Configuration Models Research Articles

A Generic Encapsulation to Unravel Social Spreading of a Pandemic: An Underlying Architecture

Cases of a new emergent infectious disease caused by mutations in the coronavirus family, called “COVID-19,” have spiked recently, affecting millions of people, and this has been classified as a global pandemic due to the wide spread of the virus. Epidemiologically, humans are the targeted hosts of COVID-19, whereby indirect/direct transmission pathways are mitigated by social/spatial distancing. People naturally exist in dynamically cascading networks of social/spatial interactions. Their rational actions and interactions have huge uncertainties in regard to common social contagions with rapid network proliferations on a daily basis. Different parameters play big roles in minimizing such uncertainties by shaping the understanding of such contagions to include cultures, beliefs, norms, values, ethics, etc. Thus, this work is directed toward investigating and predicting the viral spread of the current wave of COVID-19 based on human socio-behavioral analyses in various community settings with unknown structural patterns. We examine the spreading and social contagions in unstructured networks by proposing a model that should be able to (1) reorganize and synthesize infected clusters of any networked agents, (2) clarify any noteworthy members of the population through a series of analyses of their behavioral and cognitive capabilities, (3) predict where the direction is heading with any possible outcomes, and (4) propose applicable intervention tactics that can be helpful in creating strategies to mitigate the spread. Such properties are essential in managing the rate of spread of viral infections. Furthermore, a novel spectra-based methodology that leverages configuration models as a reference network is proposed to quantify spreading in a given candidate network. We derive mathematical formulations to demonstrate the viral spread in the network structures.

Analysis of tube-in-tube copper helical heat exchanger to improve heat transfer

The present work aims to investigate the effect of different configurations of tube-in-tube helically coiled heat exchanger. Commercial CFD codes were used to predict the fluid flow and heat transfer in a tube-in-tube helical heat exchanger. The model of different configurations of the inner tube has been simulated by varying the dean number. The numerical results are verified and found to be in good agreement with reported data in the literature. Nusselt Number and friction factor are evaluated for different angular positions. The use of geometry E increases the Nusselt Number and friction factor by 17.05% and 15% respectively at a Dean number of 400 as compared with a circular tube.

Analytical Model of a Magnetopause in a Multicomponent Collisionless Plasma with a Kappa Energy Distribution of Particles

We propose an analytical model for a distributed current sheet with a variable profile that separates two regions of anisotropic collisionless plasma with different magnetic fields and different effective temperatures of the kappa energy distributions of electrons and ions. The model also admits the presence of several ion components with different effective temperatures and spatially separated localized countercurrents of each of these components. We demonstrate the change in the characteristics of the current sheet when going from a Maxwellian to a kappa distribution, which takes into account the presence of a power-law spectrum of energetic particles typical of a nonequilibrium magnetoactive plasma. The theory developed allows us to carry out for the first time analytical modeling of such current configurations in both laboratory and cosmic plasmas, e.g., in planetary magnetopauses, coronal loops, and stellar wind with magnetic clouds.

Radiation characteristics of sharply directed conical waveguide-slot antenna arrays

Currently, much attention is paid to antenna arrays, the emitters of which can be located in the bow of unmanned aerial vehicles (UAVs). Emitters can be longitudinal, transverse or oblique slots located along the generatrix of the cone on the conducting surface. A number of specific requirements are imposed on such ARs used in on-board radar systems (radars) of UAVs, among which we can note the need to form a highly directional total-difference directional pattern (DP) with a maximum of the total DP and a minimum of a difference DP in the direction of the UAV flight axis, as well as high gain and slope of the difference characteristic. The aim of this work was to study the radiation of a waveguide-slot antenna array (WASAA) installed on a conical surface and providing linear polarization of the emitted field in the direction of the cone axis. For this, electrodynamic modeling of various configurations of WASAA, located both in free space and on a conical surface, was carried out. For the developed models of antennas, the directivity characteristics and their dependence on the geometry and dimensions of the WASAA are determined. The results of an experimental study of the characteristics of a model of a conical antenna emitting a field of linear polarization in the direction of the cone axis are presented. The experimental results are compared with the results of electrodynamic modeling. The results obtained are of practical interest for the development of airborne antenna UAVs.

Study on Heat transfer and Pressure Drop in Tube-In-Tube Helical Heat Exchanger

ABSTRACT The present work aims to investigate the effect of different configurations of the tube-in-tube helically coiled heat exchanger. Commercial CFD codes were used to predict the fluid flow and heat transfer in a tube-in-tube helical heat exchanger. The model of different configurations of the inner tube has been simulated by varying the Dean number. The numerical results are verified and found to be in good agreement with reported data in the literature. Nusselt Number and friction factor are evaluated for different angular positions. The use of geometry E increases the Nusselt number and friction factor by 19.05% and 16% respectively at a Dean number of 4000 as compared with a circular tube as compared with the circular tube.

Determinantal Point Processes for Image Processing

Determinantal point processes (DPPs) are probabilistic models of configurations that favor diversity or repulsion. They have recently gained influence in the machine learning community, mainly because of their ability to elegantly and efficiently subsample large sets of data. In this paper, we consider DPPs from an image processing perspective, meaning that the data we want to subsample are pixels or patches of a given image. To this end, our framework is discrete and finite. First, we adapt their basic definition and properties to DPPs defined on the pixels of an image, that we call determinantal pixel processes (DPixPs). We are mainly interested in the repulsion properties of such a process and we apply DPixPs to texture synthesis using shot noise models. Finally, we study DPPs on the set of patches of an image. Because of their repulsive property, DPPs provide a strong tool to subsample discrete distributions such as that of image patches.

The comparative effectiveness of different models of permanent supportive housing on problematic substance use, depression, and anxiety symptoms over time.

To compare the effectiveness of different models of permanent supportive housing (PSH), housing configuration, and service provision model on substance use, depression, and anxiety symptoms among residents over time. Linear mixed model regression was used with 888 residents of PSH to investigate the relationship between supportive housing type, service model, and housing configuration and change in mental health and substance use at baseline, 6-, 12-, and 18-month follow-up. There were few significant differences in problematic substance use, depression, or anxiety symptoms among those in different PSH types, different housing configuration models, or different service provision models. Similarly, there were no significant differences in PSH type, housing configuration, or service delivery model among those with severe mental illness (SMI), substance use disorder (SUD), or those with dual diagnoses. There is little evidence that different models of PSH result in differences in mental health and substance use outcomes. Future research should consider the number of services clients receive and critical periods in PSH residency in improving mental health and substance use outcomes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Efficient photovoltaics-integrated hydrogen fuel cell-based hybrid system: Energy management and optimal configuration

Due to their intermittent nature, the use of renewable energy sources has faced the challenges of power insecurity and low efficiency. Recently, fuel cells (FCs) have become a potential choice for backup-power generation in remote microgrids due to their reduced maintenance needs and long lifecycle. However, the efficiency of hydrogen FCs as backup power needs to be improved. The efficiency is related to system sizing and operational techniques. Thus, this paper proposes an efficient energy management strategy and optimal configuration models based on a hybrid system including photovoltaics (PVs) and hydrogen FCs to achieve a high operational efficiency and optimize the system configuration. The system model is built, and an energy management strategy is proposed first. This strategy determines when the PV and FC supply power to a load under various conditions. Proper sizing of the sub-components in the PV/FC hybrid system also plays an essential role in ensuring continuous power flow. To ensure power quality, the hybrid system configuration is estimated using a systematic method without affecting the power quality to minimize residual power losses. In addition, various essential simulations are performed to verify the proposed model. The results indicate that the total efficiency of the system can reach 47.9%.

An Availability Analysis Approach for Deployment Configurations of Containers

Operating system (OS) containers enabling the microservice-oriented architecture are becoming popular in the context of Cloud services. Containers provide the ability to create lightweight and portable runtime environments that decouple the application requirements from the characteristics of the underlying system. Services built on containers have a small resource footprint in terms of processing, storage, memory and network, allowing a more dense deployment environment. While the performance of such containers is addressed in few previous studies, understanding the failure-repair behavior of the containers remains unexplored. In this paper, from an availability point of view, we propose and compare different configuration models for deploying a containerized software system. Inspired by Google Kubernetes, a container management system, these configurations are characterized with a failure response and migration service. We develop novel non-state-space (i.e., fault tree) and state-space (i.e., stochastic reward net) analytic models for container availability analysis. Analytical as well as simulative solutions are obtained for the developed models. Our analysis provides insights on k out-of N availability and sensitivity of system availability for key system parameters. Finally, we build an open-source software tool powered by these models. The tool helps a Cloud administrator to assess the availability of a containerized system and to conduct a what-if analysis based on user-provided parameters and configurations.

Numerical Study to Evaluate the Performance of Nonuniform Stepped Spillway Using ANSYS-CFX

The main features that attract hydraulic engineers for designing stepped spillways are their ability to lose a large portion of the flow energy and add or increase aeration to the flow naturally. Hence, smaller size stilling basin and no aeration device may require. This study aims to find the amount of energy dissipation rate and the location of inception point over non-uniform stepped spillway. The numerical 2D ANSYS-CFX code is applied to generate and run thirty-two models of different configurations using two different moderate slopes (1 V:2 H and 1 V:2.5 H) as most of the downstream slopes designed for moderate slope, and two different step heights (hs= 0.08 m and hs= 0.016 m) under skimming flow discharge for different (dc/hs) ranging from dc/hs= 1–2.2, in which dc is the critical flow deptho n the crest. The volume of fluid is implemented and the renormalized group of k-ɛ turbulence model is activated. The computational results demonstrated that the amount of energy dissipation increases with decreasing the flow discharge, chute slope, and step height. In addition, it is observed that the length of the inception point is directly proportional to the discharge and inversely proportional to both the chute slopes and step height. Moreover, for the design point of view, the results revealed that configuration B can be considered as the optimal one amongst the others examined herein.

Семантический потенциал пассивных конструкций в англоязычном научном дискурсе

The study aims to identify semantic types of passive constructions in the English-language scientific discourse using material of different functional genres. Scientific novelty of the work lies in the fact that, while considering semantics of the passive construction, the method of role-semantic analysis is used for the first time to identify deep semantic configurations of the specified constructions and to determine frequent semantic types of passive voice in scientific speech. As a result of the research, 21 models of semantic configurations of passive constructions have been identified, the proportion of passives with different lexical and semantic load in the English-language scientific discourse is revealed and reasons for such distribution are given.

Mathematical model and stability investigation of plasma equilibrium around a current-carrying conductor

Magnetic Galatea-traps with current-carrying conductors immersed into the plasma are permanent topics of theoretical, experimental and numerical investigations in the controlled thermonuclear fusion field. Our paper presents a mathematical model of equilibrium magnetoplasma configurations around a straight conductor non-contacting with it. Some necessary regularities in the connection between quantitative characteristics of configurations are established. Problems on their MHD stability are set up and partially solved.

Data-Driven Identification of Nonlinear Flame Models

Abstract This paper presents a data-driven identification framework with the objective to retrieve a flame model from the nonlinear limit cycle. The motivation is to identify a flame model for configurations, which do not allow the determination of the flame dynamics: that is commonly for industrial applications where (i) optical access for nonintrusive measurements of velocity and heat release fluctuations are not feasible and (ii) unstable combustion is monitored via multiple pressure recordings. To demonstrate the usefulness of the method, we chose three test cases: (i) a classical Rijke tube; (ii) an experiment of a laminar flame (EM2C case), (iii) and a high-pressure, turbulent premixed flame (German Aerospace Center (DLR) case). The procedure is as follows: First, acoustic network models for the three cases are generated for which the in-house software taX is employed. Next, the acoustic network models are embedded in an optimization framework with the objective to identify flame parameters that match the experimental limit cycle data: based on the instability frequency and pressure amplitudes, we formulate physical constraints and an objective function in order to identify the flame model parameters gain nopt and time delay τopt in the nonlinear regime. We demonstrate for the three cases that the identified flame parameters reproduce the unstable combustion processes and highlight the usefulness of the method for control purposes.

Jigging: A Review of Fundamentals and Future Directions

For centuries, jigging has been a workhorse of the mineral processing industry. Recently, it has also found its way into the recycling industry, and the increasing concerns related to water usage has led to a renewed interest in dry jigging. However, the current scenario of increasing ore complexity and the advent of smart sensor technologies, such as sensor-based sorting (SBS), has established increasingly challenging levels for traditional concentration methods, such as jigging. Against this background, the current review attempts to summarize and refresh the key aspects and concepts about jigging available in the literature. The configuration, operational features, applications, types, and theoretical models of jigging are comprehensively reviewed. Three promising paths for future research are presented: (1) using and adapting concepts from granular physics in fundamental studies about the stratification phenomena in jigs; (2) implementing advanced control functions by using machine vision and multivariate data analysis and; (3) further studies to unlock the potential of dry jigs. Pursuing these and other innovations are becoming increasingly essential to keep the role of jigging as a valuable tool in future industry.

Weighted hypersoft configuration model

Maximum entropy null models of networks come in different flavors that depend on the type of constraints under which entropy is maximized. If the constraints are on degree sequences or distributions, we are dealing with configuration models. If the degree sequence is constrained exactly, the corresponding microcanonical ensemble of random graphs with a given degree sequence is the configuration model per se. If the degree sequence is constrained only on average, the corresponding grand-canonical ensemble of random graphs with a given expected degree sequence is the soft configuration model. If the degree sequence is not fixed at all but randomly drawn from a fixed distribution, the corresponding hypercanonical ensemble of random graphs with a given degree distribution is the hypersoft configuration model, a more adequate description of dynamic real-world networks in which degree sequences are never fixed but degree distributions often stay stable. Here, we introduce the hypersoft configuration model of weighted networks. The main contribution is a particular version of the model with power-law degree and strength distributions, and superlinear scaling of strengths with degrees, mimicking the properties of some real-world networks. As a byproduct, we generalize the notions of sparse graphons and their entropy to weighted networks.

A Development Methodology Framework of Smart Manufacturing Systems (Industry 4.0)

Numerous studies have been conducted to reveal the importance of Smart Manufacturing Systems (SMS) or Industry 4.0, but very few studies have been made to answer the question on “how to establish a new SMS” taking into account the required efficiency, reliability, cost-effectiveness, and sustainability that requires pre-implementation planning and assessment. Besides, the discussion on the challenges of SMS adoption is very limited in the literature studies. In particular, the recent configuration models proposed by literature overlooked the pivotal role of robots in any SMS project. Therefore, a clear and concise development framework is needed to provide a better understanding of the development process of a new SMS, which leads to higher adoption of this new technology. To do so, the main objective of this study is to propose a development methodology framework that enables stakeholders to build better SMS capabilities while enhancing the adoption awareness of industry 4.0 among manufacturers. The framework consists of four phases, system and robots’ configuration, smart system components, smart system integration, and evaluation and selection. This study supports the realization of Industry 4.0, particularly in Malaysia. Currently, Malaysia is behind other ASEAN countries like Indonesia and Singapore as the highest growth country in the digital economy. The proposed methodology is expected to support different industries in the adoption of the technology in building a new SMS or evaluating an existing one.

Assessing the Performance of Various Stochastic Optimization Methods on Chemical Kinetic Modeling of Combustion

The solution to chemical kinetic models for a particular reactor configuration is usually composed of a set of stiff ordinary differential equations (ODEs), where a number of rate parameters have t...

Assessment of multiple relaxation time-lattice Boltzmann method framework for non-Newtonian fluid flow simulations

A kinetic-theory based approach known as the lattice Boltzmann method (LBM) with multiple-relaxation-time (MRT) collision is employed to assess the non-Newtonian fluid models for standard two-dimensional benchmarks flow configurations. A two-dimensional nine-velocity square lattice (D2Q9) is used as a basic space-microscopic-velocity coupled LBM structure. The MRT-LBM formulation for the non-Newtonian fluids is validated for flow inside a lid-driven cavity. The non-Newtonian fluid viscosity is estimated using standard models as, Power-law, Carreau, Carreau–Yasuda, and Cross. These models are incorporated in the MRT-LBM framework to solve four standard benchmark flow configurations, namely, (a) lid-driven square cavity flow; (b) flow over a circular cylinder placed inside the lid-driven square cavity; (c) flow through two parallel plates, i.e. through a straight channel; and (d) flow over an asymmetrically placed circular cylinder in a straight channel. The simulation results for various benchmark cases found to be comparable with the earlier published data.

Numerical Finger Kinematic Models Derived From Virtual Grasping of Various Cylindrical Objects With the Family of Conic Sections

Abstract In this study, a numerical framework for joint rotation configuration models of a finger is proposed. The basic idea is to replicate the finger’s geometric posture observed when the human hand grasps a cylindrical object with various cross sections. In the model development, objects with the cross section adopted from the curves of order two (the family of conic sections) are taken into consideration to realize various finger postures. In addition, four different grasp styles, which simulate the individual-specific contact pattern between the surfaces of object and finger, are modeled and applied for the formulation of numerical models. An idea on how to change flexion/extension patterns in the middle of excursion of movement is proposed and discussed. Series of numerical studies have been conducted and analyzed to evaluate the proposed models. From the results, one can see the models’ feasibility and viability as a solution to describing finger’s flexion/extension movements (FEMs) for grasping patterns.

Size-dependent two-scale topological design for maximizing structural fundamental eigenfrequency

A two-scale concurrent topology optimization method based on the couple stress theory is proposed for maximizing structural fundamental eigenfrequency. Because of the fact that the classical mechanics theory cannot reveal the size effect because of neglecting the influence of microstructure, the theory of couple stress including the microscopic properties of materials can be used to describe the size effect in deformations. On the foundation of the couple stress theory, the two-scale optimization model for finding optimal configurations of macrostructures and their periodic composite material microstructures is built. And the fundamental eigenfrequency of the macrostructure is maximized. The effective macroscopic couple stress constitutive constants of macrostructures are calculated by the representative volume element method. And a modified solid isotropic material with a penalization model is used to effectively avoid the localized mode. The optimization algorithm based on the bidirectional evolutionary structural optimization method is proposed. The optimal results of numerical examples show that the optimal topologies and natural frequencies obtained by the couple stress theory may differ significantly from those obtained by the typical Cauchy theory. It is obvious that couple stress theory can effectively describe the size effect in topology optimization.