Numerical Measurements Research Articles

Space- and frequency-division multiplexing in photonic second-order topological insulators

Higher-order topological insulators, originally proposed in quantum condensed matters, have provided a new avenue for localizing and transmitting light in photonic devices. Nontrivial band topology in crystals with certain symmetries can host robust topological edge states and lower dimensional topological corner states (TCS), making them a promising platform for photonics applications. Here, we have designed several types of TCS with only two specific C6v-symmetric photonic crystals with various seamless splicing boundaries, where all the supposed TCS with diverse electromagnetic characteristics are visualized via numerical simulations and experimental measurements. More interestingly, we have observed that those TCS overlapping in spectral and spatial space tend to interweaved, inducing spectrum division. Meanwhile, the equivalent corners appear to have TCS with a phase difference, which is critical for directional activation of pseudospin dependence. Our findings demonstrate that coupled TCS with phase difference at different nanocavities can be selectively excited by a chiral source, which indicates that the TCS at this time have pseudospin-dependent properties. We further design a specific splicing structure to prevent coupling between adjacent TCS. This work provides a flexible approach for space- and frequency-division multiplexing in photonic devices.

Numerical modelling and measurement of the E-I characteristics of MgB2 wire in sub-cooled water ice

This work presents a comprehensive 3D numerical model of MgB2 multi-filamentary superconducting wires using the Finite Element Method (FEM) software, COMSOL Multiphysics® 6.0. The study aims to investigate the electro-thermal behavior of MgB2 composite wires during standard transport measurements at various initial temperatures under subcooled water ice conditions. By solving a series of partial differential equations governing heat transfer and dynamic current transport, the model provides detailed insights into the wire’s performance. The simulation results are rigorously compared with experimental E-I characteristics measured for 6-filament MgB2 wires with internal copper stabilization. This comparison validates the model and highlights its capability to predict the behavior of superconducting wires under cryogenic conditions. The findings offer valuable data on the current distribution, ohmic losses, and overall thermal stability of the composite wires, contributing to the advancement of cryogen-free superconducting technologies. This study bridges the gap in the literature regarding the electrothermal dynamics of MgB2 wires cooled by subcooled water ice, providing a foundation for further research and practical applications in high-field generation devices.

Harmonic analysis of nonstationary signals with application to LHC beam measurements

Harmonic analysis has provided powerful tools to accurately determine the tune from turn-by-turn data originating from numerical simulations or beam measurements in circular accelerators and storage rings. Methods that have been developed since the 1990s are suitable for stationary signals, i.e., time series whose properties do not vary with time and are represented by stationary signals. However, it is common experience that accelerator physics is a rich source of time series in which the signal amplitude varies over time. Furthermore, the properties of the amplitude variation of the signal often contain essential information about the phenomena under consideration. In this paper, a novel approach is presented, suitable for determining the tune of a nonstationary signal, which is based on the use of the Hilbert transform. The accuracy of the proposed methods is assessed in detail, and an application to the analysis of beam data collected at the CERN Large Hadron Collider is presented and discussed in detail. Published by the American Physical Society 2024

Heat Conduction Control Using Deep Q-Learning Approach with Physics-Informed Neural Networks

As modern systems become more complex, their control strategy no longer relies only on measurement data from probes; it also requires information from mathematical models for non-measurable places. On the other hand, those mathematical models can lead to unbearable computation times due to their own complexity, making the control process non-viable. To overcome this problem, it is possible to implement any kind of surrogate model that enables the computation of such estimates within an acceptable time frame, which allows for making decisions. Using a Physics-Informed Neural Network as a surrogate model, it is possible to compute the temperature distribution at each time step, replacing the need for running direct numerical simulations. This approach enables the use of a Deep Reinforcement Learning algorithm to train a control strategy. On this work, we considered a one-dimensional heat conduction problem, in which temperature distribution feeds a control system. Such control system has the objective of reacing and maintaining constant temperature value at a specific location of the 1D problem by activating a heat source; the desired location somehow cannot be directly measured so, the PINN approach allows to estimate its temperature with a minimum computational workload. With this approach, the control training becomes much faster without the need of performing numerical simulations or laboratory measurements.

Bifunctional acoustic lossy coupler for broadband power splitting and absorption

In this work, we propose a bifunctional acoustic lossy coupler for broadband power splitting and absorption. Following the three-level system in quantum physics, the three-waveguide (WG) acoustic system is proposed to obtain efficient energy transfer behaviors. Given the agreement in form between Schr o¨ dinger equation and coupled mode equation, the time-dependent external fields are mapped into space-varying coupling actions between adjacent WGs. The propagation paths of the incident waves can be predicted by Schr o¨ dinger-like equation, which are verified by numerical simulations and experimental measurements. Owing to the different responses to lossy medium in WG B for WG A incidence and WG C incidence, the acoustic coupler can be considered as a broadband power splitter and muffler by selecting different input ports. Meanwhile, according to the reversibility of acoustic path, a switchable acoustic logic gate with functions of “OR” and “XOR” is constructed as well by taking advantage of the lossless adiabatic coupler, and the function can be controlled conveniently by reversing the phase of input waves from WG A or C. Our work provides a new scheme for the design of bifunctional acoustic coupler, which may have a profound impact on the development of non-resonance acoustic high-performance devices.

Influence of Damping Plate Size on Pitch Motion Response of Floating Offshore Wind Turbine

For floating offshore wind turbines, a significant pitch and roll motion response of the platform can affect the acceleration and power generation of the nacelle. The damping plate is considered a type of attachment that can be used to reduce rotational motion, but research on its anti-rotational effect is limited. The objective of this work is to analyze the impact of installing damping plates and varying their sizes on the pitch motion response of semi-submersible platforms, while also proposing optimization strategies for damping plate design. Firstly, a comparison between numerical simulations and experimental measurements validates the accuracy of the CFD calculations. Subsequently, different sizes of damping plates are proposed for the platforms, followed by simulations under various conditions. Finally, comprehensive data analysis is conducted. The findings suggest that installing damping plates enhances both the platform’s added moment of inertia and damping coefficients while simultaneously amplifying its motion response in regular waves. Furthermore, increasing the size of damping plates leads to an increase in both the added moment of inertia and motion response for the platform, whereas the damping coefficient exhibits an initial increasing trend followed by a subsequent decrease. Ultimately, it is found that increasing the distance between damping plates and the free surface significantly reduces wave-induced loads on the platform.

Chaotic systems based on higher-order oscillatory equations

This paper discusses the design process toward new lumped chaotic systems that originates in higher-order ordinary differential equations commonly used as description of ideal oscillators. In investigated third-order case, two chaotic oscillators were constructed. These systems are dual in the sense of vector field geometry local to fixed points. The existence of robust chaos was proved by both standard routines of numerical analysis and practical measurement. For the fourth-order oscillatory equation, the concept based on interaction between superinductor and supercapacitor was examined in detail. Since both “superelements” are active, the nonlinearity essential to the evolution of chaos is fully passive. It is demonstrated that complex motion is robust and does not represent long transient behavior or numerical artefact. The existence of chaos was verified using standard quantifiers of the flow, such as the largest Lyapunov exponents, recurrence plots, approximate entropy and sensitivity calculation. A good final agreement between theoretical assumptions and practical results will be concluded, on a visual comparison basis.

Study on Wind Farm Flow Field Characteristics Based on Boundary Condition Optimization of Complex Mountain Numerical Simulation

The accurate prediction of the flow field characteristics of complex mountains is of great practical significance for the development and construction of wind farms, but it is not yet fully understood. The main purpose of this study is to propose a method for the study of flow field characteristics under complex mountain conditions, which can optimize the boundary conditions required for numerical simulation through the wind acceleration ratio and, at the same time, couple the numerical simulation and wind measurement data to reflect the real mountain flow field distribution. The results show that the proposed method has good applicability in complex mountain wind farms, can reproduce the real flow field distribution, and has a certain practical value. Wind speed distribution and turbulence intensity are greatly affected by boundary conditions such as wind speed and wind direction and are also affected by the shielding effect brought by terrain changes. The contrast between 120° and 150° wind direction is more obvious. When the incoming wind moves to the top of a mountain or the ridgeline, it will form a low-speed wake area behind it, resulting in reduced wind speed, increased turbulence intensity, and an unstable flow field.

Numerical simulation and measurements on reduced scale structures of floating production storage and offloading units

Protecting offshore structures against the effects of lightning strikes, sparks, and short circuits is a considerable challenge to designers and deployment engineers once the numerous exposed structures, pieces of equipment, and devices make the behavior of electromagnetic phenomena difficult to predict. Numerical simulations are important tools to predict such behavior. However, due to the uncertainties involved, they should be compared against laboratory results. This paper presents the results of the measurements performed on three scaled models and compares them to those obtained with two different applications, CST Studio Suite and NEC-4. We elaborate hypotheses regarding the differences between laboratory results and those obtained using simulation software. As an application, after validating modeling techniques, the paper discusses the results of induction on cable loops on “gooseneck” chimneys commonly used in ships and floating production storage and offloading units.

Numerical Study on the Summer High-Temperature Climate Adaptation of Traditional Dwellings in the Western Plains of Sichuan, China

Ongoing global climate change, marked by sustained warming and extreme weather events, poses a severe threat to both the Earth’s ecosystems and human communities. Traditional settlements that underwent natural selection and evolution developed a unique set of features to adapt to and regulate the local climate. A comprehensive exploration of the spatial patterns and mechanisms of the adaptation of these traditional settlements is crucial for investigating low-energy climate adaptation theories and methods as well as enhancing the comfort of future human habitats. This study used numerical simulations and field measurements to investigate the air temperature, relative humidity, wind speed, wind direction, and thermal comfort of traditional settlements in Western Sichuan Plain, China, and uncovered their climate suitability characteristics to determine the impact mechanisms of landscape element configurations (building height, building density, tree coverage, and tree position) and spatial patterns on microclimates within these settlements. The results revealed the structural and layout strategies adopted by traditional settlements to adapt to different climatic conditions, providing valuable insights for future rural protection and planning and enhancing climate resilience through natural means. These findings not only contribute to understanding the climate adaptability of Earth’s ecosystems and traditional settlements but also offer new theories and methods to address the challenges posed by climate change.

Predicting Financial Fraud through Pressure, Opportunity, Rationalization and Internal Control (Case Study on Food and Beverage Companies Listed on the IDX)

The Empirical Study of Food and Beverage Companies Listed on the Indonesia Stock Exchange in 2017-2019 aims to explain and forecast the impact of pressure, opportunity, rationalization, and internal control on financial statements that are false. Because it stresses verifying theories using numerical measurements of research variables and statistical data analysis, this study takes a quantitative approach. The study's population consisted of 18 companies that were listed in the food and beverage sub-sector between 2013 and 2017 and were part of the Indonesia Stock Exchange (IDX). Multiple linear regression analysis, often known as multiple regression, is the analysis model that is used to examine how the independent variables affect the dependent variable. The analysis's findings demonstrate how pressure, opportunity, rationalization, and internal control all significantly impact financial statement fraud at the same time. Internal control has little impact on fake financial statements, while pressure, opportunity, and rationalization all have a considerable impact.

Accuracy of Green Bond Issuance Predictor

Climate change is affecting the development of many industries in different aspects. These impacted enterprises transform into sustainable enterprises to avoid the risks, and by doing so they enter into the green bond market. The current literature provides effective reference indicators for participants in the green bond market. These indicators illustrate the funding size of the green bonds in different dimensions to the participants. As for the improvement of the policies about environmental protection there also emerge some new indicators such as ESG score. Besides, machine learning is an accurate and effective tool in many fields, and some researchers have established a model for predicting the issuance of green bonds but have not involved the new indicators in the past. In this paper, on the one hand, we discuss the new indicator, ESG scores, and how it affects the funding size of the green bonds, on the other hand, we add this new indicator and the old indicators into four machine learning models to compare the accuracy of predicting the issuance of green bonds of these four models. In these four models, the Random Forest Regressor and LGBM Regressor are the best models on average. The former has the best performance of accuracy but needs much more time than the latter. On the opposite, the latter is the most efficient model among all but is the second most accurate. Besides, other models have the best numerical measurements in different dimensions which means we could use different models depending on different situations. Choosing the proper model for the specific situation can optimize the benefit of the green bond market participant.

Numerical and Experimental Approach to Evaluate Microplastic Transport in Saturated Porous Media

Under varying flow rate conditions, the transport and retention of polydisperse microplastics (MPls), with an average particle size of 16 ± 6 µm, were investigated in saturated porous media. First-order reversible and irreversible kinetic sorption models were used to describe the sorption kinetics. Sensitivity analyses provided insight into the effects of each sorption parameter. Both numerical modeling and experimental measurements were utilized to evaluate the retention rates of sand filters. The influence of flow rate on sorption was reflected in variations in the distribution coefficient (Kd), the mass transfer coefficient (β), and the irreversible sorption rate (K1). Lower flow rates were associated with higher Kd and β values, indicating increased sorption and reduced mass transfer rates. An increase in Kd resulted in a more gradual sorption process, with a decrease in peak concentration, whereas changes in β had a comparatively smaller impact on sorption rate and peak concentration. Lower K1 values were linked to higher peak concentrations and decreased retention efficiency. Numerical modeling revealed retention rates of 28 ± 1% at a flow rate of 31 mL min−1 and 17 ± 1% at 65 mL min−1. The introduction of MPls into saturated sand environments modifies the transport dynamics within the medium. Consequently, these alterations affect the hydrological characteristics of porous media, impacting groundwater quality and agricultural output. The mean absolute error (MAE) of 6% between the modeled and observed retention rates indicated a high level of accuracy. This study underscores the importance of examining retention efficiency and the accuracy of numerical models in understanding MPl transport in porous media.

Using Wind Energy to Carry out Basketball Special Physical Fitness Training—Calculation and Research on Aerodynamic Efficiency of Integrated Wind Turbine in Stadiums and Gymnasiums

This study investigates the feasibility of using wind energy for basketball special physical fitness training by combining wind turbines in stadiums and gyms. The investigation focuses on measuring the aerodynamic efficiencies of the combined wind turbine systems. It starts with an analysis of wind energy utilization for fitness training, which signifies the potential benefit of harnessing the renewable energy in sports facilities. The investigation into the aerodynamic efficiency of the combined wind turbine systems, considers factors such as speed of wind, size of turbine, and energy output. Numerical simulation and measurements are conducted to determine the optimal design and placement of wind turbines in stadiums and gymnasiums. The results demonstrate the potential of wind energy to supplement traditional power sources in sports facilities, and provide sustainable energy solutions while boosting fitness and environmental awareness. The study reveals that with an average speed of 8 m/s, a properly integrated wind turbine system in a stadium or gymnasium can generate approximately 11-23% of the facility's electricity demand. This translates to an annual energy production of 510-1200 kWh per turbine, depending on the specific location and design considerations. The aerodynamic efficacy of the integrated wind turbine system is estimated to be around 40-50%, indicating a significant potential for energy savings and environmental impact reduction.

Hardware-in-the-Loop experiments in model ice for analysis of ice-induced vibrations of offshore structures

The study investigated the use of a Hardware-in-the-Loop (HiL) technique applied in model ice experiments to enable the analysis of offshore structures with low natural frequencies under dynamic ice loading. Traditional approaches were limited by facility capacities and ineffective downscaling of the geometry of the offshore structures. The goal of the present study was to overcome these challenges and to enhance the understanding and explore the applicability of a hybrid testing technique in model ice experiments. To achieve the objective, 204 Hardware-in-the-Loop simulations in model Ice (HiLI) were analyzed. Results showed robust behavior and good performance of the HiLI due to minimal variation in measured delay, normalized root mean square error, and peak tracking error and low magnitudes of such parameters despite alterations in factors such as the choice of the numerical structural model, physical prototype, measurement system, and ice type. Notably, the performance of the HiLI was affected when testing with warm model ice or scaling for harsh ice conditions, attributed to a reduced signal-to-noise ratio and instability of the system, respectively. Experimental identification of the critical delay, along with the application of an analytical stability criterion, revealed that the instability observed, was likely induced by reducing the structural stiffness of the numerical structural model to fulfil the scaling requirements when testing for harsh ice conditions. Additionally, the study showed improved HiLI performance when the physical prototype was in contact with the model ice. This observation was further analyzed and is assumed to be caused by the coupling between the ice and physical prototype, causing a coupled and thus increased eigenfrequency of the physical prototype-ice system.

Components of Mathematical Language and Mathematical Ability in 5-Year-Old Dual Language Learners

ABSTRACT A growing body of research suggests that children’s understanding of mathematical language is critical for their mathematical abilities. Most of this work has been restricted to single language learners (i.e., SLLs), and used dual language learners (i.e., DLLs) as an exclusion criterion, raising questions about the generalizability of these findings to DLLs. This is particularly important given the observed differences in the association between general language and mathematics for DLLs as compared to SLLs. In our study, conducted in Belgium, we therefore investigated the associations between components of mathematical language and different mathematical abilities in 75 DLLs and compared them to 75 age- and sex-matched SLLs (M age = 4 years 8 months; 33 females in each group). Unfortunately, the two groups could not be matched on socioeconomic status (i.e., SES), and SES-levels of the parents of DLLs were significantly lower than SES-levels of SLLs. We assessed children’s quantitative and spatial language, their mathematical abilities (numerical competencies, geometry, and measurement), as well as their general vocabulary and spatial skills. All children, including DLLs, were only tested in the language of instruction (i.e., Dutch) in which DLLs exhibited varying levels of proficiency. Results revealed that DLLs obtained lower scores than SLLs in quantitative and spatial language, mathematical abilities, general vocabulary, but not in spatial skills. Associations between components of mathematical language and mathematical abilities were similar across DLLs and SLLs, except for the relation between spatial language and geometry, which was weaker in DLLs.

Research on Key Parameters for Relieving Pressure on Roofs of Deep Mine Cutting and Retaining Roadways

Scientific and reasonable roof-cutting parameters are key to ensuring pressure relief of the retained roadway roof. This manuscript takes the 7135 working face of Qidong Coal Mine as the engineering background and uses theoretical analysis, numerical and on-site measurement methods to study the quantitative relationship and pressure relief effect between different roof-cutting parameters of GERRC. We established a fracture criterion based on the tensile strength of the main roof of the uncut joint along the cutting line. We analyzed the quantitative relationship between different main roof thickness, cutting height, cutting angle, and the main roof tensile stress of the uncut joint. We found that within a small range of cutting angles, as the cutting angle decreases, the tensile stress on the main roof of the uncut joint increases. When the cutting angle is 0, the main roof tensile stress of the uncut joint reaches its maximum. As the cutting height increases, the limitation of the cutting angle on the cutting height becomes smaller. Numerical simulation was conducted to study the distribution patterns of maximum and minimum principal stresses along the direction of the roadway roof during the retention period under different roof-cutting heights and angles. Based on this, the optimal unloading effect of the roadway roof and the minimum concentration of mining stress were obtained at a roof-cutting height of 9 m and a roof-cutting angle of 80°. Through on-site measurement of the stress on the reinforcement anchor cable during the retention period, the deformation of the sinking roadway roof, and the pressure relief control effect of the retained roadway roof, the pressure relief effect and scientific rationality of the design of the cutting height and cutting angle were verified.

Large-eddy simulation of vortex interaction in pitching-fixed tandem airfoils

In this study, the interaction of vortices generated from an oscillating airfoil with a hindfoil placed downstream of the oscillating forefoil at low-Reynolds-number flow was investigated numerically. The forefoil entered a deep dynamic stall induced by large-amplitude pitching oscillation. The dynamic stall process is characterized by unsteady separation and the formation of a strong clockwise vortex. A wall-resolved large-eddy simulation approach was applied to compute the flowfield. The numerical measurements were performed for an incompressible flow at a Reynolds number of Re = 30 000 based on chord length with a pitching reduced frequency of K= 0.5, and amplitude of A = 14.1° over Selig–Donovan 7003 airfoils. A single-airfoil case was validated against numerical and experimental measurements. In the present study, we investigated the flowfield and aerodynamic coefficients resulting from the deep dynamic stall of the pitching forefoil and the vortex interaction in tandem-airfoil configuration related to micro-air vehicle applications by employing large-eddy simulation approach. Large-eddy simulation was also compared to two-dimensional unsteady Reynolds-averaged Navier–Stokes simulation to determine the accuracy and validity of the low-fidelity approach in prediction of deep dynamic stall and vortex interaction at low-Reynolds-number flow.

Emotional Experience On E Wom Swiss Bell Silae Hotel In Palu City, Central Sulawesi

Service Quality (SQ), Customer Satisfaction (CS), and Positive Emotional Experience (PEE) have the effect of increasing the positive eWOM of hotel visits. Positive eWOM is a review of the experience felt by consumers who have had a good experience after staying at a hotel. The aim of the research is to test whether Service Quality, Customer Satisfaction (CS), and Positive Emotional Experience, have an influence on increasing positive eWOM visits to Swiss Bel Hotel Silae Palu, based on the Traveloka hotel reservation application site. The aim of the research is the influence of customer satisfaction on eWOM Swiss Bel Hotel Silae Palu. identify the influence of service quality on eWOM of Swiss Bel Hotel Silae Palu. What is the influence of positive emotional experience on eWOM Swiss Bel Hotel Silae Palu. Service quality is important for companies facing competition in the market, satisfying consumer needs and desires, paying attention to service quality (Maulana, 2016). Using quantitative uses numerical measurements. The influence of the Independent Variable on the Dependent Variable is concluded, Customer Satisfaction of the Swiss Bell Silae Hotel in Palu City, has a significant influence on the eWOM of the Swiss Bell Silae Hotel in Palu City. Service Quality provided by the Swiss Bell Silae Hotel in Palu City has a significant influence on the eWOM of the Swiss Bell Silae Hotel in Palu City, Positive Emotional Experience of Swiss Bell Silae Hotel customers in Palu City has a significant influence on Customer Satisfaction of the Swiss Bell Silae Hotel in Palu City. Positive Emotional Experience of Swiss Bell Silae Hotel customers in Palu City has a significant influence on the eWOM of Swiss Bell Silae Hotel in Palu City.

Hybrid Twins Modeling of a High-Level Radioactive Waste Cell Demonstrator for Long-Term Temperature Monitoring and Forecasting.

Monitoring a deep geological repository for radioactive waste during the operational phases relies on a combination of fit-for-purpose numerical simulations and online sensor measurements, both producing complementary massive data, which can then be compared to predict reliable and integrated information (e.g., in a digital twin) reflecting the actual physical evolution of the installation over the long term (i.e., a century), the ultimate objective being to assess that the repository components/processes are effectively following the expected trajectory towards the closure phase. Data prediction involves using historical data and statistical methods to forecast future outcomes, but it faces challenges such as data quality issues, the complexity of real-world data, and the difficulty in balancing model complexity. Feature selection, overfitting, and the interpretability of complex models further contribute to the complexity. Data reconciliation involves aligning model with in situ data, but a major challenge is to create models capturing all the complexity of the real world, encompassing dynamic variables, as well as the residual and complex near-field effects on measurements (e.g., sensors coupling). This difficulty can result in residual discrepancies between simulated and real data, highlighting the challenge of accurately estimating real-world intricacies within predictive models during the reconciliation process. The paper delves into these challenges for complex and instrumented systems (multi-scale, multi-physics, and multi-media), discussing practical applications of machine and deep learning methods in the case study of thermal loading monitoring of a high-level waste (HLW) cell demonstrator (called ALC1605) implemented at Andra's underground research laboratory.