Clay compaction modelling by homogenization theory

The modelling of hydromechanical behavior of clayey sediments by homogenization theory is described. The rheological model of clays buried in depth requires a three-dimensional approach and laboratory experiments to quantify the model parameters. An iterative process which can be coupled to any homogenization method is used to model the porous media behavior. Hydromechanical compaction results from oedometric experiments are simulated with the proposed model.     

Energy Saving in Industrial Wood Drying Addressed by a Multiscale Computational Model: Board, Stack, and Kiln

This article proposes a multiscale computational model able to calculate energy consumption in a batch lumber kiln. A dual-scale computational model of wood drying deals with the boards/stack interaction and serves as a basis for the present work. A new module was added here that calculates heat losses through kiln walls (convection, condensation) and the energy used by each kiln component (fans, heating elements, humidifier, vacuum pump, etc.). The corresponding mathematical formulation is presented and then theoretical results are compared to those collected in an industrial vacuum kiln. As application example, the effect of air reversal, air velocity, and kiln insulation are exhibited, which depicts the great potential and prospects of this new tool for energy savings in relation to the product quality.     

Advancements in the design and validation of an air pollution integrated assessment model for Spain

This paper describes the design and application of the Atmospheric Evaluation and Research Integrated model for Spain (AERIS). Currently, AERIS can provide concentration profiles of NO₂, O₃, SO₂, NH₃, PM, as a response to emission variations of relevant sectors in Spain. Results are calculated using transfer matrices based on an air quality modelling system (AQMS) composed by the WRF (meteorology), SMOKE (emissions) and CMAQ (atmospheric-chemical processes) models. The AERIS outputs were statistically tested against the conventional AQMS and observations, revealing a good agreement in both cases. At the moment, integrated assessment in AERIS focuses only on the link between emissions and concentrations. The quantification of deposition, impacts (health, ecosystems) and costs will be introduced in the future. In conclusion, the main asset of AERIS is its accuracy in predicting air quality outcomes for different scenarios through a simple yet robust modelling framework, avoiding complex programming and long computing times.     

A sliding window technique for interactive high-performance computing scenarios

Interactive high-performance computing is doubtlessly beneficial for many computational science and engineering applications whenever simulation results should be visually processed in real time, i.e. during the computation process. Nevertheless, interactive HPC entails a lot of new challenges that have to be solved – one of them addressing the fast and efficient data transfer between a simulation back end and visualisation front end, as several gigabytes of data per second are nothing unusual for a simulation running on some (hundred) thousand cores. Here, a new approach based on a sliding window technique is introduced that copes with any bandwidth limitations and allows users to study both large and small scale effects of the simulation results in an interactive fashion.     

基于二代bandelets域HMT模型的图像分割

在小波域隐马尔可夫树模型(WHMT)图像分割算法的基础上,根据二代handelets系数的分布统计特性,提出一种新的bandelets域隐马树模型(BHMT)有监督图像分割算法.新算法试图利用二代bandelets能表示图像几何规律性的特点来改进分割效果.为证明算法的有效性,用合成纹理图像和真实的航空和遥感图像做分割实验,并和小波域隐马模型树分割算法作了对比,对合成纹理图像分割,用错分概率作为评价参数.实验结果表明,此方法错分概率低、分割效果理想.     

基于小波变换的含噪人耳图像边缘检测

为了取得含噪人耳图像的理想边缘轮廓,以实现人耳识别技术的进一步应用,对小波变换边缘检测方法进行了研究,分析了噪声消除与小波变换尺度之间的关系,详细论述了模局部极大值提取边缘的原理.针对含噪人耳图像的特殊性,阐述了一般去噪和边缘检测方法的不足,并针对这些不足提出了改进方法,首先利用样条小波多尺度分解后,相邻尺度小波系数相乘得到尺度积,然后进一步求得尺度积的模和相角,通过自适应阈值去噪提取图像边缘,取得了较好效果.     

A Multi-scale Attention-based Facial Emotion Recognition Method Based on Deep Learning

Recently, people have been paying more and more attention to mental health, such as depression, autism, and other common mental diseases. In order to achieve a mental disease diagnosis, intelligent methods have been actively studied. However, the existing models suffer the accuracy degradation caused by the clarity and oc-clusion of human faces in practical applications. This paper, thus, proposes a multi-scale feature fusion network that obtains feature information at three scales by locating the sentiment region in the image, and integrates global feature information and local feature information. In addition, a focal cross-entropy loss function is designed to improve the network''s focus on difficult samples during training, enhance the training effect, and increase the model recognition accuracy. Experimental results on the challenging RAF_DB dataset show that the proposed model exhibits better facial expression recognition accuracy than existing techniques.     

Weave geometry generation avoiding interferences for mesoscale RVEs

An algorithm which allows the generation of representative volume elements (RVEs) for complex woven and warp-interlaced fiber-reinforced composite topologies while avoiding unphysical tow intersections is presented. This is achieved by extending an existing RVE generation strategy in two significant ways: (1) the local cross section shape of the tow is adjusted depending on the local tow curvature in a way that preserves the cross sectional area of the tow, and (2) the elementary crimp interval is separated into a planar and a transition region. The modifications facilitate the generation of a wide range of elaborate textile topologies without tow intersections, which are present without the proposed modifications unless complex tow to tow contact models are introduced. The mechanical properties of plain weaves were predicted based on the topology generated with the proposed algorithm as well as based on RVEs which were constructed based on actual micrographs, i.e. a “digital twin” of the actual microstructure. A comparison of the predicted mechanical properties based on finite element and Multiscale Generalized Method of Cells techniques shows close agreement. However, some differences exist with respect to experimentally determined material parameters due to the finite dimensions of the specimens. Lastly, mechanical properties of multilayered weaves are predicted with the finite element method. The considered material systems are carbon fiber in epoxy matrix as well as C/C-SiC. However, the procedure is applicable to a wide range of material systems.     

Edge detection insensitive to changes of illumination in the image

In this paper we present new edge detection algorithms which are motivated by recent developments on edge-adapted reconstruction techniques [F. Aràndiga, A. Cohen, R. Donat, N. Dyn, B. Matei, Approximation of piecewise smooth functions and images by edge-adapted (ENO-EA) nonlinear multiresolution techniques, Appl. Comput. Harmon. Anal. 24 (2) (2008) 225–250]. They are based on comparing local quantities rather than on filtering and thresholding. This comparison process is invariant under certain transformations that model light changes in the image, hence we obtain edge detection algorithms which are insensitive to changes in illumination.     

Multiscale computation for bioartificial soft tissues with complex geometries

The mechanical function of soft collagenous tissues is inherently multiscale, with the tissue dimension being in the centimeter length scale and the underlying collagen network being in the micrometer length scale. This paper uses a volume averaging multiscale model to predict the collagen gel mechanics. The model is simulated using a multiscale component toolkit that is capable of dealing with any 3D geometries. Each scale in the multiscale model is treated as an independent component that exchanges the deformation and average stress information through a scale-linking operator. An arterial bifurcation was simulated using the multiscale model, and the results demonstrated that the mechanical response of the soft tissues is strongly sensitive to the network orientation and fiber-to-fiber interactions.