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PSR J1023+0038 is the first millisecond pulsar that was ever observed as an optical and UV pulsar. So far, it is the only optical transitional millisecond pulsar. The rotation- and accretion-powered emission mechanisms hardly individually explain the observed characteristics of optical pulsations. A synergistic model, combining these standard emission processes, was proposed to explain the origin of the X-ray/UV/optical pulsations. We study the phase lag between the pulses in the optical and X-ray bands to gain insight into the physical mechanisms that cause it. We performed a detailed timing analysis of simultaneous or quasi-simultaneous observations in the X-ray band, acquired with the XMM-Newton and NICER satellites, and in the optical band, with the fast photometers SiFAP2 (mounted at the 3.6 m Telescopio Nazionale Galileo) and Aqueye+ (mounted at the 1.8 m Copernicus Telescope). We estimated the time lag of the optical pulsation with respect to that in the X-rays by modeling the folded pulse profiles with two harmonic components. Optical pulses lag the X-ray pulses by $\sim$ 150 $\mu$s in observations acquired with instruments (NICER and Aqueye+) whose absolute timing uncertainty is much smaller than the measured lag. We also show that the phase lag between optical and X-ray pulsations lies in a limited range of values, $\delta \phi \in$ (0 $-$ 0.15), which is maintained over timescales of about five years. This indicates that both pulsations originate from the same region, and it supports the hypothesis of a common emission mechanism. Our results are interpreted in the shock-driven mini pulsar nebula scenario. This scenario suggests that optical and X-ray pulses are produced by synchrotron emission from the shock that formed within a few light cylinder radii away ($\sim$ 100 km) from the pulsar, where its striped wind encounters the accretion disk inflow., Comment: 13 pages, 6 figures, 5 tables, accepted for publication in A&A

This article is concerned with the study of reliability assessment of the urea plant. A non-linear autoregressive external input (NARX) neural network was developed to predict the reliability using the failure frequency and all possible combinations of the equipment in the plant. The model was fed using field data; ten hidden layers and three subsets for the training were used: 50%, 70% and 85%. The NARX was capable of simulating the system and demonstrates a good performance comparable with the traditional reliability method and real data.

The solar telescope connected to HARPS-N has been observing the Sun since the summer of 2015. Such high-cadence, long-baseline data set is crucial for understanding spurious radial-velocity signals induced by our Sun and by the instrument. On the instrumental side, this data set allowed us to detect sub-\ms\,systematics that needed to be corrected for. The goal of this manuscript is to i) present a new data reduction software for HARPS-N, ii) demonstrate the improvement brought by this new software on the first three years of the HARPS-N solar data set, and iii) release all the obtained solar products, from extracted spectra to precise radial velocities. To correct for the instrumental systematics observed in the data reduced with the current version of the HARPS-N data reduction software (DRS version 3.7), we adapted the newly available ESPRESSO DRS (version 2.2.3) to HARPS-N and developed new optimized recipes for the spectrograph. We then compared the first three years of HARPS-N solar data reduced with the current and new DRS. The most significant improvement brought by the new DRS is a strong decrease in the day-to-day radial-velocity scatter, from 1.27 to 1.07\ms; this is thanks to a more robust method to derive wavelength solutions, but also to the use of calibrations closer in time. The newly derived solar radial-velocities are also better correlated with the chromospheric activity level of the Sun on the long-term, with a Pearson correlation coefficient of 0.93 compared to 0.77 before, which is expected from our understanding of stellar signals. Finally, we also discuss how HARPS-N spectral ghosts contaminate the measurement of the calcium activity index, and present an efficient technique to derive an index free of instrumental systematics. This paper presents a new data reduction software for HARPS-N, and demonstrates its improvements [...], Comment: 20 pages, 15 figures, 2 tables, version accepted for publication in Astronomy and Astrophysics

During the last few years we have been working on a modernization plan for the Telescopio Nazionale Galileo (TNG) Control System1,2. On October 2019 we had the opportunity to execute the first step of this process. The telescope was going to be stopped for one month due to M1 mirror being aluminized, so we could change the azimuth control system, that had been thoroughly tested during the summer, with no additional observational time loss. In this paper we present the new control system based on the CompactRIO platform from National Instruments, the switching process between the old and the new control systems, and a performance comparison between them.

Context. The existence of hot Jupiters is still not well understood. Two main channels are thought to be responsible for their current location: a smooth planet migration through the protoplanetary disk or the circularization of an initial highly eccentric orbit by tidal dissipation leading to a strong decrease in the semimajor axis. Different formation scenarios result in different observable effects, such as orbital parameters (obliquity and eccentricity) or frequency of planets at different stellar ages. Aims. In the context of the GAPS Young Objects project, we are carrying out a radial velocity survey with the aim of searching and characterizing young hot-Jupiter planets. Our purpose is to put constraints on evolutionary models and establish statistical properties, such as the frequency of these planets from a homogeneous sample. Methods. Since young stars are in general magnetically very active, we performed multi-band (visible and near-infrared) spectroscopy with simultaneous GIANO-B + HARPS-N (GIARPS) observing mode at TNG. This helps in dealing with stellar activity and distinguishing the nature of radial velocity variations: stellar activity will introduce a wavelength-dependent radial velocity amplitude, whereas a Keplerian signal is achromatic. As a pilot study, we present here the cases of two known hot Jupiters orbiting young stars: HD 285507 b and AD Leo b. Results. Our analysis of simultaneous high-precision GIARPS spectroscopic data confirms the Keplerian nature of the variation in the HD 285507 radial velocities and refines the orbital parameters of the hot Jupiter, obtaining an eccentricity consistent with a circular orbit. Instead, our analysis does not confirm the signal previously attributed to a planet orbiting AD Leo. This demonstrates the power of the multi-band spectroscopic technique when observing active stars., With funding from the Spanish government through the "María de Maeztu Unit of Excellence" accreditation (MDM-2017-0737)

In Trinidad and Tobago, it is a common practice to dispose of generated solid waste in open areas without any prior treatment. The average person generates approximately 4 lbs of waste per day This amounts to approximately 1000 tonnes of waste that reaches the landfill sites per day. Actually, the country is facing a shortage in natural gas for power generation; hence, the purpose of this article is to illustrate the environmental benefits and feasibility of utilizing landfill gas as alternative source energy. The methane generation model used for this study is the Landfill Gas Emissions Model (LandGEM). The methane generation rate constant, k and the potential methane generation capacity, L0 were determined using theoretical methods. The LandGEM model assumed 50% methane and 50% carbon dioxide landfill gas composition by volume. Using a k value of 0.119/year and a L0 value of 159 m3 methane/year the model estimated a methane generation flowrate of 30,367,038 m3/year (20,259 Mg/year) and a total landfill gas flowrate of 60,734,076 m3/year (75,846 Mg/year). This project has an IRR of 3% and is capable of generating 8.3 MW of electricity.

Use of a multiproduct pipeline operation inevitably produces an interface mixture or TRANSMIX which either has to be returned to refinery to be re-processed or downgraded into one of the adjacent batches, which is an additional cost as product is lost. In this paper, a Non-linear Autoregressive External Inputs (NARX) model is used for estimating the mixing volumes. Comparison with other models shows in the literature, the proposed neural network is reliable over a wide range of flow conditions and data. The model was fed using field data, 10 hidden layers and three subsets for the training were used: 50%, 65% and 85%. The NARX was capable of simulating the system and demonstrate a good performance comparable with the traditional methods and real data with a maximum error of 4% at 85% training data.

The article presents details of a reliability analysis for a Direct Methanol Fuel Cell system, focussing on both quantitative and qualitative methods. The system was analysed on an overall basis. The qualitative analyses presented include fault tree analyses, where four main causes of total system failure were outlined with their initiating failure modes. These included the Failure Mode, Event and Criticality analysis (FMECA) which focused on failures, causes, severity, frequency and the reaction or response to each issue. The results which included raw data for all combinations of failure were analysed in different ways and compared to the published study. It was found that for the system studied in this project, the most reliable configuration had a reliability figure of 0.98243 while the least reliable was 0.78358 compared to the published study which had a value of 0.9041. The main difference was that this study included redundancies (parallel pumps) and considered additional equipment (boost controller) compared to that of the published data. When altering the given system to match that of the published paper, the percentage error in reliability (2.1%) was very low, indicating that the differences were from configuration and analysis rather than the failure rate values.

The aim of this study was to simulate the refueling of a Natural Gas Vehicle (NGV) Cylinder from a Cascade Reservoir using chilled Natural Gas. The model was developed using the First Law of Thermodynamics, Mass balances and Gas Dynamics laws. Three distinct Cascade Reservoir temperatures were selected for simulations for this study; 288 K, 291 K and 293 K respectively. Simulations were conducted employing various initial NGV Cylinder parameters (Temperature and Pressure). The empirical findings from the simulations showed that the use of chilled Natural Gas to refuel an NGV Cylinder resulted in a reduced temperature increase during refueling in the order of 50 K-60 K as opposed to 70 K-80 K when refueling at ambient temperature. It was also observed that when using chilled natural gas to refuel, the initial cylinder temperature had no effect on the overall refueling process. However, varying initial cylinder pressures had a significant effect. Fill ratios obtained using the chilled gas were greater than refueling at ambient, however it was expected that using chilled gas fill ratios would be greater than 80%, this was not observed. The highest fill ratio obtained was 70.13%. Further analysis on the performance of the reservoir temperatures selected showed that the lower reservoir temperatures mitigated the effects of the Heat of Compression during refueling far better than refueling from ambient. This manifested in reduced in-cylinder temperature rise during refueling and higher fill ratios at completion of fill. Therefore, it was concluded that the Reservoir Temperature (T res ) has the greatest effect on the refueling process and lower Reservoir Temperatures are key to obtaining fill ratios >80%. Further study is definitely required into this novel method of obtaining a quality fill with CNG.

Context. Stellar activity is currently challenging the detection of young planets via the radial velocity (RV) technique. Aims. We attempt to definitively discriminate the nature of the RV variations for the young active K5 star BD+20 1790, for which visible (VIS) RV measurements show divergent results on the existence of a substellar companion. Methods. We compare VIS data with high precision RVs in the near infrared (NIR) range by using the GIANO - B and IGRINS spectrographs. In addition, we present for the first time simultaneous VIS-NIR observations obtained with GIARPS (GIANO - B and HARPS - N) at Telescopio Nazionale Galileo (TNG). Orbital RVs are achromatic, so the RV amplitude does not change at different wavelengths, while stellar activity induces wavelength-dependent RV variations, which are significantly reduced in the NIR range with respect to the VIS. Results. The NIR radial velocity measurements from GIANO - B and IGRINS show an average amplitude of about one quarter with respect to previously published VIS data, as expected when the RV jitter is due to stellar activity. Coeval multi-band photometry surprisingly shows larger amplitudes in the NIR range, explainable with a mixture of cool and hot spots in the same active region. Conclusions. In this work, the claimed massive planet around BD+20 1790 is ruled out by our data. We exploited the crucial role of multi- wavelength spectroscopy when observing young active stars: thanks to facilities like GIARPS that provide simultaneous observations, this method can reach its maximum potential., 12 pages, 7 figures

GIARPS (GIAno and haRPS) is a project devoted to have on the same focal station of the Telescopio Nazionale Galileo (TNG) both high resolution spectrographs, HARPS-N (VIS) and GIANO-B (NIR), working simultaneously. This could be considered the first and unique worldwide instrument providing cross-dispersed echelle spectroscopy at a resolution of 50,000 in the NIR range and 115,000 in the VIS and over in a wide spectral range (0.383-2.45 μm) in a single exposure. The science case is very broad, given the versatility of such an instrument and its large wavelength range. A number of outstanding science cases encompassing mainly extra-solar planet science starting from rocky planets search and hot Jupiters to atmosphere characterization can be considered. Furthermore both instruments can measure high precision radial velocities by means the simultaneous thorium technique (HARPS-N) and absorbing cell technique (GIANO-B) in a single exposure. Other science cases are also possible. GIARPS, as a brand new observing mode of the TNG started after the moving of GIANO-A (fiber fed spectrograph) from Nasmyth-A to Nasmyth-B where it was re-born as GIANO-B (no more fiber feed spectrograph). The official Commissioning finished on March 2017 and then it was offered to the community. Despite the work is not finished yet. In this paper we describe the preliminary scientific results obtained with GIANO-B and GIARPS observing mode with data taken during commissioning and first open time observations.

GIANO-B is the high resolution near-infrared (NIR) spectrograph of the Telescopio Nazionale Galileo (TNG), which started its regular operations in October 2017. Here we present GIANO-B Online Data Reduction Software (DRS) operating at the Telescope. GIANO-B Online DRS is a complete end-to-end solution for the spectrograph real-time data handling. The Online DRS provides management, processing and archival of GIANO-B scientific and calibration data. Once the instrument control software acquires the exposure ramp segments from the detector, the DRS ensures the complete data flow until the final data products are ingested into the science archive. A part of the Online DRS is GOFIO software, which performs the reduction process from ramp-processed 2D spectra to extracted and calibrated 1D spectra. A User Interface (UI) developed as a part of the Online DRS provides basic information on the final reduced data, thus allowing the observer to take decisions in real-time during the night and adjust the observational strategy as needed.

The NIR echelle spectrograph GIANO-B at the Telescopio Nazionale Galileo is equipped with a fully automated online DRS: part of this pipeline is the GOFIO reduction software, that processes all the observed data, from the calibrations to the nodding or stare images. GOFIO reduction process includes bad pixel and cosmic removal, flat-field and blaze correction, optimal extraction, wavelength calibration, nodding or stare group processing. An offline version of GOFIO will allow the users to adapt the reduction to their needs, and to compute the radial velocity using telluric lines as a reference system. GIANO-B may be used simultaneously with HARPS-N in the GIARPS observing mode to obtain high-resolution spectra in a wide wavelength range (383-2450 nm) with a single acquisition. In this framework, GOFIO, as part of the online DRS, provides fast and reliable data reduction during the night, in order to compare the infrared and visible observations on the fly.

In this article, a reliability analysis was carried out on a Gas Turbine Water Wash System used for washing the compressors of three (3) GE Frame 7 EA Gas Turbines using Weibull Distribution. Note that availability of this system is crucial to recovering compressor efficiency and by extension generation capability that has been lost due to contaminants on the compressor blades. This system therefore, helps maintain and improve the reliability of the turbine and of plant-wide generation. The reliability analysis covered two failure modes for each piece of equipment and took into account the reliability of the system in two operational modes, off-line washing cycle and online washing cycle for a 300 h operational time. Based on the results obtained it can be concluded that the entire water wash system can be taken as 76% reliable based on a 300 h running time. It is more reliable to perform an online water wash than an off-line water wash by at least 4% based on a 300 h operating time. This increased reliability of the water wash system to perform an online water wash is due to an off-line water wash requiring additional equipment which must be run in series. In addition to the aforementioned analysis fault trees were created to model two scenarios which relate directly to the efficiency of the gas turbine compressors and the generation capability of the turbine: (1) the likelihood of no water being present when conducting a water wash; and (2) the likelihood of cold water being sent to the water wash manifold. Based on the estimated reliabilities, the likelihood of no water being present when conducting a water wash was found to be 3.7% and the likelihood of cold water being sent to the water wash manifold is 1.6%.

Since 2012, thanks to the installation of the high-resolution echelle spectrograph in the optical range HARPS-N, the Italian telescope TNG (La Palma) became one of the key facilities for the study of the extrasolar planets. In 2014 TNG also offered GIANO to the scientific community, providing a near-infrared (NIR) cross-dispersed echelle spectroscopy covering 0.97-2.45μm at a resolution of 50000. GIANO, although designed for direct light-feed from the telescope at the Nasmyth-B focus, was provisionally mounted on the rotating building and connected via fibers to only available interface at the Nasmyth-A focal plane. The synergy between these two instruments is particularly appealing for a wide range of science cases, especially for the search of exoplanets around young and active stars and the characterisation of their atmosphere. Through the funding scheme "WOW" (a Way to Others Worlds), the Italian National Institute for Astrophysics (INAF) proposed to position GIANO at the focal station for which it was originally designed and the simultaneous use of these spectrographs with the aim to achieve high-resolution spectroscopy in a wide wavelength range (0.383-2.45μm) obtained in a single exposure, giving rise to the project called GIARPS (GIANO-B & HARPS-N). Because of its characteristics, GIARPS can be considered the first and unique worldwide instrument providing not only high resolution in a large wavelength band, but also a high-precision radial velocity measurement both in the visible and in the NIR arm, since in the next future GIANO-B will be equipped with gas absorption cells.

In all processing plants there is a great influence to improve the performance of its overall operation, safety, efficiency and production by the need to reduce the failure of its equipment. Equipment failure; even on very rare occasions, can result in great economic and financial losses. As a result of many uncertainties originating from the design and operation of the equipment at a plant there are some failure risks that cannot be avoided. In this article, the reliability of a steel refining process was predicted. Two failure modes were investigated for each type of equipment from which the reliabilities were used to determine the overall plant reliability. The maximum plant reliability was found to be 98.0%. It was noted that even though a high reliability prediction was found, it is important to employ preventative maintenance on the plant to ensure the consistent operation of the equipment and maintain the reliability.

GIARPS (GIAno & haRPS) is a project devoted to have on the same focal station of the Telescopio Nazionale Galileo (TNG) both the high resolution spectrographs HARPS-N (VIS) and GIANO (NIR) working simultaneously. This could be considered the first and unique worldwide instrument providing cross-dispersed echelle spectroscopy at a high resolution (R=115,000 in the visual and R=50,000 in the IR) and over in a wide spectral range (0.383 - 2.45 micron) in a single exposure. The science case is very broad, given the versatility of such an instrument and the large wavelength range. A number of outstanding science cases encompassing mainly extra-solar planet science starting from rocky planet search and hot Jupiters, atmosphere characterization can be considered. Furthermore both instrument can measure high precision radial velocity by means the simultaneous thorium technique (HARPS - N) and absorbing cell technique (GIANO) in a single exposure. Other science cases are also possible. Young stars and proto-planetary disks, cool stars and stellar populations, moving minor bodies in the solar system, bursting young stellar objects, cataclysmic variables and X-ray binary transients in our Galaxy, supernovae up to gamma-ray bursts in the very distant and young Universe, can take advantage of the unicity of this facility both in terms of contemporaneous wide wavelength range and high resolution spectroscopy., 8 pages, 5 figures, SPIE Conference Proceedings

The environmental characteristics of the seawater and its impacts on planning and operating RO desalination plants were always the concern of several scientists around the world. In this article, a study has been performed to investigate the seasonal characteristic of seawater in the Caribbean. The Radial Basis Function Networks (RBFN) was the methodology used in this paper where the redistribution of centres and the input training data possess significant effects in the model. The proposed method is based on clustering of input space vectors and computing weights of Euclidian distances and histogram equalization within each cluster for determining the centre and width of each receptive field. The model allows predicting the behaviour of the SDI using field data (turbidity and salinity) taking into account the tides (the Gulf of Paria) and seasonal changes (hurricane or dry seasons). The results indicated that during the hurricane season, the parameters can change up to 32% between seasons along year due to the change of direction of the inshore currents. Also values higher than 6 in the SDI indicated a very high potential for fouling. This article offers to the project engineers a new door in the application of precautionary principles in the design of desalination plants.

A study of a self-organizing controller is implemented in a way that response to controlled system follows the desired given by the model. The self-organizing controller has proven to be a valuable tool in sterilization equipment in order to verify the capacity of the response to any change in the pressure or temperature. Basically, this type of controller is based on the Self-Organizing Map (SOM) that is a neural network algorithm of unsupervised learning. The new ideas include clustering visualization, interactive training and one-dimension arrays.

In this study, the use of fuzzy logic for signal validation is introduced. This tool uses the sensor readings at the current time step to predict system state at the next time step using observers. The deviation between the sensor reading and the model prediction rises, leading to fault detection and isolation. The fault is accommodated by replacing the reading of the faulty sensor by the model prediction. The results presented in this article demonstrate that a simple scheme can carry out sensor fault detection, isolation and accommodation using a fuzzy rule-based system based on experience of an operator into heuristics. Although the method lacks the mathematical basis that other analytical methods provide, this method is simple, effective and useful. PRACTICAL APPLICATIONS The coloring process has to be controlled and monitored carefully because if the color of the MALTA is not adequate, then the MALTA has to be recycled to another unit (dilution unit) where the colorant is eliminated. This recycling process uses delay around 3 working days, and the economic impact is high. The validation of signal and reduction of fault sensor contribute to the reduction of the recycling process. In this study, the incorporation of fuzzy logic in the treatment of sensor signal represents a significant factor in the improvement of MALTA production units.

The aim of this paper is to apply a fuzzy/possibilistic approach focus in the context of the Caribbean. The fuzzy model is obtained taking into account the behaviour of salinity and total dissolved solids content according to the season (dry or hurricane season). The methodology is based on the fact that minimal/maximal values of these parameters are target values along the year rather than fixed real numbers. The results of this paper indicate that the operating costs of any desalination plant based on reverse osmosis can change up to 30% in one year.

This paper outlines the application of soft control strategies in the thermal treatment in the dairy industry. The milk pasteurizer is the most important process for guarantee the quality of the milk. The article describes with details the application of fuzzy logic and neural network in a plate heat exchanger (PHE). Recently the application of artificial intelligent has increased sharply, especially, fuzzy logic due to its easy implementation and low mathematical level. This article discusses technical features of three advanced control technologies: Fuzzy control, Model Reference Adaptive Fuzzy Control and neural networks, their implementation in food processes including a comparative study. Industrial relevance Existing control does not permit to introduce the experience of the operator for an adequate control of the milk pasteurization in industrial applications. Consequently, it was the aim of this very relevant to test the efficiency of soft techniques (fuzzy logic and neural networks) to control the temperature during milk pasteurization. The uses of soft techniques do not require complex mathematical models and complex tuning control methods. Since the controller can be realized by simple arithmetic operations, it can be improved continuously.

In this paper we describe an approach to Sensor Fault Detection, Isolation and Accommodation (SFDIA) that is mainly based on fuzzy processing of deviation from the model predictions. The predictive model is supported using a Decision Making Unit (DMU) and cased-based Reasoning principles (CRB) where pass cases are saved and filed in the Library for confirmed solution and repaired cases. This tool uses the sensor readings at the current time step to predict system state at the next time step using observers. Although the method lacks the mathematical basis that other analytical methods provide; this method is simple effective and useful.

Most of ester compounds found in beer are produced by yeast during fermentation. They contribute significantly to beer flavour. Therefore, the control of their formation is very important to maintain consistent quality of the product. In this article, the influences of fermentation temperature and dissolved oxygen content in the production of ethyl acetate and isoamyl acetate were analysed using a comparative studied between kinetic methods and neural networks. The results confirmed that the production of ester and isoamyl acetate can be expressed as a function of the ethanol formation, however the isoamyl acetate production is independent of the temperature of the fermenter. The neural networks allowed obtaining a good prediction of ester's production without to use complex model (kinetic analysis).

The aim of this paper is to apply fuzzy/possibilistic optimization focus in the context of the pyrolysis of ethane. The methodology is based on the fact that minimal/maximal values of these parameters are target values along the year rather than fixed real numbers. The fuzzy model is obtained taking into account the behaviour of the ethane conversion, steam/hydrocarbon ratio, inlet pressure and inlet temperature. The results demonstrated that the degree of optimism, α = 1, describes better the real behaviour of the process with an equilibrium approach dimensionless parameter (EA) below 0.65 and a minimum total cost of US$ 2.55.

The aim of this paper is to determine the recovery rate and other performance parameters using a numerical model. The results are presented for a two-stage seawater reverse osmosis desalination unit with spiral-wound modules. The model, which is based on the mass and momentum transport equations, takes into consideration the longitudinal variation of the velocity, the pressure and the salt concentration in the membrane modules. Data given by plant authorities reveal that the plant is currently operating at a recovery rate of 67.53%. This project has shown that for the Desalination Company of Trinidad and Tobago, the recovery rate currently achieved by the plant (67.53%) might not be the most economical. Slightly reducing the recovery rate drastically reduces the energy cost, resulting in an overall reduced cost per cubic meter of desalinated drinking water.

The aim of this paper is to apply fuzzy/possibilistic optimization focus in the context of the water conservation in a petroleum industry. The idea is assessing the water requirements of the refining industry in the operational areas: topping, cracking, petrochemicals and lubes. The result showed that the raw water consumption is 25% and the reused water consumption is 75% approximately in refineries with daily crude capacities from 94 to 1500 bbls/day.

In this paper, we describe a control laboratory course as a teaching aid during the training of undergraduate chemical engineering students. This approach facilities the understanding of the subject matter (Application of Artificial Intelligent (AI) in process control) introducing a first-hand experience at implementing intelligent control. Students execute a series of laboratory exercises, for a variety of processes, implementing fuzzy control and Neural Networks.

This article addresses the formulation of a generic model control (GMC) in a supercritical fluid extraction unit (SFE). This alternative control is solved by formulating performance objectives subject to constraints on manipulated, controlled and associated variables. This study shows the performance of the control strategy depends on how the constraints are formulated. The batch extraction of caffeine is the problem proposed in this article. The presence of constraints in the optimization problem makes the overall system nonlinear even though the process dynamics are assumed linear. Hence, the “best” control strategy was determined using field data obtained directly from the pilot plant and compared with the decoupled proportional integral derivative control system actually installed in the plant.

The knowledge-based pattern recognition (KE) approach provides a basis for classification of state of fluid systems. The new method determines bubble size distribution at high pressure that is very important for the brewery industry and other alcoholic beverages (champagne). Conforming to the principle of “decreasing precision with increasing intelligence”, the KE approach has been applied to the determination of bubble size distribution. An important feature of these architectures is that they do not require global mathematical modeling of the system.

Several production processes have been proposed for reduced-alcohol beverages. In general, the processes require specialized equipment with an inherently higher production cost. Each process, however, has its advantages and disadvantages. A study about reverse osmosis is carried out in this paper. According to the results, the reverse osmosis is not economically feasible for the production of beverages with an alcohol percentage lower 0.45%. The original extract and carbohydrates are reduced lightly such that the beverage takes a rather worthy taste. Particularly, the original beverages with higher pH produce concentration polarization phenomena such that the fouling in the membrane is increased and the solute flux is reduced considerably. However the RO system can be improved whether compensation techniques are developed.

Pasteurization is an important, if not the most important, process step in the packaging of milk. It is subject to alterations stemming from the variation in the temperature, pH and raw milk quality. The variability may manifest itself in changes in the formation of the deposit (fouling) in the pasteurization unit, such that there is a need for tools, both instrumentation and computational, to help in monitoring the process and keeping it on the desired course. In this paper we describe a practical procedure based on artificial neural networks (ANN) that allows prediction of the deposit thickness, the overall heat transfer coefficient and the critical time (the time that the unit has to be stopped for cleaning) for reducing the impact of fouling on such processes. The procedure determines when the cleaning operation is required once the system is under critical conditions of operations. A combination of fundamental studies and plant measurements were used for study of the operating conditions and thus evaluation of the trades-offs between operating conditions and longer operating life span. The results are encouraging, enough to validate current operating industrial techniques. Copyright © 2005 Society of Chemical Industry

The paper outlines the successful empirical design and validation of a space–time PI controller based on study of the controlled variable output as function of time and space. The developed control was implemented on two heat exchanger systems (falling film evaporator and milk pasteurizer). The strategy required adding a new term over the classical PI controller, such that a new parameter should be tuned. Measurements made on commercial installations have confirmed the validity of the new controller.

In this paper is introduced a general formalism for the application of advanced techniques in adaptive control as Lyapunov-based MRAFC (Model Reference Adaptive Fuzzy Control) and the hybrid system ANFIS (Adaptive-Network-based Fuzzy Inference System) for the control of the freezing fruits (strawberries). It provides a description of fuzzification, inference rules, adaptive laws and defuzzification from the fuzzy set domain. In this work, we proposed the adaptive control as an alternative to the classical control methods and illustrated as the quality of the controller can be destroyed for the linguistic interpretability of the rules.

The objective of this paper is to integrate fuzzy logic into the fermentation process in a brewery. The brewery involved is a local commercial brewery, Beamish and Crawford Brewery plc in Cork, Ireland. Our approach consists of developing a control system for a fermentation process using fuzzy logic in two stages. In the first stage the software package fuzzyTech from Inform provided the fuzzy logic controller, and in the second stage InTouch from Wonderware provided the user front-end. The results of this new controller and the fault detection system show a clear alternative over the conventional controller (PID). Optimisation of the fermentation vessel is run simultaneously with this project. The main idea is based on examining the various input parameters that influence the fermentation process. These parameters include temperature, pressure, fermentation duration and yeast count. Next the quality or output parameters are identified. These include alcohol content, present gravity, pH, colours and bitters. A model based on fuzzy logic is developed to establish the inter-relationships between these factors and how they affect the output quality factors. The ultimate objective is to integrate this fuzzy logic model into the fermentation process control system.

We present the results of our project for the design and construction and on-sky test of silicon grisms. The fabrication of such devices is a complex and critical process involving litho-masking, anisotropic etching and direct bonding techniques. After the successful fabrication of the silicon grating, we have optimized the bonding of the grating onto the hypotenuse of a silicon prism to get the final prototype. After some critical phases during the experimentation a silicon grism with 363 grooves/mm and a blaze angle of 14 degrees has been eventually fabricated. The application of an A/R coating on both the surfaces has been the last step: this procedure is critical because of the groove geometry of the diffraction grating, whose performace might be compromised by the coating. Then, the grism was inserted in the filter wheel of the Near Infrared camera NICS, at the focal plane of the National Galileo Telescope (TNG), the 3.5 m Italian facility in the Canary Islands (E). The result of the on-sky tests are given in detail., Comment: 9 pages, 13 figures, 1 table. Presented at SPIE Astronomical Telescope + Instrumentation 2014 (Ground-based and Airbone Instrumentation for Astronomy, 9151-203). To be published in Proceeding of SPIE Volume 9151

This short paper presents a design technique based on passivity for single input single output (SISO) systems through a process of feedback passivisation. The controller is implemented in the control of a tank non-isothermal for the production of pineapple syrup. The design of a model and the implementation to laboratory scale allowed the validation of the controller.

The quality of seawater is very important in the design of the pre-treatment unit of any desalination plant. It is worth noting that the operational parameters (salinity and TDS) depend on the seasons (dry or hurricane) such that they are not constants along all year. Recently, new studies indicate that the RBFN is a good tool for prediction of parameters such that the aim of this paper is to apply a RBFN approach as predictive model focus in the context of the Seawater in the Caribbean. The model is obtained taking into account the behaviour of salinity and total dissolved solids content according to the season (dry or hurricane season). The methodology is based on redistributions of centres to locations where input training data possess significant effects can lead to more efficient RBFN. The proposed method herein is based on clustering of input space vectors and computing weights of Euclidian distances and histogram equalization within each cluster will determine the centre and width of each receptive field. The results of this paper indicate that the parameters can change up to 30% along year and the accurate of the prediction obtained can be around 96.7%.

In this paper the application of a classical IMC and an IMC with modifications to a heat exchanger, is described. Here the authors suggest that the perfect controller used in the IMC system was substituted for an adaptive PID adjusted to a neural network. The heat exchanger is analysed and this paper demonstrates how, with cheaper availability of neural hardware, an efficient and intelligent controller can be designed.

We determined interfacial gas−liquid areas for the absorption of CO2 or O2 in a bubble column, with and without surfactants and/or sucrose in the absorbent liquid. All the experiments were carried out under batch processing conditions. The values obtained by the three chemical methods used have been compared, and the dependence of the operating conditions and physical properties on the interfacial area has also been analyzed. The results of experiments to determine the dependence of the area on the geometrical characteristics of the column and physical properties were fitted to within an 8% error by dimensionless modules.

We present the results of our project for the design, construction and on-sky tests of silicon grisms. Silicon grisms are optical devices, that provide a medium-high resolution spectroscopic mode in imaging instruments, without introducing major changes in instrument configuration. After some critical phases during the experimentation, a silicon grism has been eventually fabricated and inserted in the filter wheel of the Near Infrared camera NICS, at the focal plane of the National Galileo Telescope (TNG), the 3.5 m Italian facility at the Canary Islands (E). The results of the main phases of the grism fabrication and the results of the on-sky tests are detailed reported.

The Telescopio Nazionale Galileo (TNG)[9] hosts, starting in April 2012, the visible spectrograph HARPS-N. It is based on the design of its predecessor working at ESO's 3.6m telescope, achieving unprecedented results on radial velocity measurements of extrasolar planetary systems. The spectrograph's ultra-stable environment, in a temperature-controlled vacuum chamber, will allow measurements under 1 m/s which will enable the characterization of rocky, Earth-like planets. Enhancements from the original HARPS include better scrambling using octagonal section fibers with a shorter length, as well as a native tip-tilt system to increase image sharpness, and an integrated pipeline providing a complete set of parameters. Observations in the Kepler field will be the main goal of HARPS-N, and a substantial fraction of TNG observing time will be devoted to this follow-up. The operation process of the observatory has been updated, from scheduling constraints to telescope control system. Here we describe the entire instrument, along with the results from the first technical commissioning.

This short paper outlines the computer simulation using real data of a decoupled control system for a desalination unit. The control strategy incorporated a perfect decoupled controller for the control of the fresh water flow and conductivity. The model was estimated using real data and empirical tools instead of mass balances. The success is demonstrated in the reduction of wide fluctuations in the variables of the process and decreasing of the sensibility to the changes of pressure and/or pH and allows predicting problems of quality of water and waste of energy in the future.

The main objective of this note is to describe a real-time fault diagnosis and control for a cylindroconical fermenter to laboratory scale as an alternative to the classic systems. Development of a good controller for a fed-batch reactor is not enough without a fault diagnosis system. We are working to expand this idea. The failure detection system is based on the parity space approach joined with a fuzzy controller with more robustness and of superior performance in MIMO systems compared to conventional strategies. A 2-week period is reported.