LIQUEFACTION OF ELBI˙STAN AND YATAĞAN LIGNITES I N CARBON MONOXIDE/HYDROGEN GAS MIXTURES

Abstract

Thc effects of experimental parameters on the liquefaction yields of Elbistan and Yatagan lignites vcre investigated by using different solvents, guses and catalysts.

In hydroliquefaction of Elbistan lignite with anthracene and creosote oils, higher oil yields were obtained with anthracene oil. Based on this result, anthracene oil was chosen as solvent for further work done with Elbistan lignite. First the effect of moisture in lignite samples vas observed with synthesis gas as medium gas: then, the effect of carbon monoxide/ hydrogen ratio in liquefaction gas mixture was determined using moist lignite samples. The highest oil yield was obtained with moist lignite sample in 3CO/IH₂gas mixture and it was 57.3 % (daf).

The hydroliquefaction oil yields of Yatagan lignite obtained with creosote oil were higher than those obtained in anthracene ail. On Further work done with Yatagan lignite, creosote oil was chosen as solvent. First, the effects of CoMo and red mud catalysts, then in catalyzed medium, the effects of moisture in lignite samples and at last, using moist lignite samples and red mud catalyst. the effects o f carbon monaxide/hydrogen in synthesis gas medium and also, the increase in the oil yield a s an effect of catalyst presence, increased further: the 3CO/lH, ratio in gas medium was suitable for obtaining higher oil yields; and also for obtaining high oil yields, 440°c could be taken a s the most suitable temperature value and the pressure should be increased a s much as technical and economical conditions permit.     

Development and application of a new multiplex real‐time PCR assay for simultaneous identification of Brucella melitensis,Cronobacter sakazakii and Listeria monocytogenes in raw milk and cheese

Brucella melitensis, Cronobacter sakazakii and Listeria monocytogenes are important foodborne pathogens in milk and milk products, which are responsible for a variety of diseases that pose serious hazards to public health and food safety. The objective of this study was to develop a novel multiplex RTi‐PCR for the detection of B. melitensis, C. sakazakii and L. monocytogenes and to characterise the potential risk of these pathogens in raw milk and cheese. The raw milk (n = 25) and cheese samples (n = 20) were analysed by multiplex RTi‐PCR assay and detected for quantification of the three pathogens. In this study, B. melitensis, C. sakazakii and L. monocytogenes were simultaneously identified using BMEII0466, mms operon and hly as target genes, respectively. The multiplex RTi‐PCR assay that was developed showed good sensitivity and selectivity for the pathogenic microorganisms (r² = 0.986–0.997). Multiplex RTi‐PCR results showed that most of the samples were contaminated with the pathogens screened.     

Effects of water extract of Urtica dioica L. and modified atmosphere packaging on the shelf life of ground beef

Effects of lyophilized Urtica dioica L. water extract (LUWE) and modified atmosphere packaging (MAP) on the quality and shelf life of ground beef were investigated. Ground beef was stored as aerobic control, MAP (80%O₂ + 20% CO₂), MAP + 250 ppm LUWE and MAP and 500 ppm LUWE at 2 ± 0.5 °C for 14 days. MAP and LUWE had significant effects on mesophilic, psychrotrophic and lactic acid bacteria and Pseudomonas counts. Depending on the level of LUWE, Pseudomonas and psychrotrophic counts decreased. Treatment with 500 ppm LUWE + MAP showed the lowest TBARS values compared to other groups during storage. 80% O₂-MAP increased TBARS values. Treatment had no significant effect on L* and b* values of the exterior of the ground beef, but had significant effects on the color of interior sections.     

Energy Loss at a Drop Structure with a Step at the Base

Abstract

The flow over a drop structure placed in a rectangular channel was investigated through an experimental program. It was noted that the downstream depth of flow was crucial to the formulation of the problem. Two procedures were developed for the estimation of the downstream depth. The first procedure was physically based with an empirical component for the estimation of the depth of the pool formed at the base of the drop. The second was a purely empirical procedure, which resulted in an equation for the direct estimation of the downstream depth. The parameters of the equation were determined by least-squares techniques. Both procedures resulted in reasonably accurate estimates of the downstream depth. The energy loss at the drop was then calculated and compared with the results of previous studies. The investigations were repeated with a single step placed at the base of the drop. It was observed that the step significantly increased the energy loss at the drop.     

Supply chain planning for hurricane response with wind speed information updates

This paper introduces a stochastic inventory control problem that is relevant to proactive disaster recovery planning as it relates to preparing for potential hurricane activity. In particular, we consider a manufacturing or retail organization who experiences demand surge for items such as flashlights, batteries, and gas-powered generators, where the magnitude of demand surge is influenced by various characteristics of an ensuing storm. The planning horizon begins during the initial stages of storm development, when a particular tropical depression or disturbance is first observed, and ends when the storm dissipates. Since hurricane characteristics can be predicted with more accuracy during the later stages of the planning horizon relative to the earlier stages, the inventory control problem is formulated as an optimal stopping problem with Bayesian updates, where the updates are based on hurricane predictions. A dynamic programming algorithm is described to solve the problem, and several examples involving real hurricane wind speed data are presented to illustrate the methodology.     

Approximate Methods for the Estimation of Muskingum Flood Routing Parameters

There are a variety of techniques for estimating the parameters x and K of the Muskingum method of flood routing. One common difficulty in all the approaches is that different storm sequences along the same river reach would typically yield different parameter estimates. The a statistical analysis of these parameters also shows that they are highly variable. As a result achieving of a high level accuracy may not be the principle issue in describing x and K. This paper presents two approximate methods for estimating these parameters rather easily. The first method requires the computation of the slopes of the inflow and outflow hydrographs at their point of intersection, and the computation of the maximum storage within the reach. The second method requires the computation of the inflow and outflow hydrographs at two specific points. Three case studies investigated show that the first method gives estimates for the Muskingum parameters comparable to those derived by traditional estimation procedures for hydrographs showing linear characteristics.     

Prediction of the non‐ideal detonation performance of commercial explosives using the DeNE and JWL++ codes

The non‐ideal detonation performance of two commercial explosives is determined using the DeNE and JWL++ codes. These two codes differ in that DeNE is based on a pseudo‐one‐dimensional theory which is valid on the central stream‐tube and capable of predicting the non‐ideal detonation characteristics of commercial explosives as a function of the explosive type, rock properties and blasthole diameter. On the other hand, JWL++ is a hydrocode running in a 2‐D arbitrary Lagrangian–Eulerian code with CALE‐like properties and can determine the flow properties in all stream lines within the reaction zone. The key flow properties (detonation velocity, pressure, specific volume, extent of reaction and reaction zone length) at the sonic locus on the charge axis have been compared. In general, it is shown that the flow parameters determined using both codes agree well. The pressure contours determined using the JWL++ are analysed in detail for two explosives at 165 mm blastholes confined in limestone and kimberlite with a view to further investigate the explosive/rock interface. The DeNE and JWL++ codes have been validated using the measured in‐hole detonation velocity data. Copyright © 2005 John Wiley & Sons, Ltd.     

Off-chip communication architectures for high throughput network processors

In this paper, we propose a new interconnection mechanism for network line cards. We project that the packet storage needs for the next-generation networks will be much higher. Such that the number of memory modules required to store the packets will be more than that can be directly connected to the network processor (NPU). In other words, the NPU I/O pins are limited and they do not scale well with the growing number of memory modules and processing elements employed on the network line cards. As a result, we propose to explore more suitable off-chip interconnect and communication mechanisms that will replace the existing systems and that will provide extraordinary high throughput. In particular, we investigate if the packet-switched k-ary n-cube networks can be a solution. To the best of our knowledge, this is the first time, the k-ary n-cube networks are used on a board. We investigate multiple k-ary n-cube based interconnects and include a variation of 2-ary 3-cube interconnect called the 3D-mesh. All of the k-ary n-cube interconnects include multiple, highly efficient techniques to route, switch, and control packet flows in order to minimize congestion spots and packet loss within the interconnects. We explore the tradeoffs between implementation constraints and performance. Performance results show that k-ary n-cube topologies significantly outperform the existing line card interconnects and they are able to sustain higher traffic loads. Furthermore, the 3D-mesh reaches the highest performance results of all interconnects and allows future scalability to adopt more memories and/or processors to increase the line card’s processing power.     

A Back-propagation Neural Network Landmine Detector Using the Delta-technique and S-statistic

Landmines are a major problem facing the world today; there are millions of these deadly weapons still buried in various countries around the world. Humanitarian organizations dedicate an immeasurable amount of time, effort, and money to find and remove as many of these mines as possible. Unfortunately, landmines can be made out of common materials which make the correct detection of them very difficult. This paper analyzes the effectiveness of combining certain statistical techniques with a neural network to improve detection. The detection method must not only detect the majority of landmines in the ground, it must also filter out as many of the false alarms as possible. This is the true challenge to developing landmine detection algorithms. Our approach combines a Back-Propagation Neural Network (BPNN) with statistical techniques and compares the performance of mine detection against the performance of the energy detector and the δ-technique. Our results show that the combination of the δ-technique and the S-statistics with a neural network improves the performance.