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However, uncertainties in the prediction of thermal comfort restrain architects and engineers from applying this technique.
These input uncertainties propagate through models of combustion devices leading to uncertainties in the prediction of key combustion properties.
Given the uncertainties in the prediction of future biogeography, this framework provides a clear and concise determination of ecosystems' sensitivity to climatic shifts, as well as expected patterns in the amount of precipitation that ecosystems can effectively use.
However, due to uncertainties in the prediction of thermal comfort in buildings with night-time ventilation, architects and engineers are still hesitant to apply this technique.
The uncertainties in the prediction of engineering systems are known to be originated from various non-input parameters, e.g., numerics, scaling effects, etc., as well as modeling parameters such as initial and boundary conditions, and physical models.
Therefore, PSSI parameters as well as other parameters such as uncertainties in the prediction of the wave force on jacket structure and uncertainties in structural model are utilized in sensitivity analyses.
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The foundational, or small-molecule chemistry (C0C4) only contributes significantly to uncertainties in the predictions at the highest temperatures (Tc = 900 K).
This paper presents a framework for the determination of the cluster expansion coefficients using a Bayesian approach, which allows for the quantification of uncertainties in the predictions.
Using atomization energies of solids and small molecules, we train a linear model for the exchange enhancement factor using a Bayesian approach which allows for the quantification of uncertainties in the predictions.
It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C4 alcohol/air mixtures.
Lucy, D., Robertson, I., Aykroyd, R. G. & Pollard, A. M. Estimates of uncertainty in the prediction of past climatic variables.
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