Variations In Dimensions Research Articles

Static analysis of multi-turn stepped spindle shafts on nonlinear elastic supports

In this paper a mathematical model and a computational technique for the static analysis of multi-support stepped spindle shafts on nonlinear elastic supports are presented. On the basis of the Timoshenko differential equation of the beam's bent axis and the method of initial parameters, a resolving system of equations is obtained that takes into account the nonlinear dependency of the stiffness of the bearings on the forces acting on them along with the stepwise variation of the cross-sectional dimensions of the shaft. A numerical method for solving the problem has been proposed and a software tool has been developed, which performs the static analysis of multi-support stepped spindle shafts on nonlinear elastic supports in MATLAB environment.

ANALYSIS OF THE EFFECT OF COLUMN DIMENSION VARIATIONS ON THE STRUCTURE OF A 12-STORY APARTMENT BUILDING

High-rise buildings are building structures that are vulnerable to lateral forces so they must be designed to be able to withstand lateral loads, such as wind and earthquakes. Buildings in earthquake-prone areas must be planned to be able to withstand earthquakes. Basically, buildings that are designed to withstand earthquakes, the columns must be strong. The purpose of this study is to determine the effect of column dimension variations on building structure and obtain effective and efficient column dimensions in the planned building. The research method is preceded by conducting a literature study. Furthermore, data collection was carried out, making preliminary design of the structure, and conducting structural analysis using the help of ETABS 19.1.0 software. The results of analysis and comparison show that the smallest displacement value occurs in model 1 of 81.724 mm in the X direction and 83.776 mm in the Y direction. While the largest displacement occurs in model 3 of 95.222 mm in the X direction and 96.678 mm in the Y direction, but the displacement that occurs in model 3 is still within the permissible safe limit (100mm).

Vehicle Simulation Algorithm for Observations with Variable Dimensions Based on Deep Reinforcement Learning

Vehicle simulation algorithms play a crucial role in enhancing traffic efficiency and safety by predicting and evaluating vehicle behavior in various traffic scenarios. Recently, vehicle simulation algorithms based on reinforcement learning have demonstrated excellent performance in practical tasks due to their ability to exhibit superior performance with zero-shot learning. However, these algorithms face challenges in field adaptation problems when deployed in task sets with variable-dimensional observations, primarily due to the inherent limitations of neural network models. In this paper, we propose a neural network structure accommodating variations in specific dimensions to enhance existing reinforcement learning methods. Building upon this, a scene-compatible vehicle simulation algorithm is designed. We conducted experiments on multiple tasks and scenarios using the Highway-Env traffic environment simulator. The results of our experiments demonstrate that the algorithm can successfully operate on all tasks using a neural network model with fixed shape, even with variable-dimensional observations. Our model exhibits no degradation in simulation performance when compared to the baseline algorithm.

Variation of Physical and Mechanical Properties of Pinus Sylvestris L. Wood in the Boreal Zone of the European Northeast

The study considers variational aspects of physical and mechanical properties of Scots pine (Pinus sylvestris L.) wood depending on conditions and growth areas in the boreal zone of the European Northeast. Anatomical traits of xylem and its strength properties were analyzed. Based on the data received, statistical processing of the material was carried out using correlation and multivariate analysis. The impact of hazardous air emissions on variation of linear dimensions in structural elements of the annual height increment in the trunk diameter was estimated. A varying nature of the influence of environmental factors on the formation of strength properties of P. sylvestris wood in growth areas was attested. The variation value of basic wood density decreases as soil and hydrological conditions of growth improve. A significant negative correlation between basic wood density and distance to sources of hazardous air emissions in the areas of concentration of industrial enterprises was established. The results of multivariate analysis make it possible to reveal the weight of the influence of environmental factors and biometric characteristics of wood on volumetric and strength properties of pine wood. Growth in the impact zone of air emissions from large industrial enterprises in the study area does not produce a significant effect on the dynamics of wood strength properties, taking into account various growth conditions. For Scots pine growing in the European Northeast, the study determined a significant impact of the size and structure of the annual height increment of the trunk in terms of diameter, as well as the position of the wood sample in terms of trunk volume, on strength properties of pine wood.

A Methodology for Quantifying the Spatial Distribution and Social Equity of Urban Green and Blue Spaces

Urban green and blue space (UGBS) contribute to a variety of nature-based values and human health benefits. As such, they play a critical role for the quality of life and sustainability in cities. Here, we use the metropolitan area of Geneva, Switzerland, as a case study to illustrate that UGBS are heterogeneous in spatial characteristics, such as surface area, naturality, or noise levels, which are associated with key cultural ecosystems services. For each characteristic, we defined a threshold with the realization of an associated cultural ecosystem service, including a novel noise threshold (LAeq < 45 dB) compatible with the notion of “quiet”. We then used geospatial information to generate place-based and people-based indicators that collectively describe the variation in key dimensions of UGBS. We found that, in Geneva, the typical (median) resident has access to 4.7 ha of UGBS, and 89% of residents live within 300 m of the nearest UGBS. Accessible surfaces of UGBS per capita, however, were highly variable by type of UGBS and across neighbourhoods. For example, residents from precarious neighbourhoods are less likely to live within 300 m of quiet UGBS than residents of privileged neighbourhoods, and when they do, these UGBS tend to be smaller. The proposed methodology categorizes UGBS in a manner that both captures their distinct social roles and highlights potential social injustice issues.

FRACTAL DIMENSIONS OF THE LOGARITHM OF CONTINUOUS FUNCTIONS

This paper investigates the variation of fractal dimensions of continuous functions under operations. It is found that the Box dimension of the logarithm of positive continuous functions remains constant, and any nonzero real power of a positive continuous function can keep fractal dimensions variation closed. The study also discusses the fractal dimension of logarithmic function with bases of fractal functions, and the corresponding fractal dimension is determined by the function with the larger fractal dimension.

Differential diagnosis of Lewy body dementias using multivariate EEG classifiers

AbstractBackgroundLewy body dementia (LBD) results from pathology in ɑ‐synuclein and is the second most common cause of dementia. LBD has two manifestations: Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB). There is currently no non‐invasive, fast, reliable way to distinguish between early‐stage PDD, DLB, and Alzheimer’s disease (AD). Although previous traditional EEG visual rating methods have not been useful in delineating dementia subtypes, resting‐state electroencephalography (rsEEG) is a promising method for differential diagnosis of dementia, because it is inexpensive, non‐invasive, and widely available for clinical use. Here, we demonstrate how a multivariate classifier using rsEEG as input can differentiate PDD, DLB, and Alzheimer’s disease.MethodWe analyzed rsEEG data from older adults (N = 133, age 59‐89) with AD (n = 33), DLB (n = 27) or PDD (n = 45). We computed the aperiodic and periodic parameterization of brain activity, along with metrics of variation in fractal dimension within specific frequency bands. We then used these features, along with age and sex, to develop XGBoost machine‐learning models to predict patient diagnoses. Models were evaluated using cross‐validation with balanced accuracy, weighted sensitivity, and weighted specificity.ResultThe first task was a two‐way classification: Control vs Dementia (accuracy = 86%, sensitivity = 93%, specificity = 79%, p < .001). The second task was a three‐way classification: AD vs DLB vs PDD (accuracy = 66%, sensitivity = 70%, specificity = 82%, p < .001). We also evaluated two‐way models distinguishing between AD vs DLB (accuracy = 86%, sensitivity = 87%, specificity = 86%, p < .001), AD vs PDD (accuracy = 84%, sensitivity = 85%, specificity = 83%, p < .001), AD vs LBD (combined DLB and PDD; accuracy = 82%, sensitivity = 85%, specificity = 78%, p < .01), and DLB vs PDD (accuracy = 68%, sensitivity = 71%, specificity = 65%, p < .05).ConclusionMachine‐learning and rsEEG are capable of distinguishing between AD and LBD. Moreover, machine‐learning combined with spectral and fractal features can distinguish between DLB and PDD, despite both forms of dementia arising from ɑ‐synuclein pathology.

LMdist: Local Manifold distance accurately measures beta diversity in ecological gradients.

Differentiating ecosystems poses a complex, high-dimensional problem constrained by capturing relevant variation across species profiles. Researchers use pairwise distances and subsequent dimensionality reduction to highlight variation in a few dimensions. Despite popularity in analysis of ecological data, these low-dimensional visualizations can contain geometric abnormalities such as "arch" and "horseshoe" effects, potentially obscuring the impact of environmental gradients. These abnormalities appear in ordination but are in fact a product of oversaturated large pairwise distances. We present Local Manifold distance (LMdist), an unsupervised algorithm which adjusts pairwise beta diversity measures to better represent true ecological distances between samples. Beta diversity measures can have a bounded dynamic range in depicting long environmental gradients with high species turnover. Using a graph structure, LMdist projects pairwise distances onto a manifold and traverses the manifold surface to adjust pairwise distances at the upper end of the beta diversity measure's dynamic range. This allows for values beyond the range of the original measure. Not all datasets will have oversaturated pairwise distances, nor will capture variation that resembles a manifold, so LMdist adjusts only those pairwise values which may be undervalued in the presence of a sampled gradient. The adjusted distances serve as input for ordination and statistical testing. We demonstrate on real and simulated data that LMdist effectively recovers distances along known gradients and along complex manifolds such as the Swiss roll dataset. LMdist enables more powerful statistical tests for gradient effects and reveals variation orthogonal to the gradient. Available on GitHub at https://github.com/knights-lab/LMdist.

Societal transitions, ethnolinguistic identities, and marital conservatism in Central Asia

AbstractObjectiveThe study deploys an ethnolinguistic conceptual framework to examine variations in different dimensions of marital conservatism in the Kyrgyz Republic, a post‐Soviet nation in Central Asia, focusing on enduring, yet evolving, Russian linguo‐cultural influence.BackgroundThe global transformation of family and marriage systems has produced diverse local normative patterns that are historically rooted but are also reflective of context‐specific contemporary socio‐cultural, political, and economic transitions. The study investigates these patterns in a multi‐ethnic setting where Soviet‐era legacies, culturally pivoted on the use of the Russian language, have combined with post‐Soviet exposure to both Western influences and rising neo‐traditionalism.MethodThe study uses data from two rounds of a nationally representative cross‐sectional household‐based survey, with each round including standardized interviews with over 2000 men and women aged 18–49. Multi‐level regression models are fitted to predict ethnolinguistic variations in attitudes toward premarital chastity, optimal marriage age, support for parental preeminence in marital decisions, support for ethnic endogamy, and opposition to divorce, while accounting for universal correlates of marital conservatism, such as education, religiosity, and urbanicity. For most outcomes, the analyses examine separately how these attitudes apply to women versus men.ResultsThe results demonstrate the persistent normative imprints of the Russian linguistic and cultural influence but also instructive variations in them across the specific outcomes. They also suggest an overall rise in some aspects of marital conservatism.ConclusionThe findings elucidate the unique multidimensional complexities of family and marital change in transitional Eurasia, yet also its similarities with other post‐colonial contexts.

Coupled electric circuits method applied to pulsed eddy current NDT problem

The present work concerns the study of the effect of variation of the thickness of 2D cylindrical test-piece and lift-off (the air gap between the sensor and the test-piece) on the sensor response in case of transient source current. The coupled circuit’s method employed is based on the mutual’s inductances calculation and with the association to Kirchhoff laws it yields to a transient algebraic equations system which is solved at each time step. The method is applied to the study of the pulsed eddy currents in cylindrical and axisymmetric device with electrical conductivity and geometrical dimensions variations.

An Optimization Method for Improving the Accuracy of Multiple Parametric Printed Parts in FDM

Dimensional accuracy is one of the main key features for achieving the desired fit in fused deposition modeling (FDM). Printer tolerance and build orientation are the main challenges faced during the prototyping phase and hence there is a need for a method to calibrate the printer and the material being used that can serve as a guide to designing the clearances of mating parts. This paper presents the design and validation of a tolerance prototype and the study, which, with some analysis and data representation, gives the optimal solution. Hence, this can be used to compensate for the variations in dimensions while printing. A tolerance prototype model consisting of squares and circles of various dimensions is developed in Siemens NX 11.0 that tests the printer in three different orientations i.e., x-axis, y-axis and z-axis. FDM printers Accucraft i250 (heat bed type) and Flashforge (non-heat bed type) are used to print the prototype. The dimensions are measured with calipers to arrive at the dimensional correction templates that are further used to design and validate movable components.

The temporal dimension of parental employment: Temporary contracts, non-standard work schedules, and children’s education in Germany

AbstractThe increasing prevalence of non-standard work and its adverse consequences are well documented. However, we still know little about how common non-standard work is amongst parents, and whether its negative consequences are further transmitted to their children. Using data from the German Microcensus, we document the prevalence and concentration of temporary employment and non-standard work schedules in households with children in Germany. Second, we examine the extent to which variation in this temporal dimension of parental employment is associated with children’s school track. Results show that in about half of all German households with children in lower-secondary school at least one parent has a temporary contract or regularly works evenings or Saturdays. We find that children whose mother always works evenings or Saturdays are substantially less likely to transition to the academic school track. By contrast, we find no significant association between fathers’ non-standard work schedules and children’s school track. We also find no evidence of an association between parents’ temporary employment and children’s school track placement. These divergent findings highlight the importance of disaggregating non-standard work into its specific components and differentiating between mothers' and fathers' non-standard work when investigating the consequences of parental non-standard work for children’s educational and life chances.

Relating metric crown dimensions to underlying internal daily secretion rates in antimeric premolars

ObjectivesThe underlying cause for metric differences in antimeric tooth pairs is an important question for understanding dental variation. We hypothesize that localized variation in crown dimensions will be reflected in localized variation in daily enamel secretion rate. DesignCasts of pairs of human premolars from a tissue bank were 3D scanned using an optical scanning system (n = 32). Histological slides were created, and daily secretion rates (DSRs) were recorded in two areas of enamel that corresponded to scanner measurements. Antimeres were compared for both metric measurements and DSRs. Outliers for scanner measures were compared to significant differences in DSRs measurements in right and left teeth in corresponding areas. ResultsThirteen of the 16 individuals differed significantly in antimeric metric measurements, but only ten of those also differed in the underlying DSR. Fifteen of the 16 total individuals differed significantly in at least one DSR area. DiscussionWhile some individuals were outliers for metric measurements and had multiple areas of DSR differences, the majority of individuals had antimeric DSR differences regardless of metric differences. While there was no conclusive correlation between 3D metric analysis and underlying DSR differences, the most important result of this study is that DSR differences between antimeres are common.

Functions with Bounded Hessian–Schatten Variation: Density, Variational, and Extremality Properties

In this paper we analyze in detail a few questions related to the theory of functions with bounded p-Hessian–Schatten total variation, which are relevant in connection with the theory of inverse problems and machine learning. We prove an optimal density result, relative to the p-Hessian–Schatten total variation, of continuous piecewise linear (CPWL) functions in any space dimension d, using a construction based on a mesh whose local orientation is adapted to the function to be approximated. We show that not all extremal functions with respect to the p-Hessian–Schatten total variation are CPWL. Finally, we prove the existence of minimizers of certain relevant functionals involving the p-Hessian–Schatten total variation in the critical dimension d=2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$d=2$$\\end{document}.

Abstract 15800: Evaluating the Correlation Between Right Ventricular Outflow Tract Dimensions and Arrhythmia Risk Following Self-Expanding Transcatheter Pulmonary Valve Replacement

Introduction: The introduction of self-expanding valves has allowed for an expanded range of patients who can be treated with transcutaneous pulmonary valve replacement (TPVR). Though major complications are rare, ventricular tachycardia has been reported following self-expanding valve placement prompting investigation of potential risk factors. Hypothesis: Significant variation in valve dimensions within the right ventricular outflow tract (RVOT) throughout the cardiac cycle is postulated as a cause for increased arrhythmia risk. We hypothesized that greater dynamic variation of the valve in the RVOT correlates to higher ventricular arrythmia risk. Methods: A single center review was performed of patients who underwent TPVR with either Harmony TPV or Alterra Pre-stent with subsequent placement of 29mm Sapien valve between 2019 and 2023. Using post-procedural 3D rotational angiography, minimum (systole) and maximum (diastole) diameters (mm), perimeter (mm) and cross-sectional area (mm 2 ) of the valve frame were measured in two locations: closest to the branch pulmonary artery bifurcation and the RV cavity. Results: Twenty-eight patients were included (14 Harmony TPV, 14 Alterra). Higher frequency of ventricular arrythmia was seen in patients with congenital pulmonary stenosis ( p =0.004). Higher ventricular arrythmia rate was associated with larger diastolic diameter (34.1 vs 33.2mm, p =0.04), mean perimeter (118.3 vs 108.6mm, p =0.03) and area (1124.5 vs 926.2mm 2 , p =0.03) of the valve frame closest to the RV cavity. Conclusions: Increased movement of the valve frame close to the RV cavity may correlate with a higher ventricular arrythmia risk due to increased contact with the native RVOT throughout the cardiac cycle. Future studies should focus on more accurate, mathematical methodology to better understand whether the complex interaction between self-expanding valves and the native RVOT is a determinant for post-procedural ventricular arrythmia.

A remote sensing-based strategy for mapping potentially toxic elements of soils: Temporal-spatial-spectral covariates combined with random forest

The selection of predictor variables is a crucial issue in building a digital mapping model of potentially toxic elements (PTEs) in soil. Traditionally, the predictor variables for mapping models of soil PTEs have been chosen from sets of spatial parameters or spectral parameters derived from geographical environmental data. However, the enrichment of soil PTEs exhibits significant variations in both spatial and temporal dimensions, with the temporal dimension often being overlooked in the selection of predictor variables for digital mapping models. This limitation hampers the robustness and generalizability of the models. Therefore, multi-source geographical data were used in this study to determine three temporal indices for characterizing the enrichment process of soil PTEs in temporal dimensions, and additionally to construct the temporal-spatial-spectral (TSS) covariate combinations. The random forest (RF) algorithm was used to map soil PTEs at a regional scale. Results showed that: (1) When using spatial parameters or spectral parameters as predictor variables and measured Pb content as the dependent variable, the values of the model performance indicator RPIQ (ratio of performance to inter-quartile range) were 2.66 and 2.27, respectively. After incorporating the temporal parameters into the model input, values of RPIQ for the RF model reached 3.55 (using spatial-temporal covariates) and 3.21 (using spectral-temporal covariates), representing performance improvements of 33.46% and 41.41%, respectively. (2) The RF model constructed with the temporal-spatial-spectral covariates achieved satisfactory mapping accuracy (R2 = 0.85; RMSE = 0.80 mg kg−1; RPIQ = 4.09). (3) The soil Pb content in the western and northeastern regions was relatively high, while the remaining areas exhibited lower Pb levels, mainly due to industrial activities. (4) The mapping results of Pb obtained in this study were superior to other mapping methods, such as ordinary kriging, artificial neural networks, and multivariate linear regression methods. The soil PTE mapping technique employed in this study that combined TSS covariates with the RF provided an effective methodological approach for preventing soil pollution, controlling environmental risk, and improving soil management.

Multifunctional Drug Delivery System: Nanosponges.

In recent years, nanotechnology has been the focus of study for the cure of different diseases, among which nanosponge delivery system is one of a kind. Nano sponges are tiny, highly porous, three-dimensional nanostructures with a size range of 250nm-1µm in an amorphous or crystalline structure. Nanosponges usually act as an excipient or carrier of a drug in the different delivery systems. The type of polymers and cross-linkers, along with their concentration ratio, causes variation in nanosponges's dimension and encapsulation efficiency. Nanosponges have gained prominence in recent times due to their distinct ability to encapsulate both hydrophilic and lipophilic drugs within their internal cavity, thereby improving the solubility of drugs that have low water solubility. Virus-like size helps the nanosponges to circulate within the body without getting eliminated by the immune system until they stick to the targeted part of the body, which makes it the perfect candidate for a targeted drug delivery system and controlled delivery system as well because of its slow drug release property for a more extended period. Cyclodextrin-based nanosponges are the best choice for anticancer drug delivery as their small virus-like diameter helps them in passive targeting by enhancing the enhanced permeability and retention effect, allowing the anticancer drug to stay inside the tumour cell to show more significant therapeutic action on cancer, while for active targeting to the cancerous cell, nanosponges are attached with a ligand on it for receptor binding purpose. It can be used for drug delivery in many major diseases like brain-related diseases, diabetes, cancer, fungal, hypertension, etc., in different dosage forms, like oral, topical, hydrogel, parenteral, etc.

Morphometric analysis of cavitas glenoidalis with multidedector CT

The glenoid cavity is a sliced egg-shaped joint surface located on the lateral margin of the scapula to form the shoulder joint. Recognition of variations in shape and dimensions of the glenoid cavity is important for a better comprehension of joint-associated diseases, especially in total shoulder arthroplasty procedures. The aim of this study was to perform morphometric measurements on the glenoid cavity. Glenoid cavities of 391 individuals (197 males [50.4%], 194 females [49.6%]) were reviewed by using Multi-detector Computed Tomography. The maximum length and maximum width of glenoid cavities, as well as the width, depth and circumference at the notch level were measured, and the index value was calculated. The glenoid cavity shapes were typed as pear, inverted comma and oval type. Furthermore, the metric values that provide the best differentiation between genders were identified through ROC analysis. The pear glenoid cavity type was detected in 53.2%, inverted comma type was detected in 28.4%, and oval type was detected in 18.4% of cases. In all of our morphometric measurements, male values were higher than female values, and there was significant difference between them. Results of ROC analysis revealed significant measurements for the maximum length and maximum width measurements of the glenoid for gender determination. Morphometric information of the glenoid cavity can be useful in order to increase clinical success in case of Bankart lesion, rotator cuff disease, and osteochondral defect. Recognition of different shapes and dimensions of the glenoid cavity is essential for the design of the glenoid component, especially for total shoulder arthroplasty procedure. We believe that the data obtained in our study would be useful for prosthesis designers and orthopaedic surgeons.

The effect of IFRS convergence on risk disclosure: an investigation into the Indian accounting system

PurposeThis study aims to empirically investigate the effect of International Financial Reporting Standards (IFRS) convergence on corporate risk disclosure, with a particular emphasis on the quantity and coverage of risk information. The research also conducts economic benefit and cost analysis to investigate the economic implications that may arise from the transition to IFRS reporting.Design/methodology/approachA content analysis approach is used to measure two broader dimensions of risk disclosure, namely, risk disclosure quantity and risk topic coverage. Furthermore, using firm-fixed effect regression on a sample of 143 Indian-listed companies, this study investigates the variations in these risk disclosure dimensions before (2012–2016) and subsequent to (2017–2021) the convergence with IFRS.FindingsThe empirical results of this research demonstrate that IFRS convergence has led to a significant improvement in firms’ risk disclosure across several dimensions. Particularly, during the post-IFRS period, firms’ usage of risk-related words and sentences has considerably surged in MD&A, Notes and whole annual reports. In addition, upon IFRS convergence, firms’ risk descriptions have become more extensive and evenly distributed across risk topic categories. Moreover, the in-depth benefit and cost analysis revealed that firms reporting under IFRS benefit from decreased cost of equity capital, but they also incur a higher cost of audit fees.Originality/valueThis study contributes to the literature in two ways. First, this is the only study, to the best of the authors’ knowledge, to conduct a broader examination of the impact of mandatory IFRS convergence on corporate risk disclosure, with a major focus on quantity and coverage of risk information. Second, by conducting economic benefit and cost analysis, this study provides novel insights into the critical role of IFRS risk disclosures toward multiple economic outcomes.

Water flow simulation in a pelton turbine bucket with variable bucket dimensions using computational fluid dynamic

Today, especially among industrialized and developing nations, the usage of renewable energy sources is growing in popularity as a means of supplying energy needs. One of the renewable energy sources that is now being heavily exploited in Indonesia is the potential of water that may be used as a source of electrical energy by establishing a hydroelectric power plant (PLTA). One of the turbines that is frequently used in hydropower plants as a part that may transform water's kinetic energy into mechanical energy is the Pelton turbine. There is not a lot of literature on the design of Pelton turbine buckets. In order to determine the most ideal bucket dimensions that can be used with Pelton turbines, this study presents the conceptual and experimental components of the design and analysis of Pelton turbines based on bucket variations. AutoCAD was used to model the bucket and Pelton turbine, and ANSYS Fluent was used to perform the simulation so that results could be analyzed later. By comparing the simulated data of the blade variants 1 and 2, the ideal blade dimension variation is identified by the blade simulation of variant 1. The blade variation 2 with average torque of 5.859 Nm, average angular velocity of 40.822 rad/s, and average power of 242,970 watts is the most ideal blade. With an average torque of 4,735 Nm, an average corner speed of 40,404 rad/s, and an average power of 196,794 W, the blade 3 model has lower values