Fluid and Structure Analysis of Wind Turbine Blade with Winglet

One of the succeeded methods to enhance the performance of horizontal axis wind turbine (HAWT) is an attaching a winglet to the blades tip. The current paper study the effect of four key parameters that are used to describe the winglet on the performance of wind turbine which are winglet height H%R, cant angle θ, twist angle β, and taper ratio Λ. A five design cases for each geometric parameters were numerically investigated using computational fluid dynamics (CFD) by ANSYS18.1 software, which totally give a twenty different response. A validation of present computational model with reference experimental results successfully carried out with maximum inconsistency of 3%. A mathematical correlation was established from the CFD results and being used in predicting the turbine power for the different winglet geometric parameters. From CFD and mathematical correlation response, the effect of H and θ were greater than β and Λ on the turbine power. The epoxy E-glass unidirectional material was selected for current study to investigate the effect of winglet on blade structure. The power increases by 2% to 30% due to adding winglet to a wind turbine blade. The maximum power increment corresponds to the design case of W6 with H= 8%R, =30°, β = 3°, and Λ = 0.8. Form the structural analysis the addition of winglet changes the stress distribution over the blade, increasing stresses at the blade root, and achieved the transfer of the maximum deformation from the blade tip to the winglet tip.

Nonlinear Hyperparameter Optimization of a Neural Network in Image Processing for Micromachines

Deep neural networks are widely used in the field of image processing for micromachines, such as in 3D shape detection in microelectronic high-speed dispensing and object detection in microrobots. It is already known that hyperparameters and their interactions impact neural network model performance. Taking advantage of the mathematical correlations between hyperparameters and the corresponding deep learning model to adjust hyperparameters intelligently is the key to obtaining an optimal solution from a deep neural network model. Leveraging these correlations is also significant for unlocking the “black box” of deep learning by revealing the mechanism of its mathematical principle. However, there is no complete system for studying the combination of mathematical derivation and experimental verification methods to quantify the impacts of hyperparameters on the performances of deep learning models. Therefore, in this paper, the authors analyzed the mathematical relationships among four hyperparameters: the learning rate, batch size, dropout rate, and convolution kernel size. A generalized multiparameter mathematical correlation model was also established, which showed that the interaction between these hyperparameters played an important role in the neural network’s performance. Different experiments were verified by running convolutional neural network algorithms to validate the proposal on the MNIST dataset. Notably, this research can help establish a universal multiparameter mathematical correlation model to guide the deep learning parameter adjustment process.

Computer Application to Estimate PVT Conditions in Oil Wells in the Ecuadorian Amazon

A reservoir behaviour's characterisation is determined by analysing the fluids' physical properties, reported in Pressure, Volume and Temperature (PVT) tests. These tests are performed in the laboratory or are estimated by mathematical correlations with the well's basic properties. The eastern basin of Ecuador is considered a hydrocarbon zone, and the analysis of the physical properties of the fluid from oil wells is essential. The aim is to develop the PVTTESTSYSTEM software to estimate PVT conditions when there are no laboratory tests. The study methodology is based on (i) Compilation of 10 PVT laboratory tests of oil wells in the eastern basin of Ecuador; (ii) Analysis of mathematical correlations; (iii) Development of the PVTTESTSYSTEM software, with the wells' initial conditions' input, selecting the mathematical correlation and estimation of results, based on the relationship of the properties of oil and gas; iv) Comparison of data obtained by laboratory tests and PVTTESTSYSTEM software reports. The software used with a graphical interface presents a registration and login platform and five modules that allow: inserting company and field data, initial oil well data, selecting correlations, calculating PVT properties and generating a graphic report. The results show that the mathematical correlations that estimate PVT properties were systematised, which approximate the laboratory tests' real results. The approximation of the calculated results with the actual results establishes a high confidence level for the PVTTESTSYSTEM software.

Measured and predicted freeze-thaw days frequencies in climate change conditions in central Poland

The rate of progression of geomorphological phenomena is greatly influenced by freeze-thaw processes. In the face of air temperature increasing over the past few decades, a question of the future impact of these processes arises, notably in the temperate and cold climate zones. Using the mean, maximum and minimum daily air temperature data in the period 1951–2018 obtained from three weather stations located in the vicinity of Jeziorsko reservoir (central Poland), we have determined the mathematical correlation, described with a polynomial function, between the mean monthly air temperature and the monthly number of freeze-thaw days (FTD). A freeze-thaw day is a day when the maximum air temperature is above 0 °C while the minimum air temperature equals or is below this threshold. The number of FTDs within the study area averaged 64–71 and demonstrated a downward trend of 2–4 FTDs/10 years. The study period (1951–2018), includes a clearly marked distinct sub-period (1991–2018), when the reservoir was in operation, which experienced 58–68 FTDs. Considering the assumed rise in temperature, one should expect a further, though slightly slower, decline in the future number of FTDs. Depending on the accepted model of the temperature increase, which for the area of Poland (Central Europe) in the perspective of 30 years oscillates between +1.1 to +1.3 °C, the number of FTDs within the study area is expected to decline by −4.5 to −5.3 FTD, i.e. 6–7% and 5.4–5.5 FTD i.e. 8–9% respectively.

Tunable, Anisotropic Permeability and Spatial Flow of SLM Manufactured Structures

In this study, we report on a novel approach to produce defined porous selectively laser molten structures with predictable anisotropic permeability. For this purpose, in an initial step, the smallest possible wall proximity distance for selectively laser molten structures is investigated by applying a single line scan strategy. The obtained parameters are adapted to a rectangular and, subsequently, to a more complex honeycomb structure. As variation of the hatch distance directly affects the pore size, and thus the resulting porosity and finally permeability, we, in addition, propose and verify a mathematical correlation between selective laser melting process parameters, porosity, and permeability. Moreover, a triangular based anisotropic single line selectively laser molten structure is introduced, which offers the possibility of controlling the three-dimensional flow ratio of passing fluids. Basically, one spatial direction exhibits unhindered flow, whereas the second nearly completely prohibits any passage of the fluid. The amount to which the remaining orientation accounts for is controlled by spreading the basic triangular structure by variation of the included angle. As acute angles yield low passage ratios of 0.25 relative to continuous flow, more obtuse angles show increased ratios up to equal bidirectional flow. Hence, this novel procedure permits (for the first time) fabrication of selective laser molten structures with adjustable permeable properties independent of the applied process parameters.

Influence of compression stockings on the sensation of discomfort and the volume of the lower legs in healthy subjects during standing load

BACKGROUND: Edema caused by orthostasis is a common clinical picture in the medical and occupational context. Medical compression therapy with compression stockings (CS) is considered a conservative therapeutic standard in edema therapy. The effect of CS on leg discomfort and the increase of the lower leg volume during a standing load still remains questionable. In addition, it is not entirely known whether there is a correlation between volume increase and discomfort in these individuals. METHOD: A timed, controlled standing load of 15 min was conducted by the participants in this non-randomized controlled study to analyze the change in and correlation between lower leg volume increase and the occurrence of lower leg discomfort under compression therapy. Below-knee CS with an interface pressure of 23–32 mmHg were used. The lower leg volume was measured following previous studies using an optical three-dimensional volume (ml) measurement system, and sensations of discomfort and the urge to move were asked about using a numerical rating scale (NRS) of 0–10. The subjects conducted a leg movement for 15 s immediately after the standing period; the data were collected again subsequently. A correlation was calculated between the lower leg volume and the data regarding the discomfort and urge to move for each participant. The experiments had already been performed as part of a previous study including the same subjects who did not wear CS. The results of the study conducted here were compared with those of the participants who did not wear CS to investigate the effect of the CS. RESULTS: Lower leg volume increased by an average of 27 ml (p < 0.001) (without CS: by 63 ml) during standing load in the right leg. During the leg movement after standing load, the lower leg volume increased by 5 ml (n.s.). The sensations of discomfort during the orthostasis increased by 2.6 points on the NRS (p < 0.001) (without CS: by 3.46 points) and decreased by 1.67 points (p < 0.001) during the leg movement shortly after the standing period. Participants’ urge to move increased by 3.73 points on the NRS (p < 0.001) (without CS: by 3.47 points) while the participants performed the standing period and decreased by 2.73 points (p < 0.001) during the final movement exercise. A weakly significant correlation could be demonstrated between the increase in the lower leg volume and the occurrence of discomfort in 6 out of 13 subjects (p < 0.1), and between the increase in the lower leg volume and the urge to move in 8 out of 15 subjects (p < 0.1). CONCLUSION: Standing loads and lack of movement lead to an increase in the lower leg volume and sensation of discomfort in venous healthy subjects wearing CS, which are reduced by wearing them (p < 0.001). A weakly significant mathematical correlation (Pearson’s correlation coefficient) could be shown between the increase in the lower leg volume and the occurrence of the urge to move in 8 out of 15 subjects (p < 0.1) and between the increase in lower leg volume and the occurrence of leg discomfort in 6 out of 13 subjects (p < 0.1).

On detour index of cycloparaphenylene and polyphenylene molecular structures

Cycloparaphenylene is a particle that comprises a few benzene rings associated with covalent bonds in the para positions to frame a ring-like structure. Similarly, poly (para-phenylenes) are macromolecules that include benzenoid compounds straightforwardly joined to each other by C–C bonds. Because of their remarkable architectural highlights, these structures have fascinated attention from numerous vantage focuses. Descriptors are among the most fundamental segments of prescient quantitative structure-activity and property relationship (QSAR/QSPR) demonstrating examination. They encode chemical data of particles as quantitative numbers, which are utilized to create a mathematical correlation. The nature of a predictive model relies upon great demonstrating insights, yet additionally on the extraction of compound highlights. To a great extent, Molecular topology has exhibited its adequacy in portraying sub-atomic structures and anticipating their properties. It follows a two-dimensional methodology, just thinking about the interior plan, including molecules. Explicit subsets speak the design of every atom of topological descriptors. When all around picked, these descriptors give a unique method of describing an atomic system that can represent the most significant highlights of the molecular structure. Detour index is one such topological descriptor with much application in chemistry, especially in QSAR/QSPR studies. This article presents an exact analytical expression for the detour index of cycloparaphenylene and poly (para-phenylene).

Influence of surface roughness, friction coefficient, and wrap angle on clinching joint strength and its correlation with belt friction phenomenon

Clinching is an economical sheet joining technique that does not require any consumables. Besides, after its usage, the joints can be recycled without much difficulty, making clinching one of the most sustainable and eco-friendly manufacturing processes and a topic of high research potential. In this work, the influence of surface roughness on the load-bearing capacity (strength) of joints made by the mechanical clinching method in cross-tensile and lap-shear configuration is explored. Additionally, a correlating mathematical model is established between the joint strength and its surface parameters, namely, friction coefficient and wrap angle, based on the belt friction phenomenon. This correlation also explains the generally observed higher strength in lap-shear configuration compared to cross-tensile in clinching joints. From the mathematical correlation, through friction by increasing the average surface roughness, it is possible to increase the strength of the joint. The quality of the thus produced joint is analyzed by cross-sectional examination and comparison with simulation results. Experimentally, it is shown that an increment of >50% in the joint strength is achieved in lap-shear configuration by modifying the surface roughness and increasing the friction coefficient at the joint interface. Further, the same surface modification does not significantly affect the strength in cross-tensile configuration.

Voltage rise anemometry in turbulent flows applied to internal combustion engines

In an experimental procedure, a voltage rise anemometry is developed as a measurement technique for turbulent flows. Initially, fundamental investigations on a specific wind tunnel were performed for basic understanding and calibration purpose. Thus, a mathematical correlation is derived for calculating flow from measured secondary voltage of an ignition system under different thermodynamic conditions. Subsequently, the derived method was applied on a spark-ignited engine to measure in-cylinder flow. Therefore, no changes on combustion chamber were necessary avoiding any interferences of the examined flow field. Comparing four different engine configurations, a study of mean flow and turbulence was performed. Moreover, the results show a clear correlation between measured turbulence and analysed combustion parameters. Graphic abstract