5.3
Elek Analizi ve Derecelendirme Eğrileri
Elek analizi, agrega malzemelerinin parçacık boyutu dağılımını belirlemek için kullanılan bir yöntemdir. Bu işlem aşağıdaki adımları içerir:
- Gerekli m…
Agregaların elek analizi, açıklık boyutlarına göre yukarıdan aşağıya doğru azalan sırada istiflenmiş bir dizi elek kullanılarak gerçekleştirilir.
Eleklerin boyutları iri agregalar ve ince agregalar için değişir.
Havayla kurutulmuş agregalardan oluşan bir numune, belirli bir süre boyunca mekanik veya manuel olarak çalkalanarak eleklerden tartılır ve elenir.
İşlemde, her elek, daha ince parçacıkların bir sonraki eleğe geçmesine izin verirken, ağ boyutundan daha iri parçacıkları tutar.
Her bir elek üzerinde tutulan fraksiyonların ağırlığı kaydedilir, toplam kütlenin yüzdesi olarak ifade edilir ve bir tabloda temsil edilir.
En ince elekten başlayarak yukarı doğru hareket ederek, her bir elekten geçen kümülatif yüzde hesaplanır ve en yakın yüzde bire yuvarlanır.
Ayrıca, y eksenindeki geçiş yüzdesini ve logaritmik olarak ölçeklendirilmiş x eksenindeki elek açıklıklarını temsil etmek için yarı logaritmik bir grafik kullanılır.
Bu grafikte, her bir elek boyutuna karşılık gelen kümülatif geçiş yüzdesi, agrega parçacıklarının boyutlarına göre dağılımını gösteren derecelendirme eğrisini elde etmek için çizilir.
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Q1: How is sieve analysis performed on aggregate samples?
Sieve analysis begins with weighing an air-dried aggregate sample, then passing it through a stack of sieves arranged in descending order of aperture size from top to bottom. The sieves are shaken mechanically or manually for a specified time, allowing finer particles to pass through while coarser particles are retained. The weight of material retained on each sieve is recorded and expressed as a percentage of total mass.
Q2: What is the purpose of calculating cumulative percentage passing in sieve analysis?
Cumulative percentage passing is calculated from the finest sieve moving upward to establish the foundation for grading curve development. This calculation, rounded to the nearest one percent, represents the proportion of aggregate particles finer than each sieve size. These values are plotted on the y-axis of a semi-logarithmic graph to visualize particle size distribution.
Q3: Why is a semi-logarithmic graph used to represent grading curves?
A semi-logarithmic graph is used because sieve apertures are plotted on a logarithmically scaled x-axis while cumulative passing percentages are plotted linearly on the y-axis. This scaling approach effectively displays the wide range of aggregate particle sizes and produces a grading curve that clearly indicates the distribution of particles across different size ranges.
Q4: What information does a grading curve provide about aggregates?
A grading curve visually simplifies the distribution of particle sizes within an aggregate sample by plotting cumulative passing percentages against sieve apertures. This graphical representation is essential for ensuring that aggregates meet required grading specifications for construction projects and helps engineers assess whether the material is suitable for specific applications.
Q5: How do sieve sizes differ between coarse and fine aggregates?
Sieve sizes vary for coarse aggregates and fine aggregates to accommodate their different particle size ranges. Coarse aggregates require larger mesh openings, while fine aggregates use smaller mesh sizes. The specific sieve stack selected depends on the aggregate classification and the particle size distribution being analyzed.
Q6: What does the weight retained on each sieve represent in sieve analysis?
The weight retained on each sieve represents the mass of particles coarser than that sieve's mesh size. This weight is recorded after sieving and then expressed as a percentage of the total sample mass. These percentages are essential for calculating cumulative passing values and constructing the grading curve.
Q7: Why must aggregate samples be air-dried before sieve analysis?
Air-drying the aggregate sample ensures consistent and accurate results by removing surface moisture that could affect particle behavior during sieving. Moisture can cause particles to clump together or stick to sieves, leading to incorrect weight measurements and inaccurate particle size distribution data.