Deformation behavior of blended elemental ti-6ai-4v compacts

A blended elemental Ti-6A1-4V alloy powder, sintered to 99 pct theoretical density, was tested in tension and fatigue and characterized by optical, scanning, and transmission electron microscopy and by X-ray energy dispersive analysis. The microstructure consisted of a combination of equiaxed and low aspect ratio lamellar alpha phase. Two types of pores were observed: macropores at grain boundaries or triple points, and micropores within alpha regions. Chemical homogeneity was achieved within individual alpha or beta regions with slight compositional fluctuations between different grains. The deformation modes in alpha regions were investigated by transmission electron microscopy on thin foils prepared from tensile and cyclically deformed specimens. Tensile deformation occurred by homogeneous slip on both prismatic and pyramidal alpha slip planes. In cyclic deformation, on the other hand, little slip activity was found except for some heterogeneous slip on the basal plane associated with a relatively large micropore. Micropores of ?0.5 μm size were found to act as dislocation pinning sites.     

Web-based collaborative inquiry learning

Abstract This study proposes a web-based collaborative inquiry learning system. This system uses the World-wide web (WWW) as a source of knowledge exploration, and provides exploratory problems to guide students to think and explore. A concept map is used as a tool of anchoring and representing knowledge during inquiry process. In the process of learning, learners are allowed to exchange the evidence they have collected, their personal opinions, and the concept maps that they have built. In order to effectively integrate the inquiry learning, collaborative learning, and concept map in the system, this study proposes a collaborative inquiry learning model and related learning activities. Two studies were constructed based on the collaborative inquiry learning model to investigate students' learning processes in the collaborative inquiry learning on the web.     

Two Machine Scheduling under Disruptions with Transportation Considerations

Effective logistics scheduling requires synchronization of manufacturing and delivery to optimize customer service at minimum total cost. In this paper, we study a new scheduling problem that arises in a disruption environment. Such a problem occurs when a disruption unexpectedly happens, and consequently, some machines become unavailable for certain periods. Jobs that are assigned to the disrupted machines and have not yet been processed can either be moved to other available machines for processing, which may involve additional transportation time and cost, or can be processed by the same machine after the disruption. Our goal is to reschedule jobs so that an objective function, including the original cost function, and possibly transportation costs and disruption cost caused by deviating from the originally planned completion times, is minimized. In this paper, we focus on the two-machine case to demonstrate some major properties, and hope that these properties can provide insights for solving other general problems, such as multiple (more than two) machine scheduling and machine scheduling in other configurations (job shop or flow shop) under disruption. We study problems with different related costs. In each problem, we either provide a polynomial algorithm to solve the problem optimally, or show its NP-hardness. If the problem is NP-hard in the ordinary sense, we also present a pseudo-polynomial algorithm to solve the problem optimally. This research is supported in part by Hong Kong RGC grant HKUST 6145/03E and in part by NSF Grant DMI-0300156.     

Cause and pre-alarm control of bulking and foaming by Microthrix parvicella--a case study in triple oxidation ditch at a wastewater treatment plant

The cause and control of foaming and bulking in triple oxidation ditch at a wastewater treatment plant (WWTP) were investigated. The results showed that the foaming and bulking was mainly caused by the excessive propagation of Microthrix parvicella, and mostly occurred in the cold winter and spring. Batch and continuous flow experiments indicated that biological techniques such as reducing sludge retention time (SRT) and increasing F/M ratio, chemical methods such as addition of chlorine (NaOCl), quaternary ammonium salt (QAS), or cationic polyacrylamide flocculants (PAM), polyaluminum salt (PAC) could decrease Sludge Volume Index (SVI) and control foaming and bulking at different levels. In practical application, the shorter SRT was effective to control foaming and bulking in initial stage, although it took longer time. Addition of 10gClkgMLSSd(-1) could gradually change the activated sludge with serious foaming and bulking to normal state within a week. Pre-alert control strategies should be established for the control of filamentous foaming and bulking.     

Guest editorial. Introduction to the special section: 4G Health--the long-term evolution of m-Health

In the last decade, the seminal term and concept of "m-health" were first defined and introduced in this transactions as "mobile computing, medical sensor, and communications technologies for healthcare." Since that special section, the m-health concept has become one of the key technological domains that reflected the key advances in remote healthcare and e-health systems. The m-health is currently bringing together major academic research and industry disciplines worldwide to achieve innovative solutions in the areas of healthcare delivery and technology sectors. From the wireless communications perspective, the current decade is expected to bring the introduction of new wireless standards and network systems with true mobile broadband and fast internet access healthcare services. These will be developed around what is currently called the fourth-generation (4G) mobile communication systems. In this editorial paper, we will introduce the new and novel concept of 4G health that represents the long-term evolution of m-health since the introduction of the concept in 2004. The special section also presents a snapshot of the recent advances in these areas and addresses some of the challenges and future implementation issues from the evolved m-health perspective. It will also present some of the concepts that can go beyond the traditional "m-health ecosystem" of the existing systems. The contributions presented in this special section represent some of these developments and illustrate the multidisciplinary nature of this important and emerging healthcare delivery concept.     

CDF sensitivity analysis technique for ranking influential parameters in the performance assessment of the proposed high-level waste repository at Yucca Mountain, Nevada, USA

A cumulative distribution function (CDF)-based method has been used to perform sensitivity analysis on a computer model that conducts total system performance assessment of the proposed high-level nuclear waste repository at Yucca Mountain, and to identify the most influential input parameters affecting the output of the model. The performance assessment computer model referred to as the TPA code, was recently developed by the US nuclear regulatory commission (NRC) and the center for nuclear waste regulatory analyses (CNWRA), to evaluate the performance assessments conducted by the US department of energy (DOE) in support of their license application. The model uses a probabilistic framework implemented through Monte Carlo or Latin hypercube sampling (LHS) to permit the propagation of uncertainties associated with model parameters, conceptual models, and future system states. The problem involves more than 246 uncertain parameters (also referred to as random variables) of which the ones that have significant influence on the response or the uncertainty of the response must be identified and ranked. The CDF-based approach identifies and ranks important parameters based on the sensitivity of the response CDF to the input parameter distributions. Based on a reliability sensitivity concept [AIAA Journal 32 (1994) 1717], the response CDF is defined as the integral of the joint probability-density-function of the input parameters, with a domain of integration that is defined by a subset of the samples. The sensitivity analysis does not require explicit knowledge of any specific relationship between the response and the input parameters, and the sensitivity is dependent upon the magnitude of the response. The method allows for calculating sensitivity over a wide range of the response and is not limited to the mean value.     

Variable screening and ranking using sampling-based sensitivity measures

This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables.     

A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution

We address a multi-skill project scheduling problem for IT product development in this article. The goal is for product development managers to be able to generate an initial schedule at an early stage of development activities. Due to the complexity of the product structure and functionality, an IT product development effort is divided into multiple projects. Each project includes several tasks, and each task must be completed by an employee who has mastered a certain skill to complete it. A pool of multi-skilled employees is available, and the employees’ skill efficiencies are influenced by both learning and forgetting phenomena. Based on the real-world demands of product development managers, three objectives are simultaneously considered: skill efficiency gain, product development cycle time and costs. To solve this problem, we propose a multi-objective non-linear mixed integer programming model. The Non-dominated Sorting Genetic Algorithm II (NSGA-II)is designed to generate an approximation to the optimal Pareto front of this NP-hard multi-objective optimisation problem. The algorithm produces feasible schedules for all the development projects using the serial schedule generation scheme. We adopt penalty values and individual employee adjustments to address resource conflicts and constraint violations. A weighted ideal point method is used to select the final solution from the approximate Pareto solution set. An application case of a new electrical energy saving product implementation in a leading electrical device company in China is used to illustrate the proposed model and algorithm.     

EBSD investigation on microstructure transformation in low carbon steel during continuous cooling

In this study the microstructure in low carbon steel during phase transformation was systematically investigated using dilatometry, optical microscopy as well as EBSD. The specimens after annealing at 900°C for 3 min were subsequently cooled at 0·3–100°C s^?1 for dilatometry, in order to determine the continuous cooling transformation (CCT) diagram. Then the microstructures were analysed by optical microscopy (OM) and electron backscattering diffraction (EBSD). Dilatometry, optical microscopy as well as image quality technique in EBSD were combined together to determine the continuous cooling transformation diagram of low carbon steel. As increasing in the cooling rate from 1 to 30°C s^?1, the fraction of ferrite is almost 90% and the phase transformation occurs from pearite to bainite at the cooling rate between 10 to 20°C s^?1.

Dans cette étude, on a examiné systématiquement la microstructure de l’acier à faible teneur en carbone lors de la transformation de phase en utilisant la dilatométrie, la microscopie optique ainsi que la DERD. Après un recuit à 900°C pendant 3 min, on a ensuite refroidi les échantillons entre 0·3 et 100°C s^?1 pour l’étude de dilatométrie, afin de déterminer le diagramme de transformation en refroidissement continu (CCT). On a ensuite analysé la microstructure par microscopie optique (MO) et par diffraction des électrons rétrodiffusés (DERD). On a combiné la dilatométrie, la microscopie optique ainsi que la technique de haute qualité de l’image de DERD pour déterminer le diagramme de transformation en refroidissement continu de l’acier à faible teneur en carbone. Avec l’augmentation de la vitesse de refroidissement de 1 à 30°C s^?1, la fraction de ferrite atteint presque 90% et la transformation de phase de perlite à bainite a lieu à une vitesse de refroidissement entre 10 et 20°C s^?1.