Porous sandwich structures, particularly aluminum foam sandwiches (AFS), are widely used in lightweight and impact-resistant applications, yet their mechanical performance remains difficult to predict due to irregular and multiscale pore morphologies. Traditional constitutive models and current deep learning methods fall short in capturing the complex structure–property relationships of those materials. Accordingly, this work proposes a three-dimensional (3D) pore cloud representation learning method tailored for energy absorption prediction. A novel digital descriptor, termed the pore cloud, is constructed from 3D scans of real AFS cores to preserve detailed pore-level geometric and topological information. A comprehensive structure–property dataset is subsequently generated by integrating these pore cloud features with energy absorption data obtained through finite element analysis (FEA). Furthermore, this work develops PoreNet, a point cloud-based deep learning architecture that learns the direct mapping from mesoscale pore morphology to macroscopic mechanical response. The experimental results demonstrate that PoreNet achieves a high prediction accuracy of 95.12%, robust generalization across variable porosities, and fast convergence within 30 min on a consumer-grade Graphics Processing Unit (GPU). It outperforms both traditional analytical models and baseline neural networks. In addition, this study demonstrates the effectiveness of pore-level geometric learning in structure–property modeling and offers a scalable, data-driven framework for the design and optimization of advanced porous sandwich composites. The dataset and the proposed algorithm are publicly available at https://crescentrosexx.github.io/pore-net/.

The transesterification of propylene carbonate (PC) or ethylene carbonate (EC) to dimethyl carbonate (DMC) by using catalytic reactive distillation (RD) is a promising approach for carbon dioxide utilization. However, there is still scarcity of comprehensive comparison between the two RD processes. Hence, using the UNIQUAC model and kinetics calibrated by literature and our experiments, we conduct an extensive comparison of the two RD processes. Based on the kinetic insights, laboratory RD processes for both reactions are modeled, analyzed, and experimentally validated. Consequently, two RD processes designed to produce 60 ktpy of DMC are optimized and compared. The interplay and control factors between reaction and separation are elucidated and clarified via investigating variations of the actual chemical equilibrium constant profile compared with theoretical values along the reactive section at various pressures, liquid holdups, etc. The results reveal that the optimized EC RD process achieves almost 50 % reductions in both total annual cost and carbon dioxide emission compared to the PC RD process. This work facilitates the carbon neutrality and provides an essential guide for quantitatively assessing the two routes.

We present an investigation of the compact structure of the active galactic nucleus 2021+317 based on multiepoch very long baseline interferometry (VLBI) observations at 15, 22, and 43 GHz in the period from 2013 through 2024. The VLBI images show a core-jet structure extended to the south, with two stationary components in the northern region, one of which is likely to be the core of the source. We also detected two new moving jet components (S4 and S5) in the observations of 2021. Based on these observational findings, we analyzed two distinctive jet models involving one or another stationary component mentioned above as the jet core. One model assumes a moderate bulk motion velocity, a wider viewing angle, and a lower Doppler factor, with the magnetic field energy density significantly dominating over the nonthermal particle energy density. The other model involves a higher bulk motion velocity, a narrower viewing angle, and a higher Doppler factor, with an even greater dominance of magnetic field energy in the core. The position angle of the jet ridgeline rotates counterclockwise over the observed period. The apparent kinematics of the jet components is more consistent with a model of the precessing jet, which has recently completed the first half of the precession cycle. Our results provide constraints on the dynamic evolution of the jet and its interaction with the surrounding medium.

The core of self-supervised point cloud learning lies in setting up appropriate pretext tasks, to construct a pre-training framework that enables the encoder to perceive 3D objects effectively. In this article, we integrate two prevalent methods, masked point modeling (MPM) and 3D-to-2D generation, as pretext tasks within a pre-training framework. We leverage the spatial awareness and precise supervision offered by these two methods to address their respective limitations: ambiguous supervision signals and insensitivity to geometric information. Specifically, the proposed framework, abbreviated as PointCG, consists of a Hidden Point Completion (HPC) module and an Arbitrary-view Image Generation (AIG) module. We first capture visible points from arbitrary views as inputs by removing hidden points. Then, HPC extracts representations of the inputs with an encoder and completes the entire shape with a decoder, while AIG is used to generate rendered images based on the visible points’ representations. Extensive experiments demonstrate the superiority of the proposed method over the baselines in various downstream tasks. Our code will be made available upon acceptance.

The National Metrology Institute (NMI) of The Netherlands (VSL) developed a new 1200-kV reference measuring system for on-site calibration of lightning impulse (LI) voltage measuring systems. Improvement of the low-voltage grounding loop and triaxial signal transmission reduced oscillation ripples and enhanced the shielding of environmental high-frequency interference. Calibration and measurement capabilities are realized in the test voltage (U_t), front time (T₁), and time to half-value (T₂) with uncertainties of 0.7%, 3.0%, and 1.5%, respectively, up to 600 kV and 1.2%, 5.0%, and 3.0%, respectively, up to 1200 kV for direct comparison calibration. With additional linearity experiments, VSL is now able to provide LI voltage calibrations on-site up to 3000 kV. The VSL system was used as the reference for calibration and tuning of a 4000-kV LI divider to improve its accuracy performance. A measurement campaign was held to compare different LI measuring systems and research the linearity of the measuring system up to 3000 kV. The comparison results confirmed the good performance of the VSL 1200-kV reference measuring system and also indicated that the 4000-kV measuring system was improved after calibration and tuning with the VSL reference system.

Steam-assisted gravity drainage (SAGD) is one efficient and mature technology for recovering heavy oil and bitumen resources. The key underlying mechanism is the growth of the steam chamber after injecting steam. However, due to the complex geological environment, the thief zones exist and have a prejudicial effect on the development of the steam chamber, thus impacting the ultimate heavy-oil recovery. In this work, our objective is to investigate the effect of a top-water thief zone (i.e., water zone overlies the oil sand) on SAGD performance and further to understand the crucial mechanisms that control the heat loss during steam injection. A large-scale three-dimensional experimental apparatus is used to carry out the SAGD process with a top aquifer. Based on the similarity criterion, the field-scale model is transformed into a laboratory elemental model. To evaluate the SAGD performance quantitatively, the dynamic growth of the steam chamber is measured using the thermal detectors and the production data is recorded. The results show that the steam chamber exhibits three distinguished stages, that is, upward spread, lateral extension, and downward development in the presence of top-water zone. The bottom-water zone has less impact on the steam-chamber growth. The existence of a confined top-water zone, however, significantly affects SAGD performance, especially the lateral expansion of the steam chamber. The lateral propagation of the steam front is hindered by the top thief zone due to the heat exchange with the top water. Once the steam chamber reaches the boundary, the accumulation of energy in the water thief zone, in turn, can reduce the remaining oil saturation along the topwater-oil interface. This study provides us some key insights into the development of heavy oil resources with top thief zones when implementing SAGD technology.