Residual distribution schemes: Current status and future trends

An ALE residual distribution scheme for the unsteady Euler equations over triangular grids with local mesh adaptation

Hydrodynamic forces on a semi-displacement ship at high speed

Residual distribution schemes for Maxwell’s equations

We consider two problems in which a semi-infinite bubble moves into a uniformly convergent two-dimensional channel under creeping-flow conditions. In the first (steady) problem, the bubble is stationary with respect to the channel walls, which move away from the channel vertex parallel to themselves, each entraining a liquid film of uniform thickness; the appropriate flux is provided by a line source at the channel vertex. In the second (unsteady) problem, the channel walls are fixed and the bubble is drawn at a constant speed towards the channel vertex by a line sink. In this case the bubble interface assumes a self-similar shape, and wedge-shaped films are deposited on the channel walls. The boundary-element method, supported by asymptotic approximations, is used to compute flows over a range of bubble speeds (measured by a capillary number Ca) and wedge angles α. In the steady problem, the deposited film thickness increases monotonically with α at low Ca, but diminishes with increasing α at sufficiently high Ca. In the unsteady problem, the film thickness was found always to increase with both α and Ca. In both cases, the dimensionless pressure drop across the bubble tip can be nonmonotonic in α. Implications of these results in modeling coating and peeling flows are discussed.

The influence and validity of wall boundary conditions for non-equilibrium fluid flows described by the Boltzmann equation remains an open problem. The substantial computational cost of directly solving the Boltzmann equation has limited the extent of numerical validation studies to simple, often two-dimensional, flow problems. Recent algorithmic advancements for the Boltzmann–Bhatnagar–Gross–Krook equation introduced by the authors [Dzanic et al., J. Comput. Phys. 486, 112146 (2023)], consisting of a highly efficient high-order spatial discretization augmented with a discretely conservative velocity model, have made it feasible to accurately simulate unsteady three-dimensional flow problems across both the rarefied and continuum regimes. This work presents a comprehensive evaluation and validation of wall boundary conditions across a variety of flow regimes, primarily for the purpose of exploring their effects on momentum transfer in the low Mach limit. Results are presented for a range of steady and unsteady wall-bounded flow problems across both the rarefied and continuum regimes, from canonical two-dimensional laminar flows to unsteady three-dimensional transitional and turbulent flows, the latter of which are the first instances of wall-bounded turbulent flows computed by directly solving the Boltzmann equation. We show that approximations of the molecular gas dynamics equations can accurately predict both non-equilibrium phenomena and complex hydrodynamic flow instabilities and show how spatial and velocity domain resolution affect the accuracy. The results indicate that an accurate approximation of particle transport (i.e., high spatial resolution) is significantly more important than particle collision (i.e., high velocity domain resolution) for predicting flow instabilities and momentum transfer consistent with that predicted by the hydrodynamic equations and that these effects can be computed accurately even with very few degrees of freedom in the velocity domain. These findings suggest that highly accurate spatial schemes (e.g., high-order schemes) are a promising approach for solving molecular gas dynamics for complex flows and that the direct solution of the Boltzmann equation can be performed at a reasonable cost when compared to hydrodynamic simulations at the same level of resolution.

The hydraulic conductivity of a confined aquifer is estimated using the quasi-linear geostatistical approach (QLGA), based on measurements of dependent quantities such as the hydraulic head or the arrival time of a tracer. This requires the solution of the steady-state groundwater flow and solute transport equations, which are coupled by Darcy's law. The standard Galerkin finite element method (FEM) for the flow equation combined with the streamline diffusion method (SDFEM) for the transport equation is widely used in the hydrogeologists' community. This work suggests to replace the first by the two-point flux cell-centered finite volume scheme (CCFV) and the latter by the Discontinuous Galerkin (DG) method. The convection-dominant case of solute (contaminant) transport in groundwater has always posed a special challenge to numerical schemes due to non-physical oscillations at steep fronts. The performance of the DG method is experimentally compared to the SDFEM approach with respect to numerical stability, accuracy and efficient solvability of the occurring linear systems. A novel method for the reduction of numerical under- and overshoots is presented as a very efficient alternative to local mesh refinement. The applicability and software-technical integration of the CCFV/DG combination into the large-scale inversion scheme mentioned above is realized. The high-resolution estimation of a synthetic hydraulic conductivity field in a 3-D real-world setting is simulated as a showcase on Linux high performance computing clusters. The setup in this showcase provides examples of realistic flow fields for which the solution of the convection-dominant transport problem by the streamline diffusion method fails.

The transition from a linear economy (LE) to a circular economy (CE) is not just about mitigating the negative impacts of LE, but also about considering changes in infrastructure, while leveraging the power of technology to reduce resource production and consumption and waste generation, and improve long-term resilience. The existing research suggests that digital technologies (DTs) have great potential to drive the CE. However, despite the exponential growth and increasing interest in studies on DTs and the CE from year 2016 onwards, few systematic studies on the application of DTs to enable the CE have been found. In addition, the current status and development direction of the DT-driven CE is unclear, and the potential of DTs to support CE implementation is under-researched. Therefore, the aim of this paper is to explore the potential of DTs to drive the CE. This paper set out to analyze the current status and development of the DT-driven CE and examine future development trends in the field. Using a systematic literature review approach, this paper is the first attempt to use a mixed method, i.e., to combine macro-quantitative bibliometric methods with a micro-qualitative content analysis method to explore the DT-driven CE. The results, which include the research background, co-occurrence clusters, research hotspots, and development trends of keyword co-occurrence network visualization and keyword burst detection, are presented from a macro perspective using two bibliometric analysis softwares. In addition, the use of 13 specific DTs in the CE is analyzed according to seven disciplinary areas (Environmental Sciences and Ecology, Engineering, Science and Technology and Other Topics, Business Economics, Computer Science, Operations Research and Management Science, and Construction and Building Technology) of greatest interest from a micro-qualitative point of view. Further, future trends and challenges facing DT-driven CE development are explored and feasible directions for solutions are proposed.

We develop a coherent set of techniques for parallel computing. We use the Finite Element Method associated with the C++ Objects Oriented Programming with only one database. A technique of data selection called AMS - Automatic Multigrid System - is used for the determination of the data dedicated to each processor. This method is performed by a SIMD technology associated with the MPI capabilities. This parallel computing is applied to very large CPU cost problems particularly the unsteady problems or steady problems using iterative methods. Different results in Computational Fluid Dynamics are presented.KeywordsFinite Element MethodComputational Fluid DynamicsParallel ComputingObject Orient ProgramSingle Instruction Multiple DataThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

We have developed a coherent set of techniques for parallel computing. We have used the Finite Element Method associated with the C++ Object-Oriented Programming with only one database. A technique of data selection is used in the determination of the data dedicated to each processor. This method is performed by SIMD technology associated with MPI capabilities. This parallel computing is applied to very large CPU cost problems particularly the unsteady problems or steady problems using iterative methods. Different results in Computational Fluid Dynamics are presented.

A time-domain seakeeping numerical model based on a computational fluid dynamics (CFD) software FINE/Marine has been developed for nonlinear steady and unsteady viscous flows. Simulation of multi-phase flows around a Wigley hull with forward speed is performed by solving the Reynolds-average Navier-Stokes (RANS) and continuity equations with k-ω (SST-Menter) turbulence model. The water free surface is captured by Blend Reconstruction Interface Capturing Scheme (BRICS). Both steady and unsteady problems including wave-making, radiation and diffraction problems are simulated. Ship waves generated by the Wigley model advancing at a constant forward speed in calm water or incident waves are computed. The numerical results including the wave-making resistance and wave patterns for steady problem, hydrodynamic coefficients and forces for unsteady problems are illustrated and compared with experimental measurements in good agreement. It is confirmed that the present numerical model has the capability of evaluating the seakeeping performance of ships.

Compact differencing techniques have been shown to be applicable to simple first order advection equations. A second-order accurate compact upwind scheme has been derived which is identically equivalent to Keller's box method. Two fourth order compact analogs of Lax-Wendroff methods have also been shown. The accuracy of any of these compact methods is superior to a standard second-order method, even for one quarter of the nodes in the case of the fourth-order schemes.KeywordsUpwind SchemeCompact SchemeOrder UpwindCompact MethodCompact Difference SchemeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The present work focuses on the development of computer code which allow the engine designer investigate the flow behavior through a divergent nozzle. The flow is assumed as quasi one dimensional and steady inviscid compressible flow. In other word the flow is governed by compressible Euler equation depending on the local Mach number. Solving such a mixed type of equation is difficult. The boundary between hyperbolic and elliptic region is not clear. To avoid such difficulty can be done through treating a steady flow problem as unsteady flow problems with the boundary condition is fixed with respect to time. As unsteady flow problem, the Euler equation becomes hyperbolic type of partial differential equation with respect to time. This approach allows one to solve the unsteady flow problem goes to a steady state solution. There are various methods can used for solving hyperbolic type of equation, such as MacCormacks scheme, Steger Warmings scheme, Beam Warmings Scheme and TVD Scheme. The present work used MacCormacks scheme and Steger Warming scheme will be used to investigate the flow behavior through a divergent nozzle. Comparison with analytic solution shows that Steger Warmings scheme gives a better result than MacCormacks scheme.

Background: COVID-19 is a pandemic, which covered to all over the world and started the end of 2019. COVID-19 spreading rapidly from person to person and from one environment to another environment. In the current situation the entire world is passing through a very critical situation and medical services almost collapse due to the span of COVID-19. The virus is directly threatening to human being's life and attack to their nervous system, collapse lungs, breathing problems and damage other parts of the body system. The researcher build a predictive model using a Gaussian approach to find out the current status of COVID-19 and its future prediction. This predictive model is very helpful for countries and before timely they can manage their health related services, make a change in their decision making policy to stop COVID-19 spreading. Method: in this research paper the researcher builds a predicting model using real time analytics to measure the intensity of spreading COVID-19 in major concern countries. The main objective of this research article to predict the rate of spreading COVID-19 cases, visualize, and represent the future trends of COVID-19 cases. For the predictive analysis the researcher used the Gaussian Prediction model, time series analysis, exploratory data analysis, and K-means clustering. The researcher used the parameters such as rate of spreading, slow down speed, a sudden change in rate, prediction of the number of cases and differences in mortality rate. The results: The researcher discussed the weekly, monthly rate of spreading COVID-19 cases and predicted how it covered the world entire populations. The predictive model is very helpful to the countries where a number of cases are rapidly spreading and showing the future trends whether it is decreasing or increasing ratio. The countries can manage their health related services and other possible resources to stop the COVID-19 cases in their countries. If the prediction is unknown that situation is horrible for the entire world. Conclusion: Finally the researcher concluded that the predictive model of COVID-19 cases has significant impact to all over countries to show the future spreading trends, the accuracy level of this predictive model is 92% which is verified by using Gaussian approach. In some cases prediction might be unfavorable to handle the health care industries that are only %8 chances. The researcher giving the assurance the developed predictive model is more reliable and efficient to predict the COVID-19 case and its future trends, so the countries and their health related unit can manage the health related services in rapid manner.

The use of vintage surficial sediment data and sedimentary cores to determine past and future trends in estuarine metal contamination (Sydney estuary, Australia)

Storage is an important process involved in the postharvest treatment of grain-oilseed and is necessary for maintaining high quality and ensuring the long-term supply of these commodities in the food industry. Proper storage practices help prevent spoilage, maintain nutritional value, and preserve marketable quality. It is of great interest for storage to investigate flow, heat and mass transfer processes, and quality change for optimizing the operation parameters and ensuring the quality of grain-oilseed. This review discusses the mathematical models developed and applied to describe the physical field, biological field, and quality change during the storage of grain-oilseed. The advantages, drawbacks, and industrial relevance of the existing mathematical models were also critically evaluated, and an organic system was constructed by correlating them. Finally, the future research trends of the mathematical models toward the development of multifield coupling models based on biological fields to control quality were presented to provide a reference for further directions on the application of numerical simulations in this area. Meanwhile, artificial intelligence (AI) can greatly enhance our understanding of the coupling relationships within grain-oilseed storage. AI's strengths in both qualitative and quantitative analysis, as well as its effectiveness, make it an invaluable tool for this purpose.