Feb 272021
 

Download ESTECO modeFRONTIER 2020 R3 Win64 full license forever

Link download ESTECO modeFRONTIER 2020 R3 x64 full cracked 100% working

Working with ESTECO modeFRONTIER 2020 R3 full license

Working with ESTECO modeFRONTIER 2020 R3 full license

Interface language: English
System requirements: Microsoft Windows 7 / 8.1 / 10 64-bit

Description: modeFRONTIER is an environment for solving problems of criterion and multi-criteria optimization, working with various CAD, CAE, CFD and other software systems. The environment has the ability to work in automatic design and optimization of products. Implemented data processing and analysis using various methods.
Main technical characteristics:
Design of an experiment (DOE), distribution of the input population of variables, estimation of forecast accuracy
User DOE; Random; Sobol; Full factorial; Cubic-face-centered; Taguchi; Box-Benken; Montecarlo; Reduced Factorial; Latin Square; Latin Hypercube;
D-Optimal; Cross validation method; Constraint satisfaction problem
Decision making for multi-criteria optimization (MCDM):
Hurwicz criterion;
Linear algorithm;
GA algoriphm;
Minimax, savage mimimax regret criterion;
Algorithms, optimization methods:
DOE Sequence – direct enumeration of parameters;
MOGA II – genetic algorithm for multi-criteria optimization;
ARMOGA – genetic algorithm based on MOGA;
NSGA II – genetic algorithm for non-dominated sorting for multi-criteria optimization;
NASH – an algorithm based on the Nash theory of non-cooperative games for multicriteria optimization;
B-BFGS – gradient algorithm;
SIMPLEX – search for a solution without the use of derivatives by the Nelder-Mead method;
Levenberg-Marquardt;
Simulated Annealing – model hardening algorithm (simulated annealing method);
1P1-ES – evolutionary strategy;
DES – evolutionary strategy for performing criterion optimization with continuous variables;
MMES – evolutionary strategy for multicriteria optimization with discrete and continuous variables;
FMOGA II – version of the MOGA algorithm with improved convergence;
FSIMPLEX – Simplex version with improved convergence and the ability to solve multicriteria problems;
MOSA – a version of simulated annealing with the ability to solve multicriteria problems;
MACK – an algorithm for approximating response surfaces;
NLPQLP – Sequential Quadratic Programming (SQP) algorithm;
NLPQLP-NBI – Normal Boundary Intersection method + NLPQLP (algorithm with the ability to solve multicriteria nonlinear problems);
Multi-Objective Particle Swarm.
Metamodels (response surface approximation, RSM, approximate mathematical models), construction methods:
K-Nearest (Shepard-a method);
SVD (singular value decomposition);
Kriging, a regression analysis technique based on the work of Daniel Krige;
Parametric surfaces, polynomial regression;
Gaussian Processes – an approach to solving problems of regression analysis based on the work of Bezier (Bayesian);
Artificial neural networks, radial basis neural networks (radial basis function),
Meta – model validation tools.
6 Sigma, Quality Management, Design for Six Sigma (DFSS):
Sigma quality (six sigma quality);
Failure modes and analysis of their impact (discards analysis);
Ishikawa diagram.
Visual data analysis, assessment of the statistical significance of data:
Probability density function;
Study of the relationship between variables, scatter chart, line, bubble chart, trend lines;
Data distribution, histogram, pie, cumilative plot;
Linear correlation analysis, correlation matrix, scatter matrix, effects matrix
(effects matrix);
Determination of basic characteristics of samples, box-whiskers, Quantile-Quantile plot;
Calculation of the closeness of interaction of parameters;
Working with data samples of large dimension, Student’s test, analysis of variance (Bon-ferroni test, ANOVA);
Distribution fitting;
Cluster analysis methods:
– partitive clustering
– methods of hierarchical clustering (hierarchical clustering) – average-linkage, centroid-linkaga, complete-linkaga, single-linkage,
ward approach,
– k-means algorithm (K-Means Clustering), Forgy approach, Kaufman approach, Macqueen approach, random
– self-organizing maps (SOMs) algorithm,
– dendrograms
Experience of use in various fields:
– Optimization of the shape of the inlet pipes
– Optimization of the cooling system
– Optimization of the air flow in the engine compartment
– Reducing vibrations
– Aerospace industry
– The problem of optimizing the shape of a centrifugal compressor
– The problem of optimizing the shape of an axial turbine and an axial compressor
– General engineering
– Optimization of the injection molding process
– Optimization of the metal casting process
– Optimization of hot stamping technology
– Marine construction
– The task of optimizing the ship’s contours, reducing the hydrodynamic resistance
– Optimal steering wheel design
– Financial markets
– The problem of optimizing the investment portfolio of shares
– Making decisions in the financial market
ModeFRONTIER implements work with many software systems:
AMESim; AVL Boost; AVL Hydsim; Flowmaster; GT-Power; KULI; Wave Aspen PLUS; CHEMKIN; eta / VPG; LS-DYNA; MADYMO; RADIOSS; Mathematica;
Matlab; DEP; MS Excel; MySQL OpenOffice; Winbatch; ADAMS; Carsim; Dymola; RecurDyn; SIMPACK; Virtual.Lab; CADFix; CATIA; SolidWorks; I-DEAS;
UnigraphicsNX; Maxsurf; ProEngineer; JMAG; AVL-Fame; ICEMCFD; GID; Gridgen; MSC Patran; Paramesh; Sculptor; AdvantEdge; Cadmould; Magma COMSOL Multiphysiscs (FEMLAB); Simulink; ANSYS CFX; ANSYS TASCflow; FIDAP; FLUENT; GAMBIT; AVL-Fire; Star-CD; Star-CCM +; Star-Design; ABAQUS
ANSYS; ANSYS Workbench; AVL-Excite; eta / VPG; MSC MARC; MSC NASTRAN; PERMAS; SAMCEF; STRAUS7; SYSNOISE Fieldview; Friendship; Icare;
NAPA4; Nu-SHALLO; RAPID; REVA; Shipflow Condor; GridEngine; IBM LoadLeveler; LSF; NQS
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