373 research outputs found
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Prediction of Porosity in SLM Parts Using a MARS Statistical Model and Bayesian Inference
Predictive models that establish a linkage between process parameters and part properties
have been identified as a high priority research need in Additive Manufacturing. We work with
a Multivariate Adaptive Regression Splines (MARS) statistical model to predict the porosity of
parts produced using Selective Laser Melting (SLM) process as a function of process parameters. The proposed predictive model is validated through a case study on 17-4 PH stainless
steel test coupons manufactured on a ProX 100 SLM system.Mechanical Engineerin
Calendar.help: Designing a Workflow-Based Scheduling Agent with Humans in the Loop
Although information workers may complain about meetings, they are an
essential part of their work life. Consequently, busy people spend a
significant amount of time scheduling meetings. We present Calendar.help, a
system that provides fast, efficient scheduling through structured workflows.
Users interact with the system via email, delegating their scheduling needs to
the system as if it were a human personal assistant. Common scheduling
scenarios are broken down using well-defined workflows and completed as a
series of microtasks that are automated when possible and executed by a human
otherwise. Unusual scenarios fall back to a trained human assistant who
executes them as unstructured macrotasks. We describe the iterative approach we
used to develop Calendar.help, and share the lessons learned from scheduling
thousands of meetings during a year of real-world deployments. Our findings
provide insight into how complex information tasks can be broken down into
repeatable components that can be executed efficiently to improve productivity.Comment: 10 page
Comparative Evaluation for Torque Control Strategies of Interior Permanent Magnet Synchronous Motor for Electric Vehicles
This paper presents a detailed analysis and comparative investigation for the torque control techniques of interior permanent magnet synchronous motor (IPMSM) for electric vehicles (EVs). The study involves the field-oriented control (FOC), direct torque control (DTC), and model predictive direct torque control (MPDTC) techniques. The control aims to achieve vehicle requirements that involve maximum torque per ampere (MTPA), minimum torque ripples, maximum efficiency, fast dynamics, and wide speed range. The MTPA is achieved by the direct calculation of reference flux-linkage as a function of commanded torque. The calculation of reference flux-linkage is done online by the solution of a quartic equation. Therefore, it is a more practical solution compared to look-up table methods that depend on machine parameters and require extensive offline calculations in advance. For realistic results, the IPMSM model is built considering iron losses. Besides, the IGBTs and diodes losses (conduction and switching losses) in power inverter are modeled and calculated to estimate properly total system efficiency. In addition, a bidirectional dc-dc boost converter is connected to the battery to improve the overall drive performance and achieve higher efficiency values. Also, instead of the conventional PI controller which suffers from parameter variation, the control scheme includes an adaptive fuzzy logic controller (FLC) to provide better speed tracking performance. It also provides a better robustness against disturbance and uncertainties. Finally, a series of simulation results with detailed analysis are executed for a 60 kW IPMSM. The electric vehicle (EV) parameters are equivalent to Nissan Leaf 2018 electric car
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Effect of a Small Southern California Lagoon Entrance on Adjacent Beaches
Design of a new laboratory for quality control of mussel produced in Sagres
Dissertação de mestrado, Qualidade em Análises, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2014The growing demand for mussels globally has increased the competition among the producers. Production of high quality mussels demands quality controls in pre- and post-harvesting phases. The main concerns with the mussel industry relate to the pre-harvest stages where monitoring of pollution and management of production. This present work deals with designing of a laboratory at the Finisterra’s aquaculture to control the environmental conditions on the production of mussels focusing on establishing of an efficient quality system. This quality system includes top management commitment, organizational structure and systematically extensive documentation system to comply with the management requirements of the international quality standards. Whilst, the technical part of our quality system covers the environmental conditions of the laboratory, traceability of the results through calibration and quality control activities, and investment in the laboratory personnel. Such quality system will allow the laboratory to be accredited according to ISO/IEC 17025:2005. This project has been designed with enough flexibility for the Finisterra’s management to invest progressively. The base of the laboratory is wet chemistry unit which includes the routine work and preparation for the advanced analysis. Later, Finisterra can complete the work plan by investing in microbiological and advanced analysis. The key benefits stemming from implementation of this quality system are improved competiveness and reliability, increased quality awareness and teamwork. Furthermore, the laboratory will gain the confidence of the clients, researchers and governmental institutions.
Cost analysis was conducted to estimate the initial and running cost of the quality system. The initial cost is insignificant in comparison to the total laboratory cost whereas running of the quality system increases the total running cost
Antenatal dexamethasone effect on Doppler blood flow velocity in women at risk for preterm birth: prospective case series
Background: Maternal administration of corticosteroids is essential to improve fetal lung surfactant production and hasten the fetal lung maturity in women at risk for preterm birth.Objectives: The current study aims to evaluate the effects of dexamethasone on fetal and uteroplacental circulation in pregnancies at risk for preterm birth after 24 hours of its administration.Methods: A prospective cross-sectional study was carried out in a tertiary University Hospital and included 52 pregnant women with singleton pregnancies. Doppler studies were performed on maternal uterine arteries, umbilical artery, fetal middle cerebral artery (MCA) and fetal descending aorta and just before dexamethasone administration and repeated 24 hours after completion of the course.Results: There was a statistically significant difference between all Doppler indices in the umbilical artery (PI= 1.09±0.4 and 1.05±0.39, RI= 0.66±0.14 and 0.63±0.14; p=0.001), fetal MCA (RI= 0.86±0.12 and 0.83±0.13, PI= 2.19±0.72 and 2.15±0.72; p=0.001) and aorta (RI= 0.9±0.55 and 0.87±0.55; p=0.001, PI= 1.91±0.44 and 1.89±0.44; p=0.040) in comparison before and 24 hours after maternal dexamethasone administration respectively. Also uterine artery PI was significantly different (0.9±0.27 and 0.87±0.26; p=0.001).Conclusion: Antenatal dexamethasone for women at risk of preterm birth improves the fetal and uteroplacental blood flow at 24 hours after its administration.Keywords: Doppler; preterm birth; corticosteroids; dexamethasone
A Review on Process Monitoring and Control in Metal-Based Additive Manufacturing,”
There is consensus among both the research and industrial communities, and even the general public, that additive manufacturing (AM) processes capable of processing metallic materials are a set of game changing technologies that offer unique capabilities with tremendous application potential that cannot be matched by traditional manufacturing technologies. Unfortunately, with all what AM has to offer, the quality and repeatability of metal parts still hamper significantly their widespread as viable manufacturing processes. This is particularly true in industrial sectors with stringent requirements on part quality such as the aerospace and healthcare sectors. One approach to overcome this challenge that has recently been receiving increasing attention is process monitoring and real-time process control to enhance part quality and repeatability. This has been addressed by numerous research efforts in the past decade and continues to be identified as a high priority research goal. In this review paper, we fill an important gap in the literature represented by the absence of one single source that comprehensively describes what has been achieved and provides insight on what still needs to be achieved in the field of process monitoring and control for metal-based AM processes
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