Distribution kinetics is a method to analyze polymer reactions kinetically in terms of the molecular-weight (or chain-length) distributions (MWDs) of components in a macromolecular mixture. Governing equations for temporal and spatial dependence of the MWDs are based on population balance equations (PBEs) for the distinguishable species. Moments of the MWDs are related to observable properties, such as average MW and polydispersity, and can be measured for polymeric systems by procedures such as size-exclusion chromatography. The moments are related mathematically to rate parameters in the PBEs. The distribution kinetics approach is thus a method for interpreting experimental observations of MWD dynamics in terms of chemical reaction mechanisms.
A hydrogen production process comprising a membrane reactor and a carbon dioxide separator for the steam reforming of methane at 500°C has been simulated without employing a sweep gas for hydrogen separation, while the one-pass conversion of methane with a membrane reactor is 35% or below. Recycling of the reaction gas increases the apparent conversion of methane, but the conversion is gradually saturated with increasing recycling ratio (molar ratio of recycled gas to feed gas) without carbon dioxide separation. Separation of carbon dioxide from the exit gas of the membrane reactor increases the apparent conversion of methane linearly with increasing recycling ratio and 100% conversion can be attained under conditions suitable for industrial operation.
The deformation characteristics of asphalt mixtures in the crossing direction during the wheel tracking test (1 h, 2500 passes) at high temperature were investigated using dense graded (13F) and drainage asphalt mixture. The two-dimensional movement of the aggregates due to the wheel load was analyzed by right angle photography of the specimen. The behavior of the aggregates was divided into three stages (first, second, and final stage). The aggregates in each mixture moved in the vertical direction under the load, which reflects consolidation of the asphalt mixture. The aggregates moved in the horizontal direction on the surface near the load, which reflects the flow of the asphalt mixture. The aggregates also moved with rotation in both regions. The net result was absence of movement. In addition, the volume change of the asphalt mixture caused by deformation of surface was closely related to the deformation just under the load in the first stage. The asphalt mixture after the wheel tracking test was cut to measure the density. The results showed that the density increased just under the load and decreased in the upper part of the surface near the load.
A genetic algorithm (GA), which is based on the theory of biological evolution, was applied to optimize the composition of Cu-Zn-Al-Sc oxide catalyst for methanol synthesis to identify high performance catalysts faster and more effectively. Using our own GA program where the activities from experiments were used as the fitness, we could almost optimize the composition by the fifth generation. The catalyst with maximum activity at the fifth generation had higher Cu/Zn ratio than conventional catalysts. The GA is a powerful tool to optimize catalyst composition.
Optimization of catalyst composition using a genetic algorithm (GA) is intended to increase the activity in a series of repetitive steps consisting of determination of the composition, catalyst preparation, activity test and feedback to the program. The laborious steps of catalyst preparation and activity test can be replaced by calculation provided that a radial basis function network (RBFN) trained using experimental results is used to evaluate the fitness of the catalyst code. Optimization of the Cu/Zn/Al/Sc ratio of mixed oxide catalyst for methanol synthesis from syngas was simulated. In the simulation, activity was calculated by equations fitted to some experimental results to evaluate the fitness for use in the genetic algorithm program. Data of catalyst composition for input and the STY for output totalling 69-92 points were necessary for successful mapping of the catalytic activity. The network then was trained using 92 experimental results. The highest activity of the catalyst optimized by GA and RBFN was higher than that optimized by GA only. The combination of catalyst design by genetic algorithm and the activity evaluation by RBFN is promising for highly efficient catalyst screening.
Methane decomposition was carried out using Fe/Al2O3 catalyst in the absence and presence of O2 and CO2. Even in the presence of O2 and CO2 (CH4/O2/CO2 = 80/10/5 vol ratio), the deactivation of Fe/Al2O3 catalyst at temperatures below 1100 K was caused mainly by accumulation of carbon products as well as oxidation of non-oxide iron species (α-Fe and Fe3C), as confirmed by X-ray diffraction, TG/DTA, and in-situ DRIFT-IR analyses. The stability of Fe/Al2O3 catalyst in the presence of O2 and CO2 was improved by the addition of some metals into the catalyst (M/Fe = 1/1 wt ratio). Methane conversion decreased monotonously from 95 to 79% after 6 h for Fe/Al2O3 catalyst. In contrast, the activity of Fe/Mg/Al2O3 catalyst at 973 K remained unchanged after 6 h (CH4 conversion 95%). This effect could be associated with the formation of MgFe2O4. The effectiveness of other metal additives on the catalyst stability was Ce, Y > Eu, La> Pr, none > V> Nb.
Increased demand for gas supply by industry in recent years has promoted the search for optimum strategies to evaluate the performance of dry gas and gas condensate reservoirs. Equations of state (EOS) have become a standard tool to predict the performance of these reservoirs. These EOS models are, however, highly dependent on accurate experimental data both to tune the EOS and to check their validity. The principal test of these is the constant volume depletion (CVD) experiment. Due to the design of PVT cells used, errors in CVD test data have continued to be noticed in some PVT reports. Therefore, better techniques are needed to improve the accuracy of these experimental tests, to support decision-making for gas and gas-condensate reservoirs. In this report, a new technique is proposed to correct the “most-suspicious” experimental data from CVD tests by using the results obtained from a partially tuned EOS package. This technique is applied to three CVD test data for gas-condensate samples collected from the gas cap of a major reservoir in the UAE.
The oil shale deposit survey requires testing of a number of oil shale samples. However, the Fischer assay can process only 4-5 samples a day, so the number of samples should be limited. Hence a quick method to screen the samples for the Fischer assay test is required. The automatic micro carbon residue (MCR) test is proposed as a quick and simple screening method which requires only 100 mg of sample. The MCR test, as specified in JIS K 2270 (modified ISO 10370), can predict the weight loss of oil shale samples in the Fischer assay. Although the MCR test provides only data on the weight loss of oil shale, 12 samples can be processed in 2-3 h, the structure and control are simple, the cost is relatively low, and the equipment is easy to use. There is a definite correlation between the upper limit of oil yield from oil shale and the weight loss of oil shale, so the MCR test can facilitate the rapid screening of a large number of oil shale samples.