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Juan Pablo Villegas Ceballos ◽  
Carlos Andres Ramos-Paja ◽  
Elkin Edilberto Henao-Bravo

This paper proposes a battery charger solution based on the Zeta DC/DC converter to provide a general interface between batteries and microgrid direct current (DC) buses. This solution enables to interface batteries and DC buses with voltage conversion ratios lower, equal, and higher than one using the same components and without redesigning the control system, thus ensuring global stability. The converter controller is designed to require only the measurement of a single inductor current, instead of both inductors currents, without reducing the system flexibility and stability. The controller stability is demonstrated using the sliding-mode theory, and a design procedure for the parameters is developed to ensure a desired bus performance. Finally, simulations and experiments validate the performance of the proposed solution under realistic operation conditions.

2022 ◽  
Vol 18 (1) ◽  
pp. 1-13
David Thompson ◽  
Haibo Wang

This work presents a methodology to monitor the power signature of IoT devices for detecting operation abnormality. It does not require bulky measurement equipment thanks to the proposed power signature generation circuit which can be integrated into LDO voltage regulators. The proposed circuit is implemented using a 130 nm CMOS technology and simulated with power trace measured from a wireless sensor. It shows the generated power signature accurately reflects the power consumption and can be used to distinguish different operation conditions, such as wireless transmission levels, data sampling rates and microcontroller UART communications.

2022 ◽  
pp. 66-83
Qingjiao Zhu ◽  
Xintong Guo ◽  
Yanan Guo ◽  
Jingjing Ma ◽  
Qingjie Guo

With the acceleration of industrialization and urbanization in China, wastewater treatment is increasing yearly. As a by-product of wastewater treatment, the gasification of sludge with coal in chemical looping process is a clean and efficient conversion technology. To explore the reaction behavior of cogasification of sludge and coal with iron-based oxygen carriers (OCs) for producing hydrogen-rich syngas, the experiment of cogasification using Fe2O3/Al2O3 as OC in a fluidized bed reactor was conducted. The result showed that the volume percentage of hydrogen (H2) and syngas yield is proportional to the amount of sludge added. The optimal operation conditions were: temperature at 900 °C, the mass ratio of OC to coal at 5.80 and mass ratio of sludge to coal at 0.2. Under this operating condition, the volume percentage of H2 and syngas yield in the flue gas was 75.6 vol% and 97.5 L·min-1·kg-1, respectively. Besides, the OC showed a stable reactivity in the sixth redox cycle with added sludge. However, the reactivity of OC significantly declined in the seventh and eighth redox cycles. It was recovered when the ash was separated. The decrease in the specific surface area of the OC caused by ash deposition is the main reason for the decline in its reactivity. The kinetic analysis showed that the random pore model describes the reaction mechanism of sludge/coal chemical looping gasification (CLG). The addition of sludge can reduce the activation energy of coal CLG reaction, accelerate the gasification reaction rate and increase the carbon conversion.

Haichao Lv ◽  
Xiankun Huang ◽  
Lixia Kang ◽  
Yongzhong Liu

Abstract The capacity fading of lithium-ion batteries (LIBs) is reported by a linear dependency followed by a nonlinear ageing process, where the former is dominated by solid electrolyte interphase formation and reformation (SEI and SEI-re), while the latter is by lithium plating. In this work, a two-stage model is developed to quantitatively predict the turning point during the capacity fading of LIBs, which couples the electrochemical and thermal models accounting for SEI, SEI-re and lithium plating. Accordingly, a quantitative evaluation method of the turning point is proposed by attributing the transition of the capacity fading to the balance of consumption of active lithium for SEI growth and lithium plating per cycle in the two stages. The characteristics of capacity fading of LIBs are quantitatively analyzed under various operation conditions and design parameters. An NCM111/graphite battery is used to validate the proposed model. The results shows the validity of the proposed model. The turning points of the capacity fading processes are influenced by operation and design parameters of LIBs, where lithium plating or SEI growth reign. According to the effect on the turning point, the order of significance of the factors are charging current, charging cut-off voltage, temperature and N/P ratio, respectively.

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Hamid Reza Tamaddon Jahromi ◽  
Igor Sazonov ◽  
Jason Jones ◽  
Alberto Coccarelli ◽  
Samuel Rolland ◽  

Purpose The purpose of this paper is to devise a tool based on computational fluid dynamics (CFD) and machine learning (ML), for the assessment of potential airborne microbial transmission in enclosed spaces. A gated recurrent units neural network (GRU-NN) is presented to learn and predict the behaviour of droplets expelled through breaths via particle tracking data sets. Design/methodology/approach A computational methodology is used for investigating how infectious particles that originated in one location are transported by air and spread throughout a room. High-fidelity prediction of indoor airflow is obtained by means of an in-house parallel CFD solver, which uses a one equation Spalart–Allmaras turbulence model. Several flow scenarios are considered by varying different ventilation conditions and source locations. The CFD model is used for computing the trajectories of the particles emitted by human breath. The numerical results are used for the ML training. Findings In this work, it is shown that the developed ML model, based on the GRU-NN, can accurately predict the airborne particle movement across an indoor environment for different vent operation conditions and source locations. The numerical results in this paper prove that the presented methodology is able to provide accurate predictions of the time evolution of particle distribution at different locations of the enclosed space. Originality/value This study paves the way for the development of efficient and reliable tools for predicting virus airborne movement under different ventilation conditions and different human positions within an indoor environment, potentially leading to the new design. A parametric study is carried out to evaluate the impact of system settings on time variation particles emitted by human breath within the space considered.

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 525
Ran Duan ◽  
Jie Liu ◽  
Jianzhong Zhou ◽  
Pei Wang ◽  
Wei Liu

The prognostic is the key to the state-based maintenance of Francis turbine units (FTUs), which consists of performance state evaluation and degradation trend prediction. In practical engineering environments, there are three significant difficulties: low data quality, complex variable operation conditions, and prediction model parameter optimization. In order to effectively solve the above three problems, an ensemble prognostic method of FTUs using low-quality data under variable operation conditions is proposed in this study. Firstly, to consider the operation condition parameters, the running data set of the FTU is constructed by the water head, active power, and vibration amplitude of the top cover. Then, to improve the robustness of the proposed model against anomaly data, the density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean outliers and singularities in the raw running data set. Next, considering the randomness of the monitoring data, the healthy state model based on the Gaussian mixture model is constructed, and the negative log-likelihood probability is calculated as the performance degradation indicator (PDI). Furthermore, to predict the trend of PDIs with confidence interval and automatically optimize the prediction model on both accuracy and certainty, the multiobjective prediction model is proposed based on the non-dominated sorting genetic algorithm and Gaussian process regression. Finally, monitoring data from an actual large FTU was used for effectiveness verification. The stability and smoothness of the PDI curve are improved by 3.2 times and 1.9 times, respectively, by DBSCAN compared with 3-sigma. The root-mean-squared error, the prediction interval normalized average, the prediction interval coverage probability, the mean absolute percentage error, and the R2 score of the proposed method achieved 0.223, 0.289, 1.000, 0.641%, and 0.974, respectively. The comparison experiments demonstrate that the proposed method is more robust to low-quality data and has better accuracy, certainty, and reliability for the prognostic of the FTU under complex operating conditions.

Catalysts ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 80
Celia Alvarez-Gonzalez ◽  
Victoria E. Santos ◽  
Miguel Ladero ◽  
Juan M. Bolivar

Cellulose saccharification to glucose is an operation of paramount importance in the bioenergy sector and the chemical and food industries, while glucose is a critical platform chemical in the integrated biorefinery. Among the cellulose degrading enzymes, β-glucosidases are responsible for cellobiose hydrolysis, the final step in cellulose saccharification, which is usually the critical bottleneck for the whole cellulose saccharification process. The design of very active and stable β-glucosidase-based biocatalysts is a key strategy to implement an efficient saccharification process. Enzyme immobilization and reaction engineering are two fundamental tools for its understanding and implementation. Here, we have designed an immobilized-stabilized solid-supported β−glucosidase based on the glyoxyl immobilization chemistry applied in porous solid particles. The biocatalyst was stable at operational temperature and highly active, which allowed us to implement 25 °C as working temperature with a catalyst productivity of 109 mmol/min/gsupport. Cellobiose degradation was implemented in discontinuous stirred tank reactors, following which a simplified kinetic model was applied to assess the process limitations due to substrate and product inhibition. Finally, the reactive process was driven in a continuous flow fixed-bed reactor, achieving reaction intensification under mild operation conditions, reaching full cellobiose conversion of 34 g/L in a reaction time span of 20 min.

2022 ◽  
Vol 12 (2) ◽  
pp. 646
Chaimae El Fouas ◽  
Nelu Cristian Cherecheș ◽  
Sebastian Valeriu Hudișteanu ◽  
Bekkay Hajji ◽  
Emilian Florin Țurcanu ◽  

Photovoltaic/thermal (PV/T) systems are innovative cogeneration systems that ensure the cooling of photovoltaic (PV) backside and simultaneous production of electricity and heat. However, an effective cooling of the PV back is still a challenge that affects electrical and thermal performance of the PV/T system. In the present work, a PV/T numerical model is developed to simulate the heat flux based on energy balance implemented in MATLAB software. The numerical model is validated through the comparison of the three-layer PV model with the NOCT model and tested under the operation conditions of continental temperate climate. Moreover, the effect of velocity and water film thickness as important flow parameters on heat exchange and PV/T production is numerically investigated. Results revealed that the PV model is in good agreement with the NOCT one. An efficient heat transfer is obtained while increasing the velocity and water film thickness with optimal values of 0.035 m/s and 7 mm, respectively, at an inlet temperature of 20 °C. The PV/T system ensures a maximum thermal power of 1334.5 W and electrical power of 316.56 W (258.8 W for the PV). Finally, the comparison between the PV and PV/T system under real weather conditions showed the advantage of using the PV/T.

Xiaoda Wang ◽  
Yuanyuan Liu ◽  
Dayu Liu ◽  
Xuehui Ge ◽  
Ling Li ◽  

Droplet breakup in micro-constrictions is an important phenomenon in industrial applications. This work aimed to investigate the droplet breakup in the square microchannel with a short square constriction to generate the slug flow, which drew little attention before. Mechanism analysis indicated that this breakup process included the shear-force-dominated, squeezing-force-dominated, and pinch-off stages. Non-uniform daughter droplets were generated in the constriction with their interface restricted in the horizontal and perpendicular directions by the microchannel walls. The average relative deviation of the daughter droplet size was < 30%, much lower than that for the breakup with the daughter droplet restricted only in one direction. An empirical equation with a deviation of < 20% was provided to show the dependence of the daughter droplet size on the operation conditions. The comparison results suggested that the different restriction effects of microchannel wall on daughter droplets led to the different breakup mechanisms in different constrictions.

2022 ◽  
Vol 05 (02) ◽  
pp. 26-40
Abadal-Salam T. Hussain

The continuous monitoring of transmission line protection relay is desirable to ensure the system disturbance such as fault inception is detected in transmission line. Therefore, fault on transmission line needs to be detected, classified, and located accurately to maintain the stability of system. This project presents design enhancement and development under voltage relay in power system protection using MATLAB/Simulink. The under-voltage relay is a relay that has contacts that operate when voltage drops below a set voltage which is used for protection against voltage drops to detect short circuit and others. This study is carried out for all types of faults which only related with one of the parallel lines. For the overall of operation conditions, the sample data were generated for the system by varying the different fault types and fault location. This design system proposes the use of MATLAB/ Simulink based method for fast and reliable fault classification and location for a various type of fault.

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