A study of capacitance-voltage characteristics of lead zirconate titanate ferroelectric thin films and their usage to investigate polarization and coercive field.

Capacitance-voltage (C-V) characteristics of lead zirconate titanate (PZT) thin films with a thickness of 130 nm were measured between 300 and 533 K. The transition between ferroelectric and paraelectric phases was revealed to be of second order in our case, with a Curie temperature at around 450 K. A linear relationship was found between the measured capacitance and the inverse square root of the applied voltage. It was shown that such a relationship could be fitted well by a universal expression of C/A = k(V+V(0))(-1/2) and that this expression could be derived by expanding the Landau-Devonshire free energy at an effective equilibrium position of the Ti/Zr ion in a PZT unit cell. By using the derived equations in this work, the free energy parameters for an individual material can be obtained solely from the corresponding C-V data, and the temperature dependences of both remnant polarization and coercive voltage are shown to be in quantitative agreement with the experimental data.

BarraCUDA – a Fast Sequence Mapping Software using Graphics Processing Units

High-throughput DNA sequencing (HTS) instruments today are capable of generating millions of sequencing reads in a short period of time, and this represents a serious challenge to current bioinformatics pipeline in processing such an enormous amount of data in a fast and economical fashion. Modern graphics cards are powerful processing units that consist of hundreds of scalar processors in parallel in order to handle the rendering of high-definition graphics in real-time. It is this computational capability that we propose to harness in order to accelerate some of the time-consuming steps in analyzing data generated by the HTS instruments. We have developed BarraCUDA, a novel sequence mapping software that utilizes the parallelism of NVIDIA CUDA graphics cards to map sequencing reads to a particular location on a reference genome. While delivering a similar mapping fidelity as other mainstream programs , BarraCUDA is a magnitude faster in mapping throughput compared to its CPU counterparts. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the mapping throughput. BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the mapping of millions of sequencing reads generated by HTS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available at http://seqbarracuda.sf.net

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Effect of flow-geometry on turbulence-scalar interaction in premixed flames

Turbulent combustion of stoichiometric hydrogen-air mixture is simulated using direct numerical simulation methodology, employing complex chemical kinetics. Two flame configurations, freely propagating and V-flames stabilized behind a hot rod, are simulated. The results are analyzed to study the influence of flame configuration on the turbulence-scalar interaction, which is critical for the scalar gradient generation processes. The result suggests that this interaction process is not influenced by the flame configuration and the flame normal is found to align with the most extensive strain in the region of intense heat release. The combustion in the rod stabilized flame is found to be flamelet like in an average sense and the growth of flame-brush thickness with the downstream distance is represented well by Taylor theory of turbulent diffusion, when the flame-brushes are non-interacting. The thickness is observed to saturate when the flame-brushes interact, which is found to occur in the simulated rod stabilized flame with Taylor micro-scale Reynolds number of 97. © 2011 American Institute of Physics.

Generating the Sparse Point Cloud of a Civil Infrastructure Scene Using a Single Video Camera under Practical Constraints

Automating the model generation process of infrastructure can substantially reduce the modeling time and cost. This paper presents a method to generate a sparse point cloud of an infrastructure scene using a single video camera under practical constraints. It is the first step towards establishing an automatic framework for object-oriented as-built modeling. Motion blur and key frame selection criteria are considered. Structure from motion and bundle adjustment are explored. The method is demonstrated in a case study where the scene of a reinforced concrete bridge is videotaped, reconstructed, and metrically validated. The result indicates the applicability, efficiency, and accuracy of the proposed method.