Residual strength of hot pressed zirconium diboride (ZrB2) after exposure to high temperatures

ZrB2 with different amounts of B4C additive (0-5 wt.%) has been hot pressed at 2000 degrees C and 25 MPa for 1 h. By addition of B4C, density as well as micro-hardness increased. For lower B4C content (0.5 and 1 wt.%), hot pressed ZrB2 shows considerable improvement in flexural strength after exposure in air at 1000 C for 5 h, while higher B4C content (3 and 5 wt.%) leads to marginal or no improvement. For any content of B4C, flexural strength after exposure in air at 1500 degrees C for 5 h is lower than as-hot pressed ZrB2. (C) 2011 Elsevier B.V. All rights reserved.

Residual strength evaluation of concrete structural components under fatigue loading

This paper presents methodologies for residual strength evaluation of concrete structural components using linear elastic and nonlinear fracture mechanics principles. The effect of cohesive forces due to aggregate bridging has been represented mathematically by employing tension softening models. Various tension softening models such as linear, bilinear, trilinear, exponential and power curve have been described with appropriate expressions. These models have been validated by predicting the remaining life of concrete structural components and comparing with the corresponding experimental values available in the literature. It is observed that the predicted remaining life by using power model and modified bi-linear model is in good agreement with the corresponding experimental values. Residual strength has also been predicted using these tension softening models and observed that the predicted residual strength is in good agreement with the corresponding analytical values in the literature. In general, it is observed that the variation of predicted residual moment with the chosen tension softening model follows the similar trend as in the case of remaining life. Linear model predicts large residual moments followed by trilinear, bilinear and power models.

Minimal residual method provides optimal regularization parameter for diffuse optical tomography

The inverse problem in the diffuse optical tomography is known to be nonlinear, ill-posed, and sometimes under-determined, requiring regularization to obtain meaningful results, with Tikhonov-type regularization being the most popular one. The choice of this regularization parameter dictates the reconstructed optical image quality and is typically chosen empirically or based on prior experience. An automated method for optimal selection of regularization parameter that is based on regularized minimal residual method (MRM) is proposed and is compared with the traditional generalized cross-validation method. The results obtained using numerical and gelatin phantom data indicate that the MRM-based method is capable of providing the optimal regularization parameter. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). DOI: 10.1117/1.JBO.17.10.106015]

A h-Adaptive Algorithm Using Residual Error Estimates for Fluid Flows

Algorithms for adaptive mesh refinement using a residual error estimator are proposed for fluid flow problems in a finite volume framework. The residual error estimator, referred to as the R-parameter is used to derive refinement and coarsening criteria for the adaptive algorithms. An adaptive strategy based on the R-parameter is proposed for continuous flows, while a hybrid adaptive algorithm employing a combination of error indicators and the R-parameter is developed for discontinuous flows. Numerical experiments for inviscid and viscous flows on different grid topologies demonstrate the effectiveness of the proposed algorithms on arbitrary polygonal grids.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Universal flame propagation behavior in packed bed of biomass

This article aims at seeking the universal behavior of propagation rate variation with air superficial velocity (V-s) in a packed bed of a range of biomass particles in reverse downdraft mode while also resolving the differing and conflicting explanations in the literature. Toward this, measurements are made of exit gas composition, gas phase and condensed phase surface temperature (T-g and T-s), and reaction zone thickness for a number of biomass with a range of properties. Based on these data, two regimes are identified: gasificationvolatile oxidation accompanied by char reduction reactions up to 16 +/- 1cm/s of V-s and above this, and char oxidationsimultaneous char oxidation and gas phase combustion. In the gasification regime, the measured T-s is less than T-g; a surface heat balance incorporating a diffusion controlled model for flaming combustion gives and matches with the experimental results to within 5%. In the char oxidation regime, T-g and T-s are nearly equal and match with the equilibrium temperature at that equivalence ratio. Drawing from a recent study of the authors, the ash layer over the oxidizing char particle is shown to play a critical role in regulating the radiation heat transfer to fresh biomass in this regime and is shown to be crucial in explaining the observed propagation behavior. A simple model based on radiation-convection balance that tracks the temperature-time evolution of a fresh biomass particle is shown to support the universal behavior of the experimental data on reaction front propagation rate from earlier literature and the present work for biomass with ash content up to 10% and moisture fraction up to 10%. Upstream radiant heat transfer from the ash-laden hot char modulated by the air flow is shown to be the dominant feature of this model.

Epoch extraction based on integrated linear prediction residual using plosion index

Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

Oxy-steam gasification of biomass for hydrogen rich syngas production using downdraft reactor configuration

The paper focuses on the use of oxygen and steam as the gasification agents in the thermochemical conversion of biomass to produce hydrogen rich syngas, using a downdraft reactor configuration. Performance of the reactor is evaluated for different equivalence ratios (ER), steam to biomass ratios (SBR) and moisture content in the fuel. The results are compared and evaluated with chemical equilibrium analysis and reaction kinetics along with the results available in the literature. Parametric study suggests that, with increase in SBR, hydrogen fraction in the syngas increases but necessitates an increase in the ER to maintain reactor temperature toward stable operating conditions. SBR is varied from 0.75 to 2.7 and ER from 0.18 to 0.3. The peak hydrogen yield is found to be 104g/kg of biomass at SBR of 2.7. Further, significant enhancement in H-2 yield and H-2 to CO ratio is observed at higher SBR (SBR=1.5-2.7) compared with lower range SBR (SBR=0.75-1.5). Experiments were conducted using wet wood chips to induce moisture into the reacting system and compare the performance with dry wood with steam. The results clearly indicate the both hydrogen generation and the gasification efficiency ((g)) are better in the latter case. With the increase in SBR, gasification efficiency ((g)) and lower heating value (LHV) tend to reduce. Gasification efficiency of 85.8% is reported with LHV of 8.9MJNm(-3) at SBR of 0.75 compared with 69.5% efficiency at SBR of 2.5 and lower LHV of 7.4 at MJNm(-3) at SBR of 2.7. These are argued on the basis of the energy required for steam generation and the extent of steam consumption during the reaction, which translates subsequently in the LHV of syngas. From the analysis of the results, it is evident that reaction kinetics plays a crucial role in the conversion process. The study also presents the importance of reaction kinetics, which controls the overall performance related to efficiency, H-2 yield, H-2 to CO fraction and LHV of syngas, and their dependence on the process parameters SBR and ER. Copyright (c) 2013 John Wiley & Sons, Ltd.

Scientific and technological aspects of fixed bed biomass gasification

In recent years new emphasis has been placed on problems of the environmental aspects of waste disposal, especially investigating alternatives to landfill, sea dumping and incineration. There is also a strong emphasis on clean, economic and efficient processes for electric power generation. These two topics may at first appear unrelated. Nevertheless, the technological advances are now such that a solution to both can be combined in a novel approach to power generation based on waste-derived fuels, including refuse-derived fuel (RDF) and sludge power (SP) by utilising a slagging gasifier and advance fuel technology (AFT). The most appropriate gasification technique for such waste utilisation is the British Gas/Lurgi (BGL) high pressure, fixed bed slagging gasifier where operation on a range of feedstocks has been well-documented. This gasifier is particularly amenable to briquette fuel feeding and, operating in an integrated gasification combined cycle mode (IGCC), is particularly advantageous. Here, the author details how this technology has been applied to Britain's first AFT-IGCC Power Station which is now under development at Fife Energy Ltd., in Scotland, the former British Gas Westfield Development Centre.

Large-MIMO Receiver based on Linear Regression of MMSE Residual

Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs quite well: at a bit error rate (BER) of 10(-3), the SNR gain over MMSE receiver is about 7 dB for a 16 x 16 system; for a 64 x 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.

Analytical Determination of Residual Strength and Linkup Strength for Flat Panels, with Multiple Site Damage

The problem of multiple site damage in aged airplane fuselage is handled in this paper. The analytical and numerical procedures used for the estimation of the strength of a flat panel with such multi-site damage are presented. Further, numerical results are presented on the residual strength of the panel using fracture mechanics-based approach and the stress levels when the leading crack is likely to link up with multiple site damage cracks. The presence of multiple site damage cracks in the vicinity of leading crack significantly decreases the residual strength of the panel. The model is verified using experimental data from the open literature and the predictions are in good agreement with the measured residual strength.

Influence of surface area to volume ratio of fuel particles on gasification process in a fixed bed

The paper addresses the effect of particle size on tar generation in a fixed bed gasification system. Pyrolysis, a diffusion limited process, depends on the heating rate and the surface area of the particle influencing the release of the volatile fraction leaving behind residual char. The flaming time has been estimated for different biomass samples. It is found that the flaming time for wood flakes is almost one fourth than that of coconut shells for same equivalent diameter fuel samples. The particle density of the coconut shell is more than twice that of wood spheres, and almost four times compared with wood flakes; having a significant influence on the flaming time. The ratio of the particle surface area to that of an equivalent diameter is nearly two times higher for flakes compared with wood pieces. Accounting for the density effect, on normalizing with density of the particle, the flaming rate is double in the case of wood flakes or coconut shells compared with the wood sphere for an equivalent diameter. This is due to increased surface area per unit volume of the particle. Experiments are conducted on estimation of tar content in the raw gas for wood flakes and standard wood pieces. It is observed that the tar level in the raw gas is about 80% higher in the case of wood flakes compared with wood pieces. The analysis suggests that the time for pyrolysis is lower with a higher surface area particle and is subjected to fast pyrolysis process resulting in higher tar fraction with low char yield. Increased residence time with staged air flow has a better control on residence time and lower tar in the raw gas. (C) 2014 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

First and second law thermodynamic analysis of air and oxy-steam biomass gasification

Gasification is an energy transformation process in which solid fuel undergoes thermochemical conversion to produce gaseous fuel, and the two most important criteria involved in such process to evaluate the performance, economics and sustainability of the technology are: the total available energy (exergy) and the energy conserved (energy efficiency). Current study focuses on the energy and exergy analysis of the oxy-steam gasification and comparing with air gasification to optimize the H-2 yield, efficiency and syngas energy density. Casuarina wood is used as a fuel, and mixture of oxygen and steam in different proportion and amount is used as a gasifying media. The results are analysed with respect to varying equivalence ratio and steam to biomass ratio (SBR). Elemental mass balance technique is employed to ensure the validity of results. First and second law thermodynamic analysis is used towards time evaluation of energy and exergy analysis. Different component of energy input and output has been studied carefully to understand the influence of varying SBR on the availability of energy and irreversibility in the system to minimize the losses with change in input parameters for optimum performance. The energy and exergy losses (irreversibility) for oxy-steam gasification system are compared with the results of air gasification, and losses are found to be lower in oxy-steam thermal conversion; which has been argued and reasoned due to the presence of N-2 in the air-gasification. The maximum exergy efficiency of 85% with energy efficiency of 82% is achieved at SBR of 0.75 on the molar basis. It has been observed that increase in SBR results in lower exergy and energy efficiency, and it is argued to be due to the high energy input in steam generation and subsequent losses in the form of physical exergy of steam in the product gas, which alone accounts for over 18% in exergy input and 8.5% in exergy of product gas at SBR of 2.7. Carbon boundary point (CBP), is identified at the SBR of 1.5, and water gas shift (WGS) reaction plays a crucial role in H-2 enrichment after carbon boundary point (CBP) is reached. Effects of SBR and CBP on the H-2/CO ratio is analysed and discussed from the perspective of energy as well as the reaction chemistry. Energy density of syngas and energy efficiency is favoured at lower SBR but higher SBR favours H-2 rich gas at the expense of efficiency. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.