WeChat Mini Program
Old Version Features

Performance Analysis of Floating Structures in Solar-Powered Desalination

Energies(2024)SCI 4区

Vallurupalli Nageswara Rao Vignana Jyothi Inst Eng

Cited 4|Views9
Abstract
Solar desalination employs direct sunrays in order to evaporate water vapor and collect the condensed water, making it an effective solution to combat water scarcity. In this experimental study, a solar still with a floating absorber is placed on the water, which acts as a heat absorber and is used to stop the heat conducting to the condensed water present in the still. Stainless steel, with thickness of 0.05 mm and dimensions of 500 mm × 500 mm, is used; this is coated with a Cr-Mn-Fe oxide nanocoating, and a wooden frame is attached to the sheet in order to maintain the balance, allowing the still to float at a constant depth on the water. The experiment is conducted on three different levels of water (3 cm, 4 cm, and 5 cm) using a conventional solar still (CSS) and a modified solar still (MSS) under the same climatic circumstances. The total distillate for depths of 3 cm, 4 cm, and 5 cm are 390 mL, 385 mL, and 385 mL, respectively for the MSS; the depths were 250 mL, 220 mL, and 205 mL, respectively, for the CSS. Upon comparison, the MSS performed better than the CSS by 56% at the 3 cm depth of water, 75% at the 4 cm depth of water, and 87% at the 5 cm depth of water. It was deduced that desalinated water for the MSS was 15.6% more cost-effective than for the CSS, and it was also 81% more cost-effective than packaged drinking water in India.
More
Translated text
Key words
Cr-Mn-Fe oxide,floating absorber,nano-coating,solar desalination,stainless steel
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined