Search results for: partial differential equations

Authors: Aniela Pop, Ianina Birsan, Corina Orha, Rodica Pode, Florica Manea

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Carbon nanofiber-epoxy composite electrode has been investigated through voltammetric and amperometric techniques in order to detect parabens from aqueous solutions. The occurrence into environment as emerging pollutants of these preservative compounds has been extensively studied in the last decades, and consequently, a rapid and reliable method for their quantitative quantification is required. In this study, methylparaben (MP) and propylparaben (PP) were chosen as representatives for paraben class. The individual electrochemical detection of each paraben has been successfully performed. Their electrochemical oxidation occurred at the same potential value. Their simultaneous quantification should be assessed electrochemically only as general index of paraben class as a cumulative signal corresponding to both MP and PP from solution. The influence of pH on the electrochemical signal was studied. pH ranged between 1.3 and 9.0 allowed shifting the detection potential value to smaller value, which is very desired for the electroanalysis. Also, the signal is better-defined and higher sensitivity is achieved. Differential-pulsed voltammetry and square-wave voltammetry were exploited under the optimum pH conditions to improve the electroanalytical performance for the paraben detection. Also, the operation conditions were selected, i.e., the step potential, modulation amplitude and the frequency. Chronomaprometry application as the easiest electrochemical detection method led to worse sensitivity, probably due to a possible fouling effect of the electrode surface. The best electroanalytical performance was achieved by pulsed voltammetric technique but the selection of the electrochemical technique is related to the concrete practical application. A good reproducibility of the voltammetric-based method using carbon nanofiber-epoxy composite electrode was determined and no interference effect was found for the cation and anion species that are common in the water matrix. Besides these characteristics, the long life-time of the electrode give to carbon nanofiber-epoxy composite electrode a great potential for practical applications.

Keywords: Carbon nanofiber-epoxy composite electrode, electroanalysis, methylparaben, propylparaben.

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Authors: Wei-Hsin Sun, Jr-Ming Miao, Chang-Hsien Tai, Chien-Chun Hung

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The development of biomimetic micro-aerial-vehicles (MAVs) with flapping wings is the future trend in military/domestic field. The successful flight of MAVs is strongly related to the understanding of unsteady aerodynamic performance of low Reynolds number airfoils under dynamic flapping motion. This study explored the effects of flapping frequency, stroke amplitude, and the inclined angle of stroke plane on lift force and thrust force of a bio-inspiration corrugated airfoil with 33 full factorial design of experiment and ANOVA analysis. Unsteady vorticity flows over a corrugated thin airfoil executing flapping motion are computed with time-dependent two-dimensional laminar incompressible Reynolds-averaged Navier-Stokes equations with the conformal hybrid mesh. The tested freestream Reynolds number based on the chord length of airfoil as characteristic length is fixed of 103. The dynamic mesh technique is applied to model the flapping motion of a corrugated airfoil. Instant vorticity contours over a complete flapping cycle clearly reveals the flow mechanisms for lift force generation are dynamic stall, rotational circulation, and wake capture. The thrust force is produced as the leading edge vortex shedding from the trailing edge of airfoil to form a reverse von Karman vortex. Results also indicated that the inclined angle is the most significant factor on both the lift force and thrust force. There are strong interactions between tested factors which mean an optimization study on parameters should be conducted in further runs.

Keywords: biomimetic, MAVs, aerodynamic, ANOVA analysis.

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Authors: A. Fathianpour, M. B. Jelodar, S. Wilkinson

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This paper outlines the approaches taken to assess multi-hazard assessments. There is currently confusion in assessing multi-hazard impacts, and so this study aims to determine which of the available options are the most useful. The paper uses an international literature search, and analysis of current multi-hazard assessments and a case study to illustrate the effectiveness of the chosen method. Findings from this study will help those wanting to assess multi-hazards to undertake a straightforward approach. The paper is significant as it helps to interpret the various approaches and concludes with the preferred method. Many people in the world live in hazardous environments and are susceptible to disasters. Unfortunately, when a disaster strikes it is often compounded by additional cascading hazards, thus people would confront more than one hazard simultaneously. Hazards include natural hazards (earthquakes, floods, etc.) or cascading human-made hazards (for example, Natural Hazard Triggering Technological disasters (Natech) such as fire, explosion, toxic release). Multi-hazards have a more destructive impact on urban areas than one hazard alone. In addition, climate change is creating links between different disasters such as causing landslide dams and debris flows leading to more destructive incidents. Much of the prevailing literature deals with only one hazard at a time. However, recently sophisticated multi-hazard assessments have started to appear. Given that multi-hazards occur, it is essential to take multi-hazard risk assessment under consideration. This paper aims to review the multi-hazard assessment methods through articles published to date and categorize the strengths and disadvantages of using these methods in risk assessment. Napier City is selected as a case study to demonstrate the necessity of using multi-hazard risk assessments. In order to assess multi-hazard risk assessments, first, the current multi-hazard risk assessment methods were described. Next, the drawbacks of these multi-hazard risk assessments were outlined. Finally, the improvements to current multi-hazard risk assessments to date were summarised. Generally, the main problem of multi-hazard risk assessment is to make a valid assumption of risk from the interactions of different hazards. Currently, risk assessment studies have started to assess multi-hazard situations, but drawbacks such as uncertainty and lack of data show the necessity for more precise risk assessment. It should be noted that ignoring or partial considering multi-hazards in risk assessment will lead to an overestimate or overlook in resilient and recovery action managements.

Keywords: Cascading hazards, multi-hazard, risk assessment, risk reduction.

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Authors: Gozel Judakova, Markus Bause

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We present and analyze reliable numerical techniques for simulating complex flow and transport phenomena related to natural gas transportation in pipelines. Such kind of problems are of high interest in the field of petroleum and environmental engineering. Modeling and understanding natural gas flow and transformation processes during transportation is important for the sake of physical realism and the design and operation of pipeline systems. In our approach a two fluid flow model based on a system of coupled hyperbolic conservation laws is considered for describing natural gas flow undergoing hydratization. The accurate numerical approximation of two-phase gas flow remains subject of strong interest in the scientific community. Such hyperbolic problems are characterized by solutions with steep gradients or discontinuities, and their approximation by standard finite element techniques typically gives rise to spurious oscillations and numerical artefacts. Recently, stabilized and discontinuous Galerkin finite element techniques have attracted researchers’ interest. They are highly adapted to the hyperbolic nature of our two-phase flow model. In the presentation a streamline upwind Petrov-Galerkin approach and a discontinuous Galerkin finite element method for the numerical approximation of our flow model of two coupled systems of Euler equations are presented. Then the efficiency and reliability of stabilized continuous and discontinous finite element methods for the approximation is carefully analyzed and the potential of the either classes of numerical schemes is investigated. In particular, standard benchmark problems of two-phase flow like the shock tube problem are used for the comparative numerical study.

Keywords: Discontinuous Galerkin method, Euler system, inviscid two-fluid model, streamline upwind Petrov-Galerkin method, two-phase flow.

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Authors: J. Ritonja

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The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: Adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification.

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Authors: V. P. Muhamed Shajudheen, K. Viswanathan, K. Anitha Rani, A. Uma Maheswari, S. Saravana Kumar

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In this paper, a simple chemical precipitation route for the preparation of titanium dioxide nanoparticles, synthesized by using titanium tetra isopropoxide as a precursor and polyvinyl pyrrolidone (PVP) as a capping agent, is reported. The Differential Scanning Calorimetry (DSC) and Thermo Gravimetric Analysis (TGA) of the samples were recorded and the phase transformation temperature of titanium hydroxide, Ti(OH)₄ to titanium oxide, TiO₂ was investigated. The as-prepared Ti(OH)₄ precipitate was annealed at 800°C to obtain TiO₂ nanoparticles. The thermal, structural, morphological and textural characterizations of the TiO₂ nanoparticle samples were carried out by different techniques such as DSC-TGA, X-Ray Diffraction (XRD), Fourier Transform Infra-Red spectroscopy (FTIR), Micro Raman spectroscopy, UV-Visible absorption spectroscopy (UV-Vis), Photoluminescence spectroscopy (PL) and Field Effect Scanning Electron Microscopy (FESEM) techniques. The as-prepared precipitate was characterized using DSC-TGA and confirmed the mass loss of around 30%. XRD results exhibited no diffraction peaks attributable to anatase phase, for the reaction products, after the solvent removal. The results indicate that the product is purely rutile. The vibrational frequencies of two main absorption bands of prepared samples are discussed from the results of the FTIR analysis. The formation of nanosphere of diameter of the order of 10 nm, has been confirmed by FESEM. The optical band gap was found by using UV-Visible spectrum. From photoluminescence spectra, a strong emission was observed. The obtained results suggest that this method provides a simple, efficient and versatile technique for preparing TiO₂ nanoparticles and it has the potential to be applied to other systems for photocatalytic activity.

Keywords: TiO2 nanoparticles, chemical precipitation route, phase transition, Fourier Transform Infra-Red spectroscopy, micro Raman spectroscopy, UV-Visible absorption spectroscopy, Photoluminescence spectroscopy, Field Effect Scanning Electron Microscopy.

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Authors: Mohamed Elghorab, Vendra C. Madhav Rao, Jennifer X. Wen

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Turbulence modelling is still evolving, and efforts are on to improve and develop numerical methods to simulate the real turbulence structures by using the empirical and experimental information. The monotonically integrated large eddy simulation (MILES) is an attractive approach for modelling turbulence in high Re flows, which is based on the solving of the unfiltered flow equations with no explicit sub-grid scale (SGS) model. In the current work, this approach has been used, and the action of the SGS model has been included implicitly by intrinsic nonlinear high-frequency filters built into the convection discretization schemes. The MILES solver is developed using the opensource CFD OpenFOAM libraries. The role of flux limiters schemes namely, Gamma, superBee, van-Albada and van-Leer, is studied in predicting turbulent statistical quantities for a fully developed channel flow with a friction Reynolds number, Re_T = 180, and compared the numerical predictions with the well-established Direct Numerical Simulation (DNS) results for studying the wall generated turbulence. It is inferred from the numerical predictions that Gamma, van-Leer and van-Albada limiters produced more diffusion and overpredicted the velocity profiles, while superBee scheme reproduced velocity profiles and turbulence statistical quantities in good agreement with the reference DNS data in the streamwise direction although it deviated slightly in the spanwise and normal to the wall directions. The simulation results are further discussed in terms of the turbulence intensities and Reynolds stresses averaged in time and space to draw conclusion on the flux limiter schemes performance in OpenFOAM context.

Keywords: Flux limiters, MILES, OpenFOAM, turbulence structures, TVD schemes.

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Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

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In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: Automobile suspension, MATLAB, control system, PID, PSO.

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Authors: Mustafa M. Donma

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Circumference measurements may give meaningful information about the varying stages of obesity. Some formulas may be derived from a number of body circumference measurements to estimate body fat. Waist (WC), hip (HC) and neck (NC) circumferences are currently the most frequently used measurements. The aim of this study was to develop a formula derived from these three anthropometric measurements for the differential diagnosis of morbid obesity with and without metabolic syndrome (MetS), MOMetS+ and MOMetS-, respectively. 187 children were recruited from the pediatrics outpatient clinic of Tekirdag Namik Kemal University, Faculty of Medicine. Signed informed consent forms were taken from the participants. The study was carried out according to the Helsinki Declaration. The study protocol was approved by the institutional non-interventional ethics committee of Tekirdag Namik Kemal University Medical Faculty. The study population was divided into four groups as normal-body mass index (N-BMI) (n = 35), obese (OB) (n = 44), morbid obese (MO) (n = 75) and MetS (n = 33). Age- and gender-adjusted BMI percentile values were used for the classification of groups. The children in MetS group were selected based upon the nature of the MetS components described as MetS criteria. Anthropometric measurements, laboratory analysis and statistical evaluation confined to study population were performed. BMI values were calculated. A circumference index, advanced Donma circumference index (ADCI) was presented as WC*HC/NC. The statistical significance degree was chosen as p < 0.05. BMI values were 17.7 ± 2.8, 24.5 ± 3.3, 28.8 ± 5.7, 31.4 ± 8.0 kg/m2, for N-BMI, OB, MO, MetS groups (p = 0.001), respectively. An increasing trend from N-BMI to MetS was observed. However, the increase in MetS group compared to MO group was not significant. For the new index, significant differences were obtained between N-BMI and OB, MO, MetS groups (p = 0.001). A significant difference between MO and MetS groups was detected (p = 0.043). A significant correlation was found between BMI and ADCI. In conclusion, in spite of the strong correlation between BMI and ADCI values obtained when all groups were considered, ADCI, but not BMI, was the index, which was capable of differentiating cases with morbid obesity from cases with morbid obesity and MetS.

Keywords: Anthropometry, body mass index, childhood obesity, body circumference, metabolic syndrome.

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Authors: Chun-Lang Chang

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According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.

Keywords: Data mining, Hearing impairment, Logistic regression analysis, Support vector machines

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Authors: Saruhan Kartal, Ilker Kalkan

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The present paper reports the cracking moment estimates of a set of steel-reinforced, Fiber Reinforced Polymer (FRP)-reinforced and hybrid steel-FRP reinforced concrete beams, calculated from different analytical formulations in the codes, together with the experimental cracking load values. A total of three steel-reinforced, four FRP-reinforced, 12 hybrid FRP-steel over-reinforced and five hybrid FRP-steel under-reinforced concrete beam tests were analyzed within the scope of the study. Glass FRP (GFRP) and Basalt FRP (BFRP) bars were used in the beams as FRP bars. In under-reinforced hybrid beams, rupture of the FRP bars preceded crushing of concrete, while concrete crushing preceded FRP rupture in over-reinforced beams. In both types, steel yielding took place long before the FRP rupture and concrete crushing. The cracking moment mainly depends on two quantities, namely the moment of inertia of the section at the initiation of cracking and the flexural tensile strength of concrete, i.e. the modulus of rupture. In the present study, two different definitions of uncracked moment of inertia, i.e. the gross and the uncracked transformed moments of inertia, were adopted. Two analytical equations for the modulus of rupture (ACI 318M and Eurocode 2) were utilized in the calculations as well as the experimental tensile strength of concrete from prismatic specimen tests. The ACI 318M modulus of rupture expression produced cracking moment estimates closer to the experimental cracking moments of FRP-reinforced and hybrid FRP-steel reinforced concrete beams when used in combination with the uncracked transformed moment of inertia, yet the Eurocode 2 modulus of rupture expression gave more accurate cracking moment estimates in steel-reinforced concrete beams. All of the analytical definitions produced analytical values considerably different from the experimental cracking load values of the solely FRP-reinforced concrete beam specimens.

Keywords: Cracking moment, four-point bending, hybrid use of reinforcement, polymer reinforcement.

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: Dynamic modeling, missing data, multiple imputation, physiological measures.

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Authors: Sunday Olufemi Adesogan

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The supply of potable water at least is a very important index in national development. Water tariffs depend on the treatment cost which carries the highest percentage of the total operation cost in any water supply scheme. In order to keep water tariffs as low as possible, treatment costs have to be minimized. The University of Ibadan, Nigeria, water supply scheme consists of a treatment plant with three distribution stations (Amina way, Kurumi and Lander) and two raw water supply sources (Awba dam and Eleyele dam). An operational study of the scheme was carried out to ascertain the efficiency of the supply of potable water on the campus to justify the need for water supply schemes in tertiary institutions. The study involved regular collection, processing and analysis of periodic operational data. Data collected include supply reading (water production on daily basis) and consumers metered reading for a period of 22 months (October 2013 - July 2015), and also collected, were the operating hours of both plants and human beings. Applying the required mathematical equations, total loss was determined for the distribution system, which was translated into monetary terms. Adequacies of the operational functions were also determined. The study revealed that water supply scheme is justified in tertiary institutions. It was also found that approximately 10.7 million Nigerian naira (N) is lost to leakages during the 22-month study period; the system’s storage capacity is no longer adequate, especially for peak water production. The capacity of the system as a whole is insufficient for the present university population and that the existing water supply system is not being operated in an optimal manner especially due to personnel, power and system ageing constraints.

Keywords: Operational, efficiency, production, supply, water treatment plant, water loss.

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Authors: Palak J. Shukla, Atul K. Desai, Chentankumar D. Modhera

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For any country in the world, it has become a priority to protect the critical infrastructure from looming risks of terrorism. In any infrastructure system, the structural elements like lower floors, exterior columns, walls etc. are key elements which are the most susceptible to damage due to blast load. The present study revisits the state of art review of the design and analysis of reinforced concrete panels subjected to blast loading. Various aspects in association with blast loading on structure, i.e. estimation of blast load, experimental works carried out previously, the numerical simulation tools, various material models, etc. are considered for exploring the current practices adopted worldwide. Discussion on various parametric studies to investigate the effect of reinforcement ratios, thickness of slab, different charge weight and standoff distance is also made. It was observed that for the simulation of blast load, CONWEP blast function or equivalent numerical equations were successfully employed by many researchers. The study of literature indicates that the researches were carried out using experimental works and numerical simulation using well known generalized finite element methods, i.e. LS-DYNA, ABAQUS, AUTODYN. Many researchers recommended to use concrete damage model to represent concrete and plastic kinematic material model to represent steel under action of blast loads for most of the numerical simulations. Most of the studies reveal that the increase reinforcement ratio, thickness of slab, standoff distance was resulted in better blast resistance performance of reinforced concrete panel. The study summarizes the various research results and appends the present state of knowledge for the structures exposed to blast loading.

Keywords: Blast phenomenon, experimental methods, material models, numerical methods.

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Authors: Rawia M. Khalil, Ahmed A. Abd El Rahman, Mahfouz A. Kassem, Mohamed S. El Ridi, Mona M. Abou Samra, Ghada E. A. Awad, Soheir S. Mansy

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Solid lipid nanoparticles (SLNs) have gained great attention for the topical treatment of skin associated fungal infection as they facilitate the skin penetration of loaded drugs. Our work deals with the preparation of nystatin loaded solid lipid nanoparticles (NystSLNs) using the hot homogenization and ultrasonication method. The prepared NystSLNs were characterized in terms of entrapment efficiency, particle size, zeta potential, transmission electron microscopy, differential scanning calorimetry, rheological behavior and in vitro drug release. A stability study for 6 months was performed. A microbiological study was conducted in male rats infected with Candida albicans, by counting the colonies and examining the histopathological changes induced on the skin of infected rats. The results showed that SLNs dispersions are spherical in shape with particle size ranging from 83.26±11.33 to 955.04±1.09 nm. The entrapment efficiencies are ranging from 19.73±1.21 to 72.46±0.66% with zeta potential ranging from -18.9 to -38.8 mV and shear-thinning rheological Behavior. The stability studies done for 6 months showed that nystatin (Nyst) is a good candidate for topical SLN formulations. A least number of colony forming unit/ ml (cfu/ml) was recorded for the selected NystSLN compared to the drug solution and the commercial Nystatin® cream present in the market. It can be fulfilled from this work that SLNs provide a good skin targeting effect and may represent promising carrier for topical delivery of Nyst offering the sustained release and maintaining the localized effect, resulting in an effective treatment of cutaneous fungal infection.

Keywords: Candida infections, Hot homogenization, Nystatin, Solid lipid nanoparticles, Stability, Topical delivery.

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Authors: S.F.S. Draman, R. Daik, A. Musa

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Three sulphonic acid-doped polyanilines were synthesized through chemical oxidation at low temperature (0-5 oC) and potential of these polymers as sensing agent for O2 gas detection in terms of fluorescence quenching was studied. Sulphuric acid, dodecylbenzene sulphonic acid (DBSA) and camphor sulphonic acid (CSA) were used as doping agents. All polymers obtained were dark green powder. Polymers obtained were characterized by Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, thermogravimetry analysis, elemental analysis, differential scanning calorimeter and gel permeation chromatography. Characterizations carried out showed that polymers were successfully synthesized with mass recovery for sulphuric aciddoped polyaniline (SPAN), DBSA-doped polyaniline (DBSA-doped PANI) and CSA-doped polyaniline (CSA-doped PANI) of 71.40%, 75.00% and 39.96%, respectively. Doping level of SPAN, DBSAdoped PANI and CSA-doped PANI were 32.86%, 33.13% and 53.96%, respectively as determined based on elemental analysis. Sensing test was carried out on polymer sample in the form of solution and film by using fluorescence spectrophotometer. Samples of polymer solution and polymer film showed positive response towards O2 exposure. All polymer solutions and films were fully regenerated by using N2 gas within 1 hour period. Photostability study showed that all samples of polymer solutions and films were stable towards light when continuously exposed to xenon lamp for 9 hours. The relative standard deviation (RSD) values for SPAN solution, DBSA-doped PANI solution and CSA-doped PANI solution for repeatability were 0.23%, 0.64% and 0.76%, respectively. Meanwhile RSD values for reproducibility were 2.36%, 6.98% and 1.27%, respectively. Results for SPAN film, DBSAdoped PANI film and CSA-doped PANI film showed the same pattern with RSD values for repeatability of 0.52%, 4.05% and 0.90%, respectively. Meanwhile RSD values for reproducibility were 2.91%, 10.05% and 7.42%, respectively. The study on effect of the flow rate on response time was carried out using 3 different rates which were 0.25 mL/s, 1.00 mL/s and 2.00 mL/s. Results obtained showed that the higher the flow rate, the shorter the response time.

Keywords: conjugated polymer, doping, fluorescence quenching, oxygen gas.

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Authors: J. Ritonja, B. Grcar

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For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: Eigenvalue analysis, mathematical model, power system stability, synchronous generator.

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Authors: S. Sadhu, M. Ramgopal, S. Bhattacharyya

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Natural circulation loops (NCLs) are buoyancy driven flow systems without any moving components. NCLs have vast applications in geothermal, solar and nuclear power industry where reliability and safety are of foremost concern. Due to certain favorable thermophysical properties, especially near supercritical regions, carbon dioxide can be considered as an ideal loop fluid in many applications. In the present work, a high temperature NCL that uses supercritical carbon dioxide as loop fluid is analysed. The effects of relevant design and operating variables on loop performance are studied. The system operating under steady state is modelled taking into account the axial conduction through loop fluid and loop wall, and heat transfer with surroundings. The heat source is considered to be a heater with controlled heat flux and heat sink is modelled as an end heat exchanger with water as the external cold fluid. The governing equations for mass, momentum and energy conservation are normalized and are solved numerically using finite volume method. Results are obtained for a loop pressure of 90 bar with the power input varying from 0.5 kW to 6.0 kW. The numerical results are validated against the experimental results reported in the literature in terms of the modified Grashof number (Gr_m) and Reynolds number (Re). Based on the results, buoyancy and friction dominated regions are identified for a given loop. Parametric analysis has been done to show the effect of loop diameter, loop height, ambient temperature and insulation. The results show that for the high temperature loop, heat loss to surroundings affects the loop performance significantly. Hence this conjugate heat transfer between the loop and surroundings has to be considered in the analysis of high temperature NCLs.

Keywords: Conjugate heat transfer, heat loss, natural circulation loop, supercritical carbon dioxide.

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Authors: N. Santatriniaina, J. Deseure, T.Q. Nguyen, H. Fontaine, C. Beitia, L. Rakotomanana

Abstract:

Nowadays, with the increasing of the wafer's size and the decreasing of critical size of integrated circuit manufacturing in modern high-tech, microelectronics industry needs a maximum attention to challenge the contamination control. The move to 300 [mm] is accompanied by the use of Front Opening Unified Pods for wafer and his storage. In these pods an airborne cross contamination may occur between wafers and the pods. A predictive approach using modeling and computational methods is very powerful method to understand and qualify the AMCs cross contamination processes. This work investigates the required numerical tools which are employed in order to study the AMCs cross-contamination transfer phenomena between wafers and FOUPs. Numerical optimization and finite element formulation in transient analysis were established. Analytical solution of one dimensional problem was developed and the calibration process of physical constants was performed. The least square distance between the model (analytical 1D solution) and the experimental data are minimized. The behavior of the AMCs intransient analysis was determined. The model framework preserves the classical forms of the diffusion and convection-diffusion equations and yields to consistent form of the Fick's law. The adsorption process and the surface roughness effect were also traduced as a boundary condition using the switch condition Dirichlet to Neumann and the interface condition. The methodology is applied, first using the optimization methods with analytical solution to define physical constants, and second using finite element method including adsorption kinetic and the switch of Dirichlet to Neumann condition.

Keywords: AMCs, FOUP, cross-contamination, adsorption, diffusion, numerical analysis, wafers, Dirichlet to Neumann, finite elements methods, Fick’s law, optimization.

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Authors: Ferdi Sönmez, Nihal Yorulmaz

Abstract:

Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: User cost, bi-level optimization model, decision support, operator cost, transportation.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows drawing conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: Sang Wook Park, Jun Su Park, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

Abstract:

This study suggests the estimation method of stress distribution for the beam structures based on TLS (Terrestrial Laser Scanning). The main components of method are the creation of the lattices of raw data from TLS to satisfy the suitable condition and application of CSSI (Cubic Smoothing Spline Interpolation) for estimating stress distribution. Estimation of stress distribution for the structural member or the whole structure is one of the important factors for safety evaluation of the structure. Existing sensors which include ESG (Electric strain gauge) and LVDT (Linear Variable Differential Transformer) can be categorized as contact type sensor which should be installed on the structural members and also there are various limitations such as the need of separate space where the network cables are installed and the difficulty of access for sensor installation in real buildings. To overcome these problems inherent in the contact type sensors, TLS system of LiDAR (light detection and ranging), which can measure the displacement of a target in a long range without the influence of surrounding environment and also get the whole shape of the structure, has been applied to the field of structural health monitoring. The important characteristic of TLS measuring is a formation of point clouds which has many points including the local coordinate. Point clouds are not linear distribution but dispersed shape. Thus, to analyze point clouds, the interpolation is needed vitally. Through formation of averaged lattices and CSSI for the raw data, the method which can estimate the displacement of simple beam was developed. Also, the developed method can be extended to calculate the strain and finally applicable to estimate a stress distribution of a structural member. To verify the validity of the method, the loading test on a simple beam was conducted and TLS measured it. Through a comparison of the estimated stress and reference stress, the validity of the method is confirmed.

Keywords: Structural health monitoring, terrestrial laser scanning, estimation of stress distribution, coordinate transformation, cubic smoothing spline interpolation.

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Authors: Y. C. Liou, J. M. Miao, T. L. Liu, M. H. Ho

Abstract:

The purpose of this study was to explore the complex flow structure a novel active-type micromixer that based on concept of Wankle-type rotor. The characteristics of this micromixer are two folds; a rapid mixing of reagents in a limited space due to the generation of multiple vortices and a graduate increment in dynamic pressure as the mixed reagents is delivered to the output ports. Present micro-mixer is consisted of a rotor with shape of triangle column, a blending chamber and several inlet and outlet ports. The geometry of blending chamber is designed to make the rotor can be freely internal rotated with a constant eccentricity ratio. When the shape of the blending chamber and the rotor are fixed, the effects of rotating speed of rotor and the relative locations of ports on the mixing efficiency are numerical studied. The governing equations are unsteady, two-dimensional incompressible Navier-Stokes equation and the working fluid is the water. The species concentration equation is also solved to reveal the mass transfer process of reagents in various regions then to evaluate the mixing efficiency. The dynamic mesh technique was implemented to model the dynamic volume shrinkage and expansion of three individual sub-regions of blending chamber when the rotor conducted a complete rotating cycle. Six types of ports configuration on the mixing efficiency are considered in a range of Reynolds number from 10 to 300. The rapid mixing process was accomplished with the multiple vortex structures within a tiny space due to the equilibrium of shear force, viscous force and inertial force. Results showed that the highest mixing efficiency could be attained in the following conditions: two inlet and two outlet ports configuration, that is an included angle of 60 degrees between two inlets and an included angle of 120 degrees between inlet and outlet ports when Re=10.

Keywords: active micro-mixer, CFD, mixing efficiency, ports configuration, Reynolds number, Wankle-type rotor

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Authors: Qing Liu, Jean-Fabien Capsal, Claude Richard

Abstract:

In this current contribution, authors are dedicated to investigate influence of the crystal lamellae orientation on electromechanical behaviors of relaxor ferroelectric Poly (vinylidene fluoride –trifluoroethylene -chlorotrifluoroethylene) (P(VDF-TrFE-CTFE)) films by control of polymer microstructure, aiming to picture the full map of structure-property relationship. In order to define their crystal orientation films, terpolymer films were fabricated by solution-casting, stretching and hot-pressing process. Differential scanning calorimetry, impedance analyzer, and tensile strength techniques were employed to characterize crystallographic parameters, dielectric permittivity, and elastic Young’s modulus respectively. In addition, large electrical induced out-of-plane electrostrictive strain was obtained by cantilever beam mode. Consequently, as-casted pristine films exhibited surprisingly high electrostrictive strain 0.1774% due to considerably small value of elastic Young’s modulus although relatively low dielectric permittivity. Such reasons contributed to large mechanical elastic energy density. Instead, due to 2 folds increase of elastic Young’s modulus and less than 50% augmentation of dielectric constant, fullycrystallized film showed weak electrostrictive behavior and mechanical energy density as well. And subjected to mechanical stretching process, Film C exhibited stronger dielectric constant and out-performed electrostrictive strain over Film B because edge-on crystal lamellae orientation induced by uniaxially mechanical stretch. Hot-press films were compared in term of cooling rate. Rather large electrostrictive strain of 0.2788% for hot-pressed Film D in quenching process was observed although its dielectric permittivity equivalent to that of pristine as-casted Film A, showing highest mechanical elastic energy density value of 359.5 J/m3. In hot-press cooling process, dielectric permittivity of Film E saw values at 48.8 concomitant with ca.100% increase of Young’s modulus. Films with intermediate mechanical energy density were obtained.

Keywords: Crystal orientation, electrostrictive strain, mechanical energy density, permittivity, relaxor ferroelectric.

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Authors: A. Atli, K. Candelier, J. Alteyrac

Abstract:

Environmental and sustainability concerns push the industries to manufacture alternative materials having less environmental impact. The Wood Plastic Composites (WPCs) produced by blending the biopolymers and natural fillers permit not only to tailor the desired properties of materials but also are the solution to meet the environmental and sustainability requirements. This work presents the elaboration and characterization of the fully green WPCs prepared by blending a biopolymer, BIOPLAST® GS 2189 and spruce sawdust used as filler with different amounts. Since both components are bio-based, the resulting material is entirely environmentally friendly. The mechanical, thermal, structural properties of these WPCs were characterized by different analytical methods like tensile, flexural and impact tests, Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). Their water absorption properties and resistance to the termite and fungal attacks were determined in relation with different wood filler content. The tensile and flexural moduli of WPCs increased with increasing amount of wood fillers into the biopolymer, but WPCs became more brittle compared to the neat polymer. Incorporation of spruce sawdust modified the thermal properties of polymer: The degradation, cold crystallization, and melting temperatures shifted to higher temperatures when spruce sawdust was added into polymer. The termite, fungal and water absorption resistance of WPCs decreased with increasing wood amount in WPCs, but remained in durability class 1 (durable) concerning fungal resistance and quoted 1 (attempted attack) in visual rating regarding to the termites resistance except that the WPC with the highest wood content (30 wt%) rated 2 (slight attack) indicating a long term durability. All the results showed the possibility to elaborate the easy injectable composite materials with adjustable properties by incorporation of BIOPLAST® GS 2189 and spruce sawdust. Therefore, lightweight WPCs allow both to recycle wood industry byproducts and to produce a full ecologic material.

Keywords: Biodegradability, durability, mechanical properties, melt flow index, spectrophotometry, structural properties, thermal properties, wood-plastic composites.

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Authors: A. M. Pashayev, C. Ardil, D. D. Askerov, R. A. Sadiqov, P. S. Abdullayev

Abstract:

In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Keywords: Gas turbine engines, neural networks, fuzzy logic, fuzzy statistics.

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Authors: Jožef Ritonja

Abstract:

The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.

Keywords: Bioprocess engineering, biochemical reactor, fermentation process, modeling, adaptive control.

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Authors: Naoto Suzuki

Abstract:

A decline in visual sensitivity at arbitrary points on the retina can be measured using a precise perimetry apparatus along with a fundus camera. However, the retinal layer associated with this decline cannot be identified accurately with current medical technology. To investigate cryptogenic diseases, such as macular dystrophy, acute zonal occult outer retinopathy (AZOOR), and multiple evanescent white dot syndrome (MEWDS), we evaluated an electroretinogram (ERG) function that allows moving the center of the multifocal hexagonal stimulus array to a chosen position. Macular dystrophy is a generalized term used for a variety of functional disorders of the macula lutea, and the ERG shows a diminution of the b-wave in these disorders. AZOOR causes an acute functional disorder to an outer layer of the retina, and the ERG shows a-wave and b-wave amplitude reduction as well as delayed 30 Hz flicker responses. MEWDS causes acute visual loss and the ERG shows a decrease in a-wave amplitude. We combined an electroretinographic optical system and a perimetric optical system into an experimental apparatus that has the same optical system as that of a fundus camera. We also deployed an EO-50231 Edmund infrared camera, a 45-degree cold mirror, a lens with a 25-mm focal length, a halogen lamp, and an 8-inch monitor. Then, we also employed a differential amplifier with gain 10, a 50 Hz notch filter, a high-pass filter with a 21.2 Hz cut-off frequency, and two non-inverting amplifiers with gains 1001 and 11. In addition, we used a USB-6216 National Instruments I/O device, a NE-113A Nihon Kohden plate electrode, a SCB-68A shielded connector block, and LabVIEW 2017 software for data retrieval. The software was used to generate the multifocal hexagonal stimulus array on the computer monitor with C++Builder 10.2 and to move the center of the array toward the left and right and up and down. Cone and bright flash ERG results were observed using the moving ERG function. The a-wave, b-wave, c-wave, and the photopic negative response were identified with cone ERG. The moving ERG function allowed the identification of the retinal layer causing visual alterations.

Keywords: Moving ERG, multifocal ERG, precise perimetry, retinal layers, visual sensitivity

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

Abstract:

Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: Crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest.

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Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

Abstract:

In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: Carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring.

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