Measured Output Parameters Research Articles

An optimization-aided approach to parametrize scalable models of induction machines in speed variable drives

The accurate and time-saving prediction of essential machine variables (output power, torque, and efficiency) is crucial for manufacturers offering a wide power range of induction machines. Many motor variants are typically produced by axially scaling and rewinding the machine. Rescaling procedures of electromagnetic models of induction machines are in everyday use and well known. However, while a high accuracy can be achieved by rescaling in theory, more significant deviations between simulated and measured output parameters of the realized scaled device occur in praxis. These deviations can mainly be attributed to the faulty separation of effects in the distinct machine components, such as the rotor, stator, and bearings. This paper introduces an optimization-aided modeling approach based on the induction machine’s simple equivalent circuit representation. The method is validated by measurement data obtained from many induction machines with various axial lengths and winding configurations.

Atikokan Digital Twin: Machine learning in a biomass energy system

The Atikokan Generating Station, operated by Ontario Power Generation, has a 200 MW, biomass-fired tower boiler that operates on a dispatch schedule with a five-minute cycle. The boiler is generally operated in the range of 40–100 MW using two of five burner levels. In order to optimize boiler performance, we propose the implementation of a unique digital twin. Our digital twin abstraction couples Bayesian inference from science-based models and from observations (machine learning) with decision theory to predict operating-variable set points that optimize the physical asset (the boiler) in the presence of uncertainty (artificial intelligence). We focus this paper on the continuous Bayesian machine learning part of the Atikokan Digital Twin; we discuss decision theory in a companion paper. We identify and learn about 12 operational, model, and measured-output parameters and their uncertainties from high-fidelity, science-based simulations of the Atikokan boiler and from the observed measurements at the power plant. Since the goal of the Atikokan Digital Twin is to implement it online in real time, we require fast function evaluations for the quantities of interest extracted from the simulations in the Bayesian analysis. We use Gaussian process regression/interpolation to create accurate, robust surrogate models. We define the Bayesian priors and likelihood function and solve for the posterior distributions of the 12 parameters. We then propagate these distributions (i.e., parameters with uncertainty) into the predicted distributions of 790 quantities of interest to learn about the relative importance of various sources of error including experimental, model, and operating-parameter errors.

Modeling cycling performance: Effects of saddle position and cadence on cycle pedaling efficiency.

The modeling method is an effective means of estimating causality as well as examining cycle pedaling efficiency. Pedaling efficiency can also be examined by an experimental method, but the experimental method can lead to contradictory results due to perturbation of the measured output parameters. Experimental studies generally yield realistic results, but it is difficult to control for all the variables of interest and to determine the causal relationships between them. The objective of this study is to investigate the pedaling efficiency and causality with considering saddle position and pedaling cadence as variables. Based on the mathematical pedaling modeling, the internal work calculation method was used to calculate the consumed mechanical energy and energy conservation percentage (). The optimal saddle position with the lowest mechanical energy and the highest energy conservation percentage could be changed by the cadence. At the low cadence, the higher saddle position, and the shorter horizontal distance between the saddle and crankshaft led to higher pedaling efficiency (h: 0.95 m, d: 0.16 m, and knee angle: ). However, the highest pedaling efficiency was achieved at the high cadence with a saddle height (h) of 0.9 m and a horizontal distance between the saddle and the crankshaft (d) of 0.06 m (knee angle: ). The lowest cadence is the optimal cadence in terms of the consumed energy, but the optimal cadence was 90 r/min in terms of the energy conservation percentage. Compared to the energy consumption, the energy conservation percentage was demonstrated to influence the fatigue of a cycle rider more critically. The energy conservation percentage was highest at 90 r/min, and 90 r/min was close to the preferred cadence by the cyclist.

Development of virtual instrument model for parameter estimation of fractal antenna array

AbstractThis paper presents the parameter estimation of the fractal antenna array with the virtual instrument model designed in laboratory virtual instrument engineering workbench software. In this work resonant frequency, gain and voltage standing wave ratio have been used as an output parameter with the change in three input parameters such as radius of a circular patch, height of substrate, and dielectric constant of the material. Measured output parameters have been compared with neural network outputs and error has been represented in a graphical way for each output parameter of the antenna array. Along with output parameter estimation, a designing parameter such as radius of the circular patch has also been estimated with virtual instrument model and absolute error for radius has been shown in the display window of the designed model. The proposed antenna array has been fabricated and simulated results have been validated with measured results.

Natural Convection Solar Dryers for Agricultural Products — A Comprehensive Exploration

Objectives: To make review on passive solar dryers and its performance of drying agricultural products. Methods: This article focuses on the development in various categories of passive solar dryers in last six years. The different studies carried out in direct, indirect and mixed mode types of passive dryers for drying agricultural products in the year of 2014 to 2020 have been considered this review. Investigations on forced convection solar dryers have not been included in the current paper. The various experimental setups of solar dryers, specimens used for experimentation, measured output parameters and performance have been illustrated. The changes made in construction of solar dryers for improving the performance have also been reviewed. Findings:The mixed mode passive solar dryer is found to be superior in terms of drying time, better utilization of solar energy and efficiency compared to other passive dryers. Novelty: Several review articles have been published in solar dryers. Nevertheless, no comprehensive reviews have hitherto been published on passive dryers in particular. Hence, our current review article focuses on development in passive dryers and its advancements with emphasis on dryer design features, specimen and measured output parameters. Keywords: Passive solar dryers; Natural convection solar dryers; Direct solar dryers; Indirect solar dryers; Mixed mode solar dryers

The Effect of Processing on The Surface and Subsurface Characteristic of Plastic Injection Mold Steel

AISI P20 is prehardened mold steel that is commonly used to manufacture plastic injection molding. The surface characteristics of molds play crucial role to control plastic injected molds parts. Besides, the characteristic of molds is mainly influenced by machining process, the manufacturing process to produce molds. This study presents the extensive experimental work focusing on the machining processing conditions on the surface characteristics of Plastic Injection mold steels. The input parameters are cutting speeds, feed rates and cutting inserts’ geometry (wiper and non-wiper). The measured output parameters are subsurface hardness of machined parts and phase transformation induced from cutting process. Experimental results show that wiper insert significantly helps to improve surface quality of components. Besides, microhardness measurement shows that thermal softening occurs resulting from machining of this alloy. XRD data illustrates peak broadening and increased intensity with machined samples.

Effect of chilled air on delamination, induced vibration, burr formation and surface roughness in CFRP drilling: a comparative study

Exemplary mechanical properties made carbon fiber reinforced polymer (CFRP) laminates to find their place in automotive, defence and process industries. In this work, a comprehensive investigation is carried out on the vibration, thrust force, fiber pull-out, surface roughness and delamination while drilling CFRP laminates. The drilling is accomplished with different cutting velocities and feed rates under two environment viz. dry and chilled air. The investigation revealed the dominance of feed rate over cutting velocity on the measured output parameters. Drilling-induced vibrations are found to be increasing with increased feed rates. Under identical machining condition, chilled air environment could reduce the delamination factor to the maximum of about 19.49% and thus helps in mitigating the delamination and achieving good quality drilled holes.

Evolution of measured module characteristics versus labelled module characteristics of crystalline silicon based PV modules

This work outlines the evolution of measured module parameters (power Pmax, short circuit current Isc, open circuit voltage Voc) vs labelled module parameters of crystalline silicon PV modules over a number of decades at the European Solar Test Installation (ESTI) at Ispra, Italy. Manufacturers' tolerance in nameplate power has changed over the years with many claiming ±10% in the 80s and 90s. The declared tolerance over recent years has been reduced to ±5% then ±3% and today values of −0/+3% are quite common. To know the declared tolerance of modules in an operational system is useful additional information when investigating the aging of PV systems, when the original module power may either be unknown or missing with the passage of decades. Therefore, researchers have often to rely on the labelled power for the starting point of the system. Measurements at the ESTI laboratory have been performed since the early 1980s. A comparison of those modules which incorporated either a nameplate (or an associated datasheet, flash report or online information) to their measured output parameters (Pmax, Isc and Voc) has been carried out. The impact of these differences from an economic point of view has been also analysed. This work presents some selected results from a set of 992 crystalline silicon based modules, extracted from various time periods from 1982 to 2014.

Effect of cooling methods on hole quality in drilling of aluminium 6061-6T

The influence of cooling method and drilling parameters on hole production has been investigated experimentally and analytically by measuring the hole quality. A three-level, three-parameter experiment was conducted using design-of-experiment methodology. The three levels of independent input parameters were: for cooling method—flood drilling, minimum quantity lubrication (MQL) drilling and cryogenic drilling; for feed rate—0.2, 0.3 and 0.4 mm/rev; and for cutting speed—60, 75 and 100 m/min. The selected work and tool materials were aluminium 6061-6T and high speed steel (HSS), respectively. The measured output parameters were the three most widely used quality characteristics of drilled holes - diameter error, circularity and surface roughness. The results were analysed applying three methods: Pareto ANOVA, Taguchi method and traditional analysis. The findings revealed that the cooling method has a significant effect on diameter error (contribution ratio 88.27%), moderate effect on surface roughness (contribution ratio 41.74%) and relatively small effect on circularity (contribution ratio 23.64%). The best results for the dimensional accuracy and surface roughness were achieved by MQL drilling. Cryogenic drilling produced the best circularity results; however, in terms of dimensional accuracy and surface roughness it was the worst.

Effects of Insert Geometry and Feed Rate on Quality Characteristics of Turned Parts

This paper investigates experimentally and analytically the influence of insert geometry and feed rate on the quality characteristics of turned parts under the dry cutting condition. A three-level, three-parameter experiment was planned using the design of experiment methodology. The three levels of independent input parameters were: insert shape–rhombus, triangle, and square; nose radius 0.4, 0.8, and 1.2 mm; and feed rate–0.11, 0.22 and 0.33 mm/rev. The measured output parameters were the three most widely used quality characteristics of turned parts–diameter error, circularity and surface finish (arithmetic average). The results were analyzed using three methods: traditional analysis, Pareto analysis of variation and Taguchi method. The results reveal that two of the selected tool geometry parameters, insert shape and nose radius, influence diameter error considerably (total contribution 66.97%) and have minor effects on circularity (total contribution 3.67%) and surface finish (total contribution 11.60%). Feed rate is the major contributor to surface finish (76.42% contribution), whereas circularity is dominated by interaction effects such as insert shape–feed rate interaction (31.44% contribution).

Theoretical and Data-Based Mathematical Model of a Special Vehicle Breaking System

Military vehicles have to travel, at least from time to time, on the national road network. Whenever that happens, the A military vehicle doesnt have to meet all the requirements of a civilian vehicle. Moreover, its lifecycle is much longer than a civilian vehicles one. This is the reason a military vehicle doesnt have to meet all the requirements that a civilian one has to. Nevertheless, traffic security asks for periodical checks of the braking, steering and other systems. In this respect, we have been contracted to develop a method to assess the braking systems parameter of a certain class of military vehicles. When an assessment is involved, we usually develop a basic mathematical model to be the basic feature for further investigation. Since for the old vehicles there are no database, we have created two models, one by numerical simulation and the other one by processing the experimental data. Should be mentioned that prior to use one of them for further analysis, we had to check for the models accuracy. Data have been achieved using a very up-to-date measuring system. Moreover, the data was subject to filtering procedures, taking into account the noises of the system and different other measuring errors. We have tested several vehicles that were in good technical condition. All in all, we have tried to create a reliable database that should stand back from a trusting point of view. The working characteristic features of a process can be synthetically expressed as a mathematical model. For the technical systems, this model can be obtained either based on the mathematical expressions that describe the working way of the systems components or on data-base grounds that have been previously achieved throughout experimental research. As far as the validation of the mathematical model is concerned, the modelling error should be kept under tight control. Therefore, the researcher has to permanently determine the difference between either the simulated and measured output parameters. Eventually, the validated mathematical model can be used to analyse the dynamic performances of the system or a proper way to improve them, as far as the actual evolution of the system is accurately enough described. Key words: vehicles, braking system, theoretical models, data based models, modelling error

EFFECT OF ADDITIONAL FACTORS ON DIMENSIONAL ACCURACY AND SURFACE FINISH OF TURNED PARTS

This article reports the experimental and analytical results of an investigation of additional factors that affect the dimensional accuracy and surface finish of turned parts besides the three major cutting parameters—cutting speed, feed rate, and depth of cut. The selected additional factors were cooling method, blank size, and work material. A three-level, three-parameter experiment was planned using design-of-experiment methodology. The three levels of independent input parameters were: for cooling method—dry turning, flood turning, and minimum quantity lubrication turning; for blank size—φ20, 40, and 60 mm; and for work material—aluminium 6061, mild steel 1030, and alloy steel 4340. The measured output parameters were the two most widely used dimensional accuracy characteristics of turned parts—diameter error and circularity—and the surface finish characteristic arithmetic average. The results were analyzed applying three methods: traditional analysis, Pareto ANOVA, and Taguchi method. The results reveal that, while work material has the greatest effect on diameter error and surface roughness, the major contributor to circularity is blank size.

Grinding with helically grooved wheels

This study presents an experimental investigation of the cylindrical grinding process AISI 1040, AISI 8620, AISI 5140 and AISI 52100 steels with using helically grooved grinding wheels with of 15°, 30° and 45°. The main purpose of this experimental study is to investigate different angle grooved induced surface and dimensional quality, as well as one of the significant surface integrity parameters residual stress. The obtained results illustrate the significance of grooved angle in terms of measured output parameters. The experimental results showed that grinding with helically grooved wheels improves the ground surface finish. Consequently, the improvement ratios of the surface roughness, roundness and residual stress using a helically grooved grinding wheel for 45° were 28–73%, 47–137% for four steel and 4.4% for AISI 1040 steel, respectively. Moreover, the results from the analysis of the variance indicated that the materials and grinding wheels have a significant effect on both surface roughness and roundness.

Are home-use intense pulsed light (IPL) devices safe?

The domestic market for home-use hair removal devices is rapidly expanding and there are numerous intense pulsed light (IPL) products now available globally to consumers. Technological challenges for the design of such devices include the need to be cost-effective in mass production, easy to use without training, and most importantly, clinically effective while being eye-safe. However inexpensively these light-based systems are produced, they are designed to cause biological damage to follicular structures, so precautions to prevent both ocular and epidermal damage must be considered. At present, there are no dedicated international standards for IPL devices. This review directly compares three leading domestic IPL hair removal devices: iPulse Personal (CyDen, UK), Silk'n/SensEpil (Home Skinovations, Israel), and SatinLux/Lumea (Philips, Netherlands) for fluence, emitted wavelength spectrum, time-resolved footprint, and spatial distribution of energy. Although each device has a primary mechanical or electrical safety feature to ensure occlusion of the output aperture on the skin to prevent accidental eye exposure, the ocular hazard of each device has been measured to IEC TR 60825-9 standard using an Ocean Optics HR2000+ photo spectrometer for both potential corneal and retinal damage. Using established measurement methods, this review has shown that the measured output parameters were significantly different for the three systems. Using equipment traceable to national standards, one device was judged at its two highest settings to be hazardous for naked eye viewing. This investigation also reports on the significantly different pulse durations of the devices measured and considers the potential impact on safety and efficacy in the light of the theory of selective photothermolysis. Although these devices offer low-cost personal convenience of treatment in the privacy of the home, ocular safety may be inadequate in the event of primary safety mechanism failure.

Estimating the urban metabolism of Canadian cities: Greater Toronto Area case study

An urban metabolism analysis is a means of quantifying the overall fluxes of energy, water, material, and wastes into and out of an urban region. Analysis of urban metabolism can provide important information about energy efficiency, material cycling, waste management, and infrastructure in urban systems. This paper presents the first urban metabolism of a Canadian urban region, and possibly the first for a North American city. It also makes a first attempt at comparing the urban metabolisms of a few cities worldwide. The most noticeable feature of the Greater Toronto Area metabolism is that inputs have generally increased at higher rates than outputs over the study years (1987 and 1999). The inputs of water and electricity have increased marginally less than the rate of population growth (25.6%), and estimated inputs for food and gasoline have increased by marginally greater percentages than the population. With the exception of CO2 emissions, the measured output parameters are growing slower than the population; residential solid wastes and wastewater loadings have actually decreased in absolute terms over the 12 year period from 1987 to 1999.Key words: urban metabolism, urban sustainability, Canadian cities, materials, food, water and energy consumption, waste outputs.

Fluorescence spectroscopy and multivariate spectral descriptor analysis for high-throughput multiparameter optimization of polymerization conditions of combinatorial 96-microreactor arrays.

Selection of optimum process conditions in combinatorial microreactors is essential if the combinatorial synthesis process is to be correlated with the synthesis process on a more conventional scale and the materials are to have the desired chemical properties. We have developed a new methodology for the high-throughput multiparameter optimization of polymerization reaction conditions in arrays of microreactors. Our strategy is based on the application of nondestructive spectroscopic techniques to measure chemical properties of polymers directly in individual microreactors followed by the multivariate spectral descriptor analysis for rapid determination of the optimal process conditions. We have demonstrated our strategy in the high-throughput multiparameter optimization of process conditions in thin-film melt polymerization reactions performed in 96-microreactor arrays for combinatorial screening of new polymerization catalysts. The combinatorial polymerization system was optimized for the best processing parameters using a set of input variables that included reactant parameters (relative amounts of starting components and catalyst loading) and processing variables (reaction time, reaction temperature, and inert gas flow rate). The measured output parameters were the chemical properties of materials and reproducibility of the material formation in replicate polymerizations in microreactors. Spatially resolved nondestructive evaluation of polymer formation was performed directly in individual microreactors and provided information about the spatial homogeneity of polymers in microreactors. It showed to be another powerful indicator of the reproducible polymerization process on the combinatorial scale. Although the methodology described here was implemented for high-throughput optimization of polymerization conditions, it is more general and can be further implemented for a variety of applications in which optimization of process parameters can be studied in situ or off-line using spectroscopic and other tools.

LIMSoft: automated tool for sensitivity analysis and test vector generation

In analogue circuits, deviation in component values causes deviation in the measured output parameters. The relation between the two deviations is the sensitivity function. The paper presents an automated sensitivity analysis tool called LIMSoft, based on the adjoint network method which offers the possibility of DC, AC and transient sensitivity computation. The sensitivity value is then used for soft-fault test vector generation.