Finite element analysis of anchor plates using non-coaxial models

AbstractThe non-coaxial model simulating the non-coincidence between the principal stresses and the principal plastic strain rates is employed within the framework of finite element method (FEM) to predict the behaviors of anchors embedded in granular material. The non-coaxial model is developed based on the non-coaxial yield vertex theory, and the elastic and conventional coaxial plastic deformations are simulated by using elasto-perfectly plastic Drucker-Prager yield function according to the original yield vertex theory. Both the horizontal and vertical anchors with various embedment depths are considered. Different anchor shapes and soil friction and dilation angles are also taken into account. The predictions indicate that the use of non-coaxial models leads to softer responses, compared with those using conventional coaxial models. Besides, the predicted ultimate pulling capacities are the same for both coaxial and non-coaxial models. The non-coaxial influences increase with the increasing embedment depths, and circular anchors lead to larger non-coaxial influences than strip anchors. In view of the fact that the design of anchors is mainly determined by their displacements, ignoring the non-coaxiality in finite element numerical analysis can lead to unsafe results

The middle surface concept and its application to constitutive modeling of soils.

The modeling of stress-strain behavior of geomaterials, such as soils, is key to the accurate analyses of complicated geotechnical engineering structures. Traditional elastoplastic modeling concepts, characterized by a single yield surface, however, limit our ability to model complex stress-strain responses. In this dissertation, a novel modeling concept called the Middle Surface Concept (MSC), is developed using multiple pseudo yield surfaces. The MSC is first developed to model saturated sand behavior under monotonic triaxial loading conditions and then extended to the general stress space. Single element model predictions are compared to laboratory tests results for three different types of sands subjected to various loading conditions and reasonable comparisons are obtained. In order to implement the general stress space MSC sand model into a finite element method, the consistent tangent stiffness matrix is developed and the model is numerically integrated using the generalized trapezoidal rule. Some useful restrictions in terms of Poisson's ratio for various flow rules used in constitutive models for granular materials are also developed. The MSC sand model is implemented into a fully coupled computer code, DYSAC2, and predictions are made for a centrifuge model subjected to base shaking. Reasonable comparisons between DYSAC2 predictions and centrifuge model test results are obtained validating the performance of the MSC sand model in boundary value problems. Finally, the MSC is expanded to model unsaturated sand or silt behavior under triaxial monotonic loading conditions. Two pseudo yield surfaces are utilized to model the effects of suction on the stress-strain behavior of unsaturated sands and silts

Correlations between the stress paths of a monotonic test and a cyclic test under the same initial conditions

In most experimental studies on liquefaction, cyclic loadings are applied on specimens with various initial conditions. However, few studies compared cyclic test results with monotonic results under the same initial conditions. The relation between monotonic tests and cyclic tests is crucial for understanding liquefaction mechanics and liquefaction resistance. This work compares the stress paths of a monotonic test with those of a cyclic test under the same initial conditions, and concluded that the stress path of monotonic tests envelops the stress path of cyclic tests under the same initial conditions. In addition, a new parameter, Level of Liquefaction Index (LI) is proposed to evaluate the liquefaction resistance of specimens under various initial conditions, and a linear relationship between LI and number of cycles at failure is found

Efficient Semi-Supervised Federated Learning for Heterogeneous Participants

Federated Learning (FL) has emerged to allow multiple clients to collaboratively train machine learning models on their private data. However, training and deploying large-scale models on resource-constrained clients is challenging. Fortunately, Split Federated Learning (SFL) offers a feasible solution by alleviating the computation and/or communication burden on clients. However, existing SFL works often assume sufficient labeled data on clients, which is usually impractical. Besides, data non-IIDness across clients poses another challenge to ensure efficient model training. To our best knowledge, the above two issues have not been simultaneously addressed in SFL. Herein, we propose a novel Semi-SFL system, which incorporates clustering regularization to perform SFL under the more practical scenario with unlabeled and non-IID client data. Moreover, our theoretical and experimental investigations into model convergence reveal that the inconsistent training processes on labeled and unlabeled data have an influence on the effectiveness of clustering regularization. To this end, we develop a control algorithm for dynamically adjusting the global updating frequency, so as to mitigate the training inconsistency and improve training performance. Extensive experiments on benchmark models and datasets show that our system provides a 3.0x speed-up in training time and reduces the communication cost by about 70.3% while reaching the target accuracy, and achieves up to 5.1% improvement in accuracy under non-IID scenarios compared to the state-of-the-art baselines.Comment: 16 pages, 12 figures, conferenc

Magnesia-stabilised zirconia solid electrolyte assisted electrochemical investigation of iron ions in the SiO2-CaO-MgO-Al2O3 molten slag at 1723 K

Production of metallic iron through molten oxide electrolysis using inert electrodes is an alternative route for fast ironmaking without CO2 emissions. The fact that many inorganic oxides melt at ultrahigh temperatures (>1500 K) challenges conventional electro-analytical techniques used in aqueous, organic and molten salt electrolytes. However, in order to design a feasible and effective electrolytic process, it is necessary to best understand the electrochemical properties of iron ions in molten oxide electrolytes. In this work, a magnesia-stabilised zirconia (MSZ) tube with a closed end was used to construct an integrated three-electrode cell with the “MSZ | Pt | O2 (air)” assembly functioning as the solid electrolyte, the reference electrode and also the counter electrode. Electrochemical reduction of iron ions was systematically investigated on an iridium (Ir) wire working electrode in the SiO2-CaO-MgO-Al2O3 molten slag at 1723 K by cyclic voltammetry (CV), square wave voltammetry (SWV), chronopotentiometry (CP) and potentiostatic electrolysis (PE). The results show that the electro-reduction of the Fe2+ ion to Fe on the Ir electrode in the molten slag follows a single two-electron transfer step, and the rate of the process is diffusion controlled. The peak current on the obtained CVs is proportional to the concentration of the Fe2+ ion in the molten slag and the square root of scan rate. The diffusion coefficient of Fe2+ ions in the molten slag containing 5 wt% FeO at 1723 K was derived to be (3.43 ± 0.06)×10-6 cm2 s-1 from CP analysis. However, a couple of following processes, i.e. alloy formation on the Ir electrode surface and interdiffusion were found to affect the kinetics of iron deposition. An ECC mechanism is proposed to account for the CV observations. The findings from this work confirm that zirconia-based solid electrolytes can play an important role in electrochemical fundamental research in high temperature molten slag electrolytes

Monotonic direct simple shear tests on sand under multidirectional loading

Stress–strain responses of Leighton Buzzard sand are investigated under bidirectional shear. The tests are conducted by using the variable direction dynamic cyclic simple shear (VDDCSS), which is manufactured by Global Digital Systems (GDS) Instruments Ltd., U.K. Soil samples are anisotropically consolidated under a vertical normal stress and horizontal shear stress and then sheared in undrained conditions by applying a horizontal shear stress acting along a different direction from the consolidation shear stress. The influence of the orientation and magnitude of the consolidation shear stress is investigated in this study. There are only a few previous studies on soil responses under bidirectional shear, of which most studies do not consider the impact of the magnitude of the consolidation shear stress. They are compared with current studies, indicating both similarities and differences. Generally, all test results indicate that a smaller angle between the first and second horizontal shear stress leads to more brittle responses with higher peak strengths, and a larger angle leads to more ductile responses. In addition, the consolidation shear tends to make soil samples denser, and both the magnitude of consolidation shear stress and its direction influence the following stress–strain responses of soil samples

MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation

Recently, federated learning (FL) has emerged as a popular technique for edge AI to mine valuable knowledge in edge computing (EC) systems. To mitigate the computing/communication burden on resource-constrained workers and protect model privacy, split federated learning (SFL) has been released by integrating both data and model parallelism. Despite resource limitations, SFL still faces two other critical challenges in EC, i.e., statistical heterogeneity and system heterogeneity. To address these challenges, we propose a novel SFL framework, termed MergeSFL, by incorporating feature merging and batch size regulation in SFL. Concretely, feature merging aims to merge the features from workers into a mixed feature sequence, which is approximately equivalent to the features derived from IID data and is employed to promote model accuracy. While batch size regulation aims to assign diverse and suitable batch sizes for heterogeneous workers to improve training efficiency. Moreover, MergeSFL explores to jointly optimize these two strategies upon their coupled relationship to better enhance the performance of SFL. Extensive experiments are conducted on a physical platform with 80 NVIDIA Jetson edge devices, and the experimental results show that MergeSFL can improve the final model accuracy by 5.82% to 26.22%, with a speedup by about 1.74x to 4.14x, compared to the baselines

Comparison of yield-vertex tangential loading and principal stress rotational loading

The yield-vertex tangential loading theory is a constitutive approach that accounts for the plastic straining induced by the part of a stress rate directed tangential to the yield surface. One of the important applications of this theory is in the study of geotechnical problems involving significant rotation of principal stress directions. However, it is inaccurate to simply regard the tangential loading as an equivalence to the principal stress rotation. For future reference, this paper presents an investigation into the difference between the tangential loading theory and a true purely principal stress rotational loading theory. Mathematical derivation shows that the tangential stress rate includes the rotational stress rate and an additional coaxial term that is associated with the variation of the Lode angle. Numerical applications of these two theories indicate that in shear dominated problems, such as simple shear, the two theories are almost identical and interchangeable, but in non-shear dominated circumstances, such as footing, the tangential loading theory produces considerably softer results than the rotational loading theory

Association between chronic diseases and depression in the middle-aged and older adult Chinese population—a seven-year follow-up study based on CHARLS

BackgroundWith the aging of the Chinese population, the prevalence of depression and chronic diseases is continually growing among middle-aged and older adult people. This study aimed to investigate the association between chronic diseases and depression in this population.MethodsData from the China Health and Retirement Longitudinal Study (CHARLS) 2011–2018 longitudinal survey, a 7-years follow-up of 7,163 participants over 45 years old, with no depression at baseline (2011). The chronic disease status in our study was based on the self-report of the participants, and depression was defined by the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10). The relationship between baseline chronic disease and depression was assessed by the Kaplan–Meier method and Cox proportional hazards regression models.ResultsAfter 7-years follow-up, 41.2% (2,951/7163, 95% CI:40.1, 42.3%) of the participants reported depression. The analysis showed that participants with chronic diseases at baseline had a higher risk of depression and that such risk increased significantly with the number of chronic diseases suffered (1 chronic disease: HR = 1.197; 2 chronic diseases: HR = 1.310; 3 and more chronic diseases: HR = 1.397). Diabetes or high blood sugar (HR = 1.185), kidney disease (HR = 1.252), stomach or other digestive diseases (HR = 1.128), and arthritis or rheumatism (HR = 1.221) all significantly increased the risk of depression in middle-aged and older adult Chinese.ConclusionThe present study found that suffering from different degrees of chronic diseases increased the risk of depression in middle-aged and older adult people, and these findings may benefit preventing depression and improving the quality of mental health in this group

Study of long-termed displacements of a tunnel boring machine during its stoppage

This paper studies the long-termed displacement of a tunnel boring machine (TBM) resting on soft clay during its unscheduled stoppage for 100 days. It is based on a real case of tunneling in a coastal city of Ningbo in China. The numerical prediction is carried out by using different soil models in the software PLAXIS, and the prediction is compared with on-site measurement of the displacement. Different factors are considered in the prediction, including soil creeping and the disturbance to the soft clay during the tunneling. The study indicates that the consideration of disturbance is essential to the accurate prediction. While advanced soil models including the soft soil model and soft soil creep model are not able to accurately predict the TBM displacement, the consideration of soil disturbance leads to a very good agreement with the measurement. The accurate prediction of ground settlements also justifies consideration of the disturbance in the study of tunneling. © 2018 Elsevier Lt