132 research outputs found
Process Optimization of 3D Printing with Continuous Fiber Reinforced UV Curable Thermoset Resin
3D printed polymer components cannot be used as structural components due to the 3D printable material property limitations. To improve mechanical properties, a composite 3D printer is developed and studied. Technical aspects of 3D printing with continuous carbon fiber reinforced dual UV and thermal curable thermoset composite were experimented. To optimize the 3D printing process parameters, the effect of printing nozzle size, line spacing of the print, and resin flow rate was studied. To achieve minimum void content and maximum fiber volume fraction, print parameter configurations were studied using microscopic surface roughness analysis. The tensile and flexural properties of 3D printed specimens were tested. Results of the study indicated that impressive mechanical properties of the 3D printed continuous fiber reinforced UV curable thermoset composite can be achieved through the optimization of printing parameters
A Review on Semiconductors Including Applications and Temperature Effects in Semiconductors
There is no doubt that semiconductors changed the world beyond anything that could have been imagined before them. Although people have probably always needed to communicate and process data, it is thanks to the semiconductors that these two important tasks have become easy and take up infinitely less time than, e.g., at the time of vacuum tubes. Semiconductor materials are the building blocks of the entire electronics and computer industry. Small, lightweight, high speed, and low power consumption devices would not be possible without integrated circuits (chips), which consist of semiconductor materials. This paper provides a general discussion of semiconductor materials, their history, classification and the temperature effects in semiconductors. In this section we provide details about the impact of temperature on the MOSFET energy band gap, carrier density, mobility, carrier diffusion, velocity saturation, current density, threshold voltage, leakage current and interconnect resistance. We also provide the applications of semiconductor materials in different sectors of modern electronics and communications.
Vegetative Filter Strip: A Best Management Practice (Bmp) for Feedlot Runoff Pollution Control in North Dakota
Runoff from animal feeding operations is a major source of water pollution. Vegetative filter strips (VFS) are effective ways to reduce nonpoint source pollution. In this study, vegetative filter strips with different designs and in climatic and management conditions of North Dakota were evaluated. Runoff samples were collected from inflow (before entering VFS) and outflow (after exiting the VFS) locations using automatic samplers. Collected samples were analyzed for solids and nutrients. It was observed that the transport reductions by VFS were ranged from very low to up to 100%. However, soluble nutrients were not as effectively removed as sediment and sediment bound nutrients. Filter with longer length was more effective in reducing transport of sediments and nutrients. Antecedent soil moisture condition had an important effect on VFS performance. An attempt was made by varying the VFS soil pH in a broader range to investigate effect of pH on reducing transport of soluble nutrients from manure borne runoff. Soil was treated with calcium carbonate to adjust pH at different levels. Treated soil was packed into galvanized iron boxes and seeded with grasses to simulate vegetative filter strips. Runoff experiments were conducted with manure solution and inflow, outflow, and leachate samples were collected. Samples were analyzed for sediment and nutrients. It was observed that the soluble nutrients transport was influenced by the pH, and higher ortho-P transport reduction was observed in higher pH. Leaching of NO3-N at higher pH was observed, indicating potential of groundwater pollution from the soil with higher pH. Using calcium carbonate to increase soil pH and thereby reducing transport of soluble nutrient could increase VFS performance. To aid VFS design and evaluation, a model was developed to predict trapping efficiency of sediment, sediment bound P, and dissolved P from VFS. Two procedures were coded into FORTRAN and added into existing VFSMOD model. The model was calibrated and validated using field data. Due to limited data points and difficulties in measuring runoff volume, the model appeared to be under or over predicting. In future, model predictability can be improved by accurately measuring runoff volume and carefully selecting input parameters.North Dakota Department of Health (EPA Section 319 grants
Moment Tests for Window Length Selection in Singular Spectrum Analysis of Short- and Long-Memory Processes
In this paper we propose a new methodology for selecting the window length in Singular Spectral Analysis in which the window length is determined from the data prior to the commencement of modeling. The selection procedure is based on statistical tests designed to test the convergence of the autocovariance function. A classical time series portmanteau type statistic and two test statistics derived using a conditional moment principle are considered. The first two are applicable to short-memory processes, and the third is applicable to both short- and long-memory processes. We derive the asymptotic distribution of the statistics under fairly general regularity conditions and show that the criteria will identify true convergence with a finite window length with probability one as the sample size increases. Results obtained using Monte-Carlo simulation indicate the relevance of the asymptotic theory, even in relatively small samples, and that the conditional moment tests will choose a window length consistent with the Whitney embedding theorem. Application to observations on the Southern Oscillation Index shows how observed experimental behaviour can be reflected in features seen with real world data sets.Portmanteau type test, Conditional moment test, Asymptotic distribution, Linear regular process, Singular spectrum analysis, Embedding
Description Length Based Signal Detection in singular Spectrum Analysis
This paper provides an information theoretic analysis of the signal-noise separation problem in Singular Spectrum Analysis. We present a signal-plus-noise model based on the Karhunen-Loève expansion and use this model to motivate the construction of a minimum description length criterion that can be employed to select both the window length and the signal. We show that under very general regularity conditions the criterion will identify the true signal dimension with probability one as the sample size increases, and will choose the smallest window length consistent with the Whitney embedding theorem. Empirical results obtained using simulated and real world data sets indicate that the asymptotic theory is reflected in observed behaviour, even in relatively small samples.Karhunen-Loève expansion, minimum description length, signal-plus-noise model, Singular Spectrum Analysis, embedding
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