جستجوی مقالات مرتبط با کلیدواژه « decision-making » در نشریات گروه « مکانیک »
تکرار جستجوی کلیدواژه «decision-making» در نشریات گروه «فنی و مهندسی»-
با توجه به رشد روزافزون جمعیت جهان و نیازهای رو به افزایش برای محصولات سلولزی، حفظ پایداری در این صنعت بسیار اهمیت دارد. بنابراین، تعیین اهمیت شاخص های پایداری در صنایع سلولزی، بهبود عملکرد و تاثیرات محیط زیستی، اجتماعی و اقتصادی این صنعت ضروری است. زیرا، با تعیین اهمیت شاخص های پایداری در صنایع سلولزی، می توان استراتژی ها و سیاست های مناسبی را برای بهبود عملکرد پایدار در این صنعت تعیین کرد و به دستیابی به توسعه پایدار و حفظ محیط زیست کمک کرد. از این رو، هدف اصلی این پژوهش تکیه بر اهمیت ارایه شده توسعه یک مدل تصمیم گیری است که قادر می باشد ضمن شناسایی، اهمیت مقوله های (شاخص های) اثرگذار بر پایداری صنایع سلولزی و همچنین، اولویت بندی عوامل فرعی را با تجزیه و تحلیل از طریق تکنیک های تصمیم گیری چند معیاره محاسبه نماید. در این تحقیق، یک روش تلفیقی با استفاده از روش های تحلیل سلسله مراتبی و بهترین بدترین برای محاسبه وزن مقوله ها و روش اولویت بندی آراس برای انتخاب بهترین گزینه و پیشنهاد ترتیب رتبه بندی ترجیحی گزینه ها استفاده شده است. از تجزیه و تحلیل، مشخص شده است که 11 مقوله اصلی و سه مقوله فرعی بر روی پایداری صنایع سلولزی تاثیرگذار است. طبق نتایج بدست آمده، در میان مقوله های اصلی همکاری تامین کننده استراتژیک با امتیاز وزن تلفیقی0/1801 بیشترین اهمیت و بهبود مستمر با امتیاز وزن تلفیقی 0/0252 کمترین اهمیت را دارند. همچنین، در میان عوامل فرعی مدیریت محیطی با درجه مطلوبیت 1 اولویت اول و فشار محیطی با درجه مطلوبیت 0/555 اولویت آخر را دارند. علاوه بر این، با معرفی این چارچوب تصمیم گیری، تحلیل های محققین قبلی بازسازی شده است و چارچوب رتبه بندی های گزینه ها به صورت ترکیبی پیشنهاد شده است.
کلید واژگان: اولویت بندی, تصمیم گیری, اوزان تلفیقی, صنایع سلولزی, پایداری}Considering the ever-increasing growth of the world's population and the increasing needs for cellulosic products, it is very important to maintain sustainability in this industry. Therefore, it is necessary to determine the importance of sustainability indicators in cellulose industries, to improve the performance and environmental, social and economic effects of this industry. Because, by determining the importance of sustainability indicators in cellulose industries, it is possible to determine appropriate strategies and policies to improve sustainable performance in this industry and help achieve sustainable development and environmental protection.Therefore, the main goal of this research is to rely on the presented importance of developing a decision-making model that is able to identify the importance of categories (indices) affecting the sustainability of cellulose industries and also calculate the prioritization of sub-factors by analyzing through multi-criteria decision-making techniques. In this research, a combined method using hierarchical analysis and best-worst methods to calculate the weight of categories and Aras prioritization method is used to select the best option and suggest the order of preferred ranking of the options. From the analysis, it has been determined that 11 main categories and three sub-categories affect the sustainability of cellulose industries. According to the results, among the main categories of strategic supplier cooperation with a consolidated weight score of 0.1801, continuous improvement is the least important with a consolidated weight score of 0.0252. Also, among the sub-factors, environmental management with a desirability degree of 1 has the first priority and environmental pressure with a desirability degree of 0.555 has the last priority. In addition, with the introduction of this decision-making framework, the analyzes of previous researchers have been reconstructed, and the framework of alternative rankings has been proposed in a hybrid way.
Keywords: Pioritize, decision making, Consolidated weights, cellulose industries, Sustainability} -
This study first discusses the importance of data collection and sensor placement in engineering. The Value of Information (VoI) method is introduced as a new approach for optimizing sensor placement. The decision-making theories, the VoI method, and its foundations are then explained. The application of this method for optimizing sensor placement is also described. Two case examples in the field of sensor placement in engineering are presented and analyzed. The first case involves determining the load-bearing status of land, the associated risks and costs, and the need to install piles. The second case involves monitoring the creep phenomenon in high-pressure vessels and pipes, where sensor placement is determined using the VoI method based on relevant risks. The results are compared with the UNI 11096 standard for pressure and high-temperature vessels.Keywords: value of information method, optimal placement of sensors, Reliability, Bayesian Theory, Decision Making, optimization}
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Decision making and path planning in case of highly transient dynamics of the surrounding as well as the effect of road condition are the issues that are not completely solved in the previous researches. The goal is to perform a safe and comfortable lane change that includes flexible re-planning capabilities. In this paper, a novel structure for path planning and decision making part of a vehicle automatic lane change has been introduced which comprehensively considers both longitudinal and lateral dynamics of the vehicle. The presented method is able to perform re-planning even in the middle of a lane change maneuver according to new traffic condition. Inclusion of the dynamics of all involved vehicles and providing online performance are the other advantages of the proposed system. The algorithm is simulated and various scenarios are constructed to evaluate the efficiency of the system. The results show that the system has completely acceptable performance.Keywords: Automated driving, Decision making, Lane change (LC), Path planning}
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The work presented in this paper was to investigate whether a new intelligent decision-making system could have provided analysis using data sets and predicted the Buncefield UK catastrophe before it occurred. The new intelligent decision-making system is presented. It incorporates reliability engineering tools with multicriteria decision-making methods and artificial intelligence techniques. An intelligent system that recognises increasing level(s) and draws awareness to the possibility of additional increases before unsafe levels are reached is used to analyse and make critical decisions. The aim was to ensure that the causal factors of failure of the Buncefield UK incidents were predicted, ranked and solutions proffered one at a time to ensure that failures with high priority and high probability of re-occurrence were addressed.Keywords: Decision Making, Artificial intelligence, Buncefield, Storage tank, risk prediction, Catastrophes}
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This paper describes the use of the Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method for predicting the risk of leakage in a storage tank. This is the first time AHP and PROMETHEE have been used in this way. Important decisions about day to day operations are continually made in a petroleum environment. Storage tanks in refineries contain large volumes of flammable and hazardous liquids. Decision processes need to evaluate and select alternatives with a higher probability of resulting in a hazard, among many different alternatives. The new model described in this paper will aid decision-makers to predict which tank is likely to develop a leak and determine what criteria (source of risk) could result in a leak. Although the case study deals with a specific risk prediction problem, the combination of AHP and PROMETHEE methods can be applied to other decision problems.Keywords: AHP, Decision Making, Multi-criteria analysis, PROMETHEE, risk prediction}
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با گسترش روزافزون تصادفات جاده ای و به دنبال آن توسعه سیستم های کمک راننده، اهمیت خودروهای خودران بیش از پیش افزایش یافته است. همزمان با مطرح شدن بحث خودروهای خودران، لزوم توجه به ایمنی این خودروها و تاثیرات سایر خودروهای حاضر در جریان ترافیک بر عملکرد آنها نیز افزایش می یابد. طراحی و کنترل مسیر حرکت با در نظرگرفتن خودروهای اطراف در شرایط ترافیکی دینامیکی ناپایدار در حین مانورهای پیچیده از مهمترین مشکلات پیش روی خودروهای خودران می باشند. علی رغم پژوهش های مختلف در حوزه تعویض خط در شرایط ترافیکی پویا و حتی سرعت های بحرانی، درنظرگرفتن شرایط دینامیکی گذرا در آنها محدود به لحظه شروع مانور بوده و راه حلی برای تغییرات لحظه ای خودروهای اطراف در حین مانور ارایه نشده است. الگوریتم ارایه شده در این مقاله، قادر است با توجه به تصمیمات ناگهانی خودروهای اطراف در حین مانور، مسیرهای ایمن جدید را به صورت بهینه طراحی کند، همچنین اجتناب از برخورد در سراسر مانور را از طریق کنترل همزمان طولی و عرضی خودرو تضمین می کند. پس از ارزیابی عملکرد واحد تصمیم گیری توسط آزمونهای رانندگی واقعی، الگوریتم ارایه شده با سناریوهای مختلف در شرایط پیچیده ترافیکی گذرای دینامیکی با استفاده از نرم افزار متلب شبیه سازی شده و عملکرد مطلوب آن در محیط دینامیکی IPG CarMaker در حضور خودروهای اطراف به اثبات رسیده است.
کلید واژگان: تعویض خط, طراحی مسیر, تصمیم گیری, کنترلر مود لغزان, خودروهای خودران}With the increasing number of road accidents and driver assistance systems development, the automated vehicles importance has increased more than ever. As the issue of automated vehicles comes up, attending to their safety, and the impact of the other vehicles in traffic flow on their performance dramatically increased. One of the most important problems for automated vehicles is designing and controlling the trajectory regarding the surrounding vehicles in transient dynamic traffic conditions during complicated maneuvers. Although various studies have been performed in the field of lane change in dynamic traffic conditions and even in critical high speed, considering the transient dynamic conditions has been limited to the beginning of the maneuver and no solution has been provided for the surrounding vehicles’ immediate changes during the maneuver. The algorithm presented in this paper is able to design new safe optimized trajectories according to the sudden decisions of the surrounding vehicles during the lane change maneuver, also ensures collision avoidance in the whole maneuver via vehicle’s simultaneous longitudinal and lateral control. After evaluating the decision-making unit’s performance by real driving tests, the presented algorithm is simulated with different scenarios in complicated transient dynamic traffic conditions by using MATLAB software and its desired performance has been proven in the dynamic environment of IPG CarMaker, in the presence of surrounding vehicles.
Keywords: Lane change, Path planning, decision making, Sliding mode controller, Automated vehicles} -
As a result of reduction trend in exploration of super-giant carbonate fields and depletion of the proven mature fields categorized as easy oil, development of tight, deep carbonates with more complexities in reservoir rock and fluid behavior have become of interest for exploration and development companies in recent years. New challenges have arisen in development of complex carbonates due to fracture network distribution uncertainty, lateral and vertical fluid behavior heterogeneities, unstable asphaltene content, high H2S and CO2 contents and high salinity formation brine. The complexity elements and problems for downhole sampling have made the full understanding of the reservoir behavior and consequently availability of data for further routine analysis and utilization of simulation model as the main way of data integration limited. Therefore, there is an emerging need to better understand the challenges surrounding production and enhanced oil recovery strategies in these reservoirs for an improved oil recovery decision making system. In this paper, the challenges in production, stimulation and enhanced oil recovery strategies in newly-developed complex carbonates are addressed and analyzed based on the changes to the chemical and mechanical environment. An integrated decision-making workflow based on coupled hydro-mechanical mechanisms in water-based EOR methods is discussed.
Keywords: Enhanced Oil Recovery, carbonate reservoirs, decision-making, Smart Water Injection, Geomechanics} -
Finding a superior evaluation for an irreversible actual heat engine (irreversible Carnot heat engine) can be mentioned as the substantial purpose of this study. To obtain this purpose, the considered criteria are Ecological Coefficient of Performance (ECOP), exergetic performance coefficient thermo-economic, ecological-based thermo-economic, and ecologico-economical functions. These criteria are optimized by implementing NSGA II and thermodynamic analysis. Irreversibilities of the system is considered for the study assessment, consequently, two states are specified in the optimization procedure. The findings associated with every scheme are assessed independently. In the first scenario, maximizing the power output, First law efficiency of the system, and dimensionless ecological-based thermo-economic function ( ) is set as the target. In the second scenario, the three objective functions such as power output ( ), efficiency ( ) and dimensionless ecologico-economical ( ) are simultaneously maximized. To be clear, the coupled of multi-objective evolutionary approaches (MOEAs) and non-dominated sorting genetic algorithm (NSGA-II) approach are presented. The comparison of three prominent approaches such as: LINAMP, TOPSIS, and FUZZY performs in decision making. Ultimately, error analyses of results based on Maximum Absolute Percentage Error are carried out. According to the results, in the first scenario, the appropriate results were the result of the decisions made by TOPSIS and LINAMP, with a deviation index equal to 0.322 from the ideal ratio of this scenario. In the second scenario, the best decision-making results were achieved by the TOPSIS method, with a deviation index equal to 0.104 from the ideal state for this scenario.Keywords: Ecological Coefficient of Performance, ecological-based thermoeconomic function, exergetic performance coefficient thermoeconomic, Optimization, Decision Making}
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The optimal design of a plate-fin recuperator of a 200-kW microturbine was studied in this paper. The exergy efficiency, pressure drop and total cost were selected as the three important objective functions of the recuperator. Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were respectively employed for single-objective and multi-objective optimizations. By optimizing the objective functions via the single-objective optimization approach, the optimum values of exergy efficiency, pressure drop and total cost were found to be 0.966, 0.846 kPa, and 302,075$ respectively, representing the best solutions obtained from 20 iterations in GA. The cases considered for bi-objective optimizations were exergy efficiency-total cost, exergy efficiency-pressure drop and total cost-pressure drop pairs for which Pareto-optimal fronts were obtained, revealing the confliction between the two objectives in each pair. Later, a three-objective optimization was undertaken to simultaneously maximize exergy efficiency while minimizing pressure drop and total cost; the results were presented in a three-dimensional Pareto-optimal front. Moreover, the results of the multi-objective optimizations (i.e. three-objective and bi-objective optimizations) were compared with those of the single-objective one. The comparisons indicated a very good match between the multi-objective and the single-objective optimum values when it came to exergy efficiency and total cost; for pressure drop, however, significant differences were observed. Eventually, a decision-making procedure was employed for the Pareto-fronts of multi-objective optimization to find the final optimal solution.Keywords: Recuperator, Microturbine, Genetic Algorithm, Multi-Objective Optimization, Decision-Making}
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A combined cooling, heating and power (CCHP) system which provides power and heat demands of a five story benchmark residential building was considered. After calculation of power demand, cooling and heating loads, the best alternative for the prime mover and sizing strategy was selected. The selection was made by analytic hierarchy process (AHP). The decision making criteria were the life cycle cost, annual carbon dioxide emission and annual average of efficiencies. Limitations in available equipment and their specific capacities were considered in this research. According to the results, the national motor with the efficiency of 37.60%, sized based on the maximum electrical load, and with the score of 44.4/ 100 found to be the best alternative.Keywords: Combined cooling, heating, power (CCHP), Decision making, National motor (EF7), Fuel cell, Strategy of sizing the prime mover}
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طراحی سیستم های مکانیکی پیچیده معمولا شامل جنبه های متعدد وابسته به هم و همچنین توابع هدف متعارض می باشد که مستلزم تحلیل پیچیده و زمان بری در طول روند طراحی خواهد بود. طراحی بهینه چند جنبه ای یک روش طراحی سیستماتیک برای افزایش کارایی روند طراحی سیستم های مکانیکی پیچیده به ویژه در فضای طراحی غیر همکارانه می باشد. از طرف دیگر، نظریه بازی عبارت است از مجموعه ساختارهای ریاضی که به مطالعه تعاملات بین تصمیم گیرندگان منطقی و هوشمند می پردازد. در این تحقیق با توجه به شباهت و تناظر بین نظریه بازی و طراحی بهینه چند جنبه ای، یک رهیافت جدید مبتنی بر نظریه بازی برای حل مسائل بهینه سازی چند هدفی در فضای غیر همکارانه پیشنهاد و به کار برده می شود. در موقعیت هایی که حل دقیق مجموعه پاسخ منطقی بازیگران امکان پذیر نمی باشد، از برنامه ریزی ژنتیکی برای تخمین مجموعه پاسخ منطقی بازیگران استفاده شده است. علاوه بر این، روند یافتن نقطه یا نقاط تقاطع مجموعه پاسخ منطقی بازیگران در بازی های غیر همکارانه نش، در قالب یک روند کمینه سازی بیان شده است. کارایی چارچوب پیشنهادی با طراحی سه نمونه مطالعاتی در زمینه طراحی بهینه در فضای غیر همکارانه نشان داده شده است. نتایج به دست آمده بیانگر آن است که روش پیشنهادی توانایی تخمین مجموعه پاسخ منطقی بازیگران را داشته و همچنین امکان یافتن نقاط تعادل نش متعدد را زمانی که بیشتر از یک نقطه تعادل نش وجود دارد، فراهم می کند. همچنین روش پیشنهادی در تحقیق حاضر نتایج بهتری را در مقایسه با تحقیقات قبلی ارائه می کند.کلید واژگان: طراحی مکانیکی, بهینه سازی, برنامه ریزی ژنتیکی, نظریه بازی, تصمیم گیری}The design of complex mechanical systems usually involves multiple mutually coupled disciplines and competing objectives which requires complicated and time-consuming interactive analysis during the design process. Multidisciplinary design optimization (MDO) is a systematic design methodology to improve the design efficiency of complex mechanical systems specifically in non-cooperative design environments. In the other hand game theory is set of mathematical constructs that study the interaction between multiple intelligent rational decision makers. In this paper, a new game theoretic approach is proposed and applied for multi-objective MDO problems in non-cooperative design environments, considering the intrinsic similarity between the MDO and game theory. In this way, genetic programming is used as a surrogate to construct the approximate rational reaction sets (RRS) of players. Furthermore, in order to find the intersection of RRS of players in Nash game models, an objective function is proposed which should be minimized. The effectiveness of the proposed framework is demonstrated by the design of three cases study in the field of engineering design optimization in non-cooperative environment. The results show that the presented approach is able to approximate complicated RRS, in addition has the ability to find multiple Nash solutions when the Nash solution is not a singleton and generally found solutions better than those reported in the literature.Keywords: Mechanical design, Optimization, Genetic programming, Game theory, Decision making}
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