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.     

Simulated annealing heuristics for the dynamic facility layout problem

In today's economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in product mix and demand. Therefore, this paper considers the problem of arranging and rearranging (when there are changes between the flows of materials between departments) manufacturing facilities such that the sum of the material handling and rearrangement costs is minimized. This problem is known as the dynamic facility layout problem (DFLP). In this paper, two simulated annealing (SA) heuristics are developed for the DFLP. The first SA heuristic (SA I) is a direct adaptation of SA to the DFLP. The second SA heuristic (SA II) is the same as SA I with a look-ahead/look-back strategy added. To test the performance of the heuristics, a data set taken from the literature is used in the analysis. The results obtained show that the proposed heuristics are very effective for the dynamic facility layout problem.     

Condition monitoring studies on spindle bearing of a lathe

In modern industry, machinery must become increasingly flexible and automatic. In order to increase productivity, enhance quality and reduce cost, machine tools have to work free of any failure. When a failure occurs in a machine tool, it is necessary to identify the causes as early as possible. Machine tool condition monitoring is very important to achieve this goal. Condition monitoring is generally used on the critical subsystem of any machine tool. This paper endeavors to focus on the condition monitoring aspects on the machine tool element. In the present study, a critical subsystem has been identified based on the failure data analysis. Condition monitoring techniques like vibration monitoring, acoustic emission, Shock Pulse Method (SPM) and surface roughness have been successfully used for fault identification.     

A subtle review on the challenges of photocatalytic fuel cell for sustainable power production

The revolution in the arena of functional materials for the development of well advanced engineered photocatalyst can efficiently harness photon energy from a wide spectrum of electromagnetic radiation. These next-generation smart materials would be a spectacular approach in designing devices such as photovoltaic cells, photoelectrochemical cells, and photocatalytic fuel cells. Photocatalytic oxidation of water or wastewater for concurrent production of hydrogen and electric current has turned out as a principal concept for the construction of modern photocatalytic fuel cells (PFCs). Such PFCs mimics reverse photosynthesis process where electrical energy is generated from organic pollutants. In recent years many reviews on focusing the design, fabrication, and theoretical efficiency of the PFCs have been published. Hence the present review is aimed to unveil the wall-to-wall information starting from fundamentals spanning to working principles, structural configuration, electrochemical degradation of pollutants and photoelectrochemical properties, electron transport, thermodynamic behavior and columbic efficiency of studied PFCs.     

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.