Quantifying in-plane deformation of plate elements using vibration characteristics

Plate elements are used in many engineering applications. In-plane loads and deformations have significant influence on the vibration characteristics of plate elements. Numerous methods have been developed to quantify the effects of in-plane loads and deformations of individual plate elements with different boundary conditions based on their natural frequencies. However, these developments cannot be applied to the plate elements in a structural system as the natural frequency is a global parameter for the entire structure. This highlights the need for a method to quantify in-plane deformations of plate elements in structural framing systems. Motivated by this gap in knowledge, this research has developed a comprehensive vibration based procedure to quantify in-plane deformation of plate elements in a structural framing system. This procedure with its unique capabilities to capture the influence of load migration, boundary conditions and different tributary areas is presented herein and illustrated through examples.

Use of vibration characteristics to predict the axial deformation of columns

Vibration characteristics of columns are influenced by their axial loads. Numerous methods have been developed to quantify axial load and deformation in individual columns based on their natural frequencies. However, these methods cannot be applied to columns in a structural framing system as the natural frequency is a global parameter of the entire framing system. This paper presents an innovative method to quantify axial deformations of columns in a structural framing system using its vibration characteristics, incorporating the influence of load tributary areas, boundary conditions and load migration among the columns.

Dynamic optimization of migration topology in internet-based distributed genetic algorithms

Distributed Genetic Algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

Performance-driven live migration of multiple virtual machines in datacenters

Live migration of multiple Virtual Machines (VMs) has become an indispensible management activity in datacenters for application performance, load balancing, server consolidation. While state-of-the-art live VM migration strategies focus on the improvement of the migration performance of a single VM, little attention has been given to the case of multiple VMs migration. Moreover, existing works on live VM migration ignore the inter-VM dependencies, and underlying network topology and its bandwidth. Different sequences of migration and different allocations of bandwidth result in different total migration times and total migration downtimes. This paper concentrates on developing a multiple VMs migration scheduling algorithm such that the performance of migration is maximized. We evaluate our proposed algorithm through simulation. The simulation results show that our proposed algorithm can migrate multiple VMs on any datacenter with minimum total migration time and total migration downtime.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

River mouth bar formation, riverbed aggradation and channel migration in the modern Huanghe (Yellow) River delta, China

This paper addresses the recent (1970s-1990s) processes of river mouth bar formation, riverbed aggradation and distributary migration in the Huanghe River mouth area, in the light of station-based monitoring, field measurements and remote sensing interpretation. The results show that the morphological changes of the river mouth bar have been closely associated with the largely reduced fluvial discharge and sediment load. Landforrn development such as bar progradation occurred in two phases, i.e. before and after 1989, which correspond to faster and lower bar growth rates, respectively. Fast riverbed aggradation in the mouth channel was strongly related to river mouth bar progradation. During 1976-1996, about 2.8% of the total sediment loads were deposited in the river channel on the upper to middle delta. Therefore, the river water level rose by a few meters from 1984 to 1996. The frequent distributary channel migration, which switched the radial channel pattern into the SE-directed pattern in the mid-1980s, was linked with mouth bar formation. Marine conditions also constrain seaward bar progradation. Furthermore, the history of river mouth bar formation reflects human impacts, such as dredging and dyking in order to stabilize the coastal area. (c) 2005 Elsevier B.V. All rights reserved.

Observation and theoretical analysis for the sand-waves migration in the North Gulf of South China Sea

According to the environmental characteristic of the north gulf of South China Sea, a quasi-3D mechanics model has been built for simulating the small scale sand-waves migration in the seas of southwest of Hainan Island. Based on the submarine micro-geomorphic data induced by multi-beam system and hydrographic survey record, the migrations of the sand-waves in the study area are predicted. The results show that calculation is consistent with the observation data in the groove of sand ridge, but not well in the crest of sand ridge. It is indicated that the mechanics model should be used to predict the migration of the small scale sand-waves which are dominated by bed load in the seas. This paper is very meaningful to project the route of submarine pipeline.

Computer simulating a trial of a load-bearing implant: example of an intramedullary prosthesis

Computational modelling is becoming ever more important for obtaining regulatory approval for new medical devices. An accepted approach is to infer performance in a population from an analysis conducted for an idealised or ‘average’ patient; we present here a method for predicting the performance of an orthopaedic implant when released into a population—effectively simulating a clinical trial. Specifically we hypothesise that an analysis based on a method for predicting the performance in a population will lead to different conclusions than an analysis based on an idealised or ‘average’ patient. To test this hypothesis we use a finite element model of an intramedullary implant in a bone whose size and remodelling activity is different for each individual in the population. We compare the performance of a low Young’s modulus implant (View the MathML source) to one with a higher Young’s modulus (200 GPa). Cyclic loading is applied and failure is assumed when the migration of the implant relative to the bone exceeds a threshold magnitude. The analysis for an idealised of ‘average’ patient predicts that the lower modulus device survives longer whereas the analysis simulating a clinical trial predicts no statistically-significant tendency (p=0.77) for the low modulus device to perform better. It is concluded that population-based simulations of implant performance–simulating a clinical trial–present a very valuable opportunity for more realistic computational pre-clinical testing of medical devices.

Distributed Agent-Based Load Balancer for Cloud Computing

In this paper we present a concept of an agent-based strategy to allocate services on a Cloud system without overloading nodes and maintaining the system stability with minimum cost. To provide a base for our research we specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. We also present an early version of simulation environment and a prototype of agent-based load balancer implemented in functional language Scala and Akka framework.

A Meta-Heuristic Load Balancer for Cloud Computing Systems

This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded with the outputs of other meta-heuristic algorithms.

End caps prevent nail migration in elastic stable intramedullary nailing in paediatric femoral fractures: a biomechanical study using synthetic and cadaveric bones.

End caps are intended to prevent nail migration (push-out) in elastic stable intramedullary nailing. The aim of this study was to investigate the force at failure with and without end caps, and whether different insertion angles of nails and end caps would alter that force at failure. Simulated oblique fractures of the diaphysis were created in 15 artificial paediatric femurs. Titanium Elastic Nails with end caps were inserted at angles of 45°, 55° and 65° in five specimens for each angle to create three study groups. Biomechanical testing was performed with axial compression until failure. An identical fracture was created in four small adult cadaveric femurs harvested from two donors (both female, aged 81 and 85 years, height 149 cm and 156 cm, respectively). All femurs were tested without and subsequently with end caps inserted at 45°. In the artificial femurs, maximum force was not significantly different between the three groups (p = 0.613). Push-out force was significantly higher in the cadaveric specimens with the use of end caps by an up to sixfold load increase (830 N, standard deviation (SD) 280 vs 150 N, SD 120, respectively; p = 0.007). These results indicate that the nail and end cap insertion angle can be varied within 20° without altering construct stability and that the risk of elastic stable intramedullary nailing push-out can be effectively reduced by the use of end caps.

A multi-resource load balancing algorithm for cloud cache systems

With the advent of cloud computing model, distributed caches have become the cornerstone for building scalable applications. Popular systems like Facebook [1] or Twitter use Memcached [5], a highly scalable distributed object cache, to speed up applications by avoiding database accesses. Distributed object caches assign objects to cache instances based on a hashing function, and objects are not moved from a cache instance to another unless more instances are added to the cache and objects are redistributed. This may lead to situations where some cache instances are overloaded when some of the objects they store are frequently accessed, while other cache instances are less frequently used. In this paper we propose a multi-resource load balancing algorithm for distributed cache systems. The algorithm aims at balancing both CPU and Memory resources among cache instances by redistributing stored data. Considering the possible conflict of balancing multiple resources at the same time, we give CPU and Memory resources weighted priorities based on the runtime load distributions. A scarcer resource is given a higher weight than a less scarce resource when load balancing. The system imbalance degree is evaluated based on monitoring information, and the utility load of a node, a unit for resource consumption. Besides, since continuous rebalance of the system may affect the QoS of applications utilizing the cache system, our data selection policy ensures that each data migration minimizes the system imbalance degree and hence, the total reconfiguration cost can be minimized. An extensive simulation is conducted to compare our policy with other policies. Our policy shows a significant improvement in time efficiency and decrease in reconfiguration cost.

Mechanical stimulation alters pleiotrophin and aggrecan expression by human intervertebral disc cells and influences their capacity to stimulate endothelial migration

Study Design. The influence of mechanical load on pleiotrophin (PTM) and aggrecan expression by intervertebral disc (IVD) cells, and the effects of disc cell conditioned medium on endothelial cell migration was investigated. Objective. To examine possible interactions of mechanical loads and known pro- and antiangiogenic factors, which may regulate disc angiogenesis during degeneration. Summary of Background Data. Pleiotrophin expression can be influenced by mechanical stimulation and has been associated with disc vascularization. Disc aggrecan inhibits endothelial cell migration, suggesting an antiangiogenic role. A possible interplay between these factors is unknown. Methods. The influence of the respective predominant load (cyclic strain for anulus fibrosus and hydrostatic pressure for nucleus pulposus cells) on PTN and aggrecan expression by IVD cells was determined by real-time RT-PCR and Western blotting (PTN only). The effects of IVD cell conditioned medium on endothelial cell migration were analyzed in a bioassay using human microvascular endothelial (HMEC-1) cells. Results. Application of both mechanical loads resulted in significant alterations of gene expression of PTN (+67%, P = 0.004 in anulus cells; +29%, P = 0.03 in nucleus cells) and aggrecan (+42%, P = 0.03 in anulus cells, -25%, P = 0.03 in nucleus cells). These effects depended on the cell type, the applied load, and timescale. Conditioned media of nucleus pulposus cells enhanced HMEC-1 migration, but this effect was diminished after 2.5 MPa hydrostatic pressure, when aggrecan expression was diminished, but not 0.25 MPa, when expression levels were unchanged. Conclusion. Mechanical loading influences PTN expression by human IVD cells. Conditioned media from nucleus pulposus cell cultures stimulated HMEC-1 endothelial cell migration. This study demonstrates that the influence of mechanical loads on vascularization of the human IVD is likely to be complex and does not correlate simply with altered expression of known pro- and antiangiogenic factors.

A study of adaptive load balancing algorithms for distributed systems

With the advent of distributed computer systems with a largely transparent user interface, new questions have arisen regarding the management of such an environment by an operating system. One fertile area of research is that of load balancing, which attempts to improve system performance by redistributing the workload submitted to the system by the users. Early work in this field concentrated on static placement of computational objects to improve performance, given prior knowledge of process behaviour. More recently this has evolved into studying dynamic load balancing with process migration, thus allowing the system to adapt to varying loads. In this thesis, we describe a simulated system which facilitates experimentation with various load balancing algorithms. The system runs under UNIX and provides functions for user processes to communicate through software ports; processes reside on simulated homogeneous processors, connected by a user-specified topology, and a mechanism is included to allow migration of a process from one processor to another. We present the results of a study of adaptive load balancing algorithms, conducted using the aforementioned simulated system, under varying conditions; these results show the relative merits of different approaches to the load balancing problem, and we analyse the trade-offs between them. Following from this study, we present further novel modifications to suggested algorithms, and show their effects on system performance.

Load-balancing for parallel adaptive unstructured grids

A parallel method for the dynamic partitioning of unstructured meshes is outlined. The method includes diffusive load-balancing techniques and an iterative optimisation technique known as relative gain optimisationwhich both balances theworkload and attempts to minimise the interprocessor communications overhead. It can also optionally include amultilevel strategy. Experiments on a series of adaptively refined meshes indicate that the algorithmprovides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more rapidly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.