The　quantification　of　the　uncertainty　effect　of　random　system　parameters,　such　as　the　loading　conditions,　material　and　geometric　properties,　on　the　system　output　response　has　gained　significant　attention　in　recent　years.　One　of　the　well-known　methods　is　the　first　order　second-moment　(FOSM)　method,　which　can　be　used　to　determine　the　mean　value　and　variance　of　the　system　output.　However,　this　method　needs　to　derive　the　formulas　for　calculating　the　local　sensitivity　and　it　can　only　be　used　for　systems　with　low-level　uncertainties.　Polynomial　Chaos　(PC)　expansion　is　a　new　non-sampling-based　method　to　evaluate　the　uncertainty　evolution　and　quantification　of　a　dynamical　system.　In　this　paper,　PC　expansion　is　used　to　represent　the　stochastic　system　output　responses　of　civil　bridge　structures,　which　could　be　the　natural　frequencies,　linear　and　nonlinear　dynamic　responses.　The　PC　coefficients　are　obtained　from　the　non-intrusive　regression　based　method,　and　the　statistical　characteristic　can　be　evaluated　from　these　coefficients.　The　results　from　the　proposed　approach　are　compared　with　those　calculated　with　commonly　used　methods,　such　as　Monte　Carlo　Simulation　(MCS)　and　FOSM.　The　accuracy　and　efficiency　of　the　presented　PC　based　method　for　uncertainty　quantification　and　global　sensitivity　analysis　are　investigated.　Global　sensitivity　analysis　is　performed　to　quantify　the　effect　of　uncertainty　in　each　random　system　parameter　on　the　variance　of　the　stochastic　system　output　response,　which　can　be　obtained　directly　from　the　PC　coefficients.　The　results　demonstrate　that　PC　expansion　can　be　a　powerful　and　efficient　tool　for　uncertainty　quantification　and　sensitivity　analysis　in　linear　and　nonlinear　structure　analysis.　(C)　2018　Elsevier　Ltd.　All　rights　reserved.