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portada Probabilistic Intelligence in Geotechnical Engineering (en Inglés)
Formato
Libro Físico
Editorial
Idioma
Inglés
N° páginas
134
Encuadernación
Tapa Blanda
ISBN13
9798240806759

Probabilistic Intelligence in Geotechnical Engineering (en Inglés)

Paul, Jean (Autor) · Jean Paul · Tapa Blanda

Probabilistic Intelligence in Geotechnical Engineering (en Inglés) - Paul, Jean

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Reseña del libro "Probabilistic Intelligence in Geotechnical Engineering (en Inglés)"

Probabilistic Intelligence in Geotechnical Engineering* presents a focused perspective on the role of probabilistic thinking in understanding and managing uncertainty within geotechnical engineering. Geotechnical problems are inherently influenced by variable soil and rock properties, incomplete site information, spatial variability, measurement uncertainty, and the limitations of engineering models. A probabilistic approach provides a structured way to represent these uncertainties and to support more informed engineering assessment and decision-making. The subject connects geotechnical engineering with probability, uncertainty analysis, statistical reasoning, reliability concepts, and risk-informed engineering practice. Rather than treating soil and ground parameters as fixed values, probabilistic methods recognize that parameters such as strength, stiffness, density, permeability, and other geotechnical properties may vary from location to location and may be represented through distributions or other appropriate statistical descriptions. This perspective is particularly relevant when engineers must evaluate the likelihood of unfavorable conditions or assess how uncertainty can influence predicted performance. The book is centered on the concept of applying probabilistic intelligence to geotechnical engineering problems. It provides a useful conceptual framework for considering uncertainty in soil and rock mechanics, foundation engineering, ground behavior, and related civil engineering applications. Topics associated with probabilistic geotechnical assessment can include random variables, probability distributions, statistical characterization of geotechnical parameters, uncertainty propagation, reliability analysis, risk assessment, and interpretation of variable ground conditions.

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