Variable Substitution Method Research Articles

Optimization control strategy for diesel urea-selective catalytic reduction (SCR) urea injection based on the interior point method (IP) + higher order SCR model

In order to ensure that the NOx and NH3 emissions of diesel engines comply with the Euro VII emission standards, this paper optimizes the urea injection using a SCR model combined with the interior point method. First, the equations of the higher-order SCR model were simplified by the variable substitution method and the line method and solved by the backward difference formula to improve computational accuracy. The Levenberg-Marquardt algorithm was used to calibrate the chemical reaction rate parameters to optimize model performance. Second, an optimization cost function was designed to optimize the upstream NH3 concentration in combination with the interior point method and the higher-order SCR model to meet the requirements of Euro VII emission standards. Third, the model effect was verified by performing WHTC hot-start testing on an engine complying with the National VI emission standard. The results show that the average error between the measured NOx concentration and the calculated is 1.49 ppm, which verifies the high accuracy of the model. Finally, the effects of the interior point method, NSGA-II, and MOPSO algorithms in optimizing the upstream NH3 concentration were compared. The results showed that the interior point method outperformed the other algorithms in terms of optimization time and effect, with an optimization time of 149 s, a NOx conversion rate of 97.36 %, and an average downstream NH3 concentration of 4.65 ppm. This achieved a high NOx conversion rate and low NH3 slip in accordance with the requirements of the Euro VII regulation.

The influence of digital intelligence transformation on carbon emission reduction in manufacturing firms

Severe global climate change has resulted in the focus of social attention shifting to the manufacturing industry's low-carbon transformation. Digital intelligent transformation (DIT) in enterprises is identified as a crucial driver in mitigating carbon emissions. An estimation of DIT's impact on manufacturing industries' carbon emission intensity (CEI) and its underlying mechanisms was conducted using data from Chinese A-share listed companies. Research findings indicate that DIT significantly reduces corporate CEI. Robustness tests, such as the instrumental variable method and variable substitution method, confirm this conclusion. By enhancing labor productivity and accelerating capital renewal, DIT indirectly lowers CEI. Furthermore, non-state-owned enterprises with superior market competitiveness have been observed to be markedly adept at harnessing DIT for CEI. The heterogeneity test found that DIT has a considerably significant effect on reducing CEI in enterprises that are not low-carbon pilots, non-broadband pilots, smart pilots, non-provincial capitals, and eastern cities. This study provides new evidence supporting the promotion of enterprise DIT for achieving green development, offering insights for corporate policy making.

Joint Optimization Algorithm for Latency-Energy and Privacy Combining Discrete Differential Evolution and Convex Optimization

A privacy protection task offloading algorithm combining discrete differential evolution and convex optimization is proposed to resolve the new position privacy leakage problem for mobile terminal due to transferring tasks to multiple edge servers for computation via wireless networks. First, the privacy cost of offloading decision is defined for the characteristics of the position privacy problem combined with the standard deviation theory. Second, the objective problem is modeled as a joint optimization of position privacy protection, offloading decision and transmission power, and the total cost of task offloading is an optimization objective. Finally, to handle the objective problem efficiently, offloading decision variable is decoupled from the transmission power variable to decrease the computational complexity of the problem; the discrete differential evolution algorithm is designed to accumulate the approximate optimal offloading decision, and the optimal transmission power is efficiently solved by variable substitution method and subgradient method. Simulations reveal that the algorithm has excellent convergence; it improves the position privacy protection level of mobile terminal and reduces the total cost of task offloading while maintaining lower energy consumption and latency.

Construction of a measurement system and analytical solution for docking pose of large aircraft components based on draw-wire displacement sensors

Abstract Relative pose detection is a key technology in large component automatic docking systems. In this paper, a measurement system has been developed to detect the relative pose of large aircraft components with draw-wire displacement sensors, while an analytical calculation method has been proposed to determine the docking pose of large aircraft components. This method establishes a measurement model for the docking pose of large components and separates the position and orientation solutions based on the distances between seven sets of measurement points measured by the draw-wire displacement sensors. First, the principle of three-dimensional rendezvous positioning is refined to ascertain the relative position of the components. Then, by analyzing the properties of the rotation matrix and the coupling relationship between the position and orientation variables of the movable component, 15 compatible equations containing only two variables with a maximum degree of four are obtained. Based on this set of equations, a unique solution for the rotation matrix was obtained through the variable substitution method, gradually eliminating higher-order terms. Finally, the correctness of the method is verified through numerical examples. Unlike typical parallel mechanism models, this model can directly obtain 15 compatible equations without the need for methods such as Gröbner bases. Moreover, compared to the measurement method using six draw-wire displacement sensors, a unique solution can be directly determined, solving the problem of multiple solution selection. This measurement method only requires measuring the distance between measurement points to solve the relative pose, with low equipment costs and less susceptibility to external environmental factors.

ESG performance, heterogeneous creditors, and bond financing costs: Firm-level evidence

Exploiting credit spread to measure firm bond financing costs, this study explored the impact of environmental, social, and governance (ESG) performance on bond financing costs from the perspective of heterogeneous creditors. Our results revealed that national interbank bond market and qualified institutional investors are increasingly interested in aligning their capital with ESG-related investment opportunities. Thus, they require a low rate of return from firms with good ESG performance. In contrast, domestic legal and natural persons and ordinary institutional investors are unlikely to accept a low investment return in exchange for the positive impact of ESG. Additional robustness tests confirmed the results, including firm-fixed effects, variable substitution method, supplemental variable method, lagged variable approach, instrumental variable analysis, and propensity score matching. The results of mechanism analysis indicated that the bond cost reduction effect of ESG is achieved by improving firms’ information disclosure quality and reputation. In addition, because of trade-off theory and agency problems, the environmental and social factors of ESG have only a limited impact on bond cost reduction, whereas the governance factor markedly reduces bond costs.

Mine seismic source location via forward modeling of spherical waves in a multilayered horizontal or inclined medium

Seismic source location is a classic inverse problem in seismology. In mathematical physics, inverse problems have multiple natural solutions. The objective of this study was to develop a generic theory and method of seeking the true solution from multiple solutions for the location of a coal mine seismic source in an idealized velocity structure model of a coal mine with a small scale and complex geological environment. Starting from the simplest velocity structure model, the complexity of the model gradually increased, until it approached the real velocity structure model, i.e., the multilayered horizontal and inclined velocity structure model, in order to find a generic method for solving the multi-solution inverse problem of coal mine seismic source location. Specifically, the wavefront distribution equation in a two-layer horizontal medium was derived and then expanded to any multi-layer horizontal medium. Based on this equation, a positive definite nonlinear equation system was established from the perspective of any observation system. The equation system contained four unknown variables of the spatiotemporal position of the seismic source. To determine the spatiotemporal parameters of the seismic source, nonlinear equations for four stations were required. To solve the nonlinear equation system, an initial iteration value was determined. In order to reduce the difficulty of determining the initial iteration value, the variable substitution method was used to reduce the number of location parameters. By rotating the original geodetic coordinate system of the station to be parallel and orthogonal to the medium interface, the wavefront method was extended to inclined medium. In conclusion, in this study, the problem of coal mine seismic source location in a multi-layer horizontal or inclined medium was effectively solved. The method proposed in this study provides a reference for solving the true solution from multiple solutions for the location of a coal mine seismic source in small-scale coal mines with complex geological environments.

Adaptive time-step unscented kalman filtering (ATS-UKF) based observer design for urea selective catalytic reduction (SCR) performance of diesel engines

To reduce the number of sensors in the SCR catalyst, state feedback and fault diagnosis information are provided. Firstly, a model based on the coupling of flow, heat transfer, and gas-solid phase catalytic reaction in the SCR system is investigated in this paper. The parabolic partial differential equations are simplified by the variable substitution method and the method of lines approach (MOL). The simplified system of equations is solved by backward differentiation formulas (BDF) with adaptive adjustment time step strategy. Meanwhile, the chemical reaction parameters are accurately calibrated per second using the Levenberg-Marquardt method. Secondly, the ATS-UKF is designed in this paper, and to ensure the synchronisation between the ATS-UKF and the SCR model calculations, the time step of solving the BDF by the SCR model is taken as the time step of propagating the sigma points. Two observation scenarios are assumed: (1) no downstream NH3 concentration sensor, ammonia coverage and downstream NH3 concentration are observed by ATS-UKF; (2) no downstream NOx sensor, ammonia coverage and downstream NOx concentration are observed by ATS-UKF. Finally, the paper carries out bench tests. In the first case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R². The mean absolute error (MAE) between the observed and experimental values of the ATS-UKF for the downstream NH3 concentration was 2.76 ppm. In the second case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R², and the MAE between the observed and experimental values of the ATS-UKF for the downstream NOx concentration was 1.53 ppm. Environmental ImplicationThe Adaptive Time-Step Unscented Kalman Filtering (ATS-UKF) enhances urea Selective Catalytic Reduction (SCR) in diesel engines, improving environmental outcomes. This method minimizes sensor dependence, enabling more precise SCR system management and effective emission reduction. By advancing emission control technologies, ATS-UKF contributes to global air pollution mitigation efforts, supporting cleaner air and environmental sustainability. Its innovative approach in monitoring and predicting SCR performance marks a significant step towards eco-friendly diesel engine operation.

Methods of calculating electric power generation by wind turbines and their influence on wind speed

RELEVANCE of the study lies in the analysis of the influence of specifying the wind speed interval on the calculation of electricity generation by certain wind turbines used in the Crimea. PURPOSE. Analysis of techniques that can be used to estimate electric power generation by wind turbines in various cases, as well as an assessment of the impact on the accuracy of the forecast of the speed indication interval when using "semi-aggregated" data. METHODS. Analytical and computational methods were used in the study, in particular, the variable substitution method, Rayleigh distribution, and the Milewski method. RESULTS. In the article the methods of calculating the electric power generation for three cases are considered. The first case uses primary observational data, so it is applicable only when a weather station is directly present in the area. The second case describes the course of calculations when the wind characteristics sensors are partially shaded and when the terrain is more complex. Here it is necessary to classify the degree of openness of the wind speed sensor. If the site is located far from weather stations or weather posts, the third method is used. In this case, the choice of interpolation nodes of the indicators of potential power generation can be quite complex. We also evaluated the effect of wind speed on electricity generation by a wind turbine. The number of aggregation intervals and the aggregation interval itself were changed, and the results were found for two wind turbines USW56-100 and T600-48, common in the Crimea. CONCLUSIONS. Wind energy is one of the promising areas, but often because of the differences between the forecast data and the actual, there are difficulties in integrating into the overall energy system. Therefore, it is important to develop methods for estimating the generation and accuracy in their use.

Riemann problem for a 2times 2 hyperbolic system with time-gradually-degenerate damping

This paper is focused on the Riemann problem for a 2times 2 hyperbolic system of conservation laws with a time-gradually-degenerate damping. Two kinds of non-self-similar solutions involving the delta-shocks and vacuum are obtained using the variable substitution method. The generalized Rankine-Hugoniot relation and entropy condition are clarified for the delta-shock. Furthermore, the vanishing viscosity method proves the existence, uniqueness, and stability of non-self-similar solutions.

Passive Synthesis of Fractional Order Immittance of Three-Element-Kind

For the actual circuit with fractional order characteristics, the fractional order circuit model is more concise and precise than the classical circuit model. So studying the synthesis of fractional order immittance is of great significance. This paper investigates the passive synthesis method of the three-element-kind fractional order immittance function. It means designing a network with three kinds of passive fractional-order elements that exhibit a specific impedance function. This paper proposes a variable substitution method to solve this problem. The method consists of three steps: The first step of the process is to establish the correspondence between the fractional order and lossy reactance. This way, the fractional order immittance function is transformed into an integer order immittance function. Then the Brune procedure realizes the immittance function as a network with lossy reactance. Finally, a fractional order network is obtained by replacing the lossy reactance with the corresponding fractional reactance. A simulation example and an experiment are also given for verification. This method applies to all three-element-kind network impedance functions that meet the passive condition.

Joint Communication and Computation Cooperation in Wireless-Powered Mobile-Edge Computing Networks With NOMA

Incorporating wireless power transfer (WPT) into mobile edge computing (MEC) is an effective way to enhance the self-sustainability of the MEC network. However, it is susceptible to the effect of double-far-near. Meanwhile, inspired by the fact that non-orthogonal multiple access (NOMA) has shown its great potential in improving the spectral efficiency of the network over OMA, this paper investigates a cooperative computation offloading scheme for a basic three-node wireless powered MEC scenario with NOMA, where users overcome the effect of double-far-near through joint communication and computation cooperation. Specifically, we consider a “harvest-then-offload” protocol composed of three stages. In the first stage, users harvest wireless energy signals from the access point (AP). In the second and third stages, based on NOMA, users offload their partial computing tasks on the same time-frequency resource block by using the harvested energy, in which the near user can cooperatively compute and forward the computing task of the far user. We formulate an optimization problem to minimize the transmission energy consumption of the AP by jointly optimizing the transmission power, the offloading coefficient and the duration of each stage. Due to the non-convexity of the formulated problem, we first transform it into an equivalent one by using the variable substitution method. Then, we propose an efficient iterative algorithm based on the successive convex approximation (SCA) and Lagrangian duality method to solve this transformed problem. Simulation results show that the proposed algorithm has good convergence and the proposed scheme can achieve the best performance compared with several baseline schemes, which highlights the superiority of the proposed scheme.

An improved bounded real lemma for H∞ robust heading control of unmanned surface vehicle

Aiming at a mass variation of unmanned surface vehicle and the poor or even unmeasurable signal of yaw rate signal, the dynamic output feedback [Formula: see text] control method is proposed for heading regulation based on improved bounded real lemma to reduce the conservativeness and guarantee the robustness. First, a linear-varying-parameter heading error model with external disturbances is established by the consideration of mass as a variable parameter. Second, the dynamic output feedback controller with [Formula: see text] performance is presented for the linear-varying-parameter heading error model, and its nonlinear matrix inequality conditions for the stability of the closed-loop system are deduced from improved bounded real lemma by parameter-dependent Lyapunov to maintain the system robustness. Furthermore, the solution of nonlinear matrix inequality conditions relies on the variable substitution method, and improved bounded real lemma reduces the conservativeness of the controller design by introducing auxiliary relaxation variables to derive the equivalent linear matrix inequality condition. Finally, the heading control simulations for unmanned surface vehicle indicate that the dynamic output feedback [Formula: see text] method based on improved bounded real lemma (IDOF) is robust to system parameter variations and external disturbances, and can effectively reduce the conservativeness of the controller design. Moreover, dynamic output feedback H∞ method based on improved bounded real lemma has faster transient processes and smaller steady-state errors.

Low-Latency Hybrid NOMA-TDMA: QoS-Driven Design Framework

Enabling ultra-reliable and low-latency communication services while providing massive connectivity is one of the major goals to be accomplished in future wireless communication networks. In this paper, we investigate the performance of a hybrid multi-access scheme in the finite blocklength (FBL) regime that combines the advantages of both non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA) schemes. Two latency-sensitive application scenarios are studied, distinguished by whether the queuing behaviour has an influence on the transmission performance or not. In particular, for the latency-critical case with one-shot transmission, we aim at a certain physical-layer quality-of-service (QoS) performance, namely the optimization of the reliability. And for the case in which queuing behaviour plays a role, we focus on the link-layer QoS performance and provide a design that maximizes the effective capacity. For both designs, we leverage the characterizations in the FBL regime to provide the optimal framework by jointly allocating the blocklength and transmit power of each user. In particular, for the reliability-oriented design, the original problem is decomposed and the joint convexity of sub-problems is shown via a variable substitution method. For the effective-capacity-oriented design, we exploit the method of Lagrange multipliers to formulate a solvable dual problem with strong duality to the original problem. Via simulations, we validate our analytical results of convexity/concavity and show the advantage of our proposed approaches compared to other existing schemes.

A novel fixed-time stability result and its application to synchronization of delayed multidirectional associative memory neural networks with discontinuous activations

In this paper, in order to realize time-saving and low-consumption secure communication based on fixed-time (FXT) synchronization, some new FXT stability results and a smaller upper bound of settling time are obtained by using inequality techniques, variable substitution method and some special functions, including beta function and incomplete beta function. Moreover, the FXT synchronization of delayed multidirectional associative memory (MAM) neural networks with discontinuous activations is investigated by employing the differential inclusion theory, the improved FXT stability theorem and a simple delay-independent nonlinear controller. Finally, a numerical simulation is given to verify the correctness of the theoretical results and the effectiveness of FXT synchronization in secure communication. The results show that the upper bound estimation of settling time in this paper is indeed smaller than that in some previous researches. In addition, the encrypted signals can be quickly decrypted based on the improved FXT stability results, but may not be decrypted by the existing FXT stability results.

Input-Constrained Hybrid Control of a Hyper-Redundant Mobile Medical Manipulator.

To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed a hyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers. A kinematics-based tracking algorithm was designed to obtain highly accurate pose tracking. A kinematic model of the HRMMM was established and its global Jacobian matrix was deduced. An expression of the tracking error based on the Rodrigues rotation formula was designed, and the relationship between tracking errors and gripper velocities was derived to ensure accurate object tracking. Considering the input constraints of the physical system, a joint-constraint model of the HRMMM was established, and the variable-substitution method was used to transform asymmetric constraints to symmetric constraints. All constraints were normalized by dividing by their maximum values. A hybrid controller based on pseudo-inverse (PI) and quadratic programming (QP) was designed to satisfy the real-time motion-control requirements in medical events. The PI method was used when there was no input saturation, and the QP method was used when saturation occurred. A quadratic performance index was designed to ensure smooth switching between PI and QP. The simulation results showed that the HRMMM could approach the target pose with a smooth motion trajectory, while meeting different types of input constraints.

An empirical study on the asset-light operation and corporate performance of China's tourism listed companies

Transitioning to an asset-light strategy is a significant shift for tourism companies in light of the global COVID-19 outbreak. This study investigates the impact of asset-light strategy on corporate performance using a sample of 588 firm-year observations from China A-share publicly traded tourism companies from 2003 to 2021. Using two-way fixed effects models, our results indicate that adopting an asset-light strategy can significantly improve the performance of tourism enterprises. We further verify that this influence mechanism is supply chain management using path analysis. More interestingly, the positive impact of asset-light strategy on enterprise performance is particularly significant in non-state-owned enterprises. Robustness tests with the system GMM method, the variable substitution method and the two-stage instrumental variables method support our main findings. The findings have significant ramifications for assisting the tourism industry, managers, and investors to strategically cope with settings that are complex and dynamic.

Chance-constrained resource allocation for cognitive wireless-powered backscatter communication networks

With the rapid development of the Internet of Things (IoT) and the increasing number of wireless nodes, the problems of scare spectrum and energy supply of nodes have become main issues. To achieve green IoT techniques and resolve the challenge of wireless power supply, wireless-powered backscatter communication as a promising transmission paradigm has been concerned by many scholars. In wireless-powered backscatter communication networks, the passive backscatter nodes can harvest the ambient radio frequency signals for the devices’ wireless charging and also reflect some information signals to the information receiver in a low-power-consumption way. To balance the relationship between the amount of energy harvesting and the amount of information rate, resource allocation is a key technique in wireless-powered backscatter communication networks. However, most of the current resource allocation algorithms assume available perfect channel state information and limited spectrum resource, it is impractical for actual backscatter systems due to the impact of channel delays, the nonlinearity of hardware circuits and quantization errors that may increase the possibility of outage probability. To this end, we investigate a robust resource allocation problem to improve system robustness and spectrum efficiency in a cognitive wireless-powered backscatter communication network, where secondary transmitters can work at the backscattering transmission mode and the harvest-then-transmit mode by a time division multiple access manner. The total throughput of the secondary users is maximized by jointly optimizing the transmission time, the transmit power, and the reflection coefficients of secondary transmitters under the constraints on the throughput outage probability of the users. To tackle the non-convex problem, we design a robust resource allocation algorithm to obtain the optimal solution by using the proper variable substitution method and Lagrange dual theory. Simulation results verify the effectiveness of the proposed algorithm in terms of lower outage probabilities.

A splitting lattice Boltzmann scheme for (2+1)-dimensional soliton solutions of the Kadomtsev-Petviashvili equation

<abstract> <p>Recently, considerable attention has been given to (2+1)-dimensional Kadomtsev-Petviashvili equations due to their extensive applications in solitons that widely exist in nonlinear science. Therefore, developing a reliable numerical algorithm for the Kadomtsev-Petviashvili equations is crucial. The lattice Boltzmann method, which has been an efficient simulation method in the last three decades, is a promising technique for solving Kadomtsev-Petviashvili equations. However, the traditional higher-order moment lattice Boltzmann model for the Kadomtsev-Petviashvili equations suffers from low accuracy because of error accumulation. To overcome this shortcoming, a splitting lattice Boltzmann scheme for (2+1)-dimensional Kadomtsev-Petviashvili-Ⅰ type equations is proposed in this paper. The variable substitution method is applied to transform the Kadomtsev-Petviashvili-Ⅰ type equation into two macroscopic equations. Two sets of distribution functions are employed to construct these two macroscopic equations. Moreover, three types of soliton solutions are numerically simulated by this algorithm. The numerical results imply that the splitting lattice Boltzmann schemes have an advantage over the traditional high-order moment lattice Boltzmann model in simulating the Kadomtsev-Petviashvili-Ⅰ type equations.</p> </abstract>

The carbon emission reduction effect of digital agriculture in China.

Carbon emission reduction is gaining increasing attention worldwide. This paper focuses on how the development of digital agriculture contributes to agricultural carbon emission reduction. To this end, the spatial characteristics, spillover effects, and driving factors of digital agriculture on agricultural carbon emissions are explored using panel data of 31 regions in China from 2011 to 2019 using a spatial econometric model and STIRPAT model with the extension of an ARDL method that was utilized to demonstrate the linkage amid variables. The results show that digital agriculture development reduces agricultural carbon emissions. Firstly, the results remain robust after estimation using the replacement weight method and the explanatory variable substitution method. Agricultural technological progress, agricultural industry structure, and rural education level all contribute to the reduction of agricultural carbon emissions in a region. Secondly, agricultural carbon emissions in the neighboring regions have a negative relationship with the agricultural industry structure in the region and a positive relationship with rural education level and agricultural technological level. Finally, strengthening the exchange of digital agriculture between regions and leveraging the intermediary effect of digital inclusive finance can effectively enhance the carbon emission reduction effect.

Reactive Power and Voltage Optimization under High Penetration of Distributed Generations and EVs

With the consumption of fossil energy and the deterioration of the environment, both distributed generation (DGs) including photovoltaic (PVs) and electric vehicles (EVs) have ushered in a period of rapid development. However, the DG’s randomness, intermittency, and large-scale EV charging have brought challenges to the safety and economy of the distribution network (DN). This paper comprehensively considers the impact of large-scale EVs and DGs of high penetration on the DN, establishing reactive power and voltage optimization model for minimizing the network loss and voltage deviation by regulating the energy storage (ES) and voltage adjusting devices including on-load tap changer (OLTC), capacitors banks (CB), and static var compensator (SVC). Next, the proposed model is simplified by the method of variable substitution, second-order cone programming (SOCP), and linearization. Finally, the validity of the model is verified by the IEEE 33-node simulation.