Efficient Constraint Research Articles

Optimal Design of Turn-Off Switching Loss of Full-Bridge CLLC Converter

The turn-off loss of the switches is the main loss of the full-bridge CLLC converter under high-frequency conditions, and it is a variable closely related to the resonance parameters of the resonant tank and the voltage gain. Firstly, the gain characteristics of the full-bridge CLLC converter are analyzed based on the first harmonic approximation (FHA). Then, the precise functional relationships of the switches’ turn-off current and turn-off loss are derived by time domain analysis (TDA). On this basis, the constraint space of resonance parameters is reduced based on the monotonicity constraints of gain curve, soft switch realization conditions, overall efficiency constraints and turn-off loss characteristics constraints, and the particle swarm optimization (PSO) algorithm is used to solve the resonant parameter under the turn-off loss optimization. Finally, a simulation model was built through optimized parameters, and prototype experiments were carried out. Meanwhile, compared with the traditional loss optimization method, it is proved that the proposed method can make the output voltage closer to the design value and reduce the turn-off current and turn-off loss under the premise of ensuring soft switching.

Collision-Free Model Predictive Trajectory Tracking Control for UAVs in Obstacle Environment

In this paper, we propose a collision-free model predictive trajectory tracking control algorithm for unmanned aerial vehicles (UAVs) in environments with both static obstacles and dynamic obstacles. Collision avoidance is ensured by obtaining outer polyhedral approximations of each interval of the dynamic obstacles trajectories based on MINVO basis, and then optimizing a plane to separate the polyhedra and the trajectory of the UAV. By incorporating the resulting computationally efficient collisionfree constraints and divers physical constraints, a model predictive control (MPC) optimization problem is formulated with a tailored terminal constraint set, which can be solved by a standard nonlinear programming solver. Moreover, the control theoretic properties are established, including recursive feasibility, the guarantee of collision avoidance, as well as closed-loop stability. Finally, the efficacy of the proposed algorithm is successfully evaluated by a simulation in a multi-obstacle environment.

Low-carbon design based on conceptual design methods for mechanical and electrical products

This paper presents a conceptual product design method that considers the carbon emission factors of mechanical and electrical products. This method aims to consider low carbon issues prior to product design. Based on a comprehensive analysis of conventional product design procedures, the study extracts design information related to greenhouse gas (GHG) emissions, itemizes and quantifies the information, and ultimately uncovers the relationship among carbon emissions, function, and economic factors of newly designed products. This study explains the proposed concepts of carbon efficiency (CE) and carbon factor and combines them with the product design process to present a low-carbon design process of mechanical and electrical products. Furthermore, this paper presents a low-carbon design method of mechanical and electrical products, drawing on the product family design idea, with GHG efficiency and cost constraint. In particular, GHG efficiency pays attention to product function realization efficiency and economic factors. The potential value of the method is demonstrated in a case study of a tomato picking robot.

An Economic Analysis of Marketing of Maize and Constraints Faced by the Maize Growers in Production and Marketing in Ariyalur District of Tamil Nadu in India

The present study was conducted in Ariyalur district of Tamil Nadu. Totally 100 respondents were randomly selected and interviewed from the district. The data was gathered in the form of pre-structured interview schedule. The study shows that different marketing channels with their marketing efficiency and major constraints faced by the maize growers in production and marketing of maize in the district. Totally three channels are shown in the study channel I with marketing efficiency 10.15, channel II with marketing efficiency 6.72 and channel III with marketing efficiency 3.84. For production the major constraints were eccentric rainfall, high input cost required for cultivation, high wage rate for labours, drastic pest occurrence and birds that eats the crop in budding stage, especially peacocks. From the above constraints, disturbance of birds was a major constraint. While discussing about marketing constraints, price fluctuation, distant market location, commission for middlemen, lack of timely credits and high transport cost. From the above marketing constraints, price fluctuations were a major constraint identified in Ariyalur district.

Pre-Sizing Approach of a Fuel Cell-Battery Hybrid Power System with Interleaved Converters

This paper proposes a design methodology that is dedicated to improving the concept of a modular hybrid power chain that uses interleaved converters. The approach involves optimising the system under multi-physical constraints, where the number of cells in the interleaved converters is considered as a key modular parameter. The methodology uses analytical models to strike a balance between computation time and result accuracy. This compromise is indispensable to the construction of a smart design approach under multi-physical constraints, such as electric, efficiency, volume, and thermal constraints. The proposed approach has been applied to a hybrid fuel cell and battery power system for automotive applications; the goal is to obtain a global optimal architecture chain by optimising the number of interleaved converter cells and by determining appropriate power electronics components and the optimal sizing of sources. This constitutes the primary step for providing an effective pre-design support tool for considering architecture modularity, facilitating the use of new technologies in the early design stage. The results showed that the interleaving concept allows for better flexibility in respecting the design constraints to improve the design of hybrid power systems. The analysis also highlights the current limitations and performance of the optimisation method and suggests new areas for future work.

Determinants of Technical Inefficiency in Wheat Production: An Application of the Stochastic Frontier Model - Nigeria

This study examined wheat farming technical efficiency, its determinants and wheat production constraints among wheat farmers in the wheat producing states of Nigeria. The study did not cover Borno and Yobe wheat producing states due to volatile insecurity situation in the areas. Primary data were obtained from 866 farmers using proportionate selection from the states list of farmers. A structured questionnaire and interview schedule were administered to the farmers to collect data for the study. A Stochastic frontier model was used to capture wheat production efficiency and its determinants while, Likert scale was employed to reveal severity of wheat production constraints among farmers in the study area. Land size, quantity of seed planted, quantity of NPK fertilizer applied, quantity of Urea fertilizer applied and labour used in man-day were found to be positive and statistically significant. The most severe constraints affecting wheat production in the study area were poor access to credit, lack of dependable wheat market outlay, and access to improved and quality seed among others. There should be adequate incentives (timely supply of improved wheat seed, fertilizer and irrigation facilities at affordable prices.

LiteGaze: Neural architecture search for efficient gaze estimation.

Gaze estimation plays a critical role in human-centered vision applications such as human-computer interaction and virtual reality. Although significant progress has been made in automatic gaze estimation by deep convolutional neural networks, it is still difficult to directly deploy deep learning based gaze estimation models across different edge devices, due to the high computational cost and various resource constraints. This work proposes LiteGaze, a deep learning framework to learn architectures for efficient gaze estimation via neural architecture search (NAS). Inspired by the once-for-all model (Cai et al., 2020), this work decouples the model training and architecture search into two different stages. In particular, a supernet is trained to support diverse architectural settings. Then specialized sub-networks are selected from the obtained supernet, given different efficiency constraints. Extensive experiments are performed on two gaze estimation datasets and demonstrate the superiority of the proposed method over previous works, advancing the real-time gaze estimation on edge devices.

Computationally Efficient Data-Driven Joint Chance Constraints for Power Systems Scheduling

Although data-driven nonparametric Joint Chance Constraints (JCCs) may lead to more reliable decision-making than individual chance constraints, their computational complexity is a major bottleneck. This paper presents computationally efficient data-driven nonparametric joint chance-constrained programming for multi-interval power systems management. Reserve and transmission line constraints are modeled as data-driven JCCs. Piecewise uniform kernel functions incorporate historical data of uncertain parameters into optimization. Data-driven nonparametric JCCs are modeled as a product of integrated kernel functions. Two approaches are proposed to linearize data-driven nonparametric JCCs. i) The noncontinuous kernel function is linearized with Special Ordered Sets of type 1 (SOS1) variables. ii) A tight convex envelope of multilinear monomial terms, which appear due to the product of kernel functions, is approximated by an optimization subproblem making the scheduling problem bi-level optimization. The continuity and linearity of the lower-level convex envelope approximation subproblem allow replacing it with optimality conditions to form a single-level scheduling problem. Simulation results show the tightness of the proposed linearization approaches and the computational efficiency of data-driven JCC programming.

Inversion of the Complex Refractive Index of Au-Ag Alloy Nanospheres Based on the Contour Intersection Method.

The contour intersection method is a new method used to invert the complex refractive index of small particles. Research has yet to be reported on using this method to invert the complex refractive index of nanoparticles. This paper reports the feasibility and reliability of the contour intersection method in the inversion of the complex refractive index of nanoparticles using Au-Ag alloy nanospheres. The Mie theory and the size-dependent dielectric function are used to calculate the light scattering and absorption efficiency of Au-Ag alloy nanospheres corresponding to the complex refractive index. The complex refractive index of the particles is obtained by inversion with the contour intersection method. The backscattering efficiency constraint method is used to determine the unique solution when multiple valid solutions from the contour intersection method appear. The effects of the Au component percentage, particle size, and measurement errors on the inversion results are quantitatively analyzed. Finally, the inversion accuracy is compared and analyzed with the traditional iterative method. The results show that as long as the light scattering efficiency, light absorption efficiency, and backscattering efficiency of Au nanospheres can be measured, the accurate complex refractive index can also be calculated by inversion using the contour intersection method. The accuracy of the inversion results can be ensured when the measurement error is less than 5%. The results of inversion using the contour intersection method are better than those of the iterative methods under the same conditions. This study provides a simple and reliable inversion method for measuring the complex refractive index of Au-Ag alloy nanospheres.

MAPTkit: An environmental management decision‐tool for inclusive, equitable and representative stakeholder attribute mapping

Abstract Inclusive, comprehensive Stakeholder Identification and Mapping processes are vital for successful environmental management. This is relevant as multi‐disciplinary collaboration becomes increasingly popular, and the diversity of people influenced by, or involved in, the management of most projects is greater than ever before. Understanding how relevant parties are analysed in environmental management programmes is required to enable robust and considered methodologies as well as successful, just and equitable outcomes. The aim of this study was to improve the attribute mapping process, increasing transparency and ensuring representation is both comprehensive and equitable. A rapid scoping review of Scopus and Web of Science was undertaken to collate and analyse peer‐reviewed, published evidence on stakeholder analysis, with a focus on the mapping processes involved in identifying stakeholders and their attributes. Of the Initial 359 identified papers, 61 were included after three stages of screening. Our results indicate that there is little consistency among practitioners to ensure that Identifying and Mapping Stakeholders is representative: <20% of Case Studies (n = 9) checked the relevancy of their stakeholders after identification. Additionally, definitions at all stages of the stakeholder analysis process were inconsistent across the case studies. Fewer than half of the Case Studies included a definition of Stakeholder (n = 22) or of stakeholder analysis (n = 25). Capturing a representative sample of relevant parties, without compromising on efficiency, financial or practical constraints, is difficult. Having consistent definitions for the term Stakeholders and stakeholder analysis within environmental management is an important step. Based on the scoping review, we formalise the Analysis process into six stages. Through the scoping review findings, a decision support tool, MAPTkit (Mapped Attribute Profiling Toolkit) was developed to visualise the heterogeneity and representation of stakeholders across several user‐determined attributes. This tool is non‐prescriptive, drawing attention to potential issues with stakeholder analysis, such as misrepresentation of real‐world stakeholder communities. This ensures engagement across the full range of people to ensure that environmental management projects are multi‐disciplinary and collaborative, while promoting fair and equitable representation.

Rotating detonation combustors for propulsion: Some fundamental, numerical and experimental aspects

Propulsion systems based on the constant-pressure combustion process have reached maturity in terms of performance, which is close to its theoretical limit. Technological breakthroughs are needed to develop more efficient transportation systems that meet today’s demands for reduced environmental impact and increased performance. The Rotating Detonation Engine (RDE), a specific implementation of the detonation process, appears today as a promising candidate due to its high thermal efficiency, wide operating Mach range, short combustion time and, thus, high compactness. Following the first proofs of concept presented in the 1960s, the last decade has seen a significant increase in laboratory demonstrators with different fuels, injection techniques, operating conditions, dimensions and geometric configurations. Recently, two flight tests of rocket-type RDEs have been reported in Japan and Poland, supervized by Professors Kasahara (Nagoya University) and Wolanski (Warsaw University), respectively. Engineering approaches are now required to design industrial systems whose missions impose efficiency and reliability constraints. The latter may render ineffective the simplified solutions and configurations developed under laboratory conditions. This requires understanding the fundamentals of detonation dynamics relevant to the RDE and the interrelated optimizations of the device components. This article summarizes some of the authors’ experimental and numerical work on fundamental and applied issues now considered to affect, individually or in combination, the efficiency and reliability of the RDE. These are the structure of the detonation reaction zone, the detonation dynamics for rotating regimes, the injection configurations, the chamber geometry, and the integration constraints.

Optimizing Water Distribution in Transboundary Rivers Based on a Synthesis–Dynamic–Harmonious Approach: A Case Study of the Yellow River Basin, China

It has been difficult to revise and adjust the water distribution of the Yellow River in 1987 (1987 water distribution scheme). By gathering data and studies from previous literature, this paper summarized some water distribution ideas, principles and rules in transboundary rivers. We proposed the “synthesis–dynamic–harmonious” water distribution method (SDH), and applied it to the actual conditions of the Yellow River basin. Through the SDH method, we calculated a new scheme for water distribution in the Yellow River and analyzed the results. The key findings of this study are summarized below. Firstly, the water distribution of transboundary rivers required the establishment of advanced water distribution ideas. Secondly, the proposed water distribution method took into account a variety of factors: with the change in distributable water volume, the same ratio changes and meets the minimum water demand and water efficiency constraints. Thirdly, the 1987, the water distribution scheme needed some adjustment. Fourthly, under the new Yellow River basin water distribution scheme (“19ZQT” water distribution scheme), Shandong, Inner Mongolia, and Henan account for 50% of the total water distribution. Sichuan accounts for only 0.3% of the total. Compared with the 1987 water distribution scheme, Hebei and Tianjin reduced the amount of water allocated by 51.2%, while Shaanxi increased it by 24.89%. In this paper, considering the changes in the total distributable water volume, the new Yellow River water distribution scheme (“19ZQT” water distribution scheme) assumed water distribution of 37 billion m3 and 30 billion m3, upon which calculations were performed. This study should provide a scientific and reasonable scheme for water distribution of transboundary rivers, and rational utilization of water resources. It should lay a solid foundation for the high-quality development of the Yellow River basin.

Economic Analysis of Cucumber Market Performance and their Constraints in Sultanpur District of Uttar Pradesh

In this paper examine the marketing efficiency, marketing cost, market margin, price spread and marketing constraints in Sultanpur district of Uttar Pradesh. A multistage stratified purposive cum random sampling technique was applied for the selection of district, block, villages and respondents. Total 100 growers were selected randomly through proportionate allocation method in the population during 2021-22. The primary data were collected through survey schedule with the help of personal interviews. The objectives were achieved by using shephered's formula for marketing efficiency and Garrett ranking technique for the identify the major marketing constraints. There are three types of marketing channels were observed in cucumber marketing i.e., Channel-I (producer → consumer), Channel-II (producer → retailer → consumer) and Channel-III (producer → wholesaler → retailer → consumer). Overall maximum produce of cucumber was sold by different group of farms through channel-III. Moreover, cucumber growers were also faced different types of marketing constraints. Major three marketing constraints faced by the growers were perishability nature of commodity, lack of storage facilities and grading problems, respectively. Suggestions of cucumber farmers to overcome these constraints are storage facilities in mandi should be provided to the farmers for their perishable products and entrusting government representatives with marketing duties in exchange for a fair fee.

Empirical Analysis of Financing Efficiency and Constraints Effects on the Green Innovation of Green Supply Chain Enterprises: A Case Study of China

Along with the deterioration of environmental problems, the green supply chain has become an important strategy for Chinese enterprises to improve their competitiveness in the global market. Most enterprises in green supply chains have promoted their green innovation and thus have improved their green performance by managing upstream and downstream enterprises. However, the green innovation capability might be also related to the financing efficiency and financing constraints of enterprises. To reveal the impact of financing efficiency and financing constraints on corporate green innovation, we conducted an empirical study. We considered a sample of 120 listed companies of the green supply chain from 2018 to 2020. The financing efficiency score was calculated using the input–output analysis method of data envelopment analysis, while the financing constraint score was measured using the financing constraints model. Further, multiple linear regression was used to estimate the regression coefficient and investigate the impacts of financing efficiency and financing constraints on corporate green innovation. The results show that a higher financing efficiency can promote green innovation and the financing constraints can limit the green innovation of green supply chain enterprises. Afterward, we provide a summary of innovation embedded in green supply chains.

An efficient pre-hardened cryogenic forming process for AA7075 aluminum alloy sheets

Currently, due to the requirement of lightweight in the transportation field, the demand for high-strength aluminum alloy is increasing, but it is difficult for the traditional forming processes to balance the three components of formability, strength and efficiency. In order to solve this problem, a novel stamping process for high-strength AA7075 aluminum alloy sheets is proposed, termed Pre-hardened Cryogenic Forming (PCF) process. PCF process is based on the W-temper alloy and to fulfill simultaneously the demands of good cryogenic formability and high post-formed strength through a suitable ratio of microstructure between the solution-treated matrix and the pre-aged second phases, thereby cancelling the additional artificial aging treatment and achieving high-efficiency. The good cryogenic formability is assured by solution-treated matrix, while the initial strength and further artificial age-hardening during paint baking are regulated by means of pre-aged second phases. A critical issue for PCF process is to determine the pre-aging process window, i.e., a suitable combination of pre-aging temperature and time period, because there is a contradiction between the cryogenic formability and post-formed strength under the constraint of high efficiency. The results of tensile tests show that AA7075 aluminum alloy after pre-aging at 120 °C for 1 h (PA-120-1h) can achieve excellent comprehensive mechanical properties of cryogenic plasticity and post-baking strength. Combined with the analysis of micro-experimental results, the optimal pre-aging process window of AA7075 aluminum alloy is to ensure that the volume fraction of fine precipitates is between 2.5 % and 4 %, and the recommended ratio of the fine precipitates (<2 nm/≥2 nm) is about 1.5. The mixed structure of the GP zones and the η′ phases for PA-120-1h alloy is the suitable combination of strengthening precipitates for balancing cryogenic plasticity and post-baking strength. Based on the newly-designed cooling system, stamping tests are conducted on a W-shaped beam component to verify the engineering feasibility. Based on PA-120-1h alloy sheets, the component with improved surface quality can be successfully formed by PCF process. The final post-baking strength exceeds 92 % of the tensile strength of AA7075-T6 alloy without extra heat treatment, and the thickness reduction rate is within 10 %. Regardless of the immersion time of the sheets in liquid nitrogen, the PCF process can be finished within 2 min, greatly improving the forming efficiency.

Performance evaluation of a Wi-Fi-based multi-node network for distributed audio-visual sensors

The experimental research described in this manuscript proposes a complete network system for distributed multimedia acquisition by mobile remote nodes, streaming to a central unit, and centralized real-time processing of the collected signals. Particular attention is placed on the hardware structure of the system and on the research of the best network performances for an efficient and secure streaming. Specifically, these acoustic and video sensors, microphone arrays and video cameras respectively, can be employed in any robotic vehicles and systems, both mobile and fixed. The main objective is to intercept unidentified sources, like any kind of vehicles or robotic vehicles, drones, or people whose identity is not a-priory known whose instantaneous location and trajectory are also unknown. The proposed multimedia network infrastructure is analysed and studied in terms of efficiency and robustness, and experiments are conducted on the field to validate it. The hardware and software components of the system were developed using suitable technologies and multimedia transmission protocols to meet the requirements and constraints of computation performance, energy efficiency, and data transmission security.

The numerical error of the Xinanjiang model

The numerical error of the Xinanjiang (XAJ) model has long been ignored, despite its wide application in China. Separating the mathematically formulated model from the computationally formulated model and further solving by an appropriate time-stepping scheme provides a chance to systematically examine the numerical error of the XAJ model because the exact analytical solution is difficult to obtain owing to its nonlinearity. The mathematically formulated model is proposed by deriving a state-space representation of the XAJ model by identifying the state variables, fluxes, and governing differential equations. Five experiments were conducted around the original XAJ model and its state-space representation with different parameter groups, input series, and time-stepping schemes to examine the numerical error at the submodule and model levels. We found that only the tension water storage capacity curve submodule of the original XAJ model is numerical error-free, and the adaptive-step explicit fourth-order Runge-Kutta scheme is the most efficient because it balances the accuracy, efficiency, and physical constraint preservation. The numerical error of the total amount of the discharge at the watershed outlet within a time period (Q∗) produced by the original XAJ model is relatively large, which mainly comes from the free water storage capacity curve submodule. The large numerical error of Q∗ occurs with high precipitation intensity, and decreases as the flood receded. The submodules related to the runoff generation process introduce and amplify numerical errors, while the submodules related to the runoff concentration process has the ability to alleviate numerical errors. This study helps to deepen our understanding of the numerical error of the XAJ model, and thus guides its application and modification.

An efficient control allocation algorithm for over-actuated AUVs trajectory tracking with fault-tolerant control

Fault-tolerant control of actuator faults in over-actuated autonomous underwater vehicles (AUVs) during trajectory tracking has involved problems. First, the fault-tolerant control method of controlling typical rudder faults, including lost, jammed, and/or deformed rudders, is introduced to reconstruct the control input, and a complete scheme of self-diagnosis and fault-tolerant control is proposed based on a sliding mode observer (SMO). Secondly, an efficient nonlinear saturation constraint sequential quadratic programming (SC-SQP) algorithm is proposed to solve the control allocation problem of multi-constraint quadratic programming, in particular with the motion in the initial or kinetic cycle transition stages. Considering the time-varying and unknown disturbances that occur in oceans, the control moments are compensated by the SMO to resist the perturbation of the hydrodynamic coefficient. Finally, the simulations show that the SC-SQP algorithm is efficient and can be used to solve the typical rudder faults with perturbation of the hydrodynamic coefficient during the fault-tolerant trajectory tracking control for over-actuated AUVs.

Production scheduling in a reconfigurable manufacturing system benefiting from human-robot collaboration

Nowadays, the manufacturing sector needs higher levels of flexibility to confront the extremely volatile market. Accordingly, exploiting both machine and workforce reconfigurability as two critical sources of flexibility is advantageous. In this regard, for the first time, this paper explores an integrated production scheduling and workforce planning problem in a Reconfigurable Manufacturing System (RMS) benefiting from reconfigurable machines and human-robot collaboration. A new Mixed-Integer Linear Programming (MILP) model and an efficient Constraint Programming (CP) model are developed to formulate the problem, minimising the makespan as the performance metric. Due to the high complexity of the problem, the MILP model cannot handle large-sized instances. Hence, to evaluate the performance of the CP model in large-sized instances, a lower bound is derived based on the relaxation of the problem. Finally, extensive computational experiments are carried out to assess the performance of the devised MILP and CP models and provide general recommendations for managers dealing with such a complex problem. The results reveal the superiority of the CP model over the MILP model in small- and medium-sized instances. Moreover, the CP model can find high-quality solutions for large-sized instances within a reasonable computational time.

Research on the impact of digital transformation on Enterprise Risk

This paper selects Shanghai and Shenzhen A-share companies from 2011 to 2020 as research samples to explore the impact of digital transformation on enterprise market risk and its mechanism.The results show that digital transformation can effectively reduce the market risks faced by enterprises. Mechanism test shows that digitalization reduces enterprise risks by improving enterprise total factor productivity and alleviating financing constraints, and production efficiency and financing constraints play a part of the intermediary effect.The conclusion of this paper has certain reference significance for boosting the confidence of enterprises in digitalization and reducing the market risk of enterprises.