Schmidt çekici sertliği (RL
) kayaların dayanım, kesilebilirlik (doğrusal ve dairesel) ve delinebilirlik
gibi mekanik özelliklerini belirlemek için yaygın olarak kullanılan ucuz ve kolaylık sağlayan bir yüzey
sertliği ölçüsüdür. Bu çalışmada, özellikle zincirli kesme makinesinin performans tahmininde,
kullanışlı, basit ve ucuz bir test olan Schmidt çekici sertliği değişken olarak önerilmiştir. Bu
çalışmada amaç, kayaların Schmidt sertliklerinden zincirli kesme makinelerinin performansını
tahmin etmektir. Bunun için, farklı dayanım özelliklerine sahip 24 farklı doğal taş numunesi
üzerinde kesme ve kaya mekaniği testleri yapılmıştır. Bu çalışmada, zincirli kesme makinelerinin
performans tahmini için daha önce kullanılan iki modelden biri olan Zincirli Kesme Penetrasyon
İndeksi (CSPI) RL
baz alınarak öngörülmüştür. RL
değerleri ile tek eksenli basınç dayanımı,
zincirli kesme indeksi ve spesifik enerji değerlerinin korelasyonu SPSS 15.0 istatistik programı
kullanılarak yapılmıştır. Bu değerlendirme sonucunda; RL
değerleri ile tek eksenli basınç dayanımı
ve spesifik enerji değerleri arasında güçlü korelasyon olduğu belirlenmiştir. Buna göre; zincirli
kesme indeksini tahmin etmek için RL
’ye dayanan modelin zincirli kesme makinesinin performans
tahmini için geçerli ve güvenilir olduğu istatistiksel olarak kanıtlanmıştır. Bu çalışmanın sonuçları,
zincirli kesme makinelerinin zincirli kesme indeksini, RL
değerleri kullanılarak oluşturulan görgül
modeller ile güvenilir bir şekilde tahmin edilebileceğini göstermiştir.
Schmidt hammer hardness (RL) provides a quick and inexpensive measure of surface hardness
that is widely used for estimating the mechanical properties of rock material such as strength,
sawability, cuttability and drillability. In this study, RL
as predictors, which is thought to be a
useful, simple and inexpensive test particularly for performance prediction of chain saw machine
(CSM), is suggested. This study aims to estimate CSM performance from RL
values of rocks.
For this purpose, rock cutting and rock mechanics tests were performed on twenty four different
natural stone samples having different strength values. In this study, Chain Saw Penetration
Index (CSPI) has been predicted based on RL
which is one of the two models previously used for
performance prediction of CSMs. The RL
values were correlated with UCS, CSPI and SE using
simple regression analysis with SPSS 15.0. As a result of this evaluation, RL
has a strong relation
with UCS and SE. It is statistically proved that the model based on RL
for predicting CSPI is valid
and reliable for performance prediction of CSM. Results of this study indicated that the CSPI of
CSMs could be reliably predicted by empirical model using RL
.
___
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