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Dynamic stability analysis of 18650 cylindrical lithium-ion batteries on elastic foundation: result verification via machine learning algorithm
No full textThis research aims to improve the electro-mechanical and vibration characteristics of cylindrical-lithium-ion batteries using advanced nanocomposite materials reinforced with graphene platelets (GPL); these are inserted as the reinforcement of the cathode layer of spirally cross-section batteries that yield better mechanical properties, thermal conductivity as a combined group, and vibrational stability when loaded dynamically. Also, the structure is surrounded by an elastic foundation. Analytical modeling is also investigated with the Rayleigh–Ritz technique to examine the structural and vibration behavior of the cylindrical batteries, accounting for the intricate relationships between material properties and geometry. Furthermore, a deep neural network (DNN) algorithm is modeled to serve as a predictive tool for the electro-mechanical and vibration response of the batteries operating under various service and environmental conditions. The DNN framework shows remarkable accuracy and efficiency with reliable predictions and low computational cost. The results show the promise of GPL nanocomposites to significantly increase the stability and life of lithium-ion batteries when exposed to mechanical shocks and thermal excursions. This analytical and computational framework provides a solid protocol for the design of the next volume of cylindrical lithium-ion batteries to improve performance. The results clearly position advanced material incorporation and artificial intelligence (AI)-guided predictive modeling to help push the integration of efficient and sustainable energy storage technologies. This work provided a basis for battery technology advancement that will promote better energy storage solutions in multiple applications
Sol–gel synthesis and characterization of 2-phenyl-5-(pyridin-4-yl)-1,3,4-oxadiazole thin films: a structural and optical study
No full text2-phenyl-5-(pyridine-4-yl)-1,3,4-oxadiazole (PYY–OXD) thin films were produced by the spin-coating method. The produced films were annealed at four different temperatures: 60 °C, 80 °C, 100 °C, and 120 °C, and the optimum annealing temperature was determined as 60 °C. Then, to investigate the effect of molarity on the structural and optical properties of thin films, precursor solutions were prepared at two different concentrations, 0.05 M and 0.10 M. The data obtained clearly demonstrate that the concentration of the precursor solution strongly affects its crystallinity, film thickness, and optical transmittance. Films prepared from the 0.05 M solution achieved transmittance values of up to 80%, while films prepared from the 0.10 M solution showed a decrease in transmittance and an improvement in crystallinity. The calculated band gap values were 2.97 eV for 0.05 M and 3.33 eV for 0.10 M, depending on this molarity. Also, the 0.10 M PYY–OXD films showed a good antireflection behavior, with average reflectance values dropping to as low as 6.89%
Adaptation of machine learning models to saturated flow boiling in cross-collector/distributor heat sink with pin-fins under transient and variable thermal loads
No full textFlow boiling in microscale is known for its complex nature and high performance; however, by using machine learning (ML) techniques, predictive analyses can be performed for complex flow nature by eliminating long and costly experimental processes. Here, ML models were applied for first time to datasets got from flow boiling experiments performed by cross-collector/distributor heat sink with pin-fins under transient and variable thermal loads. Four different algorithms—Artificial Neural Networks (ANN), Ensemble of Trees (ET), Support Vector Machines (SVM), and Linear Regression (LR)—were applied and compared to estimate characteristics of micro-flow-boiling via input parameters, namely, mass flux (G = 155, 220, 285 kgm−2 s−1), inclination angle (IA = 0,10,25,40,55°), and effective heat flux (qeff″=179.7 to 382.6 kWm−2). A high-speed-visualization was performed. It resulted that increasing inclination angle had a beneficial impact on thermal performance at relatively low mass flux (G = 155 kgm−2 s−1). For higher mass fluxes (G = 285 kgm−2 s−1), lowest thermal performance was observed at highest angle (IA = 55°). Pressure drop (ΔP) increased with applied heating power (qap), and influence of IA on ΔP was negligible. The Ensemble of Trees (ET) model provided most accurate and reliable predictions across all target variables, while Linear Regression (LR) model showed least accurate predictions among the four models
Gübrelerin Sınıflandırılması
No full textÇay Tarımı Dersi 9. Hafta Ders Notu Konusu : Gübrelerin Sınıflandırılmas
The effectiveness of a WhatsApp-based educational intervention aimed at improving mothers' fever management: A randomized controlled trial
No full textAim This study aimed to determine the effect of WhatsApp-based education on mothers' knowledge, attitude and practices regarding fever management at home. Method The study was conducted using a randomized controlled experimental design. It included 64 mothers (32 in the intervention group and 32 in the control group) who met the inclusion criteria. The intervention group received online fever management education via WhatsApp messages. Data were collected using the “Mother and Child Information Form”, “Parent Fever Management Scale”, “Fever Management Knowledge, Attitude and Practice Questionnaire” and “E-Health Literacy Scale.” Two-way mixed-design ANOVA was used to examine group, time, and group × time interactions. Results The intervention group demonstrated significantly higher scores compared to the control group, with the intervention having a large effect on fever management ( p < 0.001, η2 = 0.320), fever knowledge, attitude and practice level (p < 0.001, η2 = 0.585), and e-health literacy level (p < 0.001, η2 = 0.215). Conclusion Online fever management education delivered via WhatsApp messages is effective in reducing mothers' fever-related care burdens, increasing fever knowledge, attitude and practice levels, and improving e-health literacy levels. Practice implications Educational content shared via WhatsApp, a widely used application, is easily accessible. These resources can be used by pediatric nurses in clinics as short and effective educational materials for mothers. The clinical trial registration number is NCT07061327
Investigation of latent heat storage performance of a solar collector incorporating dimpled dendritic fins and nano-additive phase change material
No full textIn this numerical study, the melting and thermal energy storage performance of phase change material (PCM) integrated into flat-plate solar collector (FPSC) was investigated using dendritic fins with different dimple geometries (spherical, elliptical, trapezoidal), Fe3O4 nanoparticles at different volume concentrations (φ = 0.5, 1.0, 2.0, 3.0 vol%), and metal foam (MF). The low thermal conductivity of PCMs limits the performance of latent heat thermal energy storage (LHTES) systems by prolonging the phase change periods. Therefore, the study aims to optimize the thermal performance by combining the effects of MF, which increases the effective thermal conductivity of the system, dendritic fins that increase the heat transfer surface area, and nanoparticles that improve the thermophysical properties. Numerical computations were managed under the condition of constant heat flux of q" = 1000 W m−2 using the enthalpy-porosity method and the local thermal equilibrium approach in ANSYS Fluent software. Analyses were conducted for total of 25 different cases. The results showed that the addition of nanoparticles suppressed natural convection, decreasing the melting performance, while dimpled dendritic fins increased the melting rate by 79 %. The highest melting rate was achieved with trapezoidal dimpled dendritic fins (complete melting in 21 min). Furthermore, the highest stored energy of 279 kJ kg−1 was obtained with spherical dimpled dendritic fins. The novelty of this study is the use of dimpled dendritic fins for the first time in literature and their integration into FPSC as hybrid system with MF + nano-PCM. This design contributes to the development of next-generation compact and high-efficiency LHTES system
Çay Bitkisinin Gübrelenmesi ( Doğal Gübreler)
No full textÇay Tarımı Dersi 10. Hafta Ders Notu Konusu : Çay Bitkisinin Gübrelenmesi ( Doğal Gübreler
The usage of tea factory waste as soil substrate for the production of snap bean (phaseolus vulgaris l.)
No full textIntensive use of inorganic chemicals in agriculture causes soil inefficiency. Alternative sources are needed to ensure the sustainability of agriculture. Utilizing organic wastes presents a feasible solution as they can support plant growth while ensuring their elimination. This study investigated the potential for utilizing the large amount of waste generated during tea processing in tea factories every year in snap bean cultivation. The effects of tea factory waste mixed into the soil at four different rates were compared to the soil and the soil to which farmyard manure was added. The study was conducted in pots. The experiment was designed with three replications according to randomized complete blocks. The effects of the growth media were determined using 26 parameters related to plant development and yield. Observations made 30 days after seed sowing and at the end of harvest revealed that tea factory waste treatments made significant contributions to plant height, stem diameter, and the number of trifoliate leaves compared to soil, which had no added organic matter. However, the SPAD values were negatively affected. All findings revealed that the T4 medium containing equal parts soil and tea waste created the best results, except for the growth medium containing the farmyard. In conclusion, it was found that tea factory waste can be a beneficial organic matter for the growth and development of snap bean plants. To maximize its usefulness as a new source, promoting the populations of fungal and bacterial agents that facilitate its rapid decomposition in the soil is necessary
Investigation of remainder terms in the ergodic distribution and moments of a renewal-reward process with heavy-tailed demand
No full textThis study investigated the detailed asymptotic behavior of the remainder terms in the ergodic distribution and its moments for a semi-Markovian renewal-reward process modeling an (s, S)-type inventory system. We focused on systems in which the demand random variables were heavy-tailed, specifically regularly varying with index-alpha, where 1 < alpha < 2. While the first two terms in the asymptotic expansion of such models are available in the literature, earlier works have not provided sharp quantitative descriptions of the remainder. Our aim was to derive rigorous expressions that capture the exact decay of the remainder in both the ergodic distribution function and in the corresponding moments. Building on Doney's refinement of the renewal theorem [1], which distinguishes three main settings: the non-critical case alpha not equal 3/2, the critical case alpha = 3/2 with square-integrable equilibrium distribution, and the case where such integrability fails, we established new asymptotic expansions that explicitly capture the decay structure of the remainder. Using this framework, we analyzed the remainder for both the ergodic distribution and its moments for each scenario