Unified Method Research Articles

A Numerical Method on Large Roll Motion in Beam Seas Under Intact and Damaged Conditions

The second-generation intact stability criteria, including five stability failure modes, were approved by the International Maritime Organization (IMO) in 2020, and it is an urgent task to develop the numerical method for the significant roll motion under dead conditions. Both intact and damaged stability focus on the large roll motion in beam seas. A unified numerical method is studied to predict the large roll motion in regular and irregular beam seas under intact and damaged conditions. Firstly, a sway–heave–pitch–roll–yaw-coupled equation named 5-DOF and a sway-, roll-, and yaw-coupled motion with the roll-righting arm in still water named 3-DOF are used to predict the large roll motion in regular beam seas under the intact and damaged conditions. Secondly, the method is extended for the large roll motion in irregular beam seas, where the diffraction force in the roll direction and the sway and yaw motion under intact and damaged conditions are calculated by the subharmonic superposition method. Thirdly, the roll-righting arm in the calm water, roll-damping coefficients, and the roll natural roll period, under the intact and damaged conditions, are obtained by software and a free roll decay experiment, respectively. Finally, the numerical results of a patrol boat under intact and damaged conditions are compared to the experimental results. The results show that the sway-, roll-, and yaw-coupled motion with the roll-righting arm in still water named 3-DOF can predict the large roll motion in regular and irregular beam seas under intact and damaged conditions.

The HVAC system engineering method for a new family of unified cabins of combine harvesters

BACKGROUND: Designing a combine harvester cabin climate system is a complex and multi-stage process that includes solving a set of tasks. To solve them, a design engineer must have knowledge and skills in various fields, starting with thermal engineering calculations and ending with experimental research methods and computer modeling, which requires a large amount of intellectual and time resources. Therefore, the task of creating a unified method of engineering of combine harvester cabin HVAC system is highly relevant. AIM: Development of the HVAC system for a unified cabin of a grain harvester and a forage harvester. The designed HVAC system is purposed to create a comfortable microclimate in the cabin of the combine for 2 people in summer and winter operating conditions. METHODS: The methodology of calculation and selection of the combine harvester cabin HVAC system, which includes the development of engineering calculation methods and mathematical modeling of thermodynamic and ventilation processes in the cabin, is considered. RESULTS: The main parameters were determined: heat intakes and heat losses for the grain harvester and forage harvester cabins, which amounted to 2.8 and 2.2 kW for the grain harvester, 2.9 and 2.35 kW for the forage harvester; the required air flow rate supplied to the cabin to ensure a comfortable temperature — 740 m3/h; the percentage of air recirculation regarding the conditions of absence of fogging and creation of excessive pressure in the cabin — 75%; the cooling and heating capacity of the HVAC system, taking into account the operating conditions of the combine, are 7.8 and 6.3 kW respectively. The selection of the main equipment of the HVAC system for a unified cabin for a new family of unified cabins of combines — the BUHLER 1000 MFWD evaporator-heater and the Valeo TM16 compressor are chosen. CONCLUSION: The HVAC system designed in accordance with the presented methodology is capable of ensuring a comfortable cabin air temperature in the range of 22–24 °C at various operating modes of the combine harvester in different regions. In addition, the HVAC system parameters eliminate fogging of the cabin windows and the penetration of dusty air inside due to the created excessive pressure.

A gas-surface interaction algorithm for discrete velocity methods in predicting rarefied and multi-scale flows: For Maxwell boundary model

The discrete velocity method (DVM) for rarefied flows and the unified methods (based on the DVM framework) for flows in all regimes, from continuum one to free molecular one, have worked well as precise flow solvers over the past decades and have been successfully extended to other important physical fields. Both DVM and unified methods endeavor to model the gas-gas interaction physically. However, for the gas-surface interaction (GSI) at the wall boundary, they have only use the full accommodation boundary up to now, which can be viewed as a rough Maxwell boundary with a fixed accommodation coefficient (AC) at unity, deviating from the real value. For example, the AC for metal materials typically falls in the range of 0.8 to 0.9. To overcome this bottleneck and extend the DVM and unified methods to more physical boundary conditions, an algorithm for Maxwell boundary with an adjustable AC is established into the DVM framework. The Maxwell boundary model splits the distribution of the bounce-back molecules into specular ones and Maxwellian (normal) ones. Since the bounce-back molecules after the spectral reflection does not math with the discrete velocity space (DVS), both macroscopic conservation (from numerical quadrature) and microscopic consistency in the DVS are hard to achieve in the DVM framework. In this work, this problem is addressed by employing a combination of interpolation methods for mismatch points in DVS and an efficient numerical error correction method for micro-macro consistency. On the other hand, the current Maxwell boundary for DVM takes the generality into consideration, accommodating both the recently developed efficient unstructured velocity space and the traditional Cartesian velocity space. Moreover, the proposed algorithm allows for calculations of both monatomic gases and diatomic gases with internal degrees in DVS. Finally, by being integrated with the unified gas-kinetic scheme within the DVM framework, the performance of the present GSI algorithm is validated through a series of benchmark numerical tests across a wide range of Knudsen numbers.

A unified cross-series marine propeller design method based on machine learning

Propeller design diagrams, like Bp-δ diagram, are widely applied in ship propeller design. However, different propeller series use various selection approaches, so comparisons between designs are only possible after individual candidates are chosen.This paper proposes a unified approach based on machine learning to allow efficient comparison and facilitate the selection of the optimal propeller amongst the available propeller series. The process starts by compiling propeller series data to generate a comprehensive dataset on propeller performance. This dataset is then used to train an Artificial Neural Network (ANN) model, which accurately predicts open-water propeller performance. Optimization techniques are applied to maximize propeller efficiency based on the specific needs of the vessel, while ensuring compliance with cavitation and noise constraints for safety. The model's accuracy is validated using data from the KRISO Container Ship (KCS), demonstrating the prediction's reliability. The method is then applied to select both open and ducted propellers for a variety of ship types to meet specific operational requirements. Ultimately, the optimized results are ranked by efficiency, offering an organized set of options for selecting the most suitable propeller. This approach eliminates the need for manual dataset correlation, significantly improving the efficacy of generating an outperforming initial design.

ARMNet: A Network for Image Dimensional Emotion Prediction Based on Affective Region Extraction and Multi-Channel Fusion

Compared with discrete emotion space, image emotion analysis based on dimensional emotion space can more accurately represent fine-grained emotion. Meanwhile, this high-precision representation of emotion requires dimensional emotion prediction methods to sense and capture emotional information in images as accurately and richly as possible. However, the existing methods mainly focus on emotion recognition by extracting the emotional regions where salient objects are located while ignoring the joint influence of objects and background on emotion. Furthermore, in the existing literature, when fusing multi-level features, no consideration has been given to the varying contributions of features from different levels to emotional analysis, which makes it difficult to distinguish valuable and useless features and cannot improve the utilization of effective features. This paper proposes an image emotion prediction network named ARMNet. In ARMNet, a unified affective region extraction method that integrates eye fixation detection and attention detection is proposed to enhance the combined influence of objects and backgrounds. Additionally, the multi-level features are fused with the consideration of their different contributions through an improved channel attention mechanism. In comparison to the existing methods, experiments conducted on the CGnA10766 dataset demonstrate that the performance of valence and arousal, as measured by Mean Squared Error (MSE), Mean Absolute Error (MAE), and Coefficient of Determination (R²), has improved by 4.74%, 3.53%, 3.62%, 1.93%, 6.29%, and 7.23%, respectively. Furthermore, the interpretability of the network is enhanced through the visualization of attention weights corresponding to emotional regions within the images.

Locally purified density operators for noisy quantum circuits

Abstract Simulating open quantum systems is essential for exploring novel quantum phenomena and evaluating noisy quantum circuits. In this Letter, we address the problem of whether mixed states generated from noisy quantum circuits can be efficiently represented by locally purified density operators (LPDOs). We map an LPDO of N qubits to a pure state of size 2 × N defined on a ladder and introduce a unified method for managing virtual and Kraus bonds. We numerically simulate noisy random quantum circuits with depths up to d = 40 using fidelity and entanglement entropy as accuracy measures. LPDO representation proves to be effective in describing mixed states in both quantum and classical regions but encounters significant challenges at the quantum-classical critical point, limiting its applicability to the quantum region exclusively. In contrast, the matrix product operator (MPO) successfully characterizes the entanglement trend throughout the simulation, while truncation in MPOs breaks the positivity condition required for a physical density matrix. This work advances our understanding of efficient mixed-state representation in open quantum systems and provides insights into the entanglement structure of noisy quantum circuits.

A unified noise and watermark removal from information Bottleneck-based modeling

Both image denoising and watermark removal aim to restore a clean image from an observed noisy or watermarked one. The past research consists of the non-learning type with limited effectiveness or the learning types with limited interpretability. To address these issues simultaneously, we propose a method to deal with both the image-denoising and watermark removal tasks in a unified approach. The noises and watermarks are both considered to have different nuisance patterns from the original image content, therefore should be detected by robust image analysis. The unified detection method is based on the well-known information bottleneck (IB) theory and the proposed SIB-GAN where image content and nuisance patterns are well separated by a supervised approach. The IB theory guides us to keep the valuable content such as the original image by a controlled compression on the input (the noisy or watermark-included image) and then only the content without the nuisances can go through the network for effective noise or watermark removal. Additionally, we adjust the compression parameter in IB theory to learn a representation that approaches the minimal sufficient representation of the image content. In particular, to deal with the non-blind noises, an appropriate amount of compression can be estimated from the solid theory foundation. Working on the denoising task given the unseen data with blind noises also shows the model’s generalization power. All of the above shows the interpretability of the proposed method. Overall, the proposed method has achieved promising results across three tasks: image denoising, watermark removal, and mixed noise and watermark removal, obtaining resultant images very close to the original image content and owning superior performance to almost all state-of-the-art approachesthat deal with the same tasks.

An implicit unified gas-kinetic particle method with large time steps for gray radiation transport

For a long time, efficient algorithms for high-dimensional equations, represented by photon radiation transport, have been one important topic in the development of computational methods for particle transport processes. In this paper, we present an implicit unified gas-kinetic particle (IUGKP) method for multiscale gray radiative transfer. Based on the integral solution of the radiative transfer equation, the photon transport processes are categorized into non-equilibrium transport processes with a large photon free path and equilibrium transport processes with a small photon free path. The long-path processes are solved by an implicit Monte Carlo (IMC) method, and the short-path processes are solved by an implicit diffusion system. The closure formulation of photon distribution is derived from the local integral solution of the radiative transfer equation to couple the IMC and diffusion system. The improvement of the proposed IUGKP method over UGKP method is that particles can be tracked continuously instead of just until the first collision, making simulation with large time steps possible. The IUGKP method has the properties of asymptotic-preserving (AP) and regime-adaptive (RA). The AP property states that the IUGKP method converges to the consistent numerical methods for the asymptotic limiting equations of RTE in the limiting regimes. The RA property states that the computational accuracy of the IUGKP method adapts to the regimes. In this paper, the mathematical proof of the AP and RA properties is presented, and the multiscale numerical tests are performed to demonstrate the accuracy and efficiency of the IUGKP method.

Uptake of ecosystem service concept in urban blue-green infrastructure planning and decision-making in Russia

ABSTRACT In the scientific community, ecosystem services (ESs) are well-recognized as a promising concept to more actively consider and plan for the multitude of benefits provided by the green environment and thus promote sustainable urban development. Yet, to have an impact on decision-making, the concept must spread from academia to practice. To understand to what extent ES have been adopted in practice and decision-making in Russia, we conducted a series of interviews and an online survey with both practitioners and scientists and complemented it by document analysis. Our results showed that ES are not adequately reflected in urban decision-making and planning processes. Moreover, we found no explicit references to ES in strategic urban planning and landscape development projects, although there are few implicit references in several reviewed documents. Among the identified challenges for better uptake of the concept in practice were many disagreements associated with the lack of a unified terminology, typology, and methods. Stakeholders understand the potential of applying ES valuation in practice, which includes a necessity to develop methodological materials and different tools based on real-life cases. Finally, a list of proposals on possible ways to better include ES in urban planning and in decision-making processes was formed by the respondents.

Modeling and Energy Flow Calculation of Integrated Energy System Based on Partial Differential Equation Model

This paper discusses the modeling and energy flow calculation method of integrated energy system based on partial differential equation model. By constructing a model that integrates power, heat, and natural gas networks, we analyze in detail the process of energy transmission, conversion, and storage in the system. In the process of modeling, the influence of compressor in constant compression ratio, constant outlet pressure and constant natural gas flow is specially considered, and the accuracy of the model is verified by specific data. In terms of energy flow calculation methods, we compare the performance of the unified solution method and the decomposition solution method. Data analysis shows that the non-gradient descent iterative method, gradient descent iterative method and decomposition solution method show consistency in calculation accuracy, that is, the calculation results of the three methods are the same. However, in terms of computational efficiency, the gradient descent iterative method shows significant advantages. Specifically, under identical computing conditions, our analysis reveals that the gradient descent iterative method exhibits a convergence rate approximately 30% faster than the decomposition solution method, resulting in a notable reduction of around 25% in computational time. This pivotal observation serves as a solid foundation for selecting a more computationally efficient approach in practical applications. To further enhance the computational efficiency, we have delved into deriving the Jacobian matrix of the model and subsequently proposed an advanced gradient descent iterative calculation technique. Through the actual test, this method not only improves the calculation speed, but also ensures the stability and accuracy of the calculation. The research in this paper not only provides a strong theoretical support for the optimal operation of the integrated energy system, but also provides a valuable reference for future research in related fields. Through specific data analysis, we prove the effectiveness and practicability of the proposed method, laying a solid foundation for the sustainable development of integrated energy systems.

Micro–Macro Coupling Study on the Mechanical Properties of Continuous Fiber-Reinforced Composites

As a key and weak point of continuous fiber-reinforced composites (CFRCs), the interface between the fiber and the matrix is vulnerable to failure under external loads, with its performance directly affecting the overall properties of CFRCs. Hence, a micro–macro coupling method that considered the microscopic properties of the interface was utilized to analyze and predict the mechanical properties of CFRCs more accurately. The microscopic mechanical parameters of the fiber–matrix interface, which were obtained using molecular dynamics, were transferred to the representative volume element (RVE). The stiffness matrix of the CFRC, required for the macroscopic finite element model, was then calculated using a unified periodic homogenization method based on the RVE and assigned to the finite element model for a macroscopic simulation. Nylon/continuous carbon fiber specimens were fabricated through additive manufacturing, with the tensile and bending strengths of the specimens obtained through tensile and three-point bending tests. The tensile strength of the experimental specimen was 200.1 MPa, while the result of the simulation containing the interface was 205.5 MPa, indicating a difference of less than 5% between the two. In contrast, the result of the simulation without an interface was 317.7 MPa, representing a high error of 58.7% compared with the experimental results. Moreover, the bending strength, Young’s modulus, and flexural modulus results with and without an interface showed the same trend as that for the tensile strength. This illustrates the effectiveness of the proposed micro–macro coupling method for analyzing and predicting the mechanical properties of CFRCs.

Skeletal Reorganization Emanated via the Course of Heterocyclic N1-N2 Bond Cleavage: Electrosynthetic Approach.

A unified method toward the synthesis of functionalized diazepines and quinazolines through reorganization of the molecular skeleton has been devised. The process is indulged by electrical energy via a domino N1-N2 bond cleavage followed by concomitant ring closing, initiating from cinnolines and indazoles as designed precursors. Additionally, an intermolecular ring homologation has also been established to synthesize densely functionalized dihydroquinazolines from 2,3-diaryl-indazoles and acetonitrile involving the same electrochemical strategy.

A unified approach for evaluation of the minimum circumscribed circle and maximum inscribed circle

Abstract a unified method is proposed to evaluate the minimum circumscribed circle and maximum inscribed circle. Initial three candidate points are selected with the one-point operator and two-point operator. The two-point operator is also used to select candidate points or determine redundant data points during iterations. Examples from the literatures confirm the effectiveness and accuracy of the proposed algorithm.

Machine learning prediction method for the interface bond strength between fiber reinforced polymer bars and concrete based on multi-feature driven analysis

In severe service conditions, corrosion of reinforcement poses a significant challenge for concrete structures. Fiber reinforced polymer (FRP) materials, characterized by their low weight, high strength, and superior corrosion resistance, are effective in enhancing the durability of these structures. The interfacial bond performance between FRP bars and concrete is crucial for their synergistic action and is pivotal for the design and safety evaluation of FRP-reinforced concrete structures. This paper conducts a comprehensive analysis of factors including the material and mechanical properties of FRP bars, concrete mechanical properties, and bond length. Utilizing an exhaustive search strategy, it identifies the optimal characteristic parameters for assessing the bond strength between FRP bars and concrete. Subsequently, these parameters are integrated with four machine learning (ML) algorithms—DT, SVM, RF and XGB—to train the nonlinear mapping relationship between influencing factors and bond strength, proposing a unified and interpretable prediction method for the FRP bar-concrete interface bond strength. The model's predictive accuracy is then validated using a test dataset, and a comparative analysis is performed among the predictive models generated by the four ML algorithms, as well as against empirical calculation formulas. The findings indicate that the ML models offer superior predictive performance and accuracy over empirical formulas, with the XGB algorithm demonstrating the highest overall accuracy and best performance. Moreover, to address the black-box nature of ML algorithms, the SHAP method is employed to enhance the interpretability of the bond strength prediction process. The newly developed hybrid ML model holds promise as a novel approach for accurately assessing the bond strength at the FRP bar-concrete interface.

A unified structure-preserving parametric finite element method for anisotropic surface diffusion

We propose and analyze a unified structure-preserving parametric finite element method (SP-PFEM) for the anisotropic surface diffusion of curves in two dimensions ( d = 2 ) (d=2) and surfaces in three dimensions ( d = 3 ) (d=3) with an arbitrary anisotropic surface energy density γ ( n ) \gamma (\boldsymbol {n}) , where n ∈ S d − 1 \boldsymbol {n}\in \mathbb {S}^{d-1} represents the outward unit vector. By introducing a novel unified surface energy matrix G k ( n ) \boldsymbol {G}_k(\boldsymbol {n}) depending on γ ( n ) \gamma (\boldsymbol {n}) , the Cahn-Hoffman ξ \boldsymbol {\xi } -vector and a stabilizing function k ( n ) : S d − 1 → R k(\boldsymbol {n}):\ \mathbb {S}^{d-1}\to {\mathbb R} , we obtain a unified and conservative variational formulation for the anisotropic surface diffusion via different surface differential operators, including the surface gradient operator, the surface divergence operator and the surface Laplace-Beltrami operator. A SP-PFEM discretization is presented for the variational problem. In order to establish the unconditional energy stability of the proposed SP-PFEM under a very mild condition on γ ( n ) \gamma (\boldsymbol {n}) , we propose a new framework via local energy estimate for proving energy stability/structure-preserving properties of the parametric finite element method for the anisotropic surface diffusion. This framework sheds light on how to prove unconditional energy stability of other numerical methods for geometric partial differential equations. Extensive numerical results are reported to demonstrate the efficiency and accuracy as well as structure-preserving properties of the proposed SP-PFEM for the anisotropic surface diffusion with arbitrary anisotropic surface energy density γ ( n ) \gamma (\boldsymbol {n}) arising from different applications.

DUNE: Dust depletion UNified method across cosmic time and Environments

We present a novel method to characterize dust depletion, namely, the depletion of metals into dust grains. We used observed correlations among relative abundances combining a total of 17 metals in diverse galactic environments, including the Milky Way (MW), Large Magellanic Cloud (LMC), Small Magellanic Cloud (SMC), and damped Lyman-alpha absorbers (DLAs) towards quasars and gamma-ray bursts (GRBs). We only considered the relative abundances of metals that qualify as tracers of dust and we used all available dust tracers. We find linear correlations among all studied dust tracers in a multidimensional space, where each dimension corresponds to an individual dust tracer. The fit to the linear correlations among the dust tracers describes the tendencies of different elements when depleting into dust grains. We determined the overall strength of dust depletion, Delta , along individual lines of sight, based on the correlations among different dust tracers. We avoided any preference for specific dust tracers or any other assumptions by including all available dust tracers in this multidimensional space. We also determined the dust depletion of Kr, C, O, Cl, P, Zn, Ge, Mg, Cu, Si, Fe, Ni, and Ti. Finally, we offer simple guidelines for the application of the method to the study of the observed patterns of abundances and relative abundances. This has allowed for a straightforward determination of the overall strength of depletion and the dust depletion of individual elements. We also obtained an estimate for the gas-phase metallicity and identified any additional deviations due to the nucleosynthesis of specific stellar populations. Thus, we have established a unified methodology for characterizing dust depletion across cosmic time and diverse galactic environments, offering a valuable new approach to the study of dust depletion in studies of the chemical evolution of galaxies.

Multiaxial creep deformation investigation of miniature cruciform specimen for type 304 stainless steel at 923 K using non-contact displacement-measuring method

Abstract Multiaxial creep investigations at high temperatures are required to guarantee the integrity of structural materials such as boiler pipes for power generation and turbine blades for aviation and industrial applications. The multiaxial creep testing method using a cruciform specimen has several advantages, and the authors successfully downsized the specimen. The authors also developed a technique for the in situ observation of the specimen in an electric furnace and the non-contact displacement measurement in the development of a biaxial tensile creep testing machine for the miniature cruciform specimen. By observing the specimen at a target mark during the creep testing through an observation window installed at the bottom of the furnace, it was possible to visualize the specimen surface variations and obtain the axial strain from the locus of the target marks. The Mises-type equivalent strain was calculated from the axial strains obtained in the equi-biaxial tensile multiaxial creep testing and was compared with the strains obtained in the uniaxial creep testing. The Mises-type equivalent strain can be expressed using a unified method up to approximately 5% of the initial strain in the test, even in the multiaxial stress state.

Investigation of optical soliton solutions for the cubic-quartic derivative nonlinear Schrödinger equation using advanced integration techniques

This paper aims to investigate optical soliton solutions in the context of the cubic-quartic derivative nonlinear Schrödinger equation with differential group delay, incorporating perturbation terms for the first time. Motivated by the need to better understand soliton dynamics in advanced optical communication systems, we employ three integration techniques: the direct algebraic approach, Kudryashov’s method with an addendum, and the unified Riccati equation expansion method. Our study reveals that, by appropriately selecting parameter values, the resulting solutions include Jacobi elliptic functions that describe straddle solitons, bright, dark, and singular solitons. We also identify the conditions under which these soliton pulses can exist. Furthermore, we provide numerical simulations to illustrate these solutions under specific parameter settings, highlighting their potential applications in optical fiber systems.

Investigation of exact solutions to the (2+1)-dimensional Sakovich equation with time dependent coefficients using analytical methods

In this paper, the exact solutions of the (2 + 1)-dimensional variable coefficient Sakovich equation are investigated. Four distinct analytical methods, containing the unified method, the modified Kudryashov method, the modified G′G2 -expansion method and the improved Riccati sub-equation method, are implemented to find new exact solutions of this equation. Soliton and periodic soliton solutions, elliptic solutions, kink solutions and traveling wave solutions, which are expressed in polynomial, rational, trigonometric and hyperbolic forms, have been obtained and are graphically represented with the aim of exhibiting the structures and dynamic behaviors of the equation. Furthermore, we have discussed the influence of variable coefficients on soliton behaviors in detail.

Electron-acoustic solitary waves via suprathermal populations in Saturn's magnetosphere: Bifurcation, sensitivity, and stability analysis

Cassini and Voyager space missions observed non-thermal electron populations (with varying characteristics) in Saturn's magnetosphere, which can be correctly described using kappa distributions. Based on these observations, our objective is to inspect the evolution of electron-acoustic solitary waves (EASWs) within Saturn's magnetosphere. The propagation of weakly nonlinear (EASWs) in a collisional plasma system comprising a cold electron fluid, hot electrons following a kappa distribution, and stationary ions is investigated. By employing the reductive perturbation technique, the Korteweg–de Vries Burgers (KdV–B) equation is derived. An exact solution of the KdV–B equation, with a conformable time-derivative, is found using the unified method. It is observed that plasma current-induced collision between electrons and ions leads to remarkable dissipation, generating EASWs. Furthermore, when studying the sensitivity of the system, the appearance of a positive potential is depicted as external forces vanish, which may be due to stationary ions. Additionally, bifurcation, stability, and significant influence of plasma characteristics are considered.