New development in Fe/Co catalysts:Structure modulation and performance optimization for syngas conversion

C1 chemistry is the essence of coal chemistry and natural gas chemistry. Catalytic methods to efficiently convert C1 molecules into fuels and chemicals have been extensively studied. Syngas（CO ＋H_2） conversion is the most important industrial reaction system in C1 chemistry, and Fe and Co catalysts, two major industrial catalysts, have been the focus of fundamental research and industrial application. In the last decade, considerable research efforts have been devoted to discoveries concerning catalyst structure and increasing market demands for olefins and oxygenates. Since the development of efficient catalysts would strongly benefit from catalyst design and the establishment of a new reaction system, this review comprehensively overviews syngas conversion in three main reactions, highlights the advances recently made and the challenges that remain open, and will stimulate future research activities. The first part of the review summarizes the breakthroughs in Fischer-Tropsch synthesis regarding the optimization of activity and stability, determination of the active phase, and mechanistic studies. The second part overviews the modulation of catalytic structure and product selectivity for Fischer-Tropsch to olefins（FTO）. Catalysts designed to produce higher alcohols, as well as to tune product selectivity in C1 chemistry, are described in the third section. Finally, present challenges in syngas conversion are proposed, and the solutions and prospects are discussed from the viewpoint of fundamental research and practical application. This review summarizes the latest advances in the design, preparation, and application of Fe/Co-based catalysts toward syngas conversion and presents the challenges and future directions in producing value-added fuels.

The research on direct-drive wave energy conversion system and performance optimization

A direct-drive wave energy conversion system based on a three-phase permanent magnet tubular linear generator （PMTLG） and a heaving buoy is proposed to convert wave energy into electrical energy. Sufficient experimental methods are adopted to compare the computer simulations, the validity of which is verified by the experiment results from a wave tank laboratory. In the experiment, the motion curves of heaving buoy are with small fluctuations, mainly caused by the PMTLG＇s detent force. For the reduction of these small fluctuations and a maximum operational efficiency of the direct-drive wave energy conversion system, the PMTLG＇s detent force minimization technique and the heaving buoy optimization will be discussed. It is discovered that the operational efficiency of the direct-drive wave energy conversion system increases dramatically after optimization. The experiment and optimization results will provide useful reference for the future research on ocean wave energy conversion system.

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

Ultra-broadband and wide-angle reflective terahertz polarization conversion metasurface based on topological optimization

Terahertz polarization conversion devices have significant potential applications in various fields such as terahertzimaging and spectroscopy.In this paper,we utilize genetic algorithms to topologically optimize the metasurface unit cellsand design a reflective linear polarization conversion metasurface with ultra-broadband and wide-angle characteristics.By partitioning the metallic pattern layer into quadrants,the encoding length is effectively reduced,resulting in a shorteroptimization time.The research results indicate that the converter possesses a polarization conversion efficiency ratio higherthan 90%and a relative bandwidth ratio of 125%in a range of 0.231-0.995 THz.Meanwhile,it can maintain excellentpolarization conversion properties when the incident angle of terahertz waves is less than 45°and the polarization angle isless than 15°,demonstrating excellent practicality.New insights are provided for the design of terahertz wide-angle ultrawidebandpolarization conversion devices,and the proposed metasurfce has potential applications in terahertz polarizationimaging,spectroscopy and communication fields.

Optimal Timing of Business Conversion for Solvency Improvement

In this paper,we study the optimal timing to convert the risk of business for an insurance company in order to improve its solvency.The cash flow of company evolves according to a jump-diffusion process.Business conversion option offers the company an opportunity to transfer the jump risk business out.In exchange for this option,the company needs to pay both fixed and proportional transaction costs.The proportional cost can also be seen as the profit loading of the jump risk business.We formulated this problem as an optimal stopping problem.By solving this stopping problem,we find that the optimal timing of business conversion mainly depends on the profit loading of the jump risk business.A larger profit loading would make the conversion option valueless.The fixed cost,however,only delays the optimal timing of business conversion.In the end,numerical results are provided to illustrate the impacts of transaction costs and environmental parameters to the optimal strategies.

Optimal Planning of Hybrid AC/DC Low-voltage Distribution Networks Considering DC Conversion of Three-phase Four-wire Low-voltage AC Systems

The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple pow er quality problems by the flexible power regulation capability of voltage source converters.This paper proposes schemes to es tablish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC op eration.The characteristics and DC conversion constraints of typical LVDNs are analyzed.In addition,converter configura tions for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC configurations.Moreover,an optimal planning method of hybrid AC/DC LVDNs is proposed,which is modeled as a bi-level programming model considering the annual investments and three-phase unbalance.Simulations are conducted to verify the effectiveness of the proposed optimal planning method.Sim ulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reduc ing issues related to voltage violation and unbalance.

Oscillation and Conversion Performance of Double-Float Wave Energy Converter

In this study, we investigated the hydrodynamic and energy conversion performance of a double-float wave energy converter(WEC) based on the linear theory of water waves. The generator power take-off(PTO) system is modeled as a combination of a linear viscous damping and a linear spring. Using the frequency domain method, the optimal damping coefficient of the generator PTO system is derived to achieve the optimal conversion efficiency(capture width ratio).Based on the potential flow theory and the higher-order boundary element method(HOBEM), we constructed a threedimensional model of double-float WEC to study its hydrodynamic performance and response in the time domain. Only the heave motion of the two-body system is considered and a virtual function is introduced to decouple the motions of the floats. The energy conversion character of the double-float WEC is also evaluated. The investigation is carried out over a wide range of incident wave frequency. By analyzing the effects of the incident wave frequency, we derive the PTO's damping coefficient for the double-float WEC's capture width ratio and the relationships between the capture width ratio and the natural frequencies of the lower and upper floats. In addition, it is capable to modify the natural frequencies of the two floats by changing the stiffness coefficients of the PTO and mooring systems. We found that the natural frequencies of the device can directly influence the peak frequency of the capture width, which may provide an important reference for the design of WECs.

Rate-distortion optimized frame dropping and scheduling for multi-user conversational and streaming video

We propose a Rate-Distortion (RD) optimized strategy for frame-dropping and scheduling of multi-user conversa- tional and streaming videos. We consider a scenario where conversational and streaming videos share the forwarding resources at a network node. Two buffers are setup on the node to temporarily store the packets for these two types of video applications. For streaming video, a big buffer is used as the associated delay constraint of the application is moderate and a very small buffer is used for conversational video to ensure that the forwarding delay of every packet is limited. A scheduler is located behind these two buffers that dynamically assigns transmission slots on the outgoing link to the two buffers. Rate-distortion side information is used to perform RD-optimized frame dropping in case of node overload. Sharing the data rate on the outgoing link between the con- versational and the streaming videos is done either based on the fullness of the two associated buffers or on the mean incoming rates of the respective videos. Simulation results showed that our proposed RD-optimized frame dropping and scheduling ap- proach provides significant improvements in performance over the popular priority-based random dropping (PRD) technique.

Optimization of <i>Jatropha</i>Biodiesel Production by Response Surface Methodology

Cost of biodiesel is primarily because of factors such as the feedstock, production process and materials. Apparently, the final biodiesel product is a bit expensive compared to fossil diesel fuel. While non-food feedstock of high oil content such as Jatropha curcas has been proposed to reduce the cost due to the feedstock, a promising two-step approach of hydro-esterification can possibly offset the production cost for oil resource with high free fatty acids. Most importantly, optimization of the materials and process is expected to reduce wastage, enhance product purity and generate less wastewater. However, optimizing product generation has been dauntingly elusive because several parameters are needed to be considered holistically. In this study, Response Surface Methodology (RSM) was employed to optimize the yield and conversion of Jatropha biodiesel from J. curcas hydrolysate. An optimum Yield and conversion of 96% was achieved for both responses with an optimum temperature value of 60°C, 4 wt% for catalyst loading for 6 hrs reaction time. Findings imply that optimization study of Jatropha curcas hydrolysate for yield and conversion of fatty acid methyl esters using face centered central composite design of Design Expert 6.0.8 can ensure purity of product, conserve energy and reduce waste generation providing a significant frontier in biodiesel pricing.

Enhanced Atom Search Optimization Based Optimal Control Parameter Tunning of PMSG for MPPT

For the past few years,wind energy is the most popular non-traditional resource among renewable energy resources and it’s significant to make full use of wind energy to realize a high level of generating power.Moreover,diverse maximum power point tracking(MPPT)methods have been designed for varying speed operation of wind energy conversion system(WECS)applications to obtain optimal power extraction.Hence,a novel and metaheuristic technique,named enhanced atom search optimization(EASO),is designed for a permanent magnet synchronous generator(PMSG)based WECS,which can be employed to track the maximum power point.One of the most promising benefits of this technique is powerful global search capability that leads to fast response and high-quality optimal solution.Besides,in contrast with other conventional meta-heuristic techniques,EASO is extremely not relying on the original solution,which can avoid sinking into a low-quality local maximum power point(LMPP)by realizing an appropriate trade-off between global exploration and local exploitation.At last,simulations employing two case studies through Matlab/Simulink validate the practicability and effectiveness of the proposed techniques for optimal proportional-integral-derivative(PID)control parameters tuning of PMSG based WECS under a variety of wind conditions.

Adaptive Fuzzy Sliding Mode Controller for Grid Interface Ocean Wave Energy Conversion

This paper presents a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS) driven Self-Excited Induction Generator (SEIG). The aim of the developed control method is to automatically tune and optimize the scaling factors and the membership functions of the Fuzzy Logic Controllers (FLC) using Multi-Objective Genetic Algorithms (MOGA) and Multi-Objective Particle Swarm Optimization (MOPSO). Two Pulse Width Modulated voltage source PWM converters with a carrier-based Sinusoidal PWM modulation for both Generator- and Grid-side converters have been connected back to back between the generator terminals and utility grid via common DC link. The indirect vector control scheme is implemented to maintain balance between generated power and power supplied to the grid and maintain the terminal voltage of the generator and the DC bus voltage constant for variable rotor speed and load. Simulation study has been carried out using the MATLAB/Simulink environment to verify the robustness of the power electronics converters and the effectiveness of proposed control method under steady state and transient conditions and also machine parameters mismatches. The proposed control scheme has improved the voltage regulation and the transient performance of the wave energy scheme over a wide range of operating conditions.

Design Optimization of Ocean Thermal Energy Conversion(OTEC)Considering the Off-Design Condition

The comprehensive optimization of thermodynamic and economic performances is significant for the engineering application of ocean thermal energy conversion(OTEC).Motivated by this,this paper develops a thermo-economic OTEC model and conducts a sensitivity analysis of the OTEC system concerning its thermodynamic and economic performances.Specifically,the impact of warm-seawater temperature and cold-seawater pumping depth on the net thermal efficiency and the total investment cost are investigated.The results indicate that,an increase in warm-seawater temperature and cold-seawater pumping depth can improve the net thermal efficiency and a higher installed capacity is beneficial to the system economics.Building on these,a design optimization method with considering the on-design and off-design conditions is proposed in this paper,and the dynamic variation of warm-seawater temperature are considered in this method.In multi-objective optimization procedure,with the objective functions being the average net thermal efficiency and unit power cost within the operational cycle,the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is employed to maximize the net thermal efficiency and minimize the unit power investment cost,resulting in the Pareto front.The net thermal efficiencies of OTEC systems using ammonia and R245fa as working fluids are 4.13% and 3.8%,respectively.This represents an improvement of 19.4% and 57.0%,respectively,compared to traditional optimization methods that do not account for off-design conditions.

含垃圾能源化处理及电动汽车负载的区域综合能源系统协调优化

传统能源系统互相独立、欠缺联动,容易导致能量的浪费,并且能源结构也难以优化。区域综合能源系统具备多能互补、高效利用的优点,是提高能源利用效率和环保性的重要改进技术。为了利用垃圾蕴含的能量和电动汽车负载端的能源消纳,文中建立一个考虑垃圾焚烧和电动汽车负载的区域综合能源系统模型,利用模型进行系统的优化调度研究。论文分析了系统内的多能源能量流通关系,而后对系统内的各种能源转换设备及电动汽车进行分析,引入垃圾能源化处理,将热能转化为电能,并利用电动汽车进行电能消纳的模式,得出区域综合能源系统的能源效益最大化的模型。通过python进行算例分析,结果表明,含垃圾处理和电动汽车参与的区域综合能源系统既能提高能源的利用效率,又能带来更优的经济效益。

建筑空间最优节能设计模型仿真研究

由于建筑结构主体较多,空间能耗难以合并控制,导致目前建筑空间能源耗用量较大。为此,构建基于等效转换法的建筑空间最优节能模型,并对其仿真研究。提出建筑总体能耗作为初始优化的“尺度”概念,该尺度为建筑空间的外墙、内墙、屋顶、分户楼板以及门窗等参数,求解这些尺度的最佳标准值。采用等效转换法计算在节能条件下所能接受的最大能耗范围。在此基础上,以上述范围值为约束条件,建立控制函数。将上述提到标准尺度值和最大能耗范围设置为最优解,建立最优节能设计模型,设定温差调节因子,对每一次室内外温差实施有效调节控制,保证建筑体参数符合最佳能耗范围。仿真结果证明,所提方法对冬季采暖和夏季制冷的能耗控制效果均较佳,节能效果最优且算法收敛性高,鲁棒性较好。

高含水油田“二三结合”转换时机优化

针对现有转换时机研究方法无法满足高含水期老油田“二三结合”转换时机优化设计需要的问题,在综合分析三次采油转换时机和技术经济评价方法的基础上,考虑工程技术可行性和经济效益可行性,提出综合考虑技术、经济、社会价值的“二三结合”全生命周期开发价值链理念,建立高含水期老油田“二三结合”全生命周期效益稳产开发价值链模型,并实例分析“二三结合”转换时机对油藏最终采收率和生命周期的敏感性。结果表明,稳产、效益、生命周期是“二三结合”全生命周期效益稳产开发的主要考虑因素,转换时机对效益和稳产的影响是相对立的。

属性权重动态更新的自适应群体共识决策方法

为了提高不确定语言环境下异构多属性群决策的质量、效率及可解释性,提出一种属性权重动态更新的自适应群体共识决策方法。首先,定义不确定语言变量与中间值之间的转换函数,发展多级共识测度,建立计算属性初始权重的双目标优化模型;进而,构建包含群体共识自动达成规则和属性权重动态更新机制的自适应共识模型,实现待调整值的精准定位和自动修改,在优化属性权重的同时进一步提升群体共识水平;然后,对于达成共识的群体决策矩阵,先利用转换函数将中间值转换为不确定语言变量,再使用属性权重和集结算子得到各方案的综合评价结果;最后,通过供应商选择实例和实验比较分析验证所提方法的有效性和可行性。本文研究结果为灵活、高效地求解复杂环境下的多属性群决策问题提供了有效途径。

心理账户视角下在线用户转化机理研究

在“宅经济”盛行的今天,提升在线用户转化率是App企业抢占市场、发掘商业潜力的主要途径。基于心理账户视角,运用推拉锚定模型,实证研究在线用户转化机理。研究发现:用户对产品缺陷越厌倦,心理账户的非替代性强度、预算性强度越弱,用户越容易改变心理账户设置与预算分配,进而产生消费行为;用户感知到的产品价值越大,心理账户的非替代性强度、预算性强度越弱,越容易产生消费行为;最优刺激水平高的用户更容易厌倦产品缺陷,心理账户非替代性强度、预算性强度更容易受产品缺陷厌倦感影响;最优刺激水平高的用户更容易感知产品价值,心理账户非替代性强度、预算性强度更容易受感知产品价值影响。据此提出突出付费产品特点、提升用户感知价值、完善用户激励机制、向App用户进行针对性营销推送等提高用户转化率的营销建议。

多种构型超临界CO_(2)循环热力学解构分析与参数优化

新型超临界CO_(2)(S-CO_(2))循环可通过流程改良提高效率,构型复杂多样。为了直观阐明各种流程改良措施对循环效率提升的作用机制,本文将预压缩、后压缩、再压缩、间冷、再热等五种构型的S-CO_(2)循环解构为若干热功转换过程,建立各解构过程与循环效率之间的关联方程,进而开展流程参数优化。研究结果表明,预压缩、后压缩和再压缩方案均是通过增加压缩耗功,减少吸热量实现循环效率提升,其中再压缩方案效果最优,再压缩流量优化后循环效率提高5.1%;采用部分间冷方案,可有效降低压缩功耗,同时避免高品位热量贬值,间冷压力优化后循环效率提高2.2%;再热方案在不改变压缩耗功的前提下,增加透平出功,再热压力优化后循环效率提高1.9%;最后,循环联用再压缩、间冷和再热三种节能措施,可使效率提高9.3%。

微型热电联供能源系统的优化运行

随着可再生能源的快速发展和环境保护意识的增强,微型热电联供能源系统作为一种清洁高效的能源系统逐渐受到研究者的关注。通过综合考虑用户需求、系统负荷、环境因素等多个因素,运用先进的控制技术和预测模型等合理控制策略和技术手段,可以提高系统的能源利用效率和经济性,减少能源消耗、降低排放,为用户提供稳定可靠的能源供应。本文阐述了微型热电联供能源系统的运行原理,分析了其存在的问题,提出了相应的优化策略,总结了微型热电联供能源系统的优势和未来发展方向。

面向新能源波动平抑的储能多参数等价折算配置方法

基于储能在参与调节新能源出力随机性和波动性的重要作用,针对由储能种类多样性和参数复杂性导致的储能选型和配置困难问题,提出了一种面向新能源波动平抑的储能快速选型与配置方法。首先,从储能的物理模型本质出发,综合考虑储能的多类型参数,提出了一种储能多参数等价折算的方法;该方法将储能的荷电状态(state of charge,SOC)、寿命、效率和初始投资成本等多参数对比等价折算为功率和容量的配置成本对比,对复杂参数关系进行综合量化表征,实现对储能价值的快速准确评估。然后,为保证新能源出力平滑,建立了不同时间尺度下的新能源波动平抑指标,提出了新能源波动平抑的储能优化配置模型。该模型以储能成本、限电损失费用和新能源波动越限惩罚费用最小化为目标,考虑系统的运行约束与储能约束,实现系统技术和经济性能的最优化。最后,根据某实际算例的波动平抑需求调研了多种应用广泛的储能系统,基于所提储能多参数等价折算方法对不同储能的技术经济参数进行分析与比较,验证了所提的储能选型配置方法和新能源波动平抑模型的有效性和适用性。