A　vast　city　usually　encompasses　hundreds　of　thousands　or　even　millions　of　buildings,　majority　of　which　are　regular　buildings　with　typical　structural　configurations.　In　the　seismic　damage　simulation　of　cities,　efficient　and　reliable　simplified　models　are　required　to　represent　these　buildings.　A　numerical　model　database　of　typical　regular　reinforced　concrete　(RC)　frame　structures　was　developed,　utilizing　shear　models　to　simulate　these　RC　frame　structures.　In　contrast　to　existing　shear　models　that　are　automatically　generated　based　solely　on　the　fundamental　rules　regulated　by　the　theories　of　structures　and　the　design　codes,　the　shear　models　in　this　study　were　calibrated　using　refined　numerical　models　to　guarantee　precise　depiction　of　RC　frame　structures.　The　effects　of　reinforcement　corrosion　and　the　year　of　construction　on　structural　performance　were　also　considered.　First,　108　RC　frame　structures　were　designed　with　typical　configurations,　strictly　adhering　to　the　regulations　of　design　codes.　Second,　the　refined　models　of　the　RC　frame　structures　were　established　with　modified　material　parameters　to　account　for　reinforcement　corrosion,　resulting　in　540　refined　models.　Afterward,　the　parameters　of　each　shear　model　were　calibrated　through　cyclic　pushover　analysis　of　the　corresponding　refined　numerical　model.　Finally,　the　characteristic　points　of　the　shear　models　were　further　modified　to　consider　the　different　redundant　capacities　of　the　structures　constructed　in　three　time　phases　due　to　the　update　of　design　codes,　by　which　a　simplified　numerical　model　database　containing　1620　shear　models　was　developed.　The　models＇　accuracy　in　predicting　fundamental　periods　and　seismic　damage　states　was　verified　by　comparing　them　to　the　refined　models　and　three　real　RC　frame　buildings.　The　effects　of　the　reinforcement　corrosion　and　year　of　construction　on　the　seismic　damage　states　of　the　RC　frame　structures　were　also　discussed.　The　developed　numerical　model　database　can　be　utilized　for　the　seismic　damage　assessment　of　RC　frame　structures　in　urban　building　clusters.　©　2024　Elsevier　Ltd