Optimization of thermoacoustic refrigerator using response surface methodology

Thermoacoustic refrigerator (TAR) converts acoustic waves into heat without any moving parts. The study presented here aims to optimize the parameters like frequency, stack position, stack length, and plate spacing involving in designing TAR using the Response Surface Methodology (RSM). A mathematical model is developed using the RSM based on the results obtained from DeltaEC software. For desired temperature difference of 40 K, optimized parameters suggested by the RSM are the frequency 254 Hz, stack position 0.108 m, stack length 0.08 m, and plate spacing 0.0005 m. The experiments were conducted with optimized parameters and simulations were performed using the Design Environment for Low-amplitude ThermoAcoustic Energy Conversion (DeltaEC) which showed similar results.

Development of uniformly grown ZnO NPs films using single precursor solution by pulsed spray pyrolysis technique

In this article, we have reported the controlled synthesis of uniformly grown zinc oxide nanoparticles (ZnO NPs) films by a simple, low-cost, and scalable pulsed spray pyrolysis technique. From the surface analysis it is noticed that the as-deposited films have uniformly dispersed NPs-like morphology. The structural studies reveal that these NPs films have highly crystalline hexagonal crystal structure, which are preferentially orientated along the (001) planes. The size of the NPs varied between 5 and 100 nm, and exhibited good stoichiometric chemical composition. Raman spectroscopic analysis reveals that these ZnO NPs films have pure single phase and hexagonal crystal structure. These unique nanostructured films exhibited a low electrical resistivity (5 Omega cm) and high light transmittance (90 %) in visible region.

Runtime dependence computation and execution of loops on heterogeneous systems

GPUs have been used for parallel execution of DOALL loops. However, loops with indirect array references can potentially cause cross iteration dependences which are hard to detect using existing compilation techniques. Applications with such loops cannot easily use the GPU and hence do not benefit from the tremendous compute capabilities of GPUs. In this paper, we present an algorithm to compute at runtime the cross iteration dependences in such loops. The algorithm uses both the CPU and the GPU to compute the dependences. Specifically, it effectively uses the compute capabilities of the GPU to quickly collect the memory accesses performed by the iterations by executing the slice functions generated for the indirect array accesses. Using the dependence information, the loop iterations are levelized such that each level contains independent iterations which can be executed in parallel. Another interesting aspect of the proposed solution is that it pipelines the dependence computation of the future level with the actual computation of the current level to effectively utilize the resources available in the GPU. We use NVIDIA Tesla C2070 to evaluate our implementation using benchmarks from Polybench suite and some synthetic benchmarks. Our experiments show that the proposed technique can achieve an average speedup of 6.4x on loops with a reasonable number of cross iteration dependences.

Deposition and characterization of pure and Cd doped SnO2 thin films by the nebulizer spray pyrolysis (NSP) technique

Pure and cadmium doped tin oxide thin films were deposited on glass substrates from aqueous solution of cadmium acetate, tin (IV) chloride and sodium hydroxide by the nebulizer spray pyrolysis (NSP) technique. X-ray diffraction reveals that all films have tetragonal crystalline structure with preferential orientation along (200) plane. On application of the Scherrer formula, it is found that the maximum size of grains is 67 nm. Scanning electron microscopy shows that the grains are of rod and spherical in shape. Energy dispersive X-ray analysis reveals the average ratio of the atomic percentage of pure and Cd doped SnO2 films. The electrical resistivity is found to be 10(2) Omega cm at higher temperature (170 degrees C) and 10(3) Omega cm at lower temperature (30 degrees C). Optical band gap energy was determined from transmittance and absorbance data obtained from UV-vis spectra. Optical studies reveal that the band gap energy decreases from 3.90 eV to 3.52 eV due to the addition of Cd as dopant with different concentrations.

Nanostructured GdxZn1-xO thin films by nebulizer spray pyrolysis technique: Role of doping concentration on the structural and optical properties

Nanostructured GdxZn1-xO thin films with different Gd concentration from 0% to 10% deposited at 400 degrees C using the NSF technique. The films were characterized by structural, surface and optical properties, respectively. X-ray diffraction analysis shows that the Gd doped ZnO films have lattice parameters a = 3.2497 angstrom and c = 5.2018 angstrom with hexagonal structure and preferential orientation along (002) plane. The estimated values compare well with the standard values. When film thickness increases from 222 to 240 nm a high visible region transmittance (>70%) is observed. The optical band gap energy, optical constants (n and k), complex dielectric constants (epsilon(r), and epsilon(i)) and optical conductivities (sigma(r), and sigma(i)) were calculated from optical transmittance data. The optical band gap energy is 3.2 eV for pure ZnO film and 3.6 eV for Gd0.1Zn0.9-O film. The PL studies confirm the presence of a strong UV emission peak at 399 nm. Besides, the UV emission of ZnO films decreases with the increase of Gd doping concentration correspondingly the ultra-violet emission is replaced by blue and green emissions.

Topology optimization-based design of a compliant aircraft compliant aircraft wing for morphing leading and trailing edges

In this paper, we present a methodology for designing a compliant aircraft wing, which can morph from a given airfoil shape to another given shape under the actuation of internal forces and can offer sufficient stiffness in both configurations under the respective aerodynamic loads. The least square error in displacements, Fourier descriptors, geometric moments, and moment invariants are studied to compare candidate shapes and to pose the optimization problem. Their relative merits and demerits are discussed in this paper. The `frame finite element ground structure' approach is used for topology optimization and the resulting solutions are converted to continuum solutions. The introduction of a notch-like feature is the key to the success of the design. It not only gives a good match for the target morphed shape for the leading and trailing edges but also minimizes the extension of the flexible skin that is to be put on the airfoil frame. Even though linear small-displacement elastic analysis is used in optimization, the obtained designs are analysed for large displacement behavior. The methodology developed here is not restricted to aircraft wings; it can be used to solve any shape-morphing requirement in flexible structures and compliant mechanisms.

Fast and accurate quantification using Genetic Algorithm optimized H-1-C-13 refocused constant-time INEPT

Using Genetic Algorithm, a global optimization method inspired by nature's evolutionary process, we have improved the quantitative refocused constant-time INEPT experiment (Q-INEPT-CT) of Makela et al. (JMR 204 (2010) 124-130) with various optimization constraints. The improved `average polarization transfer' and `min-max difference' of new delay sets effectively reduces the experimental time by a factor of two (compared with Q-INEPT-CT, Makela et al.) without compromising on accuracy. We also discuss a quantitative spectral editing technique based on average polarization transfer. (C) 2013 Elsevier Inc. All rights reserved.

Microcracking and fracture process in cement mortar and concrete: a comparative study using acoustic emission technique

This article reports the acoustic emission (AE) study of precursory micro-cracking activity and fracture behaviour of quasi-brittle materials such as concrete and cement mortar. In the present study, notched three-point bend specimens (TPB) were tested under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/sec and the accompanying AE were recorded using a 8 channel AE monitoring system. The various AE statistical parameters including AE event rate , AE energy release rate , amplitude distribution for computing the AE based b-value, cumulative energy (I E) pound and ring down count (RDC) were used for the analysis. The results show that the micro-cracks initiated and grew at an early stage in mortar in the pre peak regime. While in the case of concrete, the micro-crack growth occurred during the peak load regime. However, both concrete and mortar showed three distinct stages of micro-cracking activity, namely initiation, stable growth and nucleation prior to the final failure. The AE statistical behavior of each individual stage is dependent on the number and size distribution of micro-cracks. The results obtained in the laboratory are useful to understand the various stages of micro-cracking activity during the fracture process in quasi-brittle materials such as concrete & mortar and extend them for field applications.

Integrated sustainable irrigation planning with multiobjective Fuzzy optimization approach

Multiobjective fuzzy methodology is applied to a case study of Khadakwasla complex irrigation project located near Pune city of Maharashtra State, India. Three objectives, namely, maximization of net benefits, crop production and labour employment are considered. Effect of reuse of wastewater on the planning scenario is also studied. Three membership functions, namely, nonlinear, hyperbolic and exponential are analyzed for multiobjective fuzzy optimization. In the present study, objective functions are considered as fuzzy in nature whereas inflows are considered as dependable. It is concluded that exponential and hyperbolic membership functions provided similar cropping pattern for most of the situations whereas nonlinear membership functions provided different cropping pattern. However, in all the three cases, irrigation intensities are more than the existing irrigation intensity.

Optimization of HfO2 films for high transconductance back gated graphene transistors

Hafnium dioxide (HfO2) films, deposited using electron beam evaporation, are optimized for high performance back-gated graphene transistors. Bilayer graphene is identified on HfO2/Si substrate using optical microscope and subsequently confirmed with Raman spectroscopy. Back-gated graphene transistor, with 32 nm thick HfO2 gate dielectric, has been fabricated with very high transconductance value of 60 mu S. From the hysteresis of the current-voltage characteristics, we estimate the trap density in HfO2 to be in the mid 10(11)/cm(2) range, comparable to SiO2.

Photo-thermal modifications in ultrafast laser inscribed chalcogenide glass waveguides

We report here, a finite difference thermal diffusion (FDTD) model for controlling the cross-section and the guiding nature of the buried channel waveguides fabricated on GeGaS bulk glasses using the direct laser writing technique. Optimization of the laser parameters for guiding at wavelength 1550 nm is done experimentally and compared with the theoretical values estimated by FDTD model. The mode field diameter (MFD) between 5.294 mu m and 24.706 mu m were attained by suitable selection of writing speed (1mm/s to 4 mm/s) and pulse energy (623 nJ to 806 nJ) of the laser at a fixed repletion rate of 100 kHz. Transition from single-mode to multi-mode waveguide is observed at pulse energy 806nJ as a consequence of heat accumulation. The thermal diffusion model fits well for single-mode waveguides with the exception of multi-mode waveguides.

Is Granger Causality a Viable Technique for Analyzing fMRI Data?

Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC) has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI) data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a) latency differences in hemodynamic response function (HRF) across different brain regions, (b) low-sampling rates, and (c) noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC) between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1) GC following HRF convolution is a monotonically increasing function of neural GC; (2) this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3) although the detectability of monotonicity declined due to the presence of HRF latency differences, substantial recovery of detectability occurred after correcting for latency differences. These results suggest that Granger causality is a viable technique for analyzing fMRI data when the questions are appropriately formulated.

Role of substrate temperature on the properties of Na-doped ZnO thin film nanorods and performance of ammonia gas sensors using nebulizer spray pyrolysis technique

Sodium doped zinc oxide (Na:ZnO) thin films were deposited on glass substrates at substrate temperatures 300,400 and 500 degrees C by a novel nebulizer spray method. X-ray diffraction shows that all the films are polycrystalline in nature having hexagonal structure with high preferential orientation along (0 0 2) plane. High resolution SEM studies reveal the formation of Na-doped ZnO films having uniformly distributed nano-rods over the entire surface of the substrates at 400 degrees C. The complex impedance of the ZnO nano-rods shows two distinguished semicircles and the diameter of the arcs got decreased in diameter as the temperature increases from 170 to 270 degrees C and thereafter slightly increased. (c) 2013 Elsevier B.V. All rights reserved.

Probabilistic least squares approach to ordinal regression

This paper proposes a novel approach to solve the ordinal regression problem using Gaussian processes. The proposed approach, probabilistic least squares ordinal regression (PLSOR), obtains the probability distribution over ordinal labels using a particular likelihood function. It performs model selection (hyperparameter optimization) using the leave-one-out cross-validation (LOO-CV) technique. PLSOR has conceptual simplicity and ease of implementation of least squares approach. Unlike the existing Gaussian process ordinal regression (GPOR) approaches, PLSOR does not use any approximation techniques for inference. We compare the proposed approach with the state-of-the-art GPOR approaches on some synthetic and benchmark data sets. Experimental results show the competitiveness of the proposed approach.

Simultaneous feature selection and clustering using particle swarm optimization

Data clustering groups data so that data which are similar to each other are in the same group and data which are dissimilar to each other are in different groups. Since generally clustering is a subjective activity, it is possible to get different clusterings of the same data depending on the need. This paper attempts to find the best clustering of the data by first carrying out feature selection and using only the selected features, for clustering. A PSO (Particle Swarm Optimization)has been used for clustering but feature selection has also been carried out simultaneously. The performance of the above proposed algorithm is evaluated on some benchmark data sets. The experimental results shows the proposed methodology outperforms the previous approaches such as basic PSO and Kmeans for the clustering problem.