Effects of surface heat flux‐induced sea surface temperature changes on tropical cyclone intensity

It is known that in deep and open oceans, the effect of sea surface sensible and evaporative heat fluxes on the tropical cyclone‐induced sea surface cooling is small compared to that caused by turbulent mixing and cold water entrainment into the upper ocean mixed‐layer. This study shows that tropical cyclone‐induced surface heat fluxes dominate the surface cooling in near‐coastal shallow ocean regions with limited or no underlying cold water. The thermal response of the ocean to the surface heat fluxes is nearly one dimensional through very quick vertical mixing in the ocean mixed layer. The flux‐induced sea surface cooling may lead to appreciable reduction of storm intensity if the storm moves slowly. It is therefore important to account this negative feedback of ocean coupling in near‐coastal regions for more skillful forecasting of landfalling tropical cyclones

The impact of ocean coupling on hurricanes during landfall

The impact of ocean coupling on landfalling hurricanes is studied using a coupled hurricane‐ocean model with idealized atmospheric and oceanic conditions. We focus here on coastal sea surface temperature responses and their effects on hurricanes during landfall. We find that given the ocean thermal stratification, the hurricane‐induced sea surface cooling is nearly independent of the ocean depth as long as the ocean is considerably deeper than the mixed layer. After the storm center moves inland, the near‐surface processes around the storm core area are influenced by the sea surface cooling behind and on the right side of the storm track via reduction of near‐surface entropy advection into this area. The impact of ocean coupling is generally limited to the early times after landfall and nearly disappears after the hurricane center reaches about 200 km inland

Synergistic Damage Mechanic Model for Stiffness Properties of Early Fatigue Damage in Composite Laminates

AbstractIn the initial period of the life in the composite laminates, the principal types of damage are diffused ones, such as matrix crack, diffused fiber breaking and local delamination. On account of these diffused damages, a synergistic damage mechanic model was proposed for the stiffness properties. The model included the microcosmic responses of the physical damage and macroscopic performance of the material's stiffness. In micro-level, mesoscopic RVE(representative volume element) model was established to obtain crack opening displacement and crack sliding displacement, which were used to define the damage tensor. In macro- level, through homogenizing the material strain and the surface displacement of the damage, the relationship of the stiffness matrix of unidirectional laminate or laminates in damage statue and damage tense was set up. Due to restriction of NDT (non- destructive testing) technology development, only the constitutive relations of matrix cracks were constructed. The influences of the transverse matrix cracks on the stiffness properties of the laminates [0/±45]s was analyzed with the present model and showed that it is capable to predict the reduction of the stiffness properties resulted from the fatigue diffused damage in the laminates

A Sensitivity Study of the Thermodynamic Environment on GFDL Model Hurricane Intensity: Implications for Global Warming

In this study, the effect of thermodynamic environmental changes on hurricane intensity is extensively investigated with the National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory hurricane model for a suite of experiments with different initial upper-tropospheric temperature anomalies up to ±4°C and sea surface temperatures ranging from 26° to 31°C given the same relative humidity profile. The results indicate that stabilization in the environmental atmosphere and sea surface temperature (SST) increase cause opposing effects on hurricane intensity. The offsetting relationship between the effects of atmospheric stability increase (decrease) and SST increase (decrease) is monotonic and systematic in the parameter space. This implies that hurricane intensity increase due to a possible global warming associated with increased CO2 is considerably smaller than that expected from warming of the oceanic waters alone. The results also indicate that the intensity of stronger (weaker) hurricanes is more (less) sensitive to atmospheric stability and SST changes. The model-attained hurricane intensity is found to be well correlated with the maximum surface evaporation and the large-scale environmental convective available potential energy. The model-attained hurricane intensity is highly correlated with the energy available from wet-adiabatic ascent near the eyewall relative to a reference sounding in the undisturbed environment for all the experiments. Coupled hurricane–ocean experiments show that hurricane intensity becomes less sensitive to atmospheric stability and SST changes since the ocean coupling causes larger (smaller) intensity reduction for stronger (weaker) hurricanes. This implies less increase of hurricane intensity related to a possible global warming due to increased CO2

A Numerical Investigation of Land Surface Water on Landfalling Hurricanes

Little is known about the effects of surface water over land on the decay of landfalling hurricanes. This study, using the National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory hurricane model, examines the surface temperature changes due to hurricane–land surface water interactions, and their effects on the surface heat fluxes, hurricane structure, and intensity. Different water depths and surface conditions are incorporated for a variety of experiments starting with a hurricane bogus embedded in a uniform easterly mean flow of 5 m s−1. A salient feature of hurricane–land surface water interaction is the local surface cooling near the hurricane core with the largest cooling behind and on the right side of the hurricane center. Unlike the surface cooling due to hurricane–ocean interaction, the largest cooling in hurricane–land surface water interaction can be much closer to the hurricane core. Without solar radiation during night, the surface evaporation dominates the local surface cooling. This causes a surface temperature contrast between the core area and its environment. During the day, the surface temperature contrast is enhanced due to additional influence from the reduced solar radiation under the core. Related to the local surface cooling, there is a significant reduction of surface evaporation with a near cutoff behind the hurricane center. A layer of half-meter water can noticeably reduce landfall decay although the local surface temperature around the hurricane core region is more than 4°C lower than in its environment. Further experiments indicate that an increase of roughness reduces the surface winds but barely changes the surface temperature and evaporation patterns and their magnitudes since the increase of roughness also increases the efficiency of surface evaporation

Construction of a polarization insensitive lens from a quasi-isotropic metamaterial slab

We propose to employ the quasiisotropic metamaterial (QIMM) slab to construct a polarization insensitive lens, in which both E- and H-polarized waves exhibit the same refocusing effect. For shallow incident angles, the QIMM slab will provide some degree of refocusing in the same manner as an isotropic negative index material. The refocusing effect allows us to introduce the ideas of paraxial beam focusing and phase compensation by the QIMM slab. On the basis of angular spectrum representation, a formalism describing paraxial beams propagating through a QIMM slab is presented. Because of the negative phase velocity in the QIMM slab, the inverse Gouy phase shift and the negative Rayleigh length of paraxial Gaussian beam are proposed. We find that the phase difference caused by the Gouy phase shift in vacuum can be compensated by that caused by the inverse Gouy phase shift in the QIMM slab. If certain matching conditions are satisfied, the intensity and phase distributions at object plane can be completely reconstructed at image plane. Our simulation results show that the superlensing effect with subwavelength image resolution could be achieved in the form of a QIMM slab.Comment: 25 pages, 8 figure

A Micro–Macro Damage Mechanics-based Model for Fatigue Damage and Life Prediction of Fiber-reinforced Composite Laminates

A multidirectional damage model was proposed to predict fatigue damage evolution and final failure of composite laminates in this paper. A damage characterization model for composite laminates was established to characterize the influence of three main damage modes on the damaged mechanical behavior of composite laminates at micro–macro level. The damage evolution model was also established based on damage mechanics to predict the evolution of the three damage modes and stiffness degradation of composite laminates by means of damage characterization model. Then, a relationship between residual stiffness and residual strength was introduced, from which the residual strength could be obtained according to the predicted residual stiffness. When the residual strength is calculated to decrease to the maximum applied stress of fatigue loading after several cycles, the composite laminate was assumed to fail, and accordingly the fatigue life could be obtained. In order to verify the model, the predicted stiffness degradation and fatigue life of two cross-ply laminates under fatigue loadings with different stress levels were compared to experimental results. The standard derivation of stiffness degradation and average errors of fatigue between prediction results and experimental results were less than 0.1 and 8.26%, respectively, indicating the effectiveness and reliability of proposed model

MUSER: A Multi-View Similar Case Retrieval Dataset

Similar case retrieval (SCR) is a representative legal AI application that plays a pivotal role in promoting judicial fairness. However, existing SCR datasets only focus on the fact description section when judging the similarity between cases, ignoring other valuable sections (e.g., the court's opinion) that can provide insightful reasoning process behind. Furthermore, the case similarities are typically measured solely by the textual semantics of the fact descriptions, which may fail to capture the full complexity of legal cases from the perspective of legal knowledge. In this work, we present MUSER, a similar case retrieval dataset based on multi-view similarity measurement and comprehensive legal element with sentence-level legal element annotations. Specifically, we select three perspectives (legal fact, dispute focus, and law statutory) and build a comprehensive and structured label schema of legal elements for each of them, to enable accurate and knowledgeable evaluation of case similarities. The constructed dataset originates from Chinese civil cases and contains 100 query cases and 4,024 candidate cases. We implement several text classification algorithms for legal element prediction and various retrieval methods for retrieving similar cases on MUSER. The experimental results indicate that incorporating legal elements can benefit the performance of SCR models, but further efforts are still required to address the remaining challenges posed by MUSER. The source code and dataset are released at https://github.com/THUlawtech/MUSER.Comment: Accepted by CIKM 2023 Resource Trac

LEEC: A Legal Element Extraction Dataset with an Extensive Domain-Specific Label System

As a pivotal task in natural language processing, element extraction has gained significance in the legal domain. Extracting legal elements from judicial documents helps enhance interpretative and analytical capacities of legal cases, and thereby facilitating a wide array of downstream applications in various domains of law. Yet existing element extraction datasets are limited by their restricted access to legal knowledge and insufficient coverage of labels. To address this shortfall, we introduce a more comprehensive, large-scale criminal element extraction dataset, comprising 15,831 judicial documents and 159 labels. This dataset was constructed through two main steps: first, designing the label system by our team of legal experts based on prior legal research which identified critical factors driving and processes generating sentencing outcomes in criminal cases; second, employing the legal knowledge to annotate judicial documents according to the label system and annotation guideline. The Legal Element ExtraCtion dataset (LEEC) represents the most extensive and domain-specific legal element extraction dataset for the Chinese legal system. Leveraging the annotated data, we employed various SOTA models that validates the applicability of LEEC for Document Event Extraction (DEE) task. The LEEC dataset is available on https://github.com/THUlawtech/LEEC