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The Barndorff–Nielsen and Shephard (BNS) model is a representative jump-type stochastic volatility model. Still, no method exists to compute option prices numerically for the non-martingale case with infinite active jumps. In this paper, selecting the minimal martingale measure (MMM) as a representative martingale measure, we develop two simulation methods for the BNS model under the MMM. The first method simulates the asset price at maturity and the Radon–Nikodym density of the MMM separately. On the other hand, the second method directly computes the asset price distribution under the MMM. In addition, we implement some numerical experiments to evaluate the performance of our simulation methods. [ABSTRACT FROM AUTHOR]

Purpose: Nonlinear solution approaches for inverse problems require fast simulation techniques for the underlying sensing problem. In this work, the authors investigate finite element (FE) based sensor simulations for the inverse problem of electrical capacitance tomography. Two known computational bottlenecks are the assembly of the FE equation system as well as the computation of the Jacobian. Here, existing computation techniques like adjoint field approaches require additional simulations. This paper aims to present fast numerical techniques for the sensor simulation and computations with the Jacobian matrix. Design/methodology/approach: For the FE equation system, a solution strategy based on Green's functions is derived. Its relation to the solution of a standard FE formulation is discussed. A fast stiffness matrix assembly based on an eigenvector decomposition is shown. Based on the properties of the Green's functions, Jacobian operations are derived, which allow the computation of matrix vector products with the Jacobian for free, i.e. no additional solves are required. This is demonstrated by a Broyden–Fletcher–Goldfarb–Shanno-based image reconstruction algorithm. Findings: MATLAB-based time measurements of the new methods show a significant acceleration for all calculation steps compared to reference implementations with standard methods. E.g. for the Jacobian operations, improvement factors of well over 100 could be found. Originality/value: The paper shows new methods for solving known computational tasks for solving inverse problems. A particular advantage is the coherent derivation and elaboration of the results. The approaches can also be applicable to other inverse problems. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to introduce a new numerical approach based on the local weak form and the Petrov–Galerkin idea to numerically simulation of a predator–prey system with two-species, two chemicals and an additional chemotactic influence. Design/methodology/approach: In the first proceeding, the space derivatives are discretized by using the direct meshless local Petrov–Galerkin method. This generates a nonlinear algebraic system of equations. The mentioned system is solved by using the Broyden's method which this technique is not related to compute the Jacobian matrix. Findings: This current work tries to bring forward a trustworthy and flexible numerical algorithm to simulate the system of predator–prey on the nonrectangular geometries. Originality/value: The proposed numerical results confirm that the numerical procedure has acceptable results for the system of partial differential equations. [ABSTRACT FROM AUTHOR]

In this paper, we consider a regulation problem for a class of feedforward nonlinear systems with unknown control coefficients and unknown growth rate. More specifically, the unknown control coefficients are assumed to be time-varying and belong to ranges with unknown upper and lower bounds. Due to the described control coefficients with uncertain feedfoward nonlinearities, our considered system is the natural extension of the related existing results. In solving our control problem, a new adaptive controller is derived by constructing a Lyapunov function in backstepping-like procedure and utilizing appropriate parameters based on the gain scaling technique and Nussbaum function. The uniquely designed exponents of a dynamic gain overcome the difficulties caused from the unknown sign and unknown ranges of the control coefficients and uncertain nonlinearities and thus play a key role in system regulation. We give the rigorous system analysis and simulation results of the numerical example to certify our control method. [ABSTRACT FROM AUTHOR]

The dynamics of modern hybrid power systems are characterized by behaviors at different timescales, typically separated by several orders of magnitude. In this paper we apply the envelope-following method to hybrid power systems simulations, in which single-phase and three-phase representations of a power system co-occur. This simulation method is well suited for handling coexisting behaviors occurring at different timescales. Compared to the simulation approaches present in the literature, the envelope-following method does not need to continuously switch between two separate simulation engines, but rather automatically handles instantaneous variations in the dynamics of the system, such as faults or topology changes. Additionally, given the vast penetration of power electronic components in modern electricity networks, employing the envelope-following method allows using a vast array of numerical algorithms that have been developed over the years to simulate electrical and electronic circuits. The proposed approach is validated by means of power systems case studies of increasing complexity. [ABSTRACT FROM AUTHOR]

Human behavior may be one of the most challenging phenomena to model and validate. This paper proposes a method for automatically extracting and compiling evidence on human behavior determinants into a knowledge graph. The method (1) extracts associations of behavior determinants and choice options in relation to study groups and moderators from published studies using Natural Language Processing and Deep Learning, (2) synthesizes the extracted evidence into a knowledge graph, and (3) sub-selects the model components and relationships that are relevant and robust. The method can be used to either (4a) construct a structurally valid simulation model before proceeding with calibration or (4b) to validate the structure of existing simulation models. To demonstrate the feasibility of the method, we discuss an example implementation with mode of transport as behavior choice. We find that including non-frequently studied significant behavior determinants drastically improves the model's explanatory power in comparison to only including frequently studied variables. The paper serves as a proof-of-concept which can be reused, extended or adapted for various purposes. • The structure of behavior models should be validated using existing evidence. • Deep Learning can help automatize behavior evidence extraction and synthesis. • Infrequently studied significant variables improve model performance drastically. [ABSTRACT FROM AUTHOR]

The article reports on a series of tests that were conducted in order to find the perfect size and shape of paper to be used during the simulation of a blizzard. The interest in finding the answer originated from a stage performance featuring clowns and a snow storm element. The scientific community sought to find a more realistic effect.

• The paper provides a clusterwise regression model for interval-valued variables. • It uses a k-means type algorithm and the center and range non-linear regression. • It is able to select the best pair of center and range (linear/ non-inear) functions. • Applications on synthetic and real data sets corroborate the proposed method. Interval-valued variables are required in data analysis since this type of data represents either the uncertainty existing in an error measurement or the natural variability of the data. Currently, methods and algorithms which aim to manage interval-valued data are very much required. Hence, this paper presents a center and range clusterwise nonlinear regression algorithm for interval-valued data. The proposed algorithm combines a k-means type algorithm with the center and range linear and nonlinear regression methods for interval-valued data, with the aim to identify both the partition of the data and the relevant regression models fitted on the center and range of the intervals simultaneously, one for each cluster. The proposed method is able to automatically select the best pair of center and range (linear and/or nonlinear) functions according to optimization criteria. A simulation study with synthetic data sets with the purpose of assessing the parameter estimation and the prediction performance of the proposed algorithm was undertaken. Finally, applications on real data sets were performed and the prediction accuracy of the proposed method was compared to the linear case. The results obtained showed that the proposed method performed well on both synthetic and real data sets. [ABSTRACT FROM AUTHOR]

This paper presents a low-area and low-power consumption CMOS differential current controlled oscillator (CCO) for neuromorphic applications. The oscillation frequency is improved over the conventional one by reducing the number of MOS transistors thus lowering the load capacitor in each stage. The analysis shows that for the same power consumption, the oscillation frequency can be increased about 11% compared with the conventional one without degrading the phase noise. Alternatively, the power consumption can be reduced 15% at the same frequency. The prototype structures are fabricated in a standard 65 nm CMOS technology and measurements demonstrate that the proposed CCO operates from 0.7 – 1.2 V supply with maximum frequencies of 80 MHz and energy/cycle ranging from 0.11 – 0.38 pJ over the tuning range. Further, system level simulations show that the nonlinearity in current-frequency conversion by the CCO does not affect its use as a neuron in a Deep Neural Network if accounted for during training. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide simulation modelling for bulk arrival bulk service queueing system involved in a textile industry and analyze the performance metrics. Design/methodology/approach: This paper describes the simulation modelling of a bulk queueing system with limited number of admissions and multiple vacations. The model is developed for the proposed queueing system using Flexsim 2017, and it is explained through an application observed in a textile industry involving the process of cone winding. Findings: In this paper, the simulation model has been developed to study the behaviour of queues at different resources in a production system. Various performance measures such as average components, average waiting time, total number of inputs and outputs, processing time and idle time involved in a textile industry are evaluated using simulation and justified through numerical illustration. Practical implications: The proposed simulation model may be used in various scenarios wherever a real time situation exists related to bulk queueing system. The results produced in this paper can be used by the manufacturing industries to enhance the need-based accuracy. It is worth pointing out that the findings are of direct practical relevance and can be successfully used for a number of industrial applications. Originality/value: The approach suggested in this paper attempts to deal with the queueing system involved in a textile industry and provides numerical results in less time with less computer resources. It provides a reasonably good approximation for simple and complex queueing models where it is difficult to find closed form of theoretical results. [ABSTRACT FROM AUTHOR]

Recently, the ontological metamodel plays an increasingly important role to specify systems in two forms: ontology and metamodel. Ontology is a descriptive model representing reality by a set of concepts, their interrelations, and constraints. On the other hand, metamodel is a more classical, but more powerful model in which concepts and relationships are represented in a prescriptive way. This study firstly clarifies the difference between the two approaches, then explains their advantages and limitations, and attempts to explore a general ontological metamodeling framework by integrating each characteristic, in order to implement semantic simulation model engineering. As a proof of concept, this paper takes the combat effectiveness simulation systems as a motivating case, uses the proposed framework to define a set of ontological composable modeling frameworks, and presents an underwater targets search scenario for running simulations and analyzing results. Finally, this paper expects that this framework will be generally used in other fields. [ABSTRACT FROM AUTHOR]

Purpose: In recent years, domestic smog has become increasingly frequent and the adverse effects of smog have increasingly become the focus of public attention. It is a way to analyze such problems and provide solutions by mathematical methods. Design/methodology/approach: This paper establishes a new gray model (GM) (1,N) prediction model based on the new kernel and degree of grayness sequences under the case that the interval gray number distribution information is known. First, the new kernel and degree of grayness sequences of the interval gray number sequence are calculated using the reconstruction definition of the kernel and degree of grayness. Then, the GM(1,N) model is formed based on the above new sequences to simulate and predict the kernel and degree of the grayness of the interval gray number sequence. Finally, the upper and lower bounds of the interval gray number are deduced based on the calculation formulas of the kernel and degree of grayness. Findings: To verify further the practical significance of the model proposed in this paper, the authors apply the model to the simulation and prediction of smog. Compared with the traditional GM(1,N) model, the new GM(1,N) prediction model established in this paper has better prediction effect and accuracy. Originality/value: This paper improves the traditional GM(1,N) prediction model and establishes a new GM(1,N) prediction model in the case of the known distribution information of the interval gray number of the smog pollutants concentrations data. [ABSTRACT FROM AUTHOR]

Purpose: System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017. Design/methodology/approach: The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions. Findings: Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing. Originality/value: The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application. [ABSTRACT FROM AUTHOR]

In order to suffice the stringent surface requirements imposed on silicon wafers, thorough investigation of the fabrication methods is necessary. Typically, the processing conditions for slicing and grinding operations are determined via scratch experiments, where the information is mostly derived from the wear scars at the scratched surface. In order to cultivate an improved understanding of the subsurface deformations caused by silicon micro-scratching, numerical simulations are instrumental. For this purpose, a continuum particle-based micro-scale formulation is here proposed that addresses two challenges: (i) the need for a numerical methodology enabling mechanical continuum-discontinuum transitions and (ii) a constitutive model that accounts for the mechanics resulting from the underlying phase transformations. In this paper, both aspects are covered in order to simulate the basics of silicon micro-scratching. First, an extension of the recently introduced Continuum Bond Method (CBM), a continuum-based particle methodology, is presented along with its implementation details in LAMMPS. Then, the finite strain extension of an infinitesimal continuum inelastic model for silicon taken from literature is discussed which captures the mechanical effects of the underlying silicon phase transitions. The cubic diamond Si-I material serves as the parent phase which transforms to a tetragonal Si-II structure upon compression. Subsequent decompression of the Si-II phase initiates the transformation to an amorphous phase. In the constitutive model, an isotropic approach is adopted, whereby the inelastic transformation strains (both volumetric and deviatoric) follow from stress-based criteria. These two models are integrated and the continuum behavior of a silicon scratch is investigated in the context of experimental observations from literature. • Three-dimensional extension of continuum particle formulation: Continuum Bond Method. • Continuum Bond Method (CBM) implemented in particle simulator LAMMPS. • Finite strain extension of an isotropic continuum inelastic model for silicon. • Constitutive model captures underlying mechanics related to phase transformations. • Simulation results in line with experimental observations for silicon scratching. [ABSTRACT FROM AUTHOR]

Inadvertent but inevitable mismatches among nominally identical unit element 1-bit digital-to-analog converters (DACs) within a multi-bit Nyquist-rate DAC cause both static and dynamic error in the DAC’s continuous-time output waveform. Prior calibration techniques are able to suppress static mismatch error, but have had limited success in suppressing dynamic mismatch error. This paper presents a digital calibration technique that adaptively measures and cancels both static and dynamic mismatch error over the DAC’s first Nyquist band. The technique is capable of either foreground or background operation, and is relatively insensitive to non-ideal circuit behavior. The paper presents a rigorous mathematical analysis of the technique, and demonstrates the results of the paper with both behavioral and transistor-level circuit simulations. [ABSTRACT FROM PUBLISHER]

Actuator faults often occur in physical systems, which seriously affect the transient performance and control accuracy of the system. For the finite-time consensus tracking problem of multiple Lagrangian systems with actuator faults and preset error constraints, a novel distributed fault-tolerant controller is proposed in this paper. The proposed controller is developed based on the barrier Lyapunov function method and the adding a power integrator technique, which can not only guarantee the steady-state performance of the system but also its transient performance. Due to its strong sensitivity to the variation of system errors, the proposed controller can quickly eliminate the system initial errors and the error perturbations caused by actuator faults. That is, the controller can guarantee that the consensus error converges to zero in a finite time and is always constrained within the preset error bound. Finally, the effectiveness of the developed controller is verified by simulation of a multi-manipulator system. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop a subgrid-scale (SGS) model for large eddy simulation (LES) of buoyancy- and thermally driven transitional and turbulent flows and further examine its performance. Design/methodology/approach: Favre-filtered, non-dimensional LES equations are solved using non-dissipative, fully implicit, kinetic energy conserving, finite-volume algorithm which uses an iterative predictor-corrector approach based on pressure correction. Also, to develop a new SGS model which accounts for buoyancy, turbulent generation term in SGS viscosity is properly modified and enhanced by buoyancy production. Findings: The proposed model has been successfully applied to turbulent Rayleigh–Bénard convection. The results show that the model is able to reproduce the complex physics of turbulent thermal convection. In comparison with the original wall-adapting local eddy-viscosity (WALE) and buoyancy-modified (BM) Smagorinsky models, turbulent diagnostics predicted by the new model are in better agreement with direct numerical simulation. Originality/value: A BM variant of the WALE SGS model is newly developed and analyzed. [ABSTRACT FROM AUTHOR]

Traffic congestion is a global problem that cannot be solved by continuing to add new roads and extra capacity, which is accentuated in the areas where roads of unlimited-access (e.g. arterial streets) interface those of limited-access (e.g. freeways). Many researchers have addressed this problem but we present here a novel method to utilize a fuzzy logic model to reduce traffic congestion in such interfacing areas during saturated traffic conditions. More specifically this paper presents a control method for a complex traffic control system: Diverging Diamond Interchange (DDI) - Ramp Metering (RM), under oversaturated traffic conditions. The DDI is a relatively new concept of an alternative intersection geometry where two intersections serve left-turn movements without conflicts. However, such DDI left-turn movements, along with the right-turn movements from the opposite direction, put additional 'pressure' on the on-ramp of the freeways or multilane highways that intersect with DDIs. If freeway operations are saturated or near saturation, which may be the result of RM operations, this type of traffic control system can lead to a fully jammed condition with a potential spillback. The purpose of the proposed fuzzy-logic control is to prevent such a queue spillback from the metering ramp to the DDI. After presenting the fuzzy-logic control (FLC) model, we compare it to the conventional fixed time control (FTC) to evaluate potential benefits. To assess the quality of proposed analytical solutions in the real-traffic-like environment we evaluated the two logics in a VISSIM microsimulation model. The results show that, when compared to FTC, the FLC method improves traffic conditions moderately but in the oversaturated environment where there is very little room for improvement. [ABSTRACT FROM AUTHOR]

This paper describes the design of a regional observer-based controller for the locally Lipchitz nonlinear systems, which can be employed successfully to attain both monitoring and control of a wide range of systems. An observer-based control approach has been employed to attain advantages of the traditional state feedback along with the state estimation through an observer. A lot of work has been accomplished for the globally Lipchitz nonlinear systems. However, a less conservative continuity, called the generalized ellipsoidal Lipchitz condition, has been applied in this paper to consider the locally Lipchitz systems. This condition is then incorporated to attain convex routines for computing the local controller and observer gains. The focus of the present study is to investigate conditions for simultaneous design of observer and controller under locally Lipchitz nonlinearities for systems with norm-bounded disturbances that not only guarantees the stabilization and true state estimation but also robustness against external perturbations. Furthermore, the decoupling of the observer and controller design conditions has been worked out for obtainment of a simple design method. Since the resultant control approach applies to a general class of systems, it can be straightforwardly employed to the globally Lipschitz nonlinear systems as a specific case. The approach is tested via a chaotic system and simulation results are provided to validate the effectiveness of resultant control schemes for the locally Lipschitz systems. [ABSTRACT FROM AUTHOR]

This paper considers the optimization problem for partially observable Markov decision processes (POMDPs) with the continuous state, observation, and action spaces. POMDPs with the discrete spaces have emerged as a promising approach to the decision systems with imperfect state information. However, in recent applications of POMDPs, there are many problems that have continuous states, observations, and actions. For such problems, due to the infinite dimensionality of the belief space, the existing studies usually discretize the continuous spaces with the sufficient or nonsufficient statistics, which may cause the curse of dimensionality and performance degradation. In this paper, based on the sensitivity analysis of the performance criteria, we have developed a simulation-based policy iteration algorithm to find the local optimal observation-based policy for POMDPs with the continuous spaces. The proposed algorithm needs none of the specific assumptions and prior information, and has a low computational complexity. One numerical example of the complicated multiple-input multiple-output beamforming problem shows that the algorithm has a significant performance improvement. [ABSTRACT FROM AUTHOR]

Purpose: Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically express and manage the complex products design process. Design/methodology/approach: To solve these problems, a supernetwork model of complex products design is constructed and analyzed in this paper. First, the design elements (customer demands, design agents, product structures, design tasks and design resources) are identified and analyzed, then the sub-network of design elements are built. Based on this, a supernetwork model of complex products design is constructed with the analysis of the relationship among sub-networks. Second, some typical and physical characteristics (robustness, vulnerability, degree and betweenness) of the supernetwork were calculated to analyze the performance of supernetwork and the features of complex product design process. Findings: The design process of a wind turbine is studied as a case to illustrate the approach in this paper. The supernetwork can provide more information about collaborative design process of wind turbine than traditional models. Moreover, it can help managers and designers to manage the collaborative design process and improve collaborative design efficiency of wind turbine. Originality/value: The authors find a new method (complex network or supernetwork) to describe and analyze complex mechanical product design. [ABSTRACT FROM AUTHOR]

This paper presents a novel spread-spectrum clock (SSC) tracking aid for digitally-controlled clock and data recovery (CDR) loops. The proposed tracking aid accurately recovers the time instants when the slope of the incoming data frequency ramp changes its polarity, so that the CDR can pre-emptively compensate the timing errors that can otherwise be incurred when relying on feedback controls only. Compared with the existing SSC tracking aids, the proposed tracking aid’s integration-based mean-tracking loop, comprising an integrator and subsequent negative feedback loop, achieves the superior noise resilience and SSC timing accuracy. The analysis shows that the error in recovering the SSC deflection timing can be as low as 0.01% of the SSC modulation period in case of tracking a triangular SSC profile and the error does not exceed 1.5% even when the SSC profile noise is increased to the signal-to-noise-plus-distortion ratio of 20 dB. The behavioral simulation of a digitally-controlled phase-locked loop (PLL)-based CDR employing the proposed SSC tracking aid demonstrates a 0.711-UI timing margin with a BER of 10−12, which is a $1.57\times $ improvement in comparison with a PLL-based second-order CDR, when tracking a 6-Gb/s data stream modulated with a 30-kHz, 50000-ppm extended triangular-shaped SSC profile. [ABSTRACT FROM AUTHOR]

This paper studies an $H_{\infty }$ model reduction problem for interval frequency negative imaginary (IFNI) systems. For a given IFNI system, our goal is to find a reduced-order IFNI system satisfying a pre-specified $H_{\infty }$ approximation error bound over the finite-frequency interval. Necessary and sufficient conditions in terms of matrix inequalities are derived for the existence and construction of an $H_{\infty }$ reduced-order IFNI system. An improved iterative algorithm is provided to solve the matrix inequalities and to minimize the $H_{\infty }$ approximation error. The proposed method is further clarified via the application to the electrical circuits, such as high-order Sallen–Key low-pass filter, piezoelectric tube scanner, and RLC circuit. The simulation results on these electrical circuits are compared with the finite-frequency interval Gramians-based model reduction method both in the frequency domain and time domain. [ABSTRACT FROM AUTHOR]

This paper deals with the quantized control problem for nonlinear semi-Markov jump systems subject to singular perturbation under a network-based framework. The nonlinearity of the system is well solved by applying Takagi–Sugeno (T-S) fuzzy theory. The semi-Markov jump process with the memory matrix of transition probability is introduced, for which the obtained results are more reasonable and less limiting. In addition, the packet dropouts governed by a Bernoulli variable and the signal quantization associated with a logarithmic quantizer are deeply studied. The major goal is to devise a fuzzy controller, which not only assures the mean-square $\bar { \sigma }$ -error stability of the corresponding system but also allows a higher upper bound of the singularly perturbed parameter. Sufficient conditions are developed to make sure that the applicable controller could be found. The further examination to demonstrate the feasibility of the presented method is given by designing a controller of a series DC motor model. [ABSTRACT FROM AUTHOR]

In this paper, we consider the identification of matrix state-space models (MSSM) of the following form: \begin{align*} \mathbf {X}(k+1) &= \mathbf {A}_2 \mathbf {X}(k) \mathbf {A}_1^T + \mathbf {B}_2 \mathbf {U}(k) \mathbf {B}_1^T \\ \mathbf {Y}(k) &= \mathbf {C}_2 \mathbf {X}(k) \mathbf {C}_1^T + \mathbf {E}(k) \end{align*} for all time dependent quantities and matrices of appropriate dimensions. Due to the large size of these matrices, vectorization does not allow the use of standard multivariable subspace methods such as N4SID or MOESP. In this paper, the resulting Kronecker structure that appears in the system matrices due to vectorization is exploited for developing a scalable subspace-like identification approach. This approach consists of first estimating the Markov parameters associated to the MSSM via the solution of a regularized bilinear least-squares problem that is solved in a globally convergent manner. Second, a bilinear low-rank minimization problem is tackled which allows to write a three-dimensional low-rank tensor and consequently to estimate the state sequence and the lower-dimensional matrices $\mathbf {A}_1,\mathbf {A}_2,\mathbf {B}_1,\mathbf {B}_2,\mathbf {C}_1,\mathbf {C}_2$. A numerical example on a large-scale adaptive optics system demonstrates the ability of the algorithm to handle the identification of state-space models within the class of Kronecker structured matrices in a scalable manner which results in more compact models. [ABSTRACT FROM AUTHOR]

Abstract In Yin and Lin (2016), a new penalty, termed as iSCAD penalty, is proposed to obtain the maximum likelihood estimates (MLEs) of the weights and the common scale parameter of an Erlang mixture model. In that paper, it is shown through simulation studies and a real data application that the penalty provides an efficient way to determine the MLEs and the order of the mixture. In this paper, we provide a theoretical justification and show that the penalized maximum likelihood estimators of the weights and the scale parameter as well as the order of mixture are all consistent. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is the development of a CFD methodology based on LES computations to analyze the rotor–stator interaction in an axial fan stage.Design/methodology/approach A wall-modeled large eddy simulation (WMLES) has been performed for a spanwise 3D extrusion of the central section of the fan stage. Computations were performed for three different operating conditions, from nominal (Q_N) to off-design (85 per cent Q_N and 70 per cent Q_N) working points. Circumferential periodic conditions were introduced to reduce the extent of the computational domain. The post-processing procedure enabled the segregation of unsteady deterministic features and turbulent scales. The simulations were experimentally validated using wake profiles and turbulent scales obtained from hot-wire measurements.Findings The transport of rotor wakes and both wake–vane and wake–wake interactions in the stator flow field have been analyzed. The description of flow separation, particularly at off-design conditions, is fully benefited from the LES performance. Rotor wakes impinging on the stator vanes generate a coherent large-scale vortex shedding at reduced frequencies. Large pressure fluctuations in the stagnation region on the leading edge of the vanes have been found.Research limitations/implications LES simulations have shown to be appropriate for the assessment of the design of an axial fan, especially for specific operating conditions for which a URANS model presents a lower performance for turbulence description.Originality/value This paper describes the development of an LES-based simulation to understand the flow mechanisms related to the rotor–stator interaction in axial fan stages. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we investigate the adaptive subspace detection of range-spread target embedded in compound Gaussian clutter. The inverse Gaussian distribution is considered to describe the texture of the clutter in order to match the non-Gaussian characteristic of sea clutter. Moreover, the range-spread target's energy is assumed to be spread not only in range dimension but also in Doppler dimension, which is more suitable for the practical situation. Thus, the range-spread target is modeled as a subspace signal which describes the range-spread and Doppler-spread. In this paper, an adaptive detector for a subspace range-spread target is derived by using two-step generalized likelihood ratio test (GLRT). Finally, the detection performance of the proposed detector is verified by experiments based on measured data and simulation data. The experimental results show that the detection performance of the proposed detector is better than that of the existing detectors. [ABSTRACT FROM AUTHOR]

Abstract The task of recovering a sparse signal from its noisy observations can be divided into two stages; recovering the positions of the nonzero entries or support and estimating their values. In this paper, fundamental limits of sparsity pattern recovery is investigated. Although this problem has been addressed in the recent literature, there is still a gap between those results and the exact limits. In this work, first a tight upper bound is derived on the error probability of the exact sparsity pattern recovery when the Maximum Likelihood (ML) decoder is exploited. Next, a sharp sufficient condition for perfect recovery of the support from noisy projections is derived. In their analyses, the authors treat random sampling matrix with standard normal entries and Gaussian noise. It is shown that the sufficient number of observations for perfect support recovery depends on the noise variance, the minimum nonzero entry of the sparse vector, and the sparsity parameter (k) which is in agreement with previous findings. The proposed upper bound is highly close to the exact probability of error, leading to tight sufficient condition which also matches the growth rate of the necessary conditions of the previous established works. More precisely, the proposed sufficient condition and the previously-established necessary condition on the number of samples are both O (k) (linear in k). The results are proved and supported both theoretically and by simulations. Highlights • In this paper, sufficient condition for exact sparsity pattern recovery is derived for Maximum Likelihood decoder. • A new upper bound is derived on the error probability of the exact sparsity pattern recovery. • The derived upper bound is tighter than the previous upper bound. • Convergence rate of the proposed upper bound is greater than that of the previous bounds. • Results are supported by simulations which show the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper we consider Trefftz methods which are based on functions defined by single layer or double layer potentials, integrals of the fundamental solution, or their normal derivative, on cracks. These functions are called cracklets , and satisfy the partial differential equation, as long as the crack support is not placed inside the domain. A boundary element method (BEM) interpretation is to consider these cracks as elements of the original boundary, in a direct BEM approach, or elements of an artificial boundary, in an indirect BEM approach. In this paper we consider the cracklets just as basis functions in Trefftz methods, as the method of fundamental solutions (MFS). We focus on the 2D Laplace equation, and establish some comparisons and connections between these methods with cracklets and standard approaches like the BEM, indirect BEM, and the MFS. Namely, we propose the enrichment of the MFS basis with the cracklets. Several numerical simulations are presented to test the performance of the methods, in particular comparing the results with the MFS and the BEM. [ABSTRACT FROM AUTHOR]

Purpose The theoretical method of converting the magnetic circuit into an electric circuit is mature, but the way to determine the inductances in the electric circuit is not reliable, especially for the core working in saturation status, and it is impossible to determine the inductances by the transformer terminal measurements, as the measurement information is not enough to determine a number of inductances. This paper aims to propose an approach of calculating the reluctances.Design/methodology/approach In this paper, an approach of calculating the reluctances is proposed based on the numerical simulation of magnetic field in transformer with different values of current excitation. The reluctance of a core segment or air region as a branch of magnetic circuit is obtained by the magnetic energy and magnetic flux. By this way, all the reluctances as function of flux can be determined, and then the inductances can be determined. The reluctances and equivalent electric circuit of three-phase integrative transformer is determined, and its validation is proved in the paper.Findings The single phase example shows that the proposed method has a good performances on analysis of the inrush current in deep saturation. The peak value of the inrush current derived from the proposed approach matches well with the results obtained by coupled circuit-FEM analysis, and the difference is about 4.8 per cent. For studies on dual models of single phase transformers, the leakage inductances have important effects on the peak value of the inrush current. The reluctances of three-phase transformer are calculated, and the equivalent circuit simulation results are slightly smaller than the coupled circuit-FEM simulation results.Originality/value Approach of calculating the reluctances based on the numerical simulation of magnetic field in transformer is proposed. The magnetic core and air space are divided into several segments, and the reluctance for each segment is calculated based on the energy in the region and the flux of the cross-sectional area. By applying various excitation currents, all the reluctances as function of flux can be determined, and then all the non-linear inductances including the non-linear leakage inductances are obtained. The proposed approach is reliable to determine a number of inductances in the dual electric circuit, especially for deep saturation status. [ABSTRACT FROM AUTHOR]

In this paper we investigate an application of hybrid Monte Carlo Tree Search (MCTS) based algorithms to solving dynamic decision making problems. We employ UCT (the most popular MCTS approach) in combination with well-known Resource Constrained Project Scheduling Problem (RCPSP) and Stochastic Resource Constrained Project Scheduling Problem (SRCPSP) solvers to devise strategies for a generic and highly dynamic version of RCPSP, which we call Risk-Aware Project Scheduling Problem (RAPSP). We compare these strategies’ performance with results of both pure MCTS approach and non-MCTS solvers for projects of varied characteristics. We reach a conclusion that proposed hybrid simulation-heuristic methods are promising approaches to dynamic decision making problems, RAPSP in particular. Consequently, we argue that more research effort should be directed to applications of MCTS algorithm outside the domain of game-playing, with which it is commonly associated. At the same time, to the best of our knowledge, this paper is the first attempt at defining generalized SRCPSP model encompassing arbitrary risks and risk response / mitigation strategies as an optimization problem and applying Computational Intelligence methods to build fully-automated decision making systems. We strongly believe it to be a research direction worth further investigation, combining project scheduling, risk management and metaheuristic optimization techniques into a well-defined platform allowing direct comparisons of different strategies. [ABSTRACT FROM AUTHOR]

Practical fracture problems are characterised by complex patterns of multiple and branching cracks, somewhat far removed from the fracture problems used for validation of numerical methods, involving single cracks, and the simulation of complex multi-tipped cracks brings many challenges to current numerical methods. The cracking particle method (CPM) incorporates the description of a crack path into the meshless nodes or particles used to discretise a problem domain. The CPM has recently been improved to make the crack paths continuous and to include adaptivity. In this paper we take this improved CPM further and introduce new crack particles which can model multiple fractures to handle crack branches and crack junctions without the need for any specialised techniques such as enrichment. Some examples with complex crack patterns are tested to show the performance of the proposed methodology and good results are obtained which agree well with previous papers. [ABSTRACT FROM AUTHOR]

The hydraulic turbine governing system plays an indispensable role in maintaining the stability of electrical power system. In this paper, synergetic control theory is introduced to enhance the regulating ability of the hydraulic turbine governing system. For the purpose of describing the characteristics of objective system and deducing the synergetic control rule, a nonlinear mathematic model of a hydraulic turbine governing system with long tail race and two surge tanks is established. Furthermore, the nonlinear characteristic of the hydraulic turbine is described by six variable partial derivatives. For further investigation, the hydraulic turbine governing system is conducted to running under load condition when its coaxial generator connects to an infinite bus. Simulation experiments have been made under both load disturbance and three-phase short circuit fault conditions to compare the dynamic performances of proposed synergetic governing controller and classic PID controller. The results indicate that the proposed synergetic governing controller is an effective alternative in normal condition and a superior one in emergency. Moreover, the robustness of synergetic governing controller has also been discussed at the end of this paper. [ABSTRACT FROM AUTHOR]

The traditional mechanism for maintaining a list of pending events in a discrete event simulation is the simple linked list. However, in large scale simulations this list often becomes cumbersome to maintain since the number of pending events may become quite large. As a result, the execution time required by the simple linked list is often a significant portion of total simulation time. Several papers have been published suggesting improved synchronization procedures. The most efficient procedures reported are the time-indexed procedure and the two-level procedure. Both methodologies are much more efficient than simple linked lists; however, neither has been adopted by a general purpose simulation language. Further, both procedures require external parameter definition, which is a major handicap to their adoption by a general purpose language. This paper introduces a new sychronization procedure, the two-list procedure, which is much faster than simple linked lists for large pending event files. This procedure was designed for implementation in Fortran, and properly implemented it is transparent to the user. Thus it is ideal for adoption by general purpose simulation languages. [ABSTRACT FROM AUTHOR]

Delays are important processes represented by continuous simulation models; however, representing queueing delays efficiently within continuous simulations merits the development of new methodology. Rothkopf and Oren introduced the concept of using a surrogate distribution, viz., the negative-binomial, as a closure approximation to the infinite set of Chapman-Kolmogorov equations representing a nonstationary M/M/s queue. The method presented in this paper uses the Polya-Eggenberger distribution as a surrogate for the true distribution of the number in the queueing system at a particular time and only requires the numerical integration of five differential equations. The paper presents numerical results comparing the Polya surrogate and Rothkopf and Oren's approximation for a number of diverse cases, and these results indicate that the Polya surrogate is, in general, more accurate, although exceptions were encountered. Moreover, queueing delays represented by a closure approximation involving a surrogate distribution, in particular, the Polya, are suitable for use within a larger continuous simulation. [ABSTRACT FROM AUTHOR]

This paper extends the use of the regenerative property of queueing systems in the analysis of simulation output. In particular, it describes a sequential estimation method which when used with the regenerative property allows results to be obtained with specified statistical accuracy. This method includes a test to check the normality assumption on which the sequential procedure relies. The paper illustrates the method using the empty and idle state as the regenerative state. A second example then describes how using the most frequently entered state as the regenerative state reduces the chance of making a costly error in a preliminary simulation run. The paper also described how a variance reduction method due to Page [9] can be used to obtain a specified accuracy with considerably fewer job completions than are required when no variance reduction technique is applied. [ABSTRACT FROM AUTHOR]

Nowadays online consumer reviews (OCR) has increasingly received scholars' attention as an important form of word-of-mouth. Recent study shows that online reviews of a product, such as a book or a restaurant, have effect on long-term consuming behavior and the future rating of the product, it mainly reflects that the early high rating of a product will lead the decrease trend of rating over time. To confirm the existence of the effect and explore how it works, over 180,000 reviews on Dianping.com were collected to investigate the behavior patterns and intrinsic dynamics. In this paper, four temporal evolution patterns were observed via evaluating the cumulative average rating series for each restaurant. Moreover, a conceptual model considering the influence of heterogeneous preferences and the self-selection mechanism was introduced, and the numerical results coincided with the empirical analysis well enough to support the hypotheses. We find special preferences result in tendentious consumption and unrepresentative reviews, these reviews lead the potential consumers to over- or under-estimate the products and directly affect the subsequent ratings. The conclusions of this paper can contribute to the specific policies to adjust the initial rating effect for the specific marketing strategies. [ABSTRACT FROM AUTHOR]

This paper presents an interval-based discrete-event simulation (IBS) mechanism to help improve the robustness of simulations that incorporate input uncertainty. This proposed simulation mechanism is based on imprecise probability and models the parameter and model-form uncertainty without the need of sensitivity analysis in traditional simulation practice. The imprecise probabilistic measure given in an interval form is used as the input of simulation in our proposed IBS mechanism, where the statistical distribution parameters have interval values. A parameterization technique for interval probability distributions is proposed in this paper. An interval random variate generation method is used to run the simulation. Uncertainty propagation is achieved by applying Kaucher interval arithmetic. The proposed mechanism is illustrated with an M/M/1 queueing system. [ABSTRACT FROM AUTHOR]

Purpose Internet-based intangible network good (IING) has revolutionized multiple industries in recent years. This paper aims to reveal the laws of consumer’s decision-making on IING from a perspective of kinetic energy and potential energy.Design/methodology/approach In this paper, 4 aspects and 17 factors influencing IING adoption were generalized. Based on the theory of social physics, an agent-based simulation model, introducing physical energy theory to depict consumer’s decision-making, was built. An agent’s kinetic energy reflects the agent’s perceived effect of mass media on the agent’s decision-making on IING adoption. An agent’s potential energy reflects the agent’s perceived effect of social interactions on the agent’s decision-making on the adoption of IING. An agent’s final energy is the sum of the kinetic energy and potential energy, which reflects the agent’s final decision.Findings Some factors mainly influence the diffusion velocity, while other factors have a dramatic impact on both diffusion velocity and diffusion scale. The agent’s personality can make a difference at the early and middle stages of IING adoption, but a faint impact at the later stage because of the effects of network externalities and word of mouth. There is a critical value of the number of initial adopters which can dramatically speed up IING adoption.Practical implications This study provides new insights for firms on the effects of factors influencing consumers’ decision-making on IING adoption.Originality/value This paper defines a new kind of innovation, IING, and generalizes IING’s special characteristics. As a new application of social physics, the physical energy theory has been creatively introduced to depict consumer’s decision-making on IING adoption. A kinetic and potential energy model of IING adoption has been built. Based on simulation experiments, new insights of IING adoption have been gained. [ABSTRACT FROM AUTHOR]

In this paper, we mainly investigate the finite-time consensus problem of general linear multi-agent systems. The paper proposed a suitable event-triggered control strategy. The strategy has some desirable properties including: distributed, independent, and asynchronous. It is theoretical demonstrated that the multi-agent system can achieve consensus in a certain time regardless of the initial condition under this event-triggered control scheme. In addition, without finding singular triggering problem, we prove the feasibility of this proposed event-triggered control protocol. Finally, we put forward some simulation graphs for the sake of showing the availability of our conclusions. [ABSTRACT FROM AUTHOR]

This is a companion paper based on our previous work on rare event simulation methods. In this paper, we provide an alternative proof for the ergodicity of shaking transformation in the Gaussian case and propose two variants of the existing methods with comparisons of numerical performance. In numerical tests, we also illustrate the idea of extreme scenario generation based on the convergence of marginal distributions of the underlying Markov chains and show the impact of the discretization of continuous time models on rare event probability estimation. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to extend the hybrid atomistic-continuum multiscale method developed by Vu et al. (2016) to study the gas flow problems in long microchannels involving density variations.Design/methodology/approach The simulation domain is decomposed into three regions: the bulk where the continuous Navier–Stokes and energy equations are solved, the neighbourhood of the wall simulated by molecular dynamics and the overlap region which connects the macroscopic variables (density, velocity and temperature) between the two former regions. For the simulation of long micro/nanochannels, a strategy with multiple molecular blocks all along the fluid/solid interface is adopted to capture accurately the macroscopic velocity and temperature variations.Findings The validity of the hybrid method is shown by comparisons with a simplified analytical model in the molecular region. Applications to compressible and condensation problems are also presented, and the results are discussed.Originality/value The hybrid method proposed in this paper allows cost-effective computer simulations of large-scale problems with an accurate modelling of the transfers at small scales (velocity slip, temperature jump, thin condensation films, etc.). [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to assess the Boussinesq approach for a wide range of Ra (10 × 6 to 10 × 11) in two-dimensional (square cavity) and three-dimensional (cubic cavity) problems for air- and liquid-filled domains.Design/methodology/approach The thermal behavior in “differentially heated cavities” filled with air (low and medium Rayleigh) and water (high Rayleigh) is solved using computational fluid dynamics (CFDs) (OpenFOAM) with a non-compressible (Boussinesq) and compressible approach (real water properties from the IAPWS database).Findings The results from the wide range of Rayleigh numbers allowed for the establishment of the limitation of the Boussinesq approach in problems where the fluid has significant density changes within the operation temperature range and especially when the dependence of density with temperature is not linear. For these cases, the symmetry behavior predicted by Boussinesq is far from the compressible results, thus inducing a transient heat imbalance and leading to a higher mean temperature.Research limitations/implications The main limitation of the present research can be found in the shortage of experimental data for very high Rayleigh problems.Practical implications Practical implications of the current research could be use of the Boussinesq approach by carefully observing its limitations, especially for sensible problems such as the study of pressure vessels, nuclear reactors, etc.Originality/value The originality of this paper lies in addressing the limitations of the Boussinesq approach for high Rayleigh water systems. This fluid is commonly used in numerous industrial equipment. This work presents valuable conclusions about the limitations of the currently used models to carry out industrial simulations. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine numerically the three natural convection of air induced by temperature difference between a cold outer cubic enclosure and a hot inner cylinder. Simulations have been carried out for Rayleigh numbers ranging from 103 to 107 and titled angle of the enclosure from 0° to 90°. The developed mathematical model is governed by the coupled equations of continuity, momentum and energy, and is solved by finite volume method. The effects of cylinder inclination and Rayleigh number on fluid flow and heat transfer are presented. The distribution of isocontours of temperature and isosurfaces of velocity eventually reaches a steady state in the range of Rayleigh numbers between 103 and 107 for titled inclination of 90°; however, for the remaining inclinations, Rayleigh number must be in the range 103-106 to avoid unsteady state, which is manifested by the division of the area containing the maximum local heat transfer rate into three parts for a Rayleigh number equal to 107 and an inclination of 90°. We mention that instability study is not included in the present paper, which is solely devoted to three-dimensional calculations. Results also indicate that optimal average heat transfer rate is obtained for both high Rayleigh number of 106 and high inclination of 90° for the two cases of the inner cylinder and cubical enclosure.Design/methodology/approach The manuscript deals with prediction of the three-dimensional natural convection phenomena in a cubical cavity induced by an isothermal cylinder at the center with different inclinations by simulating the flow using highly numerical methods such as finite volume method.Findings It is found that the local Nusselt number through active walls for titled inclination set at 90°, the symmetry of the flow is conserved and the area containing the maximum heat transfer is divided into three smaller areas situated near the upper portion of the wall, taking the maximum value. That may be due to the preparation of local occurrence of instabilities and bifurcation phenomena that appear for Ra > 107, which is not included in the present paper to save journal space. It was found also that an optimal heat transfer appears when the cylinder orientation becomes vertical (a = 90°). For this inclination, buoyancy forces act upward, corresponding to an aiding situation. In addition, heat transfer rate is increasing with Rayleigh numbers, so correlations of average Nusselt through the cubical cavity and the cylinder are established as function of two parameters (Ra, a). Comparisons of the numerical results with those obtained from all correlations show good agreements.Originality/value To the author’s knowledge, studies have thus far adressed three-dimensional cuboids enclosures induced by an inner shape which the location is changed. However, no study has examined three-dimensional natural convection between the inner isothermal cylinder and outer cooled cubical enclosure when the outer enclosure is tilted. [ABSTRACT FROM AUTHOR]

The paper deals with two crucial steps in multi-criteria decision analysis, that are consistency of the judgments and priority vectors for alternatives/criteria. From a side, several consistency indices are proposed for measuring the consistency of a Pairwise Comparison Matrix. From another one, conditions weaker than consistency, such as transitivity and weak consistency, are proposed for representing further levels of coherence of a Decision Maker when he/she expresses his/her preferences by means of reciprocal Pairwise Comparison Matrix. Firstly, in this paper, a simulation is performed in order to establish a relation between random consistency index and coherence level. Then, since weak consistency ensures reliability to priority vectors proposed in literature, a second simulation is performed in order to measure, in case of no weak consistency, the reliability of these priority vectors. [ABSTRACT FROM AUTHOR]

This paper reports on the adaptation of a Lattice Boltzmann based free surface flow solver to the simulation of complex fluid-ship-ice interactions in marine engineering. The analysis is restricted to the interaction of already broken ice floes and the ship hull, aiming at the optimization of a ship hull’s capability to clear the ice and keep it away from the propulsion device. The ice floes and the ship hull are treated as rigid bodies. In order to model the dynamics of the colliding rigid multi-body systems, a coupling of the flow solver to the Open Dynamics Engine (ODE) is established. The basic methodology and initial validation of the fluid-structure coupling is presented. Then, basic validations of the employed collision and friction models are given, particularly focusing on interacting surface triangle meshes that later serve to describe the ice floes. Finally, a three-dimensional validation case shows that the ship-fluid-rigid-ice interaction forces agree well with available reference data. Apart from the numerical coupling, performance has to be addressed. The employed flow solver elbe uses graphics processing units (GPUs) to accelerate the numerical calculations. In order to make the GPU performance accessible to colliding multi-body systems, a careful and tailor-made implementation is presented in the paper. The resulting optimized elbe -ODE solver allows for the investigation of three-dimensional fluid-ship-ice interactions in a very competitive computational time, on off-the-shelf desktop hardware. [ABSTRACT FROM AUTHOR]

This paper studies collective formations of multi-agent systems, modeled with unicycle dynamics, while admitting heterogeneity in both controller gains and speeds of the agents along with saturation on the controller outputs. This addresses a practical scenario where the speeds are usually nonidentical and the controller gains may vary due to imperfect implementation. The paper analyzes the effect of both heterogeneous controller gains and speeds simultaneously on the collective formations obtained by optimizing the average linear momentum of the group of agents. A detailed analysis of the two-agent system is given in the paper and some results on the locus of the collective centroid with varying controller gains are obtained. Effect of saturation is also studied for two cases when the controller gains are bounded and when the control efforts are bounded. Simulation examples are given to illustrate the theoretical findings. [ABSTRACT FROM AUTHOR]

In previous papers, it has been empirically proved that descriptive (summary measures) and inferential conclusions (in particular, tests about means p -values) with imprecise-valued data are often affected by the scale considered to model such data. More concretely, conclusions from the numerical and fuzzy linguistic encodings of Likert-type data have been compared with those for fuzzy data obtained by using a totally free fuzzy assessment: the so-called fuzzy rating scale. These previous comparisons have been performed separately for each of the scales. This paper aims to perform a joint comparison in such a way that means of linked data (one associated with the fuzzy rating and the other one with the encoded Likert scale) are to be tested for equality. Two real-life examples, as well as several simulation-based synthetic ones, have unequivocally shown that the fuzzy rating scale means are significantly different from those for the encoded Likert scales. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine the convergence, offered accuracy and efficiency of the bisectional adaptive frequency sampling (AFS) scheme combined with the Stöer-Bulirsch (SB) algorithm as a tool for supporting frequency-domain method-of-moments (MoM) in broadband electromagnetic (EM) simulations.Design/methodology/approach The AFS and SB procedures have been interfaced with the MoM code, and then, an extensive parametric study has been carried out to explore the performance of the numerical solution for the test problems of reconstructing frequency responses of the wire radiator and scatterer, respectively, over at least a decade bandwidth.Findings The results give evidence for the efficiency of the overall approach and its capability of constructing the approximation of multi-resonant responses with sharp resonant peaks from a substantially reduced number of EM samples (data points) compared to that of conventional uniform sampling.Originality/value Results of the study offer thorough insight into the performance of the AFS-SB technique, and the data given in this paper may be helpful in selecting the convergence criterion and the tolerance for the AFS-SB algorithm to achieve a possibly economical broadband simulation technique. [ABSTRACT FROM AUTHOR]