Effect of Ornamental Stone Waste Incorporation on the Rheology, Hydration, Microstructure, and CO2 Emissions of Ordinary Portland Cement

The ornamental stone industry generates large amounts of waste thus creating environmental and human health hazards. Thus, pastes with 0–30 wt.% ornamental stone waste (OSW) incorporated into ordinary Portland cement (OPC) were produced and their rheological properties, hydration kinetics, and mechanical properties were evaluated. The CO2 equivalent emissions related to the pastes production were estimated for each composition. The results showed that the paste with 10 wt.% of OSW exhibited similar yield stress compared to the plain OPC paste, while pastes with 20 and 30 wt.% displayed reduced yield stresses up to 15%. OSW slightly enhanced the hydration kinetics compared to plain OPC, increasing the main heat flow peak and 90-h cumulative heat values. The incorporation of OSW reduced the 1-, 3-, and 28-days compressive strength of the pastes. Water absorption results agreed with the 28 days compressive strength results, indicating that OSW increased the volume of permeable voids. Finally, OSW incorporation progressively reduced the CO2 emission per m3 of OPC paste, reaching a 31% reduction for the highest 30 wt.% OSW content. Overall, incorporating up to 10 wt.% with OSW led to pastes with comparable fresh and hardened properties as comported to plain OPC paste.

A Deep Learning Approach to Design and Discover Sustainable Cementitious Binders: Strategies to Learn From Small Databases and Develop Closed-form Analytical Models

To reduce the energy-intensity and carbon footprint of Portland cement (PC), the prevailing practice embraced by concrete technologists is to partially replace the PC in concrete with supplementary cementitious materials [SCMs: geological materials (e.g., limestone); industrial by-products (e.g., fly ash); and processed materials (e.g., calcined clay)]. Chemistry and content of the SCM profoundly affect PC hydration kinetics; which, in turn, dictates the evolutions of microstructure and properties of the [PC + SCM] binder. Owing to the substantial diversity in SCMs’ compositions–plus the massive combinatorial spaces, and the highly nonlinear and mutually-interacting processes that arise from SCM-PC interactions–state-of-the-art computational models are unable to produce a priori predictions of hydration kinetics or properties of [PC + SCM] binders. In the past 2 decades, the combination of Big data and machine learning (ML)—commonly referred to as the fourth paradigm of science–has emerged as a promising approach to learn composition-property correlations in materials (e.g., concrete), and capitalize on such learnings to produce a priori predictions of properties of materials with new compositions. Notwithstanding these merits, widespread use of ML models is hindered because they: 1) Require Big data to learn composition-property correlations, and, in general, large databases for concrete are not publicly available; and 2) Function as black-boxes, thus providing little-to-no insights into the materials laws like theory-based analytical models do. This study presents a deep learning (DL) model capable of producing a priori, high-fidelity predictions of composition- and time-dependent hydration kinetics and phase assemblage development in [PC + SCM] pastes. The DL is coupled with: 1) A fast Fourier transformation algorithm that reduces the dimensionality of training datasets (e.g., kinetic datasets), thus allowing the model to learn intrinsic composition-property correlations from a small database; and 2) A thermodynamic model that constrains the model, thus ensuring that predictions do not violate fundamental materials laws. The training and outcomes of the DL are ultimately leveraged to develop a simple, easy-to-use, closed-form analytical model capable of predicting hydration kinetics and phase assemblage development in [PC + SCM] pastes, using their initial composition and mixture design as inputs.

New Long-Life Concrete Pavements in the Czech Republic

A jointed plain concrete pavement represents a reliable, historically proven technical solution for highly loaded roads, highways, airports and other industrial surfaces. Excellent resistance to permanent deformations (rutting) and also durability and maintenance costs play key roles in assessing the economic benefits, rehabilitation plans, traffic closures, consumption and recycling of materials. In the history of concrete pavement construction, slow-to-normal hardening Portland cement was used in Czechoslovakia during the 1970s-1980s. The pavements are being replaced after 40-50 years of service, mostly due to vertical slab displacements due to missing dowel bars. However, pavements built after 1996 used rapid hardening cements, resulting in long-term surface cracking and decreased durability. In order to build durable concrete pavements, slower hardening slag-blended binders were designed and tested in the restrained ring shrinkage test and in isothermal calorimetry. Corresponding concretes were tested mainly for the compressive/tensile strength evolution and deicing salt-frost scaling to meet current specifications. The pilot project was executed on a 14 km highway, where a unique temperature-strain monitoring system was installed to provide long-term data from the concrete pavement. A thermo-mechanical coupled model served for data validation, showing a beneficial role of slower hydration kinetics. Continuous monitoring interim results at 24 months have revealed small curling induced by drying and the overall small differential shrinkage of the slab.

Experimental Study of Slag Changes during the Very Early Stages of Its Alkaline Activation

The very early stages of alkaline activation of slag control its rheology and setting, but also affect its hydration, which occurs later. Simultaneously, these parameters are dictated by the nature and dose of the alkaline activator. Therefore, we investigated and compared the changes in slag particles (SEM, BET, laser diffraction), as well as in the pore solution composition (ICP–OES), pH, and conductivity, of alkali-activated slag (AAS) pastes containing the three most common sodium activators (waterglass, hydroxide, and carbonate) and water during the first 24 h of its activation. To ensure the best possible comparability of the pastes, a fairly nontraditional mixture design was adopted, based on the same concentration of Na+ (4 mol/dm3) and the same volume fraction of slag in the paste (0.50). The results were correlated with the pastes’ hydration kinetics (isothermal calorimetry), structural build-up (oscillatory rheology), and setting times (Vicat). Great differences were observed in most of these properties, in the formation of hydration products, and in the composition of the pore solution for each activator. The results emphasize the role of the anionic groups in the activators and of the pH, which help predict the sample’s behavior based on its calorimetric curve, and offer data for further comparisons and for the modelling of AAS hydration for specific activators.

A Coupled Model of Temperature and Pressure for Managed Pressure Cementing in Deep-Water Region

The narrow density window in deep-water environment brought great challenges to well drilling and completion by causing well control issues. Managed Pressure Cementing (MPC) is a new technology developed from Manage Pressure Drilling (MPD), which can precisely control the annular fluid pressure profile. Accurate calculation of wellbore temperature and pressure is the key to MPC. This paper focus on coupled models of temperature and pressure for MPC in deep-water region. The well cementing process can be divided into two stages: fluid displacement stage and cement setting stage, which displays different characteristics. During the cementing displacement stage, the cement is in a flowable slurry state and is circulated into the annulus. During this process, the rheology of fluids if effected by temperature in wellbore. On basis of the fluid rheology model, a coupled model of temperature and pressure in wellbore is established considering the transient flow characteristics during cementing displacement stage. During cement setting stage, the cement slurry stops flowing and the significant cement hydration reaction starts. A large amount of hydration heat and obvious pressure reduction can be observed. On basis of the cement hydration kinetics model, a coupled model of temperature and pressure in wellbore during cementing setting stage is established. Based on the models established in this paper, a series of numerical simulations are conducted using a deep-water well. Simulation results show that neglecting the complicated interactions between temperature and pressure can cause a big error. During the cementing displacement stage, higher temperature in the deep part of wellbore reduces the fluid viscosity, which leads to a smaller friction. On the contrary, larger friction is observed near seabed as a result of the low temperature in deep-water environment. The pressure in wellbore changes frequently due to the coexistence of multiple fluids in wellbore. Therefore, a frequent control of annular fluid pressure is required using the MPC technology. During the cement setting stage, an obvious temperature increase is observed as a result of cement hydration heat. The pressure decreases with the depending of cement hydration. An addition back pressure at wellhead has to be added using the MPC technology. The transient temperature and pressure have impact on the rate of cement hydration in turn. Cement in the deep part of wellbore have a faster rate of cement hydration. The low temperature at mudline slows the cement hydration process. Considering the complicated interactions between temperature, pressure, cement hydration and fluid rheology, coupled models between temperature and pressure based on hydration kinetics during well cementing in deep-water region is established in the manuscript. The new model established in this paper plays an important role in the MPC technology.

A Prediction Model of Pressure Loss of Cement Slurry in Deep-Water HTHP Directional Wells

The exploitations of deep-water wells often use directional well drilling to reach the target layer. Affected by special environments in deep water, the prediction of pressure loss of cement slurry is particularly important. This paper presents a prediction model of pressure loss suitable for deep-water directional wells. This model takes the complex interaction between the temperature, pressure and hydration kinetics of cement slurry into account. Based on the initial and boundary conditions, the finite difference method is used to discretize and calculate the model to ensure the stability and convergence of the result calculated by this model. Finally, the calculation equation of the model is used to predict the transient temperature and pressure loss of Wells X1 and X2, and a comparison is made between the predicted value and the monitoring data. The comparison results show that the maximum error between the temperature and pressure predicted by the model and the field measured value is within 6%. Thus, this model is of high accuracy and can meet the needs of site construction. It is concluded that this result can provide reliable theoretical guidance for temperature and pressure prediction, as well as the anti-channeling design of HTHP directional wells.