latom.surrogate.om_metamodels_llo2heo

@authors: Alberto FOSSA’ Giuliana Elena MICELI

Functions

save(obj, filename)

Save an object.

Classes

MetaModel([distributed, extrapolate, …])

MetaModel class sets up an OpenMDAO Problem object and a MetaModelStructuredComp subsystem to compute and exploit a surrogate model for different transfer trajectories.

RespSurf(isp, twr, param, title[, nb_lines, …])

Plots the response surface resulting from the surrogate models computations.

Spacecraft(isp, twr[, throttle_min, m0, …])

Spacecraft class defines the spacecraft characteristics.

TwoDim3PhasesLLO2HEOMetaModel([distributed, …])

TwoDim3PhasesLLO2HEOMetaModel implements MetaModel for a two-dimensional transfer from an LLO to an HEO modeled as a three-phases trajectory.

TwoDim3PhasesLLO2HEONLP(body, sc, alt, rp, …)

TwoDim3PhasesLLO2HEONLP transcribes an optimal control problem for a three-phases ascent trajectory from a circular Low Lunar Orbit (LLO) to an Highly Elliptical Orbit (HEO) into a Non Linear Programming Problem (NLP) using the OpenMDAO and dymos libraries.

TwoDimLLO2ApoAnalyzer(body, sc, alt, rp, t, …)

TwoDimLLO2HEOAnalyzer class defines the methods to analyze the results of a two dimensional simulation from a Low Lunar Orbit to an Highly Elliptical Orbit.

TwoDimLLO2ApoContinuationAnalyzer(body, sc, …)

TwoDimLLO2ApoContinuationAnalyzer class defines the methods to analyze the results of a two dimensional simulation from a Low Lunar Orbit to an Highly Elliptical Orbit using a continuation method over several thrust/weight ratios.

TwoDimLLO2ApoContinuationMetaModel([…])

TwoDimLLO2ApoContinuationMetaModel implements MetaModel for a two-dimensional escape burn from an LLO to an intermediate ballistic arc to reach the specified HEO apoapsis radius.

TwoDimLLO2ApoMetaModel([distributed, …])

TwoDimLLO2ApoMetaModel implements MetaModel for a two-dimensional escape burn from an LLO to an intermediate ballistic arc to reach the specified HEO apoapsis radius.
class latom.surrogate.om_metamodels_llo2heo.TwoDimLLO2ApoMetaModel(distributed=False, extrapolate=False, method='scipy_cubic', training_data_gradients=True, vec_size=1, rec_file=None)[source]

Bases: latom.surrogate.om_metamodels.MetaModel

TwoDimLLO2ApoMetaModel implements MetaModel for a two-dimensional escape burn from an LLO to an intermediate ballistic arc to reach the specified HEO apoapsis radius.

static solve(body, sc, alt, t_bounds, method, nb_seg, order, solver, snopt_opts=None, u_bound=None, **kwargs)[source]

Solve the NLP for the i-th twr and k-th Isp values.

Parameters

  • body (Primary) – Central attracting body

  • sc (Spacecraft) – Spacecraft object characterized by the i-th twr and k-th Isp values

  • alt (float) – Orbit altitude [m]

  • t_bounds (iterable) – Time of flight lower and upper bounds expressed as fraction of tof

  • method (str) – Transcription method used to discretize the continuous time trajectory into a finite set of nodes, allowed gauss-lobatto, radau-ps and runge-kutta

  • nb_seg (int) – Number of segments in which the phase is discretized

  • order (int) – Transcription order within the phase, must be odd

  • solver (str) – NLP solver, must be supported by OpenMDAO

  • snopt_opts (dict or None, optional) – SNOPT optional settings expressed as key-value pairs. Default is None

  • u_bound (str, optional) – Specify the bounds on the radial velocity along the transfer as lower, upper or None. Default is None

Other Parameters

  • rp (float) – HEO periapsis radius [m]

  • t (float) – HEO period [s]

Returns

  • m_prop (float) – Propellant fraction [-]

  • f (bool) – Failure status

static abs_path(rec_file)

Returns the absolute path of the file where the meta model is stored.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

Returns

fid – Full path where the meta model is stored

Return type

str

compute_grid(twr_lim, isp_lim, nb_samp)

Computes a regular sampling grid in the input space twr, Isp.

Parameters

  • twr_lim (iterable) – Thrust/weight ratio lower and upper limits [-]

  • isp_lim (iterable) – Specific impulse lower and upper limits [s]

  • nb_samp (iterable) – Number of samples along the twr and Isp axes

load(rec_file)

Loads stored data to instantiate a meta model.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

plot(nb_lines=50, kind='prop', log_scale=False)

Plot the response surface corresponding to the loaded meta model.

Parameters

  • nb_lines (int, optional) – Number of contour lines. Default is 50

  • kind (str) – prop to display the propellant fraction m_prop, final to display the final spacecraft mass 1 - m_prop

  • log_scale (bool, optional) – Set to True if the twr values are in logarithmic scale. Default is False

sampling(body, twr_lim, isp_lim, alt, t_bounds, method, nb_seg, order, solver, nb_samp, snopt_opts=None, u_bound=None, rec_file=None, **kwargs)

Compute a new set of training data starting from a given sampling grid.

Parameters

  • body (Primary) – Central attracting body

  • twr_lim (iterable) – Thrust/weight ratio lower and upper limits [-]

  • isp_lim (iterable) – Specific impulse lower and upper limits [s]

  • alt (float) – Orbit altitude [m]

  • t_bounds (iterable) – Time of flight lower and upper bounds expressed as fraction of tof

  • method (str) – Transcription method used to discretize the continuous time trajectory into a finite set of nodes, allowed gauss-lobatto, radau-ps and runge-kutta

  • nb_seg (int or iterable) – Number of segments in which each phase is discretized

  • order (int or iterable) – Transcription order within each phase, must be odd

  • solver (str) – NLP solver, must be supported by OpenMDAO

  • nb_samp (iterable) – Number of samples along the twr and Isp axes

  • snopt_opts (dict or None, optional) – SNOPT optional settings expressed as key-value pairs. Default is None

  • u_bound (str, optional) – Specify the bounds on the radial velocity along the transfer as lower, upper or None. Default is None

  • rec_file (str, optional) – Name of the file in latom.data.metamodels where the meta model will be stored. Default is None

save(rec_file)

Saves data corresponding to a meta model instance.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

setup()

Setup the OpenMDAO Problem object with known data for twr, Isp and m_prop.

class latom.surrogate.om_metamodels_llo2heo.TwoDimLLO2ApoContinuationMetaModel(distributed=False, extrapolate=False, method='scipy_cubic', training_data_gradients=True, vec_size=1, rec_file=None)[source]

Bases: latom.surrogate.om_metamodels.MetaModel

TwoDimLLO2ApoContinuationMetaModel implements MetaModel for a two-dimensional escape burn from an LLO to an intermediate ballistic arc to reach the specified HEO apoapsis radius.

For each Isp value in the sampling grid, the training data are computed using a continuation method for decreasing twr values.

Parameters

  • distributed (bool, optional) – True if the component has variables that are distributed across multiple processes, False otherwise. Default is False

  • extrapolate (bool, optional) – Sets whether extrapolation should be performed when an input is out of bounds. Default is False

  • method (str, optional) – Spline interpolation method to use for all outputs among cubic, slinear, lagrange2, lagrange3, akima, scipy_cubic, scipy_slinear, scipy_quintic. Default is scipy_cubic

  • training_data_gradients (bool, optional) – Sets whether gradients with respect to output training data should be computed. Default is True

  • vec_size (int, optional) – Number of points to evaluate at once. Default is 1

  • rec_file (str or None, optional) – Name of the file in latom.data.metamodels where the meta model is stored or None if a new model has to be built. Default is None

Variables

energy (ndarray) – Spacecraft specific energy at the end of the transfer on all training points [m^2/s^2]

load(rec_file)[source]

Loads stored data to instantiate a meta model.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

save(rec_file)[source]

Saves data corresponding to a meta model instance.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

compute_grid(twr_lim, isp_lim, nb_samp)[source]

Computes a regular sampling grid in the input space twr, Isp.

Parameters

  • twr_lim (iterable) – Thrust/weight ratio lower and upper limits [-]

  • isp_lim (iterable) – Specific impulse lower and upper limits [s]

  • nb_samp (iterable) – Number of samples along the twr and Isp axes

sampling(body, twr_lim, isp_lim, alt, t_bounds, method, nb_seg, order, solver, nb_samp, snopt_opts=None, u_bound=None, rec_file=None, **kwargs)[source]

Compute a new set of training data starting from a given sampling grid.

Parameters

  • body (Primary) – Central attracting body

  • twr_lim (iterable) – Thrust/weight ratio lower and upper limits [-]

  • isp_lim (iterable) – Specific impulse lower and upper limits [s]

  • alt (float) – Orbit altitude [m]

  • t_bounds (iterable) – Time of flight lower and upper bounds expressed as fraction of tof

  • method (str) – Transcription method used to discretize the continuous time trajectory into a finite set of nodes, allowed gauss-lobatto, radau-ps and runge-kutta

  • nb_seg (int or iterable) – Number of segments in which each phase is discretized

  • order (int or iterable) – Transcription order within each phase, must be odd

  • solver (str) – NLP solver, must be supported by OpenMDAO

  • nb_samp (iterable) – Number of samples along the twr and Isp axes

  • snopt_opts (dict or None, optional) – SNOPT optional settings expressed as key-value pairs. Default is None

  • u_bound (str, optional) – Specify the bounds on the radial velocity along the transfer as lower, upper or None. Default is None

  • rec_file (str, optional) – Name of the file in latom.data.metamodels where the meta model will be stored. Default is None

Other Parameters

  • rp (float) – HEO periapsis radius [m]

  • t (float) – HEO period [s]

  • log_scale (bool) – True if twr values are given in logarithmic scale as log(twr)

plot(nb_lines=50, kind='prop', log_scale=False)[source]

Plot the response surface corresponding to the loaded meta model.

Parameters

  • nb_lines (int, optional) – Number of contour lines. Default is 50

  • kind (str) – prop to display the propellant fraction m_prop, final to display the final spacecraft mass 1 - m_prop

  • log_scale (bool, optional) – Set to True if the twr values are in logarithmic scale. Default is False

static abs_path(rec_file)

Returns the absolute path of the file where the meta model is stored.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

Returns

fid – Full path where the meta model is stored

Return type

str

setup()

Setup the OpenMDAO Problem object with known data for twr, Isp and m_prop.

static solve(body, sc, alt, t_bounds, method, nb_seg, order, solver, snopt_opts=None, u_bound=None, **kwargs)

Solve the NLP for the i-th twr and k-th Isp values.

Parameters

  • body (Primary) – Central attracting body

  • sc (Spacecraft) – Spacecraft object characterized by the i-th twr and k-th Isp values

  • alt (float) – Orbit altitude [m]

  • t_bounds (iterable) – Time of flight lower and upper bounds expressed as fraction of tof

  • method (str) – Transcription method used to discretize the continuous time trajectory into a finite set of nodes, allowed gauss-lobatto, radau-ps and runge-kutta

  • nb_seg (int or iterable) – Number of segments in which each phase is discretized

  • order (int or iterable) – Transcription order within each phase, must be odd

  • solver (str) – NLP solver, must be supported by OpenMDAO

  • snopt_opts (dict or None, optional) – SNOPT optional settings expressed as key-value pairs. Default is None

  • u_bound (str, optional) – Specify the bounds on the radial velocity along the transfer as lower, upper or None. Default is None

Returns

  • m_prop (float) – Propellant fraction [-]

  • f (bool) – Failure status

class latom.surrogate.om_metamodels_llo2heo.TwoDim3PhasesLLO2HEOMetaModel(distributed=False, extrapolate=False, method='scipy_cubic', training_data_gradients=True, vec_size=1, rec_file=None)[source]

Bases: latom.surrogate.om_metamodels.MetaModel

TwoDim3PhasesLLO2HEOMetaModel implements MetaModel for a two-dimensional transfer from an LLO to an HEO modeled as a three-phases trajectory.

static solve(body, sc, alt, t_bounds, method, nb_seg, order, solver, snopt_opts=None, u_bound=None, **kwargs)[source]

Solve the NLP for the i-th twr and k-th Isp values.

Parameters

  • body (Primary) – Central attracting body

  • sc (Spacecraft) – Spacecraft object characterized by the i-th twr and k-th Isp values

  • alt (float) – Orbit altitude [m]

  • t_bounds (iterable) – Time of flight lower and upper bounds expressed as fraction of tof

  • method (str) – Transcription method used to discretize the continuous time trajectory into a finite set of nodes, allowed gauss-lobatto, radau-ps and runge-kutta

  • nb_seg (int) – Number of segments in which the phase is discretized

  • order (int) – Transcription order within the phase, must be odd

  • solver (str) – NLP solver, must be supported by OpenMDAO

  • snopt_opts (dict or None, optional) – SNOPT optional settings expressed as key-value pairs. Default is None

  • u_bound (str, optional) – Specify the bounds on the radial velocity along the transfer as lower, upper or None. Default is None

Other Parameters

  • rp (float) – HEO periapsis radius [m]

  • t (float) – HEO period [s]

  • phase_name (iterable) – Names for the three phases within OpenMDAO

Returns

  • m_prop (float) – Propellant fraction [-]

  • f (bool) – Failure status

static abs_path(rec_file)

Returns the absolute path of the file where the meta model is stored.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

Returns

fid – Full path where the meta model is stored

Return type

str

compute_grid(twr_lim, isp_lim, nb_samp)

Computes a regular sampling grid in the input space twr, Isp.

Parameters

  • twr_lim (iterable) – Thrust/weight ratio lower and upper limits [-]

  • isp_lim (iterable) – Specific impulse lower and upper limits [s]

  • nb_samp (iterable) – Number of samples along the twr and Isp axes

load(rec_file)

Loads stored data to instantiate a meta model.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

plot(nb_lines=50, kind='prop', log_scale=False)

Plot the response surface corresponding to the loaded meta model.

Parameters

  • nb_lines (int, optional) – Number of contour lines. Default is 50

  • kind (str) – prop to display the propellant fraction m_prop, final to display the final spacecraft mass 1 - m_prop

  • log_scale (bool, optional) – Set to True if the twr values are in logarithmic scale. Default is False

sampling(body, twr_lim, isp_lim, alt, t_bounds, method, nb_seg, order, solver, nb_samp, snopt_opts=None, u_bound=None, rec_file=None, **kwargs)

Compute a new set of training data starting from a given sampling grid.

Parameters

  • body (Primary) – Central attracting body

  • twr_lim (iterable) – Thrust/weight ratio lower and upper limits [-]

  • isp_lim (iterable) – Specific impulse lower and upper limits [s]

  • alt (float) – Orbit altitude [m]

  • t_bounds (iterable) – Time of flight lower and upper bounds expressed as fraction of tof

  • method (str) – Transcription method used to discretize the continuous time trajectory into a finite set of nodes, allowed gauss-lobatto, radau-ps and runge-kutta

  • nb_seg (int or iterable) – Number of segments in which each phase is discretized

  • order (int or iterable) – Transcription order within each phase, must be odd

  • solver (str) – NLP solver, must be supported by OpenMDAO

  • nb_samp (iterable) – Number of samples along the twr and Isp axes

  • snopt_opts (dict or None, optional) – SNOPT optional settings expressed as key-value pairs. Default is None

  • u_bound (str, optional) – Specify the bounds on the radial velocity along the transfer as lower, upper or None. Default is None

  • rec_file (str, optional) – Name of the file in latom.data.metamodels where the meta model will be stored. Default is None

save(rec_file)

Saves data corresponding to a meta model instance.

Parameters

rec_file (str) – Name of the file in latom.data.metamodels where the meta model is stored

setup()

Setup the OpenMDAO Problem object with known data for twr, Isp and m_prop.