Decay Rate Kinetics of Ozone Gas in Rice Grains

The present study was carried out to evaluate the effects of ozone on rice grains for the following three conditions: saturation time, decay rate, and half-life of ozone. Experiments were performed in different bed thicknesses (5 and 10 cm) and moisture content (11.4 and 14.2% wb) at atmospheric conditions. The lowest saturation time of ozone was 119 min, with the concentration of 516 ppm for rice grains ozonated at 5-cm bed thickness with 11.4% (wb) moisture content. The decay rate kinetics of ozone obtained were consistent with a first-order model. Regarding the half-life of ozone, the lowest value obtained was 6.78 min for rice grains ozonated at 10-cm bed thickness with 14.2% (wb) moisture content.     

A possibilistic clustering approach to novel fault detection and isolation

In this paper, a new approach for fault detection and isolation that is based on the possibilistic clustering algorithm is proposed. Fault detection and isolation (FDI) is shown here to be a pattern classification problem, which can be solved using clustering and classification techniques. A possibilistic clustering based approach is proposed here to address some of the shortcomings of the fuzzy c-means (FCM) algorithm. The probabilistic constraint imposed on the membership value in the FCM algorithm is relaxed in the possibilistic clustering algorithm. Because of this relaxation, the possibilistic approach is shown in this paper to give more consistent results in the context of the FDI tasks. The possibilistic clustering approach has also been used to detect novel fault scenarios, for which the data was not available while training. Fault signatures that change as a function of the fault intensities are represented as fault lines, which have been shown to be useful to classify faults that can manifest with different intensities. The proposed approach has been validated here through simulations involving a benchmark quadruple tank process and also through experimental case studies on the same setup. For large scale systems, it is proposed to use the possibilistic clustering based approach in the lower dimensional approximations generated by algorithms such as PCA. Towards this end, finally, we also demonstrate the key merits of the algorithm for plant wide monitoring study using a simulation of the benchmark Tennessee Eastman problem.     

国外战场雷达发展现状

本文介绍国外战场雷达的现状,包括轻小型化、武器定位及低空目标探测等几个方面。     

Data reduction algorithm based on principle of distributional equivalence for fault diagnosis

Historical data based fault diagnosis methods exploit two key strengths of multivariate statistical approaches, viz.: (i) data compression ability, and (ii) discriminatory ability. It has been shown that correspondence analysis (CA) is superior to principal components analysis (PCA) on both these counts (Detroja, Gudi, Patwardhan, & Roy, 2006a), and hence is more suited for the task of fault detection and isolation (FDI). In this paper, we propose a CA based methodology for fault diagnosis that can facilitate significant data reduction as well as better discrimination. The proposed methodology is based on the principle of distributional equivalence (PDE). The PDE is a property unique to the CA algorithm and can be very useful in analyzing large datasets. The principle, when applied to historical data sets for FDI, can significantly reduce the data matrix size without significantly affecting the discriminatory ability of the CA algorithm. This can significantly reduce computational load during statistical model building. The data reduction ability of the proposed methodology is demonstrated using a simulation case study involving benchmark quadruple tank laboratory process. The proposed methodology when applied to experimental data obtained from the quadruple tank process also demonstrated data reduction capabilities of the principle of distributional equivalence. The above aspect has also been validated for large-scale data sets using the benchmark Tennessee Eastman process simulation case study.     

Numerical Simulation and Validation of Ozone Concentration Profile in Green Gram (Vigna radiate) Bulks

The new fumigant ozone offers an alternative to contact insecticides such as phosphine and methyl bromide as a grain fumigant. This study was carried out to test the flow characteristics of ozone from points of release to the available concentration of ozone to kill pests at other areas along the storage bin. A mass transfer model which predicts ozone concentration as a function of time was applied along with continuity equation to simulate the ozone transfer in a storage bin. Ozone exchange rate based on grain bed thickness was taken into account and evaluated using the correlation developed during the experiment. The relative error between the experimental and predicted ozone concentration values for the entire bin geometry was less than 25.7%. Overall, the general trends of measured ozone concentration were compatible with the simulated ones.     

An improved tri-reforming based methanol production process for enhanced CO2 valorization

The consistent rise of CO₂ concentration in the atmosphere is known to be significantly detrimental to the environment. Thus, mitigating CO₂ has become an urgent necessity. Current methods involving CO₂ mitigation can be broadly divided into two major categories which involve (i) CO₂ capture and sequestration (CCS) and (ii) CO₂ capture and valorization. Since, production of fuels/chemicals is an added feature along with mitigation in CO₂ valorization based methods, they could be economically favorable. An energy intensive CO₂ capture step is a common drawback of most CO₂ valorization methods that aim to mitigate CO₂ from major CO₂ emission sources (such as industrial flue gases). In this paper we employ and analyze a relatively new process called tri-reforming [1,2] which was developed to directly convert power plant based flue gases to synthesis gas, while avoiding the capture step. This paper is presented as an improvement over a tri-reforming coupled methanol production process as developed by Zhang et al. [3]. The process in Zhang et al. [3] involves utilizing tri-reforming process using flue gas and methane to produce synthesis gas which is then converted to methanol in the next step. The main contributions of this paper to the tri-reforming coupled methanol production process are: (i) proposition of a high pressure tri-reforming step to limit capital costs of the process (ii) establishment of steam input coupled with water separation step as a process improvement whose impact is shown to further amplify at higher tri-reformer pressures. The paper evaluates the process in terms of the profit generating and CO₂ valorization potential of the process as reflected by two parameters, gross margin (GM) and NPCV (net percentage of CO₂ valorized) respectively. In the proposed approach, higher pressures were utilized in the tri-reforming process to ensure economic feasibility of the process by limiting the reactor volume. The process improvements for the flowsheet containing the steam input combined with water separation (SWS) step over the one without these steps (termed as WSWS) are demonstrated in terms of an increase in GM/NPCV values at various pressures. The results indicate substantial improvements in GM and NPCV values (especially at higher tri-reformer pressures) ranging from 24.30 to 84.96% and 28.80–78.44% respectively in SWS cases over WSWS cases at various pressures. The simulations have been carried out in Aspen Plus V8.4 and are optimized using sensitivity analysis.     

Rotational molding of polyethylene composites based on agave fibers

In this study, agave fiber/linear medium density polyethylene composites were manufactured by rotational molding. A laboratory scale biaxial machine was used, where the internal air temperature during the processing cycle was measured. Two sizes of agave fibers (50 and 100 mesh) were used separately and mixed together (50/50) at concentrations varying between 0 and 15 wt%. The initial mixtures were obtained by dry blending, rotomolded under different operation conditions (oven temperature, processing cycle time, and rotational speeds), and the final pieces were compared. For each process condition, a complete morphological analysis was performed to relate with mechanical properties in terms of tensile, impact, and flexural strength. The results show that there is an optimum fiber concentration around 10%, and blending fiber sizes gave better tensile properties than using each size alone. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

Polar classification with correspondence analysis for fault isolation

Data collected from operating plants can be mined to extract information related to both normal and fault modes of operation. Correspondence analysis (CA), that decomposes a measure of row–column association, to generate the lower dimensional space has been recently proposed [1] for this task. CA represents the association between samples and variables in terms of angle based measures on a biplot. Thus, toward clearer resolution of the faults, polar clustering and classification procedures are necessary. In this paper, we develop a methodology to mine the operating data and build such clusters. We demonstrate the application of this methodology on data generated from simulations and experiments involving representative systems,for detecting parametric changes and resolving sensor and actuator biases.     

Yield of hydrogen during cathodic polarisation of Al–Sn alloys

The results presented in this paper were obtained with three Al–Sn binary alloys (0.09, 0.2 and 0.4 wt.% Sn, respectively) that had been prepared on super pure (99.999%) Al base. The yield of hydrogen evolved during cathodic polarisation of Al–Sn alloys in a 2 M NaCl solution was measured volumetrically as a function of current density, temperature and tin content in the alloy. The yield was established to be somewhat below 2 at all current densities and at low temperatures, while with increasing temperature it approached the value of 4. With the increase of tin content in the alloy, the yield of hydrogen decreases, which depends on the degree of hyperactivity that occurs in Al–Sn alloys in the region of high cathodic potentials.