Numerical simulation and optimization of Al alloy cylinder body by low pressure die casting

Shrinkage defects can be formed easily at Critical location during low pressure die casting (LPDC) of aluminum alloy cylinder body. It has harmful effect on the products. Mold fi lling and solidifi cation process of a cylinder body was simulated by using of Z-CAST software. The casting method was improved based on the simulation results. In order to create effective feeding passage, the structure of casting was modifi ed by changing the location of strengthening ribs at the bottom, without causing any adverse effect on the part’s performance. Inserting copper billet at suitable location of the die is a valid way to create suitable solidifi cation sequence that is benefi cial to the feeding. Using these methods, the shrinkage defect was completely eliminated at the critical location

A Survey on Knowledge-Enhanced Pre-trained Language Models

Natural Language Processing (NLP) has been revolutionized by the use of Pre-trained Language Models (PLMs) such as BERT. Despite setting new records in nearly every NLP task, PLMs still face a number of challenges including poor interpretability, weak reasoning capability, and the need for a lot of expensive annotated data when applied to downstream tasks. By integrating external knowledge into PLMs, \textit{\underline{K}nowledge-\underline{E}nhanced \underline{P}re-trained \underline{L}anguage \underline{M}odels} (KEPLMs) have the potential to overcome the above-mentioned limitations. In this paper, we examine KEPLMs systematically through a series of studies. Specifically, we outline the common types and different formats of knowledge to be integrated into KEPLMs, detail the existing methods for building and evaluating KEPLMS, present the applications of KEPLMs in downstream tasks, and discuss the future research directions. Researchers will benefit from this survey by gaining a quick and comprehensive overview of the latest developments in this field.Comment: 19 pages, 12 figures, 192 reference

Capturing Data Uncertainty in High-Volume Stream Processing

We present the design and development of a data stream system that captures data uncertainty from data collection to query processing to final result generation. Our system focuses on data that is naturally modeled as continuous random variables. For such data, our system employs an approach grounded in probability and statistical theory to capture data uncertainty and integrates this approach into high-volume stream processing. The first component of our system captures uncertainty of raw data streams from sensing devices. Since such raw streams can be highly noisy and may not carry sufficient information for query processing, our system employs probabilistic models of the data generation process and stream-speed inference to transform raw data into a desired format with an uncertainty metric. The second component captures uncertainty as data propagates through query operators. To efficiently quantify result uncertainty of a query operator, we explore a variety of techniques based on probability and statistical theory to compute the result distribution at stream speed. We are currently working with a group of scientists to evaluate our system using traces collected from the domains of (and eventually in the real systems for) hazardous weather monitoring and object tracking and monitoring.Comment: CIDR 200

Structure Evolution of Graphene Oxide during Thermally Driven Phase Transformation: Is the Oxygen Content Really Preserved?

A mild annealing procedure was recently proposed for the scalable enhancement of graphene oxide (GO) properties with the oxygen content preserved, which was demonstrated to be attributed to the thermally driven phase separation. In this work, the structure evolution of GO with mild annealing is closely investigated. It reveals that in addition to phase separation, the transformation of oxygen functionalities also occurs, which leads to the slight reduction of GO membranes and furthers the enhancement of GO properties. These results are further supported by the density functional theory based calculations. The results also show that the amount of chemically bonded oxygen atoms on graphene decreases gradually and we propose that the strongly physisorbed oxygen species constrained in the holes and vacancies on GO lattice might be responsible for the preserved oxygen content during the mild annealing procedure. The present experimental results and calculations indicate that both the diffusion and transformation of oxygen functional groups might play important roles in the scalable enhancement of GO properties

A Factorized Version Space Algorithm for "Human-In-the-Loop" Data Exploration

International audienceWhile active learning (AL) has been recently applied to help the user explore a large database to retrieve data instances of interest, existing methods often require a large number of instances to be labeled in order to achieve good accuracy. To address this slow convergence problem, our work augments version space-based AL algorithms, which have strong theoretical results on convergence but are very costly to run, with additional insights obtained in the user labeling process. These insights lead to a novel algorithm that factorizes the version space to perform active learning in a set of subspaces. Our work offers theoretical results on optimality and approximation for this algorithm, as well as optimizations for better performance. Evaluation results show that our factorized version space algorithm significantly outperforms other version space algorithms, as well as a recent factorization-aware algorithm, for large database exploration

IMECE 2009-12513 INVESTIGATION OF INDOOR ENVIRONMENT FOR A DATA CENTER

ABSTRACT Special indoor air environment requirements are needed for the data center, such as ambient temperature, airflow pattern, relative humidity and ozone concentration to maintain the reliability of a computer system. In this paper, a numerical simulation based on 3-D Finite Volume Method has been conducted for a data center at Purdue University Calumet. The purpose of the simulation is to find out the most effective and low-cost air condition system. Results for temperature, relative humidity distributions as well as velocity patterns are presented. Mesh independent studies are performed. Numerical results are validated by experimental data. Suggestions are given based on the simulation results for improving the indoor environment of the data center

Numerical simulation and optimization of the casting process of a cast-steel wheel

The mechanism of formation and the regularity of shrinkage distributionin a cast-steel wheel were simulated by computer methods. SolidWorks softwarepackage was used to produce a three-dimensional model of the cast parts, and Experto ViewCastsoftware package was employed to simulate the casting process. The simulatedresults show that the mold filling was smooth and thus no splashing occurred. However, shrinkage and porosityappeared at the transition phase between the wheel-rim and web during the process of solidification. The reason for that isthe imperfect solidification sequence. The fast cooling rate in the final thin web position led to the block of feeding channel at the transition area. The foundry technique was improved successfully by computer-aided methods.The volume of shrinkage was reduced by applying an insulating material, which made thecastings solidify progressively as designed. The performance of the wheel produced by the improved technology agreed very well with the technical requirements

A New Form of the Polarimetric Notch Filter

Ship detection using polarimetric synthetic radar (PolSAR) imagery attracts a lot of attention in recent years. Most notably, the detector polarimetric notch filter (PNF) has been demonstrated to be effective for ship detection in PolSAR imagery, which gives excellent performances. In this work, a mathematical form of one new PNF (NPNF) based on physical mechanisms of targets and clutter is further developed for partial targets. The different mechanisms have been revealed based on the projection matrix. The experimental results including simulated and measured data demonstrate that the NPNF exhibits a better performance than the original PNF