Global error estimation in CFD mesh coarsening process for uncertainty quantification methods

Due to high performance of modern computers, Uncertainty Quantification is becoming an important part of engineering design. Every non intrusive Uncertainty Quantification method requires a considerable number of evaluations of the model, meaning that the design process is more expensive in terms of computational resources/time. In Computational Fluid Dynamics, the usual practice is to reduce the computational time by reducing the number of nodes of the used mesh. Each coarsening of the mesh leads to the increase of the error measured as the difference between the real solution and the solution provided by the computational model. In this work, an approach for quantification of the global error around the stochastic domain, in a mesh reduction process, is described and results obtained for a test case are detailed. The method is based on a comparison of the high accurate mesh against coarse mesh with lower accuracy, but less expensive in terms of computational time. The global error is defined as a volume difference between surrogate models created in the stochastic domain. The stochastic domain is given by pre-specified input variables with appropriate boundaries. Surrogate models are used and a non intrusive polynomial chaos model is created with response samples from high and low accuracy mesh. For the chosen test case, the input variables, related to the stochastic space, were the free stream pressure and free stream Mach number. A hypersonic flow solver developed at the von Karman Institute, Cosmic, was used to compute properties of a flow around the reentry spacecraft. A computational expensive mesh was used as a reference mesh. Due to computational resources, it was impossible to use expansive mesh for Monte Carlo simulation or high order Polynomial Chaos. Therefore, the global error estimation approach was applied to find an accurate and relatively inexpensive mesh for Uncertainty Quantification in hypersonic simulation. Multiple meshes with different coarsening were tested, based on expert knowledge of the problem. The global error estimation method allowed for finding a final mesh, with an error on the mean value 0.48% and on the standard deviation 5.89%, which was 4 times faster than the reference mesh

Comparison of non-intrusive approaches to uncertainty propagation in orbital mechanics

The paper presents four different non-intrusive approaches to the propagation of uncertainty in orbital dynamics with particular application to space debris orbit analysis. Intrusive approaches are generally understood as those methods that require a modification of the original problem by introducing a new algebra or by directly embedding high-order polynomial expansions of the uncertain quantities in the governing equations. Non-intrusive approaches are instead based on a polynomial representations built on sparse samples of the system response to the uncertain quantities. The paper will present a standard Polynomial Chaos Expansion, an Uncertain Quantification-High Dimensional Model Representation, a Generalised Kriging model and an expansion with Tchebycheff polynomials on sparse grids. The work will assess the computational cost and the suitability of these methods to propagate different type of orbits

A novel model for uncertainty propagation analysis applied for human thermal comfort evaluation

The comfort sensation is mainly affected by six variables: air temperature, mean radiant temperature, air velocity, relative humidity, personal metabolism and clothing insulation. These are characterized by different mean values and distributions. To analyze the uncertainty propagation three numerical models are used: the Fully Monte Carlo Simulation MCSs, the Monte Carlo Simulation Trials MCSt, and a novel model named "Adaptive Derivative based High Dimensional Model Representation" (AD-HDMR). In the paper these three different methods are applied to the thermal comfort evaluation, through the PMV Index, they are analyzed and their efficiency was verified in terms of computational time. To allow a revision of this index, the effect of the different variables was then analyzed

Aero-thermal re-entry sensitivity analysis using DSMC and a high dimensional model representation-based approach

This paper presents a sensitivity analysis for the hypersonic aero-thermal convective heat transfer from the free molecular to the slip-flow regime for cylindrical and cubic geometries. The analyses focus on a surface-averaged heat transfer coefficient at various atmospheric conditions. The sensitivity analyses have been performed by coupling a High Dimensional Model Representation based approach and a Direct Simulation Monte Carlo code. The geometries have been tested with respect to different inputs parameters; altitude, attitude, wall temperature and geometric characteristics. After the initial sensitivity analyses, the N-dimensional surrogate models of the surface-averaged heat transfer coefficient have been defined and tested. Hereby, a shape-based DSMC mesh refinement correction factor for reducing the overall analyses computational times is also presented

Prediction model of alcohol intoxication from facial temperature dynamics based on K-means clustering driven by evolutionary computing

Alcohol intoxication is a significant phenomenon, affecting many social areas, including work procedures or car driving. Alcohol causes certain side effects including changing the facial thermal distribution, which may enable the contactless identification and classification of alcohol-intoxicated people. We adopted a multiregional segmentation procedure to identify and classify symmetrical facial features, which reliably reflects the facial-temperature variations while subjects are drinking alcohol. Such a model can objectively track alcohol intoxication in the form of a facial temperature map. In our paper, we propose the segmentation model based on the clustering algorithm, which is driven by the modified version of the Artificial Bee Colony (ABC) evolutionary optimization with the goal of facial temperature features extraction from the IR (infrared radiation) images. This model allows for a definition of symmetric clusters, identifying facial temperature structures corresponding with intoxication. The ABC algorithm serves as an optimization process for an optimal cluster's distribution to the clustering method the best approximate individual areas linked with gradual alcohol intoxication. In our analysis, we analyzed a set of twenty volunteers, who had IR images taken to reflect the process of alcohol intoxication. The proposed method was represented by multiregional segmentation, allowing for classification of the individual spatial temperature areas into segmentation classes. The proposed method, besides single IR image modelling, allows for dynamical tracking of the alcohol-temperature features within a process of intoxication, from the sober state up to the maximum observed intoxication level.Web of Science118art. no. 99

Debris re-entry modeling using high dimensional derivative based uncertainty quantification

Well-known tools developed for satellite and debris re-entry perform break-up and trajectory simulations in a deterministic sense and do not perform any uncertainty treatment. In this paper, we present work towards implementing uncertainty treatment into a Free Open Source Tool for Re-entry of Asteroids and Space Debris (FOSTRAD). The uncertainty treatment in this work is limited to aerodynamic trajectory simulation. Results for the effect of uncertain parameters on trajectory simulation of a simple spherical object is presented. The work uses a novel uncertainty quantification approach based on a new derivation of the high dimensional model representation method. Both aleatoric and epistemic uncertainties are considered in this work. Uncertain atmospheric parameters considered include density, temperature, composition, and free-stream air heat capacity. Uncertain model parameters considered include object flight path angle, object speed, object mass, and direction angle. Drag is the only aerodynamic force considered in the planar re-entry problem. Results indicate that for initial conditions corresponding to re-entry from a circular orbit, the probabilistic distributions for the impact location are far from the typically used Gaussian or ellipsoids and the high probability impact location along the longitudinal direction can be spread over ∼2000 km, while the overall distribution can be spread over ∼4000 km. High probability impact location along the lateral direction can be spread over ∼400 km

Surrogate model for probabilistic modeling of atmospheric entry for small NEO's

Near Earth Objects (NEOs) enter the Earths atmosphere on a regular basis. Depending on the size, object and entry parameters; these objects can burn-up through ablation (complete evaporation), undergo fragmentation of varying nature, or impact the ground unperturbed. Parameters that influence the physics during entry are either unknown or highly uncertain. In this work, we propose a probabilistic approach for simulating entry. Probabilistic modeling typically requires an expensive Monte Carlo approach. In this work, we develop and present a novel engineering approach of developing surrogate models for simulation of the atmospheric entry accounting for drag, ablation, evaporation, fragmentation, and ground impact

Sources of Sex Information Used by Young British Women Who Have Sex with Women (WSW) and Women Who Have Sex Exclusively with Men (WSEM): Evidence from the National Survey of Sexual Attitudes and Lifestyles

There is little consideration about the provision of information about sex to women who have sex with women (WSW). This study drew on data from the third National Survey of Sexual Attitudes and Lifestyle, a nationally representative survey of people in Great Britain. Logistic regression was undertaken to examine firstly the relationships between WSW and women who have sex exclusively with men (WSEM) and their main source of information about sex, and secondly between WSW/WSEM and unmet need for information about sex. Each source was included as the binary outcome indicating yes this was the main source, or no this was not the main source of information about sex. The results found that WSW had significantly lower odds of reporting lessons at schools as their main source of information, and significantly higher odds of reporting sources defined as ‘other’ (predominantly first girlfriend/boyfriend or sexual partner) as their main source of information. Reported levels of unmet need for information was also higher amongst young WSW compared with WSEM. This study provides new insights into the sex educational needs of young women and highlights the need for sex education in schools in Great Britain to include information on a full-range of sexual practices, including same-sex sexual relationships

Thermal analysis of a BIPV system by various modelling approaches

This work presents various models developed and implemented within the SOPHIA European project in order to thermally characterize PV modules in a rooftop BIPV configuration. Different approaches have been considered, including a linear model, lumped elements models and models that make use of commercial software solvers. The validation of the models performed by comparing the results of simulations with experimental data recorded on a test bench over an entire year is presented and discussed on a seasonal basis. The results have shown that all the models implemented allow achieving a good prediction of the PV modules back surface temperature, with the minimum value of the coefficient of determination R2 around 95% on a yearly basis. Moreover, the influence of season weather conditions and of the incident solar irradiance magnitude on the accuracy of the considered thermal models is highlighted. The major result of the present study is represented by the fact that it has been possible to perform a better thermal characterization of the BIPV module by tuning some of the heat transfer coefficients, such as those relative to the effects of the wind velocity, and to the evaluation of sky temperature.The experimental data used for the thermal simulation of BIPV system behavior were obtained in the framework of the project Performance BIPV supported by the French research agency (ANR), within the research program ANR HABISOL. Authors would like to thank the European Community that supported the SOPHIA project with the funding of FP7-SOPHIA grant agreement no. 262533

OPTICAL NERVE SEGMENTATION USING THE ACTIVE SHAPE METHOD

The paper deals with the segmentation procedure for optical nerve localization and the consequent determination of geometrical parameters such as optical nerve area, radius and diameter. An extraction of these geometrical parameters is especially important for clinical practice particularly in the case where retinal lesions are present. On the base of the optical nerve extraction, we are capable of comparing it with area of retinal lesions. Via this approach it is possible to track time evaluation of retinal lesions. The proposed algorithm for segmentation of optical nerve area is performed within two main steps. In the first step, the active contour method is used specially for the localization of the optical nerve. This part of the algorithm generates mathematical model of the optical nerve in binary form. Consequently, on the base of this mathematical model of the optical nerve respective geometrical parameters are worked out for future comparison with retinal lesions. Image preprocessing is an integral part of the segmentation procedure, improving the observability of the optical nerve to ensure as relevant detection of the optical nerve as possible