Engineers have developed a groundbreaking computational model to study the movement of granular materials such as soils, sands and powders.
Engineers have developed a groundbreaking computational model to study the movement of granular materials such as soils, sands and powders. By integrating the dynamic interactions among particles, air and water phases, this state-of-the-art system can accurately predict landslides, improve irrigation and oil extraction systems, and enhance food and drug production processes.
The Hong Kong University of Science and Technology announced today that a research team from its School of Engineering has developed a groundbreaking computational model to study the movement of granular materials such as soils, sands and powders. By integrating the dynamic interactions among particles, air and water phases, this state-of-the-art system can accurately predict landslides, improve irrigation and oil extraction systems, and enhance food and drug production processes.The flow of granular materials -- such as soil, sand and powders used in pharmaceuticals and food production -- is the underlying mechanism governing many natural settings and industrial operations. Understanding how these particles interact with surrounding fluids like water and air is crucial for predicting behaviors such as soil collapse or fluid leakage. However, existing models face challenges in accurately capturing these interactions, especially in partially saturated conditions where forces like capillary action and viscosity come into play.To address these challenges, a team led by Prof. ZHAO Jidong from the Department of Civil and Environmental Engineering at HKUST has developed the Pore Unit Assembly-Discrete Element Model . Unlike conventional models that often rely on oversimplified one-way coupling , PUA-DEM incorporates rigorous physical principles to govern the dynamic interactions among particles, air, and water phases. This allows for robust multi-way coupling that accurately captures fluid flow, particle movement, and evolving stress and pressure across the entire spectrum of saturation conditions -- from fully saturated to completely dry states. Rooted in fundamental physics, the high-fidelity model is the first of its kind, achieving exceptional precision in predicting complex multiphase behaviors. It holds significant potential to advance applications in geotechnical engineering, environmental science, and many industrial processes.The team is now exploring collaboration opportunities with the government and industry to apply their model to real-world challenges. That includes developing an early landslide warning system, optimizing irrigation strategies through simulations of water retention and root-soil interactions, and enhancing carbon sequestration and oil extraction efficiency with the model's accurate multiphase flow predictions. Its precise control of powder processing also offers transformative potential for pharmaceutical manufacturing, enabling safer, more effective, and efficient drug production with enhanced consistency in dosage forms, which is critical for improving therapeutic efficacy and patient outcomes. The model's capabilities may also extend to the food industry, potentially revolutionizing the design and processing of granular products like coffee, sugar, and infant formula by optimizing texture, dissolution rates, and shelf stability while reducing waste and energy consumption. Prof. Zhao explained,"PUA-DEM represents a paradigm shift in modeling unsaturated granular systems. By resolving pore-scale fluid-solid interactions, we can now predict how microscopic processes -- like capillary bridge formation and particle swelling, govern macroscopic behaviors such as soil collapse or fluid leakage in energy reservoirs. This opens new avenues for designing safer infrastructures, optimizing agricultural practices, improving pharmaceutical manufacturing, and addressing energy-related engineering challenges."Looking ahead, Dr. Amiya Prakash DAS, the first author of this work and a recent HKUST PhD graduate, said the team planned to expand PUA-DEM's capabilities."In the next stage of our research, we aim to incorporate irregular particle shapes and wettability effects, further narrowing the gap between laboratory findings and field-scale applications. Future work will also explore hybrid computational strategies to model reactive transport and drying-induced cracking," he said.Engineers have developed a new computational approach to accurately model and predict the properties of a class of magnetic molecules called chiral helimagnets. Their work could accelerate the ... Researchers developed a method for 3D experiments that can reveal how forces are transmitted through granular materials, and how the shapes of the grains can dramatically change the outcomes. This ... Chemical engineers have developed a machine-learning model that can accurately predict the heat capacity of the versatile metal-organic framework materials. The work shows that the overall energy ... Waste materials from oil sands extraction, stored in tailings ponds, can pose a risk to the natural habitat and neighboring communities when they leach into groundwater and surface ecosystems. Until ...Study Shows Vision-Language Models Can't Handle Queries With Negation Words
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