Records Added in July 2019
Records added in July 2019
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Showing records 1 to 25 of 253. [First] Page: 1 2 3 4 5 Last
Comparative Study of the Performances of Al(OH)3 and BaSO4 in Ultrafine Powder Coatings
Weihong Li, Diego Cárdenas Franco, Marshall Shuai Yang, Xinping Zhu, Haiping Zhang, Yuanyuan Shao, Hui Zhang, Jingxu Zhu
July 31, 2019 (v1)
Subject: Materials
Keywords: Al(OH)3, BaSO4, filler, ultrafine powder coatings
Ultrafine powder coatings are one of the development directions in the powder coating industry, as they can achieve thin coatings with good leveling and high surface smoothness comparable to liquid coatings. Compared to regular coatings, they experience a higher sensitivity to any incompatibilities, e.g., filler from coating components. The properties of fillers play a great role in the performance of coating films. Aluminum trihydrate (Al(OH)3) is a well-known filler in solvent-based coatings and other polymer industries. To study and evaluate the performances of Al(OH)3 in ultrafine powder coatings, a popular filler, barium sulfate (BaSO4) is used for comparison. Both fillers are added in ultrafine powder coatings based on two of the most commonly used resin systems (polyester-epoxy and polyester). The differences of physical and chemical properties between both fillers have significant influences on several properties of powder paints and coating films. The polar groups (hydrogen bo... [more]
Hydroxymethylation-Modified Lignin and Its Effectiveness as a Filler in Rubber Composites
Nor Anizah Mohamad Aini, Nadras Othman, M. Hazwan Hussin, Kannika Sahakaro, Nabil Hayeemasae
July 31, 2019 (v1)
Subject: Materials
Keywords: bio-filler, hydroxymethylation, lignin, rubber composite
Kraft lignin was modified by using hydroxymethylation to enhance the compatibility between rubber based on a blend of natural rubber/polybutadiene rubber (NR/BR) and lignin. To confirm this modification, the resultant hydroxymethylated kraft lignin (HMKL) was characterized using Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) spectroscopy. It was then incorporated into rubber composites and compared with unmodified rubber. All rubber composites were investigated in terms of rheology, mechanical properties, aging, thermal properties, and morphology. The results show that the HMKL influenced the mechanical properties (tensile properties, hardness, and compression set) of NR/BR composites compared to unmodified lignin. Further evidence also revealed better dispersion and good interaction between the HMKL and the rubber matrix. Based on its performance in NR/BR composites, hydroxymethylated lignin can be used as a filler in the rubber industry.
Wave Characteristics of Coagulation Bath in Dry-Jet Wet-Spinning Process for Polyacrylonitrile Fiber Production Using Computational Fluid Dynamics
Son Ich Ngo, Young-Il Lim, Soo-Chan Kim
July 31, 2019 (v1)
Keywords: coagulation bath, Computational Fluid Dynamics, dry-jet wet spinning process, maximum wave amplitude, polyacrylonitrile-based carbon fiber, wave resonance
In this work, a three-dimensional volume-of-fluid computational fluid dynamics (VOF-CFD) model was developed for a coagulation bath of the dry-jet wet spinning (DJWS) process for the production of polyacrylonitrile (PAN)-based carbon fiber under long-term operating conditions. The PAN-fiber was assumed to be a deformable porous zone with variations in moving speed, porosity, and permeability. The Froude number, interpreted as the wave-making resistance on the liquid surface, was analyzed according to the PAN-fiber wind-up speed ( v P A N ). The effect of the PAN speed on the reflection and wake flow formed by drag between a moving object and fluid is presented. A method for tracking the wave amplitude with time is proposed based on the iso-surface of the liquid volume fraction of 0.95. The wave signal for 30 min was divided into the initial and resonance states that were distinguished at 8 min. The maximum wave amplitude was less than 0.5 mm around the PAN-fiber inlet nozzle... [more]
In Situ Measurements and CFD Numerical Simulations of Thermal Environment in Blind Headings of Underground Mines
Wenhao Wang, Chengfa Zhang, Wenyu Yang, Hong Xu, Sasa Li, Chen Li, Hui Ma, Guansheng Qi
July 31, 2019 (v1)
Subject: Other
Keywords: auxiliary ventilation, duct position, numerical simulations, the heat dissipation of LHD, thermal environment, ventilation cooling
In order to gain a knowledge of the heat emitted from a variety of sources at the blind heading of an underground gold mine, the present study conducts an in situ measurement study in a blind heading within the load haul dumps (LHDs) that are operating. The measurements can provide a reliable data basis for the setting of numerical simulations. The results demonstrate that the distances between the forcing outlet and the mining face (denoted as Zm), as well as the heat generation from LHDs (denoted as QL), has brought significant impacts on the airflow velocity, relative humidity, and temperature distributions in the blind heading. Setting Zm to 5 m could achieve a relative optimal cooling performance, also indicating that when the LHD is fully operating in the mining face, employing the pure forcing system has a limited effect on the temperature decrease of the blind heading. According to the numerical simulations, a better cooling performance can be achieved based on the near-forcing... [more]
A Scenario-Based Optimization Model for Planning Sustainable Water-Resources Process Management under Uncertainty
Hongchang Miao, Donglin Li, Qiting Zuo, Lei Yu, Xiaoxia Fei, Lingang Hao
July 31, 2019 (v1)
Keywords: programming, scenario analysis, South-to-North Water Diversion Project of China, uncertainty, water-resources process management
Discrepancies between water demand and supply are intensifying and creating a need for sustainable water resource process management associated with rapid economic development, population growth, and urban expansion. In this study, a scenario-based interval fuzzy-credibility constrained programming (SIFCP) method is developed for planning a water resource management system (WRMS) that can handle uncertain information by using interval values, fuzzy sets, and scenario analysis. The SIFCP-WRMS model is then applied to plan the middle route of the South-to-North Water Diversion Project (SNWDP) in Henan Province, China. Solutions of different water distribution proportion scenarios and varied credibility levels are considered. Results reveal that different water-distribution proportion scenarios and uncertainties used in the SIFCP-WRMS model can lead to changed water allocations, sewage discharges, chemical oxygen demand (COD) emissions, and system benefits. Results also indicate that the... [more]
Aeration Process in Bioreactors as the Main Energy Consumer in a Wastewater Treatment Plant. Review of Solutions and Methods of Process Optimization
Jakub Drewnowski, Anna Remiszewska-Skwarek, Sylwia Duda, Grzegorz Łagód
July 31, 2019 (v1)
Keywords: activated sludge, aeration process, bioreactors, energy consumption, nutrient removal, wastewater treatment processes
Due to the key role of the biological decomposition process of organic compounds in wastewater treatment, a very important thing is appropriate aeration of activated sludge, because microorganisms have to be supplied with an appropriate amount of oxygen. Aeration is one of the most energy-consuming processes in the conventional activated sludge systems of wastewater treatment technology (may consume from 50% to 90% of electricity used by a plant), which makes it the most cost-generating process incurred by treatment plants. The paper presents the construction of aeration systems, their classification as well as parameters and factors that significantly affect the aeration process e.g., oxygen transfer efficiency, diffuser fouling, methods of dealing with diffuser fouling, diffuser selection. Additionally, there are briefly presented “smart control” systems in wastewater treatment and effect of application control strategy based on Supervisory Control and Data Acquisition system connect... [more]
Designing, Developing and Validating a Forecasting Method for the Month Ahead Hourly Electricity Consumption in the Case of Medium Industrial Consumers
Dana-Mihaela Petroșanu
July 31, 2019 (v1)
Keywords: artificial neural networks (ANNs), electricity consumption forecasting, long short-term memory (LSTM) neural networks, medium industrial consumers, non-linear autoregressive with exogenous inputs (NARX) model, smart meter device, timestamps dataset
An accurate forecast of the electricity consumption is particularly important to both consumers and system operators. The purpose of this study is to develop a forecasting method that provides such an accurate forecast of the month-ahead hourly electricity consumption in the case of medium industrial consumers, therefore assuring an intelligent energy management and an efficient economic scheduling of their resources, having the possibility to negotiate in advance appropriate billing tariffs relying on accurate hourly forecasts, in the same time facilitating an optimal energy management for the dispatch operator. The forecasting method consists of developing first non-linear autoregressive, with exogenous inputs (NARX) artificial neural networks (ANNs) in order to forecast an initial daily electricity consumption, a forecast that is being further processed with custom developed long short-term memory (LSTM) neural networks with exogenous variables support in order to refine the daily f... [more]
Data-Driven Estimation of Significant Kinetic Parameters Applied to the Synthesis of Polyolefins
Santiago D. Salas, Amanda L. T. Brandão, João B. P. Soares, José A. Romagnoli
July 31, 2019 (v1)
Keywords: data-driven parameter estimation, global sensitivity analysis, polyolefin synthesis, retrospective cost model refinement algorithm
A data-driven strategy for the online estimation of important kinetic parameters was assessed for the copolymerization of ethylene with 1,9-decadiene using a metallocene catalyst at different diene concentrations and reaction temperatures. An initial global sensitivity analysis selected the significant kinetic parameters of the system. The retrospective cost model refinement (RCMR) algorithm was adapted and implemented to estimate the significant kinetic parameters of the model in real time. After verifying stability and robustness, experimental data validated the algorithm performance. Results demonstrate the estimated kinetic parameters converge close to theoretical values without requiring prior knowledge of the polymerization model and the original kinetic values.
Off-Grid Solar PV Power Generation System in Sindh, Pakistan: A Techno-Economic Feasibility Analysis
Li Xu, Ying Wang, Yasir Ahmed Solangi, Hashim Zameer, Syed Ahsan Ali Shah
July 31, 2019 (v1)
Keywords: CO2 mitigation, economic feasibility, off-grid Solar PV power generation, Pakistan, remote rural regions
The off-grid solar photovoltaic (PV) system is a significant step towards electrification in the remote rural regions, and it is the most convenient and easy to install technology. However, the strategic problem is in identifying the potential of solar energy and the economic viability in particular regions. This study, therefore, addresses this problem by evaluating the solar energy potential and economic viability for the remote rural regions of the Sindh province, Pakistan. The results recommended that the rural regions of Sindh have suitable solar irradiance to generate electricity. An appropriate tilt angle has been computed for the selected rural regions, which significantly enhances the generation capacity of solar energy. Moreover, economic viability has been undertaken in this study and it was revealed that the off-grid solar PV power generation system provides electricity at the cost of Pakistani Rupees (PKR) 6.87/kWh and is regarded as much cheaper than conventional energy s... [more]
Risk Rating Method Based on the Severity Probability Risk Value and Reserved Risk Maintenance Resource Cost of the Node Disconnection of the Power System
Qingwu Gong, Si Tan
July 31, 2019 (v1)
Keywords: reserve risk maintenance resource cost (RRMRC), Risk Rating Model (RRM), severity probability risk valuation (SPRV)
In order to solve the problem of traditional risk rating methods without considering the cost of risk maintenance resources and ignoring the low risk of “High Loss Severity (HLS) with low probability” and the low risk of “High Failure Probability (HFP) with low loss severity”, a node disconnection risk rating method (NDRRM) is proposed. This method considers the severity probability risk valuation (SPRV) and reserve risk maintenance resource cost (RRMRC). The risk rating method based on SPRV developed from the traditional risk valuation method can simultaneously identify the nodes with the highest severity values, the nodes with the highest probability of failure, and the nodes with the largest risk valuation. On the basis of the above model, we consider the cost constraints of the reserve risk maintenance resource and put forward a risk rating method based on SPRV and RRMRC. The risk rating results of this model are suitable for guiding risk maintenance in practice. Simulations are ca... [more]
Comparison of Riser-Simplified, Riser-Only, and Full-Loop Simulations for a Circulating Fluidized Bed
Min Wang, Yingya Wu, Xiaogang Shi, Xingying Lan, Chengxiu Wang, Jinsen Gao
July 31, 2019 (v1)
Keywords: circulating-fluidized bed, Computational Fluid Dynamics, full-loop simulation, gas–solids flow, hydrodynamics, riser
With the development of computing power, the simulation of circulating fluidized bed (CFB) has developed from riser-simplified simulation to riser-only simulation, then to full-loop simulation. This paper compared these three methods based on pilot-scale CFB experiment data to find the scope of application of each method. All these simulations, using the Eulerian−Eulerian two-fluid model with the kinetic theory of granular theory, were conducted to simulate a pilot-scale CFB. The hydrodynamics, such as pressure balance, solids holdup distribution, solids velocity distribution, and instantaneous mass flow rates in the riser or CFB system, were investigated in different simulations. By comparing the results from different methods, it was found that riser-simplified simulation is not sufficient to obtain accurate hydrodynamics, especially in higher solids circulating rates. The riser-only simulation is able to make a reasonable prediction of time-averaged behaviors of gas−solids in most p... [more]
Process Optimization by a Response Surface Methodology for Adsorption of Congo Red Dye onto Exfoliated Graphite-Decorated MnFe2O4 Nanocomposite: The Pivotal Role of Surface Chemistry
Van Thinh Pham, Hong-Tham T. Nguyen, Duyen Thi Cam Nguyen, Hanh T. N. Le, Thuong Thi Nguyen, Nhan Thi Hong Le, Kwon Teak Lim, Trinh Duy Nguyen, Thuan Van Tran, Long Giang Bach
July 31, 2019 (v1)
Subject: Materials
Keywords: Boehm titration, Congo red decontamination, exfoliated graphite, MnFe2O4 nanoparticles, response surface methodology, surface functional groups
Natural graphite, a locally available, eco-friendly, and low-cost carbonaceous source, can be easily transformed into exfoliated graphite (EG) with many surface functional groups via a chemical oxidation route. Combination between EG and magnetic MnFe2O4 is a promising strategy to create a hybrid kind of nanocomposite (EG@MnFe2O4) for the efficient adsorptive removal of Congo red (CR) dye from water. Here, we reported the facile synthesis and characterization of chemical bonds of EG@MnFe2O4 using several techniques such as Fourier-transform infrared spectroscopy (FT-IR), and X-ray photoelectron spectroscopy (XPS). In particular, the quantity method by Boehm titration was employed to identify the content of functional groups: Carboxylic acid (0.044 mmol/g), phenol (0.032 mmol/g), lactone (0.020 mmol/g), and total base (0.0156 mmol/g) on the surface of EG@MnFe2O4. Through the response surface methodology-optimized models, we found a clear difference in the adsorption capacity between EG-... [more]
Determination of the Acidity of Waste Cooking Oils by Near Infrared Spectroscopy
Juan Francisco García Martín, María del Carmen López Barrera, Miguel Torres García, Qing-An Zhang, Paloma Álvarez Mateos
July 31, 2019 (v1)
Keywords: free acidity, NIRS, partial least squares, waste cooking oil
Waste cooking oils (WCO) recycling companies usually have economic losses for buying WCO not suitable for biodiesel production, e.g., WCO with high free acidity (FA). For this reason, the determination of FA of WCO by near infrared (NIR) spectroscopy was studied in this work to assess its potential for in situ application. To do this, FA of 45 WCO was measured by the classical titration method, which ranged between 0.15 and 3.77%. Then, the NIR spectra from 800 to 2200 nm of these WCO were acquired, and a partial least squares model was built, relating the NIR spectra to FA values. The accuracy of the model was quite high, providing r2 of 0.970 and a ratio of performance to deviation (RPD) of 4.05. Subsequently, a model using an NIR range similar to that provided by portable NIR spectrometers (950−1650 nm) was built. The performance was lower (r2 = 0.905; RPD = 2.66), but even so, with good accuracy, which demonstrates the potential of NIR spectroscopy for the in situ determination of... [more]
Optimization of Macroalgal Density and Salinity for Nutrient Removal by Caulerpa lentillifera from Aquaculture Effluent
B.V.A.S. Manori Bambaranda, Nophea Sasaki, Anong Chirapart, Krishna R. Salin, Takuji W. Tsusaka
July 31, 2019 (v1)
Subject: Biosystems
Keywords: aquaculture effluent, nutrient uptake, phycoremediation, pulse amplitude-modulated fluorometry, quadratic regression
Determining the optimum levels of macroalgal density and salinity for removing aquaculture effluent has gained increasing research interest in recent years because of the growing concerns over environmental sustainability. Here, we determined the effects of macroalgal density and salinity on the uptake of NO2−, NO3−, NH3, and PO43− by Caulerpa lentillifera from the effluent of Poecilia latipinna using spectrophotometry. Laboratory experiments were conducted to measure nutrient uptake at five different macroalgal density levels (10, 20, 30, 40, and 50 g/L) and three salinity levels (20, 30, and 40 ppt) with and without aeration. Quadratic regression analysis revealed significant nonlinear and linear effects of macroalgal density on the uptake of NO2−, NO3−, NH3, and PO43−, where the maximum uptake was predicted to occur at the macroalgal densities of 31.6, 33.3, 50.0, and 20.0 g/L, respectively. Likewise, the effects of salinity on the uptake of NO2−, NO3−, NH3, and PO43− were significa... [more]
An Improved Compact Genetic Algorithm for Scheduling Problems in a Flexible Flow Shop with a Multi-Queue Buffer
Zhonghua Han, Quan Zhang, Haibo Shi, Jingyuan Zhang
July 31, 2019 (v1)
Keywords: flexible flow shop scheduling, improved compact genetic algorithm, multi-queue limited buffers, probability density function of the Gaussian distribution
Flow shop scheduling optimization is one important topic of applying artificial intelligence to modern bus manufacture. The scheduling method is essential for the production efficiency and thus the economic profit. In this paper, we investigate the scheduling problems in a flexible flow shop with setup times. Particularly, the practical constraints of the multi-queue limited buffer are considered in the proposed model. To solve the complex optimization problem, we propose an improved compact genetic algorithm (ICGA) with local dispatching rules. The global optimization adopts the ICGA, and the capability of the algorithm evaluation is improved by mapping the probability model of the compact genetic algorithm to a new one through the probability density function of the Gaussian distribution. In addition, multiple heuristic rules are used to guide the assignment process. Specifically, the rules include max queue buffer capacity remaining (MQBCR) and shortest setup time (SST), which can i... [more]
Predicting Host Immune Cell Dynamics and Key Disease-Associated Genes Using Tissue Transcriptional Profiles
Muying Wang, Satoshi Fukuyama, Yoshihiro Kawaoka, Jason E. Shoemaker
July 31, 2019 (v1)
Subject: Biosystems
Keywords: deconvolution algorithm, disease-associated gene, immune cell quantities, influenza infection, tissue gene expression
Motivation: Immune cell dynamics is a critical factor of disease-associated pathology (immunopathology) that also impacts the levels of mRNAs in diseased tissue. Deconvolution algorithms attempt to infer cell quantities in a tissue/organ sample based on gene expression profiles and are often evaluated using artificial, non-complex samples. Their accuracy on estimating cell counts given temporal tissue gene expression data remains not well characterized and has never been characterized when using diseased lung. Further, how to remove the effects of cell migration on transcript counts to improve discovery of disease factors is an open question. Results: Four cell count inference (i.e., deconvolution) tools are evaluated using microarray data from influenza-infected lung sampled at several time points post-infection. The analysis finds that inferred cell quantities are accurate only for select cell types and there is a tendency for algorithms to have a good relative fit (R 2 ) but... [more]
Highly Porous Graphitic Activated Carbons from Lignite via Microwave Pretreatment and Iron-Catalyzed Graphitization at Low-Temperature for Supercapacitor Electrode Materials
Dongdong Liu, Xiaoman Zhao, Rui Su, Zhengkai Hao, Boyin Jia, Song Li, Liangjie Dong
July 31, 2019 (v1)
Keywords: activated carbons, graphitization, high porosity, supercapacitor material
At present, the preparation of highly porous graphitic activated carbons (HPGACs) using the usual physical and chemical activation methods has met a bottleneck. In this study, HPGACs are directly synthesized from lignite at 900 °C. The whole process is completed by a microwave pretreatment, a graphitization conversion of the carbon framework at a low temperature using a small amount of FeCl3 (10−30 wt%), and a subsequent physical activation using CO2. Consequently, the dispersed and mobile iron species, in the absence of oxygen functional groups (removed during the microwave pretreatment), can greatly promote catalytic graphitization during pyrolysis, and, as an activating catalyst, can further facilitate the porosity development during activation. The as-obtained AC-2FeHLH-5-41.4(H) presents a low defect density, high purity, and specific surface area of 1852.43 m2 g−1, which is far greater than the AC-HLH-5-55.6(H) obtained solely by physical activation. AC-2FeHLH-5-41.4(H) as a supe... [more]
Influence of Injection Timing on Performance and Exhaust Emission of CI Engine Fuelled with Butanol-Diesel Using a 1D GT-Power Model
Salman Abdu Ahmed, Song Zhou, Yuanqing Zhu, Yongming Feng, Adil Malik, Naseem Ahmad
July 31, 2019 (v1)
Keywords: bio-fuels, butanol-diesel blend, diesel engine, emission, engine performance, injection timing
Injection timing variations have a significant effect on the performance and pollutant formation in diesel engines. Numerical study was conducted to investigate the impact of injection timing on engine performance and pollutants in a six-cylinder turbocharged diesel engine. Diesel fuel with different amounts (5%, 15%, and 25% by volume) of n-butanol was used. Simulations were performed at four distinct injection timings (5°, 10°, 20°, 25°CA bTDC) and two distinct loads of brake mean effective pressure (BMEP = 4.5 bar and 10.5 bar) at constant engine speed (1800 rpm) using the GT-Power computational simulation package. The primary objective of this research is to determine the optimum injection timing and optimum blending ratio for improved efficiencies and reduced emissions. Notable improvements in engine performance and pollutant trends were observed for butanol-diesel blends. The addition of butanol to diesel fuel has greatly diminished NOX and CO pollutants but it elevated HC and CO... [more]
Distinct and Quantitative Validation Method for Predictive Process Modeling with Examples of Liquid-Liquid Extraction Processes of Complex Feed Mixtures
Axel Schmidt, Jochen Strube
July 31, 2019 (v1)
Keywords: atpe, biologics, design-of-experiments, liquid-liquid extraction, Modelling, monte-carlo, quality-by-design, Simulation, validation, verification
As of today, industrial process development for liquid-liquid extraction and scale-up of extraction columns is based on an experimental procedure that requires tests in pilot-scale. This methodology consumes large amounts of material and time and the utilized scale-up equations are crude estimates including considerable safety margins. This approach is practical for well-known systems or low-value products coupled with high production scale, where such a scale-up methodology has less impact on the overall profitability. However, for new high-value products in biologics manufacturing, a process development based on process understanding and the use of validated process models is imperative. Therefore, a distinct and quantitative validation workflow for liquid-liquid extraction modeling is presented on the example of two complex feed mixtures. Monte-Carlo simulations based on the presented model parameter determination concept result for both examples in prediction accuracy comparable to... [more]
Injectable Chitosan Scaffolds with Calcium β-Glycerophosphate as the Only Neutralizing Agent
Piotr Owczarz, Anna Rył, Marek Dziubiński, Jan Sielski
July 31, 2019 (v1)
Subject: Biosystems
Keywords: bone tissue engineering, calcium β-glycerophosphate, chitosan, injectable scaffolds, rheology, sol-gel phase transitions
The presented work describes the method of preparation of thermosensitive chitosan hydrogels using calcium β-glycerophosphate salt as the only pH neutralizing agent and supporting the crosslinking process. The presence of calcium ions instead of sodium ions is particularly important in the case of scaffolds in bone tissue engineering. Rheological and physicochemical properties of low concentrated chitosan solutions with the addition of calcium β-glycerophosphate were investigated using rotational rheometry techniques, Zeta potential (by electrophoresis), XPS, and SEM analysis together with an EDS detector. It was found to be possible to prepare colloidal solutions of chitosan containing only calcium β-glycerophosphate (without sodium ions) undergoing a sol-gel phase transition at the physiological temperature of the human body. It has also been shown that it is possible to further enrich the obtained cellular scaffolds with calcium ions. Using the addition of calcium carbonate, hydroge... [more]
Multi-Objective Optimal Scheduling Method for a Grid-Connected Redundant Residential Microgrid
Weiliang Liu, Changliang Liu, Yongjun Lin, Kang Bai, Liangyu Ma, Wenying Chen
July 31, 2019 (v1)
Keywords: analytic hierarchy process (AHP), non-dominate sorting genetic algorithm II (NSGA-II), optimal scheduling, redundant residential microgrid (RR-microgrid), virtual energy storage system (VESS)
Optimal scheduling of a redundant residential microgrid (RR-microgrid) could yield economical savings and reduce the emission of pollutants while ensuring the comfort level of users. This paper proposes a novel multi-objective optimal scheduling method for a grid-connected RR-microgrid in which the heating/cooling system of the RR-microgrid is treated as a virtual energy storage system (VESS). An optimization model for grid-connected RR-microgrid scheduling is established based on mixed-integer nonlinear programming (MINLP), which takes the operating cost (OC), thermal comfort level (TCL), and pollution emission (PE) as the optimization objectives. The non-dominate sorting genetic algorithm II (NSGA-II) is employed to search the Pareto front and the best scheduling scheme is determined by the analytic hierarchy process (AHP) method. In a case study, two kinds of heating/cooling systems, the radiant floor heating/cooling system (RFHCS) and the convection heating/cooling system (CHCS) ar... [more]
Verifying the Representativeness of Water-Quality Monitoring to Manage Water Levels in the Wicheon River, South Korea
Jung Min Ahn, Yong-Seok Kim
July 31, 2019 (v1)
Keywords: backwater, monitoring networks, river management, South Korea, water quality
Changes in water level between the mainstems and tributaries of a river can create backflow effects that alter the representativeness of water-quality monitoring data. In South Korea, 16 multi-functional weirs intended to manage water levels were constructed on 4 major rivers as part of a restoration project. However, they are causing backwater effects in tributaries that coincide with poorer water-quality measurements at monitoring stations along these tributaries despite there being no change in upstream pollution sources. Therefore, this study developed a new methodology for verifying the representativeness of a water-quality monitoring network via spatiotemporal observations of electrical conductivity, self-organizing maps for monthly pattern analysis, locally weighted scatter plot smoothing for trend analysis, load duration curves, and numerical modeling. This approach was tested on the Wicheon River, a primary tributary of the Nakdong River, because the measured decline in water... [more]
Parametric Methodology to Optimize the Sizing of Solar Collector Fields in Series-Parallel Arrays
Eduardo Venegas-Reyes, Naghelli Ortega-Avila, Norma A. Rodríguez-Muñoz, Mario Nájera-Trejo, Ignacio R. Martín-Domínguez, Jonathan Ibarra-Bahena
July 31, 2019 (v1)
Keywords: heat recovery, solar heat for industrial processes (SHIP), solar thermal systems design, TRNSYS
The analysis of solar thermal systems through numerical simulation is of great importance, since it allows predicting the performance of many configurations in any location and under different climatic conditions. Most of the simulation tools are commercial and require different degrees of training; therefore, it is important to develop simple and reliable methodologies to obtain similar results. This study presents a parametric methodology to size stationary solar collector fields, with operating temperatures up to 150 °C. The costs of the collector loop piping and the pumping power of different series−parallel arrays is considered. The proposed tool was validated with experimental data and through simulations using commercial software. The tool allows establishing series−parallel arrays and calculates the volume of the storage tank according to the thermal load. The calculation is based on the system energy balance, where the mass flow and the heat losses in the interconnections of t... [more]
Heat Flux Estimation at Pool Boiling Processes with Computational Intelligence Methods
Erdem Alic, Mehmet Das, Onder Kaska
July 31, 2019 (v1)
Keywords: boiling, computational intelligence techniques, heat flux, Optimization
It is difficult to manually process and analyze large amounts of data. Therefore, to solve a given problem, it is easier to reach the solution by studying the data obtained from the environment of the problem with computational intelligence methods. In this study, pool boiling heat flux was estimated in the isolated bubble regime using two optimization methods (genetic and artificial bee colony algorithm) and three machine learning algorithms (decision tree, artificial neural network, and support vector machine). Six boiling mechanisms containing eighteen different parameters in the genetic and the artificial bee colony (ABC) algorithms were used to calculate overall heat flux of the isolated bubble regime. Support vector machine regression (SVMReg), alternating model tree (ADTree), and multilayer perceptron (MLP) regression only used the heat transfer equation input parameters without heat transfer equations for prediction of pool boiling heat transfer over a horizontal tube. The perf... [more]
Internal R&D and Acquisition Performance of Chinese Pharmaceutical Firms: Moderation Effect of Acquisition Motive and Corporate Ownership
Qi Yue, Xing Hua, Jianyuan Li
July 31, 2019 (v1)
Subject: Other
Keywords: acquisition motives, acquisition performance, corporate ownership, D, internal R&, technical acquisition
Although corporate capability has been recognized as a key factor affecting corporate acquisition performance, the role of R&D capability in acquisition performance has not been fully explained. The aim of this paper was to research the impact of internal R&D on acquisition performance according to a sample of 215 acquisitions of Chinese listed pharmaceutical companies from 2012 to 2016. First, it was found that R&D has a significant negative effect on acquisition performance. Furthermore, it was confirmed that the acquisition motive and the ownership of the acquiring firm have a moderating effect on the relationship between R&D and acquisition performance. Compared to non-technical acquisitions, the negative effect of internal R&D on acquisition performance was reduced for technical acquisitions. Compared with non-state-owned-enterprise acquisition, the negative effect of internal R&D on the acquisition performance of state-owned enterprises was weakened. Our study enriches the resear... [more]
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