Psychrophilic hydrogen production from petrochemical wastewater via anaerobic sequencing batch reactor: techno-economic assessment and kinetic modelling

Independent hydrogen production from petrochemical wastewater containing mono-ethylene glycol (MEG) via anaerobic sequencing batch reactor (ASBR) was extensively assessed under psychrophilic conditions (15–25 °C). A lab-scale ASBR was operated at pH of 5.50, and different organic loading rates (OLR) of 1.00, 1.67, 2.67, and 4.00 gCOD/L/d. The hydrogen yield (HY) progressed from 134.32 ± 10.79 to 189.09 ± 22.35 mL/gMEG_initial at increasing OLR from 1.00 to 4.00 gCOD/L/d. The maximum hydrogen content of 47.44 ± 3.60% was achieved at OLR of 4.0 gCOD/L/d, while methane content remained low (17.76 ± 1.27% at OLR of 1.0 gCOD/L/d). Kinetic studies using four different mathematical models were conducted to describe the ASBR performance. Furthermore, two batch-mode experiments were performed to optimize the nitrogen supplementation as a nutrient (C/N ratio), and assess the impact of salinity (as gNaCl/L) on hydrogen production. HY substantially dropped from 62.77 ± 4.09 to 6.02 ± 0.39 mL/gMEG_initial when C/N ratio was increased from 28.5 to 114.0. Besides, the results revealed that salinity up to 10.0 gNaCl/L has a relatively low inhibitory impact on hydrogen production. Eventually, the cost/benefit analysis showed that environmental and energy recovery revenues from ASBR were optimized at OLR of 4.0 gCOD/L/d (payback period of 7.13 yrs).     

A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.     

计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

随机库存分配问题的一种求解方法

讨论了在VMI管理思想下对具有随机需求特性的多客户库存分配问题 ,重点论述了有效近似算法的设计过程 ,最后基于一组模拟数据给出了一个算例。     

一种智能型的PCB产业需求预测方法

目前需求预测在整个印制电路板产业的生产活动控制中正扮演着越来越重要的角色。分析了影响印制电路板需求的因素和现有的预测方法,提出了一种适用于PCB产业需求预测的有效方法——遗传/BP—神经网络。实验表明该方法能够进一步改善印制电路板预测的准确度和减少生产成本的消耗。     

The Application of the Theory of the Price Elasticity of Demand to the EMS Management

1　Introduction　ExpressMailService (EMS )wasopenedupbyChinaPostintheearly 80stomeettheneedsofeco nomicdevelopment.It sthemostcompetitiveoneofthepostservices.There recivilaviation ,Chinarail wayandotherprivateexpressdeliverycompaniesdomesticallyandUPS ,TNT ,DHLandTEDEXcompetingwithEMSintheinternationalmarket.OneofthemostpowerfulcompeteweaponofthesecompaniesisthelowerpricethanEMS[1 ] .BecauseofthefiercecompetitionEMSdeclinedfromthemo nopolistindomesticandinternationalmarketoftheear…     

Study on the Complexity of the Bullwhip Effect

Recent years have witnessed a rapid growth of interest in the study of the dynamic behavior of replenishment rules of bullwhip effect. We prove that bullwhip effect and butterfly effect share a same the self-oscillation amplifying mechanism that is the ordering decisions the supplier self-oscillation amplify the perturbations brought by the errors in the processing of retailers' demand information. This results as an explicit self-similar structure of the sensitivity of the system to the initial values duty to the nonlinear mechanism. In this paper, the causes process of the bullwhip effect is described as the internal nonlinear mechanism and study on the complexity of bullwhip effect for order-up-to policy under demand signal processing. The methodology is based on fractal and chaotic theory and allows important insights to be gained about the complexity behavior of bullwhip effect.     

1，4－丁二醇的生产及市场需求

介绍了１，４－丁二醇的生产工艺、生产能力、产量和市场需求。     

国内外乙丙橡胶市场供需状况

介绍了国内外乙丙橡胶市场的供需状况，并对我国乙丙橡胶的产业发展提出了建议。     

多变量自回归模型在三江平原井灌水稻需水量预测中的应用

应用多变量自回归模型ARV(n), 利用三江平原腹地-富锦市1985～1999年气象资料, 按水稻生育期划分6个生育阶段, 建立了井灌水稻生育期内需水量预测模型. 经模型拟合与预测, 效果良好, 可以为该地区开展节水灌溉、灌溉用水管理、合理开发利用地下水资源, 缓解地下水危机提供参考依据.