• Advances in aircraft and spacecraft science
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• 제5권2호
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• pp.205-223
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• 2018

During launch a spacecraft is subjected to a variety of dynamical loads transmitted through the launcher to spacecraft interface or air-born transmission excitations in the acoustic pressure field inside the fairing. As a result, spacecraft are tested on ground to ensure and demonstrate the global integrity of the structure against these loads, to screen the flight hardware for quality of workmanship and to validate mathematical models. This paper addresses the numerical modelling and simulation of the low frequency sine and random vibration tests performed on electrodynamic shaker facilities to comprise the mechanical-borne transmission loads through the launcher to spacecraft interface. Consequently, the paper reviews techniques and methodologies to derive a reliable and representative coupled virtual vibration testing simulation environment based on experimental data. These technologies are explored with the main objectives to ensure a stable, reliable and accurate control while testing. As a result, the use of the derived simulation models in combination with the added value of improved control and signal processing algorithms can lead to a safer and smoother vibration test control of the entire environmental test campaign.

• The Plant Pathology Journal
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• 제33권6호
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• pp.529-542
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• 2017

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

• 한국물환경학회지
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• 제29권1호
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• pp.19-28
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• 2013

Artificial neural networks were used for time series modelling of algal dynamics of whole year and by season at the Paldang dam station (confluence area). The modelling was based on comprehensive weekly water quality data from 1997 to 2004 at the Paldang dam station. The results of validation of seasonal models showed that the timing and magnitude of the observed chlorophyll a concentration was predicted better, compared with the ANN model for whole year. Internal weightings of the inputs in trained neural networks were obtained by sensitivity analysis for identification of the primary driving mechanisms in the system dynamics. pH, COD, TP determined most the dynamics of chlorophyll a, although these inputs were not the real driving variable for algal growth. Short-term prediction models that perform one or two weeks ahead predictions of chlorophyll a concentration were designed for the application of Harmful Algal Alert System in Lake Paldang. Short-term-ahead ANN models showed the possibilities of application of Harmful Algal Alert System after increasing ANN model's performance.

• Computers and Concrete
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• 제10권3호
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• pp.307-330
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• 2012

This work intends to contribute for the improvement of the procedure suggested by Brazilian Technical Code that takes into account the cracked concrete stiffness in the estimative of the displacement of reinforced concrete beams submitted to service loads. A damage constitutive model accounting for induced anisotropy, plastic deformations and bimodular elastic response is used in order to simulate the concrete behaviour, while an elastoplastic behaviour is admitted for the reinforcement. The constitutive models were implemented in a program for bars structures analysis with layered finite elements. Initially, the damage model is briefly presented as well as the parametric identification of the materials that have been used in the reinforced concrete beams. After that, beams with different geometries and reinforcement area are analyzed and a statistical method (ANOVA) is employed in order to identify the main variables in the problem. Soon after, the same procedure is used with another resistance of concrete, where the compression strength is changed. The numerical responses are compared with the ones obtained by Brazilian Technical Code and experimental tests in order to validate the use of the damage model. Finally, some remarks are discussed based on responses presented in this work.

• Coupled systems mechanics
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• 제11권1호
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• pp.79-91
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• 2022

Models for water treatment processes include simulation, i.e., modelling of water quality, flow hydraulics, process controls and design. Water treatment processes are inherently dynamic because of the large variations in the influent water flow rate, concentration and composition. Moreover, these variations are to a large extent not possible to control. Mathematical models and computer simulations are essential to describe, predict and control the complicated interactions of the water treatment processes. An accurate description of such systems can therefore result in highly complex models, which may not be very useful from a practical, operational point of view. The main objective is to combine knowledge of the process dynamics with mathematical methods for processes estimation and identification. Good modelling practice is way to obtain this objective and to improve water treatment processes(its understanding, design, control and performance- efficiency). By synthesize of existing knowledge and experience on good modelling practices and principles the aim is to help address the critical strategic gaps and weaknessesin water treatment models application.

• 한국군사과학기술학회지
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• 제10권3호
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• pp.181-188
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• 2007

This paper presents a torque control method of a hydraulic actuation system for measuring the dynamic stiffness of missile fin actuators. We propose a new control technique called Dual Dynamic Torque Feedback Control(DDTFC), which improves the stability of the torque control system and enables fast tracking of torque command. The developed control scheme is derived from the physical understanding based on mathematical modelling and analysis. The dynamics of hydraulic torque control servo-system is unravelled via physics-based modelling and nonparametric system identification. In order to verify the effectiveness of the method, the experiment is carried out with a test equipment for measuring the dynamic stiffness. The experiment and simulation results show that DDTFC gives stability improvement.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.71.2-71
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• 2001

This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...

• 한국기계기술학회지
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• 제13권3호
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• pp.73-79
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• 2011

In this study, an analytical realization of end-milling system was introduced using recursive parametric modeling analysis. Also, the numerical mode analysis of end-milling system with different conditions was performed systematically. In this regard, a recursive least square modelling algorithm and the natural mode for real part and imaginary one was discussed. This recursive approach (RLSM) can be adopted for on-line end-milling identification. After experimental practice of the end-milling, the end-milling force was obtained and it was used for the calculation of FRF (Frequency response function) and mode analysis. Also the FRF was analysed for the prediction of a end-milling system using recursive algorithm.

• Structural Monitoring and Maintenance
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• 제10권1호
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• pp.63-86
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• 2023

Structural health monitoring and damage detection are essential for assessing, maintaining, and rehabilitating structures. Most of the existing damage detection approaches compare the current state structural response with the undamaged vibrational structural response, which is unsuitable for old and existing structures where undamaged vibrational responses are absent. One of the approaches for existing structures, numerical model updating/inverse modelling, available in the literature, is limited to numerical studies with high-end software. In this study, an attempt is made to study the effectiveness of the model updating technique, simplify modelling complexity, and economize its usability. The optimization-based detection problem is addressed by using programmable open-sourced code, OpenSees^® and a derivative-free optimization code, NOMAD^®. Modal analysis is used for damage identification of beam-like structures with several damage scenarios. The performance of the proposed methodology is validated both numerically and experimentally. The proposed method performs satisfactorily in identifying both locations and intensity of damage in structures.

• 대한기계학회논문집A
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• 제21권10호
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• pp.1636-1647
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• 1997

As most of today's automatic transmissions in passenger car adopt a electro-hydraulic control system, the role of electronically controlled solenoid valves occupies an important position and it is essential to predict solenoid transient characteristics in order to design and evaluate the performance of the hydraulic control system. However, in general, both the magnetic and electrical parameters f the solenoid system are hardly known and it is not easy to model this section with moderate complexity although mechanical system could be developed using the classical second order system. This paper presents a dynamic modelling technique of a solenoid valve, that is controlled by pulse width modulation for an automatic transmission, in terms of system identification theory. In nonlinear computer simulation, it is shown that the identified systems which produce magnetic force to input duty cycle for various excitation signals predict the static and dynamic performance very well near the operating point and in experiment conducted to confirm the validity of identification theory for PWM solenoid valve, we find that there is a good agreement between the experimental data and simulation result. Hence, this model can be utilized in the development of pressure control system with PWM solenoid valve.