Model For Shrinkage Research Articles

Multiscale Prediction Model for Autogenous Shrinkage of early-age Concrete Incorporating High Volume Fly Ash

Multiscale Prediction Model for Autogenous Shrinkage of early-age Concrete Incorporating High Volume Fly Ash

Numerical modelling of autogenous shrinkage of rice husk ash blended cement mortar

Addition of rice husk ash (RHA) is an effective internal curing method to mitigate self-desiccation and autogenous shrinkage of hydrating cementitious materials. Although a certain number of experimental researches on this topic have been carried out, a comprehensive study about numerical simulation of mitigating effect of RHA on autogenous shrinkage of cementitious materials is still scarce. In this study, a numerical model of autogenous shrinkage of rice husk ash blended cement mortar was proposed. The proposed numerical model was based on Pickett model and improved by taking visco-elastic behaviour of rice husk ash blended cementitious materials into account. Final setting time, chemically bound water, compressive strength, internal relative humidity (RH) and autogenous shrinkage of pure Portland cementitious materials and rice husk ash blended cementitious materials were experimentally studied. Liquid absorption capacity and water vapour desorption isotherm of rice husk ash were also measured. The comparison between the simulated and measured autogenous shrinkage showed that the autogenous shrinkage of rice husk ash blended cement mortar can be predicted accurately with the proposed numerical model.

A time-series deep learning model for predicting concrete shrinkage and creep verified with in-situ and laboratory test data

This paper proposed a time series prediction method for concrete shrinkage and creep based on deep learning and the accuracy of the method was verified by field tests. Based on the experiment data in the Northwestern University (NU database), a deep learning model considering the material, environment, and history was constructed by integrating Gated Recurrent Units and Self-Attention mechanism (GSA model). To validated the model, short-term indoor and outdoor field tests of concrete shrinkage and creep were conducted. The proposed GSA model outperformed the LSTM model for both creep and shrinkage predictions. Moreover, the comparison between the GSA model prediction and the outdoor test data indicated that the model can accurately capture the real-time outdoor temperature and humidity variation through historical data. To predict the ten-year shrinkage and creep of concrete, a recursive multi-step method was proposed to extrapolate the short-term predictions of the GSA model. The effectiveness of the recursive multi-step method was validated against the long-term test data in the NU database. Overall, the proposed GSA model demonstrated high accuracy in both short-term and long-term predictions.

Semi-empirical model for rubber shrinkage and debonding in solid rocket motors

Semi-empirical model for rubber shrinkage and debonding in solid rocket motors

Experimental and numerical study on the mitigation of autogenous shrinkage of cementitious material

This study experimentally investigated the effects of surfactants and water-repelling agents on the hydration process, relative humidity, and mechanical properties of Portland cement pastes. Based on the measurement results, the degree of hydration, degree of saturation, capillary tension of autogenous shrinkage, and magnitude of autogenous shrinkage were simulated using a numerical model. In the numerical model, the elastic and creep components of autogenous shrinkage were calculated separately, and the creep component was simulated based on the solidification theory. The simulation results indicated that adding admixtures led to lower degrees of hydration and saturation. The capillary tension of the pure Portland cement was larger than that of the other mixtures. This can be attributed to several factors, including the smaller surface tension of mixtures with surfactants, larger contact angle of mixtures with water-repelling agents, and a lower degree of hydration of mixtures with both admixtures. Analyses of the simulated and measured results for different mixtures also show that creep plays an indispensable role in autogenous shrinkage. Adding a surfactant and a water-repelling agent can effectively mitigate autogenous shrinkage. However, when an excessive amount of water-repelling agent was added, its influence on the mitigation of autogenous shrinkage was insignificant.

Phase field modeling and computation of vesicle growth or shrinkage.

We present a phase field model for vesicle growth or shrinkage induced by an osmotic pressure due to a chemical potential gradient. The model consists of an Allen-Cahn equation describing the evolution of the phase field parameter that describes the shape of the vesicle and a Cahn-Hilliard-type equation describing the evolution of the ionic fluid. We establish conditions for vesicle growth or shrinkage via a common tangent construction using free energy curves. During the membrane deformation, the model ensures total mass conservation of the ionic fluid, and we weakly enforce a surface area constraint of the vesicle. We develop a stable numerical scheme and an efficient nonlinear multigrid solver to evolve the phase and concentration fields, and we use this to evolve the fields to near equilibrium for 2D vesicles. Convergence tests confirm an [Formula: see text] accuracy for our scheme and near-optimal convergence for our multigrid solver. Numerical results reveal that the diffuse interface model captures the main features of cell shape dynamics: for a growing vesicle, there exist circle-like equilibrium shapes if the concentration difference across the membrane and the initial osmotic pressure are large enough; while for a shrinking vesicle, there exists a rich collection of finger-like equilibrium morphologies.

Coupled Pore Relative Humidity Model for Concrete Shrinkage and Creep

Coupled Pore Relative Humidity Model for Concrete Shrinkage and Creep

LASSO and attention-TCN: a concurrent method for indoor particulate matter prediction.

Long time exposure to indoor air pollution environments can increase the risk of cardiovascular and respiratory system damage. Most previous studies focus on outdoor air quality, while few studies on indoor air quality. Current neural network-based methods for indoor air quality prediction ignore the optimization of input variables, process input features serially, and still suffer from loss of information during model training, which may lead to the problems of memory-intensive, time-consuming and low-precision. We present a novel concurrent indoor PM prediction model based on the fusion model of Least Absolute Shrinkage and Selection Operator (LASSO) and an Attention Temporal Convolutional Network (ATCN), together called LATCN. First, a LASSO regression algorithm is used to select features from PM1, PM2.5, PM10 and PM (>10) datasets and environmental factors to optimize the inputs for indoor PM prediction model. Then an Attention Mechanism (AM) is applied to reduce the redundant temporal information to extract key features in inputs. Finally, a TCN is used to forecast indoor particulate concentration in parallel with inputting the extracted features, and it reduces information loss by residual connections. The results show that the main environmental factors affecting indoor PM concentration are the indoor heat index, indoor wind chill, wet bulb temperature and relative humidity. Comparing with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) approaches, LATCN systematically reduced the prediction error rate (19.7% ~ 28.1% for the NAE, and 16.4% ~ 21.5% for the RMSE) and improved the model running speed (30.4% ~ 81.2%) over these classical sequence prediction models. Our study can inform the active prevention of indoor air pollution, and provides a theoretical basis for indoor environmental standards, while laying the foundations for developing novel air pollution prevention equipment in the future.

Modelling of thermal shrinkage of seamless steel pipes using artificial neural networks (ANN) focussing on the influence of the ANN architecture

This paper presents two main novel findings. (1) The first finding is the development of an artificial neural network (ANN) model for thermal shrinkage of seamless steel pipes, which represents a new application for ANNs. Mill operators need such fast and accurate models to predict the final pipe outer diameter at ambient temperature based on the hot state immediately after rolling. The goal of this work was to lower the reject rate. However, small relative changes in the diameter are currently difficult to predict by using conventional ANNs. Therefore, a more sensitive target variable and a modified ANN architecture were applied to solve this problem. Data for training and validation were obtained from measurements on a hot-rolling mill. (2) The second finding is based on an investigation performed to determine the number of hidden neurons affected the model response, considering the data used. The knowledge obtained helps to determine the most suitable number of hidden neurons and to prevent overfitting. No generally accepted solution to these problems had previously been proposed in the literature. Consequently, this paper significantly supplements current research studies that describe applications of ANNs.

Statistical Evaluation of CEB-FIP 2010 Model for Concrete Creep and Shrinkage.

An extensive experimental database consisting of 2838 shrinkage data points and 3598 creep data points is used to evaluate the accuracy of the newly proposed CEB-FIP 2010 model in predicting the creep and shrinkage of concrete structures. To study the applicability of the model for high-strength concrete in general environments, the database was developed by only retaining the test data of concrete components with the average compressive strength greater than 30 MPa and the relative humidity in the test environment less than 95%. On this basis, combined with the B3 and CEB variation coefficient methods, the paper mainly adopts the residual method to assess the accuracy of the CEB-FIP 2010 model and compare it with the previous model, CEB-FIP 1990. The influences of several properties, such as the compressive strength, the age of concrete, the relative humidity, and the component size on the prediction accuracy of these two models are further studied. The results show that for the CEB-FIP 2010 model within the time interval of 0-9000 days, 52% and 48% of the shrinkage strain residuals of the total specimens are located in the negative and positive regions, respectively, while the positive and negative regions of the CEB-FIP 1990 model account for 73% and 27%, demonstrating the CEB-FIP 2010 model has better performance in predicting shrinkage strain than the CEB-FIP 1990 model, whereas the two models have comparable accuracy in predicting creep compliance. The CEB-FIP 2010 model is more reliable for considering the effects of compressive strength, relative humidity, and age at loading on shrinkage and creep than for considering the effect of member size.

Mortar film thickness on the autogenous shrinkage of concrete: Test and simulation

Coarse aggregate (CA) accounts for the largest volume in concrete, which has significant impact on the performance of this building material such as workability, strength and shrinkage. Based on the determination of specific surface area for CA through simple sieving curve, mortar film thickness (MFT) of fresh concrete is numerically calculated. Relationship between MFT and CA content is acquired as three-stage model with critical volume fractions of 17% and 67%. Autogenous shrinkage of concrete with various CA volume fractions were experimentally evaluated through integrated shrinkage test devices. Zero-time of autogenous shrinkage is determined based on the expansion-shrinkage behavior of concrete mixtures at very early age. The ultimate autogenous shrinkage of concrete decreases monotonously with increasing amount of CA or decrease in MFT. By comparing to existing theoretical and empirical models, new prediction model of autogenous shrinkage based on MFT is proposed with high correlation coefficient for concrete containing various CA content.

Effect of temperature rise inhibitor on early-age behavior and cracking resistance of high strength concrete under uniaxial restrained condition

Temperature rise inhibitor (TRI) is used to modify the cement hydration and reduce the heat release of high strength concrete (HSC). Many investigations on the mechanical properties, temperature process, and autogenous shrinkage of cement-based materials with TRI have been conducted. However, the evaluation of the early-age behavior and cracking resistance of HSC with TRI under uniaxial restrained condition considering the effects of temperature, shrinkage, restrained stress, and tensile creep simultaneously was rarely conducted. Temperature stress test machine, which could measure these factors simultaneously, was used to investigate the effect of TRI contents on the early-age behavior and cracking resistance of HSC in this research. The peak temperature, temperature rising rate, autogenous shrinkage, and tensile creep decreased with increasing TRI contents. The addition of TRI improved the early-age cracking resistance of HSC. A modified stress-strain failure criterion and a prediction model for autogenous shrinkage of HSC with TRI were proposed.

Early Age Shrinkage and Mechanical Effect of Ultra-High-Performance Concrete Composite Deck: A Case Study with In Situ Test and Numerical Simulation.

For the Honghe Bridge project located in Yunnan Province, Southwest China, a steel/ultrahigh-performance concrete (UHPC) composite deck is used in the suspension bridge with a 700 m main span, and the steel stud connectors are used in the 50 mm–thick UHPC layer. To investigate the shrinkage behavior of UHPC and the relevant influence, the in situ time-dependent strain is measured continuously, and within the 20-day curing time, the material behavior is summarized based on test results. This paper proposes a prediction model for UHPC shrinkage which is refined from the widely used B3 model for normal concrete material, and the parameter values are modified and optimized by experimental comparison. Combining the numerical model and the finite element analysis model of the composite deck, the detailed mechanical state in structural parts is studied. For the practical construction, the simulation results indicate that the small thickness of UHPC above the stud and weak bond strength can influence the eventual structural performance greatly. In the discussion of stress distribution at different locations of the deck, the potential crack on the edge and the corner of the UHPC–steel interface and the mechanical damage on the stud connector around are also indicated.

Experimental study and prediction model for non-uniform shrinkage of recycled aggregate concrete in composite slabs

This paper investigates the influence of coarse recycled aggregate (CRA) on the non-uniform shrinkage of concrete with a single surface exposed to the air. A 210 d experiment was conducted on 17 slabs made with recycled aggregate concrete (RAC), measuring the shrinkage strain distribution through the slab depth. The parameters considered included the replacement ratios of CRA, slab depths, and the moisture-transferring boundary conditions (MTBC). The internal relative humidity distribution through the slab depth was monitored to verify the reasonableness of the occurrence of the non-uniform shrinkage. Based on the test results, a prediction model for the non-uniform shrinkage of RAC with a single surface exposed to the air was established and validated. Based on the age-adjusted modulus method, a cross-sectional analysis was conducted on the long-term strains of composite slabs using the proposed model. The investigation results indicated that (1) the incorporation of recycled aggregate significantly increased the shrinkage gradient by 84%−102%; (2) the influence of recycled aggregate on the shrinkage distribution of single-surface exposed concrete increased with a decrease in slab depth; and (3) the proposed equations can accurately predict the non-uniform shrinkage of single-surface exposed RAC.

How Does Population Shrinkage Affect Economic Resilience? A Case Study of Resource-Based Cities in Northeast China

By constructing an index system, this study analyzed the temporal and spatial characteristics of the economic resilience of 20 resource-based cities in northeast China after the financial crisis in 2008. On this basis, a mediation model was introduced to explore the mechanism of population shrinkage affecting economic resilience. The results show that: (a) from 2009 to 2019, the trend of the economic resilience of resource-based cities in northeast China was “ascending–descending–stable”. As time went by, the spatial difference of the economic resilience of resource-based cities gradually became obvious, indicating that the number of medium- and high-class cities was increasing. (b) By applying a correlation analysis, it was found that both a significant weak correlation and medium correlation existed between population shrinkage and economic resilience during the periods of 2011–2019 and 2013–2019. (c) Six mediation factors, namely industrial output, population consumption, resource dependence, urban innovation, cultural construction and environment quality, were chosen to apply the mediation model of population shrinkage affecting economic resilience. Among them, industrial output, population consumption, urban innovation, and cultural construction exerted a partial mediation effect on the process of population shrinkage affecting economic resilience, while the meditation effects of resource dependence and environment quality were not significant.

Novel thermomechanical characterization for shrinkage evolution of unidirectional semi-crystalline thermoplastic prepregs (PPS/CF) in melt, rubbery and glassy states

Shrinkages, distortions and high residual stresses in the thermoplastic composite parts are induced due to high processing temperature, anisotropy, and fiber–matrix shrinkage mismatch. In this paper the shrinkages have been investigated experimentally and modeled by thermo-mechanical constitutive equations for PolyPhenylene Sulfide (PPS) and the unidirectional Carbon Fiber (PPS/CF) composite prepreg. The thermal shrinkage and the crystallization shrinkage were retrieved from Thermal Mechanical Analysis and compared to a Pressure specific volume Temperature diagram. To describe the crystallization shrinkage in the cooling process accurately, the crystallization kinetics of PPS was evaluated using Differential Scanning Calorimetry. The temperature-dependent elastic modulus was measured by a shear rheometer to formulate a new constitutive model. The mathematical model for shrinkage was validated by a press consolidated [0]12 laminate and unbalanced laminates in four lay-ups. The thermo-mechanical model results presented here provide significant rules for the thermomechanical and shrinkage predictions for the industrial applications of thermoplastic composite.

Effect of Graphene Oxide on Chemical Shrinkage Behavior of Cement-Based Composite Paste

As a new type of nano carbon material, graphene oxide (GO) has attracted extensive attention in the academic field over recent years due to its abundant oxygen-containing functional groups and large specific surface area, which can improve the microstructure and mechanical properties of cement-based materials. However, the effect of GO on the chemical shrinkage of cement-based materials remains unclear. Therefore, in this study, to reveal the chemical shrinkage characteristics of GO/cement composite paste (GO/CP), the chemical shrinkage of cement-based composite paste with different water/cement ratios (0.32, 0.42, and 0.52), different mass fractions of GO (0 wt%, 0.01 wt%, 0.03 wt%, and 0.05 wt%), and different mass fractions of polycarboxylate superplasticizer (PC) (0 wt%, 0.02 wt%, and 0.03 wt%) were measured using the volumetric method. The results showed that the chemical shrinkage of GO/CP increases significantly with the increasing water/cement ratio. The addition of PC appeared to compound GO/CP chemical shrinkage, showing a trend of first augmenting and then reducing with the increasing PC content. For the same water/cement ratio, the chemical shrinkage of the GO/CP specimen was lower than that of the normal cement paste (NCP). When the GO content reached the range of 0.03 wt%–0.05 wt%, the shrinkage value reached the minimum; and when the water/cement ratio was 0.42, the growth rate of chemical shrinkage of the GO/CP specimen in the middle and late hydration processes was significantly larger than that of NCP The analysis revealed that the regulating effect of GO on cement-based materials is mainly reflected in the refinement of the pore structure and bonding behavior of the hydration product Ca(OH)2. In addition, to determine the influence of GO and PC on chemical shrinkage of GO/CP, the existing model for chemical shrinkage of NCP was modified and the functions K(ξ, t) and P(λ, t) were introduced as impact parameters, after which a suitable prediction model for chemical shrinkage of GO/CP was established by curve fitting. This study provides a theoretical basis for improving the performance of cement-based materials and clarifying the function mechanism of GO.

Stability analysis of discrete population balance model for bubble growth and shrinkage

AbstractThe stability condition for solving the population balance equation (PBE) involving bubble growth and shrinkage within the Eulerian framework is proposed. The particle flux weighted average Courant number, , which reflects the propagation of particle state of the entire size classes on internal coordinates is first derived. Stability conditions of internal convection for PISO and PIMPLE algorithms are obtained by evaluating a series of tests concerning the constant bubble growth. The proposed stability conditions are then applied to simulate two kinds of laboratory experiments, that is, the bubble growth in stagnant liquid and condensing steam‐water pipe flows. The results show that the stable PBE solutions hold for the cases using either PISO or PIMPLE algorithms combined with the corresponding stability condition. Meanwhile, the conservation of the zeroth and first moments of the number density function can be guaranteed when the stability condition is satisfied. In addition, the effect of heat transfer coefficient correlations is also discussed.

Study on maintenance time based on deterioration prediction model of main girder

With the increasing number of bridges in Shanxi Province, the difficulty and complexity of bridge maintenance and management tasks have increased significantly. In this paper, based on the existing prediction model, combined with the characteristics of local heavy traffic and large temperature difference environment, the prediction model of concrete carbonation, girder cracking, prestress loss and concrete shrinkage and creep is established. According to the linear law of deterioration curve, the best maintenance time of girder suitable for local characteristics is determined, which can provide guidance for later maintenance management of bridge.

A viscous sintering model for pore shrinkage in packings of cylinders

A viscous sintering model for pore shrinkage in packings of cylinders