Numerical Models for Operational Ocean Observing

2018 ◽  
pp. 113-123
Author(s):  
Jorge E. Corredor
2007 ◽  
Vol 41 (1) ◽  
pp. 53-61 ◽  
Author(s):  
Philip Bogden ◽  
Tom Gale ◽  
Gabrielle Allen ◽  
Jon MacLaren ◽  
Guy Almes ◽  
...  

The Southeastern Universities Research Association (SURA) has advanced the SURA Coastal Ocean Observing and Prediction (SCOOP) program as a multi-institution collaboration to design and prototype a modular, distributed system for real-time prediction and visualization of the coastal impacts from extreme atmospheric events, including hurricane inundation and waves. The SCOOP program vision is a community “cyberinfrastructure” that enables advances in the science of environmental prediction and coastal hazard planning. The system architecture is a coordinated and distributed network of interoperable, modularized components that include numerical models, information catalogs, distributed archives, computing resources, and network infrastructure. The components are linked over the Internet by standardized web-service interfaces in a service-oriented architecture (SOA). The design philosophy allows geographically disparate partnering institutions to provide complementary data-provider and integration services. The overall system enables coordinated sharing of resources, tools, and ideas among a virtual community of coastal and computer scientists. The distributed design builds on the notion that standards enable innovation, and seeks to leverage successes of the World Wide Web by creating an environment that nurtures interaction between the research community, the private sector, and government agencies working together on behalf of the nation.


2020 ◽  
Vol 82 ◽  
pp. 149-160
Author(s):  
N Kargapolova

Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.


2003 ◽  
Vol 59 (3-4) ◽  
pp. 10
Author(s):  
D. Yu. Kulik ◽  
S. L. Senkevich ◽  
Victor Ivanovich Tkachenko
Keyword(s):  

OCEANS 2009 ◽  
2009 ◽  
Author(s):  
John A. Lever ◽  
Bruce Gritton ◽  
Charles Alexander

2019 ◽  
Vol 2019 (4) ◽  
pp. 23-31
Author(s):  
Jakub Wilk ◽  
Radosław Guzikowski

Abstract The paper presents the validation procedure of the model used in the analysis of the composite blade for the rotor of the ILX-27 rotorcraft, designed and manufactured in the Institute of Aviation, by means of numerical analyses and tests of composite elements. Numerical analysis using finite element method and experimental studies of three research objects made of basic materials comprising the blade structure – carbon-epoxy laminate, glass-epoxy composite made of roving and foam filler – were carried out. The elements were in the form of four-point bent beams, and for comparison of the results the deflection arrow values in the middle of the beam and axial deformations on the upper and lower surfaces were selected. The procedure allowed to adjust the discrete model to real objects and to verify and correct the material data used in the strength analysis of the designed blade.


Author(s):  
V. E. Perekutnev ◽  
V. V. Zotov

Upgrading of hoisting machines aims to improve their performance, to reduce risk of accidents, and to cut down operational and capital costs. One of the redesign solutions is replacement of steel cables by rubber cables. This novation can extend life of pulling members, decrease diameters of drive and guide wheels and, consequently, elements of the whole hoisting machines: rotor, reducing gear, motor. This engineering novation needs re-designing of hoisting machines; thus, the new design should be validated, in particular, strength characteristics of the machine members. This article considers a drive wheel of a hoisting machine with a pulling belt. In order to justify the potential range of design parameters with regard to safety factor, the numerical models of different-design drive wheels are developed and their operation with pulling belt (rubber cable) is simulated in the SolidWorks environment. The data on the stress state of the wheel elements are analyzed, the most loaded points are identified, and the maximal stresses on the sidewall surface and in the spokes of wheels of different designs are plotted.


2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>


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