Global warming potential of the sulfur–iodine process using life cycle assessment methodology

A life cycle assessment (LCA) of one proposed method of hydrogen production – thermochemical water-splitting using the sulfur–iodine cycle couple with a very high-temperature nuclear reactor – is presented in this paper. Thermochemical water-splitting theoretically offers a higher overall efficiency than high-temperature electrolysis of water because heat from the nuclear reactor is provided directly to the hydrogen generation process, instead of using the intermediate step of generating electricity. The primary heat source for the S–I cycle is an advanced nuclear reactor operating at temperatures corresponding to those required by the sulfur–iodine process. This LCA examines the environmental impact of the combined advanced nuclear and hydrogen generation plants and focuses on quantifying the emissions of carbon dioxide per kilogram of hydrogen produced. The results are presented in terms of global warming potential (GWP). The GWP of the system is 2500 g carbon dioxide-equivalent (CO₂-eq) per kilogram of hydrogen produced. The GWP of this process is approximately one-sixth of that for hydrogen production by steam reforming of natural gas, and is comparable to producing hydrogen from wind- or hydro-electric conventional electrolysis.     

Intelligent and Efficient Strategy for Unstructured Environment Sensing Using Mobile Robot Agents

In field environments it is not usually possible to provide robots in advance with valid geometric models of its task and environment. The robot or robot teams need to create these models by scanning the environment with its sensors. Here, an information-based iterative algorithm to plan the robot's visual exploration strategy is proposed to enable it to most efficiently build 3D models of its environment and task. The method assumes mobile robot (or vehicle) with vision sensors mounted at a manipulator end-effector (eye-in-hand system). This algorithm efficiently repositions the systems' sensing agents using an information theoretic approach and fuses sensory information using physical models to yield a geometrically consistent environment map. This is achieved by utilizing a metric derived from Shannon's information theory to determine optimal sensing poses for the agent(s) mapping a highly unstructured environment. This map is then distributed among the agents using an information-based relevant data reduction scheme. This method is particularly well suited to unstructured environments, where sensor uncertainty is significant. Issues addressed include model-based multiple sensor data fusion, and uncertainty and vehicle suspension motion compensation. Simulation results show the effectiveness of this algorithm.     

A HYBRID INTELLIGENT MODEL BASED ON EVOLUTIONARY FUZZY CLUSTERING AND SYNDICATE NEURAL NETWORKS

In this article, a new hybrid intelligent model comprising a cluster allocation and adaptation component is developed for solving classification and pattern recognition problems. Its computation ability has been verified through various benchmark problems and biometric applications. The proposed model consists of two components: cluster distribution and adaptation. In the first module, mean patterns are distributed into the number of clusters based on the evolutionary fuzzy clustering, which is the basis for network structure selection in next module. In the second module, training and subsequent generalization is performed by the syndicate neural networks (SNN). The number of SNNs required in the second module will be same as the number of clusters. Whereas each network contains as many output neurons as the maximum number of members assigned to each cluster. The proposed novel fusion of evolutionary fuzzy clustering with a neural network yields superior performance in classification and pattern recognition problems. Performance evaluation has been carried out over a wide spectrum of benchmark problems and real-life biometric recognition problems with noise and occlusion. Experimental results demonstrate the efficacy of the methodology over existing ones.     

Enhancing biometric recognition with spatio-temporal reasoning in smart environments

We discuss smart environments that identify and track their occupants using unobtrusive recognition modalities such as face, gait, and voice. In order to alleviate the inherent limitations of recognition, we propose spatio-temporal reasoning techniques based upon an analysis of the occupant tracks. The key idea underlying our approach is to determine the identity of a person based upon information from a track of events rather than a single event. We abstract a smart environment by a probabilistic state transition system in which each state records a set of individuals who are present in various zones of the smart environment. An event abstracts a recognition step, and the transition function defines the mapping between states upon the occurrence of an event. We express two forms of spatio-temporal reasoning in the form of transition functions: a track-based transition function and an error-correcting transition function. We also define the concepts of ‘precision’ and ‘recall’ to quantify the performance of the smart environment and provide experimental results to clarify the performance improvements from spatio-temporal reasoning. Our conclusion is that the state transition system is an effective abstraction of a smart environment and the application of spatial-temporal reasoning enhances the overall performance of a biometric recognition system.     

CFD predictions of flow near impeller blades in baffled stirred vessels: Assessment of computational snapshot approach

The present article summarizes simulations of turbulent flow generated by a Rushton turbine (six blades with disc) and a downflow pitched blade turbine (four blades, 45° inclined) using a computational snapshot approach. The computational snapshot approach proposed by Ranade and Dommeti was extended and generalized to suit impellers of any shape. The approach was implemented using a commercial CFD code, FLUENT (Fluent Inc., USA). Mean flow and turbulence characteristics were computed by solving the Reynolds averaged Navier-Stokes equations combined with the standard k - l turbulence model. The QUICK discretization scheme (with SUPERBEE limiter function) was used to discretize all the governing equations. Preliminary numerical experiments were carried out to identify adequate grid resolution. The predicted results were compared with the comprehensive data set available in the literature. Simulated results show a pair of trailing vortex behind the blades of a turbine. The results were also compared quantitatively in the near-impeller region with the published experimental data and published simulated results using other approaches. The simulations have captured most of the key features of near-impeller flows with sufficient accuracy. The results and conclusions drawn from this study will have important implications for extending the applicability of CFD models to simulate complex stirred reactors.     

Cyanate Ester-Based Encapsulation Material for High-Temperature Applications

Cyanate ester resin-based composite materials have been proposed as potential encapsulants for high-temperature applications. The objective of this study is to develop a cyanate ester-based encapsulant, which can also serve as a flip-chip underfill as well as for traditional encapsulation. Two different materials, quartz and alumina fillers, have been studied. The impact of shapes and sizes of the fillers on the overall thermomechanical properties has been investigated. The adhesion strengths of the materials to the ceramic substrate, Kovar lid, and silicon die have also been characterized. The modulus of the resin and the shape of the fillers play a pivotal role in minimizing thermal stress, generated by coefficient of thermal expansion mismatches. Smaller filler particles were found to have better adhesion to the cyanate ester resin. The high-temperature performance of the cyanate ester-based encapsulants was evaluated by thermal aging at 300°C for up to 500 h.     

Time‐dependent dosing of Fe2+ for improved lipopeptide production by marine Bacillus megaterium

BACKGROUND: Lipopeptide production is strongly influenced by trace metals. The availability of free Fe²⁺ in the media throughout the process of fermentation was found to be very critical. Since free Fe²⁺ was reported to be sequestered by the lipopeptide as it was produced, intermittent feeding of Fe²⁺ was strategized and optimized for enhanced lipopeptide production by marine Bacillus megaterium in glucose mineral salts medium (GMSM). RESULTS: Studies with the single‐dose Fe²⁺ (0.48 mmol L^?1) supplementation after 8 h of fermentation resulted in lipopeptide concentration of 3.3 ± 0.1 g L^?1. Lipopeptide production was further enhanced to 4.2 ± 0.15 g L^?1 by adopting a multi‐dose Fe²⁺ feeding strategy. The maximum product yield (Y_P/S) of 0.24 ± 0.02 g g^?1 with specific product formation rate (q_p) of 0.124 ± 0.01 g g^?1 h^?1 was achieved when 0.48 mmol L^?1 Fe²⁺ was fed intermittently at different times as per the designed strategy. CONCLUSION: Lipopeptide concentration was improved 4.7‐fold by single‐dosing and 5.8‐fold by multiple dosing of Fe²⁺, when compared with GMSM without Fe²⁺ supplementation. Copyright © 2012 Society of Chemical Industry     

Propagation Characteristics of an Elliptically-cored Highly Birefringent Fiber using an Analytical Method

By using the method of separation of variables in the elliptical coordinate system, a representative formula in terms of Mathieu and modified Mathieu functions is derived and longitudinal field components for the even and odd modes are presented for the proposed fiber. The eigen value equation for the fiber to be considered is obtained by solving the fourth order determinantal equation under weak guidance condition and is given in this paper. The cutoff frequency of several lower orders modes for different eccentricities have been obtained and their propagation characteristics have been plotted. The effect of the eccentricity on the modal cutoff values and mode transmissions is discussed. Finally, the modal birefringence in the proposed fiber is also estimated.     

Life cycle cost analysis of HPVT air collector under different Indian climatic conditions

In this communication, a study is carried out to evaluate an annual thermal and exergy efficiency of a hybrid photovoltaic thermal (HPVT) air collector for different Indian climate conditions, of Srinagar, Mumbai, Jodhpur, New Delhi and Banglore. The study has been based on electrical, thermal and exergy output of the HPVT air collector. Further, the life cycle analysis in terms of cost/kWh has been carried out. The main focus of the study is to see the effect of interest rate, life of the HPVT air collector, subsidy, etc. on the cost/kWh HPVT air collector. A comparison is made keeping in view the energy matrices. The study reveals that (i) annual thermal and electrical efficiency decreases with increase in solar radiation and (ii) the cost/kWh is higher in case of exergy when compared with cost/kWh on the basis of thermal energy for all climate conditions. The cost/kWh for climate conditions of Jodhpur is most economical.