Green and durable engineered cementitious composites (GD-ECC) with recycled PE fiber, desert sand, and carbonation curing: Mixture design, durability performance, and life-cycle analysis
Not provided.
Construction & Building Technology↗
Engineering topics
Li, Victor
Publications and source records attributed to Li, Victor.
Development of an Extremely Durable Concrete (EDC) - A Novel approach coupling Chemistry and Autogenous Crack Width Control (Final Report)
Concrete cracking is a challenging issue and a constant threat to the durability of modern physical infrastructure. It is most commonly produced by mechanical loading and environmental deformations endured under field conditions, and structural deterioration accelerates at large crack widths. There is an urgent need for dramatic reductions in O&M cost, energy use, and emissions for infrastructure. The goal of this project is to fundamentally design an Extremely Durable Concrete (EDC) with a life expectancy at least five times that of current concrete by deploying a coupled micromechanical and chemical approach in material design. EDC is expected to embody an autogenously tight crack width (<50μm), high ductility (>3%), and stable chemistry using a green binder based on Limestone Calcined Clay Cement (LC3), which together will produce a resilient formulation with self-healing capability.
36 MATERIALS SCIENCE↗
Machine learning for Deep Space Network antenna motions detection
Highly stable frequency and timing standards are essential for deep-space missions and radio science. At the NASA Deep Space Network (DSN), these standards are distributed through a network of underground fiber cables to support several Goldstone antennas. Independently developed frequency-measuring instruments generate tremendous quantities of data to monitor and validate the antennas’ stringent frequency requirements. In this paper, we propose a lightweight processing tool capable of detecting disturbances on the frequency signal caused by DSN antenna motions. Our training data is sampled from the movement log of the antenna of interest and the generated data from the fiber optic metrology instrument linked to the antenna. We demonstrate that a convolutional neural network (CNN) model can achieve high accuracies on classifying instances of antenna movements and is an effective predictor when used iteratively on longer, variable stretches of metrology data. The simplicity, low training cost, and high accuracies of our model strongly suggest its efficacy in identifying and troubleshooting frequency disturbances caused by the antenna.
Yi, Lin↗
Damage Arresting Composites for Shaped Vehicles - Phase II Final Report
This report describes the development of a novel structural concept, Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS), that addresses the demanding fuselage loading requirements for the Hybrid Wing or Blended Wing Body (BWB) airplane configuration. In addition to the analytical studies, a three specimen test program was also completed to assess the concept under axial tension loading, axial compression loading, and internal pressure loading.
Velicki, Alex↗