title: Assessment of the recycling potential of fresh concrete waste using a factorial design of experiments.
abstract: Recycling of industrial wastes and by-products can help reduce the cost of waste treatment prior to disposal and eventually preserve natural resources and energy. To assess the recycling potential of a given waste, it is important to select a tool capable of giving clear indications either way, with the least time and work consumption, as is the case of modelling the system properties using the results obtained from statistical design of experiments. In this work, the aggregate reclaimed from the mud that results from washout and cleaning operations of fresh concrete mixer trucks (fresh concrete waste, FCW) was recycled into new concrete with various water/cement ratios, as replacement of natural fine aggregates. A 3(2) factorial design of experiments was used to model fresh concrete consistency index and hardened concrete water absorption and 7- and 28-day compressive strength, as functions of FCW content and water/cement ratio, and the resulting regression equations and contour plots were validated with confirmation experiments. The results showed that the fresh concrete workability worsened with the increase in FCW content but the water absorption (5-10 wt.%), 7-day compressive strength (26-36 MPa) and 28-day compressive strength (32-44 MPa) remained within the specified ranges, thus demonstrating that the aggregate reclaimed from FCW can be recycled into new concrete mixtures with lower natural aggregate content.
authors: State University of Santa Catarina, Centre of Technology Sciences (UDESC/CCT), 89223-100 Joinville-SC, Brazil.
authors: S L
authors: SL
authors: Correia
authors: F L
authors: FL
authors: Souza
authors: G
authors: G
authors: Dienstmann
authors: A M
authors: AM
authors: Segadães
mesh_terms: D000042:Absorption; D003252:Construction Materials / Q000032:analysis* / Q000706:statistics & numerical data; D006244:Hardness; D007220:Industrial Waste / Q000032:analysis* / Q000706:statistics & numerical data; D055595:Mechanical Phenomena; D015233:Models, Statistical; D012107:Research Design; D018505:Waste Management / Q000379:methods*
chemical_list: D007220:Industrial Waste