Interest in research analyzing and predicting energy loads consumption the early stages of building design using meta-models has constantly increased recent years. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. In this study, Latin Hypercube Sampling (LHS) is proposed as an alternative Fractional Factor Design (FFD), s...

In order to improve the inspection accuracy of free-form surface by CMM, this paper adopted different sampling parameters research influence measurement surface. Through combination area uniform block random and Latin hypercube sampling, minimum grid ball diameter were taken as parameters. Firstly, analysed theoretically Secondly, carrying out experiments verified analytical results. Then, two ...

Abstract Flood events are the most commonly occurring natural disaster, with over 5 million properties at risk in UK alone. Changes global climate expected to increase frequency and magnitude of flood events. hazard assessments, using projections as input, guide policy decisions engineering projects reduce impact large return period Probabilistic modeling is required take into account uncertain...

Recently there have been advances in strati ed sampling techniques that attempt to enforce equal distributions not only across the design variables, but also onto the design space itself. This requires a numerically intensive optimization routine. Until now, no optimization strategy was able to distribute sample points evenly in the design space, but Evolutionary Algorithms (EA) act as an enabl...

In this work we augment a known Monte Carlo simulationbased approach to stochastic discrete optimization problem, the so called Sample Average Approximation (SAA) method, with a new criterion to decide when the search has to be stopped. Our approach exploits a well known and effective sampling technique, Latin Hypercube Sampling (LHS), and confidence interval analysis, a well established approx...

The variance-based Sobol' approach is one of the few global sensitivity analysis methods that is suitable for complex models with spatially distributed inputs. Yet it needs a large number of model runs to compute sensitivity indices: in the case of models where some inputs are 2D Gaussian random fields, it is of great importance to generate a relatively small set of map realizations capturing m...

The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for re...