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Predictive models implemented in medical procedures can potentially bring great benefit to patients and represent a step forward in targeted treatments based on a patient’s physiological condition. It is the purpose of this paper to outline such a model.

A multi-scale 0D-3D model based on patient specific geometry combines a 0-dimensional lumped parameter model (LPM) with a 3D computational fluid dynamics (CFD) analysis coupled in time, to obtain physiologically viable flow parameters.

A comparison of physiological data gathered from literature with flow-field measurements in this model shows the viability of this method in relation to potential predictions of pathological flows repercussions and candidate treatments.

A limitation of the model is the absence of compliance in the walls in the CFD fluid domain; however, compliance of the peripheral vasculature is accounted for by the LPM. Currently, an attempt is in progress to extend this multi-scale model to account for the fluid-structure interaction of the ventricular assist device vasculature and hemodynamics.

This work reports on a predictive pulsatile flow model that can be used to investigate surgical alternatives to reduce strokes in LVADs.

Wind loading calculations are currently performed according to the ASCE 7 standard. Values in this standard were estimated from simplified models that do not necessarily take into account relevant flow characteristics. Thus, the standard does not have provisions to handle the majority of rooftop photovoltaic (PV) systems. Accurate solutions for this problem can be produced using a full-fledged three-dimensional computational fluid dynamics (CFD) analysis. Unfortunately, CFD requires enormous computation times, and its use would be unsuitable for this application which requires real-time solutions. To this end, a real-time response framework based on the proper orthogonal decomposition (POD) method is proposed.

A real-time response framework based on the POD method was used. This framework used beforehand and off-line CFD solutions from an extensive data set developed using a predefined design space. Solutions were organized to form the basis snapshots of a POD matrix. The interpolation network using a radial-basis function (RBF) was used to predict the solution from the POD method given a set of values of the design variables. The results presented assume varying design variables for wind speed and direction on typical PV roof installations.

The trained POD–RBF interpolation network was tested and validated by performing the fast-algebraic interpolation to obtain the pressure distribution on the PV system surface and they were compared to actual grid-converged fully turbulent 3D CFD solutions at the specified values of the design variables. The POD network was validated and proved that large-scale CFD problems can be parametrized and simplified by using this framework.

The solar power industry, engineering design firms and the society as a whole could realize significant savings with the availability of a real-time in situ wind-load calculator that can prove essential for plug-and-play installation of PV systems. Additionally, this technology allows for automated parametric design optimization to arrive at the best fit for a set of given operating conditions. All these tasks are currently prohibited because of the massive computational resources and time required to address large-scale CFD analysis problems, all made possible by a simple but robust technology that can yield massive savings for the solar industry.

This paper aims to develop and describe an improved process for determining the rate of heat generation in living tissue.

Previous work by the authors on solving the bioheat equation has been updated to include a new localized meshless method which will create a more robust and computationally efficient technique. Inclusion of this technique will allow for the solution of more complex and realistic geometries, which are typical of living tissue. Additionally, the unknown heat generation rates are found through genetic algorithm optimization.

The localized technique showed superior accuracy and significant savings in memory and processor time. The computational efficiency of the newly proposed meshless solver allows the optimization process to be carried to a higher level, leading to more accurate solutions for the inverse technique. Several example cases are presented to demonstrate these conclusions.

This work includes only 2D development of the approach, while any realistic modeling for patient‐specific cases would be inherently 3D. The extension to 3D, as well as studies to improve the technique by decreasing the sensitivity to measurement noise and to incorporate non‐invasive measurement positioning, are under way.

As medical imaging continuously improves, such techniques may prove useful in patient diagonosis, as heat generation can be correlated to the presence of tumors, infections, or other conditions.

This paper describes a new application of meshless methods. Such methods are becoming attractive due to their decreased pre‐processing requirements, especially for problems involving complex geometries (such as patient specific tissues), as well as optimization problems, where geometries may be constantly changing.

An axisymmetric shock-tube model of the high-pressure shock-tube facility at the Texas A&M University has been developed. The shock tube is non-conventional with a non-uniform cross-section and features a driver section with a smaller diameter than the driven section. The paper aims to discuss these issues.

Computations were carried out based on the finite volume approach and the AUSM+ flux-differencing scheme. The adaptive mesh refinement algorithm was applied to the time-dependent flow fields to accurately capture and resolve the shock and contact discontinuities as well as the very fine scales associated with the viscous effects. The incorporation of a conjugate heat transfer model enhanced the credibility of the results.

The shock-tube model is validated with simulation of the bifurcation phenomenon and with experimental data. The model is shown to be capable of accurately simulating the shock and expansion wave propagations and reflections as well as the flow non-uniformities behind the reflected shock wave as a result of reflected shock/boundary layer interaction or bifurcation. The pressure profiles behind the reflected shock wave agree with the experimental results.

This paper presents one of the first studies to model the entire flow field history of a non-uniform diameter shock tube with a conjugate heat transfer model beginning from the bursting of the diaphragm while simultaneously resolving the fine features of the reflected shock-boundary layer interaction and the post-shock region near the end-wall, at conditions useful for chemical kinetics experiments. An important discovery from this study is the possible existence of hot spots in the end-wall region that could lead to early non-homogeneous ignition events. More experimental and numerical work is needed to quantify the hot spots.