**Transient Systems Modeling**

**DSM** offers a powerful numerical time-response solution by solving two sets of algebraic and differential equations.

Transient part of DSM can solve the systems with high stiffness and discontinuities. For example in hydraulic systems the numerical discontinuities are limits in pressure, displacements, flow reversal, cavitation and coulomb friction.

DSM has a powerful auto-adaptation time step algorithm for solving differential equations. This offers reductions in run time compared to other methods with fixed time step or traditional variable time step. The algorithm used to solve algebraic equations is very efficient. As a result these equations can be very non-linear and can be solved very fast. In transient systems, inputs or generators may vary during a simulation. For example in hydraulic systems, pump may ramp up in start, generate sinusoidal discharge or ramp down during shut down.

DSM allows users to enter the formulation of all types of inputs for different time periods.

For defining inputs there is a large mathematical library accessible to users, simple functions such as constant, ramp, sine wave, exponential, damped sine wave, pulse, linear profile, step profile or more complex functions such as Bessel functions, distribution functions, Airy functions, probability functions, etc.

DSM provides a powerful syntax and semantics error handling for input formulations.

**User Subroutines and Functions**

A very important feature of DSM is the ability to call predefined user subroutines and functions. This gives users access to a vast library of subroutines and functions that they have either developed themselves or are available in the market. For example a user may have already written a subroutine or function for a complex calculation needed in a components modeling and design. This helps the users to integrate their previous work with DSM.

**DSM** offers a general nonlinear and component-based module using the successive quadratic programming algorithm and a finite difference gradient method. This method obtains subproblems by using a quadratic approximation of the Lagrangian and by linearizing the constraints, based on the iterative formulation and solution of quadratic programming subproblems.

**Steady State Systems Modeling**

**DSM** 's Steady-State feature is used for the steady-state behavior of a system. This kind of analysis is used where the emphasis is on steady-state performance and not the transient behavior, examples of which are Heat Transfer process, fluidic, etc. This kind of analysis is also used for calculation of the parameters needed to study the stability of linearized systems.

**DSM** has a powerful algebraic equations solver with a fast convergence even for highly non-linear systems.

**User Subroutines and Functions**

A very important feature of DSM is the ability to call predefined user subroutines and functions. This gives users access to a vast library of subroutines and functions that they have either developed themselves or are available in the market. For example a user may have already written a subroutine or function for a complex calculation needed in a components modeling and design. This helps the users to integrate their previous work with DSM.

**DSM** offers a general nonlinear programming module using the successive quadratic programming algorithm and a finite difference gradient method. This method obtains subproblems by using a quadratic approximation of the Lagrangian and by linearizing the constraints, based on the iterative formulation and solution of quadratic programming subproblems. This module is not component-based. Users could enter their mathematical models. Then by defining the equality and non equality constraints and also the objective function, users could optimize their problem.

Optimization + Dynamic Systems Modeling & Simulation.