Characteristics and Performance of Cement Modified–Base Course Material in Western Australia

Hydrated Cement Treated Crushed Rock Base (HCTCRB) is produced by adding 2% Portland cement (by mass) to a standard crushed rock base (CRB) at an optimum moisture condition. The unique production process for HCTCRB is different from that of a common cement-treated base in that a re-mixing process is performed after the hydration of cement, preventing cementitious bonding to maintain the unbound material characteristics with an improvement in material engineering properties. This paper presents the resilient modulus (MR) and permanent deformation (PD) characteristics of HCTCRB after variable hydration periods, water addition during compaction and dryback. The difference in material hydration periods affected the performance of HCTCRB. However, in this study, a consistent performance trend with various hydration periods could not be found. Moisture contents have major influence on the properties of HCTCRB. The results indicate that a higher moisture content gives a more increase in PD and a more decrease in MR of this material. Addition of more water during compaction caused inferior PD and MR performance even though the samples achieved a higher dry density. A dryback process to achieve a dryer condition can improve material performance. After samples were subjected to a dryback process, it was found that samples prepared by adding water during compaction showed a decrease in material performance comparing to samples that were compacted without additional water. Thus, the amount of water addition to mixes during compaction must be controlled

Recycled Concrete Aggregates in Roadways: A Laboratory Examination of Self-Cementing Characteristics

This paper examines the self-cementing phenomenon of the road construction material known as recycled concrete aggregate (RCA). Two RCA types were selected as study materials: (1) high-grade RCA (HRCA), a quality RCA manufactured from relatively high-strength concrete structures; and (2) road base RCA (RBRCA), a high-grade RCA blend combined with brick and general clean rubble (road base material). Laboratory tests were performed to obtain the unconfined compressive strength, indirect tension dynamic modulus, and resilient modulus of the test samples to examine their hardening characteristics when subjected to varying curing periods. These tests were performed in conjunction with microstructure analyses from X-ray diffractometry (XRD) and scanning electron microscope (SEM) techniques. The HRCA samples, which were prepared and subjected to varying curing conditions, transformed from an initially unbound material into a bound (fully stabilized) material. The results of XRD and SEM analyses clearly demonstrate that secondary hydration occurred. The RBRCA samples were able to maintain their unbound granular properties, with nonsignificant self-cementing, thus supporting the hypothesis that the mixing of nonactive materials such as bricks and clean rubble into RCA will lessen the tendency of RCA toward self-cementing

Parameterization and prediction of nanoparticle transport in porous media : a reanalysis using artificial neural network

The continuing rapid expansion of industrial and consumer processes based on nanoparticles (NP) necessitates a robust model for delineating their fate and transport in groundwater. An ability to reliably specify the full parameter set for prediction of NP transport using continuum models is crucial. In this paper we report the reanalysis of a data set of 493 published column experiment outcomes together with their continuum modeling results. Experimental properties were parameterized into 20 factors which are commonly available. They were then used to predict five key continuum model parameters as well as the effluent concentration via artificial neural network (ANN)-based correlations. The Partial Derivatives (PaD) technique and Monte Carlo method were used for the analysis of sensitivities and model-produced uncertainties, respectively. The outcomes shed light on several controversial relationships between the parameters, e.g., it was revealed that the trend of math formula with average pore water velocity was positive. The resulting correlations, despite being developed based on a “black-box” technique (ANN), were able to explain the effects of theoretical parameters such as critical deposition concentration (CDC), even though these parameters were not explicitly considered in the model. Porous media heterogeneity was considered as a parameter for the first time and showed sensitivities higher than those of dispersivity. The model performance was validated well against subsets of the experimental data and was compared with current models. The robustness of the correlation matrices was not completely satisfactory, since they failed to predict the experimental breakthrough curves (BTCs) at extreme values of ionic strengths

Potential use of engineered nanoparticles in ocean fertilization for large-scale atmospheric carbon dioxide removal

Artificial ocean fertilization (AOF) aims to safely stimulate phytoplankton growth in the ocean and enhance carbon sequestration. AOF carbon sequestration efficiency appears lower than natural ocean fertilization processes due mainly to the low bioavailability of added nutrients, along with low export rates of AOF-produced biomass to the deep ocean. Here we explore the potential application of engineered nanoparticles (ENPs) to overcome these issues. Data from 123 studies show that some ENPs may enhance phytoplankton growth at concentrations below those likely to be toxic in marine ecosystems. ENPs may also increase bloom lifetime, boost phytoplankton aggregation and carbon export, and address secondary limiting factors in AOF. Life-cycle assessment and cost analyses suggest that net CO2 capture is possible for iron, SiO2 and Al2O3 ENPs with costs of 2–5 times that of conventional AOF, whereas boosting AOF efficiency by ENPs should substantially enhance net CO2 capture and reduce these costs. Therefore, ENP-based AOF can be an important component of the mitigation strategy to limit global warming

Viscoelastic gels of guar and xanthan gum mixtures provide long-term stabilization of iron micro- and nanoparticles

Iron micro- and nanoparticles used for groundwater remediation and medical applications are prone to fast aggregation and sedimentation. Diluted single biopolymer water solutions of guar gum (GG) or xanthan gum (XG) can stabilize these particles for few hours providing steric repulsion and by increasing the viscosity of the suspension. The goal of the study is to demonstrate that amending GG solutions with small amounts of XG (XG/GG weight ratio 1:19; 3 g/L of total biopolymer concentration) can significantly improve the capability of the biopolymer to stabilize highly concentrated iron micro- and nanoparticle suspensions. The synergistic effect between GG and XG generates a viscoelastic gel that can maintain 20 g/L iron particles suspended for over 24 h. This is attributed to (i) an increase in the static viscosity, (ii) a combined polymer structure the yield stress of which contrasts the downward stress exerted by the iron particles, and (iii) the adsorption of the polymers to the iron surface having an anchoring effect on the particles. The XG/GG viscoelastic gel is characterized by a marked shear thinning behavior. This property, coupled with the low biopolymer concentration, determines small viscosity values at high shear rates, facilitating the injection in porous media. Furthermore, the thermosensitivity of the soft elastic polymeric network promotes higher stability and longer storage times at low temperatures and rapid decrease of viscosity at higher temperatures. This feature can be exploited in order to improve the flowability and the delivery of the suspensions to the target as well as to effectively tune and control the release of the iron particle

Changes in the nanoparticle aggregation rate due to the additional effect of electrostatic and magnetic forces on mass transport coefficients

The need may arise to be able to simulate the migration of groundwater nanoparticles through the ground. Transportation velocities of nanoparticles are different from that of water and depend on many processes that occur during migration. Unstable nanoparticles, such as zero-valent iron nanoparticles, are especially slowed down by aggregation between them. The aggregation occurs when attracting forces outweigh repulsive forces between the particles. In the case of iron nanoparticles that are used for remediation, magnetic forces between particles contribute to attractive forces and nanoparticles aggregate rapidly. This paper describes the addition of attractive magnetic forces and repulsive electrostatic forces between particles (by 'particle', we mean both single nanoparticles and created aggregates) into a basic model of aggregation which is commonly used. This model is created on the basis of the flow of particles in the proximity of observed particles that gives the rate of aggregation of the observed particle. By using a limit distance that has been described in our previous work, the flow of particles around one particle is observed in larger spacing between the particles. Attractive magnetic forces between particles draw the particles into closer proximity and result in aggregation. This model fits more closely with rapid aggregation which occurs between magnetic nanoparticles.Ministry of Education of the Czech Republic of the Technical University in Liberec [7822]; Ministry of Education of the Czech Republic [FR-TI1/456]; Ministry of Industry and Trad