Performance analysis of hybrid power configurations: Impact on primary energy intensity,carbon dioxide emissions,and life cycle costs

Utilization of Natural gas and Hydrogen to support current and future building energy needs to offset the total electric demand while improving the grid resiliency and energy efficiency was investigated. Demand side energy management will play an important role in efficiently managing the available energy resources. Performance assessment of different power generation and energy management configurations is presented in this paper. Development of solutions in addressing grid resiliency by providing the ability to design suitable configurations for meeting individual building energy needs is discussed. Primary movers (PM) such as internal combustion engines (ICE) and fuel cells (FC) along with small scale auxiliary renewable energy source such as photovoltaics (PV) were considered. Key attributes of total carbon foot-print, life cycle costs including capital and operational expenditure, electric grid offset or peak shaving capability, thermal energy availability and its further potential to offset total electric demand, and primary energy intensity are analyzed and discussed in detail.     

Hierarchically porous carbon derived from the activation of waste chestnut shells by potassium bicarbonate (KHCO3) for high-performance supercapacitor electrode

3D hierarchical porous carbon consisting of micropores, mesopores and macropores was successfully prepared through the activation of chestnut shell via KHCO₃. The influence of KHCO₃/chestnut shell ratio on the textural properties was carefully investigated and the structure, micrographs, and surface chemical status of the materials were expressed via X-Ray diffraction (XRD), transmission electron micrographs (TEM), scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS), respectively. With the optimized amount of KHCO₃, high specific pore surface area (2298 m² g^-1) and high total pore volume (1.51 cm³ g^-1) were achieved, endowing an advantageous electrochemical characteristics for the electrode as ultracapacitors in three-electrode system. At 2 A g^-1, a high specific electric capacity of 387 F g^-1 was reached. The remarkable electrochemical performances are mainly due to hierarchical porous structure with the high specific surface area (SSA) and the eminent total pore volume. It means that this hierarchical porous carbon prepared by activated by using KHCO₃ would have more promising foreground in the field of energy storage.     

A two-dimensional material for high capacity supercapacitors: S-doped graphene

In this work, sulfur-doped graphene-coated electrodes are prepared by cyclic voltammetry in different potential ranges and different cycles (from 10 to 50) for selective modification of electrodes by different functional groups. The prepared electrodes are characterized by spectroscopic, microscopic and electrochemical methods. In scanning electron microscopic analysis, formation of graphene layers and their porous structure have been determined. Electrochemical impedance spectroscopic and cyclic voltammetric analyses are also used in electrochemical characterization of the electrodes. Then, the prepared sulfur-doped graphene-coated electrodes by using cyclic voltammetry in one-step and low cost are used as electrode materials of supercapacitor for the first time in the literature. Since the mesoporous structure of the electrodes prepared in lower potential ranges increases, specific capacitance of the electrodes increases from 74 to 1833 mF cm⁻² with 10 mA cm⁻² current density. This result shows that specific capacitances of prepared electrodes are higher than those of the electrodes prepared with metal-doped in the literature.     

A hybrid fuzzy-GA algorithm for the integrated machine allocation problem with fuzzy demands

The integrated machine allocation and facility layout problem (IMALP) is a branch of the general facility layout problem in which, besides selecting machine locations, the processing route of each product is determined. Most research in this area suppose that the flow of material is certain and exact, which is an unrealistic assumption in today's dynamic and uncertain business environment. Therefore, in this paper the demand volume has been assumed as fuzzy numbers with different membership functions. To solve this problem, the deterministic model is first integrated with a fuzzy implication via the expected value model, and thereafter an intelligent hybrid algorithm, including a genetic algorithm and a fuzzy simulation approach has been applied. Finally, the efficiency of the proposed algorithm is evaluated with a set of numerical examples. The results show the effectiveness of the hybrid algorithm in finding the IMALP solutions.     

Predicting the settlement of geosynthetic-reinforced soil foundations using evolutionary artificial intelligence technique

In order to ensure safe and sustainable design of geosynthetic-reinforced soil foundation (GRSF), settlement prediction is a challenging task for practising civil/geotechnical engineers. In this paper, a new hybrid technique for predicting the settlement of GRSF has been proposed based on the combination of evolutionary algorithm, that is, grey-wolf optimisation (GWO) and artificial neural network (ANN), abbreviated as ANN-GWO model. For this purpose, the reliable pertinent data were generated through numerical simulations conducted on validated large-scale 3-D finite element model. The predictive power of the model was assessed using various well-established statistical indices, and also validated against several independent scientific studies as reported in literature. Furthermore, the sensitivity analysis was conducted to examine the robustness and reliability of the model. The results as obtained have indicated that the developed hybrid ANN-GWO model can estimate the maximum settlement of GRSF under service loads in a reliable and intelligent way, and thus, can be deployed as a predictive tool for the preliminary design of GRSF. Finally, the model was translated into functional relationship which can be executed without the need of any expensive computer-based program.     

汽车动力系统匹配设计及发展趋势展望

介绍汽车动力系统匹配设计相关机制,并重点对混合动力汽车、智能网联汽车、燃料电池汽车的未来发展趋势进行了展望。随着计算机技术的不断发展,针对汽车动力系统进行的匹配设计过程也得以相应优化,由此显著提升了汽车技术水平及整车销量。考虑到我国汽车工业现状,仍需持续开展相关研究,逐步缩小与世界领先水平的差距。     

中国先进加工制造工艺与装备技术中的关键科学问题

根据中国国家自然科学基金委员会安排，研讨先进加工制造工艺与装备科学与技术的发展趋势。针对中国先进加工制造和装备学科存在的基础研究不系统、不深入的共性状况，以国家需求为目标，以加强先进制造工艺与装备的理论基础研究和应用基础研究为突破口，提出国家自然科学基金“十一五”(2006～2010)期间先进加工制造工艺和装备领域需要研究的科学问题、研究方向、工程目标，以及应该优先发展的重点方向。 先进加工制造是实现高效率、高精度和低成本制造的技术支撑。先进加工制造的目标是高效化、精密化、智能化、集成化、数字化和洁净化，关键技术包括高速/高效切削加工技术、高速/超高速磨削技术、精密/超精密加工技术、非传统加工及其复合加工技术，以及相关的先进加工制造装备的制造技术。 摘要根据中国国家自然科学基金委员会安排，研讨先进加工制造工艺与装备科学与技术的发展趋势。针对中国先进加工制造和装备学科存在的基础研究不系统、不深入的共性状况，以国家需求为目标，以加强先进制造工艺与装备的理论基础研究和应用基础研究为突破口，提出国家自然科学基金“十一五”(2006～2010)期间先进加工制造工艺和装备领域需要研究的科学问题、研究方向、工程目标，以及应该优先发展的重点方向。 先进加工制造是实现高效率、高精度和低成本制造的技术支撑。先进加工制造的目标是高效化、精密化、智能化、集成化、数字化和洁净化，关键技术包括高速/高效切削加工技术、高速/超高速磨削技术、精密/超精密加工技术、非传统加工及其复合加工技术，以及相关的先进加工制造装备的制造技术。 高速/高效切削加工技术的科学问题包括切削加工时刀具和工件材料相互作用过程刀具摩擦、磨损和破坏机理，工件材料高速切削变形理论与工件表面成形机理，高速切削刀具与机床的动力学分析，高速切削过程的智能监控理论与技术。研究方向包括高速/高效切削机床与刀具，难加工材料的高速/高效切削加工，高速/高效切削表面质量，高速/高效切削加工的动力学与稳定性。工程目标包括超高速切削，机床主轴转速达到1×106r·min-1，铣削铝及其合金的切削速度达到1×104m·min-1；高性能切削，机床主轴功率达到100kW，进给速度达到50m·min-1；采用多坐标驱动，提高机床的柔性和效率。     

Minimizing makespan in reentrant flow-shops using hybrid tabu search

This study considers the problem of reentrant flow-shop (RFS) scheduling, and applies hybrid tabu search (HTS) to minimize the makespan of jobs. The hybridization method is used to enhance the performance of pure tabu search. The HTS is compared to the optimal solutions generated by the integer programming technique, and to the near optimal solutions generated by pure tabu search and the non-delay schedule generation procedure. Computational experiments are performed to illustrate the effectiveness and efficiency of the proposed HTS algorithm.     

一种新颖的两通道混合滤波器组的设计原理

提出了一种全新的两通道混合滤波器组的设计方法,利用基于功率互补对的模拟分解滤波器,均匀分割输入模拟信号。利用IFFT实现了数字综合滤波器的设计,以保证近似完全重构,并提出了单路滤波的两通道混合滤波器组。32阶数字综合滤波器配合3阶模拟分解滤波器,具有2.2×1-0 6dB的最大失真误差和-110dB的最大混叠误差,满足16b it的ADC系统要求。     

A heuristic method for the combined location routing and inventory problem

The combined location routing and inventory problem (CLRIP) is used to allocate depots from several potential locations, to schedule vehicles’ routes to meet customers’ demands, and to determine the inventory policy based on the information of customers’ demands, in order to minimize the total system cost. Since finding the optimal solution(s) for this problem is a nonpolynomial (NP) problem, several heuristics for searching local optima have been proposed. However, the solutions for these heuristics are trapped in local optima. Global search heuristic methods, such as tabu search, simulated annealing method, etc., have been known for overcoming the combinatorial problems such as CLRIP, etc. In this paper, the CLRIP is decomposed into two subproblems: depot location-allocation problem, and routing and inventory problem. A heuristic method is proposed to find solutions for CLRIP. First of all, an initial solution for CLRIP is determined. Then a hybrid heuristic combining tabu search with simulated annealing sharing the same tabu list is used to improve the initial solution for each subproblem separately and alternatively. The proposed heuristic method is tested and evaluated via simulation. The results show the proposed heuristic method is better than the existing methods and global search heuristic methods in terms of average system cost.