Initial Loading Conditions Research Articles

Analysis on characteristics of ground vibration induced by underground high-speed trains based on in-situ test

With the increasingly emerging traffic intersection form of high-speed railways passing underneath integrated transport terminals, the ground vibration induced by trains running on underground high-speed railways has attracted extensive attention. In combination with the engineering example of a high-speed railway in construction passing underneath an airport, the wheel-drop impact test in the high-speed railway tunnel was designed to obtain the vibration characteristics of surrounding soil. The vehicle-track-tunnel-ground semi-analytical three-dimensional model was established to determine the initial dynamic load condition of the vehicle loads. The amplitude-frequency characteristic and transmission law of the ground vibration induced by trains running on underground high-speed railways were predicted and analyzed. The influences of different operation conditions, track parameters, and tunnel burial depths were compared. The research results show that the ground vibration obtained through the wheel-drop test is greatly attenuated within 10 m from the track centerline, with an attenuation rate up to 70%. The vertical vibration amplitude is obviously larger than that of the other two directions. The lateral ground vibration amplitude is the smallest with the slowest vibration attenuation speed. When the high-speed train passes through at the speed of 350 km/h, the vertical and lateral vibration levels of the ground surface within 80 m range are 20∼80 dB and 43∼72 dB, respectively. The maximum attenuation coefficient of Z-vibration level reaches 0.276 dB/m. For each increase of 50 km/h of the train speed, the Z-vibration level of the ground increases by about 2 dB. The smaller fastener stiffness leads to the greater ground vibration within 20∼50 Hz. The ground vibration level is positively correlated with the fastener stiffness above 79 Hz. When the burial depth of the tunnel is greater than 14 m, the burial depth of the tunnel has little effect on the change of the Z-vibration level of the ground.

Surface Modifications of Superparamagnetic Iron Oxide Nanoparticles with Polyvinyl Alcohol and Graphite as Methylene Blue Adsorbents

Methylene blue (MB) is one of the toxic synthetic dyes that are being discharged heavily into water supplies. Hence, MB removal is one of the most important tasks for a cleaner water supply. By using inexpensive, abundant, and easy-to-synthesize materials, superparamagnetic iron oxide nanoparticles, which were synthesized using the co-precipitation method with polyvinyl alcohol and graphite (SPION/PVA/GR), can be used to adsorb MB. The adsorbent was characterized using FE-SEM, FTIR, XRD, VSM, and BJH. The entrapment efficiency of MB on SPION/PVA/GR after 12 days was 33.96 ± 0.37–42.55 ± 0.39%, at 333.15, 310.15, and 298.15 K, and the initial concentration of MB was 0.017–0.020 mg/mL. The adsorption process can be considered spontaneous, endothermic, chemisorption, heterogeneous, or multilayer adsorption. When releasing MB at 298.15 K and a pH of 3.85 after 7 days, the release percentage ranged from 11.56 ± 0.33 to 22.93 ± 5.06 depending on the initial loading conditions and mainly the releasing temperature following the Higuchi kinetic model. Since this is a novel SPION-based MB adsorbent, optimization, and different forms of adsorbent (i.e., thin film composite) should be further researched.

An [formula omitted]-adaptive discontinuous Galerkin method for phase field fracture

The phase field method is becoming the de facto choice for the numerical analysis of complex problems that involve multiple initiating, propagating, interacting, branching and merging fractures. However, within the context of finite element modelling, the method requires a fine mesh in regions where fractures will propagate, in order to capture sharp variations in the phase field representing the fractured/damaged regions. This means that the method can become computationally expensive when the fracture propagation paths are not known a priori. This paper presents a 2D hp-adaptive discontinuous Galerkin finite element method for phase field fracture that includes a posteriori error estimators for both the elasticity and phase field equations, which drive mesh adaptivity for static and propagating fractures. This combination means that it is possible to be reliably and efficiently solve phase field fracture problems with arbitrary initial meshes, irrespective of the initial geometry or loading conditions. This ability is demonstrated on several example problems, which are solved using a light-BFGS (Broyden–Fletcher–Goldfarb–Shanno) quasi-Newton algorithm. The examples highlight the importance of driving mesh adaptivity using both the elasticity and phase field errors for physically meaningful, yet computationally tractable, results. They also reveal the importance of including p-refinement, which is typically not included in existing phase field literature. The above features provide a powerful and general tool for modelling fracture propagation with controlled errors and degree-of-freedom optimised meshes.

Gaussian process regression-based load-carrying capacity models of corroded prestressed concrete bridge girders for fast-screening and reliability-based evaluation

Fast screening and reliability-based evaluation of corroded prestressed concrete (PC) bridge girders for safety assessment requires efficient capacity prediction models. This paper aims at developing data-based prediction models to quantify corrosion effects on load-carrying capacity of PC girders that are precast and standardized for short-span bridges. The load-carrying capacity of corroded bridge girders depends on their initial design configuration (e.g., those characterized by the standardized PC girders), loading condition (e.g., shear-span-to-effective-depth ratio), and corrosion conditions (e.g., corrosion degree). To develop data-based prediction models, generating sufficient data through physical experimental tests of full-scale corroded PC girders is prohibitively costly. Thus, a virtual experimental database is generated numerically using two-dimensional continuum-based finite element (FE) models for corroded PC girders, after being validated using 9 corroded PC girders tested in the literature with flexure or shear failure. To this end, a total of 4,165 PC girders under point loading are simulated to consider various design, loading, and corrosion conditions to estimate their load-carrying capacities. With this database, probabilistic machine learning, specifically Gaussian process regression or kriging, is used to develop (1) a residual capacity factor model (i.e., the ratio between load-carrying capacities from corroded and uncorroded girders), and (2) a load-carrying capacity prediction model (i.e., to predict the load-carrying capacity of uncorroded/corroded girders). The first model is used to study the load-carrying capacity reduction of PC girders due to corrosion compared to their uncorroded counterparts; this can reveal how the increasing corrosion condition affects the load-carrying capacity of corroded PC girders together with other design and loading parameters. The second model is developed to predict the load-carrying capacity of corroded PC girders as a function of design, loading, and corrosion parameters; its application to conditional reliability analysis provides insights into corrosion effect on the probability of failure of corroded PC girders at given load levels when the capacity is affected by corrosion. The application results of the two models enable engineers to quantify the corrosion effect on PC girders in terms of (1) reduction in load-carrying capacity for fast screening and (2) increase in probability of failure for reliability-based evaluation.

Investigation of the effect of initial structure and loading condition on the deformation, strength, and failure characteristics of continental shale

Investigation of the effect of initial structure and loading condition on the deformation, strength, and failure characteristics of continental shale

Numerical study on buckling capacity of steel H-beams under non-uniform temperature distribution

PurposeThe strength and stiffness of steel deteriorate rapidly at elevated temperatures. Thus, the characteristics of steel structures exposed to fire have been concerned in recent years. Most studies on the fire response of steel structures were conducted at uniformly distributed temperatures. This study aims to evaluate the buckling capacity of steel H-beams subjected to different loading conditions under non-uniform heating.Design/methodology/approachA numerical investigation was conducted employing finite element analysis software, ABAQUS. A comparison between the numerical analysis results and the experimental data from previous studies was conducted to verify the beam model. Simply supported beams were loaded with several loading conditions including one end moment, end equal moments, uniformly distributed load and concentrated load at midspan. The effects of initial imperfections were considered. The buckling capacities of steel beams under fire using the existing fire design code and the previous study were also generated and compared.FindingsThe results showed that the length-to-height ratio and loading conditions have a great effect on the buckling resistance of steel beams under fire. The capacity of steel beams under non-uniform temperature distribution using the existing fire design code and the previous study can give unconservative values or too conservative values depending on loading conditions. The maximum differences of unconservative and conservative values are −44.5 and 129.2% for beams subjected to end equal moments and one end moment, respectively.Originality/valueThis study provides the buckling characteristics of steel beams under non-uniform temperature considering the influences of initial imperfections, length-to-height ratios, and loading conditions. This study will be beneficial for structural engineers in properly evaluating structures under non-uniform heating conditions.

Choices of the Critical Frequency for φ in TL-φ Algorithms When Applied to Multi-Degree of Freedom Systems

TL-φ algorithms are newly developed explicit structure-dependent integration algorithms utilized for solving the temporally discretized equations of motion. In contrast to the existing algorithms, the most significant improvement of TL-φ algorithms is in diminishing the amount of period errors by introducing a precorrection coefficient φ into the integration parameters of TL-φ algorithms, which is related to the critical frequency of a system. In the previous work, the fundamental frequency of the system is deemed to be the critical frequency, so that φ is a constant scaling corresponding to the fundamental frequency for both single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems. However, for a MDOF system, the first mode may not contribute to the total response more than other ones under a given external excitation, calculating φ only by the fundamental frequency will underestimate the contribution of the higher-frequency modes to structural dynamics. In this paper, choices of the critical frequency for φ when applying TL-φ algorithms to MDOF systems are investigated thoroughly. By considering the initial structural properties of the system and the frequency characteristics of the external excitation simultaneously, a calculation criterion of φ for MDOF systems under specific external excitations is proposed. Four numerical examples with different initial structure properties and loading conditions are designed, and the results demonstrate that the proposed criterion can be potentially used to solve structural dynamic problems of MDOF systems with a more desirable numerical dispersion performance.

Analysis head injuries of Vietnamese motorcyclist without a helmet in car to motorbike frontal impact using a computer model

Nowadays, with the increasing demand for travel, the number of people using motorbikes is increasing, especially in Vietnam. People tend to face more injury risks when they are in traffic, such as vulnerable road users (VRU) – pedestrians, cyclists, and motorcyclists. Therefore, the objective of this study is to assess how car crashes influence Vietnamese motorcyclists' bodies, in particular their heads, because they are the most vulnerable parts of their bodies. The result of this study is to let people know what they’re facing in case they are hit by a car. In addition, this research analyzes the injury to the motorcyclist's head when being hit by different configurations of the car. Due to the lack of facilities, car-to-motorcyclist frontal impact simulation has become the best way to resolve this problem. The impact conditions, which were obtained from real motorcyclist accidents in Vietnam, including the speed of vehicle and motorcycle, and impact angle, were defined as initial loading conditions in a simulation of the head striking the windscreen by using a finite element Vietnamese dummy model. Logistic regression models were developed to study brain injury risk with respect to injury-related variables: the head linear acceleration and head injury criterion (HIC) value. In this paper, the deformation of the motorbike structure model was neglected, so the material has been selected as a rigid form. The knowledge from this research could be a prerequisite for developing guidelines to improve motorcyclist safety in Vietnam.

Prediction of crushed numbers and sizes of ballast particles after breakage using machine learning techniques

Modeling the breakage of ballast particles is a key task for modeling the plastic deformation of ballast subjected to several loading cycles in DEM simulations. In this study, a series of single-particle crushing tests were performed on 700 ballast particles to specify the numbers and sizes of ballast particles crushed after ballast breakage. Four classification algorithms (support vector machine (SVM), backpropagation neural network (BPNN), random forest (RF), and CatBoost (CB)) were used to predict the number of particles crushed after ballast breakage. In addition, the particle sizes were estimated using the RF, SVM, BPNN, and eXtreme Gradient Boosting (XGB) regression algorithms. The initial particle size, shape, material, and loading conditions were considered variables for regression and classification. The dataset was divided into 75% and 25% as the training and test sets, respectively. The results indicated that CB and RF-based classification, with an accuracy of more than 91%, and RF and XGB based regression, with a normalized root-mean-squared error (NRMSE) of less than 0.08, appropriately estimated the number and sizes of crushed ballast particle. Moreover, the DEM simulation of ballast breakage using the particle bonded model (PBM) validated the values predicted using the machine learning models. The proposed method can be used to simulate ballast as bonded clumps instead of bonded pebbles with an acceptable breakage modeling accuracy.

Discrete particle simulation for mixing of granular materials in ribbon mixers: A scale-up study

This work presents a numerical study of particle mixing and scale-up of ribbon mixers with four sizes (mixer A - 5.62 L, mixer B - 49.02 L, mixer C - 142.91 L, and mixer D - 482.32 L). The results show that the mixing performance becomes worse with the mixer size increasing. A correlation is proposed to predict the mixing rate as a function of the scale-up ratio and Froude number. The top-bottom initial loading condition of granular materials mix much faster than the side-side and front-back loading conditions. With the mixer size becoming larger, the total mixing time increases significantly. The power consumption per unit mass for the four mixers is in this order: mixer A > mixer D > mixer C > mixer B. The results suggest that scale-up is necessary to save mixing time and power consumption and reduce additional operating costs such as labour and down-time.

Impact of injection rate ramp-up on nucleation and arrest of dynamic fault slip

Fluid injection into underground formations reactivates preexisting geological discontinuities such as faults or fractures. In this work, we investigate the impact of injection rate ramp-up present in many standard injection protocols on the nucleation and potential arrest of dynamic slip along a planar pressurized fault. We assume a linear increasing function of injection rate with time, up to a given time t_c after which a maximum value Q_m is achieved. Under the assumption of negligible shear-induced dilatancy and impermeable host medium, we solve numerically the coupled hydro-mechanical model and explore the different slip regimes identified via scaling analysis. We show that in the limit when fluid diffusion time scale t_w is much larger than the ramp-up time scale t_c, slip on an ultimately stable fault is essentially driven by pressurization at constant rate. Vice versa, in the limit when t_c/t_w gg 1, the pressurization rate, quantified by the dimensionless ratio dfrac{Q_m t_w}{t_c Q^*} with Q^* being a characteristic injection rate scale, does impact both nucleation time and arrest distance of dynamic slip. Indeed, for a given initial fault loading condition and frictional weakening property, lower pressurization rates delay the nucleation of a finite-sized dynamic event and increase the corresponding run-out distance approximately proportional to propto left( dfrac{Q_m t_w}{t_c Q^*}right) ^{-0.472}. On critically stressed faults, instead, the ramp-up of injection rate activates quasi-static slip which quickly turn into a run-away dynamic rupture. Its nucleation time decreases non-linearly with increasing value of dfrac{Q_m t_w}{t_c Q^*} and it may precede (or not) the one associated with fault pressurization at constant rate only.

Electromyography-Assisted Neuromusculoskeletal Models Can Estimate Physiological Muscle Activations and Joint Moments Across the Neck Before Impacts.

Knowledge of neck muscle activation strategies before sporting impacts is crucial for investigating mechanisms of severe spinal injuries. However, measurement of muscle activations during impacts is experimentally challenging and computational estimations are not often guided by experimental measurements. We investigated neck muscle activations before impacts with the use of electromyography (EMG)-assisted neuromusculoskeletal models. Kinematics and EMG recordings from four major neck muscles of a rugby player were experimentally measured during rugby activities. A subject-specific musculoskeletal model was created with muscle parameters informed from MRI measurements. The model was used in the calibrated EMG-informed neuromusculoskeletal modeling toolbox and three neural solutions were compared: (i) static optimization (SO), (ii) EMG-assisted (EMGa), and (iii) MRI-informed EMG-assisted (EMGaMRI). EMGaMRI and EMGa significantly (p < 0.01) outperformed SO when tracking cervical spine net joint moments from inverse dynamics in flexion/extension (RMSE = 0.95, 1.14, and 2.32 N·m) but not in lateral bending (RMSE = 1.07, 2.07, and 0.84 N·m). EMG-assisted solutions generated physiological muscle activation patterns and maintained experimental cocontractions significantly (p < 0.01) outperforming SO, which was characterized by saturation and nonphysiological "on-off" patterns. This study showed for the first time that physiological neck muscle activations and cervical spine net joint moments can be estimated without assumed a priori objective criteria before impacts. Future studies could use this technique to provide detailed initial loading conditions for theoretical simulations of neck injury during impacts.

Effects of dose loading conditions and device geometry on the transport and aerosolization in dry powder inhalers: A simulation study

The transport and aerosolization of particles are studied in several different dry powder inhaler geometries via Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) simulations. These simulations combine Large Eddy Simulation of gas with Discrete Element Model simulation of all the carrier particles and a representative subset of the active pharmaceutical ingredient (API) particles. The purpose of the study is to probe the dominant mechanism leading to the release of the API particles and to demonstrate the value of the CFD-DEM simulations where one tracks the motion of all the carrier and API particles. Simulations are performed at different inhalation rates and initial dose loading conditions for the screen-haler geometry, a simple cylindrical tube inhaler, and five different geometry modifications that took the form of bumpy walls and baffles. These geometry modifications alter the residence time of the powder sample in the inhaler, pressure drop across the inhaler, the severity of gas-carrier interactions, and the number of collisions experienced by the carrier particles, all of which are quantified. The quality of aerosolization is found to correlate with the average air-carrier slip velocity, while collisions played only a secondary role. Some geometry modifications improved aerosolization quality with very little increase in the pressure drop across the device.

Study on Reactor Core Physics Calculation of Marine Nuclear Power Platform

The marine nuclear power platform is an organic combination of small nuclear reactor and ship engineering technology. It has the characteristics of good manoeuvrability, long on-time charging operation cycle, high power density, low operating cost, energy saving and environmental protection. In this paper, The core geometry model is built based on the design of the marine nuclear power platform reactor core. The core reactivity and control rod worth are calculated by a Monte Carlo code MCNP for this core design at first cycle, initial loading, normal temperature, and normal pressure condition. The results of the calculation are compared with nuclear design values. It shows that MCNP code is suitable for marine nuclear power platform core design calculation, and can be verified with nuclear design values.

A two-surface plasticity model for clay; numerical implementation and applications to large deformation coupled problems of geomechanics

This paper presents numerical treatments of elastoplasticity relations for a previously developed critical state two-surface plasticity model and its implementation into a bespoke finite element code as well as the commercial software Abaqus via the user defined subroutine, UMAT. The model is implemented with an efficient integration scheme based on the explicit modified Euler scheme with automatic substepping and error control. Validation of the implemented model is assessed through simulation of several laboratory tests comprising a variety of initial states and loading conditions followed by a study on the accuracy and efficiency of the integration scheme. Subsequently, the model is employed to analyse some sophisticated boundary value problems involving finite deformations, inertia effects, soil-structure interactions and saturated porous media. The constitutive model captures particular features of clay behaviour, such as the prediction of strain rate dependence, small-strain stiffness degradation, the development of residual strength at very large shear strains and stress anisotropy. The effects of these features on the behaviour of two important geotechnical problems – including pipe-seabed interaction under lateral motion and dynamically installed anchors – are specifically investigated using two advanced finite deformation schemes: one based on the Arbitrary Lagrangian Eulerian (ALE) method and another on the Particle Finite Element Method (PFEM). The study illustrates the robustness of the proposed integration scheme and successful application of the soil model, indicating that the use of such complex soil models may be useful for realistic analyses of geotechnical problems.

Pengaruh Modifikasi Penampang pada I-Girder dan Box Girder Beton Prategang terhadap Kekakuan dan Lendutan

Prestressed concrete has been widely used in structural buildings, especially for big span length purposes. The prestressed concrete dimension cross sections normally are fixed, provided by the factory based on their experience for every span length. However, this size aspect can be developed to make better improvement. In this study, I and box girder shapes were modified with the same total cross-sectional area. Three types of modification have been made for each girder shape by giving the space on the middle for I girder and changing form from trapezoidal to rectangular section for box girder. The number of steel tendons for this research was made typically and same so that the stress and displacement can be compared fairly. Manual calculation was performed for all samples and was completed under three circumstances namely initial condition, loading condition, and final condition. Also, the manual calculation is according to Indonesian provisions, which are SNI 2833-2016 for the earthquake load and SNI 1725-2016 for normal loading on bridges. From the result, it is known that one shape for each girder shape has met the criteria for the smallest stress and displacement.

Statistical analysis of defects within concrete under elevated temperatures based on SEM image

Concrete is a multiphase composite material consisting of aggregates, mortar, and initial defects. This work aims to quantitatively study the distribution and evolution of initial defects under elevated temperatures. To minimize the effect of hydration process and thermal and endogenous shrinkage, concrete samples cured in water for 12 months is tested. In order to study the effect of external load on the initial distribution of defects within concrete, concrete samples without pre-loading and pre-applied with 30% of the failure load are selected as research objects. The evolution of defects within the concrete samples are characterized using scanning electron microscopy (SEM). By employing an image processing software, the two-dimensional configurations of defects are extracted from the backscattered images obtained by SEM. Each defect is identified and approximated using an optimal ellipse. Thereafter, the defects are automatically recognized and classified into microcracks and pores by utilizing the image processing software and MATLAB programming. Consequently, the distribution and propagation of microcracks and pores in concrete could be quantitatively and separately analyzed. Statistical analysis of area, perimeter, and fitting ellipse parameters (e.g., major axis, minor axis, coordinates of the center, axis orientation, aspect ratio, and solidity) can provide the distribution of initial defects within concrete. It is demonstrated that the area of microcracks consistently increases with temperature. Log-normal and normal distributions may be suitable for the distribution of aspect ratio and solidity of microcracks, respectively, for both concrete samples with and without pre-applied loading under all elevated temperatures (40, 105, 150, 200, and 250 ℃). However, the distributions of area, coordinates of the center, and axis orientation of microcracks may vary with the initial concrete loading condition and temperature. For the pre-loaded concrete sample, the distribution of parameters does not conform to any type of distributions. Moreover, for the sample without pre-loading, the distributions of area, coordinates of the center, and axis orientation of microcracks exhibit good fitting precisions with log-normal, normal, and normal distributions, respectively at lower temperatures (40–150 ℃); however, such relationships do not apply at higher temperatures (200 and 250 ℃). As reference for identifying the variations in microstructures, 150 ℃ is selected as the threshold temperature. The statistical approach employed in this study can lay the theoretical and experimental bases for determining the microstructure evolution in concrete. It can also be used for identifying the meso-defect and macro-defect and establishing their relationship with concrete properties.

A deep neural network inverse solution to recover pre-crash impact data of car collisions

In this work, we have successfully developed a data-driven artificial intelligence (AI) inverse problem solution for traffic collision reconstruction. In specific, we have developed and implemented a machine learning computational algorithm and built a deep neural network to determine and identify the initial impact conditions of car crash based on its final material damage state and permanently deformed structure configuration (wreckage).In this work, we have demonstrated that the developed machine learning algorithm as an inverse problem solver can accurately identify initial collision conditions in an inverse manner, which are practically unique if we use permanent plastic deformation as the forensic data signatures. In other words, we think that the massive plastic energy dissipation process and the related big data will make final structure damage state insensitive to the initial car collision conditions. Thus, it provides an inverse solution for car crash forensic analysis by reconstructing the initial failure load parameters and conditions based on the permanent plastic deformation distribution of cars. This approach has general significance in solving the inverse problem for engineering failure analysis and vehicle crashworthiness analysis, which provides a key contribution for the unmanned autonomous vehicle and the related technology.

Numerical study on fatigue crack propagation behaviors in lubricated rolling contact

The surface-initiated Rolling Contact Fatigue (RCF) including pitting and micro-pitting is one of the key issues affecting the reliability of tribological components such as gears and bearings used in various devices. In this work, a surface-initiated crack Finite Element (FE) model which considers the effect of lubricant on crack faces was developed to investigate surface-initiated RCF using an automatic crack propagating Python script. Different lubricating states, initial crack parameters and loading conditions were simulated to analyze the evolution of crack propagation and the Stress Intensity Factors (SIFs). The RCF crack propagation path and life were predicted by employing the Maximum Tangential Stress (MTS) criterion coupled with the Paris’s law. A typical RCF failure is predicted in the numerical simulation. Results reveal that the lubricating pressurization dominates the surface-initiated RCF. In addition, the initial crack angle has a significant effect on the RCF crack propagation path and the fatigue life.

Effect of Bond-Line Thickness on Fatigue Crack Growth of Structural Acrylic Adhesive Joints.

With an increasing demand for adhesives, the durability of joints has become highly important. The fatigue resistance of adhesives has been investigated mainly for epoxies, but in recent years many other resins have been adopted for structural adhesives. Therefore, understanding the fatigue characteristics of these resins is also important. In this study, the cyclic fatigue behavior of a two-part acrylic-based adhesive used for structural bonding was investigated using a fracture-mechanics approach. Fatigue tests for mode I loading were conducted under displacement control using double cantilever beam specimens with varying bond-line thicknesses. When the fatigue crack growth rate per cycle, da/dN, reached 10−5 mm/cycle, the fatigue toughness reduced to 1/10 of the critical fracture energy. In addition, significant changes in the characteristics of fatigue crack growth were observed varying the bond-line thickness and loading conditions. However, the predominance of the adhesive thickness on the fatigue crack growth resistance was confirmed regardless of the initial loading conditions. The thicker the adhesive bond line, the greater the fatigue toughness.