Small Systems Research Articles

A coupled-mode-theory formulation for periodic multi-element metasurfaces in the presence of radiation losses

We derive a coupled-mode theory (CMT) formulation for the fast analysis of periodic multi-element metasurfaces in the presence of radiation losses. Full-wave simulations of periodic multi-element metasurfaces are very time- and memory-consuming, especially as the size and complexity of the metasurface increase. The CMT formulation provides a considerably faster and efficient alternative. It results in a small system of equations with size equal to the number of supported resonator modes in the frequency range of interest, allowing to calculate the resonator mode amplitudes and, consequently, the metasurface response. Subsequently, we systematically derive analytical closed-form expressions for the coupling coefficients between two weakly coupled resonators in the presence of radiation losses and incorporate them into the CMT model, which is found important for the accurate description of the metasurface, while also providing insight into the underlying physics of complex metasurfaces. We validate the proposed formulation on benchmark examples of both metal- and dielectric-based metasurface absorbers (MSAs) by comparing the CMT results to spectral FEM simulations of the composing supercell. To further demonstrate the potential of the proposed formulation, as a proof of concept, we use the CMT to synthesize a larger optimized periodic multi-element MSA. A comprehensive comparison to full-wave FEM simulations of the composing supercell is included in terms of time and computational requirements, which shows that our method provides a valuable and efficient alternative solver for synthesizing complex metasurfaces.

Kardar-Parisi-Zhang universality in the coherence time of nonequilibrium one-dimensional quasicondensates.

We investigate the finite-size origin of the coherence time (or equivalently of its inverse, the emission linewidth) of a spatially extended, one-dimensional nonequilibrium condensate. We show that the well-known Schawlow-Townes scaling of laser theory, possibly including the Henry broadening factor, only holds for small system sizes, while in larger systems the linewidth displays a novel scaling determined by Kardar-Parisi-Zhang physics. This is shown to lead to an opposite dependence of the coherence time on the optical nonlinearity in the two cases. We then study how subuniversal properties of the phase dynamics such as the higher moments of the phase-phase correlator are affected by the finite size and discuss the relation between the field coherence and the exponential of the phase-phase correlator. We finally identify a configuration with enhanced open boundary conditions, which supports a spatially uniform steady state and facilitates experimental studies of the coherence time scaling.

Carbon neutrality strategy with small modular reactor-based hybrid energy system: A case study for a small Island and isolated power grid

As the threat of climate change intensifies, various efforts are being made to achieve carbon neutrality. Decarbonization across all industries, especially in the power generation sector, is a critical aspect to be considered. The introduction of renewable energy sources and an increase in their installed capacity in the power grid is essential to achieve carbon neutrality in the power generation sector. However, the expansion of renewable energy sources increases the vulnerability of the power grid due to their intermittent and variable characteristics and requires high levels of load-following performance from other power sources. In this study, we propose a hybrid energy system using nuclear (especially small modular reactors)-based hydrogen production, as an alternative solution for achieving carbon neutrality. The feasibility of the proposed hybrid energy system model was analyzed for the small Island isolated grid systems with simplified multi-physics simulation. The performance analysis results demonstrate that the proposed small modular reactor-hydrogen-based hybrid system can reliably meet grid demands while producing an annual surplus of 10,320.96 tons of hydrogen with reduced potential risk of thermo-mechanical-related component failures in the plant. The results of the current study can be expected to provide a significant milestone and insight into the achievement of carbon neutrality and a transition to a hydrogen economy, utilizing small modular reactor-based hydrogen production technology.

Nonlinear effect of rigidity and correlated disorder on network fracture

Mechanical rigidity and disorder are two important parameters that influence the failure process of solid materials. We investigate the nonlinear mechanics under their coupled effect as well as the influence of disorder’s spatial correlation with 2-D network model. The strain–stress relations present strong nonlinearity and rigidity regain phenomenon when there is strong disorder and high rigidity. The correlation of disorder would weaken the effect and has a great influence on the peak stress, initial stiffness, and system toughness. The crossover of power-law exponents of avalanches is observed with consideration of disorder and the transitions in the cluster distribution induced by correlated disorder disappear as the system rigidity decrease. We conclude that although the disorder can be seen as a reduction of average coordinated number for small rupture thresholds system, the correlated disorder still has a great influence on the failure behaviors of heterogeneous materials.

Experimental Study on the Influence of Air Conveyor System Parameters on Vibration of Glass Substrate

In this paper, the method of experimental research is used to minimize the micro-vibration amplitude of 0.6 mm thick glass substrates in the air conveyor system. The optimal parameter combination of the small orifice throttling glass substrate air conveyor system is obtained as follows: orifice diameter 0.25 mm, orifice spacing 60 mm and air-film thickness 50 μm. Secondly, based on the orthogonal experimental data, the influence of the main parameters of the air conveyor system at the micro vibration of the glass substrate is analyzed by variance analysis technology. The results show that the three principal parameters of the air conveyor system have significant influence on the vibration of the glass substrate. Among them, the thickness of the air-film has the greatest influence on the vibration of the glass substrate, the diameter of the orifice has the second influence, and the spacing of the orifice has the least influence. Finally, the influence of the three key parameters of orifice diameter, orifice spacing and film thickness on the micro vibration of glass substrate in the orifice throttling air flotation support system was studied and discussed, and the relationship curves between the maximum amplitude of micro-vibration of glass substrate and the main parameters of air flotation system were obtained.

Developing Uplink Power Optimization and ARS Selection Algorithm for Multi-ARS Small Cell Communication System

Small Cell (SC) models and unmanned aerial vehicles (UAVs) acting as aerial relay stations (ARSs) are both promising advancements in the development of upcoming wireless networks that contribute significantly to improving the overall service quality. In this work, we rely on the Multi-ARS Cell-Free (CF) model, where a large number of ARS coordinated by the ground base station (GBS) and cooperate to serve a large number of users within the same frequency and time resources, to develop the uplink of a multi-ARS SC system, in which each user is served by only one ARS. The time division duplex (TDD) mechanism is used for communication protocol, and the Minimum Mean Square Error (MMSE) method is implemented to estimate the uplink channel. We derive an closed-form expression for uplink user throughput. In addition, we introduce the ARS selection method based on channel conditions and propose the Bisection algorithm to optimize uplink power. The system performance is evaluated by the cumulative distribution function (CDF) of user throughput according to different parameters, such as changing the number of ARS, the number of users, the number of antennas, and the length of pilot sequences with/without power optimization. The results reveal that the ARS selection method is effectively resolved to reduce complexity and improve the practicality of the proposed system, and the power optimization problem for better throughput is non-optimization.

The performance of DST-Wavelet feature extraction for guitar chord recognition

Small systems can be designed to be more energy-efficient compared to larger systems. On small systems, the need for data processing with small data sizes becomes a necessity. In the context of small systems for guitar chord recognition, there are indications that further efforts can be made to reduce the size of feature extraction data. This paper introduces DST (Discrete Sine Transform)-Wavelet feature extraction to achieve this reduction. Basically, this work evaluated the frame blocking length, the number of DST cutting factors, and the type of wavelet filters (Daubechies and biorthogonal families) to obtain the optimal number of feature extraction data. Based on the evaluation, the optimal result obtained was a number of four feature extraction data. This optimal result was obtained by using a frame blocking length of 512 points, a DST cutting factor of 0.5, and a biorthogonal 3.3 wavelet filter. Testing with 140 test chords using these four feature extraction data could give an accuracy of up to 92.86%.

Design and realization of a small launch system with autonomous regulation and recognition guidance

A small launching system with autonomous regulation and recognition guidance is designed. Firstly, it ensures a solid and reliable transmission on the mechanical structure of the launcher and the small vehicle. Further, stepper motors and sensors are used to ensure precise control and effective feedback of the angle of the launcher. The small vehicle is equipped with the functions of guidance signal recognition and attitude adjustment, which have the advantages of strong real-time and high versatility. Finally, the practicality and accuracy of the designed launching system to a certain extent are verified through tests.

Modeling and Detection Scheme for Zero-Dynamics Attack on Wind Power System

In a wind farm, wind power system is key to maintaining continuous generation of point energy. Since Zero-Dynamics attack poses a major risk to future wind farms, investigation on the effect of Zero-Dynamics attack against wind power systems has both theoretical and practical importance. In this paper, we consider a scenario in which a wind power system is subject to Zero-Dynamics attack in power generation chain. Firstly, we transform a semi-direct D-PMSG into an equivalent circuit to establish mathematical model of wind power system under Zero-Dynamics attack. Then, we analyze and prove the advantages and limitations of Zero-Dynamics attack by divide the equation of state into a stable part and an unstable part with the help of system relative degree ρ. In addition, to better achieve desired attack effect, adjustments are made for Zero-Dynamics attack based on its limitations. Finally, we combine an Multiple Linear Regression (MRL) predictive control model with Byrnes-Isidori normal form to protect wind power system. The theoretical results were verified on designed small wind power system.

Continuous A-Mode Ultrasound-Based Prediction of Transfemoral Amputee Prosthesis Kinematics Across Different Ambulation Tasks.

Volitional control systems for powered prostheses require the detection of user intent to operate in real life scenarios. Ambulation mode classification has been proposed to address this issue. However, these approaches introduce discrete labels to the otherwise continuous task that is ambulation. An alternative approach is to provide users with direct, voluntary control of the powered prosthesis motion. Surface electromyography (EMG) sensors have been proposed for this task, but poor signal-to-noise ratios and crosstalk from neighboring muscles limit performance. B-mode ultrasound can address some of these issues at the cost of reduced clinical viability due to the substantial increase in size, weight, and cost. Thus, there is an unmet need for a lightweight, portable neural system that can effectively detect the movement intention of individuals with lower-limb amputation. In this study, we show that a small and lightweight A-mode ultrasound system can continuously predict prosthesis joint kinematics in seven individuals with transfemoral amputation across different ambulation tasks. Features from the A-mode ultrasound signals were mapped to the user's prosthesis kinematics via an artificial neural network. Predictions on testing ambulation circuit trials resulted in a mean normalized RMSE across different ambulation modes of 8.7 ± 3.1%, 4.6 ± 2.5%, 7.2 ± 1.8%, and 4.6 ± 2.4% for knee position, knee velocity, ankle position, and ankle velocity, respectively. This study lays the foundation for future applications of A-mode ultrasound for volitional control of powered prostheses during a variety of daily ambulation tasks.

Autonomous Emergency Landing for Fixed-Wing Aircraft with Energy-Constrained Closed-Loop Prediction

This paper presents a new approach for autonomous motion planning for aircraft suffering from a loss-of-thrust emergency. Specifically, we show how modifications to the Closed-Loop Rapidly exploring Random Trees (CL-RRT) framework combined with controlled energy dissipation can enable rapid and effective kinodynamic motion planning. This CL-RRT Glide algorithm uses closed-loop prediction not only for node connections but also to estimate the remaining energy and prune infeasible paths. This greatly speeds up the search process, which is essential for emergency situations. In addition, we improve the ability of the gliding aircraft to reach a goal position and energy state. We do so by creating a Dissipative Total Energy Control Scheme (TECS). Dissipative TECS enables the glider to lose excess altitude in order to reach a desired energy level. Simulation results illustrate how the proposed methods enable faster motion planning. We also integrate the system into a small unmanned aerial vehicle system and experimentally demonstrate autonomous glide planning and execution during a motor-failure event. This type of algorithm can primarily benefit unmanned aircraft but can also serve to assist pilots in stressful emergency situations.

Explosive Growth of Image Sensors in Smart Government Technology and Economic Scale

CMOS image sensor is a rapidly developing image sensor product in the past decade. Relying on the advantages of process compatibility with standard CMOS process, CMOS image sensor integrates analog photoelectric photosensitive circuit and digital signal processing circuit to become a small and powerful system on chip. This article mainly studies the explosive growth of image sensors in smart government technology and economic scale. The main purpose of this article is to study the technical application of image sensors, reduce the administrative cost of social governance, improve the level of government governance, benefit the public, and realize the requirements of smart government affairs and rapid economic development of the city. This study tested the static performance of the analog-to-digital conversion circuit by inputting a limited number of sampling points, and its integral nonlinearity and differential nonlinearity were both less than 1LSB. The bandgap reference circuit provides a reference level for the entire system. It uses two PNP-type bipolar transistors parasitic in the CMOS process to achieve a temperature and voltage-independent bandgap reference voltage through the feedback of the operational amplifier. It is ideal for use In the case of resistance simulation, its accuracy reaches 16.6ppm. The scanning method of the pixel array uses multi-sampling technology to increase the dynamic range of the sensor by 2N times. The correlated sub-sampling technology eliminates the fixed pattern noise between pixel units. The use of pipelined analog-to-digital converters can achieve good resolution, speed and area compromise.Through the realization and simulation of transistor-level circuits, the performance of each part of the system meets the requirements of design and application.

Insight into the light-flavour particle production mechanism from studies of the transverse spherocity dependence in pp collisions at √s =13 TeV with ALICE at the LHC

The Large Hadron Collider (LHC) Run 1 and Run 2 data revealed heavy-ion-like features such as enhanced strangeness production and long-range azimuthal correlation in high-multiplicity pp collisions paving the way to rethink particle production in small collision systems. Event shape observables like transverse spherocity are sensitive to isotropic and jet-like topologies, which are useful tools to distinguish the pp collisions dominated by soft or hard physics. The interplay between multiplicity and transverse spherocity on light-flavour particle production can be understood by comparing the results obtained by selecting multiplicity and/or transverse spherocity. This contribution presents recent results on light-flavour particle production (π, K, p, ф, K*0, K0s, Λ, ξ) at midrapidity obtained by the ALICE experiment in pp collisions at √s = 13 TeV as a function of event multiplicities and transverse spherocity. The results are even obtained by going to the most extreme selections such as the highest 0–1% in multiplicity and the highest 0–10% in transverse sphe rocity. The results include the transverse momentum spectra, yields, 〈pT〉 and their ratios. These measurements will be compared with the Monte Carlo (MC) predictions obtained from models such as PYTHIA8, EPOS and Herwig7.

Graph Learning-Based Voltage Regulation in Distribution Networks With Multi-Microgrids

Microgrids (MGs), as localized small power systems, can effectively provide voltage regulation services for distribution networks by integrating and managing various distributed energy resources. Existing literature employs model-based optimization approaches to formulate the voltage regulation problem of multi-MGs, which require complete system models. However, this assumption is normally impractical due to time-varying environment and privacy issues. To fill this research gap, this paper suggests a data-driven decentralized framework for the cost-effective voltage regulation of a distribution network with multi-MGs. A novel multi-agent reinforcement learning method featuring an augmented graph convolutional network and a proximal policy optimization algorithm is proposed to solve this problem. Furthermore, the techniques of critical bus and electrical distance enhance the capability of feature extractions from the distribution network, allowing for the decentralized training with privacy preserving. Simulation results based on modified IEEE 33-bus, 69-bus, and 123-bus networks are developed to validate the effectiveness of the proposed method in enabling multi-MGs to provide distribution network voltage regulation.

Do Information Systems Today Play a Strategic Role in Business?

An information system is a combination of software, hardware, and telecommunication networks to collect useful data, especially in an organisation. Many businesses use information technology to complete and manage their operations, interact with their consumers, and stay ahead of their competition. The purpose of this study is to analyze and investigate the strategic role of information systems in modern enterprises. We analyzes the components of information systems and their overall functions, as well as the importance of keeping the information system and organizational strategy aligned. By analyzing the influence of digital connection on enterprises, this paper expounds the adoption of information system in enterprises. We analyze the reasons why information systems have a significant impact on organizational operations, and the goals of an enterprise's adoption of information systems. The relationship between proper information system and improving the efficiency of company operation is analyzed. In business operation, small and medium-sized enterprises regard information system as a priority, and the impact of strategic information system on enterprises. From the above, we conclude the value of information systems in contemporary enterprises, increasing productivity, reducing resource use, and making data collection more efficient.

Online Monitoring of Oscillation Modes for Small-Signal Security Assessment

This paper presents the main concepts of small-signal security assessment of power systems, focusing on the online monitoring of small-signal stability. In this work, a computational tool for online monitoring of oscillation modes (OLMO) in power systems is proposed. The objective of the methodology consists of determining small-signal stability margins, security levels, and corrective measures that can improve the damping factor of oscillation modes present in such systems. These corrective measures can be associated with possible redispatches of power plants. In this context, the Closest Security Boundary for Generation Redispatch using Eigenvalue Sensitivities, known as CSBGRES Method, could be applied to determine an optimized redispatch for the power plants of the system to ensure a desired minimum damping factor, previously chosen, for oscillation modes. The proposed tool can be applied for controlling power plant dispatches on Smart Grids, focusing on the damping factor of oscillation modes. A small test system is used to evaluate the proposed computational feature and the results were presented to demonstrate its importance to power system security. Results of the utilization of OLMO on the Brazilian Interconnected Power System (BIPS) are presented to prove the viability of using this method in large-scale power systems.

A Versatile Calibration Method for Rotary-Wing UAS as Wind Measurement Systems

Abstract The use of small uncrewed aircraft systems (UAS) can effectively capture the wind profile in the lower atmospheric boundary layer. This study presents a calibration process to estimate the horizontal wind vector using a rotary-wing UAS in hovering conditions. This procedure does not require wind tunnels or meteorological masts, only the data from the flight control unit and a specific set of calibration flights. A model based on the UAS drag coefficient was proposed and compared to a traditional approach. Validation flights at the German Weather Service MOL-RAO observatory showed that the system can accurately predict wind speed and direction. A modified DJI S900 hexacopter with a Styrofoam sphere casing was used for the study and calibrated for wind speeds between 1 and 14 m s−1. Power spectral density analysis showed the system’s ability to resolve atmospheric eddies up to 0.1 Hz. The overall root-mean-square error was less than 0.7 m s−1 for wind speed and less than 8° for wind direction.

Signature of topology via heat transfer analysis in the Su–Schrieffer–Heeger (SSH) model

In this work, we explore how thermodynamics can be a potential tool for identifying the topological phase transition. Specifically, we focus on a one-dimensional Su–Schrieffer–Heeger (SSH) chain sandwiched between two fermionic baths. To investigate distinctive thermodynamic signatures associated with the topological phase, we employ heat flow analysis. Our results, derived using a global master equation, unveil a significant suppression of heat flow as we transition from the trivial to the topological phase. This decline in heat flow can be attributed to the reduction in transmission coefficients of non-zero energy modes within the topological phase. It may serve as an indicator of a phase transition. Furthermore, we investigate the heat flow asymmetry to search for phase transition indicators. Interestingly, no asymmetry is observed when employing fermionic baths. However, upon substituting fermionic baths with bosonic ones, we report a non-zero heat flow asymmetry. For SSH model with few fermionic sites, this asymmetry is more pronounced in the topological phase compared to the trivial phase. Therefore, the observed behavior of the heat diode provides an additional means of distinguishing between the topological and trivial phases. Finally, we delve into the contributions from both bulk and edge effects in heat flow and rectification to explore the impact of small system sizes on our findings.

Momentum budget analysis of maintenance of Arabian Sea tropical cyclone Ockhi

In this study an effort is done to explain the maintenance of the Very Severe Cyclonic Storm(VSCS) Ockhi using the angular momentum(AM) budget technique . The AM budget equation for a region bounded by , to and to in (x,y,p,t) co-ordinate system is used from an earlier study. The different terms are explained with relative importance. This technique is used to the diagnosis of different small, medium and large weather systems by several authors. The Very Severe Cyclonic Storm(VSCS) Ockhi –a rare situation in Arabian Sea – is studied with a reanalyzed dataset in a fine mesh width. The values of different terms in the AM budget equation are calculated for pressure levels-1000,800,500,200,100hpa’s and for four day periods viz. 30 Nov ,01 Dec ,02 Dec and 03 Dec 2017 .The AM budget was prepared for the eight observation time periods of 00, 03,06,09,12,15,18,21 UTC for each day. The area selected is 5.04N - 19.2N, 60E- 77E where VSCS TC Ockhi formed.The sink and source terms are compared and the results are correlated with the help of charts . The NCMRWF IMDAA data set is used and the results are depicted in charts and results are compared with the observed synoptic behavior of the system .
 Keywords: - Angular Momentum Budget, Equation, Source/Sink terms,
 VSCS Ockhi-Diagnosis

Surrogate indirect adaptive controller tuning based on polynomial response surface method and bioinspired optimization: Application to the brushless direct current motor controller

The increment of autonomous systems has stimulated the research of new controller tuning techniques to face the unpredictable disturbances and parametric uncertainties inherent in any autonomous system that affect its performance. The indirect adaptive controller tuning approach based on the general dynamic model (IACTA-GDM) and bioinspired optimization is one of the most successful elections facing parametric uncertainties and disturbances, which are intricate to handle by other controller tuning techniques. However, this controller tuning approach is limited by the complexity of the dynamic model due to the computational burden, restricting its application to relatively small systems or systems with slow responses where the tuning is updated at large time intervals. The present work proposes a novel surrogate indirect adaptive controller tuning approach based on the response surface method (SIACTA-RSM) to address computational burden limitations. The proposal is tested on the speed regulation controller of a brushless direct current motor, with the aim of reducing the speed regulation error and the control system’s power consumption. The closed-loop system performance and the required computational time obtained by the proposed SIACTA-RSM are compared to the ones of a well-established IACTA-GDM. The descriptive and inferential statistics, as well as graphical comparisons, show that the system performance obtained by the SIACTA-RSM proposal is as competitive as the IACTA-GDM approach, keeping a mean difference among the results by up to 3.18% while reducing the computational burden of IACTA-GDM by up to 90%. These outcomes show that the SIACTA-RSM proposal is a reliable alternative to overcome the computational burden limitations that affect the IACTA-GDM approach while maintaining competitive performance.