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Investigation of the main and interactive effects of mix design factors on the properties of cement emulsified asphalt mortars using Mixture Design of experiment

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CONSTRUCTION AND BUILDING MATERIALS 2021年 266卷

作者： Delarami, Aref Moghaddam, Abolfazl Mohammadzadeh Yazadani, Mohammadreza Rasaei Najjar, Shima Ferdowsi Univ Mashhad Fac Engn Dept Civil Engn Mashhad Razavi Khorasan Iran

This study investigated the effect of mixture components including cement, asphalt emulsion, sand, and water on mechanical and rheological properties of Cement Emulsified Asphalt (CA) mortars (type I and II). For this investigation, compressive strength, elastic modulus, segregation, fluidity funnel), and spread diameter and time (specific to type II mortar) tests were performed on fresh and hardened specimens. SEM technique was also employed to inspect the micro-structure of CA mortars. To study the effect of mix design factors and their interactions in the domain where rheological and mechanical requirements are met, the Mixture Design method was used in conjunction with the D-Optimal algorithm to design the experiments and analyze the results. After assuming a quadratic model for the relationships between response variables (mechanical and rheological properties) and independent variables (mixture components) including the main effects and two-way effects, 15 randomized mix designs were obtained for each type of mortar (30 mix designs in total). The test of compressive strength was performed on cubic 50 x 50 x 50 mm specimens at the age of 7 and 28 days. The Elastic modulus of the mortars was determined from the strain-strain diagram pertaining to the 28-day compressive strength specimens. Segregation was evaluated by the use of cylindrical 50 x 500 specimens. Tests of fluidity, spread diameter, and spread time were performed according to the standards of the Ministry of Railways of China. The experimental results were used to develop the estimation models of the responses, and the effect of factors and their interactions on mechanical and rheological properties were studied at 95% confidence level. The estimated statistical models could accurately predict the performance of the mortars and were therefore employed to find the optimum combinations of mixture components. Trace and ternary contour plots were drawn to analyze and discuss the effects of mixture compon

关键词： Cement Emulsified Asphalt Mortars Mixture components Mixture Design of experiment Mechanical and rheological properties SEM modeling and optimization

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Ultrasonic-Assisted Rapid Preparation of Sulfonated Polyether Ether Ketone (PEEK) and Its Testing in Adsorption of Cationic Species from Aqueous Solutions

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MATERIALS 2022年第21期15卷 7558页

作者： Baltag, Laurentiu Cojocaru, Corneliu Enache, Andra-Cristina Samoila, Petrisor Harabagiu, Valeria Petru Poni Inst Macromol Chem 41A Grigore Ghica 7 Voda Alley Iasi 700487 Romania

Herein, we report a new approach for the sulfonation of polyether ether ketone (PEEK) following a shorter path of reaction undertaken at 60 degrees C under ultrasonication. The application of this method enabled the reduction of the reaction time from several hours to less than one hour, achieving a relevant sulfonation degree. The sulfonated-PEEK (SPEEK) was characterized by advanced chemical and physical instrumental methods. According to H-1-NMR analysis, the degree of sulfonation of the polymer was equal to 70.3%. Advanced microscopy (SEM) showed that the fabricated SPEEK beads (2-4 mm) were porous inside with a log-normal distribution of pore sizes within the range 1.13-151.44 mu m. As an application, the SPEEK polymer was tested for the adsorption of a cationic organic pollutant (Methylene blue, MB) from aqueous solutions. The equilibrium studies (isotherms) disclosed maximum adsorption capacities of 217 mg/g, 119 mg/g, and 68 mg/g at temperatures of 323 K, 313 K, and 300 K, respectively. The thermodynamic calculations indicated an endothermic effect (Delta H-ad = +11.81 kJ/mol) of the investigated adsorption process. The maximum removal efficiency of 99.14% was established by process optimization using the design of experiments strategy and data-driven modeling. Additionally, molecular docking simulations were performed to disclose the mechanism of interaction at the molecular level between the adsorbent (SPEEK) and pollutant.

关键词： sulfonated polyether ether ketone adsorption Methylene Blue modeling and optimization molecular docking

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Projecting adoption of truck powertrain technologies and CO2 emissions in line-haul networks

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TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT 2020年 84卷

作者： de la Pena, Ana Guerrero Davendralingam, Navindran Raz, Ali K. DeLaurentis, Daniel Shaver, Gregory Sujan, Vivek Jain, Neera Purdue Univ Sch Mech Engn W Lafayette IN 47097 USA Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47097 USA Cummins Inc Columbus IN 47201 USA

In this paper we present a mixed-integer linear program to represent the decision-making process for heterogeneous fleets selecting vehicles and allocating them on freight delivery routes to minimize total cost of ownership. This formulation is implemented to project alternative powertrain technology adoption and utilization trends for a set of line-haul fleets operating on a regional network. Alternative powertrain technologies include compressed (CNG) and liquefied natural gas (LNG) engines, hybrid electric diesel, battery electric (BE), and hydrogen fuel cell (HFC). Future policies, economic factors, and availability of fueling and charging infrastructure are input assumptions to the proposed modeling framework. Powertrain technology adoption, vehicle utilization, and resulting CO2 emissions predictions for a hypothetical, representative regional highway network are illustrated. A design of experiments (DOE) is used to quantify sensitivity of adoption outcomes to variation in vehicle performance parameters, fuel costs, economic incentives, and fueling and charging infrastructure considerations. Three mixed-adoption scenarios, including BE, HFC, and CNG vehicle market penetration, are identified by the DOE study that demonstrate the potential to reduce cumulative CO2 emissions by more than 25% throughout the period of study.

关键词： Powertrain adoption projection CO2 emissions System-of-systems engineering modeling and optimization

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Data-Driven modeling Methods and Techniques for Pharmaceutical Processes

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PROCESSES 2023年第7期11卷

作者： Dong, Yachao Yang, Ting Xing, Yafeng Du, Jian Meng, Qingwei Dalian Univ Technol Inst Chem Proc Syst Engn Sch Chem Engn Dalian 116024 Peoples R China Dalian Univ Technol Sch Pharmaceut Sci & Technol State Key Lab Fine Chem Dalian 116024 Peoples R China

As one of the most influential industries in public health and the global economy, the pharmaceutical industry is facing multiple challenges in drug research, development and manufacturing. With recent developments in artificial intelligence and machine learning, data-driven modeling methods and techniques have enabled fast and accurate modeling for drug molecular design, retrosynthetic analysis, chemical reaction outcome prediction, manufacturing process optimization, and many other aspects in the pharmaceutical industry. This article provides a review of data-driven methods applied in pharmaceutical processes, based on the mathematical and algorithmic principles behind the modeling methods. Different statistical tools, such as multivariate tools, Bayesian inferences, and machine learning approaches, i.e., unsupervised learning, supervised learning (including deep learning) and reinforcement learning, are presented. Various applications in the pharmaceutical processes, as well as the connections from statistics and machine learning methods, are discussed in the narrative procedures of introducing different types of data-driven models. Afterwards, two case studies, including dynamic reaction data modeling and catalyst-kinetics prediction of cross-coupling reactions, are presented to illustrate the power and advantages of different data-driven models. We also discussed current challenges and future perspectives of data-driven modeling methods, emphasizing the integration of data-driven and mechanistic models, as well as multi-scale modeling.

关键词： data-driven modeling machine learning multivariate tools pharmaceutical processes process systems engineering modeling and optimization

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Global optimization and Quantitative Assessment of Large-Scale Renewables-Based Hydrogen System Considering Various Transportation Modes and Multi-Field Hydrogen Loads

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PROCESSES 2024年第7期12卷

作者： Hong, Liu Liu, Deqi Shi, Lei Tan, Yuhua Xiang, Yujin Zhang, Qian Li, Tianle Jiuquan Power Supply Co State Grid Gansu Elect Power Co Jiuquan 735000 Peoples R China Univ Shanghai Sci & Technol Dept Elect Engn Shanghai 200093 Peoples R China

In the past, hydrogen was mostly produced from fossil fuels, causing a certain degree of energy and environmental problems. With the development of low-carbon energy systems, renewable energy hydrogen production technology has developed rapidly and become one of the focuses of research in recent years. However, the existing work is still limited by small-scale hydrogen production systems, and there is a lack of comprehensive research on the whole production-storage-transportation-utilization hydrogen system (PSTUH2S), especially on the modeling of different hydrogen transportation modes and various hydrogen loads in different fields. To make up for these deficiencies, the specific physical and mathematical models of the PSTUH2S are firstly described in this paper, with a full account of large-scale water-electrolytic hydrogen production from renewable power curtailment and grid power, various hydrogen storage and transportation modes, and multi-field hydrogen consumption paths. Furthermore, to achieve the maximum economic, energy, and environmental benefits from the PSTUH2S, a multi-objective nonlinear optimization model is also presented herein and then solved by the hybrid method combining the nonlinear processing method, the CPLEX solver and the piecewise time series production simulation method. Lastly, case studies are conducted against the background of a region in northwest China, where hydrogen consumption capacity in various years is accurately assessed and the potential advantages of the PSTUH2S are demonstrated. As the simulation results show, the power curtailment of renewable energy generation can be reduced by 3.61/11.87/14.72 billion kW center dot h in 2025/2030/2035, respectively, thus contributing to a 4.98%similar to 10.09% increase in the renewable energy consumption rate and millions of tons of carbon emission reduction in these years. In terms of the total equivalent economic benefits, the proposed method is able to bring about a cost saving of

关键词： production-storage-transportation-utilization hydrogen system renewable energy modeling and optimization hydrogen consumption capacity benefit evaluation

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modeling and Sizing of a MW Solar DSG plant

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Energy Procedia 2016年 91卷 620-629页

作者： Antoine Frein Lorenzo Pistocchini Victor Tatay Mario Motta Politecnico di Milano Energy Department Via Lambruschini 4 20133 Milano Itlay

Direct Steam Generation (DSG) Concentrated Solar technology, based on Linear Fresnel Reflectors (LFR) and aimed at supplying saturated steam to industrial processes, is a promising application; nevertheless, nowadays few case studies and very few installations have been developed. A methodology for the design optimization of a MW solar DSG plant is presented in this article and applied to a real case study of a Brazilian tire manufacturing facility. A steady-state model, with spatial discretization of the ordinary equations, allows characterizing the physical phenomena such as pressure drop and heat transfer, and therefore to determine the pressure and specific enthalpy trend along the recirculation loop. For each receiver tube of the solar collectors, the occurring single or two-phase flow pattern is calculated based on specific empirical equations developed for evaporation in horizontal tubes. Two reference operating conditions have been identified for the present case study, at which the optimal field layout results to be a series connection of all the collectors, and the optimal nominal flow rate to avoid possible harmful operating conditions for the absorber tubes is 1.0 kg/s.

关键词： Solar concentration Process heat Direct Steam Generation flow pattern Linear Fresnel Reflector modeling and optimization

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Investigation of computer numerical control wood milling parameters for occupationally safer by the minimization of produced wood dust

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WOOD MATERIAL SCIENCE & ENGINEERING 2024年第3期19卷 674-682页

作者： Rabiei, F. Souri, Sh. Ilam Univ Fac Engn Dept Mech Engn Ilam Iran Univ Med Fac Hlth Dept Occupat Hlth & Safety Engn Ilam Iran

Computer numerical control (CNC) wood machining produces wood dust, harming the operator's health. In this research, the effective parameters of the amount of produced wood dust (PM) in CNC milling are investigated. The design of the experiment was done based on the response surface method (RSM) and subsequently, 27 experimental tests were performed. The results of the analysis of variance show that the parameters of the depth of cut (ap), step over (ae), feed rate (vw) and cutting speed (vc) have a great impact on PM, respectively. Changing these machining parameters leads to severe changes in the PM (0.043-11.200 mg/m3). Also in 78% of experimental tests, the amount of PM is higher than the National Institute for Occupational Safety and Health (NIOSH) standard value (1 mg/m3). In the next step, for the reduction and minimization of PM, a quadratic regression equation was derived. After model validation, the model was minimized by the distance-based optimality method at Minitab software. optimization result shows that by choosing the optimum parameters ap = 3 mm, vw = 50 mm/s, vc = 15,393 rpm and ae = 6.270 mm, PM is reduced to 0.011 mg/m3, which is much lower (about 89%) than the NIOSH standard value. This prediction was tested and validated by the experimental test.

关键词： Machining parameters modeling and optimization safe machining operator health

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The Effect of Different Additives and Medium on the Bioleaching of Molybdenite for Cu and Mo Extraction Using Mix Mesophilic Microorganism

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International Journal of Mining and Geo-Engineering 2013年第1期47卷 61-80页

作者： Hadi Abdollahi Seyed Ziaedin. Shafaei Mohammad Noaparast Z. Manafi N. Aslan A. Akcil School of Mining College of Engineering University of Tehran Department of Mining Engineering Mineral Processing Division (Mineral-Metal Recovery and Recycling Research Group) Suleyman Demirel University

Bioleaching processes for extraction of Cu and Mo from molybdenite cons. are more environmentally friendly and consume less energy than conventional technologies, yet less economically efficient. One necessary step towards arriving at a cost-effective bioleaching process is using appropriate methodology to optimize pertinent factors in such processes. To this end, the present study employed Response Surface Methodology to optimize important factors in a molybdenite bioleaching process by mix mesophilic microorganism using shake flasks. The effect of change in the levels of molybdenite concentration, pyrite and silver ion concentration as additives - in the range 3-9%, 1-5%, and 0-1.2gr/l, respectively - on the rate of Cu and Mo bioleaching was studied using a Central Composite Design. The results showed a statistically significant effect of silver ion and molybdenite concentration, and to a lesser pyrite concentration, on the rate of bioleaching of Cu and Mo. Further, different mediums and additives were evaluated for copper and molybdenum extraction from molybdenite concentrate in bioleaching process. Small amounts of silver (100mgr/l AgSO4) dramatically accelerated the copper dissolution process. Addition of FeS2 and sulfur with ferrous sulfate accelerated the acidification and raised the oxidation- reduction potential of solution (medium) with an inoculation of 15% (v/v) of active and adapted indigenous mesophilic bacteria, thus resulting in an overall increase in Mo dissolution efficiency.

关键词： additive biohydrometallurgy Cu and Mo dissolution mixed mesophilic bacteria modeling and optimization molybdenite concentrate

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Solar-driven Dish Stirling System for sustainable power generation in Bangladesh: A case study in Cox?s Bazar

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HELIYON 2023年第3期9卷 e14322页

作者： Hossain, Md. Sakib Rahat, Amimul Ihsan Khan, Shadman Hasan Salehin, Sayedus Karim, Rezwanul Islamic Univ Technol IUT Dept Mech & Prod Engn Gazipur Bangladesh

In recent years, the power sector of Bangladesh has seen a major development in terms of generation capacity. But as before, it is heavily dependent on fossil fuels overlooking the potential of renewable energy resources. The scope for grid-connected renewable energy systems has not been explored too far and in terms of solar thermal energy and concentrating solar power (CSP), it is even less. This study focuses on assessing the techno-economic feasibility of solar-driven Dish Stirling system for large-scale grid-connected power generation in Bangladesh. Detailed modeling and optimization of a 100 MW Dish Stirling power plant have been carried out in Cox's Bazar, Bangladesh, a location suitable for solar energy harnessing due to favorable climatic conditions. The modeling parameters and weather data have been collected from relevant literature, various solar data providers, and specific plant parameters have been optimized for the Bangladeshi climatic condition. Simulation of the modeled plant carried out by the System Advisor Model (SAM) shows that, it can supply 129.856 GWh electricity annually operating at an overall efficiency of 24.91% which is much higher than the values reported in similar literature for the South-Asian regions. The levelized cost of electricity (LCOE) has been determined to be 10.18 cents/kWh, which is highly competitive and promising. The insights obtained from this study can be a perfect starting point for the policymakers and concerned authorities of Bangladesh to further explore the viability of this technology for renewable and sustainable power.

关键词： Solar thermal power Dish stirling modeling and optimization

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Hummer acoustic resonance as an innovative green technology for extracting active components from mulberry leaves

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SUSTAINABLE CHEMISTRY AND PHARMACY 2024年 42卷

作者： Yan, Zixuan Zhang, Yijing Yang, Yinglian Li, Guoxiang Guan, Zhiqi Wu, Wei Li, Wenlong Tianjin Univ Tradit Chinese Med Coll Pharmaceut Engn Tradit Chinese Med Tianjin 301617 Peoples R China Tianjin Key Lab Intelligent & Green Pharmaceut Tra Tianjin 301617 Peoples R China Shenzhen Huasheng Proc Intensificat Technol Co Ltd Shenzhen 518057 Peoples R China State Key Lab Chinese Med Modernizat Tianjin 301617 Peoples R China

In this study, we investigated a novel extraction method-hummer acoustic resonance technologyfor extracting active components from mulberry leaves. Through single-factor experiments, we determined the effects of four variables: extraction time (A), extraction solvent (B), hummer acoustic resonance acceleration (C), and zirconia bead content (D) on the total flavonoid, total phenolic, and glucose contents. The extraction process was optimized using Box-Behnken design response surface methodology (BBD-RSM) and a newly established genetic algorithm coupled with support vector regression (GA-SVR), with comprehensive evaluation as the evaluation index. Multiple assessment metrics were employed to test the performance of both models. Compared to BBD-RSM, the GA-SVR model demonstrated higher fitting accuracy, smaller errors between predicted and experimental values, and more accurately described the extraction effects, proving to be an effective quantitative tool for optimizing hummer acoustic resonance extraction parameters. Finally, a comparison between hummer acoustic resonance technology and traditional reflux extraction revealed that the former outperformed the latter in terms of time efficiency and energy consumption.

关键词： Mulberry leaves extraction Hummer acoustic resonance Box-behnken design modeling and optimization

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