Search results for: compressed exponential

Authors: J. Sharon Mano Pappu, Sathyanarayana N. Gummadi

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Growth of Debaryomyces nepalensis on mixed substrates in batch culture follows diauxic pattern of completely utilizing glucose during the first exponential growth phase, followed by an intermediate lag phase and a second exponential growth phase consuming xylose. The present study deals with the development of cybernetic mathematical model for prediction of xylitol production and yield. Production of xylitol from xylose in batch fermentation is investigated in the presence of glucose as the co-substrate. Different ratios of glucose and xylose concentrations are assessed to study the impact of multi substrate on production of xylitol in batch reactors. The parameters in the model equations were estimated from experimental observations using integral method. The model equations were solved simultaneously by numerical technique using MATLAB. The developed cybernetic model of xylose fermentation in the presence of a co-substrate can provide answers about how the ratio of glucose to xylose influences the yield and rate of production of xylitol. This model is expected to accurately predict the growth of microorganism on mixed substrate, duration of intermediate lag phase, consumption of substrate, production of xylitol. The model developed based on cybernetic modelling framework can be helpful to simulate the dynamic competition between the metabolic pathways.

Keywords: co-substrate, cybernetic model, diauxic growth, xylose, xylitol

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Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Saurabh Chaudhury, Sanjeet Kumar Sinha

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The MOSFET has been the main building block in high performance and low power VLSI chips for the last several decades. Device scaling is fundamental to technological advancements, which allows more devices to be integrated on a single die providing greater functionality per chip. Ultimately, the goal of scaling is to build an individual transistor that is smaller, faster, cheaper, and consumes less power. Scaling continued following Moore's law initially and now we see an exponential growth in today's nano scaled chip. However, device scaling to deep nano meter regime leads to exponential increase in leakage currents and excessive heat generation. Moreover, fabrication process variability causing a limitation to further scaling. Researchers believe that with a mix of chemistry, physics, and engineering, nano electronics may provide a solution to increasing fabrication costs and may allow integrated circuits to be scaled beyond the limits of the modern transistor. Carbon nano tube (CNT) and nano wires (NW) based FETs have been analyzed and characterized in laboratory and also been demonstrated as prototypes. This work presents an extensive simulation based study and analysis of CNTFET and NW-FET devices and comparison of the results with conventional MOSFET. From this study, we can conclude that these devices have got some excellent properties and favorable characteristics which will definitely lead the future semiconductor devices in post silicon era.

Keywords: carbon nanotube, nanowire FET, low power, nanoscaled devices, VLSI

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Authors: Abhishek Pandey

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Ibuprofen and Acetaminophen is widely used as prescription & non-prescription medicine. Ibuprofen mainly used in the treatment of mild to moderate pain related to headache, migraine, postoperative condition and in the management of spondylitis, osteoarthritis and rheumatoid arthritis. Acetaminophen is used as an analgesic and antipyretic drug. Ibuprofen having high tendency of sticking to punches of tablet punching machine while Acetaminophen is not ordinarily compressible to tablet formulation because Acetaminophen crystals are very hard and brittle in nature and fracture very easily when compressed producing capping and laminating tablet defects therefore wet granulation method is used to make them compressible. The aim of study was to prepare Ibuprofen and Acetaminophen tablets by direct compression and top spray granulation technique. In this Investigation tablets were prepared by using directly compressible grade excipients. Dibasic calcium phosphate, lactose anhydrous (DCL21), microcrystalline cellulose (Avicel PH 101). In order to obtain best or optimized formulation, nine different formulations were generated among them batch F7, F8, F9 shows good results and within the acceptable limit. Formulation (F7) selected as optimize product on the basis of dissolution study. Furtherly, directly compressible granules of both drugs were prepared by using top spray granulation technique in fluidized bed processor equipment and compressed .In order to obtain best product process optimization was carried out by performing four trials in which various parameters like inlet air temperature, spray rate, peristaltic pump rpm, % LOD, properties of granules, blending time and hardness were optimized. Batch T3 coined as optimized batch on the basis physical & chemical evaluation. Finally formulations prepared by both techniques were compared.

Keywords: direct compression, top spray granulation, process optimization, blending time

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Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree

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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.

Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data

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Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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The solution of the nonlinear dynamic equilibrium equations of base-isolated structures adopting a conventional monolithic solution approach, i.e. an implicit single-step time integration method employed with an iteration procedure, and the use of existing nonlinear analytical models, such as differential equation models, to simulate the dynamic behavior of seismic isolators can require a significant computational effort. In order to reduce numerical computations, a partitioned solution method and a one dimensional nonlinear analytical model are presented in this paper. A partitioned solution approach can be easily applied to base-isolated structures in which the base isolation system is much more flexible than the superstructure. Thus, in this work, the explicit conditionally stable central difference method is used to evaluate the base isolation system nonlinear response and the implicit unconditionally stable Newmark’s constant average acceleration method is adopted to predict the superstructure linear response with the benefit in avoiding iterations in each time step of a nonlinear dynamic analysis. The proposed mathematical model is able to simulate the dynamic behavior of seismic isolators without requiring the solution of a nonlinear differential equation, as in the case of widely used differential equation model. The proposed mixed explicit-implicit time integration method and nonlinear exponential model are adopted to analyze a three dimensional seismically isolated structure with a lead rubber bearing system subjected to earthquake excitation. The numerical results show the good accuracy and the significant computational efficiency of the proposed solution approach and analytical model compared to the conventional solution method and mathematical model adopted in this work. Furthermore, the low stiffness value of the base isolation system with lead rubber bearings allows to have a critical time step considerably larger than the imposed ground acceleration time step, thus avoiding stability problems in the proposed mixed method.

Keywords: base-isolated structures, earthquake engineering, mixed time integration, nonlinear exponential model

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Authors: Yeliz Karaca, Carlo Cattani

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This study focuses on the local Holder exponent as a measure of the function regularity for time series related to finance data. In this study, the attributes of the finance dataset belonging to 13 countries (India, China, Japan, Sweden, France, Germany, Italy, Australia, Mexico, United Kingdom, Argentina, Brazil, USA) located in 5 different continents (Asia, Europe, Australia, North America and South America) have been examined.These countries are the ones mostly affected by the attributes with regard to financial development, covering a period from 2012 to 2017. Our study is concerned with the most important attributes that have impact on the development of finance for the countries identified. Our method is comprised of the following stages: (a) among the multi fractal methods and Brownian motion Holder regularity functions (polynomial, exponential), significant and self-similar attributes have been identified (b) The significant and self-similar attributes have been applied to the Artificial Neuronal Network (ANN) algorithms (Feed Forward Back Propagation (FFBP) and Cascade Forward Back Propagation (CFBP)) (c) the outcomes of classification accuracy have been compared concerning the attributes that have impact on the attributes which affect the countries’ financial development. This study has enabled to reveal, through the application of ANN algorithms, how the most significant attributes are identified within the relevant dataset via the Holder functions (polynomial and exponential function).

Keywords: artificial neural networks, finance data, Holder regularity, multifractals

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Authors: Blair D. Macdonald

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After nearly one hundred years of its origin, foundational quantum mechanics remains one of the greatest unexplained mysteries in physicists today. Within this time, chaos theory and its geometry, the fractal, has developed. In this paper, the propagation behaviour with an iteration of a simple fractal, the Koch Snowflake, was described and analysed. From an arbitrary observation point within the fractal set, the fractal propagates forward by oscillation—the focus of this study and retrospectively behind by exponential growth from a point beginning. It propagates a potentially infinite exponential oscillating sinusoidal wave of discrete triangle bits sharing many characteristics of light and quantum entities. The model's wave speed is potentially constant, offering insights into the perception and a direction of time where, to an observer, when travelling at the frontier of propagation, time may slow to a stop. In isolation, the fractal is a superposition of component bits where position and scale present a problem of location. In reality, this problem is experienced within fractal landscapes or fields where 'position' is only 'known' by the addition of information or markers. The quantum' measurement problem', 'uncertainty principle,' 'entanglement,' and the classical-quantum interface are addressed; these are a problem of scale invariance associated with isolated fractality. Dual forward and retrospective perspectives of the fractal model offer the opportunity for unification between quantum mechanics and cosmological mathematics, observations, and conjectures. Quantum and cosmological problems may be different aspects of the one fractal geometry.

Keywords: measurement problem, observer, entanglement, unification

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Authors: Damir Latypov

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A hybrid classical-quantum algorithm to solve boundary integral equations (BIE) arising in problems of electromagnetic and acoustic scattering is proposed. The quantum speed-up is due to a Quantum Linear System Algorithm (QLSA). The original QLSA of Harrow et al. provides an exponential speed-up over the best-known classical algorithms but only in the case of sparse systems. Due to the non-local nature of integral operators, matrices arising from discretization of BIEs, are, however, dense. A QLSA for dense matrices was introduced in 2017. Its runtime as function of the system's size N is bounded by O(√Npolylog(N)). The run time of the best-known classical algorithm for an arbitrary dense matrix scales as O(N².³⁷³). Instead of exponential as in case of sparse matrices, here we have only a polynomial speed-up. Nevertheless, sufficiently high power of this polynomial, ~4.7, should make QLSA an appealing alternative. Unfortunately for the QLSA, the asymptotic separability of the Green's function leads to high compressibility of the BIEs matrices. Classical fast algorithms such as Multilevel Fast Multipole Method (MLFMM) take advantage of this fact and reduce the runtime to O(Nlog(N)), i.e., the QLSA is only quadratically faster than the MLFMM. To be truly impactful for computational electromagnetics and acoustics engineers, QLSA must provide more substantial advantage than that. We propose a computational scheme which combines elements of the classical fast algorithms with the QLSA to achieve the required performance.

Keywords: quantum linear system algorithm, boundary integral equations, dense matrices, electromagnetic scattering theory

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Authors: T. Penchev, D. Karastoyanov

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The results from experimental research of deformation by upsetting and die forging of lead specimens wit controlled impact are presented. Laboratory setup for conducting the investigations, which uses cold rocket engine operated with compressed air, is described. The results show that when using controlled impact is achieving greater plastic deformation and consumes less impact energy than at ordinary impact deformation process.

Keywords: rocket engine, forging hammer, sticking impact, plastic deformation

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Authors: BoSheng Liu

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The research goal is to re-image a locally-sourced waste product as abuilding material. The author aims to contribute to the compressed stabilized earth block (CSEB) by investigating the promising role of dredged material as an alternative building ingredient in the production of bricks and tiles. Dredged material comes from the sediment deposited near the shore or downstream, where the water current velocity decreases. This sediment needs to be dredged to provide water transportation; thus, there are mounds of the dredged material stored at bay. It is the interest of this research to reduce the filtered un-organic soil in the production of CSEB and replace it with locally dredged material from the Atchafalaya River in Morgan City, Louisiana. Technology and mechanical innovations have evolved the traditional adobe production method, which mixes the soil and natural fiber into molded bricks, into chemically stabilized CSEB made by compressing the clay mixture and stabilizer in a compression chamber with particular loads. In the case of dredged material CSEB (DM-CSEB), cement plays an essential role as the bending agent contributing to the unit strength while sustaining the filtered un-organic soil. Each DM-CSEB unit is made in a compression chamber with 580 PSI (i.e., 4 MPa) force. The research studied the cement content from 5% to 10% along with the range of dredged material mixtures, which differed from 20% to 80%. The material mixture content affected the DM-CSEB's strength and workability during and after its compression. Results indicated two optimal workabilities of the mixture: 27% fine clay content and 63% dredged material with 10% cement, or 28% fine clay content, and 67% dredged material with 5% cement. The final product of DM-CSEB emitted between 10 to 13 times fewer carbon emissions compared to the conventional fired masonry structure. DM-CSEB satisfied the strength requirement given by the ASTM C62 and ASTM C34 standards for construction material. One of the final evaluations tested and validated the material performance by designing and constructing an architectural, conical tile-vault prototype that was 28" by 40" by 24." The vault utilized a computational form-finding approach to generate the form's geometry, which optimized the correlation between the vault geometry and structural load distribution. A series of scaffolding was deployed to create the framework for the tile-vault construction. The final tile-vault structure was made from 2 layers of DM-CSEB tiles jointed by mortar, and the construction of the structure used over 110 tiles. The tile-vault prototype was capable of carrying over 400 lbs of live loads, which further demonstrated the dredged material feasibility as a construction material. The presented case study of Dredged Material Compressed Stabilized Earth Block (DM-CSEB) provides the first impression of dredged material in the clayey mixture process, structural performance, and construction practice. Overall, the approach of integrating dredged material in building material can be feasible, regionally sourced, cost-effective, and environment-friendly.

Keywords: dredged material, compressed stabilized earth block, tile-vault, regionally sourced, environment-friendly

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Authors: Mhenga Agneta, Li Zhaomin, Zhang Chao

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When velocity is high enough, gas can entrain fluid and carry to the surface, but as time passes by, velocity drops to a critical point where fluids will start to hold up in the tubing and cause liquid loading which prevents gas production and may lead to the death of the well. Foam injection is widely used as one of the methods to unload liquid. Since wells have different characteristics, it is not guaranteed that foam can be applied in all of them and bring successful results. This research presents a technology to optimize the efficiency of foam to unload liquid by air compression. Two methods are used to explain optimization; (i) mathematical formulas are used to solve and explain the myth of how density and critical velocity could be minimized when air is compressed into foaming agents, then the relationship between flow rates and pressure increase which would boost up the bottom hole pressure and increase the velocity to lift liquid to the surface. (ii) Experiments to test foam carryover capacity and stability as a function of time and surfactant concentration whereby three surfactants anionic sodium dodecyl sulfate (SDS), nonionic Triton 100 and cationic hexadecyltrimethylammonium bromide (HDTAB) were probed. The best foaming agents were injected to lift liquid loaded in a created vertical well model of 2.5 cm diameter and 390 cm high steel tubing covered by a transparent glass casing of 5 cm diameter and 450 cm high. The results show that, after injecting foaming agents, liquid unloading was successful by 75%; however, the efficiency of foaming agents to unload liquid increased by 10% with an addition of compressed air at a ratio of 1:1. Measured values and calculated values were compared and brought about ± 3% difference which is a good number. The successful application of the technology indicates that engineers and stakeholders could bring water flooded gas wells back to production with optimized results by firstly paying attention to the type of surfactants (foaming agents) used, concentration of surfactants, flow rates of the injected surfactants then compressing air to the foaming agents at a proper ratio.

Keywords: air compression, foaming agents, gas well, liquid loading

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Authors: Ella Tyuryumina, Alexey Neznanov

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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

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Authors: Ahmed E. Hodaib, Muhammed A. Hashem

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High-speed transportation has become a growing concern. To increase high-speed efficiencies and minimize power consumption of a vehicle, we need to eliminate the friction with the ground and minimize the aerodynamic drag acting on the vehicle. Due to the complexity and high power requirements of electromagnetic levitation, we make use of the air in front of the capsule, that produces the majority of the drag, to compress it in two phases and inject a proportion of it through small nozzles to make a high-pressure air cushion to levitate the capsule. The tube is partially-evacuated so that the air pressure is optimized for maximum compressor effectiveness, optimum tube size, and minimum vacuum pump power consumption. The total relative mass flow rate of the tube air is divided into two fractions. One is by-passed to flow over the capsule body, ensuring that no chocked flow takes place. The other fraction is sucked by the compressor where it is diffused to decrease the Mach number (around 0.8) to be suitable for the compressor inlet. The air is then compressed and intercooled, then split. One fraction is expanded through a tail nozzle to contribute to generating thrust. The other is compressed again. Bleed from the two compressors is used to maintain a constant air pressure in an air tank. The air tank is used to supply air for levitation. Dividing the total mass flow rate increases the achievable speed (Kantrowitz limit), and compressing it decreases the blockage of the capsule. As a result, the aerodynamic drag on the capsule decreases. As the tube pressure decreases, the drag decreases and the capsule power requirements decrease, however, the vacuum pump consumes more power. That’s why Design optimization techniques are to be used to get the optimum values for all the design variables given specific design inputs. Aerodynamic shape optimization, Capsule and tube sizing, compressor design, diffuser and nozzle expander design and the effect of the air bearing on the aerodynamics of the capsule are to be considered. The variations of the variables are to be studied for the change of the capsule velocity and air pressure.

Keywords: tube-capsule, hyperloop, aerodynamic design optimization, air compressor, air bearing

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Authors: Shidvash Vakilipour, Masoud Mohammadi, Rouzbeh Riazi, Scott Ormiston, Kimia Amiri, Sahar Barati

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An essential component of a finite volume method (FVM) is the advection scheme that estimates values on the cell faces based on the calculated values on the nodes or cell centers. The most widely used advection schemes are upwind schemes. These schemes have been developed in FVM on different kinds of structured and unstructured grids. In this research, the physical influence scheme (PIS) is developed for a cell-centered FVM that uses an implicit coupled solver. Results are compared with the exponential differencing scheme (EDS) and the skew upwind differencing scheme (SUDS). Accuracy of these schemes is evaluated for a lid-driven cavity flow at Re = 1000, 3200, and 5000 and a backward-facing step flow at Re = 800. Simulations show considerable differences between the results of EDS scheme with benchmarks, especially for the lid-driven cavity flow at high Reynolds numbers. These differences occur due to false diffusion. Comparing SUDS and PIS schemes shows relatively close results for the backward-facing step flow and different results in lid-driven cavity flow. The poor results of SUDS in the lid-driven cavity flow can be related to its lack of sensitivity to the pressure difference between cell face and upwind points, which is critical for the prediction of such vortex dominant flows.

Keywords: cell-centered finite volume method, coupled solver, exponential differencing scheme (EDS), physical influence scheme (PIS), pressure weighted interpolation method (PWIM), skew upwind differencing scheme (SUDS)

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Authors: Eronini Iheanyi Umez-Eronini

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Most studies and existing implementations of compressed air energy storage (CAES) coupled with a wind farm to overcome intermittency and variability of wind power are based on bulk or centralized CAES plants. A dynamic model of a hybrid wind farm with wind turbines and distributed CAES, consisting of air storage tanks and compressor and expander trains at each wind turbine station, is developed and simulated in MATLAB. An ad hoc supervisory controller, in which the wind turbines are simply operated under classical power optimizing region control while scheduling power production by the expanders and air storage by the compressors, including modulation of the compressor power levels within a control range, is used to regulate overall farm power production to track minute-scale (3-minutes sampling period) TSO absolute power reference signal, over an eight-hour period. Simulation results for real wind data input with a simple wake field model applied to a hybrid plant composed of ten 5-MW wind turbines in a row and ten compatibly sized and configured Diabatic CAES stations show the plant controller is able to track the power demand signal within an error band size on the order of the electrical power rating of a single expander. This performance suggests that much improved results should be anticipated when the global D-CAES control is combined with power regulation for the individual wind turbines using available approaches for wind farm active power control. For standalone power plant fuel electrical efficiency estimate of up to 60%, the round trip electrical storage efficiency computed for the distributed CAES wherein heat generated by running compressors is utilized in the preheat stage of running high pressure expanders while fuel is introduced and combusted before the low pressure expanders, was comparable to reported round trip storage electrical efficiencies for bulk Adiabatic CAES.

Keywords: hybrid wind farm, distributed CAES, diabatic CAES, active power control, dynamic modeling and simulation

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Authors: Farnia Nayar Parshi, Mohammad Shariful Islam

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Though earth construction is an ancient technology, researchers are working on increasing its strength by adding different types of stabilizers. Ordinary Portland cement for sandy soil and lime for clayey soil is very popular practice as well as recommended by various authorities for making stabilized blocks for satisfactory performance. The addition of these additives improves compressive strength but fails to improve ductility. The addition of both synthetic and natural fibers increases both compressive strength and ductility. Studies are conducted to make earth blocks more cost-effective, energy-efficient and sustainable. In this experiment, an agricultural waste banana fiber and biochar is used to study the compressive stress-strain behavior of earth blocks made with four types of soil low plastic clay, sandy low plastic clay, very fine sand and medium to fine sand. Biochar is a charcoal-like carbon usually produced from organic or agricultural waste in high temperatures through a controlled condition called pyrolysis. In this experimental study, biochar was collected from BBI (Bangladesh Biochar Initiative) produced from wood flakes around 400 deg. Celsius. Locally available PPC (Portland Pozzolana Cement) is used. 5 cm × 5 cm × 5 cm earth blocks were made with eight different combinations such as bare soil, soil with 6% cement, soil with 6% cement and 5% biochar, soil with 6% cement, 5% biochar and 1% fiber, soil with 1% fiber, soil with 5% biochar and 1% fiber and soil with 6% cement and 1% fiber. All samples were prepared with 10-12% water content. Uniaxial compressive strength tests were conducted on 21 days old earth blocks. Stress-strain diagram shows that the addition of banana fiber improved compressive strength drastically, but the combined effect of fiber and biochar is different based on different soil types. For clayey soil, 6% cement and 1% fiber give maximum compressive strength of 991 kPa, and for very fine sand, a combination of 5% biochar, 6% cement and 1% fiber gives maximum compressive strength of 522 kPa as well as ductility. For medium-to-find sand, 6% cement and 1% fiber give the best result, 1530 kPa, among other combinations. The addition of fiber increases not only ductility but also compressive strength as well. The effect of biochar with fiber varies with the soil type.

Keywords: banana fiber, biochar, cement, compressed stabilized earth blocks, compressive strength

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Authors: Pranjali Sharma, Swati Neogi

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Composite pressure vessels are low weight structures mainly used in a variety of applications such as automobiles, aeronautics and chemical engineering. Fiber reinforced polymer (FRP) composite materials offer the simplicity of design and use, high fuel storage capacity, rapid refueling capability, excellent shelf life, minimal infrastructure impact, high safety due to the inherent strength of the pressure vessel, and little to no development risk. Apart from these preliminary merits, the subsidized weight of composite vessels over metallic cylinders act as the biggest asset to the automotive industry, increasing the fuel efficiency. The result is a lightweight, flexible, non-explosive, and non-fragmenting pressure vessel that can be tailor-made to attune with specific applications. The winding pattern of the composite over-wrap is a primary focus while designing a pressure vessel. The critical stresses in the system depend on the thickness, angle and sequence of the composite layers. The composite over-wrap is wound over a plastic liner, whose geometry can be varied for the ease of winding. In the present study, we aim to optimize the FRP vessel geometry that provides an ease in winding and also aids in weight reduction for enhancing the vessel performance. Finite element analysis is used to study the effect of dome geometry, yielding a design with maximum value of burst pressure and least value of vessel weight. The stress and strain analysis of different dome ends along with the cylindrical portion is carried out in ANSYS 19.2. The failure is predicted using different failure theories like Tsai-Wu theory, Tsai-Hill theory and Maximum stress theory. Corresponding to a given winding sequence, the optimum dome geometry is determined for a fixed internal pressure to identify the theoretical value of burst pressure. Finally, this geometry is used to decrease the number of layers to reach the set value of safety in accordance with the available safety standards. This results in decrease in the weight of the composite over-wrap and manufacturing cost of the pressure vessel. An improvement in the overall weight performance of the pressure vessel gives higher fuel efficiency for its use in automobile applications.

Keywords: Compressed Gas Storage, Dome geometry, Theoretical Analysis, Type-4 Composite Pressure Vessel, Improvement in Vessel Weight Performance

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

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In this paper, first, we propose least support orthogonal matching pursuit (LS-OMP) algorithm to improve the performance, of the OMP (orthogonal matching pursuit) algorithm. LS-OMP algorithm adaptively chooses optimum L (least part of support), at each iteration. This modification helps to reduce the computational complexity significantly and performs better than OMP algorithm. Second, we give the procedure for the invisible image watermarking in the presence of compressive sampling. The image reconstruction based on a set of watermarked measurements is performed using LS-OMP.

Keywords: compressed sensing, orthogonal matching pursuit, restricted isometry property, signal reconstruction, least support orthogonal matching pursuit, watermark

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Authors: Sujata S. Kulkarni

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Effective and efficient texture feature extraction and classification is an important problem in image understanding and recognition. This paper gives a review on effective texture classification method. The objective of the problem of texture representation is to reduce the amount of raw data presented by the image, while preserving the information needed for the task. Texture analysis is important in many applications of computer image analysis for classification include industrial and biomedical surface inspection, for example for defects and disease, ground classification of satellite or aerial imagery and content-based access to image databases.

Keywords: compressed sensing, feature extraction, image classification, texture analysis

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Authors: Rajesh Karki, Safal Bhattarai, Saket Adhikari

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Reliable and economic operation of power systems are becoming extremely challenging with large scale integration of renewable energy sources due to the intermittency and uncertainty associated with renewable power generation. It is, therefore, important to make a quantitative risk assessment and explore the potential resources to mitigate such risks. Probabilistic models for different energy storage systems (ESS), such as the flywheel energy storage system (FESS) and the compressed air energy storage (CAES) incorporating specific charge/discharge performance and failure characteristics suitable for probabilistic risk assessment in power system operation and planning are presented in this paper. The proposed methodology used in FESS modelling offers flexibility to accommodate different configurations of plant topology. It is perceived that CAES has a high potential for grid-scale application, and a hybrid approach is proposed, which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The proposed ESS models are applied to a test system to investigate the economic and reliability benefits of the energy storage technologies in system operation and planning, as well as to assess their contributions in facilitating wind integration during different operating scenarios. A comparative study considering various storage system topologies are also presented. The impacts of failure rates of the critical components of ESS on the expected state of charge (SOC) and the performance of the different types of ESS during operation are illustrated with selected studies on the test system. The paper also applies the proposed models on the test system to investigate the economic and reliability benefits of the different ESS technologies and to evaluate their contributions in facilitating wind integration during different operating scenarios and system configurations. The conclusions drawn from the study results provide valuable information to help policymakers, system planners, and operators in arriving at effective and efficient policies, investment decisions, and operating strategies for planning and operation of power systems with large penetrations of renewable energy sources.

Keywords: flywheel energy storage, compressed air energy storage, power system reliability, renewable energy, system planning, system operation

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Authors: Foo Shen Hwang, Thomas Confrey, Stephen Scully, Barry Flannery

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Thermal characterization plays an important role in battery pack design. Lithium-ion batteries have to be maintained between 15-35 °C to operate optimally. Heat is generated (Q) internally within the batteries during both the charging and discharging phases. This can be quantified using several standard methods. The most common method of calculating the batteries heat generation is through the addition of both the joule heating effects and the entropic changes across the battery. In addition, such values can be derived by identifying the open-circuit voltage (OCV), nominal voltage (V), operating current (I), battery temperature (T) and the rate of change of the open-circuit voltage in relation to temperature (dOCV/dT). This paper focuses on experimental characterization and comparative modelling of the heat generation rate (Q) across several current discharge rates (0.5C, 1C, and 1.5C) of a 18650 cell. The analysis is conducted utilizing several non-linear mathematical functions methods, including polynomial, exponential, and power models. Parameter fitting is carried out over the respective function orders; polynomial (n = 3~7), exponential (n = 2) and power function. The generated parameter fitting functions are then used as heat source functions in a 3-D computational fluid dynamics (CFD) solver under natural convection conditions. Generated temperature profiles are analyzed for errors based on experimental discharge tests, conducted at standard room temperature (25°C). Initial experimental results display low deviation between both experimental and CFD temperature plots. As such, the heat generation function formulated could be easier utilized for larger battery applications than other methods available.

Keywords: computational fluid dynamics, curve fitting, lithium-ion battery, voltage drop

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Authors: Said Ali Al-Hadhrami, Amer Ibrahim Al-Omari

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In this paper, Bayesian estimation for the mean of exponential distribution is considered using Moving Extremes Ranked Set Sampling (MERSS). Three priors are used; Jeffery, conjugate and constant using MERSS and Simple Random Sampling (SRS). Some properties of the proposed estimators are investigated. It is found that the suggested estimators using MERSS are more efficient than its counterparts based on SRS.

Keywords: Bayesian, efficiency, moving extreme ranked set sampling, ranked set sampling

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Authors: Coriolano Salvini, Ambra Giovannelli

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The use of renewable energy sources for electric power production leads to reduced CO2 emissions and contributes to improving the domestic energy security. On the other hand, the intermittency and unpredictability of their availability poses relevant problems in fulfilling safely and in a cost efficient way the load demand along the time. Significant benefits in terms of “grid system applications”, “end-use applications” and “renewable applications” can be achieved by introducing energy storage systems. Among the currently available solutions, CAES (Compressed Air Energy Storage) shows favorable features. Small-medium size plants equipped with artificial air reservoirs can constitute an interesting option to get efficient and cost-effective distributed energy storage systems. The present paper is addressed to the design and off-design analysis of the compression system of small size CAES plants suited to absorb electric power in the range of hundreds of kilowatt. The system of interest is constituted by an intercooled (in case aftercooled) multi-stage reciprocating compressor and a man-made reservoir obtained by connecting large diameter steel pipe sections. A specific methodology for the system preliminary sizing and off-design modeling has been developed. Since during the charging phase the electric power absorbed along the time has to change according to the peculiar CAES requirements and the pressure ratio increases continuously during the filling of the reservoir, the compressor has to work at variable mass flow rate. In order to ensure an appropriately wide range of operations, particular attention has been paid to the selection of the most suitable compressor capacity control device. Given the capacity regulation margin of the compressor and the actual level of charge of the reservoir, the proposed approach allows the instant-by-instant evaluation of minimum and maximum electric power absorbable from the grid. The developed tool gives useful information to appropriately size the compression system and to manage it in the most effective way. Various cases characterized by different system requirements are analysed. Results are given and widely discussed.

Keywords: artificial air storage reservoir, compressed air energy storage (CAES), compressor design, compression system management.

Procedia PDF Downloads 201

Authors: A. Pietro Rimoldi, B. Anilkumar Gopinath, C. Minimol Korulla

Abstract:

Coastal engineering structure is conventionally designed for a shorter planning horizon usually 20 years. These structures are subjected to different offshore climatic externalities like waves, tides, tsunamis etc. during the design life period. The probability of occurrence of these different offshore climatic externalities varies. The impact frequently caused by these externalities on the structures is of concern because it has a significant bearing on the capital /operating cost of the project. There can also be repeated short time occurrence of these externalities in the assumed planning horizon which can cause heavy damage to the conventional coastal structure which are mainly made of rock. A replacement of the damaged portion to prevent complete collapse is time consuming and expensive when dealing with hard rock structures. But if coastal structures are made of Geo-synthetic containment systems such replacement is quickly possible in the time period between two successive occurrences. In order to have a better knowledge and to enhance the predictive capacity of these occurrences, this study estimates risk of encounter within the design life period of various externalities based on the concept of exponential distribution. This gives an idea of the frequency of occurrences which in turn gives an indication of whether replacement is necessary and if so at what time interval such replacements have to be effected. To validate this theoretical finding, a pilot project has been taken up in the field so that the impact of the externalities can be studied both for a hard rock and a Geosynthetic tube structure. The paper brings out the salient feature of a case study which pertains to a project in which Geosynthetic tubes have been used for reformation of a seawall adjacent to a conventional rock structure in Alappuzha coast, Kerala, India. The effectiveness of the Geosystem in combatting the impact of the short-term externalities has been brought out.

Keywords: climatic externalities, exponential distribution, geosystems, planning horizon

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Authors: Seyed Nima Tayarani Bathaie

Abstract:

In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.

Keywords: face detection algorithm, Haar features, security of ATM

Procedia PDF Downloads 389

Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Iftikhar Ahmad, A. Benallegue, A. El Hadri

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In this paper, we have proposed an observer for the reconstruction and a control law for the rejection application of unknown bounded external disturbance in a dynamical system. The strategy of both the observer and the controller is designed like a second order sliding mode with a proportional-integral (PI) term. Lyapunov theory is used to prove the exponential convergence and stability. Simulations results are given to show the performance of this method.

Keywords: non-linear systems, sliding mode observer, disturbance rejection, nonlinear control

Procedia PDF Downloads 310

Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Mohammad R. Rahim, Shagil Akhtar, Prem K. Bharti, Syed Muneeb Iqbal

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Deformation and energy absorption studies with corrugated tubes where corrugation is perpendicular to the line of action which coincides exactly with the unstrained axis of the tubes. In the present study, several specimens with various geometric parameters are prepared and compressed quasi-statistically in ANSYS Workbench. It is observed that tubes with perpendicular corrugation alters the deformation condition considerably and culminates in a substantial escalation in energy absorption scope in juxtaposed with the tubes having a circular cross-section. This study will help automotive, aerospace and various other industries to design superior components with perpendicular corrugated tubes and will reduce the experimental trials by conducting the numerical simulations.

Keywords: ANSYS Workbench, deformation and energy absorption, corrugated tubes, quasi-static compression

Procedia PDF Downloads 354