دانلود و نمایش مقالات مرتبط با Response surface::صفحه 1
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نتیجه جستجو - Response surface

تعداد مقالات یافته شده: 17
ردیف عنوان نوع
1 بهینه سازی شرایط فرآیند تولید کربن فعال بسیار متخلخل از ضایعات پوست خرما به منظور حذف آلاینده های موجود در آب
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 32
در این مطالعه ، فرآیند تهیه کربن فعال بسیار متخلخل (AC) از پوست خرما از طریق روش سطح پاسخ، بهینه سازی شد. شرایط بهینه آماده سازی AC از طریق روش ترکیبی تجزیه حرارتی با فعال سازی شیمیایی با استفاده از اسید فسفریک در حدود 3 ساعت زمان فعال سازی ، 400 درجه سانتیگراد درجه حرارت فعال سازی و 40وزنی برای مقدار عامل فعال بدست آمد. بالاترین مقادیر سطح خاص و تعداد ید تحت شرایط بهینه عبارتند از902 متر مربع در گرم و 983 میلی گرم در گرم، که تخلخل بسیار بالای ساختار AC را تأیید می کند. همچنین AC آماده به دلیل مساحت زیاد و وجود گروههای عملکردی اسیدی در سطح آن ، توانایی چشمگیری در از بین بردن آلاینده های مختلف از جمله آرسنیک (V) ، متیلن آبی ، متیل نارنجی و کوئرستین داشت. سرانجام ، شاخص تجاری محاسباتی در حدود 451 مترمربع در هر واحد مواد به دست آمد که کاربرد پوست خرما را به عنوان یک پیش درآمد ارزان قیمت و امیدوار کننده برای آماده سازی تجاری AC تأیید می کند.
واژه های کلیدی: پوست خرما | روش سطح پاسخ | سطح خاص | شماره ید | کوئرستین
مقاله ترجمه شده
2 بهبود تولید بیودیزل با کمک اولتراسونیک حاصل از ضایعات صنعت گوشت (چربی خوک) با استفاده از نانوکاتالیزور اکسید مس سبز: مقایسه سطح پاسخ و مدل سازی شبکه عصبی
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 11 - تعداد صفحات فایل doc فارسی: 25
سوخت زیستی سبز ، تمیز و پایدار تنها گزینه به منظور کاهش کابرد سوخت های فسیلی ، پاسخگویی به تقاضای زیاد انرژی و کاهش آلودگی هوا است. تولید بیودیزل زمانی ارزان می شود که از یک پیش ماده ارزان ، کاتالیزور سازگار با محیط زیست و فرآیند مناسب استفاده کنیم. پیه خوک از صنعت گوشت حاوی اسید چرب بالا است و به عنوان یک پیش ماده موثر برای تهیه بیودیزل کاربرد دارد. این مطالعه بیودیزل را از روغن پیه خوک از طریق فرآیند استری سازی دو مرحله ای با کمک اولتراسونیک و کاتالیزور تولید می کند. عصاره Cinnamomum tamala (C. tamala) برای تهیه نانوذرات CuO مورد استفاده قرار گرفت و با استفاده از طیف مادون قرمز ، پراش اشعه ایکس ، توزیع اندازه ذرات ، میکروسکوپ الکترونی روبشی و انتقال مشخص شد. تولید بیودیزل با استفاده از طرح Box-Behnken (BBD) و شبکه عصبی مصنوعی (ANN) ، در محدوده متغیرهای زمان اولتراسونیک (us )(20-40 min)، بارگیری نانوکاتالیزور 1-3) CuO درصد وزنی( ، و متانول به قبل از نسبت مولی PTO (10:1e30:1) مدلسازی شد. آنالیز آماری ثابت کرد که مدل سازی شبکه عصبی بهتر از BBD است. عملکرد بهینه 97.82٪ با استفاده از الگوریتم ژنتیک (GA) در زمان US: 35.36 دقیقه ، بار کاتالیزور CuO: 2.07 درصد وزنی و نسبت مولی: 29.87: 1 به دست آمد. مقایسه با مطالعات قبلی ثابت کرد که اولتراسونیک به میزان قابل توجهی موجب کاهش بار نانوکاتالیزور CuO می شود ، و نسبت مولی را افزایش می دهد و این فرایند را بهبود می بخشد.
کلمات کلیدی: چربی خوک | التراسونیک | اکسید مس | سنتز سبز | شبکه عصبی | سطح پاسخ
مقاله ترجمه شده
3 Geothermal resource and reserve assessment methodology: Overview, analysis and future directions
منابع زمین گرمایی و روش ارزیابی ذخایر: بررسی اجمالی ، تجزیه و تحلیل و مسیرهای آینده-2020
Resource assessment and reserve estimation play a crucial role in the decision-making, financing, development, and operation of geothermal projects. The present study critically examines all existing resource assessment methodology and practices when quantifying power potential of geothermal fields. The potential generating capacity of geothermal projects at the early stage of development, where there is limited information about the resource, is typically estimated using the volumetric method. Sustainable operation and management of existing geothermal fields, on the other hand, rely on developing and updating a calibrated numerical reservoir model. To-date, the volumetric method and reservoir simulation remain the most appropriate tools to use for geothermal resource assessment. The former method is the recommended approach for projects that are still at the early stage of development, while the latter technique is for predicting sustainable production capacity after exploration drilling. However, building a numerical model for a project at the early due diligence stage is also useful and can complement the volumetric method. Most studies of resource assessment methodologies highlight the difficulty of obtaining accurate, predictable generating output potential. Quantification of uncertainty in predictable output is carried out using the Monte Carlo method. This review demonstrates that the probabilistic assessment using Experimental Design (ED) and Response Surface Methodology (RSM) is a more promising technique that can be easier and quicker to implement.
Keywords: Resource assessment | Resource assessment methodology | Power potential | Volumetric method | Numerical reservoir simulation | Probabilistic resource assessment
مقاله انگلیسی
4 An efficient simulation optimization methodology to solve a multi-objective problem in unreliable unbalanced production lines
یک روش بهینه سازی شبیه سازی کارآمد برای حل یک مشکل چند هدف در خطوط تولید نامتوازن غیرقابل اعتماد-2019
This research develops an expert system to addresses a novel problem in the literature of buffer allo- cation and production lines. We investigate real-world unreliable unbalanced production lines where all time-based parameters are probabilistic including time between parts arrivals, processing times, time be- tween failures, repairing times, and setup times. The main contributions of the paper are a twofold. First and foremost, the mean processing times of workstations and buffer capacities, unlike the existing litera- ture, are considered as decision variables in a multi-objective optimization problem which maximizes the throughput rate and minimizes the total buffer capacities as well as the total cost of the mean process time reductions. Secondly, an efficient methodology is developed that can precisely reflect a real-world system without any unrealistic and/or restrictive assumptions on the probabilistic nature of the system, which are commonly assumed in the existing literature. One of the greatest challenges in this research is to estimate the throughput rate function since it highly depends on the random behavior of the sys- tem. Thus, a simulation optimization approach is developed based on the Design of Experiments and Re- sponse Surface Methodology to fit a regression model for throughput rate. Finally, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Non-dominated Ranked Genetic Algorithm (NRGA) are used to gener- ate high-quality solutions for the aforementioned problem. This methodology is run on a real numerical case. The experimental results confirm the advantages of the proposed methodology. This methodology is an innovative expert system with a knowledge-base developed through this simulation optimization approach. This expert system can be applied to complex production line problems in large or small scale with different types of decision variables and objective functions. The application of this expert system is transformative to other manufacturing systems.
Keywords: Unreliable unbalanced production lines | Buffer allocation problem | Simulation optimization | Design of experiments | Response surface methodology | Meta-heuristics
مقاله انگلیسی
5 Selection of an optimized metal oxide semiconductor sensor (MOS) array for freshness characterization of strawberry in polymer packages using response surface method (RSM)
انتخاب آرایه سنسور نیمه هادی اکسید فلزی بهینه سازی شده (MOS) برای توصیف طراوت توت فرنگی در بسته های پلیمری با استفاده از روش سطح پاسخ (RSM)-2019
An eight metal oxide semiconductor sensor (MOS) based electronic nose (e-nose) has been used to characterize freshness of strawberry in different polymer package types. Pattern recognition methods such as principal component analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) were used to classify and investigate the effects of polymer packages on strawberry freshness. The packages were Ethylene Vinyl Alcohol (EVOH), Polypropylene (PPP), and Polyvinyl chloride (PVC). The response surface method (RSM) was considered for selection of optimized sensor array in terms of the contribution of each sensor in sample classification. Sample headspace patterns were examined on days 1, 8 and 16. The results revealed that PCA explains 84% of the variance between the data. The LDA classified samples with an accuracy of 86.4%. The SVM method with polynomial function could accurately recognize samples as C-SVM by 86.4% and 50.6% in training and validation, and as Nu-SVM by 85.2% and 55.6% in training and validation with a radial basis function, respectively. Finally, among the eight sensors used in the study, MQ8, MQ3, TGS813, MQ4, and MQ136 sensors were selected as optimal response sensors using RSM to reduce the cost of fabrication. Furthermore, optimal application sensors for each polymer package were identified using RSM.
Keywords: Electronic nose | Strawberry | Response surface | Optimized sensors
مقاله انگلیسی
6 Expert system based on a fuzzy logic model for the analysis of the sustainable livestock production dynamic system
سیستم خبره مبتنی بر یک مدل منطق فازی برای تجزیه و تحلیل سیستم پویا تولید دام پایدار-2019
This essay documents the development of an “Expert System” based on a Fuzzy Logic model, designed to analyze the outcome a number of variables have on the performance of livestock production (milk and meat) in the Huasteca region of Veracruz in order to support the decision-making of a Sustainable Livestock Production Dynamic System (SLPDS). The Expert System takes into consideration the following input variables: Temperature (T), Rain (RA), Breed (B), Health Plan Implementation (HP), Feeding Plan (FP) and Production System (PS). The aforementioned variables then have an impact on three output variables: Lactation Days (LD), Daily Milk Production (DMP) and Intervals between Births (IBB). Once the Fuzzy Logic model has been developed, an assessment of the variables is made through the Response Surface technique, which allows verifying how the variables behave in the system under study, and their impact on the output variables; as well as, testing different scenarios in order to validate the model and to identify the Livestock Production Systeḿs behavioral patterns. Through the application of Fuzzy Logic regarding the modeling of the 6 variables that impact the performance of livestock production, it is possible to capitalize on the knowledge and experience that producers have and what they have learned based on the observation and practice of many years. Therefore, being able to obtain reliable results that can be shared with agricultural producers and technicians for the improvement of the livestock productivity of the Huasteca region in the state of Veracruz. The Expert System is efficient showing an 86.67% reliability by comparing its results with a panel of specialists in livestock production. The test of the different scenarios shows interesting results when exposing the application of good livestock practices in certain conditions (temperature and rainfall) that maximize the milk and meat production of the region under study.
Keyword: Sustainable livestock production | Expert system | Fuzzy logic | Response surface
مقاله انگلیسی
7 بهینه سازی ساچمه پاشی ‏ با ابزار تصمیم گیری پیچیده: تصمیم گیری چند معیاره
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 9 - تعداد صفحات فایل doc فارسی: 25
فرایند ساچمه پاشی ‏ کنترل شده با دو روش مستقل: (1) ساچمه پاشی اولیه از نوار Almen برای تعیین شدت مورد نظر، (2) ساچمه کاری نمونه واقعی با شدت Almen ، انجام شد. ساچمه پاشی Almen در مرحله اول زمان زیادی طول می کشد. که علت آن این است که علاوه بر استفاده از پارامترهای ورودی، اندازه گیری ارتفاع قوس و کنترل شدت Almen نیز باید به طور پیوسته انجام شود. نتایج به طور مستقیم بر ویژگی های واقعی موثر است. با این حال اندازه گیری ارتفاع و تنظیم پارامترهای ورودی به تکنسین کارفرما بستگی دارد. بنابراین، روش عددی با مدلسازی اجزای محدود (FEM) ، شبکه عصبی مصنوعی (ANN) و RSM (روش شناسی سطح پاسخ) پیشرفت بیشتری دارد. بدین منظور، روش عددی دیگری از جمله تصمیم گیری چند معیاره (MCDM) توسعه یافته اند و همچنین در مقایسه با نتایج آزمایشگاهی، زبری سطح و سختی سطح قرار گرفت. نتایج نشان داد که روش های MCDM با خودشان سازگار هستند و در چارچوب پارامترهای ورودی (فشار هوا، اندازه ساچمه، طول ساچمه باری) و پارامترهای خروجی نیز سازگار است (سختی سطح، زبری سطح). رویکرد Topsis نتایج سازگار را در مقایسه با دیگر رویکردها و شرایط آزمایشی ارائه می دهد.
کليدواژگان: شدت Almen | ساچمه کاری | Topsis | Vikor | GRA | MCDM
مقاله ترجمه شده
8 City-specific vehicle emission control strategies to achieve stringent emission reduction targets in Chinas Yangtze River Delta region
استراتژی های کنترل انتشار خودرو از سوی شهر برای رسیدن به اهداف دقیق کاهش انتشار در منطقه ی دلتای رودخانه یانگ تی چینی-2017
The Yangtze River Delta (YRD) region is one of the most prosperous and densely populated regions in China and is facing tremendous pressure to mitigate vehicle emissions and improve air quality. Our assessment has revealed that mitigating vehicle emissions of NOx would be more difficult than reducing the emissions of other major vehicular pollutants (e.g., CO, HC and PM2.5) in the YRD region. Even in Shanghai, where the emission control implemented are more stringent than in Jiangsu and Zhejiang, we observed little to no reduction in NOx emissions from 2000 to 2010. Emission–reduction targets for HC, NOx and PM2.5 are determined using a response surface modeling tool for better air quality. We design city-specific emission control strategies for three vehicle-populated cities in the YRD region: Shanghai and Nanjing and Wuxi in Jiangsu. Our results indicate that even if stringent emission control consisting of the Euro 6/VI standards, the limitation of vehicle population and usage, and the scrappage of older vehicles is applied, Nanjing and Wuxi will not be able to meet the NOx emissions target by 2020. Therefore, additional control measures are proposed for Nanjing and Wuxi to further mitigate NOx emissions from heavy-duty diesel vehicles.
Keywords: Vehicle | Emission control | Scenario | Yangtze River Delta
مقاله انگلیسی
9 What are causes of cash flow bullwhip effect in centralized and decentralized supply chains?
علل اثرگذاری جریان پول نقد در چرخه عرضه متمرکز و غیر متمرکز چیست؟-2017
Bullwhip effect in supply chain is a phenomenon which can emerge in both inventory lev els and replenishment orders. Bullwhip effect causes variations in cash conversion cycle (CCC) across cash flow of supply chain. As a result, it can lead to inefficiencies such as cash flow bullwhip (CFB). Due to negative impact of CFB on cash flow of supply chain, it can lead to a decrease in efficiency of supply chain management (SCM). That is why sup ply chain modeling is a proper start point for effective management and control of the CFB. This paper aims to analyze concurrent impact of causes of inventory bullwhip effect and effect of their interactions on CFB based on generalized OUT policy from aspect of CCC variance. To this end, first we develop system dynamics structure of beer distribution game as simulation model which includes multi-stage supply chain under both central ized and decentralized supply chains. Then, in order to develop CFB function, we design experiments in developed simulation model using response surface methodology (RSM). Results demonstrate that if each chain member uses generalized OUT policy as replen ishment model, there still exists CFB in both chains and CFB largely stems from rationing and shortage gaming in both centralized and decentralized supply chain. In addition, when information on ordering parameters are not shared among members, parameters of down stream stage (i.e. retailer) are more important than parameters of upstream stage (i.e. man ufacturer) in reducing CFB function.
Keywords: Supply chain management | Bullwhip effect | Cash flow bullwhip |Response surface methodology
مقاله انگلیسی
10 Performance of coated and uncoated mixed ceramic tools in hard turning process
عملکرد ابزار سرامیک مخلوط پوششدار و بدون پوشش در فرایند تبدیل سخت-2016
The present contribution deals with the study of the effects of cutting speed, feed rate and depth of cut on the performance of machining which traditionally named ‘‘machinability”. The focus is made on the effect of the pre-cited cutting parameters on the evolution of sur- face roughness and cutting force components during hard turning of AISI D3 cold work tool steel with CC6050 and CC650 ceramic inserts. Also, for both ceramics a comparison of theirwear evolution with time and its impact on the surface equality was proposed. The plan-Keywords:Hard turningning of experiments was based on Taguchi’s L16orthogonal array. The analysis of varianceSurface roughness Cutting forceTool wear Taguchi method RSM(ANOVA), the signal-to-noise ratio and response surface methodology (RSM) were adopted.Consequently, the validity of proposed linear regression model was checked and the most important parameter affecting the surface roughness and cutting force components were determined. Furthermore, in order to determine the levels of the cutting regime that lead to minimum surface roughness and minimum machining force the relationship between cutting factors was analyzed. The results revealed that the surface quality obtained with the coated CC6050 ceramic insert is 1.6 times better than the one obtained with uncoated CC650 ceramic insert. However, the uncoated ceramic insert was useful in reducing the machining force.© 2015 Elsevier Ltd. All rights reserved.
Keywords: Hard turning | Surface roughness | Cutting force | Tool wear | Taguchi method | RSM
مقاله انگلیسی
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