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Compressed earth blocks (CEBs) represent a cost-effective, sustainable, and environmentally-friendly building alternative to traditional masonry elements. Block performance depends heavily on the qualities of the soil used and it is important to be able to identify a soil’s qualities rapidly in the field. Soil classification systems such as the Unified Soil Classification System (USCS) provide standardized methodologies with which to evaluate the qualities of a soil, however these methods require laboratory space and specialized equipment which are often unavailable in field conditions. This paper presents an artificial neural network framework that processes qualitative and quantitative field test data in lieu of ASTM laboratory test results. This neural network approach rapidly and accurately assigns USCS classifications to various soils based solely on qualitative and quantitative field soil analysis. [ABSTRACT FROM AUTHOR]

Compressed earth blocks (CEBs) are masonry units that combine soil, stabilizer, and water under pressure to form an earth block. Unit block performance is dependent on the characteristics of soil and the mix design. This paper presents CEB unit strength test methods and results for CEBs produced from 14 mix designs at 7 and 28 day curing times in both saturated and unsaturated conditions. Trends in the effect of mix design on block strength reflect that strength increases with both moisture and cement content in the regimes of applicability for the production machinery. The unsaturated, 28-day unit compressive strengths ranged from 4.92 MPa to 15.72 MPa. The optimal mix contained 10.91% cement and 11.40% water which resulted in an average compressive strength of 15.15 MPa; ASTM C90 mandates a minimum compressive strength of 13.79 MPa. [ABSTRACT FROM AUTHOR]