Influence of soil density on gas permeability and water retention in soils amended with in-house produced biochar

Biochar has been used as an environment-friendly enhancer to improve the hydraulic properties(e.g.suction and water retention) of soil.However,variations in densities alter the properties of the soil-biochar mix.Such density variations are observed in agriculture(loosely compacted) and engineering(densely compacted) applications.The influence of biochar amendment on gas permeability of soil has been barely investigated,especially for soil with diffe rent densities.The maj or obj ective of this study is to investigate the water retention capacity,and gas permeability of biochar-amended soil(BAS) with different biochar contents under varying degree of compaction(DOC) conditions.In-house produced novel biochar was mixed with the soil at different amendment rates(i.e.biochar contents of 0%,5% and 10%).All BAS samples were compacted at three DOCs(65%,80% and 95%) in polyvinyl chloride(PVC)tubes.Each soil column was subjected to drying-wetting cycles,during which soil suction,water content,and gas permeability were measured.A simplified theoretical framework for estimating the void ratio of BAS was proposed.The experimental results reveal that the addition of biochar significantly decreased gas permeability k_g as compared with that of bare soil(BS).However,the addition of 5%biochar is found to be optimum in decreasing kg with an increase of DOC(i.e.k_(g,65%) k_(g,80%) k_(g,95%)) at a relatively low suction range(200 kPa) because both biochar and compaction treatment reduce the connected pores.     

Study on effect of diverse air inlet arrangement on thermal management of cylindrical lithium-ion cells

Lithium-ion cells are preferred in the electrical powertrain due to high-power density, compactness, and modularity. In real driving conditions, the cells undergo discharge rates as high as 4 C resulting in high heat generation affecting the performance. To obtain the maximum performance the pack construction and thermal management of cells are crucial parameters. In our work, air-cooled technique with diverse air inlet and staggered scheme with a two-channel partition approach for thermal management of the cylindrical lithium-ion cells are studied in computational fluid dynamics. The simulation model is validated with experimental results. The obtained results demonstrate that the cells in the dual-directional air inlet arrangement had low maximum temperature difference among and within the cells and required least fan work. This arrangement required least fan work to generate optimal air inlet velocity of 2 m/s for 1, 2, and 3 C and 4 m/s for 4 C discharge rates. There is a reduction of 50% and 33% fan work for 3 and 4 C discharge rates, which are the majority operating points. Also, it shows that the temperature uniformity within the cells has improved. The results of this study can used to optimize parameters for designing an enhanced thermal management system.     

Phase development and pore stability of yttria- and ytterbia-stabilized zirconia aerogels

High-porosity yttria- and ytterbia-stabilized zirconia aerogels offer the potential of extremely low thermal conductivity materials for high-temperature applications. Yttria- and ytterbia-doped zirconia aerogels were synthesized using a sol-gel approach over the dopant range of 0-20 atomic percent. Surface area, pore volume, and morphology of the as-dried aerogels and materials thermally exposed for short periods of time to temperatures up to 1200°C were characterized by nitrogen physisorption, scanning and transmission electron microscopy, and X-ray diffraction. The aerogels as supercritically dried all were X-ray amorphous. At a 5% dopant level, a tetragonal structure with a smaller monoclinic phase developed on thermal exposure. Mixed tetragonal and cubic phases or predominantly cubic materials were observed at higher dopant levels, depending on the dopant level, temperature and exposure time. The formation of crystalline phases was accompanied by loss of surface area and pore volume, although some mesoporous structure was maintained on short-term exposure to 1000°C. Incorporation of the smaller Yb atom into the lattice structure resulted in smaller lattice dimensions on crystallization than was seen with Y doping and favored a more highly equiaxed structure. Aerogels synthesized with 15% Y maintained the smallest particle size without evidence of sintering at 1100°C. Largest shrinkage and loss of pore volume occurred on crystallization from the amorphous phase, with further loss of pores at temperatures above 1000°C attributable to changes in lattice parameters.     

Robust model for optimization of forming process for metallic bipolar plates of cleaner energy production system

Energy production systems such as proton-exchange membrane fuel cell (PEMFC) has a promising future in the cleaner energy market due to zero emissions. Rubber pad forming (RPF) process of metallic bipolar plates of PEMFCs is gaining attention among the researchers. Studies based on design of experiments have been conducted to find the crucial parameters of the forming process. These methods are based on the assumptions of the model structure, correlated residuals, etc., which can cause uncertainty in estimation ability of the model on unseen data. Therefore, the present study focuses on the design of robust models of these parameters for PEMFCs using an optimization approach of genetic programming (GP). The inputs from the experiments considered in GP are radius, the friction coefficient, the filling factor and the minimum thickness. Experiments on PEMFCs validates the performance of the GP models. Further, the relationships between the two inputs and the three outputs for PEMFCs are generated as well as the contributions of each input to each of the output. Optimization of the models generated by GP can further determine the forming quality of metallic bipolar plates of PEMFCs by an appropriate setting of the two inputs.     

Experimental and optimization of material synthesis process parameters for improving capacity of lithium‐ion battery

New methods for synthesis of active materials have been developed to improve capacity and cycle life performance of lithium‐ion batteries. Past studies have focused on routes of development of materials and new processes, which might not be economical for large‐scale production. In this regard, this study examines a widely employed carbothermal reduction technology for the synthesis of lithium‐iron phosphate (LiFePO₄/C) and investigates effects of process conditions during this synthesis on final battery performance. An experimental combined genetic programming approach is used to model the effects of crucial process conditions (sintering time, the carbon content, and the sintering temperature) on the discharge capacity of the assembled battery. Experiments are conducted to collect the discharge capacity data based on varying LiFePO₄/C synthesis conditions, and genetic programming is employed to develop a suitable functional relationship between them. The results show that the battery discharge capacity is controlled significantly by adjusting sintering temperature and carbon content, while the effect of sintering time is found to be insignificant. Further, the interaction effect of the sintering time and carbon content is much more obvious than that of the sintering time and the sintering temperature. The findings from the study pave the way for the optimum design of the synthesis process of LiFePO₄/C for a higher battery performance.     

Durability of YSZ coated Ti2AlC in 1300°C high velocity burner rig tests

A thermal barrier coating (TBC) system survived 500 hours in aggressive, 1300°C burner rig testing. The yttria-stabilized zirconia (7YSZ) TBC was plasma sprayed on an oxidation-resistant Ti₂AlC-type MAX phase and tested in a jet fuel burner at 100 m/s, using 5 hours cycles. No coating spallation or surface recession was observed; Al₂O₃-scale growth produced a slight 2.4 mg/cm² mass gain. The coating surface exhibited craze-cracked colonies of [111]_flourite textured columns, with no visible moisture attack. The 20 μm alumina scale remained intact under the YSZ face, about twice that producing failure for TBC/superalloy systems. TiO₂ nodules, initially formed on the uncoated backside, were removed, and Al₂O₃ was etched through volatile hydroxides formed in water vapor (~10%). Overall, the test indicated exceptional stability of the YSZ/Al₂O₃/Ti₂AlC system under turbine conditions due in large part to close thermal expansion matching.     

A coupled and interactive influence of operational parameters for optimizing power output of cleaner energy production systems under uncertain conditions

The mechanisms in proton‐exchange membrane fuel cells (PEMFCs) cannot be explicitly represented by a mathematical function because the PEMFC system is multi‐dimensional and complex and represents uncertainty in operation variables, which cannot be modeled by experiments or by trial‐and‐error approach. Therefore, this work proposes to study the coupled and interactive influence of stack current (SC), stack temperature (ST), oxygen excess ratio (OER), hydrogen excess ratio (HER), and inlet air humidity (IAH) for optimizing the power output of PEMFC. The data obtained from the experiments have been inserted into architecture of automated neural‐network search, which automates the selection of error function, activation function, uncertainties in inputs and number of hidden neurons in formulation of a robust and accurate model for power density as a function of five operational variables. Among the operational variables, the correlation coefficient between the SC and the output power is the highest, followed by OER, and the ST. However, for HER and IAH, the power output follows negative nonlinear relation. The optimization converged at 130^th iteration results in maximum power output of 3410 W for an optimum value of SC (51A), ST (59°C), OER (3:2), HER (1:10), and IAH (0.8).     

KAGO: an approximate adaptive grid-based outlier detection approach using kernel density estimate

Pattern Analysis and Applications - Outlier detection approaches show their efficacy while extracting unforeseen knowledge in domains such as intrusion detection, e-commerce, and fraudulent...     

Aging model development based on multidisciplinary parameters for lithium-ion batteries

In this paper, a method composed of state of health (SOH) testing experiments and artificial intelligence simulation is proposed to carry out the study on the change of battery characteristic during its operation and generate mathematical models for the prediction of aging behaviour of battery. An experiment comprising of multidisciplinary parameters-based SOH detection is conducted to study the battery aging characteristics from several aspects (ie, electrochemistry, electric, thermal behaviour and mechanics). In total, 200 sets of data (corresponding 200 charging/discharging cycles) are collected from the experiment. The data obtained from the first 150 cycles are employed in generation of the models. The result of sensitivity analysis based on the obtained genetic programming models shows that it is better to apply voltage value at the end of charging step, charging time and cycle number to predict the operational performance of the battery. The average predicted accuracy of model (without stress) is 94.52%, whereas the average predicted accuracy of model (with stress effect) is 99.42%. The proposed models could be useful for defining the optimised charging strategy, fault diagnosis and spent batteries disposal strategies.