scholarly journals Automated Multistep Parameter Identification of SPMSMs in Large-Scale Applications Using Cloud Computing Resources

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4699
Author(s):  
Elia Brescia ◽  
Donatello Costantino ◽  
Federico Marzo ◽  
Paolo Roberto Massenio ◽  
Giuseppe Leonardo Cascella ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Large Scale ◽  
Measurement Data ◽  
Research Area ◽  
Operating Conditions ◽  
Permanent Magnet Synchronous Machines ◽  
Identification Schemes ◽  
Human Interventions ◽  
Multistep Procedure ◽  
Parameter Identifications

Parameter identification of permanent magnet synchronous machines (PMSMs) represents a well-established research area. However, parameter estimation of multiple running machines in large-scale applications has not yet been investigated. In this context, a flexible and automated approach is required to minimize complexity, costs, and human interventions without requiring machine information. This paper proposes a novel identification strategy for surface PMSMs (SPMSMs), highly suitable for large-scale systems. A novel multistep approach using measurement data at different operating conditions of the SPMSM is proposed to perform the parameter identification without requiring signal injection, extra sensors, machine information, and human interventions. Thus, the proposed method overcomes numerous issues of the existing parameter identification schemes. An IoT/cloud architecture is designed to implement the proposed multistep procedure and massively perform SPMSM parameter identifications. Finally, hardware-in-the-loop results show the effectiveness of the proposed approach.

Soil/Tire Interaction Analysis Using FEM and FVM

2005 ◽  
Vol 33 (1) ◽  
pp. 38-62 ◽  
Author(s):  
S. Oida ◽  
E. Seta ◽  
H. Heguri ◽  
K. Kato
Keyword(s):  
Large Scale ◽  
Interaction Analysis ◽  
Yield Criterion ◽  
Surrounding Medium ◽  
Flow Analysis ◽  
Measurement Data ◽  
Traction Force ◽  
Elastoplastic Material ◽  
The Road ◽  
Soil Flow

Abstract Vehicles, such as an agricultural tractor, construction vehicle, mobile machinery, and 4-wheel drive vehicle, are often operated on unpaved ground. In many cases, the ground is deformable; therefore, the deformation should be taken into consideration in order to assess the off-the-road performance of a tire. Recent progress in computational mechanics enabled us to simulate the large scale coupling problem, in which the deformation of tire structure and of surrounding medium can be interactively considered. Using this technology, hydroplaning phenomena and tire traction on snow have been predicted. In this paper, the simulation methodology of tire/soil coupling problems is developed for pneumatic tires of arbitrary tread patterns. The Finite Element Method (FEM) and the Finite Volume Method (FVM) are used for structural and for soil-flow analysis, respectively. The soil is modeled as an elastoplastic material with a specified yield criterion and a nonlinear elasticity. The material constants are referred to measurement data, so that the cone penetration resistance and the shear resistance are represented. Finally, the traction force of the tire in a cultivated field is predicted, and a good correlation with experiments is obtained.

Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model

2019 ◽  
Author(s):  
Ryther Anderson ◽  
Achay Biong ◽  
Diego Gómez-Gualdrón
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Molecular Simulation ◽  
Large Scale ◽  
Learning Model ◽  
Operating Conditions ◽  
Small Subset ◽  
Screening Methods ◽  
Large Set ◽  
Metal Organic

<div>Tailoring the structure and chemistry of metal-organic frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), molecular simulation, such as grand canonical Monte Carlo (GCMC), has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent experiments to focus only on a small subset of the most promising MOFs. In many instances, however, even molecular simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede molecular simulation efforts. In this study, as a proof of concept, we trained a neural network as the first example of a machine learning model capable of predicting full adsorption isotherms of different molecules not included in the training of the model. To achieve this, we trained our neural network only on alchemical species, represented only by their geometry and force field parameters, and used this neural network to predict the loadings of real adsorbates. We focused on predicting room temperature adsorption of small (one- and two-atom) molecules relevant to chemical separations. Namely, argon, krypton, xenon, methane, ethane, and nitrogen. However, we also observed surprisingly promising predictions for more complex molecules, whose properties are outside the range spanned by the alchemical adsorbates. Prediction accuracies suitable for large-scale screening were achieved using simple MOF (e.g. geometric properties and chemical moieties), and adsorbate (e.g. forcefield parameters and geometry) descriptors. Our results illustrate a new philosophy of training that opens the path towards development of machine learning models that can predict the adsorption loading of any new adsorbate at any new operating conditions in any new MOF.</div>

scholarly journals Inverse Infiltration Modeling of Dike Covers Made of Dredged Material Using PEST and AMALGAM

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 41
Author(s):  
Tim Jurisch ◽  
Stefan Cantré ◽  
Fokke Saathoff
Keyword(s):  
Large Scale ◽  
Measurement Data ◽  
Fine Grained ◽  
Dredged Materials ◽  
Measurement Results ◽  
Large Scale Field ◽  
Eigenvalue Ratio ◽  
Ill Posed ◽  
Materials Used ◽  
Installation Technology

A variety of studies recently proved the applicability of different dried, fine-grained dredged materials as replacement material for erosion-resistant sea dike covers. In Rostock, Germany, a large-scale field experiment was conducted, in which different dredged materials were tested with regard to installation technology, stability, turf development, infiltration, and erosion resistance. The infiltration experiments to study the development of a seepage line in the dike body showed unexpected measurement results. Due to the high complexity of the problem, standard geo-hydraulic models proved to be unable to analyze these results. Therefore, different methods of inverse infiltration modeling were applied, such as the parameter estimation tool (PEST) and the AMALGAM algorithm. In the paper, the two approaches are compared and discussed. A sensitivity analysis proved the presumption of a non-linear model behavior for the infiltration problem and the Eigenvalue ratio indicates that the dike infiltration is an ill-posed problem. Although this complicates the inverse modeling (e.g., termination in local minima), parameter sets close to an optimum were found with both the PEST and the AMALGAM algorithms. Together with the field measurement data, this information supports the rating of the effective material properties of the applied dredged materials used as dike cover material.

scholarly journals Heat Transfer in Rotating Serpentine Passages With Trips Normal to the Flow

1992 ◽  
Vol 114 (4) ◽  
pp. 847-857 ◽  
Author(s):  
J. H. Wagner ◽  
B. V. Johnson ◽  
R. A. Graziani ◽  
F. C. Yeh
Keyword(s):  
Heat Transfer ◽  
Turbine Blade ◽  
Large Scale ◽  
Flow Direction ◽  
Operating Conditions ◽  
Transfer Model ◽  
Transfer Coefficients ◽  
Flow Equations ◽  
Turbine Blade Cooling ◽  
Heat Transfer Coefficients

Experiments were conducted to determine the effects of buoyancy and Coriolis forces on heat transfer in turbine blade internal coolant passages. The experiments were conducted with a large-scale, multipass, heat transfer model with both radially inward and outward flow. Trip strips on the leading and trailing surfaces of the radial coolant passages were used to produce the rough walls. An analysis of the governing flow equations showed that four parameters influence the heat transfer in rotating passages: coolant-to-wall temperature ratio, Rossby number, Reynolds number, and radius-to-passage hydraulic diameter ratio. The first three of these four parameters were varied over ranges that are typical of advanced gas turbine engine operating conditions. Results were correlated and compared to previous results from stationary and rotating similar models with trip strips. The heat transfer coefficients on surfaces, where the heat transfer increased with rotation and buoyancy, varied by as much as a factor of four. Maximum values of the heat transfer coefficients with high rotation were only slightly above the highest levels obtained with the smooth wall model. The heat transfer coefficients on surfaces where the heat transfer decreased with rotation, varied by as much as a factor of three due to rotation and buoyancy. It was concluded that both Coriolis and buoyancy effects must be considered in turbine blade cooling designs with trip strips and that the effects of rotation were markedly different depending upon the flow direction.

Comparison of the efficiency of large-scale ceramic and membrane aeration systems with the dynamic off-gas method

2002 ◽  
Vol 46 (4-5) ◽  
pp. 317-324 ◽  
Author(s):  
J.A. Libra ◽  
A. Schuchardt ◽  
C. Sahlmann ◽  
J. Handschag ◽  
U. Wiesmann ◽  
...  
Keyword(s):  
Large Scale ◽  
Operating Conditions ◽  
Air Distribution ◽  
Energy Costs ◽  
Dissolved Oxygen Concentration ◽  
Membrane Aeration ◽  
Aeration System ◽  
Oxygen Transfer Efficiency ◽  
Aeration Efficiency ◽  
Period Measurement

The aeration systems of two full-scale activated sludge basins were compared over 2.5 years under the same operating conditions using dynamic off-gas testing. Only the material of the diffuser was different, membrane vs. ceramic tube diffusers. The experimental design took the complexity and dynamics of the system into consideration. The investigation has shown that, although the membrane diffusers have higher initial standard oxygen transfer efficiency (SOTE) and standard aeration efficiency (SAE), these decreased over time, while the SAE of the ceramic diffusers started lower, but increased slightly over the whole period. Measurement of air distribution in the basins along with dissolved oxygen concentration profiles have provided important information on improving process control and reducing energy costs. The results show that dynamic off-gas testing can effectively be used for monitoring the aeration system and to check design assumptions under operating conditions. The information can be used to improve the design of new aeration systems or in retro-fitting existing basins.

Advances in Water Treatment Application of Sepiolite Mineral Materials

2013 ◽  
Vol 710 ◽  
pp. 217-220 ◽  
Author(s):  
Fei Wang ◽  
Lei Feng ◽  
Meng Ran Tang ◽  
Ji Yuan Li ◽  
Qing Guo Tang
Keyword(s):  
Water Treatment ◽  
Size Effect ◽  
Large Scale ◽  
Surface Effect ◽  
Development Trend ◽  
High Energy ◽  
Research Area ◽  
Group Mineral ◽  
Active Research ◽  
Treatment Application

Synthetic nanomaterials have the disadvantages of large-scale investment, high energy consumption, complex production process and heavy environmental load. Mineral nanomaterials such as sepiolite group mineral nanomaterials are characterized by small size effect, quantum size effect and surface effect. Water treatment application of sepiolite group mineral nanomaterials has become an active research area and showed good development and application prospects. Based on the above reasons, this paper systematically summarizes the water treatment application of sepiolite group mineral nanomaterials, and development trend related to water treatment application of sepiolite group mineral nanomaterials were also proposed.

scholarly journals Material parameter identification using finite elements with time-adaptive higher-order time integration and experimental full-field strain information

2021 ◽  
Author(s):  
Stefan Hartmann ◽  
Rose Rogin Gilbert
Keyword(s):  
Experimental Data ◽  
Finite Elements ◽  
Parameter Identification ◽  
Material Parameter ◽  
Measurement Data ◽  
Least Square ◽  
Image Correlation ◽  
Field Strain ◽  
Material Parameter Identification ◽  
Full Field

AbstractIn this article, we follow a thorough matrix presentation of material parameter identification using a least-square approach, where the model is given by non-linear finite elements, and the experimental data is provided by both force data as well as full-field strain measurement data based on digital image correlation. First, the rigorous concept of semi-discretization for the direct problem is chosen, where—in the first step—the spatial discretization yields a large system of differential-algebraic equation (DAE-system). This is solved using a time-adaptive, high-order, singly diagonally-implicit Runge–Kutta method. Second, to study the fully analytical versus fully numerical determination of the sensitivities, required in a gradient-based optimization scheme, the force determination using the Lagrange-multiplier method and the strain computation must be provided explicitly. The consideration of the strains is necessary to circumvent the influence of rigid body motions occurring in the experimental data. This is done by applying an external strain determination tool which is based on the nodal displacements of the finite element program. Third, we apply the concept of local identifiability on the entire parameter identification procedure and show its influence on the choice of the parameters of the rate-type constitutive model. As a test example, a finite strain viscoelasticity model and biaxial tensile tests applied to a rubber-like material are chosen.

scholarly journals Hardware-in-the-loop simulation of wave energy converters based on dielectric elastomer generators

Meccanica ◽  
2021 ◽  
Vol 56 (5) ◽  
pp. 1223-1237
Author(s):  
Giacomo Moretti ◽  
Andrea Scialò ◽  
Giovanni Malara ◽  
Giovanni Gerardo Muscolo ◽  
Felice Arena ◽  
...  
Keyword(s):  
Wave Energy ◽  
Large Scale ◽  
Low Cost ◽  
Test Site ◽  
Dielectric Elastomer ◽  
Operating Conditions ◽  
Polymer Materials ◽  
Hardware In The Loop ◽  
Wave Energy Converters ◽  
Energy Converters

AbstractDielectric elastomer generators (DEGs) are soft electrostatic generators based on low-cost electroactive polymer materials. These devices have attracted the attention of the marine energy community as a promising solution to implement economically viable wave energy converters (WECs). This paper introduces a hardware-in-the-loop (HIL) simulation framework for a class of WECs that combines the concept of the oscillating water columns (OWCs) with the DEGs. The proposed HIL system replicates in a laboratory environment the realistic operating conditions of an OWC/DEG plant, while drastically reducing the experimental burden compared to wave tank or sea tests. The HIL simulator is driven by a closed-loop real-time hydrodynamic model that is based on a novel coupling criterion which allows rendering a realistic dynamic response for a diversity of scenarios, including large scale DEG plants, whose dimensions and topologies are largely different from those available in the HIL setup. A case study is also introduced, which simulates the application of DEGs on an OWC plant installed in a mild real sea laboratory test-site. Comparisons with available real sea-test data demonstrated the ability of the HIL setup to effectively replicate a realistic operating scenario. The insights gathered on the promising performance of the analysed OWC/DEG systems pave the way to pursue further sea trials in the future.

Experimental Study on the Behavior of a Swimming Pool Onboard a Large Passenger Ship

2009 ◽  
Vol 46 (01) ◽  
pp. 27-33
Author(s):  
Pekka Ruponen ◽  
Jerzy Matusiak ◽  
Janne Luukkonen ◽  
Mikko Ilus
Keyword(s):  
Large Scale ◽  
Hydraulic Cylinder ◽  
Operating Conditions ◽  
Swimming Pool ◽  
Scale Model ◽  
Longitudinal Motion ◽  
Sea State ◽  
Passenger Ship ◽  
Large Scale Model ◽  
Computer Controlled

The water in a swimming pool on the top deck of a large passenger ship can be excited to a resonant motion, even in a moderate sea state. The motion of the water in the pool is mainly caused by longitudinal acceleration, resulting from the ship's pitch and surge motions. At resonance, there can be high waves in the pool and splashing of water. In this study the behavior of the Solarium Pool of the Freedom of the Seas was examined in various sea states and operating conditions. The motions of the pool were calculated on the basis of a linear seakeeping method, and the behavior of the water in the pool was studied with experimental model tests. A large-scale model of the pool was constructed and fitted to a purpose-built test bench that could be axially moved by a computer-controlled hydraulic cylinder. Water elevation in the pool was measured, and all tests were video recorded. Different modifications of the pool were tested to improve the behavior of the pool. A strong correlation between the longitudinal motion and the behavior of the water in the pool was found.

Sign in / Sign up

Export Citation Format

Share Document