Instantaneous Model Research Articles

A Neural Network and Generalized Predictive Control Framework for Urban Traffic System Optimal Perimeter Control

Optimal perimeter control is one of the effective control technologies to alleviate urban congestion, which is based on macroscopic fundamental diagrams (MFDs). However, most previous optimal perimeter control methods used a linearization model at the desired point to approximate a nonlinear MFDs system, which is vulnerable to causing a potential mismatch between the linearization model and the environmental dynamics. However, this mismatch often leads to performances degradation. To solve this problem, this paper uses a neural network trained from data to approximate the complex nonlinear urban traffic system globally. To facilitate the design and control, this framework linearizes the nonlinear neural network of the traffic system to an instantaneous linearization model. The optimal perimeter control problem is finally solved by generalized predictive control (GPC) with the instantaneous linearization model. A key advantage of the proposed framework is that the global instantaneous linearization model is more accurate than the linearization model around the desired point. Simulation results show that the proposed framework significantly alleviates congestion and reduces the total travel time spent (TTS) in the traffic system compared with no control, “greedy” feedback control and PID control.

Instantaneous amplitude and phase signal modeling for harmonic removal in wind turbines

We present a novel approach to harmonic disturbance removal in single-channel wind turbine acceleration data by means of time-variant signal modeling. Harmonics are conceived as a set of quasi-stationary sinusoids whose instantaneous amplitude and phase vary slowly and continuously in a short-time analysis frame. These non-stationarities in the harmonics are modeled by low-degree time polynomials whose coefficients capture the instantaneous dynamics of the corresponding waveforms. The model is linear-in-parameters and is straightforwardly estimated by the linear least-squares algorithm. Estimates from contiguous analysis frames are further combined in the overlap-add fashion in order to yield overall harmonic disturbance waveform and its removal from the data. The algorithm performance analysis, in terms of input parameter sensitivity and comparison against three state-of-the-art methods, has been carried out with synthetic signals. Further model validation has been accomplished through real-world signals and stabilization diagrams, which are a standard tool for determining modal parameters in many time-domain modal identification algorithms. The results show that the proposed method exhibits a robust performance particularly when only the average rotational speed is known, as is often the case for stand-alone sensors which typically carry out data pre-processing for structural health monitoring. Moreover, for real-world analysis scenarios, we show that the proposed method delivers consistent vibration mode parameter estimates, which can straightforwardly be used for structural health monitoring.

CalBMP, a web-based modeling tool for evaluating pesticide offsite movement and best management practice scenarios in California agricultural land

Quantitative evaluation of best management practice (BMP) effectiveness can help stakeholders to make better watershed management decisions. However, such evaluations are always challenging as they require complex algorithms to simulate the relevant hydrological processes, crop growth and the corresponding pollutant transport pathways in order to evaluate potential BMPs and select the best one for the specific field conditions. In this study, a web-based interface (CalBMP) was developed to predict BMP effectiveness in California, focusing on pesticide modeling at the field scale. With built-in databases for soil, weather, crop, pesticides, and BMPs, users can run simulations for baseline and BMP scenarios using their site-specific field conditions by simply providing the field information, such as zip code, soil, crop management, and pesticide application data. CalBMP uses PRZM5 + , a USEPA model, to simulate pesticide transport and fate at the field edge. The CalBMP simulations were validated based on measurements from an alfalfa field study. The results indicated that the CalBMP interface could reasonably simulate the runoff and adsorbed pesticide loss leaving the field with default parameters from previously known field parameters or public databases. CalBMP underestimated sediment erosion, possibly due to uncertainties in field measurements or inaccurate simulation of the temporal distribution of flood irrigation. CalBMP is likely to underestimate pesticides with greater solubility, such as diuron, because PRZM5 + uses the simplified instantaneous equilibrium sorption model. In addition, a strawberry field study was adopted to demonstrate the capability of the CalBMP interface for simulating BMP effectiveness (pesticide reduction percentage in the main pathways) with easy-to-understand graphs and tables. The results indicated that users can easily compare and review the results from multiple scenarios, which could facilitate the decision-making process for mitigating the amount of active ingredient bifenthrin leaving the field. The CalBMP tool provides useful information on pesticide runoff potential and BMP selection at the field scale. With increasingly stringent regulations for water quality protection, CalBMP will add to the growers’ toolbox for minimizing the environmental impacts from their inevitable pesticide usage.

Comprehensive Identification of Driving Style Based on Vehicle's Driving Cycle Recognition

The driving style of human automobile drivers plays a vital role in vehicle energy management and driving safety. Human drivers often exhibit different driving styles during different driving cycles. Moreover, short-term driving behaviors cannot accurately reflect their comprehensive driving styles. Thus, a comprehensive driving style identification model, based on driving cycle recognition, is proposed in this study. The model was developed to comprehensively assess and more accurately identify long-term driving styles. First, the characteristic parameters of the driving cycle and style are selected and calculated, and the dimensions of the data collected from real vehicles are minimized through principal component analysis (PCA). Second, a two-stage clustering algorithm based on the particle swarm optimization K-means optimized by the genetic algorithm (GA-PSO-K-means) is used to obtain the type labels of driving cycles and styles to ensure the stability of the clustering algorithm. Third, an artificial neural network (ANN) is utilized to build the instantaneous recognition model of the driving cycle and style. Based on this, a comprehensive driving style identification model is built using the analytic hierarchy process(AHP). Finally, the bench and real vehicle tests are used to verify that the proposed model is accurate and effective.

Dynamics and energy harvesting performance of a nonlinear arc-cylinder type dielectric elastomer oscillator under unidirectional harmonic excitations

To harvest vibration energy, a nonlinear arc-cylinder type dielectric elastomer oscillator (ADEO), which has greater advantages than the VI DEG in vibration environments, is proposed. We first study the dynamic behaviors and the energy harvesting (EH) performance of the ADEO subjected to unidirectional harmonic excitations. The energy harvester, which consists of a hollow arc cylinder, two pairs of straight cylindrical frames, two dielectric elastomer membranes (DEMs) and an inner free moving ball, can convert vibration energy into electricity. The dynamic and electrical analysis models of the ADEO system are developed under the unidirectional harmonic excitation. Two impact models are verified by experimental results and are compared with each other, and the instantaneous impact model with computational efficiency and accuracy is selected. The rich dynamic behaviors of the ADEO system under diverse parameters, including the excitation amplitude and frequency, the tilt angle, the impact angle and the radius of the curvilinear motion of the ball, are fully investigated through two kinds of bifurcation diagrams and 3-D frequency spectrums. The effects of these parameters on the system EH performance are also studied. The research results show that the system EH performance can be enhanced by appropriately adjusting these parameters. This work can not only help guide the design and optimization of the ADEO system under the unidirectional vibration, but also lay the foundation for the design and optimization of the system in the bidirectional vibration environment.

A Constitutive Model of Time-Dependent Deformation Behavior for Sandstone

Considering sandstone's heterogeneity in the mesoscale and homogeneity in the macroscale, it is very difficult to describe its time-dependent behavior under stress. The mesoscale heterogeneity can affect the initiation and propagation of cracks. Clusters of cracks have a strong influence on the formation of macroscale fractures. In order to investigate the influence of crack evolution on the formation of fractures during creep deformation, a time-dependent damage model is introduced in this paper. First, the instantaneous elastoplastic damage model of sandstone was built based on the elastoplastic theory of rock and the micro-heterogeneous characteristics of sandstone. A viscoelastic plastic creep damage model was established by combining the Nishihara model and the elastoplastic damage constitutive model. The proposed models have been validated by the results of corresponding analytical solutions. To help back up the model, some conventional constant strain rate tests and multi-step creep tests were carried out to analyze the time-dependent behavior of sandstone. The results show that the proposed damage model can not only reflect the time-dependent viscoelastic deformation characteristics of sandstone, but also provide a good fit to the viscoelastic plastic deformation characteristics of sandstone's creep behavior. The damage model can also reproduce the propagation process of mesoscopic cracks in sandstone upon the damage and failure of micro-units. This research can provide an effective tool for studying the propagation of microscopic cracks in sandstone.

Geodynamic, geodetic, and seismic constraints favour deflated and dense-cored LLVPs

Two continent-sized features in the deep mantle, the large low-velocity provinces (LLVPs), influence Earth's supercontinent cycles, mantle plume generation, and geochemical budget. Seismological advances have steadily improved LLVP imaging, but several fundamental questions remain unanswered, including: What is the true vertical extent of the buoyancy anomalies within these regions? And, are they purely thermal features, or are they also compositionally distinct? Here, we address these questions using a comprehensive range of geophysical observations. The relationship between measured geoid anomalies and long-wavelength dynamic surface topography places an important upper limit on the vertical extent of large-scale, LLVP-related density anomalies at ∼900 km above the core-mantle boundary (CMB). Instantaneous mantle flow modelling suggests that anomalously dense material must exist at their base to simultaneously reproduce geoid, dynamic topography, and CMB ellipticity observations. We demonstrate that models incorporating this dense basal layer are consistent with independent measurements of semi-diurnal Earth tides and Stoneley mode splitting functions. Our thermodynamic calculations indicate that the presence of early-formed, chondrite-enriched basalt in the deepest 100–200 km of the LLVPs is most compatible with these geodynamic, geodetic, and seismological constraints. By reconciling these disparate datasets for the first time, our results demonstrate that, although LLVPs are dominantly thermal structures, their basal sections likely represent a primitive chemical reservoir that is periodically tapped by upwelling mantle plumes.

Modelling of fracture intensity increase due to interacting blast waves in three-dimensional granitic rocks

The complexity of the physics of rock blasting is a longstanding modelling challenge. This work presents in detail a three-dimensional, material non-linear finite element based model for wave propagation, combined with a postprocessing procedure to determine the fracture intensity caused by blasting. The rock is described with the Johnson–Holmquist-2 constitutive model, an elastoplastic-damage model designed for brittle materials undergoing high strain rates and high pressures and fracturing; it is also combined with an instantaneous tensile failure model. Additionally, material heterogeneity is introduced into the model through variation of the material properties at the element level, ensuring jumps in strain. A detailed algorithm for the combined Johnson–Holmquist-2 and tensile failure model is presented and is demonstrated to be energy-conserving, and is complemented with an open-source MATLABTM implementation of the model. A range of sub-scale numerical experiments are performed to validate the modelling and postprocessing procedures, and a range of materials, explosive waves and geometries are considered to demonstrate the model’s predictive capability quantitatively and qualitatively for fracture intensity. Fracture intensities on 2D planes and 3D volumes are presented. The mesh dependence of the method is explored, demonstrating that mesh density changes maintain similar results and improve with increasing mesh quality. Damage patterns in simulations are self-organising, and form thin, planar, fracture-like structures that closely match the observed fractures in the experiments. The presented model is an advancement in realism for continuum modelling of blasts as it enables fully three-dimensional wave interaction, handles damage due to both compression and tension, and relies only on measurable material properties.

Digital-holography efficiency measurements using a heterodyne-pulsed configuration

A digital-holography (DH) system is created in a heterodyne-pulsed configuration, meaning that the reference and signal pulses are nondeterministically correlated in time. Using the off-axis image plane recording geometry, two performance metrics are measured: (1) the total-system efficiency and (2) the ambiguity efficiency. These metrics are compared against the same measured efficiencies for a DH system in a homodyne-pulsed configuration, which uses deterministically correlated reference and signal pulses. The total-system efficiency of both systems is found to be consistent with one another, showing that no new component efficiencies are required when switching from a homodyne- to a heterodyne-pulsed configuration. Additionally, an instantaneous phase modulation model is used to characterize system performance in terms of nonideal pulse overlap. Such a model validates the use of the ambiguity efficiency for future efforts.

Instantaneous prediction of irregular ocean surface wave based on deep learning

Ocean surface wave environment due to its randomness has mostly been analyzed and understood from a statistical way. Accurate and reliable wave prediction is the basic guarantee for ocean transportation and offshore operation. However, the significant nonlinearity of the ocean surface wave in real sea will result in a simulation and prediction challenge. To solve the problem, this paper proposes a Deep Learning instantaneous prediction model based on a Convolutional Neural Network-Long Short Term Memory model (CNN-LSTM) and wavelet function proven as the activation function of the neural network model to strengthen the fitting of the nonlinear mapping relationship between waves appearing in two successive different time periods. And the results shows that the wavelet activation function has better generalization ability than the traditional activation function for irregular wave data. In the numerical verification test, the two-parameter spectrum of International Towing Tank Conference (ITTC) and the combined model of extreme wave and random wave are used to simulate the irregular wave. The standardized time series of free surface elevation is made into a data set for model training and verification. In order to improve the performance of the model as accurate as possible, main parameters of the model are investigated in this paper. The optimal parameters are obtained and the model tuning suggestion is developed for future studies.

Preventing Crack in an Aluminum Alloy Complex Structure during Welding Process Based on Numerical Simulation Technology

Aluminum alloy structures are widely used for weight reduction in aviation, shipbuilding, rail vehicles and automotive industries. Fusion welding technology is one of the most important joining methods for lightweight structure assembly due to its advantages such as flexibility in design, high production efficiency, and low cost. However, the local centralized heating during fusion welding inevitably produces residual stress and welding deformation. For actual engineering structures, if the product design is unreasonable or the external restraint is inappropriate, the transient stress or residual stress become a key factor resulting in cracking during the assembly process. In the current study, an effective computational approach was developed based on the MSC Marc software to simulate transient and residual stress fields for complex aluminum alloy structures during the welding process. In the developed computational approach, according to the location and arrangement of welding lines, an instantaneous heat source model was used to replace the traditional moving heat source model, and as a result significanlty improved the calculation efficiency to meet actual engineering needs. The welding stresses, including transient and residual stress, of an A6061 aluminum alloy complex structure were calculated by the developed numerical simulation technology. The simulation results indicated that the cracking was produced by excessive transient stress during welding process. Subsequently, the effect of external restraint intensity on welding stress at the key location was examined numerically. Based on the simulation results, measures to reduce welding stress and cracking risk were put forward based on adjusting the external restraint intensity.

Study on kinematic characteristics of the vertical-wheel on hybrid PDC bit

Aiming at improving the ROP of PDC bits in hard-to-drill formation, a new hybrid PDC bit with vertical-wheel is proposed in this paper, furtherly, the kinematic characteristics of the vertical-wheel are researched. Firstly, the coordinate system of the vertical-wheel is established, on basis of which the motion equation, the speed equation and the acceleration equation of the vertical-wheel is derived. Secondly, a series of unit rock-breaking experiments on the vertical-wheel with variable parameters are carried out, so that the average speed of vertical-wheel under different conditions is obtained and the theoretical model of average speed is established, furthermore, the influence of diameter and normal angle of the wheel on the average speed is analyzed. Thirdly, the speed of vertical-wheel under different conditions is measured on basis of the speed model with compensation coefficient, specifically, the calculated average speed of the Ø18 mm vertical-wheel according to the instantaneous speed model is 4.532 r/s, while the average speed obtained in experiment is 4.491 r/s, with an error of 0.9%, proving that the measuring method and modeling of the instantaneous speed are credible. Lastly, the theoretical conditions for continuous rotation of the wheel are obtained. The research results are of great significance to study the working mechanism of the vertical-wheel and provide technical support for the application of the hybrid PDC bit with vertical-wheels.

Bifurcation and chaos analysis of mold splicing zone vibration under thermal-mechanical coupling

To improve the machining quality of the splicing area of the hardened steel mold, this paper proposes a bifurcation and chaos analysis method for the milling vibration of the splicing area of the mold under the coupled thermal-mechanical effect. First, based on the instantaneous milling force model at the splice, the milling dynamics equations of a two-degree-of-freedom rectangular spliced mold part are established. By applying the Galerkin method, the resulting nonlinear partial differential equation is reduced to a single-degree-of-freedom nonlinear system. Meanwhile, by using the Melnikov function method, the criteria for chaos motion are obtained by the Smale horseshoe mapping. Then, the fourth-order Runge-Kutta algorithm is applied to solve the bifurcation diagram, largest Lyapunov exponent diagram, displacement waveform diagram, and phase plane diagram of the nonlinear dynamic system in the mold splicing area. Subsequently, the influence of spindle speed and cutting depth on the nonlinear vibration system in the mold splice area is quantitatively analyzed. Finally, the effect of spindle speed and cutting depth on the vibration system of the workpiece is investigated through experiments. The obtained results indicate that the milling vibration amplitude in the rectangular splicing mold area can be controlled more easily and effectively by changing the cutting depth than by changing the spindle speed.

How accelerating the electrification of the van sector in Great Britain can deliver faster CO2 and NOx reductions

As a major emission contributor with significant growth potential, the light goods vehicles (vans) play an important part in achieving net-zero. In 2020 the UK government committed to phasing out sales of new internal combustion engine (ICE) vans by 2030, but the impact of the policy and how far are we to decarbonize the entire van fleet by 2050 is unclear. This paper investigates the CO2 and NOx emission trends in the van sector in Great Britain under the 2030 ICE phase-out. ECCo model11http://www.element-energy.co.uk/sectors/low-carbon-transport/project-case-studies/ is used to forecast the future van population by powertrain. The annual van mileage is estimated based on the van activity survey22https://www.gov.uk/government/statistics/van-statistics-2019-to-2020. The instantaneous emission model PHEM, NAEI emissions inventory and remote sensing measurements are used to parameterize real-world driving emission factors of CO2 and NOx. Scenarios have been set out to assess the impact of enablers and barriers affecting the pace of emission reductions. Results suggest vans are on track to reach the tailpipe net-zero target by 2050 under all scenarios, and the speed of NOx reduction is even faster. A rapid transition to battery electric vans in the early to mid-2020s will significantly lower CO2, with associated estimated monetary benefits of £1.3 billion.

Electrochemical properties of Bi2Se3 layers semiconductor elaborated by electrodeposition

• Bismuth selenide (Bi 2 Se 3 ) thin films with nanoparticles was electrodeposited from a nitric bath. • The electrodeposition mechanism of Bi 2 Se 3 alloy into ITO substrate is three-dimensional instantaneous nucleation. • The reaction of Bi 2 Se 3 deposition is quasi-reversible controlled by the diffusion process, with the diffusion coefficient D of Bi and Se in the Bi 2 Se 3 system are 1.756 10 -7 cm 2 s -1 and 0.196 10 -7 cm 2 s -1 , respectively. • The interesting properties of the resulting Bi 2 Se 3 make it a relevant material for future developments in photovoltaics and optoelectronics. The semiconductor, Bi 2 Se 3 layers was electrochemically deposited on Indium Tin Oxide substrate (ITO) from a nitric acid, Bi (NO 3 ) 3 ·5H 2 O and H 2 SeO 3 solution. The results of the electrochemical behavior of Bi 2 Se 3 were as follows: Cyclic voltammetry (CV) studies revealed that the electrodeposition of Bi 2 Se 3 was performed at a negative potential of −0.22 V vs SCE, according to a quasi-reversible reaction controlled by the diffusion process. Chronoamperometry (CA) showed that the electrodeposition of Bi 2 Se 3 follows a 3D instantaneous nucleation model with diffusion-controlled growth. X-ray diffraction analysis indicated that the resulting layers at −0.22 V vs SCE exhibited a Rhombohedral Bi 2 Se 3 structure with a preferred orientation (1 1 3) and the 2:3 stoichiometric ratio of Bi and Se was checked by EDS quantitative analysis. SEM images revealed the formation of a uniform size mainly consisting of nanoparticles with spherical shapes. The Bi 2 Se 3 obtained layers are n -type semiconductors with an optical band gap of 2.35 eV.

3-D quantitative seismic imaging of tectonically-influenced Middle-Eocene carbonates stratigraphic traps of SE-Asian basins using spectral decomposition: Implications for hydrocarbon exploration

Carbonates form energetic stratigraphic petroleum systems. The tectonic uplifting and subsidence significantly affect the overall reservoir configurations. During these stratigraphic scenarios, the prediction of accurate thickness for subsidence and uplifting zones becomes challenging. The band-limited seismic data interpretation tools fail to detect the zones of thinning and thickening of sediments along with uplifting and subsidence. The band-limited seismic does not have the tuning frequency, that can be used to predict the accurate vertical thickness of the thin-bedded carbonates. The constant wavelet-based transformation tool (WT) and inverted reservoir simulations have robust implications for the quantification of any depositional system. Especially, when the reservoir is shallow marine, the application of WT has resolved a variety of stratigraphic traps in terms of their seismic and sedimentological aspects. The stratigraphic traps are comprised of thin beds, which are not resolvable on conventional seismic. These traps require a specific tuning frequency, which is the key ingredient for the prediction of oil and gas inside them and can only be obtained by the implementation of the WT tool. Therefore, the WT, static stratigraphic thickening wedge models (SSTWM), and WT–based instantaneous spectral thickness modeling (ISTM) tools are applied on a gas field in Indus Basin, Pakistan. The 43-Hz CWT images the densely fractured and faulted network within the shoal reservoir limestone lenticular lens (SRLL) with an aerial extent of 208 km2 in southwest-northeast orientations. The band-limited attributes revealed poor imaging of sub-surface carbonate systems. The 43-Hz wavelet-based SSTWM predicts a 15-m-thick coarse-grained SRLL along subsidence and a 12-m-thick fine-grained SRLL along uplifting zones. Post-stack processing at 43-Hz CWT tuning frequency predicts the 18 and 10 m thick sediments for SRLL along the subsidence and uplifting zone. The ISTM predicts a thickness of 31 m during subsidence within the SRLL and 14 m for uplifting zones. The 43-Hz tuning frequency-based processing at ISTM predicts enhanced thicknesses of 41 and 18 m for subsiding and uplifting sediments that are trapped inside the shoal limestone petroleum systems. The quantitative visualization of AI with the predicted thicknesses at ISTM has provided robust clues for imaging the internal stratigraphic architecture of the SRLL. The linear regression analysis remained a very successful tool for assessing the quantitative aspects of SRLL with a strong R2 > 0.95, which has implicated the real-time imagining of sea-level fall and rise. Only post-stack seismic data processing at 43-Hz found a very effective exploration tactic in predicting the enhanced thicknesses, and lateral continuity of the reservoir, and improved the S/N by removing the tuning effect of ambiguous lithology/fluids, which have accurately predicted the exact location along the subsidence zones. This workflow can act as an analogue stratigraphic exploration of remaining gas fields within Asian Basins and similar geological settings.

Quantum and quasi-classical effects in the strong field ionization and subsequent excitation of nitrogen molecules.

The processes leading to the N2 + lasing are rather complex and even the population distribution after the pump laser excitation is unknown. In this paper, we study the population distribution at electronic and vibrational levels in N2 + driven by ultra-short laser pulse at the wavelengths of 800 nm and 400 nm by using the quantum-mechanical time-domain incoherent superposition model based on the time-dependent Schrödinger equation and the quasi-classical model assuming instantaneous ionization injection described by density matrix. It is shown that while both models provide qualitatively similar results, the quasi-classical instantaneous ionization injection model underestimates the population inversions corresponding to the optical transitions at 391 nm, 423 nm and 428 nm due to the assumption of quantum mixed states at the ionization time. A fast and accurate correction to this error is proposed. This work solidifies the theoretical models for population at vibrational states in N2 + and paves the way to uncover the mechanism of the N2 + lasing.

Instantaneous Torque Modeling and Torque Ripple Reduction Strategy for Flux Modulated Doubly-Salient Reluctance Motor Drives

In this article, a novel instantaneous electromagnetic torque modeling technique and current component distribution strategy are proposed for torque ripple reduction in three-phase flux modulated doubly-salient reluctance motor (FMDRM) drives. First, the analytical model of the instantaneous electromagnetic torque of a three-phase FMDRM is established, where the contributions of current components and harmonic inductance components are considered. The generation mechanisms of the average torque and torque ripple components are investigated in detail. Furthermore, based on the analytical instantaneous electromagnetic torque model, a simplified current component distribution strategy is proposed to further reduce the torque ripple of the FMDRM. Taking the torque ripple minimization as the optimization objective, the current advanced angle is optimized and the corresponding current component distribution strategy is carried out to reduce the torque ripple. The magnetic circuit saturation effect is also taken into account. Compared to the conventional scheme, the control freedom degree of the three-dimensional current controller in the FMDRM drive is fully utilized and the torque ripple of the FMDRM can be significantly reduced without the sacrifice of output torque capability and system efficiency. Experimental results are carried out on a three-phase 12/8 FMDRM prototype to verify the effectiveness of the proposed control strategy.

Diffusion resisting performance of concrete modified with sodium methyl silicate in saline soil area

• A new type of concrete mixed 2.4% sodium methyl silicate was prepared. • An instantaneous diffusion model of chloride ions in concrete was proposed. • The diffusion reducing performance of the new concrete were compared against ordinary concrete. • A useful means for the corrosion resistance of tunnel lining was proposed. Concrete of tunnel lining in saline soil area is subjected to compound salt attacks, which decrease the service life of tunnel. In this study, a new type of concrete mixed 2.4 % sodium methyl silicate was prepared to improve the compound salt damage resistance of concrete. The properties of the concrete, including chloride diffusion resisting performance, compressive strength, and water absorption, were investigated. The results showed that the chloride diffusion resisting performance of the concrete modified with methyl sodium silicate was notably better than that of normal concrete in compound salt solution. The maximum compressive strength had not changed significantly compared with normal concrete, while the occurrence of peak strength was delayed by about 30 days. The water absorption of the concrete modified with sodium methyl silicate was reduced by 21.09 % compared with the normal concrete. Moreover, chloride diffusion resisting mechanism of the concrete immersed in compound salt solution was elucidated. Furthermore, based on the Fick’s second law and experimental results, a time-varying diffusion model for predicting the chloride ion mass fraction of chloride in the concrete was proposed in this paper. The proposed approach is a useful means for the chloride diffusion resisting of concrete in some saline soil area of Western China.

Numerical simulation of residual stress of butt-welded joint involved in complex column-beam welded structure

The objective of this work is to clarify the effect of the structural restraint and the adjacent welded joints in column-beam welded structure on the final residual stress distribution and its evolution process of the butt-welded joint between the diaphragm and the flange through numerical simulation method. Based on ABAQUS software, a three dimensional thermal-mechanical coupled method was developed to predict the residual stress distribution for multi-pass welded joints. To improve calculation efficiency, an effective computational approach that combines a relatively coarse mesh design and an instantaneous heat source model was proposed to analyze the residual stress distribution for complex welded structures. Firstly, both a fine mesh model with moving heat source and a relatively coarse mesh model with instantaneous heat source were employed to predict the residual stress distribution in the same thick-plate butt-welded joint made of high strength low alloy steel. The computational accuracy of the proposed computational method was verified through comparing the results of the fine mesh model with moving heat source and the corresponding experimental data. Then, the residual stress distributions of the column-beam welded structure, the butt-welded joint under structural restraint condition and free state were calculated using the proposed computational approach. Results suggest that the structural restraint and the adjacent welded joints in the structure have a significant effect on the residual stress distribution.