Search results for: system decomposition

Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

Abstract:

Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

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The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT

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Authors: Onyekachi Ogbonnaya Iroanya, Taiye Abdullahi Gegele, Frank Tochukwu Egwuatu

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Introduction: Forensic taphonomy is a multifaceted area that incorporates decomposition, chemical and biological cadaver exposure in post-mortem event chronology and reconstruction to predict the Post Mortem Interval (PMI). The aim of this study was to evaluate the integrity of DNA extracted from the remains of embalmed decomposed Sus domesticus tissues buried in different soil types. Method: A total of 12 limbs of Sus domesticus weighing between 0.7-1.4 kg were used. Each of the samples across the groups was treated with 10% formaldehyde, absolute methanol and 50% Pine oil for 24 hours before burial except the control samples, which were buried immediately. All samples were buried in shallow simulated Clay, Sandy and Loamy soil graves for 12 months. The DNA for each sample was extracted and quantified with Nanodrop Spectrophotometer (6305 JENWAY spectrometers). The rate of decomposition was examined through the modified qualitative decomposition analysis. Extracted DNA was amplified through PCR and bands visualized via gel electrophoresis. A biochemical enzyme assay was done for each burial grave soil. Result: The limbs in all burial groups had lost weight over the burial period. There was a significant increase in the soil urease level in the samples preserved in formaldehyde across the 3 soil type groups (p≤0.01). Also, the control grave soils recorded significantly higher alkaline phosphatase, dehydrogenase and calcium carbonate values compared to experimental grave soils (p≤0.01). The experimental samples showed a significant decrease in DNA concentration and purity when compared to the control groups (p≤0.01). Obtained findings of the soil biochemical analysis showed the embalming treatment altered the relationship between organic matter decomposition and soil biochemical properties as observed in the fluctuations that were recorded in the soil biochemical parameters. The PCR amplified DNA showed no bands on the gel electrophoresis plates. Conclusion: In criminal investigations, factors such as burial grave soil, grave soil biochemical properties, antemortem exposure to embalming chemicals should be considered in post-mortem interval (PMI) determination.

Keywords: forensic taphonomy, post-mortem interval (PMI), embalmment, decomposition, grave soil

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Authors: A. S. Al-Fatesh, A. A. Ibrahim, A. M. AlSharekh, F. S. Alqahtani, S. O. Kasim, A. H. Fakeeha

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Hydrogen is the expected future fuel since it produces energy without any pollution. It can be used as a fuel directly or through the fuel cell. It is also used in chemical and petrochemical industry as reducing agent or in hydrogenation processes. It is produced by different methods such as reforming of hydrocarbon, electrolytic method and methane decomposition. The objective of the present paper is to study the decomposition of methane reaction at 700°C and 800°C. The catalysts were prepared via impregnation method using 20%Fe and different proportions of combined alumina and silica support using the following ratios [100%, 90%, 80%, and 0% Al₂O₃/SiO₂]. The prepared catalysts were calcined and activated at 600 OC and 500 OC respectively. The reaction was carried out in fixed bed reactor at atmospheric pressure using 0.3g of catalyst and feed gas ratio of 1.5/1 CH₄/N₂ with a total flow rate 25 mL/min. Catalyst characterizations (TPR, TGA, BET, XRD, etc.) have been employed to study the behavior of catalysts before and after the reaction. Moreover, a brief description of the weight loss and the CH₄ conversions versus time on stream relating the different support ratios over 20%Fe/Al₂O₃/SiO₂ catalysts has been added as well. The results of TGA analysis provided higher weights losses for catalysts operated at 700°C than 800°C. For the 90% Al₂O₃/SiO₂, the activity decreases with the time on stream using 800°C reaction temperature from 73.9% initial CH₄ conversion to 46.3% for a period of 300min, whereas the activity for the same catalyst increases from 47.1% to 64.8% when 700°C reaction temperature is employed. Likewise, for 80% Al₂O₃/SiO₂ the trend of activity is similar to that of 90% Al₂O₃/SiO₂ but with a different rate of activity variation. It can be inferred from the activity results that the ratio of Al₂O₃ to SiO₂ is crucial and it is directly proportional with the activity. Whenever the Al/Si ratio decreases the activity declines. Indeed, the CH₄ conversion of 100% SiO₂ support was less than 5%.

Keywords: Al₂O₃, SiO₂, CH₄ decomposition, hydrogen, iron

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Authors: Michael Tupý, Jaroslav Císař, Pavel Mokrejš, Dagmar Měřínská, Alice Tesaříková-Svobodová

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The worldwide problem is that the recycled PVB is wildly stored in landfills. However, PVB have very similar chemical properties such as PVC. Moreover, both of them are used in plasticized form. Thus, the thermal properties of plasticized PVC obtained from primary production and the PVB was obtained by recycling of windshields are compared. It is carried out in order to find degradable conditions and decide if blend of PVB/PVC can be processable together. Tested PVC contained 38 % of plasticizer diisononyl phthalate (DINP) and PVB was plasticized with 28 % of triethylene glycol, bis(2-ethylhexanoate) (3GO). Thermal and thermo-oxidative decomposition of both vinyl polymers are compared such as DSC and OOT analysis. The tensile strength analysis is added.

Keywords: polyvinyl chloride, polyvinyl butyral, recycling, reprocessing, thermal analysis, decomposition

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Authors: Nada R. Abuknesha, John P. Morgan, Andrew J. Searle

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Information regarding post-mortem interval (PMI) in criminal investigations is vital to establish a time frame when reconstructing events. PMI is defined as the time period that has elapsed between the occurrence of death and the discovery of the corpse. Adipocere, commonly referred to as ‘grave-wax’, is formed when post-mortem adipose tissue is converted into a solid material that is heavily comprised of fatty acids. Adipocere is of interest to forensic anthropologists, as its formation is able to slow down the decomposition process. Therefore, analysing the changes in the patterns of fatty acids during the early decomposition process may be able to estimate the period of burial, and hence the PMI. The current study concerned the investigation of the fatty acid composition and patterns in buried pig fat tissue. This was in an attempt to determine whether particular patterns of fatty acid composition can be shown to be associated with the duration of the burial, and hence may be used to estimate PMI. The use of adipose tissue from the abdominal region of domestic pigs (Sus-scrofa), was used to model the human decomposition process. 17 x 20cm piece of pork belly was buried in a shallow artificial grave, and weekly samples (n=3) from the buried pig fat tissue were collected over an 11-week period. Marker fatty acids: palmitic (C16:0), oleic (C18:1n-9) and linoleic (C18:2n-6) acid were extracted from the buried pig fat tissue and analysed as fatty acid methyl esters using the gas chromatography system. Levels of the marker fatty acids were quantified from their respective standards. The concentrations of C16:0 (69.2 mg/mL) and C18:1n-9 (44.3 mg/mL) from time zero exhibited significant fluctuations during the burial period. Levels rose (116 and 60.2 mg/mL, respectively) and fell starting from the second week to reach 19.3 and 18.3 mg/mL, respectively at week 6. Levels showed another increase at week 9 (66.3 and 44.1 mg/mL, respectively) followed by gradual decrease at week 10 (20.4 and 18.5 mg/mL, respectively). A sharp increase was observed in the final week (131.2 and 61.1 mg/mL, respectively). Conversely, the levels of C18:2n-6 remained more or less constant throughout the study. In addition to fluctuations in the concentrations, several new fatty acids appeared in the latter weeks. Other fatty acids which were detectable in the time zero sample, were lost in the latter weeks. There are several probable opportunities to utilise fatty acid analysis as a basic technique for approximating PMI: the quantification of marker fatty acids and the detection of selected fatty acids that either disappear or appear during the burial period. This pilot study indicates that this may be a potential semi-quantitative methodology for determining the PMI. Ideally, the analysis of particular fatty acid patterns in the early stages of decomposition could be an additional tool to the already available techniques or methods in improving the overall processes in estimating PMI of a corpse.

Keywords: adipocere, fatty acids, gas chromatography, post-mortem interval

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Authors: Sushil Kumar Saraswat, K. K. Pant

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Co metal supported on SiO2 and Al2O3 catalysts with a metal loading varied from 30 of 70 wt.% were evaluated for decomposition of methane to CO/CO2 free hydrogen and carbon nano materials. The catalytic runs were carried out from 550-800 oC under atmospheric pressure using fixed bed vertical flow reactor. The fresh and spent catalysts were characterized by BET surface area analyzer, TPR, XRD, SEM, TEM, and TG analysis. The data showed that 50% Co/Al2O3 catalyst exhibited remarkable higher activity and stability up to 10 h time-on-stream at 750 oC with respect to H2 production compared to rest of the catalysts. However, the catalytic activity and durability was greatly declined at a higher temperature. The main reason for the catalytic inhibition of Co containing SiO2 catalysts is the higher reduction temperature of Co2SiO4. TEM images illustrate that the carbon materials with various morphologies, carbon nanofibers (CNFs), helical-shaped CNFs, and branched CNFs depending on the catalyst composition and reaction temperature, were obtained. The TG data showed that a higher yield of MWCNTs was achieved over 50% Co/Al2O3 catalyst compared to other catalysts.

Keywords: carbon nanotubes, cobalt, hydrogen production, methane decomposition

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Authors: Jina Lee

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Methane gas is a common byproduct in any process of rot and degradation of organic matter. This gas, when decomposition occurs, is emitted directly into the atmosphere. Methane is the simplest alkane hydrocarbon that exists. Its chemical formula is CH₄. This means that there are four atoms of hydrogen and one of carbon, which is linked by covalent bonds. Methane is found in nature in the form of gas at normal temperatures and pressures. In addition, it is colorless and odorless, despite being produced by the rot of plants. It is a non-toxic gas, and the only real danger is that of burns if it were to ignite. There are several ways to generate methane gas in homes, and the amount of methane gas generated by the decomposition of organic matter varies depending on the type of matter in question. An experiment was designed to measure the efficiency, such as a relationship between the amount of raw material and the amount of gas generated, of three different mixtures of organic matter: 1. food remains of home; 2. animal waste (excrement) 3. equal parts mixing of food debris and animal waste. The results allowed us to conclude which of the three mixtures is the one that grants the highest efficiency in methane gas generation and which would be the most suitable for methane gas generation systems for homes in order to occupy less space generating an equal amount of gas.

Keywords: alternative energy source, energy conversion, methane gas conversion system, waste management

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Authors: Hwan-Jun Choi, Sung-Bok Choi, Hyoung-Kyu Song

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Recently, among the MIMO-OFDM detection techniques, a lot of papers suggested V-BLAST scheme which can achieve high data rate. Therefore, the signal detection of MIMOOFDM system is important issue. In this paper, efficient iterative VBLAST detection technique is proposed in wireless communication system. The proposed scheme adjusts the number of candidate symbol and iterative scheme based on channel state. According to the simulation result, the proposed scheme has better BER performance than conventional schemes and similar BER performance of the QRD-M with iterative scheme. Moreover complexity of proposed scheme has 50.6 % less than complexity of QRD-M detection with iterative scheme. Therefore the proposed detection scheme can be efficiently used in wireless communication.

Keywords: MIMO-OFDM, V-BLAST, QR-decomposition, QRDM, DFE, iterative scheme, channel condition

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Authors: Kirill D. Semavin, Norbert S. Chilingarov, Eugene.V. Skokan

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The ionic liquids (ILs) based on imidazolium cation are well known nowadays. The changing anions and substituents in imidazolium ring may lead to different physical and chemical properties of ILs. It is important that such ILs with halogen as anion are characterized by a low thermal stability. The data about thermal stability of 1-ethyl-3-methylimidazolium chloride are ambiguous. In the works of last years, thermal stability of this IL was investigated by thermogravimetric analysis and obtained results are contradictory. Moreover, in the last study, it was shown that the observed temperature of the beginning of decomposition significantly depends on the experimental conditions, for example, the heating rate of the sample. The vapor pressure of this IL is not presented at the literature. In this study, the vapor pressure of 1-ethyl-3-methylimidazolium chloride was obtained by Knudsen effusion mass-spectrometry (KEMS). The samples of [ЕMIm]Cl (purity > 98%) were supplied by Sigma–Aldrich and were additionally dried at dynamic vacuum (T = 60 0C). Preliminary procedures with Il were derived into glove box. The evaporation studies of [ЕMIm]Cl were carried out by KEMS with using original research equipment based on commercial MI1201 magnetic mass spectrometer. The stainless steel effusion cell had an effective evaporation/effusion area ratio of more than 6000. The cell temperature, measured by a Pt/Pt−Rh (10%) thermocouple, was controlled by a Termodat 128K5 device with an accuracy of ±1 K. In first step of this study, the optimal temperature of experiment and heating rate of samples were customized: 449 K and 5 K/min, respectively. In these conditions the sample is decomposed, but the experimental measurements of the vapor pressures are possible. The thermodynamic activity of [ЕMIm]Cl is close to 1 and products of decomposition don’t affect it at firstly 50 hours of experiment. Therefore, it lets to determine the saturated vapor pressure of IL. The electronic ionization mass-spectra shows that the decomposition of [ЕMIm]Cl proceeds with two ways. Nonetheless, the MALDI mass spectra of the starting sample and residue in the cell were similar. It means that the main decomposition products are gaseous under experimental conditions. This result allows us to obtain information about the kinetics of [ЕMIm]Cl decomposition. Thus, the original KEMS-based procedure made it possible to determine the IL vapor pressure under decomposition conditions. Also, the loss of sample mass due to the evaporation was obtained.

Keywords: ionic liquids, Knudsen effusion mass spectrometry, thermal stability, vapor pressure

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Authors: Toufik Bensana, Medkour Mihoub, Slimane Mekhilef

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally nonstationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA), and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, rolling element bearing, local mean decomposition, condition monitoring

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Authors: Hassan Manouzi

Abstract:

We present in this paper a useful strategy to solve stochastic partial differential equations (SPDEs) involving stochastic coefficients. Using the Wick-product of higher order and the Wiener-Itˆo chaos expansion, the SPDEs is reformulated as a large system of deterministic partial differential equations. To reduce the computational complexity of this system, we shall use a decomposition-coordination method. To obtain the chaos coefficients in the corresponding deterministic equations, we use a least square formulation. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated.

Keywords: least squares, wick product, SPDEs, finite element, wiener chaos expansion, gradient method

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Authors: Nor Mazlin Zahari, Lian Gan, Xuerui Mao

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The power production in wind farms and the mechanical loads on the turbines are strongly impacted by the wake of the wind turbine. Thus, there is a need for understanding and modelling the turbine wake dynamic in the wind farm and the layout optimization. Having a good wake model is important in predicting plant performance and understanding fatigue loads. In this paper, the Dynamic Mode Decomposition (DMD) was applied to the simulation data generated by a Direct Numerical Simulation (DNS) of flow around a turbine, perturbed by upstream inflow noise. This technique is useful in analyzing the wake flow, to predict its future states and to reflect flow dynamics associated with the coherent structures behind wind turbine wake flow. DMD was employed to describe the dynamic of the flow around turbine from the DNS data. Since the DNS data comes with the unstructured meshes and non-uniform grid, the interpolation of each occurring within each element in the data to obtain an evenly spaced mesh was performed before the DMD was applied. DMD analyses were able to tell us characteristics of the travelling waves behind the turbine, e.g. the dominant helical flow structures and the corresponding frequencies. As the result, the dominant frequency will be detected, and the associated spatial structure will be identified. The dynamic mode which represented the coherent structure will be presented.

Keywords: coherent structure, Direct Numerical Simulation (DNS), dominant frequency, Dynamic Mode Decomposition (DMD)

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Authors: Charles Lee

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The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

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Authors: Geraldine Giraldo

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In the research of advanced materials, ceramics based on KNN are an important topic, especially for multifunctional applications. In this work, the physical, structural, and microstructural properties of the (KNN-CaLi-xSm) system were analyzed by varying the concentration of samarium, which was prepared using the conventional solid-state reaction method by mixing oxides. It was found that the increase in Sm+3 concentration led to higher porosity in the sample and, consequently, a decrease in density, which is attributed to the structural vacancies at the A-sites of the perovskite-type structure of the ceramic system. In the structural analysis, a coexistence of Tetragonal (T) and Orthorhombic (O) phases were observed at different rare-earth ion contents, with a higher content of the T phase at xSm=0.010. Furthermore, the structural changes in the calcined powders at different temperatures were studied using the results of DTA-TG, which allowed for the analysis of the system's composition. It was found that the lowest total decomposition temperature occurred when xSm=0.010 at 770°C.

Keywords: perovskite, piezoelectric, multifunctional, Structure, ceramic

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Authors: Yousef M. Al-Roomi, Kaneez Fatema Hussain

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This work evaluates the thermal degradation kinetic parameters of CaSO₄-complex isolated after the inhibition effect of maleic-anhydride based polymer (YMR-polymers). Pyrolysis experiments were carried out at four heating rates (5, 10, 15 and 20°C/min). Several analytical model-free methods were used to determine the kinetic parameters, including Friedman, Coats and Redfern, Kissinger, Flynn-Wall-Ozawa and Kissinger-Akahira–Sunose methods. The Criado model fitting method based on real mechanism followed in thermal degradation of the complex has been applied to explain the degradation mechanism of CaSO₄-complex. In addition, a simple dynamic model was proposed over two temperature ranges for successive decomposition of CaSO₄-complex which has a combination of organic and inorganic part (adsorbed polymer + CaSO₄.2H₂O scale). The model developed enabled the assessment of pre-exponential factor (A) and apparent activation-energy (Eₐ) for both stages independently using a mathematical developed expression based on an integral solution. The unique reaction mechanism approach applied in this study showed that (Eₐ₁-160.5 kJ/mole) for organic decomposition (adsorbed polymer stage-I) has been lower than Eₐ₂-388 kJ/mole for the CaSO₄ decomposition (inorganic stage-II). Further adsorbed YMR-antiscalant not only reduced the decomposition temperature of CaSO₄-complex compared to CaSO₄-blank (CaSO₄.2H₂O scales in the absence of YMR-polymer) but also distorted the crystal lattice of the organic complex of CaSO₄ precipitates, destroying their compact and regular crystal structures observed from XRD and SEM studies.

Keywords: CaSO₄-complex, maleic-anhydride polymers, thermal degradation kinetics and mechanism, XRD and SEM studies

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Authors: Hassan Manouzi, Taous-Meriem Laleg-Kirati

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In this paper we study mathematically the eigenvalue problem for stochastic elliptic partial differential equation of Wick type. Using the Wick-product and the Wiener-Ito chaos expansion, the stochastic eigenvalue problem is reformulated as a system of an eigenvalue problem for a deterministic partial differential equation and elliptic partial differential equations by using the Fredholm alternative. To reduce the computational complexity of this system, we shall use a decomposition-coordination method. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated.

Keywords: eigenvalue problem, Wick product, SPDEs, finite element, Wiener-Ito chaos expansion

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Pritika Ramharack, Mahmoud E. S. Soliman

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The re-emerging Zika virus is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus already been linked to irreversible chronic central nervous system (CNS) conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA-approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of Zika virus Methyltransferase and RNA-dependent RNA polymerase. This in silico “per-residue energy decomposition pharmacophore” virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.

Keywords: NS5 protein inhibitors, per-residue decomposition, pharmacophore model, virtual screening, Zika virus

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Authors: Anthony R. Hassan, Jacob A. Gbadeyan

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In this paper, the analysis of a reactive hydromagnetic Poiseuille fluid flow under each of sensitized, Arrhenius and bimolecular chemical kinetics through a channel in the presence of heat source is carried out. An exothermic reaction is assumed while the concentration of the material is neglected. Adomian Decomposition Method (ADM) together with Pade Approximation is used to obtain the solutions of the governing nonlinear non – dimensional differential equations. Effects of various physical parameters on the velocity and temperature fields of the fluid flow are investigated. The entropy generation analysis and the conditions for thermal criticality are also presented.

Keywords: chemical kinetics, entropy generation, thermal criticality, adomian decomposition method (ADM) and pade approximation

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Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

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It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

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Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab

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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.

Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover

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Authors: Gudakesh Yadav

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Uttar Pradesh is one of the poorest performing states of India in terms of child health. Using data from the three round of NFHS and two rounds of DLHS, this paper attempts to examine tempo-spatial change in child health and care practices in Uttar Pradesh and its regions. Rate-ratio, CI, multivariate, and decomposition analysis has been used for the study. Findings demonstrate that child health care practices have improved over the time in all regions of the state. However; western and southern region registered the lowest progress in child immunization. Nevertheless, there is no decline in prevalence of diarrhea and ARI over the period, and it remains critically high in the western and southern region. These regions also poorly performed in giving ORS, diarrhoea and ARI treatment. Public health services are least preferred for diarrhoea and ARI treatment. Results from decomposition analysis reveal that rural area, mother’s illiteracy and wealth contributed highest to the low utilization of the child health care practices consistently over the period of time. The study calls for targeted intervention for vulnerable children to accelerate child health care service utilization. Poor performing regions should be targeted and routinely monitored on poor child health indicators.

Keywords: Acute Respiratory Infection (ARI), decomposition, diarrhea, inequality, immunization

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Authors: O. Acan, Y. Keskin

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In this study, we will carry out a comparative study between the reduced differential transform method, the adomian decomposition method, the variational iteration method and the homotopy analysis method. These methods are used in many fields of engineering. This is been achieved by handling a kind of 2-Dimensional and forth-order partial differential equations called the Kuramoto–Sivashinsky equations. Three numerical examples have also been carried out to validate and demonstrate efficiency of the four methods. Furthermost, it is shown that the reduced differential transform method has advantage over other methods. This method is very effective and simple and could be applied for nonlinear problems which used in engineering.

Keywords: reduced differential transform method, adomian decomposition method, variational iteration method, homotopy analysis method

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Authors: Yingxu Wang

Abstract:

This work presents basic research on the recursive structures and dual sequential patterns of primes for the formal proof of the Twin-Prime Conjecture (TPC). A rigorous methodology of Twin-Prime Decomposition (TPD) is developed in MATLAB to inductively verify potential twins in the dual sequences of primes. The key finding of this basic study confirms that the dual sequences of twin primes are not only symmetric but also infinitive in the unique base 6 cycle, except a limited subset of potential pairs is eliminated by the lack of dual primality. Both theory and experiments have formally proven that the infinity of twin primes stated in TPC holds in the P x P space.

Keywords: number theory, primes, twin-prime conjecture, dual primes (P x P), twin prime decomposition, formal proof, algorithm

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Authors: B. Palanikumaran, N. Kanagaraj, M. Sangareswari, V. Sailaja, Kapil Sihag

Abstract:

The present study aimed to estimate the carbon sequestration potential of major forest types present in the foothills of Nilgiri biosphere reserve. The total biomass carbon stock was estimated in tropical thorn forest, tropical dry deciduous forest and tropical moist deciduous forest as 14.61 t C ha⁻¹ 75.16 t C ha⁻¹ and 187.52 t C ha⁻¹ respectively. The density and basal area were estimated in tropical thorn forest, tropical dry deciduous forest, tropical moist deciduous forest as 173 stems ha⁻¹, 349 stems ha⁻¹, 391 stems ha⁻¹ and 6.21 m² ha⁻¹, 31.09 m² ha⁻¹, 67.34 m² ha⁻¹ respectively. The soil carbon stock of different forest ecosystems was estimated, and the results revealed that tropical moist deciduous forest (71.74 t C ha⁻¹) accounted for more soil carbon stock when compared to tropical dry deciduous forest (31.80 t C ha⁻¹) and tropical thorn forest (3.99 t C ha⁻¹). The tropical moist deciduous forest has the maximum annual leaf litter which was 12.77 t ha⁻¹ year⁻¹ followed by 6.44 t ha⁻¹ year⁻¹ litter fall of tropical dry deciduous forest. The tropical thorn forest accounted for 3.42 t ha⁻¹ yr⁻¹ leaf litter production. The leaf litter carbon stock of tropical thorn forest, tropical dry deciduous forest and tropical moist deciduous forest found to be 1.02 t C ha⁻¹ yr⁻¹ 2.28 t⁻¹ C ha⁻¹ yr⁻¹ and 5.42 t C ha⁻¹ yr⁻¹ respectively. The results explained that decomposition percent at the soil surface in the following order.tropical dry deciduous forest (77.66 percent) > tropical thorn forest (69.49 percent) > tropical moist deciduous forest (63.17 percent). Decomposition percent at soil subsurface was studied, and the highest decomposition percent was observed in tropical dry deciduous forest (80.52 percent) followed by tropical moist deciduous forest (77.65 percent) and tropical thorn forest (72.10 percent). The decomposition percent was higher at soil subsurface. Among the three forest type, tropical moist deciduous forest accounted for the highest bacterial (59.67 x 105cfu’s g⁻¹ soil), actinomycetes (74.87 x 104cfu’s g⁻¹ soil) and fungal (112.60 x10³cfu’s g⁻¹ soil) population. The overall observation of the study helps to conclude that, the tropical moist deciduous forest has the potential of storing higher carbon content as biomass with the value of 264.68 t C ha⁻¹ and microbial populations.

Keywords: basal area, carbon sequestration, carbon stock, Nilgiri biosphere reserve

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Authors: Nasser A. M. Habib

Abstract:

The impressive physical properties of graphene derivatives, including thermal properties, have made them an attractive addition to advanced construction nanomaterial. In this study, we investigated the impact of incorporating low amounts of graphene oxide (GO) into cement mixture nanocomposites on their heat storage and thermal stability. The composites were analyzed using Fourier transmission infrared, thermo-gravimetric analysis, and field emission scanning electron microscopy. Results showed that GO significantly improved specific heat by 30%, reduced thermal conductivity by 15%, and reduced thermal decomposition to only 3% at a concentration of 1.2 wt%. These findings suggest that the cement mixture can withstand high temperatures and may be suitable for specific applications requiring thermal stability and insulation properties.

Keywords: cement mixture composite, graphene oxide, thermal decomposition, thermal conductivity

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Authors: Yingxu Wang

Abstract:

The base 6 structure and properties of mirror primes are discovered in this work towards the proof of Goldbach Conjecture. This paper reveals a fundamental pattern on pairs of mirror primes adjacent to any even number nₑ > 2 with symmetrical distances on both sides determined by a methodology of Mirror Prime Decomposition (MPD). MPD leads to a formal proof of the Goldbach conjecture, which states that the conjecture holds because any pivot even number, nₑ > 2, is a sum of at least an adjacent pair of primes divided by 2. This work has not only revealed the analytic pattern of base 6 primes but also proven the infinitive validation of the Goldbach conjecture.

Keywords: number theory, primes, mirror primes, double recursive patterns, Goldbach conjecture, formal proof, mirror-prime decomposition, applications

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Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

Abstract:

The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: DT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

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Authors: Nicolas Haber

Abstract:

The study addresses the conceptual design of Product-Service Systems (PSSs) as a means of innovating solutions with the aim of reducing the environmental load of conventional product based solutions. Functional approaches targeting PSS solutions are developed in instinctive methods within the constraints of the setting in which they are conceived. Adopting morphological matrices in designing PSS concepts allows a thorough understanding of the settings, stakeholders, and functional requirements. Additionally, such a methodology is robust and adaptable to product-oriented, use-oriented and result-oriented systems. The research is based on a functional decomposition of the task in a similar way as in product design; while extended to include service components, providers, and receivers, while assessing the adaptability and homogeneity of the selected components and actors. A use-oriented concept is presented via a practical case study at an agricultural boom-sprayer manufacturer to demonstrate the effectiveness of the morphological approach to justify its viability. Additionally, a life cycle analysis is carried out in order to evaluate the environmental advantages inherited in a PSS solution versus a conventional solution. In light of the applications presented, the morphological approach appears to be a valid and generic tactic to conceiving integrated solutions whilst capturing the interrelations between the actors and elements of an integrated product-service system.

Keywords: conceptual design, design for sustainability, functional decomposition, product-service systems

Procedia PDF Downloads 240