Recovery System Research Articles

Wearable damaged clothing fabric image recognition system based on image restoration algorithm

With the improvement of people's living standards and the rapid growth of national technological strength, wearable devices have gradually integrated into people's daily lives, making them convenient for people's work and lives. Traditional fabric detection methods often rely on manual visual inspection, which has low efficiency and accuracy that does not meet the requirements. In view of this, the research has innovatively integrated GAN, CNN, field Programmable gate array (FPGA), multi-stage image recovery algorithm based on graph neural network, for high frequency and low frequency fusion, and combined it with wearable devices to develop a new wearable fabric recovery and recognition system. The results showed that in the COCO dataset, after 250 iterations, the WFR2S algorithm achieved a damage identification accuracy of 95.5 %, a mean absolute error of 0.011, a real-time processing speed of 30 fps, and a resource consumption of 2.4 W. These data demonstrate the significant performance advantages of WFR2S in image recovery and damage detection. The newly developed image recovery algorithm improves the accuracy, availability and stability of damage recognition in garment fabrics. This study not only has theoretical value but also has broad application prospects in practical application. The aim is to contribute to the intelligent development of the garment industry.

Insights into anode substrate optimization in bioelectrochemical systems for efficient cathodic lanthanum recovery during wastewater treatment

Wastewater containing lanthanum (La) is a significant global environmental concern, prompting the development of various treatment technologies. Existing methods are often costly, generate secondary waste streams, and prioritize removal over recovery. This study investigated La recovery in bioelectrochemical systems (BESs) using diverse substrates (acetate, lactate, methanol, and glucose) with anaerobic sludge as the inoculum. The results showed that acetate-fueled BESs achieved the highest power density (439.29 mW/m2), a chemical oxygen demand (COD) reduction efficiency of 96.52 ± 1.56 %, and a coulombic efficiency of 35.18 ± 1.86 %. Acetate and lactate-fed biofilms achieved high La recovery rates (98.96 ± 1.64 % and 98.24 ± 2.16 %, respectively) by the 36th hour. After 48 h, La was undetectable in these systems, surpassing the environmental guidelines. In contrast, methanol and glucose-fed systems yielded lower recoveries (80 ± 0.04 % and 32.8 ± 1.4 %, respectively) after 48 h, with final La concentrations remaining above the guideline levels. Acetate also enhanced the production of extracellular polymeric substances (EPS). Microbial community analysis revealed that Desulfovibrio and Geobacter predominated in acetate-fed microbial fuel cells (MFCs), while Klebsiella and Simplicispira were dominant in glucose and methanol-fed MFCs, respectively. Recovered La deposits, identified as La2O3 and La(OH)3, on the cathodic surfaces were confirmed via SEM-EDX, XRD, and XPS analyses. This study demonstrates the potential of BESs for efficient La recovery from wastewater.

Integrating machine learning and thermodynamic modeling for performance prediction and optimization of supercritical CO2 and gas turbine combined power systems

The supercritical carbon dioxide (SCO2) cycle has drawn attention to extracting energy and generating power from low-grade heat resources due to its higher efficiency, lower cost, and compactness. Combining the SCO2 cycle with a gas turbine (GT) is a promising field of research with applications in industries such as waste heat recovery (WHR) systems. In this research, three different configurations of power generation SCO2 cycles, including recuperation, precompression, and reheating, were thermodynamically designed and modeled. Extracting the main parameters of cycles, and the appropriate objective, which is cycle energy efficiency, up to 80,000 data constructed. Random forest (RF) and support vector regression (SVR), machine learning (ML) techniques, are used for the performance prediction of cycles. The results show the strength of the RF method to predict the cycle efficiency with up to 3% error and the SVR method with more than 90% accuracy. Sensitivity analysis and Particle Swarm Optimization (PSO) algorithm are employed for optimizing the recuperation cycle. The outcomes of the optimization model, based on the prediction models as proxies, have results in nearly close to those of traditional optimization, which is based on a thermodynamic model. In conclusion, ML models can be used in industry for prediction and maintenance since the methods are up to 5 times faster than thermodynamic models.

Rotary kiln simulation for energy recovery: The precalciner cement kiln case

Cement production process is energy intensive both in terms of the thermal and electrical energy. In fact, energy demand accounts for about 40 % of operational costs. Significant heat losses are present even in modern plants, affecting negatively both on production costs and emissions. These losses are mainly due to the sensible heat in the hot flue gases and exhaust air streams used for cooling down the clinker (35 % of the process heat losses). Given the good quality of the available sensible heat in these streams (temperatures above 280 °C), a heat recovery system can be considered to increase the overall efficiency of the cement plant. The aim of this work is to create a simplified model of a cement rotary kiln to study the heat recovery optimization. Results were consistent with the temperature, pressure and flowrates ranges indicated in the literature. The model here proposed can be adapted to simulate other processes involving a rotary kiln. As a result of the study of the proposed case scenario, the plant was found to potentially generate 3.2 kWh/ton of clinker of electricity, equivalent to approximately 20 % of the total plant electrical consumption.

Thermal and electrical performance analysis of a lightweight micro CHP system for recreational vehicles

For comfortable use of a Recreational Vehicle (RV), there is a need to supply electrical energy to recharge the batteries and supply the installed equipment, as well as thermal energy, for hot water and ambient heating. A conventional solution for supplying electrical energy is the installation of photovoltaic modules combined with connection to an electrical grid, when possible. Water heating is generally done using a passage gas heater or hybrid gas/electric storage heater. Imported vehicles have gas heating and many other vehicles have diesel heaters. To develop an alternative to currently available energy supply methods, this work proposes the creation of a cogeneration system for RVs. From a literature review, a research gap was identified in relation to micro CHP devices for RVs. In the development of this work, a micro CHP prototype was created, with 980 W of maximum electrical power, consisting of a single-cylinder internal combustion engine, an automotive alternator and heat exchangers for heat recovery. The prototype was enclosed and instrumented, allowing to evaluate the thermal power obtained in water flowing through exhaust gases, lubricating oil and cooling air heat recovery systems, in addition to measuring the electrical power of the alternator. Operational tests were carried out with 46 different test conditions, combining variations in the engine speed (N) and in electrical load. The prototype electrical efficiency reached 10.18 % ±0.2 % at 3008 rpm with 83 % load. The maximum electrical power was 0.746 kW±0.015 kW at 3637 rpm and 100 % load. The maximum thermal energy recovery rate was 3.267 kW±0.039 kW. Utilization factor reached 65.57 % ±0.33 % at 3208 rpm with 63 % load. Compared to traditional means of providing electrical power and thermal power for RVs, the prototype proved to be more advantageous when the demand is for electrical power and space heating. However, for conditions in which the demand is for electrical power and water heating, or just electrical power, the current solutions available are still more efficient.

Improvement of Air Purification and Heat Recovery Systems for Industrial Emissions

Improvement of Air Purification and Heat Recovery Systems for Industrial Emissions

Physics-based machine learning optimization of thermoelectric assembly for maximizing waste heat recovery

With the increasing energy consumption of data centers around the world, the recovery of low-grade waste heat in data centers has become increasingly important. To maximize the waste heat recovery of thermoelectric modules in data centers, physics-based machine learning optimization of the thermoelectric assembly was carried out. A theoretical model and machine learning model of a fan-heat sink-thermoelectric generator system for waste heat recovery were proposed for predicting the performance of a thermoelectric assembly. Genetic algorithms were used to find the best heat sink geometric parameters for the possible greatest power generation. Given a temperature difference constraint of 75 °C between the heat source and the environment, the greatest output power from the thermoelectric assembly was 3.836 (watts), with the optimal plate fin height of 60 (mm), 50 fins, and 1.7 (mm) of fin pitch over a 120 mm × 120 mm area under the determined parameters of the thermoelectric module with a 120 mm cooling fan. In addition, by comparing different machine learning algorithms, the results revealed the superiority of random forest regression in solving optimal problems. This work provides a convenient and practical means for the fast optimization of thermoelectric assembly.

Numerical analysis and evaluation of a tropical classroom for thermal comfort, indoor air quality, and energy consumption using ventilation with air-to-air total heat recovery system (MemHEX)

ABSTRACT Lecture rooms in the Philippines often experience unfavourable temperatures and elevated carbon dioxide (CO2) concentrations, impacting the well-being, health, and learning efficiency of both students and educators. This research seeks to evaluate the thermal comfort, indoor air quality, and energy usage in a standard Philippine lecture room by implementing a membrane-type total heat exchanger (MemHEX). The research used computational fluid dynamics (CFD) simulations, which were validated by field measurements and showed the effectiveness of the MemHEX. Energy consumption was modelled using EnergyPlus to compare potential impacts of various ventilation approaches. Room temperature and humidity fall short of thermal comfort standards, suggesting the need for a higher-capacity air conditioning unit (ACU). Average CO2 concentration exceeds 1000 ppm, signalling a demand for ventilation. Post-MemHEX installation, temperature and humidity slightly rise with increased air changes per hour (ACH), introducing warm outdoor air. Indoor air quality improves with rising ACH, reducing CO2 levels by exchanging fresh outdoor air. Comparing mechanical ventilation and MemHEX reveals MemHEX as more energy-efficient, maintaining better indoor conditions. These findings provide valuable insights for the field of research by demonstrating the feasibility and benefits of using MemHEX to improve the indoor environment and energy efficiency of a typical Philippine classroom.

Electric Taxiing System. Kinetic Energy Recovery System as an Electric Taxiing Solution: Economic and environmental analysis: Phenom 300 case study

The aviation industry has thrived in recent years, with a significant increase in passenger numbers, leading to the development of larger aircraft fleets and the expansion of airport infrastructure. In 2019, more than 4.5 billion passengers traveled by airplane, which represents an 80% increase compared to 2009. As a consequence, this growth has also resulted in longer taxiing times for aircraft, increasing fuel consumption and operational costs. The industry's CO2 emissions have quadrupled since the 1960s, with over 1 billion tons released in 2019, contributing to global warming. Given that the improvements being made to current propulsion systems and the production of over 600 million liters of SAF (Sustainable Aviation Fuel) in 2023 do not seem sufficient to meet the ambitious goals set by regulators and operators, the logical solution would be to develop a system capable of moving the aircraft on the ground using alternative, cleaner, and cheaper energies, such as electric power. This paper explores the latest advancements in electric propulsion systems, specifically focusing on external and onboard systems. After the state of the art is established, this paper will cover a case study and propose a new alternative for an onboard system called ETS – Electric Taxiing System. The ETS is a 100% electric system for ground handling operations designed to use only the kinetic energy stored in a battery pack, which is recovered during aircraft landing and braking events. Although there are some studies on this topic, the author considers this paper to be more comprehensive as the results computed here take into account 96 variables, 60 simulations, several flight plans, and real-world data. The case study focuses on the implementation and dimensioning of the ETS, considering electric motor power and torque, and battery capacity for the Embraer Phenom 300. A brief economic and environmental analysis was also conducted, considering the operation of NetJets Europe, the world's leading and largest private jet company.

Research on double‐USVs fuzzy‐priority NSB behavior fusion formation control method for oil spill recovery

AbstractReplacing manned ships with unmanned surface vehicle (USV) for oil spill containment can reduce the consumption of manpower and resources. This article studies the formation control method of dual USVs during the process of capturing oil spill, based on the engineering background of towing oil boom by dual USVs oil spill recovery system. To calculate the drag force of the oil boom acting on the USV, the shape of the oil boom is simplified into a catenary, the oil boom is modeled, and the hydrodynamic numerical simulation is carried out. To address the issue of “winding” phenomenon and “towing separation,” the formation behavior is designed when double USVs are towing oil fences to capture oil spill. In response to the problem of low task execution efficiency caused by fixed behavior priority in traditional null‐space‐based (NSB) behavior fusion methods, a fuzzy‐priority NSB (FNSB) behavior fusion formation method is proposed by combining fuzzy control with NSB behavior fusion method. In the FNSB behavior fusion formation control method, a smooth transition rule is introduced to make the behavior priority change, USVs can still maintain good formation performance, ensuring the smooth execution of oil spill recovery tasks. Simulation shows that FNSB behavior fusion formation method based on flexible transition rules can improve the rounding efficiency by 26.6% in the environment without obstacles and 37.2% in the environment with multiple obstacles compared with the NSB method. The effectiveness and practicality of this method have been verified through simulation experiments and field experiments on the “Dolphin” series of small USVs.

Design and Implementation of Iron-Based Electrochemical System for Simultaneous Carbon Capture and Hydrogen Gas Recovery

The catastrophic results of climate change and energy crisis, such as the rise in wildfires, floods, and ecosystem disruptions highlight the critical need of urgent and innovative global-scale solutions for carbon dioxide (CO2) removal (CDR). Ocean-based CDR methods, leveraging the ocean's capacity as a large sink to sequester up to 30% of emissions, offer a great promise. Yet, implementing and testing marine CO2 removal (mCDR) techniques such as ocean iron fertilization (OIF) or ocean alkalinity enhancement (OAE) face significant challenges. To overcome these challenges, a novel self-operating electrochemical technology is designed and presented in this work. The proposed technology, namely electrochemical OIF (EOIF), does not only combine OIF and OAE, but also recovers hydrogen gas (H2) from seawater, offering a promising solution for achieving quantifiable and transparent large-scale mCDR. The EOIF design s focused on employing Fe/Fe-producing anodes to eliminate the production of acids at the anode in traditional electrochemical OAE systems and replace it with Fe release, where the cathode can be made from naturally abundant cost-effective materials, such as carbon. The obtained results show that the EOIF system can be implemented to increase both the concentration of ferrous iron (Fe+2) by 0-0.5 mg/L, and the seawater pH by 8% (i.e., 25% decrease in the hydrogen ions concentration). It also offers the flexibility to optimize the release of iron (Fe+2/Fe+3) by adjusting the magnitude of the electric current in the systems, as well as by optimizing the electrode material and geometry. In certain ocean regions, enhanced iron concentrations stimulate the naturally occurring biological carbon pump (BCP), leading to increased phytoplankton growth, CO2 uptake, and subsequent export of carbon to the deep ocean. Simultaneously, the system increases seawater alkalinity and the buffer capacity, enhancing CO2 solubility and storage in the shallow ocean through the solubility pump. The techno-economic assessment shows that the combined advantages of the EOIF system can lower the mCDR cost by more than 95% compared to the traditional methods. The obtained measurements demonstrate the scalability of EOIF and its ability to operate using solar energy at a lower cost. Overall, the proposed EOIF technology offers a practical, effective, and sustainable solution for addressing climate change and energy recovery on a large-scale.

Insights into the Significance of Ternary Hybrid Nanofluid Flow Between Two Rotating Disks in the Presence of Gyrotactic Microorganisms

The ecology of marine life and other biotic processes, such as septicity, are influenced by the drive of microorganism cells in the fluid. Considering the transference mechanism in nanofluids including a microbial suspension is imperative for several chemical and medical applications. This study examines the bioconvection of an Al2O3-Graphene-CNT/water ternary hybrid nanofluid between two infinitely parallel spinning disks in a porous media under the influence of heat source/sink and radiation. The Cattaneo–Christov model has been employed to inspect the transference mechanism of mass and heat. The MATLAB function “bvp4c” is used to numerically tackle the governing equations. The relationship between the most relevant variables and the motile microorganism’s density, velocity, temperature, concentration of nanoparticles and other characteristics is graphically represented. Last, figures are provided to illustrate how several important elements relate to the Nusselt and Sherwood number, and local motile microbe density number. The heat transfer rate is seen to be higher at the upper disk than at the lower disk. A rise in the volume fraction of nanoparticles causes the heat transfer rate at both disks to increase. The outcomes of this study will be useful for a wide range of architectural designs, transportation systems, oil recovery systems with microbes, medical sectors and other industries that utilize nanofluids.

Electrochemically-Driven Reversible Catch and Release of Rare Earth Elements

The sustainable recovery of critical materials, such as rare earth elements (REEs), from dilute and non-traditional sources is pivotal for securing a reliable domestic supply. Using environmentally friendly methods is necessary to maximize the economic and sustainability benefits. One of the most promising approaches is the electrochemically controlled recovery of REEs, which becomes even more compelling when integrated with renewable energy sources. We developed a groundbreaking electroactive material with an exceptional affinity for REEs in their trivalent state. This material demonstrates a remarkable ability for highly reversible binding and release of REEs, controlled by the redox state of the material. We will present the REE recovery system's design principles and performance characteristics, mainly focusing on its efficacy in extracting REEs from dilute sources and structure-property relationships.

Genetic algorithm-based optimization of combined supercritical CO2 power and flash-tank enhanced transcritical CO2 refrigeration cycle for shipboard waste heat recuperation

The shipping industry significantly contributes to global trade and economy, but is also responsible for approximately ∼3 % of global greenhouse gas (GHG) emissions. Harnessing waste heat from marine vessels to perform useful work is a potential solution to reduce these emissions. Although the Organic Rankine Cycle (ORC) and CO2 cycles have been studied separately for waste heat recovery, a combined power and refrigeration systems, utilizing both cycles have not been reported. Herein, a combined system, “Marine Energy Recovery System (MERS)”, that integrates the supercritical CO2 Brayton power cycle with a flash-tank-enhanced transcritical CO2 refrigeration cycle, is proposed, aiming to generate power and provide cooling simultaneously. The power cycle incorporates an ORC, and a flash-tank is introduced within the refrigeration cycle to improve system performance. Both cycles share a low-temperature recuperator and a gas cooler to further utilize the heat between them. The MERS is evaluated from both a 1st and 2nd law perspective against various performance metrics under different operating conditions, such as: gas cooler pressure, evaporation temperature, and turbine inlet temperature and pressure. Results elucidated that the MERS achieved energy and exergy efficiencies of 54.62 % and 54.90 %, respectively, representing significant improvements over similar systems. The net work output improved by 717.55 kW and the net cooling capacity by 515.7 kW relative to the reference system. Furthermore, a COP of 2.99 outlines its potential as a cooling system. To further enhance MERS’s performance, a multi-objective optimization approach is employed, utilizing Artificial Neural Network (ANN) and Genetic Algorithm (GA). Optimal operational conditions yielded an energy efficiency of 74.95 % while maintaining a net work output of 6890.55 kW with gas cooler pressure, turbine inlet temperature, and gas cooler outlet temperature being 9.5 MPa, 461.76°C and 50°C respectively. These findings support the reliability and improved design of the MERS for future marine applications.

Consensus Control of Heterogeneous Uncertain Multiple Autonomous Underwater Vehicle Recovery Systems in Scenarios of Implicit Reduced Visibility

This paper investigates consensus control in heterogeneous and uncertain multiple autonomous underwater vehicle (AUV) systems under implicit reduced visibility conditions. We address challenges such as environmental uncertainties and system nonlinearity by utilizing a unified connectivity approach to model low-visibility interactions and heterogeneous multi-AUV dynamics. Our main contributions include developing a feedback linearization model for heterogeneous multi-AUV systems that accounts for uncertainties, introducing an adaptive consensus controller based on relative positioning that effectively manages implicit visual interaction limitations and validating our strategies through stability analysis and numerical simulations. Our simulations demonstrate approximately a 60% improvement in accuracy compared to previous algorithms, highlighting the practical value of our approach in AUV recovery operations. These advancements provide a robust solution for consensus control in complex underwater environments.

CIGALE: an innovative gas neutralizer based high efficiency neutral beam injector concept for future fusion reactors

This paper outlines the main features of a new high efficiency (η > 62%) high power (∼18 MW D0) neutral beam (NB) concept based on pragmatic solutions suitable with the reactor requirements. The injector is modular (several beamlines in parallel) with independent ion sources referenced to the ground potential and gas neutralizers held at +1 MV. This topology leads to numerous simplifications; it overcomes the main issues of conventional NB systems, such as the complex 1 MV electrical setup, the difficult ion source remote maintenance, the high caesium consumption. The other key parameter is the gas neutralization concept which minimizes the amount of gas by operating at a low gas target and low neutralizer duct conductance. The implementation of an energy recovery system for the residual 1 MeV D− is essential to attain a high wall-plug efficiency. These specific features require thin laminar D− beams provided by a pre-acceleration up to 100 keV in slotted grid apertures to form thin blade-like beamlets, followed by the post-acceleration to 1 MeV by merging the beamlets in a single beam in five gaps (+200 kV per gap). All these specific aspects minimize the beams losses and thermal loads along the beamline and enhance the injector reliability and availability.

Avoiding future surprises after acute shocks: long-term flood risk lessons catalysed by the 2021 summer flood in the Netherlands

In summer 2021, the Dutch Province of Limburg faced an acute high-water event caused by two days of heavy rainfall, resulting in €383 million worth of damage. Afterwards, various policy actors organised a number of evaluations. This study analyses these evaluations and the long-term lessons drawn from this flood event. Dealing with climate change requires insights into how lessons from acute shocks such as floods can stimulate the anticipation of climate change and solutions that can cope with future extremes. This study therefore applies policy learning theory—single, double and triple loop learning—to different layers of flood safety to analyse the extent to which governments prepare for future events and how.The results show that pre-2021 water and flood risk management policies—our point of comparison to derive what lessons emerge after the 2021 flood—focused mostly on flood prevention (layer 1) and from 1996 onwards with the start of the Room for the River programme also on spatial planning (layer 2), without paying much attention to crisis management (layer 3). Based on the 2021 flood, the official evaluation committee recommends adding two more layers to the multilayer flood safety approach: increasing water awareness (layer 0 as a base layer for the other layers) and focusing on climate-robust recovery after floods (layer 4) to improve long-term robustness. Based on our research, triple-loop learning as the deepest type of learning appeared in the form of applying the Room for the River approach to the tributary brooks systems. To prepare for the future, policy evaluations recommend improving stress tests to better deal with climate change. Futures scenarios and visions for the future are also recommended. Creating future visions can help to steer changes in existing land use and re-think areas to build or to use for water retention, for example. Governments are advised to strengthen their anticipatory capacities as part of their crisis management response and recovery systems. Furthermore, governments will need to apply the different layers for multilayer safety in an integrated way to ensure that regions are able to prepare for future floods.

Technological and economical analysis of the heat recovery system from flue gas in a thermal waste treatment plant

A heat recovery system from flue gas increases the overall efficiency of a district heating or CHP plant, as the system recovers the waste energy contained in the flue gas at the chimney outlet. This makes it possible to increase thermal energy production with the same fuel consumption. A method for calculating the thermodynamic parameters of municipal waste incineration plants was developed as part of the work carried out. The mathematical models prepared made it possible to analyse the impact of the heat recovery system from flue gas on technical and economic parameters and the environment, including, among other things, an estimate of the annual amount of heat recovered, the amount of additional electricity consumed, the amount of condensate treated, the estimated capital expenditure, operating profits and operating costs. The results of the analyses were the basis for designing and constructing a heat recovery system from flue gas equipped with a condensation heat exchanger for the municipal waste incineration plant in Cracow. The calculation results were compared with the measurement results obtained during the test run of the constructed installation.

Emergoenvironmental analysis and sustainable flexible peaking of a novel solar-assisted solid oxide fuel cell cogeneration system

The development of green and sustainable conversion technologies is imperative to alleviate the current severe energy and environmental crises and to achieve the goal of carbon neutrality. This project presents a novel cogeneration system that integrates a solid oxide fuel cell afterburning system, an energy recovery system, and a parallel heating system equipped with multistage utilization, solar-assisted, and flexible peaking technologies. Following the establishment and validation of the system, power source analysis, parameter sensitivity studies, three-objective optimization, and internal exergy flow investigation are carried out. Subsequently, the positive impacts of multistage utilization, solar-assisted, and flexible peaking technologies, as well as the thermoeconomic and emergoenvironmental operating characteristics of the system, are discussed. The numerical results demonstrate that the emergoenvironmental factor and emergy environmental impact difference of the system are 70.15 % and 82.52 %, and the energy efficiency is improved by 1.41 %∼19.09 %, respectively, compared with similar solid oxide fuel cell systems, confirming its favorable thermodynamic performance and emergoenvironmental impact. The system achieves daily heating savings of 3302 kWh and life cycle economic benefits of $19,310,524, with a repayment of the investment cost in 4.17 years, reflecting considerable economic benefits. This project also demonstrates exergy flow, module defects, and improvement mechanisms from the perspective of emergoenvironmental, providing a valuable reference for the promotion of green energy.

Sustainable wastewater recovery system employing geothermal energy – Performance and feasibility study

In this study, a sustainable wastewater recovery system employing geothermal energy has been proposed. The efficiency of the suggested sustainable system has been simulated using heat transfer. Then, component-wise validation has been carried out with the existing data available in the literature wherever applicable and estimated an error of ± 8 %. The proposed sustainable system’s parametric and performance analyses have employed the developed vapor. From the parametric study, it is observed that hot spring temperatures have a significant influence on sustainable systems. Further, through performance investigation, it is understood that low dam/river/sea water temperatures and enhancing the water condenser effectiveness and flow rate ratio simultaneously improve the system performance. For different climatic regions of India, explored the feasible geothermal hotspots near dams/rivers/seawater and analyzed that among the hot and dry, hot and humid, composite and cold regions, the proposed sustainable system is best suitable at a composite region with a maximum possible water extraction/freshwater generation rate of 0.78 L/h for the given specifications and operating range. Moreover, it is assessed that hot spring temperature is the deciding factor for sustainable system performance in different climatic regions. Further, the current study can be used as a reference for understanding the phenomenon of potential geothermal hotspots for wastewater recovery in various climatic areas