Numerous Strategies Research Articles

Towards Hybrid-Optimization Video Coding

Video coding that pursues the highest compression efficiency is the art of computing for rate-distortion optimization. The optimization has been approached in different ways, exemplified by two typical frameworks: block-based hybrid video coding and end-to-end learned video coding. The block-based hybrid framework encompasses more and more coding modes that are available at the decoder side; an encoder tries to search for the optimal coding mode for each block to be coded. This is an online, discrete, search-based optimization strategy. The end-to-end learned framework embraces more and more sophisticated neural networks; the network parameters are learned from a collection of videos, typically using gradient descent-based methods. This is an offline, continuous, numerical optimization strategy. Having analyzed these two strategies, both conceptually and with concrete schemes, this paper suggests investigating hybrid -optimization video coding, that is to combine online and offline, discrete and continuous, search-based and numerical optimization. For instance, we propose a hybrid-optimization video coding scheme, where the decoder consists of trained neural networks and supports several coding modes, and the encoder adopts both numerical and search-based algorithms for the online optimization. Our scheme achieves promising compression efficiency on par with H.265/HM for the random-access configuration.

Numerical Investigation of Some Reductions for the Gatenby–Gawlinski Model

Two (consecutive) reductions of the complete Gatenby–Gawlinski model for cancer invasion are proposed in order to investigate the mathematical framework, mainly from a computational perspective. After a brief overview of the full model, we proceed by examining the case of a two-equations-based and one-equation-based reduction, both obtained by means of a quasi-steady-state assumption. We focus on invasion fronts, exploiting a numerical strategy based on a finite volume approximation, and perform corresponding computational simulations to study the sharpness/smoothness of the traveling waves. Then, we employ a space-averaged wave speed estimate—referred to as the LeVeque–Yee formula—to quantitatively approach the propagation phenomenon. Concerning the one-equation-based model, we propose a scalar degenerate reaction-diffusion equation, which proves to be effective in order to qualitatively recover the typical trends arising from the Gatenby–Gawlinski model. Finally, we carry out some numerical tests in a specific case where the analytical solution is available.

A modeling strategy for the simulation of box sections with layered shell elements

This paper presents a numerical strategy to model box sections from bridge girders using horizontal layered shell finite elements. The basic idea is to avoid the construction of more computational expensive meshes based on the use of folded shell and brick finite elements. The numerical strategy imposes the deactivation of those layers related to empty spaces within the bridge cross-section. The performance of this technique is explored by means of two demanding practical applications related to bridge structures with constant and variable deck thicknesses. The first application deals with the static truck load test of the Caynarachi Bridge, located in Peru, and for which measured field data exists, while the second application is related to the construction stage analysis of a box bridge structure including time effects due to concrete creep, shrinkage and steel relaxation. The results demonstrate that the studied technique acceptably correlates with the measured field data,expressed in terms of vertical displacements,with correlation coefficients exceeding 0.94.Additionally, the outcomes align well with the results of other numerical techniques, allowing applicants to use this simplified modeling approach in daily design office.

Comparison of Single-Phase Mathematical Models for Solid-State Packed Beds for Thermal Energy Storage

This article presents an analytical solution for the evaluation of the thermal performance of packed bed sensible heat storage. The numerical model developed was tested for four different solid storage mediums. The thermal energy equation is solved numerically by deploying the finite difference method. The presented analytical solution is based on a novel mathematical approach. The numerical model was validated using the computer simulation package Comsol Multiphysics v5.3. Our numerical model results are in good agreement with the published experimental data, with an overall difference of ~10%. Hence, the numerical model is an efficient way of evaluating the thermal performance of packed bed thermal energy storage systems compared to other numerical strategies or computer simulation techniques. This proves that the novel analytical model has shown to be a reliable and broadly accurate approach to acquire the thermal performance of sensible heat storage.

Fractional cyclic cohesive zone model for time-dependent fatigue behavior of soft adhesives under mode-II loading

Soft adhesives exhibit nonlinear viscoelastic behavior during cyclic loading, suggesting that their cycle-dependent fatigue behavior can be significantly affected by the time-dependent deformation behavior. Soft adhesives are frequently subject to various cyclic conditions in practical applications, presenting potential safety risks. This paper has proposed a fractional cyclic cohesive zone model (CZM) to characterize the time-dependent fatigue behavior of soft adhesives. To capture the nonlinear evolution of fatigue damage under asymmetric stress-controlled cyclic loading, a fatigue damage model that considers the contribution of in-situ stress/strain was incorporated into fractional-order viscoelastic model. The proposed CZM was validated through single-lap shear creep tests at various stress levels and fatigue tests at various stress amplitudes and loading periods. Furthermore, the impacts of stress ratio and peak stress level on fatigue failure under different loading periods were investigated using the proposed CZM. The results indicate that under a short loading period, the failure of the soft adhesives is primarily influenced by cycle-dependent fatigue damage, while under a long loading period, it is primarily affected by time-dependent creep deformation. Overall, this work offers a numerical strategy to describe the fatigue failure of nonlinear viscoelastic soft adhesives and to understand their time-dependent fatigue failure mechanism, with implications for product design and optimization.

Kosambi-Cartan-Chern perspective on chaos: Unveiling hidden attractors in nonlinear autonomous systems.

This article confronts the formidable task of exploring chaos within hidden attractors in nonlinear three-dimensional autonomous systems, highlighting the lack of established analytical and numerical methodologies for such investigations. As the basin of attraction does not touch the unstable manifold, there are no straightforward numerical processes to detect those attractors and one has to implement special numerical and analytical strategies. In this article we present an alternative approach that allows us to predict the basin of attraction associated with hidden attractors, overcoming the existing limitations. The method discussed here is based on the Kosambi-Cartan-Chern theory which enables us to conduct a comprehensive theoretical analysis by means of evaluating geometric invariants and instability exponents, thereby delineating the regions encompassing chaotic and periodic zones. Our analytical predictions are thoroughly validated by numerical results.

New insights into estimating the cementation exponent of the tight and deep carbonate pore systems via rigorous numerical strategies

One of the main constituents of any reservoir characterization is an accurate forecast of water saturation, which is highly dependent upon the cementation exponent. Even though there have been a lot of studies, the most common correlations depend on total porosity. This means that they do not work as well in heterogeneous carbonate reservoirs, especially tight formations with total porosities less than 10%. This study aims to develop accurate and universal models for estimating the cementation exponent in deep and tight carbonate pore systems located in West Asia. Two heuristic algorithms, including the radial basis function neural network optimized by ant colony optimization (RBFNN-ACO) and gene expression programming (GEP), were employed to calculate the cementation exponent. To do this, we prepared a databank incorporating cementation exponents, total porosity, and various pore types. Then, the databank is classified into the test subset (for model prediction checking) and the train subset (for model construction). The reliability of the new recommended models is inspected by applying several statistical quality measures associated with graphical analyses. So, the consequences of the modeling disclose the large precision of the above-mentioned RBFNN-ACO, GEP Model-I, and GEP Model-II by average absolute percentage relative deviations (AAPRD%) of 6.28%, 6.39%, and 7.45%, respectively. Based on the outliers analysis, nearly 95% of the databank and model estimations are, respectively, valid and reliable. Additionally, the three input variables, including moldic porosity (with a + 70% impact value), non-fabric-selective dissolution (connected) porosity (with a -30% impact value), and interparticle porosity (with a -23% impact value), exhibit the main affecting parameters on the cementation exponent. Comparing current results with traditional literature correlations demonstrates the supremacy of the RBFNN-ACO model (AAPRD = 6.28% and root mean squared error (RMSE) = 0.17) over the examined literature correlations such as Borai’s equation (AAPRD = 12.30% and RMSE = 0.41). In addition, RBFNN-ACO can give better results than Borai’s Eqn. for tight (porosity less than 10%) and deep carbonate samples.

An inverse problem for nonlocal reaction-diffusion equations with time-delay

The reaction-diffusion equations have been studied in various aspects of nature, such as heat transfer and biological dynamic modelling. In this paper, we study a nonlocal reaction-diffusion model with time delay associated with the density and diffusion behaviour of biological populations. Based on our previous conclusions and numerical strategy of the direct problem, we continue to study the inverse problem about the diffusion coefficient as well as the parameters in the birth function, and also perform numerical simulations with error analysis. In addition, we further generalize the constant diffusion coefficient to the position-dependent diffusion rate, which is intended to improve the generalizability to multiple organisms diffusion in nature.

An efficient method for electro-thermo-mechanical coupling effect in electrical contact on rough surfaces

In this study, a numerical strategy based on the boundary element method (BEM) is developed to simulate the electrical contact behavior on rough surfaces. By using the Fourier transform, the solutions of the electric potential, temperature rise, and displacement fields in the Fourier space are derived with finite boundaries, in which the electro-thermo-mechanical coupling effect is considered. With the consideration of the contact condition, an iterative algorithm is proposed to seek the solutions of rough surface electrical contact under a given contact force and total electric potential drop. The contact pressure, real contact area, electrical contact resistance, electric current, and temperature rise distribution are predicted. For the validation, the electrical contact results of a spherical punch-half space contact and a rough surface-elastic substrate contact are calculated based on the finite element method. The good agreement between the results from the BEM-based method and the finite element method indicates the accuracy of the presented method. Then, the effect of the total electric potential and the thermal expansion on the electrical contact behavior, the relationship between the contact conductance and contact stiffness, and the probability density function of the contact pressure and temperature rise distributions are evaluated using the proposed method.

Numerical Simulation of MHD Radiative Casson Nanofluid Flow over a Nonlinearly Heated Stretching Sheet Embedded in Porous Medium

This study intends to assess the heat transmission of a steady two-dimensional MHD Casson nanofluid flow across a non-linearly stretching sheet concerning viscous dissipation, heat generation, thermal radiation, and chemical radiate parameters. Mathematically, the flow is outlined as PDE systems, converted to ODE systems by a well-posed transformation, which are afterwards solved numerically in Matlab employing the fourth-order precision program (Bvp4c). The comparison indicates adequate agreement, demonstrating the correctness of the numerical strategy. It is observed that in the existence of a chemical reaction, the temperature is elevated, while the concentration profile is markedly reduced, in contrast to a scenario where no chemical reaction is taking place. In consideration of viscosity, heat radiation, thermophoresis impact, and suction or injection parameter, the Nusselt number reveals a growing tendency. In contrast, it exhibits opposing behavior with regard to the other addressed factors. The findings of this study have applications in the engineering, biomedical and industrial sectors, including food processing, polymer making, glass and fiber production, material processing, and enhanced oil recovery.

Multi-Step Mechanical and Thermal Homogenization for the Warpage Estimation of Silicon Wafers.

In response to the increasing demand for high-performance capacitors, with a simultaneous emphasis on minimizing their physical size, a common practice involves etching deep vias and coating them with functional layers to enhance operational efficiency. However, these deep vias often cause warpages during the processing stage. This study focuses on the numerical modeling of wafer warpage that occurs during the deposition of three thin layers onto these vias. A multi-step mechanical and thermal homogenization approach is proposed to estimate the warpage of the silicon wafer. The efficiency and accuracy of this numerical homogenization strategy are validated by comparing detailed and homogenized models. The multi-step homogenization method yields more accurate results compared to the conventional direct homogenization method. Theoretical analysis is also conducted to predict the shape of the wafer warpage, and this study further explores the impact of via depth and substrate thickness.

Optimization of MTI structure based on material characteristics under extreme aerodynamic heating environment

Thermal insulation structure is a key factor to protect a high-speed aircraft to work safely and complete various tasks. The multilayer thermal insulation (MTI) structure has attracted much attention because of its light weight and good thermal insulation effect. The performance of an MTI structure is not only related to its physical sizes, but also closely related to the material optimization and temperature influences. A transient nonlinear thermal transfer model of the MTI structure is established, and a numerical solution strategy of the nonlinear thermal transfer model is proposed. Considering material selection, introducing the temperature influence of materials, and taking the geometric dimensions and equivalent mechanical properties of the MTI structures as constraints, an optimization frame of the MTI structures is established. Then two intelligent methods are adopted to solve the problem. Using the aerodynamic heating environment of X-43 flight trajectory, the results of a typical high-speed aircraft show that the proposed optimization framework can reduce the structural mass density from 13.95 kg‧m−2 to 9.10 kg‧m−2 by about 34.8 %. The temperature effect analysis shows that the temperature variation has an important influence on the optimization results. If the temperature effect on material properties is not considered, the optimized design scheme may not meet the temperature design constraints (The maximum temperature of the inner surface is 410 K, far exceeding the maximum allowable temperature of 320 K) which further leads to structural failures. Finally, the reliability and rationality of the optimization scheme are verified by a finite element model (FEM). The equivalent modulus of the optimized MTI structure is 146 GPa and the mass area density of the MTI structure is 7.7 kg‧m−2. The optimization design method of an MTI structure proposed in the current paper provides a technical support and lays a foundation for the overall design of a high-speed aircraft.

Revisiting Tensor Basis Neural Network for Reynolds stress modeling: Application to plane channel and square duct flows

Recent advances in computing power devoted to Computational Fluid Dynamics (CFD) have opened up a new avenue for addressing the turbulence closure problem through Machine Learning (ML). Several Tensor Basis Neural Network (TBNN) frameworks aimed at enhancing turbulence Reynolds-Averaged Navier–Stokes (RANS) modeling have recently been proposed in the literature as data-driven constitutive models for systems with known invariance properties. However, persistent ambiguities remain regarding the physical adequacy of applying the General Eddy Viscosity Model (GEVM) within these frameworks. This work aims at investigating this aspect in an a priori stage for better predictions of the Reynolds stress anisotropy tensor, while preserving the Galilean and rotational invariances. In particular, we propose a general framework providing optimal tensor basis models for two types of canonical flows with increasing complexity: Plane Channel Flow (PCF) and Square Duct Flow (SDF). Subsequently, deep neural networks based on these optimal models are trained using state-of-the-art strategies to achieve a balanced and physically sound prediction of the full anisotropy tensor. A priori results obtained by the proposed framework are in very good agreement with the reference Direct Numerical Simulations (DNS) data. Notably, our shallow network with three layers excels in providing accurate predictions of the anisotropy tensor for PCF at unobserved friction Reynolds numbers, both in interpolation and extrapolation scenarios. The learning of the SDF case is more challenging because of its physical nature but also due to a lack of training data at various regimes. We propose a numerical strategy to alleviate this problem based on Transfer Learning (TL). In order to more efficiently generalize to an unseen intermediate Reτ regime, we take advantage of our prior knowledge acquired from a training with a larger and wider dataset. Our results indicate the potential of the developed network model, and demonstrate the feasibility and efficiency of the TL process in terms of training data size and training time. Based on these results, we believe there is a promising future by integrating these neural networks into an adapted in-house RANS solver.

Sirt5-mediated lysine desuccinylation regulates oxidative stress adaptation in Magnaporthe oryzae during host intracellular infection.

Plant pathogenic fungi elaborate numerous detoxification strategies to suppress host reactive oxygen species (ROS), but their coordination is not well-understood. Here, we show that Sirt5-mediated protein desuccinylation in Magnaporthe oryzae is central to host ROS detoxification. SIRT5 encodes a desuccinylase important for virulence via adaptation to host oxidative stress. Quantitative proteomics analysis identified a large number of succinylated proteins targeted by Sirt5, most of which were mitochondrial proteins involved in oxidative phosphorylation, TCA cycle, and fatty acid oxidation. Deletion of SIRT5 resulted in hypersuccinylation of detoxification-related enzymes, and significant reduction in NADPH : NADP+ and GSH : GSSG ratios, disrupting redox balance and impeding invasive growth. Sirt5 desuccinylated thioredoxin Trx2 and glutathione peroxidase Hyr1 to activate their enzyme activity, likely by affecting proper folding. Altogether, this work demonstrates the importance of Sirt5-mediated desuccinylation in controlling fungal process required for detoxifying host ROS during M. oryzae infection.

An insight into the capability of the actuator line method to resolve tip vortices

Abstract. The actuator line method (ALM) is increasingly being preferred to the ubiquitous blade element momentum (BEM) approach in several applications related to wind turbine simulation, thanks to the higher level of fidelity required by the design and analysis of modern machines. Its capability to resolve blade tip vortices and their effect on the blade load profile is, however, still unsatisfactory, especially when compared to other medium-fidelity methodologies such as the lifting line theory (LLT). Despite the numerical strategies proposed so far to overcome this limitation, the reason for such behavior is still unclear. To investigate this aspect, the present study uses the ALM tool developed by the authors for the ANSYS® Fluent® solver (v. 20.2) to simulate a NACA0018 finite wing for different pitch angles. Three different test cases were considered: high-fidelity blade-resolved computational fluid dynamics (CFD) simulations (to be used as a benchmark), standard ALM, and ALM with the spanwise force distribution coming from blade-resolved data (frozen ALM). The last option was included to isolate the effect of force projection, using three different smearing functions. For the postprocessing of the results, two different techniques were applied: the LineAverage sampling of the local angle of attack along the blade and state-of-the-art vortex identification methods (VIMs) to outline the blade vortex system. The analysis showed that the ALM can account for tip effects without the need for additional corrections, provided that the correct angle of attack sampling and force projection strategies are adopted.

Decellularized Placental Sponge Seeded with Human Mesenchymal Stem Cells Improves Deep Skin Wound Healing in the Animal Model.

Skin injuries lead to a large burden of morbidity. Although numerous clinical and scientific strategies have been investigated to repair injured skin, optimal regeneration therapy still poses a considerable obstacle. To address this challenge, decellularized extracellular matrix-based scaffolds recellularized with stem cells offer significant advancements in skin regeneration and wound healing. Herein, a decellularized human placental sponge (DPS) was fabricated using the decellularization and freeze-drying technique and then recellularized with human adipose-derived mesenchymal cells (MSCs). The biological and biomechanical properties and skin full-thickness wound healing capacity of the stem cells-DPS constructs were investigated in vitro and in vivo. The DPS exhibited a uniform 3D microstructure with an interconnected pore network, 89.21% porosity, a low degradation rate, and good mechanical properties. The DPS and MSCs-DPS constructs were implanted in skin full-thickness wound models in mice. An accelerated wound healing was observed in the wounds implanted with the MSCs-DPS construct when compared to DPS and control (wounds with no treatment) during 7 and 21 days postimplantation follow-up. In the MSCs-DPS group, the wound was completely re-epithelialized, the epidermis layer was properly organized, and the dermis and epidermis' bilayer structures were restored after 7 days. Our findings suggest that DPS is an excellent carrier for MSC culture and delivery to skin wounds and now promises to proceed with clinical evaluations.

Tracing the STING exocytosis pathway during herpes viruses infection.

The STimulator of INterferon Genes (STING) constitutes a major DNA-sensing pathway that restricts HSV-1 infection in different models by activating type I interferon and pro-inflammatory responses. To counteract STING, HSV-1 has evolved numerous strategies including mechanisms to interfere with its oligomerization, post-translational modifications, and downstream signaling. Previously, we demonstrated that STING is packaged in extracellular vesicles (EVs) produced from HSV-1-infected cells. These EVs activated antiviral responses in uninfected recipient cells and suppressed a subsequent HSV-1 infection in a STING-dependent manner. Here, we provide information on the packaging of STING in EVs and its exocytosis. We found that STING exocytosis did not occur in CD63 knockdown cells supporting that STING follows the CD63 exocytosis pathway. Consistently, we found that STING co-localized with CD63 in cytoplasmic globular structures and exosomal STING and CD63 co-fractionated. Both golgicide A and brefeldin A prevented STING exocytosis during HSV-1 infection suggesting that STING trafficking through the Golgi is required. A STING ligand was insufficient for STING exocytosis, and downstream signaling through TBK1 was not required. However, STING palmitoylation and tethering to the ER by STIM1 were required for STING exocytosis. Finally, we found that HSV-1 replication/late gene expression triggered CD63 exocytosis that was required for STING exocytosis. Surprisingly, HSV-2 strain G did not trigger CD63 or STING exocytosis as opposed to VZV and HCMV. Also, EVs from HSV-1(F)- and HSV-2(G)-infected cells displayed differences in their ability to restrict these viruses. Overall, STING exocytosis is induced by certain viruses and shapes the microenvironment of infection.IMPORTANCEExtracellular vesicles (EVs) are released by all types of cells as they constitute a major mechanism of intercellular communication. The packaging of specific cargo in EVs and the pathway of exocytosis are not fully understood. STING is a sensor of a broad spectrum of pathogens and a key component of innate immunity. STING exocytosis during HSV-1 infection has been an intriguing observation, raising questions of whether this is a virus-induced process, the purpose it serves, and whether it is observed after infection with other viruses. Here, we have provided insights into the pathway of STING exocytosis and determined factors involved. STING exocytosis is a virus-induced process and not a response of the host to the infection. Besides HSV-1, other herpes viruses triggered STING exocytosis, but HSV-2(G) did not. HSV-1 EVs displayed different restriction capabilities compared with HSV-2(G) EVs. Overall, STING exocytosis is triggered by viruses to shape the microenvironment of infection.

A numerical investigation on coupling of conforming and hybridizable interior penalty discontinuous Galerkin methods for fractured groundwater flow problems

The present paper focuses on the numerical modeling of groundwater flows in fractured porous media using the codimensional model description. Therefore, fractures are defined explicitly as a (d−1)-dimensional geometric object immersed in a d-dimensional region and can act arbitrarily as a drain or a barrier. We numerically investigate a novel numerical strategy combining distinctive classes of conforming and nonconforming high-order Galerkin methods, both eligible for static condensation. This procedure is here particularly relevant, leading to a smaller and sparser final system with coupled degrees of freedom solely on the mesh skeleton. Precisely, we combine an inspired hybridizable interior penalty discontinuous Galerkin (HIP) formulation inside the bulk region and a standard continuous Galerkin (CG) approximation on the fracture network. The distinctive discretization of corresponding PDEs and the coupling strategy are rigorously exposed, and the local and global matrix assemblies are detailed. Extensive numerical experiments are then achieved to prove the model’s performances for 2D/3D analytic and realistic benchmarks. Qualitative comparisons are also considered with other discretization methods and commercial software, such as comsol.

Cell-centered indirect Arbitrary Lagrangian-Eulerian numerical strategy for solving 3D gas dynamics equations

Solving the Euler equations under the Lagrangian formalism enables to simulate various complex engineering applications. However, the use of this formalism can lead to significant mesh deformations as the mesh follows the fluid velocity. The mesh quality may be considerably deteriorated requiring a regularization procedure. In the present document, it is shown that the ideas presented by J. Yao (2013)[68] and J. Yao and D. Stillman (2016) [30] may be used efficiently in a 3D hydrodynamics code to perform reliable regularization steps. The flexibility of the methodology in addition to its simplicity, since it only relies on trivial geometrical considerations, opens the way for various extensions. The remapping step then considered, uses the geometrical splitting procedure of the Lagrangian phase to perform effective projections. This coherence ensures the compactness of the overall algorithm. At last but not least, a 3D Flux-Corrected-Remapping method is presented. This yields a particularly robust remapping algorithm while also leading the way for higher order projection extensions.

Sensor Fish Deployments at the Xayaburi Hydropower Plant: Measurements and Simulations

Fish protection is a priority in regions with ongoing and planned development of hydropower production, like the Mekong River system. The evaluation of the effects of turbine passage on the survival of migratory fish is a primary task for informing hydropower plant operators and authorities about the environmental performance of plant operations. The present work characterizes low pressures and collision rates through the Kaplan-type runners of the Xayaburi hydropower station. Both an experimental method based on the deployment of Sensor Fish and a numerical strategy based on flow and passage simulations were implemented on the analysis of two release elevations at one operating point. Nadir pressures and pressure drops through the runner were very sensitive to release elevation, but collision rates on the runner were not. The latter showed a frequency of occurrence of 8.2–9.3%. Measured magnitudes validated the corresponding simulation outcomes in regard to the averaged magnitudes as well as to the variability. Central to this study is that simulations were conducted based on current industry practices for designing turbines. Therefore, the reported agreement helps turbine engineers gain certainty about the prediction power of flow and trajectory simulations for fish passage assessments. This can accelerate the development of environmentally enhanced technology with minimum impact on natural resources.