Search results for: scanning time

Authors: Tran Gia Khanh, Dao Phuong Nam, Do Trong Tan, Nguyen Van Huong, Mai Xuan Sinh

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This work presents the problem of tube-based robust model predictive controller for a class of continuous-time systems in the presence of input disturbances. The main objective is to point out the state trajectory of closed system being maintained inside a sequence of tubes. An estimation of attraction region of the closed system is pointed out based on input state stability (ISS) theory and linearized model in each time interval. The theoretical analysis and simulation results demonstrate the performance of the proposed algorithm for a wheeled inverted pendulum system.

Keywords: input state stability (ISS), tube-based robust MPC, continuous-time nonlinear systems, wheeled inverted pendulum

Procedia PDF Downloads 202

Authors: Gyeong-Suk Jo, Soo-Hyun Ji, You-Seok Lee, Jeong-Hwa Kang

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To develop an flavor oil using Sarcodon aspratus (Sarcodon aspratus Berk. S. Ito), infiltration extraction method was used to add dried mushroom flavor of Sarcodon aspratus to base olive oil. Edible base oil used during infiltration extraction was pressed olive oil, and infiltration extraction was done while varying extraction temperature to 20, 30, 40 and 50(℃) extraction time to 24 hours, 48 hours and 72 hours. Amount of Sarcodon aspratus added to base oil was 20% compared to 100% of base oil. Production yield of Sarcodon aspratus flavor oil decreased with increasing extraction frequency. Aroma intensity was 2195~2447 (A.U./1㎖), and it increased with increasing extraction temperature and extraction time. Chromaticity of Sarcodon aspratus flavor oil was bright pale yellow with pH of 4.5, sugar content of 71~72 (°Brix), and highest average turbidity of 16.74 (Haze %) shown by the 40℃ group. In the aromatic evaluation, increasing extraction temperature and extraction time resulted in increase of cheese aroma, savory sweet aroma and beef jerky aroma, as well as spicy taste comprised of slight bitter taste, savory taste and slight acrid taste, to make aromatic oil with unique flavor.

Keywords: Flavor Characteristics, Flavor Oil, Infiltration extraction method, mushroom, Sarcodon aspratus (Sarcodon aspratus Berk. S. Ito)

Procedia PDF Downloads 352

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

Procedia PDF Downloads 362

Authors: Sasangka Prasetyawan, Anna Roosdiana, Diah Mardiana, Suratmo

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Pectinase are enzymes that hydrolyze pectin compounds. The use of this enzyme is primarily to reduce the viscosity of the beverage thus simplifying the purification process. Pectinase activity influenced by microbial sources . Exploration of two types of microbes that Aspergillus spp. and Bacillus spp. pectinase give different performance, but the use of local strain is still not widely studied. The aim of this research is exploration of pectinase from A. niger and B. firmus include production conditions and characterization. Bacillus firmus incubated and shaken at a speed of 200 rpm at pH variation (5, 6, 7, 8, 9, 10), temperature (30, 35, 40, 45, 50) °C and incubation time (6, 12, 18, 24, 30, 36 ) hours. Media was centrifuged at 3000 rpm, pectinase enzyme activity determined. Enzyme production by A. niger determined to variations in temperature and pH were similar to B. firmus, but the variation of the incubation time was 24, 48, 72, 96, 120 hours. Pectinase crude extract was further purified by precipitation using ammonium sulfate saturation in fraction 0-20 %, 20-40 %, 40-60 %, 60-80 %, then dialyzed. Determination of optimum conditions pectinase activity performed by measuring the variation of enzyme activity on pH (4, 6, 7, 8, 10), temperature (30, 35, 40, 45, 50) °C, and the incubation time (10, 20, 30, 40, 50) minutes . Determination of kinetic parameters of pectinase enzyme reaction carried out by measuring the rate of enzyme reactions at the optimum conditions, but the variation of the concentration of substrate (pectin 0.1 % , 0.2 % , 0.3 % , 0.4 % , 0.5 % ). The results showed that the optimum conditions of production of pectinase from B. firmus achieved at pH 7-8.0, 40-50 ⁰C temperature and fermentation time 18 hours. Purification of pectinase showed the highest purity in the 40-80 % ammonium sulfate fraction. Character pectinase obtained : the optimum working conditions of A. niger pectinase at pH 5 , while pectinase from B. firmus at pH 7, temperature and optimum incubation time showed the same value, namely the temperature of 50 ⁰C and incubation time of 30 minutes. The presence of metal ions can affect the activity of pectinase , the concentration of Zn 2 + , Pb 2 + , Ca 2 + and K + and 2 mM Mg 2 + above 6 mM inhibit the activity of pectinase .

Keywords: pectinase, Bacillus firmus, Aspergillus niger, green chemistry

Procedia PDF Downloads 350

Authors: Gagandeep Kaur

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Cloud computing uses various computing resources such as CPU, memory, processor etc. which is used to deliver service over the network and is one of the emerging fields for large scale distributed computing. In cloud computing, execution of large number of tasks with available resources to achieve high performance, minimal total time for completion, minimum response time, effective utilization of resources etc. are the major research areas. In the proposed research, an algorithm has been proposed to achieve high performance in load balancing and resource utilization. The proposed algorithm is used to reduce the makespan, increase the resource utilization and performance cost for independent tasks. Further scheduling metrics based on algorithm in cloud computing has been proposed.

Keywords: resource utilization, response time, load balancing, performance cost

Procedia PDF Downloads 166

Authors: Yuichi Anada

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Electrical properties of polymer solid is characterized by dielectric relaxation phenomenon. Complex permittivity shows a high dependence on frequency of external stimulation in the broad frequency range from 0.1mHz to 10GHz. The complex-permittivity dispersion gives us a lot of useful information about the molecular motion of polymers and the structure of polymer aggregates. However, the large dispersion of permittivity at low frequencies due to DC conduction of impurity ions often covers the dielectric relaxation in polymer solid. In experimental investigation, many researchers have tried to remove the DC conduction experimentally or analytically for a long time. On the other hand, our laboratory chose another way of research for this problem from the point of view of a reversal in thinking. The way of our research is to use the impurity ions in the DC conduction as a probe to detect the motion of polymer molecules and to investigate the structure of polymer aggregates. In addition to the complex permittivity, the electric modulus and the conductivity relaxation time are strong tools for investigating the ionic motion in DC conduction. In a non-crystalline part of melt-crystallized polymers, free spaces with inhomogeneous size exist between crystallites. As the impurity ions exist in the non-crystalline part and move through these inhomogeneous free spaces, the motion of ions reflects the microstructure of non-crystalline part. The ionic motion of impurity ions in poly(vinylidene fluoride) (PVDF) is investigated in this study. Frequency dependence of the loss permittivity of PVDF shows a characteristic of the direct current (DC) conduction below 1 kHz of frequency at 435 K. The electric modulus-frequency curve shows a characteristic of the dispersion with the single conductivity relaxation time. Namely, it is the Debye-type dispersion. The conductivity relaxation time analyzed from this curve is 0.00003 s at 435 K. From the plot of conductivity relaxation time of PVDF together with the other polymers against permittivity, it was found that there are two group of polymers; one of the group is characterized by small conductivity relaxation time and large permittivity, and another is characterized by large conductivity relaxation time and small permittivity.

Keywords: conductivity relaxation time, electric modulus, ionic motion, permittivity, poly(vinylidene fluoride), DC conduction

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Authors: Nattawat Thongpraphai, Anusorn Boonpoke

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This study aimed to determine the removal of colour and curcuminoids from turmeric wastewater using granular activated carbon (GAC) adsorption. The adsorption isotherm and kinetic behavior of colour and curcuminoids was invested using batch and fixed bed columns tests. The results indicated that the removal efficiency of colour and curcuminoids were 80.13 and 78.64%, respectively at 8 hr of equilibrium time. The adsorption isotherm of colour and curcuminoids were well fitted with the Freundlich adsorption model. The maximum adsorption capacity of colour and curcuminoids were 130 Pt-Co/g and 17 mg/g, respectively. The continuous experiment data showed that the exhaustion concentration of colour and curcuminoids occurred at 39 hr of operation time. The adsorption characteristic of colour and curcuminoids from turmeric wastewater by GAC can be described by the Thomas model. The maximum adsorption capacity obtained from kinetic approach were 39954 Pt-Co/g and 0.0516 mg/kg for colour and curcuminoids, respectively. Moreover, the decrease of colour and curcuminoids concentration during the service time showed a similar trend.

Keywords: adsorption, turmeric, colour, curcuminoids, activated carbon

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Authors: Xuelin Zhang, Shouxiang Lu, Changhai Li

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The commercial retardant flame polycarbonate samples as the main high speed train interior carriage material with different thicknesses were investigated in Fire Propagation Apparatus with different external heat fluxes under different oxygen concentration from 12% to 40% to study the fire characteristics and quantitatively analyze the ignition time, mass loss rate and heat blockage. The additives of commercial retardant flame polycarbonate were intumescent and maintained a steady height before ignition when heated. The results showed the transformed ignition time (1/t_ig)ⁿ increased linearly with external flux under different oxygen concentration after deducting the heat blockage due to pyrolysis products, the mass loss rate was taken on linearly with external heat fluxes and the slop of the fitting line for mass loss rate and external heat fluxes decreased with the enhanced oxygen concentration and the heat blockage independent on external heat fluxes rose with oxygen concentration increasing. The inquired data as the input of the fire simulation model was the most important to be used to evaluate the fire risk of commercial retardant flame polycarbonate.

Keywords: ignition time, mass loss rate, heat blockage, fire characteristic

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Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

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Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

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Authors: Surjyakanta Rana, Sreekantha B. Jonnalagadda

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Synthesis of well distributed Pd nanoparticles (3 – 7 nm) on organo amine-functionalized graphene is reported, which demonstrated excellent catalytic activity towards Suzuki coupling reaction. The active material was characterized by X-ray diffraction (XRD), BET surface area, X-ray photoelectron spectra (XPS), Fourier-transfer infrared spectroscopy (FTIR), Raman spectra, Scanning electron microscope (SEM), Transmittance electron microscopy (TEM) analysis and HRTEM. FT-IR revealed that the organic amine functional group was successfully grafted onto the graphene oxide surface. The formation of palladium nanoparticles was confirmed by XPS, TEM and HRTEM techniques. The catalytic activity in the coupling reaction was superb with 100% conversion and 98 % yield and also activity remained almost unaltered up to six cycles. Typically, an extremely high turnover frequency of 185,078 h-1 is observed in the C-C Suzuki coupling reaction using organo di-amine functionalized graphene as catalyst.

Keywords: Di-amine, graphene, Pd nanoparticle, suzuki coupling

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

Procedia PDF Downloads 91

Authors: Rakesh Prajapati, Purvik Patel, Avadhoot Rajurkar

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Nowadays, manufacturing industries augment their production lines with modern machining centers backed by CAM software. Several attempts are being made to cut down the programming time for machining complex geometries. Special programs/software have been developed to generate the digital numerical data and to prepare NC programs by using suitable post-processors for different machines. By selecting the tools and manufacturing process then applying tool paths and NC program are generated. More and more complex mechanical parts that earlier were being cast and assembled/manufactured by other processes are now being machined. Majority of these parts require lots of pocketing operations and find their applications in die and mold, turbo machinery, aircraft, nuclear, defense etc. Pocketing operations involve removal of large quantity of material from the metal surface. The modeling of warm cast and clamping a piece of food processing parts which the used of Pro-E and MasterCAM^® software. Pocketing operation has been specifically chosen for toolpath optimization. Then after apply Pocketing toolpath, Multi Tool Selection and Reduce Air Time give the results of software simulation time and experimental machining time.

Keywords: toolpath, part program, optimization, pocket

Procedia PDF Downloads 277

Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Naik Muhammad, Zahid Ullah, Dong-Ho Choi

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Submerged floating tunnel (SFT) is a new solution for the transportation infrastructure through sea straits, fjords, and inland waters, and can be a good alternative to long span suspension bridges. SFT is a massive cylindrical structure that floats at a certain depth below the water surface and subjected to extreme environmental conditions. The identification of dominant structural response of SFT becomes more important due to intended environmental conditions for the design of SFT. The time domain dynamic problem of SFT moored by vertical and inclined mooring cables/anchors is formulated. The dynamic time history analysis of SFT subjected to hydrodynamic and seismic excitations is performed. The SFT is modeled by finite element 3D beam, and the mooring cables are modeled by truss elements. Based on the dynamic time history analysis the displacements and internal forces of SFT were calculated. The response of SFT is presented for hydrodynamic and seismic excitations. The transverse internal forces of SFT were the maximum compared to vertical direction, for both hydrodynamic and seismic cases; this indicates that the cable system provides very small stiffness in transverse direction as compared to vertical direction of SFT.

Keywords: submerged floating tunnel, hydrodynamic analysis, time history analysis, seismic response

Procedia PDF Downloads 316

Authors: Nicholas D. Assimakis

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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: discrete time, estimation, Kalman filter, Kalman filter gain

Procedia PDF Downloads 172

Authors: Hyung-Jin Kim, Dae-Wan Kim, Moo-Yeon Lee

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The objective of this study is to experimentally investigate the heat transfer characteristics of 200 W class woofer speaker units with the input voice signals. The temperature and heat transfer characteristics of the 200 W class woofer speaker unit were experimentally tested with the several input voice signals such as 1500 Hz, 2500 Hz, and 5000 Hz respectively. From the experiments, it can be observed that the temperature of the woofer speaker unit including the voice-coil part increases with a decrease in input voice signals. Also, the temperature difference in measured points of the voice coil is increased with decrease of the input voice signals. In addition, the heat transfer characteristics of the woofer speaker in case of the input voice signal of 1500 Hz is 40% higher than that of the woofer speaker in case of the input voice signal of 5000 Hz at the measuring time of 200 seconds. It can be concluded from the experiments that initially the temperature of the voice signal increases rapidly with time, after a certain period of time it increases exponentially. Also during this time dependent temperature change, it can be observed that high voice signal is stable than low voice signal.

Keywords: heat transfer, temperature, voice coil, woofer speaker

Procedia PDF Downloads 339

Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

Procedia PDF Downloads 116

Authors: Roshani S. Golhar, Neerajkumar S. Sathawane, Snehal Dongre

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Background and objectives: As the, cardiovascular illnesses increasing and becoming cause of mortality worldwide, killing around lot of people each year. Arrhythmia is a type of cardiac illness characterized by a change in the linearity of the heartbeat. The goal of this study is to develop novel deep learning algorithms for successfully interpreting arrhythmia using a single second segment. Because the ECG signal indicates unique electrical heart activity across time, considerable changes between time intervals are detected. Such variances, as well as the limited number of learning data available for each arrhythmia, make standard learning methods difficult, and so impede its exaggeration. Conclusions: The proposed method was able to outperform several state-of-the-art methods. Also proposed technique is an effective and convenient approach to deep learning for heartbeat interpretation, that could be probably used in real-time healthcare monitoring systems

Keywords: electrocardiogram, ECG classification, neural networks, convolutional neural networks, portable document format

Procedia PDF Downloads 55

Authors: Maryam Kiani

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The aim of this study was to investigate the influence of nanoparticles additive on the properties of fly ash-based geopolymer. The geopolymer samples were prepared using fly ash as the primary source material, along with an alkali activator solution and different concentrations of carbon black additive. The effects of nanoparticles flexural strength, water absorption, and micro-structural properties of the cured samples. The results revealed that the inclusion of nanoparticles additive significantly enhanced the mechanical and electrical properties of the geopolymer binder. Micro-structural analysis using scanning electron microscopy (SEM) revealed a more compact and homogeneous structure in the geopolymer samples with nanoparticles. The dispersion of nanoparticles particles within the geopolymer matrix was observed, suggesting improved inter-particle bonding and increased density. Overall, this study demonstrates the positive impact of nanoparticles additive on the qualities of fly ash-based geopolymer, emphasizing its potential as an effective enhancer for geopolymer binder applications for the development of construction and infrastructure for energy buildings.

Keywords: fly-ash, geopolymer, energy buildings, nanotechnology

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Authors: Eva Tvrdá, Boris Botman, Marek Halenár, Tomáš Slanina, Norbert Lukáč

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In vitro storage and processing of animal semen represents a risk factor to spermatozoa vitality, potentially leading to reduced fertility. A variety of substances isolated from natural sources may exhibit protective or antioxidant properties on the spermatozoon, thus extending the lifespan of stored ejaculates. This study compared the ability of different concentrations of the Salvia officinalis extract on the motility, mitochondrial activity, viability and reactive oxygen species (ROS) production by bovine spermatozoa during different time periods (0, 2, 6 and 24 h) of in vitro culture. Spermatozoa motility was assessed using the Computer-assisted sperm analysis (CASA) system. Cell viability was examined using the metabolic activity MTT assay, the eosin-nigrosin staining technique was used to evaluate the sperm viability and ROS generation was quantified using luminometry. The CASA analysis revealed that the motility in the experimental groups supplemented with 0.5-2 µg/mL Salvia extract was significantly lower in comparison with the control (P<0.05; Time 24 h). At the same time, a long-term exposure of spermatozoa to concentrations ranging between 0.05 µg/mL and 2 µg/mL had a negative impact on the mitochondrial metabolism (P<0.05; Time 24 h). The viability staining revealed that 0.001-1 µg/mL Salvia extract had no effects on bovine male gametes, however 2 µg/mL Salvia had a persisting negative effect on spermatozoa (P<0.05). Furthermore 0.05-2 µg/mL Salvia exhibited an immediate ROS-promoting effect on the sperm culture (P>0.05; Time 0 h and 2 h), which remained significant throughout the entire in vitro culture (P<0.05; Time 24 h). Our results point out to the necessity to examine specific effects the biomolecules present in Salvia officinalis may have individually or collectively on the in vitro sperm vitality and oxidative profile.

Keywords: bulls, CASA, MTT test, reactive oxygen species, sage, Salvia officinalis, spermatozoa

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Authors: Jurriaan Gillissen

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This work is concerned with stabilizing the numerical integration of the Navier-Stokes equation (NSE), backwards in time. Applications involve the detection of sources of, e.g., sound, heat, and pollutants. Stable reverse numerical integration of parabolic differential equations is also relevant for image de-blurring. While the literature addresses the reverse integration problem of the advection-diffusion equation, the problem of numerical reverse integration of the NSE has, to our knowledge, not yet been addressed. Owing to the presence of viscosity, the NSE is irreversible, i.e., when going backwards in time, the fluid behaves, as if it had a negative viscosity. As an effect, perturbations from the perfect solution, due to round off errors or discretization errors, grow exponentially in time, and reverse integration of the NSE is inherently unstable, regardless of using an implicit time integration scheme. Consequently, some sort of filtering is required, in order to achieve a stable, numerical, reversed integration. The challenge is to find a filter with a minimal adverse affect on the accuracy of the reversed integration. In the present work, we explore an adjoint gradient method (AGM) to achieve this goal, and we apply this technique to two-dimensional (2D), decaying turbulence. The AGM solves for the initial velocity field u0 at t = 0, that, when integrated forward in time, produces a final velocity field u1 at t = 1, that is as close as is feasibly possible to some specified target field v1. The initial field u0 defines a minimum of a cost-functional J, that measures the distance between u1 and v1. In the minimization procedure, the u0 is updated iteratively along the gradient of J w.r.t. u0, where the gradient is obtained by transporting J backwards in time from t = 1 to t = 0, using the adjoint NSE. The AGM thus effectively replaces the backward integration by multiple forward and backward adjoint integrations. Since the viscosity is negative in the adjoint NSE, each step of the AGM is numerically stable. Nevertheless, when applied to turbulence, the AGM develops instabilities, which limit the backward integration to small times. This is due to the exponential divergence of phase space trajectories in turbulent flow, which produces a multitude of local minima in J, when the integration time is large. As an effect, the AGM may select unphysical, noisy initial conditions. In order to improve this situation, we propose two remedies. First, we replace the integration by a sequence of smaller integrations, i.e., we divide the integration time into segments, where in each segment the target field v1 is taken as the initial field u0 from the previous segment. Second, we add an additional term (regularizer) to J, which is proportional to a high-order Laplacian of u0, and which dampens the gradients of u0. We show that suitable values for the segment size and for the regularizer, allow a stable reverse integration of 2D decaying turbulence, with accurate results for more then O(10) turbulent, integral time scales.

Keywords: time reversed integration, parabolic differential equations, adjoint gradient method, two dimensional turbulence

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Authors: Bhavesh D. Gajbhiye, Divya Raghunandanan, C. S. Sona, Channamallikarjun S. Mathpati

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Molten fluoride salt FLiNaK (LiF-NaF-KF: 46.5-11.5-42 mol %) is a promising candidate as high temperature coolant for next generation nuclear reactors due to its superior thermophysical properties. Corrosion of alloys in molten FLiNaK has however been recognized as a serious issue in the selection of structural materials. Corrosion experiments of alloys Inconel-625 (Fe-Ni alloy) and Hastelloy-B (Ni-Mo alloy) were performed in FLiNaK salt. The tests were carried out at a temperature of 650°C in graphite crucibles for 60 hours under inert atmosphere. Corrosion experiments were performed to study the effect of moisture removal in the salt by pre heating and vacuum drying. Weight loss of the alloy samples due to corrosion was measured and corrosion rate was estimated. The surface morphology of the alloy samples was analyzed by Scanning Electron Microscopy. A significant decrease in the corrosion rate was observed for the alloys studied in moisture removed salt.

Keywords: FLiNaK, hastelloy, inconel, weight loss

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Authors: Ghazi Faisal Najmuldeen, Noridah Abdullah, Mimi Sakinah

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Bioethanol is an alcohol made by fermentation, mostly from carbohydrates, Cellulosic biomass, derived from non-food sources, such as castor shell waste, is also being developed as a feedstock for ethanol production Cellulose extracted from biomass sources is considered the future feedstock for many products due to the availability and eco-friendly nature of cellulose. In this study, castor shell (CS) biowaste resulted from the extraction of Castor oil from castor seeds was evaluated as a potential source of cellulose. The cellulose was extracted after pretreatment process was done on the CS. The pretreatment process began with the removal of other extractives from CS, then an alkaline treatment, bleaching process with hydrogen peroxide, and followed by a mixture of acetic and nitric acids. CS cellulose was analysed by infrared absorption spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). The result showed that the overall process was adequate to produce cellulose with high purity and crystallinity from CS waste. The cellulose was then hydrolyzed to produce glucose and then fermented to bioethanol.

Keywords: bioethanol, castor shell, cellulose, biowaste

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Authors: Kassahun Birhanu Tadesse, Megersa Olumana Dinka

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Reliable future river flow information is basic for planning and management of any river systems. For data scarce river system having only a river flow records like the Waterval River, a univariate time series models are appropriate for river flow forecasting. In this study, a univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for forecasting Waterval River flow using GRETL statistical software. Mean monthly river flows from 1960 to 2016 were used for modeling. Different unit root tests and Mann-Kendall trend analysis were performed to test the stationarity of the observed flow time series. The time series was differenced to remove the seasonality. Using the correlogram of seasonally differenced time series, different SARIMA models were identified, their parameters were estimated, and diagnostic check-up of model forecasts was performed using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AIc) and Hannan-Quinn (HQc) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 was selected as the best model for Waterval River flow forecasting. Therefore, this model can be used to generate future river information for water resources development and management in Waterval River system. SARIMA model can also be used for forecasting other similar univariate time series with seasonality characteristics.

Keywords: heteroscedasticity, stationarity test, trend analysis, validation, white noise

Procedia PDF Downloads 188

Authors: Artion Kashuri, Rozana Liko

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In this paper, the authors establish an integral identity using delta differentiable functions. By applying this identity, some new results via a general class of convex functions with respect to two nonnegative functions on a time scale are given. Also, for suitable choices of nonnegative functions, some special cases are deduced. Finally, in order to illustrate the efficiency of our main results, some applications to special means are obtained as well. We hope that current work using our idea and technique will attract the attention of researchers working in mathematical analysis, mathematical inequalities, numerical analysis, special functions, fractional calculus, quantum mechanics, quantum calculus, physics, probability and statistics, differential and difference equations, optimization theory, and other related fields in pure and applied sciences.

Keywords: convex functions, Hermite-Hadamard inequality, special means, time scale

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Authors: M. Abdel-Hamid, P. Saporito, R. V. Mateiu, A. Osman, E. Romeih, H. Jenssen

Abstract:

Camel milk whey (CMW) was hydrolyzed with papain from Carica papaya and fractionated by size exclusion chromatography (SEC). The antibacterial and anti-biofilm activity of the CMW, Camel milk whey hydrolysate (CMWH) and the obtained SEC-fractions was assessed against Pseudomonas aeruginosa and Methicillin-resistant Staphylococcus aureus (MRSA). SEC-F2 (fraction 2) exhibited antibacterial effectiveness against MRSA and P. aeruginosa with the minimum inhibitory concentration of 0.31 and 0.156 mg/ml, respectively. Furthermore, SEC-F2 significantly decreased biofilm biomass by 71% and 83 % for MRSA and P. aeruginosa in a crystal violet microplate assay. Scanning electron microscopy showed that the SEC-F2 caused changes in the treated bacterial cells. Additionally, LC/MS analysis was used to characterize the peptides of SEC-F2. Two major peptides were detected in SEC-F2 having masses of 414.05 Da and 456.06 Da. In conclusion, this study has demonstrated that hydrolysis of CMW with papain generates small and extremely potent antibacterial and anti-biofilm peptides against both MRSA and P. aeruginosa.

Keywords: camel milk, whey proteins, antibacterial peptide, anti-biofilm

Procedia PDF Downloads 200

Authors: R. C. Sharma, Rishabh Bansal, Prajwal Menon, Manoj K. Sharma

Abstract:

Silicon-air battery is highly promising for electric vehicles due to its high theoretical energy density (8470 Whkg⁻¹) and its discharge products are non-toxic. For the first time, pure silicon and germanium powders are used as anode material. Nickel wire meshes embedded with charcoal and manganese dioxide powder as cathode and concentrated potassium hydroxide is used as electrolyte. Voltage-time curves have been presented in this study for pure silicon and germanium powder and 5% and 10% germanium with silicon powder. Silicon powder cell assembly gives a stable voltage of 0.88 V for ~20 minutes while Si-Ge provides cell voltage of 0.80-0.76 V for ~10-12 minutes, and pure germanium cell provides cell voltage 0.80-0.76 V for ~30 minutes. The cell voltage is higher for concentrated (10%) sodium hydroxide solution (1.08 V) and it is stable for ~40 minutes. A sharp decrease in cell voltage beyond 40 min may be due to rapid corrosion.

Keywords: Silicon-air battery, Germanium-air battery, voltage-time curve, open circuit voltage, Anodic corrosion

Procedia PDF Downloads 217

Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

Abstract:

Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

Procedia PDF Downloads 121

Authors: Yen-Luan Chen

Abstract:

Maintenance has a great impact on the capacity of production and on the quality of the products, and therefore, it deserves continuous improvement. Maintenance procedure done before a failure is called preventive maintenance (PM). Sequential PM, which specifies that a system should be maintained at a sequence of intervals with unequal lengths, is one of the commonly used PM policies. This article proposes a generalized sequential PM policy for a system subject to shocks with imperfect maintenance and random working time. The shocks arrive according to a non-homogeneous Poisson process (NHPP) with varied intensity function in each maintenance interval. As a shock occurs, the system suffers two types of failures with number-dependent probabilities: type-I (minor) failure, which is rectified by a minimal repair, and type-II (catastrophic) failure, which is removed by a corrective maintenance (CM). The imperfect maintenance is carried out to improve the system failure characteristic due to the altered shock process. The sequential preventive maintenance-last (PML) policy is defined as that the system is maintained before any CM occurs at a planned time Ti or at the completion of a working time in the i-th maintenance interval, whichever occurs last. At the N-th maintenance, the system is replaced rather than maintained. This article first takes up the sequential PML policy with random working time and imperfect maintenance in reliability engineering. The optimal preventive maintenance schedule that minimizes the mean cost rate of a replacement cycle is derived analytically and determined in terms of its existence and uniqueness. The proposed models provide a general framework for analyzing the maintenance policies in reliability theory.

Keywords: optimization, preventive maintenance, random working time, minimal repair, replacement, reliability

Procedia PDF Downloads 250

Authors: Rupali, Anil Kumar Jaiswal

Abstract:

Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc.  Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively.  Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.

Keywords: physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model

Procedia PDF Downloads 147