Structure-thermal coupling in viscoelastic material in rubber bushing of vehicle system

The objective of this research is to utilize the frequency-dependent viscoelastic material model and characterize the dynamic response of rubber bushing under external excitation. Furthermore, with appropriate modeling, two heat generation mechanisms of rubber bushing are explored and their thermal fields are investigated. Due to the nonlinear force-deflection relationship of the viscoelastic material, finding satisfactory mechanical properties of rubber components still poses a great challenge. However, industry nowadays is in urgent demand for precise finite element analysis (FEA) modeling of rubber components. For example, a proper constitutive relationship of rubber components is critical to providing a reliable and trustable simulation of vehicle suspension systems. As for current FEA commercial software, the frequency-dependent modulus of viscoelastic material hasn\u27t been presented well and they have failed to provide satisfactory results. Therefore, two approaches, FEA and the multi-body dynamic analysis have been selected together to give a more comprehensive and credible prediction of suspension system\u27s performance in different working conditions. The FEA approach evaluated the stability of rubber bushing in view of the dynamic response and temperature distribution under high frequency excitation. With these results, the life prediction of rubber bushing becomes more feasible. The multi-body dynamic analysis explores the structure instability of rubber bushing when exposed to extremely high frequency and estimates the energy dissipation in the rubber core.^ The key innovations of this paper can be classified into four aspects. The first one is the application of multi-body dynamics in the dynamic analysis of rubber bushing. Based on experimental modal analysis, the sandwich cylindrical rubber bushing is treated as multi-body. With the multi-body model, the transfer function of the rubber bushing is calculated in order to estimate the dynamic response. The second innovation comes from the development of the FORTRAN program to solve the system transfer function of the structure made of viscoelastic material. Since the geometry and boundary conditions are amenable in FEA compared with the experimental modal testing, this approach is not just applicable in rubber bushing dynamic analysis, but also useful in dynamic analysis of different rubber components. The third innovative contribution of this research is connecting the multi-body analysis with continuum mechanics to evaluate the mechanical properties of rubber bushing. The last innovation is the structure-thermal coupling of rubber bushing to predict its temperature distribution based on the heat source calculated from the FEA simulation. The finite volume method (FVM) is applied using MATLAB in the simulation of temperature distribution. In this research, the classical standard linear model is applied in the FEA program to characterize the variation of viscoelastic material in the frequency domain. The three parameters of this model have been identified with the batch data measurement using dynamic mechanical analysis equipment (DMA). Specially, two heat generation mechanisms are explored to emphasize the friction-induced hysteresis damping except for the commonly discussed viscous damping. As complementation of FORTRAN program simulation in the frequency domain, the multi-physics commercial software COMSOL is employed to estimate the dynamic response of rubber bushing and temperature distribution in the time domain. To verify the results of FEA and multi-body dynamic approach in the dynamic and thermal analysis of rubber bushing, dynamic tests have been carried out using torsion and tensile testing machines. The experimental temperature distribution is in good agreement with the simulation results, which indicated the feasibility of the FEA method.^ However, due to the limited experience and complicated constitutive relationship of the viscoelastic material, the standard linear viscoelastic model is chosen to simulate the heat dissipation mechanism of rubber core. The high-frequency or high-temperature dynamic testing are almost impossible because of the experiment equipments\u27 range of service. As the first step of predicting the dissipation energy density and temperature distribution of rubber components, the initial explorations are significant and provide a proper guidance for further predictions about life expectation

Light Regulation of Phytoplankton Growth in San Francisco Bay Studied Using a 3D Sediment Transport Model

In San Francisco Bay (SFB), light availability is largely determined by the concentration of suspended particulate matter (SPM) in the water column. SPM exhibits substantial variation with time, depth, and location. To study how SPM influences light and phytoplankton growth, we coupled a sediment transport model with a hydrodynamic model and a biogeochemical model. The coupled models were used to simulate conditions for the year of 2011 with a focus on northern SFB. For comparison, two simulations were conducted with ecosystem processes driven by SPM concentrations supplied by the sediment transport model and by applying a constant SPM concentration of 20 mg l1. The sediment transport model successfully reproduced the general pattern of SPM variation in northern SFB, which improved the chlorophylla simulation resulting from the biogeochemical model, with vertically integrated primary productivity varying greatly, from 40 g[C] m2 year1 over shoals to 160 g[C] m2 year1 in the deep channel. Primary productivity in northern SFB is influenced by euphotic zone depth (Ze). Our results show that Ze in shallow water regions (\u3c2 \u3em) is mainly determined by water depth, while Ze in deep water regions is controlled by SPM concentration. As a result, Ze has low (high) values in shallow (deep) water regions. Large (small) differences in primary productivity exist between the two simulations in deep (shallow) water regions. Furthermore, we defined a new parameter Flight for “averaged light limitation” in the euphotic zone. The averaged chlorophyll-a concentration in the euphotic zone and Flight share a similar distribution such that both have high (low) values in shallow (deep) water regions. Our study demonstrates that light is a critical factor in regulating the phytoplankton growth in northern SFB, and a sediment transport model improves simulation of light availability in the water column

Assessment of Hydrodynamic and Water Quality Impacts for Channel Deepening in the Thimble Shoals, Norfolk Harbor, and Elizabeth River Channels : Final report on the “hydrodynamic modeling”

For over twenty years, the U. S. Army Corps of Engineers (USACE) and the Virginia Port Authority (VPA), representing the Commonwealth Secretary of Transportation, have collaborated on projects key to port development that also preserve the environmental integrity of both Hampton Roads and the Elizabeth River. The USACE and the VPA are working to investigate channel deepening in this region to provide access to a new generation of cargo ships (e.g., Panamax-class). The main goal of this project is to investigate the feasibility for Norfolk Harbor channel deepening in the lower James and Elizabeth Rivers and assess the environmental impact of the shipping channels dredging in Atlantic Ocean Channel, Thimble Shoal Channel, Elizabeth River channel, and the Southern Branch. Specifically, we support the request of “Planning and Engineering Services for Norfolk Harbor” in three areas: (1) using high-resolution hydrodynamic modeling to evaluate the change of hydrodynamics resulting from Channel Deepening (2) assessment of water quality modeling using the Hydrodynamic Eutrophication Model (HEM3D) (3) conducting the statistical measure of impacts resulting from Channel Deepening. Virginia Institute of Marine Science (VIMS) team has applied a3D unstructured-grid hydrodynamic model (SCHISM, Zhang et al., 2016) in the study of impact of channel dredging on hydrodynamics in the project area. The model was adopted due to its flexible gridding systems used: hybrid triangular-quadrangular unstructured grids in the horizontal and flexible vertical coordinate system in the vertical (Zhang et al. 2015). High resolution (up to 15m) is used to faithfully resolve the channels and other important features such as tunnel islands, etc

FedALA: Adaptive Local Aggregation for Personalized Federated Learning

A key challenge in federated learning (FL) is the statistical heterogeneity that impairs the generalization of the global model on each client. To address this, we propose a method Federated learning with Adaptive Local Aggregation (FedALA) by capturing the desired information in the global model for client models in personalized FL. The key component of FedALA is an Adaptive Local Aggregation (ALA) module, which can adaptively aggregate the downloaded global model and local model towards the local objective on each client to initialize the local model before training in each iteration. To evaluate the effectiveness of FedALA, we conduct extensive experiments with five benchmark datasets in computer vision and natural language processing domains. FedALA outperforms eleven state-of-the-art baselines by up to 3.27% in test accuracy. Furthermore, we also apply ALA module to other federated learning methods and achieve up to 24.19% improvement in test accuracy.Comment: Accepted by AAAI 202

FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy

Recently, personalized federated learning (pFL) has attracted increasing attention in privacy protection, collaborative learning, and tackling statistical heterogeneity among clients, e.g., hospitals, mobile smartphones, etc. Most existing pFL methods focus on exploiting the global information and personalized information in the client-level model parameters while neglecting that data is the source of these two kinds of information. To address this, we propose the Federated Conditional Policy (FedCP) method, which generates a conditional policy for each sample to separate the global information and personalized information in its features and then processes them by a global head and a personalized head, respectively. FedCP is more fine-grained to consider personalization in a sample-specific manner than existing pFL methods. Extensive experiments in computer vision and natural language processing domains show that FedCP outperforms eleven state-of-the-art methods by up to 6.69%. Furthermore, FedCP maintains its superiority when some clients accidentally drop out, which frequently happens in mobile settings. Our code is public at https://github.com/TsingZ0/FedCP.Comment: Accepted by KDD 202

GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning

Federated Learning (FL) is popular for its privacy-preserving and collaborative learning capabilities. Recently, personalized FL (pFL) has received attention for its ability to address statistical heterogeneity and achieve personalization in FL. However, from the perspective of feature extraction, most existing pFL methods only focus on extracting global or personalized feature information during local training, which fails to meet the collaborative learning and personalization goals of pFL. To address this, we propose a new pFL method, named GPFL, to simultaneously learn global and personalized feature information on each client. We conduct extensive experiments on six datasets in three statistically heterogeneous settings and show the superiority of GPFL over ten state-of-the-art methods regarding effectiveness, scalability, fairness, stability, and privacy. Besides, GPFL mitigates overfitting and outperforms the baselines by up to 8.99% in accuracy.Comment: Accepted by ICCV202

Cross-Scale Baroclinic Simulation of the Effect of Channel Dredging in an Estuarine Setting

Holistic simulation approaches are often required to assess human impacts on a river-estuary-coastal system, due to the intrinsically linked processes of contrasting spatial scales. In this paper, a Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) is applied in quantifying the impact of a proposed hydraulic engineering project on the estuarine hydrodynamics. The project involves channel dredging and land expansion that traverse several spatial scales on an ocean-estuary-river-tributary axis. SCHISM is suitable for this undertaking due to its flexible horizontal and vertical grid design and, more importantly, its efficient high-order implicit schemes applied in both the momentum and transport calculations. These techniques and their advantages are briefly described along with the model setup. The model features a mixed horizontal grid with quadrangles following the shipping channels and triangles resolving complex geometries elsewhere. The grid resolution ranges from similar to 6.3 km in the coastal ocean to 15 m in the project area. Even with this kind of extreme scale contrast, the baroclinic model still runs stably and accurately at a time step of 2 min, courtesy of the implicit schemes. We highlight that the implicit transport solver alone reduces the total computational cost by 82%, as compared to its explicit counterpart. The base model is shown to be well calibrated, then it is applied in simulating the proposed project scenario. The project-induced modifications on salinity intrusion, gravitational circulation, and transient events are quantified and analyzed

A hydrodynamic model for Galveston Bay and the shelf in the northern Gulf of Mexico

A 3-D unstructured-grid hydrodynamic model for the northern Gulf of Mexico was developed, with a hybrid s–z vertical grid and high-resolution horizontal grid for the main estuarine systems along the Texas–Louisiana coast. This model, based on the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), is driven by the observed river discharge, reanalysis atmospheric forcing, and open boundary conditions from global HYCOM output. The model reproduces the temporal and spatial variation of observed water level, salinity, temperature, and current velocity in Galveston Bay and on the shelf. The validated model was applied to examine the remote influence of neighboring large rivers, specifically the Mississippi–Atchafalaya River (MAR) system, on salinity, stratification, vertical mixing, and longshore transport along the Texas coast. Numerical experiments reveal that the MAR discharge could significantly decrease the salinity and change the stratification and vertical mixing on the inner Texas shelf. It would take about 25 and 50 d for the MAR discharge to reach the mouth of Galveston Bay and Port Aransas, respectively. The influence of the MAR discharge is sensitive to the wind field. Winter wind constrains the MAR freshwater to form a narrow lower-salinity band against the shore from the Mississippi Delta all the way to the southwestern Texas coast, while summer wind reduces the downcoast longshore transport significantly, weakening the influence of the MAR discharge on surface salinity along Texas coast. However, summer wind causes a much stronger stratification on the Texas shelf, leading to a weaker vertical mixing. The decrease in salinity of up to 10 psu at the mouth of Galveston Bay due to the MAR discharge results in a decrease in horizontal density gradient, a decrease in the salt flux, and a weakened estuarine circulation and estuarine–ocean exchange. We highlight the flexibility of the model and its capability to simulate not only estuarine dynamics and shelf-wide transport, but also the interactions between them

Meta-analysis of structural and functional alterations of brain in patients with attention-deficit/hyperactivity disorder

BackgroundA large and growing body of neuroimaging research has concentrated on patients with attention-deficit/hyperactivity disorder (ADHD), but with inconsistent conclusions. This article was intended to investigate the common and certain neural alterations in the structure and function of the brain in patients with ADHD and further explore the differences in brain alterations between adults and children with ADHD.MethodsWe conducted an extensive literature search of whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies associated with ADHD. Two separate meta-analyses with the seed-based d mapping software package for functional neural activation and gray matter volume (GMV) were carried out, followed by a joint analysis and a subgroup analysis.ResultsThis analysis included 29 VBM studies and 36 fMRI studies. Structurally, VBM analysis showed that the largest GMV diminutions in patients with ADHD were in several frontal-parietal brain regions, the limbic system, and the corpus callosum. Functionally, fMRI analysis discovered significant hypoactivation in several frontal-temporal brain regions, the right postcentral gyrus, the left insula, and the corpus callosum.ConclusionThis study showed that abnormal alterations in the structure and function of the left superior frontal gyrus and the corpus callosum may be the key brain regions involved in the pathogenesis of ADHD in patients and may be employed as an imaging metric for patients with ADHD pending future research. In addition, this meta-analysis discovered neuroanatomical or functional abnormalities in other brain regions in patients with ADHD as well as findings that can be utilized to guide future research

Regulation of the G2–M cell cycle progression by the ERK5–NFκB signaling pathway

Elucidation of mechanisms regulating cell cycle progression is of fundamental importance for cell and cancer biology. Although several genes and signaling pathways are implicated in G1–S regulation, less is known regarding the mechanisms controlling cell cycle progression through G2 and M phases. We report that extracellular signal–regulated kinase 5 (ERK5), a member of the mitogen-activated protein kinases, is activated at G2–M and required for timely mitotic entry. Stimulation of ERK5 activated nuclear factor κB (NFκB) through ribosomal S6 kinase 2 (RSK2)-mediated phosphorylation and degradation of IκB. Furthermore, selective inhibition of NFκB at G2–M phases substantially delayed mitotic entry and inhibited transcription of G2–M–specific genes, including cyclin B1, cyclin B2, Plk-1, and cdc25B. Moreover, inhibition of NFκB at G2–M diminished mitosis induced by constitutive activation of ERK5, providing a direct link between ERK5, NFκB, and regulation of G2–M progression. We conclude that a novel ERK5–NFκB signaling pathway plays a key role in regulation of the G2–M progression