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This paper is concerned with the development and application of optimally efficient numerical methods for the simulation of vascular tumour growth. This model used involves the flow and interaction of four different, but coupled, phases which are each treated as incompressible fluids, Hubbard and Byrne (2013). A finite volume scheme is used to approximate mass conservation, with conforming finite element schemes to approximate momentum conservation and an associated equation. The principal contribution of this paper is the development of a novel block preconditioner for solving the linear systems arising from the discrete momentum equations at each time step. In particular, the preconditioned system has both a solution time and a memory requirement that is shown to scale almost linearly with the problem size. [ABSTRACT FROM AUTHOR]

This paper presents a distributed swarm system for small fixed-wing unmanned aerial vehicles (UAVs). In particular, to perform various missions with multiple UAVs that are densely gathered and collision free, a hybrid-flocking control algorithm is synthesized by using three types of control protocols: vector field guidance (for path following/loitering), augmented Cucker–Smale (ACS) model (for collective flocking behavior), and potential field (for collision avoidance). In particular, to address the issue of conflicts between different control protocols, the adaptive ACS model is proposed and the optimization problem is formulated to determine the suitable mixing weights of control protocols. We also design the transition of multiple operation modes and communication architecture for the swarm system. The system is evaluated using the proposed hybrid-flocking control algorithm by proof-of-concept real flight experiments using 18 small fixed-wing UAVs as well as extensive numerical simulations. Flight experiments are successfully performed for multiple consecutive tasks including the individual task, circular path loitering and elliptical path loitering while avoiding collisions among UAVs. • The distributed small fixed-wing UAV swarm system is designed. • The hybrid-flocking control algorithm is proposed by combining three control protocols. • The optimal mixing weight improves the mission performance. • Numerical simulations and flight experiments validate the hybrid-flocking algorithm. [ABSTRACT FROM AUTHOR]

The envisaged usage of multiple Unmanned Aerial Vehicles (UAVs) to perform cooperative tasks is a promising concept for future autonomous military systems. An important aspect to make this usage a reality is the solution of the task allocation problem in these cooperative systems. This paper addresses the problem of tasks allocation among agents representing UAVs, considering that the tasks are created by a central entity, in which the decision of which task will be performed by each agent is not decided by this central entity, but by the agents themselves. The assumption that tasks are created by a central entity is a reasonable one, given the way strategic planning is carried up in military operations. To enable the UAVs to have the ability to decide which tasks to perform, concepts from swarm intelligence and multi-agent system approach are used. Heuristic methods are commonly used to solve this problem, but they present drawbacks. For example, many tasks end up not begin performed even if the UAVs have enough resources to execute them. To cope with this problem, this paper proposes three algorithm variants that complement each other to form a new method aiming to increase the amount of performed tasks, so that a better task allocation is achieved. Through experiments in a simulated environment, the proposed method was evaluated, yielding enhanced results for the addressed problem compared to existing methods reported in the literature. [ABSTRACT FROM AUTHOR]

• Improved iterative method based on Gerchberg-Saxton (GS) algorithm. • Red, green, and blue channels of images is recorded in three holograms. • Constraint that consists of modified amplitudes with a weighting factor. • Reconstruction for three layer images. Depth-division multiplexing (DDM) is distinguished for generating full-color holograms. However, this method is confronted with such issues as poor quality and severe crosstalk when reconstructing multiplane color images. In this paper, we propose an improved iterative method based on Gerchberg-Saxton (GS) algorithm to generate multiplane full-color phase-only holograms (POHs), and the information of red (R), green (G), and blue (B) channels of images is recorded in three POHs, respectively. In the iterative process, we introduce an improved hologram plane constraint that consists of modified amplitudes given a static weighting factor, and display the reconstruction results for three-layer images, which ultimately improve the quality of the reconstructed images and effectively avoid the crosstalk among different color channels. And compared with GS algorithm, our method can effectively balance the reconstruction quality of three-color channels of each image. The feasibility of the method is verified by numerical simulations and optical experiments. [ABSTRACT FROM AUTHOR]

This paper reviews and advances a data science framework for capturing and communicating critical information regarding the evolution of material structure in spatiotemporal multiscale simulations. This approach is called the MKS (Materials Knowledge Systems) framework, and was previously applied successfully for capturing mainly the microstructure-property linkages in spatial multiscale simulations. This paper generalizes this framework by allowing the introduction of different basis functions, and explores their potential benefits in establishing the desired process-structure-property (PSP) linkages. These new developments are demonstrated using a Cahn-Hilliard simulation as an example case study, where structure evolution was predicted three orders of magnitude faster than an optimized numerical integration algorithm. This study suggests that the MKS localization framework provides an alternate method to learn the underlying embedded physics in a numerical model expressed through Green’s function based influence kernels rather than differential equations, and potentially offers significant computational advantages in problems where numerical integration schemes are challenging to optimize. With this extension, we have now established a comprehensive framework for capturing PSP linkages for multiscale materials modeling and simulations in both space and time. [ABSTRACT FROM AUTHOR]

This paper proposes a new pretension simulation algorithm and examines the pretension feasibility for a new type of cable dome: a negative Gaussian curvature cable dome. First, the paper gives a pretension simulation algorithm based on the fuzzy relationship between the prestress and internal force. Second, a negative Gaussian curvature cable dome is proposed and the corresponding experimental model is designed and pretensioned according to the simulation results from the proposed simulation algorithm. The results indicate that the pretension simulation algorithm is efficient and accurate for simulating the pretension process and guiding the practical pretension. And the results also confirm that the negative Gaussian curvature cable dome can be pretensioned successfully, thus it can be constructed as a new type of cable dome. [ABSTRACT FROM AUTHOR]

Harvesting daylight for improving building energy performance has become an important issue in recent years. Most energy simulation tools use a Daylight Factor (DF) based algorithm to capture the complexity of daylight behaviors. However, DF has a limitation for fully accounting realistic daylight conditions, and several modifications or integrations with other supporting tools were developed to compensate for this limitation. This paper uses the Kriging method to predict daylight conditions for a whole year, and couples this method with energy simulation tools. Kriging is a group of geo-statistical techniques used to interpolate the value of a random field at an unobserved location from discrete observed values at nearby locations. In previous research, the Kriging method showed promising outcomes; that result was significantly better than current daylight modeling in energy simulation tool, and very close to the results from advanced physics-based daylight simulation tool. However, Kriging also comes with certain limitations that require further investigation. One major hurdle was Kriging’s long computational time compared to current daylight models in energy simulation tools. For this reason, this paper aims to find possibilities to reduce computational time to realistic levels that can be applicable in practice. Furthermore, it proposes a method to integrate Kriging-based daylight model with an energy simulation tool that can plot hourly indoor light distribution. This proposal obtains more realistic results than current energy simulation daylight models, while reducing computational expense. [ABSTRACT FROM AUTHOR]

In this paper, we consider numerical approximations for solving the anisotropic Cahn–Hilliard model. We combine the Scalar Auxiliary Variable (SAV) approach with the stabilization technique to arrive at a novel Stabilized-SAV approach, where three linear stabilization terms, which are shown to be crucial to remove the oscillations caused by the anisotropic coefficient, are added to enhance the stability while keeping the required accuracy. The schemes are very easy-to-implement and fast in the sense that all nonlinear terms are treated in a semi-explicit way, and one only needs to solve three decoupled linear equations with constant coefficients at each time step. We further prove the unconditional energy stabilities rigorously and present numerous 2D and 3D numerical simulations to demonstrate the stability and accuracy. • We propose a novel Stabilized-SAV approach for solving the anisotropic Cahn–Hilliard model. • The scheme is linear, second-order accurate, provably unconditionally energy stable, and non-iterative. • Three crucial linear stabilization terms are added to remove oscillations caused by anisotropy. • One only need to solve three decoupled linear equations at each time step. • We further prove the unconditional energy stabilities rigorously and present numerous simulations. [ABSTRACT FROM AUTHOR]

Highlights • Simulation of microwave rotating heating is realized by ALE method. • The simulation results compared with conventional methods is more accurate and efficient. • This method can be used for microwave heating simulation of other food movements. Abstract In a particular condition, moving elements are typically used to improve heating uniformity during microwave heating. However, due to the complexity of mathematical models, the simulation of moving elements during microwave heating process remains a challenge. In this paper, a novel continuous algorithm based on Arbitrary Lagrangian-Eulerian method is developed to compute this heating process. By introducing the ALE method, the mesh of moving domain are set as a function of space coordinate and time, the mesh of surrounding domain is free deformation under the action of the moving domain, ensuring the accuracy and continuity of calculation by remesh the deformed configuration. A 2-D model and a 3-D model with a rotating turntable are used to illustrate the proposed method in detail. The change of temperature was measured by experiments to verify the rationality and accuracy of the proposed method. This method can be used in microwave heating simulation of other food movements and assist microwaveable food product development. [ABSTRACT FROM AUTHOR]

Abstract Model predictive control strategies have been applied successfully when controlling solar plants. If the control algorithm uses a linear model associated only to an operating point, when the plant is working far from the design conditions, the performance of the controller may deteriorate. In this paper, a gain scheduling model predictive control strategy is designed for the Fresnel collector field located at the Escuela Superior de Ingenieros de Sevilla. Simulation results are provided comparing the proposed strategy with another linear MPC controller showing a better performance. Furthermore, two real tests are presented showing the effectiveness of the proposed strategy. Highlights • Advances control techniques play an important role in operating solar plants. • Simple linear control strategies do not perform well in the entire operation range. • Thus, adaptative or nonlinear control strategies are needed. • A gain scheduling GPC is developed. • Simulations and real tests show the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Abstract In this paper, the windup problem in active vibration control (AVC) is studied systematically. Instead of evaluating the performance of several anti-windup compensators implemented on independent abstract simulation problems, a unified benchmark setup in active-damping control (ADC) is used. The investigated anti-windup schemes (analysis and synthesis) are adapted to the disturbance rejection control. Large attention is given to capture the similarities and differences of the methods in dealing with the windup event in a practical context. Therefore, instead of categorizing the methods into static and non-static methods or model recovery and direct linear anti-windup schemes, a logical route is followed to highlight the significance of each method. The mathematical interpretations of the methods are provided for the vibration engineer while delivering forthright implementation algorithms for AVC. The tackled methods are unified on a state space model obtained from the frequency-domain subspace system identification approach. Practical issues that may raise for each technique are mentioned, and detained guidelines are provided for tuning each algorithm. Finally, in order to compare the compensated system's performance, comprehensive time-domain studies are carried out by separating the transient response of the compensated systems to three modes: linear mode, where the actuation nonlinearity is inactive; the nonlinear mode, where the windup event is in progress, and finally, the output mismatch rejection mode, where the windup incident is over, but performance degradation is still present. Highlights • A unified framework for anti-windup compensator design is provided. • The analysis and synthesis process are adapted for active vibration control problem. • Detailed experimental investigations are carried out for extraction of the true goal of anti-windup compensators. [ABSTRACT FROM AUTHOR]

Abstract In the scope of linear anisotropic elasticity, the fourth-order elasticity tensor or tetrad has to be identified. This can be done either by measurements or by numerical simulations. An important task is then to identify a given tetrad, probably with some experimental or numerical scattering, with one of the symmetry classes. For this purpose one needs a distance function between a given tetrad and the class of all tetrads with a particular symmetry, which is zero if the tetrad obeys this symmetry, or non-zero otherwise. In this paper we present a fast method to solve these problems. We firstly introduce the 8th order projectors that map any stiffness tetrad into the part that is invariant under the action of a specific fixed symmetry group. For this purpose we consider the seven out of the eight symmetry classes that are distinguishable in linear elasticity. Secondly, since the symmetry axes of the specific stiffness tensor under consideration is generally not aligned with the used tensorial basis of the projector, we need to rotate the sample stiffness. The optimal orientation is obtained when the distance between the rotated stiffness and the rotated and projected stiffness is minimal. Thus, we need to apply only linear mappings and minimize over three Euler angles. The latter is quite simple, as the domain of the Euler angles is periodic, and the number of local minima is limited. This procedure has the advantage that it is applicable in an algorithmic manner, and does not require an a priori identification of symmetry planes, symmetry axes or component symmetries, which are only apparent under special choices for the tensorial basis. [ABSTRACT FROM AUTHOR]

Highlights • A model based on the minimization of Gibbs free energy has been developed. • The algorithm implemented in a free open source platform is presented. • The model allows the evaluation of pollutants besides energy related species. Abstract This paper presents a non-stoichiometric equilibrium model for the simulation of the biomass gasification process in downdraft gasifiers to be used within simulation models of complex energy systems. The chemical equilibrium is determined by minimizing the Gibbs free energy. The feedstock is composed of five elements, while fifteen chemical species are considered for the syngas. The model calculates the relative quantities of gasification products and the lower heating value of the syngas. An advantage of the non-stoichiometric approach is that it can easily calculate not only the concentrations of the main gasification products, but also the concentrations of minor products, especially the pollutant chemical species containing nitrogen and sulfur. To analyse the behaviour of the model, a sensitivity analysis of its process parameters is presented. The model is then validated by comparing its results with the results of the simulation carried out with equilibrium models and with experimental data found in literature. Finally, the model is applied to the study of the gasification of forest waste. [ABSTRACT FROM AUTHOR]

Plant-wide oscillation detection is an important task in the maintenance of large-scale industrial control systems, owing to the fact that in an interactive multi-loop environment oscillation generated in one loop may propagate to the different parts of the plant. In such a scenario, it is required that different loops oscillating due to a common cause and hence similar frequency may be grouped together. In this paper an adaptive method for plant-wide oscillation detection based on multivariate empirical mode decomposition (MEMD) along with a grouping algorithm is proposed. The method can identify multiple oscillation groups among different variables as well as variables with random noise only. The proposed method is also applicable to both non-linear and non-stationary time series where the techniques based on the conventional Fourier analysis are prone to errors. Within each group that oscillate due to a common cause, the method can also indicate the location of the probable root cause of oscillations. The efficacy of the proposed method is established with the help of both simulation and industrial case studies. [ABSTRACT FROM AUTHOR]

Artificial gas-lift (AGL) technique is commonly used to enhance oil production when the reservoir pressure in wells is not enough to sustain acceptable oil flow rate. However, the gas-lift wells are prone to instability, characterized by regular oscillations of pressure and flow. This phenomenon is known as casing-heading instability. It results in production loss and negative impact on downstream equipment, and has been a challenging problem to both industry and academia. In this paper, a novel concept of optimal tracking control is proposed for stabilization and operating mode transition in gas-lift wells when casing-heading phenomenon occurs. The stability of artificial gas-lift process is ensured by manipulating both gas lift choke and oil production choke, where the openings of both choke valves can vary from fully closed to fully open. Through the simulation of the open-loop system, a stability map of AGL process is produced. Then a trajectory optimization algorithm is developed based on this stability map, which is synthesized with a tracking controller to achieve trajectory optimization control. Also, a nonlinear state observer is designed to ensure estimation of unmeasurable variables. Through simulation studies, the effectiveness of proposed trajectory optimization control is demonstrated. [ABSTRACT FROM AUTHOR]

In this paper we investigate dynamic causalities in membrane systems by proposing the concept of “predictor”, originally defined in the context of the reaction systems by Brijder, Ehrenfeucht and Rozenberg. The goal is to characterise sufficient and necessary conditions for the presence of a multiset of molecules of interest in the configuration of a P system at a given evolution step (independently from the non-deterministic choices taken). These conditions can be used to study causal relationships between molecules and, therefore, to predict some aspects of future development of multiset rewriting systems. To achieve this goal, we introduce the new concept of “multiset pattern” representing a logical formula on multisets. A sufficient predictor can be expressed as a pattern characterising initial multisets that will surely evolve , after the given number of evolution steps, into a multiset containing the molecules of interest. On the other hand, a necessary predictor models initial multisets that may evolve after the given number of evolution steps, into a multiset containing the molecules of interest. Necessary predictors can be used to characterise initial multisets that will surely not evolve (in the required number of steps) into a multiset that contains such molecules. We inductively define operators able to compute these predictors. The patterns obtained from our operators are sound (sufficient or necessary) predictors, but, in general, they are not complete. [ABSTRACT FROM AUTHOR]

This paper presents an aerodynamic model-based robust adaptive control algorithm for close formation flight. The leader aircraft is assumed to be at level and straight flight which characterizes the most common scenario for close formation flight. The formation aerodynamic effects are assumed to be unknown, but an online formation aerodynamic model is available to predict those effects. In light of the online formation aerodynamic model, a robust adaptive control algorithm is thereafter developed on the follower aircraft to counteract the unknown formation aerodynamic effects and obtain highly accurate formation tracking performance. The proposed control algorithm is composed of a baseline controller and an integrator-augmented robust adaptive controller, which can efficiently deal with both matched and mismatched formation aerodynamic effects and external disturbances. The major advantage of the proposed design is that it can achieve at least ultimate bounded tracking control with certain transient performance guaranty. The efficiency and robustness of the proposed control design are eventually validated via numerical simulations of close formation flight at two different scenarios. [ABSTRACT FROM AUTHOR]

Static input-oriented sampling approaches are often used for generating model-based scenarios. However, for models of deeply uncertain and dynamically complex issues, there is no guarantee that such approaches reveal the total behavioral spectrum that could be generated by simulating them. In this paper, we present an adaptive output-oriented sampling approach for exploring the full behavioral spectrum that could be generated by computational models in view of generating interesting, even previously undiscovered, scenarios. In this paper, we use a resource scarcity model to illustrate the approach, show the difference between static sampling and adaptive sampling, and demonstrate the usefulness for scenario discovery of the latter combined with other methods. We show that this approach can be used for revealing the behavioral spectrum of models, identifying regions of the input space that generate particular behaviors, and selecting (sets of) scenarios that are representative in terms of output and input spaces. [ABSTRACT FROM AUTHOR]

Natural or man-made disasters can cause different kinds of moving obstacles (e.g., fires, plumes, floods), which make some parts of the road network temporarily unavailable. After such incidents occur, responders have to go to different destinations to perform their tasks in the environment affected by the disaster. Therefore they need a path planner that is capable of dealing with such moving obstacles, as well as generating and coordinating their routes quickly and efficiently. In this paper, we present a novel approach for using a multi-agent system for navigating one or multiple responders to one or multiple destinations in the presence of moving obstacles. Our navigation system supports information collection from hazard simulations, spatio-temporal data processing and analysis, connection with a geo-database, and route generation in dynamic environments affected by disasters. We design and develop a set of software geospatial agents that assist emergency actors in dealing with the spatio-temporal data required for emergency navigation, based on their roles in the disaster response. One of the key components of the system is the path planning module, which combines the modified A* algorithm, insertion heuristics, and auction algorithm to calculate obstacle-avoiding routes for multiple responders with multiple destinations. A spatial data model is designed to support the storage of information about the tasks and routes produced during the disaster response. Our system has been validated using four navigation cases. Some preliminary results are presented in this paper and show the potential of the system for solving more navigation cases. [ABSTRACT FROM AUTHOR]

Urban land used for parking lots can contribute to the effect of overheating, whereas vegetation, especially high growth vegetation (trees), can mitigate this effect. Accordingly, in this paper we propose an algorithm, the inputs to which consist of predetermined parameters of a parking lot's geometry, trees and surrounding buildings, where the shadows help to mitigate the heat. The algorithm optimizes tree locations, aiming to provide maximum overshadowing of the parking lots, while leaving the useable parking area and the parking lot shape intact. The paper focuses on parameterization of elements that are important for this analysis process as well as combinatory calculations. These combinatory calculations are based on solar simulations, which are carried out, and take into account climate and geographical data. The algorithm is applied to several cases, depicting real world examples, as well as those based on design and greening instruction manuals. The results indicate that the tree locations estimated by the algorithm increase parking lot overshadowing, indicating that the algorithm efficiently decreases the negative influence of urban overheating. [ABSTRACT FROM AUTHOR]

This paper proposes a technique for optimizing the power generated from stationary stochastic vibratory disturbances, using a resonant energy harvester. Although the theory is general, the target application of the paper concerns ocean wave energy harvesting. The control technique involves the use of a causal discrete-time feedback algorithm to dynamically optimize the power extracted from the waves. The theory assumes that the input impedance of the harvester is known precisely, but that a priori models are unavailable for the characterization of the stochastic behavior of the incident waves as well as the transfer functions characterizing their hydrodynamic excitation of the system. For these assumptions, we develop an adaptive control technique, which adapts the feedback law at each time step based on updated estimates for the stochastic disturbance model, obtained through a subspace-based system identification algorithm. The technique is demonstrated on a simulation example pertaining to a cylindrical surface-floating wave energy converter in heave. [ABSTRACT FROM AUTHOR]

This paper presents a whole body control framework for the control of a dual arm underwater vehicle manipulator system developed in the context of the MARIS Italian research project, which deals with the control and coordination of underwater vehicles for manipulation and transportation problems. The proposed framework is the extension of the one used in the successful TRIDENT FP7 project that has been improved to be able to deal with multidimensional inequality control objectives. After the presentation of the mathematical background, the paper presents some simulation results showing the good performances of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of artificial intelligence. However, choosing a suitable machine learning algorithm for a recommender system is difficult because of the number of algorithms described in the literature. Researchers and practitioners developing recommender systems are left with little information about the current approaches in algorithm usage. Moreover, the development of recommender systems using machine learning algorithms often faces problems and raises questions that must be resolved. This paper presents a systematic review of the literature that analyzes the use of machine learning algorithms in recommender systems and identifies new research opportunities. The goals of this study are to (i) identify trends in the use or research of machine learning algorithms in recommender systems; (ii) identify open questions in the use or research of machine learning algorithms; and (iii) assist new researchers to position new research activity in this domain appropriately. The results of this study identify existing classes of recommender systems, characterize adopted machine learning approaches, discuss the use of big data technologies, identify types of machine learning algorithms and their application domains, and analyzes both main and alternative performance metrics. [ABSTRACT FROM AUTHOR]

With the increasing consumption of energy in data centers, the demand for energy efficient multiprocessor job scheduling is growing dramatically. Besides flow time, energy conservation has become a significant issue and drawn enormous interest. In this paper, an online non-clairvoyant scheduling algorithm Significance-based Multiprocessor Round Robin (SbMRR) is proposed. SbMRR utilizes the unbounded speed model, where the range of the speed of any processor is from zero to infinity. To validate the effectiveness of the algorithm, mathematical and simulation-based analysis are conducted which demonstrates that SbMRR provides the minimum sum of significance-based flow time and energy consumed. SbMRR is O(α)-competitive, more precisely ((α + 1)⁄((1–1⁄αβ)))-competitive, where β ≥ 4 a constant. The competitive ratio of SbMRR is least to date. SbMRR provides the minimum sum of energy consumed and significance-based flow-time. [ABSTRACT FROM AUTHOR]

This paper presents a method to identify regions that make up features like holes, slots, pockets as well as interacting features in a three-dimensional mesh of a computer-aided design (CAD)/Engineering model. Feature recognition is an important area in the field of CAD/Engineering with applications in model retrieval, creating an analysis model by defeaturing of the designed model for finite element applications, etc. Most feature recognition methods use either a cluster-based decomposition or feature line extraction through solid angles or curvature values, followed by graph-based heuristics. Such approaches require a user parameter for clustering or a threshold value for angle/curvature, neither of which is an easily deterministic one. The proposed algorithm identifies the features using contours generated by random cutting planes, followed by graph traversals (and not using heuristics) and without using parameter/threshold values. The algorithm can identify blind holes, through holes, slots and pockets. The geometry of most of the extracted features has also been identified using Gauss map. Interacting features have also been extracted and separated, which normally pose difficulty for most algorithms. Extensive experiments on CAD models from various benchmarks show that the algorithm is robust. Comparison with different algorithms (of which code was available) shows that our approach performs admirably and in the case of interacting features, the algorithm performs better than the existing ones. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm for performing explicit integration of constitutive models for unsaturated soils in problems where consideration of stress rate objectivity becomes necessary due to large deformations. As many constitutive models for unsaturated soils incorporate suction forces, as well as stresses and strains, into the material description, an accurate integration procedure is more complicated than similar schemes proposed for saturated soils. The difficulties of integration are also coupled with the need to incorporate objectivity (frame independency) within the integration procedure. Application of the proposed method is limited to constitutive models that assume additive decomposition of the strains. A fully coupled finite deformation numerical model is considered with displacement, pore water pressure and suction as the nodal variables. Details of the implementation of the stress integration algorithm at each stage of an analysis are given. The algorithm is then applied to solve some large-scale geotechnical problems. Numerical examples are also provided to assess the performance of the algorithm under different loading conditions. [ABSTRACT FROM AUTHOR]

This paper presents techniques for constructing numerical solutions for some of the problems formulated in Part I. An algorithm to search for periodic solutions is developed and implemented in software. It is shown that there exist a finite number of discrete well defined periodic solutions for the lateral buckling problem of a straight pipeline under constant pressure and temperature. It is also shown that periodic solutions are unstable. A second numerical algorithm is developed for solving lateral buckling problem for an initially straight semi-infinite pipeline terminating at a sliding manifold under constant or varying temperature profiles. The resulting boundary value problem requires special numerical methods due to the stiffness of the governing differential equations. Algorithm is applied to find the solutions of problems for three different size pipelines; an 8.625 inch, a 16 inch, and a 32 inch diameter. Multiple stable chaotic solutions corresponding to distinct but extremely close initial conditions are revealed. The characteristics of these solutions match with the characteristics of the periodic solutions. This suggests that unstable periodic solutions act as separatrix between narrow zones containing stable chaotic solutions. It is seen that chaotic solutions can relieve a significant portion of the thermal and pressure loads without inducing excessive pipeline displacements. The results show that the pipeline end expansion is significantly less than the value given by common engineering methods. It is also shown that pipeline operating conditions and soil-pipe interaction parameters influence the stability and bifurcations of solutions. [ABSTRACT FROM AUTHOR]

Smoothed particle hydrodynamics (SPH) is a meshfree, Lagrangian particle method which has advantages in handling solids with extremely large deformation. Like any other numerical methods, cares must be taken to ensure its desirable accuracy and stability through considering several correction techniques in calculation. The selection of values for parameters in those correction approaches is a key step in SPH simulation, which is always difficult for new beginners to deal well with effectively. This paper examines the common inconsistency and instability problems in SPH method and studies its computational efficiency when applied to hydrodynamics problems with material strength like soil column collapse. We analyzed in detail how the correction techniques mitigate these inconsistency and instability problems. Also, the numerical testing results associate with different values for the parameters used in the correction techniques are provided for better understanding the influence of these parameters and for finding out the desirable values. It is found that (1) the SPH method is easily subjected to an inconsistency problem in the boundary area due to the boundary deficiency, and it can be treated well by adopting “virtual particles” contributing to the particle summations. (2) The numerical oscillation in SPH simulation can be mitigated effectively by artificial viscosity with the suggested parameter values. (3) The tension cracking treatment, artificial viscosity and artificial stress work well in removing the tensile instability problem in SPH method. In addition, the nearest neighboring particle searching (NNPS) algorithm, spacing ratio, smoothing length and time step influence the efficiency and accuracy of SPH method significantly. It is shown that SPH method with suggested parameters values can produce a very good result compared with the experimental result. [ABSTRACT FROM AUTHOR]

The pipe network flow model can simulate the seepage process with DEM conveniently because of its simple algorithm. However, whether it can recover the correct seepage process has not been verified. In this paper, the equation to update the fluid pressure is rebuilt according to the flow conservation. Through the steady seepage simulation, this algorithm is verified to be able to recover Darcy’s law, and the equation to calibrate the aperture according to macro permeability is derived. Furthermore, the modified algorithm is used to simulate the unsteady seepage process, and the results show good agreement with the analytical solutions. [ABSTRACT FROM AUTHOR]

The Particle Finite Element Method (PFEM) is evaluated in the context of the numerical simulation of bird strike events. To assess the possibilities of the method, theoretical analyses are initially performed based on the impact of a water jet on a rigid surface. Then, the influence of the geometry of a more realistic projectile is analyzed and the capability of the method to take into account separation and fragmentation is highlighted. Finally, the method is tested for impacts against deformable targets, using a partitioned algorithm with dynamic relaxation for the fluid-structure interaction, combining the PFEM for the description of the bird with a non-linear Finite Element approach for the description of the impacted structure, which can undergo large plastic deformations. To assess the quality of the obtained results a series of numerical examples from the literature has been selected and used as a reference throughout the paper. Among the studies presented in this work also a novel numerical benchmark for the evaluation of bird impact simulations is proposed. [ABSTRACT FROM AUTHOR]

Objective: Dynamic ambulance redeployment policies tend to introduce much more flexibilities in improving ambulance resource allocation by capitalizing on the definite geospatial-temporal variations in ambulance demand patterns over the time-of-the-day and day-of-the-week effects. A novel modelling framework based on the Approximate Dynamic Programming (ADP) approach leveraging on a Discrete Events Simulation (DES) model for dynamic ambulance redeployment in Singapore is proposed in this paper.Methods: The study was based on the Singapore's national Emergency Medical Services (EMS) system. Based on a dataset comprising 216,973 valid incidents over a continuous two-years study period from 1 January 2011-31 December 2012, a DES model for the EMS system was developed. An ADP model based on linear value function approximations was then evaluated using the DES model via the temporal difference (TD) learning family of algorithms. The objective of the ADP model is to derive approximate optimal dynamic redeployment policies based on the primary outcome of ambulance coverage.Results: Considering an 8min response time threshold, an estimated 5% reduction in the proportion of calls that cannot be reached within the threshold (equivalent to approximately 8000 dispatches) was observed from the computational experiments. The study also revealed that the redeployment policies which are restricted within the same operational division could potentially result in a more promising response time performance. Furthermore, the best policy involved the combination of redeploying ambulances whenever they are released from service and that of relocating ambulances that are idle in bases.Conclusion: This study demonstrated the successful application of an approximate modelling framework based on ADP that leverages upon a detailed DES model of the Singapore's EMS system to generate approximate optimal dynamic redeployment plans. Various policies and scenarios relevant to the Singapore EMS system were evaluated. [ABSTRACT FROM AUTHOR]

Abstract: In the framework of dependent risks it is a crucial task for risk management purposes to quantify the probability that the aggregated risk exceeds some large value . Motivated by Asmussen et al. (2011) [1] in this paper we introduce a modified Asmussen–Kroese estimator for simulation of the rare event that the aggregated risk exceeds . We show that in the framework of log-Gaussian risks our novel estimator has the best possible performance i.e., it has asymptotically vanishing relative error. For the more general class of log-elliptical risks with marginal distributions in the Gumbel max-domain of attraction we propose a modified Rojas-Nandayapa estimator of the rare events of interest, which for specific importance sampling densities has a good logarithmic performance. Our numerical results presented in this paper demonstrate the excellent performance of our novel Asmussen–Kroese algorithm. [Copyright &y& Elsevier]

Abstract: This paper presents a detailed experimental and numerical investigation for a turbine cascade with different trailing edge ejection. The numerical simulation is based on Three-Dimensional Navier–Stokes equations coupled with an effective ejection model, where a high resolution non-oscillatory scheme, LU-SGS implicit algorithm and Baldwin-Lomax turbulence model are employed. The experiments presented in this paper focused on a transonic turbine cascade performance with different ejection to validate the numerical simulation results. The results show that the blowing ratio has a small effect on the Mach number distribution and exit flow angle with two slot types. However the energy loss coefficient increases initially, and subsequently has a decrease tendency with the increasing of blowing ratio. The ejection from the symmetry slot blows away the vortex at the blade trailing edge and strengthens the mixing between the wake and main flow. The ejection from the pressure side cutback only clears up the vortex near the slot surface, and has small effect on the flow field near the trailing edge. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a social approach for learning agents. In dynamic environments, smart agents should detect changes and adapt themselves, applying dynamic learning strategies and drift detection algorithms. Recent studies note that an ensemble of learners can be coordinated by simple protocols based on votes or weighted votes; however, they are not capable of determining the number of learners or the ensemble composition properly. Conversely, we show in this paper that Social Network Theory can provide the multi-agent learning community with sophisticated and well-founded reputation models that outperform well-known ensemble-based drift detection techniques, generating accurate and small ensembles of learning agents. Our approach is evaluated considering dynamic bilateral negotiation scenarios and benchmark databases, presenting statistically significant results that are better than those of other ensemble-based techniques. [Copyright &y& Elsevier]

Surface exploration is an important way to improve the understanding of small bodies. Considering the irregular and weak gravity field near a small body, the movement of the surface explorer is generally achieved by hopping. In this paper, a guidance algorithm method based on convex optimization approach for pinpoint hopping movement on a small body is developed in order to improve the stability and accuracy of surface exploration. We formulate a fuel-optimal control problem for the single pinpoint hopping and convert it into a second-order cone programming (SOCP) problem which can be solved effectively by primal-dual-interior points method. A multi-hopping scenario is also proposed for the long-distance transfer. To certificate the performance of the proposed guidance algorithm, a full set of simulations are conducted and the effectiveness are analyzed. [ABSTRACT FROM AUTHOR]

In the past decades, simulation frameworks have greatly increased in complexity, due to coupling of models from various disciplines into so-called integrated models. Recently, the combination with tools for uncertainty quantification, inverse modelling, optimization and control started a development towards what we call extended simulation frameworks. While there is an ongoing discussion on quality assurance and reproducibility for simulation frameworks, we have not observed a similar discussion for the extended case. Particularly for extended frameworks, the need for quality assurance is high: The overwhelming range of options and algorithms is unmanageable by a domain expert and opaque to decision makers or the public. The resulting demand for ‘intelligent software’ with automated configuration can lead to a blind trust in simulation results even if they are incorrect. This is a threatening scenario due to potential consequences in simulation-based engineering or political decisions. In this paper, we analyze the increasing complexity of scientific computing workflows, and discuss the corresponding problems of extended scientific simulation frameworks. We propose a paradigm that regulates the allowable properties of framework components, supports the framework configuration for complex simulations, enforces automatic self-tests of configured frameworks, and communicates automated algorithm choices, potentially critical user settings or convergence issues with adaptive detail level and urgency to the end-user. Our goal is to start transferring the quality assurance discussion in the field of integrated modeling and conventional software frameworks to the area of extended simulation frameworks. With this, we hope to increase the reliability and transparency of (extended) frameworks, framework use and of the corresponding simulation results. [ABSTRACT FROM AUTHOR]

In this paper the authors present an algorithm that abstracts an arbitrarily shaped set of building volumes into a group of simplified ‘shoebox’ building energy models. It is shown that for generic perimeter and core floorplans the algorithm provides a faster but comparably accurate simulation results of annual load profiles vis-à-vis multi-zone thermal models generated according to ASHRAE90.1 Appendix G guidelines. Envisioned applications range from rapid thermal model generation for urban building energy modelling to schematic architectural design. Following a description of the algorithm, its ability to produce load profiles for a mixed-use neighborhood of 121 fully conditioned buildings for a variety of climates is demonstrated. The comparison yields relative mean square errors in simulated annual building energy use intensity of five to 10 percent compared to ASHRAE 90.1 compliant building energy models while reducing simulation times by a factor of 296. [ABSTRACT FROM AUTHOR]

A numerical simulation of kinetic friction function in the fracture process of rocks in the framework of General Particle Dynamics (GPD) is performed in this paper. The frictional algorithm is implemented into the General Particle Dynamics code (GPD) to describe frictional behavior of particles, where frictional forces among discrete particles are formulated using the principle of balance of two forces based on ideal plastic contact between two surfaces of solids. In General Particle Dynamics code (GPD), interaction among discrete particles is formulated using the virtual-bond method. Fractures of virtual bonds among particles are determined through the Hoek-Brown damage evolution law of rock materials. Three numerical cases are to verify the stability and accuracy of the numerical algorithm. Then, the numerical results are compared with analytical solutions and experimental results. It is found that the numerical results are in good agreement with the experimental ones. [ABSTRACT FROM AUTHOR]

In this paper, we consider a feasible primal–dual interior point method for linear semidefinite programming problem ( S D P ) based on Alizadeh–Haeberly–Overton ( AHO ) direction (Monteiro, 1997). Firstly, and by a new and simple technique, we establish the existence and uniqueness of optimal solution of the perturbed problem ( S D P ) μ and its convergence to optimal solution of ( S D P ) . Next, we present new different alternatives to calculate the displacement step. After, we establish the convergence of the obtained algorithm and we show that its complexity is O ( n ln [ ε − 1 ( 〈 X 0 , S 0 〉 ) ] ) . Finally, we present some numerical simulations which show the effectiveness of the algorithm developed in this work. [ABSTRACT FROM AUTHOR]

Abstract: This paper introduces a nonlinear function into the frequency spectrum that improves the detection of vowels, diphthongs, and semivowels within the speech signal. The lower efficiency of consonant detection was solved by implementing the hangover and hangbefore criteria. This paper presents a procedure for faster definition of those optimal constants used by hangover and hangbefore criteria. A nonlinearly changed frequency spectrum is used in the proposed GMM (Gaussian Mixture Model) based VAD (Voice Activity Detection) algorithm. Comparative tests between the proposed VAD algorithm and seven other VAD algorithms were made on the Aurora 2 database. The experiments were based on frame error detection and on speech recognition performance for two types of acoustic training modes (multi-condition and clean only). The lowest average percentage of frame errors was obtained by the proposed VAD algorithm, which also achieved positive improvement in the speech recognition performance for both types of acoustic training modes. [Copyright &y& Elsevier]

Abstract: This paper deals with robust blind linear minimum mean square error (LMMSE) detection using the particle swarm optimization (PSO) algorithm in the presence of code mismatch. The paper shows that the PSO algorithm incorporating the linear system of the LMMSE detector, which is termed as LPSO, can significantly improve the bit error rate (BER) and the system capacity. As the code mismatch occurs, the output BER performance is vulnerable to degradation for LPSO. To remedy this problem, a blind LMMSE scheme is proposed and combined with PSO to form a robust blind LPSO (BLPSO) detector under code mismatch scenarios. Several computer simulations are provided to demonstrate the effectiveness of the proposed scheme. [Copyright &y& Elsevier]

This paper presents the first part of a study aiming at error state selection in Kalman filters applied to the stationary self-alignment and calibration (SSAC) problem of strapdown inertial navigation systems (SINS). Estimation algorithms are derived through the analytical manipulation of the full SINS error model, thereby enabling us to investigate the dynamic coupling existing between the state variables. As contributions of this work, we demonstrate that the vertical velocity error is very important for the estimation of almost all error states. Latitude and altitude errors, in turn, are shown to uniquely affect the inertial sensor bias estimates. Besides, the longitude error is found to be totally detached from the system. As straightforward consequence, Bar-Itzhack and Berman's error model turns out to be inadequate for real implementations, and a 12-state Kalman filter is shown to be the optimal error state selection for SSAC purposes. Simulated and experimental tests confirm the adequacy of the outlined conclusions. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates adaptive control design for nonlinear square MIMO systems. The control scheme is based on recurrent neural networks emulator and controller with decoupled adaptive rates. Networks'' parameters are updated according to an autonomous algorithm inspired from the Real Time Recurrent Learning (RTRL). The contributions of this paper are the determination of Lyapunov sufficient stability conditions for decoupled adaptive rates of the emulator and controller and the development of new adaptation strategies based on the tracking error dynamics and Lyapunov stability analysis to improve the closed loop performances. Efficiency of the proposed controller is illustrated with nonlinear system simulations. An application of the developed approaches to a hot-air blower is presented in order to validate simulations results. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the model of communication where wireless devices can either switch their radios off to save energy (and hence, can neither send nor receive messages), or switch their radios on and engage in communication. The problem has been extensively studied in practice, in the setting such as deployment and clock synchronization of wireless sensor networks. We distill a clean theoretical formulation of minimizing radio use and present near-optimal solutions. Our base model ignores issues of communication interference, although we also extend the model to handle this requirement. We assume that nodes intend to communicate periodically, or according to some time-based schedule. Clearly, perfectly synchronized devices could switch their radios on for exactly the minimum periods required by their joint schedules. The main challenge in the deployment of wireless networks is to synchronize the devices’ schedules, given that their initial schedules may be offset relative to one another (even if their clocks run at the same speed). In this paper, we study how frequently the devices must switch on their radios in order to both synchronize their clocks and communicate. In this setting, we significantly improve previous results, and show optimal use of the radio for two processors and near-optimal use of the radio for synchronization of an arbitrary number of processors. In particular, for two processors we prove deterministic matching upper and lower bounds on the number of times the radio has to be on, where is the discretized uncertainty period of the clock shift between the two processors. (In contrast, all previous results for two processors are randomized.) For processors (for any positive ) we prove is the lower bound on the number of times the radio has to be switched on (per processor), and show a nearly matching (in terms of the radio use) Õ randomized upper bound per processor. For our algorithm runs with at most poly-log radio invocations per processor. Our bounds also hold in a radio-broadcast model where interference must be taken into account. [Copyright &y& Elsevier]

Hydraulic fracturing of rocks has various engineering applications. However, there has been limited research into crack propagation prediction by three dimensional analytical techniques. This paper discusses such a technique for predicting the propagation surface of a pressurized circular crack subjected to various loading conditions. The propagation surfaces predicted from the proposed crack front propagation algorithm align well with published results. The suggested method consumes only a fraction of the time needed for a numerical simulation, and therefore it could be useful in assisting the design of hydraulic fracturing operations. [ABSTRACT FROM AUTHOR]

This paper presents a new Electromagnetism-like Mechanism (EM) algorithm with Split, Probe and Compare feature (SPC-EM). The proposed algorithm replaces the local search segment of a standard EM with a new search scheme named Split, Probe, and Compare (SPC). A nonlinear equation is designed to systematically and dynamically adjust the length of the probes based on the outcome of the Compare segment in each iteration. Extensive computational simulations and comparisons on 10 different benchmark problems from the literature were carried out. Results show that the new modified mechanism outperformed all other algorithms involved in the benchmarking. We thus conclude that the proposed SPC-EM works well with the designed probe-length tuning equation in solving numerical optimization problems. [ABSTRACT FROM AUTHOR]

This paper presents a numerical model to simulate the evolution of waves and their interactions with a restrained ship that is moored in coastal waters. The model aims to be applicable at the scale of a harbour or coastal region, while accounting for the key physical processes that determine the hydrodynamic loads on the ship. Its methodology is based on the non-hydrostatic wave-flow model SWASH, which provides an efficient tool to simulate the nonlinear dynamics that govern the nearshore wave field. In this work, we propose a new numerical algorithm that accounts for the presence of a non-moving floating body, to resolve the wave impact on a restrained ship. The model is validated through comparisons with an analytic solution, a numerical solution, and two laboratory campaigns. The results of the model-data comparison demonstrate that the model captures the scattering of waves by a restrained body. Furthermore, it gives a reasonable prediction of the hydrodynamic loads that act on a restrained container ship for a range of wave conditions. Importantly, the model captures these dynamics efficiently, which demonstrates that it retains this favourable property of the non-hydrostatic approach when a floating body is included. The findings of this study suggest that the model provides a promising new alternative to simulate the nonlinear evolution of waves and their impact on a restrained ship at the scale of a realistic harbour or coastal region. [ABSTRACT FROM AUTHOR]

Abstract: The objective of the work presented in this paper is an attempt at solving and transforming of the known from the classical mechanics three dimensional – single mass mathematical and mechanical vibration models in a higher order dimensional space with any virtual sectional curvature – positive or negative, constant or variable. The object of the investigation is a class of three dimensional surfaces. The aims of the work presented in this paper are to illustrate the performance of the common algorithm in three dimensional linear motion transformation, that means to transform 3D space in a higher order dimensional space and a comparison is derived on the behavior of the common algorithm depending on the surface properties. A characterization of the Riemannian Manifolds is performed by means of curvature operators in the three dimensional solution. The computer codes Mathematica and MATLAB are used in the numerical simulation. The system motion is investigated in a 3-D qualitative aspect in time and frequency domain. The application can be in topology when geodesists make snap shots of the surface profile, then the curved lines can be analyzed and transformed in the desired space dimension. Any kind of a trajectory of motion can be transformed successfully in a higher order dimensional space and vice verse by means of applying of the common algorithm. [Copyright &y& Elsevier]