AN EXPERIMENTAL TECHNIQUE FOR MEASURING LOCAL SOLAR IRRADIATION WITH A MODEL SPACECRAFT

Author(s):  
Richard P. Bobco
Author(s):  
Z.L. Wang

An experimental technique for performing electron holography using a non-FEG, non-biprism transmission electron microscope (TEM) has been introduced by Ru et al. A double stacked specimens, one being a single crystal foil and the other the specimen, are loaded in the normal specimen position in TEM. The single crystal, which is placed onto the specimen, is responsible to produce two beams that are equivalent to two virtual coherent sources illuminating the specimen beneath, thus, permitting electron holography of the specimen. In this paper, the imaging theory of this technique is described. Procedures are introduced for digitally reconstructing the holograms.


2019 ◽  
Vol 17 (3) ◽  
Author(s):  
Lamhot P. Manalu

Crop drying is essential for preservation in agricultural applications. It is performed either using fossil fuels in an artificial mechanical drying process or by placing the crop under the open sun. The first method is costly and has a negative impact on the environment, while the second method is totally dependent on the weather. The drying process requires a lot of energy in relation to the amount of water that must be evaporated from the product. It is estimated that 12% of the total energy used by the food industries and agriculture absorbed in this process. Due to the limitation of energy resources, it is important to keep researching and developing of diversification and optimization of energy This study aims to assess the use of energy for cocoa drying using solar energy dryer and bin-type dryer, as well as to determine the drying efficiency of each type of dryer. The results showed that the efficiency of the solar dryer drying system ranges between 36% to 46%, while the tub-type dryers between 21.7% to 33.1%. The specific energy of solar dryer ranged from 6.17-7.87 MJ / kg, while the tub-type dryers 8.58-13.63 MJ / kg. Dryer efficiency is influenced by the level of solar irradiation and the amount of drying load, the higher the irradiation received and more cocoa beans are dried, the drying efficiency is also higher and the specific energy further down.Proses pengeringan memerlukan banyak energi sehubungan dengan banyaknya air yang harus diuapkan dari bahan yang dikeringkan. Pengeringan dapat dilakukan dengan menggunakan pengering mekanis berbahan bakar fosil atau dengan menempatkan produk di bawah matahari terbuka. Metode pertama adalah mahal dan memiliki dampak negatif pada lingkungan, sedangkan metode kedua sangat tergantung pada cuaca. Diperkirakan bahwa 12% dari total energi yang dipergunakan oleh industri pangan dan pertanian diserap untuk proses ini. Mengingat semakin terbatasnya sumber energi bahan bakar minyak maka usaha diversifikasi dan optimasi energi untuk pengeringan perlu terus diteliti dan dikembangkan. Salah satunya adalah pemanfaatan energi surya sebagai sumber energi terbarukan. Penelitian ini bertujuan untuk mengkaji penggunaan energi untuk pengeringan kakao dengan memakai pengering energi surya dan pengering tipe bak, serta untuk mengetahui efisiensi pengeringan dari masing-masing tipe pengering. Hasil kajian menunjukkan bahwa efisiensi total sistem pengeringan alat pengering surya berkisar antara 36% dan 46%, sedangkan pengering tipe bak antara 21.7% dan 33.1%. Kebutuhan energi spesifik alat pengering surya berkisar antara 6.17-7.87 MJ/kg, sedangkan alat pengering tipe bak 8.58-13.63 MJ/kg. Efisiensi alat pengering dipengaruhi oleh tingkat iradiasi surya dan jumlah beban pengeringan, semakin tinggi iradiasi yang diterima pengering serta semakin banyak biji kakao yang dikeringkan, maka efisiensi pengeringan juga semakin tinggi dan kebutuhan energi spesifik semakin turun.Keywords: energy, efficiency, cocoa, solar dryer, bin-type dryer.


Author(s):  
Edy Saputra

Statements of fact and opinion in the articles in the Journal of Applied Materials and Technology are those of the respective authors and contributors and not of Journal of Applied Materials and Technology or the institution of Applied Materials and Technology Society and Faculty of Engineering, Universitas Riau. Neither Applied Materials and Technology Society and Faculty of Engineering, Universitas Riau nor Journal of Applied Materials and Technology make any representation, express or implied, in respect of the accuracy of the material in this journal and cannot accept any legal responsibility or liability for any errors or omissions that may be made by the reader should make her or his own evaluation as to the appropriateness or otherwise of any experimental technique described.


Jurnal MIPA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 181
Author(s):  
Imriani Moroki ◽  
Alfrets Septy Wauran

Energi terbarukan adalah salah satu masalah energi paling terkenal saat ini. Ada beberapa sumber potensial energi terbarukan. Salah satu energi terbarukan yang umum dan sederhana adalah energi matahari. Masalah besar ketersediaan energi saat ini adalah terbatasnya sumber energi konvensional seperti bahan bakar. Ini semua sumber energi memiliki banyak masalah karena memiliki jumlah energi yang terbatas. Penting untuk membuat model dan analisis berdasarkan ketersediaan sumber energi. Energi matahari adalah energi terbarukan yang paling disukai di negara-negara khatulistiwa saat ini. Tergantung pada produksi energi surya di daerah tertentu untuk memiliki desain dan analisis energi matahari yang baik. Untuk memiliki analisis yang baik tentang itu, dalam makalah ini kami membuat model prediksi energi surya berdasarkan data iradiasi matahari. Kami membuat model energi surya dan angin dengan menggunakan Metode Autoregresif Integrated Moving Average (ARIMA). Model ini diimplementasikan oleh R Studio yang kuat dari statistik. Sebagai hasil akhir, kami mendapatkan model statistik solar yang dibandingkan dengan data aktualRenewable energy is one of the most fomous issues of energy today. There are some renewable energy potential sources. One of the common n simple renewable energy is solar energy. The big problem of the availability of energy today is the limeted sources of conventional enery like fuel. This all energy sources have a lot of problem because it has a limited number of energy. It is important to make a model and analysis based on the availability of the energy sources. Solar energy is the most prefered renewable energy in equator countries today. It depends on the production of solar energy in certain area to have a good design and analysis of  the solar energy. To have a good analysis of it, in this paper we make a prediction model of solar energy based on the data of solar irradiation. We make the solar and wind enery model by using Autoregresif Integrated Moving Average (ARIMA) Method. This model is implemented by R Studio that is a powerfull of statistical. As the final result, we got the statistical model of solar comparing with the actual data


Author(s):  
Lahcen El Mentaly ◽  
Abdellah Amghar ◽  
Hassan Sahsah

Background: The solar field on our planet is inexhaustible, which favors the use of photovoltaic electricity which generates no nuisance: no greenhouse gases, no waste. Methods: It is a high value-added energy that is produced directly at the place of consumption through photovoltaic (PV) solar panels. Notwithstanding these advantages, the maximum power depends strongly on solar irradiation and temperature, which means that a Maximum Power Point Tracking (MPPT) controller must be inserted between the PV panel and the load in order to follow the Maximum Power Point (MPP) continuously and in real time. In this work, MPP’s behavior was simulated at different temperatures and solar irradiations using seven techniques which identify the MPP by different methods. Results: The novelty of this work is that the seven MPPT methods were compared according to a very selective criterion which is the MPPT efficiency as well as a purely digital duty cycle control without using the PI controller. The simulation under the PSIM software shows that the FLC, TP, FSCC, TG, HC and IC methods have almost the same efficiency of 99%, whereas the FOCV method had a low efficiency of 96%. Conclusion: This makes it possible to conclude that the best methods are FLC, HC and IC because they use fewer sensors compared to the rest.


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