This paper delves into the practical application of K-Nearest Neighbors (KNN), Kernel Ridge Regression (KRR), and Lasso for prediction viscosity ionic liquids in a dataset characterized by categorical variables (Cation, Anion) numeric (T(K), xIL(mol%)). Indeed, mole percentage temperature were considered as inputs models. The models' effectiveness is rigorously assessed, with notably exhibiting exceptional predictive performance. To enhance model accuracy, Tabu Search employed an...

We find the optimally time-dependent (OTD) orthogonal modes about a time-varying flow generated by strong gust vortex impacting NACA 0012 airfoil. This OTD analysis reveals amplification characteristics of perturbations unsteady base and their amplified spatiotemporal structures that evolve over time. consider four laminar flows in which with strength corresponding to ratio $G$ $\{-1,-0.5,0.5,1\}$ impinges on leading edge airfoil at an angle attack $12^\circ$. In these cases, impingement...

We find the optimally time-dependent (OTD) orthogonal modes about a time-varying flow generated by strong gust vortex impacting NACA 0012 airfoil. This OTD analysis reveals amplification characteristics of perturbations unsteady base and their amplified spatiotemporal structures that evolve over time. consider four laminar flows in which with strength corresponding to ratio $G$ $\{-1,-0.5,0.5,1\}$ impinges on leading edge airfoil at an angle attack $12^\circ$ . In these cases, impingement...

Understanding the linear growth of disturbances due to external forcing is crucial for flow stability analysis, control, and uncertainty quantification. These applications typically require a large number forward simulations forced linearized dynamics, often in brute-force fashion. When dealing with simple steady-state or periodic base flows, there exist powerful cost-effective solution operator techniques. Once these operators are constructed, they can be used determine response various...

The development of artificial microscopic robots, like synthetic microswimmers, is one the state-of-the-art research topics due to their promising biomedical applications. movement microswimmers affected by stringent constraints because low Reynolds number surrounding environment. Researchers have been working on enhancing microrobots' propulsion tactics and figuring out new approaches find optimal strategies. In this research, we employ a Reinforcement Learning (RL) algorithm, specifically...

New strategy is presented to optimize the performance of Thermoelectric (TE) coolers. This approach breaks optimizing TE coolers free from traditional methods controlling temperature or engineering materials and structural properties junctions. We introduced a dimensionless figure, {\gamma}, that shows ratio unavailable cooling capacity available capacity. parameter relates coolers' coefficient (COP) COP reversible cycle (second law thermodynamics efficiency) for given electrical current....

We explore the collaborative dynamics of an innovative language model interaction system involving advanced models such as GPT-4-0125-preview, Meta-LLaMA-3-70B-Instruct, Claude-3-Opus, and Gemini-1.5-Flash. These generate answer complex, PhD-level statistical questions without exact ground-truth answers. Our study investigates how inter-model consensus enhances reliability precision responses. By employing methods chi-square tests, Fleiss' Kappa, confidence interval analysis, we evaluate...

Understanding the linear growth of disturbances due to external forcing is crucial for flow stability analysis, control, and uncertainty quantification. These applications typically require a large number forward simulations forced linearized dynamics, often in brute-force fashion. When dealing with simple steady-state or periodic base flows, there exist powerful cost-effective solution operator techniques. Once constructed, these operators can be used determine response various forcings...