İnşaat Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/205

Browse

Now showing 1 - 4 of 4

Developing New Empirical Formulae for the Resilient Modulus of Fine-Grained Subgrade Soils Using a Large Long-Term Pavement Performance Dataset and Artificial Neural Network Approach
(SAGE Publications Ltd, 2022) Fedakar, Halil Ibrahim; 0000-0002-7561-5363; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Fedakar, Halil Ibrahim
Artificial neural network (ANN) has been successfully used for developing prediction models for resilient modulus (Mr). However, no reliable Mr formula derived from these models has been proposed in previous studies, although engineers/ researchers need empirical formulae for hand calculation of Mr. Therefore, this study aimed to propose reliable empirical formulae for the Mr of fine-grained soils using ANN. For this purpose, thousands of ANN models were developed using the long-term pavement performance (LTPP) and external datasets. The input parameters were the percentage of soil particles passing through #200 sieve (P200), silt percentage (SP), clay percentage (CP), liquid limit (LL), plasticity index (PI), maximum dry density ([rdry]max), optimum moisture content (wopt), confining pressure (sc), and nominal maximum axial stress (sz). The ANN models were compared with several constitutive models. The results indicate that the constitutive models failed to predict the Mr, and the best Mr predictions were obtained by the ANN-C9 (P200, SP, CP, LL, PI, sc, and sz), ANN-C10 (P200, SP, CP, [rdry]max, wopt, sc, and sz), and ANN-C11 (P200, SP, CP, LL, PI, [rdry]max, wopt, sc, and sz) models. Thus, the structures of these ANN models were formulated and proposed as the new empirical formulae for the Mr of fine-grained soils. Sensitivity analysis was also performed on these ANN models. It was determined that (rdry)max is the most influential parameter in the ANN-C10 model, and LL is the most influential parameter in the ANN-C9 and ANN-C11 models. On the other hand, sc and sz are the least influential parameters.
Effluent treatment in denim and jeans manufacture
(ELSEVIER, 2015) Uzal, Nigmet; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Nigmet
This chapter discusses the major strategies that should be considered in the treatment of denim dyeing and jeans processing wastewater. It first gives an overview of wastewater characteristics and further elaborates on the different techniques currently available for treating wastewater. There follow the strategies to be adopted for water reuse and the recovery of dyes and chemicals. Also emphasised is the utilisation of novel technologies that provide waste minimisation, recovery and reuse opportunities and pollution prevention, instead of end of pipe approaches for treating this highly polluted wastewater.
Modeling of suspended sediment concentration carried in natural streams using fuzzy genetic approach
(SPRINGER LINK, 2014) Kisi, Ozgur; Fedakar, Halil Ibrahim; 0000-0002-7561-5363; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Fedakar, Halil Ibrahim
This chapter proposes fuzzy genetic approach so as to predict suspended sediment concentration (SSC) carried in natural rivers for a given stream cross section. Fuzzy genetic models are improved by combining two methods, fuzzy logic and genetic algorithms. The accuracy of fuzzy genetic models was compared with those of the adaptive network-based fuzzy inference system, multilayer perceptrons, and sediment rating curve models. The daily streamflow and suspended sediment data belonging to two stations, Muddy Creek near Vaughn (Station No: 06088300) and Muddy Creek at Vaughn (Station No: 06088500), operated by the US Geological Survey were used as case studies. The root mean square errors and determination coefficient statistics were used for evaluating the accuracy of the models. The comparison results revealed that the fuzzy genetic approach performed better than the other models in the estimation of the SSC.
Properties of concrete with high-volume pozzolans
(ELSEVIER, 2013) Uzal, Burak; 0000-0002-3810-7263; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Burak
This chapter focuses on the materials and properties of high-volume natural pozzolan (HVNP) concrete. The characteristics of natural pozzolans used in high-volume pozzolan mixtures are discussed, together with the fresh and hardened properties of HVNP cementitious systems, their hydration characteristics and their microstructures.

Browse

Browsing İnşaat Mühendisliği Bölümü Koleksiyonu by Publication Category "Kitap Bölümü - Uluslararası"