Tempus_StepperNewmarkImplicitDForm_decl.hpp

Go to the documentation of this file.

// @HEADER
// ****************************************************************************
//                Tempus: Copyright (2017) Sandia Corporation
//
// Distributed under BSD 3-clause license (See accompanying file Copyright.txt)
// ****************************************************************************
// @HEADER

#ifndef Tempus_StepperNewmarkImplicitDForm_decl_hpp
#define Tempus_StepperNewmarkImplicitDForm_decl_hpp

#include "Tempus_WrapperModelEvaluatorSecondOrder.hpp"
#include "Tempus_StepperImplicit.hpp"

namespace Tempus {

/** \brief Newmark time stepper.
 *
 *  Here, we implement the Newmark scheme in displacement predictor/corrector
 *  form; see equations (34)-(35) in: A. Mota, W. Klug, M. Ortiz,
 *  "Finite element simulation of firearm injury to the human cranium",
 *  Computational Mechanics 31(1) 115-121 (2003).
 *
 *  Newmark has two parameters: \f$\beta\f$
 *  and \f$\gamma\f$, both of which need to be in the range \f$[0,1]\f$.
 *  Newmark can be an explicit or implicit method, depending on
 *  the value of the \f$\beta\f$ parameter. If \f$\beta = 0\f$, the method
 *  is explicit; but note that the d-form of the Newmark scheme is not defined
 *  for the explicit case.
 *
 *  Newmark is second order accurate if \f$\gamma =  0.5\f$; otherwise it
 *  is first order accurate.  Some additional properties about the Newmark
 *  Beta scheme can be found
 *  <a href="http://opensees.berkeley.edu/wiki/index.php/Newmark_Method">here</a>.
 *
 *  The First-Step-As-Last (FSAL) principle is not used with the
 *  Newmark implicit D-Form method.
 */
template <class Scalar>
class StepperNewmarkImplicitDForm : virtual public Tempus::StepperImplicit<Scalar> {
 public:

  /** \brief Default constructor.
   *
   *  Requires subsequent setModel(), setSolver() and initialize()
   *  calls before calling takeStep().
  */
  StepperNewmarkImplicitDForm();

  /// Constructor
  StepperNewmarkImplicitDForm(
    const Teuchos::RCP<const Thyra::ModelEvaluator<Scalar>>& appModel,
    const Teuchos::RCP<StepperObserver<Scalar> >& obs,
    const Teuchos::RCP<Thyra::NonlinearSolverBase<Scalar> >& solver,
    bool useFSAL,
    std::string ICConsistency,
    bool ICConsistencyCheck,
    bool zeroInitialGuess,
    std::string schemeName,
    Scalar beta,
    Scalar gamma);

  /// \name Basic stepper methods
  //@{
  virtual void
  setModel(const Teuchos::RCP<const Thyra::ModelEvaluator<Scalar>>& appModel);

  virtual void setObserver(
    Teuchos::RCP<StepperObserver<Scalar> > /* obs */ = Teuchos::null){}

  virtual Teuchos::RCP<StepperObserver<Scalar> > getObserver() const
  { return Teuchos::null; }

  /// Initialize during construction and after changing input parameters.
  virtual void
  initialize();

  /// Set the initial conditions and make them consistent.
  virtual void setInitialConditions (
    const Teuchos::RCP<SolutionHistory<Scalar> >& /* solutionHistory */){}

  /// Take the specified timestep, dt, and return true if successful.
  virtual void
  takeStep(const Teuchos::RCP<SolutionHistory<Scalar>>& solutionHistory);

  /// Get a default (initial) StepperState
  virtual Teuchos::RCP<Tempus::StepperState<Scalar>>
  getDefaultStepperState();
  virtual Scalar
  getOrder() const {
    if (gamma_ == 0.5)
      return 2.0;
    else
      return 1.0;
  }
  virtual Scalar
  getOrderMin() const {
    return 1.0;
  }
  virtual Scalar
  getOrderMax() const {
    return 2.0;
  }
  virtual bool isExplicit()         const {return false;}
  virtual bool isImplicit()         const {return true;}
  virtual bool isExplicitImplicit() const
    {return isExplicit() and isImplicit();}
  virtual bool isOneStepMethod()   const {return true;}
  virtual bool isMultiStepMethod() const {return !isOneStepMethod();}

  virtual OrderODE getOrderODE()   const {return SECOND_ORDER_ODE;}
  //@}

  /// Return W_xDotxDot_coeff = d(xDotDot)/d(x).
  virtual Scalar getW_xDotDot_coeff (const Scalar dt) const
    { return Scalar(1.0)/(beta_*dt*dt); }
  /// Return alpha = d(xDot)/d(x).
  virtual Scalar getAlpha(const Scalar dt) const { return gamma_/(beta_*dt); }
  /// Return beta  = d(x)/d(x).
  virtual Scalar getBeta (const Scalar ) const { return Scalar(1.0); }

  Teuchos::RCP<const Teuchos::ParameterList> getValidParameters() const;

  /// \name Overridden from Teuchos::Describable
  //@{
    virtual void describe(Teuchos::FancyOStream& out,
                          const Teuchos::EVerbosityLevel verbLevel) const;
  //@}

  void
  predictVelocity(
      Thyra::VectorBase<Scalar>& vPred, const Thyra::VectorBase<Scalar>& v,
      const Thyra::VectorBase<Scalar>& a, const Scalar dt) const;

  void
  predictDisplacement(
      Thyra::VectorBase<Scalar>& dPred, const Thyra::VectorBase<Scalar>& d,
      const Thyra::VectorBase<Scalar>& v, const Thyra::VectorBase<Scalar>& a,
      const Scalar dt) const;

  void
  correctVelocity(
      Thyra::VectorBase<Scalar>& v, const Thyra::VectorBase<Scalar>& vPred,
      const Thyra::VectorBase<Scalar>& a, const Scalar dt) const;

  void
  correctDisplacement(
      Thyra::VectorBase<Scalar>& d, const Thyra::VectorBase<Scalar>& dPred,
      const Thyra::VectorBase<Scalar>& a, const Scalar dt) const;

  void
  correctAcceleration(
      Thyra::VectorBase<Scalar>& a, const Thyra::VectorBase<Scalar>& dPred,
      const Thyra::VectorBase<Scalar>& d, const Scalar dt) const;


  void setSchemeName(std::string schemeName);
  void setBeta(Scalar beta);
  void setGamma(Scalar gamma);

 protected:

  Thyra::ModelEvaluatorBase::InArgs<Scalar> inArgs_;
  Thyra::ModelEvaluatorBase::OutArgs<Scalar> outArgs_;

  std::string schemeName_;
  Scalar beta_;
  Scalar gamma_;

  Teuchos::RCP<Teuchos::FancyOStream> out_;

};
}  // namespace Tempus

#endif  // Tempus_StepperNewmarkImplicitDForm_decl_hpp