conducted to categorize DMs into several communities. Secondly, driven by exploring the consistency of HFLPR matrices and interactive trusts between DMs, a novel optimization model is established to estimate the missing elements. Thirdly, the 2-order additive fuzzy measures of different coalitions between divided communities for capturing their fully or partially interactions are derived by a consistency-based optimization model. Accordingly, the attitudinal Choquet integral operator is employed to aggregate preferences into the collective one. Fourthly, a consensus improving mechanism is devised to achieve the unanimous agreement of DMs characterized by the bounded confidence. Personalized and specific adjustment scales obtained by investigating interval consistency of HFLPRs are provided in support of DMs’ modifications. Finally, an illustrative case on syndicated venture capital investment selection is conducted and related simulation analyses are performed to elucidate the feasibility and validity of the proposed methods. The comparisons with other approaches reveal the superiority and improvement of our proposal.

Testing [formula omitted]-attractor quintessential inflation against CMB and low-redshift data

Due to universality and attractor properties, α-attractor quintessential inflation establishes direct relations between inflationary observables such as the scalar tilt ns and the tensor-to-scalar ratio r, and late-time dark energy equation of state parameters w0 and wa. In this work, we examine three different physically motivated regimes, considering complete freedom in the parameter α, models inspired by supergravity where α takes on values up to α=7/3, and Starobinsky inflation (α=1). We investigate the consistency and constraints imposed by Cosmic Microwave Background measurements from the Planck satellite, B-mode polarization data from the BICEP/Keck collaboration, and low-redshift observations. Additionally, we consider small-scale CMB measurements released by the Atacama Cosmology Telescope, which give results approaching the Harrison–Zel’dovich spectrum (ns≈1). Here α-attractors lead to an improved fit over ΛCDM. For the large-scale CMB measurements, α≳2 models can provide equally good fits as ΛCDM.

High spatial resolution φ-OFDR based on frequency-shift averaging and rotating vector summation

The coherent fading noise hinders the spatial resolution enhancements of phase optical frequency domain reflectometry (φ-OFDR). To mitigate the coherent fading noise, this study introduces frequency-shift averaging and rotating vector summation for strain measurements. The original Rayleigh backscattering signal was first divided into numerous sub-segments in frequency domain by using the frequency-shift averaging, and each sub-signal segment was transferred into vector signal with both intensity and phase information by using the rotating vector summation. Furthermore, a spatial position correction algorithm is incorporated to counteract the degradation of phase coherent, facilitating large-scale strain measurements. After optimizing the sub-frequency range and overlap ratio of the sub-signal in the frequency domain, we experimentally demonstrated that this method achieves strain measurement with a broad strain range of 2000 με, a high spatial resolution of 0.54 mm, and a high precision of 0.87%.

Future projections for mammalian whole-brain simulations based on technological trends in related fields

Large-scale brain simulation allows us to understand the interaction of vast numbers of neurons having nonlinear dynamics to help understand the information processing mechanisms in the brain. The scale of brain simulations continues to rise as computer performance improves exponentially. However, a simulation of the human whole brain has not yet been achieved as of 2024 due to insufficient computational performance and brain measurement data. This paper examines technological trends in supercomputers, cell type classification, connectomics, and large-scale activity measurements relevant to whole-brain simulation. Based on these trends, we attempt to predict the feasible timeframe for mammalian whole-brain simulation. Our estimates suggest that mouse whole-brain simulation at the cellular level could be realized around 2034, marmoset around 2044, and human likely later than 2044.

A Photometric Redshift Catalogue of Galaxies from the DESI Legacy Imaging Surveys DR10

The large-scale measurement of galaxy redshifts holds significant importance for cosmological research, as well as for understanding the formation and evolution of galaxies. This study utilizes a known sample obtained by cross-correlating the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys DR10 galaxy catalog with various galaxy catalogs from different spectroscopic surveys. The methods Easy and Accurate Photometric Redshifts from Yale (EAZY) and CatBoost are employed to estimate redshifts. In the case of EAZY, the known sample is used solely for testing, while CatBoost utilizes it for both training and testing purposes. The known sample is categorized into different subsamples based on various classification methods. Several CatBoost regression models are trained and optimized using these subsamples. By comparing the performance of different methods and models, it is observed that the two-step and two-part models outperform the one-step model, with further enhancements achieved through the combination of the two-step and two-part models. Based on the findings from all experiments, we propose a photometric redshift estimation workflow designed to facilitate the photometric redshift measurement of all galaxies within the DESI Legacy Imaging Surveys DR10. Consequently, a photometric redshift catalog has been released, comprising a total of 1,533,107,988 galaxies. Among these, 312,960,837 galaxies have reliable redshift estimates, determined using the CatBoost algorithm, with magnitude limits set at g > 24.0, r > 23.4, and z > 22.5. For galaxies with g, r, and z magnitudes exceeding these thresholds, the photometric redshifts estimated by EAZY can be employed as a reference.

Study on the Interface Reinforcement Effect of Bamboo Grid in Filled Loess Embankment in a High and Steep Gully

A bamboo grid is a new type of reinforcement material, which can replace traditional geogrids in the reinforcement of embankments. In this study, the reinforcement effect of the bamboo grid that is only set at the interface between the filled and undisturbed soils of the filled loess embankment in a high and steep gully was investigated. The influence of reinforcement position and grid spacing on the reinforcement effect was studied by carrying out a large-scale direct shear test, numerical simulation, and field measurement. The results indicated that the bamboo grid could enhance the shear strength of the reinforcement interface. The interface shear strength first improved and then decreased with the decrease in grid spacing. The differential settlement was significantly reduced after the reinforcement of the bamboo grid at the interface. Compared with other reinforcement positions, setting the bamboo grid in the upper part of the embankment was the most efficient and economical. When the grid spacing became dense, the reinforcement effect was improved as the differential settlement decreased. However, the improvement in the reinforcement effect by decreasing the grid spacing was limited, which meant there was an optimal grid spacing.