A FEATURE－BASED PRODUCT MODELLING SYSTEM ON PC （CASE STUDY OF PARTS DESIGN FOR PRESS MACHINE）

ＡＦＥＡＴＵＲＥ－ＢＡＳＥＤＰＲＯＤＵＣＴＭＯＤＥＬＬＩＮＧＳＹＳＴＥＭＯＮＰＣ（ＣＡＳＥＳＴＵＤＹＯＦＰＡＲＴＳＤＥＳＩＧＮＦＯＲＰＲＥＳＳＭＡＣＨＩＮＥ）ＹｏｎａｓＨａｇｏｓ；ＴｏｎｇＢｉｎｇｓｈｕＡｂｓｔｒａｃｔ：Ｔｈｉｓａｒｔｉｃｌｅｒｅｐｏ...     

Assessing the aptitude of vesicular volcanic rocks as pozzolanic sources for supplementary cementitious materials

Bulletin of Engineering Geology and the Environment - The research was conducted to verify two vesicular basalt deposits identified for pozzolanic sources. These are Wejerat site, in southern...     

Kinetic and CFD Modeling of Exhaust Gas Reforming of Natural Gas in a Catalytic Fixed-Bed Reactor for Spark Ignition Engines

Fuel reforming is an attractive method for performance enhancement of internal combustion engines fueled by natural gas, since the syngas can be generated inline from the reforming process. In this study, 1D and 2D steady-state modeling of exhaust gas reforming of natural gas in a catalytic fixed-bed reactor were conducted under different conditions. With increasing engine speed, methane conversion and hydrogen production increased. Similarly, increasing the fraction of recirculated exhaust gas resulted in higher consumption of methane and generation of H₂ and CO. Steam addition enhanced methane conversion. However, when the amount of steam exceeded that of methane, less hydrogen was produced. Increasing the wall temperature increased the methane conversion and reduced the H₂/CO ratio.     

Effect of fuel injection timing of hydrogen rich syngas augmented with methane in direct-injection spark-ignition engine

The product of gasification of solid biomass, also called syngas is believed to be good fuel for internal combustion engines in the move from the carbon based fuel to zero emission fuels. The only problem is its lower calorific value which is placed at one third of that of compressed natural gas (CNG). There are latest efforts to enhance the hydrogen rich syngas by augmenting it with methane so that the calorific value can be improved. This paper presents experimental results of the effect of the start of fuel injection timing (SOI) on the combustion characteristics, performance and emissions of a direct-injection spark-ignition engine fueled with a 20% methane augmented hydrogen rich syngas of molar ratio of 50% H₂ and 50% CO composition. The engine was operated at fully open throttle and the start of fuel injection (SOI) was varied at 90, 120 and 180° before top dead center (BTDC). The experiment was conducted at lean mixture conditions in the low and medium engine speed ranges (1500–2400 RPM). The spark advance was set to the minimum advance for a maximum brake torque in all the test parameters. The methane augmented hydrogen rich syngas was observed to perform well over wide range of operation with SOI = 180°CA BTDC. However, SOI = 120°CA BTDC performed well at lower speeds recording improved performance and emissions. Limitation of operable load was observed for both SOI = 120°CA BTDC and 90°CA BTDC due to an insufficient time for complete injection of fuel at lower relative air–fuel ratio (λ) with higher speeds.     

Improvements in hydrogen production from methane dry reforming on filament-shaped mesoporous alumina-supported cobalt nanocatalyst

The mesoporous gamma-alumina (γ-Al₂O₃) synthesized via evaporation-induced self-assembly method (EISA) using inorganic salt, Al(NO₃)₃·9H₂O precursor and water-ethanol solvent mixture was implemented as a support for Co catalyst in methane dry reforming at 973–1073 K under 1 atm. The γ-Al₂O₃ support possessed filament-shaped morphology with surface area of 173.4 m² g^?1 and cobalt nanoparticles were successfully dispersed on support with small crystallite size of 7.8 nm. The stability of 10%Co/Al₂O₃ was evident for CH₄ and CO₂ conversions at 1023 and 1073 K. CH₄ conversion could reach to 76.2% while 81.6% was observed for CO₂ conversion at 1073 K. Although graphitic and amorphous carbons were unavoidably formed on used catalyst, 10%Co/Al₂O₃ exhibited an outstanding performance comparable to noble metals with the desired ratio of H₂/CO for downstream Fischer-Tropsch process.     

An updated and expanded set of thermal property data for green roof growing media

Vegetated (green) roofs alter the roof surface energy balance and hence affect both building energy consumption and the transport of heat into the environment. Quantitative evaluation of the energetics of green roof systems requires accurate knowledge of the moisture-dependent thermal properties of the growing media. To support this need for data and to supplement previously published data we conducted a laboratory study to measure thermal conductivity, volumetric heat capacity, and thermal diffusivity of 12 green roof soil samples of varying composition. The results indicate that thermal properties vary significantly as a function of growing media design. Growing media incorporating expanded slate as their aggregate had thermal conductivities that were two to three times those of media that used a porous silica-based aggregate. Media incorporating expanded clay as the aggregate had thermal conductivities roughly in the middle of these extremes. In general the thermal conductivity nearly tripled as the growing media moisture levels were increased from relatively dry to saturated. Also, it was found that compaction typical of green roof systems that have been installed for multiple seasons can increase thermal conductivity of moist soils by 30-40% over their uncompressed values.     

A quantitative risk assessment model for Staphylococcus aureus and Salmonella associated with consumption of informally marketed milk products in Tigray,Ethiopia

The aim of this work was to collect relevant input data for integration into Monte-Carlo simulation using 10,000 iterations to obtain quantitative estimates of exposure and associated risk to Staphylococcus aureus and Salmonella. Higher prevalence rates of S. aureus (54.9 vs. 28.3%) and Salmonella (12.9 vs. 11.1%) were observed for raw milk distributed via collection milk collection centers (MCC) compared to those via dairy farms (DF). Prevalence found for S. aureus in traditionally fermented milk averaged only 3.7%. Although the 90% CI estimated probabilities of exposures to S. aureus due to DF and MCC raw milk consumption at levels higher than the D-R value found were 10.6 and 23.5%, respectively, exposures to Salmonella were within the pathogen's tolerable limit. While annual likely of risk of illness by S. aureus due to DF and MCC raw milk consumptions resulted in up to 24.2 and 48.3% estimated illnesses, respectively, traditionally fermented milk consumption was found very much less risky; and resulted only 2.5% estimated illnesses per-serving-per-year. The corresponding values for Salmonella per-serving-per-year estimated illnesses via raw milk sales are, respectively, 5.72 and 11.41% compared to 1.8 and 4.02% when they come in boiled forms.     

Inspiratory Off-Switch Mediated by Optogenetic Activation of Inhibitory Neurons in the preBötzinger Complex In Vivo

The role of inhibitory neurons in the respiratory network is a matter of ongoing debate. Conflicting and contradicting results are manifold and the question whether inhibitory neurons are essential for the generation of the respiratory rhythm as such is controversial. Inhibitory neurons are required in pulmonary reflexes for adapting the activity of the central respiratory network to the status of the lung and it is hypothesized that glycinergic neurons mediate the inspiratory off-switch. Over the years, optogenetic tools have been developed that allow for cell-specific activation of subsets of neurons in vitro and in vivo. In this study, we aimed to identify the effect of activation of inhibitory neurons in vivo. Here, we used a conditional transgenic mouse line that expresses Channelrhodopsin 2 in inhibitory neurons. A 200 µm multimode optical fiber ferrule was implanted in adult mice using stereotaxic surgery, allowing us to stimulate inhibitory, respiratory neurons within the core excitatory network in the preBötzinger complex of the ventrolateral medulla. We show that, in anesthetized mice, activation of inhibitory neurons by blue light (470 nm) continuously or with stimulation frequencies above 10 Hz results in a significant reduction of the respiratory rate, in some cases leading to complete cessation of breathing. However, a lower stimulation frequency (4–5 Hz) could induce a significant increase in the respiratory rate. This phenomenon can be explained by the resetting of the respiratory cycle, since stimulation during inspiration shortened the associated breath and thereby increased the respiratory rate, while stimulation during the expiratory interval reduced the respiratory rate. Taken together, these results support the concept that activation of inhibitory neurons mediates phase-switching by inhibiting excitatory rhythmogenic neurons in the preBötzinger complex.     

Syngas (H2/CO) in a spark-ignition direct-injection engine. Part 1: Combustion,performance and emissions comparison with CNG

The combustion, performance, and emissions of syngas (H₂/CO) in a four-stroke, direct-injection, spark-ignition engine were experimentally investigated. The engine was operated at various speeds, ranging from 1500 to 2400 rev/min, with the throttle being held in the wide-open position. The start of fuel injection was fixed at 180° before the top dead center, and the ignition advance was set at the maximal brake torque. The air/fuel ratio was varied from the technically possible lowest excess air ratio (λ) to lean operation limits. The results indicated that a wider air/fuel operating ratio is possible with syngas with a very low coefficient of variation. The syngas produced a higher in-cylinder peak pressure and heat-release rate peak and faster combustion than for CNG. However, CNG produced a higher brake thermal efficiency (BTE) and lower brake specific fuel consumption (BSFC). The BTE and BSFC of the syngas were on par to those of CNG at higher speeds. For the syngas, the total hydrocarbon emission was negligible at all load conditions, and the carbon monoxide emission was negligible at higher loads and increased under lower load conditions. However, the emission of nitrogen oxides was higher at higher loads with syngas.     

A Fuzzy-Stochastic Modeling Approach for Multiple Criteria Decision Analysis of Coupled Groundwater-Agricultural Systems

The complexity of water resources management increases when decisions about environmental and social issues are considered in addition to economic efficiency. Such complexities are further compounded by multiple uncertainties about the consequences of potential management decisions. In this paper, a new fuzzy-stochastic multiple criteria decision-making approach is proposed for water resources management in which a variety of criteria in terms of economic, environmental and social dimensions are identified and taken into account. The goal is to evaluate multiple conflicting criteria under uncertainties and to rank a set of management alternatives. The methodology uses a simulation-optimization water management model of a strongly interacting groundwater-agriculture system to enumerate criteria based on these bio-physical process interactions. Fuzzy and/or qualitative information regarding the decision-making process for which quantitative data is not available are evaluated in linguistic terms. Afterwards, Monte Carlo simulation is applied to combine these information and to generate a probabilistic decision matrix of management alternatives versus criteria in an uncertain environment. Based on this outcome, total performance values of the management alternatives are calculated using ordered weighted averaging. The proposed approach is applied to a real world example, where excessive groundwater withdrawal from the coastal aquifer for irrigated agriculture has resulted in saltwater intrusion, threatening the economical basis of farmers and associated societal impacts. The analysis has provided potential decision alternatives which can serve as a platform for negotiation and further exploration. Furthermore, sensitivity of different inputs to resulting rankings is investigated. It is found that decision makers’ risk aversion and risk taking attitude may yield different rankings. The presented approach suits to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management.