Analytical Simulation Research Articles

Two-plasmon decay of microwaves in low temperature magnetized laboratory plasmas

Observations from magnetically confined fusion experiments have in the past decades revealed instances of two-plasmon decay instabilities (TPDIs) between injected 2nd harmonic X-mode waves and trapped upper hybrid (UH) waves near half frequency of the injected wave. We present and compare growth rates of TPDIs computed from reduced analytical models and particle-in-cell (PIC) simulations in low-temperature plasmas, emulating conditions found in more accessible controllable laboratory devices. The growth rates obtained from simulations agree with our modeling, confirming that we can model TPDIs using both analytical models and PIC simulations in low-temperature plasmas. Furthermore, the growth rates are on the order of 0.01 ns−1 to 0.1 ns−1 for injected waves with intensity of 103 W/cm2, which indicates that we can expect to see signals of TPDIs in controllable laboratory plasma devices.

MTR Model-Based Testing Framework MTR Model-Based Testing Framework MTR Model-Based Testing Framework

In this article we propose a novel, free and open- source model-based testing framework for finite state machine specifications. The various model handling and test generation options make the framework suitable for testing complex systems and provide a solid background for investigating different automated test design methodologies. The complexity and fault detection capabilities of the available algorithms are investigated through analytical analyses and simulations applying randomly injected faults.

NLOS Transmission Analysis for Mobile SLIPT Using Resonant Beam

Simultaneous lightwave information and power transfer (SLIPT) is a potential way to meet the demands of sustainable power supply and high-rate data transfer in next-generation networks. Although resonant beam-based SLIPT (RB-SLIPT) can realize high-power energy transfer, high-rate data transfer, human safety, and self-alignment simultaneously, mobile transmission channel (MTC) analysis under non-line-of-sight (NLOS) propagation has not been investigated. In this paper, we propose analytical models and simulation tools for reflector-assisted NLOS transmission of RB-SLIPT, where transmission loss and accurate beam field profile of NLOS MTC can be obtained with a receiver at arbitrary positions and attitude angles. We establish analytical models relying on full diffraction theory for beam propagation between tilted or off-axis planes. Then, we provide three numerical methods (i.e., NUFFT-based, cubic interpolation-based, and linear interpolation-based methods) in simulations. Moreover, to deal with the contradiction between limited computing memory and high sampling requirements for long-range transmission analysis, we propose a multi-hop sliding window approach, which can reduce the sampling number by a factor of thousands. Finally, numerical results demonstrate that RB-SLIPT can achieve 3W charging power and 10bit/s/Hz data rate over a 2m distance in NLOS scenarios.

Systematic effects on the upcoming NIKA2 LPSZ scaling relation

In cluster cosmology, cluster masses are the main parameter of interest. They are needed to constrain cosmological parameters through the cluster number count. As the mass is not an observable, a scaling relation is needed to link cluster masses to the integrated Compton parameters Y, i.e. the Sunyaev-Zeldovich observable (SZ). Planck cosmological results obtained with cluster number counts are based on a scaling relation measured with clusters at low redshift (z<0.5) observed in SZ and X-ray. In the SZ Large Program (LPSZ) of the NIKA2 collaboration, the scaling relation will be obtained with a sample of 38 clusters at intermediate to high redshift (0.5 < z < 0.9) and observed at high angular resolution in both SZ and X-ray. Thanks to analytical simulation of LPSZ-like samples, we take into account the LPSZ selection function and correct for its effects. Besides, we show that white and correlated noises in the SZ maps do not affect the scaling relation estimation.

Experimental Digital Twins with Socio-Economic Artificial Environments of Forecast and Analytical Simulation Models

The technological development of Russia in recent years has been moving at an active pace due to external challenges that dictate the need to search for internal resources and poses serious challenges to the scientific community in terms of developing research potential and creating software and technological sovereignty, especially emphasizing the importance of the IT industry and long-term forecasting. Nanotechnology, which incorporates the concepts of IT, is a supra-industry technology, that is, it is the basis for achieving progress in any area of human activity. Without the use of information technology, it will be extremely difficult to achieve outstanding achievements in a dynamically changing world. There is an emerging interest in new computer modeling methods that make it possible to create experimental digital twins in the form of simulation models and can partially compensate for the incompleteness of information. Having modeled the necessary processes, it is possible to make management decisions on the construction of facilities, simulate socio-economic processes, and formulate a 10-year forecast about the demographic situation of the country. The applied modeling tools discussed in the article demonstrate the usefulness of such management tools with developed functional elements in information and analytical management structures. Soon, this trend will increase and those countries that will take leading positions in this direction will be able to create ultra-effective forecasting and analytical scenarios with various levels of detail. By using all the functionality of simulation modeling, it is possible to create truly applied instrumental complexes with a potential basis for the implementation of such solutions in the structures of systems of distributed situational centers for the future development of technological sovereignty and the introduction of fundamentally new methods of strategic forecasting in the Russian Federation.

An Indigenous Computational Platform for Nowcasting and Forecasting Non-Linear Spread of COVID-19 across the Indian Sub-continent: A Geo-Temporal Visualization of Data

The rapid spread of the COVID-19 pandemic necessitated unprecedented collective action against coronavirus disease. In this light,we are proposing a novel online platform for the visualization of epidemiological data incorporating social determinants for understanding the patterns associated with the spread of COVID-19. The current AI computational platform combines modeling methodologies along with temporal geospatial visualization of COVID-19 data, providing real-time sharing of graphic analytical simulation of vulnerable hotspots of recurrent (nowcasting) and emergent (forecasting) infections visualized on a spatiotemporal scale on geoportals. The proposed study will be a secondary data analysis of primary data accessed from the national portal (Indian Council of Medical Research (ICMR)) incorporating 766 districts in India. Epidemiological data related to spatiotemporal visualization of the demographic spread of COVID-19 will be displayed using a compartmental socio-epidemiological model, reproduction number R, epi-curve diagrams as well as choropleth maps for different levels of administrative and development units at the district levels.

Analytical and numerical simulation of the conformable new extended (2 + 1) dimensional Kadomtsev–Petviashvili equation

Partial differential equations are used to model problems in many scientific fields. To solve these equations, analytical and numerical techniques are created. This study considers the conformable version of the expanded Kadomtsev–Petviashvili equation in -dimensions for the first time. New exact and approximative solutions to the equation that do not exist in the literature are obtained using the analytical techniques of the -expansion and modified Kudryashov methods, as well as the numerical technique residual power series method. To better understand the dynamic nature of these findings, we have given 3D, contour, and 2D plots of some of the solutions. The development of numerous new exact solutions has demonstrated the reliability and effectiveness of the methods. We also provide an approximation table of values for the approximate solutions of the given equation using different values for various parameters.

Study of leakage current in underground mine power network: a case study in mining in Vietnam

Purpose. To determine DC leakage current in mine power network with long DC power transmission. Methodology. Nowadays, the increase in capacity and working depth leads to the use of DC power transmission, which has many benefits both economically and technically in mining. However, the appearance of DC power transmission changes the structure of the network. In the underground mine power network, there will be electrical networks with industrial frequency 50 Hz, DC power networks, and power networks after variable frequency inverters. The correlation of these network parameters complicates leakage protection in the mine power network. For DC power transmission in mining, the DC network parts have a large length, so during the working process, electricity leakage in these parts of the network often occurs. Leakage current in a DC network depends not only on DC network parameters but also on AC network parameters. The article uses analytical methods and simulation methods on Matlab/Simulink software to determine leakage currents in underground mine power networks with DC transmission when there is a change in power network parameters. Findings. The research results show that the leakage current value of the DC network is greatly affected when the insulation parameters of the electrical network change, not only in the DC power network but also in the AC network before and after the inverter. This causes the unreliable operation of the leakage protection device in this DC transmission network. Originality. Calculation model and simulation of DC leakage current in underground mine power networks with long DC transmission in mining in Vietnam Practical value. The research results are the basis for calculating and selecting leakage protection equipment for the purpose of improving safety in underground mining in Vietnam.

Analytical Analysis of Flexible Microfluidic Based Pressure Sensor Based on Triple-Channel Design

In designing a flexible microfluidic-based pressure sensor, the microchannel plays an important role in maximizing the sensor's performance. Similarly, the material used for the sensor's membrane is crucial in achieving optimal performance. This study presents an analytical analysis and FEA simulation of the membrane and microchannel of the flexible pressure sensor, aimed at optimizing it design and material selection. Different types of materials, including two commonly used polymers, Polyimide (PI) and Polydimethylsiloxane (PDMS) were evaluated. Moreover, different designs of the microchannel, including single-channel, double-channel, and triple-channel, were analyzed. The applied pressure, width of the microchannel, and length of the microchannel were varied to study the normalized resistance of the microchannel and maximize the performance of the pressure sensor. The results showed that the triple-channel design produced the highest normalized resistance. To achieve maximum performance, it is found that using a membrane with a large area facing the applied pressure was optimal in terms of dimensions. In conclusion, optimizing the microchannel and membrane design and material selection is crucial in improving the overall performance of flexible microfluidic-based pressure sensors.

Lightweight Computational Complexity Stepping Up the NTRU Post-Quantum Algorithm Using Parallel Computing

The Nth-degree Truncated polynomial Ring Unit (NTRU) is one of the famous post-quantum cryptographic algorithms. Researchers consider NTRU to be the most important parameterized family of lattice-based public key cryptosystems that has been established to the IEEE P1363 standards. Lattice-based protocols necessitate operations on large vectors, which makes parallel computing one of the appropriate solutions to speed it up. NTRUEncrypt operations contain a large amount of data that requires many repetitive arithmetic operations. These operations make it a strong candidate to take advantage of the high degree of parallelism. The main costly operation that is repeated in all NTRU algorithm steps is polynomial multiplication. In this work, a Parallel Post-Quantum NTRUEncrypt algorithm called PPQNTRUEncrypt is proposed. This algorithm exploits the capabilities of parallel computing to accelerate the NTRUEncrypt algorithm. Both analytical and Apache Spark simulation models are used. The proposed algorithm enhanced the NTRUEncrypt algorithm by approximately 49.5%, 74.5%, 87.6%, 92.5%, 93.4%, and 94.5%, assuming that the number of processing elements is 2, 4, 8, 12, 16, and 20 respectively.

Relative Characteristics of Various Nano-Cement Composite

A comparative study between two nano cementitious materials, i.e., Graphene Nanoplatelet (GNP) and Montmorillonite Nano Clay (MNC) cement matrix are considered in this paper. Nanofibers are introduced as an alternative to macro reinforcement to enhance the mechanical property and reduce the crack growth in the cement matrix at the nanoscale. Various analytical simulation has been carried out by ANSYS 15.0 to know the optimum percentage of water. A 3D Represent Volume Element (RVE) is used to simulate nano cementitious material as the material sizes differ. RVE is the minimum volume upon which a measurement can make, yielding an expected value of the entire. The GNPs and MNCs are added to the cement matrix with various percentages (0.02%, 0.08%, 0.1%, 0.15%, 0.17%, 0.22%, and 0.3%) by the weight of cement. After simulating the pullout models with proper boundary conditions, the behavior of nano-cementitious material is observed. A comparative study of all percentage variations revealed that the mechanical property increases up to 0.17% and 0.22% for GNPs and MNCs. It also observed that GNPs cementitious material performs better than MNCs cement matrix.

A Back–Forward Approach-Based Efficiency Performance Analysis Model for Hybrid Electric Propulsion Ships Using the Holtrop–Mennen Method

Due to tightening regulations on exhaust emissions from ships, there is a growing need to develop electric or hybrid electric propulsion systems to replace conventional diesel-based ship power systems. The hybrid electric propulsion system is suitable for small and medium-sized vessels and its energy efficiency significantly depends on the arrangement of different power sources, power control strategies for energy sources, and energy storage system (ESS). Therefore, an analytical simulation to evaluate the energy efficiency of ships with their structure and control strategies is needed. In this study, a back–forward approach-based efficiency performance analysis model was developed using the Holtrop–Mennen resistance model to calculate ship resistance and power demand based on a given ship’s speed profiles. This model has the advantages of using easily obtainable ship speed profiles as the input and can be modularized for each power source and ESS, incorporating mechanical performance limitations, and allows for rapid analysis. The developed analytical model was applied to a hybrid electric propulsion system in a marine support vessel and its energy efficiency was evaluated by establishing rule-based power control strategies. As a result, the engine efficiency of the hybrid electric propulsion system increased from about 27% to 30% compared to the existing system, and the final effect of reducing fuel consumption by about 10% compared to the existing system was confirmed through the developed simulator. In the future, this analytical model could be utilized to derive the optimal layout of hybrid electric propulsion systems, and to formulate power control strategies.

Analytical simulation of mode I fracture generation from dynamic frictional surfaces governed by slip weakening model

Analytical simulation of mode I fracture generation from dynamic frictional surfaces governed by slip weakening model

Precise parameter control of multicycle terahertz generation in PPLN using flexible pulse trains.

The low (sub %) efficiencies so-far demonstrated for nonlinear optical down-conversion to terahertz (THz) frequencies are a primary limiting factor in the generation of high-energy, high-field THz-radiation pulses (in particular narrowband, multicycle pulses) needed for many scientific fields. However, simulations predict that far higher conversion efficiencies are possible by use of suitably-optimized optical sources. Here we implement a customized optical laser system producing highly-tunable trains of infrared pulses and systematically explore the experimental optimization of the down-conversion process. Our setup, which allows tuning of the energy, duration, number and periodicity of the pulses in the train, provides a unique capability to test predictions of analytic theory and simulation on the parameter dependences for the optical-to-THz difference-frequency generation process as well as to map out, with unprecedented precision, key properties of the nonlinear crystal medium. We discuss the agreements and deviations between simulation and experimental results which, on the one hand, shed light on limitations of the existing theory, and on the other hand, provide the first steps in a recipe for development of practical, high-field, efficiency-optimized THz sources.

Probabilistic modeling of 10-min mean wind speed and its application in analytical simulation of snowdrift on building roofs

The typical resolution for long-term wind speed records that are publicly available in China is daily, this is too coarse for a sound analytical simulation of snowdrift on building roofs. Take Harbin, China as an example, an algorithm was proposed in this study to address this issue, where the commonly-used 2-parameter Weibull distribution was applied to fit the distribution of 10-min mean wind speed. A parameter estimation method, which combines the method of moment and cumulative probability, was proposed to estimate the parameters of Weibull distribution using very limited information on wind speed. The fitted probability model was validated using high-resolution wind speed data by comparing the snowdrift estimated by the modeled wind speed and that estimated by the actual wind speed. Finally, an analytical simulation of snowdrift on a flat roof was carried out to illustrate the application of the proposed model, and the probabilistic characteristic of the derived ground-to-roof conversion factors for snow loads were analyzed. It is indicated that the proposed model is easy to implement and provides a good estimation of the snowdrift on building roofs, and the derived conversion factors could be satisfactorily modeled using a Generalized Extreme Value (GEV) distribution or a normal distribution.

Mathematical Modeling of Dynamic Supply Chains Subject to Demand Fluctuations

This research work aims to develop the mathematical modeling for a class of dynamic supply chains. Demand fluctuation corresponds to product demand volatility, which increases or decreases over a given time frame. Industrial engineering practitioners should consider the function that applied mathematical modeling plays in providing approximations of solutions that may be used in simulations and technical implementations at the strategic, tactical, and operational levels of an organization. In order to achieve proper results, two mathematical models are presented in this paper: In addition to a finite-dimensional system of Ordinary Differential Equations (ODEs) for coupled dynamic pricing, production rate, and inventory level, which properly integrates Lyapunov stability analysis of the dynamical system and simulations, there is an infinite-dimensional Partial Differential Equation (PDE) production level modeling system available. Infinite and finite-dimensional systems incorporate a dynamic pricing approach in the mathematical modeling. The main research goal of this work is to explore the dynamic nature of supply chains applying PDE and ODE methods, with proper analytical analysis and simulations for both systems.

Dark matter capture in celestial objects: treatment across kinematic and interaction regimes

Signatures of dark matter in celestial objects have become of increasing interest due to their powerful detection prospects. To test any of these signatures, the fundamental quantity needed is the rate in which dark matter is captured by celestial objects. Depending on whether dark matter is light, heavy, or comparable in mass to the celestial-body scattering targets, there are different considerations when calculating the capture rate. Furthermore, if dark matter has strong or weak interactions, the physical behaviour important for capture varies. Using both analytic approximations and simulations, we demonstrate how to treat dark matter capture in a range of celestial objects for arbitrary dark matter mass and interaction strength. We release our calculation framework as a public package available in both Python and Mathematica versions, called Asteria.

Sigma vector calculations in nodal aberration theory and experimental validation using a Cassegrain telescope

Nodal Aberration Theory (NAT) was developed to explain the field dependency of aberration field centers in the image plane of nominally rotationally symmetric optical systems that have lost their symmetry through misalignments. A new insight into the theory led to calculating the sigma vectors, which locate the aberration field centers, using the angle between a real-ray trace of the optical axis ray (OAR) and the normal of the local surface where “local” refers to the object and image optical spaces of that surface. Here, we detail the sigma vector calculations for general optical systems and provide an experimental investigation of a misaligned system with a high-precision customized Cassegrain telescope. In the simulations, a Newtonian telescope, a Cassegrain telescope, and a three-mirror anastigmat telescope were misaligned intentionally in ray-tracing software. The sigma vectors were calculated analytically for the third-order aberrations of astigmatism and coma. Experimentally, the same perturbations were implemented for the Cassegrain telescope system, and the aberrations were quantified through interferometric measurements on a grid of field points in the image plane that verified the analytical derivation and simulations.

Enhancing the Design Space of Bistable Laminates by Tailoring the Attachment Boundary Conditions

Abstract Bistable and multistable laminates are structural elements with more than one stable equilibrium configuration. The bistability makes them very interesting for the design of compliant mechanisms. However, these laminates are extremely sensitive to boundary conditions and attachment methods. It has been shown prior in the literature that restrictive boundary conditions can lead to the loss of bistability or unwanted deformation modes. This article develops attachment concepts that leverage the structural behavior changes caused by boundary conditions to expand the design space of bistable elements for structural applications. A systematic means of using the boundary conditions to improve the stability margins and load introduction of bistable tape springs is demonstrated. The stability margins and the achievable angles have been quantified using an analytical model previously developed by Guest and Pellegrino. Subsequently, high-fidelity finite element (FE) simulations are done in abaqus™ to determine the limits of the proposed method in terms of localization effects. Based on the analytical model and simulation outcomes, layup, size, and attachment points are determined, and two prototypes are fabricated, illustrating the effectiveness of the proposed method in expanding the design space of traditional bistable tape springs.

Galvanic Corrosion of Strands in Re-Grouted, Post-Tensioned Concrete Bridges

Grouted, post-tensioned (PTD) concrete systems are widely used to construct bridges, typically with an anticipated corrosion-free service life of 100+ y. However, the usage of inadequate grout materials and grouting practices in PTD concrete systems have caused unwanted air voids in ducts, leading to strand/grout/air interface, carbonation of exposed grout layer, and localized corrosion of strands (say, within about 10 y to 20 y). Re-grouting of voids as a tendon repair strategy has led to accelerated galvanic corrosion of the portion of strands at the interface between the carbonated base grout and repair grout with different chemistry, raising concerns and reluctance in re-grouting of voids in tendons. This work focused on understanding and quantifying the galvanic corrosion at the interface of carbonated base grout and repair grout in a re-grouted tendon. The theoretical analysis based on mixed potential theory estimated a galvanic current density of approximately 2 µA/cm2 and showed that the galvanic coupling can increase the corrosion current density of the prestressing steel in the base grout by about two-fold. The study on prestressed steel in simulated solutions estimated a galvanic current density of approximately 20 µA/cm2. Then, the study on prestressing steel in grouts and the analytical simulation estimated galvanic current densities around 1.5 µA/cm2 to 2 µA/cm2 at 95% external relative humidity (ERH) and 25°C. A model relating the galvanic current density in grouted systems as a function of ERH was developed, which showed an exponential increase in the galvanic corrosion with an increase in ERH. Also, a case study showed that if the tendon anchorage region experiences 95% ERH for about 20 y, sufficient strand corrosion could happen, and structural behavior can change from ductile to brittle nature, which could be a serious concern for structures in the coastal zone.