Lift Ratio Research Articles

Wireless driven and self-sensing flexible gripper based on piezoelectric elastomer/high-entropy alloy magnetoelectric composite

The mechanical gripper shows significant importance as an alternative to manual work, but presents certain limitations in its gas or electric power with complex wire connection, presents limited available area and loud working noise, and lacks sensing function for feedback to the environment. In the present work, a novel magnetically driven and self-sensing flexible gripper was prepared based on piezoelectric elastomer and high-entropy alloy composite. The high-entropy alloy is prepared as FeCoNi(AlGa)0.5 to realize high permeability, while the piezoelectric elastomer is synthesized with superior elasticity and low modulus. The incorporation of FeCoNi(AlGa)0.5 into the piezoelectric elastomer exhibits high flexibility, magnetostriction performances and piezoelectric responses, reaching maximum strain of 1534.5 %, maximum magnetostrictive coefficient of 320 ppm and maximum piezoelectric response of 0.28 V/N. Meanwhile, the flexible gripper achieves synchronous wireless driven gripping function with a maximum lifting ratio to dead load over 41.38, and self-sensing function of target physical size with accuracy over 95 %. The flexible gripper shows maximum work power as low as 5 W. Thus, the magnetically driven and self-sensing flexible gripper shows great potential in intelligent industrial equipment.

Flow physics of a subcritical carbon dioxide jet in a multiphase ejector

Existing literature on ejectors, different researchers utilized different turbulence models by their choice, neither analyzing the physics of turbulence nor providing any sufficient optical diagnostics of the flow field. In this article, the physics captured by the Unsteady Reynolds Averaged Navier–Stokes (URANS) and Large Eddy Simulation (LES) are compared based on well-posed boundary conditions obtained experimentally from a carbon dioxide (CO2) vapor compression cycle with an error ≤2.5%. The experimental results utilized for this study are at Reynold’s number (Re) 1.2e5 at the high-pressure inlet (motive flow) maintaining CO2 in subcritical state. The low-pressure inlet (suction flow) is maintained at Re = 9.8e4 with CO2 in vapor state, providing a pressure lift ratio of 1.2 at the diffuser outlet. Comparison of flow topologies with different URANS models reveals that only standard, Shear Stress Transport (SST) k−ω, and Reynold’s Stress Model-Shear Stress Gradient (RSM-SSG) are the suitable URANS models capturing a linearly increasing anisotropy tensor component with increasing strain in the flow. LES also predicted the similar physics. However, standard k−ω overpredicted the suction pressure beyond the acceptable uncertainty limits, which made it inapplicable. For the first time, a spatio-temporal representation of the flow topology with LES revealed the actual jet morphology of a CO2 ejector. Specifically, finger-like structures are key features to entrain more surrounding warm fluid into the colder dense core fluid at the cost of destabilizing and breaking up the jet by stretching the streamwise vortices and obstructing the increase in pressure-lift ratio.

Product Layout Analysis Based on Consumer Purchasing Patterns Using Apriori Algorithm

In every self-service store, it is certain to have a sales transaction data, where the data will continue to grow every day. But in self-service stores the data is only a record of sales at the store. Whereas transaction data can be used as information on how consumer purchasing patterns when shopping at the store, but not all supermarkets know this. So this research aims to find information on these purchasing patterns, where to do this research using the apriori algorithm which is part of the association technique which is also part of data mining, where in its application it will calculate the support value, confindence value and will be tested using the lift ratio. And after the calculation is carried out, optimization will be carried out using the high utility itemset mining variable which will calculate the highest profit value on the product, so that based on the calculation, the final result is obtained with a support value of 85%, a confidence value of 86%, a lift ratio test of 1.01 and the high utility gets the highest result of Rp. 567,000.

Association Relationship Analysis in Finding Sales of Goods With Apriori Algorithm

Technology can be designed to help human life from all aspects ranging from agriculture, health science, industry and daily life. Toko Intan, a business engaged in the sale of basic and daily necessities. Every day, Toko Intan records every sales transaction in an archive stored in Microsoft Excel, containing data on goods sold every day. The purpose of this research is to find out what items are bought simultaneously by consumers to manage inventory, with the data mining method used in this research is the Association Rules method. Association Rules is one of the data mining techniques from the a priori algorithm which functions to find a combination pattern of an item. Tests carried out to process data in this study using the RapidMiner application, from tests carried out with the specified parameters, namely minimum support 30% and minimum confidence 65%, resulted in a lift ratio validation rule of 1.206. Personal Care Biscuits with 30.8% support and 90.9% confidence with a validation lift ratio of 1.206. Sales transaction data analysis can be applied well, and is able to generate a new association rule from the sales transaction dataset. With this research, it is hoped that it can provide information to the owner of the Intan store in providing the stock of goods needed by consumers and to find out the combination of item sets from the sales transaction dataset.

Comprehensive performance evaluation on a transcritical CO2 ejector-expansion heat pump system

In order to reduce irreversible loss and recover expansion work for improving automotive thermal system performance, this study experimentally evaluated the performances and characteristics of a CO2 ejector-expansion (EJE) heat pump system for electric vehicles under typical cooling and heating operating modes, examined the adaptability of the EJE system with a fixed-dimension ejector, and compared the EJE system with the basic-regenerative (REG) and vapor-injection (INJ) systems in the − 30 °C to 50 °C range. The results show that the increasing electronic expansion valve (EXV) opening leads to an increasing entrainment ratio and a decreasing lift ratio in both two modes. The maximum COP is 2.00 at 35 °C/27 °C (out-cabin/in-cabin air temperature) and 1.85 at 0 °C/20 °C. The COP improvement reaches a maximum of 21.6 % and 31.0 % at the ejector design temperature of 45 °C, compared to the REG and INJ systems, respectively. However, the heating performance of the ejector designed at a high temperature significantly decreases as the ambient temperature goes down. At − 30 °C/20 °C, the EJE system performs worse with a COP degradation of 6.1 % compared to the REG system.

Development and performance evaluation of a high solar contribution resorption-compression cascade heat pump for cold climates

Absorption-resorption heat pumps (ARHPs) have great potential in utilizing low-temperature solar heat for efficient winter heating, but are limited by their weak adaptability to cold climates relative to absorption heat pumps (AHPs) and vapor compression heat pumps (VCHPs). In this work, a resorption-compression cascade system consisting of ARHP and VCHP subsystems is proposed and investigated, with the goal of achieving efficient winter heating with improved solar contribution in cold climates. Thermodynamic models of the two subsystems and of the whole cascade system are developed for system feasibility verification and performance evaluations. Feasible operation temperature and pressure conditions are identified in terms of internal subsystem matching. Based on these operation conditions, the primary energy ratio (PER) – which is a key performance evaluation index – is investigated over a range of solar fractions (f). The results show that for cases without solar contribution, the PER can be generally >0.95 under feasible operating conditions. In addition, the primary energy saving ratio (PESR) and heating capacity lift ratio (εlift), as well as the heat source temperature (Th) and ambient temperature (Tamb) restriction, are all investigated and compared to those of other, competing heating systems. The results show that the proposed system can reduce the Th demand to 69 °C (with a minimum Tamb of −21 °C) and extend the operational Tamb to −31 °C (with a minimum Th of 90 °C), while importantly achieving PESR > 0.20 and εlift > 20 % under the above extreme conditions. Moreover, when integrating the system with solar heat with f > 43 %, the proposed solar-assisted system has a clear PER advantage over an equivalent VCHP system in the Tamb range from −31 °C to 10 °C, highlighting the possibility of achieving higher solar contribution in cold climates.

Optimal blade design of a spherical water turbine

The use of in-pipe water turbines for small-scale energy harvesting from pipe networks is starting to gain popularity. However, limited research have looked into whether adding helical blade turbines would be feasible with a spherical lift base in a water supply network. Three Naca airfoil (0012, 2412, 4412) were used to study the ratio of lift to drag force for each wing, Benefit from Qblade and ANSYS CFX software, and choosing the wing that has the highest ratio. The study investigates the feasibility of improving the design of spherical turbine blades by increasing the ratio of lift to drag. The results show that the Naca airfoil 4412 had the highest lift-to-drag force ratio, which was equal to 19.95. Through the improvement process for the Naca 4412 airfoil, the increase was made by 13.34 %, and the lift-to-drag ratio became 22.61. The study also dealt with the design of a turbine through the improved airfoil. 230 mm. It has the engineering characteristics of the number of helical blades, 5, The measurement of the blade's length chord 15 % of the turbine diameter, and the Angle of Attack, 9.5°

Enhancing the Versatility and Performance of Soft Robotic Grippers, Hands, and Crawling Robots Through Three-Dimensional-Printed Multifunctional Buckling Joints.

Soft robotic grippers and hands offer adaptability, lightweight construction, and enhanced safety in human-robot interactions. In this study, we introduce vacuum-actuated soft robotic finger joints to overcome their limitations in stiffness, response, and load-carrying capability. Our design-optimized through parametric design and three-dimensional (3D) printing-achieves high stiffness using vacuum pressure and a buckling mechanism for large bending angles (>90°) and rapid response times (0.24 s). We develop a theoretical model and nonlinear finite-element simulations to validate the experimental results and provide valuable insights into the underlying mechanics and visualization of the deformation and stress field. We showcase versatile applications of the buckling joints: a three-finger gripper with a large lifting ratio (∼96), a five-finger robotic hand capable of replicating human gestures and adeptly grasping objects of various characteristics in static and dynamic scenarios, and a planar-crawling robot carrying loads 30 times its weight at 0.89 body length per second (BL/s). In addition, a jellyfish-inspired robot crawls in circular pipes at 0.47 BL/s. By enhancing soft robotic grippers' functionality and performance, our study expands their applications and paves the way for innovation through 3D-printed multifunctional buckling joints.

Numerical investigation and parametric study of NACA 0009 airfoil with bumps inspired by mako-shark skin denticles

In the current research, a numerical study of 53 airfoils inspired by the surface scales of the mako-shark skin based on NACA0009 airfoil has been performed. The airflow simulations were performed in different angles of attack from 4° to 11° and the validations are presented in two stages compared with two different studies. The diagrams of [Formula: see text] parameter, shear stress, pressure coefficient, and also the contours of velocity and streamlines are reported. The results of the lift, drag, and diagram of lift to drag ratios have been presented and analyzed for different geometries and angles of attack. The results show that by creating bumps’ pattern taken from the shark skin mounted over the suction side of the airfoils the ratio of lift to drag increases. For example up to 28% increment of average of Cl/Cd in the above mentioned range of angles of attack can be obtained utilizing just one bump with 0.7 mm thickness (0.7% of chord length) mounted at 23% of the chord on suction side.

Influence of the suspension gap on the wake characteristics of a 600 km/h superconducting maglev train

Although the suspension gap between a maglev train and its track is narrow, it has a significant impact on the aerodynamic performance of the train. This study investigated the effect of the suspension gap on the wake flow of a superconducting maglev train traveling at a speed of 600 km/h by comparing the aerodynamics and flow field structure of a tail car (TC) with suspension gaps of 8, 10, 12, and 14 cm. The results showed that with increasing suspension gap, the vortex structures in the wake region move closer to the TC, the airflow from the suspension gap inhibits the high-pressure region of the wake, and the pressure and velocity fluctuations significantly increase near the nose tip of the TC. Moreover, the suspension gap was found to have a significant impact on lift and almost no effect on drag. Increasing the suspension gap leads to a balance in the lift between the head car (HC) and the TC; as the gap continues to increase, the lift ratio of the HC and TC rapidly decreases.

Penerapan Data Mining Algoritma Apriori untuk Menemukan Pola Hubungan Status Gizi Balita

Malnutrition of toddlers can cause severely health problems, growth retardation, and decreased intelligence. Therefore, it is important to know the pattern of the relationship between the nutritional status of toddlers, especially against the condition of malnutrition to get information about the possible risk of nutritional coexistence problems. The purpose of this research is to apply data mining using the apriori algorithm in finding patterns of relationships betweennutritional status and to produce an accuracy level of association rules based on the value of support, confidence, and validation with the lift ratio. The results of this study are expected to generate information that can help prevent and treat malnutrition, as well as appropriate nutrition interventions. Analysis and implementation of data using the a priori algorithm method. Manual calculations are carried out using Microsoft Excell and accurate calculations with python programming. Data on the nutritional status of children under five, especially undernourished conditions will be processed to find patterns of association relationships. Determined the minimum support value of 0.1 or 10% and the minimum confidence of 0.5 or 50%. The research produces association rules in the form of association relationship patterns of nutritional status specifically malnutrition conditions (Underweight?Stunting ) with a support of 0.25 or 25% and confidence 0.57 or 57%. The rules have met the minimum support and minimum confidence values and have been validated by the lift ratio with a value > 1.

ATURAN ASOSIASI UNTUK REKOMENDASI STRATEGI PEMASARAN PRODUK KERAJINAN MENGGUNAKAN FREQUENT PATTERN GROWTH

Besides selling equipments and spareparts for two-wheeled vehicles, NTN Racing Store also sells handicraft products made from water hyacinth. Lately, NTN Racing Store facing challenges in selling its products, as evidence by the unpredictable monthly revenue. The reason is insufficiency of customer purchasing patterns understanding. The impacts are the declining of the marketing and sales performance for creative water hyacinth handicrafts products since 2020. The main purpose of this studi is to identify which products are purchase together by customers in one transaction when shopping for water hyacinth products. Market Basket Analysis is a rule that determines associations between various attributes and is a key application in the retail industry. This method is use to analyze past consumer purchasing behavior to determine items that are frequently purchase together. Its purpose is to uncover relationships between products purchased by customers in a single transaction. On the other hand, Frequent Pattern Growth is an alternative algorithm use to identify the most frequently occurring datasets within a collection of data. The testing results of 435 transactional data points from NTN Racing Store, using 1% minimum support value and 25% minimum confidence value, resulting four association rules within lift ratios above 1 which indicates significant relationships among itemsets. From these evaluation results, customer purchasing patterns can be identifying trough the association analysis rules. This information can assist the store owner in determining bundling packages to sell and to devise store sales strategies.

Product Bundling Strategy for Office Supplies Retailer through Association Rules Mining: Comparative Study of Apriori and ECLAT Algorithms

Our study aims to develop an effective bundled product promotion strategy for the office supply store to boost sales. The primary challenge is comprehending which product combinations align with customer preferences and cater to their needs. We leverage the Apriori and ECLAT algorithms for consistent rule generation, revealing robust associations between product purchases. Notably, a strong positive correlation rule emerges at a confidence level of 0.8, while at 0.9, no results are found. The identical rules derived from both algorithms signify their reliability. The shop owner employs two rules for bundled products based on a minimum Lift Ratio of 1.96. The first bundle focuses on 70gsm natural paper in Folio and Quarto sizes, capitalizing on their popularity, even though customers may prefer one size. The second bundle emphasizes notebooks, often bought together but in smaller quantities than paper products, reflecting diverse customer needs and behaviors.

Penerapan Data Mining Dalam Menganalisis Pola Belanja Konsumen Menggunakan Market Basket Analysis

Currently, almost every activity is related to data. in the business sector, daily sales transaction data stored in the database system will always increase and accumulate. The existing data is only used as an archive by the shop owner so that it has an impact on sales strategies that are not implemented well, even though the existing data can be processed into information to determine the layout of goods so that it has an impact on increasing the occurrence of impulse buying, increasing or maintaining turnover, and minimizing product waste. accumulate until it expires which can be detrimental to the shop.The aim of this research is to find consumer shopping patterns using Marker Basket Analysis. This research method is called market basket analysis or also called association rules, which is a data mining technique for finding patterns that often appear simultaneously in transaction data, so that it can be used as a method for finding information about what kinds of goods are frequently used. purchased by consumers simultaneously. The results of this research, based on data analysis using the Rapidminer application, found 25 associative relationships or rules with a lift ratio value of more than 1, these rules become a reference in determining the layout of goods. Providing recommendations for layout changes aims to make it easier for consumers to shop, increase the possibility of impulse buying by consumers, and maximize product display, thereby reducing the accumulation of goods in the Purnama Store Warehouse.

Enhancing Marketing Strategies for Office Stationery Stores Using Equivalence Class Transformation Algorithms

Office stationery stores facilitate operations for offices, schools, and businesses. However, the store owner must overcome the challenge of selecting the right products for promotion. This research aims to tackle this issue by comparing the performance of the Equivalence Class Transformation algorithms in discovering association rules using Support, confidence, and lift ratios. The findings reveal that the algorithm generates association rules based on Support, confidence, and lift values. Ten critical rules are identified, shedding light on algorithm effectiveness. Ultimately, this study underscores the significance of refining marketing approaches for brick-and-mortar stationery businesses and the value of data-driven methods in aiding decision-making. In the early promotion catalog phase, priority is assigned to rules with solid agreement by the Shop Owner, guiding the selection of featured items based on robust product associations.

Experimental investigation on the drying characteristics in a solar assisted ejector enhanced heat pump dryer system

A new designed solar assisted ejector enhanced heat pump dryer system (SE-HPD) with closed-loop drying chamber using the R134A refrigerant has been experimentally investigated. In the SE-HPD, a hot water cycle system has been designed to simulate the solar collector. The dynamic drying characteristic of SE-HPD and the conventional heat pump dryer system (CHPD) were compared. Further, various drying characteristic parameters and the ejector performances of the new system under different solar radiation intensities, valve opening (OP) of electronic expansion valves and by-pass return air ratios (BR) were studied. The experimental results revealed that the exergy efficiency and moisture extraction rate (MER) of SE-HPD were always better than those of the CHPD. The exergy efficiency and MER of SE-HPD were improved by 28.7% and 54.3% compared with those of CHPD under the given operating condition. It was found that higher solar radiation intensity could significantly improve the pressure lift ratio of the ejector and contributed to the higher heating performance of SE-HPD. The optimum OP and BR to obtain the maximum MER for SE-HPD were also found to be 50 % and 70 %, respectively. The performance advantages of the proposed system have been verified through this experimental research.

Analysis of the Apriori Algorithm for Enhancing Retail Product Staple Sales Recommendations

Products are fundamental commodities in the market that cater to various consumer needs and desires. This research employs the Apriori algorithm to generate product recommendations based on the analysis of high-demand patterns arising from product sales and association patterns. Specifically, we focus on identifying elevated sales in categories such as Bulk Products, Biscuits/Snacks, Drinks, Milk/Coffee/Tea, and Sauces & Spices during specific time intervals. The model's evaluation and validation entail measuring the Lift Ratio value, a key metric. In our assessment using the RapidMiner Studio application, we find that the Lift Ratio value equals 1. Consequently, our model asserts that combinations with a Lift Ratio value greater than or equal to 1 are deemed valid and beneficial.

Product Stock Supply Analysis System with FP Growth Algorithm

This study explores the application of Data Mining in deciphering consumer purchasing patterns at Tani Heritage Shop, a retailer specializing in agricultural products. Facing the challenge of managing a high volume of daily sales transactions, the shop often encounters difficulties in tracking which products are frequently purchased together. This lack of insight leads to a critical issue: popular products running out of stock unexpectedly. To address this, the research focuses on developing a product stock supply analysis system, utilizing the FP Growth Algorithm. The FP Growth Algorithm, a powerful tool in Data Mining, is employed to analyze sales transaction data and identify consumer purchasing trends, particularly products bought simultaneously. This approach is designed to provide insights into optimal stocking strategies, ensuring the availability of in-demand products. The research methodology involves applying the FP Growth Algorithm to model the product stock supply system, using specific sales data attributes. The results of this study are significant. By setting parameters such as a minimum support value of 30%, a confidence value of 70%, and targeting the highest lift ratio value of 3.67, the research successfully derives several key association rules from the FP Growth algorithm. These rules are instrumental in optimizing the product stock supply analysis system.

Associative Classification with Classification Based Association (CBA) Algorithm on Transaction Data with Rshiny

Data mining can be used for businesses with large amounts of data. One of the data mining techniques is Associative Classification. It is a new strategy in data processing that combines association and classification techniques to build a classification model. This research used an associative classification technique on sales transaction data of Frozen Food Stores, which had sales transaction data on their business activities. It would be used in sales strategies to find items often purchased by class customers, namely, members and general. This research aimed to classify based on association rules using the CBA (Classification based Association) algorithm on sales transaction data. The application used the R programming language that business owners could use. The results of the rules obtained from the trial had the value of support, confidence, coverage, and lift ratio, which were the best value levels of a rule. The results of the rules that had the highest lift ratio value from all the data that have been inputted can be used as a reference to be implemented in sales strategies in knowing consumer needs.

Preliminary assessment of the NACA0021 trailing edge wedge for wind turbine application

The airfoil blade is the primary component of a wind turbine, and its aerodynamic properties play a crucial role in determining the energy conversion efficiency of these blades. Many researchers have proposed different airfoil modifications intending to enhance the aerodynamic characteristics and limit the unsteady interaction with the atmospheric boundary layer. This study evaluates the benefits of mounting wedge tails (WTs) on the trailing edge of an airfoil. The aerodynamic characteristics of a 2-D, steady-state NACA 0021 airfoil featuring the wedge tails (WT) and fish wedge tails (FWT) were studied computationally by employing the shear stress transport (SST) k-ω turbulence model. Different WT and FWT configurations were studied at various wedge length (L) to wedge height (H) ratios, L/H, at the airfoil's trailing edge. The effects of different L/H ratios, including L/H > 1, L/H = 1, and L/H < 1, were considered in the present study to determine the optimal configuration to achieve the maximum glide ratio, CL/CD at the Reynolds number of 180,000. The findings indicate that the performance of the NACA 0021 airfoil was notably affected by the height of the tail; however, the length had only a minor impact when L/H was less than 1. The mounted FWT resulted in significant enhancements to both the lift and glide ratio of the airfoil. Specifically, the lift ratio experienced an increase of over 41 % compared to the clean airfoil, while the glide ratio increased by more than 31 %. These improvements were observed at an ideal height and length of 2.5 % and 1 % of the airfoil, respectively. Moreover, the mounted FWT performed better than the Gurney flap using the same configurations.