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• MULTIPHYSICS SIMULATION IN ANSYS CFX AND SYSTEM COUPLING OF HEAT TRANSFER INSIDE HERMRTIC CASE OF STRAPDOWN INERTIAL NAVIGATION SYSTEM

  А.А. Medeltsev, P. А. Shapovalov, М. V. Voronov, А. I. Polukhina, P.N. Sigaleva, А.V. Frolov

  2022-04-21

  Abstract ▼

  The article presents a numerical simulation of non-stationary convective-conductive heat
  transfer of the strapdown inertial navigation system (SINS), developed in the JSC «CNIIAG».
  The numerical simulation is carried out in the ANSYS Mechanical. The aim of the study is a comprehensive
  analysis of heat exchange processes, which are characteristic to the device operation,
  including mutual spatial influence of thermal powers on each other, as well as on the block of
  sensitive elements. The simulation of heat transfer inside the hermetic case of the SINS is carried out for critical operating conditions in a strongly and weakly coupled consideration with a comparison
  of both approaches. ANSYS Mechanical, CFX and System Coupling simulation modules
  are chosen for program implementation of each approach. The k-e model of air turbulence with
  implicit consideration of the effect in the boundary layers and diffusion correction in shear flows is
  chosen for this approach. External heat exchange with ambient air is considered by setting convective
  boundary conditions on the external surfaces of the SINS, considering their orientation.
  To obtain numerical values of the heat transfer coefficients, the orientation of each surface in
  space is taken into account by using the appropriate coefficient. The presence of irregularities on
  the surfaces of the SINS in the contacts between solid components is considered by using the calculation
  of thermal resistances of the actual contact and intercontact layer. The simulation results
  of deformed state of SINS structural system, resulting from the action of a non-symmetric thermal
  field, is presented. The analysis of the obtained graphs is carried out. Stiffness indicators of the
  SINS structural system is defined as angles of deviation of sensitivity axes caused by thermal deformations.
  The obtained results make it possible to evaluate the engineering solutions for the
  quality of heat removal from the elements of the PCBs, bypassing the sensitive elements of the
  device, adopted at the stage of product layout.

• HARDWARE AND SOFTWARE MEANS FOR DYNAMIC RECONFIGURATION OF A GROUP OF SMALL SPACE VEHICLES

  S.N. Emelyanov, S.N. Frolov, Е.А. Titenko, D.P. Teterin, А.P. Loktionov

  2024-08-12

  Abstract ▼

  The goal of the study is to automate the control of a group of nanosatellites in conditions of its
  variable number by updating its state based on sending and processing broadcast requests between
  nanosatellites and using the Transformer neural network. A neural network is needed to make predi ctions
  about the state of the spacecraft network. The problem of ensuring connectivity of a network of
  nanosatellites is studied, which comes down to the implementation of adaptive network control with
  assessment and prediction of the state of communication channels between pairs of devices based on a
  neural network. Dynamic reconfiguration and machine learning of a network of devices have been developed.
  Algorithmic tools have been defined for the initial training of a neural network and its subs equent
  additional training, taking into account the preprocessing of the original sparse or fully connected
  data sets about the network of devices. Upon completion of training on synthetic data, the created
  neural network is able to predict the quality of communication, taking into account line of sight, signal
  attenuation depending on distance and the state of the nanosatellite hardware platform. The developed
  software system performs deterministic reconfiguration based on the current state of the nanosatellite
  network and adaptive reconfiguration based on historical data by analyzing the hidden patterns of
  nanosatellite functioning using the Transformer neural network. To predict the quality of communication,
  a functional is used to connect the geodetic coordinates of pairs of satellites and the vectors of
  their states with the elements of the matrix of the quality of communication between nanosatellites with
  a given initial time, the value of the time interval, and the value of the sampling step of the measurement
  process. The use of neural networks implemented on GPUs made it possible to predict possible
  states of nanosatellites and carry out reconfiguration of the constellation ahead of schedule, including
  removing “problematic” nanosatellites from the network.

• METHODOLOGICAL BASES AND PRACTICAL ASPECTS OF OPTIMIZATION TASKS OF THE BEARING STRUCTURES OF THE STRAPDOWN INERTIAL NAVIGATION SYSTEMS

  P.А. Shapovalov, Y.V. Mikhaylov, А.V. Frolov, D.O. Savvateev

  2023-04-10

  Abstract ▼

  This article describes approaches to solving problems of optimization of bearing structure
  of strapdown inertial navigation systems (SINS). A typical optimization problem in this case is
  multiobjective parametric optimization of the bearing structure of the SINS accelerometer triad in
  order to minimize the mass of the bearing structure and minimize deviation angles of the accelerometer
  axes under the action of external loads. The ANSYS Mechanical and ANSYS
  DesignXplorer modules are used as a tool for numerical modeling and optimization, respectively.
  Practical issues related to parameterization of SINS bearing structure 3D-models, calculation of
  accelerometer axes deviation angles, possible variants of numerical experiment plans, estimation
  of response sensitivity to input parameters, generation and refinement of the response surface, and
  multiobjective optimization are considered. For the rational parametrization of geometry, the
  SINS device assembly was decomposed, as a result of which the parts and structural elements that have the greatest influence on the considered objective functions were identified. To calculate the
  deviation angles of the sensitive elements axes, special two-node finite elements and relations for
  the Bryant angles were used, which describe the relative position in space of two coordinate systems.
  When planning a numerical experiment, at the first stage of optimization, a central composition
  plan was used, and at subsequent stages, the parameter space was filled using the Latin hypercube
  method with the option of relations between parameters, which made it possible to avoid
  degenerate design options. The response surface was built using the genetic aggregation method
  and subsequently refined based on a set of optimal solutions. Optimization for conflicting goals of
  mass minimization and stiffness maximization was carried out using a multiobjective genetic algorithm.
  The described set of approaches to solving optimization problems as a result of an exemplary
  series of calculations made it possible to reduce the mass of a serial SINS bearing structure
  part by 23% with fixed stiffness.