Integration and optimization of pressure retarded osmosis with reverse osmosis for power generation and high efficiency desalination

© 2016 Elsevier Ltd. Salinity gradient power is proposed as a source of renewable energy when two solutions of different salinity are mixed. In particular, Pressure Retarded Osmosis (PRO) coupled with a Reverse Osmosis process (RO) has been previously suggested for power generation, using RO brine as the draw solution. However, integration of PRO with RO may have further value for increasing the extent of water recovery in a desalination process. Consequently, this study was designed to model the impact of various system parameters to better understand how to design and operate practical PRO-RO units. The impact of feed salinity and recovery rate for the RO process on the concentration of draw solution, feed pressure, and membrane area of the PRO process was evaluated. The PRO system was designed to operate at maximum power density of δP=δπ2. Model results showed that the PRO power density generated intensified with increasing seawater salinity and RO recovery rate. For an RO process operating at 52% recovery rate and 35 g/L feed salinity, a maximum power density of 24 W/m2 was achieved using 4.5 M NaCl draw solution. When seawater salinity increased to 45 g/L and the RO recovery rate was 46%, the PRO power density increased to 28 W/m2 using 5 M NaCl draw solution. The PRO system was able to increase the recovery rate of the RO by up to 18% depending on seawater salinity and RO recovery rate. This result suggested a potential advantage of coupling PRO process with RO system to increase the recovery rate of the desalination process and reduce brine discharge

INDOOR PHOTOGRAMMETRY USING UAVS WITH PROTECTIVE STRUCTURES: ISSUES AND PRECISION TESTS

Abstract. Management of disaster scenarios requires applying emergency procedures ensuring maximum safety and protection for field operators. Actual conditions of disaster sites are labelled as "Triple-D: Dull, Dusty, Dangerous" areas. It is well known that in this kind of areas and situations remote surveying systems are at their very best effective, and among these UAVs currently are an effective and performing field tool. Indoor spaces are a particularly complex scenario for this kind of surveys. In this case, technological advances currently offer micro-UAV systems, featuring 360° protective cages, which are able to collect video streams while flying in very tight spaces. Such cases require manual control of the vehicle, with the operator piloting the aircraft without prior knowledge of the status quo of the survey object and therefore without prior planning of flight paths. A possible benefit in terms of knowledge of the survey object could lay in the creation of a 3D model based on images extracted by video streams; to date, widely tested methods and techniques are available for processing UAV-borne video streams to obtain such models. Anyway, the protective cage and the need to use, in these operating conditions, wide-angle lenses presents some issues linked to ever-changing image framing, due to the presence of the cage wires on the field of view. The present work focused on this issue. Using this type of UAVs, video streams have been collected in different environments, both indoors and outdoors, testing several procedures for photogrammetric processing in order to assess the ability to create 3D models. These have been tested for reliability based on data collection conditions, also assessing the level of automation and speed attainable in post-processing. The present paper describes the different tests carried out and the related results.</p

Evaluation the potential and energy efficiency of dual stage pressure retarded osmosis process

© 2017 Power generation by means of Pressure Retarded Osmosis (PRO) has been proposed for harvesting the energy of a salinity gradient. Energy recovery by the PRO process decreases along the membrane module due to depleting of the chemical potential across the membrane and concentration polarization effects. A dual stage PRO (DSPRO) design can be used to rejuvenate the chemical potential difference and reduce the concentration polarization on feed solution. Several design configurations were suggested for the membrane module arrangements in the first and second stage of the PRO process. PRO performance was evaluated for a number of salinity gradients proposed by coupling Dead Sea water or Reverse Osmosis (RO) brine with seawater or wastewater effluent. Maximum specific energy of inlet and outlet feeds was calculated using a developed computer model to identify the amount of recovered and remaining energy. Initially, specific power generation by the PRO process increased by increasing the number of modules of the first stage. Maximum specific energy is calculated along the PRO module to understand the degradation of the maximum specific energy in each module before introducing a second stage PRO process. Adding a second stage PRO process resulted in a sharp increase of the chemical potential difference and the specific energy yield of the process. Between 10% and 13% increase of the specific power generation was achieved by the DSPRO process for the Dead Sea-seawater salinity gradient depending on the dual stage design configuration. For Dead Sea-RO brine, 12–16% increase of the specific power generation was achieved by the dual stage PRO process. For Dead Sea-wastewater and RO brine-wastewater, a neutral and sometimes negative impact occurred when a second stage PRO process was introduced. We concluded that, for a given draw solution concentration, dual stage performs better than the conventional PRO process at high feed salinities, yet requires lower hydraulic pressure

Forward osmosis process for supply of fertilizer solutions from seawater using a mixture of draw solutions

© 2016 Balaban Desalination Publications. All rights reserved. Novel desalination approaches are required to provide both drinking and agricultural water as there is ever increasing stress upon precious freshwater resources. It was our hypothesis that a modified Forward Osmosis (FO) process had the potential for production of irrigation water comprising of appropriate concentrations of fertilizers from a seawater feed. Four agents, KNO3, Na2SO4, CaNO3, and MgCl2, plus 35 g/L seawater were used as the draw and feed solutions of the FO process. Net Driving Pressure in the FO process was manipulated either by increasing the concentration of draw solution (FO process) or by increasing feed pressure (Pressure Assisted FO (PAFO) process). A series of nanofiltration (NF) and reverse osmosis (RO) membranes were used for the regeneration of draw solution. The results suggested that a PAFO process was more energy efficient than simple FO, provided the energy relating to the brine flow from the NF/RO membrane for pressurizing the feed solution of PAFO process was used. Furthermore, this study suggested using a mixture of a primary draw solution, MgCl2, and a secondary draw solution, KNO3, for NO3 supply into the irrigation water was preferable. As such, MgCl2 provided the driving force for fresh water extraction while KNO3 was the source of fertilizer in the irrigation water. Results showed that water quality provided by application of a MgCl2 + KNO3 draw solution was better than that from KNO3 or Ca(NO3)2. The concentrations of NO3 and SO4 in irrigation water were within recommended levels when the diluted draw solution was regenerated by a dual stage low-pressure RO process

ACCURACY ASSESSMENT IN STRUCTURE FROM MOTION 3D RECONSTRUCTION FROM UAV-BORN IMAGES: THE INFLUENCE OF THE DATA PROCESSING METHODS

The evolution of Structure from Motion (SfM) techniques and their integration with the established procedures of classic stereoscopic photogrammetric survey have provided a very effective tool for the production of three-dimensional textured models. Such models are not only aesthetically pleasing but can also contain metric information, the quality of which depends on both survey type and applied processing methodologies. An open research topic in this area refers to checking attainable accuracy levels. The knowledge of such accuracy is essential, especially in the integration of models obtained through SfM with other models derived from different sensors or methods (laser scanning, classic photogrammetry ...). Accuracy checks may be conducted by either comparing SfM models against a reference one or measuring the deviation of control points identified on models and measured with classic topographic instrumentation and methodologies. This paper presents an analysis of attainable accuracy levels, according to different approaches of survey and data processing. For this purpose, a survey of the Church of San Miniato in Marcianella (Pisa, Italy), has been used. The dataset is an integration of laser scanning with terrestrial and UAV-borne photogrammetric surveys; in addition, a high precision topographic network was established for the specific purpose. In particular, laser scanning has been used for the interior and the exterior of the church, with the exclusion of the roof, while UAVs have been used for the photogrammetric survey of both roof, with horizontal strips, and façade, with vertical strips

Impact of membrane orientation on the energy efficiency of dual stage pressure retarded osmosis

© 2018 Elsevier Ltd The performance of Dual Stage Pressure Retarded Osmosis (DSPRO) was analyzed using a developed computer model. DSPRO process was evaluated on Pressure Retarded Osmosis (PRO) and Forward Osmosis (FO) operating modes for different sodium chloride (NaCl) draw and feed concentrations. Simulation results revealed that the total power generation in the DSPRO process operating on the PRO mode was 2.5–5 times more than that operating on the FO mode. For DSPRO operating on the PRO mode, the higher power generation was in the case of 2 M NaCl-fresh and 32% the contribution of the second stage to the total power generation in the DSPRO. To the contrast, he total power generated in the DSPRO operating on the FO mode was in the following order 5M-0.6M > 5M-0.7M > 2M-0.01 > 2M-0.6 M. Interestingly, single stage process operating on the FO mode performed better than DSPRO process due to the severe concentration polarization effects. The results also showed that power density of the DSPRO reached a maximum amount at a hydraulic pressure less than the average osmotic pressure gradient, Δπ/2, due to the variation of optimum operating pressure of each stage. Moreover, results showed that the effective specific energy in the PRO process was lower than the maximum specific energy. However, the effective specific energy of the DSPRO was larger than that of the single stage PRO due to the rejuvenation of the salinity gradient, emphasizing the high potential of the DSPRO process for power generation

Single and dual stage closed-loop pressure retarded osmosis for power generation: Feasibility and performance

© 2017 Elsevier Ltd This work proposes an analysis of conventional (single stage) and dual stage Closed-Loop Pressure Retarded Osmosis (CLPRO) for power generation from a salinity gradient resource. Model calculations were performed taking into account the influence of operating parameters such as the draw solution concentration, membrane area, and draw solution pressure on the performance of the CLPRO process. Modeling results showed that the dual stage CLPRO process outperformed the conventional CLPRO process and power generation increased 18% by adding a second stage of PRO membrane. Multi-Effect Distillation (MED) was selected for the regeneration of the draw solution taking advantage of an available source of waste heat energy. The performance of MED process has been assessed by investigating two key parameters: the specific thermal consumption and the specific heat transfer area. The model calculations showed that the power generation by the single and dual stage CLPRO was higher than the electrical power consumption by the MED plant. In the case of the power generation obtained by the dual stage CLPRO, it was 95% higher than the electrical power consumption by the MED plant, proving the possibility of using low-grade heat for producing electricity from a salinity gradient resource

Deep Neural Networks for Document Processing of Music Score Images

[EN] There is an increasing interest in the automatic digitization of medieval music documents. Despite efforts in this field, the detection of the different layers of information on these documents still poses difficulties. The use of Deep Neural Networks techniques has reported outstanding results in many areas related to computer vision. Consequently, in this paper, we study the so-called Convolutional Neural Networks (CNN) for performing the automatic document processing of music score images. This process is focused on layering the image into its constituent parts (namely, background, staff lines, music notes, and text) by training a classifier with examples of these parts. A comprehensive experimentation in terms of the configuration of the networks was carried out, which illustrates interesting results as regards to both the efficiency and effectiveness of these models. In addition, a cross-manuscript adaptation experiment was presented in which the networks are evaluated on a different manuscript from the one they were trained. The results suggest that the CNN is capable of adapting its knowledge, and so starting from a pre-trained CNN reduces (or eliminates) the need for new labeled data.This work was supported by the Social Sciences and Humanities Research Council of Canada, and Universidad de Alicante through grant GRE-16-04.Calvo-Zaragoza, J.; Castellanos, F.; Vigliensoni, G.; Fujinaga, I. (2018). Deep Neural Networks for Document Processing of Music Score Images. Applied Sciences. 8(5). https://doi.org/10.3390/app8050654S85Bainbridge, D., & Bell, T. (2001). Computers and the Humanities, 35(2), 95-121. doi:10.1023/a:1002485918032Byrd, D., & Simonsen, J. G. (2015). Towards a Standard Testbed for Optical Music Recognition: Definitions, Metrics, and Page Images. Journal of New Music Research, 44(3), 169-195. doi:10.1080/09298215.2015.1045424LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444. doi:10.1038/nature14539Rebelo, A., Fujinaga, I., Paszkiewicz, F., Marcal, A. R. S., Guedes, C., & Cardoso, J. S. (2012). Optical music recognition: state-of-the-art and open issues. International Journal of Multimedia Information Retrieval, 1(3), 173-190. doi:10.1007/s13735-012-0004-6Louloudis, G., Gatos, B., Pratikakis, I., & Halatsis, C. (2008). Text line detection in handwritten documents. Pattern Recognition, 41(12), 3758-3772. doi:10.1016/j.patcog.2008.05.011Montagner, I. S., Hirata, N. S. T., & Hirata, R. (2017). Staff removal using image operator learning. Pattern Recognition, 63, 310-320. doi:10.1016/j.patcog.2016.10.002Calvo-Zaragoza, J., Micó, L., & Oncina, J. (2016). Music staff removal with supervised pixel classification. International Journal on Document Analysis and Recognition (IJDAR), 19(3), 211-219. doi:10.1007/s10032-016-0266-2Calvo-Zaragoza, J., Pertusa, A., & Oncina, J. (2017). Staff-line detection and removal using a convolutional neural network. Machine Vision and Applications, 28(5-6), 665-674. doi:10.1007/s00138-017-0844-4Shelhamer, E., Long, J., & Darrell, T. (2017). Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4), 640-651. doi:10.1109/tpami.2016.2572683Kato, Z. (2011). Markov Random Fields in Image Segmentation. Foundations and Trends® in Signal Processing, 5(1-2), 1-155. doi:10.1561/2000000035Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278-2324. doi:10.1109/5.72679

Commercial scale membrane distillation for solar desalination

Abstract Membrane distillation is an attractive technology for solar-powered decentralized desalination that has not yet reached commercial breakthrough on a large scale. The main barriers are energy consumption and cost. Since the latter are mostly related to the former, thermal energy efficiency is key to assessing the potential of the different available membrane distillation systems at a commercial scale. As discussed here, existing membrane distillation technologies use mostly flat sheet membranes in plate and frame and spiral-wound modules. Modules based on hollow fibre membranes are also considered, as well as the concept of multi-effect vacuum membrane distillation for improved heat recovery. The heat efficiency of each system is analysed based on available experimental results. Better internal heat recovery and capacity for upscaling are found to be important elements of distinction which make multi-channelled spiral-wound modules working in air-gap configuration stand out currently, with the lowest heat consumption of all large scale modules. Potential for improvement of this and other technologies is also discussed, and an estimation based on the associated costs for solar energy is used for establishing boundary conditions towards the implementation of membrane distillation for solar desalination