PROCJENA HRAPAVOSTI POVRŠINE PRIRODNIH STIJENSKIH PUKOTINA TEMELJENA NA TEHNICI NENADZIRANOG PREPOZNAVANJA UZORAKA POMOĆU 2D PROFILA

The stability of a jointed rock mass is generally controlled by its shear strength that significantly depends on surface roughness. So far, different methods have been presented for determining surface roughness using 2D profiles. In this study, a new method based on the unsupervised pattern recognition technique using a combination of statistical, geostatistical, directional, and spectral methods for the quantification of the surface roughness will be proposed. To reach this goal, more than 10,000 profiles gathered from 92 surfaces of natural rock joints were scanned. The samples were collected from limestone cores of the Lar Dam located in the Mazandaran Province, Iran. After introducing a new spectral index, determined from the fast Fourier transform for measuring the unevenness of rough profiles, statistical, geostatistical, directional, and spectral features revealing waviness and unevenness of the 2D profiles were extracted, and a representative vector and profile for each surface were introduced through the weighted mean and median of the profile features. Principal component analysis (PCA) was utilized for finding the direction of the maximum variance of information. Then, clustering of the 92 samples was performed via K-means, and the silhouette measure was used in order to find the optimal number of clusters resulted in the creation of 13 clusters. To verify the procedure, a sample was selected in each cluster, and direct shear tests were performed on the samples. Comparing the experiments and the clustering results shows they are in good agreement. Thus, the method is an efficient tool for the quantitative recognition of surface roughness considering the waviness and unevenness of a surface.Stabilnost raspucane stijenske mase općenito se kontrolira posmičnom čvrstoćom koja značajno ovisi o hrapavosti površine. Do sada su prikazane različite metode za određivanje hrapavosti površine pomoću 2D profila. U ovom radu predlaže se nova metoda koja se temelji na tehnici nenadziranog prepoznavanja uzoraka kombinacijom statističkih, geostatističkih, usmjerenih i spektralnih metoda za kvantifikaciju hrapavosti površine. Kako bi se postigao taj cilj, skenirano je više od 10.000 profila prikupljenih s 92 površine prirodnih stijenskih pukotina. Uzorci su prikupljeni iz vapnenačkih jezgri brane Lar koja se nalazi u pokrajini Mazandaran u Iranu. Nakon uvođenja novog spektralnog indeksa, određenog Fourierovom transformacijom za mjerenje neravnina hrapavih profila, izvučene su statističke, geostatističke, usmjerene i spektralne značajke koje opisuju valovitost i neravnine 2D profila, a reprezentativni vektor i profil za svaku površinu uvedeni su kroz ponderiranu aritmetičku sredinu i medijan značajki profila. Analiza glavnih komponenti (PCA) korištena je za pronalaženje smjera najvećeg odstupanja informacija. Zatim je grupiranje 92 uzorka provedeno putem metode K-sredina, a mjera siluete korištena je kako bi se pronašao optimalan broj grupa, a to je rezultiralo stvaranjem 13 grupa. Za provjeru postupka odabran je uzorak u svakoj grupi, a na tim uzorcima provedena su ispitivanja izravnog smicanja. Usporedba rezultata ispitivanja i grupiranja pokazala je dobro slaganje, stoga je ova metoda učinkovit alat za kvantitativno utvrđivanje hrapavosti s obzirom na valovitost i neravnine površine

Proposing an Approach for Additive and Multiplicative risks With the Case Study in Gas Transmission lines

Abstract Failure mode and effects analysis (FMEA) is a powerful tool for identifying and assessing potential failures. The tool has become increasingly important in gas and A failure mode in one component can serve as the cause of a failure mode in another component. A failure cause is defined as a design weakness that may result in a failure. Failure mode and effects analysis (FMEA) is an engineering technique used to define, identify and eliminate known and/or potential failures, problems, and errors from the system, design,process,and/or service before they reach the customer. It is counted as one of the effective models to predict failures and find the least expensive solution to prevent these, ensuring the safety and trustworthy in productions as well as processes. When applying FMEA, a cross functional and multidisciplinary team identifies failure modes,evaluates their risks and prioritizes them so that appropriate corrective actions can be taken. A failure effect is defined as the result of a failure mode on the function of the product or process as perceived by the customer. The traditional FMEA determines the risk priorities of failure modes through the risk priority number (RPN),which is determined byRPN = O × S × D where the risk factors O and S are occurrence and severity of a failure,and D is the ability to detect the failure before it reaches the customer.The three risk factors are evaluated using the ratings (also called ranks or scores) from 1 to 10. The RPN has been criticized for a variety of reasons some of which are listed as follows: Different combinations of O, S and D may produce exactly the same value of RPN, but their hidden risk implications may be totally different. For example, two different events with the values of 2, 3, 2 and 4, 1, 3 for O, S and D, respectively, have the same RPN value of 12. However, the hidden risk implications of the two events may not necessarily be the same. This may cause a waste of resources andtime, and in some cases a high risk event may go noticed. The relative importance among O, S and D is not taken into consideration. The three risk factors are assumed to be equally important. This may not be the case when considering a practical application of FMEA. The mathematical formula for calculating RPN is questionable and debatable. There is no rationale as to why O, S and D should be multiplied to produce the RPN

Comparison of female reading with male interpretation on the issue of guardianship in verse 34 in chapter An-Nisa

Since much of the existing commentary has traditionally been written by Muslim men, how gender relations and women's rights are described plays significant role. But with the rise of Islamic feminism, some Muslim women in this movement are debating new evaluations of these traditional interpretations in order to conceive of equality between men and women from an Islamic perspective based on religious principles. They support the Quran. Meanwhile, some pioneers of this idea have focused their work on re-reading the text of the Qur'an as the most basic Islamic source, claiming that Muslim men have read the Qur'an from patriarchal perspective, thereby incorporating gender inequality and patriarchy into the interpretation of the Qur'an. the authors claim that such a rule doesn̓t have a patriarchal view among Shiite thinkers and commentators, and although gender can be effective in reading the text, adherence to the original Qur'anic principles and the centrality of the monotheistic paradigm will prevent biased interpretations. The study of the strength of men over women, which is one of the most challenging verses of the Qur'an on women's rights, from two perspectives of women (Wadud, Barlas and Hebri) and men (Tabatabai, Javadi Amoli, Motahhari) despite differences in intellectual, doctrinal and emergence, It gives similar results, indicating biased interpretations by Shiite commentators. That masculinity is a limited and conditional virtue for men is in order to fulfill family and social responsibilities in support of women's rights, and the meanings of superiority and domination over women are nothing more than misconception

Numerical Modeling Of Rock Blocks With Nonpersistent Rough Joints Subjected To Uniaxial Compressive And Shear Loadings

Characterizing the mechanical behavior of jointed rocks is important to understand the behavior of structures in rock masses. Jointed rocks can be composed of persistent and nonpersistent joints where the impact of nonpersistent joints requires careful consideration for an accurate rock mass mechanical characterization. Most previous investigations into nonpersistent jointed rocks focused on joints with smooth surfaces, and a few experimental studies focused on nonpersistent rough joints and nothing specific has been reported numerically. Therefore, this study investigated several synthetic jointed rocks with nonpersistent rough joints numerically under uniaxial compressive and shear loadings. The PFC2D-based synthetic rock mass (SRM) approach was adopted to assess the impact of bridge angle (γ) and length (L), joint roughness coefficient (JRC), and normal stress (σn) on the shear strength (τn) and cracking in jointed rocks with nonpersistent rough joints. In addition, the impacts of γ, L, JRC, and joint inclination (θ) on the uniaxial compressive strength (UCS or σcm), elastic modulus (Em), and failure pattern in the jointed blocks were examined numerically. First, several numerical models were developed and verified by the laboratory data, followed by an extensive parametric study to assess the effects of the defined parameters further. The effects of JRC and σn on τn were more pronounced than γ and L due to the formation of interlocking cracks, which could cause significant shear resistance during shear loading. In addition, the numerical results under axial loading revealed that an increase in θ could reduce the deformation modulus and the value of the other parameters, in particular the JRC, could lead to an increase in the strength of jointed samples

Evaluation of degradation in chemical compounds of wood in historical buildings using ft-ir and ft-raman vibrational spectroscopy

Vibrational spectroscopy approaches like FT-IR and FT-Raman, as analytical method, can be used to assess chemical changes in historical wood structures. In this study, wood samples of three historical buildings, in Gorgan, Iran, namely Tekie Estebar, Molla Esmaiel Mosque, and the Esmaieli Buildings were selected. Wood species was determined by their macroscopic characteristics which were hornbeam (Carpinus betulus), oak (Quercus castaneifolia), beech (Fagus orientalis), and elm (Ulmus glabra), as hardwood species, and yew (Taxus baccata) as a softwood species. Also, some samples of oak were collected from northern and southern sides of the Esmaieli Building in order to compare deterioration environmental factors.. The approximate assignment of the experimental bands was completed by comparing. For this purpose, the experimental bands with the calculated band frequencies of cellulose, hemicellulose and lignin. In addition, the reported assignment for softwood and hardwood was used to confirm the vibrational assignments. The results of spectroscopy revealed that biodegradation had occurred in all species. Comparison between the most important vibrational band frequencies related to carbohydrates and lignin in hardwood species suggested that degradation of carbohydrates was greater than lignin, which could be attributed to brown rot and hydrolysis. Reduction of chemical compounds in south oak samples was higher and could be associated with prevailing wind and UV ray in this side. In the only softwood species (yew), because of its highest exposure to frequent raining, deterioration was observed in both carbohydrates and lignin

QCD analysis of nucleon structure functions in deep-inelastic neutrinonucleon scattering: Laplace transform and Jacobi polynomials approach

We present a detailed QCD analysis of nucleon structure functions x F 3 ( x , Q 2 ) , based on Laplace transforms and the Jacobi polynomials approach. The analysis corresponds to the next-to-leading order and next-to-next-to-leading order approximations of perturbative QCD. The Laplace transform technique, as an exact analytical solution, is used for the solution of nonsinglet Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equations at low- and large-x values. The extracted results are used as input to obtain the x and Q 2 evolution of x F 3 ( x,Q2) structure functions using the Jacobi polynomials approach. In our work, the values of the typical QCD scale Λ ( n f)MS and the strong coupling constant α s (M2Z) are determined for four quark flavors (n f =4) as well. A careful estimation of the uncertainties shall be performed using the Hessian method for the valence-quark distributions, originating from the experimental errors. We compare our valence-quark parton distribution functions sets with those of other collaborations, in particular with the CT14, MMHT14, and NNPDF sets, which are contemporary with the present analysis. The obtained results from the analysis are in good agreement with those from the literature

Evaluation of Applicability and Accuracy of Bus Travel Time Prediction in High and Low Frequency Bus Routes Using Tree-Based ML Techniques

Prediction of bus travel time is a key component of an intelligent transportation system and has many benefits for both service users and providers. Although there is a rich literature on bus travel prediction, some limitations can still be observed. First, high-frequency and low-frequency bus routes have different characterizations in both operational and passenger behavior aspects. Therefore, it is highly expected that bus travel time prediction methods for different frequencies must have different outputs. Second, in the era of big data, applications of machine learning (ML) techniques in travel time prediction have significantly increased. However, there is no single ML model introduced in the literature that is the most accurate in predicting bus travel, especially with regard to bus service frequency. Consequently, the main objective of this study is to determine the most applicable route construction approach and most accurate tree-based ML technique for predicting bus travel time on high- and low-frequency bus routes. The following tree-based ML techniques were adopted in this study: chi-square automatic interaction detection (CHAID), random forest (RF), and gradient-boosted tree (GBT). According to the results, CHAID was selected as the most accurate model for predicting travel time on high-frequency routes, while GBT showed the best performance for low-frequency service. CHIAD analysis identified distance between stops and terminal departure behavior as the most significant factors of travel time on high-frequency routes. Moreover, we introduced the "key stop-based" route construction method for the first time, which is an accurate, reliable, and applicable method