Videos, Webinars & More

Portland Cement Association’s Roadmap to Carbon Neutrality by 2050 lays out the cement and concrete industry’s commitment to a lower carbon future and how that will be attained. This effort includes both current and emerging technologies to reduce CO2 while continuing to serve the needs of designers, builders, and owners. Today, after decades of research and use in other parts of the world, portland-limestone cements (PLCs) are being embraced by the US and Canada as a ready-to-implement change to lower concrete’s initial CO2 footprint.

To reduce the carbon footprint of the Portland cement (PC) industry, the prevailing practice is to partially replace the PC in concrete with supplementary cementitious materials (SCMs). Each SCM, owing to its distinctive chemical composition and molecular structure, affects hydration kinetics and microstructural evolution of cementitious binders uniquely. Current computational models cannot produce reliable predictions of hydration kinetics of complex [PC + SCM] binders. In the past two decades, the combination of Big data and machine learning (ML) has emerged as a promising tool to produce predictions for material properties. This study employs ML models to produce predictions of hydration kinetics of PC replaced by various SCMs at different replacement levels. However, ML cannot produce highly reliable predictions of hydration kinetics of [PC + SCM] binders because it is hard for ML to completely learn highly nonlinear correlations from a small database. To enhance prediction accuracy, we introduce two methods – Fourier transformation and phase boundary nucleation model – to reduce the degree of complexity of the database, which allows ML to produce highly reliable predictions. Furthermore, thermodynamic constraints derived from thermodynamic criteria are applied to inform and guide the ML model.

This is a recorded webinar from May 21, 2019. The presentation provides a general overview of performance-based specifications. A review of the state of prescription in a sampling of project specifications will be first discussed. An approach to implement performance-based specifications consistent with ACI Codes and specifications will be outlined.

As the knowledge, testing and experience of using synthetic macrofiber reinforced concrete continues to grow for use in infrastructure projects, their successful use and benefits are now being realized through full scale and long term demonstration projects. Over the past several years, there has been a renewed interest in the use of fiber reinforcement in concrete pavements for parking lots, white toppings, bridge decks and roadways. Various technical organizations such as the American Concrete Institute, American Concrete Pavement Association and the National Concrete Pavement Technology Center have developed new guidance and recommendations on how to properly select and use fiber types in concrete. However, many prospective engineers, architectural firms and clients are now requesting additional information as to the environmental impacts of using fibers in replacement of traditional reinforcement or as an added material in concrete to improve durability and useful service life.

“Low Carbon Concrete” is the new mantra for our industry, yet many people are unaware that much of the concrete we produce now has a greatly reduced carbon footprint than that of 50 years ago. The factor being that no-one was counting this before. The webinar will look at that point, along with the use of silica fume, especially in conjunction with other SCMs. By improving the overall performance of the concrete – strength and durability parameters – the longevity of the concrete is increased, resulting in less ‘new’ concrete being produced for repairs or rebuilds. Silica Fume is a key component of multiple blend systems, where the higher reactivity compensates for the slower pozzolanic action of Fly Ash or Slag cement. The synergistic pozzolanic effects in the short and long term mean high performance concrete can be produced with much lower Portland cement contents with a cumulative reduction of the CO2 from each SCM. Reference projects will be shown where the CO2 levels have been calculated for comparison and where the cost effectiveness is outlined.

Calcium sulfoaluminate cements (CSACs)—for which CO2 emissions are ~50% lower compared to Portland cement (PC)—present a tremendous opportunity to develop sustainable binders for construction infrastructure. To further reduce the energy-intensity and carbon footprint of CSAC, supplementary cementitious materials (SCMs: e.g., a mixture of limestone and fly ash) can be used—at least in theory to replace up to 50% of the CSAC in the binder. That said, owing to the substantial diversity in SCMs’ compositions—plus the massive combinatorial spaces, and complex SCM-CSAC interactions—current computational models are unable to produce a priori predictions of properties of [CSAC + SCM] binders. This study presents a deep learning (DL) model capable of producing a priori, high-fidelity predictions of composition- and time-dependent hydration kinetics, phase assemblage development, and compressive strength development in [CSAC + SCM] pastes. The DL is coupled with a thermodynamic model that constrains and guides the DL, thus ensuring that predictions do not violate fundamental materials laws. The training and outcomes of the DL are ultimately leveraged to develop a high-fidelity prediction tool to determine optimum precursor chemistry and mixture designs of [CSAC + SCM] binders that exhibit superior compliance-relevant properties compared to PC concretes, while restricting the CSAC content to ~50%.