@Article{ReisJúniorAmbrSousSilv:2021:SpReTh,
               author = "Reis J{\'u}nior, Jos{\'e} Daniel and Ambr{\'o}sio, Ana Maria 
                         and Sousa, Fabiano Luis de and Silva, Douglas Felipe da",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Spacecraft real-time thermal simulation using artificial neural 
                         networks",
              journal = "Journal of the Brazilian Society of Mechanical Sciences and 
                         Engineering",
                 year = "2021",
               volume = "43",
               number = "4",
                pages = "e198",
                month = "Apr.",
             keywords = "Real-time simulation · Artifcial neural networks · Machine 
                         learning · Thermal control · Space engineering.",
             abstract = "Spacecraft Operational Simulators are mainly used for training 
                         satellite operators, to test the ground control system, and the 
                         evaluation of operational and onboard procedures before their 
                         execution in the real satellite. To achieve these objectives, all 
                         the internal models of the Operational Simulator must provide 
                         information in real time. Traditionally, the thermal simulation in 
                         these simulators is accomplished through interpolation on a set of 
                         pre-calculated scenarios or by the integration of a very 
                         simplified mathematical model. Both approaches, however, have 
                         limitations in both fidelity and runtime. In order to overcome 
                         these limitations, in this work it is proposed to build the 
                         thermal model of a Spacecraft Operational Simulator using 
                         artificial neural networks. This approach was applied to the 
                         Amazonia-1, a medium size satellite currently being developed at 
                         the Brazilian National Institute for Space Research. The obtained 
                         results show increased fidelity and an extremely short execution 
                         time, evidencing the potential of the approach to simulate 
                         satellite thermal behavior in Operational Simulators.",
                  doi = "10.1007/s40430-021-02908-7",
                  url = "http://dx.doi.org/10.1007/s40430-021-02908-7",
                 issn = "1678-5878",
             language = "en",
           targetfile = "reis junior_spacecraft.pdf",
        urlaccessdate = "09 maio 2024"
}