THREE-DIMENSIONAL NUMERICAL SIMULATION OF TSUNAMI WAVES BASED ON THE NAVIER-STOKES EQUATIONS

A numerical algorithm of solving the three-dimensional system of Navier-Stokes equations to simulate free surface waves and flows with gravity is presented. The main problem here is to ensure that the gravity force is properly accounted in the presence of discontinuities in the medium density. The task is made more complicated due the use of unstructured computational grids with collocated placement of unknown quantities and splitting algorithms based on SIMPLE-type methods. To obtain correctly the hydrostatic pressure, it is suggested that the contribution of the gravitational force in the equation for pressure should be distinguished explicitly; the latter being calculated by using the solution of the two-phase medium gravitational balance problem. To ensure the balance of the gravity force and the pressure gradient in the case of rest an algorithm in which the pressure gradient in the equation of motion is replaced by a modification considering the gravitational force action is suggested. This method is demonstrated by the example of tsunami wave propagation in the real water area of the World Ocean

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

Research on the Application of Vortex Lattice Method and Doublet Lattice Method in Aerodynamic Analysis of the Wing of Solar-Powered Unmanned Aerial Vehicle

In this paper the application of doublet lattice method and vortex lattice method is discussed. A wing of a solar-powered unmanned aerial vehicle (UAV) is chosen as the model. Both the methods are used to calculating the pressure distribution. The results show that the two methods can be used for unsteady aerodynamic analysis of such aircraft in time domain and frequency domain respectively

Analysis of the Sound Field Structure in the Cabin of the RRJ-95NEW-100 Prototype Aircraft

The results of in-flight experiments to determine the structure of the sound field in the cabin and pressure fluctuation fields on the surface of the fuselage of the RRJ-95NEW-100 prototype aircraft are presented here. Wall pressure fluctuation spectrums are obtained for three zones of measuring windows (forward, center, and rear fuselage) in cruising flight mode. The effect of the jet on the pressure fluctuation levels in the tail fuselage is considered. For an aircraft without an interior, the contribution of the main sources to the total intensity calculated through A-weighted overall sound pressure levels is determined. It has been determined that the main noise sources in the cabin of the RRJ-95NEW-100 prototype aircraft in cruising flight mode are pressure fluctuation fields on the fuselage surface (turbulent boundary layer noise) and the air conditioning system. The ratio between the sources varies along the length of the cabin

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The Gene Ontology knowledgebase in 2023.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The Gene Ontology Knowledgebase in 2023

: The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology - a computational knowledge structure describing functional characteristics of genes; 2) GO annotations - evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) - mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project