There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Statistics for Spatial Data.

▶ Addresses a wide range of timely environment, economic and energy topics ▶ A forum to review, analyze and stimulate the development, testing and implementation of mitigation and adaptation strategies at regional, national and global scales ▶ Contributes to real-time policy analysis and development as national and international policies and agreements are discussed and promulgated ▶ 94% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again

Mitigation and Adaptation Strategies for Global Change

This paper developed an effective multiscale method for analysing the deformation of NanoElectroMechanical (NEM) switches based on carbon nanotubes. The switches were simplified to beam systems with loads calculated from three-coupled energy domains: the electrostatic energy domain, the elastostatic energy domain, and the van der Waals energy domain. A meshless formulation was then used to discretise the switches to establish the non-linear system of equations for solution. The pull-in voltage characteristics of the fixed-fixed and cantilever nanoswitches based on the single-walled nanotube and the double-walled nanotube are analysed. A parametric comparison with the results in the literature showed that the method developed in this paper is very effective.

A simple method for analysing the deformation of nanoelectromechanical switches based on carbon nanotubes

Purpose – The purpose of this paper is to develop an effective numerical approach to assess the nonlinear dynamic responses of a near‐bed submarine pipeline.Design/methodology/approach – A coupled numerical approach is proposed in this paper to assess the nonlinear dynamic responses of this pipeline. The boundary‐element method is first used to get the nonlinear dynamic fluid loading induced by the asymmetric flow. The meshless technique is used to discretize the structure of the pipeline. A numerical example is first presented to verify the effectivity of the present method. Then, the coupled technique is used to simulate the nonlinear dynamic fluid‐structure interaction problem of a near‐bed pipeline. A Newton‐Raphson iteration procedure is used herein to solve the nonlinear system of equations, and the Newmark method is adopted for the time integration.Findings – The presence of seabed results in a large negative lift on a pipeline in a horizontal current. Studies reveal that there exists a critical cu...

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A coupled numerical approach for nonlinear dynamic fluid‐structure interaction analysis of a near‐bed submarine pipeline

Impact characteristics of a flexible road barrier and vehicle crash response

Deep learning (DL) relies heavily on data, and the quality of data influences its performance significantly. However, obtaining high-quality, well-annotated datasets can be challenging or even impossible in many real-world applications, such as structural risk estimation and medical diagnosis. This presents a significant barrier to the practical implementation of DL in these fields. Physics-guided deep learning (PGDL) is a novel type of DL that can integrate physics laws to train neural networks. This can be applied to any systems that are controlled or governed by physics laws, such as mechanics, finance and medical applications. It has been demonstrated that, with the additional information provided by physics laws, PGDL achieves great accuracy and generalisation in the presence of data scarcity. This review provides a detailed examination of PGDL and offers a structured overview of its use in addressing data scarcity across various fields, including physics, engineering and medical applications. Moreover, the review identifies the current limitations and opportunities for PGDL in relation to data scarcity and offers a thorough discussion on the future prospects of PGDL.

Utilising physics-guided deep learning to overcome data scarcity

It is generally assumed that influence of the red blood cells (RBCs) is predominant in blood rheology. The healthy RBCs are highly deformable and can thus easily squeeze through the smallest capillaries having internal diameter less than their characteristic size. On the other hand, RBCs infected by malaria or other diseases are stiffer and so less deformable. Thus it is harder for them to flow through the smallest capillaries. Therefore, it is very important to critically and realistically investigate the mechanical behavior of both healthy and infected RBCs which is a current gap in knowledge. The motion and the steady state deformed shape of the RBCs depend on many factors, such as the geometrical parameters of the capillary through which blood flows, the membrane bending stiffness and the mean velocity of the blood flow. In this study, motion and deformation of a single two-dimensional RBC in a stenosed capillary is explored by using smoothed particle hydrodynamics (SPH) method. An elastic spring network is used to model the RBC membrane, while the RBC's inside fluid and outside fluid are treated as SPH particles. The effect of RBC's membrane stiffness (kb), inlet pressure (P) and geometrical parameters of the capillary on the motion and deformation of the RBC is studied. The deformation index, RBC's mean velocity and the cell membrane energy are analyzed when the cell passes through the stenosed capillary. The simulation results demonstrate that the kb, P and the geometrical parameters of the capillary have a significant impact on the RBCs' motion and deformation in the stenosed section.

YuanTong Gu

Papers

A simple method for analysing the deformation of nanoelectromechanical switches based on carbon nanotubes

A coupled numerical approach for nonlinear dynamic fluid‐structure interaction analysis of a near‐bed submarine pipeline

Impact characteristics of a flexible road barrier and vehicle crash response

Utilising physics-guided deep learning to overcome data scarcity

Numerical investigation of motion and deformation of a single red blood cell in a stenosed capillary