توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Impact of Impinging Jets on Moisture Variations of the Iranian Bread
اطلاعات انتشار: شانزدهمین کنفرانس سالانه مهندسی مکانیک، سال
تعداد صفحات: ۶
In this study, bread moisture variation during baking was modeled as a function of baking time, impinging jet velocity and temperature and the bread temperature using Artificial Neural Networks (ANN). An experimental impinging jet oven was developed to acquire the data for training and testing of ANN. An online data–acquisition system was developed for data recording. The baking experiences were carried out at oven temperatures of 150, 175, 200, 225 and 250 C ° and five different jet velocities. 625 series of data were acquired. The network of one hidden layer with 8 neurons was able to predict bread moisture during baking reasonably well. This ANN model predicts the bread moisture with MRE of 6.64% and MAE of 1.23 based on testing data. Conducted experiments showed that variation in oven jet temperature strongly affects
the bread moisture, in comparison with little influence of jet velocity on this parameter.<\div>

۲Development of Air Impingement Technology and Data Acquisition System for Bread Baking Study
اطلاعات انتشار: شانزدهمین کنفرانس سالانه مهندسی مکانیک، سال
تعداد صفحات: ۵
An experimental impinging jet oven with flexiblegeometry and variable jet velocity and temperature wasdeveloped to investigate and optimize the Iranian breadbaking using a novel heating mode: impingement. Thisoven was equipped to online data–acquisition system.The fully transient nature of the baking process makesthe simultaneous measurement of the baking parametersnecessary, which was neglected at previous studies onbread baking in Iran. Thus, the required hardware andsoftware, written by Borland Delphi®, were developedto measure and record the data throughout the bakingexperiences. Weight and temperature of the bread werecontinuously measured through appropriate sensors. Thecapability of the oven control instruments to diminishthe fluctuations of the impinging jet velocity andtemperature resulted in test repeatability and moreexperimental accuracy.<\div>

۳Development of Measurement Methods for the Main Parameters of the Iranian Bread Baking Process in the Impinging Jet Medium
اطلاعات انتشار: یازدهمین کنفرانس دینامیک شاره ها، سال
تعداد صفحات: ۷
In this study, an experimental impinging jet oven equipped with an online data–acquisition system was developed to study and then improve the bread baking throughout the country. The fully transient nature of the baking process makes the simultaneous measurement of the baking parameters necessary, which was neglected at previous studies on bread baking in Iran. Thus, the required hardware and software, written by Borland Delphi®, were developed to measure and record the data throughout the baking experiences. Furthermore, this oven is characterized by the high quality control mechanisms employed. So the fluctuations of oven temperature and jet velocity were constricted down using electronic circuits and controllers leading to an increase in testing repeatability and measurement accuracy. The weight and temperature change of the bread during baking were measured and recorded showing pretty good agreement with previous experimental results.<\div>

۴Assessment of the Effects of Hot Air Jets on Iranian Bread Baking
اطلاعات انتشار: دوازدهمین کنفرانس دینامیک شاره ها، سال
تعداد صفحات: ۱۰
In this study, an experimental impinging jet oven equipped with an online data acquisition system was developed. A software pack was 'Mitten for data acquisition. The baking experiences were carried out at oven temperatures of 150, 175, 200, 225 and 250°C and five different jet velocities. Then, 1025 series of acquired data were employed in Neural network (NN) training and testing process. This NN was able to predict bread moisture and thickness variations as a function of bread temperature, baking time and jet temperature and velocity. The best NN structure, regarding the minimum difference between experimental and NN outputs, consisted of one hidden layer with 12 neurons which predicts bread moisture and thickness variations reasonably good for the period of baking. R2 of NN outputs in comparison with experimental results were obtained 0.969 for moisture and 0.958 for thickness.<\div>

۵Prediction of Temperature and Moisture Variations withinIranian Bread during Baking in an Experimental Impinging JetOven
اطلاعات انتشار: دوازدهمین کنفرانس دینامیک شاره ها، سال
تعداد صفحات: ۹
The baking process is the result of thermal processes like non–enzymatic browning, starch gelatinization and protein denaturation which involve heat and mass transfer inside the bread and to the ambient. In this study, considering both heat and mass transfer simultaneously, the moisture diffusion is modeled separately for liquid water and water vapor as well. The required boundary conditions in numerical modeling were acquired by measuring temperature at top and bottom surfaces of the bread at oven temperatures of 150, 172, 200, 225 and 250 C. The resulted equations were solved using Finite Difference Method (FDM) and solution was compared experimental results of flat bread baking in the experimental impinging jet oven developed by the same authors. The results showed that the moisture content of the bread at top and bottom surfaces of the bread decreases while it increases at internal, so cooler, parts of bread. These variations are in agreement with theory of vaporization–condensation of water inside the porous media. The results of the numerical solution were employed in training of a Neural Network (NN) which predicted the bread temperature with MRE and MAE of 2.06% and 1.82 and moisture content with MRE of 12.47% and 0.017, respectively (Based on testing data).<\div>

۶Modeling of moisture vaiations of the iranian bread during baking
اطلاعات انتشار: هفدهمین کنفرانس سالانه مهندسی مکانیک، سال
تعداد صفحات: ۶
In this study bread moisture variation during baking was modeled as a function of baking time impinging jet velocity and temperature and the bread temerature using artificial neural networks(ANN).<\div>
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