With margins and their uncertainties, QMU (Quantification of Margin and Uncertainty) method can be used to make decisions on whether performances of a product reach demands or not. Recur to new methods of UQ (Uncertainty Quantification) for M&S (Modeling & Simulation), QMU is actualized with input information directly from M&S and its uncertainties. With reliability assessment for a stockpiled product, main ideas and executing details of QMU decision are demonstrated.

Propagation analysis often overrate uncertainty of numerical simulation, especially as many uncertain inputs exist. Taking advantage of the reality that calibration can reduce epistemic uncertainty of system-level numerical simulation, a method for uncertainty quantification is offered synthetically using comparison information based on available test data and additional propagation information of modeling and simulation. An example with virtual test is displayed in which the method is demonstrated and validated.

According to the principles of Modeling & Simulation(M&S)and charactersitic of detonation system that final performances are determined by initial conditions,total uncertainties are sorted to three parts that varying along with initial conditions.It reveals how uncertainties are brought on and evolve from benchmark models to new models.Based on engineering practices and technology of verification & validation,a framework of quantification about uncertainty is brought forward in detonation simulation.An example is presented to demonstrate general idea in quantifying uncertainty of M&S.

Kernel functions approximate physical quantities in smoothed particle hydrodynamics (SPH) method.However,approximation accuracy decreases near boundaries.By reconstruction of a kernel with correcting function,reproducing kernel particle method (RKPM) improves approximation accuracy and computational stability at internal or boundary points.Though correction is proposed to approximate functions accurately,it also benefits in approximation of derivatives.