Cracking and Damage in a Notched Unidirectional Fiber-Reinforced Brittle Matrix Composite

Results of four-point bend tests on notched beams of a laminated unidirectional fiber-reinforced glass matrix composite are presented. The failure sequence has been established through in situ examination. The dominant damage mode is a mixed-mode, split crack that runs parallel to the predominant fiber directions. The crack interacts with and crosses over imperfectly aligned fibers. The resulting bridging tractions are sufficient to cause the critical strain energy release rate to increase substantially as the crack extends. Several other damage modes are also observed. These include mode I (tensile) matrix cracks bridged by fibers, mode II (shear) cracks, and compressive damage at the loading points.     

Facile hyphenation of gas chromatography and a microcantilever array sensor for enhanced selectivity

The very simple coupling of a standard, packed-column gas chromatograph with a microcantilever array (MCA) is demonstrated for enhanced selectivity and potential analyte identification in the analysis of volatile organic compounds (VOCs). The cantilevers in MCAs are differentially coated on one side with responsive phases (RPs) and produce bending responses of the cantilevers due to analyte-induced surface stresses. Generally, individual components are difficult to elucidate when introduced to MCA systems as mixtures, although pattern recognition techniques are helpful in identifying single components, binary mixtures, or composite responses of distinct mixtures (e.g., fragrances). In the present work, simple test VOC mixtures composed of acetone, ethanol, and trichloroethylene (TCE) in pentane and methanol and acetonitrile in pentane are first separated using a standard gas chromatograph and then introduced into a MCA flow cell. Significant amounts of response diversity to the analytes in the mixtures are demonstrated across the RP-coated cantilevers of the array. Principal component analysis is used to demonstrate that only three components of a four-component VOC mixture could be identified without mixture separation. Calibration studies are performed, demonstrating a good linear response over 2 orders of magnitude for each component in the primary study mixture. Studies of operational parameters including column temperature, column flow rate, and array cell temperature are conducted. Reproducibility studies of VOC peak areas and peak heights are also carried out showing RSDs of less than 4 and 3%, respectively, for intra-assay studies. Of practical significance is the facile manner by which the hyphenation of a mature separation technique and the burgeoning sensing approach is accomplished, and the potential to use pattern recognition techniques with MCAs as a new type of detector for chromatography with analyte-identifying capabilities.     

The Effective Fracture Toughness in Hydraulic Fracturing

This paper examines the effective fracture toughness approach which is used in hydraulic fracturing in order to explain the high net-pressures that are often observed in field operations. The effective fracture toughness is calculated using a fully deterministic elasto-plastic hydraulic fracturing model. Rock is modelled by Mohr–Coulomb flow theory of plasticity for cohesive-frictional dilatant material. Fluid flow is modelled by lubrication theory. A cohesive crack model which takes into account the softening behaviour of rocks is employed as the propagation criterion. The fully coupled model is solved numerically by the finite element method and the effective fracture toughness is calculated using the path independent J-integral. The results show that plastic yielding near the tip of a propagating fracture provides an effective shielding, resulting in an increase in the rock effective fracture toughness by more than an order of magnitude. It is demonstrated that an elastic model based on the concept of effective fracture toughness matches the results of plasticity quite well. The effective fracture toughness increases with formation yielding, which is influenced by the deviator of the in-situ stresses, the rock strength, the elastic modulus and the pumping parameters. Tables of effective fracture toughness for a representative set of physical parameters are presented. This revised version was published online in July 2006 with corrections to the Cover Date.     

An editing tool that manages device associations in an in-home environment

The forthcoming home environment will comprise numerous computationally enhanced artifacts that are autonomous, but interconnected via an invisible web of network-based services. The approach presented in this paper is to enable end users to make their own applications by linking such artifacts, which are treated as reusable components. A key requirement to achieve this is the availability of editing tools that meet the needs of different classes of users. A tool of this kind designed for end users is presented in this paper, together with the outcome of user evaluation sessions.     

Benchmarking and learning garbage collection delays for resource-restricted graphical user interfaces

Tablets, smartphones, and wearables have limited resources. Applications on these devices employ a graphical user interface (GUI) for interaction with users. Language runtimes for GUIs employ dynamic memory management using garbage collection (GC). However, GC policies and algorithms are designed for data centers and cloud computing, but they are not necessarily ideal for resource-constrained embedded devices. In this article, we present GUI GC, a JavaFX GUI benchmark, which we use to compare the performance of the four GC policies of the Eclipse OpenJ9 Java runtime on a resource-constrained environment. Overall, our experiments suggest that the default policy Gencon registered significantly lower execution times than its counterparts. The region-based policy, Balanced, did not fully utilize blocking times; thus, using GUI GC, we conducted experiments with explicit GC invocations that measured significant improvements of up to 13.22% when multiple CPUs were available. Furthermore, we created a second version of GUI GC that expands on the number of controllable load-stressing dimensions; we conducted a large number of randomly configured experiments to quantify the performance effect that each knob has. Finally, we analyzed our dataset to derive suitable knob configurations for desired runtime, GC, and hardware stress levels.     

从软件质量控制到软件质量保证

本文阐述了在嵌入式系统和在其他执行关键任务的软件中由传统的软件质量控制技术到前涉的质量保证方案的转化：软件在每一个产品和每一个组织中所发挥的作用日益重要。近年来,执行关键任务的应用系统的数量以指数速度增长。这些系统要么失败后损失巨大（空中交换管制系统和其他生命支持产品）。要么纠正费用高（便携式电话和其他用户产品）。为嵌入式系统设计的软件在更多的时候属于“执行关键任务”的范畴,而对嵌入式系统的需求也在继续升温,因此对前涉的质量保证的需求要高于以往任何时候。本文把质量控制到质量保证的转化分为两个阶段：1质量评估（第一阶段）：在开发周期的早期,即在软件到达用户之前,甚至在测试之前识别和排除软件故障,同时提供客观定量的质量评估。2质量保证（第二阶段）：在作更改的时候,通过精确的影响分析,采用强制执行编码标准和防止新错误出现的方法来防止错误进入代码基数。     

Accelerating SPARQL queries by exploiting hash-based locality and adaptive partitioning

State-of-the-art distributed RDF systems partition data across multiple computer nodes (workers). Some systems perform cheap hash partitioning, which may result in expensive query evaluation. Others try to minimize inter-node communication, which requires an expensive data preprocessing phase, leading to a high startup cost. Apriori knowledge of the query workload has also been used to create partitions, which, however, are static and do not adapt to workload changes. In this paper, we propose AdPart, a distributed RDF system, which addresses the shortcomings of previous work. First, AdPart applies lightweight partitioning on the initial data, which distributes triples by hashing on their subjects; this renders its startup overhead low. At the same time, the locality-aware query optimizer of AdPart takes full advantage of the partitioning to (1) support the fully parallel processing of join patterns on subjects and (2) minimize data communication for general queries by applying hash distribution of intermediate results instead of broadcasting, wherever possible. Second, AdPart monitors the data access patterns and dynamically redistributes and replicates the instances of the most frequent ones among workers. As a result, the communication cost for future queries is drastically reduced or even eliminated. To control replication, AdPart implements an eviction policy for the redistributed patterns. Our experiments with synthetic and real data verify that AdPart: (1) starts faster than all existing systems; (2) processes thousands of queries before other systems become online; and (3) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in subseconds.     

Simulating pavement structural condition using artificial neural networks

This article aims to investigate the feasibility of incorporating of an artificial neural network (ANN) as an innovative technique for modelling the pavement structural condition, into pavement management systems. For the development of the ANN, strain assessment criteria are set in order to characterise the structural condition of flexible asphalt pavements with regards to fatigue failure. This initial task is directly followed with the development of an ANN model for the prediction of strains primarily based on in situ field gathered data and not through the usage of synthetic databases. For this purpose, falling weight deflectometer (FWD) measurements were systematically conducted on a highway network, with ground-penetrating radar providing the required pavement thickness data. The FWD data (i.e. deflections) were back-analysed in order to assess strains that would be utilised as output data in the process of developing the ANN model. A paper exercise demonstrates how the developed ANN model combined with the suggested conceptual approach for characterising pavement structural condition with regard to strain assessment could make provisions for pavement management activities, categorising network pavement sections according to the need for maintenance or rehabilitation. Preliminary results indicate that the ANN technique could help assist policy decision makers in deriving optimum strategies for the planning of pavement infrastructure maintenance.