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Closed Form G
NASTRAN Interface
Customized Interface
Generic Interface

 

UNIPASS™ offers many outstanding capabilities and features, including: 

  •  4 Problem Types: 

  • Component Problem

  • Series System Problem

  • Parallel System Problem

  • General System Problem

  •  4 Analysis Types: 

  • Probability Analysis

  • Inverse Probability Analysis

  • CDF/PDF Analysis

  • Design Optimization - Robust Design

  •  Bayesian Analysis

  •  6 PROBABILISTIC ANALYSIS Methods

  • First-Order Reliability Methods (FORM)

  • Second-Order Reliability Methods (SORM)

  • Simulation Methods (SM)

  • Importance Sampling Method (ISM)

  • Response Surface Methods (RSM)

  • Mean Value-based Methods (MVBM)

  • 11 MPP Identification Methods 

  • U-based/U-linearized MPPL method 

  • Modified U-based/U-linearized MPPL method 

  • U-based/X-linearized MPPL method 

  • Modified U-based/X-linearized MPPL method 

  • HL-RF method 

  • Modified HL-RF method 

  • Improved HL-RF method 

  • Sequential Quadratic method 

  • Gradient Projection method 

  • Modified Gradient Projection method 

  • Simulation Search method (non-gradient-based method)

  •   2 Second-order Reliability Methods 

  • Curvature-Fitting paraboloid 

  • Point-Fitting piecewise paraboloid 

  •  3 Simulation Methods 

  • Monte Carlo Simulation 

  • Directional Simulation 

  • Latin Hypercube Simulation 

  •   3 Important Sampling Methods 

  • Monte Carlo Importance Sampling

  • Sphere-based importance sampling 

  • Directional importance sampling

  •  2 Response Surface Methods 

  • Expansion around the mean point

  • Expansion around the user-defined point

  • 3 Mean-Value-Based Methods 

  • Mean-value first-order second-moment method (MVFOSM)

  • Mean-value method (MV)

  • Advanced mean-value method (AMV)

  •  Various Sensitivity Analysis 

  1. Sensitivity of limit-state function with respect to the random variables at the MPP in both the standard normal space and the original space

  2. Sensitivity of failure probability and reliability index with respect to the random variables

  3.  Sensitivity of failure probability and reliability index with respect to means and standard deviations of random variables

  4. Sensitivity of failure probability and reliability index with respect to distribution parameters, which may be correlation coefficients, bounds or other parameters used to define the distribution

  5. Dimensionless sensitivity of failure probability and reliability index with respect to mean standard deviations of random variables

  •  Flexible CDF/PDF Analysis

  1.  By specifying upper and lower bounds of failure probability

  2.  By specifying upper and lower bounds of reliability index

  3. By specifying upper and lower bounds of limit-state function

  4. By specifying individual failure probability values

  5. By specifying individual reliability indexes

  6. By specifying individual g values

  •   4 Classes of Random Variables 

    1. Statistically independent (SI)

    2. Marginal with correlation coefficient matrix (MR)

    3. Conditional distributions on SI random variables (Hyper Parametric Distribution I)

    4. Conditional distributions on MR random variables (Hyper Parametric Distribution II)

  •  37 Statistical Distributions 

  1.  High-level precision consistent to 14 decimal points

  2. Wide range of CDF values stretching from 2.8 ´ 10-55 to 0.9999999999999 (i.e., F[-15.615] to F[7.385])

  3.  Flexible input methods (up to 7 methods)

  4. 37 Distribution Types:

Deterministic Beta
Chi-square Double exponential
Exponential F distribution
Gamma Gumbel  (Type I Largest)
Logistic Lognormal
Maxwell Normal
Pareto Rayleigh
Student t Triangular
Truncated normal

Type I smallest

Type II largest Uniform
Weibull (Type III Smallest) Truncated Lognormal
Truncated Exponential Truncated Gamma
Truncated Rayleigh Truncated Gumbel
Truncated Type I Smallest Truncated Type II Largest

Truncated Weibull (Two parameters)

Truncated Chi square

Truncated Maxwell Truncated Double Exponential
Truncated Student t Truncated F
Truncated Logistic Truncated Pareto

User Provided PDF/CDF Points

 

  • 61  Internal Mathematical Functions to Define the Limit-state Functions

  1.  Scripting type input format

  2.  Limit-state functions expressed in terms of random variables and random functions

  3. Operators: ** (or ^), *, /, +, -

  4. 61 supported functions

ABS(argf) ACOS(argf) ACOSD(argf) ANSYS(arg)
ASIN(argf) ASIND(argf) ATAN(argf) ATAND(argf)
CDF(argi, argj) CDFIN(argi, argj) CHIS(argfi, argfj) CHISIN(argf, argf)
COS(argf) COSD(argf) COSH(argf) COTAN(argf)
COTAND(argf) EXP(argf) GAMMA(argf) EXTERNAL(argi)
INT(argf) LOG(argf) LOG10(argf) MAX(argfi, argfj)
MAXA(argfi, argfj) MAXAV(argi, argj) MAXV(argi, argj) MEAN(arg)
MIN(argfi, argfj) MINA(argfi, argfj) MINAV(argi, argj) MINV(argi, argj)
MOD(argfi, argfj) NASTRAN(arg) PDF(argi, argj) PHI(argf)
PHIIN(argf) PI( )

PROD(argi, argj)

PRODA(argi, argj)

SIN(argf) SIND(argf) SINH(argf)

SQRT(argf)

STD(arg) SUM(argi, argj) SUM_M(argi, argj) SUM_SD(argi, argj)
SUMA(argi, argj) SUMA_M(argi, argj)

SUMSQ(argi, argj)

SUMSQ_M(argi, argj)

SUMSQ_SD(argi, argj) SYSTEM(argi, command) TAN(argf) TAND(argf)
TANH(argf) USERC1(arg) USERC2(arg) USERF1(arg)
USERF2(arg)      

 

  •  Interfaces with Commercial Software MSC/NASTRAN™

  1. Graphic User Interface (GUI) input window

  2. Direct substitution of random variable names and random function names as input parameters in a NASTRAN bulk data input file

  3. Tracking capability for detecting the effect of a particular random variable. A feedback control loop designed to minimize the number of NASTRAN calls

  4. Probabilistic Analysis in conjunction with full utilization of MSC/NASTRAN capabilities

Response type:

Nodal displacement

Element stress

Element strain

Element force

Response location:

    Specific node or element number

    Maximum response value

    Minimum response value

    Maximum absolute response value

  •  Customized Interface 

  1. Interface with unlimited number of in-house or commercial software for probabilistic analysis

  2. Unlimited number of input files for each external software

  3. GUI input window to guide users to input data for the interface

  4. Direct substitution of random variable names and random function names as input parameters in the external software’s native input file done by UNIPASS™

  5. Implemented with easy and minimum C/FORTRAN coding in a DLL (Dynamic Link Library) format to extract the desired data and pass it to UNIPASS™

  6. Tracking capability for detecting the effect of random variables to minimize the number of external software calls

  7.  Probabilistic Analysis in conjunction with full utilization of the external software’s capabilities

  •  Generic Interface

  1. Interface with unlimited number of in-house or commercial software for probabilistic analysis

  2. Unlimited number of input files for each external software

  3. GUI input window to guide users to input data for the interface

  4. Direct substitution of random variable names and random function names as input parameters in the external software’s native input file done by UNIPASS™

  5. No programming work

  6. Multi key words to identify the desired response from the output of external software

  7. Tracking capability for detecting the effect of random variables to minimize the number of external software calls

  8. Probabilistic Analysis in conjunction with full utilization of the external software’s capabilities

  •  System Command Interface

  1. Using UNIPASS™ built in function SYSTEM to perform interface with other external software

  2. Interface with unlimited number of in-house or commercial software for probabilistic analysis

  3. No GUI  window  for the interface

  4. Direct substitution of random variable names and random function names as input parameters in the external software’s native input file done by users

  5. Programming work by users required for preparing the input file of external solver, executing the external solver, and extracting desired response from output file of external solver to UNIPASS™

  6. Tracking capability for detecting the effect of random variables to reduce the number of external software calls

  7. Probabilistic Analysis in conjunction with full utilization of the external software’s capabilities

  • Characteristic Outputs

  1. The coordinates of linearization points and the associated limit-state function values

  2. The approximated mean and standard deviation of limit-state function evaluated at linearization points

  3. MPP, reliability index, limit-state function value and the vector of directional cosine for the MPP

  4. Failure probability, reliability and generalized reliability index

  5. Sensitivity measurements

  6. Simulation results

  7. PDF/CDF of limit-state function

 

Closed Form G ] NASTRAN Interface ] Customized Interface ] Generic Interface ]

Last Updated 11/12/08

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