Modelos de capacidade de suporte de carga e suas relações com atributos físicos e mecânicos em argissolo amarelo distrocoeso.

• Ano de defesa: 2013
• Autor(a) principal: LIMA, Renato Paiva de
• Orientador(a): ROLIM, Mário Monteiro
• Banca de defesa: FERREIRA, Rinaldo Luiz Caraciolo, SANTOS, Djail
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal Rural de Pernambuco
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Ambiental
• Departamento: Departamento de Engenharia Agrícola
• País: Brasil
• Palavras-chave em Português: Compressibilidade; Tensão de pré-consolidação; Física do solo; Modelagem; Compressibility; Pre-consolidation stress; Physical attributes; Modelling
• Área do conhecimento CNPq: CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
• Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5670

Models that predict pre-consolidation stress in Ultisol are scarce, given the importance of these soils for the production of sugarcane in the Northeast. The current study aimed to fit linear and nonlinear regression models and study the relationship of soil physical attributes on pre-consolidation stress (σp) variation. On a plot, 42 points were delimited to get samples in the layers 0-0.20 and 0.20-0.40 m, totaling 84 samples. Deformed and undeformed samples were collected to obtain the variables: water content (θ), bulk density (BD), soil resistance to penetration (RP), organic carbon (OC), clay content (C), plastic limit (PL) and liquid limit (LL), as well as the pre-consolidation stress (σp). Four models were fitted to predict the σp: linear multiple regression, two nonlinear multiple model and charge supporter capacity model. Was also held for each layer a principal component analysis was performed and, after obtaining the scores for those components retained, a linear multiple regression model was fitted for the σp data to establishment of the relationships. The average of σp was 73.0 kPa. The multiple linear regression model was the best fit soil conditions and management of the area in the two analyzed layers. Only soil bulk density and penetration resistance contributed significantly to variation σp models with the best settings. The θ and the OC showed negative relations with σp; while BD, RP, C, LL and PL showed positive relation. Higher values of σp are associated with higher values of BD, RP, C, LL and PL, as well as smaller values are linked with the increase of OC concentration and θ.