5.4
Module de finesse
Le module de finesse (FM) des granulats est un indice numérique qui mesure la grosseur ou la finesse des particules. Il est calculé en additionnant le…
Considérons un échantillon d’agrégats fins tamisés à travers un ensemble standard de tamis. Notez le poids des agrégats retenus sur chaque tamis.
Calculer le poids cumulé des agrégats conservés sur chaque tamis et l’exprimer en pourcentage du poids total de l’échantillon.
Si, par exemple, toutes les particules sont retenues sur ou au-dessus d’un tamis particulier, et que rien ne le traverse, le pourcentage cumulé retenu pour ce tamis et ceux empilés en dessous est de 100.
Le module de finesse est calculé en additionnant le pourcentage cumulé retenu sur chaque tamis et en divisant le total par 100.
Le module de finesse est un indice numérique qui représente le classement des granulats.
Lorsque l’on utilise des granulats provenant de la même source, de légères variations dans la gradation des granulats fins sont moins évidentes visuellement qu’avec des granulats grossiers.
Ces différences se refléteront dans la valeur du module de finesse, ce qui sera plus perspicace pour les agrégats fins que pour les agrégats grossiers.
En règle générale, la valeur du module de finesse pour les granulats fins varie de 2,3 à 3,1 ; plus la valeur est élevée, plus les agrégats sont grossiers.
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Q1: How is fineness modulus calculated from sieve analysis?
Fineness modulus is calculated by summing the cumulative percentage retained on each sieve and dividing the total by 100. First, record the weight retained on each sieve, then calculate cumulative weights and express them as percentages of total sample weight. Finally, add all cumulative percentages and divide by 100 to obtain the fineness modulus value.
Q2: What does a higher fineness modulus value indicate about aggregate particles?
A higher fineness modulus value indicates coarser aggregates, while lower values indicate finer particles. For fine aggregates, fineness modulus typically ranges from 2.3 to 3.1. This numerical index effectively reflects variations in aggregate gradation and provides more meaningful differentiation for fine aggregates than for coarse aggregates.
Q3: Why is fineness modulus more useful for fine aggregates than coarse aggregates?
When aggregates from the same source are used, slight variations in fine aggregate gradation are less visually obvious than with coarse aggregates. The fineness modulus value captures these subtle differences more insightfully for fine aggregates, making it a more sensitive indicator of particle size distribution in finer materials.
Q4: What is the typical fineness modulus range for sand?
Sand typically has a fineness modulus ranging from 2.3 to 3.1. Lower values within this range indicate finer sand with smaller particles, while higher values indicate coarser sand with larger particles. This range helps classify sand quality for construction and concrete applications.
Q5: How do you express aggregate retained on each sieve as a percentage?
To express aggregate retained as a percentage, divide the cumulative weight retained on each sieve by the total sample weight, then multiply by 100. For example, if 60 grams are cumulatively retained on a sieve from a 500-gram sample, the cumulative percentage retained is 12 percent.
Q6: What happens when all particles are retained on or above a particular sieve?
When all particles are retained on or above a particular sieve and nothing passes through it, the cumulative percentage retained for that sieve and all sieves stacked underneath it is entered as 100 percent. This indicates that no material finer than that sieve size is present in the sample.
Q7: What does fineness modulus represent in aggregate grading?
Fineness modulus is a numerical index that represents the grading of aggregates by measuring the coarseness or fineness of particles. It provides a single quantitative value that characterizes the particle size distribution of an aggregate sample, enabling standardized comparison and quality control in construction materials.