Northeastern University
A team of researchers from Northeastern University has made a breakthrough in developing a novel approach to fault detection for network systems composed of multiple clusters with unknown system matrices. This approach, which utilizes the subspace instrumental variable method and unknown input decomposition, has been shown to be effective in
Numerical analysis
Researchers at the University of Colorado Colorado Springs have conducted a study on the effectiveness of Phase Change Materials (PCMs) in passive thermal management in microgravity environments. The study, funded by the CRCW grant from the University of Colorado Colorado Springs, investigated the thermal performance of different Triply Periodic Minimal
Numerical analysis
Researchers at Xinjiang University in Urumqi, People's Republic of China, have explored the dynamics of rumor propagation on heterogeneous social networks. Their study reveals that controlling nodes with a large degree in the network, improving the ability of the general public to discern rumors, and appropriately intervening with
Numerical analysis
Researchers from Tianjin University, in collaboration with Bin Rong, Yuancong Wu, Chen Sun, Xiaochen Peng, and Shuoyang Zhang, have conducted an experimental and numerical analysis on the flexural behavior of U-bar loop connections with lap height. The study, funded by the Tianjin Transportation Technology Development Plan, aimed to provide guidelines
Numerical analysis
Researchers from Shaanxi Normal University have proposed a novel Brinkman-triple-porosity-permeability model to describe fluid flow between filled conduits, matrix, micro-caves, and micro-fractures. The model removes the assumptions of sequential flow and allows direct communication of fluid between different porosity types. The study was financially supported by the National Natural Science
Numerical analysis
Researchers at Texas Technical University have made significant breakthroughs in the separation of magnetic nanoparticles from liquid solutions using a quadrupole magnetic sorter (QMS) and small-angle X-ray scattering (SAXS) technique. The research, supported by various institutions including the National Science Foundation (NSF) and the Defense Advanced Research Projects Agency (DARPA)
Numerical analysis
A team of researchers at the School of Mechanical & Electrical Engineering, led by Wangqing Wu, has successfully optimized the design of extrusion die structures for TC4 titanium alloy Y-shaped profiles used in the aerospace field. The study employed a high-precision Hansel-Spittel constitutive model to simulate the material's
Numerical analysis
Fresh data on Mathematics-Nonlinear Science and Numerical Simulation have been presented by a team of researchers from the Xi'an University of Architecture and Technology. The study aimed to develop three strategies to eliminate the nonphysical attraction force that distorts the impact behavior in granular systems, using the viscous
Numerical analysis
Research conducted by Changrui Xing and colleagues at the Nanjing University of Finance and Economics has led to the development of a novel method for detecting phosphoproteins using lateral flow immunoassays. The new method allows for the detection of bovine milk adulteration in goat and camel milk, achieving linear ranges
Numerical analysis
Researchers at Massey University have made significant advancements in the field of nonlinear science and numerical simulation by exploring the properties of fractional order systems in denatured Morris-Lecar neurons. This research focuses on the Caputo-type fractional differential equations for a reduced neuron model, known as the denatured Morris-Lecar (dML) system,
Numerical analysis
Researchers at Arak University, led by Omid Ali Akbari, have conducted a comprehensive numerical simulation to investigate the mixed convection of water/Ag nanofluid in a circular cavity. The study has shown that the presence of nanoparticles enhances the heat transfer and cooling capabilities of the fluid, making it a
Northeastern University
A team of researchers from Northeastern University has made a breakthrough in developing a novel approach to fault detection for network systems composed of multiple clusters with unknown system matrices. This approach, which utilizes the subspace instrumental variable method and unknown input decomposition, has been shown to be effective in
