IYTE GCRIS Database (Izmir Institute of Technology)
Not a member yet
11968 research outputs found
Sort by
Effect of external electric field on fluidization of rodlike particles using CFD-DEM
No full textGiven the significant impact of an external electric field on fluidized bed hydrodynamics and the practical importance of rodlike particles, this study examines the behavior of a fluidized bed containing rodlike particles under various external electric fields. Simulations were performed using a coupled computational fluid dynamics-discrete element method, and rodlike particles were generated using a multisphere approach aided by quaternions. The effect of different vertical and horizontal external electric fields on the orientation of particles was investigated. Also, the effect of particle size on their orientation in the presence of constant vertical and horizontal external electric fields was explored in this work. The results showed that increasing the electric field strength and reducing the size of rodlike particles lead to an increment in the tendency of particles to become oriented along the direction of the electric field. Moreover, the effect of the external electric field at various inlet gas velocities on the probability distribution of the porosity in the bed was studied. Finally, the effect of vertical and horizontal electric fields on the bubble diameter was examined. This study offers a deeper understanding of the fluidization of rodlike particles in the presence of an electric field, and its findings can be applied to design and optimize related processes
Sediment Transport Modelling in Densly Populated Urban Areas Due To Earthfill Dam Break
No full textThis study simulates two dimensional sediment transport, as a result of overtopping earthfill dam break, in urban areas. The model can consider breaching, removal of sediment from dam body, and transport of sediment. The model is first validated by simulating laboratory experimental data that involved measurements of levels, and longitudinal sediment profiles, and sediment distribution. Downstream side of the experimental canal is designed as; (1) smooth bed, and (2) rough bed with concrete blocks. For both cases, the model simulations are found to be satisfactory. The model is then applied to simulate artificial overtopping break scenarios of two real earthfill dams. The AW3D30 is used as the source data for representing the topographic surfaces and the LULC dataset is generated from the ESA's Sentinel-2 imagery. The results reveal that downstream of the dams can be subject to both scour, at onset of the dam break, and substantial deposition after having reservoir completely emptied. The cut can go all the way to dam bed. The scoured areas can be refilled after peak discharge recedes. Sediment depths can reach up to 1.5 m in the case of Urkmez Dam break in some areas in the vicinity of Urkmez Town and up to 3 m at the downstream area of Alibey Dam in Istanbul, implying disastrous consequences for the settlement areas
Chlorinated Phosphorene for Energy Application (vol 231, 112625, 2024)
No full text[No Abstract Available
Review of Cell Level Battery (calendar and Cycling) Aging Models: Electric Vehicles
No full textElectrochemical battery cells have been a focus of attention due to their numerous advantages in distinct applications recently, such as electric vehicles. A limiting factor for adaptation by the industry is related to the aging of batteries over time. Characteristics of battery aging vary depending on many factors such as battery type, electrochemical reactions, and operation conditions. Aging could be considered in two sections according to its type: calendar and cycling. We examine the stress factors affecting these two types of aging in detail under subheadings and review the battery aging literature with a comprehensive approach. This article presents a review of empirical and semi-empirical modeling techniques and aging studies, focusing on the trends observed between different studies and highlighting the limitations and challenges of the various models
Archaeometric Study of Roman Bricks and Cocciopesto Aggregates From the Ancient City of Nysa, Western Anatolia
No full textThe aim of this study is to identify the similarities and differences in the raw material properties and manufacturing processes of the building bricks and cocciopesto aggregates present in the lime mortars and plasters from the ancient city of Nysa. For this purpose, X-ray diffraction, Fourier transformed infrared spectroscopy, X-ray fluorescence spectroscopy, scanning electron microscopy coupled with energy dispersive spectroscopy, and thermogravimetric analysis were used to determine their pozzolanic activities, chemical and mineralogical compositions, and microstructural properties. The XRF results were evaluated to determine differences in the chemical composition of the building bricks and cocciopesto aggregates using empirical statistical analyses. Analyses included descriptive statistics, scatter plots, and hierarchical clustering. The bricks were only partially sintered and did not contain high temperature products such as mullite, indicating moderate firing temperatures (900 °C). The cocciopesto aggregates used in the mortars exhibit good pozzolanicity, unlike the building bricks, mainly due to their higher content of amorphous products. This suggests that pozzolanic cocciopesto aggregates were intentionally produced for the purpose of obtaining hydraulic mortars. The significant statistical differences in major oxide and trace element compositions suggest that the use of raw materials with different chemical compositions in the production of bricks and aggregates. The results reveal that pozzolanic cocciopesto aggregates were intentionally manufactured differently to building bricks to create hydraulic lime mortars. © 2024 Elsevier Lt
Art and Construction Related Qualities of 14th‒15th Century Monuments in a Rural Landscape on the Western Coast of Türkiye
No full textThis study aims to contribute to the understanding of the evolution of art and construction in the early settlements established by Turkish communities on the far west Asian coast by focusing on two developed examples in Urla Peninsula. Conventional surveying and evaluation techniques of architectural restoration and civil engineering were utilized. Key findings include the understanding of the hierarchy of rural settlements in the studied landscape: old Çesme the most developed village of peninsula in the 16th century. It was positioned along a valley in distance to coast, but in control of harbor that played significant role in commerce between Europe and Asia. Its mosque and tomb, dated to late 14th – early 15th centuries, used to crown it. Cylindrical minaret tower of mosque, domed tomb tower on a cubical base and squinch in the transition zone of mosque are evidences for Central Asian roots. Usage of local lime stone, re-usage of andesite blocks, framing of the stone blocks with bricks, and pendentive in tomb refer to Roman-Byzantine constructions. The study presents the development of Turkish art and construction on the far west Asian coast in the 14th‒15th centuries. Findings will be a guide for related conservation management in similar contexts. © 2024 The Author(s
Enhancing Low- and High-Frequency Components of the Seismic Data To Emphasise Bsrs and Bright Spots and Implications for Seismic Attribute Analysis
No full textAbstract: The bandwidth of recorded seismic signals is typically limited and influenced by various factors, including seismic source characteristics, receiver response, recording parameters, and subsurface properties. It is always preferable that the data contain both high- and low-frequencies to obtain seismic data with a broad bandwidth to achieve the desired resolution. High frequencies facilitate the discrimination of thin layers, while low-frequency components play a crucial role in hydrocarbon exploration due to the attenuation of the high-frequency seismic signal within the hydrocarbon zone. In this study, a straightforward approach to enhance the low- or high-frequency components of seismic data is proposed to emphasise the BSRs and bright spots. The method involves the integration and differentiation processes, which correspond to linear scaling of the amplitude spectrum of the input seismic data. Through the integration process, the amplitudes of the low-frequency components in the seismic data are amplified, resulting in enhanced visibility of bottom simulating reflections (BSRs) and bright spots. These zones become more prominent in the instantaneous amplitude and frequency sections, and the reflections with reversed polarity, typically obtained from shallow gas accumulations and BSRs, are more continuous in the apparent polarity sections after the integration process. This situation makes the integration process suitable for the submarine fluid flow investigations. On the other hand, the differentiation process enhances the amplitudes of high-frequency components, thus enhancing the temporal resolution of the seismic data. This aspect makes the differentiation process well-suited for studying thin reservoirs or conducting facies analysis in complex sedimentation areas. Research highlights: Integration and differentiation processes correspond to linear scaling of amplitude spectrum. Integration enhances the low-frequency components of the seismic data. Differentiation increases the amplitudes of the high-frequency components. Integration makes the BSRs and bright spots more clear. Differentiation increases the temporal resolution. © Indian Academy of Sciences 2024
Optimization of Injection Molding Process Parameters for Cycle Time
No full textPlastic, an integral part of modern life, is widely used in various sectors such as automotive, aerospace, and healthcare. The rapid advancements in the plastic industry have improved plastic processing technologies. Among contemporary production methods, plastic injection molding has become one of the most commonly used techniques. As industrial markets evolve rapidly, the need to shorten product cycle times, reduce production costs, and increase production speeds to respond swiftly to demand has become increasingly urgent. In this context, the thesis addresses the reduction of cycle times through the optimization of process parameters in the injection molding process. By utilizing experimental data available in the literature, a mathematical model of the injection molding process has been developed using a hybrid method known as Neuro-regression approach and cross-validation technique. To minimize the cycle time of the injection molding process, multi-objective optimization scenarios were created using seven different process parameters and two parameters affecting product quality. Optimization studies were carried out using stochastic optimization methods with the 'Simulated Annealing,' 'Random Search,' 'Nelder-Mead,' and 'Differential Evolution' algorithms in the 'Wolfram Mathematica' program with the help of the 'NMinimize' tool. When comparing the obtained optimization results with those in the literature, it was found that the model and optimization methods used in the study are reliable and applicable.Modern yaşamın en önemli parçası haline gelen plastik, otomotiv, havacılık, tıp gibi çeşitli sektörlerde sıkça kullanılmaktadır. Plastik endüstrisindeki hızlı gelişmeler, plastik işleme teknolojilerini geliştirmiştir. Günümüzün üretim yöntemlerinde, plastik enjeksiyon kalıplama, en yaygın kullanılan üretim yöntemlerinden olmuştur. Endüstriyel pazarlar hızla gelişirken, ürün çevrim sürelerini kısaltma, üretim maliyetlerini düşürmek ve üretim hızlarının arttırılmasıyla talebe hızlı cevap verme ihtiyacı giderek daha acil hale gelmiştir. Bu bağlamda, tez çalışmasında enjeksiyon kalıplama prosesinin proses parametrelerinin optimizasyonu ile çevrim süresinin kısaltılması ele alınmıştır. Literatürde bulunan deneysel veriler kullanılarak, hibrit bir yöntem olan Nöro-regresyon yaklaşımı ve çapraz doğruluma tekniği ile enjeksiyon kalıplama prosesinin matematiksel modellemesi yapılmıştır. Enjeksiyon kalıplama prosesinin çevrim süresinin minimize etme amacıyla, yedi farklı proses parametresi ve iki adet ürün kalitesine etki eden parameter kullanılarak çok amaçlı optimizasyon senaryoları oluşturulmuştur. Optimizasyon çalışmaları, 'Simulated Annealing', 'Random Search', 'Nelder-Mead' ve 'Differential Evolution' algoritmaları kullanılarak 'Wolfram Mathematica' programında 'NMinimize' aracı yardımıyla stokastik optimizasyon yöntemleri ile gerçekleştirilmiştir. Elde edilen optimizasyon sonuçları ve literatürdeki sonuçlar karşılaştırıldığında çalışmada kullanılan modelin ve optimizasyon yöntemlerinin güvenilir ve uygulanabilir olduğu görülmüştür
Simultaneous Topology Design and Optimization of Pde Constrained Processes Based on Mixed Integer Formulations
No full textSimultaneous topological design and optimization of complex processes that are described by partial differential equations is a challenging but promising research area. Widely adopted nested and sequential approaches are mostly applicable based on heuristic solutions, hindering the theoretical improvement potential due to decentralized decision-making in subsequent stages with a significant number of trial-and-error procedures. This study introduces a mixed integer formulation addressing the governing equations and case-dependent topological constraints at each discretization point, enabling solutions through rigorous solvers under process-related constraints and objectives. Nonlinear expressions in the formulations are further tailored using piecewise linear approximations, still representing the major nonlinear trends through a mixed-integer linear nature to favor global optimality and benefit from computational advancements, when needed. Heat and Stokes flow problems are used as case studies to demonstrate the applicability of the methodology. © 2024 Elsevier B.V
A Novel Land Surface Temperature Reconstruction Method and Its Application for Downscaling Surface Soil Moisture With Machine Learning
No full textDownscaling of soil moisture data is important for high resolution hydrological modeling. Most downscaling studies in the literature have used spatially discontinuous land surface temperature (LST) maps as the main auxiliary parameter, which limits the creation of continuous soil moisture maps. The number of studies on soil moisture downscaling with machine learning that use gapless LST maps is limited. With this motivation, a hybrid reconstruction method has been proposed in this study to practically obtain continuous LST maps, which are then used to produce high resolution surface soil moisture (SSM) datasets. The proposed method is shown to have high mean performance with R2 and RMSE values of 0.94 and 1.84°K, respectively, for the period between 2019 and 2022. The developed reconstructed LST maps were then used to downscale original 9 km spatial resolution soil moisture datasets of SMAP L3 and SMAP L4 with Random Forest (RF) machine learning algorithm. The RF model were run with four different rainfall datasets, and the MSWEP rainfall dataset was found to produce the best results. The use of antecedent rainfall values as input variables in machine learning models has been shown to improve the performance of the models R2 0.76 to 0.93. The accuracy of the downscaled data was later evaluated for Western Anatolia Basins (WAB) in Türkiye with 31 in-situ stations. The downscaled SMAP L4 had good average statistical indicators R (0.815 ± 0.1), RMSE (0.09 ± 0.047 cm3/cm3), and ubRMSE (0.058 ± 0.025 cm3/cm3). Downscaled SMAP L3 was also validated with in-situ observations with satisfactory R (0.79 ± 0.074), RMSE (0.09 ± 0.043 cm3/cm3), and ubRMSE (0.06 ± 0.026 cm3/cm3) statistics. Furthermore, the performance of the downscaled SMAP L3 was also cross validated with SMAP + Sentinel 1 (L2) dataset between 2019 and 2022. The mean statistics of R (0.761 ± 0.11) and Root Mean Squared Difference (RMSD) (0.05 ± 0.014 cm3/cm3) between downscaled SMAP L3 and L2 data revealed that the new reconstruction method of LST used in the RF model for downscaling of soil moisture performed well to obtain high resolution soil moisture datasets. The proposed technique also overcame the difficulties associated with coastal regions where data was masked for quality considerations, by not only enhancing overall spatial resolution but also filling these data gaps and giving a complete SSM coverage. © 2024 Elsevier B.V