Showing papers in "International Journal of Advances in Engineering Sciences and Applied Mathematics in 2017"

Development of ductile cementitious composites incorporating microencapsulated phase change materials

Abstract: In the past two decades, much research has been devoted to overcoming the inherent brittleness of cementitious materials. To that end, several solutions have been proposed, mainly utilizing fibres. One of the most promising classes of materials is strain hardening cementitious composite (SHCC). It utilizes PVA fibres, and it is relatively costly compared to regular concrete, so it is commonly used only in surface layers. In this paper, a multi-functional ductile cementitious composite based on SHCC has been developed. It uses microencapsulated phase change materials (PCMs), capable of reducing temperature fluctuations in the material due to their high heat of fusion. It is shown that, although addition of microencapsulated PCMs are detrimental to compressive strength, they have very little effect on the flexural strength and deflection capacity. In the future work, mixtures with higher PCM contents will be developed in order to exploit their heat storage capability better. This material has potential to reduce temperature effects on concrete surfaces, while at the same time being extremely ductile.

Imaging water ingress into concrete using electrical resistance tomography

Abstract: This paper investigates the feasibility of imaging the movement of water into partially saturated concrete using electrical resistance tomography (ERT). With this technique, the spatial distribution of electrical resistance within the concrete sample was acquired from 4-point electrical measurements obtained on its surface. As the ingress of water influences the electrical properties of the concrete, it is shown that ERT can assist in monitoring and visualising water movement within concrete. To this end, the difference-imaging technique was used to obtain a qualitative representation of moisture distribution within concrete during the initial 20-h absorption. It is shown that the technique also enables the influence of surface damage to be studied.

Using X-ray fluorescence to assess the chemical composition and resistivity of simulated cementitious pore solutions

Abstract: Ionic transport in concrete can be described using the formation factor, which is the ratio of the resistivity of the concrete and the pore solution resistivity. The pore solution resistivity may be assumed, directly measured, or computed from the pore solution composition. This paper describes an experimental investigation aimed at determining the feasibility of using X-ray fluorescence (XRF) to obtain the alkali concentrations of the pore solution which enable the calculation of pore solution resistivity. In order to do this, simulated pore solutions containing known amounts of sodium and potassium were prepared and analyzed using XRF. XRF was performed on two sample types: (1) the simulated solutions and (2) beads where the water from the solution is evaporated and the remaining material is fused using a fluxing agent. The compositions obtained experimentally from XRF are compared to known compositions to demonstrate the accuracy of the technique. In addition, the measured simulated pore solution resistivity was compared to the simulated pore solution resistivity calculated from XRF measurements. The results indicate that the composition had an average error of 0.50% while the estimated simulated pore solution resistivity had an average error of 10.95%. The results of this study indicate that XRF has the potential to be an alternative to the time consuming methods currently used to measure the composition of the pore solution.

Hamiltonian coupling of electromagnetic field and matter

Abstract: Reversible part of evolution equations of physical systems is often generated by a Poisson bracket. We discuss geometric means of construction of Poisson brackets and their mutual coupling (direct, semidirect and matched pair products) as well as projections of Poisson brackets to less detailed Poisson brackets. This way the Hamiltonian coupling of transport of mixtures with electrodynamics is elucidated.

Can the dual-permeability model be used to simulate unsaturated moisture flow in damaged mortar and concrete?

Abstract: Moisture is one of the main contributors to the majority of the deterioration processes that occur in reinforced concrete structures. Moisture ingress, very often, occurs in unsaturated concrete structures. In addition, some level of damage is usually present in structural concrete, for example, due to mechanical or environmental loading. Therefore, for a more accurate service life prediction of reinforced concrete structures, methods for modeling unsaturated flow in damaged cement-based materials are needed. Previous works have shown that the classical isothermal unsaturated flow modeling fails to adequately describe the long-term moisture ingress in damaged cement-based materials since this method of modeling neglects air diffusion/dissolution and does not explicitly account for the matrix-fracture interaction. In the present paper we (1) investigate whether the dual-permeability modeling approach can be used to more accurately model unsaturated moisture flow in damaged cement-based materials especially at later stages of moisture ingress, (2) propose methods of obtaining the transport modeling parameters of the fracture phase that cannot be directly measured, and (3) propose a model for moisture transfer coefficient across matrix-fracture interface and discuss the effect of this parameter on the results. We compare the results of dual-permeability and classical isothermal modeling against experimental results for damaged mortar and concrete. Finally, we discuss modeling challenges that may arise in applications of the dual-permeability model in simulating unsaturated moisture flow in damaged mortar and concrete.

Modeling chloride ingress in concrete with thermodynamically calculated chemical binding

Abstract: An alternative approach is developed to incorporate chloride binding/release processes during modeling of ingress of external chlorides in concrete through the use of thermodynamic modeling of chemical reactions. Transport of chloride in concrete is modeled through transient finite element analysis. At each time marching step, the chloride binding/release reactions are modeled using thermodynamic calculations. For this purpose, an open-source thermodynamic modeling software is used to model all possible reactions within the cementitious matrix including the reactions of chlorides with unhydrated and hydrated cementitious materials. The predictive ability of thermodynamic calculations is presented by comparing them with experimental data. The proposed and traditional modeling approaches for chloride transport with binding are compared. Finally, a parametric investigation is presented to demonstrate some of the strengths of the proposed approach using thermodynamic calculations over the traditional approach using binding isotherms to simulate chloride ingress in concrete.

Using social media for classifying actionable insights in disaster scenario

Abstract: Micro-blogging sites are important source of real-time situational information during disasters such as earthquakes, hurricanes, wildfires, flood etc. Such disasters cause miseries in the lives of affected people. Timely identification of steps needed to help the affected people in such situations can mitigate those miseries to a large extent. In this paper, we focus on the problem of automated classification of disaster related tweets to a set of predefined categories. Some example categories considered are resource availability, resource requirement, infrastructure damage etc. Proper annotation of the tweets with these class information can help in timely determination of the steps needed to be taken to address the concerns of the people in the affected areas. Depending on the information category, different feature sets might be useful for proper identification of posts belonging to that category. In this work, we define multiple feature sets and use them with various supervised classification algorithms from literature to study the effectiveness of our approach in annotating the tweets with their appropriate information categories.

Numerical simulations of permeability of plain and blended cement pastes

Abstract: The durability of a concrete structure is principally dependent on its permeability, which governs the rate of transport of fluid through the concrete pore network. This paper presents a numerical model based on the lattice Boltzmann method (LBM) to calculate the saturated permeability of cement pastes, including blended cement pastes, wherein cement is replaced partially by an inert filler. The LBM uses a discretized form of the Boltzmann equation to simulate the pressure-gradient induced flow of a fluid through a porous microstructure. The accuracy of the algorithms implemented in the LBM are verified against analytical solutions of permeability of simple geometries. A microstructural model is used to generate three dimensional (3D) microstructures of cement pastes. The effects of liquid-to-solid ratio (l/s), degree of hydration of cement (DOH), filler content, and physical properties of the cement and filler (e.g., PSD: particle size distribution, affinity towards nucleation of hydrates on their surfaces) are evaluated. The simulations are verified against experimental measurements and numerically derived values of permeability published in literature. Results obtained from the simulations show that in both plain and blended pastes, the permeability increases and decreases monotonically, though in a nonlinear manner, over several orders of magnitude, in relation to the effective capillary porosity and the DOH, respectively. At equivalent DOHs, pastes consisting of finer anhydrous (i.e., cement or filler) particles have lower permeability compared to those prepared with coarser particles. This is attributed to the improved packing of finer particles at the time of mixing, which increases the likelihood of 3D percolation of solid phases and, ultimately, results in a higher connected volume of solid phases and a poorly connected capillary pore space within the microstructure. It is shown that in blended pastes, those prepared using a filler with a greater affinity towards nucleation and growth of hydrates on their surfaces have a higher volume of percolated solid phases, and, hence, lower permeability.

Reconstruction of missing data in multivariate processes with applications to causality analysis

Abstract: Recovery of missing observations in time-series has been a century-long subject of study, giving rise to two broad classes of methods, namely, one that reconstructs data and the other that directly estimate the statistical properties of the data, largely for univariate processes. In this work, we present a data reconstruction technique for multivariate processes. The proposed method is developed in the framework of sparse optimization while adopting a parametric approach using vector auto-regressive (VAR) models, where both the temporal and spatial correlations can be exploited for efficient data recovery. The primary purpose of recovering the missing data in this work is to develop a directed graphical or a network representation of the multivariate process under study. Existing methods for data-driven network reconstruction are built on the assumption of data being available at regular intervals. In this respect, the proposed method offers an effective methodology for reconstructing weighted causal networks from missing data. The scope of this work is restricted to linear, jointly stationary multivariate processes that can be suitably represented by VAR models of finite order and missing data of the random type. Simulation studies on different data generating processes with varying proportions of missing observations illustrate the efficacy of the proposed method in recovering the multivariate signals and thereby reconstructing weighted causal networks.

Analytical procedures for design of strain softening and hardening cement composites

Abstract: Fiber reinforced concrete (FRC) can be designed to exhibit pronounced ductility, energy absorption capacity, post-cracking strength depending on the fiber type and volume fraction. FRC have been classified into two categories, namely, strain softening and strain hardening cement composites (SSCC and SHCC). SSCC and SHCC are ultra-ductile class of materials developed for applications in the large material volume usage in the cost sensitive construction industry. Strain hardening behavior can be obtained by adding relatively low volume (typically <2%) of randomly distributed fibers and demonstrates a well formed distributed crack system. Mechanical properties under uniaxial tensile, flexural, and shear tests indicate superior performance such as tensile strength as high as 25 MPa, and strain capacity of 1–8%. Development of proper design and analysis tools are very essential to fully utilize these materials. Several approaches are presented in this paper for analysis, simulation, back-calculation, and design of strain softening and strain hardening cement composite systems, and are applicable to all classes of SSCC and SHCC such as steel fiber reinforced concrete, textile reinforced concrete, and ultra-high performance fiber reinforced concrete.

Estimating fracture toughness of C–S–H using nanoindentation and the extended finite element method

Abstract: In this paper, an approach to integrating nanoindentation testing and finite element simulations is introduced to compute the fracture toughness of cementitious materials. Calcium silicate hydrate (C–S–H) was synthesized using the standard procedure of mixing calcium oxide (CaO) and silicate (SiO2) at a mixture ratio of 1.5. C–S–H powder was filtered, dried to a relative humidity of 11%, and then compacted at 400 MPa. Nanoindentation tests incorporating dwell time were performed on polished C–S–H specimens using a Berkovich indenter tip. The reduced elastic moduli of the C–S–H specimens were extracted from the nanoindentation measurements. Viscoelastic and viscoelastic-plastic finite element models with creep and cracking capabilities were developed to simulate the nanoindentation tests and to extract the fracture energy. The viscoelastic-plastic model utilized the extended finite element method (XFEM) to describe cracking and evaluate the cracking surface of C–S–H. The analysis showed that the proposed approach could fairly predict the fracture energy release rate and thus fracture toughness of C–S–H. The calculated fracture toughness was in agreement with the fracture toughness values reported in the literature.

Managing longitudinal exposure of socially shared data on the Twitter social media

Abstract: On most online social media sites today, user-generated data remains accessible to allowed viewers unless and until the data owner changes her privacy preferences. In this paper, we present a large-scale measurement study focused on understanding how users control the longitudinal exposure of their publicly shared data on social media sites. Our study, using data from Twitter, finds that a significant fraction of users withdraw a surprisingly large percentage of old publicly shared data—more than 28% of 6-year old public posts (tweets) on Twitter are not accessible today. The inaccessible tweets are either selectively deleted by users or withdrawn by users when they delete or make their accounts private. We also found a significant problem with the current exposure control mechanisms—even when a user deletes her tweets or her account, the current mechanisms leave traces of residual activity, i.e., tweets from other users sent as replies to those deleted tweets or accounts still remain accessible. We show that using this residual information one can recover significant information about the deleted tweets or even characteristics of the deleted accounts. To the best of our knowledge, we are the first to study the information leakage resulting from residual activities of deleted tweets and accounts. Finally, we propose two exposure control mechanisms that eliminates information leakage via residual activities. One of our mechanisms optimize for allowing meaningful social interactions with user posts and another mechanism aims to control longitudinal exposure via anonymization . We discuss the merits and drawbacks of our proposed mechanisms compared to existing mechanisms.

Flow of blood in micro-channels: recent results based on mixture theory

Abstract: Blood, composed of red blood cells (RBCs), white blood cells, platelets and plasma, is a non-linear fluid exhibiting complex behavior, such as plasma-skimming and the Fahraeus effect, which are observed especially in microscale applications. In this paper, we use Mixture Theory to model blood as a two-fluid (two-component) system. Plasma is treated as a viscous fluid and the RBCs are modeled as a nonlinear fluid with a shear dependent viscosity, with the effect of the hematocrit included. The drag force and the shear lift force between the RBCs and plasma are also accounted for. We present an overview of our recent studies which show very good agreement between our numerical results and available experimental results.

The significance of pore liquid pressure and disjoining pressure on the desiccation shrinkage of cementitious materials

Abstract: There are several conflicting opinions in the literature concerning the significance and role of bulk pore liquid pressure and disjoining pressure on the desiccation shrinkage of cementitious materials. While the applicability of the Kelvin–Laplace equation in fine pores (due to the unstable nanosized meniscus) has been questioned by some, disjoining pressure has been advocated to be the primary mechanism driving desiccation shrinkage in cementitious materials. In order to elucidate the proper contribution and understanding of these two mechanisms, a thermodynamics-based mechanistic approach has been utilized here to derive expressions for both the bulk liquid pressure and the disjoining pressure. The validity of the poromechanical approach to modeling shrinkage of a porous body has also been examined. It has been concluded that the determination of pore liquid pressure via the Kelvin–Laplace equation does not require the presence of a stable meniscus and is applicable to nanosized pores. As such, the pore liquid pressure is found to be the primary mechanism associated with the desiccation shrinkage of cementitious materials. While disjoining pressure does not induce any change in the bulk liquid stress during drying, it plays a significant role in counterbalancing the liquid pressure in the thin film separating the vapor phase from the pore wall, which justifies poromechanical shrinkage models that consider pressurization to occur only in the portion of the pores containing bulk pore liquid.

Modeling the mechanical behavior of crystallizable shape memory polymers: incorporating temperature-dependent viscoelasticity

Abstract: Shape memory polymers (SMPs) are soft active materials that have an ability to retain a temporary shape, and revert back to their original shape when triggered by a suitable stimulus, typically an increase in temperature. These materials are finding wide use in a variety of fields such as biomedical and aerospace engineering; hence it is important to model their mechanical behavior. Crystallizable shape memory polymers (CSMPs) is an important subclass of SMPs, and their temporary shape is fixed by a crystalline phase, while return to the original shape is due to the melting of this crystalline phase. In our earlier work, we have studied the mechanical behavior of CSMPs within a mechanical setting by considering the original amorphous network above the recovery temperature as a hyperelastic material. In this article, we extend our earlier work to incorporate the temperature-dependent viscoelasticity into the developed constitutive model to study the mechanical behavior of CSMPs. The viscoelastic behavior of the polymers at high temperature is simulated through a rate type model. Furthermore, the model of the semi-crystalline polymer after the onset of crystallization is developed based on the mixture theory and the theory of “multiple natural configurations”. In addition, we have applied the model to a specific boundary value problem, namely uniaxial extension. The shape memory cycles of the CSMPs under different stretch rates have been studied. The results are consistent with what has been observed in experiments.

On some practical issues concerning the implementation of Cahn–Hilliard–Navier–Stokes type models

Abstract: Suspensions, solutions and colloids are physical systems that can be generally denoted as “multicomponent systems” or “mixtures”. Physical systems of this type are frequently met in many industrial applications which rises the need for numerical simulations of the behaviour of such complex systems. A particular practical example of such system is glass/tin/nitrogen system that must be studied in modelling of the float glass process (Pilkington process) that partly motivated this research. The aim of this paper is to discuss the numerical challenges along with some practical issues concerning the implementation of a chosen Cahn–Hilliard–Navier–Stokes type model that showed up to be particularly suitable for the description of three-component systems. The discretization of the system of governing partial differential equations is based on the finite element method using the FEniCS Project. Numerical experiments carried out in two and three spatial dimensions verify our straightforward implementation that uses parallel direct sparse solvers to resolve the intermediate linear systems of algebraic equations. Possible improvements of the current implementation are briefly outlined within the paper.

Remarks on continuum theory of mixtures: editorial to special issue on mixture theory

Abstract: Models based on mixture theory allow for a systematic study of the response of mixtures by considering the responses of individual constituents and their interactions. Several classical models and their generalizations can be derived consistently from continuum theory of mixtures using special constitutive assumptions and approximations. In this paper some intriguing applications, where mixture theory approach is applied under different settings, are discussed. The need and scope for experimental design and measurement techniques for validation of mixture models is also discussed. A brief note on the boundary conditions and mathematical issues concerning the numerical simulations is made.

Predicting fly ash dosages to prevent ASR by introducing the concrete prism test (CPT) chemical index model

Abstract: This study modifies the chemical index model (Malvar and Lenke in ACI Mater J 103(5):319–326, 2006) to predict the fly dosage needed to mitigate ASR (alkali-silica reaction) based on concrete prism test (CPT) expansion data. The utility of such a model (known as the CPT chemical index model) is that it reduces a two-year long test (CPT) to a calculation. Over eighty CPT data points of different aggregate, cement, and fly ash combinations from different literature sources were collated to create a model to predict the fly ash dosage (on a mass basis) necessary to prevent ASR. The CPT chemical index model developed from this study is slightly conservative for Class F fly ashes (0–10% greater replacement than actual) and conservative for Class C fly ashes (0–15% greater replacement than actual). The Standard Error of the Regression is 0.1614. Despite the presence of a relatively large Standard Error of the Regression, the conservative values of this model show promise for predicting ASR expansions with Class F fly ahes.

Prediction of esophageal cancer using demographic, lifestyle, patient history, and basic clinical tests

Abstract: An early detection of a disease can save many lives but it is impractical to undergo all medical tests for many prevalent diseases. Further these tests are costly, painful, time consuming and may have side effects. We have tried to predict esophageal cancer using demographics, lifestyle, medical history information, and basic clinical tests initially and later removed all clinical tests one after another to study the change of the accuracy without these clinical tests. It is well studied that no single classification technique turns out to be best for all the problems. Here, we test Naive Bayes classification, random forests, support vector machines (SVM) and logistic regression (LR), which perform similarly when all tests are used. However, as we reduce the number of tests, naive versions of these classifiers perform worse than kernelized versions of SVM and LR. We test our methodology with electronic medical record (EMR) of 3500 patients (approx.). The four methods described above, demonstrate a high accuracy with all features, including basic clinical test and show very low accuracy without the basic clinical tests measured by medical practitioner (MP). LR with a polynomial feature transformation of degree three yields an accuracy of 100% (approx), even without the MP features. Further dropping clinical tests one after another we see a decline in the accuracy of detection to 96%. We have also observed high sensitivity to 100% which indicates that no real patients are undetected in this experiment.