A general framework for probabilistic fatigue damage prognosis using maximum entropy concept is proposed in this paper. The fatigue damage is calculated using a physics-based crack growth model. Due to the stochastic nature of crack growth process, uncertainties arising from the underlying physical model, parameters of the model, and the measurement noise are considered and integrated into this...

A Bayesian updating model is developed to capture the mechanism by which travelers update their travel time perceptions from one day to the next in light of information provided by Advanced Traveler Information Systems (ATIS) and their previous experience. The availability and perceived quality of trac information are explicitly modeled within the proposed framework. The uncertainty associated...

performance evaluation of electricity distribution units is an important issue between researchers and regulators. classic data envelopment analysis models with deterministic data have been used by many authors to measure efficiency of power distribution units in different countries. however, data envelopment analysis with stochastic data are rarely used to measure efficiency of distribution co...

Uncertainty induced by our incomplete state of knowledge about engineering systems and their surrounding environment give rise to challenging problems in the process of building predictive models for the system behavior. One such challenge is the model selection problem, which arises due to the existence of invariably multiple candidate models with different mathematical forms to represent the ...

Abstract The Bhattacharyya distance has been developed as a comprehensive uncertainty quantification metric by capturing multiple sources from both numerical predictions and experimental measurements. This work pursues further investigation of the performance in different methodologies for stochastic model updating, thus to prove universality various currently popular updating procedures. first...

We investigate simulations for gauge theories on a Minkowskian space-time lattice. We employ stochastic quantization with optimized updating using stochastic reweighting or gauge fixing, respectively. These procedures do not affect the underlying theory but strongly improve the stability properties of the stochastic dynamics, such that simulations on larger real-time lattices can be performed. ...

the hub location decision is a long term investment and any changes in it take considerable time and money. in real situations, some parameters are uncertain hence, deterministic models cannot be more efficient. the ability of two-stage stochastic programming is to make a long-term decision by considering effects of it in short term decisions simultaneously. in the two-stage stochastic programm...