Deviations Of Parameters Research Articles

Optimisation of synthesis procedures and structural investigation of monazite-cheralite solid solutions

The monazite-cheralite solid solutions LnPO4-Ca0.5Th0.5PO4 with Ln = La, Gd were prepared via a co-precipitation route, showcasing an optimised, scalable synthesis procedure for a possible waste form accommodating high level liquid waste streams. A distortion of the cheralite structure with respect to the monazite structure was observed throughout both solid solutions as evidenced by a deviation of the lattice parameters from the linear behaviour known from other monazite solid solutions. Using a high temperature flux method, cheralite single crystals were grown for the first time for in-depth structural investigations. Both thorium and calcium were found to deviate from the central position of the LnO9 polyhedron, supporting previous neutron diffraction investigations of identical cheralite samples.Graphical

Calibration of Static Errors and Compensation of Dynamic Errors for Cable-driven Parallel 3D Printer

As rigid robots suffer from the higher inertia of their rigid links, cable-driven parallel robots (CDPRs) are more suitable for large-scale three-dimensional (3D) printing tasks due to their outstanding reconfigurability, high load-to-weight ratio, and extensive workspace. In this paper, a parallel 3D printing robot is proposed, comprising three pairs of driving cables to control the platform motion and three pairs of redundant cables to adjust the cable tension. To improve the motion accuracy of the moving platform, the static kinematic error model is established, and the error sensitivity coefficient is determined to reduce the dimensionality of the optimization function. Subsequently, the self-calibration positions are determined based on the maximum cable length error in the reachable workspace. A self-calibration method is proposed based on the genetic algorithm to solve the kinematic parameter deviations. Additionally, the dynamic errors are effectively reduced by compensating for the elastic deformation errors of the cable lengths. Furthermore, an experimental prototype is developed. The results of dynamic error compensation after the self-calibration indicate a 67.4% reduction in terms of the maximum error along the Z-axis direction. Finally, the developed prototype and proposed calibration and compensation methods are validated through the printing experiment.

Influence of urban environment factors on morphometric parameters and accumulation of secondary metabolites in Cercis canadensis L. and Cercis siliquastrum ‘Alba’

Consideration of the role of green spaces in urban landscaping is extremely important, as they not only decorate the urban landscape, but also effectively reduce air pollution, regulate the microclimate and play an important role in improving the ecology and quality of life of residents. The purpose of the study was to determine the influence of urban environmental factors on the development and secondary metabolism of plants of the genus Cercis L. Plants growing in Kyiv (Ukraine) under conditions with different air humidity, anthropogenic load, and excess or lack of insolation were selected for the study. Plant growth processes were studied by morphometric parameters of annual shoots of Cercis siliquastrum ‘Alba’ and Cercis canadensis L. growing under different conditions. Morphometric methods, fluorescence microscopy, high-performance thin-layer chromatography and regression analysis were used in the study. The research data show that insufficient sunlight has a negative impact on shoot growth. The specificity of the phenolic profiles that can be used to distinguish between the species Cercis canadensis L. and Cercis siliquastrum ‘Alba’ was established. The principal component analysis confirmed that phenolic profiles depend on habitat conditions and affect plant growth and development. The Gaussian model was used to analyse the growth dynamics of annual shoots during the growing season, which allowed us to describe the specifics of internode formation during the growing season quite accurately. This model allowed us to detect the phenomenon of the last internodes falling off at the end of the growing season, which caused the deviation of the morphometric parameters of metameres from the normal distribution along the time axis. Anatomical studies confirmed that the separation of one or more of the last internodes was due to active corking of the internal tissues of the stem, blocking of the xylem and formation of a separating layer, which led to the fall of the shoot tip. This phenomenon shows signs of plant adaptation to low temperatures in winter. The tops of the shoots often do not have time to lignify and accumulate the required amount of cryoprotectants. With the formation of a separating layer, the available energy resources are redistributed to the lateral buds, which receive the necessary resources to prepare for the winter period and provide new growth in the next growing season. The adaptive potential of the two species of the genus Cercis L. confirms the prospects of their use in urban ecosystems, which can positively affect the conservation of biodiversity in general

Effects of queen excluders on the colony dynamics of honeybees (Apis mellifera L.) under biodynamic management

The evaluation of beekeeping management practices (BMPs) is important for beekeepers worldwide because their choice affects health and survival of managed honeybee (A. mellifera L.) colonies and touches ethical and economic questions. This study focusses on queen excluders, a common hive addition in contemporary beekeeping. Its impacts are controversially discussed but have not been studied scientifically yet. Within a 4-year participatory on-farm experiment, we assessed the effects on colony dynamics in 64 hives in 8 apiaries during one season in Germany using the Liebefeld estimation method. We found no significant deviation for parameters of colony dynamics between hives managed with and without queen excluders. A qualitative decision-making tool (Pugh decision matrix) facilitated concept selection only for specific beekeepers.

ЗМЕНШЕННЯ ВПЛИВУ ВІДХИЛЕНЬ ПАРАМЕТРІВ ГЕНЕРАТОРІВ У ПРЕЦИЗІЙНИХ КВАДРАТУРНИХ МОСТАХ

The article is devoted to solving the problem of attestation of electric capacity standards at industrial frequency. The expediency of using a quadrature bridge of alternating current to determine the parameters of standards of electric capacity at industrial frequency by comparison with the parameters of standards of active resistance was noted. The advantage of using a bridge imbalance indicator with high input impedance is shown, which consists in the possibility of reducing the influence of higher harmonics of the supply voltages. An analysis of the well-known method of reducing of measurement errors caused by the deviation of the generator parameters from the calculated ones was carried out. It is shown that the known method does not provide sufficient compensation for the influence of these errors when the deviations of the generator parameters increase, as well as when the deviations of the bridge from the balance state increase. An iterative algorithm for calculating the measured deviation of the impedance ratio of the compared standards from the nominal value is proposed. Mathematical expressions for calculating the measured quantity are given. Calculations of the components of the measurement error for different values of generator voltage deviations were carried out. Calculations were performed for two variants of generator voltage variation implementation: multiplicative voltage amplitude variation and additive voltage phase variation. The developed iterative correction method allows to reduce the specified errors to the required levels in a small number of iteration steps - in the vast majority of cases, two steps are enough. The application of the method allows obtaining high metrological characteristics with rather large deviations of the voltage ratio of bridge generators, which makes it possible to reduce hardware costs when implementing quadrature alternating current bridges for comparing capacitance and active resistance standards. References 15, figure 1, table 1.

Optimal design of Luenberger reduced-order observer with low sensitivity for linear multivariable systems

For the linear multivariable systems, by combining both merits of orthogonal-function approach and evolutionary optimization, in this paper, a new method is presented for designing a Luenberger reduced-order observer to solve the low-sensitivity design issue for physical system parameter deviation and simultaneously to minimize a measurement of the quadratic performance for reducing state transient estimation error. Two given examples illustrate the effectiveness of the presented new low-sensitivity design approach on state estimation performance. From the given examples, it shows that the estimated state errors are not sensitive to system parameter deviation and have the asymptotical convergence property. Besides, the performances are apparently superior to those without considering low-sensitivity design means.

Uncertainty Propagation in a Simplified Integrated Thermal Management System

An integrated generic plate model that describes single-phase transport combining heat acquisition and rejection regimes is investigated. Transient processes and input uncertainty propagation impacting temperature variations in this simplified, dimensionless integrated thermal management system are discussed. The heat acquisition plate is surface-heated on one side, with the heat being conducted into a liquid. The heated liquid is assumed to be adiabatically advected to the heat rejection plate. Convection boundary conditions are considered for both plates. The range of mean values of dimensionless input parameters, such as the Biot and Prandtl numbers, is determined by the choice of a particular plate metal and flowing liquid, and their stochastic nature is described by the Gaussian distributions. Adiabatic solutions for the dimensionless temperature variations in the plates are obtained for different temperatures and Reynolds numbers. As is shown, even an assumed small standard deviation for the input parameters may result in a drastic increase in the stochastic spread in the temperature variation in the heat rejection plate. Unlike the temperature variation across the acquisition plate, the temperature variation profile for the heat rejection plate is sensitive to the temperature of the incoming liquid and heat input at the acquisition plate.

A prospective observational study of sepsis-associated coagulopathy (SAC) in septic shock in the pediatric intensive care unit of tertiary care hospital in central rural India

Background: Sepsis-associated coagulopathy (SAC) is a frequently encountered clinical scenario in pediatric critical care practice. The disruptions within the normal coagulation cascade in cases of sepsis significantly impact the ultimate patient outcome. Objective: This study aims to evaluate the associations between sepsis-associated coagulopathy (SAC) in pediatric septic shock cases and their corresponding clinical outcomes. Methods: This study will be conducted within a tertiary care Pediatric Intensive Care Unit (PICU), focusing on children aged one month to 18 years who have been admitted to manage sepsis. Cases diagnosed with sepsis will undergo evaluation and treatment according to the established PICU protocol. Coagulation profiles, encompassing International Normalized Ratio (INR), activated Partial Thromboplastin Time (aPTT), Prothrombin Time (PT), and platelet counts, will be subjected to analysis. Any deviations in coagulation parameters will be compared and correlated with morbidity and mortality outcomes. Expected results: This study will establish correlations between the severity of sepsis and its subsequent outcomes, specifically concerning aberrations in coagulation profile levels. A meticulous analysis will focus on critically ill cases necessitating various interventions and exhibiting deviant coagulation patterns. Conclusions: This research aims to unravel potentially pivotal prognostic correlations within sepsis cases. The coagulation profile, a standard investigation, can be a predictive tool for outcomes within the Pediatric Intensive Care Unit (PICU).

LIDAR‐assisted feedforward individual pitch control of a 15 MW floating offshore wind turbine

AbstractNacelle‐mounted, forward‐facing light detection and ranging (LIDAR) technology can deliver benefits to rotor speed regulation and loading reductions of floating offshore wind turbines (FOWTs) when assisting with blade pitch control in above‐rated wind speed conditions. Large‐scale wind turbines may be subject to significant variations in structural loads due to differences in the wind profile across the rotor‐swept area. These loading fluctuations can be mitigated by individual pitch control (IPC). This paper presents a novel LIDAR‐assisted feedforward IPC approach that uses each blade's rotor azimuth position to allocate an individual pitch command from a multi‐beam LIDAR. In this study, the source code of OpenFAST wind turbine modelling software was modified to enable LIDAR simulation and LIDAR‐assisted control. The LIDAR simulation modifications were accepted by the National Renewable Energy Laboratory (NREL) and are now present within OpenFAST releases from v3.5 onwards. Simulations of a 15 MW FOWT were performed across the above‐rated wind spectrum. Under a turbulent wind field with an average wind speed of 17 ms−1, the LIDAR‐assisted feedforward IPC delivered up to 54% reductions in the root mean squared errors and standard deviations of key FOWT parameters. Feedforward IPC delivered enhancements of up to 12% over feedforward collective pitch control, relative to the baseline feedback controller. The reductions to the standard deviation and range of the rotor speed may enable structural optimization of the tower, while the reductions in the variations of the loadings present an opportunity for reduced fatigue damage on turbine components and, consequently, a reduction in maintenance expenditure.

Natural frequency analysis of gear system with interval shaft misalignment in multidimensions

Due to the existing tolerances, the shaft misalignment of gear system is inevitably uncertain and shows interval property, which will cause the natural frequency to fluctuate in an interval range, therefore the traditional dynamics analysis that takes it as a deterministic parameter cannot reflect the interval characteristics of natural frequency. To overcome this conundrum, an improved interval eigenvalue algorithm based on matrix non-negative factorization and the Chebyshev inclusion function was proposed to find the natural frequency range of gear system under such uncertainty. First, the average meshing stiffness range of the gears with interval shaft misalignment is obtained by the Chebyshev interval approach. Then combined with the consideration of the remaining excitation parameter deviation coefficients, the global interval stiffness matrix and mass matrix of a single-stage gear system are obtained. Afterwards, the non-negative factorizations of these two interval matrices are carried out and parameter vertex theory is finally employed to obtain the upper and lower bounds of the eigenvalues. The feasibility of the applied algorithm is verified through comparison with the scanning method. Numerical results show that the uncertainty of shaft misalignment will enormously widen the system's resonance bandwidth and intensify oscillation, these will provide a new and valuable perspective for the tolerance allocation in gearbox design.

Kinematic calibration and feedforward control of a heavy-load manipulator using parameters optimization by an ant colony algorithm

AbstractMost of the currently available three-degree-of-freedom manipulators are light load and cannot achieve full continuous rotation; given this, we designed a heavy-load manipulator that achieves unrestricted and continuous rotation. Due to manufacturing and assembly errors, parameter deviations between the real manipulator and its underlying theoretical model were unavoidable. Because of the lack of high-precision, high-frequency, and real-time closed-loop detection methods, we proposed a type of kinematics calibration of parameterized ant colony optimization and feedforward control methods. This was done to achieve high-precision motion control. First, an error model combining structural parameters and joint output angles was established, and the global sensitivity of each error source was analyzed to distinguish both primary and secondary sources. Based on the measured data of a laser tracker, the ant colony optimization was then used to identify six error sources. This resulted in both link length and joint driving errors of the designed manipulator. As it is a type of systematic error, the rounding error of the theoretical trajectory was carefully analyzed, and feedforward control methods with different coefficients were designed to further improve positioning accuracy based on the kinematic calibration. Experimental results showed that the proposed kinematic calibration and feedforward control methods achieved relatively precise motion control for the designed manipulator.

Embedding and cross-sectioning as a sample preparation procedure for accurate and representative size and shape measurement of nanopowders

Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer–Emmet–Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed.

Artificial intelligence-based optimal EVCS integration with stochastically sized and distributed PVs in an RDNS segmented in zones

The growing interest in electric vehicles (EVs) for transportation has led to increased production and government support through legislation since they offer environmental benefits such as reduced air pollution and carbon emissions compared to conventional combustion engine vehicles. This shift toward EV technology aligns with the goal of preserving the natural environment. To fully utilize EVs, effective management of the power grid is crucial, particularly in radial distribution network systems (RDNS) as they pose stress and deviation of power system parameters from their normal. This study proposes a novel strategy for maximizing EV utilization through EV charging stations (EVCSs) in an RDNS by considering factors such as load voltage deviation, line losses, and the presence of distributed solar photovoltaic systems at load centers. The research begins by segmenting the RDNS into zones, followed by the application of an artificial intelligence-based hybrid genetic algorithm (GA) and particle swarm optimization (PSO) approach known as hybrid GA–PSO. This approach identifies optimal locations for EVCSs integrated with photovoltaics within the network. Subsequently, the employment of individual GA and PSO algorithms to optimize EVCS placement focuses on minimizing power loss and enhancing voltage. The effectiveness of the hybrid GA–PSO algorithm is compared to that of separate GA and PSO methods. Extensive simulations using the IEEE 33-node test feeders validate the proposed techniques, demonstrating the usefulness of the hybrid GA–PSO algorithm in identifying optimal EVCS placement within each zone. The results also highlight the advantages and novelty of hybrid GA–PSO in achieving optimal EVCS placement with stochastically sized and distributed photovoltaic in an RDNS.

A robust data analytical method to investigate sequence dependence in flow-based peptide synthesis.

Computer-assisted methods, which hold the promise to transform synthetic organic chemistry, are often limited by experimental data lacking in quality, diversity, and quantity. In solid-phase peptide synthesis (SPPS), automated flow chemistry is well-suited to deliver such data, which is key for prediction and optimization of sequence-dependent "difficult couplings", and insights obtained in flow-SPPS can be transferred to batch-SPPS. The current data analysis techniques rely on the height and the width of fluorenylmethoxycarbonyl (Fmoc) deprotection peaks and perform well under standard conditions. Yet any deviation in parameters (e.g. temperature, flow rate, resin loading) leads to incomplete capture of information and exclusion from the dataset. Here, we present a flexible and robust processing and analysis method that is based on the Gaussian shape of the deprotection peaks to overcome these challenges, which drastically increases the interpretable size of our data set. Using this straightforward method retains the full information and data quality while the generation of hazardous dimethylformamide solvent waste is reduced by 50%. Overall, this work highlights how the interplay between synthetic and computational analysis enables the collection of high-quality data even under non-ideal, non-standard conditions.

Using KMeans Clustering to Evaluate and Alert for Deviations of Linac Photon Beam Parameters.

To analyse the daily measured Dosimetric Quality Assurance (QA) parameters of linear accelerator (linac) using Unsupervised Machine Learning (ML) Algorithm thereby evaluating the current machine status and to highlight the probable cause of the 'out-of-range' measured parameter. Five Parameters measured using PTW QuickCheckwebline device in a linac is subjected to KMeans clustering technique. The measured parameters comprise of Central Axis Dose (CAX), Beam Flatness, SymmetryLR, SymmetryGT and Beam Quality (BQF). Data from Varian with 55- and 107-day's measurements and from Elekta with 75 days measurements from 2 beam matched linacs were used in this clustering technique. This evaluation is used to review the current linac status and obtain 1) Upper and lower limits of each parameter (CAX, Flatness, Symmetry, Beam Quality), 2) Frequency of the days when the linac parameters are closer to the target value and when they deviate from the target value. 3) The date when these parameters deviate from the estimated limits. 4) The probable reason for the deviation and 5) Finally if the machine requires maintenance. This methodology ensures that the machine is always closest to the target value, thus providing quality radiation treatment for the cancer patients. Moreover, the performance of the linac is studied meticulously and the need for maintenance is alerted before the linac beam shows marked deviation from the base value. KMeans clustering is a very simple and easy to use ML tool. With quick computation time and with lesser data it can arrive at the actual limits of the linac parameters and help to determine if the linac needs maintenance well in advance.

Phytochemical Profiling and Therapeutic Potential of Abelmoschus esculentus Fruit Extracts: Insights Into Antidiabetic Potential in In Vitro and In Vivo Experiments

Due to inadequate treatment, diabetes mellitus, which is characterized by hyperglycemia, is a global health challenge that requires creative management techniques. This study explores the therapeutic potential of Abelmoschus esculentus L. Moench fruit extracts in diabetes, offering an ample approach includes phytochemical analysis, qualitative and quantitative assessments, antidiabetic efficacy, antioxidant potential, and in vivo and in vitro investigations. Thin‐layer chromatography (TLC), high‐performance liquid chromatography (HPLC), and gas chromatography–mass spectrometry (GC–MS) were utilized to disclose the phytochemical profile of the fruit extracts, which indicated a diverse range of bioactive compounds. Four polyphenolic compounds including chlorogenic acid, quercetin, rutin, and morin were confirmed by HPLC fingerprinting, with rutin being the most prevalent. Qualitative analysis reveals the presence of carbohydrates, emodin, terpenoids, lignin, glycosides, and anthraquinones, while indicating the absence of amino acids, anthocyanins, phlobatannins, lactones, and leucoanthocyanins. Quantitative analysis reveals total phenolic, tannin, and flavonoid. In vitro assessments demonstrate the ability of the extracts to inhibit alpha amylase. Radical scavenging activities were evaluated through DPPH assay, underscoring their antioxidant capacity with high effect in methanol extracts. Additionally, the methanol extract decreased the blood glucose level of Type 2 diabetic mice. Notably, test samples stabilized blood glucose levels, reversed deviations in blood profile parameters, blood biochemistry, and regulated organ weight. Based on its antioxidant and antidiabetic effects, as well as positive effects on the physiology of Type 2 diabetic mice, A. esculentus emerges as an important nutraceutical vegetable. As an important nutraceutical vegetable, it holds promise for diabetes management. A. esculentus can be incorporated into dietary interventions for individuals with diabetes, harnessing its natural antioxidant and antidiabetic properties. Our findings validate the traditional use of A. esculentus in green therapeutics. In conclusion, A. esculentus emerges as a valuable ally in the fight against diabetes, bridging the gap between ancient wisdom and modern science. Further research and practical implementation are warranted to fully realize its potential.

Detection of poikilocytosis cells in anemia using (ANN) & embedded systems

In the bloodstream, erythrocytes stand as vital carriers of oxygen and carbon dioxide, facilitated by the presence of hemoglobin within their structures. However, deviations in erythrocyte size can lead to the formation of Poikilocyte cells, a characteristic feature of conditions like Iron Deficiency Anemia. Variants of Poikilocytoses, such as Degmacyte, Dacrocyte, Schistocyte, and Elliptocyte, denote distinct alterations in erythrocyte morphology, often associated with diminished iron levels crucial for haemoglobin synthesis. In a recent study, the differentiation between normal RBCs and Poikilocyte cells has been addressed through the application of Artificial Neural Network (ANN) algorithms, leveraging extracted features from digital images of blood smears. This approach offers a more precise means of identifying blood disorders compared to traditional visual inspection, utilizing image analysis techniques to detect deviations in color, size, and statistical parameters. The methodology involves a series of computational steps including preprocessing, segmentation, morphological operations, feature extraction, and classification, all executed within the Matlab environment. Furthermore, to enhance diagnostic capabilities, the system integrates glucose level measurement alongside erythrocyte analysis, transmitting data to a controller which relays results via GSM signal as SMS and LCD display. This comprehensive approach not only automates cell identification and classification but also ensures efficient and accurate analysis, including the automated separation of overlapped cells.

CRITERION METHOD FOR MODELLING THERMODYNAMIC INSTABILITY IN MIXING HEATERS OF TURBO INSTALLATIONS

The relevance of the issue of modelling the conditions and consequences of thermodynamic instability in mixing heaters is confirmed by the analysis of the experience of operating turbo installations and the problem of hydrodynamic shocks and their impact on the functioning of the equipment. A thermodynamic mathematical model of heat and mass transfer processes in the volume of mixing heaters has been developed, which, unlike known approaches, takes into account the influence of fluctuating deviations of thermodynamic parameters from the equilibrium state on the conditions of thermodynamic instability. The analysis of the obtained criteria and conditions of thermodynamic instability and hydrodynamic shocks was carried out. Based on the developed model, an original method of determining the conditions and consequences of thermodynamic instability in the volume of mixing heaters is presented. The criterion of thermodynamic instability in the developed method defines the conditions of simultaneous change of pressure and mass in the two-phase volume of the mixing heater. The conditions for the occurrence of thermodynamic instability in mixing heaters are determined, which significantly depend on the ratio of steam and condensate flow rates. The results obtained in the work can be applied for: development of systems for diagnosing the state of mixing heaters based on the regularly controlled parameters of the turbo installation, substantiating technical solutions for preventing thermodynamic instability and hydrodynamic “shocks” on the design of heaters, substantiating technical solutions for modernization of turbo installation systems. These issues determine the need for further analysis of the feasibility of modernizing thermodynamic instability modelling methods in mixing heaters of NPP turbo-installations. Keywords: thermodynamic instability, mixing heaters of turbo installations

Mechanical Property Evaluation of Stir-Squeeze Cast Al-Based Nano SiC Composites

This study focuses on the production of stir-squeeze cast hybrid composites made of aluminium with reinforcements. Base metal AA6105 is combined with SiC/TiC. TiC is changed from 3 to 9 wt% while SiC is kept constant (3wt%).Nine specimens are created using the deviation of the stir casting parameters of Stirrer speed (SP) 350-550rpm, Stir-time (TI) 15-25 min, and Reinforcement (RE) 3-19 w.t% in accordance with L9 Taguchi's design. By applying pressure of 60 MPa during squeeze casting, reinforced composites are created. Both stir casting and squeeze cast specimens are examined for their mechanical characteristics, such as tensile strength (TS) and hardness (BHN). Based on elongation, tension, and strain, TS was assessed for both processes. The outcomes showed that SQC sample L6 obtained the maximum TS of 303.19 MPa while STC specimen only managed to reach 269.88 MPa. The STC method produced a hardness value of roughly 83.56 Hv, whereas the greatest hardness value of 94.73 Hv was obtained with SQC sample L9 (SP-550 rpm, TI-25 min & RE-6%).

Low-loss weak-coupling 6-mode hollow-core negative curvature fiber based on symmetric double-ring nested tube

Few-mode optical fibers have played an increasingly important role in breaking through the transmission capacity limitations of single-mode optical fiber and alleviating the bandwidth crisis in optic fiber communication systems in recent years. Nevertheless, traditional solid core few-mode optical fibers usually suffer optical fiber nonlinearity and mode coupling, leading to mode crosstalk between channels. Hollow core negative curvature fibers (HC-NCF) have attracted widespread attention due to their advantages, such as low latency, low nonlinearity, low dispersion, low transmission loss, and large operating bandwidth. In this work, a novel low-loss few-mode HC-NCF with symmetrically double ring nested tube structure is designed, which supports six core modes including LP<sub>01</sub>, LP<sub>11</sub>, LP<sub>21</sub>, LP<sub>02</sub>, LP<sub>31<i>a</i></sub>, and LP<sub>31<i>b</i></sub>. The designed optical fiber is based on silica dioxide substrate and adopts a unique symmetrical double ring nested cladding structure, which can effectively suppress the coupling between the core mode and the cladding mode. The finite element method (FDE) is used to numerically analyze the properties of the proposed few-mode HC-NCF and optimize the structural parameters of the few-mode HC-NCF. Moreover, the confinement loss and bending loss of all core modes are investigated. The simulation results show that the proposed few-mode HC-NCF can support the independent transmission of six weakly coupled core modes (with the effective refractive index difference greater than 1×10<sup>–4</sup> between the adjacent core modes, which greatly avoids the coupling between the adjacent modes in the fiber core). In the 400 nm bandwidth (1.23–1.63 μm, covering the O, E, S, C, and L bands), all six modes in the fiber core maintain low loss transmission. Moreover, in the range of 1.3–1.63 μm, the confinement loss (CL) of LP<sub>01</sub>, LP<sub>11</sub> and LP<sub>21</sub> mode are all less than 1×10<sup>–3</sup> dB/m, and the CL of LP<sub>02</sub> and LP<sub>31<i>b</i></sub> mode are both less than 3×10<sup>–3</sup> dB/m. The CL of each mode reaches the lowest value at 1.4 μm, and the LP<sub>01</sub> mode has the lowest CL of 4.3×10<sup>–7</sup> dB/m. In addition, for a bending radius of 7 cm, each mode maintains the low bending loss characteristic in a certain operating wavelength range. In the range of 1.23–1.61 μm, the BL of LP<sub>01</sub> is less than 4.5×10<sup>–4</sup> dB/m, and the BL of LP<sub>11</sub> is less than 1.3×10<sup>–3</sup> dB/m. The tolerance analysis shows that even with the deviation of structural parameters of ±1%, the few-mode HC-NCF can still maintain the characteristic of low-loss and weak coupling. The designed few-mode HC-NCF has ultra-low CL and bending-insensitive characteristics while supporting independent transmission of six modes, which will find huge potential applications in future high performance mode division multiplexing systems.