Multifactorial fuzzy approach to the sawability classification of building stones

Tutmez, Bulent; Kahraman, S.; Günaydın, Osman

doi:10.1016/j.conbuildmat.2006.05.023

Cited by 49 publications

(12 citation statements)

References 13 publications

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“…In other research fields such as concrete or rock, the hardness test, replacing the UCS test, has frequently been used to obtain the strength characteristics, due to its simplicity, rapidity, and low cost (Yılmaz and Sendir 2002;Tutmez et al 2007;Bandini and Berry 2010;Tarefder et al 2010). However, there are few investigations into the hardness of cement-stabilized clay.…”

Section: Introductionmentioning

confidence: 98%

Rapid field evaluation of the strength of cement-stabilized clayey soil

Wang

Yin

2014

Bull Eng Geol Environ

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This paper presents an investigation into the hardness and unconfined compressive strength (UCS) of cement-stabilized Shanghai clay. Various specimens with different cement content and curing time were made in order to conduct hardness tests and unconfined compression tests. The Shore-A durometer was used in a pioneer manner to measure the hardness of stabilized clay. Hardness tests suggest that the measured values of degree of hardness ranged from 1 to 87 DH, and the unconfined compression tests showed that the measured UCS varied from 56 to 1,061 kPa. Test results indicate that the average degree of hardness decreases dramatically with an increase in the clay-water/ cement ratio. It is shown that the relationship between the degree of hardness and the curing time is approximately linear in the semi-logarithmic plot. An exponential equation is proposed to express the unique relationship between the UCS (q u ) and the ratio of degree of hardness (S/S r ) by regression analysis. The expected prediction range of UCS using the Shore-A durometer was calculated to be between 0.04 and 1.79 MPa. The exponential equation proposed in this study may be used to produce a quick prediction of UCS by measuring the hardness of samples in the field.

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Section: Introductionmentioning

confidence: 98%

Rapid field evaluation of the strength of cement-stabilized clayey soil

Wang

Yin

2014

Bull Eng Geol Environ

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“…With the preceding three elements, for a given u∈ U, its evaluation result D (u) ∈ F(E) can be derived. The multifactorial evaluation model suggests that a mapping consists of factor weights (W) and relation matrix (R) which combines with an aggregation function as follows (Tutmez et al, 2007):…”

Section: Fuzzy Multifactorial Evaluationmentioning

confidence: 99%

Applying fuzzy logic theory to performance management

Ardil¹

2017

Pressacademia

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Organizations usually apply classical methods of employee performance evaluation. In this classical system, employee performance depends on work results, and it is evaluated only as success or failure in job behaviors. The non-classical performance evaluation methods such as fuzzy logic may mainly be used to many forms of decision-making including artificial intelligence systems. This research proposes a new employee performance evaluation method based on fuzzy logic systems. The process of performance measurement for evaluating the effectiveness, efficiency, and productivity of employees encompasses data collection, data design, and data analysis stages and it involves a level of uncertainty associated with performance measures. In evaluating employee performance, it usually involves granting numerical values or linguistic labels to employee performance in the organization. The scores accorded by the appraisers are only approximations, which are then, used to represent each employee's achievement by reasoning incorporated in the computational methods. In this paper, the fuzzy logic theory approach is used to represent the uncertainty caused by performance measures during its design, use and analysis stages. This research seeks to describe and execute the fuzzy logic theory approach for decision making in the employee performance appraisal process. Finally, reasoning based on fuzzy logic theory provides an alternative way in dealing with imprecise data, which is often reflected in the way humans think and make judgments in real life.

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“…Up to now, many studies have been done on the relations between sawability and rock characteristics in stone processing (Burgess, 1978;Wright & Cassapi, 1985;Birle & Ratterman, 1986;Jennings & Wright, 1989;Clausen et al, 1996;Tonshoff et al, 2002;Eyuboglu et al, 2003;Wei et al, 2003;Ersoy & Atici, 2004;Gunaydin et al, 2004;Kahraman et al, 2004;Özçelik et al, 2004;Delgado et al, 2005;Ersoy et al, 2005;Buyuksagis & Goktan, 2005;Kahraman et al, 2006;Fener et al, 2007;Tutmez et al, 2007;Özçelik, 2007;Buyuksagis, 2007;Kahraman et al, 2007;Mikaeil et al, 2008Mikaeil et al, , 2011aMikaeil et al, -c, 2012Mikaeil et al, , 2013aKrauze et al, 2009;Atici & Ersoy, 2009;Ataei et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Predicting the Relationship Between System Vibration With Rock Brittleness Indexes in Rock Sawing Process

Mikaeil¹,

Ataei²,

Ghadernejad³

et al. 2014

Archives of Mining Sciences

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The system vibration is a very significant measure of the sawing performance, because it indicates the amount of energy required to saw the rock. The maintenance cost of system is also dependant on system vibration. A few increases in system vibration cause a huge increase in the maintenance cost of the system. In this paper, the vibration of system in terms of RMSa was investigated and models for estimation of vibration by means of rock brittleness indexes and operational specifications were designed via statistical models and multiple curvilinear regression analysis. In this study, the relationships between rock brittleness indexes and operational specifications were investigated by regression analysis in statistical package for social science (SPSS) and the results of determination coefficients have been presented. In the second part, the diagrams show that a point lying on the line indicates an exact estimation. In the plot for model, the points are scattered uniformly about the diagonal line, suggesting that the models are good. It is very useful to evaluate the vibration of system and select the suitable operational characteristics by only some mechanical properties of rock.Keywords: system vibration, brittleness indexes, sawing process, statistical analysis Drgania układu uważane są za miernik wydajności procesu urabiania, ponieważ pokazują ilość energii niezbędnej do urabiania skały. Od poziomu drgań zależą także koszty eksploatacji systemu. Nieznaczny nawet wzrost poziomu drgań prowadzi do znacznego zwiększenia kosztów eksploatacyjnych urządzenia. W pracy tej przeprowadzono analizę drgań (ich wartości skutecznych) i opracowano model estymacji poziomu drgań w oparciu o współczynnik kruchości skał i parametry eksploatacyjne urządzenia. W pracy wykorzystano modele statystyczne i wielokrotną analizę metodą regresji krzywoliniowej. W pracy obecnej związek pomiędzy współczynnikiem kruchości skał a parametrami eksploatacyjnymi urządzenia badano z wykorzystaniem analizy metodą regresji dostępnej w statystycznym pakiecie oprogramowania dla nauk

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Multifactorial fuzzy approach to the sawability classification of building stones

Cited by 49 publications

References 13 publications

Rapid field evaluation of the strength of cement-stabilized clayey soil

Rapid field evaluation of the strength of cement-stabilized clayey soil

Applying fuzzy logic theory to performance management

Predicting the Relationship Between System Vibration With Rock Brittleness Indexes in Rock Sawing Process

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