scholarly journals Optimization of small portable hoist load-capacity model

2017 ◽  
Author(s):  
Yuanheng Tang ◽  
Hao Yin ◽  
Zuotang Liang ◽  
Cheng Xu
Keyword(s):  
Load Capacity ◽  
Capacity Model

scholarly journals Improvement on Load-Induced Cascading Failure in Asymmetrical Interdependent Networks: Modeling and Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Haiyan Han ◽  
Rennong Yang
Keyword(s):  
Load Capacity ◽  
Small World ◽  
Cascading Failure ◽  
Modeling And Analysis ◽  
Interdependent Networks ◽  
Interdependent Network ◽  
Capacity Model ◽  
Weight Structure ◽  
Edge Failure ◽  
Asymmetrical Model

Many real-world systems can be depicted as interdependent networks and they usually show an obvious property of asymmetry. Furthermore, node or edge failure can trigger load redistribution which leads to a cascade of failure in the whole network. In order to deeply investigate the load-induced cascading failure, firstly, an asymmetrical model of interdependent network consisting of a hierarchical weighted network and a WS small-world network is constructed. Secondly, an improved “load-capacity” model is applied for node failure and edge failure, respectively, followed by a series of simulations of cascading failure over networks in both interdependent and isolated statuses. The simulation results prove that the robustness in isolated network changes more promptly than that in the interdependent one. Network robustness is positively related to “capacity,” but negatively related to “load.” The hierarchical weight structure in the subnetwork leads to a “plateau” phenomenon in the progress of cascading failure.

scholarly journals Controllability Robustness Against Cascading Failure for Complex Logistics Networks Based on Nonlinear Load-Capacity Model

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 7993-8003 ◽  
Author(s):  
Yue Yang ◽  
Baofeng Sun ◽  
Shaohua Wang ◽  
Yongxing Li ◽  
Xiaoni Li
Keyword(s):  
Load Capacity ◽  
Cascading Failure ◽  
Nonlinear Load ◽  
Logistics Networks ◽  
Capacity Model

scholarly journals Body Composition Characteristics of a Load-Capacity Model: Age-Dependent and Sex-Specific Percentiles in 5- to 17-Year-Old Children

Obesity Facts ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 593-603
Author(s):  
Isabel Gätjens ◽  
Steffen Christian Ekkehard Schmidt ◽  
Sandra Plachta-Danielzik ◽  
Anja Bosy-Westphal ◽  
Manfred James Müller
Keyword(s):  
Body Composition ◽  
Children And Adolescents ◽  
Fat Mass ◽  
Reference Data ◽  
Load Capacity ◽  
Childhood And Adolescence ◽  
Overweight Children ◽  
Body Composition Assessment ◽  
Capacity Model ◽  
Age Dependent

<b><i>Introduction:</i></b> Body composition assessment is superior to the use of body mass index (BMI) to characterize the nutritional status in pediatric populations. For data interpretation, suitable reference data are needed; hence, we aimed to generate age-dependent and sex-specific body composition reference data in a larger population of children and adolescents in Germany. <b><i>Methods:</i></b> This is a cross-sectional study on a representative group of 15,392 5- to 17-year-old children and adolescents. Body composition was assessed by bioelectrical impedance analysis using a population-specific algorithm validated against air displacement plethysmography. Age- and sex-specific percentiles for BMI, fat mass index (FMI), fat-free mass index (FFMI), and a “load-capacity model” (characterized by the ratios of fat mass [FM]/ fatt-free mass [FFM] and FM/FFM<sup>2</sup>) were modeled using the LMS method. <b><i>Results:</i></b> BMI, FMI, FFMI, FM/FFM, and FM/FFM<sup>2</sup> curves showed similar shapes between boys and girls with steady increases in BMI, FMI, and FFMI, while FM/FFM<sup>2</sup>-centiles decreased during early childhood and adolescence. Sex differences were observed in FMI and FM/FFM percentiles with increases in FMI up to age 9 years followed by a steady decrease in FM/FFM during and after puberty with a fast-growing FFMI up to age 17 in boys. The prevalence of low FFM relative to FM reached more than 60% in overweight children and adolescents. <b><i>Conclusion:</i></b> These pediatric body composition reference data enable physicians and public health scientists to monitor body composition during growth and development and to interpret individual data. The data point out to an early risk of sarcopenia in overweight children and adolescents.

scholarly journals Bioinspired Mitigation Scheme for Cascading Failures in Farmland Wireless Sensor Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jun Wang ◽  
Zhuangzhuang Du ◽  
Xunyang Wang ◽  
Zhengkun He
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Load Capacity ◽  
Mitigation Strategies ◽  
Wireless Sensor ◽  
Cascading Failures ◽  
Spider Web ◽  
Positive Effects ◽  
Capacity Model ◽  
Node Failures

Existing mitigation strategies on wireless sensor networks (WSNs) against cascading failures cannot appropriately adapt the particular characteristics of farmland WSNs. Spider web provides a new reference for improving network invulnerability. In this study, a bionic network scheme is built based on symmetric analysis of a series of spider-web vibration transmission trials, which include networking methodology, communication rules, and load capacity model. The basic idea of this scheme is to apply the cascading-failure coping mechanism inspired by spider web into the construction and operation of farmland WSNs. We found that the link backup contributed by a topological structure and communication rules had positive effects on suppressing the spread of cascading failures. The study showed that the damages of cascading failures can be efficiently lowered by regulating the adjustment coefficient of the load capacity model. The difference between the inner-layer node failures and outer-layer node failures for network invulnerability was verified under deliberate attack circumstances. Based on these results, the proposed network scheme can be utilized to enhance the invulnerability performance of farmland WSNs.

Robustness and recovery mechanism under the interaction of dependent networks

2021 ◽  
pp. 1-8
Author(s):  
Zhiyang Gao ◽  
Yaqi Liu Feng Qi ◽  
Huaijin Chen
Keyword(s):  
Load Capacity ◽  
Urban Infrastructure ◽  
Propagation Characteristics ◽  
Matlab Simulation ◽  
Actual System ◽  
Simulation Experiments ◽  
Infrastructure Networks ◽  
Recovery Mechanism ◽  
Interdependent Network ◽  
Capacity Model

With the development of society and the progress of science and technology, the process of urban infrastructure construction is accelerating, various infrastructure networks are constantly improving, and the links between different infrastructure networks are getting closer. Compared with a single network, this kind of interdependent network is more complex, and the research results of the existing single network are difficult to explain the nature and phenomenon of this kind of network. This article mainly introduces the research on the robustness and recovery mechanism of interdependent networks. From the perspective of a complex network, this paper combines the interdependence between the networks in the actual system and the node load and builds an interdependent network model. On the basis of the load capacity model, an interdependent network error model is established. And through matlab simulation experiments, the fault propagation characteristics of dependent networks under three conditions and the reliability attack methods of dependent networks are studied. The experimental results in this article show that dependent networks show exceptional vulnerability under deliberate attack functions, while dependent networks show good robustness under random attack modes. In addition, increasing the network node tolerance coefficient can improve the robustness of the interdependent network. When the tolerance is increased from 1 to 10, the robustness of the dependent network is increased by 18%.

scholarly journals Further development of a numerical method for analyzing the load capacity of clinched joints in versatile process chains

2021 ◽  
Author(s):  
Christian Roman Bielak ◽  
Max Böhnke ◽  
Mathias Bobbert ◽  
Gerson Meschut
Keyword(s):  
Numerical Method ◽  
Process Model ◽  
Load Capacity ◽  
Geometrical Properties ◽  
Capacity Model ◽  
Process Chains ◽  
Wide Range ◽  
Metal Sheets ◽  
Further Development ◽  
Joining Process

In many branches of production, components using large number of joints are combined together to make complex structures. The use of mechanical joining techniques offers the possibility to join structures with a wide range of material/geometry configurations. Due to changing in material properties during the production of formed parts, the robustness of the joint must be guaranteed. In this regard, a numerical method has been developed to predict the geometrical properties of the joint as a function of pre-straining of the metal sheets. In this way, the material combination and the joining tools are to be considered. The resulting metamodels were used to estimate the robustness of the joining process. In this study, the method is extended by a numerical load capacity model, which is generated from the joining process model using an automatic algorithm. The simulation model used for predicting the load capacity is validated by experiments. It is shown that the resulting automatic method is able to completely map a process chain and to predict the load capacity of the mechanical joints under consideration of the pre-strain. Furthermore, the correlation between the pre-strain and the load capacity is presented.

scholarly journals Body composition indices of a load–capacity model: gender- and BMI-specific reference curves

2014 ◽  
Vol 18 (7) ◽  
pp. 1245-1254 ◽  
Author(s):  
Mario Siervo ◽  
Carla M Prado ◽  
Emily Mire ◽  
Stephanie Broyles ◽  
Jonathan CK Wells ◽  
...  
Keyword(s):  
Body Composition ◽  
Muscle Mass ◽  
Risk Prediction ◽  
Fat Mass ◽  
Disease Risk ◽  
Load Capacity ◽  
Specific Reference ◽  
Capacity Model ◽  
Reference Curves ◽  
Obese Subjects

AbstractObjectiveFat mass (FM) and fat-free mass (FFM) are frequently measured to define body composition phenotypes. The load–capacity model integrates the effects of both FM and FFM to improve disease-risk prediction. We aimed to derive age-, gender- and BMI-specific reference curves of load–capacity model indices in an adult population (≥18 years).DesignCross-sectional study. Dual-energy X-ray absorptiometry was used to measure FM, FFM, appendicular skeletal muscle mass (ASM) and truncal fat mass (TrFM). Two metabolic load–capacity indices were calculated: ratio of FM (kg) to FFM (kg) and ratio of TrFM (kg) to ASM (kg). Age-standardised reference curves, stratified by gender and BMI (<25·0 kg/m2, 25·0–29·9 kg/m2, ≥30·0 kg/m2), were constructed using an LMS approach. Percentiles of the reference curves were 5th, 15th, 25th, 50th, 75th, 85th and 95th.SettingSecondary analysis of data from the 1999–2004 National Health and Nutrition Examination Survey (NHANES).SubjectsThe population included 6580 females and 6656 males.ResultsThe unweighted proportions of obesity in males and females were 25·5 % and 34·7 %, respectively. The average values of both FM:FFM and TrFM:ASM were greater in female and obese subjects. Gender and BMI influenced the shape of the association of age with FM:FFM and TrFM:ASM, as a curvilinear relationship was observed in female and obese subjects. Menopause appeared to modify the steepness of the reference curves of both indices.ConclusionsThis is a novel risk-stratification approach integrating the effects of high adiposity and low muscle mass which may be particularly useful to identify cases of sarcopenic obesity and improve disease-risk prediction.

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