Ihab Sraj

Global sensitivity analysis in an ocean general circulation model: a sparse spectral projection approach

Polynomial chaos (PC) expansions are used to propagate parametric uncertainties in ocean global circulation model. The computations focus on short-time, high-resolution simulations of the Gulf of Mexico, using the hybrid coordinate ocean model, with wind stresses corresponding to hurricane Ivan. A sparse quadrature approach is used to determine the PC coefficients which provides a detailed representation of the stochastic model response. The quality of the PC representation is first examined through a systematic refinement of the number of resolution levels. The PC representation of the stochastic model response is then utilized to compute distributions of quantities of interest (QoIs) and to analyze the local and global sensitivity of these QoIs to uncertain parameters. Conclusions are finally drawn regarding limitations of local perturbations and variance-based assessment and concerning potential application of the present methodology to inverse problems and to uncertainty management.

Cell deformation cytometry using diode-bar optical stretchers

The measurement of cell elastic parameters using optical forces has great potential as a reagent-free method for cell classification, identification of phenotype, and detection of disease; however, the low throughput associated with the sequential isolation and probing of individual cells has significantly limited its utility and application. We demonstrate a single-beam, high-throughput method where optical forces are applied anisotropically to stretch swollen erythrocytes in microfluidic flow. We also present numerical simulations of model spherical elastic cells subjected to optical forces and show that dual, opposing optical traps are not required and that even a single linear trap can induce cell stretching, greatly simplifying experimental implementation. Last, we demonstrate how the elastic modulus of the cell can be determined from experimental measurements of the equilibrium deformation. This new optical approach has the potential to be readily integrated with other cytometric technologies and, with the capability of measuring cell populations, enabling true mechanical-property-based cell cytometry.

A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database

This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting.

Bayesian Inference of Drag Parameters Using AXBT Data from Typhoon Fanapi

AbstractThe authors introduce a three-parameter characterization of the wind speed dependence of the drag coefficient and apply a Bayesian formalism to infer values for these parameters from airborne expendable bathythermograph (AXBT) temperature data obtained during Typhoon Fanapi. One parameter is a multiplicative factor that amplifies or attenuates the drag coefficient for all wind speeds, the second is the maximum wind speed at which drag coefficient saturation occurs, and the third is the drag coefficients rate of change with increasing wind speed after saturation. Bayesian inference provides optimal estimates of the parameters as well as a non-Gaussian probability distribution characterizing the uncertainty of these estimates. The efficiency of this approach stems from the use of adaptive polynomial expansions to build an inexpensive surrogate for the high-resolution numerical model that couples simulated winds to the oceanic temperature data, dramatically reducing the computational burden of the M...

Drag Parameter Estimation Using Gradients and Hessian from a Polynomial Chaos Model Surrogate

A variational inverse problem is solved using polynomial chaos expansions to infer several critical variables in the Hybrid Coordinate Ocean Model’s (HYCOM’s) wind drag parameterization. This alternative to the Bayesian inference approach in Sraj et al. avoids the complications of constructing the full posterior with Markov chain Monte Carlo sampling. It focuses instead on identifying the center and spread of the posterior distribution. The present approach leverages the polynomial chaos series to estimate, at very little extra cost, the gradients and Hessian of the cost function during minimization. The Hessian’s inverse yields an estimate of the uncertainty in the solution when the latter’s probability density is approximately Gaussian. The main computational burden is an ensemble of realizations to build the polynomial chaos expansion; no adjoint code or additional forward model runs are needed once the series is available. The ensuing optimal parameters are compared to those obtained in Sraj et al. where the full posterior distribution was constructed. The similarities and differences between the new methodology and a traditional adjoint-based calculation are discussed.

Dynamic ray tracing for modeling optical cell manipulation

Current methods for predicting stress distribution on a cell surface due to optical trapping forces are based on a traditional ray optics scheme for fixed geometries. Cells are typically modeled as solid spheres as this facilitates optical force calculation. Under such applied forces however, real and non-rigid cells can deform, so assumptions inherent in traditional ray optics methods begin to break down. In this work, we implement a dynamic ray tracing technique to calculate the stress distribution on a deformable cell induced by optical trapping. Here, cells are modeled as three-dimensional elastic capsules with a discretized surface with associated hydrodynamic forces calculated using the Immersed Boundary Method. We use this approach to simulate the transient deformation of spherical, ellipsoidal and biconcave capsules due to external optical forces induced by a single diode bar optical trap for a range of optical powers.

Numerical simulation of shock initiation of Ni/Al multilayered composites

The initiation of chemical reaction in cold-rolled Ni/Al multilayered composites by shock compression is investigated numerically. A simplified approach is adopted that exploits the disparity between the reaction and shock loading timescales. The impact of shock compression is modeled using CTH simulations that yield pressure, strain, and temperature distributions within the composites due to the shock propagation. The resulting temperature distribution is then used as initial condition to simulate the evolution of the subsequent shock-induced mixing and chemical reaction. To this end, a reduced reaction model is used that expresses the local atomic mixing and heat release rates in terms of an evolution equation for a dimensionless time scale reflecting the age of the mixed layer. The computations are used to assess the effect of bilayer thickness on the reaction, as well as the impact of shock velocity and orientation with respect to the layering. Computed results indicate that initiation and evolution o...

Multi-scale simulation of L-selectin–PSGL-1-dependent homotypic leukocyte binding and rupture

L-selectin–PSGL-1-mediated polymorphonuclear (PMN) leukocyte homotypic interactions potentiate the extent of PMN recruitment to endothelial sites of inflammation. Cell–cell adhesion is a complex phenomenon involving the interplay of bond kinetics and hydrodynamics. As a first step, a 3-D computational model based on the Immersed Boundary Method is developed to simulate adhesion-detachment of two PMN cells in quiescent conditions. Our simulations predict that the total number of bonds formed is dictated by the number of available receptors (PSGL-1) when ligands (L-selectin) are in excess, while the excess amount of ligands influences the rate of bond formation. Increasing equilibrium bond length results in a higher number of receptor–ligand bonds due to an increased intercellular contact area. On-rate constants determine the rate of bond formation, while off-rates control the average number of bonds by modulating bond lifetimes. Application of an external pulling force leads to time-dependent on- and off-rates and causes bond rupture. Moreover, the time required for bond rupture in response to an external force is inversely proportional to the applied load and decreases with increasing off-rate.

Self-propagating reactive fronts in compacts of multilayered particles

Reactive multilayered foils in the form of thin films have gained interest in various applications such as joining, welding, and ignition. Typically, thin film multilayers support self-propagating reaction fronts with speeds ranging from 1 to 20m/s. In some applications, however, reaction fronts with much smaller velocities are required. This recently motivated Fritz et al. (2011) to fabricate compacts of regular sized/shaped multilayered particles and demonstrate self-sustained reaction fronts having much smaller velocities than thin films with similar layering. In this work, we develop a simplified numerical model to simulate the selfpropagation of reactive fronts in an idealized compact, comprising identical Ni/Al multilayered particles in thermal contact. The evolution of the reaction in the compact is simulated using a two-dimensional transient model, based on a reduced description of mixing, heat release, and thermal transport. Computed results reveal that an advancing reaction front can be substantially delayed as it crosses from one particle to a neighboring particle, which results in a reduced mean propagation velocity. A quantitative analysis is thus conducted on the dependence of these phenomena on the contact area between the particles, the thermal contact resistance, and the arrangement of the multilayered particles.

Linear diode laser bar optical stretchers for cell deformation.

To investigate the use of linear diode laser bars to optically stretch cells and measure their mechanical properties, we present numerical simulations using the immersed boundary method (IBM) coupled with classic ray optics. Cells are considered as three-dimensional (3D) spherical elastic capsules immersed in a fluid subjected to both optical and hydrodynamic forces in a periodic domain. We simulate cell deformation induced by both single and dual diode laser bar configurations and show that a single diode laser bar induces significant stretching but also induces cell translation of speed < 10 µm/sec for applied 6.6 mW/µm power in unconfined systems. The dual diode laser bar configuration, however, can be used to both stretch and optically trap cells at a fixed position. The net cell deformation was found to be a function of the total laser power and not the power distribution between single or dual diode laser bar configurations.