Trajectories of knowledge economy in SSA and MENA countries

In the first critical assessment of knowledge economy dynamic paths in Africa and the Middle East, but for a few exceptions, we find overwhelming support for diminishing cross-country disparities in knowledge-based economy dimensions. The paper employs all the four components of the World Bank's Knowledge Economy Index (KEI): economic incentives, innovation, education, and information infrastructure. The main finding suggests that sub-Saharan African (SSA) and the Middle East and North African (MENA) countries with low levels of KE dynamics and catching-up their counterparts of higher KE levels. We provide the speeds of integration and time necessary to achieve full (100%) integration. Policy implications are also discussed.     

Effects of different carbon sources and C/N values on nonvolatile taste components of Pleurotus eryngii

Pleurotus eryngii, the second largest industrial cultivation mushroom in China, is usually cultivated on substrates mainly consisting of sawdust and corncob. In this study, experiments were performed to determine the effects of different carbon sources and C/N values on nonvolatile taste components of P. eryngii. The effects of different carbon sources on nonvolatile taste components levels revealed that sawdust was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while corncob was beneficial to high contents of carbohydrate, polysaccharides and trehalose. At the similar C/N values, relatively higher sawdust content was beneficial to umami amino acid production, while relatively higher corncob content was beneficial to high contents of carbohydrate, polysaccharides and mannitol. Higher C/N value was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while lower C/N value was beneficial to high contents of carbohydrate, polysaccharides and trehalose. These results provided information for P. eryngii fruit body industrial cultivation to obtain specific nonvolatile taste components with high levels.     

Optimized PI+ load–frequency controller using BWNN approach for an interconnected reheat power system with RFB and hydrogen electrolyser units

This paper investigates a renewable energy resource’s application to the Load–Frequency Control of interconnected power system. The Proportional-Integral (PI) controllers are replaced with Proportional-Integral Plus (PI+) controllers in a two area interconnected thermal power system without/with the fast acting energy storage devices and are designed based on Control Performance Standards (CPS) using conventional/Beta Wavelet Neural Network (BWNN) approaches. The energy storing devices Hydrogen generative Aqua Electroliser (HAE) with Fuel cell and Redox Flow Battery (RFB) are incorporated to the two area interconnected thermal power system to efficiently damp out the electromechanical oscillations in the power system because of their inherent efficient storage capacity in addition to the kinetic energy of the generator rotor, which can share the sudden changes in power requirements. The system was simulated and the frequency deviations in area 1 and area 2 and tie-line power deviations for 5% step- load disturbance in area 1 are obtained. The comparison of frequency deviations and tie-line power deviations of the two area interconnected thermal power system with HAE and RFB designed with BWNN controller reveals that the PI+ controller designed using BWNN approach is found to be superior than that of output response obtained using PI+ controller. Moreover the BWNN based PI+ controller exhibits a better transient and steady state response for the interconnected power system with Hydrogen generative Aqua Electroliser (AE) unit than that of the system with Redox Flow Battery (RFB) unit.     

Decomposition of first-order hybrid Petri nets for hierarchical control of manufacturing systems

Although hybrid Petri net (HPN) is a popular formalism in modelling hybrid production systems, the HPN model of large scale systems gets substantially complicated for analysis and control due to large dimensionality of such systems. To overcome this problem, a typical approach is to decompose the net into subnets and then control the plant through hierarchical or decentralized structures. Although this concept has been widely discussed in the literature for discrete PNs, there is a lack of research for HPNs. In this paper, a new method of decomposition of first-order hybrid Petri nets (FOHPNs) is proposed first and then the hierarchical control of the subnets through a coordinator is introduced. The advantage of using the proposed approach is validated by an existing example. A sugar milling case study is analysed by using a decomposed FOHPN model and the optimization results are compared against the results of the approaches presented in other papers. Simulation results show not only an improvement in production rate, but also show the ability to control the plant online. In addition, by using the hierarchical control structure for an FOHPN model, it is possible to reduce the cost of communication links, improve the reliability of the system, maintain the plant locally, and partially redesign the system.     

Accounting for the uncertainties in the estimation of average shear wave velocity using V S– N correlations

Site-specific seismic hazard analysis is crucial for designing earthquake resistance structures, particularly in seismically active regions. Shear wave velocity ( V _S) is a key parameter in such analysis, although the economy and other factors restrict its direct field measurement in many cases. Various V _S–SPT– N correlations are routinely incorporated in seismic hazard analysis to estimate the value of V _S. However, many uncertainties question the reliability of these estimated V _S values. This paper comes up with a statistical approach to take care of such uncertainties involved in V _S calculations. The measured SPT– N values from all the critical boreholes were converted into statistical parameters and passed through various correlations to estimate V _S at different depths. The effect of different soil layers in the boreholes on the Vs estimation was also taken into account. Further, the average shear wave velocity of the top 30 m soil cover ( V _S30) is estimated after accounting for various epistemic and aleatoric uncertainties. The scattering nature of the V _S values estimated using different V _S– N correlations was reduced significantly with the application of the methodology. Study results further clearly demonstrated the potential of the approach to eliminate various uncertainties involved in the estimation of V _S30 using general and soil-specific correlations.     

基于设备改造的选煤厂介质消耗控制研究

同忻选煤厂采用重介质选煤技术,磁性介质的消耗较大,为此,相关技术人员针对介质回收系统设备进行了改造设计。改造后,设备运行稳定,介质消耗降低,提高了原煤的分选效率,创造了较好的安全经济效益。     

注塑机料筒温度调控和计算机仿真研究

利用模糊控制和比例积分微分(PID)控制相结合的手段对注塑机料筒温度进行了控制,同时以Matlab 6.0软件为仿真平台,对料筒温度控制进行了模拟仿真研究。实验发现,在注塑机料筒升温过程中利用CHR整定的PID控制手段和模糊控制手段,恒温过程中利用人工整定的PID控制手段,可保证快速的料筒升温响应速率和稳定的保温过程。通过实际注塑实验对该仿真结果进行了验证,在十组实验中,料筒温度误差不超过2%,产品翘曲变形量不超过0.059 mm。     

刮板输送机中板仿生耐磨优化试验研究

刮板输送机中板磨损失效已成为输送机运行故障的主要原因之一，为了提高中板耐磨性，基于蜣螂非光滑单元进行了仿生中板设计，以磨损量为响应值，进行了单因素和响应面法优化试验。根据响应面法试验结果得到的因素显著性影响顺序（从高至低）依次为：径向距离，深径比，直径，节距角。基于试验结果建立了磨损量与因素的回归预测模型，经试验对比发现，预测模型与真实试验的相对误差为3.2%。在特定工况（煤散料粒度为6~8 mm、载荷为20 N、刮板链速为0.65 m/s及试验时长为6 600 s）下，当深径比为1.41、直径为0.69 mm、节距角为6.55°和径向距离为4.66 mm时，磨损量最小，仿生中板的耐磨性提高了12.6%。分析其耐磨机理发现，与光滑板相比，仿生板的磨粒磨损及黏着磨损较轻。凹坑分布可破坏持续切削中板表面的煤粒运动状态。中板的仿生优化可为今后刮板输送机的设计提供一定参考。     

Event-triggered variable horizon Supervisory Predictive control of hybrid power plants

The supervision of a hybrid power plant, including solar panels, a gas microturbine and a storage unit operating under varying solar power profiles is considered. The Economic Supervisory Predictive controller assigns the power references to the controlled subsystems of the hybrid cell using a financial criterion. A prediction of the renewable sources power is embedded into the supervisor. Results deteriorate when the solar power is unsteady, owing to the inaccuracy of the predictions for a long-range horizon of 10 s. The receding horizon is switched between an upper and a lower value according to the amplitude of the solar power trend. Theoretical results show the relevance of horizon switching, according to a tradeoff between performance and prediction accuracy. Experimental results, obtained in a Hardware In the Loop (HIL) framework, show the relevance of the variable horizon approach. Power amplifiers allow us to simulate virtual components, such as a gas microturbine, and to blend their powers with that of real devices (storage unit, real solar panels). In this case, fuel savings, reaching 15%, obtained under unsteady operating conditions lead to a better overall performance of the hybrid cell. The overall savings obtained in the experiments amount to 12%.