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Search Results (1,787)

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20 pages, 27208 KiB  
Article
Optimization of Organic Rankine Cycle for Hot Dry Rock Power System: A Stackelberg Game Approach
by Zhehao Hu, Wenbin Wu and Yang Si
Energies 2024, 17(20), 5151; https://doi.org/10.3390/en17205151 - 16 Oct 2024
Viewed by 250
Abstract
Due to its simple structure and stable operation, the Organic Rankine Cycle (ORC) has gained significant attention as a primary solution for low-grade thermal power generation. However, the economic challenges associated with development difficulties in hot dry rock (HDR) geothermal power systems have [...] Read more.
Due to its simple structure and stable operation, the Organic Rankine Cycle (ORC) has gained significant attention as a primary solution for low-grade thermal power generation. However, the economic challenges associated with development difficulties in hot dry rock (HDR) geothermal power systems have necessitated a better balance between performance and cost effectiveness within ORC systems. This paper establishes a game pattern of the Organic Rankine Cycle with performance as the master layer and economy as the slave layer, based on the Stackelberg game theory. The optimal working fluid for the ORC is identified as R600. At the R600 mass flow rate of 50 kg/s, the net system cycle work is 4186 kW, the generation efficiency is 14.52%, and the levelized cost of energy is 0.0176 USD/kWh. The research establishes an optimization method for the Organic Rankine Cycle based on the Stackelberg game framework, where the network of the system is the primary optimization objective, and the heat transfer areas of the evaporator and condenser serve as the secondary optimization objective. An iterative solving method is utilized to achieve equilibrium between the performance and economy of the ORC system. The proposed method is validated through a case study utilizing hot dry rock data from Qinghai Gonghe, allowing for a thorough analysis of the working fluid and system parameters. The findings indicate that the proposed approach effectively balances ORC performance with economic considerations, thereby enhancing the overall revenue of the HDR power system. Full article
(This article belongs to the Special Issue Big Data Analysis and Application in Power System)
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Figure 1
<p>ORC system flowchart.</p>
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<p>Schematic diagram of Stackelberg game pattern for ORC system optimization.</p>
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<p>Shell and tube heat exchanger geometry.</p>
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<p>Schematic diagram of heat exchange process of evaporator.</p>
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<p>Schematic diagram of tube bundle arrangement.</p>
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<p>Schematic diagram of condenser heat exchange process.</p>
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<p>ORC system optimization Stackelberg game approach.</p>
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<p>Optimal network of organic working fluids.</p>
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<p>Minimum heat transfer area per kW for organic working fluids.</p>
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<p>Levelized cost of energy for organic working fluids.</p>
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<p>Relationship between tube bundle arrangement and heat transfer area.</p>
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16 pages, 2751 KiB  
Article
The Impact of Abrupt Sunlight Reduction Scenarios on Renewable Energy Production
by Ashitosh Rajesh Varne, Simon Blouin, Baxter Lorenzo McIntosh Williams and David Denkenberger
Energies 2024, 17(20), 5147; https://doi.org/10.3390/en17205147 - 16 Oct 2024
Viewed by 466
Abstract
To combat global warming, energy systems are transitioning to generation from renewable sources, such as wind and solar, which are sensitive to climate conditions. While their output is expected to be little affected by global warming, wind, and solar electricity generation could be [...] Read more.
To combat global warming, energy systems are transitioning to generation from renewable sources, such as wind and solar, which are sensitive to climate conditions. While their output is expected to be little affected by global warming, wind, and solar electricity generation could be affected by more drastic climatic changes, such as abrupt sunlight reduction scenarios (ASRSs) caused by nuclear war (“nuclear winter”) or supervolcanic eruptions (“volcanic winter”). This paper assesses the impacts of an ASRS on global energy supply and security in a 100% renewable energy scenario. National generation mixes are determined according to roadmaps for a global transition to renewable energy, with wind and solar contributing a combined 94% of the global energy supply. Wind and solar generation are determined for a baseline climate and an ASRS following a large-scale nuclear exchange. While effects vary by country, overall wind and solar generation are expected to reduce by 59% in the first year following an ASRS, requiring over a decade for full recovery. Ensuring sufficient energy for everyone’s critical needs, including water, food, and building heating/cooling, would require international trade, resilient food production, and/or resilient energy sources, such as wood, geothermal, nuclear power, tidal power, and hydropower. Full article
(This article belongs to the Section A: Sustainable Energy)
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Figure 1
<p>Percentage of energy provided by solar photovoltaics for baseline climate in a 100% renewable scenario.</p>
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<p>Global wind and solar production for 12 years after an ASRS caused by a nuclear exchange between NATO and Russia.</p>
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<p>Solar energy generation compared to baseline in the first calendar year after nuclear war.</p>
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<p>Wind energy generation compared to baseline in the first calendar year after nuclear war.</p>
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<p>Wind and solar (overall energy) production compared to baseline in the first calendar year after nuclear war.</p>
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<p>Percentage of the population of each country fed without resilient foods [<a href="#B63-energies-17-05147" class="html-bibr">63</a>]. The dashed line represents current energy requirements for critical needs (20,200 MJ, or 5600 kWh, per year, per capita), and the solid line represents the amount of energy needed to fill the food gap with resilient food production, assuming calories are met by an equal distribution of mushrooms, cellulosic sugar, methane single-cell protein, seaweed, and petroleum fat.</p>
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28 pages, 1353 KiB  
Review
Solar Organic Rankine Cycle (ORC) Systems: A Review of Technologies, Parameters, and Applications
by Dominika Matuszewska
Energies 2024, 17(20), 5106; https://doi.org/10.3390/en17205106 (registering DOI) - 14 Oct 2024
Viewed by 366
Abstract
The Organic Rankine Cycle (ORC) is a widely utilized technology for generating electricity from various sources, including geothermal energy, waste heat, biomass, and solar energy. Harnessing solar radiation to drive ORC is a promising renewable energy technology due to the high compatibility of [...] Read more.
The Organic Rankine Cycle (ORC) is a widely utilized technology for generating electricity from various sources, including geothermal energy, waste heat, biomass, and solar energy. Harnessing solar radiation to drive ORC is a promising renewable energy technology due to the high compatibility of solar collector operating temperatures with the thermal requirements of the cycle. The aim of this review article is to present and discuss the principles of solar-ORC technology and the broad range of solar-ORC systems that have been explored in the literature. Various solar energy technologies capable of powering ORC are investigated, including flat plate collectors, vacuum tube collectors, compound parabolic collectors, and parabolic trough collectors. The review places significant emphasis on the operating parameters of technology. Full article
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<p>Basic ORC system with key component and state-point notations.</p>
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<p>Temperature-specific entropy diagram of an ORC system.</p>
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<p>Temperature–heat diagram for preheater, evaporator, and superheater.</p>
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<p>Some of the wet, isentropic, and dry fluids using in ORCs.</p>
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<p>Temperature ranges typical for different solar thermal collectors [<a href="#B54-energies-17-05106" class="html-bibr">54</a>].</p>
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<p>Schematic layout of a direct solar-ORC system.</p>
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<p>Schematic layout of indirect solar-ORC system.</p>
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26 pages, 5090 KiB  
Article
Analysis and Optimization of a s-CO2 Cycle Coupled to Solar, Biomass, and Geothermal Energy Technologies
by Orlando Anaya-Reyes, Iván Salgado-Transito, David Aarón Rodríguez-Alejandro, Alejandro Zaleta-Aguilar, Carlos Benito Martínez-Pérez and Sergio Cano-Andrade
Energies 2024, 17(20), 5077; https://doi.org/10.3390/en17205077 - 12 Oct 2024
Viewed by 330
Abstract
This paper presents an analysis and optimization of a polygeneration power-production system that integrates a concentrating solar tower, a supercritical CO2 Brayton cycle, a double-flash geothermal Rankine cycle, and an internal combustion engine. The concentrating solar tower is analyzed under the weather [...] Read more.
This paper presents an analysis and optimization of a polygeneration power-production system that integrates a concentrating solar tower, a supercritical CO2 Brayton cycle, a double-flash geothermal Rankine cycle, and an internal combustion engine. The concentrating solar tower is analyzed under the weather conditions of the Mexicali Valley, Mexico, optimizing the incident radiation on the receiver and its size, the tower height, and the number of heliostats and their distribution. The integrated polygeneration system is studied by first and second law analyses, and its optimization is also developed. Results show that the optimal parameters for the solar field are a solar flux of 549.2 kW/m2, a height tower of 73.71 m, an external receiver of 1.86 m height with a 6.91 m diameter, and a total of 1116 heliostats of 6 m × 6 m. For the integrated polygeneration system, the optimal values of the variables considered are 1437 kPa and 351.2 kPa for the separation pressures of both flash chambers, 753 °C for the gasification temperature, 741.1 °C for the inlet temperature to the turbine, 2.5 and 1.503 for the turbine pressure ratios, 0.5964 for the air–biomass equivalence ratio, and 0.5881 for the CO2 mass flow splitting fraction. Finally, for the optimal system, the thermal efficiency is 38.8%, and the exergetic efficiency is 30.9%. Full article
(This article belongs to the Section B2: Clean Energy)
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<p>Schematic diagram of the integrated polygeneration power system under study.</p>
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<p>DNI observed in the Mexicali Valley, Mexico [<a href="#B36-energies-17-05077" class="html-bibr">36</a>].</p>
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<p>Cosine efficiency of the heliostat field.</p>
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<p>Optical efficiency of the heliostat field.</p>
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<p>Solar flux profile at the receiver.</p>
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<p>Effect of the gasification temperature on the syngas LHV and production rate m<sup>3</sup> of syngas/kg of biomass.</p>
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<p>Effect of the gasification temperature on the first and second law efficiencies of the gasification system.</p>
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<p>Effect of <math display="inline"><semantics> <mi>ξ</mi> </semantics></math> on the syngas LHV and production rate of the gasification system.</p>
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<p>Effect of <math display="inline"><semantics> <mi>ξ</mi> </semantics></math> on the energetic and exergetic efficiencies of the gasification system.</p>
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<p>Effect of <math display="inline"><semantics> <msub> <mi>T</mi> <mi>GTI</mi> </msub> </semantics></math> on the energetic and exergetic efficiencies of the Brayton cycle.</p>
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<p>Effect of <math display="inline"><semantics> <mi>γ</mi> </semantics></math> on the energetic and exergetic efficiencies of the Brayton cycle.</p>
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<p>Effect of <math display="inline"><semantics> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> </semantics></math> on the energetic and exergetic efficiencies of the Brayton cycle.</p>
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<p>Effect of <math display="inline"><semantics> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> </semantics></math> on the energetic and exergetic efficiencies of the Brayton cycle.</p>
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<p>Effect of <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mrow> <mi>sep</mi> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> on the energetic and exergetic efficiencies of the Rankine cycle.</p>
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<p>Effect of <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mrow> <mi>sep</mi> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> on the energetic and exergetic efficiencies of the Rankine cycle.</p>
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<p>Percentage of exergy destruction rates by component.</p>
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44 pages, 4346 KiB  
Review
Cleaning Up Metal Contamination after Decades of Energy Production and Manufacturing: Reviewing the Value in Use of Biochars for a Sustainable Future
by Priyanka, Isobel E. Wood, Amthal Al-Gailani, Ben W. Kolosz, Kin Wai Cheah, Devika Vashisht, Surinder K. Mehta and Martin J. Taylor
Sustainability 2024, 16(20), 8838; https://doi.org/10.3390/su16208838 - 12 Oct 2024
Viewed by 606
Abstract
The lasting impact of ancestral energy production operations and global manufacturing has not only generated substantial CO2 emissions, but it has also led to the release of metal-based pollutants into Earth’s water bodies. As we continue to engineer, mine (coal and metals), [...] Read more.
The lasting impact of ancestral energy production operations and global manufacturing has not only generated substantial CO2 emissions, but it has also led to the release of metal-based pollutants into Earth’s water bodies. As we continue to engineer, mine (coal and metals), and now bore into geothermal wells/fracking sites for alternative energy sources, we continue to contaminate drinking water supplies with heavy metals through infiltration and diffusion, limiting progress towards achieving Sustainable Development Goals 3 (Sustainable Development Goal 3: Good health and well-being), 6 (Sustainable Development Goal 6: Clean water and sanitation), 14 (Sustainable Development Goal 14: Life below water), and 15 (Sustainable Development Goal 15: Life on land). This review shows how the research community has designed and developed mesoporous biochars with customizable pore systems, as well as functionalized biochars, to extract various heavy metals from water sources. This article investigates how biochar materials (non-activated, activated, functionalized, or hybrid structures) can be adapted to suit their purpose, highlighting their recyclability/regeneration and performance when remediating metal-based pollution in place of conventional activated carbons. By utilizing the wider circular economy, “waste-derived” carbonaceous materials will play a pivotal role in water purification for both the developed/developing world, where mining and heavy manufacturing generate the most substantial contribution to water pollution. This review encompasses a wide range of global activities that generate increased heavy metal contamination to water supplies, as well as elucidates emerging technologies that can augment environmental remediation activities, improving the quality of life and standard of living for all. Full article
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<p>The structure of the core organic components in lignocellulosic biomass includes lignin, represented as three different hydroxycinnamyl alcohols (blue box): (<b>A</b>) coniferyl alcohol, (<b>B</b>) paracoumaryl alcohol, and (<b>C</b>) sinapyl alcohol. Hemicellulose (green box) represented as (<b>D</b>) xylose, a monomer found in xylan, and cellulose (orange box) depicted as (<b>E</b>) a cellulose polymer and (<b>F</b>) an individual glucose monomer. Adapted from [<a href="#B56-sustainability-16-08838" class="html-bibr">56</a>,<a href="#B57-sustainability-16-08838" class="html-bibr">57</a>,<a href="#B58-sustainability-16-08838" class="html-bibr">58</a>].</p>
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<p>The primary uses of geothermal fluids.</p>
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<p>Diagram representing the process of fracking, adapted from [<a href="#B128-sustainability-16-08838" class="html-bibr">128</a>,<a href="#B129-sustainability-16-08838" class="html-bibr">129</a>].</p>
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<p>The mechanism for the pollutant adsorption onto biochar adapted from [<a href="#B141-sustainability-16-08838" class="html-bibr">141</a>], biochar image adapted from [<a href="#B142-sustainability-16-08838" class="html-bibr">142</a>].</p>
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<p>Mechanisms of heavy metal microbial bioremediation in a microbial cell (reproduced from [<a href="#B248-sustainability-16-08838" class="html-bibr">248</a>,<a href="#B249-sustainability-16-08838" class="html-bibr">249</a>]).</p>
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21 pages, 6225 KiB  
Article
3D Surface Velocity Field Inferred from SAR Interferometry: Cerro Prieto Step-Over, Mexico, Case Study
by Ignacio F. Garcia-Meza, J. Alejandro González-Ortega, Olga Sarychikhina, Eric J. Fielding and Sergey Samsonov
Remote Sens. 2024, 16(20), 3788; https://doi.org/10.3390/rs16203788 - 12 Oct 2024
Viewed by 814
Abstract
The Cerro Prieto basin, a tectonically active pull-apart basin, hosts significant geothermal resources currently being exploited in the Cerro Prieto Geothermal Field (CPGF). Consequently, natural tectonic processes and anthropogenic activities contribute to three-dimensional surface displacements in this pull-apart basin. Here, we obtained the [...] Read more.
The Cerro Prieto basin, a tectonically active pull-apart basin, hosts significant geothermal resources currently being exploited in the Cerro Prieto Geothermal Field (CPGF). Consequently, natural tectonic processes and anthropogenic activities contribute to three-dimensional surface displacements in this pull-apart basin. Here, we obtained the Cerro Prieto Step-Over 3D surface velocity field (3DSVF) by accomplishing a weighted least square algorithm inversion from geometrically quasi-orthogonal airborne UAVSAR and RADARSAT-2, Sentinel 1A satellite Synthetic Aperture-Radar (SAR) imagery collected from 2012 to 2016. The 3DSVF results show a vertical rate of 150 mm/yr and 40 mm/yr for the horizontal rate, where for the first time, the north component displacement is achieved by using only the Interferometric SAR time series in the CPGF. Data integration and validation between the 3DSVF and ground-based measurements such as continuous GPS time series and precise leveling data were achieved. Correlating the findings with recent geothermal energy production revealed a subsidence rate slowdown that aligns with the CPGF’s annual vapor production. Full article
(This article belongs to the Special Issue Advanced Remote Sensing Technology in Geodesy, Surveying and Mapping)
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<p>Study area. (<b>a</b>) Location of the region described in (<b>b</b>). (<b>b</b>) Red square indicates the CPSO area described in (<b>c</b>). Footprints of Sentinel 1A ascending and descending SAR images are denoted by big squares (black and dark blue), and footprints of UAVSAR east and west passes are denoted by rectangles (gray). Black arrows denote the different sensors’ line of sight direction. Red lines are the main fault systems. (<b>c</b>) Gray contours show the subsidence displacement rate (cm/yr) from leveling measurements (2012–2015) surveyed by the Mexican Institute of Water Technology (IMTA). Recent earthquakes <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">M</mi> </mrow> <mrow> <mi mathvariant="normal">L</mi> </mrow> </msub> </mrow> </semantics></math> &gt; 5 occurred before the study period are denoted by red stars. 1.-<math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">M</mi> </mrow> <mrow> <mi mathvariant="normal">L</mi> </mrow> </msub> </mrow> </semantics></math>5.4, May/2006; 2.-<math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">M</mi> </mrow> <mrow> <mi mathvariant="normal">L</mi> </mrow> </msub> </mrow> </semantics></math>5.3, September/2009; 3.-<math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">M</mi> </mrow> <mrow> <mi mathvariant="normal">L</mi> </mrow> </msub> </mrow> </semantics></math>6.0, December/2009. Main tectonic faults are indicated by continuous red lines. Large-scale tectonic motion is shown by black arrows. The CPGF area is marked as dashed gray lines. Abbreviations NA = North American plate; PA = Pacific plate; EZ = exploitation zone of the CPGF, RZ = recharge zone, CPF = Cerro Prieto Fault, GF = Guerrero Fault, HF = Hidalgo Fault, LF = L Fault, IMF = Imperial Fault, MF = Morelia Fault, SF = Saltillo Fault, SF’ = Saltillo Fault continuation, CPV = Cerro Prieto Volcano. Vector data of the CPGF limits were taken from [<a href="#B19-remotesensing-16-03788" class="html-bibr">19</a>].</p>
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<p>Timeframe of imagery from spaceborne Sentinel 1A/RADARSAT-2 and airborne UAVSAR missions. Abbreviations: SLC = Single Look Complex, T166 = Sentinel ascending orbital pass, T173 = Sentinel descending orbital pass, MF1 = RADARSAT-2 ascending orbital pass, MF4N = RADARSAT-2 descending orbital pass, 08514S3 = Segment #3 of the flight line 08514, 26515S2 = Segment #2 of the flight line 26515. Black dots are the UAVSAR acquisition times. Gray boxes indicate temporal matching between sensors used for 3D decomposition. Dates format: YYYY/MM/DD (e.g., 1 February 2012).</p>
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<p>Method flowchart for InSAR data processing. ECMWF global model is the European Centre for Medium-Range Weather Forecasts. <sup>1</sup> Jackknife test for uncertainty estimations. This workflow was elaborated based on the implemented processing software (<sup>2</sup> and <sup>3</sup>).</p>
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<p>Synthetic data of the components of the 3D displacement vector of the CPGF [<a href="#B17-remotesensing-16-03788" class="html-bibr">17</a>]. (<b>a</b>) Synthetic data. (<b>b</b>) Calculated 3D surface displacement data. In (<b>a</b>,<b>b</b>), colors denote the vertical displacement and red color vectors represent the horizontal displacements (east-north). (<b>c</b>) Differences between synthetic and calculated 3D surface displacement data. (<b>d</b>) Flowchart for 3D inversion code validation by using synthetic data. LOSdisp = Line of Sight displacement, WLSS = Weighted Least Squares Solution.</p>
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<p>Maps of average LOS displacement rate (mm/yr). (<b>a</b>,<b>b</b>) RADARSAT-2 ascending and descending orbital passes, respectively. Stable reference point used in (<b>a</b>,<b>b</b>) is located to the northwest of the Cerro Prieto basin out of the map’s data frame [<a href="#B21-remotesensing-16-03788" class="html-bibr">21</a>]. (<b>c</b>,<b>d</b>) UAVSAR east and west flight segments, respectively. Maps cover 2.8 years. Areas with a coherence value below 0.27 are masked. The red flag in (<b>c</b>,<b>d</b>) shows the location of the reference point. The color palette corresponds to the LOS displacement rate. Black arrows denote the sensors’ line of sight direction. Main faults are denoted by continuous red lines. Abbreviations Ifg = interferogram, LOS = line of sight, CPF = Cerro Prieto Fault, IMF = Imperial Fault, MF = Morelia Fault, SF = Saltillo, SF’ = Saltillo Fault continuation [<a href="#B30-remotesensing-16-03788" class="html-bibr">30</a>], and CPV = Cerro Prieto Volcano.</p>
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<p>Maps of average LOS displacement rate (mm/yr). (<b>a</b>,<b>b</b>) Sentinel 1A ascending and descending orbital passes, respectively. (<b>c</b>,<b>d</b>) UAVSAR east and west flight segments, respectively. Maps (<b>a</b>–<b>d</b>) cover one year. Areas with a coherence value below 0.2 are masked. In (<b>a</b>), the orange squares mark the location of specific points in the exploitation (EZ) and recharge (RZ) zones. The red flag shows the location of the reference point. Notation as in <a href="#remotesensing-16-03788-f005" class="html-fig">Figure 5</a>.</p>
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<p>Maps of displacement vector components, derived from the RADARSAT-2 and UAVSAR datasets’ combination for the February/2012–November/2014 period. (<b>a</b>) Vertical displacement rate. Negative values indicate subsidence. (<b>b</b>) North displacement rate. Negative values indicate southward movement. (<b>c</b>) East displacement rate. Negative values indicate westward movement. Areas of low coherence (&lt;0.27) are masked out. In (<b>a</b>), the orange squares mark the location of specific points in the exploitation (EZ) and recharge (RZ) zones. Black dots a and b indicate the location of MBIG and NVLX GPS sites, respectively. SAR stands for Synthetic Aperture Radar. ADEW stands for Ascending/Descending/East/North, which refers to the flight direction combination of the different SAR geometries. Notation as in <a href="#remotesensing-16-03788-f005" class="html-fig">Figure 5</a>.</p>
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<p>Maps of displacement vector components, derived from the Sentinel 1A and UAVSAR datasets’ combination for the April/2015–April/2016 period. (<b>a</b>) Vertical displacement rate. Negative values indicate subsidence. (<b>b</b>) North displacement rate. Negative values indicate southward movement. (<b>c</b>) East displacement rate. Negative values indicate westward movement. Areas of low coherence (&lt;0.2) and errors (&lt;20 mm/yr) are masked out. In (<b>a</b>), the orange squares mark the location of the exploitation (EZ) and recharge (RZ) zones. The green inverted triangle marks the Ejido Nuevo León location and black dots a and b indicate the location of the MBIG and NVLX GPS sites, respectively. SAR stands for Synthetic Aperture Radar. ADEW stands for Ascending/Descending/East/North, which refers to the flight direction combination of the different SAR geometries. Notation as in <a href="#remotesensing-16-03788-f005" class="html-fig">Figure 5</a>.</p>
Full article ">Figure 8 Cont.
<p>Maps of displacement vector components, derived from the Sentinel 1A and UAVSAR datasets’ combination for the April/2015–April/2016 period. (<b>a</b>) Vertical displacement rate. Negative values indicate subsidence. (<b>b</b>) North displacement rate. Negative values indicate southward movement. (<b>c</b>) East displacement rate. Negative values indicate westward movement. Areas of low coherence (&lt;0.2) and errors (&lt;20 mm/yr) are masked out. In (<b>a</b>), the orange squares mark the location of the exploitation (EZ) and recharge (RZ) zones. The green inverted triangle marks the Ejido Nuevo León location and black dots a and b indicate the location of the MBIG and NVLX GPS sites, respectively. SAR stands for Synthetic Aperture Radar. ADEW stands for Ascending/Descending/East/North, which refers to the flight direction combination of the different SAR geometries. Notation as in <a href="#remotesensing-16-03788-f005" class="html-fig">Figure 5</a>.</p>
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<p>Contour maps of vertical displacement rate (cm/yr) from (<b>a</b>) leveling measurements (2012–2015) and (<b>b</b>) 3D displacement vector decomposition (2012–2014); (<b>c</b>) contour map of the difference (residual) between leveling measurements (IMTA) and InSAR vertical displacement rate. Blue triangles are benchmarks used for interpolation and contouring. In (<b>a</b>,<b>b</b>), the contours are every 1 cm, and in (<b>c</b>), are every 0.4 cm. In (<b>a</b>,<b>b</b>), RP is the reference area centered at the “10037” benchmark location and is represented by a black tringle. Tectonic faults are shown as continuous red lines. The red flag in (<b>b</b>,<b>c</b>) shows the location of the InSAR reference point. InSAR stands for Interferometric Aperture Radar. Notation as in <a href="#remotesensing-16-03788-f005" class="html-fig">Figure 5</a>.</p>
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<p>(<b>a</b>) Total RMSE and difference histogram of vertical displacement rate (cm/yr); (<b>b</b>) correlation coefficient between leveling data (2012–2015) and vertical InSAR (February/2012–Novemeber/2014).</p>
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<p>(<b>a</b>) The vertical displacement rate (mm/yr) obtained here vs. other works [<a href="#B13-remotesensing-16-03788" class="html-bibr">13</a>,<a href="#B19-remotesensing-16-03788" class="html-bibr">19</a>,<a href="#B67-remotesensing-16-03788" class="html-bibr">67</a>] in the exploitation and recharge zones in the CPSO. See <a href="#remotesensing-16-03788-f007" class="html-fig">Figure 7</a>a and <a href="#remotesensing-16-03788-f008" class="html-fig">Figure 8</a>a for zones’ location. (<b>b</b>) Production and injection wells (number of wells) vs. total electricity generated in the CPGF. In (<b>a</b>), continuous and dashed lines represent a location in the exploitation and recharge zones, respectively. Texts in parentheses denote the works of other authors and are associated with a color for clarity.</p>
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64 pages, 8926 KiB  
Review
Emerging and Conventional Water Desalination Technologies Powered by Renewable Energy and Energy Storage Systems toward Zero Liquid Discharge
by Mahmoud M. Elewa
Separations 2024, 11(10), 291; https://doi.org/10.3390/separations11100291 - 11 Oct 2024
Viewed by 1509
Abstract
The depletion of fossil fuels has become a significant global issue, prompting scientists to explore and refine methods for harnessing alternative energy sources. This study provides a comprehensive review of advancements and emerging technologies in the desalination industry, focusing on technological improvements and [...] Read more.
The depletion of fossil fuels has become a significant global issue, prompting scientists to explore and refine methods for harnessing alternative energy sources. This study provides a comprehensive review of advancements and emerging technologies in the desalination industry, focusing on technological improvements and economic considerations. The analysis highlights the potential synergies of integrating multiple renewable energy systems to enhance desalination efficiency and minimise environmental consequences. The main areas of focus include aligning developing technologies like membrane distillation, pervaporation and forward osmosis with renewable energy and implementing hybrid renewable energy systems to improve the scalability and economic viability of desalination enterprises. The study also analyses obstacles related to desalination driven by renewable energy, including energy storage, fluctuations in energy supply, and deployment costs. By resolving these obstacles and investigating novel methodologies, the study enhances the understanding of how renewable energy can be used to construct more efficient, sustainable, and economical desalination systems. Thermal desalination technologies require more energy than membrane-based systems due to the significant energy requirements associated with water vaporisation. The photovoltaic-powered reverse osmosis (RO) system had the most economically favourable production cost, while MED powered via a concentrated solar power (CSP) system had the highest production cost. The study aims to guide future research and development efforts, ultimately promoting the worldwide use of renewable energy-powered desalination systems. Full article
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<p>Categorisation of desalination technologies.</p>
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<p>Factors that affect the choice of desalination technology.</p>
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<p>Status update on renewable energy powered desalination plants—blue bars represent thermal desalination while red bars represent membrane–based desalination.</p>
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<p>Potential alternatives for desalination utilising renewable energy sources.</p>
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<p>Categorisation of primary energy storage systems [<a href="#B96-separations-11-00291" class="html-bibr">96</a>].</p>
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<p>The current status of desalination technology in relation to renewable energy [<a href="#B29-separations-11-00291" class="html-bibr">29</a>].</p>
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<p>Schematic representation of the HPRO system [<a href="#B153-separations-11-00291" class="html-bibr">153</a>].</p>
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<p>Osmotic pressure varies according to solution concentration. The red line represents the range in which RO may be used, and the yellow line shows the range in which HPRO can be used [<a href="#B153-separations-11-00291" class="html-bibr">153</a>].</p>
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<p>Flux directions and driving forces in several osmotic membrane processes, such as pressure-assisted forward osmosis (PAFO), FO, pressure-retarded osmosis (PRO), OARO, and RO, are compared [<a href="#B161-separations-11-00291" class="html-bibr">161</a>].</p>
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<p>(<b>a</b>) Enhancing energy efficiency in the salt water V-MEMD desalination process through the utilisation of condensation latent heat recovery [<a href="#B127-separations-11-00291" class="html-bibr">127</a>], (<b>b</b>) desalination method utilising seawater AGMD with internal condensation latent heat recovery [<a href="#B127-separations-11-00291" class="html-bibr">127</a>].</p>
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<p>The diagram illustrates the process of forward osmosis (FO) and reverse osmosis (RO), with Δπ representing the difference in osmotic pressure between the two sides [<a href="#B213-separations-11-00291" class="html-bibr">213</a>].</p>
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<p>Hybrid systems that combine FO and RO are utilised to desalinate seawater, as well as simultaneously treating wastewater and desalinating it [<a href="#B214-separations-11-00291" class="html-bibr">214</a>].</p>
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<p>A typical setup for electrodialysis, with the electrode rinse solution, cation-exchange membrane (CEM), anion-exchange membrane (AEM), cations (C<sup>+</sup>), and anions (A<sup>−</sup>) [<a href="#B224-separations-11-00291" class="html-bibr">224</a>]. (*) stands for: Electrode rinsing solution.</p>
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<p>A reverse electrodialysis (RED) stack, with the labels HC representing high salt concentration and LC representing low salt concentration [<a href="#B225-separations-11-00291" class="html-bibr">225</a>].</p>
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<p>Schematic illustration ED metathesis (EDM) [<a href="#B168-separations-11-00291" class="html-bibr">168</a>].</p>
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<p>MED-MVC schematic [<a href="#B242-separations-11-00291" class="html-bibr">242</a>].</p>
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<p>The process of desalination using the humidification–dehumidification (HDH) method in a direct and uncomplicated manner [<a href="#B29-separations-11-00291" class="html-bibr">29</a>].</p>
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<p>Typical schematic diagram for (<b>a</b>) BC and (<b>b</b>) BCr [<a href="#B302-separations-11-00291" class="html-bibr">302</a>].</p>
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<p>A schematic representation of a spray drier (SD) [<a href="#B168-separations-11-00291" class="html-bibr">168</a>].</p>
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<p>Representative phase diagram for a binary system consisting of water and salt [<a href="#B306-separations-11-00291" class="html-bibr">306</a>].</p>
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<p>Concise schematic of the EFC process [<a href="#B306-separations-11-00291" class="html-bibr">306</a>].</p>
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<p>Schematic diagram illustrating the processes of wind-aided intensified evaporation (WAIV) [<a href="#B168-separations-11-00291" class="html-bibr">168</a>].</p>
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<p>Feed salinity and SEC (specific energy consumption) for various novel methods.</p>
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23 pages, 7766 KiB  
Article
Hydrochemical Characteristics and Formation Mechanism of Geothermal Fluids in Zuogong County, Southeastern Tibet
by Sihang Han, Dawa Nan, Zhao Liu, Nima Gesang, Chengcuo Bianma, Haihua Zhao, Yadong Zheng and Peng Xiao
Water 2024, 16(19), 2852; https://doi.org/10.3390/w16192852 - 8 Oct 2024
Viewed by 428
Abstract
Zuogong County is located in the southeast of Tibet, which is rich in hot spring geothermal resources, but its development and utilization degree are low, and the genetic mechanism of the geothermal system is not clear. Hydrogeochemical characteristics of geothermal water are of [...] Read more.
Zuogong County is located in the southeast of Tibet, which is rich in hot spring geothermal resources, but its development and utilization degree are low, and the genetic mechanism of the geothermal system is not clear. Hydrogeochemical characteristics of geothermal water are of great significance in elucidating the genesis and evolution of geothermal systems, as well as the sustainable development and utilization of geothermal resources. The hydrogeochemical characteristics and genesis of the geothermal water in Zuogong County were investigated using hydrogeochemical analysis, a stable isotope (δD, δ18O) approach, and an inverse simulation model for water–rock reactions using the PHREEQC. The results indicated that the Zuogong geothermal system is a deep circulation heating type without a magmatic heat source. The chemical types present in the geothermal water from the Zuogong area are HCO3 and HCO3·SO4, and the main cations are Na+ and Ca2+. The groundwater is replenished by atmospheric precipitation and glacier meltwater. The salt content of geothermal water mainly comes from the interaction between water and surrounding rocks during the deep circulation process. The reservoir temperature of geothermal water in Zuogong is 120–176 °C before mixing with non-geothermal water and drops to 62–98 °C after mixing with 58 to 79% of non-geothermal water. According to the proposed conceptual model, geothermal water mainly produces water–rock interaction with aluminosilicate minerals in the deep formation, while in shallow areas it interacts mainly with sulfate minerals. These findings contribute to a better understanding of the geothermal system in Zuogong County, Tibet. Full article
(This article belongs to the Section Hydrogeology)
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<p>(<b>a</b>) Geological diagram of Zuogong County, Tibet. (<b>b</b>) Sampling location diagram of Zuogong County, Tibet.</p>
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<p>Piper diagram of thermal groundwater and non-thermal groundwater from Zuogong County, Tibet.</p>
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<p>The correlations of TDS vs. main anions and cations in thermal groundwater and non-thermal groundwater from Zuogong County, Tibet.</p>
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<p>The correlations of TDS vs. typical geothermal components in thermal groundwater and non-thermal groundwater from Zuogong County, Tibet.</p>
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<p>Cl–SO<sub>4</sub>–HCO<sub>3</sub> ternary diagram for the water samples in Zuogong County, Tibet.</p>
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<p>Box diagram of F, Li, B, and As components in geothermal water from Rehai, Yangbajing, and Zuogong.</p>
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<p>Box plots for measuring and estimating temperature. (Note: MEE: multicomponent mineral equilibrium; SEMM: silica-enthalpy mixing model).</p>
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<p>Saturation indices (SIs) vs. temperature to estimate reservoir temperature for four thermal wells and five thermal springs.</p>
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<p>Si-enthalpy of the thermal reservoir from the Zuogong, Tibet.</p>
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<p>The δD-δ<sup>18</sup>O relationship of groundwater in Zuogong County, Tibet.</p>
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<p>Na-K-Mg ternary diagram for the water samples in Zuogong County, Tibet.</p>
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<p>Conceptual model of geothermal genesis in Zuogong County, Tibet.</p>
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28 pages, 2842 KiB  
Review
Heat Transfer Performance Factors in a Vertical Ground Heat Exchanger for a Geothermal Heat Pump System
by Khaled Salhein, C. J. Kobus, Mohamed Zohdy, Ahmed M. Annekaa, Edrees Yahya Alhawsawi and Sabriya Alghennai Salheen
Energies 2024, 17(19), 5003; https://doi.org/10.3390/en17195003 - 8 Oct 2024
Viewed by 699
Abstract
Ground heat pump systems (GHPSs) are esteemed for their high efficiency within renewable energy technologies, providing effective solutions for heating and cooling requirements. These GHPSs operate by utilizing the relatively constant temperature of the Earth’s subsurface as a thermal source or sink. This [...] Read more.
Ground heat pump systems (GHPSs) are esteemed for their high efficiency within renewable energy technologies, providing effective solutions for heating and cooling requirements. These GHPSs operate by utilizing the relatively constant temperature of the Earth’s subsurface as a thermal source or sink. This feature allows them to perform greater energy transfer than traditional heating and cooling systems (i.e., heating, ventilation, and air conditioning (HVAC)). The GHPSs represent a sustainable and cost-effective temperature-regulating solution in diverse applications. The ground heat exchanger (GHE) technology is well known, with extensive research and development conducted in recent decades significantly advancing its applications. Improving GHE performance factors is vital for enhancing heat transfer efficiency and overall GHPS performance. Therefore, this paper provides a comprehensive review of research on various factors affecting GHE performance, such as soil thermal properties, backfill material properties, borehole depth, spacing, U-tube pipe properties, and heat carrier fluid type and velocity. It also discusses their impact on heat transfer efficiency and proposes optimal solutions for improving GHE performance. Full article
(This article belongs to the Special Issue Advances in Refrigeration and Heat Pump Technologies)
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<p>Installed capacity (MWt) of geothermal heat pump systems worldwide from 1995 to 2020 [<a href="#B18-energies-17-05003" class="html-bibr">18</a>].</p>
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<p>Schematic diagram of geothermal heat pump system [<a href="#B7-energies-17-05003" class="html-bibr">7</a>].</p>
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<p>Schematic diagram of single U-tube vertical ground heat exchanger.</p>
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<p>Thermal performance factors of the vertical ground heat exchanger [<a href="#B7-energies-17-05003" class="html-bibr">7</a>].</p>
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<p>Relationship between the geothermal heat transfer rate and thermal resistance [<a href="#B5-energies-17-05003" class="html-bibr">5</a>].</p>
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<p>Relationship between the geothermal heat transfer rate and coefficient of performance [<a href="#B5-energies-17-05003" class="html-bibr">5</a>].</p>
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<p>Shank space in a horizontal cross-section of a U-tube pipe in a vertical ground heat exchanger (GHE) [<a href="#B5-energies-17-05003" class="html-bibr">5</a>].</p>
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<p>Relationship between the water velocity and geothermal pipe length [<a href="#B5-energies-17-05003" class="html-bibr">5</a>].</p>
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<p>Illustration of the behavior of water temperature inside a vertical single U-tube pipe at various velocities (0.35, 0.45, 0.9, and 1.2 m/s) during heating mode (i.e., winter operation) [<a href="#B7-energies-17-05003" class="html-bibr">7</a>].</p>
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<p>Illustration of the behavior of water temperature inside a vertical single U-tube pipe at various velocities (0.35, 0.45, 0.9, and 1.2 m/s) during cooling mode (i.e., summer operation) [<a href="#B7-energies-17-05003" class="html-bibr">7</a>].</p>
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16 pages, 6453 KiB  
Article
Sampling Confined Fission Tracks for Constraining Geological Thermal Histories
by Raymond Jonckheere, Carolin Aslanian, Hongyang Fu and Florian Trilsch
Minerals 2024, 14(10), 1016; https://doi.org/10.3390/min14101016 - 8 Oct 2024
Viewed by 472
Abstract
Fission-track modeling rests on etching, counting and measuring the lattice damage trails from uranium fission. The tools for interpreting fission-track data are advanced but the results are never better than the data. Confined-track samples must be an adequate size for statistical analysis, representative [...] Read more.
Fission-track modeling rests on etching, counting and measuring the lattice damage trails from uranium fission. The tools for interpreting fission-track data are advanced but the results are never better than the data. Confined-track samples must be an adequate size for statistical analysis, representative of the track population and consistent with the model assumptions and with the calibration data. Geometrical and measurement biases are understood and can be dealt with up to a point. However, the interrelated issues of etching protocol and track selection are more difficult to untangle. Our investigation favors a two-step protocol. The duration of the first step is inversely proportional to the apatite etch rate so that different apatites etch to the same Dpar. A long immersion reveals many more confined tracks, terminated by basal and prism faces. This allows consistent length measurements and permits orienting each track relative to the c-axis. Long immersion times combined with deep ion irradiation reveal confined tracks deep inside the grains. Provided it is long enough, the precise immersion time is not important if the effective etch times of the selected tracks are calculated from their measured widths. Then, whether the sample is mono- or multi-compositional, we can, post hoc, select tracks with the desired properties. The second part of the protocol has to do with the fact that fossil tracks in geological samples appear to be under-etched compared to induced tracks etched under the same conditions. This should be assumed if the semi-axes of a fitted ellipse plot above the induced-track line. In that case, an additional etch can increase the track lengths to a point where they are consistent with the model based on lab-annealing of induced tracks, a condition for valid thermal histories. Here too, it is possible to select a subset of tracks with effective etch times consistent with the model if the widths of confined tracks are measured along with their lengths and orientations. Full article
(This article belongs to the Special Issue Thermal History Modeling of Low-Temperature Thermochronological Data)
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<p>Unannealed horizontal induced confined track in Durango apatite after (<b>a</b>) 15 s, (<b>b</b>) 30 s and (<b>c</b>) 45 s of immersion in 5.5 M HNO<sub>3</sub> at 21 °C, and superimposed outlines (<b>d</b>); <span class="html-italic">t<sub>I</sub></span>: immersion time; <span class="html-italic">t<sub>E</sub></span>: effective etch time; <span class="html-italic">l</span>: track length c-c: apatite <b><span class="html-italic">c</span></b>-axis; <span class="html-italic">v<sub>T</sub></span>: track etch rate; <span class="html-italic">v<sub>L</sub></span>: rate of length increase; <span class="html-italic">v<sub>R</sub></span>, apatite etch rate perpendicular to the track axis. The host track intersects at ¼ track length from endpoint α.</p>
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<p>(<b>a</b>) Chemical etching of single-crystal spheres illustrates that rounded forms are not their natural boundaries (modified, after [<a href="#B33-minerals-14-01016" class="html-bibr">33</a>]). (<b>b</b>) The rounded track tip at γ in <a href="#minerals-14-01016-f001" class="html-fig">Figure 1</a> is the result of a decreasing track etch rate (motorboat effect; [<a href="#B31-minerals-14-01016" class="html-bibr">31</a>]) caused by an intermittent latent track structure [<a href="#B34-minerals-14-01016" class="html-bibr">34</a>].</p>
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<p>Two grains etched for 40 s in 5.5 M HNO<sub>3</sub> at 21 °C illustrate the contrast between fast- and slow-etching surfaces; the slow-etching prism surface (grain 1) is more or less still at the same level as that of the unetched mount, as indicated by its sharp outline in (<b>a</b>), whereas the surface of the fast-etching crystal (grain 2) has been lowered to a level so far below that of the mount that it is out of focus in (<b>a</b>); it comes into sharp focus after lowering the objective to the point where the image of grain 1 becomes blurred (<b>b</b>); (<b>c</b>) the outline of a single well-etched confined track allows one to determine the <b><span class="html-italic">c</span></b>-axis azimuth.</p>
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<p>Calculation of (<b>a</b>) the length (<span class="html-italic">l</span>) and (<b>b</b>) the <b><span class="html-italic">c</span></b>-axis angle (<span class="html-italic">ϕ</span>) of a dipping confined fission track (FT) from measurements of its projection (<span class="html-italic">h</span>) and of a section of ion track (IT; <span class="html-italic">p</span>) extending over the same depth (<span class="html-italic">v</span>) as the fission track.</p>
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<p>Track widths and etch rates vs. angle to the <b><span class="html-italic">c</span></b>-axis; (<b>a</b>) widths of induced confined tracks in Durango apatite after 15 s (no shading), 30 s (light shading) and 45 s (dark shading) of immersion in 5.5 M HNO<sub>3</sub> at 21 °C vs. their <b><span class="html-italic">c</span></b>-axis angles (<span class="html-italic">ϕ</span>); (<b>b</b>) apatite etch rate <span class="html-italic">v<sub>R</sub></span> vs. <b><span class="html-italic">c</span></b>-axis angle of the etch rate vector (<span class="html-italic">ϕ’</span> = 90 − <span class="html-italic">ϕ</span>), calculated from the width increase from 15 s to 30 s of immersion (no shading) and from 30 s to 45 s (light shading); dashed line: [<a href="#B27-minerals-14-01016" class="html-bibr">27</a>]; solid line: [<a href="#B29-minerals-14-01016" class="html-bibr">29</a>]; (<b>c</b>) track etch rate <span class="html-italic">v<sub>T</sub></span> vs. angle to the <b><span class="html-italic">c</span></b>-axis (<span class="html-italic">ϕ</span>); no shading: 15 s data; light shading: 30 s data, dark shading: 45 s data; the dashed lines are second-degree polynomial fits; (<b>d</b>) rate of length increase <span class="html-italic">v<sub>L</sub></span> vs. angle to the <b><span class="html-italic">c</span></b>-axis (<span class="html-italic">ϕ</span>), calculated from the length increase from 15 s to 30 s of immersion (no shading) and from 30 s to 45 s (light shading).</p>
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<p>(<b>a</b>) Induced confined track lengths in Durango apatite plotted against the effective etch times calculated from their widths measured after 15 (white), 30 (light shading) and 45 s (dark shading) of immersion in 5.5 M HNO<sub>3</sub> at 21 °C; the histograms represent the effective etch time frequencies after 15, 30 and 45 s of immersion; (<b>b</b>) arithmetic means of the interpolated induced and fossil track lengths, normalized to their final values, plotted against effective etch time (<span class="html-italic">t<sub>E</sub></span>; lower scale) and effective etch action (<span class="html-italic">t<sub>A</sub></span> = <span class="html-italic">t<sub>E</sub></span> × <span class="html-italic">Dpar</span>; upper scale); solid line: mean normalized lengths; dotted lines: 2σ-confidence interval of the mean. The dashed red lines have been added to illustrate linear sections; the red band at the bottom shows a suitable effective etch time interval for fossil and induced tracks in Durango apatite.</p>
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<p>(<b>a</b>) Mean track length <span class="html-italic">l<sub>M</sub></span> vs. etch action <span class="html-italic">t<sub>A</sub> = Dpar × t<sub>E</sub></span>. Data: [<a href="#B27-minerals-14-01016" class="html-bibr">27</a>] (fossil tracks—DR, Durango), [<a href="#B29-minerals-14-01016" class="html-bibr">29</a>] (fossil tracks—BZ, Brazil, BB, Bamble, SY, Sludjanka, PQ, Panasqueira), [<a href="#B3-minerals-14-01016" class="html-bibr">3</a>] (induced tracks—WC) and [<a href="#B4-minerals-14-01016" class="html-bibr">4</a>] (induced tracks—JB). In the samples with fossil tracks, variation along the <span class="html-italic">t<sub>A</sub></span>-axis is due to step-etching and the associated increase in <span class="html-italic">t<sub>E</sub></span>, while <span class="html-italic">Dpar</span> is constant for each sample. In the case of the induced-track data, apatites with different compositions (<span class="html-italic">Dpar</span>) were etched for the same immersion time <span class="html-italic">t<sub>I</sub></span>. For plotting the data, we assumed that their average effective etch times are half the immersion time: <span class="html-italic">t<sub>E</sub></span> ≈ ½ <span class="html-italic">t<sub>I</sub></span>. (<b>b</b>) Aslanian et al. ([<a href="#B27-minerals-14-01016" class="html-bibr">27</a>]; DR) and Fu et al. ([<a href="#B29-minerals-14-01016" class="html-bibr">29</a>]; PQ, SY, BZ, BB) used immersion times <span class="html-italic">t<sub>I</sub></span> ≈ 50 × <span class="html-italic">Dpar</span><sup>−1</sup> for samples in the <span class="html-italic">Dpar</span> range 1.6–4.6 µm etched in 5.5 M HNO<sub>3</sub> at 21 °C, resulting in mean effective etch times <span class="html-italic">m</span>(<span class="html-italic">t<sub>E</sub></span>)≈ 25 × <span class="html-italic">Dpar</span><sup>−1</sup>.</p>
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<p>(<b>a</b>) <b><span class="html-italic">a</span></b>-axis vs. <b><span class="html-italic">c</span></b>-axis intercepts of ellipses fitted to (1) induced tracks annealed to different lengths (yellow), (2) simulated complex length distributions made by combining up to four induced-track samples into one (orange), (3) fossil-track samples from various geological studies (white). (<b>b</b>) Conceptual illustration of how underetching leads to more isotropic length distributions than expected for their means.</p>
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<p>(<b>a</b>) Unconstrained (solid) and constrained (dotted lines; <span class="html-italic">l<sub>A</sub></span> = 1.632 <span class="html-italic">l<sub>C</sub></span>—10.978; [<a href="#B53-minerals-14-01016" class="html-bibr">53</a>]) ellipses fitted to the interpolated length and angle data for effective etch times of 10, 15, 20, 25, 30 and 35 s. (<b>b</b>) Unconstrained (solid) and constrained (dotted; <span class="html-italic">l<sub>A</sub></span> = <span class="html-italic">l<sub>C</sub></span>) lines fitted to the <b><span class="html-italic">c</span></b>-axis projected lengths vs. <b><span class="html-italic">c</span></b>-axis angles. (<b>c</b>) The <b><span class="html-italic">a</span></b>-axis intercepts vs. <b><span class="html-italic">c</span></b>-axis intercepts of unconstrained ellipses fitted to the interpolated lengths and orientations of step-etched induced confined tracks in Durango apatite (<a href="#minerals-14-01016-f009" class="html-fig">Figure 9</a>a).</p>
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<p>(<b>a</b>) The <b><span class="html-italic">a</span></b>-axis intercepts (<span class="html-italic">l<sub>A</sub></span>) vs. <b><span class="html-italic">c</span></b>-axis intercepts (<span class="html-italic">l<sub>C</sub></span>) of unconstrained ellipses fitted to the lengths and orientations of step-etched fossil confined tracks in apatites with different compositions (open circles: first step; filled circles: second step). Immersion times for the first step are shown in <a href="#minerals-14-01016-f007" class="html-fig">Figure 7</a>b; the second measurement was performed after an additional immersion of 15 s in 5.5 M HNO<sub>3</sub> at 21 °C [<a href="#B27-minerals-14-01016" class="html-bibr">27</a>,<a href="#B29-minerals-14-01016" class="html-bibr">29</a>]. (<b>b</b>) The <b><span class="html-italic">a</span></b>-axis intercepts vs. <b><span class="html-italic">c</span></b>-axis intercepts of unconstrained ellipses fitted to the lengths and orientations of step-etched fossil (filled) and induced (open) confined fission tracks in prism faces of Durango apatite etched for different immersion times (<span class="html-italic">t<sub>I</sub></span>; numbers inside circles).</p>
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34 pages, 4940 KiB  
Review
Nanoparticles in Drilling Fluids: A Review of Types, Mechanisms, Applications, and Future Prospects
by Vasanth Gokapai, Prasad Pothana and Kegang Ling
Eng 2024, 5(4), 2462-2495; https://doi.org/10.3390/eng5040129 - 3 Oct 2024
Viewed by 727
Abstract
Nanofluids have gained significant attention as a promising solution to several challenges in drilling operations. Nanoparticles, due to their exclusive properties such as high specific surface area, strong adsorption potential, and excellent thermal conductivity, offer significant potential to improve the efficiency and performance [...] Read more.
Nanofluids have gained significant attention as a promising solution to several challenges in drilling operations. Nanoparticles, due to their exclusive properties such as high specific surface area, strong adsorption potential, and excellent thermal conductivity, offer significant potential to improve the efficiency and performance of drilling processes. Regardless of the advancements in drilling fluids and techniques that have improved borehole stability, hole cleaning, and extreme operational condition (HTHP) management, limitations still persist. This review discusses a detailed summary of existing research on the application of nanofluids in drilling, exploring their types, properties, and specific uses in areas such as fluid loss control, wellbore stability, and thermal management. It also reports the challenges and future potential of nanotechnology in drilling, including nanoparticle stability, environmental considerations, and cost concerns. By synthesizing current research and highlighting gaps for further study, this review intends to guide researchers and industry professionals in effectively integrating nanofluid usage to optimize drilling practices and support a more sustainable energy future. Full article
(This article belongs to the Special Issue GeoEnergy Science and Engineering 2024)
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<p>Classification of drilling fluids and types.</p>
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<p>Evolution of research on nanoparticles in drilling: a bibliometric analysis (2007–2023). Data sourced from Dimensions.ai, focusing on publications with the keyword “nanoparticles in drilling” in their titles and abstracts.</p>
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<p>Nanofluid preparation process: (<b>a</b>) initial mixing of nanoparticles, dispersant, and base fluid; (<b>b</b>) mechanical stirring for preliminary dispersion; (<b>c</b>) ultrasonication for particle size reduction and stability enhancement; (<b>d</b>) final stable nanofluid with well-dispersed nanoparticles.</p>
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<p>Classification of nanoparticles employed in the formulation of drilling nanofluids.</p>
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<p>Fluid loss mechanisms: (<b>a</b>) conventional drilling fluid—thick, porous filter cake allows filtrate to escape into the formation; (<b>b</b>) nanoparticle-laden drilling fluid—nanoparticles bridge pore spaces in the filter cake, forming a thin, impermeable barrier that minimizes fluid loss.</p>
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<p>(<b>A</b>) Particle size distribution curve demonstrates the high surface area of the material. (<b>B</b>) SEM image of SDFL (a polymer-based nano-silica composite with a core–shell structure) reveals the morphology of the composite particles. The polymer matrix appears to form connections between the particles. (<b>C</b>) TEM image of SDFL confirms good dispersion in aqueous media, likely due to the hydrophobic polymer coating on the nano-silica particles, which supports the formation of a core–shell structured composite. (<b>D</b>) ESEM image of SDFL shows the strong crosslinking within the composite when nano-silica is mixed with the polymer, resulting in a tightly knit grid-like structure. (figure sourced from [<a href="#B94-eng-05-00129" class="html-bibr">94</a>]).</p>
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<p>Scanning electron microscopy (SEM) images of (<b>a</b>,<b>b</b>) an untreated shale surface; (<b>c</b>,<b>d</b>) a shale surface treated with 1.0 wt% hydrophobic nano-silica (HNS) at 120 °C for 16 h; and (<b>e</b>,<b>f</b>) a lotus leaf surface (for comparison). HNS adsorption modifies the shale’s microstructure, significantly increasing the contact angle and thus reducing surface free energy. This change in wettability hinders hydration and enhances wellbore stability by efficiently closing shale pores and forming a smooth, water-resistant film (figure adapted from [<a href="#B123-eng-05-00129" class="html-bibr">123</a>]).</p>
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<p>Wellbore stability mechanisms. (<b>a</b>) A stable wellbore is characterized by the presence of tiny microfractures and pores, which are effectively sealed by a thin layer of filter cake. (<b>b</b>) An enlarged view of a microfracture illustrates how nanoparticles can penetrate and fill the void spaces within the fracture, further enhancing wellbore stability and preventing fluid loss.</p>
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<p>Schematic illustrating the stuck pipe mitigation with nanofluids. (<b>a</b>) A wellbore scenario where a drill pipe becomes stuck due to thick filter cake buildup on the wellbore wall. (<b>b</b>) Enlarged cross-section illustrating how the increased contact surface area of thick filter cake contributes to the pipe sticking. (<b>c</b>) Nanofluids offer a solution by forming a thin filter cake, reducing contact area, maintaining good particle suspension, and enhancing cuttings transport to prevent stuck pipe incidents.</p>
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<p>The static mechanism of heat transfer in nanofluids: (<b>a</b>) representation of how the liquid layering occurs at the solid–liquid interface of the nanoparticles; (<b>b</b>) aggregation of nanoparticles that act as a pathway for heat transfer.</p>
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<p>Dynamic mechanism of heat transfer: as the particles move in a Brownian motion (irregular movement), they collide with each other and also induce convection for the nearby liquid molecules of the base fluid, thus increasing the thermal conductivity.</p>
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<p>High-resolution transmission electron microscopy (HR-TEM) analysis of graphene nanoplatelet composites (GN). (<b>a</b>) HR-TEM image of modified GN-CS (GN-TX) surface post-modification, revealing significant alterations in surface morphology. (<b>b</b>) Magnified image of GN-TX highlighting the firm attachment and dispersion of the modified materials after ultrasonic treatment. Visible wrinkles (represented by arrows) indicate the presence of multiple (squares with dotted lines) graphene layers. (<b>c</b>) Intensity pattern of GN-TX, confirming the strong attachment of Triton to the GN-CS surface. (<b>d</b>) HR-TEM image of GN-CS, emphasizing the wrinkly regions with entangled graphene sheets. (<b>e</b>) Magnified image of GN-CS showing the multiple (squares with dotted lines), wrinkly (indicated by arrows) graphene layers that contribute to the composite’s thermal stability. (<b>f</b>) Intensity patterns of GN-CS further reveal the structural details (figure adapted from [<a href="#B160-eng-05-00129" class="html-bibr">160</a>]).</p>
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20 pages, 7079 KiB  
Article
Cement-Formation Debonding Due to Temperature Variation in Geothermal Wells: An Intensive Numerical Simulation Assessment
by Ionut Lambrescu, Khizar Abid and Catalin Teodoriu
Energies 2024, 17(19), 4953; https://doi.org/10.3390/en17194953 - 3 Oct 2024
Viewed by 700
Abstract
Geothermal wells are subjected to higher loads compared to conventional oil and gas wells due to the thermal cycles that occur during both production and non-production phases. These temperature variations can affect the cohesion of the cement within the formation and casing, creating [...] Read more.
Geothermal wells are subjected to higher loads compared to conventional oil and gas wells due to the thermal cycles that occur during both production and non-production phases. These temperature variations can affect the cohesion of the cement within the formation and casing, creating micro-annuli channels that can ultimately compromise the integrity of the well. Therefore, this study employs an intensive finite element methodology to analyze the debonding criteria of casing–cement systems in geothermal wells by examining over 36 independent models. The wellbore cooling and heating processes were simulated using three cohesive zone models (CZM): Type I (tensile), Type II (shear), and mixed (Type I and II simultaneously). The analysis revealed that Type I debonding occurs first during cooling at a temperature of around 10 °C, while Type II is the primary failure mode during heating. Evaluations of interfacial bonding shear strength (IBSS) values indicated that the debonding of the cement would even occur at high IBSS values (3 and 4 MPa) at a differential temperature of 300 °C, while the other IBSS of 1 MPa withstands only 60 °C. However, achieving an IBSS of 4 MPa with current technology is highly unlikely. Therefore, geothermal well operation and construction must be modified to keep the differential temperature below the critical temperature at which the debonding of the cement initiates. The study also found that debonding during cooling happens at lower differential temperatures due to generally lower values for interfacial bonding tensile strength (IBTS), typically less than 1 MPa. The novelty of the study is that it provides new insights into how specific temperatures trigger different types of debonding, highlights that high IBSS values may not prevent debonding at high differential temperatures, and recommends operational adjustments to maintain temperatures below critical levels to enhance cement integrity. Additionally, this study reveals that debonding during cooling occurs at a lower differential temperature change due to the reduced value of the interfacial bonding tensile strength (IBTS). Full article
(This article belongs to the Section H: Geo-Energy)
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<p>Model and meshing structure.</p>
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<p>Radial displacement (gap) for 2, 10, and 100 m models.</p>
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<p>Axial displacement for 2, 10 and 100 m models.</p>
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<p>Gap size formed in the 100 °C cooling scenario.</p>
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<p>Axial displacement in the 100 °C cooling scenario.</p>
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<p>Impact of temperature variation on the magnitude of gap size.</p>
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<p>System deformation comparison for 200 °C differential cooling. (<b>a</b>) ΔT 200 °C. Radial and axial displacement. Cooling, elastic boundary, mixed mode. (<b>b</b>) ΔT 200 °C. Radial and axial displacement. Cooling, free boundary, mixed mode.</p>
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<p>System deformation comparison for 200 °C differential heating. (<b>a</b>) ΔT 200 °C. Axial displacement. Heating, elastic support, mixed mode. (<b>b</b>) ΔT 200 °C. Axial displacement. Heating, free cement, mixed mode.</p>
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<p>Sliding distance for the casing–cement contact for various values of IBSS.</p>
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<p>Position of selected reference nodes to measure the axial displacement of the casing–cement–formation system.</p>
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<p>Axial displacement of node 6084.</p>
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<p>Axial displacement of node 591 for the heating process.</p>
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<p>Zoomed-in section of the heating zone for the axial displacement of node 591.</p>
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<p>Axial displacement of node 591 for the cooling process (positive displacement) compared with heating (negative displacement).</p>
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<p>Radial stress at node 591 showing very early debonding induced by temperature variation (cooling).</p>
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<p>Zoom-out of the initial simulation time, showing very early debonding during the cooling process.</p>
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13 pages, 1073 KiB  
Article
Extrusion and Injection Molding of Polyethylene Loaded with Recycled Textiles: Mechanical Performance and Thermal Conductivity
by Mateo Gasselin, Adib Kalantar, Sofi Karlsson, Peter Leisner, Mikael Skrifvars and Pooria Khalili
J. Compos. Sci. 2024, 8(10), 399; https://doi.org/10.3390/jcs8100399 - 2 Oct 2024
Viewed by 618
Abstract
The aim of this project was to assess the thermal conductivity of polyethylene (PE) filled with carbon black (CB), specifically for geothermal pipes. The project explored the potential modification of PE’s thermal conductivity by incorporating recycled textile fibers. Different types of shredded recycled [...] Read more.
The aim of this project was to assess the thermal conductivity of polyethylene (PE) filled with carbon black (CB), specifically for geothermal pipes. The project explored the potential modification of PE’s thermal conductivity by incorporating recycled textile fibers. Different types of shredded recycled fibers were tested, including two types of polyamide fibers with varying contaminations and one type of polyester fiber. Following several preparation steps, various composite materials were manufactured and compared to bulk PE using various testing methods: Differential Scanning Calorimetry analysis (DSC), mechanical testing (flexural and tensile), and laser flash analysis (LFA). The results revealed alterations in the mechanical properties of the composite materials in comparison to PE filled with CB. The LFA tests demonstrated the effectiveness in reducing polymer thermal diffusivity at higher temperatures, particularly when the material was loaded with recycled polyester fillers. Full article
(This article belongs to the Special Issue Composites: A Sustainable Material Solution)
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<p>Shredded textile waste: polyester fabric (<b>a</b>) and PA textile (<b>b</b>).</p>
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<p>Specimens of PA321-PE composite produced from the injection mold.</p>
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<p>A schematic representation of the production process.</p>
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<p>The stress–strain curves from the tensile tests for each material.</p>
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<p>Rupture profile for the PE + PA321 (<b>a</b>) and the PE filled with CB (<b>b</b>).</p>
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<p>The force–position curves of the bending tests for each material.</p>
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<p>The thermal diffusivity of the PE-based composites at various temperatures.</p>
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18 pages, 4603 KiB  
Article
Modelling the Flow in the Utah FORGE Wells Disrete Fracture Network
by Pouria Aghajannezhad and Mathieu Sellier
Fluids 2024, 9(10), 229; https://doi.org/10.3390/fluids9100229 - 30 Sep 2024
Viewed by 371
Abstract
The focus of this paper is the efficient numerical solution of the fluid flow in the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) reservoir. In this study, the public data available for Discrete Fracture Networks (DFN) around well 58-32 is used [...] Read more.
The focus of this paper is the efficient numerical solution of the fluid flow in the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) reservoir. In this study, the public data available for Discrete Fracture Networks (DFN) around well 58-32 is used to represent the DFN. In this research, a novel computationally efficient method called Hele-Shaw (HS) approximation is used for modeling fluid flow in FORGE well. An analysis of the influence of fracture intensity in a network is carried out using the HS method. The HS method was validated by solving the full Navier–Stokes equations (NSE) for a network of eight fractures. A good agreement was observed between the evaluated results (average deviation of 0.76%). Full article
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<p>Location of the FORGE site [<a href="#B4-fluids-09-00229" class="html-bibr">4</a>]. (<b>a</b>) Topological map and (<b>b</b>) the location of well 58-32.</p>
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<p>Geological map of the Utah FORGE site based on previous works [<a href="#B17-fluids-09-00229" class="html-bibr">17</a>].</p>
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<p>Bearings of the azimuth compass on the left. Bearings of the quadrant compass on the right [<a href="#B32-fluids-09-00229" class="html-bibr">32</a>].</p>
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<p>Definition of strike and dip. The blue plane is the plane of interest.</p>
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<p>Definition of (<b>a</b>) trend, plunge and (<b>b</b>) pitch.</p>
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<p>The DFN model region of FORGE. (<b>a</b>) The boundaries of the reservoir. (<b>b</b>) The classification of the lithology [<a href="#B7-fluids-09-00229" class="html-bibr">7</a>].</p>
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<p>Location of the production and injection wells (<b>a</b>). Cross-sectional view of the network (<b>b</b>). The boundary condition for pressure inlets is created by choosing the interaction edges between the injection well and fractures (the blue edges in <b>b</b>). Similarly, the interaction between the production well and fractures are prescribed as pressure outlets. The dimensions of all fractures were imported from available public data [<a href="#B39-fluids-09-00229" class="html-bibr">39</a>].</p>
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<p>Mesh diagram of FORGE network. Here are two views: (<b>a</b>) standard and (<b>b</b>) the reflection of skewness over fractures.</p>
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<p>Mesh independency analysis of 350 fractures flow rate against the number of elements.</p>
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<p>The configuration of validation case and boundary conditions. There are blue and orange arrows that represent constant pressure Dirichlet inlets and outlets, respectively. A global pressure difference of 1.0 <math display="inline"><semantics> <mrow> <mo>×</mo> <mspace width="3.33333pt"/> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>7</mn> </mrow> </msup> </mrow> </semantics></math> (Pa) was applied for this verification.</p>
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<p>Pressure distribution obtained using (<b>a</b>) HS approximation (<b>b</b>) NSE. (<b>c</b>) Percentage of deviation between the evaluated pressure by the HS and NSE over Fracture 4.</p>
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<p>Random removal of fractures from different regions of the network. Blue-colored fractures are indicating the removed fractures from the network. Each network are representing the number of removed fractures (<b>a</b>) 43, (<b>b</b>) 57, and (<b>c</b>) 72.</p>
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<p>The utilized clip plane along the network for counting the number of fractures for calculation of fracture frequency (P<sub>10</sub>). The length of the network is 1000 m.</p>
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<p>Measurements of fracture frequency (P<sub>10</sub>) and flow rate along the reservoir.</p>
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<p>The section of the Hele-Shaw cell on x-z plane.</p>
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<p>The location of HS cell for making the comparison with the results of solved NSE.</p>
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15 pages, 6146 KiB  
Article
An Analytical Solution for Characterizing Mine Water Recharge of Water Source Heat Pump in Abandoned Coal Mines
by Kun Tu, Xiaoqiang Pan, Hongwei Zhang, Xiang Li and Hongyi Zhao
Water 2024, 16(19), 2781; https://doi.org/10.3390/w16192781 - 30 Sep 2024
Viewed by 398
Abstract
Due to tremendous mining operations, large quantities of abandoned mines with considerable underground excavated space have formed in China during the past decades. This provides huge potential for geothermal energy production from mine water in abandoned coal mines to supply clean heating and [...] Read more.
Due to tremendous mining operations, large quantities of abandoned mines with considerable underground excavated space have formed in China during the past decades. This provides huge potential for geothermal energy production from mine water in abandoned coal mines to supply clean heating and cooling for buildings using heat pump technologies. In this study, an analytical model describing the injection pressure of mine water recharge for water source heat pumps in abandoned coal mines is developed. The analytical solution in the Laplace domain for the injection pressure is derived and the influences of different parameters on the injection pressure are investigated. This study indicates that a smaller pumping rate results in a smaller injection pressure, while smaller values of the hydraulic conductivity and the thickness of equivalent aquifer induce larger injection pressures. The well distance has insignificantly influenced the injection pressure at the beginning, but a smaller well distance leads to a larger injection pressure at later times. Additionally, the sensitivity analysis, conducted to assess the behavior of injection pressure with concerning changes in each input parameter, shows that the pumping rate and the hydraulic conductivity have a large influence on injection pressure compared with other parameters. Full article
(This article belongs to the Special Issue Innovative Technologies for Mine Water Treatment)
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<p>An overview of geothermal energy extraction with heat pump technology from an abandoned coal mine.</p>
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<p>The schematic showing a geothermal energy extraction system in an abandoned coal mine.</p>
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<p>Comparison of the analytical solution in this study with the results of Ma et al. [<a href="#B46-water-16-02781" class="html-bibr">46</a>].</p>
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<p>The variations of injection pressure for different pumping rates.</p>
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<p>The variations of injection pressure for different well distances.</p>
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<p>The variations of injection pressure for different specific storages.</p>
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<p>The variations of injection pressure for different hydraulic conductivities.</p>
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<p>The variations of injection pressure for different thicknesses of equivalent aquifer in goaf.</p>
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<p>The normalized sensitivity of injection pressure to selected parameters.</p>
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