Search results for: set-based particle swarm optimization

Authors: Ahmed Elreedy, Ahmed Tawfik

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This investigation aims to assess the effect of inoculum to substrate ratio (ISR) and nitrogen to phosphorous balance on simultaneous biohydrogen and methane production from anaerobic decomposition of mono-ethylene glycol (MEG). Different ISRs were applied in the range between 2.65 and 13.23 gVSS/gCOD, whereas the tested N/P ratios were changed from 4.6 to 8.5; both under thermophilic conditions (55°C). The maximum obtained methane and hydrogen yields (MY and HY) of 151.86±10.8 and 22.27±1.1 mL/gCODinitial were recorded at ISRs of 5.29 and 3.78 gVSS/gCOD, respectively. Unlikely, the ammonification process, in terms of net ammonia produced, was found to be ISR and COD/N ratio dependent, reaching its peak value of 515.5±31.05 mgNH4-N/L at ISR and COD/N ratio of 13.23 gVSS/gCOD and 11.56. The optimum HY was enhanced by more than 1.45-fold with declining N/P ratio from 8.5 to 4.6; whereas, the MY was improved (1.6-fold), while increasing N/P ratio from 4.6 to 5.5 with no significant impact at N/P ratio of 8.5. The results obtained revealed that the methane production was strongly influenced by initial ammonia, compared to initial phosphate. Likewise, the generation of ammonia was markedly deteriorated from 535.25±41.5 to 238.33±17.6 mgNH4-N/L with increasing N/P ratio from 4.6 to 8.5. The kinetic study using Modified Gompertz equation was successfully fitted to the experimental outputs (R2 > 0.9761).

Keywords: mono-ethylene glycol, biohydrogen and methane, inoculum to substrate ratio, nitrogen to phosphorous balance, ammonification

Procedia PDF Downloads 363

Authors: A. Aulinger, A. M. Backes, J. Bieser, V. Matthias, M. Quante

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High concentrations of particles pose a threat to human health. Thus, legal maximum concentrations of PM10 and PM2.5 in ambient air have been steadily decreased over the years. In central Europe, the inorganic species ammonium sulphate and ammonium nitrate make up a large fraction of fine particles. Many studies investigate the influence of emission reductions of sulfur- and nitrogen oxides on aerosol concentration. Here, we focus on the influence of ammonia (NH3) emissions. While emissions of sulphate and nitrogen oxides are quite well known, ammonia emissions are subject to high uncertainty. This is due to the uncertainty of location, amount, time of fertilizer application in agriculture, and the storage and treatment of manure from animal husbandry. For this study, we implemented a crop growth model into the SMOKE emission model. Depending on temperature, local legislation, and crop type individual temporal profiles for fertilizer and manure application are calculated for each model grid cell. Additionally, the diffusion from soils and plants and the direct release from open and closed barns are determined. The emission data was used as input for the Community Multiscale Air Quality (CMAQ) model. Comparisons to observations from the EMEP measurement network indicate that the new ammonia emission module leads to a better agreement of model and observation (for both ammonia and ammonium). Finally, the ammonia emission model was used to create emission scenarios. This includes emissions based on future European legislation, as well as a dynamic evaluation of the influence of different agricultural sectors on particle formation. It was found that a reduction of ammonia emissions by 50% lead to a 24% reduction of total PM2.5 concentrations during winter time in the model domain. The observed reduction was mainly driven by reduced formation of ammonium nitrate. Moreover, emission reductions during winter had a larger impact than during the rest of the year.

Keywords: ammonia, ammonia abatement strategies, ctm, seasonal impact, secondary aerosol formation

Procedia PDF Downloads 332

Authors: Saleem Z. Ramadan

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This paper discusses the effects of using progressive Type-I right censoring on the design of the Simple Step Accelerated Life testing using Bayesian approach for Weibull life products under the assumption of cumulative exposure model. The optimization criterion used in this paper is to minimize the expected pre-posterior variance of the PTH percentile time of failures. The model variables are the stress changing time and the stress value for the first step. A comparison between the conventional and the progressive Type-I right censoring is provided. The results have shown that the progressive Type-I right censoring reduces the cost of testing on the expense of the test precision when the sample size is small. Moreover, the results have shown that using strong priors or large sample size reduces the sensitivity of the test precision to the censoring proportion. Hence, the progressive Type-I right censoring is recommended in these cases as progressive Type-I right censoring reduces the cost of the test and doesn't affect the precision of the test a lot. Moreover, the results have shown that using direct or indirect priors affects the precision of the test.

Keywords: reliability, accelerated life testing, cumulative exposure model, Bayesian estimation, progressive type-I censoring, Weibull distribution

Procedia PDF Downloads 493

Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

Procedia PDF Downloads 371

Authors: Ria Forner

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Introduction: Due to increases in the SNR at 7T and above, it becomes more favourable to make use of X-nuclear imaging. Integrated body coils tuned to 120MHz for 31P, 79MHz for 23Na, and 75 MHz for 13C at 7T were simulated with a human male, female, or child body model to assess strategies of use for metabolic MR imaging in the body. Methods: B1 and SAR efficiencies in the heart, liver, spleen, and kidneys were assessed using numerical simulations over the three frequencies with phase shimming. Results: B1+ efficiency is highly variable over the different organs, particularly for the highest frequency; however, local SAR efficiency remains relatively constant over the frequencies in all subjects. Although the optimal phase settings vary, one generic phase setting can be identified for each frequency at which the penalty in B1+ is at a max of 10%. Discussion: The simulations provide practical strategies for power optimization, B1 management, and maintaining safety. As expected, the B1 field is similar at 75MHz and 79MHz, but reduced at 120MHz. However, the B1 remains relatively constant when normalised by the square root of the peak local SAR. This is in contradiction to generalized SAR considerations of 1H MRI at different field strengths, which is defined by global SAR instead. Conclusion: Although the B1 decreases with frequency, SAR efficiency remains constant throughout the investigated frequency range. It is possible to shim the body coil to obtain a maximum of 10% extra B1+ in a specific organ in a body when compared to a generic setting.

Keywords: birdcage, multi-nuclear, B1 shimming, 7 Tesla MRI, liver, kidneys, heart, spleen

Procedia PDF Downloads 45

Authors: S. M. Chabane sari S. Zargou, A.R. Senoudi, F. Benmouna

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Immobilization of nano particles (NPs) is the subject of numerous studies pertaining to the design of polymer nano composites, supported catalysts, bioactive colloidal crystals, inverse opals for novel optical materials, latex templated-hollow inorganic capsules, immunodiagnostic assays; “Pickering” emulsion polymerization for making latex particles and film-forming composites or Janus particles; chemo- and biosensors, tunable plasmonic nano structures, hybrid porous monoliths for separation science and technology, biocidal polymer/metal nano particle composite coatings, and so on. Particularly, in the recent years, the literature has witnessed an impressive progress of investigations on polymer coatings, grafts and particles as supports for anchoring nano particles. This is actually due to several factors: polymer chains are flexible and may contain a variety of functional groups that are able to efficiently immobilize nano particles and their precursors by dispersive or van der Waals, electrostatic, hydrogen or covalent bonds. We review methods to prepare polymer-immobilized nano particles through a plethora of strategies in view of developing systems for separation, sensing, extraction and catalysis. The emphasis is on methods to provide (i) polymer brushes and grafts; (ii) monoliths and porous polymer systems; (iii) natural polymers and (iv) conjugated polymers as platforms for anchoring nano particles. The latter range from soft bio macromolecular species (proteins, DNA) to metallic, C60, semiconductor and oxide nano particles; they can be attached through electrostatic interactions or covalent bonding. It is very clear that physicochemical properties of polymers (e.g. sensing and separation) are enhanced by anchored nano particles, while polymers provide excellent platforms for dispersing nano particles for e.g. high catalytic performances. We thus anticipate that the synergetic role of polymeric supports and anchored particles will increasingly be exploited in view of designing unique hybrid systems with unprecedented properties.

Keywords: gold, layer, polymer, macromolecular

Procedia PDF Downloads 381

Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

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Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

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Authors: Hazem Abd El Megeed, Mohamed El-Refaay, Norhan Magdi Osman

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Spectrum scarcity is a challenging obstacle in wireless communications systems. It hinders the introduction of innovative wireless services and technologies that require larger bandwidth comparing to legacy technologies. In addition, the current worldwide allocation of radio spectrum bands is already congested and can not afford additional squeezing or optimization to accommodate new wireless technologies. This challenge is a result of accumulative contributions from different factors that will be discussed later in this paper. One of these factors is the radio spectrum allocation policy governed by national regulatory authorities nowadays. The framework for this policy allocates specified portion of radio spectrum to a particular wireless service provider on exclusive utilization basis. This allocation is executed according to technical specification determined by the standard bodies of each Radio Access Technology (RAT). Dynamic access of spectrum is a framework for flexible utilization of radio spectrum resources. In this framework there is no exclusive allocation of radio spectrum and even the public safety agencies can share their spectrum bands according to a governing policy and service level agreements. In this paper, we explore different methods for accessing the spectrum dynamically and its associated implementation challenges.

Keywords: licensed shared access, cognitive radio, spectrum sharing, spectrum congestion, dynamic spectrum access, spectrum database, spectrum trading, reconfigurable radio systems, opportunistic spectrum allocation (OSA)

Procedia PDF Downloads 408

Authors: Nooshin Salari, Viliam Makis

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In this paper, we propose a condition-based maintenance policy for multi-unit systems considering the existence of economic dependency among units. We consider a system composed of N identical units, where each unit deteriorates independently. Deterioration process of each unit is modeled as a three-state continuous time homogeneous Markov chain with two working states and a failure state. The average production rate of units varies in different working states and demand rate of the system is constant. Units are inspected at equidistant time epochs, and decision regarding performing maintenance is determined by the number of units in the failure state. If the total number of units in the failure state exceeds a critical level, maintenance is initiated, where units in failed state are replaced correctively and deteriorated state units are maintained preventively. Our objective is to determine the optimal number of failed units to initiate maintenance minimizing the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. A numerical example is developed to demonstrate the proposed policy and the comparison with the corrective maintenance policy is presented.

Keywords: reliability, maintenance optimization, semi-Markov decision process, production

Procedia PDF Downloads 142

Authors: Mateusz Paszko, Miroslaw Wendeker, Adam Majczak

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High temperature waste energy offers a number of management options. The most common energy recuperation systems, that are actually used to utilize energy from the high temperature sources are steam turbines working in a high pressure and temperature closed cycles. Due to the high costs of production of energy recuperation systems, especially rotary turbine discs equipped with blades, currently used solutions are limited in use with waste energy sources of temperature below 100 °C. This study presents the results of simulating the flow of the water vapor in various configurations of flow ducts in a reaction steam turbine based on Hero’s steam turbine. The simulation was performed using a numerical model and the ANSYS Fluent software. Simulation computations were conducted with use of the water vapor as an internal agent powering the turbine, which is fully safe for an environment in case of a device failure. The conclusions resulting from the conducted numerical computations should allow for optimization of the flow ducts geometries, in order to achieve the greatest possible efficiency of the turbine. It is expected that the obtained results should be useful for further works related to the development of the final version of a low drag steam turbine dedicated for low cost energy recuperation systems.

Keywords: energy recuperation, CFD analysis, waste energy, steam turbine

Procedia PDF Downloads 195

Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

Procedia PDF Downloads 141

Authors: A. Prajapati, K. L. Koo, F. Ghassemi, M. Mulimakwenda

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In the UK, as the volume of non-linear loads connected to transmission grid continues to rise steeply, the harmonic distortion levels on transmission network are becoming a serious concern for the network owners and system operators. This paper outlines the findings of the study conducted to verify the proposal that the harmonic mitigation could be optimized and can be managed economically and effectively at the transmission network level by the Transmission Owner (TO) instead of the individual polluter connected to the grid. Harmonic mitigation studies were conducted on selected regions of the transmission network in England for recently connected offshore wind power plants to strategize and optimize selected harmonic filter options. The results – filter volume and capacity – were then compared against the mitigation measures adopted by the individual connections. Estimation ratios were developed based on the actual installed and optimal proposed filters. These estimation ratios were then used to derive harmonic filter requirements for future contracted connections. The study has concluded that a saving of 37% in the filter volume/capacity could be achieved if the TO is to centrally manage the harmonic mitigation instead of individual polluter installing their own mitigation solution.

Keywords: C-type filter, harmonics, optimization, offshore wind farms, interconnectors, HVDC, renewable energy, transmission owner

Procedia PDF Downloads 147

Authors: J. Skibinski, P. Caban, T. Wejrzanowski, K. J. Kurzydlowski

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In the present study, numerical simulations of heat and mass transfer during gallium nitride growth process in Metal Organic Vapor Phase Epitaxy reactor AIX-200/4RF-S is addressed. Existing knowledge about phenomena occurring in the MOVPE process allows to produce high quality nitride based semiconductors. However, process parameters of MOVPE reactors can vary in certain ranges. Main goal of this study is optimization of the process and improvement of the quality of obtained crystal. In order to investigate this subject a series of computer simulations have been performed. Numerical simulations of heat and mass transfer in GaN epitaxial growth process have been performed to determine growth rate for various mass flow rates and pressures of reagents. According to the fact that it’s impossible to determine experimentally the exact distribution of heat and mass transfer inside the reactor during the process, modeling is the only solution to understand the process precisely. Main heat transfer mechanisms during MOVPE process are convection and radiation. Correlation of modeling results with the experiment allows to determine optimal process parameters for obtaining crystals of highest quality.

Keywords: Finite Volume Method, semiconductors, epitaxial growth, metalorganic vapor phase epitaxy, gallium nitride

Procedia PDF Downloads 379

Authors: Pawit Tangviroon, Apichit Svang-Ariyaskul

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Rubber seed oil is an attractive alternative feedstock for biodiesel production because it is not related to food-chain plant. Rubber seed oil contains large amount of free fatty acids, which causes problem in biodiesel production. Free fatty acids can react with alkaline catalyst in biodiesel production. Acid esterification is used as pre-treatment to convert unwanted compound to desirable biodiesel. Phase separation of oil and methanol occurs at low ratio of methanol to oil and causes low reaction rate and conversion. Acid esterification requires large excess of methanol in order to increase the miscibility of methanol in oil and accordingly, it is a more expensive separation process. In this work, the kinetics of esterification of rubber seed oil with methanol is developed from available experimental results. Reactive distillation process was designed by using Aspen Plus program. The effects of operating parameters such as feed ratio, molar reflux ratio, feed temperature, and feed stage are investigated in order to find the optimum conditions. Results show that the reactive distillation process is proved to be better than conventional process. It consumes less feed methanol and less energy while yielding higher product purity than the conventional process. This work can be used as a guideline for further development to industrial scale of biodiesel production using reactive distillation.

Keywords: biodiesel, reactive distillation, rubber seed oil, transesterification

Procedia PDF Downloads 331

Authors: Christian Liebchen

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Both from an environmental perspective and with respect to road traffic flow quality, planning so-called green waves along major road axes is a well-established target for traffic engineers. For one-way road axes (e.g. the Avenues in Manhattan), this is a trivial downstream task. For bidirectional arterials, the well-known necessary condition for establishing a green wave in both directions is that the driving times between two subsequent crossings must be an integer multiple of half of the cycle time of the signal programs at the nodes. In this paper, we propose an integer linear optimization model to establish fixed-time green waves in both directions that are as long and as wide as possible, even in the situation where the driving time condition is not fulfilled. In particular, we are considering an arterial along whose nodes separate left-turn signal groups are realized. In our computational results, we show that scheduling left-turn phases before or after the straight phases can reduce waiting times along the arterial. Moreover, we show that there is always a solution with green waves in both directions that are as long and as wide as possible, where absolute priority is put on just one direction. Compared to optimizing both directions together, establishing an ideal green wave into one direction can only provide suboptimal quality when considering prioritized parts of a green band (e.g., first few seconds).

Keywords: traffic light coordination, synchronization, phase sequencing, green waves, integer programming

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: wavelet transform, computational error, computational duration, strong ground motion data

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Authors: Jayprakash Yadav, Nivedita Patra

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Polyhydroxybutyrate (PHB) is an interesting material in the field of medical science, pharmaceutical industries, and tissue engineering because of its properties such as biodegradability, biocompatibility, hydrophobicity, and elasticity. PHB is naturally accumulated by several microbes in their cytoplasm during the metabolic process as energy reserve material. PHB can be extracted from cell biomass using halogenated hydrocarbons, chemicals, and enzymes. In this study, a cheaper and non-toxic solvent, acetone, was used for the extraction process. The different parameters like acetone percentage, and solvent pH, process temperature, and incubation periods were optimized using the Response Surface Methodology (RSM). RSM was performed and the determination coefficient (R2) value was found to be 0.8833 from the quadratic regression model with no significant lack of fit. The designed RSM model results indicated that the fitness of the response variable was significant (P-value < 0.0006) and satisfactory to denote the relationship between the responses in terms of PHB recovery and purity with respect to the values of independent variables. Optimum conditions for the maximum PHB recovery and purity were found to be solvent pH 7, extraction temperature - 43 °C, incubation time - 70 minutes, and percentage acetone – 30 % from this study. The maximum predicted PHB recovery was found to be 0.845 g/g biomass dry cell weight and the purity was found to be 97.23 % using the optimized conditions.

Keywords: acetone, PHB, RSM, halogenated hydrocarbons, extraction, bacillus subtilis.

Procedia PDF Downloads 425

Authors: Haitao Yang, Zhenjiang Ruan, Fei Xu, Lanting Xia

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Industry data centers often need to sync data changes reliably and instantly from a large-scale of heterogeneous autonomous relational databases accessed via the not-so-reliable Internet, for which a practical universal sync middle of low maintenance and operation costs is most wanted, but developing such a product and adapting it for various scenarios are a very sophisticated and continuous practice. The authors have been devising, applying, and optimizing a generic sync middleware system, named GSMS since 2006, holding the principles or advantages that the middleware must be SyncML-compliant and transparent to data application layer logic, need not refer to implementation details of databases synced, does not rely on host computer operating systems deployed, and its construction is light weighted and hence, of low cost. A series of ultimate experiments with GSMS sync performance were conducted for a persuasive example of a source relational database that underwent a broad range of write loads, say, from one thousand to one million intensive writes within a few minutes. The tests proved that GSMS has achieved an instant sync level of well below a fraction of millisecond per record sync, and GSMS’ smooth performances under ultimate write loads also showed it is feasible and competent.

Keywords: heterogeneous massive data, instantly sync intensive writes, Internet generic middleware design, optimization

Procedia PDF Downloads 105

Authors: Réka Sárközi, Péter Iványi, Attila B. Széll

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The aim of this paper is to present the adaptation of the dome construction tool for formex algebra to the parametric design software Grasshopper. Formex algebra is a mathematical system, primarily used for planning structural systems such like truss-grid domes and vaults, together with the programming language Formian. The goal of the research is to allow architects to plan truss-grid structures easily with parametric design tools based on the versatile formex algebra mathematical system. To produce regular structures, coordinate system transformations are used and the dome structures are defined in spherical coordinate system. Owing to the abilities of the parametric design software, it is possible to apply further modifications on the structures and gain special forms. The paper covers the basic dome types, and also additional dome-based structures using special coordinate-system solutions based on spherical coordinate systems. It also contains additional structural possibilities like making double layer grids in all geometry forms. The adaptation of formex algebra and the parametric workflow of Grasshopper together give the possibility of quick and easy design and optimization of special truss-grid domes.

Keywords: parametric design, structural morphology, space structures, spherical coordinate system

Procedia PDF Downloads 237

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

Procedia PDF Downloads 59

Authors: Sanjay Singh, Karunanithi Priyanka, Ramoji Kosuru, Raju Prasad Sharma

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Herbal drugs are well known for their mixed pharmacological activities with the benefit of no harmful side effects. The use of herbal drugs is limited because of their higher dose requirement, frequent drug administration, poor bioavailability of phytochemicals and delayed onset of action. Ficus religiosa, a potent anti-oxidant plant useful in the treatment of diabetes and cancer was selected for the study. Solid lipid nanoparticles (SLN) of Ficus religiosa extract was developed for the enhancement in oral bioavailability of stigmasterol and β-sitosterol-d-glucoside, principal components present in the extract. Hot homogenization followed by ultrasonication method was used to develop extract loaded SLN. Developed extract loaded SLN were characterized for particle size, PDI, zeta potential, entrapment efficiency, in vitro drug release and kinetics, fourier transform infra-red spectroscopy, differential scanning calorimetry, powder X-ray diffractrometry and stability studies. Entrapment efficiency of optimized extract loaded SLN was found to be 68.46 % (56.13 % of stigmasterol and 12.33 % of β-sitosteryl-d-glucoside, respectively). RP HPLC method development was done for simultaneous estimation of stigmasterol and β-sitosterol-d-glucoside in Ficus religiosa extract in rat plasma. Bioavailability studies were carried out for extract in suspension form and optimized extract loaded SLN. AUC of stigmasterol and β-sitosterol-d-glucoside were increased by 6.7-folds by 9.2-folds, respectively in rats treated with extract loaded SLN compared to extract suspension. Also, Cmax of stigmasterol and β-sitosterol-d-glucoside were increased by 4.3-folds by 3.9-folds, respectively in rats treated with extract loaded SLN compared to extract suspension. Mean residence times (MRT) for stigmasterol were found to be 12.3 ± 0.67 hours from extract and 7.4 ± 2.1 hours from SLN and for β-sitosterol-d-glucoside, 10.49 ± 2.9 hours from extract and 6.4 ± 0.3 hours from SLN. Hence, it was concluded that SLN enhanced the bioavailability and reduced the MRT of stigmasterol and β-sitosterol-d-glucoside in Ficus religiosa extract which in turn may lead to reduction in dose of Ficus religiosa extract, prolonged duration of action and also enhanced therapeutic efficacy.

Keywords: Ficus religiosa, phytosterolins, bioavailability, solid lipid nanoparticles, stigmasterol and β-sitosteryl-d-glucoside

Procedia PDF Downloads 456

Authors: Shahzamani Kiana, Esmaeil Lashgarian Hamed, Merat Shahin

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HCV and GBV-C belong to the Flaviviridae family of viruses and GBV-C is the closest virus to HCV genetically. Accumulative research is in progress all over the world to clarify clinical aspects of GBV-C. Possibility of interaction between HCV and GBV-C and also its consequence with other liver diseases are the most important clinical aspects which encourage researchers to develop a technique for simultaneous detection of these viruses. In this study a SYBR Green multiplex real time RT-PCR technique as a new economical and sensitive method was optimized for simultaneous detection of HCV/GBV-C in HCV positive plasma samples. After designing and selection of two pairs of specific primers for HCV and GBV-C, SYBR Green Real time RT-PCR technique optimization was performed separately for each virus. Establishment of multiplex PCR was the next step. Finally our technique was performed on positive and negative plasma samples. 89 cirrhotic HCV positive plasma samples (29 of genotype 3 a and 27 of genotype 1a) were collected from patients before receiving treatment. 14% of genotype 3a and 17.1% of genotype 1a showed HCV/GBV-C co-infection. As a result, 13.48% of 89 samples had HCV/GBV-C co-infection that was compatible with other results from all over the world. Data showed no apparent influence of HGV co-infection on the either clinical or virological aspect of HCV infection. Furthermore, with application of multiplex Real time RT-PCR technique, more time and cost could be saved in clinical-research settings.

Keywords: HCV, GBV-C, cirrhotic patients, multiplex real time RT- PCR

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Authors: Asif Zaman, Moinul Islam Zaber, Amin Ahsan Ali

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In recent years of industrialization, the South Asian countries are being affected by air pollution due to a severe increase in fine particulate matter 2.5 (PM₂.₅). Among them, Bangladesh is one of the most polluting countries. In this paper, statistical analyses were conducted on the time series of PM₂.₅ from various districts in Bangladesh, mostly around Dhaka city. Research has been conducted on the dynamic interactions and relationships between PM₂.₅ concentrations in different zones. The study is conducted toward understanding the characteristics of PM₂.₅, such as spatial-temporal characterization, correlation of other contributors behind air pollution such as human activities, driving factors and environmental casualties. Clustering on the data gave an insight on the districts groups based on their AQI frequency as representative districts. Seasonality analysis on hourly and monthly frequency found higher concentration of fine particles in nighttime and winter season, respectively. Cross correlation analysis discovered a phenomenon of correlations among cities based on time-lagged series of air particle readings and visualization framework is developed for observing interaction in PM₂.₅ concentrations between cities. Significant time-lagged correlations were discovered between the PM₂.₅ time series in different city groups throughout the country by cross correlation analysis. Additionally, seasonal heatmaps depict that the pooled series correlations are less significant in warmer months, and among cities of greater geographic distance as well as time lag magnitude and direction of the best shifted correlated particulate matter time series among districts change seasonally. The geographic map visualization demonstrates spatial behaviour of air pollution among districts around Dhaka city and the significant effect of wind direction as the vital actor on correlated shifted time series. The visualization framework has multipurpose usage from gathering insight of general and seasonal air quality of Bangladesh to determining the pathway of regional transportation of air pollution.

Keywords: air quality, particles, cross correlation, seasonality

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Authors: Elsayed A. Elkhatib, Ahmed M. Mahdy, Mohamed L. Moharem, Mohamed O. Mesalem

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Mercury (Hg) is one of the most toxic and bio-accumulative heavy metal in the environment. However, cheap and effective in situ remediation technology is lacking. In this study, the effects of water treatment residuals nanoparticles (nWTR) on mobility, fractionation and speciation of mercury in an arid zone soil from Egypt were evaluated. Water treatment residual nanoparticles with high surface area (129 m 2 g-1) were prepared using Fritsch planetary mono mill. Scanning and transmission electron microscopy revealed that the nanoparticles of WTR nanoparticles are spherical in shape, and single particle sizes are in the range of 45 to 96 nm. The x-ray diffraction (XRD) results ascertained that amorphous iron, aluminum (hydr)oxides and silicon oxide dominating all nWTR, with no apparent crystalline iron–Al (hydr)oxides. Addition of nWTR, greatly increased the Hg sorption capacities of studied soils and greatly reduced the cumulative Hg released from the soils. Application of nWTR at 0.10 and 0.30 % rates reduced the released Hg from the soil by 50 and 85 % respectively. The power function and first order kinetics models well described the desorption process from soils and nWTR amended soils as evidenced by high coefficient of determination (R2) and low SE values. Application of nWTR greatly increased the association of Hg with the residual fraction. Meanwhile, application of nWTR at a rate of 0.3% greatly increased the association of Hg with the residual fraction (>93%) and significantly increased the most stable Hg species (Hg(OH)2 amor) which in turn enhanced Hg immobilization in the studied soils. Fourier transmission infrared spectroscopy analysis indicated the involvement of nWTR in the retention of Hg (II) through OH groups which suggest inner-sphere adsorption of Hg ions to surface functional groups on nWTR. These results demonstrated the feasibility of using a low-cost nWTR as best management practice to immobilize excess Hg in contaminated soils.

Keywords: release kinetics, Fourier transmission infrared spectroscopy, Hg fractionation, Hg species

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Authors: B. Mavhuru, N. S. Nethengwe

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Human activities on land degradation have triggered several environmental problems especially in rural areas that are underdeveloped. The main aim of this study is to analyze the contribution of different land uses to gully development and sediment load on the Nzhelele River Valley in the Limpopo Province. Data was collected using different methods such as observation, field data techniques and experiments. Satellite digital images, topographic maps, aerial photographs and the sediment load static model also assisted in determining how land use affects gully development and sediment load. For data analysis, the researcher used the following methods: Analysis of Variance (ANOVA), descriptive statistics, Pearson correlation coefficient and statistical correlation methods. The results of the research illustrate that high land use activities create negative changes especially in areas that are highly fragile and vulnerable. Distinct impact on land use change was observed within settlement area (9.6 %) within a period of 5 years. High correlation between soil organic matter and soil moisture (R=0.96) was observed. Furthermore, a significant variation (p ≤ 0.6) between the soil organic matter and soil moisture was also observed. A very significant variation (p ≤ 0.003) was observed in bulk density and extreme significant variations (p ≤ 0.0001) were observed in organic matter and soil particle size. The sand mining and agricultural activities has contributed significantly to the amount of sediment load in the Nzhelele River. A high significant amount of total suspended sediment (55.3 %) and bed load (53.8 %) was observed within the agricultural area. The connection which associates the development of gullies to various land use activities determines the amount of sediment load. These results are consistent with other previous research and suggest that land use activities are likely to exacerbate the development of gullies and sediment load in the Nzhelele River Valley.

Keywords: drainage basin, geomorphological processes, gully development, land degradation, riparian land use and sediment load

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Authors: Hao Liu, Lihui Zheng, Chinedu J. Okere, Chao Wang, Xiangchun Wang, Peng Zhang

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The coalbed methane (CBM) extraction industry (an unconventional energy source) is yet to promulgated an established standard code of practice for the experimental evaluation of sensitivity damage of coal samples. The existing experimental process of previous researches mainly followed the industry standard for conventional oil and gas reservoirs (CIS). However, the existing evaluation method ignores certain critical differences between CBM reservoirs and conventional reservoirs, which could inevitably result in an inaccurate evaluation of sensitivity damage and, eventually, poor decisions regarding the formulation of formation damage prevention measures. In this study, we propose improved experimental guidelines for evaluating seepage sensitivity damage of CBM reservoirs by leveraging on the shortcomings of the existing methods. The proposed method was established via a theoretical analysis of the main drawbacks of the existing methods and validated through comparative experiments. The results show that the proposed evaluation technique provided reliable experimental results that can better reflect actual reservoir conditions and correctly guide future development of CBM reservoirs. This study is pioneering the research on the optimization of experimental parameters for efficient exploration and development of CBM reservoirs.

Keywords: coalbed methane, formation damage, permeability, unconventional energy source

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Authors: Gurinder Singh Brar, Sarbjeet Singh, Harry Garg

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Wire Electric Discharge Machining (WEDM) is thermal machining process capable of machining very hard electrically conductive material irrespective of their hardness. WEDM is being widely used to machine micro-scale parts with the high dimensional accuracy and surface finish. The objective of this paper is to optimize the process parameters of wire EDM to fabricate the microchannels and to calculate the surface finish and material removal rate of microchannels fabricated using wire EDM. The material used is aluminum 6061 alloy. The experiments were performed using CNC wire cut electric discharge machine. The effect of various parameters of WEDM like pulse on time (TON) with the levels (100, 150, 200), pulse off time (TOFF) with the levels (25, 35, 45) and current (IP) with the levels (105, 110, 115) were investigated to study the effect on output parameter i.e. Surface Roughness and Material Removal Rate (MRR). Each experiment was conducted under different conditions of a pulse on time, pulse off time and peak current. For material removal rate, TON and Ip were the most significant process parameter. MRR increases with the increase in TON and Ip and decreases with the increase in TOFF. For surface roughness, TON and Ip have the maximum effect and TOFF was found out to be less effective.

Keywords: microchannels, Wire Electric Discharge Machining (WEDM), Metal Removal Rate (MRR), surface finish

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Authors: Romuald Temomo Wamba, Robert Wanda

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The issue of creative accounting in the psychological and sociological framework has been a mixed subject for over 60 years. The objective of this article is to ensure the existence of creative accounting in Cameroonian entities on the one hand and to understand the strategies used by audit agents to detect errors, omissions, irregularities, or inadequacies in the financial state; optimization techniques used by account preparers to strategically bypass texts on the other hand. To achieve this, we conducted an exploratory study using a cognitive approach, and the data analysis was performed by the software 'decision explorer'. The results obtained challenge the authors' cognition (manifest latent and deceptive behavior). The tax inspectors stress that the entities in Cameroon do not derogate from the rules of piloting in the financial statements. Likewise, they claim a change in current income and net income through depreciation, provisions, inventories, and the spreading of charges over long periods. This suggests the suspicion or intention of manipulating the financial statements. As for the techniques, the account preparers manage the accruals at the end of the year as the basis of the practice of creative accounting. Likewise, management accounts are more favorable to results management.

Keywords: creative accounting, sociocognitive approach, psychological and sociological approach, cognitive dissonance theory, cognitive mapping

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Authors: C. Bay, A. Mahr, H. Groneberg, F. Döpper

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Additive Manufacturing processes are becoming increasingly established in the industry for the economic production of complex prototypes and functional components. Laser beam melting (LBM), the most frequently used Additive Manufacturing technology for metal parts, has been gaining in industrial importance for several years. The LBM process chain – from material storage to machine set-up and component post-processing – requires many manual operations. These steps often depend on the manufactured component and are therefore not standardized. These operations are often not performed in a standardized manner, but depend on the experience of the machine operator, e.g., levelling of the build plate and adjusting the first powder layer in the LBM machine. This lack of standardization limits the reproducibility of the component quality. When processing metal powders with inhalable and alveolar particle fractions, the machine operator is at high risk due to the high reactivity and the toxic (e.g., carcinogenic) effect of the various metal powders. Faulty execution of the operation or unintentional omission of safety-relevant steps can impair the health of the machine operator. In this paper, all the steps of the LBM process chain are first analysed in terms of their influence on the two aforementioned challenges: reproducibility and work safety. Standardization to avoid errors increases the reproducibility of component quality as well as the adherence to and correct execution of safety-relevant operations. The corresponding lean method 5S will therefore be applied, in order to develop approaches in the form of recommended actions that standardize the work processes. These approaches will then be evaluated in terms of ease of implementation and their potential for improving reproducibility and work safety. The analysis and evaluation showed that sorting tools and spare parts as well as standardizing the workflow are likely to increase reproducibility. Organizing the operational steps and production environment decreases the hazards of material handling and consequently improves work safety.

Keywords: additive manufacturing, lean production, reproducibility, work safety

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Authors: Xiao Zhang, Wensheng Xiao, Junguo Cui, Hongmin Wang

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Submersible permanent magnet linear synchronous motors (SPMLSMs) are electromagnetic devices, which can directly drive plunger pump to obtain the crude oil. Those motors have been gradually applied in oil fields due to high thrust force density and high efficiency. Since the force performance closely depends on the concrete structural parameters, the seven different structural parameters are investigated in detail. This paper presents an optimum design of an SPMLSM to minimize the detent force and maximize the thrust by using design of experiment (DOE) and genetic algorithm (GA). The three significant structural parameters (air-gap length, slot width, pole-arc coefficient) are separately screened using 27 1/16 fractional factorial design (FFD) to investigate the significant effect of seven parameters used in this research on the force performance. Response surface methodology (RSM) is well adapted to make analytical model of thrust and detent force with constraints of corresponding significant parameters and enable objective function to be easily created, respectively. GA is performed as a searching tool to search for the Pareto-optimal solutions. By finite element analysis, the proposed PMLSM shows merits in improving thrust and reducing the detent force dramatically.

Keywords: optimization, force performance, design of experiment (DOE), genetic algorithm (GA)

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