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Mechanism of Packing Rigidity Gain in Sand Aging: From the Perspective of Structural Order Evolution
Chengjun Liu,Pei Tai,Zhaofeng Li,Wenbiao Hu 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.6
Rigidity gain can be observed in sand aging but is usually accompanied by minute densification.This phenomenon is inconsistent with the conventional diagram of rigidity/jamming transition for granules and therefore too enigmatic to be utilized in the field by engineers. Therefore, this study aims to reveal the mechanism of rigidity gain and reconcile the inconsistency in sand aging. The aging processes of two sand packings with the same mono-sized spheres but different initial densities were reproduced via discrete element method simulations. In the simulations, sudden increases in the solid fraction destroyed the similarity between the evolution processes of rigidity gain and densification, confirming the inadequacy of explaining this gain considering densification alone. The bond-orientational order remained almost unchanged, while the contact-force order generally increased over time with distinct drops, similar to the change in rigidity gain. This evolution pattern is attributed to the laws of thermodynamics, which require the Gibbs energy of the sand packing to decrease over time, and contact-force order reduction assists with this decrease. Simultaneously, this reduces the nonaffinity under shear and rigidity demolition, consequently dominating the rigidity gain mechanism in sand aging. Based on these findings, the conventional diagram of rigidity transition was modified to jointly consider the effects of the solid fraction and structural orders. The proposed diagram can depict how the sand packing rigidity is enhanced over time and can better guide the consideration of the sand aging effect in the field.
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Tristan Reddan,Jonathan Corness,Fiona Harden,Wenbiao Hu,Kerrie Mengersen 대한의료정보학회 2019 Healthcare Informatics Research Vol.25 No.3
Objectives: Ultrasound has an established role in the diagnostic pathway for children with suspected appendicitis. Relevant clinical information can influence the diagnostic probability and reporting of ultrasound findings. A Bayesian network (BN) is a directed acyclic graph (DAG) representing variables as nodes connected by directional arrows permitting visualisation of their relationships. This research developed a BN model with ultrasonographic and clinical variables to predict acute appendicitis in children. Methods: A DAG was designed through a hybrid method based on expert opinion and a review of literature to define the model structure; and the discretisation and weighting of identified variables were calculated using principal components analysis, which also informed the conditional probability table of nodes. Results: The acute appendicitis target node was designated as an outcome of interest influenced by four sub-models, including Ultrasound Index, Clinical History, Physical Assessment, and Diagnostic Tests. These sub-models included four sonographic, three blood-test, and six clinical variables. The BN was scenario tested and evaluated for face, predictive, and content validity. A lack of similar networks complicated concurrent and convergent validity evaluation. Conclusions: To our knowledge, this is the first BN model developed for the identification of acute appendicitis incorporating imaging variables. It has particular benefit for cases in which variables are missing because prior probabilities are built into corresponding nodes. It will be of use to clinicians involved in ultrasound examination of children with suspected appendicitis, as well as their treating clinicians. Prospective evaluation and development of an online tool will permit validation and refinement of the BN.
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