SRPH Journal of Fundamental Sciences and Technology最新文献

Evaluation of multivariable regression in predicting rock slake durability index 多变量回归预测岩湖耐久性指标的评价

SRPH Journal of Fundamental Sciences and Technology Pub Date : 2022-05-30 DOI: 10.47176/sjfst.4.1.1

M. Rahimi Shahid

{"title":"Evaluation of multivariable regression in predicting rock slake durability index","authors":"M. Rahimi Shahid","doi":"10.47176/sjfst.4.1.1","DOIUrl":"https://doi.org/10.47176/sjfst.4.1.1","url":null,"abstract":"The durability of stone against erosion, weathering and dissolution against water flow is an important parameter in Civil engineering projects. It is absolutely necessary to check the quality of slake durability rock against water flow in all types of stone breakwaters, rips - rap in dams, including building materials (a wide range of decorative stones). Slake durability testing is a common method for assessing the durability of rocks. The durability of stone has a lot to do with the texture, weathering and physical and mechanical properties of the stone. In this study, by performing slake durability tests on samples belonging to the Tale Zang Formation, the slake durability index (SDI) of limestone belonging to this formation was investigated. The effect of the number of cycles and the relationship between slake durability index and physical and mechanical properties have also been investigated. Univariable and multivariable regression relationships were used to predict the slake durability index. The results show that multivariable linear regression using a combination of geomechanical properties offers a higher correlation between these properties and the slake durability index (SDI) of the studied limestones. In multivariable regression models, n, UCS, E and BTS properties in different relationships have the greatest effect on the SDI value","PeriodicalId":198734,"journal":{"name":"SRPH Journal of Fundamental Sciences and Technology","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121571918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Investigation of the Sound Absorbing Performance of the Hollow Carbon Nanospheres as an Acoustic Absorbent 中空碳纳米球吸声性能的研究

SRPH Journal of Fundamental Sciences and Technology Pub Date : 2021-10-20 DOI: 10.47176/sjfst.3.3.10

Mahdi Teymourzadeh, M. Seifi, Ibrahim Hasanzadeh

引用次数: 0

Nano-Structural Characteristics and Optical and Electrical Properties of Obliquely Deposited Manganese Oxide Thin Films 斜沉积氧化锰薄膜的纳米结构特征及光电性能

SRPH Journal of Fundamental Sciences and Technology Pub Date : 2021-10-20 DOI: 10.47176/sjfst.3.4.1

Fatemeh Chahshouri, Elehe Khani, H. Savaloni, Rojan Savari

{"title":"Nano-Structural Characteristics and Optical and Electrical Properties of Obliquely Deposited Manganese Oxide Thin Films","authors":"Fatemeh Chahshouri, Elehe Khani, H. Savaloni, Rojan Savari","doi":"10.47176/sjfst.3.4.1","DOIUrl":"https://doi.org/10.47176/sjfst.3.4.1","url":null,"abstract":"In this work, manganese oxide thin films as a graded helical square tower-like (terraced) sculptured thin films with 8, 9, and 10 arms were deposited on a glass substrate by oblique angle deposition (OAD) method. Structural and morphological characteristics of the produced samples were obtained through xray diffraction (XRD), atomic force microscopy (AFM), and field emission electron microscopy (FESEM) analyses. The optical and electrical properties of manganese oxide thin film were studied by Photoluminescence (PL), UVvisible (UV-VIS), and V-I measurement. The spectrophotometry analysis on both s-and p-polarized lights at 90° incident light angles carried out for obtaining the optical spectra of the samples. Then, it used to calculate refractive index, energy gaps, and absorption peaks. Photoluminescence spectra for MnO films showed a 2.31, 2.28, and 2.26 eV gap energy in 8, 9, and 10 arms. The electrical resistance measurements of these samples showed that the resistance has strongly dependent on the intensity and energy of the incident light. The electrical resistance of these samples was also investigated under green, blue, red, and light radiation with 100 watts/cm2 power density.","PeriodicalId":198734,"journal":{"name":"SRPH Journal of Fundamental Sciences and Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128094690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Utilization of Rock Mass Parameters for Performance Prediction of Rock TBMs Using Machine Learning Algorithms 岩体参数在岩石掘进机性能预测中的应用

SRPH Journal of Fundamental Sciences and Technology Pub Date : 2021-10-20 DOI: 10.47176/sjfst.3.3.1

Hanan Samadi, E. Farrokh

{"title":"Utilization of Rock Mass Parameters for Performance Prediction of Rock TBMs Using Machine Learning Algorithms","authors":"Hanan Samadi, E. Farrokh","doi":"10.47176/sjfst.3.3.1","DOIUrl":"https://doi.org/10.47176/sjfst.3.3.1","url":null,"abstract":"Existing rock mass parameters, such as uniaxial compressive strength (UCS), rock quality designation (RQD), and distance between planes of weakness (DPW), are being widely used in the prediction of TBM performance in various hard rock conditions. In this paper, these factors are considered as input parameters to estimate the rate of penetration (ROP) based on 180 compiled data from two projects including the Queens water tunnel lot 3, Stage 2 in USA and KarajTehran water transfer tunnel in Iran. This study aims to evaluate the influence of rock mass parameters on TBM performance and develop a new empirical equation to estimate ROP using multivariate regression analysis and artificial intelligence algorithms. In this regard, by taking advantage of machine learning algorithms, two types of artificial intelligence techniques, including particle swarm optimization (PSO) and radial basis function network (RBF), have been employed to develop predictor networks to estimate TBM performance. To explain the relationships among rock mass parameters and ROP and to offer new empirical equations, regression analysis is also utilized. The proposed models have been validated based on the various machine learning loss functions including, MAD, RRSE, rRMSE, MSE, MAPE, and sensitivity analysis. The obtained results demonstrate that the calculated values are in good agreement with the actual data.","PeriodicalId":198734,"journal":{"name":"SRPH Journal of Fundamental Sciences and Technology","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133191567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Coacervation process for preparation of encapsulate Lambda-Cyhalothrin 包封高效氯氟氰菊酯的凝聚制备工艺

SRPH Journal of Fundamental Sciences and Technology Pub Date : 2021-04-10 DOI: 10.47176/SJFST.3.2.1

H. Saghafi, F. Zarkesh, Hassan Kooshyar

引用次数: 0

Wastewater Treatment using Magnetic Nanoparticles and Nanocomposites 磁性纳米颗粒和纳米复合材料处理废水

SRPH Journal of Fundamental Sciences and Technology Pub Date : 2020-10-15 DOI: 10.47176/SJFST.2.4.8

Z. Nasrollahi

引用次数: 1

Evaluating brain signal of patients with mild Alzheimer in order to early separation of them from normal individuals 评估轻度阿尔茨海默病患者的脑信号，以便尽早将其与正常人区分开来

SRPH Journal of Fundamental Sciences and Technology Pub Date : 2019-12-01 DOI: 10.29252/sjfst.1.1.1

Fereydoon Naseri

引用次数: 0