journal article·2014-03-28

Producing synthetic lightweight aggregates by treating waste TFT-LCD glass powder and reservoir sediments

Chao-Wei Tang

Computers and Concrete· Volume 13· Issue 3
Publisher page

Abstract

The use of lightweight aggregate (LWA) instead of ordinary aggregate may make lightweight aggregate concrete, which possesses many advantages such as lightweight, lower thermal conductivity, and better fire and seismic resistance. Recently the developments of LWA have been focused on using industrial wastes as raw materials to reduce the use of limited natural resources. In view of this, the intent of this study was to apply Taguchi optimization technique in determining process condition for producing synthetic LWA by incorporating waste thin film transition liquid crystal displays (TFT-LCD) glass powder with reservoir sediments. In the study the waste TFT-LCD glass cullet was used as an additive. It was incorporated with reservoir sediments to produce LWA. Taguchi method with an orthogonal array L16(45) and five controllable 4-level factors (i.e., cullet content, preheat temperature, preheat time, sintering temperature, and sintering time) was adopted. Then, in order to optimize the selected parameters, the analysis of variance method was used to explore the effects of the experimental factors on the performances (particle density, water absorption, bloating ratio, and loss of ignition) of the produced LWA. The results showed that it is possible to produce high performance LWA by incorporating waste TFT-LCD glass cullet with reservoir sediments. Moreover, Taguchi method is a promising approach for optimizing process condition of synthetic LWA using recycled glass cullet and reservoir sediments and it significantly reduces the number of tests.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Recycling and utilization of industrial and municipal waste in materials production · Concrete and Cement Materials Research · Recycled Aggregate Concrete Performance

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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