Results 1 to 10 of about 3,975 (137)
Influence of blade installation angle spanwise distribution on the energy characteristics of mining contra-rotating axial flow fan [PDF]
As the global demand for energy conservation increases, achieving efficient energy conversion in fans has become a significant challenge in the field of mine ventilation.
Yongping Chen +7 more
doaj +3 more sources
Flow Characteristics and Loss Mechanism of Tip Leakage Flow in Mining Contra-Rotating Axial Flow Fan
Tip leakage flow interacts with the mainstream, impacting the energy transmission process within the impeller of the fan and causing a significant flow loss.
Yongping Chen +3 more
doaj +3 more sources
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza +4 more
wiley +1 more source
Seismic analysis and design of tunnels within fault ground: A review
The research methods of seismic response of tunnels within fault ground, including field investigations, analytical solutions, physical experiments, and numerical simulations, and seismic countermeasures are discussed. The present study examines the shortcomings and limitations of the current research and design, and puts forward proposals for future ...
Xingda Wang +6 more
wiley +1 more source
How Signals of Silence Sustain Sexual Harassment and What to Do About It
ABSTRACT Sexual harassment has persisted for decades as an open secret within organizations, creating an ongoing challenge for Human Resource practitioners. Many employees experience or witness harassment yet say nothing. When they contemplate complaining, they are discouraged from doing so. Some still muster the courage to speak out about these abuses,
Angela L. Workman‐Stark +6 more
wiley +1 more source
Negative Stiffness Induced and Controlled by Constriction
Structures with negative stiffness can be stabilized by constriction of external displacement. Furthermore, constriction can make a conventional positive stiffness material exhibit negative stiffness, either bidirectional or unidirectional (shown in the figure).
Elena Pasternak, Arcady V. Dyskin
wiley +1 more source

