Optimization-based Modeling and Economic Comparison of Membrane Distillation Configurations for Application in Shale Gas Produced Water Treatment

Elmira Mohammadi Shamlou,Radisav Vidic,Vikas Khanna

Desalination（2022）

Cited 10|Views17

Abstract

Membrane distillation (MD) is an emerging membrane technology with great potential for treatment of hypersaline wastewater generated by unconventional (shale) oil and gas reservoirs. However, the low energy efficiency of this technology makes the operating cost of MD systems relatively high, especially in the absence of waste heat. There are several MD configurations with inherent advantages and disadvantages and varying performance. As such, there is a need for thermo-economic optimization of MD systems in a systematic manner to assess their economic performance. We present an optimization framework to model and compare the performance of six MD configurations (DCMD, AGMD, PGMD, CGMD, SGMD, and VMD) in continuous recirculation mode for treatment of hypersaline wastewater. The optimization results show that AGMD with small gap size operated at low stream Reynolds number outperforms all other configurations with treatment cost of 4.57 US $/m3 of feed. However, restricting the system design to more practically relevant operating conditions, such as higher Reynolds number and larger gap size, diminishes the cost superiority of AGMD over other configurations. We also observed that treatment cost using PGMD configuration approaches those of CGMD and DCMD, particularly when modules with small gaps are used.

Translated text

Key words

Membrane distillation,Continuous recirculation,Optimization,Produced water,Desalination

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

【要点】：本文提出了一种基于优化的膜蒸馏配置建模与经济比较方法，用于评估六种不同膜蒸馏配置在连续循环模式下处理页岩气开采废水中的经济性能，并发现特定条件下的膜蒸馏配置可降低处理成本。

【方法】：研究构建了一个优化框架，通过该框架对六种膜蒸馏配置（DCMD、AGMD、PGMD、CGMD、SGMD和VMD）进行了建模与性能比较。

【实验】：通过连续循环模式的模拟实验，使用不同配置处理高盐废水，数据集为实验模拟所得，最终结果显示在低雷诺数下运行的AGMD配置具有最优的处理成本（4.57美元/立方米），但在更实际的操作条件下，AGMD的成本优势减少，PGMD配置的成本则与CGMD和DCMD接近。