scholarly journals An Automatic and Simplified Approach to Muscle Path Modelling

2021 ◽  
Author(s):  
Claire Livet ◽  
Theo Rouvier ◽  
Georges Dumont ◽  
Charles Pontonnier
Keyword(s):  
Input Data ◽  
Musculoskeletal Model ◽  
Computational Time ◽  
Computationally Efficient ◽  
Simplified Approach ◽  
Moment Arms ◽  
Path Modelling ◽  
Optimization Routine ◽  
Musculoskeletal Simulations ◽  
Relative Root

Abstract The current paper aims at proposing an automatic method to design and adjust simplified muscle paths of a musculoskeletal model. These muscle paths are composed of a limited set of via points and an optimization routine is developed to place these via points on the model in order to fit moment arms and musculotendon lengths input data. The method has been applied to a forearm musculoskeletal model extracted from the literature, using theoretical input data as an example. Results showed that for $75\%$ of the muscle set, the relative root mean square error was under $29.23\%$ for moment arms and of $1.09\%$ for musculotendon lengths with regard to the input data. These results confirm the ability of the method to automatically generate computationally efficient muscle paths for musculoskeletal simulations. Using only via points lowers computational expense compared to paths exhibiting wrapping objects. A proper balance between computational time and anatomical realism should be found to help those models being interpreted by practitioners.

scholarly journals A computationally efficient hybrid 2D–3D subwoofer model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ahmad H. Bokhari ◽  
Martin Berggren ◽  
Daniel Noreland ◽  
Eddie Wadbro
Keyword(s):  
Hybrid Model ◽  
3D Model ◽  
Element Model ◽  
Acoustic Properties ◽  
Computational Time ◽  
Average Response ◽  
Frequency Range ◽  
Computationally Efficient ◽  
Lumped Element ◽  
Lumped Element Model

AbstractA subwoofer generates the lowest frequency range in loudspeaker systems. Subwoofers are used in audio systems for live concerts, movie theatres, home theatres, gaming consoles, cars, etc. During the last decades, numerical simulations have emerged as a cost- and time-efficient complement to traditional experiments in the design process of different products. The aim of this study is to reduce the computational time of simulating the average response for a given subwoofer design. To this end, we propose a hybrid 2D–3D model that reduces the computational time significantly compared to a full 3D model. The hybrid model describes the interaction between different subwoofer components as interacting modules whose acoustic properties can partly be pre-computed. This allows us to efficiently compute the performance of different subwoofer design layouts. The results of the hybrid model are validated against both a lumped element model and a full 3D model over a frequency band of interest. The hybrid model is found to be both accurate and computationally efficient.

scholarly journals IOT and XBee triggered based adaptive intrusion detection using geophone and quick response by UAV

2018 ◽  
Vol 7 (2.6) ◽  
pp. 12
Author(s):  
Rohit Samkaria ◽  
Rajesh Singh ◽  
Anita Gehlot ◽  
Rupendra Pachauri ◽  
Amardeep Kumar ◽  
...  
Keyword(s):  
Present Method ◽  
Input Data ◽  
Sensor Node ◽  
Quick Response ◽  
Statistical Measure ◽  
Control Room ◽  
Computationally Efficient ◽  
Remote Areas ◽  
Additional Layer ◽  
Security Application

Monitoring of remote areas needs a lot of man power, in this contrast an important additional layer to perimeter protection for home land security application is Seismic footstep detection based systems. This paper mainly concerns with the detection of any human intrusion by the detection of the footsteps from a person from few tens of meters away using an underground seismic sensor, Geophone and placing the intrusion data over the cloud by using IOT. Presence of footstep is indicated by the impulses in the geophone signal. Kurtosis, a statistical measure is used to identify the impulses, can apply for a short duration of time for which a footstep exists. Present method is less complex and computationally efficient, all the input data stored in memory, which are read through microcontroller through ADC and stored in memory is subjected to kurtosis using microcontroller. Many such nodes are connected in a topology to build a Sensor Network. Indication of the intrusion will occur when microcontroller of sensor node calculates higher kurtosis value and will send this value to control room and data is uploaded to cloud at the same time.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2018 ◽  
Author(s):  
Feng Jie Zheng ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Pressure Fluctuation ◽  
Large Scale ◽  
Three Dimensional ◽  
Industrial Process ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial process. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operation such as rapid valve opening/closing. To investigate the pressure especially the pressure fluctuation in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled by a zero-dimensional virtual point, the pipe is modeled by a one-dimensional MOC, and the valve is modeled by a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted, in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve are obtained. The results show that the proposed model is in good agreement with the full CFD model in both large-scale and small-scale spaces. Moreover, the proposed model is more computationally efficient than the CFD model, which provides a feasibility in the analysis of complex RPV system within an affordable computational time.

scholarly journals lassosum2: an updated version complementing LDpred2

2021 ◽  
Author(s):  
Florian Privé ◽  
Bjarni J. Vilhjálmsson ◽  
Timothy S. H. Mak
Keyword(s):  
Sample Size ◽  
Input Data ◽  
R Package ◽  
Computational Time ◽  
Polygenic Score ◽  
Score Method

AbstractWe present lassosum2, a new version of the polygenic score method lassosum, which we re-implement in R package bigsnpr. This new version uses the exact same input data as LDpred2 and is also very fast, which means that it can be run with almost no extra coding nor computational time when already running LDpred2. It can also be more robust than LDpred2, e.g. in the case of a large GWAS sample size misspecification. Therefore, lassosum2 is complementary to LDpred2.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Feng Jie Zheng ◽  
Chao Yong Zong ◽  
William Dempster ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Large Scale ◽  
Pressure Fluctuations ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Dimensional System ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial processes. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operations such as rapid valve opening or closing. To investigate the pressure response, with particular interest in the pressure fluctuations in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled as a zero-dimensional virtual point, the pipe is modeled as a one-dimensional system using the MOC, and the valve is modeled using a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve is obtained. The results show that the proposed model is in good agreement when compared with a high fidelity CFD model used to represent both large-scale and small-scale spaces. As expected, the proposed model is significantly more computationally efficient than the CFD model. This demonstrates the feasibility of analyzing complex RPV systems within an affordable computational time.

Efficient Robust Design Optimization of a Stacker–Reclaimer Structure Under Uncertainty

2019 ◽  
Vol 26 (02) ◽  
pp. 1950009
Author(s):  
Soumya Bhattacharjya ◽  
Mithun Sarkar ◽  
Gaurav Datta ◽  
Saibal Kumar Ghosh
Keyword(s):  
Design Optimization ◽  
Robust Design ◽  
Least Squares Method ◽  
Bulk Material ◽  
Robust Design Optimization ◽  
Computational Time ◽  
Computationally Efficient ◽  
Massive Structure ◽  
Accurate Design ◽  
Design Solutions

A stacker–reclaimer structure (SRS) is a massive structure used for bulk material exploration. Performance of SRS is sensitive to the effect of uncertainty which may lead to catastrophic failure consequences. Thus, in this paper a comparatively new robust design optimization (RDO) approach for design of SRS is explored. The involved parameter of SRS e.g., material loading, incrustation, normal digging, etc., may not have well-defined probability density functions and can be expressed as uncertain but bounded (UBB) type parameters. Hence, RDO is explored for probabilistic as well as UBB cases. Solution of such RDO problem in full simulation approach would require extensive computational time. Hence, response surface method (RSM) based metamodeling approach has been adopted here to alleviate computational burden. Also, as conventional least squares method (LSM) based RSM may be a source of error, this study adopts a comparatively new moving LSM (MLSM) based adaptive RSM in RDO. The RDO results depict that UBB type uncertainty is more critical than the probabilistic case. The proposed MLSM based RDO approach yields reasonably accurate design solutions in a computationally efficient way. The proposed MLSM based RDO approach yields design solutions which ensures safe performance of SRS even in the presence of uncertainty.

Ensemble of surrogates and cross-validation for rapid and accurate predictions using small data sets

2019 ◽  
Vol 33 (4) ◽  
pp. 484-501 ◽  
Author(s):  
Reza Alizadeh ◽  
Liangyue Jia ◽  
Anand Balu Nellippallil ◽  
Guoxin Wang ◽  
Jia Hao ◽  
...  
Keyword(s):  
Cross Validation ◽  
Weighted Average ◽  
Computational Time ◽  
Small Data ◽  
Data Sets ◽  
Computationally Efficient ◽  
Cross Validation Error ◽  
Rod Rolling ◽  
Ensemble Of Surrogates ◽  
Time Required

AbstractIn engineering design, surrogate models are often used instead of costly computer simulations. Typically, a single surrogate model is selected based on the previous experience. We observe, based on an analysis of the published literature, that fitting an ensemble of surrogates (EoS) based on cross-validation errors is more accurate but requires more computational time. In this paper, we propose a method to build an EoS that is both accurate and less computationally expensive. In the proposed method, the EoS is a weighted average surrogate of response surface models, kriging, and radial basis functions based on overall cross-validation error. We demonstrate that created EoS is accurate than individual surrogates even when fewer data points are used, so computationally efficient with relatively insensitive predictions. We demonstrate the use of an EoS using hot rod rolling as an example. Finally, we include a rule-based template which can be used for other problems with similar requirements, for example, the computational time, required accuracy, and the size of the data.

scholarly journals A 3D musculoskeletal model of the western lowland gorilla hind limb: moment arms and torque of the hip, knee and ankle

2017 ◽  
Vol 231 (4) ◽  
pp. 568-584 ◽  
Author(s):  
Colleen Goh ◽  
Mary L. Blanchard ◽  
Robin H. Crompton ◽  
Michael M. Gunther ◽  
Sophie Macaulay ◽  
...  
Keyword(s):  
Hind Limb ◽  
Musculoskeletal Model ◽  
Western Lowland Gorilla ◽  
Moment Arms

Incorporating large datasets of synthetic tropical cyclones with Global Tide and Surge Model (GTSM) for global assessment of extreme sea levels.

2020 ◽  
Author(s):  
Maria Chertova ◽  
Sanne Muis ◽  
Inti Pelupessy ◽  
Philip Ward
Keyword(s):  
Tropical Cyclones ◽  
Large Scale ◽  
Large Datasets ◽  
Water Levels ◽  
Computational Time ◽  
Potential Hazard ◽  
Computationally Efficient ◽  
Sea Levels ◽  
Starting Point ◽  
Extreme Sea Levels

<p>Coastal flooding due to tropical cyclones (TC) is one of the world’s most threatening hazards. The potential increase in the probability of these events in the future, due to climate change, necessitates the more accurate simulation of their potential hazard and resulting risks. This contribution is a step of a MOSAIC (MOdelling Sea level And Inundation for Cyclones) project that aims at developing and validating a computationally efficient, scalable, framework for large-scale flood risk assessment, combining cutting-edge disciplinary science and eScience technologies. As the first step, we develop a computationally efficient method for more accurately simulating current and future TC hazard and risk, by incorporating large datasets of tropical cyclones within the Global Tide and Surge Model (GTSM). The starting point is simulating the spatially explicit extreme sea levels for a large number of synthetic TCs. The difficulty lies in high computational time required for running GTSM models, as with duration of one simulation running on 24 cores of 5 days ( for 1yr). Until present each TC was simulated separately*, which is not feasible when modelling thousands of TC events. Here we present the development of an algorithm for the spatio-temporal optimization of the placing of TCs within GTSM in order to allow optimal use of the computational resources. This can be achieved because the region of influence of a particular TC in the model is limited in space and time (e.g. a TC making landfall in Florida will not materially affect water levels near New York).  This will enable running a large number of TCs in one simulation and will significantly reduce the required total computation time. We investigate a large range of parameters, such as distance between cyclones, time to the landfall, category of cyclone, and others, to optimize the distribution of TC within a single model run. We demonstrate a significant speedup relative to the sequential running of the cyclones within a single simulation.</p><p>*Muis, S., Verlaan, M., Winsemius, H. C., Aerts, J. C. J. H., & Ward, P. J. (2016). A global reanalysis of storm surge and extreme sea levels. Nature Communications, 7(7:11969), 1–11.</p>

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