بررسی روش‌های طراحی آزمایش و آماری در بهینه‌سازی تولید هیدروژن زیستی با روش تخمیر در تاریکی

نوع مقاله : مقاله مروری

نویسندگان

1 کارشناس پژوهشی سازمان پژوهش های علمی و صنعتی ایران

2 هیات علمی- سازمان پژوهش های علمی و صنعتی ایران

چکیده

هیدروژن زیستی دارای بالاترین محتوای انرژی شناخته‌شده تا به امروزاست که بر اثر احتراق آن بخار آب تولید میشود و در تبدیل به الکتریسیته در پیل سوختی‌ بازده زیادی دارد؛ در نتیجه منبع منتخب انرژی پایدار در آینده به ‌شمار می‌رود. تولید هیدروژن زیستی با روش تخمیر در تاریکینسبت به روش­های فتوسنتزی برتری‌هایی مانند بینیازی از نور، قابلیت مصرف پیش‌ماده‌های متنوع ازجمله قندهای 5 و 6 کربنه و برخی از پساب‌ها و پس‌ماندهای تبدیلی با آهنگ و بازدهی زیادتری دارد. تولید هیدروژن تخمیری فرایندی پیچیده و متأثر از چندین عامل است که با روش آماری میتوان تأثیر اندرکنش­ها را به روش بهتری درک کرد. یکی از روش‌های افزایش آهنگ و بازدهی فرایند، بهینه‌سازی تأثیر عوامل انتخابی مانند دما، pH ، نوع و غلظت پیش‌ماده، تلقیح و عوامل دیگر است که تأثیرمؤثر بر پاسخ دارند و می‌توان با به‌کارگیری روش‌های آماری به آن دست یافت. برای غربالگری و رگراسیون از روش ANOVA استفاده شده است.در میان روش‌های آماری گوناگون، طراحی‌ها مانند تکعاملی، چندعاملی، تاگوچی، پلاکت- برمن، مرکب مرکزی، باکس-بن­کن، روش تندترین­صعود/ نزول و شبکۀ عصبی­مصنوعی (ANN) و الگوریتم ژنتیک و رویۀ پاسخ سطح (RSM) در تولید هیدروژن تخمیری استفاده میشود. مقالۀ گردآوری حاضر بعضی از برتری‌ها و کاستی‌ها و تجزیه‌­و­تحلیل روشهای طراحی آزمایش و آماری را پوشش میدهد. انتخاب روش صحیح غربالگری، طراحی آزمایش و روش آماری باعث درک بیشتر اندرکنش­ها میشود و این دانش عمیق در کاهش تعداد آزمایش­ها، هزینه­ها، افزایش بازدهی و بهینهسازی فرایند تولید هیدروژن زیستی تخمیردر تاریکیمفید است.

کلیدواژه‌ها


عنوان مقاله [English]

Verification of Experimental Design and Statistical Methods for Optimization of Dark Hydrogen Production

نویسندگان [English]

  • Z. Esfahani Bolandbalaei 1
  • Kh. Rostami 2
1 Iranian Research Organization for Science and Technology
2 Iranian Research Organization for Science and Technology
چکیده [English]

Hydrogen has high energy content known to date, which produces water vapor due to combustion and is converted to electricity by fuel cells with high efficiency, therefore is considered as a candidate of future energy source. Production of bio- hydrogen through dark fermentation can ferment sustainable renewable substances such as C5 and C6, wastewater and converted waste, compared to photosynthetic methods requires no light, has higher production rate and yields. Fermentative hydrogen production is a complex process and is influenced by several factors, statistical methods of optimization offer relatively understandable interaction among the factors. One of the approach to increase the rate and yield of reaction is to screen, model, and optimize factors which have strong influence on the response comprising inucolum, operating temperature, pH, type and concentration of substrates etc by employing appropriate method. For screening factors and performing regression ANOVA is used. The experimental design method used for screening and understanding the effect of factors are
one-factor-at-a-time, full factorial, fractional factorial, Taguchi, Plackett–Burman,central composite and
Box–Behnken design, steepest inclined or declined, neural network ANN, genetic algorithms and, for optimization response surface methodology is frequently applied. The overview, presents appropriate advantages and disadvantages of analyzing abilities of modeling of experiments and addresses few statistical methods of optimization to understand complex effect of factors on fermentative dark hydrogen production. Such deep knowldge leads in understanding more in details the interactions of complex reactions involved and to select sound statistical method of optimization, resulting in reasonable reduced number of experiments to achieve higher rate and yield of production at lower cost of operation.

کلیدواژه‌ها [English]

  • Biohydrogen Production by Dark Fermentation
  • Design of Experiments
  • Plackett–Burman Design
  • Response Surface Methodology
  • Neural Network
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