This paper describes the use of CyclePad—an articulate virtual laboratory for creating and analyzing thermodynamics cycles—at three different types of educational institutions: a research university, an engineering technology program in a large state university, and a military academy. Case studies of each site were created based on classroom observations, student surveys, and interviews with faculty. In comparing these three institutions, we found that the context of the school and the ways in which professors chose to implement CyclePad led to different student experiences. Depending on the types of problems that students worked on, they found the software more or less helpful in increasing their understanding of thermodynamics. Students in the class that had the most constraints on its curriculum, where little change was possible, were less able to take full advantage of the software's capabilities. 相似文献
A general analytic technique is given for the design of FIR digital filters with simultaneous conditions on both the amplitude and delay responses. It is shown that phase linearity can be maintained only within the passband, resulting in increased amplitude selectivity as compared with filters with exact linear phase at all frequencies. 相似文献
Protection of Metals and Physical Chemistry of Surfaces - The present study deals with the application of activated carbon for the adsorptive removal of Cu(II) from its aqueous solutions. This... 相似文献
A digitally-programmable circuit is proposed to provide high-voltage protection at start-up, overload, and supply loss conditions in continuous-time passive–active sigma delta ADCs implemented in low-voltage nanometer CMOS technologies. The circuit optimizes the common-mode level at the input stage of the ADC enabling it to interface with input levels beyond its own supply voltage with no impact on device reliability or distortion levels, and minimum impact on area and noise performance, which provides maximum flexibility in the ADC usage. The proposed circuit along with the full ADC is implemented in a typical 65 nm CMOS technology. 相似文献
White Etching Cracks (WEC) in gearbox bearings is a major concern in the wind turbine industry, which can lead to a premature failure of the gearbox. Though many hypotheses regarding the generation of WEC have been proposed over the decades, the answer is still disputable. To trace back the failures to earlier stages before they occur, an innovative sensor-set has been utilized on a test rig to monitor the influencing factors that lead to WEC. This paperwork seeks to recognize abnormal patterns from recorded sensor data and derive statements of sensible sensor combinations in WEC early detection. A Long Short Term Memory (LSTM) network-based autoencoder is proposed for the anomaly detection (AD) task. Employing an auto-associative sequence-to-sequence predictor, a model is trained to reconstruct the normal time series data without WEC. The reconstruction error of testing time series data is evaluated for the determination of its anomaly. The results show that the specified LSTM autoencoder framework can qualitatively distinguish anomalies from collected multivariate time series data. Moreover, the anomaly score evaluated via reconstruction-error-based metrics can discriminate normal and abnormal behaviors in the study. This investigation’s results entail a significant step towards early WEC risk detection and more cost-efficient wind turbine technology if this approach can be further applied on stream data with plausible thresholds in monitoring system.
An explanation of what switched-capacitor (SC) filters are and how they work is given. Attention is focused on low-sensitivity SC filters, which can be developed from a general passive ladder where the branches are arbitrary impedances. The equations that describe the filter components are reviewed, and the characteristics of these low-sensitivity filters are outlined. Applications of the filters in telecommunications are discussed 相似文献
The thermal conductivity of Li2O·Al2O3· n SiO2 glass-ceramics is studied for n = 4, 6, 8, 10 between 5 and 100 K. A monotonic increase in conductivity is observed for all samples. This behavior is different from that of glassy counterparts which exhibit a plateau in thermal conductivity between 10 and 20 K. It is also observed that while the conductivity of glass-ceramics is lower than that of glasses at low temperatures, the situation is reversed at higher temperatures. A crossover occurs around 40 K for all studied samples. The glass-ceramic behavior is interpreted in the light of the acoustic mismatch theory of Little. At low temperatures, the thermal boundary resistance that exists at the crystalline-amorphous mismatch is high and the thermal conductivity is low. At higher temperatures, the boundary resistance is very small and the high conductivity is mainly due to the crystalline region within the amorphous structure. 相似文献
Cellular manufacturing system (CMS) is one of the group technology (GT) usages. Among the necessary decisions for a successful CMS implementation, cell formation problem (CFP) and cell layout problem (CLP) are two most popular ones. The majority of past studies in CMS discussed on CFPs and some of those focused on CLP ones. A few researchers solve the CPF and CLP simultaneously. In this paper, we present a new integrated mathematical model considering cell formation and cell layout simultaneously. The goal of our model is to group similar parts and corresponding different machines in same cells. Machines sequence in each cell and cell positions is also specified in the system. Moreover, our proposed model considers forward and backtracking movements as well as new assumptions for distances between cells using sequence data and production volume. One appropriate adjusted measure from the literature and two new measures of performance for evaluating solutions are defined. To validate the model, two well-known critical benchmark examples are employed. Computational experiments demonstrate that our proposal is a proficient model and show the effectiveness of our implementation. 相似文献
A current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.