Efficient inner-outer decoupling scheme for non-probabilistic model updating with high dimensional model representation and Chebyshev approximation

•Interval model updating is split into two layers of inner uncertainty propagation and outer interval optimization.•An efficient inner-outer-layer decoupling scheme is proposed for interval model updating.•HDMR is utilized to decompose model outputs into multiple univariate functions in the inner uncertainty propagation.•Stationary points of each decomposed univariate function are efficiently derived based on Chebyshev polynomials.•A new scheme based on stationary points is proposed to accelerate tracking the bounds in the outer interval optimization.