Stimuli-responsive triblock copolymer for biomedical applications

Conference (2011, April 29)

Stimuli-responsive triblock copolymer for biomedical applications

Poster (2010, May 25)

Stimulus spacing effects in temporal bisection by humans

in Quarterly Journal of Experimental Psychology (1995), 48B(4), 289-310

Stochastic analysis of a stadium roof from deterministic wind tunnel measurements

in 13th International Conference on Wind Engineering (2010)

Dynamic analyses of structures under buffeting wind loads can be performed in a deterministic (Clough and Penzien, 1997) or stochastic (Preumont, 1994) context, both with a modal approach for ... [more ▼]

Dynamic analyses of structures under buffeting wind loads can be performed in a deterministic (Clough and Penzien, 1997) or stochastic (Preumont, 1994) context, both with a modal approach for computational efficiency reasons. In the first option, the forces are deterministically given, and the uncoupled modal equations of motion are solved either in the time domain with a stepby- step method, either in the frequency domain, with Fourier transformation. In the second option, the analysis relies on the determination of the Power Spectral Density (PSD) matrix of the structural response given that of the loading. The choice of one or another method usually depends on whether the loading is provided in the time or frequency domain and as a deterministic (a single time history) or stochastic manner. From a designer’s point of view, the wind loading can be defined using design codes (e.g. Eurocode, 2005) where analytical expressions of (i) the PSD of wind velocities (Davenport, Von Karman, etc) (ii) the coherence functions and (iii) the pressure coefficients are given to compute, finally, (iv) the PSD of the aerodynamic pressures. Design engineers are usually familiar with this probabilistic approach. Alternatively, the design may be conducted from aerodynamic pressures measured in a wind tunnel. This approach is more realistic than the aforementioned codified procedure since a number of phenomena as (a) the aerodynamic instabilities, (b) aerodynamic admittance (Scanlan and Jones, 1999), (c) site effects are taken into account. Pressures are thus given as unique (deterministic) time histories at each sensor. In a Finite Element context and a modal analysis, the generalized forces are computed from the measured pressures. With the firm wish to perform the analysis in a stochastic manner (for a number of good reasons mentioned next), we suggest to fit a probabilistic model to the measured data. Such a model could be fitted to the measured pressures right away, or any other subsequent quantity such as the generalized forces. The following discussion is about the most favorable quantity that has to be fitted and how to do it appropriately in view of typical measurement imperfections. [less ▲]

Stochastic analysis of the effect of spatial variability of diffusion parameters on radionuclide transport in a low permeability clay layer

in Hydrogeology Journal (2006), 14(7), 1094-1106

Most studies that incorporate subsurface heterogeneity in groundwater flow and transport models only analyze and simulate the spatial variability of hydraulic conductivity. Heterogeneity of the other flow ... [more ▼]

Most studies that incorporate subsurface heterogeneity in groundwater flow and transport models only analyze and simulate the spatial variability of hydraulic conductivity. Heterogeneity of the other flow and transport parameters are usually neglected. This approach is often justified, but there are, however, cases in which disregarding the heterogeneity of the other flow and transport parameters can be questionable. In low permeability media, for instance, diffusion is often the dominant transport mechanism. It therefore seems logical to incorporate the spatial variability of the diffusion parameters in the transport model. This study therefore analyses and simulates the spatial variability of the effective diffusion coefficient and the diffusion accessible porosity with geostatistical techniques and incorporates their heterogeneity in the transport model of a low permeability formation. The formation studied was Boom clay (Belgium), a candidate host rock for the deep geological disposal of high-level radioactive waste. The calculated output radionuclide fluxes of this model are compared with the fluxes calculated with a homogeneous model and a model with a heterogeneous hydraulic conductivity distribution. This analysis shows that the heterogeneity of the diffusion parameters has a much larger effect on the calculated output radionuclide fluxes than the heterogeneity of hydraulic conductivity in the low permeability medium under study. [less ▲]

Stochastic analysis of the recharge uncertainty of a regional aquifer in extreme arid conditions

in Stauffer, Fr.; Dassargues, Alain (Eds.) Quantitative Geology from Multiple Sources: S10 Use of multiple sources in conditioning/calibrating groundwater flow and transport models (2006)

The Pampa del Tamarugal Aquifer (PTA) is an important source of groundwater in northern Chile. Since the study area is situated in the Atacama Desert, the estimation of groundwater recharge based on ... [more ▼]

The Pampa del Tamarugal Aquifer (PTA) is an important source of groundwater in northern Chile. Since the study area is situated in the Atacama Desert, the estimation of groundwater recharge based on conventional hydrological methods is subject to large uncertainties. To account for variations in the groundwater balance, caused by uncertainties in the average recharge rates, randomly generated recharge values with different levels of uncertainty are simulated using a groundwater flow model. Results show that evaporation and groundwater outflows are insensitive to the recharge uncertainty, while the storage terms can vary considerably. Considering current groundwater abstraction and random recharge rates, it is unlikely that the cumulative discharged volume from the aquifer, after a 45 years simulation period, will be larger than 12% of the estimated groundwater reserve. Simulated groundwater heads fluctuations due to uncertainties in the average recharge rates are more noticeable in certain areas. These fluctuations could explain anomalies in the observed groundwater heads in these areas. [less ▲]

Stochastic Dimension Reduction of Multi Physics Systems through Measure Transformation

Conference (2013, February 26)

Uncertainty quantification of multiphysics systems represents numerous mathematical and computational challenges. Indeed, uncertainties that arise in each physics in a fully coupled system must be ... [more ▼]

Uncertainty quantification of multiphysics systems represents numerous mathematical and computational challenges. Indeed, uncertainties that arise in each physics in a fully coupled system must be captured throughout the whole system, the so-called curse of dimensionality. We present techniques for mitigating the curse of dimensionality in network-coupled multiphysics systems by using the structure of the network to transform uncertainty representations as they pass between components. Examples from the simulation of nuclear power plants will be discussed. [less ▲]

Stochastic excitation of gravity modes in massive main-sequence stars

in Astrophysics & Space Science (2010), 328

We investigate the possibility that gravity modes can be stochastically excited by turbulent convection in massive main-sequence (MS) stars. We build stellar models of MS stars with masses M=10 M [SUB]ȯ ... [more ▼]

We investigate the possibility that gravity modes can be stochastically excited by turbulent convection in massive main-sequence (MS) stars. We build stellar models of MS stars with masses M=10 M [SUB]ȯ[/SUB],15 M [SUB]ȯ[/SUB], and 20 M [SUB]ȯ[/SUB]. For each model, we then compute the power supplied to the modes by turbulent eddies in the convective core (CC) and the outer convective zones (OCZ). We found that, for asymptotic gravity modes, the major part of the driving occurs within the outer iron convective zone, while the excitation of low n order modes mainly occurs within the CC. We compute the mode lifetimes and deduce the expected mode amplitudes. We finally discuss the possibility of detecting such stochastically-excited gravity modes with the CoRoT space-based mission. [less ▲]

Stochastic excitation of nonradial modes. II. Are solar asymptotic gravity modes detectable?

in Astronomy and Astrophysics (2009), 494

Context: Detection of solar gravity modes remains a major challenge to our understanding of the inner parts of the Sun. Their frequencies would enable the derivation of constraints on the core physical ... [more ▼]

Context: Detection of solar gravity modes remains a major challenge to our understanding of the inner parts of the Sun. Their frequencies would enable the derivation of constraints on the core physical properties, while their amplitudes can put severe constraints on the properties of the inner convective region. Aims: Our purpose is to determine accurate theoretical amplitudes of solar g modes and estimate the SOHO observation duration for an unambiguous detection of individual modes. We also explain differences in theoretical amplitudes derived from previous works. Methods: We investigate the stochastic excitation of modes by turbulent convection, as well as their damping. Input from a 3D global simulation of the solar convective zone is used for the kinetic turbulent energy spectrum. Damping is computed using a parametric description of the nonlocal, time-dependent, convection-pulsation interaction. We then provide a theoretical estimation of the intrinsic, as well as apparent, surface velocity. Results: Asymptotic g-mode velocity amplitudes are found to be orders of magnitude higher than previous works. Using a 3D numerical simulation from the ASH code, we attribute this to the temporal-correlation between the modes and the turbulent eddies, which is found to follow a Lorentzian law rather than a Gaussian one, as previously used. We also find that damping rates of asymptotic gravity modes are dominated by radiative losses, with a typical life time of 3 × 10[SUP]5[/SUP] years for the ell=1 mode at nu=60 muHz. The maximum velocity in the considered frequency range (10-100 muHz) is obtained for the ell=1 mode at nu=60 muHz and for the ell=2 at nu=100 muHz. Due to uncertainties in the modeling, amplitudes at maximum i.e. for ell=1 at 60 muHz can range from 3 to 6 mm s[SUP]-1[/SUP]. The upper limit is too high, as g modes would have been easily detected with SOHO, the GOLF instrument, and this sets an upper constraint mainly on the convective velocity in the Sun. [less ▲]

Stochastic Finite Element Analysis of Thermoelastic Effects in Micro-Resonators

Conference (2006, July 17)

In the design of micro-electromechanical systems (MEMS) such as micro-resonators, dissipation mechanisms may have detrimental effects on the quality factor. One of the major dissipation phenomena to ... [more ▼]

In the design of micro-electromechanical systems (MEMS) such as micro-resonators, dissipation mechanisms may have detrimental effects on the quality factor. One of the major dissipation phenomena to consider in such systems is thermoelastic damping. Hence, the performance of such MEMS is directly related to their thermoelastic quality factor which has to be predicted accurately. Moreover, the performance of MEMS can vary because manufacturing processes may leave substantial uncertainty in the geometry and in the material properties of the device. The reliability of MEMS devices is affected by the inability to accurately predict the stochastic behavior of the system due to the presence of these uncertainties. The aim of this paper is to provide a framework to account for uncertainties in the finite element analysis of the thermoelastic quality factor. The present work focuses on second moment approaches, in which the first two statistical moments, i.e. the mean and the variance, are estimated. The perturbation stochastic finite element method is used in order to determine the mean and the variance of the thermoelastic quality factor of MEMS. The perturbation SFEM [1] consists in a deterministic analysis complemented by a sensitivity analysis with respect to the random parameters. This enables the development of a Taylor series expansion of the response, from which the mean and variance of the response can be derived knowing the mean and variance of the random parameters. The perturbation SFEM is applied on the analysis of the thermoelastic quality factor of a micro-beam whose elastic modulus is considered as a random variable. Due to the nature of the thermoelastic problem, this study involves the calculation of eigenvalue sensitivities of a non-symmetric damped system [2]. The mean and variance of the quality factor are compared to the results obtained by Monte-Carlo simulations. References: [1] Kleiber, M., Hien, T.D., The stochastic finite element method: basic perturbation technique and computer implementation. Wiley & Sons, Chichester, 1992. [2] Choi, K.M., Jo, H.K., Kim, W.H., Lee, I.W., Sensitivity analysis of non-conservative eigensystems, Journal of Sound and Vibration, v. 274, p. 997-1011, 2004. [less ▲]