Numerical investigation of light gas release,stratification and dissolution in TH22 test facility using 3-D CFD code GASFLOW-MPI

An accurate prediction of the hydrogen behaviors in the accident and management process is a crucial topic for both the hydrogen safety assessment and safety analysis in the confined enclosure like the containment of the nuclear power plant (NPP). Hence, the hydrogen behaviors including the transient light gas release, stratification and dissolution in the TH22 test facility for the NPP containment are analyzed and compared using the 3-D CFD code GASFLOW-MPI in this study. In this paper, the light gas helium is adopted as a substitute for the hydrogen in the calculations in accordance with the experiment. Firstly, the detached eddy simulation (DES) turbulence model, 3-D numerical model and experiment setup are introduced. Then, the hydrogen behaviors with the GASFLOW-MPI including the light gas release, stratification and dissolution are analyzed and validated with the experiment data. In addition, the velocity profiles, light gas concentrations, dimensionless numbers and temperature distributions are evaluated for the characteristics of the hydrogen behaviors. The results indicate that the calculation results agree well with the experiment data. Foremostly, the relative errors between the calculation results and experiment data during the phase of the dissolution of the light gas cloud are within 11.9%. Meanwhile, the relative errors of the time for the complete dissolution during the phase of the dissolution of the light gas cloud are within 5.0%. For the light gas release and stratification phase, the jet flow dominates as the Froude (Fr) number exceeds 10 during the time t = 600 s–800 s. Additionally, the time averaged centerline velocity and light gas concentration after the potential core region decay with a slop of 1/z which coincide with the theoretical jet limit. Lastly, the light gas concentrations and temperature distributions in all three phases are captured clearly with the GAFLOW-MPI. It demonstrates that the GASFLOW-MPI can accurately described the details of the related hydrogen behaviors in the accident and management process in the confined enclosure like the NPP. This paper can provide guidance for the numerical computation of the hydrogen safety issues in the confined space.     

Experimental investigation on the dynamic responses of vented hydrogen explosion in a 40-foot container

To investigate the structural dynamics of a container subjected to a vented hydrogen explosion, 48 field tests were conducted in a 40-foot container with roof vents and an end vent. The effects of the hydrogen concentration, ignition position, and obstacles on the evolution of the dynamic responses were investigated. Three stages were generally observed for displacements: (1) At the stage of the vent rupture, the displacement could be approximated as a quasi-static response, and there was a linear relationship between the peaks of positive overpressure and displacement. (2) Structural deformation appeared as reciprocating vibration at the stage of Helmholtz oscillation. (3) The structure exhibited relatively weak irregular fluctuation when high-frequency acoustic oscillation occurred. Two types of the structural acceleration with low and high amplitudes resulting from Helmholtz oscillation and acoustic oscillation, respectively, were clearly observed. For the end-vented explosion, multiple peaks were observed for the displacement at the quasi-static stage due to the rupture, discharge, and external explosion. Moreover, the displacement was sensitive to hydrogen concentration, whereas the number of obstacles and the ignition position had significant influences on the peak acceleration for roof venting. This work conducted the fundamental explanation for the evolution law of structural responses induced by vented hydrogen explosions from the perspective of structural dynamics and enriched the experimental accumulation in a large-scale container with congestion in this field.     

Worldwide aflatoxin contamination of agricultural products and foods: From occurrence to control

Aflatoxins represent a global public health and economic concern as they are responsible for significant adverse health and economic issues affecting consumers and farmers worldwide. Produced by fungal species from the Aspergillus genus, aflatoxins are a toxic, mutagenic, and carcinogenic group of fungal metabolites that routinely contaminate food and agricultural products. Climate and diet are essential factors in the aflatoxin contamination of food and subsequent human exposure process. Countri es with warmer climates and staple foods that are aflatoxin-susceptible shoulder a substantial portion of the global aflatoxins burden. Enactment of regulations, prevention of pre- and postharvest contamination, decontamination, and detoxification have been used to prevent human dietary exposure to aflatoxin. Exploiting their chemical and structural properties, means are devised to detect and quantify aflatoxin presence in foods. Herein, recent developments in several important aspects impacting aflatoxin contamination of the food supply, including: fungal producers of the toxin, occurrence in food, worldwide regulations, detection methods, preventive strategies, and removal and degradation methods were reviewed and presented. In conclusion, aflatoxin continues to be a major food safety problem, especially in developing countries where regulatory limits do not exist or are not adequately enforced. Finally, knowledge gaps and current challenges in each discussed aspect were identified, and new solutions were proposed.     

An unsupervised approach for fault diagnosis of power transformers

Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, various advanced analytical methods have been proposed in the literature. Nonetheless, these methods are often hard to interpret by the decision-maker and require a substantial amount of failure records to be trained. In the context of the PTs, failure data quality is recurrently questionable, and failure records are scarce when compared to nonfailure records. This work tackles these challenges by proposing a novel unsupervised methodology for diagnosing PT condition. Differently from the supervised approaches in the literature, our method does not require the labeling of DGA records and incorporates a visual representation of the results in a 2D scatter plot to assist in interpretation. A modified clustering technique is used to classify the condition of different PTs using historical DGA data. Finally, well-known engineering methods are applied to interpret each of the obtained clusters. The approach was validated using data from two different real-world data sets provided by a generation company and a distribution system operator. The results highlight the advantages of the proposed approach and outperformed engineering methods (from IEC and IEEE standards) and companies legacy method. The approach was also validated on the public IEC TC10 database, showing the capability to achieve comparable accuracy with supervised learning methods from the literature. As a result of the methodology performance, both companies are currently using it in their daily DGA diagnosis.     

Life-cycle assessment of hydrogen technologies with the focus on EU critical raw materials and end-of-life strategies

We present the results of a life-cycle assessment (LCA) for the manufacturing and end-of-life (EoL) phases of the following fuel-cell and hydrogen (FCH) technologies: alkaline water electrolyser (AWE), polymer-electrolyte-membrane water electrolyser (PEMWE), high-temperature (HT) and low-temperature (LT) polymer-electrolyte-membrane fuel cells (PEMFCs), together with the balance-of-plant components. New life-cycle inventories (LCIs), i.e., material inputs for the AWE, PEMWE and HT PEMFC are developed, whereas the existing LCI for the LT PEMFC is adopted from a previous EU-funded project. The LCA models for all four FCH technologies are created by modelling the manufacturing phase, followed by defining the EoL strategies and processes used and finally by assessing the effects of the EoL approach using environmental indicators. The effects are analysed with a stepwise approach, where the CML2001 assessment method is used to evaluate the environmental impacts. The results show that the environmental impacts of the manufacturing phase can be substantially reduced by using the proposed EoL strategies (i.e., recycled materials being used in the manufacturing phase and replacing some of the virgin materials). To point out the importance of critical materials (in this case, the platinum-group metals or PGMs) and their recycling strategies, further analyses were made. By comparing the EoL phase with and without the recycling of PGMs, an increase in the environmental impacts is observed, which is much greater in the case of both fuel-cell systems, because they contain a larger quantity of PGMs.     

Validation of two-layer model for underexpanded hydrogen jets

Previous studies have shown that the two-layer model more accurately predicts hydrogen dispersion than the conventional notional nozzle models without significantly increasing the computational expense. However, the model was only validated for predicting the concentration distribution and has not been adequately validated for predicting the velocity distributions. In the present study, particle imaging velocimetry (PIV) was used to measure the velocity field of an underexpanded hydrogen jet released at 10 bar from a 1.5 mm diameter orifice. The two-layer model was the used to calculate the inlet conditions for a two-dimensional axisymmetric CFD model to simulate the hydrogen jet downstream of the Mach disk. The predicted velocity spreading and centerline decay rates agreed well with the PIV measurements. The predicted concentration distribution was consistent with data from previous planar Rayleigh scattering measurements used to verify the concentration distribution predictions in an earlier study. The jet spreading was also simulated using several widely used notional nozzle models combined with the integral plume model for comparison. These results show that the velocity and concentration distributions are both better predicted by the two-layer model than the notional nozzle models to complement previous studies verifying only the predicted concentration profiles. Thus, this study shows that the two-layer model can accurately predict the jet velocity distributions as well as the concentration distributions as verified earlier. Though more validation studies are needed to improve confidence in the model and increase the range of validity, the present work indicates that the two-layer model is a promising tool for fast, accurate predictions of the flow fields of underexpanded hydrogen jets.     

Effect of water distribution in gas diffusion layer on proton exchange membrane fuel cell performance

Water management of proton exchange membrane fuel cells remains a prominent issue in research concerning fuel cells. In this study, the gas diffusion layer (GDL) of a fuel cell is partially treated with a hydrophobic agent, and the effect of GDL hydrophobicity on the water distribution in the fuel cell is examined. First, the effect of the position of the cathode GDL hydrophobic area relative to the channel on the fuel cell performance is investigated. Then, the water distribution in the fuel cell cathode GDL is observed using X-ray imaging. The experimental results indicate that when the hybrid GDL's hydrophobic area lies on the channel, water tends to accumulate under the rib, and the water content in the channel is low; this improves the fuel cell performance. When the hydrophobic area is under the rib, the water distribution is more uniform, but the performance deteriorates.     

Efficient fault diagnosis method of PEMFC thermal management system for various current densities

The temperature of a fuel cell has a considerable impact on the saturation of a membrane, electrochemical reaction speed, and durability. So thermal management is considered one of the critical issues in polymer electrolyte membrane fuel cells. Therefore, the reliability of the thermal management system is also crucial for the performance and durability of a fuel cell system. In this work, a methodology for component-level fault diagnosis of polymer electrolyte membrane fuel cell thermal management system for various current densities is proposed. Specifically, this study suggests fault diagnosis using limited data, based on an experimental approach. Normal and five component-level fault states are diagnosed with a support vector machine model using temperature, pressure, and fan control signal data. The effects of training data at different operating current densities on fault diagnosis are analyzed. The effects of data preprocessing method are investigated, and the cause of misdiagnosis is analyzed. On this basis, diagnosis results show that the proposed methodology can realize efficient component-level fault diagnosis using limited data. The diagnosis accuracy is over 92% when the residual basis scaling method is used, and data at the highest operating current density is used to train the support vector machine.