The Centennial Variation of El Niño Impact on Atlantic Tropical Cyclones

Predicting tropical cyclone (TC) activity becomes more important every year while the understanding of what factors impact them continues to be complicated. El Niño–Southern Oscillation (ENSO) is one of the primary factors impacting the activities in both the Pacific and the Atlantic, but an extensive examination of the fluctuation in this system has yet to be studied in its entirety. This article analyzes the ENSO impacts on the Atlantic tropical cyclone activity during the assessed warm and cold years to show the dominant centennial-scale variation impact. This study looks to plausibly link this variation to the Southern Ocean centennial variability, which is rarely mentioned in any factors affecting the Atlantic tropical cyclone activity. This centennial variability could be used to enhance future work related to predicting tropical cyclones

Transonic Inviscid Disc Flows in the Schwarzschild Metric – I

The coupled hydrodynamic equations governing equatorial flows applicable to inviscid disc accretion in the Schwarzschild metric are solved analytically and numerically. Here, we concentrate on the transonic solutions, that represent physically allowed accretion on to black holes. A polytropic equation linking gas pressure and density is assumed, and solutions are obtained for different conditions, such as isothermal and adiabatic gas flows. The dependence of those solutions on the angular momentum is explored. Under certain conditions, when there exist multiple possible sonic points, the numerical simulation automatically zeros in to the unique transonic solution passing through one of the sonic points

Shock Study in Fully Relativistic Isothermal Flows. II

The isothermal shocks and their stabilities in fully relativistic accretion wedge flows onto black holes are studied. The jump condition across the shock is modified by the relativistic effects when the sound speed is comparable to the speed of light. With a new kind of instability analysis, it is found that only one of the two possible shocks is stable. The results are applied to the QPO behavior in galactic black hole candidates such as Cygnus X-1

Improved Associated Conditions in Rapid Intensifications of Tropical Cyclones

Rapid intensification (RI) of tropical cyclones (TC) is a major error source in TC intensity forecasting. In order to improve the estimates of RI probability, association rules are used to facilitate the process of mining for candidate sets of conditions. Compared to the relation analysis method, the technique of association rules can simply explore associations among multiple conditions. Our mining results identified a reduced predictor set with fewer factors identified in previous studies but improved RI probabilities. That is, the RI probability with three conditions satisfied: low vertical shear, high humidity, and the TC being in an intensification phase is higher than that with five satisfied conditions including high sea surface temperature and an intensity far away from the maximum potential intensity in addition to the above three

Numerical Simulation on Heat Transfer Performance of Silicon Carbide/ Nitrate Composite for Solar Power Generation

KNO3 was used as the phase change material (PCM), but its thermal conductivity is too low to transfer heat between the PCM and conduction oil efficiently. In this thesis, on the basis of the previous studies (Yong Li, 2015), the solar power generation efficiency is enhanced with high temperature interval (280℃—400℃), and the new composite which are composed by the SiC honeycomb (SCH) frame and infiltrated KNO3 is simulated by using Fluent software. The results show that the new composite of the KNO3 +30%SCH suit for the requirement of the charging time and capacity in the design of the thermal energy storage units (TESU); The comparable simulation for the long and short pipe models supplies the evidences that the long pipe simulation can be substituted by the short pipe simulation relatively, which reduces the 3-D simulation time enormously; The comparable simulation of the radial dimensions supplies some theory foundations for the design of the module thermal energy storage tank (MTEST) . These simulation results have important guidance on the design of the thermal energy storage unit and the module thermal energy storage tank

Robust Power Allocation for UAV-aided ISAC Systems with Uncertain Location Sensing Errors

Unmanned aerial vehicle (UAV) holds immense potential in integrated sensing and communication (ISAC) systems for the Internet of Things (IoT). In this paper, we propose a UAV-aided ISAC framework and investigate three robust power allocation schemes. First, we derive an explicit expression of the Cram\'er-Rao bound (CRB) based on time-of-arrival (ToA) estimation, which serves as the performance metric for location sensing. Then, we analyze the impact of the location sensing error (LSE) on communications, revealing the inherent coupling relationship between communication and sensing. Moreover, we formulate three robust communication and sensing power allocation problems by respectively characterizing the LSE as an ellipsoidal distributed model, a Gaussian distributed model, and an arbitrary distributed model. Notably, the optimization problems seek to minimize the CRB, subject to data rate and total power constraints. However, these problems are non-convex and intractable. To address the challenges related to the three aforementioned LSE models, we respectively propose to use the ${\cal{S}}$-Procedure and alternating optimization (${\cal{S}}$-AO) method, Bernstein-type inequality and successive convex approximation (BI-SCA) method, and conditional value-at-risk (CVaR) and AO (CVaR-AO) method to solve these problems. Finally, simulation results demonstrate the robustness of our proposed UAV-aided ISAC system against the LSE by comparing with the non-robust design, and evaluate the trade-off between communication and sensing in the ISAC system

High-dimensional FGM-ResNet modelling of turbulent spray combustion: Effects of evaporation non-adiabacity and scalar correlation

In the stratified or partially premixed piloted jet flames, previous experimental and priori studies have identified a strong correlation between mixture fraction and progress variable. In the framework of large-eddy simulation (LES) and flamelet-generated manifolds (FGM) approach, a joint probability density function (PDF) method is constructed to characterize subgrid correlations. To pave the way for high dimensional tabulation modeling, a deep residual network (ResNet) is trained, dramatically reducing the memory footprint of tabulation. The Message Passing Interface (MPI) shared memory technique is applied to load the original chemical table during parallel computations. Application of LES to a partially pre-vaporized ethanol spray flame demonstrates good agreement with experimental results. Consideration of the subgrid correlation results in a noticeable improvement in temperature prediction. Calculations using ResNet show a notable consistency with those using chemical tables. Visualization of enthalpy highlights the significance of non-adiabatic tabulation in modeling liquid fuel combustion. The unscaled progress variable is selected to better describe the chemical reaction rate in the blending zone of an air stream and a pilot stream with the product of a fully burnt lean fuel mixture. The impact of the source term due to evaporation in the transport equation of the progress variable is validated. The correlation coefficient is found to significantly influence the chemical reaction rate. The subgrid-scale interaction between liquid fuel evaporation and subgrid correlation is elucidated

Confidence Calibration and Rationalization for LLMs via Multi-Agent Deliberation

Uncertainty estimation is a significant issue for current large language models (LLMs) that are generally poorly calibrated and over-confident, especially with reinforcement learning from human feedback (RLHF). Unlike humans, whose decisions and confidences not only stem from intrinsic beliefs but can also be adjusted through daily observations, existing calibration methods for LLMs focus on estimating or eliciting individual confidence without taking full advantage of the "Collective Wisdom": the interaction among multiple LLMs that can collectively improve both accuracy and calibration. In this work, we propose Collaborative Calibration, a post-hoc training-free calibration strategy that leverages the collaborative and expressive capabilities of multiple tool-augmented LLM agents in a simulated group deliberation process. We demonstrate the effectiveness of Collaborative Calibration on generative QA tasks across various domains, showing its potential in harnessing the rationalization of collectively calibrated confidence assessments and improving the reliability of model predictions.Comment: Accepted at ICLR 2024 Workshop on Reliable and Responsible Foundation Model

Role of Anomalous Warm Gulf Waters in the Intensification of Hurricane Katrina

The year 2005 experienced several strong hurricanes intensifying in the Gulf of Mexico before making landfall that severely damaged the Gulf States, especially Hurricane Katrina. Remarkable similarities between sea surface temperature anomaly (SSTA) and major hurricane (categories 3 and higher) activity over the Gulf are identified. However, the intensification of individual hurricanes may not necessarily be temporally and spatially coincident with the distribution of warm waters or high sea surface temperature (SST). High SST values are found in advance of significant intensification of Hurricane Katrina. We emphasize that high SSTA which occurred at the right time and right place was conducive to the hurricane intensification. In particular, high SSTA in the northeastern quadrant of the storm track induced significant increases in surface latent heat fluxes (LHF) contributing to the rapid intensification of Katrina. We also compared and verified model simulations with buoy observations