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Previous studies show that the indoor environment quality (IEQ) of buildings directly affects human health and comfort. This study aims to predict the change of indoor parameters at the next moment under the influences of the current indoor climate and outdoor climate and control the IEQ parameters based on the human thermal adaption in advance. We combine the simulation and the mathematical method to establish the office building model with air-conditioning and lighting systems and construct the bilinear model of the IEQ parameters and control variables. Unknown parameters are identified using the experimental method. Model predictive control (MPC) based on human thermal comfort is discussed by considering human thermal adaptation, and the neutral temperature is calculated through the dynamic relationship between outdoor and indoor temperatures. Results show that the temperature setpoint is adjusted in accordance with human adaptability, and the air-conditioning, fan, and lighting systems are controlled via MPC. The usage time of air-conditioning and light is reduced, and thus, energy is saved.

Airline disruption is universal phenomenon that block the originally scheduled flights, and the slow recovery scheduling causes a lot of losses to both the airline companies and the passengers. However, it is very difficult to generate a new recovery scheduling in a reasonable time by traditional methods, especially for large dimension airline disruption problem. To deal with this problem rapidly, the airline disruption problem will be reformulated as integer programmings and a distributed network, which is based on the fixed-point iterative method for integer programming, will be developed in this paper. In response to the airport closure, an airplane reschedule is constructed by these feasible flight lines. In the implementation of distributed network, a certain number of independent segments are obtained by dividing the solution space. As a feature of this fixed-point method, the number of partial feasible flight lines, which have to be calculated for finding an optimized airplane reschedule, is much fewer compared with the number needed by CPLEX CP Optimizer. This is the first distributed integer programming method to large airline disruption problems caused by airports closure. In the numerical results, the proposed distributed approach shows promising, especially for solving the large dimension airline disruption problem. CA extern

The execution of the airline operation is often deviated from the original schedule due to some unexpected disruptions, such as aircraft breakdowns and severe weather conditions. In this situation, a recovery plan is needed to get the irregular operation back to normal to minimize the losses of the airline. To produce recovery plans and solve the airline disruption problems, a novel modified traveling salesman problem model is proposed to generate sets of the feasible flight routes for each aircraft fleet type. Then, the feasible flight routes are reassigned to the available aircrafts in each fleet to form a recovery plan. Numerical results show that the approach proposed in this paper is efficient and promising.

There is a trade-off between human visual performance and energy cost. With an open office as the research object, personalised control with demand and daylight adaptation is considered in a lighti...

Graph partitioning, a classical NP-hard combinatorial optimization problem, is widely applied to industrial or management problems. In this study, an approximated solution of the graph partitioning problem is obtained by using a deterministic annealing neural network algorithm. The algorithm is a continuation method that attempts to obtain a high-quality solution by following a path of minimum points of a barrier problem as the barrier parameter is reduced from a sufficiently large positive number to 0. With the barrier parameter assumed to be any positive number, one minimum solution of the barrier problem can be found by the algorithm in a feasible descent direction. With a globally convergent iterative procedure, the feasible descent direction could be obtained by renewing Lagrange multipliers red. A distinctive feature of it is that the upper and lower bounds on the variables will be automatically satisfied on the condition that the step length is a value from 0 to 1. Four well-known algorithms are compared with the proposed one on 100 test samples. Simulation results show effectiveness of the proposed algorithm.

Public lighting has become a large energy consumption in the building automation. Therefore, it is a hot topic to design a reasonable and effective controller for smart light. Based on the calculation formula of the personnel location and the related knowledge of solid geometry and optics, this paper develops a lighting model which is mapping form the person’s position to the lighting area. Using this model, the lighting strategy, which satisfies both the energy saving and the personnel comfortableness, will be obtained. Numerical results show that with the movement of person the lamps also change to meet the illumination standard and to minimize the energy consumption. In this situation, the energy consumption of the lighting system reduces.

Considering the privacy requirements on initial states for second-order consensus in wireless sensor and actuator networks (WSAN s), we focus on the design of one privacy-preserving second-order consensus (PPSC) protocol in a distributed way, and investigate this issue from both the viewpoints of limiting the kind of information to be broadcasted and adding random noises to the broadcasted information. We also investigate the convergence rate and the privacy level of the proposed PPSC protocol, and drive that if only limited information of one node is kept by its neighboring nodes, both its initial velocity and position states will be privacy-preserved. Finally, simulation results are presented to verify the effectiveness of the proposed algorithm.

A new type of electronic voltage transformer is proposed in this study for big data background. By using the conventional inverted SF_6 transformer insulation structure, a coaxial capacitor sensor was constructed by designing a middle coaxial electrode between the high-voltage electrode and the ground electrode. The measurement of the voltage signal could be obtained by detecting the capacitance current i of the SF_6 coaxial capacitor. To improve the accuracy of the integrator, a high-precision digital integrator based on the Romberg algorithm is proposed in this study. This can not only guarantee the accuracy of computation, but also reduce the consumption time; in addition, the sampling point can be reused. By adopting the double shielding effect of the high-voltage shell and the grounding metal shield, the ability and stability of the coaxial capacitor divide could be effectively improved to resist the interference of stray electric fields. The factors that affect the coaxial capacitor were studied, such as position, temperature, and pressure, which will influence the value of the coaxial capacitor. Tests were carried out to verify the performance. The results showed that the voltage transformer based on the SF_6 coaxial capacitor satisfies the requirements of the 0.2 accuracy class. This study can promote the use of new high-performance products for data transmission in the era of big data and specific test analyses.

Classic core-based instrument transformers are more prone to magnetic saturation. This affects the measurement accuracy of such transformers and limits their applications in measuring large direct current (DC). Moreover, protection and control systems may exhibit malfunctions due to such measurement errors. This paper presents a more accurate method for current measurement based on a circular magnetic field sensing array. The proposed measurement approach utilizes multiple hall sensors that are evenly distributed on a circle. The average value of all hall sensors is regarded as the final measurement. The calculation model is established in the case of magnetic field interference of the parallel wire, and the simulation results show that the error decreases significantly when the number of hall sensors n is greater than 8. The measurement error is less than 0.06% when the wire spacing is greater than 2.5 times the radius of the sensor array. A simulation study on the off-center primary conductor is conducted, and a kind of hall sensor compensation method is adopted to improve the accuracy. The simulation and test results indicate that the measurement error of the system is less than 0.1%.

Graphene sheets are widely applied due to their unique and highly valuable properties, such as energy conservation materials in buildings. In this paper, we investigate the vibration behavior of double layer graphene sheets (DLGSs) in thermal environments which helps probe into the mechanism of energy conservation of graphene sheets in buildingmaterials. The nonlocal elastic theory and classical plate theory (CLPT) are used to derive the governing equations. The element-free method is employed to analyze the vibration behaviors of DLGSs embedded in an elastic medium. The accuracy of the solutions in this study is demonstrated by comparison with published results in the literature. Furthermore, a number of numerical results are presented to investigate the effects of various parameters (boundary conditions, nonlocal parameter, aspect ratio, side length, elastic foundation parameter, and temperature) on the frequency of DLGSs. OA gold - CA extern

The knapsack feasibility problems have been intensively studied both because of their immediate applications in industry and financial management, but more pronounced for theoretical reasons, as knapsack problems frequently occur by relaxation of various integer programming problems. In this work, the large-scale knapsack feasibility problem is divided into two subproblems. The first subproblem is transforming of the knapsack feasibility problem into a polytope judgement problem which is based on lattice basis reduction. In the next subproblem, a distributed implementation of Dang and Ye’s fixed-point iterative algorithm is introduced to solve the polytope judgement problem generated in the former subproblem. Compared with the branch and bound method, numerical results show that this distributed fixed-point method is effective.

Considering the energy consumption in open office lighting systems, one average-consensus-based distributed lighting control method is proposed in this paper. In the proposed system, each light emitting diode (LED) luminary is equipped with a co-located sensor-actuator in the ceiling, and the desired illuminance level for each workspace is set by the wireless smart device. With the introduction of average consensus algorithm, the average desired level for the open office is derived by the sensor- actuator nodes. Taking into account the daylight contributions, the actual and the error illuminance level at the workspace are calculated by the sensor-actuator nodes. Meanwhile the pulse width modulation (PWM) output for each LED luminary is modified according to the error illuminance level of its neighboring workspace in a distributed way. Simulations results verify the effectiveness of the proposed average-consensus-based distributed lighting control method.

This article proposed a controller base on On- Policy Monte Carlo Control method. It is aimed at operating indoor systems, such as air conditioner system, lightning system and air flow system. A state-of-the-art policy was found, dealing well with the trade off between power consumption and indoor satisfaction. Compared with fuzzy control, this policy works better than fuzzy control. Its convergence accuracy speed and convergence accuracy are greater than the fuzzy control.

The copper-benzene-1,3,5-tricarboxylate (Cu-BTC) attracts increasing attention because of its large BET surface area available for the adsorption of gases. However, low stability in water creates a barrier for its potential applications. In this study, graphene oxide (GO) and reduced graphene oxide (RGO) are adopted to modify the Cu-BTC. The influence of GO and RGO on the resulting BET surface area, pore diameter distribution, morphology and yield of the Cu-BTC are revealed. It is found that the adsorption abilities of the resulting composites for the polar and nonpolar gas molecules are closely related to the presence at surface of the functional groups of the used graphene samples, which provides a potential method to achieve selective adsorption. Furthermore, the preparation processes of the GO/Cu-BTC and RGO/Cu-BTC exert a significant effect on the performances of the resulting product, which is also studied in detail.

A novel thermal-resistance film is proposed, and its thermal post-buckling behavior is studied by using the meshless method. The Von Kármán plate model together with the nonlocal theory is adopted for the formulation of the problem. The post-buckling curve of the graphene sheet (GS) film is obtained. The effect of the parameters, such as nonlocal parameters, geometric size, geometric shape and elastic medium, on the thermal post-buckling response of the GSs film is examined. It is found that it is important to design proper geometric size and geometric shape and control the radius of tensionless area. This study provides theoretical guidance for fire resistance design of thermal-resistance films attached to glass façade.

Given the unique and extremely valuable properties, research has significantly focussed on graphene sheets (GSs). To premeditate the small-scale effect, the present work applies the nonlocal theory to study the buckling behavior of a double-layered GS (DLGS) embedded in an elastic foundation. To derive the equation, classical plate theory is adopted. For the elastic foundation, Pasternak-type model is used. In terms of buckling response, a meshless method is utilized to compute simulation results. Accordingly, we examine the effects of aspect ratio, geometry, boundary conditions and nonlocal parameters on the buckling responses of DLGSs.

A implementation of the distributed Dang and Ye’s fixed-point algorithm, which is a new alternative algorithm for integer programming, is developed in this paper. This fixed-point algorithm is derived from an increasing mapping which satisfies certain properties. A classical problem, which is called market split problem, has been solved by this distributed implementation. It is shown that this implementation is effective in numerical results. Besides, it can be used to other similar integer problems.

A distributed implementation of Dang's Fixed-Point iterative method is proposed to solve the market split problem which has been considered as a benchmark and a challenge to the algorithms solving linear systems with 0/1 variables. There are two steps to solve the market split problem in this paper. The first step is converting the problem to a reformulated polytope judgement problem based on lattice basis reduction. In the next step, the distributed Dang's method is used to judge whether there exits an integer point in the polytope. This is the first distributed implementation to solve the market split problem to our knowledge. Numerical results show that the approach is effective and it is more powerful than CPLEX to solve the market split problem.