The clinical assessment of abdominal aortic aneurysm (AAA) rupture risk is based on the quantification of AAA size by measuring its maximum diameter from computed tomography (CT) images and estimating the expansion rate of the aneurysm sac over time. Recent findings have shown that geometrical shape and size, as well as local wall thickness may be related to this risk; thus, reliable noninvasive image-based methods to evaluate AAA geometry have a potential to become valuable clinical tools. Utilizing existing CT data, the three-dimensional geometry of nine unruptured human AAAs was reconstructed and characterized quantitatively. We propose and evaluate a series of 1D size, 2D shape, 3D size, 3D shape, and second-order curvature-based indices to quantify AAA geometry, as well as the geometry of a size-matched idealized fusiform aneurysm and a patient-specific normal abdominal aorta used as controls. The wall thickness estimation algorithm, validated in our previous work, is tested against discrete point measurements taken from a cadaver tissue model, yielding an average relative difference in AAA wall thickness of 7.8%. It is unlikely that any one of the proposed geometrical indices alone would be a reliable index of rupture risk or a threshold for elective repair. Rather, the complete geometry and a positive correlation of a set of indices should be considered to assess the potential for rupture. With this quantitative parameter assessment, future research can be directed toward statistical analyses correlating the numerical values of these parameters with the risk of aneurysm rupture or intervention (surgical or endovascular). While this work does not provide direct insight into the possible clinical use of the geometric parameters, we believe it provides the foundation necessary for future efforts in that direction.

Lithium-ion batteries (LIBs) are leading the energy storage market. Significant efforts are being made to widely adopt LIBs due to their inherent performance benefits and reduced environmental impact for transportation electrification. However, achieving this widespread adoption still requires overcoming critical technological constraints impacting battery aging and safety. Battery aging, an inevitable consequence of battery function, might lead to premature performance losses and exacerbated safety concerns if effective thermo-electrical battery management strategies are not implemented. Battery aging effects must be better understood and mitigated, leveraging the predictive power of aging modelling methods. This review paper presents a comprehensive overview of the most recent aging modelling methods. Furthermore, a multiscale approach is adopted, reviewing these methods at the particle, cell, and battery pack scales, along with corresponding opportunities for future research in LIB aging modelling across these scales. Battery testing strategies are also reviewed to illustrate how current numerical aging models are validated, thereby providing a holistic aging modelling strategy. Finally, this paper proposes a combined multiphysics- and data-based modelling framework to achieve accurate and computationally efficient LIB aging simulations.

Electric vehicle battery performance near end-of-life is limited by mismatched cell degradation, leading to an estimated 5-10% cell capacity variation across the pack. Active cell balancing hardware architectures incorporating a Low-Voltage (LV) bus supply have been introduced to unlock lost capacity due to cell imbalance at reduced cost, through elimination of the vehicle's 400-to-12V dc-dc converter. In this work, a hierarchical model-predictive control scheme is applied to a time-shared isolated converter active balancing architecture that incorporates LV bus supply. The proposed controller efficiently divides computation among the battery management system hardware components. The energy-buffering capability of the lead-acid battery, which is connected to the LV bus, is used to trade-off balancing and bus regulation objectives, reducing peak power and improving the system cost-effectiveness. Simultaneous state-of-charge balancing and LV bus regulation is verified in simulation and experiment using real-world drive and LV load data collected from a GM Bolt electric vehicle. Similar controller performance compared to a central scheme is achieved in simulation. The experimental setup includes a custom 12S2P, 3.9kWh, liquid-cooled Lithium Nickel Manganese Cobalt battery module with embedded battery management system. The controller performance is evaluated with an initial maximum state-of-charge imbalance of 6.8%.

Promoting coherent transport of phonons at material interfaces is a promising strategy for controlling thermal transport in nanostructures and an alternative to traditional methods based on structural defects. Coherent transport is particularly relevant in short-period heterostructures with smooth interfaces and long-wavelength heat-carrying phonons, such as two-dimensional superlattices of graphene and boron nitride. In this work, we predict phonon properties and thermal conductivities in these superlattices using a normal mode decomposition approach. We study the variation of the frequency dependence of these properties with the periodicity and interface configuration (zigzag and armchair) for superlattices with period lengths within the coherent regime. Our results showed that the thermal conductivity decreases significantly from the first period length (0.44 nm) to the second period length (0.87 nm), 13% across the interfaces and 16% along the interfaces. For greater periods, the conductivity across the interfaces continues decreasing at a smaller rate of 11 W/mK per period length increase (0.43 nm), driven by changes in the phonon group velocities (coherent effects). In contrast, the conductivity along the interfaces slightly recovers at a rate of 2 W/mK per period, driven by changes in the phonon relaxation times (diffusive effects). By changing the interface configuration from armchair to zigzag, the conductivities for all period lengths increase by approximately 7% across the interfaces and 19% along the interfaces.