Thermomechanical stability and inelastic energy dissipation as durability criteria for fuel cell gas diffusion media with pre-assembly effects

In this article, pre-assembly hot-press pressure and thermal expansion effects in gas-diffusion layers (GDLs) are addressed to explore the practicalities of the constitutive model reported in the companion article. A facile technique is proposed to include deformation history dependent residual strain effects. The model is implemented in the numerical environment and compared with widely followed conventional models such as isotropic and orthotropic material models. With the normal and accelerated thermal expansion effects no significant variation in stresses or strains is reported with the compressible GDL model in contrast to the conventional incompressible form of the GDL model. The present work identifies the critical differences with advanced and extended variants of the model along with conventional GDL material models in terms of planar stress/strain distribution and the membrane response. Finally, the model is simulated for micro-cyclic stress loads of varying amplitudes that imitate the real working conditions of fuel cell. The inelastic energy dissipation in GDLs is predicted using the proposed model, which is utilized further to distinguish the safe (elastic) and unsafe (inelastic shakedown) operating limits. The inelastic collapse of GDLs is shown to be a active function of high amplitude micro-cyclic load with high initial clamping load.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

Life cycle cost of conventional,battery electric,and fuel cell electric vehicles considering traffic and environmental policies in China

Electric vehicles (EVs) are considered a promising alternative to conventional vehicles (CVs) to alleviate the oil crisis and reduce urban air pollution and carbon emissions. Consumers usually focus on the tangible cost when choosing an EV or CV but overlook the time cost for restricting purchase or driving and the environmental cost from gas emissions, falling to have a comprehensive understanding of the economic competitiveness of CVs and EVs. In this study, a life cycle cost model for vehicles is conducted to express traffic and environmental policies in monetary terms, which are called intangible cost and external cost, respectively. Battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), and CVs are compared in four first-tier, four new first-tier, and 4 s-tier and below cities in China. The comparison shows that BEVs and FCEVs in most cities are incomparable with CVs in terms of tangible cost. However, the prominent traffic and environmental policies in first-tier cities, especially in Beijing and Shanghai, greatly increase the intangible and external costs of CVs, making consumers more inclined to purchase BEVs and FCEVs. The main policy benefits of BEVs and FCEVs come from three aspects: government subsidies, purchase and driving restrictions, and environmental taxes. With the predictable reduction in government subsidies, traffic and environmental policies present important factors influencing the competitiveness of BEVs and FCEVs. In first-tier cities, BEVs and FCEVs already have a competitive foundation for large-scale promotion. In new first-tier and second-tier and below cities, stricter traffic and environmental policies need to be formulated to offset the negative impact of the reduction in government subsidies on the competitiveness of BEVs and FCEVs. Additionally, a sensitivity analysis reveals that increasing the mileage and reducing fuel prices can significantly improve the competitiveness of BEVs and FCEVs, respectively.     

Techno-economical evaluations of decarbonized hydrogen production based on direct biogas conversion using thermo-chemical looping cycles

Hydrogen production by biogas conversion represent a promising solution for reduction of fossil CO₂ emissions. In this work, a detailed techno-economic analysis was performed for decarbonized hydrogen production based on biogas conversion using calcium and chemical looping cycles. All evaluated concepts generate 100,000 Nm³/h high purity hydrogen. As reference cases, the biogas steam reforming design without decarbonization and with CO₂ capture by gas-liquid chemical absorption were also considered. The results show that iron-based chemical looping design has higher energy efficiency compared with the gas-liquid absorption case by 2.3 net percentage points as well as a superior carbon capture rate (99% vs. 65%). The calcium looping case shows a lower efficiency than chemical scrubbing, with about 2.5 net percentage points, but the carbon capture rate is higher (95% vs. 65%). The hydrogen production cost increases with decarbonization, the calcium looping shows the most favourable situation (37.14 €/MWh) compared to the non-capture steam reforming case (33 €/MWh) and MDEA and iron looping cases (about 42 €/MWh). The calcium looping case has the lowest CO₂ avoidance cost (10 €/t) followed by iron looping (20 €/t) and MDEA (31 €/t) cases.     

Use of La2O3 with 8YSZ as thermal barrier coating and its effect on thermal cycle behavior,microstructure, mechanical properties and performance of diesel engine operated by hydrogen-algae biodiesel blend

In this present work, the effect of lanthanum oxides (La₂O₃) on the thermal cycle behavior of TBC coatings and mechanical properties such as adhesion strength and microhardness of 8% Yttria Stabilized Zirconia (8YSZ) TBCs were investigated. CoNiCrAlY and aluminium alloy (Al–13%Si) were used as bond coat and substrate materials. 8YSZ and different wt % of La₂O₃ (10, 20, and 30%) top coatings were applied using the atmospheric plasma spray (APS) method. The thermal cycling test for TBC coated samples were conducted at 800 °C in the electric furnace. The XRD pattern shows that the La₂O₃ doped 8YSZ material transformed to cubic pyrochloric structured La₂Zr₂O₇ during thermal cycling. Further, the Taguchi-based grey relation analysis (GRA) method was applied to optimize the TBC coating parameters to achieve better mechanical properties such as adhesion strength and microhardness. And the optimized La₂O₃/8YSZ TBC coating was coated on CRDI engine combustion chamber components. The engine was tested with microalgae biodiesel and hydrogen, and the results were promising for the TBC-coated engine. The engine performance increased while using La₂O₃/8YSZ coated components, and the emissions from engine exhaust gas such as CO, HC, and smoke reduced considerably. It was found that there was no separation crack and spallation of the coating layer in the microstructure. Ultimately, the microstructural analysis of the optimized TBC coated piston sample after 50 h of running in the diesel engine confirmed that the developed coating had a superior thermal insulation effect and longer life.     

Use of a smartphone-based Student Response System in large active-learning Chemical Engineering Thermodynamics classrooms

Smartphones are a promising tool as student response systems (SRS) for interactive teaching due to their widespread diffusion. Here, the main purpose is to assess the efficacy of smartphone-based SRS in large classroom settings of undergraduate Thermodynamics, as representative of engineering courses requiring high-level cognitive skills for problem solving. Four sets of multiple-choice questions were presented during the course. Overall, the results refer to 1055 students between control and SRS classes, each corresponding to a3 years period.One of the main results of this work is the strong linear correlation between the average questionnaire score and the final exam grade (R² = 0.91). A similar correlation, although with a lower value of R², is already found in the first questionnaire, thus showing the SRS high predictive power of class performance. The results of this study provide guidance for a quantitative use of smartphone-based SRS in teaching basic disciplines. The SRS monitoring capability allows early detection of struggling students, thus paving the way to personalized tutoring and improved student engagement in active learning practices. This approach is especially important in emergency situations, such as the SARS-Cov-2 pandemic, when distance learning is widely adopted, and remote interactive tools are highly needed.     

Exploring the feasibility of green hydrogen production using excess energy from a country-scale 100% solar-wind renewable energy system

When planning large-scale 100% renewable energy systems (RES) for the year 2050, the system capacity is usually oversized for better supply-demand matching of electrical energy since solar and wind resources are highly intermittent. This causes excessive excess energy that is typically dissipated, curtailed, or sold directly. The public literature shows a lack of studies on the feasibility of using this excess for country-scale co-generation. This study presents the first investigation of utilizing this excess to generate green hydrogen gas. The concept is demonstrated for Jordan using three solar photovoltaic (PV), wind, and hybrid PV-wind RESs, all equipped with Lithium-Ion battery energy storage systems (ESSs), for hydrogen production using a polymer electrolyte membrane (PEM) system. The results show that the PV-based system has the highest demand-supply fraction (>99%). However, the wind-based system is more favorable economically, with installed RES, ESS, and PEM capacities of only 23.88 GW, 2542 GWh, and 20.66 GW. It also shows the highest hydrogen annual production rate (172.1 × 10³ tons) and the lowest hydrogen cost (1.082 USD/kg). The three systems were a better option than selling excess energy directly, where they ensure annual incomes up to 2.68 billion USD while having payback periods of as low as 1.78 years. Furthermore, the hydrogen cost does not exceed 2.03 USD/kg, which is significantly lower than the expected cost of hydrogen (3 USD/kg) produced using energy from fossil fuel-based systems in 2050.     

Trade-off study between risk and benefit in safety devices for hydrogen refueling stations using a dynamic physical model

As hydrogen refueling stations become increasingly common, it is clear that a high level of economic efficiency and safety is crucial to promoting their use. One way to reduce costs is to use a simple orifice instead of an excess flow valve, which Japanese safety regulations have identified as a safety device. However, there is concern about its effect on refueling time and on risk due to hydrogen leakage. To clarify the effect, we did a study of model-based refueling time evaluation and quantitative risk assessment for a typical refueling station. This study showed that an orifice is an effective alternative safety device. The increase in refueling time was less than 10%, based on simulations using a dynamic physical model of the station. Neither was there a significant difference in the risk between a configuration with excess flow valves and one with an orifice.     

Thermo-economic investigation on the hydrogen production through the stored solar energy in a salinity gradient solar pond: A comparative study by employing APC and ORC with zeotropic mixture

In this paper, a salinity gradient solar pond (SGSP) is used to harness the solar energy for hydrogen production through two cycles. The first cycle includes an absorption power cycle (APC), a proton exchange membrane (PEM) electrolyzer, and a thermoelectric generator (TEG) unit; in the second one, an organic Rankine cycle (ORC) with the zeotropic mixture is used instead of APC. The cycles are analyzed through the thermoeconomic vantage point to discover the effect of key decision variables on the cycles’ performance. Finally, NSGA-II is used to optimize both cycles. The results indicate that employing ORC with zeotropic mixture leads to a better performance in comparison to utilizing APC. For the base mode, unit cost product (UCP), exergy, and energy efficiency when APC is employed are 59.9 $/GJ, 23.73%, and 3.84%, respectively. These amounts are 47.27 $/GJ, 29.48%, and 5.86% if ORC with the zeotropic mixture is utilized. The APC and ORC generators have the highest exergy destruction rate which is equal to 6.18 and 10.91 kW. In both cycles, the highest investment cost is related to the turbine and is 0.8275 $/h and 0.976 $/h for the first and second cycles, respectively. In the optimum state the energy efficiency, exergy efficiency, UCP, and H₂ production rate of the system enhances 42.44%, 27.54%,15.95%, and 38.24% when ORC with the zeotropic mixture is used. The maximum H₂ production is 0.47 kg/h, and is obtained when the mass fraction of R142b, LCZ temperature, pumps pressure ratio, generator bubble point temperature are 0.603, 364.35 K, 2.12, 337.67 K, respectively.