, Narapong Hongprasith

• 2016

Paddle wheels are widely used in aquaculture pond in Thailand due to convenient installation and operation, with an ability to supply oxygen together with making water circulation as their advantage. But the low oxygen transfer efficiency (OTE) and energy performance (Aeration efficiency, AE) should be considered as the main drawback of this aerator type, because they can make a contacting area between air (oxygen) and water at the water surface only. While diffused aerators present a high OTE and AE. However, their mixing performance in the vertical direction is not enough for a large aquaculture pond. Then it is necessary to apply another equipment to perform water flow or horizontal water circulation, such as axial propellers, water pump, or paddle wheels. To fulfill this gap, a combination aeration system was setup by combining the diffused aerators and water pumps: diffused aerators play the role for an oxygen transfer mechanism, while water pumps creating a horizontal circulation for the oxygen distribution. It was found that the highest AE (0.47 kg-O2/kW-hr) was obtained when applying 57 mm/s of the horizontal water velocity during the aeration by 2 sets of the flexible rubber tube diffuser. This AE value was closed to 0.51 kg-O2/kW-hr of 3 sets of diffusers, and higher than a system contained by 2 units of 60W water pumps, (which represented as a paddle wheels system) up to 47 times. The uniform DO distribution was obtained by 57 mm/s of the horizontal water velocity, and the improvement of oxygen transfer was obtained by reducing of bubble size (dB) and their rising velocity (UB) which can produce more interfacial area (a-area) up to 278%. Moreover, both of oxygen transfer parameters and bubble hydrodynamic parameters can be predicted accurately by the theoretical prediction models with an error lower than 10% for the combination aeration system that can be used as a criterion for the aeration system design.

, Preety Aneja

Journal of Advanced Research in Alternative Energy, Environment and Ecology • 2023

Solar energy is one of the richest source of renewable energy on Earth, thus its harnessing is very much necessary for the useful conversion of light energy into electric energy. Solar panels are developed in this direction. Many scientists have developed various methods to gather the solar irradiation in order to maximize the extraction of electric power from the Photovoltaic generators. However, the problem with the solar power is that it is directly dependent on light intensity. The main hindrance with solar panels is their low efficiency with huge investment. Studies show that a solar panel converts 20-40% of energy incident on it to electrical energy. The solution is to use a tracking system1, 7 that maintains the panel’s position orthogonal with the light source. There are many tracking systems designs available including passive and active systems with one or two axes of freedom.8, 9 It has been found that the overall efficiency gain in single-axis solar tracker designed in10 is 27% than that of fixed mechanism. We had optimised the tracker efficiency by performing the experiment with solar tracker for consecutive three days and thus results were analysed by using stat-ease software. Moreover, the testing showed that the power used by the tracking system was much less than that of power gained by tracking system. While working on the developed set-up, focus was given on the incremental efficiency of the solar power generation system. In the present work, further performance analysis is taken up with the help of various parameters viz. Specific Energy Production (SEP), Performance Ratio (PR), Ground Cover Ratio (GCR) and Surface Performance Ratio (SPR)11 to further elaborate the efficiency enhancement in solar trackers as compared to fixed systems.

Khaya Pearlman Shabangu, Nhlanhla Mthembu, Manimagalay Chetty et al.

International Journal of Energy Research • 2024

Owing to the depletion of fossil fuels, rising energy costs, and environmental pollution, there has been a growing focus on exploring and exploiting renewable energy sources. This study aims to demonstrate the modeling of a grid‐connected double‐chamber microbial fuel cell (DCMFC) biomass energy system via MATLAB Simulink software. The experimental measurements obtained from DCMFC outputs served as the basis for developing the inverter‐grid connection model and simulation output in MATLAB Simulink software. Briefly, the DCMFC DC boost voltage was connected to the positive and negative buses of the three‐phase DC‒AC inverter circuit, with switching patterns controlled by gate pulses in each transistor. Full square wave single‐stage PWM pulses are generated by the gate for control. The power generated by the inverter was measured via a three‐phase VI block for analysis, with voltages and currents displayed via a scope. To address potential noise during switching, an LC filter is employed to suppress noise output and stabilize power generation. Another power meter measures power from the grid, with waveforms displayed via scope blocks. Before synchronization between power from the DCMFC and the grid occurs, four requirements must be met: the grid voltage must match the inverter output voltage, the inverter frequency must match the grid frequency, the phase sequence must be the same, and the phase angle of the inverter must match that of the grid. Additionally, Institute of Electrical and Electronics Engineers (IEEE)‐specific requirements were evaluated during the simulation for this study. In addition, this study critically examined whether the DCMFC inverter model conforms to conventional requirements, International Electrotechnical Commission (IEC) standards, and IEEE standards for the integration of inverters into the grid. Compared with previous studies on inverter modeling for grid connections, past studies have emphasized the efficacy of biomass power plants and different inverter topologies for photovoltaic (PV) systems. The current study focuses on optimizing a multilevel inverter‐based model, achieving low total harmonic distortion (THD) below IEEE standards. In this study, the use of a multilevel inverter configuration proved highly effective in reducing the harmonic content, leading to synchronized phase sequences and enhanced coherence between the grid and inverter voltages. With a THD of 4.75% at 50 Hz, supported by a harmonic distortion value of 422.5, the chosen configuration significantly minimized the harmonic distortion. This success underpins the system’s reliability and efficiency, offering promising implications for practical applications.

Anoud Saud Alshammari, Ghada Mohamed Aleid, Alamri Rahmah Dhahawi Ahmad et al.

Journal of Chemistry • 2024

Microbial fuel cell (MFC) is a new and interesting technology that can be used to treat wastewater without using electricity. The current research focuses on electron generation, which is one of the technique’s major challenges. According to the latest literature, the study was planned to successfully remove the metals from artificial wastewater at high concentrations and generate electricity. On average, after 18 days of operation, it offered 610 mV with 1000 ῼ constant external resistance. The internal resistance was found to be 520 ῼ. The achieved power density was 3.164 mW/m2 at an external resistance of 1000 ῼ. The achieved removal efficiencies of Pb2+, Cd2+, Cr3+, and Ni2+ were 83.67%, 84.10%, 84.55%, and 95.99%, respectively. The operation lasted for 25 days. The cyclic voltameter studies show that there is a gradual oxidation rate of organic substances, while on day 25, the removal efficiency reached its maximum. The specific capacitance was found to be high between days 15 and 20, i.e., 0.0000540 F/g. It also indicated that biofilm was stable around day 18. Furthermore, the biological characterization also demonstrated that MFC operation was very smooth throughout the process, even at high concentrations (100 mg/L) of metal ions. Finally, there is the MFC method, as well as some new challenges and future recommendations.

Michael A. Yandrasits, Sudha Marimannikkuppam, Matthew J. Lindell et al.

Journal of The Electrochemical Society • 2022

Open circuit voltage tests were conducted on sixteen 3M Ionomer and eight Nafion™ NR211 membranes. Lifetime distributions were determined, and ion chromatography (IC) techniques were used to measure fluoride, sulfate, trifluoro acetate, and oxalate ions. Combustion Ion Chromatography (CIC) was used to determine the total organic fluoride (TOF) associated with water soluble membrane degradation fragments. The ratio of these products relative to the fluoride release rates were used to infer the likely degradation mechanism for each membrane. Peroxide attack at the sulfonic acid side chain was determined to be the least relevant reaction pathway while the long-proposed polymer chain end unzipping appears to be the dominant mechanism. Abstraction of the tertiary fluorine in the NR211 backbone and side chain is evident by organic fluoride release rates higher than can be explained by unzipping alone.

Abdulbaset Abdulhamed Mohamed Nureddin, Javad Rahebi, Adel Ab-BelKhair

International Journal of Photoenergy • 2020

Nowadays, the power demand is increasing day by day due to the growth of the population and industries. The conventional power plant alone is incompetent to meet the consumer demand due to environmental concerns. In this present situation, the essential thing is to be find an alternate way to meet the consumer demand. In present days most of the developed countries concentrate to develop alternative resources and invest huge money for its research and development activities. Most renewable energy sources are naturally friendly sources such as wind, solar, fuel cell, and hydro/water sources. The results of power generation using renewable energy sources only depend on the availability of the resources. The availability of renewable energy sources throughout the day is variable due to fluctuations in the natural resources. This research work discusses two major renewable energy power generating sources: photovoltaic (PV) cell and fuel cell. Both of them provide foundations for power generation, so they are very popular because of their impressive performance mechanisms. The mentioned renewable energy-based power generating systems are static devices, so the power losses are generally ignorable as compared to line losses in the main grid. The PV and fuel cell (FC) power systems need a controller for maximum power generation during fluctuations in the input resources. Based on the investigation report, an algorithm is proposed for an advanced maximum power point tracking (MPPT) controller. This paper proposes a deep neural network- (DNN-) based MPPT algorithm, which has been simulated using MATLAB both for PV and for FC. The main purpose behind this paper has been to develop the latest DNN controller for improving the output power quality that is generated using a hybrid PV and fuel cell system. After developing and simulating the proposed system, we performed the analysis in different possible operating conditions. Finally, we evaluated the simulation outcomes based on IEEE 1547 and 519 standards to prove the system’s effectiveness.

Rasmus Friberg, Rob Winkel, Richard Smokers et al.

3rd International Conference on Fuel Cell Science, Engineering and Technology • 2004

FCTESTNET (Fuel Cell Testing and Standardization Network) is an ongoing European network project within framework program 5. It is a three-year project that commenced 2003, with 55 partners from European research centers, universities, and industry, working in the fuel cell field. The main objective of FCTESTNET is to promote the harmonization of testing procedures and methodologies within the European Union. The lack of standardized test methods for fuel cell technology is a fact. The development of standardized test methods is very important for the commercialization of the fuel cell technology. Standardized test methods are one of the most important instruments in the quality management work of any industrial process. The players that have a common interest to promote and develop harmonized test methods for fuel cell technology are: • Standardization bodies (IEC and ISO); • Fuel cell manufacturing industry (type testing and routine testing); • OEMs (acceptance testing); • Research institutes and universities (R&D). The current work presents one of the core results from the FCTESTNET project, namely a proposal of a harmonized testing format for fuel cell technology. The harmonized testing format has been developed based on a testing model that was proposed in the initial phase of FCTESTNET. The testing model describes the common process steps in testing and has been a valuable tool to communicate testing activities and develop test format within the network. The testing model describes testing in general and fuel cell testing in particular. It is a three-step model. The first step is the planning step and comprises the listing of standardized test methods and other references that are required for the execution of any specific testing activity. The second step of the testing model is the testing execution, which is where the actual testing is carried out. The result of the testing execution is here referred to as test output data or test output. The test output is analysed and compared with input data from the planning step and finally reported in the third step, that is the evaluation step. Some examples of specific test inputs, in the context of fuel cell testing, are temperature, vibration, fuel flow, rain, etc. Examples of specific test outputs are current, voltage, gas emissions, heat, degradation, etc. In professional testing, the internal function of the test object is of secondary importance. The object is to be treated as a “black box”. It is the test output and the test result that are of primary importance. Based on terminology originating from the testing model, such as test object, test inputs, test outputs, etc, a harmonized testing format has been developed and proposed. The key terms in the harmonized testing format are test programme and test module. The test programme is defined as a programme comprising two or more test modules. A test module is a test method defined as the variation of one single test input, for example the testing of power output as function of ambient temperature. Furthermore, a test module comprises the objectives, the scope, the test input varied, the test outputs tested, test object class (fuel cell, fuel cell stack or fuel cell system), test procedure, test report, etc.

Y.‐J. He, Z.‐F. Ma

Fuel Cells • 2016

Abstract Rapidly and accurately modeling of microbial fuel cells (MFCs) plays an important role not only in thorough understanding of the effects of operating conditions on system performance, but also in the successful implementation of real‐time maximization of power output. Although the first principle electrochemical model has better generalization performance, it is often time‐consuming for model construction and is hard to real‐time application. In this study, a nonparametric Gaussian process regression (GPR) model is used to capture the nonlinear relationship between operating conditions and output voltage in the MFCs. A simple online learning strategy is proposed to recursively update the hyper‐parameters of the GPR model. The applicability and effectiveness of the proposed method is validated by both the simulation and experimental datasets from the acetate and the glucose and glutamic acid two‐chamber MFCs. The results illustrate that the online GPR model provides a promising method for capturing the complex nonlinearity phenomenon in MFCs, which can be greatly helpful for further real‐time optimization of MFCs.

Abuzar B. M. Adam, Xiaoyu Wan, Zhengqiang Wang

Applied Sciences • 2019

In this paper, we investigate the energy efficiency (EE) maximization in multi-cell multi-carrier non-orthogonal multiple access (MCMC-NOMA) networks. To achieve this goal, an optimization problem is formulated then the solution is divided into two parts. First, we investigate the inter-cell interference mitigation and then we propose an auction-based non-cooperative game for power allocation for base stations. Finally, to guarantee the rate requirements for users, power is allocated fairly to users. The simulation results show that the proposed scheme has the best performance compared with the existing NOMA-based fractional transmit power allocation (FTPA) and the conventional orthogonal frequency division multiple access (OFDMA).

Necla ALTIN, Başar Uyar

JOURNAL OF CHARACTERIZATION • 2022

Enerji kaynaklarının giderek sınırlı hale geldiği bir çağda, sürdürülebilir ve yenilenebilir enerji üretimi arayışı ön plana çıkmıştır. Mikrobiyal yakıt hücreleri bu arayışın sonucunda ortaya çıkmış ve son yıllarda önem kazanmıştır. Bu hücreler, mikroorganizmaların biyokimyasal reaksiyonları yoluyla organik maddeleri doğrudan elektriğe dönüştürebilme yeteneğine sahiptirler. Bu çalışmada anot bölmesinde at gübresi atık suyu ve kuru mikroalg biyokütlesi substrat olarak, Chlamydomonas sp. mikroalg türü ise katot bölmesinde bir elektron alıcısı olarak kullanılmıştır. Her iki bölmede de grafit keçe elektrot kullanılmıştır. Bu sistemde gerçekleştirilen deneyler sonucunda 29,93 mW/m2’lik maksimum güç yoğunluğu ve 599.6 mV açık devre voltajı kaydedilmiştir. Aynı zamanda % 49,35 KOİ giderimi elde edilmiştir. Bu çalışma, atık su ve mikroalglerin kullanıldığı çift odacıklı mikrobiyal yakıt hücresinin enerji üretim potansiyelini vurgulamaktadır. Chlamydomonas sp. mikroalglerinin katot bölgesinde kullanılması, fotosentetik aktivite sonucu üretilen oksijenin elektron transferinde nasıl kullanılabileceğini göstermektedir. Bu sonuçlar, atık suyun sürdürülebilir şekillerde arıtılması ve aynı zamanda mikroalgler gibi biyolojik organizmaların enerji üretiminde kullanılmasının, çevresel ve enerji alanında umut vadeden bir strateji olduğunu göstermektedir. Bu yöntem, atık yönetimi ile yenilenebilir enerji üretimini bir araya getirerek çevresel sürdürülebilirliğe katkı sağlamaktadır.

Shubham Arun Parwate, Wenchao Xue, Thammarat Koottatep et al.

Processes • 2024

Food waste (FW), piggery waste (PW), and activated sludge (AS) were investigated as potential organic feeds for bioelectricity generation in laboratory-scale microbial fuel cells (MFCs). The MFCs fed by FW gained the highest maximum power density at 7.25 W/m3, followed by those fed by PW at 3.86 W/m3 and AS at 1.54 W/m3. The tCOD removal in the FW-, PW-, and AS-MFCs reached 76.9%, 63.9%, and 55.22%, respectively, within a 30-day retention time. Food waste, which resulted in the highest power density and tCOD removal, was selected for a series of following tests to investigate the effects of some physicochemical properties of organic feed on the performance of MFCs. The effect of feed particle size was tested with three controlled size ranges (i.e., 3, 1, and <1 mm) in MFCs. A smaller feed particle size provided a higher power density of 7.25 W/m3 and a tCOD removal of 76.9% compared to the MFCs fed with organic waste with a larger particle size. An increment in feed moisture from 70% to 90% improved the maximum power density from 7.2 to 8.5 W/m3, with a 17.5% enhancement, and improved the tCOD removal from 75.8% to 83.3%, with a 10.0% enhancement. A moderate C/N ratio of approximately 30/1 maximized the power density and COD removal (7.25 W/m3 and 81.73%) in the MFCs compared to C/N ratios of 20/1 (4.0 W/m3 and 64.14%) and 45/1 (4.38 W/m3 and 71.34%).

Mehdi Mohaghegh

• 2024

In the pursuit of sustainable energy solutions, solar power plants, particularly in dry and semi-dry areas, face the challenge of dust accumulation on panels, significantly reducing efficiency. Traditional cleaning methods, often reliant on scarce water resources, present an environmental paradox in these water-stressed regions. Our innovative approach involves the development of a smart clearing robot that addresses this issue effectively and sustainably. This robot utilises advanced digital technologies to both forecast power plant performance and clean solar panels without water usage. Incorporating elements of IoT, Machine Learning, and predictive analytics, the robot provides valuable insights into the plant's operational status while maintaining optimal panel cleanliness through a waterless cleaning mechanism. This approach not only conserves precious water resources but also enhances the overall efficiency and lifespan of solar panels. Our solution represents a practical application of the Water-Energy-Food (WEF) Nexus, demonstrating how digital innovation can overcome specific challenges while contributing to the broader goals of sustainable development, particularly UN SDGs 6 (Clean Water and Sanitation), 7 (Affordable and Clean Energy), and 13 (Climate Action). This abstract proposes a pioneering step in utilising digital technology for environmental sustainability, showcasing a synergistic approach to addressing the intertwined challenges of water scarcity and energy efficiency in solar power generation.

Ashley Sharkey, Ali Zare

Energies • 2024

As the need for alternative energy sources and reduced emissions grows, proven technologies are often sidelined in favour of emerging solutions that lack the infrastructure for mass adoption. This study explores a transitional approach by modifying existing compression ignition engines to run on a hydrogen/diesel mixture for performance improvement, utilising water injection to mitigate the drawbacks associated with hydrogen combustion. This approach can yield favourable results with current technology. In this modelling study, ten hydrogen energy ratios (0–90%) and nine water injection rates (0–700 mg/cycle) were tested in a turbocharged Cummins ISBe 220 31 six-cylinder diesel engine. An engine experiment was conducted to validate the model. Key performance indicators such as power, mechanical efficiency, thermal efficiency, indicated mean effective pressure (IMEP), and brake-specific fuel consumption (BSFC) were measured. Both water injection and hydrogen injection led to slight improvements in all performance metrics, except BSFC, due to hydrogen’s lower energy density. In terms of emissions, CO and CO2 levels significantly decreased as hydrogen content increased, with reductions of 94% and 96%, respectively, at 90% hydrogen compared to the baseline diesel. Water injection at peak rates further reduced CO emissions by approximately 40%, though it had minimal effect on CO2. As expected, NOx (which is a typical challenge with hydrogen combustion and also with diesel engines in general) increased with hydrogen fuelling, resulting in an approximately 70% increase in total NOx emissions over the range of 0–90% hydrogen energy. Similar increases were observed in NO and NO2, e.g., 90% and 57% increases with 90% hydrogen, respectively. However, water injection reduced NO and NO2 levels by up to 16% and 83%, respectively, resulting in a net decrease in NOX emissions in many combined cases, not only with hydrogen injection but also when compared to baseline diesel.

Marco Aurélio Andrade Cacheado, Isabel Cristina Braga Rodrigues, Edson Romano Nucci

Revista de Gestão Social e Ambiental • 2024

Objective: The objective of this study was to apply Artificial Neural Networks to evaluate the performance of Microbial Energy Cells, to identify the best network configuration for cell evaluation. Theoretical Framework: Although several of the widely used effluent treatment methods show results, most of them have a common disadvantage: they lose the chemical energy contained in the treated effluent and have high energy consumption for their conduction. Therefore, an increasing effort has been made to develop effluent treatment technologies capable of recovering part of the energy contained in the waste to be treated. In this scenario, microbial energy cells (CEM) emerge as a potential technology, as they are devices that simultaneously treat effluent biologically and generate electrical energy. Methodology: For the application and evaluation of ANNs in CEM, a feedforward neural network was used, with a Levenberg-Marquardt training algorithm, 1 or 2 hidden layers, with sigmoid and tansig activation functions, and an accuracy factor of 10-5. The data used for training and validation for the ANN were obtained through a literature search. Networks with 15, 30, 50, 90, 100, 130, 150, and 200 neurons were used for testing to evaluate the best performance. Results and Discussion: With the results obtained, it was observed that the best adjustment of the network occurred with the 2-layer configuration, one layer with 100 neurons and the other output layer, with 49 interactions and R2 of 0.91 in the training adjustment, 0 .78 in the validation fit and 0.90 in the fit with all experimental data evaluated, respectively. Originality/Value: This study contributes to the literature by evaluating the application of artificial neural networks, which are empirical modeling mechanisms, inspired by biological nervous systems, with processing abilities, in microbial energy cells.

Kristian K. Justesen, Søren Juhl Andreasen, Hamid Reza Shaker

Journal of Fuel Cell Science and Technology • 2013

In this work, a dynamic matlab Simulink model of an H3-350 reformed methanol fuel cell (RMFC) stand-alone battery charger produced by Serenergy® is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous hydrogen, which is difficult and energy-consuming to store and transport. The models include thermal equilibrium models of the individual components of the system. Models of the heating and cooling of the gas flows between components are also modeled and adaptive neuro-fuzzy inference system models of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other's output. The models take this into account using an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model, which is adapted to fit the measured performance of the H3-350 module. All of the individual parts of the model are verified and fine-tuned through a series of experiments and are found to have mean absolute errors between 0.4% and 6.4% but typically below 3%. After a comparison between the performance of the combined model and the experimental setup, the model is deemed to be valid for control design and optimization purposes.

, Pau Aragón Grabiel

• 2024

Nuclear fuel is the result of a long optimization process aimed at improving its performance and reliability under reactor conditions. This pursuit of excellence in fuel behaviour also extends to research on accident conditions, which has gained significant momentum since the Fukushima Daiichi accident in 2011, resulting in the consolidation of advanced technology fuel (ATF) development. ATFs are designed to maintain or enhance fuel performance during normal operating conditions while providing an improved response to some of the scenarios described by anticipated operational occurrences, design basis accidents, and design extension conditions. Among the challenges posed by ATFs is the demonstration of their safe behaviour in such scenarios. Therefore, the development of fuel performance modelling capabilities becomes paramount. The ultimate goal of this thesis is to contribute to the development of reliable predictive tools for assessing the thermo-mechanical behaviour of ATFs, specifically Cr-doped UO2, FeCrAl cladding, and Cr-coated Zircaloy cladding. The fuel performance codes (FPCs) FRAPCON-4.0 and FRAPTRAN-2.0 serve as the foundation for the developments outlined in this thesis, as their original versions are limited to modelling UO2 and MOX fuel, along with Zr-based cladding. The chapters of this thesis are structured around specific objectives that represent the necessary steps toward achieving its ultimate goal. These steps include: (i) building a material property database of models and correlations sourced from the open literature, (ii) developing and improving models and correlations from the data compiled in the material property database, (iii) implementing the resulting models and correlations into the baseline FPCs, and (iv) verifying and validating the extended codes. Additionally, these codes have been coupled with the statistical tool DAKOTA and integrated into a best-estimate plus uncertainty fuel safety evaluation methodology, which has been applied to assess ATF cladding performance under two postulated loss-of-coolant accident (LOCA) scenarios. The baseline FPC have been extended for ATF simulation. Specifically, FRAPCON-4.0 now includes simulation capabilities for Cr-doped UO2 and FeCrAl cladding, while FRAPTRAN-2.0 has been extended to simulate FeCrAl and Cr-coated Zircaloy cladding. The latter task required the development of TUmech, a standalone version of the TRANSURANUS mechanical model with additional simplifications to focus on the cladding response to LOCA conditions. The FRAPTRAN-TUmech coupling enabled independent modelling of the coating and cladding substrate, a capability not offered by the original mechanical model in FRAPTRAN-2.0. After extending the baseline FPC, the next step involves code verification and validation. However, integral effects test data were only available for Cr-doped UO2 under normal operating and power ramp conditions. Consequently, only the extension of FRAPCON-4.0 to Cr-doped UO2 has undergone data-code comparison. Due to the lack of integral effects test data for FeCrAl and Cr-coated Zircaloy, the extension of FRAPTRAN-2.0 for these ATF cladding materials could only be verified, not validated. In this task, emphasis was placed on comparing their behaviour to conventional Zircaloy to qualitatively demonstrate the consistency of the predictions under LOCA conditions. Despite the extent, robustness, and significance of the contributions this thesis has made to the development of predictive tools for ATFs, key areas still need to be addressed. Of particular relevance is the validation of FRAPTRAN-2.0 and FRAPTRAN-TUmech. Regarding recommendations, it is crucial to emphasize the imperative need for representative experimental data, including measurements on irradiated material under test conditions extending beyond the current safety criteria, as these may change for ATFs. RESUMEN El combustible nuclear es el resultado de un largo proceso de optimización destinado a mejorar su rendimiento y fiabilidad bajo las condiciones en reactor. Esta búsqueda de la excelencia también se extiende a la investigación en condiciones de accidente, que ha experimentado un impulso significativo tras el accidente de Fukushima Daiichi, resultando en la consolidación de los combustibles de tecnología avanzada (ATFs). Los ATFs están diseñados para mantener o mejorar el rendimiento del combustible en condiciones normales de operación, al mismo tiempo que ofrecen una respuesta mejorada ante algunos de los escenarios descritos por sucesos operativos previstos, accidentes base de diseño y condiciones de extensión de diseño. Entre los desafíos planteados por los ATFs está la demostración de su comportamiento seguro en tales escenarios. En este contexto, el desarrollo de capacidades de modelado es esencial. El objetivo de esta tesis es contribuir al desarrollo de herramientas predictivas fiables para evaluar el comportamiento termo-mecánico de los ATFs, en particular, UO2 dopado con Cr, vaina de FeCrAl y vaina de Zircaloy recubierta con Cr. Los códigos termo-mecánicos (FPC) FRAPCON-4.0 y FRAPTRAN-2.0 sirven como base para los desarrollos presentados, ya que sus versiones originales están limitadas al modelado de UO2 y MOX, junto con vainas basadas en Zr. Los capítulos de esta tesis están estructurados en torno a los pasos necesarios para alcanzar su fin último. Estos pasos incluyen: (i) construir una base de datos de modelos y correlaciones obtenidos de la literatura abierta, (ii) desarrollar y mejorar modelos y correlaciones a partir de la información compilada, (iii) implementar los modelos y correlaciones resultantes en los FPC de referencia, y (iv) verificar y validar los códigos extendidos. Además, estos códigos se han acoplado con la herramienta estadística DAKOTA e integrado en una metodología de cálculo realista con incertidumbre, la cual se ha aplicado para evaluar el comportamiento de la vaina ATF bajo accidentes de pérdida de refrigerante (LOCA). Los FPC de referencia se han extendido para la simulación de ATFs. FRAPCON-4.0 ahora incluye capacidades de simulación para UO2 dopado con Cr y vaina de FeCrAl, mientras que FRAPTRAN-2.0 se ha extendido para simular vainas de FeCrAl y Zircaloy recubierto con Cr. Esta última tarea requirió el desarrollo de TUmech, una versión independiente del modelo mecánico de TRANSURANUS con simplificaciones adicionales para centrarse en la respuesta de la vaina ante condiciones LOCA. El acoplamiento FRAPTRAN-TUmech permitió el modelado independiente del recubrimiento y el sustrato de la vaina, una capacidad no ofrecida por el modelo mecánico de FRAPTRAN-2.0. El siguiente paso tras extender los FPC de referencia implica su verificación y validación. Sin embargo, solo se disponía de datos de ensayos de efectos integrales para UO2 dopado bajo condiciones de operación normal y rampas de potencia. En consecuencia, solo la extensión de FRAPCON-4.0 para UO2 dopado ha sido sometida a validación. Debido a la falta de datos de ensayos de efectos integrales para FeCrAl y Zircaloy recubierto con Cr, la extensión de FRAPTRAN-2.0 para estos materiales solo pudo ser verificada. Esta verificación ha consistido en comparar su comportamiento con el de la vaina convencional para demostrar cualitativamente la consistencia de las predicciones bajo condiciones LOCA. A pesar de la extensión, robustez y relevancia de las contribuciones que esta tesis ha hecho al desarrollo de códigos termo-mecánicos para ATFs, aún quedan áreas clave por abordar. De particular relevancia es la validación de FRAPTRAN-2.0 y FRAPTRAN-TUmech. En cuanto a recomendaciones, es crucial destacar la necesidad de datos experimentales representativos, incluyendo mediciones de materiales irradiados en condiciones que se extiendan más allá de los criterios de seguridad actuales, dado que estos podrían cambiar para los ATFs.

Celso Recalde, Denys López, Diana Aguay et al.

Sensors • 2023

The increasing need for fresh water in a climate change scenario requires remote monitoring of water bodies in high-altitude mountain areas. This study aimed to explore the feasibility of SMFC operation in the presence of low dissolved oxygen concentrations for remote, on-site monitoring of physical environmental parameters in high-altitude mountainous areas. The implemented power management system (PMS) uses a reference SMFC (SMFCRef) to implement a quasi-maximum power point tracking (quasi-MPPT) algorithm to harvest energy stably. As a result, while transmitting in a point-to-point wireless sensor network topology, the system achieves an overall efficiency of 59.6%. Furthermore, the control mechanisms prevent energy waste and maintain a stable voltage despite the microbial fuel cell (MFC)’s high impedance, low time response, and low energy production. Moreover, our system enables a fundamental understanding of environmental systems and their resilience of adaptation strategies by being a low-cost, ecological, and environmentally friendly alternative to power-distributed and dynamic environmental sensing networks in high-altitude mountain ecosystems with anoxic environmental conditions.

Jian Cheng, Liejin Guo, Shisen Xu et al.

Journal of Chemistry • 2013

A key component in the molten carbonate fuel cell (MCFC) is electrolyte matrix, which provides both ionic conduction and gas sealing. The aim of this work is to investigate the effects of selected operating conditions on the performance of the matrix preparation. Slurries were prepared to produce matrices by the technique of tape casting. The characteristics of the slurries and matrices were examined by laser particle size analyzer, scanning electron microscopy, and BET surface area analyzer. The testing results revealed that a slurry composition with 40 wt.% lithium aluminate was the optimal formulation to produce a good matrix with a pore size distribution of 0.1–0.4 μ m and porosity of 50 vol.%. Coarse and fine LiAlO 2 particles were added in the matrix slurry to enhance the mechanical strength. Several green sheets were heated and pressed to enhance the bulk density to get a dense matrix of MCFC. Finally, a single MCFC was assembled and tested. The testing results showed the matrix with 40% solid loading gave the maximum discharge current of 20 A at 0.56 V.

Edward A. VanDyne, Michael B. Riley

ASME 2007 Internal Combustion Engine Division Fall Technical Conference • 2006

Turbochargers provide an efficient method of utilizing exhaust energy to boost intake air pressure for improved engine performance and efficiency. However transient operation requires increased air delivery (via quicker compressor response) to allow more rapid fueling for acceleration in both diesel and natural gas engines. In diesel engines rapid boosting will avoid increased particulates caused by excessive fueling during acceleration. Further, in applications that use either a wastegate, inlet bypass or variable vanes in the turbine to limit boost pressures, the excess energy in the exhaust is thrown away. The SuperTurbo™ (or superturbocharger) can recover much of the wasted energy and return it to the crankshaft, increasing overall efficiency. Woodward has developed a mechanical geartrain connected to the turbine shaft that transmits power through a variable speed hydraulic transmission to the crankshaft of an engine. This combination, a superturbocharger, provides the needed characteristics of (a) recovery of energy at high speed/load operating points (turbocompounding), (b) very rapid acceleration of the turbine shaft during transients (supercharging), (c) elimination of boost limitation devices, and (d) a variable speed hydraulic transmission that will be lower cost than a high-speed, high-power electrical system. While the air requirements are different for diesel and natural gas engines, both have sufficient exhaust energy to drive a turbine beyond the needs of the compressor for much of the performance map. Part load operation may be different as natural gas engines are usually throttled. The choice of a diesel or natural gas application was influenced by the availability of a suitable engine. The first prototype superturbocharger was built and tested on a Mack E7G natural gas engine, replacing the wastegated turbocharger of the stock engine. Preliminary results show fuel economy improvements of almost 6% at high speeds and high loads. In addition the load response of the engine was greatly increased due to the ability to accelerate turbine shaft speed, increasing boost. However there was a peak power output drop due to limitations in boost and imperfect sizing.

Lejun Wang, Ce Wang, Hua Yang et al.

Frontiers in Human Neuroscience • 2022

The present study examined the effects of transcranial direct current stimulation (tDCS) using Halo Sport on the time to exhaustion (TTE) in relation with muscle activities and corticomuscular coupling of agonist and antagonist muscles during a sustained isometric fatiguing contraction performed with the elbow flexors. Twenty healthy male college students were randomly assigned to tDCS group and control group. The two group participants performed two experimental sessions which consisted of pre-fatigue isometric maximal voluntary contraction (MVC), sustained submaximal voluntary contractions (30% maximal torque) performed to exhaustion, and post-fatigue MVC with the right elbow flexor muscles. Sham stimulation (90 s) and tDCS (20 min) were applied for control and tDCS group participants 20 min prior to the second session test, respectively. MVC strength in pre- and post-fatigue test, TTE, electroencephalogram (EEG), and electromyography (EMG) of biceps brachii (BB) and triceps brachii (TB) were recorded during the tests. It was found that tDCS using the Halo Sport device significantly increased TTE and thus improved muscular endurance performance. The improvement may be partly related to the improvement of neuromuscular efficiency as reflected by decrease of antagonistic muscle coactivation activities, which may be related to cortical originated central processing mechanism of neuromuscular activities.

Yohan Grandperrin, Sidney Grosprêtre, Magali Nicolier et al.

Research Square • 2019

Abstract Background Transcranial direct current stimulation (tDCS) is promising for improving motor and cognitive performance. Nevertheless, its mechanisms of action are unclear and need to be better characterised according to the stimulated brain area and the type of exercise performed.Methods/design This is a double-blind cross-over study, organised into two parts: the first is to assess the effects of tDCS on explosive performance (jump task) and the second is to assess the effects on endurance performance (cycling time trial task). Participants, who are recreationally active or athletes (cyclists, parkour practitioners), will receive two active tDCS sessions (over the left dorsolateral prefrontal cortex and right motor cortex) and one sham tDCS session (part A) or two daily tDCS sessions (one active sequence and one sham) over five days (part B). Motor and cognitive performance will be compared before and after the tDCS sessions (part A) and before and after the first session, after the last session and at day 12 and day 30 of each tDCS sequence (part B).Discussion This study investigates the acute and long-term effects of tDCS on the motor and cognitive performance in healthy subjects. It will try to evaluate if tDCS could be considered as a neuroenhancement technology according to the physical task investigated (endurance versus explosive).

Nibir Mondol, Kazi Siamul Islam, Md Rafiqul Islam et al.

AIP Advances • 2023

Perovskite solar cells have pulled off a level of conversion efficiency comparable to other well-established photovoltaics, such as silicon and cadmium telluride. Organic–inorganic halide perovskite materials are one of the most appealing and imminent options for developing high performance and cost-effective photovoltaic cells. In this simulation-based research, a highly efficient 2-terminal perovskite-on-silicon (PVK–Si) tandem configuration has been proposed with improved stability and significant cost savings. Initially, the MAPbI3 based perovskite top cell with 1.57 eV bandgap is tested with several distinct hole transport materials (HTMs) and electron transport materials (ETMs), four each. Spiro-OMeTAD as HTM and C60 as ETM are the best performing materials and employed in final top cell configuration to have a power conversion efficiency (PCE) of 23.05%. The systems for tandem configuration are experimented after setting the layers of individual top and bottom sub-cells to optimized thicknesses. The thicknesses of both top and bottom absorber layer are adjusted to find out the current matching point. The tandem configuration exhibits optimized thicknesses of 250 nm and 150 µm for top and bottom sub-cells, respectively. Performance evaluation of the top cell involves standard AM 1.5G solar spectrum illumination at a 250 nm absorber thickness, while the bottom cell’s performance is assessed using top cell filtered spectrum. The simulated tandem configuration composed of IZO/C60/MAPbI3/spiro-OMeTAD/n-nc-SiOx/n-c-Si/P+ Si showed a champion PCE of 35.31% with a fill factor of 79.46% and open-circuit voltage of 2.12 V. These findings signify substantial advancements in the field of PVK-Si tandem photovoltaic cells, marking a significant stride toward potential commercial applications.

Rabi Narayan Mishra, Kanungo Barada Mohanty

Journal of Renewable and Sustainable Energy • 2017

This article focuses on the design and implementation of a hybrid fuel cell supply system to deliver the power demanded by the feedback linearization (FBL) based induction motor (IM) drive. The proposed modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) with intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burdens by improving computational efficiency over conventional NFSMC and thus suitable for real-time industrial applications. The parameters of the modified neuro-fuzzy control are tuned by an adaptive mechanism based on sliding-mode control. A fuel cell stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the fuel cell during different operating conditions of the drive system. The effectiveness of the proposed method using the fuel cell-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated by experiment using DSP2812. It is evident from the results that the system provides optimal dynamic performance in terms of remarkably reduced torque ripple, good load disturbance rejection, and reduced speed settling time responses by around 92%, 50%, and 41%, respectively, compared to the PI-controller. The system is also robust in terms of parameter variation and external load.

H Kyrölänen, P. V. Komi, D. H Kim

Scandinavian Journal of Medicine & Science in Sports • 1991

Effects of power training with stretch‐shortening cycle (SSC) exercises on mechanical efficiency (ME) were investigated with 9 young women who trained 3 times a week for 4 months. The training included various types of jumping exercises. Before and after the training as well as after the detraining (2 months) the subjects performed 6 different submaximal exercises with a special sledge apparatus. Each exercise involved 60 muscle actions lasting for a total of 3 min per testing condition. The work intensities were determined individually according to the recordings of distance obtained during the single maximal concentric exercises. The training caused the greatest changes of ME in conditions of higher prestretch intensities. The ME values changed from 49.3 ± 12.9% to 55.4 ± 12.1% in pure eccentric exercises and from 39.5 ± 4.6% to 46.1 ± 5.0% in SSC exercises during the training. After the training, the subjects preactivated their leg extensor muscles earlier before the impact, and the eccentric working phase was more powerful, because of higher tendomuscular stiffness. Higher preactivation of the measured muscles, higher flexion of knee and increased dorsiflexion of ankle joints in the beginning of contact caused the increased stiffness, possibly through more powerful reflex activation. At the same time the metabolic demands of muscles decreased, causing the increases of ME.

L. Holt, U. Rohde, M. Seidl et al.

Volume 5: Innovative Nuclear Power Plant Design and New Technology Application; Student Paper Competition • 2014

In the last two decades the reactor dynamics code DYN3D was coupled to thermal hydraulics system codes, a sub-channel thermal hydraulics code and CFD codes. These earlier developed code systems allow modeling of the thermal hydraulics phenomena occurring during reactor transients and accidents in greater detail. Still these code systems lack a sufficiently sophisticated fuel behavior model, which is able i.e. to take into account the fission gas behavior during normal operation, off-normal conditions and transients. To our knowledge a two-way coupling to a fuel performance code hasn’t so far been reported in the open literature for calculating a full core with detailed and well validated fuel behavior models. A new two-way coupling approach between DYN3D and the fuel performance code TRANSURANUS is presented. In the coupling, DYN3D provides the time-dependent rod power and thermal hydraulics conditions to TRANSURANUS, which in turn transfers parameters like fuel temperature and cladding temperature back to DYN3D. The main part of the development is a general TRANSURANUS coupling interface that is applicable for linking of any other reactor dynamics codes, thermal hydraulics system codes and sub-channel codes to TRANSURANUS. Beside its generality, other features of this interface are the application at either fuel assembly or fuel rod level, one-way or two-way coupling, automatic switching from steady to transient conditions in TRANSURANUS (including update of the material properties etc.), writing of all TRANSURANUS output files and the possibility of manual pre- and post-calculations with TRANSURANUS in standalone mode. The TRANSURANUS code can be used in combination with this coupling interface in various scenarios: different fuel compositions in the reactor types BWR, PWR, VVER, HWR and FBR, considering time scales from milliseconds (i.e. RIA) over seconds/ minutes (i.e. LOCA) to years (i.e. normal operation) and thence different reactor states. Results of DYN3D-TRANSURANUS are shown for a control rod ejection transient in a German PWR. In particular, it appears that for all burn-up levels the two-way coupling approach systematically calculates higher maximum values for the node fuel enthalpy (max. difference of 46 J/g) and node centerline fuel temperature (max. difference of 181 K), compared to DYN3D standalone in best estimate calculations. These differences can be completely explained by the more detailed TRANSURANUS modeling of fuel thermal conductivity, radial power density profile and heat transfer in the gap. As known from fuel performance codes, the modeling of the heat transfer in the gap is sensitive and causes also larger differences in case of low burn-up. The numerical convergence for DYN3D-TRANSURANUS is quick and stable. The coupled code system can improve the assessment of safety criteria, at a reasonable computational cost with a CPU time of less than seven hours without parallelization.

, Kanhu Charan Bhuyan, Pushpak Jain et al.

International Journal of Engineering and Advanced Technology • 2023

The world's growing economy and demographic advancement are driving an increase in global energy demand. As worries about carbon emissions grow and the demand for electrical energy production continues to rise, it is necessary to develop new methods of electricity production. Fuel cell energy system is one of the promising factors for addressing this problem due to its low emissions, easy accessibility, and fuel flexibility. In this paper, a mathematical model of Solid Oxide Fuel Cell (SOFC) is designed and used as an input for the KY converter. As the output voltage of the fuel cell is low, a KY Converter is desired to raise the output voltage for required applications. To regulate the electrical output voltage of the KY Converter, PID, Fuzzy Logic Controller (FLC), hybrid fuzzy PID, and an ANFIS feedback control mechanism have been simulated and investigated. The function of a fuel cell with a KY Converter, as well as state-space modelling, is developed. The Ziegler-Nichols technique is used to determine the gain parameters of a PID controller, which are Kp, Ki, and Kd. The fuel cell with a Closed-loop system of KY converter is developed using MATLAB/Simulink software. Thus, the fuel cell power system can be used for a variety of applications, including rural and military.

Hussain Attia

International Journal of Power Electronics and Drive Systems (IJPEDS) • 2019

<span lang="EN-US">This paper presents a new design of a standalone photovoltaic system which is supplying the required power to a direct current water pump that have difficulty to supply by the utility electricity. The system is controlled by an artificial neural networks (ANN) algorithm with function softening by PI controller that to guarantee the maximum power point tracking (MPPT) working conditions. A parallel connected PV array is designed to supply the required power to the water pump. The proposed design considers Permanent Magnet DC motor (PMDC) of 48 Volts, and 500 Watts as a water pump’s motor, the direct current (DC) pump is adopted to avoid the complexity of the alternating current AC pumping system which includes inverter, power filter, and insulated step up transformer, so the presented design avoids the mentioned AC system components. A feed forward ANN algorithm is adopted in this study to produce the reference voltage for the MPPT functioning of the PV system, Proportional Integral (PI) controller is inserted to soften the MPPT controller performance. System design, MATLAB simulation with results and the results’ analysis all are presented in this paper. The study conclusion confirms the effectiveness of the proposal as a successful system for practical applications. </span>

K Wan, J Taylor, S Hajat

European Journal of Public Health • 2024

Abstract Cold temperatures have been widely acknowledged as an important burden of poor health in many parts of the world including the UK. Although the temperature is expected to increase in the future due to climate change, the latest UK Health Effects of Climate Change (HECC) report projected that the number of cold-related deaths in the UK is expected to be more than 2 times of heat in the 2070s even under a high emission climate change scenario (RCP8.5). Therefore, it is still imperative to take intervention to reduce the health impacts of cold. People spent more than 90% of their time indoor and hence being able to stay in warm homes is crucial for reducing the impact of cold. However, some people may not be able to warm their home enough, a problem known as fuel poverty. Multiple factors can contribute to fuel poverty, including low income, poor housing performance, high fuel price as well as competing interest in fuel consumption and other essential living expenses. These challenges have been witnessed markedly during the cost of living crisis since 2021. This research investigates the effect of fuel poverty on cold-related mortality risk in England and Wales using small areal data. The underlying contributing factors of fuel poverty are explored to study the main mechanisms. The findings can support the identification of those who may be mostly affected by fuel poverty, and hence improve policies and interventions on reducing fuel poverty and protecting the public health from low temperatures.

Satish Bonthu, Runar Unnthorsson, Hordur Sigurbjarnarson et al.

Volume 7: Energy • 2023

Abstract This paper presents the successful retrofitting of an old whale-watching boat incorporating a larger propeller and a new reduction gear. The retrofit resulted in an impressive, 30% improvement in fuel efficiency across the entire operating range of the propulsion system. This significant improvement directly translates to a reduction in carbon emissions, underscoring the project’s importance for further investigation. Given that the propeller contributes to 80–90% of the vessel’s fuel consumption, a detailed analysis of the hydrodynamic performance improvement is warranted. To address this, a cost-effective and efficient computational fluid dynamics (CFD) approach is proposed to qualitatively connect the observed field performance of the vessel with the mechanical performance of the new propeller. The study highlights the accuracy of this approach in realistically predicting the field performance of both the old and new propellers under different operating conditions derived from sea trials. In conclusion, this study demonstrates the potential for retrofitting existing vessels with improved propulsion systems, resulting in increased fuel efficiency and reduced carbon emissions.

Rong Hai Huang, Bing Mo, Feng Zhao et al.

Key Engineering Materials • 2014

Microbial fuel cells (MFCs) are regarded as a promising and environmental friendly method for wastewater treatment and bio-production. The output power of a single cell is inadequate to drive loads directly. Microbial fuel cells stacked in serials will promote bio-production or bioremediation and the voltage of the MFCs can be scaled up by connecting the cells in serials, whereas voltage reversal may emerge in this case. The causes for reversing polarity of MFCs have received great attention in recent years. This paper designs a power management circuit for microbial fuel cell, studies the mechanisms of voltage reversal and the approaches to solve the problem.

Massewa D.A

Proceedings of Indonesian Petroleum Association, 46th Annual Convention & Exhibition, 2022 • 2022

Batang is a marginal oil field in Indonesia with heavy oil and high pour point oil characteristics. When the well temperature drops during production, usually the water cut increases due to the lower mobility of oil. Hence, cyclic steam stimulation (CSS) is routinely needed to increase the well temperature and reduce the viscosity of oil, which improves flow assurance from the wells to the gathering station. Currently, marine fuel oil (MFO) is used as the fuel for the steam generator unit. However, the cost of MFO is even higher than the steam generator’s daily operation cost and the urge to reduce CO2 emissions is contrary to the utilization of this fuel. So a trial of compressed natural gas (CNG) has been introduced to tackle the problems from using MFO, and this trial has successfully lowered both the fuel price and the impact on the environment. MFO is simpler to use than using CNG, because MFO can easily be transported using tanker trucks without the need to maintain the tank within specific parameters. Also, MFO can be offloaded easily to the storage tank of the steam generator unit. CNG utilization is more complicated because firstly gas from the source needs to be compressed, which needs investment in a gas compression station to be built near the gas sales point based on an agreement between the buyer and the seller. Then, the CNG needs to be transported using a gas transportation module (GTM) to maintain the CNG’s parameters until reaching the location. After arriving, the gas needs to be decompressed to suit the steam generator’s operating parameters by using a pressure regulating system (PRS), and then the gas will be delivered to the steam generator to be used as fuel for CSS. A trial of CNG utilization has been performed in Batang and the results are promising. Using CNG reduces costs by 60% whilst also reducing CO2 emissions, which supports the company’s goal to achieve net zero emission. Beside the benefit of this conversion, deep risk mitigation was performed due to the additional hazards from CNG usage such as high pressure and temperature. This paper will discuss the detail of the technical execution, a comparison of parameters achieved, risk analysis, environmental impact, and an economic evaluation. This CNG fuel conversion for CSS activity can be a benchmark for the energy industry to significantly reduce both operational costs and environmental impact while maintaining the stimulation to increase oil production.

K R S Pamintuan, M M D Virata, M F C Yu

IOP Conference Series: Earth and Environmental Science • 2019

Abstract The relationship between power generation in a Plant-Microbial Fuel Cell (PMFC) and phytoremediation were observed in this paper. It is hypothesized that both power generation and metal uptake capacity will be enhanced synergistically upon the combination of the two processes. To test the hypothesis, the experiment was composed of three set-ups: (A) PMFC only, (B) phytoremediation only, and (C) PMFC combined with phytoremediation. A maximum power density for set-up A of 3.43 μW/m 2 and 247.11 μW/m 2 for Azolla pinnata and Lemna minor , respectively, while a maximum power density for set-up C of 17.82 μW/m 2 and 1076.16 μW/m 2 for the two plants were observed. The values showed a significant increase in power density for set-ups where copper ions are present (set-up C). The internal resistance of the PMFCs were also investigated. It was observed that internal resistance continuously decreased through time and the presence of copper ions in set-up C of both plants resulted to a lower internal resistance, equating to higher power densities. In terms of phytoremediation potential, the results showed that the presence of electrodes in the hybrid set-up induced the plants to absorb more copper ions than the control. The copper ion uptake increased by about 18% for A. pinnata and 38% for L. minor in phytoremediation tests in PMFCs. Overall, the combination of PMFC technology and the concept of phytoremediation has been shown to benefit both power generation and metal uptake capacity. The results of this study can be used to enhance the clean-up of metal contaminants while simultaneously providing power in-situ.

mohammed benghernit, mostefa kameche, fatima zohra zerhouni et al.

Research Square • 2022

Abstract A microbial fuel cell (MFC) has been conceived and constructed for the treatment of the sheep manure wastes and conversion them into clean sustainable renewable energy. The chemical oxygen demand (COD) removal of 10 days running MFC increased by 58.7% showing simultaneously an increase in the cell voltage. However, this MFC technology faces practical barriers since it produces low electric energy. A power management system including the MFC, operational amplifier, solar photovoltaic panel and a boost DC/DC converter, was elaborated in this respect. The low voltage output obtained from the MFC, was thus substantially increased by the amplifier prior to polarization by a photovoltaic module with solar radiation. The amplified voltage was thus sufficiently enough and in consequence, utilized to feed a light emitting diode. The low output voltage 0.5 V was simply harvested, successfully boosted up to approximately 2 V (i.e. 4 times higher) and effectively harnessed as a power supply. This novel application is very interesting to utilize the natural bioenergy contained in wastes to supply small electronic devices.

Hujun Peng, Jianxiang Li, Kai Deng et al.

Vehicles • 2022

In this work, a machine learning-based energy management system is developed using a long short-term memory (LSTM) network for fuel cell hybrid buses. The neural network implicitly learns the complex relationship between various factors and the optimal power control from massive data. The selection of the neural network inputs is inspired by the adaptive Pontryagin’s minimum principle (APMP) strategy. Since an estimated value of the global average fuel cell power is required in the machine learning-based energy management strategy (EMS), some global features of driving cycles are extracted and then applied in a feedforward neural network to predict the average fuel cell power appropriately. The effectiveness of the machine learning-based energy management, with the integration of the mechanism of estimating the average fuel cell power based on the forward neural network, is tested under two different driving cycles from the training environment, with comparisons to a commercially used rule-based strategy. Based on the simulation results, the learning-based strategy outperforms the rule-based strategy regarding the charge-sustaining mode conditions and fuel economy. Moreover, compared to the best offline hydrogen consumption, the machine learning-based strategy consumed 0.58% and 0.36% more than the best offline results for both driving cycles. In contrast, the rule-based strategy consumed 1.80% and 0.96% more than optimal offline results for the two driving cycles, respectively. Finally, simulations under battery and fuel cell aging conditions show that the fuel economy of the machine learning-based strategy experiences no performance degradation under components aging compared to offline strategies.

Quan Hou, Han Wang, Dan Zhu

SAE Technical Paper Series • 2025

<div class="section abstract"><div class="htmlview paragraph">Hydrogen fuel cell trucks have enormous development potential in the pursuit of global carbon neutrality and sustainable development. However, their commercialization and mass production are facing challenges in various aspects, especially the durability problem of fuel cells. This paper is intended to set up a high-power hydrogen fuel cell system (FCS) model, considering the fuel cell degradation factors, and based on this, proposes a two-layer fuzzy energy management strategy (EMS) to optimize the life of fuel cell and the total energy consumption of the vehicle. The first control layer provides real-time energy distribution efficiently from multiple sources and thus allows flexibility in energy supply. The second layer regulates the dynamic adjustment of fuel cell output power with degradation of both fuel cells and batteries considered, to make the prolonging of system lifetime possible. In this respect, the equivalent hydrogen consumption, which incorporates fuel cell degradation, is used as the objective function. A genetic algorithm is employed to optimize the membership functions and rule weights involved in the fuzzy control system, considering the determination of the best energy management solution. Simulation results of a 115 kW fuel cell truck operating based on the China World Transient Vehicle Cycle (C-WTVC) conditions show that the proposed strategy reduces fuel cell degradation by 36.7% compared to that of traditional single-layer fuzzy control methods under extreme operating conditions. These results clearly depict gains in economic efficiency and sustainability of the system and hence indicate the advantages of the two-layer control strategy.</div></div>

Youjie Shi, Bangyin Liu, Shanxu Duan

IET Power Electronics • 2018

A large amount of ripple at twice the output frequency will emerge in the input current due to the pulsating output power in a single‐phase inverter. A current‐fed‐type single‐stage single‐phase inverter is investigated. Based on the switch multiplexing technique, it can realise not only dc–ac power conversion but also low‐frequency input current ripple reduction with a lower number of power switches. A control strategy is proposed, which is capable of controlling both the input and output port performance. The operation performance is analysed, including circuit parameters, efficiency and dynamic behaviour. Besides, the equivalence of control strategy and the similarity of circuit component rating are revealed between this single‐stage inverter and a conventional two‐stage inverter. The single‐stage inverter is preferred in the applications which are sensitive to the power switch number and low‐frequency input current ripple. Finally, some experimental results are performed to verify the theoretical analysis.

Bhuvana J, Nidhi Saraswat, Savita et al.

E3S Web of Conferences • 2023

Power generation by using hydrogen energy is having significant priority during peak loads or under lower power generation conditions. Electricity can be easily produced by hydrogen with releasing any harmful gases to atmosphere as well as can meet load demand very quickly. During deficiency in generation from other power sources, the frequency of the system can be maintained through hydrogen based power generation units. A fuel cell (FC) stack can able to produce required amount of electricity from hydrogen and oxygen. Therefore grid connected FC can maintain power quality at local buses as well as can meet the load demand. Apart from transferring active power into grid from FC, the interfacing inverter of FC into grid can also improve power quality at local buses by injecting reactive power to make constant voltage during low voltages of grids. A novel control scheme based powers is implemented in this paper with the help of proportional plus integral (PI) controllers. The modeling of FC is also incorporated in the paper for best understanding.Various performances of the proposed method are tested under various case studies to present results by using MATLAB/Simulink package.

Huiduo Wu, Haitao Min, Honghui Zhao et al.

SAE Technical Paper Series • 2025

<div class="section abstract"><div class="htmlview paragraph">Energy management strategy (EMS) based on vehicle speed prediction has been widely used in fuel cell vehicles (FCVs). Actually, not only the actual power demand but also other factors affect the optimal power allocation between fuel cell system (FCS) and battery. However, this relationship is difficult to express in formulas especially under urban conditions because the power demand fluctuates greatly under the above conditions. To address the issue, a novel EMS for FCV based on short-term power demand and FCS output power is proposed. In the offline part, the short-term SOC change rate is used to characterize short-term power allocation. Besides, the average of short-term power demand and the FCS output power are selected as input factors. The feedforward neural network is used to learn the relationship of the above three state variables based on historical driving cycles. In the online part, a long short-term memory (LSTM) network is used to predict the short-term speed based on the vehicle historical motion states, then the power demand sequence can be calculated using dynamic model. Based on the short-term power demand and FCS output power, the well-trained feedforward network predicts the short-term optimal SOC change rate, then the short-term reference SOC can be obtained, which is used to find the optimal co-state of Pontryagin's minimum principle (PMP) for each horizon. In the local level, shooting method is used to determine the co-state for each horizon. The results show that LSTM network meets the require of short-term speed prediction. In addition, the proposed EMS makes the terminal SOC close to the target value and reduces the total cost by 12.14% compared with the benchmark strategy.</div></div>

Arifa Hossain Oishi, Md Tanveer Anjum, Md Muhsiul Islam et al.

European Journal of Electrical Engineering and Computer Science • 2023

Perovskite solar cells (PSCs) have a high-power conversion efficiency that exceeds 20%, distinguishing them from other new photovoltaic technologies. The Solar Cell Capacitance Simulator (SCAPS-1D) was used in this study to investigate the effects of absorber layer properties on photovoltaic solar cell performance. SCAPS simulation software employs a numerical simulation technique to fully comprehend the principles of solar cell operation and predict the best power conversion efficiency. A three-layer solar cell model comprised of an Electron Transport Layer (ETL), a Hole Transport Layer (HTL), and a Perovskite Absorber Layer was used in this study. The variations in Voc, Jsc, FF, and PCE were investigated by varying the thickness of the absorber layer. The purpose of this research is to find the absorber layer thickness that produces the highest efficiency for two different ETM layer ZnO and SnO2. This simulation model can significantly aid in the fabrication of high-efficiency ZnO and SnO2 based PSCs.

Wael ABDULLAH, Ryam ALMUSHIKYA

East Journal of Applied Science • 2025

With the expansion of the spread of solar energy in recent years, its applications are in many fields, and the trend of consumers towards it as energy-saving and environmentally friendly, working to raise its efficiency is something that has become important to pay attention to, and anti-reflection coating (ARC) is one of the most important factors that increase the efficiency of the solar cell from By reducing reflection losses, raising the absorption factor, and enhancing the conversion efficiency (PCE), the efficiency of solar cells varies depending on the type of ARC material used and its properties. Therefore, in this study, simulations of 6 different anti-reflective coating materials (ARC) were analyzed in terms of their performance to increase the cell efficiency. Using the PC1D simulation software, the results revealed that at the wavelength of 550 nm, the MgF2/CdS coating would be the best ARC for the two-layer ARC design due to its highest efficiency of 27.85%.