Prediction of hydrate equilibrium conditions using k-nearest neighbor algorithm to CO2 capture

Gas or clathrate hydrates are an important issue when they form in the oil and gas pipelines. Since the determination of the hydrate formation temperature and pressure is very difficult experimentally for every gas system and it is impossible in terms of cost and time approximately, mathematical models can be useful tools to overcome these difficulties. In this study, k-nearest neighbor model was used to predict the equilibrium conditions of hydrate formation in absorption and separation of carbon dioxide from flue gas mixture, containing carbon dioxide and nitrogen. At the training phase, temperature and composition data of nitrogen and carbon dioxide in the flue gas mixture at equilibrium conditions and the equilibrium pressures of hydrate formation were used as input and output, respectively. The error percentage less than 0.38% indicates the high accuracy of the proposed model. In this study, 80%, 85%, and 90% of the training data are examined for three numbers of nearest. For three numbers of used nearest (k = 1, k = 2 and k = 3), the value of k = 1 leads to the lowest error; so, it is selected as the best nearest in the presented model.     

Economic and economic-statistical designs of MEWMA control charts—a hybrid Taguchi loss, Markov chain, and genetic algorithm approach

Economic design of multivariate exponentially weighted moving average (MEWMA) control charts for monitoring the process mean vector involves determining economically the optimum values of the three control parameters: the sample size, the sampling interval between successive samples, and the control limits or the critical region of the chart. In the economic-statistical design, constraints (including the requirements of type I error probability and power) are added such that the statistical property of the chart is satisfied. In this paper, using the multivariate Taguchi loss approach, the Lorenzen–Vance (Technometrics 28:3-10, 1) cost function of implementing the control chart is extended to include intangible external costs along with the in-control average run length (ARL₀) and out-of-control average run length (ARL₁) as statistical constraints. A Markov chain model is then developed to estimate the ARLs and a genetic algorithm whose parameters are optimally obtained by design of experiments is used to solve the model and estimate the optimum values of the control chart parameters. A numerical example and a sensitivity analysis are provided to illustrate the solution procedure and to investigate the effects of cost parameters on the optimal designs. The results show that the proposed economic-statistical design of the chart has better statistical properties in comparison to the economic design while the difference between the costs is negligible.     

Numerical study of n-heptane/benzene separation by thermal diffusion column

In this article,numerical simulations are performed to investigate the performance of the thermal diffusion column for the separation of n-heptane/benzene mixture.The present work tried to optimize column by analyzing significant parameters such as feed flow rate,temperature and cut.In order to obtain the hydrodynamic and temperature and mass distribution inside thermal diffusion column,computational fluid dynamic(CFD) method is applied to solve the Navier-Stocks equations.Numerical simulations are conducted to study the main parameters in both stationary and time-dependent conditions.By using the separation work unit as a function of cut,the optimal cut for maximum SWU occurs within a limited range of 0.47-0.5 for feed rate between 0.5 and 4 g min-1.Our findings reveal that the optimum feed rate in the range of optimum cut is about 1 g min~(-1).In transient study,results show that the best cut for reaching to steady-state condition is θ=0.5.     

Acrylamide in Foods: Chemistry and Analysis. A Review

Acrylamide is a potential cause of a wide spectrum of toxic effects and is classified as probably “carcinogenic in humans”. The discovery of acrylamide in human foods has given rise to extensive studies exploring its formation mechanisms and levels of exposure and has spurred search into suitable analytical procedures for its determination in foodstuffs. However, the exact chemical mechanisms governing acrylamide formation are not yet known and cheap, convenient, and rapid screening methods are still to be developed. Acrylamide in food is produced by heat-induced reactions between the amino group of asparagine and the carbonyl group of reducing sugars along with thermal treatment of early Maillard reaction products (N-glycosides). Similarly, the decarboxylated Schiff base and decarboxylated Amadori compounds of asparagine as well as the Strecker aldehyde have been proposed as direct precursors and intermediates of acrylamide. Corresponding chromatographic methods are used to determine various structural groups present in Maillard reaction model systems. Gas chromatography-mass spectrometry and liquid chromatography with tandem mass spectrometry analysis are both acknowledged as the main, useful, and authoritative methods for acrylamide determination. This review is an attempt to summarize the state-of-the-art knowledge of acrylamide chemistry, formation mechanisms, and analytical methods. Special attention is given to comparison of different chromatographic techniques, particularly the novel, simple, and low-cost methods of its determination.     

Improved impossible differential and biclique cryptanalysis of HIGHT

HIGHT is a lightweight block cipher introduced in CHES 2006 by Hong et al as a block cipher suitable for low‐resource applications. In this paper, we propose improved impossible differential and biclique attacks on HIGHT block cipher both exploiting the permutation‐based property of the cipher's key schedule algorithm as well as its low diffusion. For impossible differential attack, we found a new 17‐round impossible differential characteristic that enables us to propose a new 27‐round impossible differential attack. The total time complexity of the attack is 2^120.4 where an amount of 2^59.3 chosen plaintext‐ciphertext pairs and 2^107.4 memory are required. We also instantiate a new biclique cryptanalysis of HIGHT, which is based on the new idea of splitting each of the forward and backward keys into 2 parts where the computations associated to each one are performed independently. The time complexity and data complexity of this attack are 2^125.7 and 2⁴², respectively. To the best of our knowledge, this is the fastest biclique attack on full‐round HIGHT.     

Phase Transformation Kinetics During Annealing of Cold-Rolled AISI 309Si Stainless Steel

Metallurgical and Materials Transactions A - The effects of cold rolling and the subsequent annealing were studied for the AISI 309Si stainless steel. During annealing of cold-rolled sheets, the...     

Generalized carrier to interference ratio analysis for shotgun cellular systems in multiple dimensions over composite Rayleigh–Lognormal (Suzuki) fading

Telecommunication Systems - This paper analyzes the carrier-to-interference ratio (CIR) of the so-called shotgun cellular systems (SCSs) in $$\tau $$ dimensions ( $$\tau =1, 2,$$ and 3). SCSs are...     

New Approaches for Estimation of Monthly Rainfall Based on GEP-ARCH and ANN-ARCH Hybrid Models

Accurate estimation of rainfall has an important role in the optimal water resources management, as well as hydrological and climatological studies. In the present study, two novel types of hybrid models, namely gene expression programming-autoregressive conditional heteroscedasticity (GEP-ARCH) and artificial neural networks-autoregressive conditional heteroscedasticity (ANN-ARCH) are introduced to estimate monthly rainfall time series. To fulfill this purpose, five stations with various climatic conditions were selected in Iran. The lagged monthly rainfall data was utilized to develop the different GEP and ANN scenarios. The performance of proposed hybrid models was compared to the GEP and ANN models using root mean square error (RMSE) and coefficient of determination (R²). The results show that the proposed GEP-ARCH and ANN-ARCH models give a much better performance than the GEP and ANN in all of the studied stations with various climates. Furthermore, the ANN-ARCH model generally presents better performance in comparison with the GEP-ARCH model.