Pressure drop across vortex diodes: Experiments and design guidelines

Vortex diodes are used as leaky non-return valves in applications where it is desirable to avoid valves with moving parts. Despite their use in practice for several decades, no clear guidelines for design and optimization of vortex diodes are available. Detailed experimental study on flow and pressure drop characteristics of vortex diodes was therefore carried out to evolve such guidelines. The study covered a wide range of vortex diodes. The variation of diodicity (ratio of pressure drop for reverse and forward flow for the same flow rate) with respect to diode geometry, diode size (d_C), aspect ratio (d_C/h), nozzle configuration and Reynolds number (Re) was studied. The experimental results were critically analyzed to develop a design methodology. The methodology is shown to be useful for obtaining the diode dimensions that would yield the desired diodicity for the required operating flow rate.     

Growth of PbSe Quantum Dots Within High‐Index Lead‐Phosphate Glass for Infrared Saturable Absorbers

PbSe quantum dots (QDs) were grown in high‐refractive‐index low‐melting‐temperature lead‐phosphate glass. The lowest energy exciton transition of the QDs was tuned over a wide range within the infrared spectral region (0.93–2.75 μm) by a controlled heat treatment. The measured QD radius ranged between 2 and 5.3 nm, with a time (t) dependence of t^0.29 for long dwelling times during the heat treatment, indicating that the QD growth mechanism tends to follow Lifshitz‐Slyozov‐Wagner theory. The QD saturable absorber behavior at 1.2 μm had a measured saturation fluence of ~2.1 μJ/cm².     

Fast mining of distance-based outliers in high-dimensional datasets

Defining outliers by their distance to neighboring data points has been shown to be an effective non-parametric approach to outlier detection. In recent years, many research efforts have looked at developing fast distance-based outlier detection algorithms. Several of the existing distance-based outlier detection algorithms report log-linear time performance as a function of the number of data points on many real low-dimensional datasets. However, these algorithms are unable to deliver the same level of performance on high-dimensional datasets, since their scaling behavior is exponential in the number of dimensions. In this paper, we present RBRP, a fast algorithm for mining distance-based outliers, particularly targeted at high-dimensional datasets. RBRP scales log-linearly as a function of the number of data points and linearly as a function of the number of dimensions. Our empirical evaluation demonstrates that we outperform the state-of-the-art algorithm, often by an order of magnitude.     

Recursive identification algorithms to design fault detection systems

This paper deals with the recursive identification of the parity space based fault detection systems. We propose two such algorithms that update the eigenstructure after every new measurement with significantly less computational cost. Its immediate application is in the design of adaptive parity space based residual generators. The method improves the fault detection performance against uncertain changes, especially the frequent shifts in operating points, or parameter variations. The algorithms are compared with the existing techniques and applied to the hybrid simulation platform of continuously stirred tank heater.     

Classification of complex environments using pixel level fusion of satellite data

The present study reports classification and analysis of composite land features using fusion images obtained by fusing two original hyperspectral and multispectral datasets. The high spatial-spectral resolution, multi-instrument and multi-period satellite images were used for fusion. Three pixel level fusion based techniques, Color Normalized Spectral Sharpening (CNSS), Principal Component Spectral Sharpening Transform (PCSST) and Gram-Schmidt Transform (GST), were implemented on the datasets. Performance evaluations of three fusion algorithms were done using classification results. The Support Vector Machine (SVM) and Gaussian Maximum Likelihood Classification (MLC) were used for classification using five types of images, viz. hyperspectral, multispectral and three fused images. Number of classes considered was eight. Sufficient number of ground field data for each class has also been acquired which was needed for supervise based classification. The accuracy was improved from 74.44 to 97.65% when the fused images were considered with SVM classifier. Similarly, the results were improved from 69.25 to 94.61% with original and fused data using MLC classifier. The fusion image technique was found to be superior to the single original image and the SVM is better than the MLC method.

     

双极主观等级量表的级别选取

双极等级工具(Bipolar rating instruments)用来测量人们对产品的情感观点.这种方法的常用和典型代表就是分为5,7和9这三种等级级别的等级量表(Rating Scales),其中的数字代表了等级级别的数目(例如,'5'表示总共有5种等级级别).然而到目前很少有文献关注等级量表的最佳的级别数目问题.这里对这一问题进行了初步研究,尤其是针对这样的三种等级量表(S<,5>,S<,7>,S<,9>),通过实验采给出了答案;研究表明,由于其高可靠性S7最为适合.     

Mechanical properties of solution-precursor plasma-sprayed thermal barrier coatings

The microstructure of thermal barrier coatings (TBCs) of 7 wt.% Y₂O₃ stabilized ZrO₂ (7YSZ) deposited using the solution-precursor plasma spray (SPPS) method has: (i) controlled porosity, (ii) vertical cracks, and (iii) lack of large-scale “splat” boundaries. An unusual feature of such SPPS TBCs is that they are well-adherent in ultra-thick forms (~ 4 mm thickness), where most other types of ultra-thick ceramic coatings fail spontaneously. Here a quantitative explanation is provided as to why as-deposited ultra-thick SPPS TBCs are so well-adherent. The mode II toughness of thin (0.2 mm) SPPS TBCs has been measured using the “barb” shear test, which is found to be 66 J m^− 2. Residual stresses in SPPS TBCs of thickness 0.2, 1.5, and 4.0 mm have been estimated using a microstructure-based object-oriented finite element (OOF) method. These stresses are found to be low, as a result of the strain-tolerant microstructure of the SPPS TBCs. The corresponding strain energy release rates that drive mode II cracks in the three different thickness SPPS TBCs have been found to be less than the mode II toughness.     

Effect of addition of Zr,Ni, and Zr-Ni alloy on the hydrogen absorption of Body Centred Cubic 52Ti-12V-36Cr alloy

The effects of addition of Zr, Ni and Zr₇Ni₁₀ on the crystal structure, microstructure and hydrogen absorption of Body Centred Cubic (BCC) 52Ti-12V-36Cr were investigated. We found that addition of Zr and/or Ni led to the formation of a Ni/Zr rich secondary phase. This secondary phase is responsible for the much faster first hydrogenation of the alloys with additives compared to the bare BCC alloy. Zirconium addition had positive influence on incubation time and intrinsic hydrogenation kinetics while nickel addition improved the hydrogen capacity. Among the additives tested, Zr₇Ni₁₀ is the best for optimized hydrogenation kinetics and capacity.