Constraint Conditions Research Articles

The Impact of Assimilating Cirrus‐Effected Infrared Satellite Radiance From the FY‐4A AGRI on Water Vapor Analysis and Rainstorm Forecasting

AbstractIn this study, a method for assimilating FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances (CER) is investigated, and the impact of this method on water vapor analysis and rainstorm forecasting is examined through observing system simulation experiments and actual case experiments. The high proportion of inverted humidity profiles in the cirrus‐effected pixels is the main reason for the negative effect of assimilation in the mid‐to‐lower troposphere. To address this, relevant constraint conditions are incorporated into the cost function. The statistical results reveal that the addition of a CER assimilation improves the analysis increment of water vapor, with pattern correlation coefficients of 0.33, 0.35, and 0.20 at 200, 300, and 400 hPa, respectively, which are greater than those of a clear‐sky radiance assimilation (0.28, 0.33, and 0.17, respectively). Moreover, the inclusion of a CER assimilation greatly improves data utilization, and has a neutral to positive effect on precipitation forecasting.

Optimization of Radio Energy Transmission System Efficiency Based on Genetic Algorithm

In order to better understand the efficiency optimization problem of radio energy transmission systems, the author proposes a genetic algorithm based research on efficiency optimization of radio energy transmission systems. The author first addresses the issue of improving the efficiency of magnetic coupled radio energy transmission. On the basis of ensuring a certain transmission distance and voltage gain, the system is mathematically modeled using coupling circuit theory, and mathematical expressions such as transmission efficiency, transmission distance, and voltage gain are obtained as the objective functions of the algorithm. Secondly, the impact of metal obstacles on the transmission system was analyzed. Design a radio energy transmission compensation circuit, and through simulation, obtain three transmission system parameter schemes that meet the objective function and constraint conditions. Finally, the multi-objective genetic algorithm is used to optimize the system parameter design and obtain the optimal combination of transmission system parameters, with coupling coefficient k=0.1818 and mutual inductance coefficient M=23.165 × 10^(-5) H. Using multi-objective genetic algorithm, the algorithm has a fast convergence function in terms of the number of iterations, a non dominated function solution, and Pareto graphs have verified that the numerical value (3) in the text is the optimal combination design for the transmission system.

Design and Parameter Optimization of Double-Mosquito Combination Coils for Enhanced Anti-Misalignment Capability in Inductive Wireless Power Transfer Systems

This paper proposes a novel double-mosquito combination (DMC) coil for inductive wireless power transfer (IPT) systems to improve their anti-misalignment capability. The DMC coil consists of a mosquito coil with single-turn spacing and a tightly wound close-wound coil. By superimposing the magnetic fields generated by both coils, a relatively uniform magnetic field distribution is achieved on the receiving coil plane. This approach addresses the challenges of significant output voltage fluctuations and reduced transmission efficiencies caused by coupling coil misalignments in conventional IPT systems. To further optimize the DMC coil, an interaction law between its parameters and the mutual inductance is established, setting the coil mutual inductance fluctuation rate as the optimization objective, and using the coil turn spacing, number of turns, and outer diameter as constraint conditions. The beetle antennae search algorithm (BAS) is employed to enhance the whale optimization algorithm (WOA), facilitating the adaptive optimization of the coil parameters. An experimental IPT system platform with a 50 mm transmission distance is developed to validate the robust anti-misalignment capability of the proposed coil. The results demonstrate that within a horizontal misalignment range of 50 mm, the system’s output voltage fluctuation rate stays below 7.4%, and the transmission efficiency remains above 83%.

Multi-level index construction method based on master-slave blockchains.

Master-slave blockchain is a novel information processing technology that is domain-oriented and uses efficient cryptography principles for trustworthy communication and storage of big data. Existing indexing methods primarily target the creation of a single-structured blockchain, resulting in extensive time and memory requirements. As the scale of domain data continues to grow exponentially, master-slave blockchain systems face increasingly severe challenges with regards to low query efficiency and extended traceback times. To address these issues, this paper propose a multi-level index construction method for the master-slave blockchain (MLI). Firstly, MLI introduces a weight matrix and partitions the entire master-slave blockchain based on the master chain structure, the weight of each partition is assigned. Secondly, for the master blockchain in each partition, a master chain index construction method based on jump consistent hash (JHMI) is proposed, which takes the key value of the nodes and the number of index slots as input and outputs the master chain index. Finally, a bloom filter is introduced to improve the column-based selection function and build a secondary composite index on the subordinate blockchain corresponding to each master block. Experimental results on three constraint conditions and two types of datasets demonstrate that the proposed method reduce the index construction time by an average of 9.28%, improve the query efficiency by 12.07%, and reduce the memory overhead by 24.4%.

Thermal performance enhancement of multiple tubes latent heat thermal energy storage system using sinusoidal wavy fins and tubes geometry modification

In this paper, performance enhancement of a shell and multiple tube latent heat thermal energy storage system (LHTESS) is numerically investigated by implementing sinusoidal wavy fins and different geometrical designs of heat transfer tubes. The annular space of the shell is filled with the paraffin wax RT35 as phase change material (PCM) and absorbs heat from hot water through the multiple tubes. With the constant total cross-section area of all tubes and fins as the constraint condition, the effect of tube number and tube shape incorporated with the proposed fins on the heat transfer properties of PCM during the melting process is evaluated. The computational results demonstrate that the sinusoidal wavy fins can improve the phase change efficiency compared to the conventional straight fins. The double-pitch sinusoidal wavy fins decrease the total melting time by 9.5% compared to the straight fins for the single-tube case. As the number of HTF tubes increased from one to four, the complete PCM melting time decreased by 38.3%. Geometrical design alterations of heat transfer tubes from circular to petal-shaped are proposed to further improve the thermal performance of multiple tubes LHTESS. The melting rate of PCM is accelerated with an increase in the number of petals. The petal tubes with nine petals can save the charging time up to 24 % in comparison with the circular tubes in a four-tube case with double-pitch sinusoidal wavy fins, and up to 57% compared to the base case with a single circular HTF tube and straight fins.

Experimental and numerical investigations of a staged energy dissipation device

Energy-dissipating devices (EDDs) are widely used in building structures to mitigate seismic disasters. This study designed a fully assembled friction-metal series damper which is one kind of the staged energy dissipation devices (SEDD). Quasi-static tests were conducted to examine the behaviour of the SEDDs. The influence of factors such as the configurations of the restrainers, pre-tightening force, and material of the metal strip module was investigated. The work behaviour of the SEDD consists of three stages: elastic, frictional energy dissipation, and metallic elastic–plastic energy dissipation stages. The experimental results verified the effectiveness of the predicted working mechanism and showed that the bearing capacity and energy dissipation of the SEDD increased with the configuration of the restrainers, pre-tightening force, and yield strength of the metal strip module. The experiment also showed that the rotation of the outer plates caused an unexpected force mode in the metal strip module. Subsequently, numerical models of the test specimens were built, and good agreement was observed between the numerical simulations and test results for the hysteresis performance, loading capacity, and stress distribution. To further improve the mechanical properties of the SEDD, an optimised model was established and studied. The SEDDs with optimised strip shapes and constraint conditions of the outer plate exhibited better mechanical performance, and their load capacities increased by 11 % and 41 %, respectively.

Real-time visual SLAM based YOLO-Fastest for dynamic scenes

Within the realm of autonomous robotic navigation, simultaneous localization and mapping (SLAM) serves as a critical perception technology, drawing heightened attention in contemporary research. The traditional SLAM systems perform well in static environments, but in the real physical world, dynamic objects can destroy the static geometric constraints of the SLAM system, further limiting its practical application in the real world. In this paper, a robust dynamic RGB-D SLAM system is proposed to expand the number of static points in the scene by combining with YOLO-Fastest to ensure the effectiveness of the geometric constraints model construction, and then based on that, a new thresholding model is designed to differentiate the dynamic features in the objection bounding box, which takes advantage of the double polyline constraints and the residuals after reprojection to filter the dynamic feature points. In addition, two Gaussian models are constructed to segment the moving objects in the bounding box in the depth image to achieve the effect similar to the instance segmentation under the premise of ensuring the computational speed. In this paper, experiments are conducted on dynamic sequences provided by the TUM dataset to evaluate the performance of the proposed method, and the results show that the root mean squared error metric of the absolute trajectory error of the algorithm of this paper has at least 80% improvement compared to ORB-SLAM2. Higher robustness in dynamic environments with both high and low dynamic sequences compared to DS-SLAM and Dynaslam, and can effectively provide intelligent localization and navigation for mobile robots.

LeCaSiM: Learning Causal Structure via Inverse of M-Matrices with Adjustable Coefficients

The objective of causal discovery is to uncover the causal relationships among natural phenomena or human behaviors, thus establishing the basis for subsequent prediction and inference. Traditional ways to reveal the causal structure between variables, such as interventions or random trials, are often deemed costly or impractical. With the diversity of means of data acquisition and abundant data, approaches that directly learn causal structure from observational data are attracting more interest in academia. Unfortunately, learning a directed acyclic graph (DAG) from samples of multiple variables has been proven to be a challenging problem. Recent proposals leverage the continuous optimization method to discover the structure of the target DAG from observational data using an acyclic constraint function. Although it has an elegant mathematical form, its optimization process is prone to numerical explosion or the disappearance of high-order gradients of constraint conditions, making the convergence conditions unstable and the result deviating from the true structure. To tackle these issues, we first combine the existing work to give a series of algebraic equivalent conditions for a DAG and its corresponding brief proofs, then leverage the properties of the M-matrix to derive a new acyclic constraint function. Based on the utilization of this function and linear structural equation models, we propose a novel causal discovery algorithm called LeCaSiM, which employs continuous optimization. Our algorithm exploits the spectral radius of the adjacency matrix to dynamically adjust the coefficients of the matrix polynomial, effectively solving the above problems. We conduct extensive experiments on both synthetic and real-world datasets, the results show our algorithm outperforms the existing algorithms on both computation time and accuracy under the same settings.

Stress-driven nonlocal integral model with discontinuity for size-dependent buckling and bending of cracked nanobeams using Laplace transform

Due to the frequent occurrence of cracks as structures age, examining the size-dependent responses of cracked micro/nanobeams is critical for safely designing and optimizing high-tech devices such as those used in MEMS/NEMS. With this understanding, we present the size-dependent bending and buckling studies of cracked nanobeams with different boundary edges adopting the well-posed stress-driven nonlocal integral model with discontinuity. Since the presence of a crack, the beam is divided into two segments connected by a rotary spring and a linear spring, whose elastic coefficients can be determined through compliance calibration methods. We propose an efficient method to solve the original integral model directly by converting the integral form of the nonlocal constitutive equation into a general equation through the Laplace transform technique, equipped with three extra constraint conditions. Subsequently, the governing equations of two beam segments are solved by considering the standard boundary and compatibility conditions as well as the extra constraint conditions, while the bending deformation and buckling loads of various bounded nanobeams are presented analytically in the presence of a crack. After verifying the derived formulation, the influence of crack length and location as well as nonlocality on the beam deflections and buckling loads of the first several modes are investigated in detail. Communicated by Rossana Dimitri.

Dynamic analysis of aircraft towing slip-out system considering vertical wheel constraints

Abstract To analyze the vertical dynamic characteristics of the aircraft towing system under different constraints on the nose landing gear wheels of the aircraft during the towing slip-out mode, a dynamic model of the towing system considering the constraints between the clamping mechanism and the aircraft nose landing gear wheels was established based on the general towing system dynamic model. On this basis, an analysis was conducted to determine whether considering the aircraft wheel constraints affects the vertical vibration acceleration of the towing vehicle and the nose landing gear in low-speed (10 km/h) and high-speed (40 km/h) operating conditions. With the consideration of constraints at both ends of the aircraft wheels, the vertical acceleration of the towing vehicle's center of mass increased by 153% and 172% at low speed and high speed, respectively, compared to not considering the aircraft wheel constraints. Additionally, with the consideration of constraints at both ends of the aircraft wheels, the vertical acceleration of the nose landing gear's center of mass decreased to 20% and 57% at low speed and high speed, respectively, compared to not considering the aircraft wheel constraints. An analysis of the vertical vibration acceleration of the towing vehicle under different wheel constraint conditions found that the RMS value of the vertical vibration acceleration of the towing vehicle's center of mass was minimized when the clamping angles of the clamping mechanism to the nose landing gear wheels were 63° and 64°, respectively. Under this clamping angle, the influence of the clamping forces at both ends of the clamping mechanism on the vertical vibration acceleration of the towing vehicle was minimal. The research results provide valuable reference for the direct constraints between the clamping mechanism and the nose landing gear wheels in the aircraft towing slip-out system.

To Be Experienced or Not? Unpacking the Relationship between Leader Tenure and Counterinsurgency Efforts

ABSTRACT Although countering insurgencies through violence is common yet costly, we occasionally observe governments take this cost by adopting non-violent strategies. Hence, under what circumstances do leaders choose non-violent or violent ones in tackling with insurgencies? We empirically investigate how leader experience in office affects what type of counterinsurgency measures leaders employ, and how domestic political constraints condition the decision-making process. We argue that inexperienced leaders tend to use violence, while experienced ones may adopt conciliatory tactics, as the former are more risk prone to prove their strong leadership immediately. However, we also contend that institutional mechanisms could moderate this effect depending on the level of constraints they impose. Drawing on Asal et al. dataset on governments’ counterinsurgency activities, we find that inexperienced leaders are more likely to resort to violence as a counterinsurgency strategy; whereas experienced ones are more likely to avoid solely violent measures, and adopt non-violent ones, as well. Plus, the effect is conditional on regime type, as experienced leaders’ acts vary depending on if they maintain a sear in a democratic or anocratic regime. Our findings contribute to the conflict studies by opening the door to the examination of leader-level factors on counterinsurgency more explicitly.

Fuel Combination Optimization Model of Thermal Power Plant Based on New Particle Swarm Optimization Algorithm

Influenced by the unbalanced state of particle swarm in the process of fuel combustion in thermal power plants, the fuel cost in the thermal power generation stage is relatively high. Therefore, a new particle swarm optimization model for fuel combination in thermal power plants is proposed. Combined with the combustion properties of different fuels, from the point of view of particle swarm optimization, in the process of carrying out specific particle swarm optimization simulation, the original particle swarm optimization algorithm is improved adaptively. A new particle swarm optimization algorithm is constructed by coupling it with a multiphase turbulence model. The fuel combustion performance of the power plant is analyzed by using its coupling. The optimization model of fuel combination in the thermal power plant is constructed by maximizing the energy release of fuel as the core, and the state of the fluid-particle field is taken as the constraint condition. In the test results, the design of the fuel combination optimization model can fully improve the energy release degree of fuel and reduce fuel consumption under the same power generation demand, which has a positive effect on power generation cost control.

Breather wave solutions on the Weierstrass elliptic periodic background for the (2 + 1)-dimensional generalized variable-coefficient KdV equation.

In this paper, the Nth Darboux transformations for the (2+1)-dimensional generalized variable-coefficient Koretweg-de Vries (gvcKdV) equation are proposed. By using the Lamé function method, the generalized Lamé-type solutions for the linear spectral problem associated with the gvcKdV equation with the static and traveling Weierstrass elliptic ℘-function potentials are derived, respectively. Then, the nonlinear wave solutions for the gvcKdV equation on the static and traveling Weierstrass elliptic ℘-function periodic backgrounds under some constraint conditions are obtained, respectively, whose evolutions and dynamical properties are also discussed. The results show that the degenerate solutions on the periodic background can be obtained by taking the limits of the half-periods ω1,ω2 of ℘(x), and the evolution curves of nonlinear wave solutions on the periodic background are determined by the coefficients of the gvcKdV equations.

Improvement of SAC0307/Cu column friction plunge micro-welding quality by static constraint

PurposeTo solve the problems caused by using precise molds for copper column positioning in the current column grid array package, this paper aims to optimize the proposed friction plunge micro-welding (FPMW) technology without mold assistance, to overcome the problems of low interfacial bonding strength, shrinkage cavities and flash defects caused by the low hold-tight force of solder on the copper column.Design/methodology/approachA pressurizing device installed under the drill chuck of the friction welding machine is designed, which is used to apply a static constraint to the solder ball obliquely downward to increase the hold-tight force of the peripheral solder on the copper column during welding and promote the friction metallurgical connection between them.FindingsThe results show that the application of static constraint during welding can increase the compactness of the solder near the friction interface and effectively inhibit occurrences of flash, shrinkage cavities and crystal defects such as vacancies. Therefore, compared with the unconstrained (UC) FPMW, the average strength of the statically constrained (SC) FPMW joints and aged SC-FPMW joints can be increased by 51.1% and 122.6%, and the problem of the excessive growth of the interfacial connection layer in the UC-FPMW joints during aging can be effectively avoided.Originality/valueThe application of static constraint effectively inhibits the occurrence of defects such as shrinkage cavities, vacancies and flash in FPMW joints, and the welding quality is significantly improved.

Avoiding stick-slip limit cycle vibration in electric vehicle brake system via brake force distribution

Brake creep groan, a friction-induced nonlinear vibration in the brake system, has significantly contributed to the reduction of ride comfort. In order to mitigate brake creep groan, a brake force distribution strategy based on the stick-slip curve is proposed and examined. The critical boundary of the stick-slip limit cycle is determined and established as the constraint condition. Focusing on avoiding stick-slip limit cycle vibration, an adaptive particle swarm optimization method is employed to study the distribution of brake force between regenerative brake and friction brake, with energy recovery efficiency serving as the objective function. Four distinct operational conditions—NEDC, UDDS, WLTP, and FTP—are simulated. The results demonstrate that under these conditions, vibrations associated with the stick-slip limit cycle can be reduced by up to 23.596%, 15.368%, 15.342%, and 17.557%, respectively. Considering the peak power and peak torque of the drive motor, three regions can be identified: the region where stick-slip limit cycle vibration cannot be avoided, the region where avoidance efficiency increases with the rise in the drive motor’s peak torque and peak power, and the region where avoidance efficiency remains constant despite increases in the drive motor’s peak torque and peak power.

Optical solitons, qualitative analysis and multistability response to study the dynamical behaviour of light wave promulgation

Our aim is to explore novel optical solitons within the context of an extended higher-order nonlinear Schrödinger equation that governs the behaviour of propagating light waves. Primarily, this research finds abundant types of solitons, such as singular, kink and trigonometric functions subject to certain constraint conditions. We have utilized G ′ / ( b G ′ + G + a ) -expansion method, which has proved effective in retrieving these solitons and presenting them for further analysis. The model's dynamic behaviour is then investigated through bifurcation, quasi-periodic oscillations, chaotic behaviour, and sensitivity. These include methods like phase portrait rendering, time series scrutiny, Lyapunov exponents calculation, and the assessment of multi-stability. Finally, sensitivity analysis is conducted at three distinct initial conditions, revealing that the model displays a high level of sensitivity, with substantial alterations occurring in response to minor changes in the initial conditions. The results of this study are revolutionary, intriguing, and possess crucial theoretical importance in evolution disruptions.

Fatigue Crack Growth on Several Materials under Single-Spike Overloads and Aircraft Spectra during Constraint-Loss Behavior

Abstract The phenomenon of flat-to-slant crack growth has been studied by many in the fracture mechanics community. At low stress-intensity factors, a fatigue-crack surface is flat (tensile mode) and the crack-front region is under plane-strain conditions (high constraint). As the crack grows with higher stress-intensity factors, a 45° shear lip occurs through the thickness of the sheet or plate. This behavior is the shear mode, which is under low constraint or plane-stress conditions. In 1966, Schijve found that the transition from flat-to-slant crack growth on a 2024-T3 Alclad aluminum alloy over a wide range in stress ratios (R) occurred at a “constant” crack-growth rate. Also, Newman and Hudson showed the same behavior on 7075-Temper-6 and Ti–8Al–1Mo–1V alloys, validating Schijve’s observation that crack-growth rate was the key parameter for flat-to-slant crack-growth behavior. The materials considered herein are 2024-T3, 7075-T6, and 9310 steel. Crack-growth behavior during single-spike overloads and simulated aircraft spectrum loading are presented. The fatigue structural analysis (FASTRAN) crack-closure based life-prediction code was used to correlate the constant-amplitude (CA) crack-growth-rate data over a wide range in stress ratios (R = Smin/Smax) and rates from threshold to near fracture, and to calculate or predict the crack-growth behavior on single-spike overload tests. Crack-closure behavior is strongly dependent upon the level of constraint. The main objective was to see if the constraint-loss region is the primary reason for crack-growth delays after single-spike overloads. Also, crack-growth analyses are presented on tests that were conducted by Wanhill on 2024-T3 Alclad aluminum alloy under the transport wing standard (TWIST) spectrum. Crack-growth analyses using crack-closure theory without constraint loss was “unable” to predict crack growth under spike overloads or simulated aircraft spectra. However, predicted crack length against cycles with constraint-loss behavior compared reasonably well with all tests.

Numerical Simulation of the Marine Environmental Capacity of Jinpu Bay

Based on the study of the marine environmental capacity, a water quality model and a response field-based linear programming method are adopted here. Water quality control objectives are taken as the constraint conditions, according to the requirements of Jinpu Bay’s functional zoning. The pollutant response coefficient and water quality background value are combined with the values of the water concentration quality control points set in each functional area and the target value of the functional area wherein they are located. The maximum allowable emission intensity of inorganic nitrogen, phosphate and chemical oxygen demand (COD) can be calculated using the linear programming method of the maximum allowable emission of pollutants at estuaries or sewage outfall points on Jinpu Bay. The research results reveal the diffusion of marine pollutants and the marine environmental capacity of Jinpu Bay. Some rivers need to reduce the discharge intensity and some other outlets still have a certain residual capacity. Based on this, the environmental capacity of Jinpu Bay was evaluated, and a technical reference is provided for the economic development of the region and the formulation of pollutant emission control policies.

Nonlinear complex generalized zakharov dynamical system inconformal sense utilizing new kudryashov method

We take into account the nonlinear complex generalized Zakharov dynamical system which models the spread of the Langmuir waves in ionized plasma, in the conformal sense in this manuscript. Fractional wave transformation is enforced to convert the nonlinear fractional system to a nonlinear ordinary differential equation system. The new Kudryashov method which was recently introduced and is an efficient method, is implemented to the presented equation to acquire analytical solutions. The required constraint conditions are offered to ensure the validity of the obtained solutions. To analyze the physical interpretations for some of the produced solutions, we illustrate some graphical representations. We derive the bright and singular solitons. Furthermore, 2D views of the behavior of the solitons are represented to investigate the effect of the values of the parameters in the proposed model and fractional parameters. Also, the modulation instability of the model is investigated to ensure the obtained results are stable.

Multi-satellite cooperative scheduling method for large-scale tasks based on hybrid graph neural network and metaheuristic algorithm

Traditional heuristic optimization algorithms are no longer applicable to the multiple satellites scheduling with large-scale tasks, as they are unable to provide satisfactory performance in terms of convergence and speed when addressing complex constraint conflicts. Therefore, we propose a multi-satellite cooperative scheduling method for large-scale tasks based on a hybrid graph neural network (GNN) and metaheuristic algorithm. By using the representation and extraction capability of GNN for relations in graph, the features of large-scale tasks and their constraint relations were expressed, and the generalized knowledge was extracted. And combined with metaheuristic algorithm, the optimization framework for large-scale satellite task scheduling based knowledge and data was implemented. The method consists of a GNN pre-solver module for static constraint conflicts and a metaheuristic optimization module for dynamic constraint conflicts of satellite missions. In the GNN pre-solver module, the graph sample and aggregate network was used to learn and extract the common knowledge in the static task-conflict graph, and provided effective prior information for the metaheuristic optimization module. The quadratic unconstrained binary optimization loss function was designed with multiple influencing factors, to convert the discrete optimization function into a continuous function; a greedy threshold was also added to improve the task completion rate. Finally, numerical experimental results showed that the proposed method can achieve an efficient solution to the multi-satellite scheduling problem with tens of thousands tasks. Compared with the commonly used multi-satellite scheduling algorithms (the genetic algorithm (GA) and greedy-GA), the proposed method can obtain higher-quality solutions under the same conditions and greatly improve the computational efficiency of large-scale mission planning.