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This review emphasizes the significance of formulating control strategies for biological and advanced oxidation process (AOP)-based wastewater treatment systems. The aim is to guarantee that the effluent quality continuously aligns with environmental regulations while operating costs are minimized. It highlights the significance of understanding the dynamic behaviour of the process in developing effective control schemes. The most common process control strategies in wastewater treatment plants (WWTPs) are explained and listed. It is emphasized that the proper control scheme should be selected based on the process dynamic behaviour and control goal. This study further discusses the challenges associated with the control of wastewater treatment processes, including inadequacies in developed models, the limitations of most control strategies to the simulation stage, the imperative requirement for real-time data, and the financial and technical intricacies associated with implementing advanced controller hardware. It is discussed that the necessity of the availability of real-time data to achieve reliable control can be achieved by implementing proper, accurate hardware sensors in suitable locations of the process or by developing and implementing soft sensors. This study recommends further investigation on available actuators and the criteria for choosing the most appropriate one to achieve robust and reliable control in WWTPs, especially for biological and AOP-based treatment approaches.

Reef reservoirs are characterised by a complex structure of void space, which is a combination of intergranular porosity, fractures, and vuggy voids distributed chaotically in the carbonate body in different proportions. This causes great uncertainty in the distribution of porosity and permeability properties in the reservoir volume, making field development a complex and unpredictable process associated with many risks. High densities of carbonate secondary alterations can lead to the formation of zones with abnormally high porosity and permeability—high permeability streaks or super-reservoirs. Taking into account super-reservoirs in the bulk of the deposit is necessary in the dynamic modelling of complex-structure reservoirs because it affects the redistribution of filtration flows and is crucial for reservoir management. This paper proposes a method for identifying superreservoirs by identifying enormously high values of porosity and permeability from different-scale study results, followed by the combination and construction of probabilistic curves of superreservoirs. Based on the obtained curves, three probabilistic models of the existence of a superreservoir were identified: P10, P50, and P90, which were further distributed in the volume of the reservoir and on the basis of which new permeability arrays were calculated. Permeability arrays were simulated in a dynamic model of the Alpha field. The P50 probabilistic model showed the best history matching after one iteration.

• A dynamic refrigerator model of a top mounted, serial system refrigerator is developed using Modelica and validated through experiments. • Sensitivity analysis is carried out for different compressor speeds. • Door opening and placement of warm load is modelled to simulate load processing operation. • The model captures the temperature, power, and energy consumption quite well. • For all tests, simulated power consumption is within 10%, while energy consumption is within ±5%. A dynamic model of a domestic refrigerator is developed in this study and is used to analyse both the steady state (cyclic) and warm load cooling (load processing) operation. The compressor is modelled semi-empirically using loss parameters, while the capillary tube is modelled by incorporating both friction and momentum pressure drop. Heat exchangers (condenser and evaporator) are modelled as tubes divided into finite volume cells. The capillary tube-suction line heat exchanger is treated by connecting part of the capillary tube to the suction line via a heat resistor. The cabinet model consists of submodels for walls, air and shelves connected in a network to allow for thermal interaction. All the components are then arranged in a cycle, and cyclic operation is validated at 32 °C using a fixed speed compressor. A sensitivity analysis is then carried out by varying the compressor speed. In the second part of the study, the model is modified to include the effect of placing a warm load of water in the refrigerator and simulating the subsequent processing operation. This is validated using an experiment in which 20 L of water at 27 °C is placed inside the Fresh Food compartment. Results show that the power consumption value is captured well, with the average power consumption deviating less than 10% for all tests. The energy consumption is within ±5% for all tests. For load processing, the deviation in water temperature was a maximum of 1.2 °C for the whole cooling period. [ABSTRACT FROM AUTHOR]

Pollen is naturally distributed by wind or animals, but agricultural fields might suffer from lack of pollination due to a variety of factors. Artificial pollination is necessary for walnut trees because of dichogamy and lack of pollen in their early years. An airborne artificial pollination system is introduced and studied. As an automated solution, a quadrotor unmanned aerial vehicle (UAV) was fabricated for artificial pollination of walnut trees. The robot was designed, modelled and tested by releasing pollen over walnut trees. Airflow under the UAV was simulated using computational fluid dynamic (CFD) software. This simulation helped determine pollen streams under the robot to ensure that the released pollen reached the target trees. The quadrotor controller was designed and simulated in MATLAB, for system stability. For dynamic simulation, the robot was modelled in ADAMS software, and a co-simulation of MATLAB and ADAMS was used to tune and test the controller that was implemented for field experiments. The motion and stability of the UAV over farms with and without moderate winds were observed. To investigate the field performance of the proposed system, the pollination system is used on a walnut orchard. Different mixtures of pollen diluted with talcum powder were distributed over different groups of trees, using the quadrotor. After a few months, the results achieved on the trees were measured and the merits of the proposed system were evaluated. • A new quadrotor pollinator is introduced. • The pollinator is designed, simulated, and fabricated. • Modelling, control and simulation of the pollinator and pollination are presented. • The pollinator was used experimentally on an orchard and the results are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid unmanned aerial vehicle configuration, the quad tilt rotor (QTR), which combines both the tandem wing configuration and the quadrotor configuration using a tilt mechanism. The paper focuses on the vehicle configuration, transition control scheme and modified proportional-integral-derivative (PID) control. The effectiveness of a tilt rotor configuration depends on its smooth transition from rotary wing to tandem wing flight during take-off and vice-versa during landing. An autonomous transition control scheme for the QTR using a modified PID controller is proposed to maintain desirable attitudes during transition. The derivative control of error term in a conventional PID controller is replaced by the rate of change of the control parameter in the modified PID controller. The modified PID controller provides the desired response with significantly reduced oscillations and actuator control effort than the conventional PID controller. The QTR configuration is simulated in a software-in-the-loop (SIL) simulation using MATLAB Simulink and the X-Plane simulator to analyze the controller performance and flight characteristics during transitions from rotary wing to tandem wing flight during take-off and vice-versa during landing. The simulation is performed with and without atmospheric disturbance and the simulation results showed acceptable deviation in attitude during the transition even under atmospheric disturbances. [ABSTRACT FROM AUTHOR]

In order to understand how the in-situ primary stress state has evolved with subsidence and uplift in a granitic rock mass for anticipated of a radioactive waste repository in Hungary, the authors investigated the applicability of seismic tomography as an interpretive tool. Very high P wave velocity (Vp) values were obtained during the tomographic scanning of the study area of the repository, and these were compared with existing findings of in-situ and laboratory seismic measurements. Apart from seismic tomographic survey, dynamic FEM numerical modelling, empirical calculations of residual stresses, laboratory measurements of compression wave (ultrasonic) velocities on intact rock cores, in-situ primary stress measurements as well as site geological model were integrated to evaluate the use of seismic tomography for identifying possible in-situ stress increases around the excavation. A detailed calibration modelling was carried out based on the site seismic tomography measurements and during the large-scale modelling. It was observed that the increasing Vp is directly related to simulated increasing directional loadings on the rock mass. Using a measured wave raypath it was possible to check the different in-situ stress parametrizations which resulted in the best approximation to the measured Vp values. It was concluded that the rock mass under investigation to extend the repository must have higher in-situ stress values than the area of the constructed deposition chambers nearby. The results of this research indicated that seismic tomography is a useful tool for determining relative stress around and within the vicinity of underground excavation. [ABSTRACT FROM AUTHOR]

Copyright of Engineer Military Bulletin / Muszaki Katonai Közlöny is the property of National University of Public Service and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This task‐force paper documents and summarizes the models of power transformers that have been proposed, used, and validated in the exercise of digital real‐time simulation. Power transformer is one of the most important equipment in power systems, and its modelling for electromagnetic transient simulation has evolved over time, especially in the area of real‐time simulation. The focus of the paper is to document and archive the models that have been well accepted and used for transient analysis in digital real‐time simulation so that readers can use it as a master document for transformer modelling in real‐time simulation studies. It includes both conventional and specialized models of power transformers that have been broadly acknowledged by the power engineering community. The models provided here come with detailed mathematical representation and their implementation techniques. A comparative study is also performed to illustrate the differences in their performances. In the end, an application guideline has been provided to guide the readers to select the appropriate model for their study. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) storage and redistribution across the landscape (through erosion and deposition) are linked to soil physicochemical properties and can affect soil quality. However, the spatial and temporal variability of soil erosion and SOC remains uncertain. Whether soil redistribution leads to SOC gains or losses continues to be hotly debated. These considerations cannot be modelled using conventional soil carbon models and digital soil mapping. This paper presents a coupled-model combining RothPC-1 which considers soil carbon (C) down to 1 m and a soil redistribution model. The soil redistribution component is based on a cellular automata technique using the multi-direction flow (FD8) algorithm. With the optimized input values based on land use, we simulated SOC changes upon soil profiles to 1 m across the Lower Hunter Valley area (11,300 ha) in New South Wales, Australia from the 1970s to 2016. Results were compared to field observations and showed that erosion was predicted mostly in upslope areas and deposition in low-lying areas. We further simulated SOC trends from 2017 until ~2045 in the area under three climate scenarios and five land use projections. The variation in the magnitude and direction of SOC change with different projections shows that the main factors influencing SOC changes considering soil redistribution are climate change which controlled the trend of SOC stocks, followed by land use change. Neglecting soil erosion in carbon models could lead to an overestimation of SOC stocks. This paper provides a framework for incorporating soil redistribution into the SOC dynamics modelling and also postulates the thinking that soil erosion is not just a removal process by surface runoff. [ABSTRACT FROM AUTHOR]

This paper proposes a comprehensive approach to the dynamic modelling of Cable-Driven Parallel Robots (CDPRs) by means of Differential-Algebraic Equations (DAEs). CDPRs are usually modelled through a minimal set of Ordinary Differential Equations (ODEs), often by making some simplification or just focusing on the unconstrained platform/end-effector dynamics. The alternative use of redundant DAEs provides several benefits since several non-ideal properties and peculiar operations of CDPRs can be easily and accurately modelled. To provide a comprehensive modelling frame, the typical components of a CDPR with rigid cables are here discussed and modelled by exploiting the concept of DAEs, which use redundant coordinates and embed kinematic constraints in the algebraic part of the equations. Through such advantageous features, it is possible to model swivelling guiding pulleys with non-negligible dimensions and mass. The use of rheonomous constraints is proposed as well, to represent in a simple way the effect of the movable exit-points, that are widely adopted in reconfigurable CDPRs. Finally, the use of Natural Coordinates is proposed for representing spatial end-effectors and modelling some challenging operations such as its overturning or the picking of heavy objects. Numerical simulations and the comparison with the results provided by a benchmark software are shown to demonstrate the accuracy and the computational efficiency of the proposed approach. • Cable Driven Parallel Robots are modelled through Differential Algebraic Equations. • A comprehensive approach for numerical simulation is proposed. • Natural Coordinates are exploited to model spatial end-effectors. • Swivel pulley dynamics, cable failure and reconfigurability are modelled. • Some challenging robot operations can be effectively simulated. [ABSTRACT FROM AUTHOR]

• The vibration suppression performance of composite conical–cylindrical shells with damping coating is studied. • A dynamic model is proposed for predicting the vibration characteristics of conical–cylindrical shells with advanced coating. • The solution approach of the natural frequencies, mode shapes and vibration displacement responses. • Some key design recommendations are summarized to enhance the vibration resistance. This study presents the theoretical and experimental investigations on vibration behaviours of carbon fiber/ resin composite conical-cylindrical shells (or C C shells) with damping coating. First, an analytical model of such a combined shell with coating material considers the effects of base harmonic excitation load under arbitrary boundary conditions is proposed using the first-order shear deformation theory, virtual artificial spring technique, modal superposition approach, the Rayleigh-Ritz method, etc. Subsequently, the solutions of fundamental frequencies, mode shapes, and vibration displacements in the frequency domain are acquired by deriving the corresponding energy expressions and motion equations. Convergence analysis is utilized to determine the virtual spring stiffness value and the appropriate truncation numbers. Both literature and experimental results are conducted to give an adequate validation of the current model, in which the continuous 3D printing technology is adapted to fabricate two C C shell specimens with one of the outside surfaces being sprayed by coating material using an atomization deposition approach. Finally, the effects of the coating thickness ratio, Young's modulus ratio of the coating and the substrate shell, the semi-vertex angle, and the fiber laying angle on the free vibration and forced vibrations of the coated structure are discussed, with some practical recommendations being provided to improve the vibration suppression of such a coated structure. [ABSTRACT FROM AUTHOR]

• The optimal margin setting policy is derived from a multi-period model. • Countercyclical margin setting may reduce the expected loss of the CCP. • By smoothing out margins, the CCP can calm the markets. • Active risk management requires generating relevant volatility scenarios. In response to the Global Financial Crisis of 2007–2009, by now, most of the financial transactions must be cleared through central counterparties operating a dynamic margin setting mechanism. High margin calls can reduce counterparty risk in a turbulent market, but at the same time, increase liquidity risk and escalate systemic risk. In this paper, we construct a theoretical model to address this challenge, deriving an optimal margin setting policy framed as a stochastic control problem. Our analysis reveals that an adaptive, countercyclical approach is superior to a purely risk-sensitive strategy, primarily by minimizing the expected loss for the clearing institution. [ABSTRACT FROM AUTHOR]

Regional sensitivity analysis is a part of global sensitivity analysis methods. In this study, a multivariate sensitivity analysis was conducted on a qualitative-phenomenological model. Study results allowed us to pinpoint the most influential parameters. Moreover, important measures or ranking gave more insight into factors ordering according to their relative influence and permitted them to follow parameter sensitivities over time. Lastly, a confirmatory procedure using extensive parameter randomisation that covered a broad range of the parameters space allowed more insight into and certainty of each input parameters’ relative importance.

The paper describes an inverter control scheme which incorporates both a phase-locked loop (PLL) for voltage synchronization and power-frequency droop for load sharing. As such, it is a hybrid grid-forming/following controller and offers beneficial characteristics of both. The model describing the dynamic behaviour of the inverter control scheme is presented and connections with grid-forming and grid-following control strategies are considered. A process for black-starting the PLL-based inverter control scheme is described. Case studies explore controller small- and large-disturbance performance under a variety of system conditions.

The development of dynamic models for control purposes is characterised by the challenge of finding a compromise between the minimum necessary information about the system dynamics contained in the model and a model with a low level of complexity such that the model-based control system design becomes comfortable. To achieve this balance, a modified dynamic model for the drivetrain of a wind turbine is proposed in this contribution. The main idea is to introduce the tip-speed ratio as a state variable so that an interval observer can be designed in such a way that its estimates can be used in the torque control during the partial load operation as well as for the estimation of the effective wind speed. During the runtime, the observer's matrix gain is recalculated to adapt the behaviour to the current operational state, which changes all the time with the wind speed. Besides the theoretical formulation, a numerical example of a 20 MW reference wind turbine illustrates the utility of the method. The results show good control performance concerning the tip-speed ratio control loop and a satisfactory estimation of the effective wind speed. [ABSTRACT FROM AUTHOR]

In recent years, numerous projects for floating PV systems have been developed. These plants of various sizes have mainly been installed on enclosed lakes or basins characterised by the absence of external forcing related to waves and currents. However, offshore installation would allow the development of such plants in areas where land is not available, such as islands. This paper analyses the state of the art of floating PV, describes the design of a floating PV platform and the development of a numerical model to evaluate the system performance in an offshore environment. The case study of the island of Lampedusa is then analyzed: starting from a single floating foundation with its mooring system, a floating PV system is designed to meet the island's electricity needs. In order to provide the competitiveness of the system, a techno-economic analysis is carried out, evaluating the main cost items of Capex, Opex and LCOE. Although the LCOE obtained is significantly higher than a traditional solar plant installed on land, this technology is competitive compared to other offshore marine technologies such as offshore wind and wave energy. [ABSTRACT FROM AUTHOR]

This work presents a solar-driven air conditioning system based on ejector technology with closed-loop vertical geothermal boreholes. Modeling and simulation are carried out using Dymola software for dynamic transient analysis, with the refrigerant R134a. Condenser temperature regulation produces a 267% improvement of performance compared to a solar-only configuration. Solar fraction increases with increasing solar collector area, which benefits the system up to the limit of 27 m2 for a cooling load of 9 kW. The reservoir volume ensuring high solar fraction is 14 m3. Optimal generator saturation temperature ensures a seasonal coefficient of performance value of 0.772 and a maximum overall efficiency of 39%. When the system encounters deviations from the optimum set point, the overall efficiency becomes 37.4%. [ABSTRACT FROM AUTHOR]

PTFE and filled PTFE are used in sealing applications such as rotary valves, quarter-turn ball valves and pipeline gaskets, among others. Many times, these seals are designed to operate below their yield point such that plastic effects are negligible and viscoelastic effects dominate. This may lead to leakage since these devices are placed in service environments that are subjected to vibration. In seals made of viscoelastic materials, this vibration can lead to separation of the seal faces due to the delayed recovery of the material. In this paper, the isothermal viscoelastic dynamic response of a PTFE seal subjected to a harmonic input and static preload from an ideally rigid opposing face is examined. The model is a hybrid that combines the Golla–Hughes–McTavish finite element approach, a delayed recovery creep model and a penalty method contact model. Parameters for the models are taken from experimental data using a Dynamic Mechanical Analyzer test for pure PTFE material. Results for a simple application show face separation magnitude as a function of frequency and harmonic displacement amplitude. Results show that face separation occurs in PTFE seals even for small amplitude harmonic vibrations and that this is due to delayed recovery at low frequencies and to the viscoelastic damping at higher frequencies. A threshold of static preload is also found above which there is no separation and a leakage estimation is presented. [ABSTRACT FROM AUTHOR]

• The operation of solar tower external receiver is dynamically simulated in Modelica. • The creep-fatigue lifetime of each receiver panel is estimated for three materials. • Temperature spikes due to clouds passages significantly affect the panels lifetime. • Creep-fatigue analysis based on clear-sky operation leads to 30% error on lifetime. This paper proposes a methodology for the dynamic thermal analysis of solar tower external receivers and for the assessment of their lifetime. A dynamic thermal model is implemented in Modelica to assess the temperature distributions of receiver tubes and heat transfer fluid (HTF), considering real weather data with a 10-minute time resolution and PI controllers based mass flow rate control. Three representative days are simulated, and the resulting tubes temperature distributions are used to assess the elastic stresses distributions during the investigated days. Subsequently, the creep-fatigue lifetime of each receiver panel is evaluated accounting for material plasticity and creep-induced stress relaxation. The developed methodology is applied to compare three materials for solar receivers: Inconel 740H, Haynes 230, and Incoloy 800H. Results show that fatigue can be negligible with respect to creep for all investigated materials and the shortest lifetime is obtained for 800H, followed by H230, and 740H. The approximation of a receiver operation for 365 clear-sky days per year leads to errors around 30 % on the lifetime. For 740H and 800H, the damage accumulation during cloudy days with high DNI peaks is greater than during clear-sky days due to the remarkable creep damage originated during temperature spikes which follow clouds passages. H230 instead, accumulates more creep damage during clear-sky operation. This emphasizes the potential of the developed methodology to compare different HTF mass flow rate control strategies as well as receiver geometries and materials, HTFs, and heliostats aiming strategies, accounting for the trade-off between energy yield and receiver lifetime. [ABSTRACT FROM AUTHOR]

The damping properties of a commercial polymer concrete are the subject of this application-driven study, which is aimed to investigate the material suitability as a filler of machine bed components to limit vibrations arising in machine tools and automatic machines working at high dynamics. Two main goals are targeted: (i) quantitative evaluation of the elastodynamic effects due to the polymer concrete insertion into typical components of machine beds, in order to effectively assess its practical potential and (ii) determination of reliable models of the material, needed to simulate the dynamic response of new design solutions of machines featuring structural components filled with the polymer concrete. The paper is mainly focused on the methodological approach of both the experimental campaign and the signal processing that were carried out. Based on the promising results achieved, the possible use of the polymer concrete as a viable solution to enhance the dynamic behavior of an automatic machine is finally investigated and discussed as a case study. [ABSTRACT FROM AUTHOR]

The performance of electrocatalytic water splitting in polymer electrolyte membrane electrolysis is substantially determined by the microkinetic processes of the oxygen evolution reaction (OER). Even highly active catalysts such as the nanoparticulated transition metal oxides IrO2, RuO2 and their mixtures, IrxRu1−xO2, exhibit overpotentials up to several hundreds of millivolts. The surface of the oxide mixtures IrxRu1−xO2 is found to consist of actives sites of both Ir and Ru on which the OER mechanism is processed independently and at different overpotentials. By applying microkinetic modelling and parameterization via cyclic voltammograms we show that there is a correlation between performance and the relative Ir content, that can be explained by two different deprotonation steps. These are in particular the formation of the adsorbate species *OOH on rutile RuO2 and *OO on IrO2. The respective free reaction energies are quantified to 1.44 eV and 1.58 eV, which are the highest values of the process and thus determining the overpotential. The additional finding of adsorbed oxygen *O covering >40 % of the active sites during the OER suggests that subsequent water adsorption is the major performance limiting step. Finally, a synergetic effect between both active sites on the binary transition metal oxides is identified: the respective other metal lowers the potential determining reaction energy on the Ru or Ir active site. This insight into the surface processes on Ir and Ru binary oxides forms the basis for deeper understanding of the active sites for further OER catalyst development. [ABSTRACT FROM AUTHOR]

In recent years, the lower limb exoskeleton has been more and more widely used in military, medical and other fields. In this paper, the muscle–bone model of the lower limb during the human walking process is analyzed, and a lower limb exoskeleton with the purpose of loadbearing is designed. The exoskeleton is driven by four hydraulic cylinders to the hip and knee joints whose design load is 50 kg. The kinematic and dynamic model of the exoskeleton designed in this paper is established and analyzed, and it is simulated. Finally, the experiments were carried out on the exoskeleton test platform to verify that the stability, bearing capacity, tracking effect and durability of the exoskeleton can meet the requirements. [ABSTRACT FROM AUTHOR]

The Single Linear Induction Motor (SLIM) is a specialized electrical machine that produces linear motion instead of the rotary motion produced by a traditional rotary induction motor. SLIM's accurate dynamic model is required to analyze the performance of the motor under different operating conditions. Dynamic modelling of SLIM using the traditional DQ- axis equivalent circuits is difficult due to the time-varying parameters such as end effect, air gap flux, saturation, and half-filled slot. The two methods for modelling SLIMs were compared, namely the conventional method and the split method. The results of the comparison showed that both methods provided similar results, but the split method offered a more detailed analysis of the components and provided deeper insight into the behavior of the motor. The choice between the two methods depends on the specific requirements and objectives of the analysis. In this paper, the dynamic model of SLIM is modelled using conventional and split methods in MATLAB/SIMULINK. The results of the two modelling methods are compared with each other, and it is concluded that the splitting method provides better transient performance than traditional D-Q axis methods. [ABSTRACT FROM AUTHOR]

The robust rotor structure and fault-tolerance characteristics of the Switched Reluctance Motors (SRMs) are the best choice for next-generation Electric Vehicle (EV) applications. This machine has few restraints like high torque and flux ripples. However, the existing Model Predictive Control (MPC) using multiple control objectives and maximum sectors in the switching table results in high torque ripples due to the improper sector partition, Voltage Vectors (VVs) and weight factor ( K 1 ) selection. This paper proposes a Finite Set-Model Predictive Control (FS-MPC) for an analytical model of a non-linearity SRM machine to analyze the torque ripple performance. The proposed VVs are derived using sector partition based on the rotor position. The control is designed as a single cost function with the weighting factor contributing to smooth torque by selecting optimal control signals. Simulation studies and experiments with a four-phase 8/6 SRM drive verifies the enhanced FS-MPC for real-time implementation. The dynamic speed and ripple values of SRM Drives are measured using a mixed signal oscilloscope and the sensor probes. The laboratory outcomes calculate the analytical equations to validate the findings. The calculated value of torque ripple is 9 % through this FS-MPC. The study reveals that the proposed method is well suited for torque ripple reduction than flux ripples., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Corresponding author (Praveen Kumar Balachandran) currently holds the Associate Editor position in Heliyon, Energy. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 Published by Elsevier Ltd.)

Wind turbines are exposed to a variety of faults some of which can cause irreparable economic losses. Therefore, identifying the faults in a short time, ensures the correct operation of the system and prevents the mentioned losses. In this paper, using a dynamic model for wind turbines which includes mechanical and electrical parts with appropriate details, an intelligent fault detection and isolation system is designed utilizing recurrent neural networks. The proposed system can identify the occurred faults in pitch sensors and pitch actuators. Then, in order to consider the robustness of the system, it is suggested to use an adaptive fuzzy threshold in decision making block. Simulation results for the fixed threshold, robust thresholds, and the proposed adaptive fuzzy threshold validate that the suggested adaptive threshold reduces the detection time. In addition, the number of false alarms, and the number of missed ones are reduced by using the intelligent fault detection system.

Modelling the fate of micropollutants in different wastewater treatment processes is of present concern. Moreover, during the last few years, there has been an increasing interest in the development of hybrid reactors which contain both suspended biomass and biofilm. Here, a new model developed which tries to determine the fate of micropollutants in hybrid reactors such as moving bed biofilm reactor (MBBR) and called the ASM-biofilm-MPs model considered the main mechanisms leading to the micropollutant removal (sorption/desorption, biodegradation, cometabolism) in hybrid reactors. This dynamic model describes the fate of micropollutants in a hybrid reactor using first-order kinetics for biotransformation and sorption/desorption equations. Also, it considered the reactions for carbon oxidation, nitrification, and denitrification in attached and suspended biomass under aerobic conditions. The mathematical model consists of three connected models for the simulation of micropollutants, suspended biomass, and biofilm. Biochemical conversions are evaluated according to the Activated Sludge Model No. 1 (ASM1) for both attached and suspended biomass. The model is applied for a laboratory MBBR, which fed with synthetic wastewater containing 4-nonylphenol (4-NP) as micropollutant, and accurately describes the experimental concentrations of COD, attached and suspended biomass, nitrogen, and 4-NP micropollutant obtained during 180 days working at different loadings. The differences between simulations and experiments in all operational periods for sCOD, NH4–N, NO3–N, and attached and suspended biomass concentrations were less than 15%, 10%, 10%, 5% and 5%, respectively. Finally, the contribution of adsorption and biodegradation mechanisms in the fate of 4-NP was calculated, when 4-NP concentration is set to 1 µg/L (biodegradation = 86.5%, sorption = 5%) and 50 µg/L (biodegradation = 55.9%, sorption = 34.7%). [ABSTRACT FROM AUTHOR]

This paper presents aspects of how an exoskeleton assists disabled people to walk on an inclined plane. This study is carried out with the help of the dynamic modelling software for mobile mechanical systems, ADAMS. Variation laws of kinematic parameters of interest, such as rotation angles in knee and hip kinematic couplings, and connecting forces in kinematic couplings are presented. The next stage in the development of this research is the realization of the experimental prototype using 3D printing technology. For this purpose, in the last part of the work we performed a structural optimization using ANSYS software for a kinematic element of the exoskeleton structure. The results obtained allow us to validate the virtual model and give us the certainty of the functionality of the robotic system for assisting human subjects when walking on an inclined plane. [ABSTRACT FROM AUTHOR]

The present study aims to improve the efficacy of water budget (WB) estimations from various hydrological data products, by (1) evaluating the uncertainties of hydrological data products, (2) merging four precipitation and six evapotranspiration products using their error variances, and (3) employing the constrained Kalman filter (CKF) method to distribute residual errors among water budget components based on their relative uncertainties. The results show that applying bias correction before the merging process improved estimations of precipitation products with decreasing root mean square error (RMSE), except Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Variable Infiltration Capacity (VIC) and bias-corrected Climate Prediction Center Morphing Technique (CMORPH) products outperformed other evapotranspiration and bias-corrected precipitation products, respectively, in terms of mean merging weights. The terrestrial water storage change is the primary reason for non-closure errors, mainly caused by the coarse resolution of Gravity Recovery and Climate Experiment (GRACE). The CKF results were insensitive to variations in uncertainties of runoff. Precipitation derived from the CKF was the best precipitation output, with the highest correlation coefficient (CC) and smallest root mean square deviation (RMSD). [ABSTRACT FROM AUTHOR]

This article presents a novel hybrid algorithm based on the grey-wolf optimizer and whale optimization algorithm, referred here as grey-wolf optimizer–whale optimization algorithm, for the dynamic parametric modelling of a four degree-of-freedom master–slave robot manipulator system. The first part of this work consists of testing the feasibility of the grey-wolf optimizer–whale optimization algorithm by comparing its performance with a grey-wolf optimizer, whale optimization algorithm and particle swarm optimization using 10 benchmark functions. The grey-wolf optimizer–whale optimization algorithm is then used for the model identification of an experimental master–slave robot manipulator system using the autoregressive moving average with exogenous inputs model structure. Obtained results demonstrate that the hybrid algorithm is effective and can be a suitable substitute to solve the parameter identification problem of robot models. [ABSTRACT FROM AUTHOR]

A dynamic-kinetic model for gas fermentation of C. carboxidivorans is presented. The model described the acid/alcohol production in gas-fed stirred tank reactors (GFSTR) and in batch pressurized reactors. The model took into account gas-liquid mass transfer rate, carbon monoxide uptake rate and three conversion paths: cell growth associated with acid/alcohol production, alcohol production by acid conversion and direct alcohol production not associated to cell growth. The assessment of kinetic parameters/yields was carried out by regression of experimental data retrieved from the literature. The model was then used to study the effects of several process conditions on the fermentation performances. The sensitivity was analysed with respect to three operating variables (agitation speed, gas feeding flow-rate and bioreactor filling ratio) and also to the kinetic parameters/yields. The proposed model successfully reproduced the experimental data: the R² of the investigated variable concentrations ranged between 0.769 and 0.885. Sensitivity analysis pointed out that: i) the model was significantly affected by parameters related to the growth kinetic whereas it was not impacted by parameters related to direct alcohol production; ii) fermentation performances could be improved tuning the operating conditions, in particular, the decrease of the mass transfer rate could increase the cell/metabolite production. [ABSTRACT FROM AUTHOR]

There has been growing interest on forecasting mortality. In this article, we propose a novel dynamic Bayesian approach for modelling and forecasting the age‐at‐death distribution, focusing on a three‐component mixture of a Dirac mass, a Gaussian distribution and a skew‐normal distribution. According to the specified model, the age‐at‐death distribution is characterized via seven parameters corresponding to the main aspects of infant, adult and old‐age mortality. The proposed approach focuses on coherent modelling of multiple countries, and following a Bayesian approach to inference we allow to borrow information across populations and to shrink parameters towards a common mean level, implicitly penalizing diverging scenarios. Dynamic modelling across years is induced through an hierarchical dynamic prior distribution that allows to characterize the temporal evolution of each mortality component and to forecast the age‐at‐death distribution. Empirical results on multiple countries indicate that the proposed approach outperforms popular methods for forecasting mortality, providing interpretable insights on its evolution. [ABSTRACT FROM AUTHOR]

Maintaining good water quality is essential for successful fish production in land-based recirculating aquaculture systems (RAS). Numerous interdependent factors influence water quality parameters, making it difficult to evaluate which operational strategies are most favorable. Mathematical models and model simulations have proven to be powerful tools to evaluate how RAS design and operation are linked to RAS dynamics, but these models rarely implement pH and carbonate species as dynamic variables. Here, we present a dynamic model for RAS (dynRAS) that combines rates of TAN (total ammonia nitrogen) removal, fish growth, and CO 2 and TAN excretion, with a reaction model for pH and the carbonate system formulated based on the law of mass action. A novel aspect of our approach is the incorporation of a dosage system modelled by a Hill-function, enabling the exploration of diverse dosing strategies for pH and alkalinity management. The model was validated based on empirical data from a pilot scale RAS system operated with a feeding regime involving 12 h of feeding per day. We found that model simulations could be used to accurately predict diurnal cycling patterns in RAS water quality parameters. Furthermore, we made use of simulations to assess how diurnal cycling varies with changing pH and alkalinity levels. Model results emphasize the complexity of pH and alkalinity control in RAS in relation to overall water quality management. Based on our simulations, we argue that what should be considered as optimal pH and alkalinity in RAS depends on the state of the system. Accordingly, optimal pH and alkalinity thresholds may vary between different RAS units and between different time points of a rearing cycle. More generally, we demonstrate how modelling and model simulations can be an effective way of getting insights into the dynamics of complex RAS interactions and provide a valuable tool to efficiently explore effects of different operational strategies on water quality parameters. • We developed a mathematical model for RAS dynamics analysis. • Model simulations are consistent with observed dynamics. • Model simulations show that optimal control alkalinity is state-dependent. [ABSTRACT FROM AUTHOR]