Skeletal reduction of boundary value problems

Boundary value problems posed over thin solids are amenable to a dimensional reduction in that one or more spatial variables may be eliminated from the governing equation, resulting in significant computational gains with minimal loss in accuracy. Extant dimensional reduction techniques rely on representing the solid as a hypothetical mid‐surface plus a possibly varying thickness. Such techniques are however hard to automate since the mid‐surface is often ill‐defined and ambiguous. We propose here a skeletal representation based dimensional reduction of boundary value problems. The proposed technique has the computational advantages of mid‐surface reduction, but can be easily automated. A systematic methodology is presented for reducing boundary value problems to lower‐dimensional problems over the skeleton of a solid. The theoretical properties of the proposed method are derived, and supported by representative numerical experiments. Copyright © 2005 John Wiley & Sons, Ltd.     

Rapid and Accurate Contact Determination between Spline Models using ShellTrees

In this paper, we present an efficient algorithm for contact determination between spline models. We make use of a new hierarchy, called ShellTree , that comprises of spherical shells and oriented bounding boxes. Each spherical shell corresponds to a portion of the volume between two concentric spheres. Given large spline models, our algorithm decomposes each surface into Bézier patches as part of pre-processing. At runtime it dynamically computes a tight fitting axis-aligned bounding box across each Bézier patch and efficiently checks all such boxes for overlap. Using off-line and on-line techniques for tree construction, our algorithm computes ShellTrees for Bézier patches and performs fast overlap tests between them to detect collisions. The overall approach can trade off runtime performance for reduced memory requirements. We have implemented the algorithm and tested it on large models, each composed of hundred of patches. Its performance varies with the configurations of the objects. For many complex models composed of hundreds of patches, it can accurately compute the contacts in a few milliseconds.     

Data token heuristic scheduling of the Kalman algorithm onto a message-passing multiprocessor system

Scheduling the tasks of a parallel algorithm onto a network of processors to minimize the completion time of the task graph is an NP-hard problem, and heuristic methods are commonly used to solve this problem. Published works in this area, however, do not take advantage of the following aspects of the problem: (i) the availability of the full knowledge of the data that is being transferred during inter-task communication, and (ii) the availability of full duplex high-speed communication links in many multiprocessors (such as transputers). The scheduling approach presented in this paper, the data token heuristic (DTH) approach, exploits the above features, leading to a reduced schedule length. This is achieved by checking the pool of data tokens in the processors, and routing the required data token to the processor through the dynamic shortest path. The DTH approach is then used to find the best transputer network topology that gives the minimum schedule length for the parallel implementation of the Kalman algorithm. Quantitative results of scheduling the Kalman algorithm on a 4-transputer network with T-805 transputers are presented.     

A new fluoride mediated synthesis of mesoporous silica and their usefulness in controlled delivery of duloxetine hydrochloride a serotonin re-uptake inhibitor

A new type of mesoporous silica nanoparticle (MSN) was synthesized in fluoride media via sol–gel technique using TritonX 100 and Tween-20. The surface area and pore volume of the MSN particles were modified by varying the concentration of Tween-20. The prepared MSN nanoparticles with large surface area and pore volume (T-2, T-3) were selected to accommodate the model drug duloxetine hydrochloride (DX) for evaluation of their drug-loading and release abilities. Calcined and DX loaded nanoparticles were characterized by Brunauer–Emmett–Teller technique (BET), powder X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric (TG) analysis and UV-diffuse reflectance (UV-DRS). In vitro release studies proved that the particle displays an initial burst release followed by sustained release for up to 140 h. From the studies it is evident that the synthesized particle may be useful as a carrier for sustained release of active pharmaceutical ingredients (APIs).     

Tracer design for magnetic particle imaging (invited)

Magnetic particle imaging (MPI) uses safe iron oxide nanoparticle tracers to offer fundamentally new capabilities for medical imaging, in applications as vascular imaging and ultra-sensitive cancer therapeutics. MPI is perhaps the first medical imaging platform to intrinsically exploit nanoscale material properties. MPI tracers contain magnetic nanoparticles whose tunable, size-dependent magnetic properties can be optimized by selecting a particular particle size and narrow size-distribution. In this paper we present experimental MPI measurements acquired using a homemade MPI magnetometer: a zero-dimensional MPI imaging system designed to characterize tracer performance by measuring the derivative of the time-varying tracer magnetization, M'(H(t)), at a driving frequency of 25 kHz. We show that MPI performance is optimized by selecting phase-pure magnetite tracers of a particular size and narrow size distribution; in this work, tracers with 20 nm median diameter, log-normal distribution shape parameter, σ(v), equal to 0.26, and hydrodynamic diameter equal to 30 nm showed the best performance. Furthermore, these optimized MPI tracers show 4?×?greater signal intensity (measured at the third harmonic) and 20% better spatial resolution compared with commercial nanoparticles developed for MRI.     

Effect of Dynamic Change in Strain Rate on Mechanical and Stress Corrosion Cracking Behavior of a Mild Steel

The current work analyzes the effect of the dynamic change in strain rate during tensile loading of a mild steel on its mechanical and stress corrosion behavior in 3.5 wt.% NaCl solution. The sample experiences high strain rate (10^?2 s^?1) up to 10, 15 and 20% of total deformation and then very low strain rate of 10^?6 s^?1 till fracture without any unloading in between. The behavioral characteristics of the steel under these circumstances are found to be different from that exhibited during complete loading till fracture both at high and slow strain rates separately. Total strain increases with the increase in the strain at which change in strain rate happens, and this is attributed to the generation of large number of dislocations at higher strain rate and subsequently release of dislocation at low strain rate during change over due to more time available for dynamic recovery. This observation is common for both in air and corrosive environment. One unique observation in this study is the higher total strain and lower strength observed during dynamic change in strain rate in the corrosive environment compared to that in air, which is attributed to the hydrogen-induced plasticity mechanism.     

Synthesis of 3D nanostructured metal alloy of immiscible materials induced by megahertz-repetition femtosecond laser pulses

In this work, we have proposed a concept for the generation of three-dimensional (3D) nanostructured metal alloys of immiscible materials induced by megahertz-frequency ultrafast laser pulses. A mixture of two microparticle materials (aluminum and nickel oxide) and nickel oxide microparticles coated onto an aluminum foil have been used in this study. After laser irradiation, three different types of nanostructure composites have been observed: aluminum embedded in nickel nuclei, agglomerated chain of aluminum and nickel nanoparticles, and finally, aluminum nanoparticles grown on nickel microparticles. In comparison with current nanofabrication methods which are used only for one-dimensional nanofabrication, this technique enables us to fabricate 3D nanostructured metal alloys of two or more nanoparticle materials with varied composite concentrations under various predetermined conditions. This technique can lead to promising solutions for the fabrication of 3D nanostructured metal alloys in applications such as fuel-cell energy generation and development of custom-designed, functionally graded biomaterials and biocomposites.