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The article is an editorial introducing a special issue of the scientific journal Axioms titled "Mathematical Models and Simulations." The issue contains 13 papers that cover various mathematical models and simulations in fields such as physics, biology, finance, and engineering. The papers explore different types of mathematical models, including deterministic and stochastic models, and discuss their applications and numerical simulations. The authors provide a brief overview of each paper, highlighting their main findings and methodologies. The article aims to provide library patrons with a concise summary of the special issue, allowing them to decide if they want to explore the individual papers further. [Extracted from the article]

In this paper, we improved a mathematical model of monkeypox disease with a time delay to a crossover model by incorporating variable-order and fractional differential equations, along with stochastic fractional derivatives, in three different time intervals. The stability and positivity of the solutions for the proposed model are discussed. Two numerical methods are constructed to study the behavior of the proposed models. These methods are the nonstandard modified Euler Maruyama technique and the nonstandard Caputo proportional constant Adams-Bashfourth fifth step method. Many numerical experiments were conducted to verify the efficiency of the methods and support the theoretical results. This study's originality is the use of fresh data simulation techniques and different solution methodologies. [ABSTRACT FROM AUTHOR]

Current physical systems are built in more that one coordinate: for example, electrical power systems, aeronautical systems and robotic systems can be modeled in multibond graphs (M B G) . However, in these systems, some elements use only one axis or dimension—for example, actuators and controllers—which can be modeled in bond graphs (B G) . Therefore, in this paper, modeling of systems in multibond graphs and bond graphs ( M B G - B G ) is presented. Likewise, the junction structure of systems represented by ( M B G - B G ) is introduced. From this structure, mathematical modeling in the state space is presented. Likewise, modeling of systems on a platform ( M B G - B G ) can be seen as symmetric to the mathematical model that represents these systems. Finally, a synchronous generator modeled by ( M B G - B G ) as a case study is developed, and simulation results using 20-Sim software are shown. Furthermore, an electrical power system connected to the power supply of a DC motor as another case study is explained. [ABSTRACT FROM AUTHOR]

In this paper, a light-controlled variable damping system (LCVDS) is proposed based on PLZT ceramics and electrorheological fluid (ERF). The mathematical models for the photovoltage of PLZT ceramics and the hydrodynamic model for the ERF are established, and the relationship between the pressure difference at both ends of the microchannel and the light intensity is deduced. Then, simulations are conducted by applying different light intensities in the LCVDS to analyze the pressure difference at both ends of the microchannel using COMSOL Multiphysics. The simulation results show that the pressure difference at both ends of the microchannel increases with the increase in light intensity, which is consistent with results from the mathematical model established in this paper. The error rate of the pressure difference at both ends of the microchannel is within 13.8% between the theoretical and simulation results. This investigation lays the foundation for the application of light-controlled variable damping in future engineering. [ABSTRACT FROM AUTHOR]

The intensive development of photovoltaic (PV) micro-systems contributes to increased interest in energy efficiency and diagnosing the condition of such solutions. Optimizing system energy efficiency and servicing costs are particularly noteworthy among the numerous issues associated with this topic. This research paper addresses the easy and reliable diagnosis of PV system malfunctions. It discusses the original PV system energy efficiency simulation model with proprietary methods for determining total solar irradiance on the plane of cells installed at any inclination angle and azimuth, as well as PV cell temperature and efficiency as a function of solar irradiance. Based on this simulation model, the authors developed procedures for the remote diagnosis of PV micro-systems. Verification tests covered two independent PV systems over the period from April 2022 to May 2023. The obtained results confirm the high credibility level of both the adopted energy efficiency simulation model and the proposed method for diagnosing PV system functional status. [ABSTRACT FROM AUTHOR]

Agent-based modeling (ABM) is a flexible and simulation-friendly modeling approach. Ambient-oriented modeling is effective for systems containing ambient and spatial representations. In this paper we propose a framework for the integrated use of agent-based modeling and ambient-oriented modeling. We analyze both agents and ambient in detail. We also compare both modeling approaches as well and analyze their similarities and differences. The integrated implementation provides a new link between mathematical modeling and simulations. The model developed using this framework has four parts. The first part constitutes the identification, definition, and relations of agents. In this part, we use agent-based modeling along with the concepts of discrete-event simulations and system dynamics. The second part of the model is the mathematical representation of the relations of agents, i.e., the parent and child relation of agents. The third part of the model is the representation of the messages along with relational symbols where we utilize the concepts and symbols of relations and messages from ambient-oriented modeling. The fourth and final part of the model is the simulation, where we describe the rules that govern the processes represented in first two parts. The framework is helpful in overcoming certain limitations of both approaches. Moreover, we provide a scenario of a bus rapid transit system (BRTS) as a proof of concept, and we examine the generic concept of BRTSs using the proposed framework. [ABSTRACT FROM AUTHOR]

The optimizing design for enhancement of the micro performance of manipulator based on analytical models is investigated in this paper. By utilizing the established uncanonical linear homogeneous equations, the quasi-static analytical model of the micro-manipulator is built, and the theoretical calculation results are tested by FEA simulations. To provide a theoretical basis for a micro-manipulator being used in high-precision engineering applications, this paper investigates the modal property based on the analytical model. Based on the finite element method, with multipoint constraint equations, the model is built and the results have a good match with the simulation. The following parametric influences studied show that the influences of other objectives on one objective are complicated. Consequently, the multi-objective optimization by the derived analytical models is carried out to find out the optimal solutions of the manipulator. Besides the inner relationships among these design objectives during the optimization process are discussed. [ABSTRACT FROM AUTHOR]

This paper investigates the controllability of a closed-loop tracking synchronization network based on multiple linear-switched reluctance machines (LSRMs). The LSRM network is constructed from a global closed-loop manner, and the closed loop only replies to the input and output information from the leader node. Then, each local LSRM node is modeled as a general second-order system, and the model parameters are derived by the online system identification method based on the least square method. Next, to guarantee the LSRM network's controllability condition, a theorem is deduced that clarifies the relationship among the LSRM network's controllability, the graph controllability of the network and the controllability of the node dynamics. A state feedback control strategy with the state observer located on the leader is then proposed to improve the tracking performance of the LSRM network. Last, both the simulation and experiment results prove the effectiveness of the network controller design scheme and the results also verify that the leader-based global feedback strategy not only improves the tracking performance but also enhances the synchronization accuracy of the LSRM network experimentally. [ABSTRACT FROM AUTHOR]

In this paper a two-input, two-output (TITO) fractional order mathematical model of a laboratory prototype of a hydraulic canal is proposed. This canal is made up of two pools that have a strong interaction between them. The inputs of the TITO model are the pump flow and the opening of an intermediate gate, and the two outputs are the water levels in the two pools. Based on the experiments developed in a laboratory prototype the parameters of the mathematical models have been identified. Then, considering the TITO model, a first control loop of the pump is closed to reproduce real-world conditions in which the water level of the first pool is not dependent on the opening of the upstream gate, thus leading to an equivalent single input, single output (SISO) system. The comparison of the resulting system with the classical first order systems typically utilized to model hydraulic canals shows that the proposed model has significantly lower error: about 50%, and, therefore, higher accuracy in capturing the canal dynamics. This model has also been utilized to optimize the design of the controller of the pump of the canal, thus achieving a faster response to step commands and thus minimizing the interaction between the two pools of the experimental platform. [ABSTRACT FROM AUTHOR]

Helicopters are extraordinarily complex mechanisms. Such complexity makes it difficult to model, simulate and pilot a helicopter. The present paper proposes a mathematical model of a fantail helicopter type based on Lie-group theory. The present paper first recalls the Lagrange–d'Alembert–Pontryagin principle to describe the dynamics of a multi-part object, and subsequently applies such principle to describe the motion of a helicopter in space. A good part of the paper is devoted to the numerical simulation of the motion of a helicopter, which was obtained through a dedicated numerical method. Numerical simulation was based on a series of values for the many parameters involved in the mathematical model carefully inferred from the available technical literature. [ABSTRACT FROM AUTHOR]

Considerable efforts are currently being made by several international working groups focused on the development of generic, also known as simplified or standard, wind turbine models for power system stability studies. In this sense, the first edition of International Electrotechnical Commission (IEC) 61400-27-1, which defines generic dynamic simulation models for wind turbines, was published in February 2015. Nevertheless, the correlations of the IEC generic models with respect to specific wind turbine manufacturer models are required by the wind power industry to validate the accuracy and corresponding usability of these standard models. The present work conducts the validation of the two topologies of variable speed wind turbines that present not only the largest market share, but also the most technological advances. Specifically, the doubly-fed induction machine and the full-scale converter (FSC) topology are modeled based on the IEC 61400-27-1 guidelines. The models are simulated for a wide range of voltage dips with different characteristics and wind turbine operating conditions. The simulated response of the IEC generic model is compared to the corresponding simplified model of a wind turbine manufacturer, showing a good correlation in most cases. Validation error sources are analyzed in detail, as well. In addition, this paper reviews in detail the previous work done in this field. Results suggest that wind turbine manufacturers are able to adjust the IEC generic models to represent the behavior of their specific wind turbines for power system stability analysis. [ABSTRACT FROM AUTHOR]

Utilization of hydraulic-fracturing technology is dramatically increasing in exploitation of natural gas extraction. However the prediction of the configuration of propagated hydraulic fracture is extremely challenging. This paper presents a numerical method of obtaining the configuration of the propagated hydraulic fracture into discrete natural fracture network system. The method is developed on the basis of weighted fracture which is derived in combination of Dijkstra's algorithm energy theory and vector method. Numerical results along with experimental data demonstrated that proposed method is capable of predicting the propagated hydraulic fracture configuration reasonably with high computation efficiency. Sensitivity analysis reveals a number of interesting observation results: the shortest path weight value decreases with increasing of fracture density and length, and increases with increasing of the angle between fractures to the maximum principal stress direction. Our method is helpful for evaluating the complexity of the discrete fracture network, to obtain the extension direction of the fracture. [ABSTRACT FROM AUTHOR]

In this paper, the spatio-temporal (multi-channel) linear models, which use temporal and the neighbouring wind speed measurements around the target location, for the best short-term wind speed forecasting are investigated. Multi-channel autoregressive moving average (MARMA) models are formulated in matrix form and efficient linear prediction coefficient estimation techniques are first used and revised. It is shown in detail how to apply these MARMA models to the spatially distributed wind speed measurements. The proposedMARMAmodels are tested using real wind speed measurements which are collected from the five stations around Canakkale region of Turkey. According to the test results, considerable improvements are observed over the well known persistence, autoregressive (AR) and multi-channel/vector autoregressive (VAR) models. It is also shown that the model can predict wind speed very fast (in milliseconds) which is suitable for the immediate short-term forecasting. [ABSTRACT FROM AUTHOR]

When faults and disturbances occur in power systems, backup power resources respond to maintain the system's frequency, and the frequency recovery effect is related to the primary frequency regulation of the reserve capacity provided by and the response speeds of the system's generating units and interruptible loads. The relationships between a system's frequency and the frequency regulation capacity of the generating units and the interruptible loads are different. In this paper, an index for the frequency recovery effect is proposed based on the static frequency adjustment coefficient of the interruptible load and the adjustment coefficients of the generating units, and an optimization model of an interruptible load participating in primary frequency regulation is built with the objective of minimizing the cost of the primary frequency regulation reserve that uses the system's frequency recovery effect as a constraint. The simulation results verify the validity of the model. [ABSTRACT FROM AUTHOR]

Numerical simulation of shielding effectiveness (SE) of a perforated shielding enclosure is carried out, using the finite element method (FEM). Possibilities of model definitions and differences between 2D and 3D models are discussed. An important part of any simulation is verification of the model results-here the simulation result are verified in terms of convergence of the model in dependence on the degrees of freedom (DOF) and by measurements. The experimental method is based on measurement of electric field inside the enclosure using an electric field probe with small dimensions is described in the paper. Solution of an illustrative example of SE by FEM is shown and simulation results are verified by experiments. [ABSTRACT FROM AUTHOR]

In this study, a novel intentional island model of a distribution system with distributed generations (DGs) is presented and the improved Dijkstra algorithm is used to solve this model. This paper abstracts the distribution network with DGs to the layered directed tree according to its radial structure and power restoration process. In consideration of grade, controllability, capacity, level and electrical betweenness of load, the model weights load and maximizes total load weight in the island. The proposed model considers power balance, node voltage, phase angle and transmission capability of the branch, and network connectivity to meet practical engineering requirements. The improved Dijkstra algorithm formulates a search rule to select the load that can be divided into an island in descending order of the shortest path between the load node and DG node. An optimal island partition scheme is achieved through three stages: origin island, baby island and mature island. Meanwhile, scheme adjustment and constraint checking are used alternately to balance objective functions and constraints. The improved IEEE 43-bus distribution network is applied to verify the validity of the algorithm. A comparison of two island methods shows that the proposed algorithm can generate a reasonable scheme for island partitioning. [ABSTRACT FROM AUTHOR]

It has recently been shown that using battery storage systems (BSSs) to provide reactive power provision in a medium-voltage (MV) active distribution network (ADN) with embedded wind stations (WSs) can lead to a huge amount of reverse power to an upstream transmission network (TN). However, unity power factors (PFs) of WSs were assumed in those studies to analyze the potential of BSSs. Therefore, in this paper (Part-I), we aim to further explore the pure reactive power potential of WSs (i.e., without BSSs) by investigating the issue of variable reverse power flow under different limits on PFs in an electricity market model. The main contributions of this work are summarized as follows: (1) Introducing the reactive power capability of WSs in the optimization model of the active-reactive optimal power flow (A-R-OPF) and highlighting the benefits/impacts under different limits on PFs. (2) Investigating the impacts of different agreements for variable reverse power flow on the operation of an ADN under different demand scenarios. (3) Derivation of the function of reactive energy losses in the grid with an equivalent-Л circuit and comparing its value with active energy losses. (4) Balancing the energy curtailment of wind generation, active-reactive energy losses in the grid and active-reactive energy import-export by a meter-based method. In Part-II, the potential of the developed model is studied through analyzing an electricity market model and a 41-bus network with different locations of WSs. [ABSTRACT FROM AUTHOR]

Resection of the epilepsy foci is the best treatment for more than 15% of epileptic patients or 50% of patients who are refractory to all forms of medical treatment. Accurate mapping of the locations of epileptic neuronal networks can result in the complete resection of epileptic foci. Even though currently electroencephalography is the best technique for mapping the epileptic focus, it cannot define the boundary of epilepsy that accurately. Herein we put forward a new accurate brain mapping technique using superparamagnetic nanoparticles (SPMNs). The main hypothesis in this new approach is the creation of super-paramagnetic aggregates in the epileptic foci due to high electrical and magnetic activities. These aggregates may improve tissue contrast of magnetic resonance imaging (MRI) that results in improving the resection of epileptic foci. In this paper, we present the mathematical models before discussing the simulation results. Furthermore, we mimic the aggregation of SPMNs in a weak magnetic field using a low-cost microfabricated device. Based on these results, the SPMNs may play a crucial role in diagnostic epilepsy and the subsequent treatment of this disease. [ABSTRACT FROM AUTHOR]

A single-species population model exhibiting a symmetric slow variation for the carrying capacity and intrinsic growth rate is evaluated explicitly. However, it is unrealistic to eliminate the possibility of a clear separation in the evolution of the biotic environmental elements; thus, this paper considers the situation where these elements have a hierarchical variation on the time scales. Accordingly, two particular situations are recognized, which are the carrying capacity varies faster than the growth rate and vice versa. Applying the multi-time scaling technique in such a system provides a small parameter, which leads us to construct analytical approximate expressions for the population behavior, using the perturbation approach. Such approximations display very good agreement with the numerical simulations. [ABSTRACT FROM AUTHOR]

For the interconnected power system with large-scale wind power, the problem of the small signal stability has become the bottleneck of restricting the sending-out of wind power as well as the security and stability of the whole power system. Around this issue, this paper establishes a small signal stability region boundary model of the interconnected power system with large-scale wind power based on catastrophe theory, providing a new method for analyzing the small signal stability. Firstly, we analyzed the typical characteristics and the mathematic model of the interconnected power system with wind power and pointed out that conventional methods can't directly identify the topological properties of small signal stability region boundaries. For this problem, adopting catastrophe theory, we established a small signal stability region boundary model of the interconnected power system with large-scale wind power in two-dimensional power injection space and extended it to multiple dimensions to obtain the boundary model in multidimensional power injection space. Thirdly, we analyzed qualitatively the topological property's changes of the small signal stability region boundary caused by large-scale wind power integration. Finally, we built simulation models by DIgSILENT/PowerFactory software and the final simulation results verified the correctness and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

In the last two decades, microneedles (MNs) have received significant interest due to their potential for painless transdermal drug delivery (TDD) and minimal skin damage. MNs have found applications in a range of research and development areas in drug delivery. They have been prepared using a variety of materials and fabrication techniques resulting in MN arrays with different dimensions, shapes, and geometries for delivery of a variety of drug molecules. These parameters play crucial roles in determining the drug release profiles from the MNs. Developing mathematical modelling, simulation, and optimisation techniques is vital to achieving the desired MN performances. These will then be helpful for pharmaceutical and biotechnological industries as well as professionals working in the field of regulatory affairs focusing on MN based TDD systems. This is because modelling has a great potential to reduce the financial and time cost of both the MNs' studies and manufacturing. For example, a number of robust mathematical models for predicting the performance of the MNs in vivo have emerged recently which incorporate the roles of the structural and mechanical properties of the skin. In addressing these points, this review paper aims to highlight the current status of the MN modelling research, in particular, the modelling, simulation and optimisation of the systems for drug delivery. The theoretical basis for the simulation of MN enhanced diffusion is discussed within this paper. Thus, this review paper provides a better understanding of the modelling of the MN mediated drug delivery process. [ABSTRACT FROM AUTHOR]

In this paper, a novel approach for the simulation of cavitation and aeration in hydraulic systems using the lumped parameter method is presented. The presented approach called the Hybrid Rayleigh–Plesset Equation model is derived from the Rayleigh–Plesset Equation representative of bubble dynamics and overcomes several shortcomings present in existing lumped parameter based cavitation modeling approaches. Models based on static approximations do not consider the non-equilibrium effects of phase change on the system and incorrectly predict the system dynamics. On the other hand, the existing dynamic cavitation modeling strategies account for the non-equilibrium effects of phase change but express the evolution of phases through approximations of the Rayleigh–Plesset Equation (such as exclusion of nonlinear interactions in bubble dynamics), which often lead to physically unrealistic time-scales of bubble growth or dissolution. This paper presents a dynamic model for cavitation which is capable of predicting cavitation in hydraulic systems while preserving the nonlinear dynamics arising from the Rayleigh–Plesset Equation. The derived model determines the evolution of phases in terms of physically realizable parameters such as the bubble radius and the nuclei density, which can be estimated or determined experimentally. The paper demonstrates the effectiveness of the derived modeling approach with the help of numerical simulations of an External Gear Machine. Results from the simulations employing the proposed model are compared with an existing dynamic cavitation modeling approach and validated with experimental results over a range of dynamic parameters. [ABSTRACT FROM AUTHOR]

Finite-control-set model predictive current control (FCS-MPCC) has been widely investigated in the field of motor control. When the discrete motor prediction model is not obtained accurately, prediction error often occurs, which can result in improper determinations of optimal voltage vectors and can further affect the control performance of motor systems. However, papers evaluating the motor control performance employing FCS-MPCC rarely consider prediction error and its utilization to weaken the influence of inaccurate prediction model. This paper investigates in depth the prediction error caused by three influencing factors from the perspective of model accuracy—discretization method, prediction stepsize, and parameter mismatch. Firstly, the evaluation index, prediction error, is defined and its formulas considering the above three factors are derived based on interior permanent magnet synchronous motor (IPMSM). Then, the theoretical analysis of prediction error is provided. Finally, experimental results of an IPMSM drive system are presented to verify and complement the theoretical analysis. Both the theoretical analysis and experimental results fully elaborate the prediction error, which can offer practical guidelines for the evaluation and improvement of motor control performance, especially for FCS-MPCC in IPMSM applications. [ABSTRACT FROM AUTHOR]

In this paper, a novel finite-time nonlinear extended state observer (NLESO) is proposed and employed in active disturbance rejection control (ADRC) to stabilize a nonlinear system against system's uncertainties and discontinuous disturbances using output feedback based control. The first task was to aggregate the uncertainties, disturbances, and any other undesired nonlinearities in the system into a single term called the "generalized disturbance". Consequently, the NLESO estimates the generalized disturbance and cancel it from the input channel in an online fashion. A peaking phenomenon that existed in linear ESO (LESO) has been reduced significantly by adopting a saturation-like nonlinear function in the proposed nonlinear ESO (NLESO). Stability analysis of the NLEO is studied using finite-time Lyapunov theory, and the comparisons are presented over simulations on permanent magnet DC (PMDC) motor to confirm the effectiveness of the proposed observer concerning LESO. [ABSTRACT FROM AUTHOR]

Bottom-up integrated assessment models, like MESSAGEix, depend on the description of the capabilities and limitations of technological, economical and ecological parameters, and their development over long-time horizons. Even small models of a few nodes, technologies and model years require input-data sets involving several hundred thousand data points. Such data sets quickly become incomprehensible, which makes error detection, collaborative working and the interpretation of results challenging, especially for non-self-created models. In response to the resulting need for manageable, comprehensible, and traceable representation of input-data, we developed a Python-based spreadsheet interface (d2ix) that enables presentation and editing of model input-data in a concise form. By increasing accessibility and transparency of the model input-data, d2ix reduces barriers to entry for new modellers and simplifies collaborative working. This paper describes the methodology and introduces the open-source Python-package d2ix. The package is available under the Apache License, Version 2.0 on GitHub. [ABSTRACT FROM AUTHOR]

This paper reports a novel frandsen generalized wake model and its variation model-frandsen generalized normal distribution wake model for off-shore wind farms. Two different new wake models in off-shore wind farms have been studied comparatively. Their characteristics have been analyzed through mathematical modeling and derivation. Meanwhile, simulation experiments show that the proposed two new wake models have different properties. Furthermore, the distributions of wind speed and wind direction are modeled by the statistical methods and Extreme Learning Machine through the off-shore wind farms of Yangshan Deepwater Harbor in the Port of Shanghai, China. In addition, the data of wind energy are provided to verify and test the correctness and effectiveness of the proposed two models. Wind power has been demonstrated by wind rose and wind resources with real-time data. These techniques contribute to enhance planning, utilization and exploitation for wind power of off-shore wind farms. [ABSTRACT FROM AUTHOR]

In this paper, the finite control set model predictive control (FCS–MPC) technique-based controller is proposed for the inverter of the uninterrupted power supply (UPS) system. The proposed controller uses the mathematical model of the system to forecast the response of voltage for each possible switching state for every sampling instant. Following this, the cost function was used to determine the switching state, applied to the next sampling instant. First, the proposed control strategy was implemented for the single inverter of the UPS system. Finally, the droop control strategy was implemented for parallel inverters to guarantee actual power sharing among a multiple-parallel UPS system. To validate the performance of the proposed controller under steady-state conditions and dynamic-transient conditions, extensive simulations were conducted using MATLAB/Simulink. The proposed work shows a low computational burden, good steady state performance, fast transient response, and robust results against parameter disturbances as compared to linear control. The simulation results showed that total harmonic distortion (THD) for the linear load was 0.9% and THD for the nonlinear load was 1.42%. [ABSTRACT FROM AUTHOR]

The cooperative localization of submerged autonomous underwater vehicles (AUVs) using the Time Difference of Arrival (TDOA) measurements of surface AUV sensors is an effective method for many applications of AUVs. Proper positioning of the sensors to maximize the observability of the AUVs is very critical for cooperative localization. In this paper, a novel method for obtaining the optimal formation of sensor AUVs has been presented for the three-dimensional (3D) cooperative localization of targets using the TDOA technique. An evaluation function for estimating the optimal formation has been derived based on Fisher Information Matrix (FIM) theory for a single target as well as multiple-target cooperative localization systems. An iterative stepping algorithm has been followed to solve the evaluation function and obtain the optimal positions of the sensors. The algorithm ensured that the computation complexity should remain limited, even when the number of sensor AUVs is increased. Various simulation examples are then presented to calculate the optimal formation for different systems/situations. The effect of the position of the reference sensor and operating depth of the target AUVs on the optimal formation of the sensors has also been studied, and conclusions are drawn. For implementation of the proposed method for more practical scenarios, a simulation example is also presented for cases when the target's position is only known with uncertainty. [ABSTRACT FROM AUTHOR]

The mathematical model of the polymer plasticization in the reciprocating screw injection moulding machine is presented in this paper. Methods of calculation of the most important flow characteristics, such as the solid bed profile, the pressure and temperature profiles, the mass flow rate, the power demand, the screw torque and the energy consumption were analysed. According to the mathematical model, a computer program was developed. Based on the computer program, simulation studies of the injection moulding process were conducted. Thereafter, the experimental studies, evaluating the theoretical model from the accuracy and usefulness point of view, were carried out. Important output quantities, such as the temperature and pressure profiles, the power demand by the screw, the torque on the screw and the screw rotation time were measured. The studies were performed on a specially made research office. The simulation results were compared with the experimental data measured for the most popular polymers and different operating parameters of the injection machine. The experimental studies have indicated the need to introduce some corrections to the mathematical model. Several modifications have been made to the model, mainly related to the methods of stress determining in the polymer layer. Finally, the output characteristics of the plasticization process in the injection moulding are now correctly determined by the model with an average error less than 10%. [ABSTRACT FROM AUTHOR]

The correct approximation of parallel resistance (Rp) and series resistance (Rs) poses a major challenge for the single diode model of the photovoltaic module (PV). The bottleneck behind the limited accuracy of the model is the static estimation of resistive parameters. This means that Rp and Rs, once estimated, usually remain constant for the entire operating range of the same weather condition, as well as for other conditions. Another contributing factor is the availability of only standard test condition (STC) data in the manufacturer’s datasheet. This paper proposes a single-diode model with dynamic relations of Rp and Rs. The relations not only vary the resistive parameters for constant/distinct weather conditions but also provide a non-iterative solution. Initially, appropriate software is used to extract the data of current-voltage (I-V) curves from the manufacturer’s datasheet. By using these raw data and simple statistical concepts, the relations for Rp and Rs are designed. Finally, it is proved through root mean square error (RMSE) analysis that the proposed model holds a one-tenth advantage over numerous recently proposed models. Simultaneously, it is low complex, iteration-free (0 to voltage in maximum power point Vmpp range), and requires less computation time to trace the I-V curve. [ABSTRACT FROM AUTHOR]

This paper assesses the impact of a farm of wave energy converters on a nearby offshore aquaculture installation and on the nearshore dynamics. The coastal area targeted is Aguçadoura, located in the north of Portugal, where the world’s first wave farm operated in 2008. The study is focused mainly on the evaluation of the sheltering effect provided by the wave farm to the aquaculture cages. Furthermore, the possible impact on the coastal wave climate of such an energy park is also evaluated. These objectives are accomplished by performing simulations, corresponding to the wave conditions, which are more often encountered in that coastal environment. The SWAN model (Simulating WAves Nearshore) was adopted for this. Various transmission scenarios are considered to account for the impact of different types of wave converter farms on the downwave conditions. The results show that such a wave energy park might have a clear positive impact on the wave conditions fish farm installed downwave and it might also have a beneficial influence on shoreline dynamics from the perspective of coastal protection. [ABSTRACT FROM AUTHOR]

Nowadays, more and more applications are dependent on storage and management of semi-structured information. For scientific research and knowledge-based decision-making, such data often needs to be published, e.g., medical data is released to implement a computer-assisted clinical decision support system. Since this data contains individuals’ privacy, they must be appropriately anonymized before to be released. However, the existing anonymization method based on l-diversity for hierarchical data may cause serious similarity attacks, and cannot protect data privacy very well. In this paper, we utilize fuzzy sets to divide levels for sensitive numerical and categorical attribute values uniformly (a categorical attribute value can be converted into a numerical attribute value according to its frequency of occurrences), and then transform the value levels to sensitivity levels. The privacy model ( α l e v h , k)-anonymity for hierarchical data with multi-level sensitivity is proposed. Furthermore, we design a privacy-preserving approach to achieve this privacy model. Experiment results demonstrate that our approach is obviously superior to existing anonymous approach in hierarchical data in terms of utility and security. [ABSTRACT FROM AUTHOR]

In this paper we devise a neural-network-based model to improve the production workflow of organic solar cells (OSCs). The investigated neural model is used to reckon the relation between the OSC's generated power and several device's properties such as the geometrical parameters and the active layers thicknesses. Such measurements were collected during an experimental campaign conducted on 80 devices. The collected data suggest that the maximum generated power depends on the active layer thickness. The mathematical model of such a relation has been determined by using a feedforward neural network (FFNN) architecture as a universal function approximator. The performed simulations show good agreement between simulated and experimental data with an overall error of about 9%. The obtained results demonstrate that the use of a neural model can be useful to improve the OSC manufacturing processes. [ABSTRACT FROM AUTHOR]