We present Chopper, a tool that efficiently explores the vast input space of file system policies to find behaviors that lead to costly performance problems. We focus specifically on block allocation, as unexpected poor layouts can lead to high tail latencies. Our approach utilizes sophisticated statistical methodologies, based on Latin Hypercube Sampling (LHS) and sensitivity analysis, to expl...

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...

This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and ch...

Two lumped parameter watershed scale hydrology and water quality models (WATGIS and QUALGIS) which describe the nitrogen loadings at the’outlet of coastal plain watersheds were examined with respect to their accuracy and uncertainty of model results. Latin Hypercube Sampling (LHS) was applied to determine the impact of uncertainty in estimating field exports and decay coefficients on the uncert...

A novel two stage Improved Radial Basis Function (IRBF) neural network for the damage identification of a multimember structure in the frequency domain is presented. The improvement of the proposed IRBF network is carried out in two stages. Conventional RBF network is used in the first stage for preliminary damage prediction and in the second stage reduced search space moving technique is used ...

MGDA stands for Multiple-Gradient Descent Algorithm was introduced in [1]. In a previous report [2], MGDA was tested on several analytical test cases and also compared with a well-known Evolution Strategy algorithm, Pareto Archived Evolution Strategy (PAES) [3]. Using MGDA in a multi-objective optimization problem requires the evaluation of a substantial number of points with regard to criteria...

This paper proposes a novel method to select an experimental design for interpolation in random simulation. (Though the paper focuses on Kriging, this method may also apply to other types of metamodels such as linear regression models.) Assuming that simulation requires much computer time, it is important to select a design with a small number of observations (or simulation runs). The proposed ...

To accurately describe the mechanical properties of aluminium alloy sheet during deformation, an inverse identification was presented to deal with material parameters from the popular punch stretch test. In the identification procedure, the optimization strategy combines finite element method (FEM), Latin hypercube sampling (LHS), Kriging model and multi-island genetic algorithm (MIGA). The pro...

Accurate estimation of wind-driven rain (WDR) load on building facades is paramount importance for the assessment moisture-induced damage risks. The response facade depends used meteorological data, which can show significant variation over time, especially considering climate change. In this study, a statistical approach based Latin Hypercube Sampling (LHS) to generate reduced samples, accurat...