scholarly journals Determining the likely localization of methane sources using forecast time series and satellite data

2021 ◽  
Author(s):  
M.V. Platonova ◽  
E.G. Klimova
Keyword(s):  
Observational Data ◽  
Mathematical Formulation ◽  
Three Dimensional ◽  
Measurement Data ◽  
Real Data ◽  
Optimization Method ◽  
Satellite Measurement ◽  
Time Interval ◽  
Methane Fluxes ◽  
Forecast Time

The paper is devoted to the topical problem of determining the sources of methane from observational data. An algorithm based on the statistical optimization method used to estimate a time constant parameter is considered. To implement the algorithm, a variant of ensemble smoothing is used, which is an optimal estimate of the desired parameter based on observational data and forecast for a given time interval. This paper presents the implementation of the algorithm for real observational and forecast data, the results of a three-dimensional transport and diffusion model are taken as a mathematical model, and satellite measurement data are used as observational data. Methane fluxes are estimated in subdomains of the Earth’s surface for specified time intervals. The paper contains a mathematical formulation of the problem, a scheme for its numerical implementation. The results of numerical experiments with model and real data are presented.

scholarly journals On finding a cavity in a thermoelastic body using a single displacement measurement over a finite time interval on the surface of the body

2018 ◽  
Vol 26 (3) ◽  
pp. 369-394 ◽  
Author(s):  
Masaru Ikehata
Keyword(s):  
Time Domain ◽  
Mathematical Formulation ◽  
Three Dimensional ◽  
Coupled System ◽  
The Body ◽  
Time Interval ◽  
Heat Equations ◽  
Time Domain Data ◽  
Thermoelastic Body ◽  
The Time Domain

AbstractA mathematical formulation of an estimation problem of a cavity inside a three-dimensional thermoelastic body by using time domain data is considered. The governing equation of the problem is given by a system of equations in the linear theory of thermoelasticity which is a coupled system of the elastic wave and heat equations. A new version of the enclosure method in the time domain which is originally developed for the classical wave equation is established. For a comparison, the results in the decoupled case are also given.

scholarly journals A Novel Mathematical Formulation for Density-based Topology Optimization Method Considering Multi-Axis Machining Constraint

2021 ◽  
pp. 1-13
Author(s):  
Hao Deng ◽  
Albert C. To
Keyword(s):  
Structural Design ◽  
Mathematical Formulation ◽  
Three Dimensional ◽  
Optimization Method ◽  
Machining Process ◽  
Minimum Size ◽  
Heaviside Function ◽  
Machining Processes ◽  
Multiaxis Machining ◽  
2.5D Milling

Abstract This paper proposes a novel density-based method for structural design considering restrictions of multiaxis machining processes. A new mathematical formulation based on Heaviside function is presented to transform the design field into a geometry which can be manufactured by multi-axis machining process. The formulation is developed for 5-axis machining, which can be also applied to 2.5D milling restriction. The filter techniques are incorporated to effectively control the minimum size of void region. The proposed method is demonstrated by solving the compliance minimization problem for different machinable freeform designs. Several two and three-dimensional numerical examples are presented and discussed in detail.

Carbon Monoxide Variations in the Antarctic Atmosphere from Ground-Based and Satellite Measurement Data

2019 ◽  
Vol 55 (9) ◽  
pp. 1210-1217
Author(s):  
V. P. Ustinov ◽  
E. L. Baranova ◽  
K. N. Visheratin ◽  
M. I. Grachev ◽  
A. V. Kal’sin
Keyword(s):  
Carbon Monoxide ◽  
Measurement Data ◽  
Satellite Measurement ◽  
The Antarctic

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

scholarly journals Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Yuhang Yang ◽  
Zhiqiao Dong ◽  
Yuquan Meng ◽  
Chenhui Shao
Keyword(s):  
High Resolution ◽  
High Performance ◽  
Sampling Design ◽  
Three Dimensional ◽  
Measurement Data ◽  
Data Driven ◽  
Surface Measurement ◽  
Smart Manufacturing ◽  
Future Research ◽  
3D Surface

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.

scholarly journals Optimal Temperature-Based Condition Monitoring System for Wind Turbines

2021 ◽  
Vol 6 (4) ◽  
pp. 50
Author(s):  
Payam Teimourzadeh Baboli ◽  
Davood Babazadeh ◽  
Amin Raeiszadeh ◽  
Susanne Horodyvskyy ◽  
Isabel Koprek
Keyword(s):  
Monitoring System ◽  
Wind Turbines ◽  
Wind Farm ◽  
Measurement Data ◽  
Real Data ◽  
Offshore Wind ◽  
Risk Indicator ◽  
Real World Data ◽  
The Real ◽  
Data Driven Modeling

With the increasing demand for the efficiency of wind energy projects due to challenging market conditions, the challenges related to maintenance planning are increasing. In this paper, a condition-based monitoring system for wind turbines (WTs) based on data-driven modeling is proposed. First, the normal condition of the WTs key components is estimated using a tailor-made artificial neural network. Then, the deviation of the real-time measurement data from the estimated values is calculated, indicating abnormal conditions. One of the main contributions of the paper is to propose an optimization problem for calculating the safe band, to maximize the accuracy of abnormal condition identification. During abnormal conditions or hazardous conditions of the WTs, an alarm is triggered and a proposed risk indicator is updated. The effectiveness of the model is demonstrated using real data from an offshore wind farm in Germany. By experimenting with the proposed model on the real-world data, it is shown that the proposed risk indicator is fully consistent with upcoming wind turbine failures.

Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength

2021 ◽  
pp. 095441192098703
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang
Keyword(s):  
Experimental Data ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Three Dimensional ◽  
Optimization Method ◽  
Weight Lifting ◽  
Joint Torque ◽  
Maximum Weight ◽  
Angular Velocities ◽  
Asymmetric Lifting

In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.

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