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Records Added in August 2019
Records added in August 2019
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Showing records 51 to 75 of 77. [First] Page: 1 2 3 4 Last
Uncovering Novel Pathways for Enhancing Hyaluronan Synthesis in Recombinant Lactococcus lactis: Genome-Scale Metabolic Modeling and Experimental Validation
Abinaya Badri, Karthik Raman, Guhan Jayaraman
August 7, 2019 (v1)
Subject: Biosystems
Keywords: genome-scale metabolic network model, hyaluronic acid, inosine supplementation, Lactococcus lactis, metabolic engineering
Hyaluronan (HA), a glycosaminoglycan with important medical applications, is commercially produced from pathogenic microbial sources. The metabolism of HA-producing recombinant generally regarded as safe (GRAS) systems needs to be more strategically engineered to achieve yields higher than native producers. Here, we use a genome-scale model (GEM) to account for the entire metabolic network of the cell while predicting strategies to improve HA production. We analyze the metabolic network of Lactococcus lactis adapted to produce HA and identify non-conventional strategies to enhance HA flux. We also show experimental verification of one of the predicted strategies. We thus identified an alternate route for enhancement of HA synthesis, originating from the nucleoside inosine, that can function in parallel with the traditionally known route from glucose. Adopting this strategy resulted in a 2.8-fold increase in HA yield. The strategies identified and the experimental results show that the... [more]
Optimal Design of a Carbon Dioxide Separation Process with Market Uncertainty and Waste Reduction
Juan Pablo Gutierrez, Eleonora Erdmann, Davide Manca
August 7, 2019 (v1)
Keywords: carbon dioxide separation, economic uncertainty, environmental impact, market prediction, optimal conceptual design
The aim of this work is to optimize the conceptual design of an amine-based carbon dioxide (CO2) separation process for Enhanced Oil Recovery (EOR). A systematic approach is applied to predict the economic profitability of the system while reducing the environmental impacts. Firstly, we model the process with UniSim and determine the governing degrees of freedom (DoF) through a sensitivity analysis. Then, we proceed with the formulation of the economic problem, where the employment of econometric models allows us to predict the highest dynamic economic potential (DEP). In the second part, we apply the Waste Reduction (WAR) algorithm to quantify the environmental risks of the studied process. This method is based on the minimization of the potential environmental indicator (PEI) by using the generalization of the Waste Reduction algorithm. Results show that the CO2 separation plant is promising in terms of economic revenues. However, the PEI value indicates that the higher the profitabi... [more]
Sweep Frequency Heating based on Injection Locked Magnetron
Fengming Yang, Wenwen Wang, Bo Yan, Tao Hong, Yang Yang, Huacheng Zhu, Li Wu, Kama Huang
August 7, 2019 (v1)
Subject: Other
Keywords: heating uniformity, injection-locking, microwave heating, sweep frequency
Conventional microwave heating has serious problems such as non-uniform heating and low efficiency. A novel magnetron microwave sweep frequency heating method is proposed to improve microwave heating uniformity. In this method, the frequency-sweeping signal is injected into the magnetron by the injection frequency-locking technique, and the microwave sweep frequency heating of the magnetron is realized. In this paper, a complicated injection frequency locking system is given and analyzed and a multiphysics calculation model based on the finite element method for electromagnetic waves and heat transfer is established. The calculation of microwave sweep frequency heating is realized by the combination of COMSOL and MATLAB. The results show that the sweep frequency heating has an obvious superiority. An experiment is carried out to verify the simulation results. The simulation results are in agreement with the experimental data. Moreover, the effect of sweep bandwidth and sweep interval o... [more]
Fault Identification Using Fast k-Nearest Neighbor Reconstruction
Zhe Zhou, Zuxin Li, Zhiduan Cai, Peiliang Wang
August 7, 2019 (v1)
Keywords: faulty variable identification, k-nearest neighbor estimation, process monitoring, variable contribution
Data with characteristics like nonlinear and non-Gaussian are common in industrial processes. As a non-parametric method, k-nearest neighbor (kNN) rule has shown its superiority in handling the data set with these complex characteristics. Once a fault is detected, to further identify the faulty variables is useful for finding the root cause and important for the process recovery. Without prior fault information, due to the increasing number of process variables, the existing kNN reconstruction-based identification methods need to exhaust all the combinations of variables, which is extremely time-consuming. Our previous work finds that the variable contribution by kNN (VCkNN), which defined in original variable space, can significantly reduce the ratio of false diagnosis. This reliable ranking of the variable contribution can be used to guide the variable selection in the identification procedure. In this paper, we propose a fast kNN reconstruction method by virtue of the ranking of VCk... [more]
Biopolymer Solution Evaluation Methodology: Thermal and Mechanical Assessment for Enhanced Oil Recovery with High Salinity Brines
Mohammad A. Al-Saleh, Abdirahman A. Yussuf, Mohammad A. Jumaa, Abbas Hammoud, Tahani Al-Shammari
August 7, 2019 (v1)
Subject: Materials
Keywords: biopolymer, mechanical degradation, polymer flooding, rheology, thermal stability
The methodology to study an eco-friendly and non-toxic, Schizophyllan, biopolymer for enhanced oil recovery (EOR) polymer flooding is described. The methodology is divided into two parts; the first part estimates the molar concentration of the biopolymer, which is needed to prepare the biopolymer solution with optimal viscosity. This is required to improve the sweep efficiency for the selected reservoir in Kuwait. The second part of this generalized methodology evaluates the biopolymer solution capability to resist degradation and maintain its essential properties with the selected reservoir conditions. The evaluation process includes thermal and mechanical assessment. Furthermore, to study the biopolymer solution behavior in both selected reservoir and extreme conditions, the biopolymer solution samples were prepared using 180 g/L and 309 g/L brine. It was found that the prepared biopolymer solution demonstrated great capability in maintaining its properties; and therefore, can be int... [more]
Catalytic Effect of NaCl on the Improvement of the Physicochemical Structure of Coal-Based Activated Carbons for SO2 Adsorption
Dongdong Liu, Rui Su, Zhengkai Hao, Xiaoman Zhao, Boyin Jia, Liangjie Dong
August 7, 2019 (v1)
Keywords: activated carbons, catalytic activation, physicochemical structure, SO2 adsorption
The utilization of coal-based activated carbons focuses on improving the physicochemical structure for achieving high-capacity. Herein, the catalytic effect of NaCl (1 and 3 wt%) in the presence of oxygen functional groups on the improvement of the physicochemical structure of coal-based activated carbons is studied in this work. A large quantity of Na can be retained in 1NaJXO and 3NaJXO with the presence of oxygen functional groups to promote further its catalytic characteristics during pyrolysis, resulting in the disordered transformation of the carbon structure. In addition, the development of micropores is mainly affected by the distribution and movement of Na catalyst, whereas the growth of mesopores is mainly influenced by the evolution of oxygen functional groups. Then, the active sites of 3NaJXO-800 can no longer be consumed preferentially in the presence of Na catalyst during subsequent CO2 activation to facilitate the sustained disordered conversion of the microstructure and... [more]
Multi-Label Classification Based on Random Forest Algorithm for Non-Intrusive Load Monitoring System
Xin Wu, Yuchen Gao, Dian Jiao
August 7, 2019 (v1)
Keywords: multi-label classification, non-intrusive load monitoring, random forest
Non-intrusive load monitoring (NILM) is an effective method to optimize energy consumption patterns. Since the concept of NILM was proposed, extensive research has focused on energy disaggregation or load identification. The traditional method is to disaggregate mixed signals, and then identify the independent load. This paper proposes a multi-label classification method using Random Forest (RF) as a learning algorithm for non-intrusive load identification. Multi-label classification can be used to determine which categories data belong to. This classification can help to identify the operation states of independent loads from mixed signals without disaggregation. The experiments are conducted in real environment and public data set respectively. Several basic electrical features are selected as the classification feature to build the classification model. These features are also compared to select the most suitable features for classification by feature importance parameters. The clas... [more]
Advancements in Canadian Biomaterials Research in Neurotraumatic Diagnosis and Therapies
Suzan Chen, Angela M. Auriat, Tongda Li, Taisa R. Stumpf, Ryan Wylie, Xiongbiao Chen, Stephanie M. Willerth, Maria DeRosa, Maryam Tarizian, Xudong Cao, Eve C. Tsai
August 7, 2019 (v1)
Subject: Biosystems
Keywords: 3D printing, biomaterials, imaging, nerve regeneration, neurotrauma, tissue engineering scaffold
Development of biomaterials for the diagnosis and treatment of neurotraumatic ailments has been significantly advanced with our deepened knowledge of the pathophysiology of neurotrauma. Canadian research in the fields of biomaterial-based contrast agents, non-invasive axonal tracing, non-invasive scaffold imaging, scaffold patterning, 3D printed scaffolds, and drug delivery are conquering barriers to patient diagnosis and treatment for traumatic injuries to the nervous system. This review highlights some of the highly interdisciplinary Canadian research in biomaterials with a focus on neurotrauma applications.
Experimental Study on Spent FCC Catalysts for the Catalytic Cracking Process of Waste Tires
Chuansheng Wang, Xiaolong Tian, Baishun Zhao, Lin Zhu, Shaoming Li
August 7, 2019 (v1)
Keywords: catalytic cracking, chemical raw materials, spent FCC catalysts, sulfur-containing material conversion, used tires
Research on the synergistic high-value reuse of waste tires and used catalysts in spent fluid catalytic cracking (FCC) catalysts was carried out in this study to address the serious ecological and environmental problems caused by waste tires and spent FCC catalysts. The experiment, in which a spent FCC catalyst was applied to the catalytic cracking of waste tires, fully utilized the residual activity of the spent FCC catalyst and was compared with a waste tire pyrolysis experiment. The comparative experimental results indicated that the spent FCC catalyst could improve the cracking efficiency of waste tires, increase the output of light oil in pyrolysis products, and improve the quality of pyrolysis oil. It could also be used for the conversion of sulfur compounds during cracking. The content of 2-methyl-1-propylene in catalytic cracking gas was found to be up to 65.59%, so a new method for producing high-value chemical raw materials by the catalytic cracking of waste tires with spent... [more]
Simulation Optimization for Complex Multi-Domain Physical Systems Based on Partial Resolving
Kexi Hou, Yaohui Li
August 7, 2019 (v1)
Subject: Optimization
Keywords: differential-algebraic equations, minimum solving graph, Modelica, multi-domain simulation, partial resolving, simulation optimization
The iterative process of simulation optimization is a time-consuming task, as it involves executing the main simulation program in order to evaluate the optimal constraints and objective functions repeatedly according to the values of tuner parameters. Parameter optimization for a model of a multi-domain physical system based on Modelica is a typical simulation optimization problem. Traditionally, each simulation during each iterative step needs resolve all the variables in all the mass differential-algebraic equations (DAE) generated from the simulation model through constructing and traversing the solving dependency graph of the model. In order to improve the efficiency of the simulation optimization process, a new method named partial simulation resolving algorithm based on the set of input parameters and output variables for complex simulation model was proposed. By using this algorithm, a minimum solving graph (MSG) of the simulation model was built according to the set of paramet... [more]
Transient Modeling of Grain Structure and Macrosegregation during Direct Chill Casting of Al-Cu Alloy
Qipeng Chen, Hongxiang Li, Houfa Shen
August 7, 2019 (v1)
Keywords: cellular automaton, direct chill casting, finite element, grain structure, macrosegregation, solidification
Grain structure and macrosegregation are two important aspects to assess the quality of direct chill (DC) cast billets, and the phenomena responsible for their formation are strongly interacted. Transient modeling of grain structure and macrosegregation during DC casting is achieved with a cellular automaton (CA)−finite element (FE) model, by which the macroscopic transport is coupled with microscopic relations for grain growth. In the CAFE model, a two-dimensional (2D) axisymmetric description is used for cylindrical geometry, and a Lagrangian representation is employed for both FE and CA calculations. This model is applied to the DC casting of two industrial scale Al-6.0 wt % Cu round billets with and without grain refiner. The grain structure and macrosegregation under thermal and solutal convection are studied. It is shown that the grain structure is fully equiaxed in the grain-refined billet, while a fine columnar grain region and a coarse columnar grain region are formed in the n... [more]
Electrolyte Effects on Poly (Acrylic Acid)-Based Aircraft De-icing Fluids
Yuchen Wang, Nicholas E. Hudson, Richard A. Pethrick, Carl J. Schaschke
August 7, 2019 (v1)
Subject: Materials
Keywords: calcium and potassium ions, poly (acrylic acid), polyelectrolytes, rheology, salt effects, water/glycol mixtures
Poly (acrylic acid) [PAA]-based aircraft de-icing fluids are widely used commercially but are known to be subject to the formation of insoluble gel particles within wing structures. In this study, the rheological effects of the sodium chloride, potassium formate, and calcium acetate with commercially used PAA-based fluids are reported across the temperature range of −15 to 15 °C. Calcium ions have the potential to create gel particles, reflected in the shifts in the viscosity−temperature profile, while PAA aggregation is influenced by the concentrations and compositions of sodium and potassium salts in the water used for dilution. From the data presented, it is possible to create de-icing fluid formulations with the necessary rheological characteristics from stock solutions by dilution using available water sources, providing that the ion concentration is known.
Development of Hydrophilic Drug Encapsulation and Controlled Release Using a Modified Nanoprecipitation Method
Jiang Xu, Yuyan Chen, Xizhi Jiang, Zhongzheng Gui, Lei Zhang
August 7, 2019 (v1)
Subject: Biosystems
Keywords: diblock copolymers, drug delivery systems, nanoparticles, nanoprecipitation, self-assembly
The improvement of the loading content of hydrophilic drugs by polymer nanoparticles (NPs) recently has received increased attention from the field of controlled release. We developed a novel, simply modified, drop-wise nanoprecipitation method which separated hydrophilic drugs and polymers into aqueous phase (continuous phase) and organic phase (dispersed phase), both individually and involving a mixing process. Using this method, we produced ciprofloxacin-loaded NPs by Poly (d,l-lactic acid)-Dextran (PLA-DEX) and Poly lactic acid-co-glycolic acid-Polyethylene glycol (PLGA-PEG) successfully, with a considerable drug-loading ability up to 27.2 wt% and an in vitro sustained release for up to six days. Drug content with NPs can be precisely tuned by changing the initial drug feed concentration of ciprofloxacin. These studies suggest that this modified nanoprecipitation method is a rapid, facile, and reproducible technique for making nano-scale drug delivery carriers with high drug-loadin... [more]
Numerical Study on the Gas-Water Two-Phase Flow in the Self-Priming Process of Self-Priming Centrifugal Pump
Chuan Wang, Bo Hu, Yong Zhu, Xiuli Wang, Can Luo, Li Cheng
August 7, 2019 (v1)
Keywords: Computational Fluid Dynamics, gas-water two-phase flow, self-priming pump
A self-priming centrifugal pump can be used in various areas such as agricultural irrigation, urban greening, and building water-supply. In order to simulate the gas-water two-phase flow in the self-priming process of a self-priming centrifugal pump, the unsteady numerical calculation of a typical self-priming centrifugal pump was performed using the ANSYS Computational Fluid X (ANSYS CFX) software. It was found that the whole self-priming process of a self-priming pump can be divided into three stages: the initial self-priming stage, the middle self-priming stage, and the final self-priming stage. Moreover, the self-priming time of the initial and final self-priming stages accounts for a small percentage of the whole self-priming process, while the middle self-priming stage is the main stage in the self-priming process and further determines the length of the self-priming time.
Enhanced Production of Anti-PD1 Antibody in CHO Cells through Transient Co-Transfection with Anti-Apoptotic Gene Bcl-xL Combined with Rapamycin
Yunxia Li, Xinyu Zhang, Lei Wang, Huifang Zong, Yuan Yuan, Lei Han, Xi Li, Chenxiao Xu, Jingyi Zhang, Jianwei Zhu, Baohong Zhang
August 7, 2019 (v1)
Subject: Biosystems
Keywords: anti-apoptotic gene, Bcl-xL, Chinese Hamster Ovary, rapamycin, transient gene expression technology
CHO cells are often used to produce monoclonal antibodies in mammalian cell expression systems. In the process of large-scale cell culture, apoptosis is related to cell survival and product quality. Over-expressing an anti-apoptotic gene to delay apoptosis and improve cell growth is one of the strategies for improving productivity of monoclonal antibodies. Autophagy inducer rapamycin can extend the culture duration of CHO cells and affect the yield of antibodies. A method was developed for transient co-transfection of anti-apoptotic genes and genes of interest combined with rapamycin to increase the transient expression of the anti-PD1 antibody. Under the optimal transfection conditions, the combination of Bcl-xL and rapamycin can significantly delay cell apoptosis, inhibit cell proliferation, and prolong cell life-time. As a result, anti-PD1 monoclonal antibody expression levels are increased by more than 2 times.
Scaling Relations in Modular Process Design
Michael Baldea, Burke A. Snowden, Tam T. Do, Calvin Tsay
August 6, 2019 (v1)
Keywords: Process Design, Process Modularization
This presentation deals with the issue of modularization of chemical plants, defined in the sense of designing smaller-capacity facilities (“modules”) that could be used to process geographically-distributed resources or serve distributed customers. Using established scaling relations, it is demonstrated that technologies that scale up well (i.e., for which capital cost increases sublinearly with capacity) scale down poorly, and vice versa. A further analysis of scale-down and modularization is carried out from the perspective of scaling of individual unit operations and their contribution to the plant cost stack. Following the same line of reasoning, it is shown that units that scale down well will scale up poorly and vice-versa. On this basis, it is argued that scaling relations can be used not only to guide the design of modular processes based on existing technology, but also to direct research towards new designs that alleviate the cost problems associated with units that have poo... [more]
Study on Grid-Connected Strategy of Distribution Network with High Hydropower Penetration Rate in Isolated Operation
Zifan Zhang, Zhidong Wang, Zhifeng Chen, Gan Wang, Na Shen, Changxing Guo
August 5, 2019 (v1)
Keywords: grid-connected strategy, island operation, small hydropower
As the largest global renewable source, hydropower is a useful supplement to mountainous distribution networks with abundant water resources, and shoulders a large portion of the regulation duty in many power systems. In particular, in the form of decentralized energy sources located to their customers, small hydropower (SHP) improve grid stability by diversifying the electricity system and reducing power loss. The mountainous distribution networks supplied by small hydropower are closed-loop design but open-loop operation, which easily causes the tripping of tie line even further the off-grid operation of small hydropower system. Once the tie line trips, the current countermeasures—such as hydropower shutdown and load shedding—do not fully guarantee the reliability of power supply and the utilization efficiency of hydropower. This paper studies the amplitude-frequency characteristics of SHP off-grid, according to the typical integration of hydropower in South China, a SHP on-grid/off-... [more]
The Influence and Optimization of Geometrical Parameters on Coast-Down Characteristics of Nuclear Reactor Coolant Pumps
Yuanyuan Zhao, Xiangyu Si, Xiuli Wang, Rongsheng Zhu, Qiang Fu, Huazhou Zhong
August 5, 2019 (v1)
Keywords: coast-down characteristics, geometrical parameters, multiple linear regression, reactor coolant pump, transition process
Coast-down characteristics are the crucial safety evaluation factors of nuclear reactor coolant pumps. The energy stored at the highest moment of inertia of the reactor coolant pump unit is utilized to maintain a normal coolant supply to the core of the cooling loop system for a short period of time during the coast-down transition. As a result of the high inertia moment of the rotor system, the unit requires a high reliability of the nuclear reactor coolant pump and consumes considerable energy in the start-up and normal operation. This paper considers the operational characteristics of the coast-down transition process based on the existing hydraulic model of the nuclear reactor coolant pump. With the implementation of an orthogonal test, the hydraulic performance of the nuclear reactor coolant pump was optimized, and the optimal combination of impeller geometrical parameters was selected using multivariate linear regression to prolong the coast-down time of the reactor coolant pump... [more]
Sustainable Biotransformation of Oleic Acid to 10-Hydroxystearic Acid by a Recombinant Oleate Hydratase from Lactococcus garvieae
Jing Zhang, Muhammad Bilal, Shuai Liu, Jiaheng Zhang, Hedong Lu, Hongzhen Luo, Chuping Luo, Hao Shi, Hafiz M. N. Iqbal, Yuping Zhao
August 5, 2019 (v1)
Subject: Biosystems
Keywords: 10-hydroxystearic acid, bio-based process, biotransformation, Lactococcus garvieae, oleate acid, oleate hydratase, Optimization
Enzymatic hydration of oleic acid into 10-hydroxystearic acid (10-HSA) represents a theme of substantial scientific and practical interest. In this study, a fatty acid hydratase (OHase) from Lactococcus garvieae was cloned and expressed in Escherichia coli. The recombinantly expressed enzyme was identified as oleate hydratase (EC 4.2.1.53) confirming its highest hydration activity for oleic acid. The optimally yielded enzyme fraction was purified and subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). A solitary band on SDS-PAGE confirmed the molecular weight of 65 kDa. Gas chromatography-mass spectrometry (GC-MS) analysis scrutinized the silylated hydroxy fatty acid products acquired from the hydration of oleic acid by the oleate hydratase from L. garvieae. Optimal reaction conditions for the enzymatic production of 10-HSA from oleic acid using the purified oleate hydratase were pH 7.5, 30 °C, 105.49 U/mL enzyme solution and 30 g/L oleic acid. In the pre... [more]
Measuring Energy Efficiency and Environmental Performance: A Case of South Asia
Yumei Hou, Wasim Iqbal, Ghulam Muhammad Shaikh, Nadeem Iqbal, Yasir Ahmad Solangi, Arooj Fatima
August 5, 2019 (v1)
Subject: Energy Policy
Keywords: Energy Efficiency, energy efficiency indicators, environmental performance, South Asia region
When assessing energy efficiency, most studies have frequently ignored environmental aspects even though the concept has been widely used in the past. This study evaluates the energy efficiency and environmental performance of South Asia by using DEA (data envelopment analysis) like mathematical composite indicator. We construct a comprehensive set of indicators, including an energy self-sufficiency ratio, energy production over consumption ratio, energy imports, diversification index of energy imports, energy reserve ratio, GDP productivity, energy intensity, per capita energy consumption index, carbon emission index, carbon emission index per unit of energy consumption and share of renewable energy in order to develop an energy efficiency and environmental performance index. Unlike other studies, this study first examines each indicator and then estimates a combined score for each country. The results reveal that Bhutan as a more secure country and Pakistan showed a decreasing trend,... [more]
Productivity Models of Infill Complex Structural Wells in Mixed Well Patterns
Liang Sun, Baozhu Li, Yong Li
August 5, 2019 (v1)
Keywords: complex structural well, mixed well pattern, productivity evaluation, semi-analytical model, well location optimization
The mathematical models of productivity calculation for complex structural wells mainly focus on the single well or the regular well pattern. Previous research on the seepage theory of complex structural wells and vertical wells in mixed well pattern is greatly insufficient. Accordingly, this article presents a methodology of evaluating the productivity of infill complex structural wells in mixed well patterns. On the basis of the mirror-image method and source−sink theory, two semi-analytical models are established. These models are applied to the productivity prediction of an infill horizontal well inhorizontal-vertical well pattern and an infill multilateral well inmultilateral-vertical well pattern, respectively, in which the interference of other wells, the randomicity of well patterns, and the pressure drawdown along the horizontal laterals are taken into account. The semi-analytical models’ results are consistent with those calculated by the Eclipse reservoir simulator with the... [more]
Optimization of Distillation Sequences with Nonsharp Separation Columns
Xi Wang, Zengzhi Du, Yunlu Zhang, Jingde Wang, Jianhong Wang, Wei Sun
August 5, 2019 (v1)
Keywords: Aspen, nonsharp distillation sequence, Optimization
Nonsharp distillation sequences are widely used in industrial separation processes; however, most current research has not discussed this topic, except in sequences with heat integration under special operating conditions, including complex columns. The sequence with nonsharp separation has the features of general distillation sequences, which are usually optimized by adjusting the separation sequence and the design/operation parameters of each column in the sequence, making the optimization a mixed integer nonlinear programming (MINLP) problem, which is usually hard to solve. With inclusion of nonsharp separation columns, the sequence optimization becomes even more complicated and computationally intensive. This work aimed to optimize the distillation sequence, including nonsharp distillation alongside simple columns and dividing wall columns. Inspired by the dynamic programing method for sharp distillation sequence, a framework for automatic optimization is proposed to decompose the... [more]
Reactive Power Optimization of Large-Scale Power Systems: A Transfer Bees Optimizer Application
Huazhen Cao, Tao Yu, Xiaoshun Zhang, Bo Yang, Yaxiong Wu
August 5, 2019 (v1)
Keywords: behavior transfer, reactive power optimization, reinforcement learning, state-action chains, transfer bees optimizer
A novel transfer bees optimizer for reactive power optimization in a high-power system was developed in this paper. Q-learning was adopted to construct the learning mode of bees, improving the intelligence of bees through task division and cooperation. Behavior transfer was introduced, and prior knowledge of the source task was used to process the new task according to its similarity to the source task, so as to accelerate the convergence of the transfer bees optimizer. Moreover, the solution space was decomposed into multiple low-dimensional solution spaces via associated state-action chains. The transfer bees optimizer performance of reactive power optimization was assessed, while simulation results showed that the convergence of the proposed algorithm was more stable and faster, and the algorithm was about 4 to 68 times faster than the traditional artificial intelligence algorithms.
Day-Ahead Prediction of Microgrid Electricity Demand Using a Hybrid Artificial Intelligence Model
Yuan-Jia Ma, Ming-Yue Zhai
August 5, 2019 (v1)
Keywords: Artificial Intelligence, electricity demand, feedforward artificial neural network, forecasting, microgrid, simulated annealing, smart grid, wavelet transform
Improved-performance day-ahead electricity demand forecast is important to deliver necessary information for right decision of energy management of microgrids. It supports microgrid operators and stakeholders to have better decisions on microgrid flexibility, stability and control. The available conventional forecasting methods for electricity demand at national or regional level are not effective for electricity demand forecasting in microgrids. This is due to the fact that the electricity consumption in microgrids is many times less than the regional or national demands and it is highly volatile. In this paper, an integrated Artificial Intelligence (AI) based approach consisting of Wavelet Transform (WT), Simulated Annealing (SA) and Feedforward Artificial Neural Network (FFANN) is devised for day-ahead prediction of electric power consumption in microgrids. The FFANN is the basic forecasting engine of the proposed model. The WT is utilized to extract relevant features of the target... [more]
Photocatalytic Treatment of Paracetamol Using TiO2 Nanotubes: Effect of pH
S. Alejandro Lozano-Morales, Graciela Morales, Miguel Ángel López Zavala, Augusto Arce-Sarria, Fiderman Machuca-Martínez
August 5, 2019 (v1)
Subject: Materials
Keywords: emerging contaminants, paracetamol, pH, photocatalysis, TiO2 nanotubes
Pharmaceuticals are considered among the group of emerging contaminants. Paracetamol is a moderate painkiller, which has been detected in ground and surface water. Photodegradation of paracetamol at a wavelength of radiation of 254 nm with TiO2 nanotubes was studied by UV-spectroscopy, HPLC and measurement of the potential zeta in dependence of the solution pH. The efficiency of the photodegradation of paracetamol (20 mg L−1) was 99% after 100 min exposure. Application of the Langmuir-Hinshelwood equation allowed the evaluation of the rate constant. Non-organic by-products were detected under the conditions of the chromatographic analysis. The photoreaction was faster at pH 6.5, a value at which adsorption was favored, leading to higher efficiency.
Showing records 51 to 75 of 77. [First] Page: 1 2 3 4 Last
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