Search results for: cruise speed optimization

Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

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Authors: Youssef Mazloum, Haytham Sayah, Maroun Nemer

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The penetration of renewable energy sources into the electric grid is significantly increasing. However, the intermittence of these sources breaks the balance between supply and demand for electricity. Hence, the importance of the energy storage technologies, they permit restoring the balance and reducing the drawbacks of intermittence of the renewable energies. This paper discusses the modeling and the cost-effectiveness of an isobaric adiabatic compressed air energy storage (IA-CAES) system. The proposed system is a combination among a compressed air energy storage (CAES) system with pumped hydro storage system and thermal energy storage system. The aim of this combination is to overcome the disadvantages of the conventional CAES system such as the losses due to the storage pressure variation, the loss of the compression heat and the use of fossil fuel sources. A steady state model is developed to perform an energy and exergy analyses of the IA-CAES system and calculate the distribution of the exergy losses in the latter system. A sensitivity analysis is also carried out to estimate the effects of some key parameters on the system’s efficiency, such as the pinch of the heat exchangers, the isentropic efficiency of the rotating machinery and the pressure losses. The conducted sensitivity analysis is a local analysis since the sensibility of each parameter changes with the variation of the other parameters. Therefore, an exergoeconomic study is achieved as well as a cost optimization in order to reduce the electricity cost produced during the production phase. The optimizer used is OmOptim which is a genetic algorithms based optimizer.

Keywords: cost-effectiveness, Exergoeconomic analysis, isobaric adiabatic compressed air energy storage (IA-CAES) system, thermodynamic modeling

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Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

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In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

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Authors: P. Leo, E. Cerri, L. Fratini, G. Buffa

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The Friction Stir Welding process uses an inert rotating mandrel and a force on the mandrel normal to the plane of the sheets to generate the frictional heat. The heat and the stirring action of the mandrel create a bond between the two sheets without melting the base metal. As matter of fact, the use of a solid state welding process limits the insurgence of defects, due to the presence of gas in melting bath, and avoids the negative effects of materials metallurgical transformation strictly connected with the change of phase. The industrial importance of Ti-6Al-4V alloy is well known. It provides an exceptional good balance of strength, ductility, fatigue and fracture properties together with good corrosion resistance and good metallurgical stability. In this paper, the authors analyze the microstructure of friction stir welded joints of Ti-6Al-4V processed at the same travel speed (35 mm/min) but at different rotation speeds (300-500 rpm). The microstructure of base material (BM), as result from both optical microscope and scanning electron microscope analysis is not homogenous. It is characterized by distorted α/β lamellar microstructure together with smashed zone of fragmented β layer and β retained grain boundary phase. The BM has been welded in the-as received state, without any previous heat treatment. Even the microstructure of the transverse and longitudinal sections of joints is not homogeneous. Close to the top of weld cross sections a much finer microstructure than the initial condition has been observed, while in the center of the joints the microstructure is less refined. Along longitudinal sections, the microstructure is characterized by equiaxed grains and lamellae. Both the length and area fraction of lamellas increases with distance from longitudinal axis. The hardness of joints is higher than that of BM. As the process temperature increases the average microhardness slightly decreases.

Keywords: friction stir welding, microhardness, microstructure, Ti-6Al-4V

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Authors: Zoran Herceg, Višnja Stulić, Anet Režek Jambrak, Tomislava Vukušić

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Electrical discharge plasma is a new non-thermal processing technique which is used for the inactivation of contaminating and hazardous microbes in liquids. Plasma is a source of different antimicrobial species including UV photons, charged particles, and reactive species such as superoxide, hydroxyl radicals, nitric oxide and ozone. Escherichia coli was studied as foodborne pathogen. The aim of this work was to examine inactivation effects of electrical discharge plasma treatment on the Escherichia coli MG 1655 in pure culture. Two types of plasma configuration and polarity were used. First configuration was with titanium wire as high voltage needle and another with medical stainless steel needle used to form bubbles in treated volume and titanium wire as high voltage needle. Model solution samples were inoculated with Escerichia coli MG 1655 and treated by electrical discharge plasma at treatment time of 5 and 10 min, and frequency of 60, 90 and 120 Hz. With the first configuration after 5 minutes of treatment at frequency of 120 Hz the inactivation rate was 1.3 log₁₀ reduction and after 10 minutes of treatment the inactivation rate was 3.0 log₁₀ reduction. At the frequency of 90 Hz after 10 minutes inactivation rate was 1.3 log₁₀ reduction. With the second configuration after 5 minutes of treatment at frequency of 120 Hz the inactivation rate was 1.2 log₁₀ reduction and after 10 minutes of treatment the inactivation rate was also 3.0 log₁₀ reduction. In this work it was also examined the formation of biofilm, nucleotide and protein leakage at 260/280 nm, before and after treatment and recuperation of treated samples. Further optimization of method is needed to understand mechanism of inactivation.

Keywords: electrical discharge plasma, escherichia coli MG 1655, inactivation, point-to-plate electrode configuration

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Authors: Biruk Abate

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Evaporative cooling occurs when air with high temperature and reduced humidity passes over a wet porous surface and a higher degree of cooling process is achieved for storage of fruits and vegetables due to greater rate of evaporation. The main objective of this reviewed study is to understand the effect of evaporative surface pad thickness and geometric configuration on the saturation efficiency of evaporative cooler and to state some related factors affecting the performance of the system. From this overview, selection of pad thickness and geometrical shape with suitable characteristics of heat and mass transfer and water holding capacity of the pads was reviewed as these parameters are important for saturation efficiency of evaporative cooling. Increasing the cooling pad thickness through increasing the face velocity increases the effectiveness of wet-bulb saturation. Increasing ambient temperature, inlet air speed and ambient air humidity decreases the wet bulb effectiveness and it increases with increasing length of the pad. Increasing the ambient temperature and inlet air velocity decreases the humidity ratio, but increases with increasing ambient air humidity and lengths of the pad. Increasing the temperature-humidity index is possible with increasing ambient temperature, inlet air velocity, ambient air humidity and pad length. Generally, all materials having a higher wetted surface area per unit volume give higher efficiency. Materials with higher thickness increase the wetted surface area for better mix-up of air and water to give higher efficiency for the same shape and this in turn helps to store fruits and vegetables.

Keywords: Degree of cooling, heat and mass transfer, evaporative cooling, porous surface

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Authors: Yue Huang, Hongcheng Gan

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The new urbanization pattern has led to a rapid growth in demand for short-distance intercity travel, and the emergence of new travel modes has also increased the variety of intercity travel options. In previous studies on intercity travel mode choice behavior, the impact of functional amenities of travel mode and travelers’ long-term personality characteristics has rarely been considered, and empirical results have typically been calibrated using revealed preference (RP) or stated preference (SP) data. This study designed a questionnaire that combines the RP and SP experiment from the perspective of a trip chain combining inner-city and intercity mobility, with consideration for the actual condition of the Huainan-Hefei traffic corridor. On the basis of RP/SP fusion data, a hybrid choice model considering both random taste heterogeneity and psychological characteristics was established to investigate travelers’ mode choice behavior for traditional train, high-speed rail, intercity bus, private car, and intercity online car-hailing. The findings show that intercity time and cost exert the greatest influence on mode choice, with significant heterogeneity across the population. Although inner-city cost does not demonstrate a significant influence, inner-city time plays an important role. Service attributes of travel mode, such as catering and hygiene services, as well as free wireless network supply, only play a minor role in mode selection. Finally, our study demonstrates that safety-seeking tendency, hedonism, and introversion all have differential and significant effects on intercity travel mode choice.

Keywords: intercity travel mode choice, stated preference survey, hybrid choice model, RP/SP fusion data, psychological latent variable, heterogeneity

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Authors: Bryce R. Jolley, Michael Uchic

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This study presents initial results toward the correlative characterization of inherent defects of Ti-6Al-4V additive manufacture (AM). X-Ray Computed Tomography (CT) defect data are compared and correlated with microscopic photographs obtained via automated serial sectioning. The metal AM specimen was manufactured out of Ti-6Al-4V virgin powder to specified dimensions. A post-contour was applied during the fabrication process with a speed of 1050 mm/s, power of 260 W, and a width of 140 µm. The specimen was stress relief heat-treated at 16°F for 3 hours. Microfocus CT imaging was accomplished on the specimen within a predetermined region of the build. Microfocus CT imaging was conducted with parameters optimized for Ti-6Al-4V additive manufacture. After CT imaging, a modified RoboMet. 3D version 2 was employed for serial sectioning and optical microscopy characterization of the same predetermined region. Automated montage capture with sub-micron resolution, bright-field reflection, 12-bit monochrome optical images were performed in an automated fashion. These optical images were post-processed to produce 2D and 3D data sets. This processing included thresholding and segmentation to improve visualization of defect features. The defects observed from optical imaging were compared and correlated with the defects observed from CT imaging over the same predetermined region of the specimen. Quantitative results of area fraction and equivalent pore diameters obtained via each method are presented for this correlation. It is shown that Microfocus CT imaging does not capture all inherent defects within this Ti-6Al-4V AM sample. Best practices for this correlative effort are also presented as well as the future direction of research resultant from this current study.

Keywords: additive manufacture, automated serial sectioning, computed tomography, nondestructive evaluation

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Authors: Kulvinder Bajwa, Narsi R. Bishnoi

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Finding a sustainable alternative for today’s petrochemical industry is a major challenge facing by researchers, scientists, chemical engineers, and society at the global level. Microorganisms are considered to be sustainable feedstock for 3rd generation biofuel production. In this study, we have investigated the potential of a native bacterial strain isolated from a petrol contaminated site for the production of biodiesel. The bacterium was identified to be Rhodococcus opacus by biochemical test and 16S rRNA. Compositional analysis of bacterial biomass has been carried out by Fourier transform infrared spectroscopy (FTIR) in order to confirm lipid profile. Lipid and biomass were optimized by combination with Box Behnken design (BBD) of response surface methodology. The factors selected for the optimization of growth condition were glucose, yeast extract, and ammonium nitrate concentration. The experimental model developed through RSM in terms of effective operational factors (BBD) was found to be suitable to describe the lipid and biomass production, which indicated higher lipid and biomass with a minimum concentration of ammonium nitrate, yeast extract, and quite higher dose of glucose supplementation. Optimum results of the experiments were found to be 2.88 gL⁻¹ biomass and lipid content 38.75% at glucose 20 gL⁻¹, ammonium nitrate 0.5 gL⁻¹ and yeast extract 1.25 gL⁻¹. Furthermore, GCMS study revealed that Rhodococcus opacus has favorable fatty acid profile for biodiesel production.

Keywords: biofuel, Oleaginious bacteria, Rhodococcus opacus, FTIR, BBD, free fatty acids

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Authors: R. Khenata, T. Djied, R. Ahmed, H. Baltache, S. Bin-Omran, A. Bouhemadou

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We predict structural, phase transition as well as opto-electronic properties of the filled-tetrahedral (Nowotny-Juza) NaZnAs compound in this study. Calculations are carried out by employing the full potential (FP) linearized augmented plane wave (LAPW) plus local orbitals (lo) scheme developed within the structure of density functional theory (DFT). Exchange-correlation energy/potential (EXC/VXC) functional is treated using Perdew-Burke and Ernzerhof (PBE) parameterization for generalized gradient approximation (GGA). In addition to Trans-Blaha (TB) modified Becke-Johnson (mBJ) potential is incorporated to get better precision for optoelectronic properties. Geometry optimization is carried out to obtain the reliable results of the total energy as well as other structural parameters for each phase of NaZnAs compound. Order of the structural transitions as a function of pressure is found as: Cu2Sb type → β → α phase in our study. Our calculated electronic energy band structures for all structural phases at the level of PBE-GGA as well as mBJ potential point out; NaZnAs compound is a direct (Γ–Γ) band gap semiconductor material. However, as compared to PBE-GGA, mBJ potential approximation reproduces higher values of fundamental band gap. Regarding the optical properties, calculations of real and imaginary parts of the dielectric function, refractive index, reflectivity coefficient, absorption coefficient and energy loss-function spectra are performed over a photon energy ranging from 0.0 to 30.0 eV by polarizing incident radiation in parallel to both [100] and [001] crystalline directions.

Keywords: NaZnAs, FP-LAPW+lo, structural properties, phase transition, electronic band-structure, optical properties

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Authors: A. M. Bumbea, A. Musetescu, P. Ciurea, A. Bighea

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Objectives: The authors present a Parsonage Turner syndrome, a rare disease characterized by onset in apparently healthy person with shoulder and/or arm pain, sensory deficit, motor deficit. The causes are not established, could be determinate by vaccination, postoperative, immunologic disease, post traumatic etc. Methods: The authors present a woman case, 32 years old, (in 2006), no medical history, with arm pain and no other symptom. The onset was sudden with pain at very high level quantified as 10 to a 0 to 10 scale, with no response to classical analgesic and corticoids. The only drugs which can reduce the intensity of pain were oxycodone hydrochloride, 60 mg daily and pregabalinum150 mg daily. After two weeks the intensity of pain was reduced to 5. The patient started a rehabilitation program. After 6 weeks the patient associated sensory and motor deficit. We performed electromyography for upper limb that showed incomplete denervation with reduced neural transmission speed. The patient receives neurotrophic drugs and painkillers for a long period and physical and kinetic therapy. After 6 months the pain was reduced to level 2 and the patient maintained only 150 mg pregabalinum for another 6 months. Then, the evaluation showed no pain but general amiotrophy in upper limb. Results: At the evaluation in 2009, the patient developed a rheumatoid syndrome with tender and swelling joints, but no positive inflammation test, no antibodies or rheumatoid factor. After two years, in 2011 the patient develops an increase of antinuclear antibodies. This context certifies the diagnosis of lupus and the patient receives the specific therapy. Conclusions: This case is not a typical case of onset of lupus with PTS, but the onset of PTS could include the onset of an immune disease.

Keywords: lupus, arm pain, patient, swelling

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Naser Kazemi Eilaki, Ilona Heldal, Carolyn Ahmer, Bjarne Christian Hagen

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Elderly people and people with disabilities are recognized as at-risk groups when it comes to egress and travel from hazard zone to a safe place. One's disability can negatively influence her or his escape time, and this becomes even more important when people from this target group live alone. While earlier studies have frequently addressed quantitative measurements regarding at-risk groups' physical characteristics (e.g., their speed of travel), this paper considers the influence of at-risk groups’ characteristics on their decision and determining better escape routes. Most of evacuation models are based on mapping people's movement and their behaviour to summation times for common activity types on a timeline. Usually, timeline models estimate required safe egress time (RSET) as a sum of four timespans: detection, alarm, premovement, and movement time, and compare this with the available safe egress time (ASET) to determine what is influencing the margin of safety.This paper presents a cross-sectional study for identifying the most critical items on RSET and people's decision-making and with possibilities to include safety knowledge regarding people with physical or cognitive functional impairments. The result will contribute to increased knowledge on considering at-risk groups and disabilities for designing and developing safe escape routes. The expected results can be an asset to predict the probabilistic behavioural pattern of at-risk groups and necessary components for defining a framework for understanding how stakeholders can consider various disabilities when determining the margin of safety for a safe escape route.

Keywords: fire safety, evacuation, decision-making, at-risk groups

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Authors: Khaled M. Nabil

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This paper introduces the Nested Vortexes conception of the universe structure and interprets all the physical phenomena according this conception. The paper first reviews recent physics theories, either in microscopic scale or macroscopic scale, to collect evidence that the space is not empty. But, these theories describe the property of the space medium without determining its structure. Determining the structure of space medium is essential to understand the mechanism that leads to its properties. Without determining the space medium structure, many phenomena; such as electric and magnetic fields, gravity, or wave-particle duality remain uninterpreted. Thus, this paper introduces a conception about the structure of the universe. It assumes that the universe is a medium of ultra-tiny homogeneous particles which are still undiscovered. Like any medium with certain movements, possibly because of a great asymmetric explosion, vortexes have occurred. A vortex condenses the ultra-tiny particles in its center forming a bigger particle, the bigger particles, in turn, could be trapped in a bigger vortex and condense in its center forming a much bigger particle and so on. This conception describes galaxies, stars, protons as particles at different levels. Existing of the particle’s vortexes make the consistency of the speed of light postulate is not true. This conception shows that the vortex motion dynamic agrees with the motion of all the universe particles at any level. An experiment has been carried out to detect the orbiting effect of aggregated vortexes of aligned atoms of a permanent magnet. Based on the described particle’s structure, the gravity force of a particle and attraction between particles as well as charge, electric and magnetic fields and quantum mechanics characteristics are interpreted. All augmented physics phenomena are solved.

Keywords: astrophysics, cosmology, particles’ structure model, particles’ forces

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Authors: Solange Adechian, Michèle Balage, Didier Remond, Carole Migné, Annie Quignard-Boulangé, Agnès Marset-Baglieri, Sylvie Rousset, Yves Boirie, Claire Gaudichon, Dominique Dardevet, Laurent Mosoni

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Studies have shown that timing of protein intake, leucine content, and speed of digestion significantly affect postprandial protein utilization. Our aim was to determine if one can spare lean body mass during energy restriction by varying the quality and the timing of protein intake. Obese volunteers followed a 6-wk restricted energy diet. Four groups were compared: casein pulse, casein spread, milk-soluble protein (MSP, = whey) pulse, and MSP spread (n = 10-11 per group). In casein groups, caseins were the only protein source; it was MSP in MSP groups. Proteins were distributed in four meals per day in the proportion 8:80:4:8% in the pulse groups; it was 25:25:25:25% in the spread groups. We measured weight, body composition, nitrogen balance, 3-methylhistidine excretion, perception of hunger, plasma parameters, adipose tissue metabolism, and whole body protein metabolism. Volunteers lost 7.5 ± 0.4 kg of weight, 5.1 ± 0.2 kg of fat, and 2.2 ± 0.2 kg of lean mass, with no difference between groups. In adipose tissue, cell size and mRNA expression of various genes were reduced with no difference between groups. Hunger perception was also never different between groups. In the last week, due to a higher inhibition of protein degradation and despite a lower stimulation of protein synthesis, postprandial balance between whole body protein synthesis and degradation was better with caseins than with MSP. It seems likely that the positive effect of caseins on protein balance occurred only at the end of the experiment.

Keywords: lean body mass, fat mass, casein, whey, protein metabolism

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Authors: Bokkasam Sasidhar, Ibrahim Aljasser

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The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Vishnu A., Ashesh Saha

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The operation of high-speed rotating machinery in industries is accompanied by rotor vibrations due to many factors. One of the primary instability mechanisms in a rotor system is the centrifugal force induced due to the eccentricity of the center of mass away from the center of rotation. These unwanted vibrations may lead to catastrophic fatigue failure. So, there is a need to control these rotor vibrations. In this work, control of rotor vibrations by using a 4-pole Radial Active Magnetic Bearing (RAMB) as an actuator is analysed. A continuous rotor system model is considered for the analysis. Several important factors, like the gyroscopic effect and rotary inertia of the shaft and disc, are incorporated into this model. The large deflection of the shaft and the restriction to axial motion of the shaft at the bearings result in nonlinearities in the system governing equation. The rotor system is modeled in such a way that the system dynamics can be related to the geometric and material properties of the shaft and disc. The mathematical model of the rotor system is developed by incorporating the control forces generated by the RAMB. A simple PD controller is used for the attenuation of system vibrations. An analytical expression for the amplitude and phase equations is derived using the Method of Multiple Scales (MMS). Analytical results are verified with the numerical results obtained using an ‘ode’ solver in-built into MATLAB Software. The control force is found to be effective in attenuating the system vibrations. The multi-valued solutions leading to the jump phenomenon are also eliminated with a proper choice of control gains. Most interestingly, the shape of the backbone curves can also be altered for certain values of control parameters.

Keywords: rotor dynamics, continuous rotor system model, active magnetic bearing, PD controller, method of multiple scales, backbone curve

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Authors: Maurice Brogly, Edwige Privas, Rajesh K. Gajendran, Sophie Bistac

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Anti-sticky coatings based on perfluoroalkoxy (PFA) coatings are widely used in food processing industry especially for bread making. Their tribological performance, such as low friction coefficient, low surface energy and high heat resistance, make them an appropriate choice for anti-sticky coating application in moulds for food processing industry. This study is dedicated to evidence the transfer of contaminants from the coating due to wear and thermal ageing of the mould. The risk of contamination is induced by the damage of the coating by bread crust during the demoulding stage. The study focuses on the wear resistance and potential transfer of perfluorinated polymer from the anti-sticky coating. Friction between perfluorinated coating and bread crust is modeled by a tribological pin-on-disc test. The cellular nature of the bread crust is modeled by a polymer foam. FTIR analysis of the polymer foam after friction allow the evaluation of the transfer from the perfluorinated coating to polymer foam. Influence of thermal ageing on the physical, chemical and wear properties of the coating are also investigated. FTIR spectroscopic results show that the increase of PFA transfer onto the foam counterface is associated to the decrease of the friction coefficient. Increasing lubrication by film transfer results in the decrease of the friction coefficient. Moreover increasing the friction test parameters conditions (load, speed and sliding distance) also increase the film transfer onto the counterface. Thermal ageing increases the hydrophobic character of the PFA coating and thus also decreases the friction coefficient.

Keywords: fluorobased polymer coatings, FTIR spectroscopy, non-stick food moulds, wear and friction

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Authors: Walid Tawfik

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The interaction of high intensity ultrashort laser pulses with plasma generates many significant applications, including soft x-ray lasers, time-resolved laser induced plasma spectroscopy LIPS, and laser-driven accelerators. The development in producing of femtosecond down to ten femtosecond optical pulses has facilitates scientists with a vital tool in a variety of ultrashort phenomena, such as high field physics, femtochemistry and high harmonic generation HHG. In this research, we generate a two-octave-wide ultrashort supercontinuum pulses with an optical spectrum extending from 3.5 eV (ultraviolet) to 1.3 eV (near-infrared) using a capillary fiber filled with neon gas. These pulses are formed according to nonlinear self-phase modulation in the neon gas as a nonlinear medium. The investigations of the created pulses were made using spectral phase interferometry for direct electric-field reconstruction (SPIDER). A complete description of the output pulses was considered. The observed characterization of the produced pulses includes the beam profile, the pulse width, and the spectral bandwidth. After reaching optimization conditions, the intensity of the reconstructed pulse autocorrelation function was applied for the shorts pulse duration to achieve transform limited ultrashort pulses with durations below 6-fs energies up to 600μJ. Moreover, the effect of neon pressure variation on the pulse width was examined. The nonlinear self-phase modulation realized to be increased with the pressure of the neon gas. The observed results may lead to an advanced method to control and monitor ultrashort transit interaction in femtochemistry.

Keywords: supercontinuum, ultrafast, SPIDER, ultra-broadband

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Authors: Pia Wetzl

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The learning process of students can be optimized by combining online teaching with face-to-face sessions. So-called blended learning offers extensive flexibility as well as contact opportunities with fellow students and teachers. Furthermore, learning can be individualized and self-regulated. The aim of this article is to investigate which factors are necessary for blended learning to be successful. Semi-structured interviews were conducted with students (N = 60) and lecturers (N = 21) from different disciplines at two German universities. The questions focused on the perception of online, face-to-face and blended learning courses. In addition, questions focused on possible optimization potential and obstacles to practical implementation. The results show that on-site presence is very important for blended learning to be successful. If students do not get to know each other on-site, there is a risk of loneliness during the self-learning phases. This has a negative impact on motivation. From the perspective of the lecturers, the willingness of the students to participate in the sessions on-site is low. Especially when there is no obligation to attend, group work is difficult to implement because the number of students attending is too low. Lecturers would like to see more opportunities from the university and its administration to enforce attendance. In their view, this is the only way to ensure the success of blended learning. In addition, they see the conception of blended learning courses as requiring a great deal of time, which they are not always willing to invest. More incentives are necessary to keep the lecturers motivated to develop engaging teaching material. The study identifies factors that can help teachers conceptualize blended learning. It also provides specific implementation advice and identifies potential impacts. This catalogue has great value for the future-oriented development of courses at universities. Future studies could test its practical use.

Keywords: blended learning, higher education, teachers, student learning, qualitative research

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Authors: Ephraim Ugwu, Christopher Ehinomen

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Despite efforts by the Nigerian government to harmonize the macroeconomic policy implementations by establishing various committees to resolve disputes between the fiscal and monetary authorities, it is still evident that the federal government had continued its expansionary policy by increasing spending, thus creating huge budget deficit. This study evaluates the effect of macroeconomic policy coordination on economic growth uncertainty in Nigeria from 1980 to 2020. Employing the Auto regressive distributed lag (ARDL) bound testing procedures, the empirical results shows that the error correction term, ECM(-1), indicates a negative sign and is significant statistically with the t-statistic value of (-5.612882 ). Therefore, the gap between long run equilibrium value and the actual value of the dependent variable is corrected with speed of adjustment equal to 77% yearly. The long run coefficient results showed that the estimated coefficients of the intercept term indicates that other things remains the same (ceteris paribus), the economics growth uncertainty will continue reduce by 7.32%. The coefficient of the fiscal policy variable, PUBEXP, indicates a positive sign and significant statistically. This implies that as the government expenditure increases by 1%, economic growth uncertainty will increase by 1.67%. The coefficient of monetary policy variable MS also indicates a positive sign and insignificant statistically. The coefficients of merchandise trade variable, TRADE and exchange rate EXR show negative signs and significant statistically. This indicate that as the country’s merchandise trade and the rate of exchange increases by 1%, the economic growth uncertainty reduces by 0.38% and 0.06%, respectively. This study, therefore, advocate for proper coordination of monetary, fiscal and exchange rate policies in order to actualize the goal of achieving a stable economic growth.

Keywords: macroeconomic, policy coordination, growth uncertainty, ARDL, Nigeria

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Authors: Luis Guiliana, Andrea Osorio

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The lack of comprehension of the reservoir geomechanics conditions may cause operational problems that cost to the industry billions of dollars per year. The drilling operations at the Ceuta Field, Area 2 South, Maracaibo Lake, have been very expensive due to problems associated with drilling. The principal objective of this investigation is to develop a 3D geomechanical model in this area, in order to optimize the future drillings in the field. For this purpose, a 1D geomechanical model was built at first instance, following the workflow of the MEM (Mechanical Earth Model), this consists of the following steps: 1) Data auditing, 2) Analysis of drilling events and structural model, 3) Mechanical stratigraphy, 4) Overburden stress, 5) Pore pressure, 6) Rock mechanical properties, 7) Horizontal stresses, 8) Direction of the horizontal stresses, 9) Wellbore stability. The 3D MEM was developed through the geostatistic model of the Eocene C-SUP VLG-3676 reservoir and the 1D MEM. With this data the geomechanical grid was embedded. The analysis of the results threw, that the problems occurred in the wells that were examined were mainly due to wellbore stability issues. It was determined that the stress field change as the stratigraphic column deepens, it is normal to strike-slip at the Middle Miocene and Lower Miocene, and strike-slipe to reverse at the Eocene. In agreement to this, at the level of the Eocene, the most advantageous direction to drill is parallel to the maximum horizontal stress (157º). The 3D MEM allowed having a tridimensional visualization of the rock mechanical properties, stresses and operational windows (mud weight and pressures) variations. This will facilitate the optimization of the future drillings in the area, including those zones without any geomechanics information.

Keywords: geomechanics, MEM, drilling, stress

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Authors: Devendra Sillu, Shekhar Agnihotri

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The 'nano-biocatalyst' utilizes an ordered assembling of enzyme on to nanomaterial carriers to catalyze desirable biochemical kinetics and substrate selectivity. The current study describes an inter-disciplinary approach for converting agriculture waste, sugarcane bagasse into D-glucose exploiting halloysite nanotubes (HNTs) decorated cellulase enzyme as nano-biocatalytic system. Cellulase was successfully immobilized on HNTs employing polydopamine as an eco-friendly crosslinker while iron oxide nanoparticles were attached to facilitate magnetic recovery of material. The characterization studies (UV-Vis, TEM, SEM, and XRD) displayed the characteristic features of both cellulase and magnetic HNTs in the resulting nanocomposite. Various factors (i.e., working pH, temp., crosslinker conc., enzyme conc.) which may influence the activity of biocatalytic system were investigated. The experimental design was performed using Response Surface Methodology (RSM) for process optimization. Analyses data demonstrated that the nanobiocatalysts retained 80.30% activity even at elevated temperature (55°C) and excellent storage stabilities after 10 days. The repeated usage of system revealed a remarkable consistent relative activity over several cycles. The immobilized cellulase was employed to decompose agro-waste and the maximum decomposition rate of 67.2 % was achieved. Conclusively, magnetic HNTs can serve as a potential support for enzyme immobilization with long term usage, good efficacy, reusability and easy recovery from solution.

Keywords: halloysite nanotubes, enzyme immobilization, cellulase, response surface methodology, magnetic recovery

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Authors: Anil Bhandari, Imran Khan Pathan, Peeyush K. Sharma, Rakesh K. Patel, Suresh Purohit

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The purpose of this study was to prepare time and pH dependent release tablets of Ayurvedic Churna formulation and evaluate their advantages as colon targeted drug delivery system. The Vidangadi Churna was selected for this study which contains Embelin and Gallic acid. Embelin is used in Helminthiasis as therapeutic agent. Embelin is insoluble in water and unstable in gastric environment so it was formulated in time and pH dependent tablets coated with combination of two polymers Eudragit L100 and ethyl cellulose. The 150mg of core tablet of dried extract and lactose were prepared by wet granulation method. The compression coating was used in the polymer concentration of 150mg for both the layer as upper and lower coating tablet was investigated. The results showed that no release was found in 0.1 N HCl and pH 6.8 phosphate buffers for initial 5 hours and about 98.97% of the drug was released in pH 7.4 phosphate buffer in total 17 hours. The in vitro release profiles of drug from the formulation could be best expressed first order kinetics as highest linearity (r2= 0.9943). The results of the present study have demonstrated that the time and pH dependent tablets system is a promising vehicle for preventing rapid hydrolysis in gastric environment and improving oral bioavailability of Embelin and Gallic acid for treatment of Helminthiasis.

Keywords: embelin, gallic acid, Vidangadi Churna, colon targeted drug delivery

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Authors: Mahfoodha Al-Kitani, Dylan Thompson, Keith Stokes

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Sickle cell disease (SCD) and sickle cell trait (SCT) are the most common hematological diseases in Oman according to the national survey of genetic blood disorders. The aim of this study was to determine markers of physical fitness and anthropometrics indices in children with sickle cell disease and children with sickle cell trait and compare them with normal healthy children of the same age. One hundred and twenty male children participated in the present study divided to three groups: 40 with sickle disease (SCD; age, 13.3(.80), height, 131.9(3.5), mass, 29.2(3.1)); 40 with sickle cell trait (SCT; age, 12.2(.80), height, 141.0(9.9), mass, 38.0(4.4)); and 40 controls with normal hemoglobin (Con; age, 12.8(.80), height, 139.4(8.7), mass, 37.2(4.3)). All children completed a 5-min running exercise test on a treadmill at speed corresponding to 5 km/hr. Heart rate and was recorded during exercise and during 10-min of recovery. Blood lactate was measured before and 5 min after the completion of exercise. Children with SCD exhibited a higher mean value (P < 0.05) for percent body fat and fat mass than the normal healthy subjects and SCT subjects. Resting values of hemoglobin were similar in SCT (11.04(.78)) and control (10.8(94)) groups, and lower in SCD (8.89(.54); P < 0.05). There was a strong correlation between peak heart rate and resting hemoglobin levels for the three groups (r= -.472. n= 120, p < .0005).The SCD group (175.2(10.3)) exhibited higher mean heart rate during exercise than those observed in the SCT (143.7(9.5)) and normal control children (144.5(22.4); P < 0.05). Additionally, SCD children showed higher serum lactate values before and after treadmill exercise compared to the other groups (P < 0.05). Children with sickle cell trait demonstrate similar physical fitness level and similar exercise responses to treadmill stress test to normal children. In contrast, SCD children have lower body mass, higher fat mass and lower physical fitness than children with SCT and healthy controls.

Keywords: sickle cell disease, sickle cell trait, children, exercise

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Zohreh Soleimani, Sally Salome Shahzad, Stamatis Zoras

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As a result of current energy and environmental issues, the human body is known as one of the promising candidate for converting wasted heat to electricity (Seebeck effect). Thermoelectric generator (TEG) is one of the most prevalent means of harvesting body heat and converting that to eco-friendly electrical power. However, the uneven distribution of the body heat and its curvature geometry restrict harvesting adequate amount of energy. To perfectly transform the heat radiated by the body into power, the most direct solution is conforming the thermoelectric generators (TEG) with the arbitrary surface of the body and increase the temperature difference across the thermoelectric legs. Due to this, a computational survey through COMSOL Multiphysics is presented in this paper with the main focus on the impact of integrating a flexible wearable TEG with a corrugated shaped heat sink on the module power output. To eliminate external parameters (temperature, air flow, humidity), the simulations are conducted within indoor thermal level and when the wearer is stationary. The full thermoelectric characterization of the proposed TEG fabricated by a wavy shape heat sink has been computed leading to a maximum power output of 25µW/cm2 at a temperature gradient nearly 13°C. It is noteworthy that for the flexibility of the proposed TEG and heat sink, the applicability and efficiency of the module stay high even on the curved surfaces of the body. As a consequence, the results demonstrate the superiority of such a TEG to the most state of the art counterparts fabricated with no heat sink and offer a new train of thought for the development of self-sustained and unobtrusive wearable power suppliers which generate energy from low grade dissipated heat from the body.

Keywords: device simulation, flexible thermoelectric module, heat sink, human body heat

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Authors: Rakesh Kumar, A. K. Ghosh

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The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

Procedia PDF Downloads 443